Current techniques for the real-time processing of complex radar signatures

NASA Astrophysics Data System (ADS)

Clay, E.

A real-time processing technique has been developed for the microwave receiver of the Brahms radar station. The method allows such target signatures as the radar cross section (RCS) of the airframes and rotating parts, the one-dimensional tomography of aircraft, and the RCS of electromagnetic decoys to be characterized. The method allows optimization of experimental parameters including the analysis frequency band, the receiver gain, and the wavelength range of EM analysis.

Characteristic vector analysis as a technique for signature extraction of remote ocean color data

NASA Technical Reports Server (NTRS)

Grew, G. W.

1977-01-01

Characteristic vector analysis is being used to extract spectral signatures of suspended matter in the ocean from remote ocean color data collected with MOCS (Multichannel Ocean Color Sensor), a multispectral scanner. Spectral signatures appear to be obtainable either directly from characteristic vectors or through a transformation of these eigenvectors. Quantification of the suspended matter associated with each resulting signature seems feasible using associated coefficients generated by the technique. This paper presents eigenvectors associated with algae, 'sediment', acid waste, sewage sludge, and oil. The results suggest an efficient method of transmitting from satellites multispectral data of pollution in our oceans.

Real time gamma-ray signature identifier

DOEpatents

Rowland, Mark [Alamo, CA; Gosnell, Tom B [Moraga, CA; Ham, Cheryl [Livermore, CA; Perkins, Dwight [Livermore, CA; Wong, James [Dublin, CA

2012-05-15

A real time gamma-ray signature/source identification method and system using principal components analysis (PCA) for transforming and substantially reducing one or more comprehensive spectral libraries of nuclear materials types and configurations into a corresponding concise representation/signature(s) representing and indexing each individual predetermined spectrum in principal component (PC) space, wherein an unknown gamma-ray signature may be compared against the representative signature to find a match or at least characterize the unknown signature from among all the entries in the library with a single regression or simple projection into the PC space, so as to substantially reduce processing time and computing resources and enable real-time characterization and/or identification.

Water quality parameter measurement using spectral signatures

NASA Technical Reports Server (NTRS)

White, P. E.

1973-01-01

Regression analysis is applied to the problem of measuring water quality parameters from remote sensing spectral signature data. The equations necessary to perform regression analysis are presented and methods of testing the strength and reliability of a regression are described. An efficient algorithm for selecting an optimal subset of the independent variables available for a regression is also presented.

Spectral signature verification using statistical analysis and text mining

NASA Astrophysics Data System (ADS)

DeCoster, Mallory E.; Firpi, Alexe H.; Jacobs, Samantha K.; Cone, Shelli R.; Tzeng, Nigel H.; Rodriguez, Benjamin M.

2016-05-01

In the spectral science community, numerous spectral signatures are stored in databases representative of many sample materials collected from a variety of spectrometers and spectroscopists. Due to the variety and variability of the spectra that comprise many spectral databases, it is necessary to establish a metric for validating the quality of spectral signatures. This has been an area of great discussion and debate in the spectral science community. This paper discusses a method that independently validates two different aspects of a spectral signature to arrive at a final qualitative assessment; the textual meta-data and numerical spectral data. Results associated with the spectral data stored in the Signature Database1 (SigDB) are proposed. The numerical data comprising a sample material's spectrum is validated based on statistical properties derived from an ideal population set. The quality of the test spectrum is ranked based on a spectral angle mapper (SAM) comparison to the mean spectrum derived from the population set. Additionally, the contextual data of a test spectrum is qualitatively analyzed using lexical analysis text mining. This technique analyzes to understand the syntax of the meta-data to provide local learning patterns and trends within the spectral data, indicative of the test spectrum's quality. Text mining applications have successfully been implemented for security2 (text encryption/decryption), biomedical3 , and marketing4 applications. The text mining lexical analysis algorithm is trained on the meta-data patterns of a subset of high and low quality spectra, in order to have a model to apply to the entire SigDB data set. The statistical and textual methods combine to assess the quality of a test spectrum existing in a database without the need of an expert user. This method has been compared to other validation methods accepted by the spectral science community, and has provided promising results when a baseline spectral signature is present for comparison. The spectral validation method proposed is described from a practical application and analytical perspective.

A Self-Directed Method for Cell-Type Identification and Separation of Gene Expression Microarrays

PubMed Central

Zuckerman, Neta S.; Noam, Yair; Goldsmith, Andrea J.; Lee, Peter P.

2013-01-01

Gene expression analysis is generally performed on heterogeneous tissue samples consisting of multiple cell types. Current methods developed to separate heterogeneous gene expression rely on prior knowledge of the cell-type composition and/or signatures - these are not available in most public datasets. We present a novel method to identify the cell-type composition, signatures and proportions per sample without need for a-priori information. The method was successfully tested on controlled and semi-controlled datasets and performed as accurately as current methods that do require additional information. As such, this method enables the analysis of cell-type specific gene expression using existing large pools of publically available microarray datasets. PMID:23990767

Joint Estimation of Time-Frequency Signature and DOA Based on STFD for Multicomponent Chirp Signals

PubMed Central

Zhao, Ziyue; Liu, Congfeng

2014-01-01

In the study of the joint estimation of time-frequency signature and direction of arrival (DOA) for multicomponent chirp signals, an estimation method based on spatial time-frequency distributions (STFDs) is proposed in this paper. Firstly, array signal model for multicomponent chirp signals is presented and then array processing is applied in time-frequency analysis to mitigate cross-terms. According to the results of the array processing, Hough transform is performed and the estimation of time-frequency signature is obtained. Subsequently, subspace method for DOA estimation based on STFD matrix is achieved. Simulation results demonstrate the validity of the proposed method. PMID:27382610

Joint Estimation of Time-Frequency Signature and DOA Based on STFD for Multicomponent Chirp Signals.

PubMed

Zhao, Ziyue; Liu, Congfeng

2014-01-01

In the study of the joint estimation of time-frequency signature and direction of arrival (DOA) for multicomponent chirp signals, an estimation method based on spatial time-frequency distributions (STFDs) is proposed in this paper. Firstly, array signal model for multicomponent chirp signals is presented and then array processing is applied in time-frequency analysis to mitigate cross-terms. According to the results of the array processing, Hough transform is performed and the estimation of time-frequency signature is obtained. Subsequently, subspace method for DOA estimation based on STFD matrix is achieved. Simulation results demonstrate the validity of the proposed method.

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge

PubMed Central

Wagner, Florian

2015-01-01

Method Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. Results I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets. PMID:26575370

Assessment of Gamma-Ray Spectra Analysis Method Utilizing the Fireworks Algorithm for various Error Measures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alamaniotis, Miltiadis; Tsoukalas, Lefteri H.

2018-01-01

Significant role in enhancing nuclear nonproliferation plays the analysis of obtained data and the inference of the presence or not of special nuclear materials in them. Among various types of measurements, gamma-ray spectra is the widest used type of data utilized for analysis in nonproliferation. In this chapter, a method that employs the fireworks algorithm (FWA) for analyzing gamma-ray spectra aiming at detecting gamma signatures is presented. In particular FWA is utilized to fit a set of known signatures to a measured spectrum by optimizing an objective function, with non-zero coefficients expressing the detected signatures. FWA is tested on amore » set of experimentally obtained measurements and various objective functions -MSE, RMSE, Theil-2, MAE, MAPE, MAP- with results exhibiting its potential in providing high accuracy and high precision of detected signatures. Furthermore, FWA is benchmarked against genetic algorithms, and multiple linear regression with results exhibiting its superiority over the rest tested algorithms with respect to precision for MAE, MAPE and MAP measures.« less

Vibration signature analysis of multistage gear transmission

NASA Technical Reports Server (NTRS)

Choy, F. K.; Tu, Y. K.; Savage, M.; Townsend, D. P.

1989-01-01

An analysis is presented for multistage multimesh gear transmission systems. The analysis predicts the overall system dynamics and the transmissibility to the gear box or the enclosed structure. The modal synthesis approach of the analysis treats the uncoupled lateral/torsional model characteristics of each stage or component independently. The vibration signature analysis evaluates the global dynamics coupling in the system. The method synthesizes the interaction of each modal component or stage with the nonlinear gear mesh dynamics and the modal support geometry characteristics. The analysis simulates transient and steady state vibration events to determine the resulting torque variations, speeds, changes, rotor imbalances, and support gear box motion excitations. A vibration signature analysis examines the overall dynamic characteristics of the system, and the individual model component responses. The gear box vibration analysis also examines the spectral characteristics of the support system.

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.

PubMed

Wagner, Florian

2015-01-01

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

A reduction in ag/residential signature conflict using principal components analysis of LANDSAT temporal data

NASA Technical Reports Server (NTRS)

Williams, D. L.; Borden, F. Y.

1977-01-01

Methods to accurately delineate the types of land cover in the urban-rural transition zone of metropolitan areas were considered. The application of principal components analysis to multidate LANDSAT imagery was investigated as a means of reducing the overlap between residential and agricultural spectral signatures. The statistical concepts of principal components analysis were discussed, as well as the results of this analysis when applied to multidate LANDSAT imagery of the Washington, D.C. metropolitan area.

Assessment of Gamma-Ray-Spectra Analysis Method Utilizing the Fireworks Algorithm for Various Error Measures

DOE PAGES

Alamaniotis, Miltiadis; Tsoukalas, Lefteri H.

2018-01-01

The analysis of measured data plays a significant role in enhancing nuclear nonproliferation mainly by inferring the presence of patterns associated with special nuclear materials. Among various types of measurements, gamma-ray spectra is the widest utilized type of data in nonproliferation applications. In this paper, a method that employs the fireworks algorithm (FWA) for analyzing gamma-ray spectra aiming at detecting gamma signatures is presented. In particular, FWA is utilized to fit a set of known signatures to a measured spectrum by optimizing an objective function, where non-zero coefficients express the detected signatures. FWA is tested on a set of experimentallymore » obtained measurements optimizing various objective functions—MSE, RMSE, Theil-2, MAE, MAPE, MAP—with results exhibiting its potential in providing highly accurate and precise signature detection. Finally and furthermore, FWA is benchmarked against genetic algorithms and multiple linear regression, showing its superiority over those algorithms regarding precision with respect to MAE, MAPE, and MAP measures.« less

Real-time detection of deoxyribonucleic acid bases via their negative differential conductance signature.

PubMed

Dragoman, D; Dragoman, M

2009-08-01

In this Brief Report, we present a method for the real-time detection of the bases of the deoxyribonucleic acid using their signatures in negative differential conductance measurements. The present methods of electronic detection of deoxyribonucleic acid bases are based on a statistical analysis because the electrical currents of the four bases are weak and do not differ significantly from one base to another. In contrast, we analyze a device that combines the accumulated knowledge in nanopore and scanning tunneling detection and which is able to provide very distinctive electronic signatures for the four bases.

Feature-space-based FMRI analysis using the optimal linear transformation.

PubMed

Sun, Fengrong; Morris, Drew; Lee, Wayne; Taylor, Margot J; Mills, Travis; Babyn, Paul S

2010-09-01

The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.

Quantitative comparison of microarray experiments with published leukemia related gene expression signatures.

PubMed

Klein, Hans-Ulrich; Ruckert, Christian; Kohlmann, Alexander; Bullinger, Lars; Thiede, Christian; Haferlach, Torsten; Dugas, Martin

2009-12-15

Multiple gene expression signatures derived from microarray experiments have been published in the field of leukemia research. A comparison of these signatures with results from new experiments is useful for verification as well as for interpretation of the results obtained. Currently, the percentage of overlapping genes is frequently used to compare published gene signatures against a signature derived from a new experiment. However, it has been shown that the percentage of overlapping genes is of limited use for comparing two experiments due to the variability of gene signatures caused by different array platforms or assay-specific influencing parameters. Here, we present a robust approach for a systematic and quantitative comparison of published gene expression signatures with an exemplary query dataset. A database storing 138 leukemia-related published gene signatures was designed. Each gene signature was manually annotated with terms according to a leukemia-specific taxonomy. Two analysis steps are implemented to compare a new microarray dataset with the results from previous experiments stored and curated in the database. First, the global test method is applied to assess gene signatures and to constitute a ranking among them. In a subsequent analysis step, the focus is shifted from single gene signatures to chromosomal aberrations or molecular mutations as modeled in the taxonomy. Potentially interesting disease characteristics are detected based on the ranking of gene signatures associated with these aberrations stored in the database. Two example analyses are presented. An implementation of the approach is freely available as web-based application. The presented approach helps researchers to systematically integrate the knowledge derived from numerous microarray experiments into the analysis of a new dataset. By means of example leukemia datasets we demonstrate that this approach detects related experiments as well as related molecular mutations and may help to interpret new microarray data.

A Simple Model-Based Approach to Inferring and Visualizing Cancer Mutation Signatures

PubMed Central

Shiraishi, Yuichi; Tremmel, Georg; Miyano, Satoru; Stephens, Matthew

2015-01-01

Recent advances in sequencing technologies have enabled the production of massive amounts of data on somatic mutations from cancer genomes. These data have led to the detection of characteristic patterns of somatic mutations or “mutation signatures” at an unprecedented resolution, with the potential for new insights into the causes and mechanisms of tumorigenesis. Here we present new methods for modelling, identifying and visualizing such mutation signatures. Our methods greatly simplify mutation signature models compared with existing approaches, reducing the number of parameters by orders of magnitude even while increasing the contextual factors (e.g. the number of flanking bases) that are accounted for. This improves both sensitivity and robustness of inferred signatures. We also provide a new intuitive way to visualize the signatures, analogous to the use of sequence logos to visualize transcription factor binding sites. We illustrate our new method on somatic mutation data from urothelial carcinoma of the upper urinary tract, and a larger dataset from 30 diverse cancer types. The results illustrate several important features of our methods, including the ability of our new visualization tool to clearly highlight the key features of each signature, the improved robustness of signature inferences from small sample sizes, and more detailed inference of signature characteristics such as strand biases and sequence context effects at the base two positions 5′ to the mutated site. The overall framework of our work is based on probabilistic models that are closely connected with “mixed-membership models” which are widely used in population genetic admixture analysis, and in machine learning for document clustering. We argue that recognizing these relationships should help improve understanding of mutation signature extraction problems, and suggests ways to further improve the statistical methods. Our methods are implemented in an R package pmsignature (https://github.com/friend1ws/pmsignature) and a web application available at https://friend1ws.shinyapps.io/pmsignature_shiny/. PMID:26630308

Signatures of polygenic adaptation associated with climate across the range of a threatened fish species with high genetic connectivity.

PubMed

Harrisson, Katherine A; Amish, Stephen J; Pavlova, Alexandra; Narum, Shawn R; Telonis-Scott, Marina; Rourke, Meaghan L; Lyon, Jarod; Tonkin, Zeb; Gilligan, Dean M; Ingram, Brett A; Lintermans, Mark; Gan, Han Ming; Austin, Christopher M; Luikart, Gordon; Sunnucks, Paul

2017-11-01

Adaptive differences across species' ranges can have important implications for population persistence and conservation management decisions. Despite advances in genomic technologies, detecting adaptive variation in natural populations remains challenging. Key challenges in gene-environment association studies involve distinguishing the effects of drift from those of selection and identifying subtle signatures of polygenic adaptation. We used paired-end restriction site-associated DNA sequencing data (6,605 biallelic single nucleotide polymorphisms; SNPs) to examine population structure and test for signatures of adaptation across the geographic range of an iconic Australian endemic freshwater fish species, the Murray cod Maccullochella peelii. Two univariate gene-association methods identified 61 genomic regions associated with climate variation. We also tested for subtle signatures of polygenic adaptation using a multivariate method (redundancy analysis; RDA). The RDA analysis suggested that climate (temperature- and precipitation-related variables) and geography had similar magnitudes of effect in shaping the distribution of SNP genotypes across the sampled range of Murray cod. Although there was poor agreement among the candidate SNPs identified by the univariate methods, the top 5% of SNPs contributing to significant RDA axes included 67% of the SNPs identified by univariate methods. We discuss the potential implications of our findings for the management of Murray cod and other species generally, particularly in relation to informing conservation actions such as translocations to improve evolutionary resilience of natural populations. Our results highlight the value of using a combination of different approaches, including polygenic methods, when testing for signatures of adaptation in landscape genomic studies. © 2017 John Wiley & Sons Ltd.

HTSFinder: Powerful Pipeline of DNA Signature Discovery by Parallel and Distributed Computing

PubMed Central

Karimi, Ramin; Hajdu, Andras

2016-01-01

Comprehensive effort for low-cost sequencing in the past few years has led to the growth of complete genome databases. In parallel with this effort, a strong need, fast and cost-effective methods and applications have been developed to accelerate sequence analysis. Identification is the very first step of this task. Due to the difficulties, high costs, and computational challenges of alignment-based approaches, an alternative universal identification method is highly required. Like an alignment-free approach, DNA signatures have provided new opportunities for the rapid identification of species. In this paper, we present an effective pipeline HTSFinder (high-throughput signature finder) with a corresponding k-mer generator GkmerG (genome k-mers generator). Using this pipeline, we determine the frequency of k-mers from the available complete genome databases for the detection of extensive DNA signatures in a reasonably short time. Our application can detect both unique and common signatures in the arbitrarily selected target and nontarget databases. Hadoop and MapReduce as parallel and distributed computing tools with commodity hardware are used in this pipeline. This approach brings the power of high-performance computing into the ordinary desktop personal computers for discovering DNA signatures in large databases such as bacterial genome. A considerable number of detected unique and common DNA signatures of the target database bring the opportunities to improve the identification process not only for polymerase chain reaction and microarray assays but also for more complex scenarios such as metagenomics and next-generation sequencing analysis. PMID:26884678

HTSFinder: Powerful Pipeline of DNA Signature Discovery by Parallel and Distributed Computing.

PubMed

Karimi, Ramin; Hajdu, Andras

2016-01-01

Comprehensive effort for low-cost sequencing in the past few years has led to the growth of complete genome databases. In parallel with this effort, a strong need, fast and cost-effective methods and applications have been developed to accelerate sequence analysis. Identification is the very first step of this task. Due to the difficulties, high costs, and computational challenges of alignment-based approaches, an alternative universal identification method is highly required. Like an alignment-free approach, DNA signatures have provided new opportunities for the rapid identification of species. In this paper, we present an effective pipeline HTSFinder (high-throughput signature finder) with a corresponding k-mer generator GkmerG (genome k-mers generator). Using this pipeline, we determine the frequency of k-mers from the available complete genome databases for the detection of extensive DNA signatures in a reasonably short time. Our application can detect both unique and common signatures in the arbitrarily selected target and nontarget databases. Hadoop and MapReduce as parallel and distributed computing tools with commodity hardware are used in this pipeline. This approach brings the power of high-performance computing into the ordinary desktop personal computers for discovering DNA signatures in large databases such as bacterial genome. A considerable number of detected unique and common DNA signatures of the target database bring the opportunities to improve the identification process not only for polymerase chain reaction and microarray assays but also for more complex scenarios such as metagenomics and next-generation sequencing analysis.

Interactome-transcriptome analysis discovers signatures complementary to GWAS Loci of Type 2 Diabetes

PubMed Central

Li, Jing-Woei; Lee, Heung-Man; Wang, Ying; Tong, Amy Hin-Yan; Yip, Kevin Y.; Tsui, Stephen Kwok-Wing; Lok, Si; Ozaki, Risa; Luk, Andrea O; Kong, Alice P. S.; So, Wing-Yee; Ma, Ronald C. W.; Chan, Juliana C. N.; Chan, Ting-Fung

2016-01-01

Protein interactions play significant roles in complex diseases. We analyzed peripheral blood mononuclear cells (PBMC) transcriptome using a multi-method strategy. We constructed a tissue-specific interactome (T2Di) and identified 420 molecular signatures associated with T2D-related comorbidity and symptoms, mainly implicated in inflammation, adipogenesis, protein phosphorylation and hormonal secretion. Apart from explaining the residual associations within the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study, the T2Di signatures were enriched in pathogenic cell type-specific regulatory elements related to fetal development, immunity and expression quantitative trait loci (eQTL). The T2Di revealed a novel locus near a well-established GWAS loci AChE, in which SRRT interacts with JAZF1, a T2D-GWAS gene implicated in pancreatic function. The T2Di also included known anti-diabetic drug targets (e.g. PPARD, MAOB) and identified possible druggable targets (e.g. NCOR2, PDGFR). These T2Di signatures were validated by an independent computational method, and by expression data of pancreatic islet, muscle and liver with some of the signatures (CEBPB, SREBF1, MLST8, SRF, SRRT and SLC12A9) confirmed in PBMC from an independent cohort of 66 T2D and 66 control subjects. By combining prior knowledge and transcriptome analysis, we have constructed an interactome to explain the multi-layered regulatory pathways in T2D. PMID:27752041

Summary and Statistical Analysis of the First AIAA Sonic Boom Prediction Workshop

NASA Technical Reports Server (NTRS)

Park, Michael A.; Morgenstern, John M.

2014-01-01

A summary is provided for the First AIAA Sonic Boom Workshop held 11 January 2014 in conjunction with AIAA SciTech 2014. Near-field pressure signatures extracted from computational fluid dynamics solutions are gathered from nineteen participants representing three countries for the two required cases, an axisymmetric body and simple delta wing body. Structured multiblock, unstructured mixed-element, unstructured tetrahedral, overset, and Cartesian cut-cell methods are used by the participants. Participants provided signatures computed on participant generated and solution adapted grids. Signatures are also provided for a series of uniformly refined workshop provided grids. These submissions are propagated to the ground and loudness measures are computed. This allows the grid convergence of a loudness measure and a validation metric (dfference norm between computed and wind tunnel measured near-field signatures) to be studied for the first time. Statistical analysis is also presented for these measures. An optional configuration includes fuselage, wing, tail, flow-through nacelles, and blade sting. This full configuration exhibits more variation in eleven submissions than the sixty submissions provided for each required case. Recommendations are provided for potential improvements to the analysis methods and a possible subsequent workshop.

Component-Level Electronic-Assembly Repair (CLEAR) Spacecraft Circuit Diagnostics by Analog and Complex Signature Analysis

NASA Technical Reports Server (NTRS)

Oeftering, Richard C.; Wade, Raymond P.; Izadnegahdar, Alain

2011-01-01

The Component-Level Electronic-Assembly Repair (CLEAR) project at the NASA Glenn Research Center is aimed at developing technologies that will enable space-flight crews to perform in situ component-level repair of electronics on Moon and Mars outposts, where there is no existing infrastructure for logistics spares. These technologies must provide effective repair capabilities yet meet the payload and operational constraints of space facilities. Effective repair depends on a diagnostic capability that is versatile but easy to use by crew members that have limited training in electronics. CLEAR studied two techniques that involve extensive precharacterization of "known good" circuits to produce graphical signatures that provide an easy-to-use comparison method to quickly identify faulty components. Analog Signature Analysis (ASA) allows relatively rapid diagnostics of complex electronics by technicians with limited experience. Because of frequency limits and the growing dependence on broadband technologies, ASA must be augmented with other capabilities. To meet this challenge while preserving ease of use, CLEAR proposed an alternative called Complex Signature Analysis (CSA). Tests of ASA and CSA were used to compare capabilities and to determine if the techniques provided an overlapping or complementary capability. The results showed that the methods are complementary.

Imaging systems and methods for obtaining and using biometric information

DOEpatents

McMakin, Douglas L [Richland, WA; Kennedy, Mike O [Richland, WA

2010-11-30

Disclosed herein are exemplary embodiments of imaging systems and methods of using such systems. In one exemplary embodiment, one or more direct images of the body of a clothed subject are received, and a motion signature is determined from the one or more images. In this embodiment, the one or more images show movement of the body of the subject over time, and the motion signature is associated with the movement of the subject's body. In certain implementations, the subject can be identified based at least in part on the motion signature. Imaging systems for performing any of the disclosed methods are also disclosed herein. Furthermore, the disclosed imaging, rendering, and analysis methods can be implemented, at least in part, as one or more computer-readable media comprising computer-executable instructions for causing a computer to perform the respective methods.

An Optimal Deconvolution Method for Reconstructing Pneumatically Distorted Near-Field Sonic Boom Pressure Measurements

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Haering, Edward A., Jr.; Ehernberger, L. J.

1996-01-01

In-flight measurements of the SR-71 near-field sonic boom were obtained by an F-16XL airplane at flightpath separation distances from 40 to 740 ft. Twenty-two signatures were obtained from Mach 1.60 to Mach 1.84 and altitudes from 47,600 to 49,150 ft. The shock wave signatures were measured by the total and static sensors on the F-16XL noseboo. These near-field signature measurements were distorted by pneumatic attenuation in the pitot-static sensors and accounting for their effects using optimal deconvolution. Measurement system magnitude and phase characteristics were determined from ground-based step-response tests and extrapolated to flight conditions using analytical models. Deconvolution was implemented using Fourier transform methods. Comparisons of the shock wave signatures reconstructed from the total and static pressure data are presented. The good agreement achieved gives confidence of the quality of the reconstruction analysis. although originally developed to reconstruct the sonic boom signatures from SR-71 sonic boom flight tests, the methods presented here generally apply to other types of highly attenuated or distorted pneumatic measurements.

Necessary storage as a signature of discharge variability: towards global maps

NASA Astrophysics Data System (ADS)

Takeuchi, Kuniyoshi; Masood, Muhammad

2017-09-01

This paper proposes the use of necessary storage to smooth out discharge variability to meet a discharge target as a signature of discharge variability in time. Such a signature has a distinct advantage over other statistical indicators such as standard deviation (SD) or coefficient of variation (CV) as it expresses hydrological variability in human terms, which directly indicates the difficulty and ease of managing discharge variation for water resource management. The signature is presented in the form of geographical distribution, in terms of both necessary storage (km3) and normalized necessary storage (months), and is related to the basin characteristics of hydrological heterogeneity. The signature is analyzed in different basins considering the Hurst equation of range as a reference. The slope of such a relation and the scatter of departures from the average relation are analyzed in terms of their relationship with basin characteristics. As a method of calculating necessary storage, the flood duration curve (FDC) and drought duration curve (DDC) methods are employed in view of their relative advantage over other methods to repeat the analysis over many grid points. The Ganges-Brahmaputra-Meghna (GBM) basin is selected as the case study and the BTOPMC hydrological model with Water and Global Change (WATCH) Forcing Data (WFD) is used for estimating FDC and DDC. It is concluded that the necessary storage serves as a useful signature of discharge variability, and its analysis could be extended to the entire globe and in this way seek new insights into hydrological variability in the storage domain at a larger range of scales.

A method for detecting structural deterioration in bridges

NASA Technical Reports Server (NTRS)

Cole, H. A., Jr.; Reed, R. E., Jr.

1974-01-01

The problem of detecting deterioration in bridge structures is studied with the use of Randomdec analysis. Randomdec signatures, derived from the ambient bridge vibrations in the acoustic range, were obtained for a girder bridge over a period of a year to show the insensitivity of the signatures to environmental changes. A laboratory study was also conducted to show the sensitivity of signatures to fatigue cracks on the order of a centimeter in length in steel beams.

An Analysis of Measured Pressure Signatures From Two Theory-Validation Low-Boom Models

NASA Technical Reports Server (NTRS)

Mack, Robert J.

2003-01-01

Two wing/fuselage/nacelle/fin concepts were designed to check the validity and the applicability of sonic-boom minimization theory, sonic-boom analysis methods, and low-boom design methodology in use at the end of the 1980is. Models of these concepts were built, and the pressure signatures they generated were measured in the wind-tunnel. The results of these measurements lead to three conclusions: (1) the existing methods could adequately predict sonic-boom characteristics of wing/fuselage/fin(s) configurations if the equivalent area distributions of each component were smooth and continuous; (2) these methods needed revision so the engine-nacelle volume and the nacelle-wing interference lift disturbances could be accurately predicted; and (3) current nacelle-configuration integration methods had to be updated. With these changes in place, the existing sonic-boom analysis and minimization methods could be effectively applied to supersonic-cruise concepts for acceptable/tolerable sonic-boom overpressures during cruise.

Observation of a 27-day solar signature in noctilucent cloud altitude

NASA Astrophysics Data System (ADS)

Köhnke, Merlin C.; von Savigny, Christian; Robert, Charles E.

2018-05-01

Previous studies have identified solar 27-day signatures in several parameters in the Mesosphere/Lower thermosphere region, including temperature and Noctilucent cloud (NLC) occurrence frequency. In this study we report on a solar 27-day signature in NLC altitude with peak-to-peak variations of about 400 m. We use SCIAMACHY limb-scatter observations from 2002 to 2012 to detect NLCs. The superposed epoch analysis method is applied to extract solar 27-day signatures. A 27-day signature in NLC altitude can be identified in both hemispheres in the SCIAMACHY dataset, but the signature is more pronounced in the northern hemisphere. The solar signature in NLC altitude is found to be in phase with solar activity and temperature for latitudes ≳ 70 ° N. We provide a qualitative explanation for the positive correlation between solar activity and NLC altitude based on published model simulations.

Application of Independent Component Analysis for the Data Mining of Simultaneous EEG-fMRI: Preliminary Experience on Sleep Onset

PubMed Central

Lee, Jong-Hwan; Oh, Sungsuk; Jolesz, Ferenc A.; Park, Hyunwook; Yoo, Seung-Schik

2010-01-01

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with the ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta- and alpha-rhythms that are sleep onset related EEG signatures along with the subsequent neural circuitries from a sleep deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable. PMID:19922343

Application of independent component analysis for the data mining of simultaneous Eeg-fMRI: preliminary experience on sleep onset.

PubMed

Lee, Jong-Hwan; Oh, Sungsuk; Jolesz, Ferenc A; Park, Hyunwook; Yoo, Seung-Schik

2009-01-01

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta and alpha rhythms that are sleep onset-related EEG signatures along with the subsequent neural circuitries from a sleep-deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable.

Importance of correlation between gene expression levels: application to the type I interferon signature in rheumatoid arthritis.

PubMed

Reynier, Frédéric; Petit, Fabien; Paye, Malick; Turrel-Davin, Fanny; Imbert, Pierre-Emmanuel; Hot, Arnaud; Mougin, Bruno; Miossec, Pierre

2011-01-01

The analysis of gene expression data shows that many genes display similarity in their expression profiles suggesting some co-regulation. Here, we investigated the co-expression patterns in gene expression data and proposed a correlation-based research method to stratify individuals. Using blood from rheumatoid arthritis (RA) patients, we investigated the gene expression profiles from whole blood using Affymetrix microarray technology. Co-expressed genes were analyzed by a biclustering method, followed by gene ontology analysis of the relevant biclusters. Taking the type I interferon (IFN) pathway as an example, a classification algorithm was developed from the 102 RA patients and extended to 10 systemic lupus erythematosus (SLE) patients and 100 healthy volunteers to further characterize individuals. We developed a correlation-based algorithm referred to as Classification Algorithm Based on a Biological Signature (CABS), an alternative to other approaches focused specifically on the expression levels. This algorithm applied to the expression of 35 IFN-related genes showed that the IFN signature presented a heterogeneous expression between RA, SLE and healthy controls which could reflect the level of global IFN signature activation. Moreover, the monitoring of the IFN-related genes during the anti-TNF treatment identified changes in type I IFN gene activity induced in RA patients. In conclusion, we have proposed an original method to analyze genes sharing an expression pattern and a biological function showing that the activation levels of a biological signature could be characterized by its overall state of correlation.

Distinguishing signatures of determinism and stochasticity in spiking complex systems

PubMed Central

Aragoneses, Andrés; Rubido, Nicolás; Tiana-Alsina, Jordi; Torrent, M. C.; Masoller, Cristina

2013-01-01

We describe a method to infer signatures of determinism and stochasticity in the sequence of apparently random intensity dropouts emitted by a semiconductor laser with optical feedback. The method uses ordinal time-series analysis to classify experimental data of inter-dropout-intervals (IDIs) in two categories that display statistically significant different features. Despite the apparent randomness of the dropout events, one IDI category is consistent with waiting times in a resting state until noise triggers a dropout, and the other is consistent with dropouts occurring during the return to the resting state, which have a clear deterministic component. The method we describe can be a powerful tool for inferring signatures of determinism in the dynamics of complex systems in noisy environments, at an event-level description of their dynamics.

A study of the limitations of linear theory methods as applied to sonic boom calculations

NASA Technical Reports Server (NTRS)

Darden, Christine M.

1990-01-01

Current sonic boom minimization theories have been reviewed to emphasize the capabilities and flexibilities of the methods. Flexibility is important because it is necessary for the designer to meet optimized area constraints while reducing the impact on vehicle aerodynamic performance. Preliminary comparisons of sonic booms predicted for two Mach 3 concepts illustrate the benefits of shaping. Finally, for very simple bodies of revolution, sonic boom predictions were made using two methods - a modified linear theory method and a nonlinear method - for signature shapes which were both farfield N-waves and midfield waves. Preliminary analysis on these simple bodies verified that current modified linear theory prediction methods become inadequate for predicting midfield signatures for Mach numbers above 3. The importance of impulse is sonic boom disturbance and the importance of three-dimensional effects which could not be simulated with the bodies of revolution will determine the validity of current modified linear theory methods in predicting midfield signatures at lower Mach numbers.

Relationship between Effective Application of Machine Learning and Malware Detection: A Quantitative Study

ERIC Educational Resources Information Center

Enfinger, Kerry Wayne

2016-01-01

The number of malicious files present in the public domain continues to rise at a substantial rate. Current anti-malware software utilizes a signature-based method to detect the presence of malicious software. Generating these pattern signatures is time consuming due to malicious code complexity and the need for expert analysis, however, by making…

Multi-look fusion identification: a paradigm shift from quality to quantity in data samples

NASA Astrophysics Data System (ADS)

Wong, S.

2009-05-01

A multi-look identification method known as score-level fusion is found to be capable of achieving very high identification accuracy, even when low quality target signatures are used. Analysis using measured ground vehicle radar signatures has shown that a 97% correct identification rate can be achieved using this multi-look fusion method; in contrast, only a 37% accuracy rate is obtained when single target signature input is used. The results suggest that quantity can be used to replace quality of the target data in improving identification accuracy. With the advent of sensor technology, a large amount of target signatures of marginal quality can be captured routinely. This quantity over quality approach allows maximum exploitation of the available data to improve the target identification performance and this could have the potential of being developed into a disruptive technology.

Isotopic Characterisation of Methane Emissions: use of Keeling-plot Methods to Identify Source Signatures in Boreal Wetlands and Other Settings

NASA Astrophysics Data System (ADS)

Fisher, R. E.; Lowry, D.; France, J.; Lanoiselle, M.; Zazzeri, G.; Nisbet, E. G.

2012-12-01

Different methane sources have different δ13CCH4 and δDCH4 signatures, which potentially provides a powerful constraint on models of methane emission budgets. However source signatures remain poorly known and need to be studied in more detail if isotopic measurements of ambient air are to be used to constrain regional and global emissions. The Keeling plot method (plotting δ13CCH4 or δDCH4 against 1/CH4 concentration in samples of ambient air in the close vicinity of known sources) directly assesses the source signature of the methane that is actually emitted to the air. This contrasts with chamber studies, measuring air within a chamber, where local micro-meteorological and microbiological processes are occurring. Keeling plot methods have been applied to a wide variety of settings in this study. The selection of appropriate background measurements for Keeling plot analysis is also considered. The method has been used on a local scale to identify the source signature of summer emissions from subarctic wetlands in Fennoscandia. Samples are collected from low height (0.3-3m) over the wetlands during 24-hour periods, to collect daily emissions maxima (warm late afternoons), inversion maxima (at the coldest time of the 24hr daylight: usually earliest morning), and ambient minima when mixing occurs (often mid afternoon). Some results are comparable to parallel chamber studies, but in other cases there are small but significant shifts between CH4 in chamber air and CH4 that is dispersing in the above-ground air. On a regional to continental scale the isotopic signature of bulk sources of emissions can be identified using Keeling plots. The methodology is very applicable for use in urban and urban-rural settings. For example, the winter SE monsoon sweeps from inland central Asia over China to Hong Kong. Application of back trajectory analysis and Keeling plot methods implied coal emissions may be a significant Chinese source of methane in January, although in other months biological sources dominate. Similarly, in London the method has been used to test the London methane emission inventory.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development.

PubMed

Ozerov, Ivan V; Lezhnina, Ksenia V; Izumchenko, Evgeny; Artemov, Artem V; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N; Labat, Ivan; West, Michael D; Buzdin, Anton; Cantor, Charles R; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-11-16

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development

PubMed Central

Ozerov, Ivan V.; Lezhnina, Ksenia V.; Izumchenko, Evgeny; Artemov, Artem V.; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N.; Labat, Ivan; West, Michael D.; Buzdin, Anton; Cantor, Charles R.; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-01-01

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy. PMID:27848968

Simulating realistic predator signatures in quantitative fatty acid signature analysis

USGS Publications Warehouse

Bromaghin, Jeffrey F.

2015-01-01

Diet estimation is an important field within quantitative ecology, providing critical insights into many aspects of ecology and community dynamics. Quantitative fatty acid signature analysis (QFASA) is a prominent method of diet estimation, particularly for marine mammal and bird species. Investigators using QFASA commonly use computer simulation to evaluate statistical characteristics of diet estimators for the populations they study. Similar computer simulations have been used to explore and compare the performance of different variations of the original QFASA diet estimator. In both cases, computer simulations involve bootstrap sampling prey signature data to construct pseudo-predator signatures with known properties. However, bootstrap sample sizes have been selected arbitrarily and pseudo-predator signatures therefore may not have realistic properties. I develop an algorithm to objectively establish bootstrap sample sizes that generates pseudo-predator signatures with realistic properties, thereby enhancing the utility of computer simulation for assessing QFASA estimator performance. The algorithm also appears to be computationally efficient, resulting in bootstrap sample sizes that are smaller than those commonly used. I illustrate the algorithm with an example using data from Chukchi Sea polar bears (Ursus maritimus) and their marine mammal prey. The concepts underlying the approach may have value in other areas of quantitative ecology in which bootstrap samples are post-processed prior to their use.

Distance measures and optimization spaces in quantitative fatty acid signature analysis

USGS Publications Warehouse

Bromaghin, Jeffrey F.; Rode, Karyn D.; Budge, Suzanne M.; Thiemann, Gregory W.

2015-01-01

Quantitative fatty acid signature analysis has become an important method of diet estimation in ecology, especially marine ecology. Controlled feeding trials to validate the method and estimate the calibration coefficients necessary to account for differential metabolism of individual fatty acids have been conducted with several species from diverse taxa. However, research into potential refinements of the estimation method has been limited. We compared the performance of the original method of estimating diet composition with that of five variants based on different combinations of distance measures and calibration-coefficient transformations between prey and predator fatty acid signature spaces. Fatty acid signatures of pseudopredators were constructed using known diet mixtures of two prey data sets previously used to estimate the diets of polar bears Ursus maritimus and gray seals Halichoerus grypus, and their diets were then estimated using all six variants. In addition, previously published diets of Chukchi Sea polar bears were re-estimated using all six methods. Our findings reveal that the selection of an estimation method can meaningfully influence estimates of diet composition. Among the pseudopredator results, which allowed evaluation of bias and precision, differences in estimator performance were rarely large, and no one estimator was universally preferred, although estimators based on the Aitchison distance measure tended to have modestly superior properties compared to estimators based on the Kullback-Leibler distance measure. However, greater differences were observed among estimated polar bear diets, most likely due to differential estimator sensitivity to assumption violations. Our results, particularly the polar bear example, suggest that additional research into estimator performance and model diagnostics is warranted.

Analysis of thematic mapper simulator data collected over eastern North Dakota

NASA Technical Reports Server (NTRS)

Anderson, J. E. (Principal Investigator)

1982-01-01

The results of the analysis of aircraft-acquired thematic mapper simulator (TMS) data, collected to investigate the utility of thematic mapper data in crop area and land cover estimates, are discussed. Results of the analysis indicate that the seven-channel TMS data are capable of delineating the 13 crop types included in the study to an overall pixel classification accuracy of 80.97% correct, with relative efficiencies for four crop types examined between 1.62 and 26.61. Both supervised and unsupervised spectral signature development techniques were evaluated. The unsupervised methods proved to be inferior (based on analysis of variance) for the majority of crop types considered. Given the ground truth data set used for spectral signature development as well as evaluation of performance, it is possible to demonstrate which signature development technique would produce the highest percent correct classification for each crop type.

Extraction of small boat harmonic signatures from passive sonar.

PubMed

Ogden, George L; Zurk, Lisa M; Jones, Mark E; Peterson, Mary E

2011-06-01

This paper investigates the extraction of acoustic signatures from small boats using a passive sonar system. Noise radiated from a small boats consists of broadband noise and harmonically related tones that correspond to engine and propeller specifications. A signal processing method to automatically extract the harmonic structure of noise radiated from small boats is developed. The Harmonic Extraction and Analysis Tool (HEAT) estimates the instantaneous fundamental frequency of the harmonic tones, refines the fundamental frequency estimate using a Kalman filter, and automatically extracts the amplitudes of the harmonic tonals to generate a harmonic signature for the boat. Results are presented that show the HEAT algorithms ability to extract these signatures. © 2011 Acoustical Society of America

Highly sensitive molecular diagnosis of prostate cancer using surplus material washed off from biopsy needles

PubMed Central

Bermudo, R; Abia, D; Mozos, A; García-Cruz, E; Alcaraz, A; Ortiz, Á R; Thomson, T M; Fernández, P L

2011-01-01

Introduction: Currently, final diagnosis of prostate cancer (PCa) is based on histopathological analysis of needle biopsies, but this process often bears uncertainties due to small sample size, tumour focality and pathologist's subjective assessment. Methods: Prostate cancer diagnostic signatures were generated by applying linear discriminant analysis to microarray and real-time RT–PCR (qRT–PCR) data from normal and tumoural prostate tissue samples. Additionally, after removal of biopsy tissues, material washed off from transrectal biopsy needles was used for molecular profiling and discriminant analysis. Results: Linear discriminant analysis applied to microarray data for a set of 318 genes differentially expressed between non-tumoural and tumoural prostate samples produced 26 gene signatures, which classified the 84 samples used with 100% accuracy. To identify signatures potentially useful for the diagnosis of prostate biopsies, surplus material washed off from routine biopsy needles from 53 patients was used to generate qRT–PCR data for a subset of 11 genes. This analysis identified a six-gene signature that correctly assigned the biopsies as benign or tumoural in 92.6% of the cases, with 88.8% sensitivity and 96.1% specificity. Conclusion: Surplus material from prostate needle biopsies can be used for minimal-size gene signature analysis for sensitive and accurate discrimination between non-tumoural and tumoural prostates, without interference with current diagnostic procedures. This approach could be a useful adjunct to current procedures in PCa diagnosis. PMID:22009027

Identification of atypical flight patterns

NASA Technical Reports Server (NTRS)

Statler, Irving C. (Inventor); Ferryman, Thomas A. (Inventor); Amidan, Brett G. (Inventor); Whitney, Paul D. (Inventor); White, Amanda M. (Inventor); Willse, Alan R. (Inventor); Cooley, Scott K. (Inventor); Jay, Joseph Griffith (Inventor); Lawrence, Robert E. (Inventor); Mosbrucker, Chris (Inventor)

2005-01-01

Method and system for analyzing aircraft data, including multiple selected flight parameters for a selected phase of a selected flight, and for determining when the selected phase of the selected flight is atypical, when compared with corresponding data for the same phase for other similar flights. A flight signature is computed using continuous-valued and discrete-valued flight parameters for the selected flight parameters and is optionally compared with a statistical distribution of other observed flight signatures, yielding atypicality scores for the same phase for other similar flights. A cluster analysis is optionally applied to the flight signatures to define an optimal collection of clusters. A level of atypicality for a selected flight is estimated, based upon an index associated with the cluster analysis.

Radar cross section fundamentals for the aircraft designer

NASA Technical Reports Server (NTRS)

Stadmore, H. A.

1979-01-01

Various aspects of radar cross-section (RCS) techniques are summarized, with emphasis placed on fundamental electromagnetic phenomena, such as plane and spherical wave formulations, and the definition of RCS is given in the far-field sense. The basic relationship between electronic countermeasures and a signature level is discussed in terms of the detectability range of a target vehicle. Fundamental radar-signature analysis techniques, such as the physical-optics and geometrical-optics approximations, are presented along with examples in terms of aircraft components. Methods of analysis based on the geometrical theory of diffraction are considered and various wave-propagation phenomena are related to local vehicle geometry. Typical vehicle components are also discussed, together with their contribution to total vehicle RCS and their individual signature sensitivities.

Multivariate Statistical Analysis of Orthogonal Mass Spectral Data for the Identification of Chemical Attribution Signatures of 3-Methylfentanyl

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayer, B. P.; Valdez, C. A.; DeHope, A. J.

Critical to many modern forensic investigations is the chemical attribution of the origin of an illegal drug. This process greatly relies on identification of compounds indicative of its clandestine or commercial production. The results of these studies can yield detailed information on method of manufacture, sophistication of the synthesis operation, starting material source, and final product. In the present work, chemical attribution signatures (CAS) associated with the synthesis of the analgesic 3- methylfentanyl, N-(3-methyl-1-phenethylpiperidin-4-yl)-N-phenylpropanamide, were investigated. Six synthesis methods were studied in an effort to identify and classify route-specific signatures. These methods were chosen to minimize the use of scheduledmore » precursors, complicated laboratory equipment, number of overall steps, and demanding reaction conditions. Using gas and liquid chromatographies combined with mass spectrometric methods (GC-QTOF and LC-QTOF) in conjunction with inductivelycoupled plasma mass spectrometry (ICP-MS), over 240 distinct compounds and elements were monitored. As seen in our previous work with CAS of fentanyl synthesis the complexity of the resultant data matrix necessitated the use of multivariate statistical analysis. Using partial least squares discriminant analysis (PLS-DA), 62 statistically significant, route-specific CAS were identified. Statistical classification models using a variety of machine learning techniques were then developed with the ability to predict the method of 3-methylfentanyl synthesis from three blind crude samples generated by synthetic chemists without prior experience with these methods.« less

Instrumentation for motor-current signature analysis using synchronous sampling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Castleberry, K.N.

1996-07-01

Personnel in the Instrumentation and Controls Division at Oak Ridge National Laboratory, in association with the United States Enrichment Corporation, the U.S. Navy, and various Department of Energy sponsors, have been involved in the development and application of motor-current signature analysis for several years. In that time, innovation in the field has resulted in major improvements in signal processing, analysis, and system performance and capabilities. Recent work has concentrated on industrial implementation of one of the most promising new techniques. This report describes the developed method and the instrumentation package that is being used to investigate and develop potential applications.

Using multi-scale entropy and principal component analysis to monitor gears degradation via the motor current signature analysis

NASA Astrophysics Data System (ADS)

Aouabdi, Salim; Taibi, Mahmoud; Bouras, Slimane; Boutasseta, Nadir

2017-06-01

This paper describes an approach for identifying localized gear tooth defects, such as pitting, using phase currents measured from an induction machine driving the gearbox. A new tool of anomaly detection based on multi-scale entropy (MSE) algorithm SampEn which allows correlations in signals to be identified over multiple time scales. The motor current signature analysis (MCSA) in conjunction with principal component analysis (PCA) and the comparison of observed values with those predicted from a model built using nominally healthy data. The Simulation results show that the proposed method is able to detect gear tooth pitting in current signals.

A two-step sensitivity analysis for hydrological signatures in Jinhua River Basin, East China

NASA Astrophysics Data System (ADS)

Pan, S.; Fu, G.; Chiang, Y. M.; Xu, Y. P.

2016-12-01

Owing to model complexity and large number of parameters, calibration and sensitivity analysis are difficult processes for distributed hydrological models. In this study, a two-step sensitivity analysis approach is proposed for analyzing the hydrological signatures in Jinhua River Basin, East China, using the Distributed Hydrology-Soil-Vegetation Model (DHSVM). A rough sensitivity analysis is firstly conducted to obtain preliminary influential parameters via Analysis of Variance. The number of parameters was greatly reduced from eighteen-three to sixteen. Afterwards, the sixteen parameters are further analyzed based on a variance-based global sensitivity analysis, i.e., Sobol's sensitivity analysis method, to achieve robust sensitivity rankings and parameter contributions. Parallel-Computing is applied to reduce computational burden in variance-based sensitivity analysis. The results reveal that only a few number of model parameters are significantly sensitive, including rain LAI multiplier, lateral conductivity, porosity, field capacity, wilting point of clay loam, understory monthly LAI, understory minimum resistance and root zone depths of croplands. Finally several hydrological signatures are used for investigating the performance of DHSVM. Results show that high value of efficiency criteria didn't indicate excellent performance of hydrological signatures. For most samples from Sobol's sensitivity analysis, water yield was simulated very well. However, lowest and maximum annual daily runoffs were underestimated. Most of seven-day minimum runoffs were overestimated. Nevertheless, good performances of the three signatures above still exist in a number of samples. Analysis of peak flow shows that small and medium floods are simulated perfectly while slight underestimations happen to large floods. The work in this study helps to further multi-objective calibration of DHSVM model and indicates where to improve the reliability and credibility of model simulation.

Comprehensive sieve analysis of breakthrough HIV-1 sequences in the RV144 vaccine efficacy trial.

PubMed

Edlefsen, Paul T; Rolland, Morgane; Hertz, Tomer; Tovanabutra, Sodsai; Gartland, Andrew J; deCamp, Allan C; Magaret, Craig A; Ahmed, Hasan; Gottardo, Raphael; Juraska, Michal; McCoy, Connor; Larsen, Brendan B; Sanders-Buell, Eric; Carrico, Chris; Menis, Sergey; Kijak, Gustavo H; Bose, Meera; Arroyo, Miguel A; O'Connell, Robert J; Nitayaphan, Sorachai; Pitisuttithum, Punnee; Kaewkungwal, Jaranit; Rerks-Ngarm, Supachai; Robb, Merlin L; Kirys, Tatsiana; Georgiev, Ivelin S; Kwong, Peter D; Scheffler, Konrad; Pond, Sergei L Kosakovsky; Carlson, Jonathan M; Michael, Nelson L; Schief, William R; Mullins, James I; Kim, Jerome H; Gilbert, Peter B

2015-02-01

The RV144 clinical trial showed the partial efficacy of a vaccine regimen with an estimated vaccine efficacy (VE) of 31% for protecting low-risk Thai volunteers against acquisition of HIV-1. The impact of vaccine-induced immune responses can be investigated through sieve analysis of HIV-1 breakthrough infections (infected vaccine and placebo recipients). A V1/V2-targeted comparison of the genomes of HIV-1 breakthrough viruses identified two V2 amino acid sites that differed between the vaccine and placebo groups. Here we extended the V1/V2 analysis to the entire HIV-1 genome using an array of methods based on individual sites, k-mers and genes/proteins. We identified 56 amino acid sites or "signatures" and 119 k-mers that differed between the vaccine and placebo groups. Of those, 19 sites and 38 k-mers were located in the regions comprising the RV144 vaccine (Env-gp120, Gag, and Pro). The nine signature sites in Env-gp120 were significantly enriched for known antibody-associated sites (p = 0.0021). In particular, site 317 in the third variable loop (V3) overlapped with a hotspot of antibody recognition, and sites 369 and 424 were linked to CD4 binding site neutralization. The identified signature sites significantly covaried with other sites across the genome (mean = 32.1) more than did non-signature sites (mean = 0.9) (p < 0.0001), suggesting functional and/or structural relevance of the signature sites. Since signature sites were not preferentially restricted to the vaccine immunogens and because most of the associations were insignificant following correction for multiple testing, we predict that few of the genetic differences are strongly linked to the RV144 vaccine-induced immune pressure. In addition to presenting results of the first complete-genome analysis of the breakthrough infections in the RV144 trial, this work describes a set of statistical methods and tools applicable to analysis of breakthrough infection genomes in general vaccine efficacy trials for diverse pathogens.

Mixed-Fidelity Approach for Design of Low-Boom Supersonic Aircraft

NASA Technical Reports Server (NTRS)

Li, Wu; Shields, Elwood; Geiselhart, Karl

2011-01-01

This paper documents a mixed-fidelity approach for the design of low-boom supersonic aircraft with a focus on fuselage shaping.A low-boom configuration that is based on low-fidelity analysis is used as the baseline. The fuselage shape is modified iteratively to obtain a configuration with an equivalent-area distribution derived from computational fluid dynamics analysis that attempts to match a predetermined low-boom target area distribution and also yields a low-boom ground signature. The ground signature of the final configuration is calculated by using a state-of-the-art computational-fluid-dynamics-based boom analysis method that generates accurate midfield pressure distributions for propagation to the ground with ray tracing. The ground signature that is propagated from a midfield pressure distribution has a shaped ramp front, which is similar to the ground signature that is propagated from the computational fluid dynamics equivalent-area distribution. This result supports the validity of low-boom supersonic configuration design by matching a low-boom equivalent-area target, which is easier to accomplish than matching a low-boom midfield pressure target.

SurvMicro: assessment of miRNA-based prognostic signatures for cancer clinical outcomes by multivariate survival analysis.

PubMed

Aguirre-Gamboa, Raul; Trevino, Victor

2014-06-01

MicroRNAs (miRNAs) play a key role in post-transcriptional regulation of mRNA levels. Their function in cancer has been studied by high-throughput methods generating valuable sources of public information. Thus, miRNA signatures predicting cancer clinical outcomes are emerging. An important step to propose miRNA-based biomarkers before clinical validation is their evaluation in independent cohorts. Although it can be carried out using public data, such task is time-consuming and requires a specialized analysis. Therefore, to aid and simplify the evaluation of prognostic miRNA signatures in cancer, we developed SurvMicro, a free and easy-to-use web tool that assesses miRNA signatures from publicly available miRNA profiles using multivariate survival analysis. SurvMicro is composed of a wide and updated database of >40 cohorts in different tissues and a web tool where survival analysis can be done in minutes. We presented evaluations to portray the straightforward functionality of SurvMicro in liver and lung cancer. To our knowledge, SurvMicro is the only bioinformatic tool that aids the evaluation of multivariate prognostic miRNA signatures in cancer. SurvMicro and its tutorial are freely available at http://bioinformatica.mty.itesm.mx/SurvMicro. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemia.

PubMed

Yang, Xinan Holly; Li, Meiyi; Wang, Bin; Zhu, Wanqi; Desgardin, Aurelie; Onel, Kenan; de Jong, Jill; Chen, Jianjun; Chen, Luonan; Cunningham, John M

2015-03-24

Genes that regulate stem cell function are suspected to exert adverse effects on prognosis in malignancy. However, diverse cancer stem cell signatures are difficult for physicians to interpret and apply clinically. To connect the transcriptome and stem cell biology, with potential clinical applications, we propose a novel computational "gene-to-function, snapshot-to-dynamics, and biology-to-clinic" framework to uncover core functional gene-sets signatures. This framework incorporates three function-centric gene-set analysis strategies: a meta-analysis of both microarray and RNA-seq data, novel dynamic network mechanism (DNM) identification, and a personalized prognostic indicator analysis. This work uses complex disease acute myeloid leukemia (AML) as a research platform. We introduced an adjustable "soft threshold" to a functional gene-set algorithm and found that two different analysis methods identified distinct gene-set signatures from the same samples. We identified a 30-gene cluster that characterizes leukemic stem cell (LSC)-depleted cells and a 25-gene cluster that characterizes LSC-enriched cells in parallel; both mark favorable-prognosis in AML. Genes within each signature significantly share common biological processes and/or molecular functions (empirical p = 6e-5 and 0.03 respectively). The 25-gene signature reflects the abnormal development of stem cells in AML, such as AURKA over-expression. We subsequently determined that the clinical relevance of both signatures is independent of known clinical risk classifications in 214 patients with cytogenetically normal AML. We successfully validated the prognosis of both signatures in two independent cohorts of 91 and 242 patients respectively (log-rank p < 0.0015 and 0.05; empirical p < 0.015 and 0.08). The proposed algorithms and computational framework will harness systems biology research because they efficiently translate gene-sets (rather than single genes) into biological discoveries about AML and other complex diseases.

Factor models for cancer signatures

NASA Astrophysics Data System (ADS)

Kakushadze, Zura; Yu, Willie

2016-11-01

We present a novel method for extracting cancer signatures by applying statistical risk models (http://ssrn.com/abstract=2732453) from quantitative finance to cancer genome data. Using 1389 whole genome sequenced samples from 14 cancers, we identify an ;overall; mode of somatic mutational noise. We give a prescription for factoring out this noise and source code for fixing the number of signatures. We apply nonnegative matrix factorization (NMF) to genome data aggregated by cancer subtype and filtered using our method. The resultant signatures have substantially lower variability than those from unfiltered data. Also, the computational cost of signature extraction is cut by about a factor of 10. We find 3 novel cancer signatures, including a liver cancer dominant signature (96% contribution) and a renal cell carcinoma signature (70% contribution). Our method accelerates finding new cancer signatures and improves their overall stability. Reciprocally, the methods for extracting cancer signatures could have interesting applications in quantitative finance.

Seismic signature analysis for discrimination of people from animals

NASA Astrophysics Data System (ADS)

Damarla, Thyagaraju; Mehmood, Asif; Sabatier, James M.

2013-05-01

Cadence analysis has been the main focus for discriminating between the seismic signatures of people and animals. However, cadence analysis fails when multiple targets are generating the signatures. We analyze the mechanism of human walking and the signature generated by a human walker, and compare it with the signature generated by a quadruped. We develop Fourier-based analysis to differentiate the human signatures from the animal signatures. We extract a set of basis vectors to represent the human and animal signatures using non-negative matrix factorization, and use them to separate and classify both the targets. Grazing animals such as deer, cows, etc., often produce sporadic signals as they move around from patch to patch of grass and one must characterize them so as to differentiate their signatures from signatures generated by a horse steadily walking along a path. These differences in the signatures are used in developing a robust algorithm to distinguish the signatures of animals from humans. The algorithm is tested on real data collected in a remote area.

A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

PubMed Central

2009-01-01

Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical. Conclusion Feature variability can have a strong impact on breast cancer signature composition, as well as the classification of individual patient samples. We therefore strongly recommend that feature variability is considered in analyzing data from microarray breast cancer expression profiling experiments. PMID:19941644

Search by photo methodology for signature properties assessment by human observers

NASA Astrophysics Data System (ADS)

Selj, Gorm K.; Heinrich, Daniela H.

2015-05-01

Reliable, low-cost and simple methods for assessment of signature properties for military purposes are very important. In this paper we present such an approach that uses human observers in a search by photo assessment of signature properties of generic test targets. The method was carried out by logging a large number of detection times of targets recorded in relevant terrain backgrounds. The detection times were harvested by using human observers searching for targets in scene images shown by a high definition pc screen. All targets were identically located in each "search image", allowing relative comparisons (and not just rank by order) of targets. To avoid biased detections, each observer only searched for one target per scene. Statistical analyses were carried out for the detection times data. Analysis of variance was chosen if detection times distribution associated with all targets satisfied normality, and non-parametric tests, such as Wilcoxon's rank test, if otherwise. The new methodology allows assessment of signature properties in a reproducible, rapid and reliable setting. Such assessments are very complex as they must sort out what is of relevance in a signature test, but not loose information of value. We believe that choosing detection times as the primary variable for a comparison of signature properties, allows a careful and necessary inspection of observer data as the variable is continuous rather than discrete. Our method thus stands in opposition to approaches based on detections by subsequent, stepwise reductions in distance to target, or based on probability of detection.

Analysis of an Indirect Neutron Signature for Enhanced UF6 Cylinder Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kulisek, Jonathan A.; McDonald, Benjamin S.; Smith, Leon E.

2017-02-21

The International Atomic Energy Agency (IAEA) currently uses handheld gamma-ray spectrometers combined with ultrasonic wall-thickness gauges to verify the declared enrichment of uranium hexafluoride (UF6) cylinders. The current method provides relatively low accuracy for the assay of 235U enrichment, especially for natural and depleted UF6. Furthermore, the current method provides no capability to assay the absolute mass of 235U in the cylinder due to the localized instrument geometry and limited penetration of the 186-keV gamma-ray signature from 235U. Also, the current verification process is a time-consuming component of on-site inspections at uranium enrichment plants. Toward the goal of a more-capablemore » cylinder assay method, the Pacific Northwest National Laboratory has developed the hybrid enrichment verification array (HEVA). HEVA measures both the traditional 186-keV direct signature and a non-traditional, high-energy neutron-induced signature (HEVANT). HEVANT enables full-volume assay of UF6 cylinders by exploiting the relatively larger mean free paths of the neutrons emitted from the UF6. In this work, Monte Carlo modeling is used as the basis for characterizing HEVANT in terms of the individual contributions to HEVANT from nuclides and hardware components. Monte Carlo modeling is also used to quantify the intrinsic efficiency of HEVA for neutron detection in a cylinder-assay geometry. Modeling predictions are validated against neutron-induced gamma-ray spectra from laboratory measurements and a relatively large population of Type 30B cylinders spanning a range of enrichments. Implications of the analysis and findings on the viability of HEVA for cylinder verification are discussed, such as the resistance of the HEVANT signature to manipulation by the nearby placement of neutron-conversion materials.« less

Formal Methods for Cryptographic Protocol Analysis: Emerging Issues and Trends

DTIC Science & Technology

2003-01-01

signatures , which depend upon the homomor- phic properties of RSA. Other algorithms and data structures, such as Chaum mixes [17], designed for...Communications Security, pages 176–185. ACM, Novem- ber 2001. [17] D. Chaum . Untraceable electronic mail, return addresses and digital signatures ...something like the Diffie- Hellman algorithm, which depends, as a minimum, on the commutative properties of exponentiation, or something like Chaum’s blinded

Mechatronics technology in predictive maintenance method

NASA Astrophysics Data System (ADS)

Majid, Nurul Afiqah A.; Muthalif, Asan G. A.

2017-11-01

This paper presents recent mechatronics technology that can help to implement predictive maintenance by combining intelligent and predictive maintenance instrument. Vibration Fault Simulation System (VFSS) is an example of mechatronics system. The focus of this study is the prediction on the use of critical machines to detect vibration. Vibration measurement is often used as the key indicator of the state of the machine. This paper shows the choice of the appropriate strategy in the vibration of diagnostic process of the mechanical system, especially rotating machines, in recognition of the failure during the working process. In this paper, the vibration signature analysis is implemented to detect faults in rotary machining that includes imbalance, mechanical looseness, bent shaft, misalignment, missing blade bearing fault, balancing mass and critical speed. In order to perform vibration signature analysis for rotating machinery faults, studies have been made on how mechatronics technology is used as predictive maintenance methods. Vibration Faults Simulation Rig (VFSR) is designed to simulate and understand faults signatures. These techniques are based on the processing of vibrational data in frequency-domain. The LabVIEW-based spectrum analyzer software is developed to acquire and extract frequency contents of faults signals. This system is successfully tested based on the unique vibration fault signatures that always occur in a rotating machinery.

An archaeal genomic signature

NASA Technical Reports Server (NTRS)

Graham, D. E.; Overbeek, R.; Olsen, G. J.; Woese, C. R.

2000-01-01

Comparisons of complete genome sequences allow the most objective and comprehensive descriptions possible of a lineage's evolution. This communication uses the completed genomes from four major euryarchaeal taxa to define a genomic signature for the Euryarchaeota and, by extension, the Archaea as a whole. The signature is defined in terms of the set of protein-encoding genes found in at least two diverse members of the euryarchaeal taxa that function uniquely within the Archaea; most signature proteins have no recognizable bacterial or eukaryal homologs. By this definition, 351 clusters of signature proteins have been identified. Functions of most proteins in this signature set are currently unknown. At least 70% of the clusters that contain proteins from all the euryarchaeal genomes also have crenarchaeal homologs. This conservative set, which appears refractory to horizontal gene transfer to the Bacteria or the Eukarya, would seem to reflect the significant innovations that were unique and fundamental to the archaeal "design fabric." Genomic protein signature analysis methods may be extended to characterize the evolution of any phylogenetically defined lineage. The complete set of protein clusters for the archaeal genomic signature is presented as supplementary material (see the PNAS web site, www.pnas.org).

In-depth analysis and characterization of a dual damascene process with respect to different CD

NASA Astrophysics Data System (ADS)

Krause, Gerd; Hofmann, Detlef; Habets, Boris; Buhl, Stefan; Gutsch, Manuela; Lopez-Gomez, Alberto; Kim, Wan-Soo; Thrun, Xaver

2018-03-01

In a 200 mm high volume environment, we studied data from a dual damascene process. Dual damascene is a combination of lithography, etch and CMP that is used to create copper lines and contacts in one single step. During these process steps, different metal CD are measured by different measurement methods. In this study, we analyze the key numbers of the different measurements after different process steps and develop simple models to predict the electrical behavior* . In addition, radial profiles have been analyzed of both inline measurement parameters and electrical parameters. A matching method was developed based on inline and electrical data. Finally, correlation analysis for radial signatures is presented that can be used to predict excursions in electrical signatures.

76 FR 60372 - Application for Annuity or Lump Sum

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-29

... regulations to allow alternative signature methods in addition to the traditional pen-and-ink or ``wet... to allow signature alternatives to the traditional pen-and-ink (``wet'') signature. The Board changes... the agency. The second alternate method is referred to as an ``alternative signature'' or ``signature...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, S; Jaing, C

The goal of this project is to develop forensic genotyping assays for select agent viruses, addressing a significant capability gap for the viral bioforensics and law enforcement community. We used a multipronged approach combining bioinformatics analysis, PCR-enriched samples, microarrays and TaqMan assays to develop high resolution and cost effective genotyping methods for strain level forensic discrimination of viruses. We have leveraged substantial experience and efficiency gained through year 1 on software development, SNP discovery, TaqMan signature design and phylogenetic signature mapping to scale up the development of forensics signatures in year 2. In this report, we have summarized the Taqmanmore » signature development for South American hemorrhagic fever viruses, tick-borne encephalitis viruses and henipaviruses, Old World Arenaviruses, filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus and Japanese encephalitis virus.« less

Resolving prokaryotic taxonomy without rRNA: longer oligonucleotide word lengths improve genome and metagenome taxonomic classification.

PubMed

Alsop, Eric B; Raymond, Jason

2013-01-01

Oligonucleotide signatures, especially tetranucleotide signatures, have been used as method for homology binning by exploiting an organism's inherent biases towards the use of specific oligonucleotide words. Tetranucleotide signatures have been especially useful in environmental metagenomics samples as many of these samples contain organisms from poorly classified phyla which cannot be easily identified using traditional homology methods, including NCBI BLAST. This study examines oligonucleotide signatures across 1,424 completed genomes from across the tree of life, substantially expanding upon previous work. A comprehensive analysis of mononucleotide through nonanucleotide word lengths suggests that longer word lengths substantially improve the classification of DNA fragments across a range of sizes of relevance to high throughput sequencing. We find that, at present, heptanucleotide signatures represent an optimal balance between prediction accuracy and computational time for resolving taxonomy using both genomic and metagenomic fragments. We directly compare the ability of tetranucleotide and heptanucleotide world lengths (tetranucleotide signatures are the current standard for oligonucleotide word usage analyses) for taxonomic binning of metagenome reads. We present evidence that heptanucleotide word lengths consistently provide more taxonomic resolving power, particularly in distinguishing between closely related organisms that are often present in metagenomic samples. This implies that longer oligonucleotide word lengths should replace tetranucleotide signatures for most analyses. Finally, we show that the application of longer word lengths to metagenomic datasets leads to more accurate taxonomic binning of DNA scaffolds and have the potential to substantially improve taxonomic assignment and assembly of metagenomic data.

Design of Experiments for Both Experimental and Analytical Study of Exhaust Plume Effects on Sonic Boom

NASA Technical Reports Server (NTRS)

Castner, Raymond S.

2009-01-01

Computational fluid dynamics (CFD) analysis has been performed to study the plume effects on sonic boom signature for isolated nozzle configurations. The objectives of these analyses were to provide comparison to past work using modern CFD analysis tools, to investigate the differences of high aspect ratio nozzles to circular (axisymmetric) nozzles, and to report the effects of under expanded nozzle operation on boom signature. CFD analysis was used to address the plume effects on sonic boom signature from a baseline exhaust nozzle. Nearfield pressure signatures were collected for nozzle pressure ratios (NPRs) between 6 and 10. A computer code was used to extrapolate these signatures to a ground-observed sonic boom N-wave. Trends show that there is a reduction in sonic boom N-wave signature as NPR is increased from 6 to 10. As low boom designs are developed and improved, there will be a need for understanding the interaction between the aircraft boat tail shocks and the exhaust nozzle plume. These CFD analyses will provide a baseline study for future analysis efforts. For further study, a design of experiments has been conducted to develop a hybrid method where both CFD and small scale wind tunnel testing will validate the observed trends. The CFD and testing will be used to screen a number of factors which are important to low boom propulsion integration, including boat tail angle, nozzle geometry, and the effect of spacing and stagger on nozzle pairs. To design the wind tunnel experiment, CFD was instrumental in developing a model which would provide adequate space to observe the nozzle and boat tail shock structure without interference from the wind tunnel walls.

Phenotypic signatures arising from unbalanced bacterial growth.

PubMed

Tan, Cheemeng; Smith, Robert Phillip; Tsai, Ming-Chi; Schwartz, Russell; You, Lingchong

2014-08-01

Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth condition. Here, we present a method to identify "phenotypic signatures" by time-frequency analysis of unbalanced growth curves measured with high temporal resolution. The signatures are then applied to differentiate amongst different bacterial strains or the same strain under different growth conditions, and to identify the essential architecture of the gene network underlying the observed growth dynamics. Our method has implications for both basic understanding of bacterial physiology and for the classification of bacterial strains.

Damage sensitivity investigations of EMI technique on different materials through coupled field analysis

NASA Astrophysics Data System (ADS)

Joshi, Bhrigu; Adhikari, Sailesh; Bhalla, Suresh

2016-04-01

This paper presents a comparative study through the piezoelectric coupled field analysis mode of finite element method (FEM) on detection of damages of varying magnitude, encompassing three different types of structural materials, using piezo impedance transducers. An aluminum block, a concrete block and a steel block of dimensions 48×48×10 mm were modelled in finite element software ANSYS. A PZT patch of 10×10×0.3 mm was also included in the model as surface bonded on the block. Coupled field analysis (CFA) was performed to obtain the admittance signatures of the piezo sensor in the frequency range of 0-250 kHz. The root mean square deviation (RMSD) index was employed to quantify the degree of variation of the signatures. It was found that concrete exhibited deviation in the signatures only with the change of damping values. However, the other two materials showed variation in the signatures even with changes in density and elasticity values in a small portion of the specimen. The comparative study shows that the PZT patches are more sensitive to damage detection in materials with low damping and the sensitivity typically decreases with increase in the damping.

Identification of Chemical Attribution Signatures of Fentanyl Syntheses Using Multivariate Statistical Analysis of Orthogonal Analytical Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayer, B. P.; Mew, D. A.; DeHope, A.

Attribution of the origin of an illicit drug relies on identification of compounds indicative of its clandestine production and is a key component of many modern forensic investigations. The results of these studies can yield detailed information on method of manufacture, starting material source, and final product - all critical forensic evidence. In the present work, chemical attribution signatures (CAS) associated with the synthesis of the analgesic fentanyl, N-(1-phenylethylpiperidin-4-yl)-N-phenylpropanamide, were investigated. Six synthesis methods, all previously published fentanyl synthetic routes or hybrid versions thereof, were studied in an effort to identify and classify route-specific signatures. 160 distinct compounds and inorganicmore » species were identified using gas and liquid chromatographies combined with mass spectrometric methods (GC-MS and LCMS/ MS-TOF) in conjunction with inductively coupled plasma mass spectrometry (ICPMS). The complexity of the resultant data matrix urged the use of multivariate statistical analysis. Using partial least squares discriminant analysis (PLS-DA), 87 route-specific CAS were classified and a statistical model capable of predicting the method of fentanyl synthesis was validated and tested against CAS profiles from crude fentanyl products deposited and later extracted from two operationally relevant surfaces: stainless steel and vinyl tile. This work provides the most detailed fentanyl CAS investigation to date by using orthogonal mass spectral data to identify CAS of forensic significance for illicit drug detection, profiling, and attribution.« less

Source signature estimation from multimode surface waves via mode-separated virtual real source method

NASA Astrophysics Data System (ADS)

Gao, Lingli; Pan, Yudi

2018-05-01

The correct estimation of the seismic source signature is crucial to exploration geophysics. Based on seismic interferometry, the virtual real source (VRS) method provides a model-independent way for source signature estimation. However, when encountering multimode surface waves, which are commonly seen in the shallow seismic survey, strong spurious events appear in seismic interferometric results. These spurious events introduce errors in the virtual-source recordings and reduce the accuracy of the source signature estimated by the VRS method. In order to estimate a correct source signature from multimode surface waves, we propose a mode-separated VRS method. In this method, multimode surface waves are mode separated before seismic interferometry. Virtual-source recordings are then obtained by applying seismic interferometry to each mode individually. Therefore, artefacts caused by cross-mode correlation are excluded in the virtual-source recordings and the estimated source signatures. A synthetic example showed that a correct source signature can be estimated with the proposed method, while strong spurious oscillation occurs in the estimated source signature if we do not apply mode separation first. We also applied the proposed method to a field example, which verified its validity and effectiveness in estimating seismic source signature from shallow seismic shot gathers containing multimode surface waves.

Simultaneous determination of the quantity and isotopic signature of dissolved organic matter from soil water using high-performance liquid chromatography/isotope ratio mass spectrometry.

PubMed

Scheibe, Andrea; Krantz, Lars; Gleixner, Gerd

2012-01-30

We assessed the accuracy and utility of a modified high-performance liquid chromatography/isotope ratio mass spectrometry (HPLC/IRMS) system for measuring the amount and stable carbon isotope signature of dissolved organic matter (DOM) <1 µm. Using a range of standard compounds as well as soil solutions sampled in the field, we compared the results of the HPLC/IRMS analysis with those from other methods for determining carbon and (13)C content. The conversion efficiency of the in-line wet oxidation of the HPLC/IRMS averaged 99.3% for a range of standard compounds. The agreement between HPLC/IRMS and other methods in the amount and isotopic signature of both standard compounds and soil water samples was excellent. For DOM concentrations below 10 mg C L(-1) (250 ng C total) pre-concentration or large volume injections are recommended in order to prevent background interferences. We were able to detect large differences in the (13)C signatures of soil solution DOM sampled in 10 cm depth of plots with either C3 or C4 vegetation and in two different parent materials. These measurements also demonstrated changes in the (13)C signature that demonstrate rapid loss of plant-derived C with depth. Overall the modified HLPC/IRMS system has the advantages of rapid sample preparation, small required sample volume and high sample throughput, while showing comparable performance with other methods for measuring the amount and isotopic signature of DOM. Copyright © 2011 John Wiley & Sons, Ltd.

A Mixed-Fidelity Approach for Design of Low-Boom Supersonic Aircraft

NASA Technical Reports Server (NTRS)

Li, Wu; Shields, Elwood; Geiselhart, Karl A.

2010-01-01

This paper documents a mixed-fidelity approach for the design of low-boom supersonic aircraft as a viable approach for designing a practical low-boom supersonic configuration. A low-boom configuration that is based on low-fidelity analysis is used as the baseline. Tail lift is included to help tailor the aft portion of the ground signature. A comparison of low- and high-fidelity analysis results demonstrates the necessity of using computational fluid dynamics (CFD) analysis in a low-boom supersonic configuration design process. The fuselage shape is modified iteratively to obtain a configuration with a CFD equivalent-area distribution that matches a predetermined low-boom target distribution. The mixed-fidelity approach can easily refine the low-fidelity low-boom baseline into a low-boom configuration with the use of CFD equivalent-area analysis. The ground signature of the final configuration is calculated by using a state-of-the-art CFD-based boom analysis method that generates accurate midfield pressure distributions for propagation to the ground with ray tracing. The ground signature that is propagated from a midfield pressure distribution has a shaped ramp front, which is similar to the ground signature that is propagated from the CFD equivalent-area distribution. This result confirms the validity of the low-boom supersonic configuration design by matching a low-boom equivalent-area target, which is easier to accomplish than matching a low-boom midfield pressure target.

Genome signature analysis of thermal virus metagenomes reveals Archaea and thermophilic signatures

PubMed Central

Pride, David T; Schoenfeld, Thomas

2008-01-01

Background Metagenomic analysis provides a rich source of biological information for otherwise intractable viral communities. However, study of viral metagenomes has been hampered by its nearly complete reliance on BLAST algorithms for identification of DNA sequences. We sought to develop algorithms for examination of viral metagenomes to identify the origin of sequences independent of BLAST algorithms. We chose viral metagenomes obtained from two hot springs, Bear Paw and Octopus, in Yellowstone National Park, as they represent simple microbial populations where comparatively large contigs were obtained. Thermal spring metagenomes have high proportions of sequences without significant Genbank homology, which has hampered identification of viruses and their linkage with hosts. To analyze each metagenome, we developed a method to classify DNA fragments using genome signature-based phylogenetic classification (GSPC), where metagenomic fragments are compared to a database of oligonucleotide signatures for all previously sequenced Bacteria, Archaea, and viruses. Results From both Bear Paw and Octopus hot springs, each assembled contig had more similarity to other metagenome contigs than to any sequenced microbial genome based on GSPC analysis, suggesting a genome signature common to each of these extreme environments. While viral metagenomes from Bear Paw and Octopus share some similarity, the genome signatures from each locale are largely unique. GSPC using a microbial database predicts most of the Octopus metagenome has archaeal signatures, while bacterial signatures predominate in Bear Paw; a finding consistent with those of Genbank BLAST. When using a viral database, the majority of the Octopus metagenome is predicted to belong to archaeal virus Families Globuloviridae and Fuselloviridae, while none of the Bear Paw metagenome is predicted to belong to archaeal viruses. As expected, when microbial and viral databases are combined, each of the Octopus and Bear Paw metagenomic contigs are predicted to belong to viruses rather than to any Bacteria or Archaea, consistent with the apparent viral origin of both metagenomes. Conclusion That BLAST searches identify no significant homologs for most metagenome contigs, while GSPC suggests their origin as archaeal viruses or bacteriophages, indicates GSPC provides a complementary approach in viral metagenomic analysis. PMID:18798991

Genome signature analysis of thermal virus metagenomes reveals Archaea and thermophilic signatures.

PubMed

Pride, David T; Schoenfeld, Thomas

2008-09-17

Metagenomic analysis provides a rich source of biological information for otherwise intractable viral communities. However, study of viral metagenomes has been hampered by its nearly complete reliance on BLAST algorithms for identification of DNA sequences. We sought to develop algorithms for examination of viral metagenomes to identify the origin of sequences independent of BLAST algorithms. We chose viral metagenomes obtained from two hot springs, Bear Paw and Octopus, in Yellowstone National Park, as they represent simple microbial populations where comparatively large contigs were obtained. Thermal spring metagenomes have high proportions of sequences without significant Genbank homology, which has hampered identification of viruses and their linkage with hosts. To analyze each metagenome, we developed a method to classify DNA fragments using genome signature-based phylogenetic classification (GSPC), where metagenomic fragments are compared to a database of oligonucleotide signatures for all previously sequenced Bacteria, Archaea, and viruses. From both Bear Paw and Octopus hot springs, each assembled contig had more similarity to other metagenome contigs than to any sequenced microbial genome based on GSPC analysis, suggesting a genome signature common to each of these extreme environments. While viral metagenomes from Bear Paw and Octopus share some similarity, the genome signatures from each locale are largely unique. GSPC using a microbial database predicts most of the Octopus metagenome has archaeal signatures, while bacterial signatures predominate in Bear Paw; a finding consistent with those of Genbank BLAST. When using a viral database, the majority of the Octopus metagenome is predicted to belong to archaeal virus Families Globuloviridae and Fuselloviridae, while none of the Bear Paw metagenome is predicted to belong to archaeal viruses. As expected, when microbial and viral databases are combined, each of the Octopus and Bear Paw metagenomic contigs are predicted to belong to viruses rather than to any Bacteria or Archaea, consistent with the apparent viral origin of both metagenomes. That BLAST searches identify no significant homologs for most metagenome contigs, while GSPC suggests their origin as archaeal viruses or bacteriophages, indicates GSPC provides a complementary approach in viral metagenomic analysis.

Global point signature for shape analysis of carpal bones

NASA Astrophysics Data System (ADS)

Chaudhari, Abhijit J.; Leahy, Richard M.; Wise, Barton L.; Lane, Nancy E.; Badawi, Ramsey D.; Joshi, Anand A.

2014-02-01

We present a method based on spectral theory for the shape analysis of carpal bones of the human wrist. We represent the cortical surface of the carpal bone in a coordinate system based on the eigensystem of the two-dimensional Helmholtz equation. We employ a metric—global point signature (GPS)—that exploits the scale and isometric invariance of eigenfunctions to quantify overall bone shape. We use a fast finite-element-method to compute the GPS metric. We capitalize upon the properties of GPS representation—such as stability, a standard Euclidean (ℓ2) metric definition, and invariance to scaling, translation and rotation—to perform shape analysis of the carpal bones of ten women and ten men from a publicly-available database. We demonstrate the utility of the proposed GPS representation to provide a means for comparing shapes of the carpal bones across populations.

Identification of endometrial cancer methylation features using combined methylation analysis methods

PubMed Central

Trimarchi, Michael P.; Yan, Pearlly; Groden, Joanna; Bundschuh, Ralf; Goodfellow, Paul J.

2017-01-01

Background DNA methylation is a stable epigenetic mark that is frequently altered in tumors. DNA methylation features are attractive biomarkers for disease states given the stability of DNA methylation in living cells and in biologic specimens typically available for analysis. Widespread accumulation of methylation in regulatory elements in some cancers (specifically the CpG island methylator phenotype, CIMP) can play an important role in tumorigenesis. High resolution assessment of CIMP for the entire genome, however, remains cost prohibitive and requires quantities of DNA not available for many tissue samples of interest. Genome-wide scans of methylation have been undertaken for large numbers of tumors, and higher resolution analyses for a limited number of cancer specimens. Methods for analyzing such large datasets and integrating findings from different studies continue to evolve. An approach for comparison of findings from a genome-wide assessment of the methylated component of tumor DNA and more widely applied methylation scans was developed. Methods Methylomes for 76 primary endometrial cancer and 12 normal endometrial samples were generated using methylated fragment capture and second generation sequencing, MethylCap-seq. Publically available Infinium HumanMethylation 450 data from The Cancer Genome Atlas (TCGA) were compared to MethylCap-seq data. Results Analysis of methylation in promoter CpG islands (CGIs) identified a subset of tumors with a methylator phenotype. We used a two-stage approach to develop a 13-region methylation signature associated with a “hypermethylator state.” High level methylation for the 13-region methylation signatures was associated with mismatch repair deficiency, high mutation rate, and low somatic copy number alteration in the TCGA test set. In addition, the signature devised showed good agreement with previously described methylation clusters devised by TCGA. Conclusion We identified a methylation signature for a “hypermethylator phenotype” in endometrial cancer and developed methods that may prove useful for identifying extreme methylation phenotypes in other cancers. PMID:28278225

Pathway-GPS and SIGORA: identifying relevant pathways based on the over-representation of their gene-pair signatures

PubMed Central

Foroushani, Amir B.K.; Brinkman, Fiona S.L.

2013-01-01

Motivation. Predominant pathway analysis approaches treat pathways as collections of individual genes and consider all pathway members as equally informative. As a result, at times spurious and misleading pathways are inappropriately identified as statistically significant, solely due to components that they share with the more relevant pathways. Results. We introduce the concept of Pathway Gene-Pair Signatures (Pathway-GPS) as pairs of genes that, as a combination, are specific to a single pathway. We devised and implemented a novel approach to pathway analysis, Signature Over-representation Analysis (SIGORA), which focuses on the statistically significant enrichment of Pathway-GPS in a user-specified gene list of interest. In a comparative evaluation of several published datasets, SIGORA outperformed traditional methods by delivering biologically more plausible and relevant results. Availability. An efficient implementation of SIGORA, as an R package with precompiled GPS data for several human and mouse pathway repositories is available for download from http://sigora.googlecode.com/svn/. PMID:24432194

Interim Report on SNP analysis and forensic microarray probe design for South American hemorrhagic fever viruses, tick-borne encephalitis virus, henipaviruses, Old World Arenaviruses, filoviruses, Crimean-Congo hemorrhagic fever viruses, Rift Valley fever

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jaing, C; Gardner, S

The goal of this project is to develop forensic genotyping assays for select agent viruses, enhancing the current capabilities for the viral bioforensics and law enforcement community. We used a multipronged approach combining bioinformatics analysis, PCR-enriched samples, microarrays and TaqMan assays to develop high resolution and cost effective genotyping methods for strain level forensic discrimination of viruses. We have leveraged substantial experience and efficiency gained through year 1 on software development, SNP discovery, TaqMan signature design and phylogenetic signature mapping to scale up the development of forensics signatures in year 2. In this report, we have summarized the whole genomemore » wide SNP analysis and microarray probe design for forensics characterization of South American hemorrhagic fever viruses, tick-borne encephalitis viruses and henipaviruses, Old World Arenaviruses, filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus and Japanese encephalitis virus.« less

Comprehensive Sieve Analysis of Breakthrough HIV-1 Sequences in the RV144 Vaccine Efficacy Trial

PubMed Central

Edlefsen, Paul T.; Rolland, Morgane; Hertz, Tomer; Tovanabutra, Sodsai; Gartland, Andrew J.; deCamp, Allan C.; Magaret, Craig A.; Ahmed, Hasan; Gottardo, Raphael; Juraska, Michal; McCoy, Connor; Larsen, Brendan B.; Sanders-Buell, Eric; Carrico, Chris; Menis, Sergey; Bose, Meera; Arroyo, Miguel A.; O’Connell, Robert J.; Nitayaphan, Sorachai; Pitisuttithum, Punnee; Kaewkungwal, Jaranit; Rerks-Ngarm, Supachai; Robb, Merlin L.; Kirys, Tatsiana; Georgiev, Ivelin S.; Kwong, Peter D.; Scheffler, Konrad; Pond, Sergei L. Kosakovsky; Carlson, Jonathan M.; Michael, Nelson L.; Schief, William R.; Mullins, James I.; Kim, Jerome H.; Gilbert, Peter B.

2015-01-01

The RV144 clinical trial showed the partial efficacy of a vaccine regimen with an estimated vaccine efficacy (VE) of 31% for protecting low-risk Thai volunteers against acquisition of HIV-1. The impact of vaccine-induced immune responses can be investigated through sieve analysis of HIV-1 breakthrough infections (infected vaccine and placebo recipients). A V1/V2-targeted comparison of the genomes of HIV-1 breakthrough viruses identified two V2 amino acid sites that differed between the vaccine and placebo groups. Here we extended the V1/V2 analysis to the entire HIV-1 genome using an array of methods based on individual sites, k-mers and genes/proteins. We identified 56 amino acid sites or “signatures” and 119 k-mers that differed between the vaccine and placebo groups. Of those, 19 sites and 38 k-mers were located in the regions comprising the RV144 vaccine (Env-gp120, Gag, and Pro). The nine signature sites in Env-gp120 were significantly enriched for known antibody-associated sites (p = 0.0021). In particular, site 317 in the third variable loop (V3) overlapped with a hotspot of antibody recognition, and sites 369 and 424 were linked to CD4 binding site neutralization. The identified signature sites significantly covaried with other sites across the genome (mean = 32.1) more than did non-signature sites (mean = 0.9) (p < 0.0001), suggesting functional and/or structural relevance of the signature sites. Since signature sites were not preferentially restricted to the vaccine immunogens and because most of the associations were insignificant following correction for multiple testing, we predict that few of the genetic differences are strongly linked to the RV144 vaccine-induced immune pressure. In addition to presenting results of the first complete-genome analysis of the breakthrough infections in the RV144 trial, this work describes a set of statistical methods and tools applicable to analysis of breakthrough infection genomes in general vaccine efficacy trials for diverse pathogens. PMID:25646817

Anomaly Detection in Gamma-Ray Vehicle Spectra with Principal Components Analysis and Mahalanobis Distances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tardiff, Mark F.; Runkle, Robert C.; Anderson, K. K.

2006-01-23

The goal of primary radiation monitoring in support of routine screening and emergency response is to detect characteristics in vehicle radiation signatures that indicate the presence of potential threats. Two conceptual approaches to analyzing gamma-ray spectra for threat detection are isotope identification and anomaly detection. While isotope identification is the time-honored method, an emerging technique is anomaly detection that uses benign vehicle gamma ray signatures to define an expectation of the radiation signature for vehicles that do not pose a threat. Newly acquired spectra are then compared to this expectation using statistical criteria that reflect acceptable false alarm rates andmore » probabilities of detection. The gamma-ray spectra analyzed here were collected at a U.S. land Port of Entry (POE) using a NaI-based radiation portal monitor (RPM). The raw data were analyzed to develop a benign vehicle expectation by decimating the original pulse-height channels to 35 energy bins, extracting composite variables via principal components analysis (PCA), and estimating statistically weighted distances from the mean vehicle spectrum with the mahalanobis distance (MD) metric. This paper reviews the methods used to establish the anomaly identification criteria and presents a systematic analysis of the response of the combined PCA and MD algorithm to modeled mono-energetic gamma-ray sources.« less

A quantum cascade laser infrared spectrometer for CO2 stable isotope analysis: Field implementation at a hydrocarbon contaminated site under bio-remediation.

PubMed

Guimbaud, Christophe; Noel, Cécile; Chartier, Michel; Catoire, Valéry; Blessing, Michaela; Gourry, Jean Christophe; Robert, Claude

2016-02-01

Real-time methods to monitor stable isotope ratios of CO2 are needed to identify biogeochemical origins of CO2 emissions from the soil-air interface. An isotope ratio infra-red spectrometer (IRIS) has been developed to measure CO2 mixing ratio with δ(13)C isotopic signature, in addition to mixing ratios of other greenhouse gases (CH4, N2O). The original aspects of the instrument as well as its precision and accuracy for the determination of the isotopic signature δ(13)C of CO2 are discussed. A first application to biodegradation of hydrocarbons is presented, tested on a hydrocarbon contaminated site under aerobic bio-treatment. CO2 flux measurements using closed chamber method is combined with the determination of the isotopic signature δ(13)C of the CO2 emission to propose a non-intrusive method to monitor in situ biodegradation of hydrocarbons. In the contaminated area, high CO2 emissions have been measured with an isotopic signature δ(13)C suggesting that CO2 comes from petroleum hydrocarbon biodegradation. This first field implementation shows that rapid and accurate measurement of isotopic signature of CO2 emissions is particularly useful in assessing the contribution of contaminant degradation to the measured CO2 efflux and is promising as a monitoring tool for aerobic bio-treatment. Copyright © 2016. Published by Elsevier B.V.

Wall Interference Study of the NTF Slotted Tunnel Using Bodies of Revolution Wall Signature Data

NASA Technical Reports Server (NTRS)

Iyer, Venkit; Kuhl, David D.; Walker, Eric L.

2004-01-01

This paper is a description of the analysis of blockage corrections for bodies of revolution for the slotted-wall configuration of the National Transonic Facility (NTF) at the NASA Langley Research Center (LaRC). A wall correction method based on the measured wall signature is used. Test data from three different-sized blockage bodies and four wall ventilation settings were analyzed at various Mach numbers and unit Reynolds numbers. The results indicate that with the proper selection of the boundary condition parameters, the wall correction method can predict blockage corrections consistent with the wall measurements for Mach numbers as high as 0.95.

Improving LiDAR Data Post-Processing Techniques for Archaeological Site Management and Analysis: A Case Study from Canaveral National Seashore Park

NASA Astrophysics Data System (ADS)

Griesbach, Christopher

Methods used to process raw Light Detection and Ranging (LiDAR) data can sometimes obscure the digital signatures indicative of an archaeological site. This thesis explains the negative effects that certain LiDAR data processing procedures can have on the preservation of an archaeological site. This thesis also presents methods for effectively integrating LiDAR with other forms of mapping data in a Geographic Information Systems (GIS) environment in order to improve LiDAR archaeological signatures by examining several pre-Columbian Native American shell middens located in Canaveral National Seashore Park (CANA).

Material quality assessment of silk nanofibers based on swarm intelligence

NASA Astrophysics Data System (ADS)

Brandoli Machado, Bruno; Nunes Gonçalves, Wesley; Martinez Bruno, Odemir

2013-02-01

In this paper, we propose a novel approach for texture analysis based on artificial crawler model. Our method assumes that each agent can interact with the environment and each other. The evolution process converges to an equilibrium state according to the set of rules. For each textured image, the feature vector is composed by signatures of the live agents curve at each time. Experimental results revealed that combining the minimum and maximum signatures into one increase the classification rate. In addition, we pioneer the use of autonomous agents for characterizing silk fibroin scaffolds. The results strongly suggest that our approach can be successfully employed for texture analysis.

Simultaneous quantification of α-lactalbumin and β-casein in human milk using ultra-performance liquid chromatography with tandem mass spectrometry based on their signature peptides and winged isotope internal standards.

PubMed

Chen, Qi; Zhang, Jingshun; Ke, Xing; Lai, Shiyun; Li, Duo; Yang, Jinchuan; Mo, Weimin; Ren, Yiping

2016-09-01

In recent years, there is an increasing need to measure the concentration of individual proteins in human milk, instead of total human milk proteins. Due to lack of human milk protein standards, there are only few quantification methods established. The objective of the present work was to develop a simple and rapid quantification method for simultaneous determination of α-lactalbumin and β-casein in human milk using signature peptides according to a modified quantitative proteomics strategy. The internal standards containing the signature peptide sequences were synthesized with isotope-labeled amino acids. The purity of synthesized peptides as standards was determined by amino acid analysis method and area normalization method. The contents of α-lactalbumin and β-casein in human milk were measured according to the equimolar relationship between the two proteins and their corresponding signature peptides. The method validation results showed a satisfied linearity (R(2)>0.99) and recoveries (97.2-102.5% for α-lactalbumin and 99.5-100.3% for β-casein). The limit of quantification for α-lactalbumin and β-casein was 8.0mg/100g and 1.2mg/100g, respectively. CVs for α-lactalbumin and β-casein in human milk were 5.2% and 3.0%. The contents of α-lactalbumin and β-casein in 147 human milk samples were successfully determined by the established method and their contents were 205.5-578.2mg/100g and 116.4-467.4mg/100g at different lactation stages. The developed method allows simultaneously determination of α-lactalbumin and β-casein in human milk. The quantitative strategy based on signature peptide should be applicable to other endogenous proteins in breast milk and other body fluids. Copyright © 2016 Elsevier B.V. All rights reserved.

Circulating neutrophil transcriptome may reveal intracranial aneurysm signature

PubMed Central

Tutino, Vincent M.; Poppenberg, Kerry E.; Jiang, Kaiyu; Jarvis, James N.; Sun, Yijun; Sonig, Ashish; Siddiqui, Adnan H.; Snyder, Kenneth V.; Levy, Elad I.; Kolega, John

2018-01-01

Background Unruptured intracranial aneurysms (IAs) are typically asymptomatic and undetected except for incidental discovery on imaging. Blood-based diagnostic biomarkers could lead to improvements in IA management. This exploratory study examined circulating neutrophils to determine whether they carry RNA expression signatures of IAs. Methods Blood samples were collected from patients receiving cerebral angiography. Eleven samples were collected from patients with IAs and 11 from patients without IAs as controls. Samples from the two groups were paired based on demographics and comorbidities. RNA was extracted from isolated neutrophils and subjected to next-generation RNA sequencing to obtain differential expressions for identification of an IA-associated signature. Bioinformatics analyses, including gene set enrichment analysis and Ingenuity Pathway Analysis, were used to investigate the biological function of all differentially expressed transcripts. Results Transcriptome profiling identified 258 differentially expressed transcripts in patients with and without IAs. Expression differences were consistent with peripheral neutrophil activation. An IA-associated RNA expression signature was identified in 82 transcripts (p<0.05, fold-change ≥2). This signature was able to separate patients with and without IAs on hierarchical clustering. Furthermore, in an independent, unpaired, replication cohort of patients with IAs (n = 5) and controls (n = 5), the 82 transcripts separated 9 of 10 patients into their respective groups. Conclusion Preliminary findings show that RNA expression from circulating neutrophils carries an IA-associated signature. These findings highlight a potential to use predictive biomarkers from peripheral blood samples to identify patients with IAs. PMID:29342213

Analysis of Non-contact Acousto Thermal Signature Data (Postprint)

DTIC Science & Technology

2016-02-01

AFRL-RX-WP-JA-2016-0321 ANALYSIS OF NON- CONTACT ACOUSTO-THERMAL SIGNATURE DATA (POSTPRINT) Amanda K. Criner AFRL/RX...October 2014 – 16 September 2015 4. TITLE AND SUBTITLE ANALYSIS OF NON- CONTACT ACOUSTO-THERMAL SIGNATURE DATA (POSTPRINT) 5a. CONTRACT NUMBER...words) The non- contact acousto-thermal signature (NCATS) is a nondestructive evaluation technique with potential to detect fatigue in materials such as

Comparing performance of standard and iterative linear unmixing methods for hyperspectral signatures

NASA Astrophysics Data System (ADS)

Gault, Travis R.; Jansen, Melissa E.; DeCoster, Mallory E.; Jansing, E. David; Rodriguez, Benjamin M.

2016-05-01

Linear unmixing is a method of decomposing a mixed signature to determine the component materials that are present in sensor's field of view, along with the abundances at which they occur. Linear unmixing assumes that energy from the materials in the field of view is mixed in a linear fashion across the spectrum of interest. Traditional unmixing methods can take advantage of adjacent pixels in the decomposition algorithm, but is not the case for point sensors. This paper explores several iterative and non-iterative methods for linear unmixing, and examines their effectiveness at identifying the individual signatures that make up simulated single pixel mixed signatures, along with their corresponding abundances. The major hurdle addressed in the proposed method is that no neighboring pixel information is available for the spectral signature of interest. Testing is performed using two collections of spectral signatures from the Johns Hopkins University Applied Physics Laboratory's Signatures Database software (SigDB): a hand-selected small dataset of 25 distinct signatures from a larger dataset of approximately 1600 pure visible/near-infrared/short-wave-infrared (VIS/NIR/SWIR) spectra. Simulated spectra are created with three and four material mixtures randomly drawn from a dataset originating from SigDB, where the abundance of one material is swept in 10% increments from 10% to 90%with the abundances of the other materials equally divided amongst the remainder. For the smaller dataset of 25 signatures, all combinations of three or four materials are used to create simulated spectra, from which the accuracy of materials returned, as well as the correctness of the abundances, is compared to the inputs. The experiment is expanded to include the signatures from the larger dataset of almost 1600 signatures evaluated using a Monte Carlo scheme with 5000 draws of three or four materials to create the simulated mixed signatures. The spectral similarity of the inputs to the output component signatures is calculated using the spectral angle mapper. Results show that iterative methods significantly outperform the traditional methods under the given test conditions.

Methods and apparatus for multi-parameter acoustic signature inspection

DOEpatents

Diaz, Aaron A [Richland, WA; Samuel, Todd J [Pasco, WA; Valencia, Juan D [Kennewick, WA; Gervais, Kevin L [Richland, WA; Tucker, Brian J [Pasco, WA; Kirihara, Leslie J [Richland, WA; Skorpik, James R [Kennewick, WA; Reid, Larry D [Benton City, WA; Munley, John T [Benton City, WA; Pappas, Richard A [Richland, WA; Wright, Bob W [West Richland, WA; Panetta, Paul D [Richland, WA; Thompson, Jason S [Richland, WA

2007-07-24

A multiparameter acoustic signature inspection device and method are described for non-invasive inspection of containers. Dual acoustic signatures discriminate between various fluids and materials for identification of the same.

Directional fractal signature methods for trabecular bone texture in hand radiographs: Data from the Osteoarthritis Initiative

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolski, M., E-mail: marcin.wolski@curtin.edu.au; Podsiadlo, P.; Stachowiak, G. W.

Purpose: To develop directional fractal signature methods for the analysis of trabecular bone (TB) texture in hand radiographs. Problems associated with the small size of hand bones and the orientation of fingers were addressed. Methods: An augmented variance orientation transform (AVOT) and a quadrant rotating grid (QRG) methods were developed. The methods calculate fractal signatures (FSs) in different directions. Unlike other methods they have the search region adjusted according to the size of bone region of interest (ROI) to be analyzed and they produce FSs defined with respect to any chosen reference direction, i.e., they work for arbitrary orientation ofmore » fingers. Five parameters at scales ranging from 2 to 14 pixels (depending on image size and method) were derived from rose plots of Hurst coefficients, i.e., FS in dominating roughness (FS{sub Sta}), vertical (FS{sub V}) and horizontal (FS{sub H}) directions, aspect ratio (StrS), and direction signatures (StdS), respectively. The accuracy in measuring surface roughness and isotropy/anisotropy was evaluated using 3600 isotropic and 800 anisotropic fractal surface images of sizes between 20 × 20 and 64 × 64 pixels. The isotropic surfaces had FDs ranging from 2.1 to 2.9 in steps of 0.1, and the anisotropic surfaces had two dominating directions of 30° and 120°. The methods were used to find differences in hand TB textures between 20 matched pairs of subjects with (cases: approximate Kellgren-Lawrence (KL) grade ≥2) and without (controls: approximate KL grade <2) radiographic hand osteoarthritis (OA). The OA Initiative public database was used and 20 × 20 pixel bone ROIs were selected on 5th distal and middle phalanges. The performance of the AVOT and QRG methods was compared against a variance orientation transform (VOT) method developed earlier [M. Wolski, P. Podsiadlo, and G. W. Stachowiak, “Directional fractal signature analysis of trabecular bone: evaluation of different methods to detect early osteoarthritis in knee radiographs,” Proc. Inst. Mech. Eng., Part H 223, 211–236 (2009)]. Results: The AVOT method correctly quantified the isotropic and anisotropic surfaces for all image sizes and scales. Values of FS{sub Sta} were significantly different (P < 0.05) between the isotropic surfaces. Using the VOT and QRG methods no differences were found at large scales for the isotropic surfaces that are smaller than 64 × 64 and 48 × 48 pixels, respectively, and at some scales for the anisotropic surfaces with size 48 × 48 pixels. Compared to controls, using the AVOT and QRG methods the authors found that OA TB textures were less rough (P < 0.05) in the dominating and horizontal directions (i.e., lower FS{sub Sta} and FS{sub H}), rougher in the vertical direction (i.e., higher FS{sub V}) and less anisotropic (i.e., higher StrS) than controls. No differences were found using the VOT method. Conclusions: The AVOT method is well suited for the analysis of bone texture in hand radiographs and it could be potentially useful for early detection and prediction of hand OA.« less

A gene-signature progression approach to identifying candidate small-molecule cancer therapeutics with connectivity mapping.

PubMed

Wen, Qing; Kim, Chang-Sik; Hamilton, Peter W; Zhang, Shu-Dong

2016-05-11

Gene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research in connectivity mapping mainly focused on two of the key components in the framework, namely, the reference gene expression profiles and the connectivity mapping algorithms. The other key component in this framework, the query gene signature, has been left to users to construct without much consensus on how this should be done, albeit it has been an issue most relevant to end users. As a key input to the connectivity mapping process, gene signature is crucially important in returning biologically meaningful and relevant results. This paper intends to formulate a standardized procedure for constructing high quality gene signatures from a user's perspective. We describe a two-stage process for making quality gene signatures using gene expression data as initial inputs. First, a differential gene expression analysis comparing two distinct biological states; only the genes that have passed stringent statistical criteria are considered in the second stage of the process, which involves ranking genes based on statistical as well as biological significance. We introduce a "gene signature progression" method as a standard procedure in connectivity mapping. Starting from the highest ranked gene, we progressively determine the minimum length of the gene signature that allows connections to the reference profiles (drugs) being established with a preset target false discovery rate. We use a lung cancer dataset and a breast cancer dataset as two case studies to demonstrate how this standardized procedure works, and we show that highly relevant and interesting biological connections are returned. Of particular note is gefitinib, identified as among the candidate therapeutics in our lung cancer case study. Our gene signature was based on gene expression data from Taiwan female non-smoker lung cancer patients, while there is evidence from independent studies that gefitinib is highly effective in treating women, non-smoker or former light smoker, advanced non-small cell lung cancer patients of Asian origin. In summary, we introduced a gene signature progression method into connectivity mapping, which enables a standardized procedure for constructing high quality gene signatures. This progression method is particularly useful when the number of differentially expressed genes identified is large, and when there is a need to prioritize them to be included in the query signature. The results from two case studies demonstrate that the approach we have developed is capable of obtaining pertinent candidate drugs with high precision.

Plume mapping and isotopic characterisation of anthropogenic methane sources

NASA Astrophysics Data System (ADS)

Zazzeri, G.; Lowry, D.; Fisher, R. E.; France, J. L.; Lanoisellé, M.; Nisbet, E. G.

2015-06-01

Methane stable isotope analysis, coupled with mole fraction measurement, has been used to link isotopic signature to methane emissions from landfill sites, coal mines and gas leaks in the United Kingdom. A mobile Picarro G2301 CRDS (Cavity Ring-Down Spectroscopy) analyser was installed on a vehicle, together with an anemometer and GPS receiver, to measure atmospheric methane mole fractions and their relative location while driving at speeds up to 80 kph. In targeted areas, when the methane plume was intercepted, air samples were collected in Tedlar bags, for δ13C-CH4 isotopic analysis by CF-GC-IRMS (Continuous Flow Gas Chromatography-Isotope Ratio Mass Spectrometry). This method provides high precision isotopic values, determining δ13C-CH4 to ±0.05 per mil. The bulk signature of the methane plume into the atmosphere from the whole source area was obtained by Keeling plot analysis, and a δ13C-CH4 signature, with the relative uncertainty, allocated to each methane source investigated. Both landfill and natural gas emissions in SE England have tightly constrained isotopic signatures. The averaged δ13C-CH4 for landfill sites is -58 ± 3‰. The δ13C-CH4 signature for gas leaks is also fairly constant around -36 ± 2‰, a value characteristic of homogenised North Sea supply. In contrast, signatures for coal mines in N. England and Wales fall in a range of -51.2 ± 0.3‰ to -30.9 ± 1.4‰, but can be tightly constrained by region. The study demonstrates that CRDS-based mobile methane measurement coupled with off-line high precision isotopic analysis of plume samples is an efficient way of characterising methane sources. It shows that isotopic measurements allow type identification, and possible location of previously unknown methane sources. In modelling studies this measurement provides an independent constraint to determine the contributions of different sources to the regional methane budget and in the verification of inventory source distribution.

Signature extraction of ocean pollutants by eigenvector transformation of remote spectra

NASA Technical Reports Server (NTRS)

Grew, G. W.

1978-01-01

Spectral signatures of suspended matter in the ocean are being extracted through characteristic vector analysis of remote ocean color data collected with MOCS (Multichannel Ocean Color Sensor). Spectral signatures appear to be obtainable through analyses of 'linear' clusters that appear on scatter diagrams associated with eigenvectors. Signatures associated with acid waste, sewage sludge, oil, and algae are presented. The application of vector analysis to two acid waste dumps overflown two years apart is examined in some detail. The relationships between eigenvectors and spectral signatures for these examples are analyzed. These cases demonstrate the value of characteristic vector analysis in remotely identifying pollutants in the ocean and in determining the consistency of their spectral signatures.

Dynamic analysis environment for nuclear forensic analyses

NASA Astrophysics Data System (ADS)

Stork, C. L.; Ummel, C. C.; Stuart, D. S.; Bodily, S.; Goldblum, B. L.

2017-01-01

A Dynamic Analysis Environment (DAE) software package is introduced to facilitate group inclusion/exclusion method testing, evaluation and comparison for pre-detonation nuclear forensics applications. Employing DAE, the multivariate signatures of a questioned material can be compared to the signatures for different, known groups, enabling the linking of the questioned material to its potential process, location, or fabrication facility. Advantages of using DAE for group inclusion/exclusion include built-in query tools for retrieving data of interest from a database, the recording and documentation of all analysis steps, a clear visualization of the analysis steps intelligible to a non-expert, and the ability to integrate analysis tools developed in different programming languages. Two group inclusion/exclusion methods are implemented in DAE: principal component analysis, a parametric feature extraction method, and k nearest neighbors, a nonparametric pattern recognition method. Spent Fuel Isotopic Composition (SFCOMPO), an open source international database of isotopic compositions for spent nuclear fuels (SNF) from 14 reactors, is used to construct PCA and KNN models for known reactor groups, and 20 simulated SNF samples are utilized in evaluating the performance of these group inclusion/exclusion models. For all 20 simulated samples, PCA in conjunction with the Q statistic correctly excludes a large percentage of reactor groups and correctly includes the true reactor of origination. Employing KNN, 14 of the 20 simulated samples are classified to their true reactor of origination.

Comprehensive analysis of the functional microRNA–mRNA regulatory network identifies miRNA signatures associated with glioma malignant progression

PubMed Central

Li, Yongsheng; Xu, Juan; Chen, Hong; Bai, Jing; Li, Shengli; Zhao, Zheng; Shao, Tingting; Jiang, Tao; Ren, Huan; Kang, Chunsheng; Li, Xia

2013-01-01

Glioma is the most common and fatal primary brain tumour with poor prognosis; however, the functional roles of miRNAs in glioma malignant progression are insufficiently understood. Here, we used an integrated approach to identify miRNA functional targets during glioma malignant progression by combining the paired expression profiles of miRNAs and mRNAs across 160 Chinese glioma patients, and further constructed the functional miRNA–mRNA regulatory network. As a result, most tumour-suppressive miRNAs in glioma progression were newly discovered, whose functions were widely involved in gliomagenesis. Moreover, three miRNA signatures, with different combinations of hub miRNAs (regulations≥30) were constructed, which could independently predict the survival of patients with all gliomas, high-grade glioma and glioblastoma. Our network-based method increased the ability to identify the prognostic biomarkers, when compared with the traditional method and random conditions. Hsa-miR-524-5p and hsa-miR-628-5p, shared by these three signatures, acted as protective factors and their expression decreased gradually during glioma progression. Functional analysis of these miRNA signatures highlighted their critical roles in cell cycle and cell proliferation in glioblastoma malignant progression, especially hsa-miR-524-5p and hsa-miR-628-5p exhibited dominant regulatory activities. Therefore, network-based biomarkers are expected to be more effective and provide deep insights into the molecular mechanism of glioma malignant progression. PMID:24194606

Raman spectral signatures of cervical exfoliated cells from liquid-based cytology samples

NASA Astrophysics Data System (ADS)

Kearney, Padraig; Traynor, Damien; Bonnier, Franck; Lyng, Fiona M.; O'Leary, John J.; Martin, Cara M.

2017-10-01

It is widely accepted that cervical screening has significantly reduced the incidence of cervical cancer worldwide. The primary screening test for cervical cancer is the Papanicolaou (Pap) test, which has extremely variable specificity and sensitivity. There is an unmet clinical need for methods to aid clinicians in the early detection of cervical precancer. Raman spectroscopy is a label-free objective method that can provide a biochemical fingerprint of a given sample. Compared with studies on infrared spectroscopy, relatively few Raman spectroscopy studies have been carried out to date on cervical cytology. The aim of this study was to define the Raman spectral signatures of cervical exfoliated cells present in liquid-based cytology Pap test specimens and to compare the signature of high-grade dysplastic cells to each of the normal cell types. Raman spectra were recorded from single exfoliated cells and subjected to multivariate statistical analysis. The study demonstrated that Raman spectroscopy can identify biochemical signatures associated with the most common cell types seen in liquid-based cytology samples; superficial, intermediate, and parabasal cells. In addition, biochemical changes associated with high-grade dysplasia could be identified suggesting that Raman spectroscopy could be used to aid current cervical screening tests.

Magnetic resonance imaging-based cerebral tissue classification reveals distinct spatiotemporal patterns of changes after stroke in non-human primates.

PubMed

Bouts, Mark J R J; Westmoreland, Susan V; de Crespigny, Alex J; Liu, Yutong; Vangel, Mark; Dijkhuizen, Rick M; Wu, Ona; D'Arceuil, Helen E

2015-12-15

Spatial and temporal changes in brain tissue after acute ischemic stroke are still poorly understood. Aims of this study were three-fold: (1) to determine unique temporal magnetic resonance imaging (MRI) patterns at the acute, subacute and chronic stages after stroke in macaques by combining quantitative T2 and diffusion MRI indices into MRI 'tissue signatures', (2) to evaluate temporal differences in these signatures between transient (n = 2) and permanent (n = 2) middle cerebral artery occlusion, and (3) to correlate histopathology findings in the chronic stroke period to the acute and subacute MRI derived tissue signatures. An improved iterative self-organizing data analysis algorithm was used to combine T2, apparent diffusion coefficient (ADC), and fractional anisotropy (FA) maps across seven successive timepoints (1, 2, 3, 24, 72, 144, 240 h) which revealed five temporal MRI signatures, that were different from the normal tissue pattern (P < 0.001). The distribution of signatures between brains with permanent and transient occlusions varied significantly between groups (P < 0.001). Qualitative comparisons with histopathology revealed that these signatures represented regions with different histopathology. Two signatures identified areas of progressive injury marked by severe necrosis and the presence of gitter cells. Another signature identified less severe but pronounced neuronal and axonal degeneration, while the other signatures depicted tissue remodeling with vascular proliferation and astrogliosis. These exploratory results demonstrate the potential of temporally and spatially combined voxel-based methods to generate tissue signatures that may correlate with distinct histopathological features. The identification of distinct ischemic MRI signatures associated with specific tissue fates may further aid in assessing and monitoring the efficacy of novel pharmaceutical treatments for stroke in a pre-clinical and clinical setting.

Classification of a large microarray data set: Algorithm comparison and analysis of drug signatures

PubMed Central

Natsoulis, Georges; El Ghaoui, Laurent; Lanckriet, Gert R.G.; Tolley, Alexander M.; Leroy, Fabrice; Dunlea, Shane; Eynon, Barrett P.; Pearson, Cecelia I.; Tugendreich, Stuart; Jarnagin, Kurt

2005-01-01

A large gene expression database has been produced that characterizes the gene expression and physiological effects of hundreds of approved and withdrawn drugs, toxicants, and biochemical standards in various organs of live rats. In order to derive useful biological knowledge from this large database, a variety of supervised classification algorithms were compared using a 597-microarray subset of the data. Our studies show that several types of linear classifiers based on Support Vector Machines (SVMs) and Logistic Regression can be used to derive readily interpretable drug signatures with high classification performance. Both methods can be tuned to produce classifiers of drug treatments in the form of short, weighted gene lists which upon analysis reveal that some of the signature genes have a positive contribution (act as “rewards” for the class-of-interest) while others have a negative contribution (act as “penalties”) to the classification decision. The combination of reward and penalty genes enhances performance by keeping the number of false positive treatments low. The results of these algorithms are combined with feature selection techniques that further reduce the length of the drug signatures, an important step towards the development of useful diagnostic biomarkers and low-cost assays. Multiple signatures with no genes in common can be generated for the same classification end-point. Comparison of these gene lists identifies biological processes characteristic of a given class. PMID:15867433

A Robust Blind Quantum Copyright Protection Method for Colored Images Based on Owner's Signature

NASA Astrophysics Data System (ADS)

Heidari, Shahrokh; Gheibi, Reza; Houshmand, Monireh; Nagata, Koji

2017-08-01

Watermarking is the imperceptible embedding of watermark bits into multimedia data in order to use for different applications. Among all its applications, copyright protection is the most prominent usage which conceals information about the owner in the carrier, so as to prohibit others from assertion copyright. This application requires high level of robustness. In this paper, a new blind quantum copyright protection method based on owners's signature in RGB images is proposed. The method utilizes one of the RGB channels as indicator and two remained channels are used for embedding information about the owner. In our contribution the owner's signature is considered as a text. Therefore, in order to embed in colored image as watermark, a new quantum representation of text based on ASCII character set is offered. Experimental results which are analyzed in MATLAB environment, exhibit that the presented scheme shows good performance against attacks and can be used to find out who the real owner is. Finally, the discussed quantum copyright protection method is compared with a related work that our analysis confirm that the presented scheme is more secure and applicable than the previous ones currently found in the literature.

Detrending the realized volatility in the global FX market

NASA Astrophysics Data System (ADS)

Schmidt, Anatoly B.

2009-05-01

There has been growing interest in realized volatility (RV) of financial assets that is calculated using intra-day returns. The choice of optimal time grid for these calculations is not trivial and generally requires analysis of RV dependence on the grid spacing (so-called RV signature). Typical RV signatures have a maximum at the finest time grid spacing available, which is attributed to the microstructure effects. This maximum decays into a plateau at lower frequencies, which implies (almost) stationary return variance. We found that the RV signatures in the modern global FX market may have no plateau or even have a maximum at lower frequencies. Simple averaging methods used to address the microstructure effects in equities have no practical effect on the FX RV signatures. We show that local detrending of the high-frequency FX rate samples yields RV signatures with a pronounced plateau. This implies that FX rates can be described with a Brownian motion having non-stationary trend and stationary variance. We point at a role of algorithmic trading as a possible cause of micro-trends in FX rates.

Towards a Holistic Cortical Thickness Descriptor: Heat Kernel-Based Grey Matter Morphology Signatures.

PubMed

Wang, Gang; Wang, Yalin

2017-02-15

In this paper, we propose a heat kernel based regional shape descriptor that may be capable of better exploiting volumetric morphological information than other available methods, thereby improving statistical power on brain magnetic resonance imaging (MRI) analysis. The mechanism of our analysis is driven by the graph spectrum and the heat kernel theory, to capture the volumetric geometry information in the constructed tetrahedral meshes. In order to capture profound brain grey matter shape changes, we first use the volumetric Laplace-Beltrami operator to determine the point pair correspondence between white-grey matter and CSF-grey matter boundary surfaces by computing the streamlines in a tetrahedral mesh. Secondly, we propose multi-scale grey matter morphology signatures to describe the transition probability by random walk between the point pairs, which reflects the inherent geometric characteristics. Thirdly, a point distribution model is applied to reduce the dimensionality of the grey matter morphology signatures and generate the internal structure features. With the sparse linear discriminant analysis, we select a concise morphology feature set with improved classification accuracies. In our experiments, the proposed work outperformed the cortical thickness features computed by FreeSurfer software in the classification of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, on publicly available data from the Alzheimer's Disease Neuroimaging Initiative. The multi-scale and physics based volumetric structure feature may bring stronger statistical power than some traditional methods for MRI-based grey matter morphology analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Systems and methods for detecting a failure event in a field programmable gate array

NASA Technical Reports Server (NTRS)

Ng, Tak-Kwong (Inventor); Herath, Jeffrey A. (Inventor)

2009-01-01

An embodiment generally relates to a method of self-detecting an error in a field programmable gate array (FPGA). The method includes writing a signature value into a signature memory in the FPGA and determining a conclusion of a configuration refresh operation in the FPGA. The method also includes reading an outcome value from the signature memory.

Universal DNA-based methods for assessing the diet of grazing livestock and wildlife from feces.

PubMed

Pegard, Anthony; Miquel, Christian; Valentini, Alice; Coissac, Eric; Bouvier, Frédéric; François, Dominique; Taberlet, Pierre; Engel, Erwan; Pompanon, François

2009-07-08

Because of the demand for controlling livestock diets, two methods that characterize the DNA of plants present in feces were developed. After DNA extraction from fecal samples, a short fragment of the chloroplastic trnL intron was amplified by PCR using a universal primer pair for plants. The first method generates a signature that is the electrophoretic migration pattern of the PCR product. The second method consists of sequencing several hundred DNA fragments from the PCR product through pyrosequencing. These methods were validated with a blind analysis of feces from concentrate- and pasture-fed lambs. The signature method allowed differentiation of the two diets and confirmed the presence of concentrate in one of them. The pyrosequencing method allowed the identification of up to 25 taxa in a diet. These methods are complementary to the chemical methods already used. They could be applied to the control of diets and the study of food preferences.

Pathway analysis from lists of microRNAs: common pitfalls and alternative strategy

PubMed Central

Godard, Patrice; van Eyll, Jonathan

2015-01-01

MicroRNAs (miRNAs) are involved in the regulation of gene expression at a post-transcriptional level. As such, monitoring miRNA expression has been increasingly used to assess their role in regulatory mechanisms of biological processes. In large scale studies, once miRNAs of interest have been identified, the target genes they regulate are often inferred using algorithms or databases. A pathway analysis is then often performed in order to generate hypotheses about the relevant biological functions controlled by the miRNA signature. Here we show that the method widely used in scientific literature to identify these pathways is biased and leads to inaccurate results. In addition to describing the bias and its origin we present an alternative strategy to identify potential biological functions specifically impacted by a miRNA signature. More generally, our study exemplifies the crucial need of relevant negative controls when developing, and using, bioinformatics methods. PMID:25800743

Molecular Signature of Indeterminate Thyroid Lesions: Current Methods to Improve Fine Needle Aspiration Cytology (FNAC) Diagnosis

PubMed Central

Cantara, Silvia; Marzocchi, Carlotta; Pilli, Tania; Cardinale, Sandro; Forleo, Raffaella; Castagna, Maria Grazia; Pacini, Furio

2017-01-01

Fine needle aspiration cytology (FNAC) represents the gold standard for determining the nature of thyroid nodules. It is a reliable method with good sensitivity and specificity. However, indeterminate lesions remain a diagnostic challenge and researchers have contributed molecular markers to search for in cytological material to refine FNAC diagnosis and avoid unnecessary surgeries. Nowadays, several “home-made” methods as well as commercial tests are available to investigate the molecular signature of an aspirate. Moreover, other markers (i.e., microRNA, and circulating tumor cells) have been proposed to discriminate benign from malignant thyroid lesions. Here, we review the literature and provide data from our laboratory on mutational analysis of FNAC material and circulating microRNA expression obtained in the last 6 years. PMID:28383480

Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

PubMed

van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B

2015-01-01

Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, Yi; Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo; Song, Jie

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162more » robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6). Conclusion: Quantitative analysis identified novel {sup 18}F-fluorodeoxyglucose positron emission tomography image features that showed improved prognostic value over conventional imaging metrics. If validated in large, prospective cohorts, the new prognostic signature might be used to identify patients for individualized risk-adaptive therapy.« less

Label-Free Raman Imaging to Monitor Breast Tumor Signatures

NASA Astrophysics Data System (ADS)

Ciubuc, John

Methods built on Raman spectroscopy have shown major potential in describing and discriminating between malignant and benign specimens. Accurate, real-time medical diagnosis benefits in substantial improvements through this vibrational optical method. Not only is acquisition of data possible in milliseconds and analysis in minutes, Raman allows concurrent detection and monitoring of all biological components. Besides validating a significant Raman signature distinction between non-tumorigenic (MCF-10A) and tumorigenic (MCF-7) breast epithelial cells, this study reveals a label-free method to assess overexpression of epidermal growth factor receptors (EGFR) in tumor cells. EGFR overexpression sires Raman features associated with phosphorylated threonine and serine, and modifications of DNA/RNA characteristics. Investigations by gel electrophoresis reveal EGF induction of phosphorylated Akt, agreeing with the Raman results. The analysis presented is a vital step toward Raman-based evaluation of EGF receptors in breast cancer cells. With the goal of clinically applying Raman-guided methods for diagnosis of breast tumors, the current results lay the basis for proving label-free optical alternatives in making prognosis of the disease.

Identification of human-to-human transmissibility factors in PB2 proteins of influenza A by large-scale mutual information analysis

PubMed Central

Miotto, Olivo; Heiny, AT; Tan, Tin Wee; August, J Thomas; Brusic, Vladimir

2008-01-01

Background The identification of mutations that confer unique properties to a pathogen, such as host range, is of fundamental importance in the fight against disease. This paper describes a novel method for identifying amino acid sites that distinguish specific sets of protein sequences, by comparative analysis of matched alignments. The use of mutual information to identify distinctive residues responsible for functional variants makes this approach highly suitable for analyzing large sets of sequences. To support mutual information analysis, we developed the AVANA software, which utilizes sequence annotations to select sets for comparison, according to user-specified criteria. The method presented was applied to an analysis of influenza A PB2 protein sequences, with the objective of identifying the components of adaptation to human-to-human transmission, and reconstructing the mutation history of these components. Results We compared over 3,000 PB2 protein sequences of human-transmissible and avian isolates, to produce a catalogue of sites involved in adaptation to human-to-human transmission. This analysis identified 17 characteristic sites, five of which have been present in human-transmissible strains since the 1918 Spanish flu pandemic. Sixteen of these sites are located in functional domains, suggesting they may play functional roles in host-range specificity. The catalogue of characteristic sites was used to derive sequence signatures from historical isolates. These signatures, arranged in chronological order, reveal an evolutionary timeline for the adaptation of the PB2 protein to human hosts. Conclusion By providing the most complete elucidation to date of the functional components participating in PB2 protein adaptation to humans, this study demonstrates that mutual information is a powerful tool for comparative characterization of sequence sets. In addition to confirming previously reported findings, several novel characteristic sites within PB2 are reported. Sequence signatures generated using the characteristic sites catalogue characterize concisely the adaptation characteristics of individual isolates. Evolutionary timelines derived from signatures of early human influenza isolates suggest that characteristic variants emerged rapidly, and remained remarkably stable through subsequent pandemics. In addition, the signatures of human-infecting H5N1 isolates suggest that this avian subtype has low pandemic potential at present, although it presents more human adaptation components than most avian subtypes. PMID:18315849

Note: Model identification and analysis of bivalent analyte surface plasmon resonance data.

PubMed

Tiwari, Purushottam Babu; Üren, Aykut; He, Jin; Darici, Yesim; Wang, Xuewen

2015-10-01

Surface plasmon resonance (SPR) is a widely used, affinity based, label-free biophysical technique to investigate biomolecular interactions. The extraction of rate constants requires accurate identification of the particular binding model. The bivalent analyte model involves coupled non-linear differential equations. No clear procedure to identify the bivalent analyte mechanism has been established. In this report, we propose a unique signature for the bivalent analyte model. This signature can be used to distinguish the bivalent analyte model from other biphasic models. The proposed method is demonstrated using experimentally measured SPR sensorgrams.

Mathematical and information maintenance of biometric systems

NASA Astrophysics Data System (ADS)

Boriev, Z.; Sokolov, S.; Nyrkov, A.; Nekrasova, A.

2016-04-01

This article describes the different mathematical methods for processing biometric data. A brief overview of methods for personality recognition by means of a signature is conducted. Mathematical solutions of a dynamic authentication method are considered. Recommendations on use of certain mathematical methods, depending on specific tasks, are provided. Based on the conducted analysis of software and the choice made in favor of the wavelet analysis, a brief basis for its use in the course of software development for biometric personal identification is given for the purpose of its practical application.

Signature detection and matching for document image retrieval.

PubMed

Zhu, Guangyu; Zheng, Yefeng; Doermann, David; Jaeger, Stefan

2009-11-01

As one of the most pervasive methods of individual identification and document authentication, signatures present convincing evidence and provide an important form of indexing for effective document image processing and retrieval in a broad range of applications. However, detection and segmentation of free-form objects such as signatures from clustered background is currently an open document analysis problem. In this paper, we focus on two fundamental problems in signature-based document image retrieval. First, we propose a novel multiscale approach to jointly detecting and segmenting signatures from document images. Rather than focusing on local features that typically have large variations, our approach captures the structural saliency using a signature production model and computes the dynamic curvature of 2D contour fragments over multiple scales. This detection framework is general and computationally tractable. Second, we treat the problem of signature retrieval in the unconstrained setting of translation, scale, and rotation invariant nonrigid shape matching. We propose two novel measures of shape dissimilarity based on anisotropic scaling and registration residual error and present a supervised learning framework for combining complementary shape information from different dissimilarity metrics using LDA. We quantitatively study state-of-the-art shape representations, shape matching algorithms, measures of dissimilarity, and the use of multiple instances as query in document image retrieval. We further demonstrate our matching techniques in offline signature verification. Extensive experiments using large real-world collections of English and Arabic machine-printed and handwritten documents demonstrate the excellent performance of our approaches.

A BRCA1 deficient-like signature is enriched in breast cancer brain metastases and predicts DNA damage-induced poly (ADP-ribose) polymerase inhibitor sensitivity

PubMed Central

2014-01-01

Introduction There is an unmet clinical need for biomarkers to identify breast cancer patients at an increased risk of developing brain metastases. The objective is to identify gene signatures and biological pathways associated with human epidermal growth factor receptor 2-positive (HER2+) brain metastasis. Methods We combined laser capture microdissection and gene expression microarrays to analyze malignant epithelium from HER2+ breast cancer brain metastases with that from HER2+ nonmetastatic primary tumors. Differential gene expression was performed including gene set enrichment analysis (GSEA) using publicly available breast cancer gene expression data sets. Results In a cohort of HER2+ breast cancer brain metastases, we identified a gene expression signature that anti-correlates with overexpression of BRCA1. Sequence analysis of the HER2+ brain metastases revealed no pathogenic mutations of BRCA1, and therefore the aforementioned signature was designated BRCA1 Deficient-Like (BD-L). Evaluation of an independent cohort of breast cancer metastases demonstrated that BD-L values are significantly higher in brain metastases as compared to other metastatic sites. Although the BD-L signature is present in all subtypes of breast cancer, it is significantly higher in BRCA1 mutant primary tumors as compared with sporadic breast tumors. Additionally, BD-L signature values are significantly higher in HER2-/ER- primary tumors as compared with HER2+/ER + and HER2-/ER + tumors. The BD-L signature correlates with breast cancer cell line pharmacologic response to a combination of poly (ADP-ribose) polymerase (PARP) inhibitor and temozolomide, and the signature outperformed four published gene signatures of BRCA1/2 deficiency. Conclusions A BD-L signature is enriched in HER2+ breast cancer brain metastases without pathogenic BRCA1 mutations. Unexpectedly, elevated BD-L values are found in a subset of primary tumors across all breast cancer subtypes. Evaluation of pharmacological sensitivity in breast cancer cell lines representing all breast cancer subtypes suggests the BD-L signature may serve as a biomarker to identify sporadic breast cancer patients who might benefit from a therapeutic combination of PARP inhibitor and temozolomide and may be indicative of a dysfunctional BRCA1-associated pathway. PMID:24625110

Should fatty acid signature proportions sum to 1 for diet estimation?

USGS Publications Warehouse

Bromaghin, Jeffrey F.; Budge, Suzanne M.; Thiemann, Gregory W.

2016-01-01

Knowledge of predator diets, including how diets might change through time or differ among predators, provides essential insights into their ecology. Diet estimation therefore remains an active area of research within quantitative ecology. Quantitative fatty acid signature analysis (QFASA) is an increasingly common method of diet estimation. QFASA is based on a data library of prey signatures, which are vectors of proportions summarizing the fatty acid composition of lipids, and diet is estimated as the mixture of prey signatures that most closely approximates a predator’s signature. Diets are typically estimated using proportions from a subset of all fatty acids that are known to be solely or largely influenced by diet. Given the subset of fatty acids selected, the current practice is to scale their proportions to sum to 1.0. However, scaling signature proportions has the potential to distort the structural relationships within a prey library and between predators and prey. To investigate that possibility, we compared the practice of scaling proportions with two alternatives and found that the traditional scaling can meaningfully bias diet estimators under some conditions. Two aspects of the prey types that contributed to a predator’s diet influenced the magnitude of the bias: the degree to which the sums of unscaled proportions differed among prey types and the identifiability of prey types within the prey library. We caution investigators against the routine scaling of signature proportions in QFASA.

Carbon isotope analyses of n-alkanes released from rapid pyrolysis of oil asphaltenes in a closed system.

PubMed

Chen, Shasha; Jia, Wanglu; Peng, Ping'an

2016-08-15

Carbon isotope analysis of n-alkanes produced by the pyrolysis of oil asphaltenes is a useful tool for characterizing and correlating oil sources. Low-temperature (320-350°C) pyrolysis lasting 2-3 days is usually employed in such studies. Establishing a rapid pyrolysis method is necessary to reduce the time taken for the pretreatment process in isotope analyses. One asphaltene sample was pyrolyzed in sealed ampoules for different durations (60-120 s) at 610°C. The δ(13) C values of the pyrolysates were determined by gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS). The molecular characteristics and isotopic signatures of the pyrolysates were investigated for the different pyrolysis durations and compared with results obtained using the normal pyrolysis method, to determine the optimum time interval. Several asphaltene samples derived from various sources were analyzed using this method. The asphaltene pyrolysates of each sample were similar to those obtained by the flash pyrolysis method on similar samples. However, the molecular characteristics of the pyrolysates obtained over durations longer than 90 s showed intensified secondary reactions. The carbon isotopic signatures of individual compounds obtained at pyrolysis durations less than 90 s were consistent with those obtained from typical low-temperature pyrolysis. Several asphaltene samples from various sources released n-alkanes with distinct carbon isotopic signatures. This easy-to-use pyrolysis method, combined with a subsequent purification procedure, can be used to rapidly obtain clean n-alkanes from oil asphaltenes. Carbon isotopic signatures of n-alkanes released from oil asphaltenes from different sources demonstrate the potential application of this method in 'oil-oil' and 'oil-source' correlations. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd

PubMed Central

Wang, Zichen; Monteiro, Caroline D.; Jagodnik, Kathleen M.; Fernandez, Nicolas F.; Gundersen, Gregory W.; Rouillard, Andrew D.; Jenkins, Sherry L.; Feldmann, Axel S.; Hu, Kevin S.; McDermott, Michael G.; Duan, Qiaonan; Clark, Neil R.; Jones, Matthew R.; Kou, Yan; Goff, Troy; Woodland, Holly; Amaral, Fabio M R.; Szeto, Gregory L.; Fuchs, Oliver; Schüssler-Fiorenza Rose, Sophia M.; Sharma, Shvetank; Schwartz, Uwe; Bausela, Xabier Bengoetxea; Szymkiewicz, Maciej; Maroulis, Vasileios; Salykin, Anton; Barra, Carolina M.; Kruth, Candice D.; Bongio, Nicholas J.; Mathur, Vaibhav; Todoric, Radmila D; Rubin, Udi E.; Malatras, Apostolos; Fulp, Carl T.; Galindo, John A.; Motiejunaite, Ruta; Jüschke, Christoph; Dishuck, Philip C.; Lahl, Katharina; Jafari, Mohieddin; Aibar, Sara; Zaravinos, Apostolos; Steenhuizen, Linda H.; Allison, Lindsey R.; Gamallo, Pablo; de Andres Segura, Fernando; Dae Devlin, Tyler; Pérez-García, Vicente; Ma'ayan, Avi

2016-01-01

Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization. PMID:27667448

Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd.

PubMed

Wang, Zichen; Monteiro, Caroline D; Jagodnik, Kathleen M; Fernandez, Nicolas F; Gundersen, Gregory W; Rouillard, Andrew D; Jenkins, Sherry L; Feldmann, Axel S; Hu, Kevin S; McDermott, Michael G; Duan, Qiaonan; Clark, Neil R; Jones, Matthew R; Kou, Yan; Goff, Troy; Woodland, Holly; Amaral, Fabio M R; Szeto, Gregory L; Fuchs, Oliver; Schüssler-Fiorenza Rose, Sophia M; Sharma, Shvetank; Schwartz, Uwe; Bausela, Xabier Bengoetxea; Szymkiewicz, Maciej; Maroulis, Vasileios; Salykin, Anton; Barra, Carolina M; Kruth, Candice D; Bongio, Nicholas J; Mathur, Vaibhav; Todoric, Radmila D; Rubin, Udi E; Malatras, Apostolos; Fulp, Carl T; Galindo, John A; Motiejunaite, Ruta; Jüschke, Christoph; Dishuck, Philip C; Lahl, Katharina; Jafari, Mohieddin; Aibar, Sara; Zaravinos, Apostolos; Steenhuizen, Linda H; Allison, Lindsey R; Gamallo, Pablo; de Andres Segura, Fernando; Dae Devlin, Tyler; Pérez-García, Vicente; Ma'ayan, Avi

2016-09-26

Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.

Gene signature associated with benign neurofibroma transformation to malignant peripheral nerve sheath tumors

PubMed Central

Sorzano, Carlos O. S.; Pascual-Montano, Alberto; Carazo, Jose M.

2017-01-01

Benign neurofibromas, the main phenotypic manifestations of the rare neurological disorder neurofibromatosis type 1, degenerate to malignant tumors associated to poor prognosis in about 10% of patients. Despite efforts in the field of (epi)genomics, the lack of prognostic biomarkers with which to predict disease evolution frustrates the adoption of appropriate early therapeutic measures. To identify potential biomarkers of malignant neurofibroma transformation, we integrated four human experimental studies and one for mouse, using a gene score-based meta-analysis method, from which we obtained a score-ranked signature of 579 genes. Genes with the highest absolute scores were classified as promising disease biomarkers. By grouping genes with similar neurofibromatosis-related profiles, we derived panels of potential biomarkers. The addition of promoter methylation data to gene profiles indicated a panel of genes probably silenced by hypermethylation. To identify possible therapeutic treatments, we used the gene signature to query drug expression databases. Trichostatin A and other histone deacetylase inhibitors, as well as cantharidin and tamoxifen, were retrieved as putative therapeutic means to reverse the aberrant regulation that drives to malignant cell proliferation and metastasis. This in silico prediction corroborated reported experimental results that suggested the inclusion of these compounds in clinical trials. This experimental validation supported the suitability of the meta-analysis method used to integrate several sources of public genomic information, and the reliability of the gene signature associated to the malignant evolution of neurofibromas to generate working hypotheses for prognostic and drug-responsive biomarkers or therapeutic measures, thus showing the potential of this in silico approach for biomarker discovery. PMID:28542306

41 CFR Appendix C to Chapter 301 - Standard Data Elements for Federal Travel [Traveler Identification

Code of Federal Regulations, 2010 CFR

2010-07-01

... Method employee used to purchase transportation tickets Method Indicator GTR U.S. Government Transportation Request Central Billing Account A contractor centrally billed account Government Charge Card In.../Date Fields Claimant Signature Traveler's signature, or digital representation. The signature signifies...

Trabecular morphometry by fractal signature analysis is a novel marker of osteoarthritis progression.

PubMed

Kraus, Virginia Byers; Feng, Sheng; Wang, ShengChu; White, Scott; Ainslie, Maureen; Brett, Alan; Holmes, Anthony; Charles, H Cecil

2009-12-01

To evaluate the effectiveness of using subchondral bone texture observed on a radiograph taken at baseline to predict progression of knee osteoarthritis (OA) over a 3-year period. A total of 138 participants in the Prediction of Osteoarthritis Progression study were evaluated at baseline and after 3 years. Fractal signature analysis (FSA) of the medial subchondral tibial plateau was performed on fixed flexion radiographs of 248 nonreplaced knees, using a commercially available software tool. OA progression was defined as a change in joint space narrowing (JSN) or osteophyte formation of 1 grade according to a standardized knee atlas. Statistical analysis of fractal signatures was performed using a new model based on correlating the overall shape of a fractal dimension curve with radius. Fractal signature of the medial tibial plateau at baseline was predictive of medial knee JSN progression (area under the curve [AUC] 0.75, of a receiver operating characteristic curve) but was not predictive of osteophyte formation or progression of JSN in the lateral compartment. Traditional covariates (age, sex, body mass index, knee pain), general bone mineral content, and joint space width at baseline were no more effective than random variables for predicting OA progression (AUC 0.52-0.58). The predictive model with maximum effectiveness combined fractal signature at baseline, knee alignment, traditional covariates, and bone mineral content (AUC 0.79). We identified a prognostic marker of OA that is readily extracted from a plain radiograph using FSA. Although the method needs to be validated in a second cohort, our results indicate that the global shape approach to analyzing these data is a potentially efficient means of identifying individuals at risk of knee OA progression.

Can specific transcriptional regulators assemble a universal cancer signature?

NASA Astrophysics Data System (ADS)

Roy, Janine; Isik, Zerrin; Pilarsky, Christian; Schroeder, Michael

2013-10-01

Recently, there is a lot of interest in using biomarker signatures derived from gene expression data to predict cancer progression. We assembled signatures of 25 published datasets covering 13 types of cancers. How do these signatures compare with each other? On one hand signatures answering the same biological question should overlap, whereas signatures predicting different cancer types should differ. On the other hand, there could also be a Universal Cancer Signature that is predictive independently of the cancer type. Initially, we generate signatures for all datasets using classical approaches such as t-test and fold change and then, we explore signatures resulting from a network-based method, that applies the random surfer model of Google's PageRank algorithm. We show that the signatures as published by the authors and the signatures generated with classical methods do not overlap - not even for the same cancer type - whereas the network-based signatures strongly overlap. Selecting 10 out of 37 universal cancer genes gives the optimal prediction for all cancers thus taking a first step towards a Universal Cancer Signature. We furthermore analyze and discuss the involved genes in terms of the Hallmarks of cancer and in particular single out SP1, JUN/FOS and NFKB1 and examine their specific role in cancer progression.

Pose-oblivious shape signature.

PubMed

Gal, Ran; Shamir, Ariel; Cohen-Or, Daniel

2007-01-01

A 3D shape signature is a compact representation for some essence of a shape. Shape signatures are commonly utilized as a fast indexing mechanism for shape retrieval. Effective shape signatures capture some global geometric properties which are scale, translation, and rotation invariant. In this paper, we introduce an effective shape signature which is also pose-oblivious. This means that the signature is also insensitive to transformations which change the pose of a 3D shape such as skeletal articulations. Although some topology-based matching methods can be considered pose-oblivious as well, our new signature retains the simplicity and speed of signature indexing. Moreover, contrary to topology-based methods, the new signature is also insensitive to the topology change of the shape, allowing us to match similar shapes with different genus. Our shape signature is a 2D histogram which is a combination of the distribution of two scalar functions defined on the boundary surface of the 3D shape. The first is a definition of a novel function called the local-diameter function. This function measures the diameter of the 3D shape in the neighborhood of each vertex. The histogram of this function is an informative measure of the shape which is insensitive to pose changes. The second is the centricity function that measures the average geodesic distance from one vertex to all other vertices on the mesh. We evaluate and compare a number of methods for measuring the similarity between two signatures, and demonstrate the effectiveness of our pose-oblivious shape signature within a 3D search engine application for different databases containing hundreds of models.

Evaluation of Grid Modification Methods for On- and Off-Track Sonic Boom Analysis

NASA Technical Reports Server (NTRS)

Nayani, Sudheer N.; Campbell, Richard L.

2013-01-01

Grid modification methods have been under development at NASA to enable better predictions of low boom pressure signatures from supersonic aircraft. As part of this effort, two new codes, Stretched and Sheared Grid - Modified (SSG) and Boom Grid (BG), have been developed in the past year. The CFD results from these codes have been compared with ones from the earlier grid modification codes Stretched and Sheared Grid (SSGRID) and Mach Cone Aligned Prism (MCAP) and also with the available experimental results. NASA's unstructured grid suite of software TetrUSS and the automatic sourcing code AUTOSRC were used for base grid generation and flow solutions. The BG method has been evaluated on three wind tunnel models. Pressure signatures have been obtained up to two body lengths below a Gulfstream aircraft wind tunnel model. Good agreement with the wind tunnel results have been obtained for both on-track and off-track (up to 53 degrees) cases. On-track pressure signatures up to ten body lengths below a Straight Line Segmented Leading Edge (SLSLE) wind tunnel model have been extracted. Good agreement with the wind tunnel results have been obtained. Pressure signatures have been obtained at 1.5 body lengths below a Lockheed Martin aircraft wind tunnel model. Good agreement with the wind tunnel results have been obtained for both on-track and off-track (up to 40 degrees) cases. Grid sensitivity studies have been carried out to investigate any grid size related issues. Methods have been evaluated for fully turbulent, mixed laminar/turbulent and fully laminar flow conditions.

A preliminary analysis of trace-elemental signatures in statoliths of different spawning cohorts for Dosidicus gigas off EEZ waters of Chile

NASA Astrophysics Data System (ADS)

Liu, Bilin; Chen, Xinjun; Fang, Zhou; Hu, Song; Song, Qian

2015-12-01

We applied solution-based ICP-MS method to quantify the trace-elemental signatures in statoliths of jumbo flying squid, Dosidius gigas, which were collected from the waters off northern and central Chile during the scientific surveys carried out by Chinese squid jigging vessels in 2007 and 2008. The age and spawning date of the squid were back-calculated based on daily increments in statoliths. Eight elemental ratios (Sr/Ca, Ba/Ca, Mg/Ca, Mn/Ca, Na/Ca, Fe/Ca, Cu/Ca and Zn/Ca) were analyzed. It was found that Sr is the second most abundant element next to Ca, followed by Na, Fe, Mg, Zn, Cu, Ba and Mn. There was no significant relationship between element/Ca and sea surface temperature (SST) and sea surface salinity (SSS), although weak negative or positive tendency was found. MANOVA analysis showed that multivariate elemental signatures did not differ among the cohorts spawned in spring, autumn and winter, and no significant difference was found between the northern and central sampling locations. Classification results showed that all individuals of each spawned cohorts were correctly classified. This study demonstrates that the elemental signatures in D. gigas statoliths are potentially a useful tool to improve our understanding of its population structure and habitat environment.

Rewinding the waves: tracking underwater signals to their source.

PubMed

Kadri, Usama; Crivelli, Davide; Parsons, Wade; Colbourne, Bruce; Ryan, Amanda

2017-10-24

Analysis of data, recorded on March 8th 2014 at the Comprehensive Nuclear-Test-Ban Treaty Organisation's hydroacoustic stations off Cape Leeuwin Western Australia, and at Diego Garcia, reveal unique pressure signatures that could be associated with objects impacting at the sea surface, such as falling meteorites, or the missing Malaysian Aeroplane MH370. To examine the recorded signatures, we carried out experiments with spheres impacting at the surface of a water tank, where we observed almost identical pressure signature structures. While the pressure structure is unique to impacting objects, the evolution of the radiated acoustic waves carries information on the source. Employing acoustic-gravity wave theory we present an analytical inverse method to retrieve the impact time and location. The solution was validated using field observations of recent earthquakes, where we were able to calculate the eruption time and location to a satisfactory degree of accuracy. Moreover, numerical validations confirm an error below 0.02% for events at relatively large distances of over 1000 km. The method can be developed to calculate other essential properties such as impact duration and geometry. Besides impacting objects and earthquakes, the method could help in identifying the location of underwater explosions and landslides.

Novel Methods to Determine Feeder Locational PV Hosting Capacity and PV Impact Signatures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reno, Matthew J.; Coogan, Kyle; Seuss, John

Often PV hosting capacity analysis is performed for a limited number of distribution feeders. For medium - voltage distribution feeders, previous results generally analyze less than 20 feeders, and then the results are extrapolated out to similar types of feeders. Previous hosting capacity research has often focused on determining a single value for the hosting capacity for the entire feeder, whereas this research expands previous hosting capacity work to investigate all the regions of the feeder that may allow many different hosting capacity values wit h an idea called locational hosting capacity (LHC)to determine the largest PV size that canmore » be interconnected at different locations (buses) on the study feeders. This report discusses novel methods for analyzing PV interconnections with advanced simulati on methods. The focus is feeder and location - specific impacts of PV that determine the locational PV hosting capacity. Feeder PV impact signature are used to more precisely determine the local maximum hosting capacity of individual areas of the feeder. T he feeder signature provides improved interconnection screening with certain zones that show the risk of impact to the distribution feeder from PV interconnections.« less

A New Metabolomic Signature in Type-2 Diabetes Mellitus and Its Pathophysiology

PubMed Central

Padberg, Inken; Peter, Erik; González-Maldonado, Sandra; Witt, Henning; Mueller, Matthias; Weis, Tanja; Bethan, Bianca; Liebenberg, Volker; Wiemer, Jan; Katus, Hugo A.; Rein, Dietrich; Schatz, Philipp

2014-01-01

Objective The objective of the current study was to find a metabolic signature associated with the early manifestations of type-2 diabetes mellitus. Research Design and Method Modern metabolic profiling technology (MxP™ Broad Profiling) was applied to find early alterations in the plasma metabolome of type-2 diabetic patients. The results were validated in an independent study. Eicosanoid and single inon monitoring analysis (MxP™ Eicosanoid and MxP™ SIM analysis) were performed in subsets of samples. Results A metabolic signature including significantly increased levels of glyoxylate as a potential novel marker for early detection of type-2 diabetes mellitus was identified in an initial study (Study1). The signature was significantly altered in fasted diabetic and pre-diabetic subjects and in non-fasted subjects up to three years prior to the diagnosis of type-2 diabetes; most alterations were also consistently found in an independent patient group (Study 2). In Study 2 diabetic and most control subjects suffered from heart failure. In Study 1 a subgroup of diabetic subjects, with a history of use of anti-hypertensive medication further showed a more pronounced increase of glyoxylate levels, compared to a non-diabetic control group when tested in a hyperglycemic state. In the context of a prior history of anti-hypertensive medication, alterations in hexosamine and eicosanoid levels were also found. Conclusion A metabolic signature including glyoxylate was associated with type-2 diabetes mellitus, independent of the fasting status and of occurrence of another major disease. The same signature was also found to be associated with pre-diabetic subjects. Glyoxylate levels further showed a specifically strong increase in a subgroup of diabetic subjects. It could represent a new marker for the detection of medical subgroups of diabetic subjects. PMID:24465478

Queued History based Mediator Identification for an Incentive Attached peer to peer Electronic Coupon System

NASA Astrophysics Data System (ADS)

Shojima, Taiki; Ikkai, Yoshitomo; Komoda, Norihisa

An incentive attached peer to peer (P2P) electronic coupon system is proposed in which users forward e-coupons to potential users by providing incentives to those mediators. A service provider needs to acquire distribution history for incentive payment by recording UserIDs (UIDs) in the e-coupons, since this system is intended for pure P2P environment. This causes problems of dishonestly altering distribution history. In order to solve such problems, distribution history is realized in a couple of queues structure. They are the UID queue, and the public key queue. Each element of the UID queue at the initial state consists of index, a secret key, and a digital signature. In recording one's UID, the encrypted UID is enqueued to the UID queue with a new digital signature created by a secret key of the dequeued element, so that each UID cannot be altered. The public key queue provides the functionality of validating digital signatures on mobile devices. This method makes it possible both each UID and sequence of them to be certificated. The availability of the method is evaluated by quantifying risk reduction using Fault Tree Analysis (FTA). And it's recognized that the method is better than common encryption methods.

Benchmarking desktop and mobile handwriting across COTS devices: The e-BioSign biometric database

PubMed Central

Tolosana, Ruben; Vera-Rodriguez, Ruben; Fierrez, Julian; Morales, Aythami; Ortega-Garcia, Javier

2017-01-01

This paper describes the design, acquisition process and baseline evaluation of the new e-BioSign database, which includes dynamic signature and handwriting information. Data is acquired from 5 different COTS devices: three Wacom devices (STU-500, STU-530 and DTU-1031) specifically designed to capture dynamic signatures and handwriting, and two general purpose tablets (Samsung Galaxy Note 10.1 and Samsung ATIV 7). For the two Samsung tablets, data is collected using both pen stylus and also the finger in order to study the performance of signature verification in a mobile scenario. Data was collected in two sessions for 65 subjects, and includes dynamic information of the signature, the full name and alpha numeric sequences. Skilled forgeries were also performed for signatures and full names. We also report a benchmark evaluation based on e-BioSign for person verification under three different real scenarios: 1) intra-device, 2) inter-device, and 3) mixed writing-tool. We have experimented the proposed benchmark using the main existing approaches for signature verification: feature- and time functions-based. As a result, new insights into the problem of signature biometrics in sensor-interoperable scenarios have been obtained, namely: the importance of specific methods for dealing with device interoperability, and the necessity of a deeper analysis on signatures acquired using the finger as the writing tool. This e-BioSign public database allows the research community to: 1) further analyse and develop signature verification systems in realistic scenarios, and 2) investigate towards a better understanding of the nature of the human handwriting when captured using electronic COTS devices in realistic conditions. PMID:28475590

Benchmarking desktop and mobile handwriting across COTS devices: The e-BioSign biometric database.

PubMed

Tolosana, Ruben; Vera-Rodriguez, Ruben; Fierrez, Julian; Morales, Aythami; Ortega-Garcia, Javier

2017-01-01

This paper describes the design, acquisition process and baseline evaluation of the new e-BioSign database, which includes dynamic signature and handwriting information. Data is acquired from 5 different COTS devices: three Wacom devices (STU-500, STU-530 and DTU-1031) specifically designed to capture dynamic signatures and handwriting, and two general purpose tablets (Samsung Galaxy Note 10.1 and Samsung ATIV 7). For the two Samsung tablets, data is collected using both pen stylus and also the finger in order to study the performance of signature verification in a mobile scenario. Data was collected in two sessions for 65 subjects, and includes dynamic information of the signature, the full name and alpha numeric sequences. Skilled forgeries were also performed for signatures and full names. We also report a benchmark evaluation based on e-BioSign for person verification under three different real scenarios: 1) intra-device, 2) inter-device, and 3) mixed writing-tool. We have experimented the proposed benchmark using the main existing approaches for signature verification: feature- and time functions-based. As a result, new insights into the problem of signature biometrics in sensor-interoperable scenarios have been obtained, namely: the importance of specific methods for dealing with device interoperability, and the necessity of a deeper analysis on signatures acquired using the finger as the writing tool. This e-BioSign public database allows the research community to: 1) further analyse and develop signature verification systems in realistic scenarios, and 2) investigate towards a better understanding of the nature of the human handwriting when captured using electronic COTS devices in realistic conditions.

FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data.

PubMed

DeTomaso, David; Yosef, Nir

2016-08-23

A key challenge in the emerging field of single-cell RNA-Seq is to characterize phenotypic diversity between cells and visualize this information in an informative manner. A common technique when dealing with high-dimensional data is to project the data to 2 or 3 dimensions for visualization. However, there are a variety of methods to achieve this result and once projected, it can be difficult to ascribe biological significance to the observed features. Additionally, when analyzing single-cell data, the relationship between cells can be obscured by technical confounders such as variable gene capture rates. To aid in the analysis and interpretation of single-cell RNA-Seq data, we have developed FastProject, a software tool which analyzes a gene expression matrix and produces a dynamic output report in which two-dimensional projections of the data can be explored. Annotated gene sets (referred to as gene 'signatures') are incorporated so that features in the projections can be understood in relation to the biological processes they might represent. FastProject provides a novel method of scoring each cell against a gene signature so as to minimize the effect of missed transcripts as well as a method to rank signature-projection pairings so that meaningful associations can be quickly identified. Additionally, FastProject is written with a modular architecture and designed to serve as a platform for incorporating and comparing new projection methods and gene selection algorithms. Here we present FastProject, a software package for two-dimensional visualization of single cell data, which utilizes a plethora of projection methods and provides a way to systematically investigate the biological relevance of these low dimensional representations by incorporating domain knowledge.

Novel signatures of cancer-associated fibroblasts.

PubMed

Bozóky, Benedek; Savchenko, Andrii; Csermely, Péter; Korcsmáros, Tamás; Dúl, Zoltán; Pontén, Fredrik; Székely, László; Klein, George

2013-07-15

Increasing evidence indicates the importance of the tumor microenvironment, in particular cancer-associated fibroblasts, in cancer development and progression. In our study, we developed a novel, visually based method to identify new immunohistochemical signatures of these fibroblasts. The method employed a protein list based on 759 protein products of genes identified by RNA profiling from our previous study, comparing fibroblasts with differential growth-modulating effect on human cancers cells, and their first neighbors in the human protein interactome. These 2,654 proteins were analyzed in the Human Protein Atlas online database by comparing their immunohistochemical expression patterns in normal versus tumor-associated fibroblasts. Twelve new proteins differentially expressed in cancer-associated fibroblasts were identified (DLG1, BHLHE40, ROCK2, RAB31, AZI2, PKM2, ARHGAP31, ARHGAP26, ITCH, EGLN1, RNF19A and PLOD2), four of them can be connected to the Rho kinase signaling pathway. They were further analyzed in several additional tumor stromata and revealed that the majority showed congruence among the different tumors. Many of them were also positive in normal myofibroblast-like cells. The new signatures can be useful in immunohistochemical analysis of different tumor stromata and may also give us an insight into the pathways activated in them in their true in vivo context. The method itself could be used for other similar analysis to identify proteins expressed in other cell types in tumors and their surrounding microenvironment. Copyright © 2013 UICC.

A multigene predictor of metastatic outcome in early stage hormone receptor-negative and triple-negative breast cancer

PubMed Central

2010-01-01

Introduction Various multigene predictors of breast cancer clinical outcome have been commercialized, but proved to be prognostic only for hormone receptor (HR) subsets overexpressing estrogen or progesterone receptors. Hormone receptor negative (HRneg) breast cancers, particularly those lacking HER2/ErbB2 overexpression and known as triple-negative (Tneg) cases, are heterogeneous and generally aggressive breast cancer subsets in need of prognostic subclassification, since most early stage HRneg and Tneg breast cancer patients are cured with conservative treatment yet invariably receive aggressive adjuvant chemotherapy. Methods An unbiased search for genes predictive of distant metastatic relapse was undertaken using a training cohort of 199 node-negative, adjuvant treatment naïve HRneg (including 154 Tneg) breast cancer cases curated from three public microarray datasets. Prognostic gene candidates were subsequently validated using a different cohort of 75 node-negative, adjuvant naïve HRneg cases curated from three additional datasets. The HRneg/Tneg gene signature was prognostically compared with eight other previously reported gene signatures, and evaluated for cancer network associations by two commercial pathway analysis programs. Results A novel set of 14 prognostic gene candidates was identified as outcome predictors: CXCL13, CLIC5, RGS4, RPS28, RFX7, EXOC7, HAPLN1, ZNF3, SSX3, HRBL, PRRG3, ABO, PRTN3, MATN1. A composite HRneg/Tneg gene signature index proved more accurate than any individual candidate gene or other reported multigene predictors in identifying cases likely to remain free of metastatic relapse. Significant positive correlations between the HRneg/Tneg index and three independent immune-related signatures (STAT1, IFN, and IR) were observed, as were consistent negative associations between the three immune-related signatures and five other proliferation module-containing signatures (MS-14, ONCO-RS, GGI, CSR/wound and NKI-70). Network analysis identified 8 genes within the HRneg/Tneg signature as being functionally linked to immune/inflammatory chemokine regulation. Conclusions A multigene HRneg/Tneg signature linked to immune/inflammatory cytokine regulation was identified from pooled expression microarray data and shown to be superior to other reported gene signatures in predicting the metastatic outcome of early stage and conservatively managed HRneg and Tneg breast cancer. Further validation of this prognostic signature may lead to new therapeutic insights and spare many newly diagnosed breast cancer patients the need for aggressive adjuvant chemotherapy. PMID:20946665

Determination of community structure through deconvolution of PLFA-FAME signature of mixed population.

PubMed

Dey, Dipesh K; Guha, Saumyen

2007-02-15

Phospholipid fatty acids (PLFAs) as biomarkers are well established in the literature. A general method based on least square approximation (LSA) was developed for the estimation of community structure from the PLFA signature of a mixed population where biomarker PLFA signatures of the component species were known. Fatty acid methyl ester (FAME) standards were used as species analogs and mixture of the standards as representative of the mixed population. The PLFA/FAME signatures were analyzed by gas chromatographic separation, followed by detection in flame ionization detector (GC-FID). The PLFAs in the signature were quantified as relative weight percent of the total PLFA. The PLFA signatures were analyzed by the models to predict community structure of the mixture. The LSA model results were compared with the existing "functional group" approach. Both successfully predicted community structure of mixed population containing completely unrelated species with uncommon PLFAs. For slightest intersection in PLFA signatures of component species, the LSA model produced better results. This was mainly due to inability of the "functional group" approach to distinguish the relative amounts of the common PLFA coming from more than one species. The performance of the LSA model was influenced by errors in the chromatographic analyses. Suppression (or enhancement) of a component's PLFA signature in chromatographic analysis of the mixture, led to underestimation (or overestimation) of the component's proportion in the mixture by the model. In mixtures of closely related species with common PLFAs, the errors in the common components were adjusted across the species by the model.

Detectable Changes in The Blood Transcriptome Are Present after Two Weeks of Antituberculosis Therapy

PubMed Central

Bloom, Chloe I.; Graham, Christine M.; Berry, Matthew P. R.; Wilkinson, Katalin A.; Oni, Tolu; Rozakeas, Fotini; Xu, Zhaohui; Rossello-Urgell, Jose; Chaussabel, Damien; Banchereau, Jacques; Pascual, Virginia; Lipman, Marc; Wilkinson, Robert J.; O’Garra, Anne

2012-01-01

Rationale Globally there are approximately 9 million new active tuberculosis cases and 1.4 million deaths annually. Effective antituberculosis treatment monitoring is difficult as there are no existing biomarkers of poor adherence or inadequate treatment earlier than 2 months after treatment initiation. Inadequate treatment leads to worsening disease, disease transmission and drug resistance. Objectives To determine if blood transcriptional signatures change in response to antituberculosis treatment and could act as early biomarkers of a successful response. Methods Blood transcriptional profiles of untreated active tuberculosis patients in South Africa were analysed before, during (2 weeks and 2 months), at the end of (6 months) and after (12 months) antituberculosis treatment, and compared to individuals with latent tuberculosis. An active-tuberculosis transcriptional signature and a specific treatment-response transcriptional signature were derived. The specific treatment response transcriptional signature was tested in two independent cohorts. Two quantitative scoring algorithms were applied to measure the changes in the transcriptional response. The most significantly represented pathways were determined using Ingenuity Pathway Analysis. Results An active tuberculosis 664-transcript signature and a treatment specific 320-transcript signature significantly diminished after 2 weeks of treatment in all cohorts, and continued to diminish until 6 months. The transcriptional response to treatment could be individually measured in each patient. Conclusions Significant changes in the transcriptional signatures measured by blood tests were readily detectable just 2 weeks after treatment initiation. These findings suggest that blood transcriptional signatures could be used as early surrogate biomarkers of successful treatment response. PMID:23056259

Signature extension: An approach to operational multispectral surveys

NASA Technical Reports Server (NTRS)

Nalepka, R. F.; Morgenstern, J. P.

1973-01-01

Two data processing techniques were suggested as applicable to the large area survey problem. One approach was to use unsupervised classification (clustering) techniques. Investigation of this method showed that since the method did nothing to reduce the signal variability, the use of this method would be very time consuming and possibly inaccurate as well. The conclusion is that unsupervised classification techniques of themselves are not a solution to the large area survey problem. The other method investigated was the use of signature extension techniques. Such techniques function by normalizing the data to some reference condition. Thus signatures from an isolated area could be used to process large quantities of data. In this manner, ground information requirements and computer training are minimized. Several signature extension techniques were tested. The best of these allowed signatures to be extended between data sets collected four days and 80 miles apart with an average accuracy of better than 90%.

Diagnostic value of microRNAs in asbestos exposure and malignant mesothelioma: systematic review and qualitative meta-analysis

PubMed Central

Micolucci, Luigina; Akhtar, Most Mauluda; Olivieri, Fabiola; Rippo, Maria Rita; Procopio, Antonio Domenico

2016-01-01

Background Asbestos is a harmful and exceptionally persistent natural material. Malignant mesothelioma (MM), an asbestos-related disease, is an insidious, lethal cancer that is poorly responsive to current treatments. Minimally invasive, specific, and sensitive biomarkers providing early and effective diagnosis in high-risk patients are urgently needed. MicroRNAs (miRNAs, miRs) are endogenous, non-coding, small RNAs with established diagnostic value in cancer and pollution exposure. A systematic review and a qualitative meta-analysis were conducted to identify high-confidence miRNAs that can serve as biomarkers of asbestos exposure and MM. Methods The major biomedical databases were systematically searched for miRNA expression signatures related to asbestos exposure and MM. The qualitative meta-analysis applied a novel vote-counting method that takes into account multiple parameters. The most significant miRNAs thus identified were then subjected to functional and bioinformatic analysis to assess their biomarker potential. Results A pool of deregulated circulating and tissue miRNAs with biomarker potential for MM was identified and designated as “mesomiRs” (MM-associated miRNAs). Comparison of data from asbestos-exposed and MM subjects found that the most promising candidates for a multimarker signature were circulating miR-126-3p, miR-103a-3p, and miR-625-3p in combination with mesothelin. The most consistently described tissue miRNAs, miR-16-5p, miR-126-3p, miR-143-3p, miR-145-5p, miR-192-5p, miR-193a-3p, miR-200b-3p, miR-203a-3p, and miR-652-3p, were also found to provide a diagnostic signature and should be further investigated as possible therapeutic targets. Conclusion The qualitative meta-analysis and functional investigation confirmed the early diagnostic value of two miRNA signatures for MM. Large-scale, standardized validation studies are needed to assess their clinical relevance, so as to move from the workbench to the clinic. PMID:27259231

Mutational Signatures in Cancer (MuSiCa): a web application to implement mutational signatures analysis in cancer samples.

PubMed

Díaz-Gay, Marcos; Vila-Casadesús, Maria; Franch-Expósito, Sebastià; Hernández-Illán, Eva; Lozano, Juan José; Castellví-Bel, Sergi

2018-06-14

Mutational signatures have been proved as a valuable pattern in somatic genomics, mainly regarding cancer, with a potential application as a biomarker in clinical practice. Up to now, several bioinformatic packages to address this topic have been developed in different languages/platforms. MutationalPatterns has arisen as the most efficient tool for the comparison with the signatures currently reported in the Catalogue of Somatic Mutations in Cancer (COSMIC) database. However, the analysis of mutational signatures is nowadays restricted to a small community of bioinformatic experts. In this work we present Mutational Signatures in Cancer (MuSiCa), a new web tool based on MutationalPatterns and built using the Shiny framework in R language. By means of a simple interface suited to non-specialized researchers, it provides a comprehensive analysis of the somatic mutational status of the supplied cancer samples. It permits characterizing the profile and burden of mutations, as well as quantifying COSMIC-reported mutational signatures. It also allows classifying samples according to the above signature contributions. MuSiCa is a helpful web application to characterize mutational signatures in cancer samples. It is accessible online at http://bioinfo.ciberehd.org/GPtoCRC/en/tools.html and source code is freely available at https://github.com/marcos-diazg/musica .

Improvements in estimating proportions of objects from multispectral data

NASA Technical Reports Server (NTRS)

Horwitz, H. M.; Hyde, P. D.; Richardson, W.

1974-01-01

Methods for estimating proportions of objects and materials imaged within the instantaneous field of view of a multispectral sensor were developed further. Improvements in the basic proportion estimation algorithm were devised as well as improved alien object detection procedures. Also, a simplified signature set analysis scheme was introduced for determining the adequacy of signature set geometry for satisfactory proportion estimation. Averaging procedures used in conjunction with the mixtures algorithm were examined theoretically and applied to artificially generated multispectral data. A computationally simpler estimator was considered and found unsatisfactory. Experiments conducted to find a suitable procedure for setting the alien object threshold yielded little definitive result. Mixtures procedures were used on a limited amount of ERTS data to estimate wheat proportion in selected areas. Results were unsatisfactory, partly because of the ill-conditioned nature of the pure signature set.

Game meat authentication through rare earth elements fingerprinting.

PubMed

Danezis, G P; Pappas, A C; Zoidis, E; Papadomichelakis, G; Hadjigeorgiou, I; Zhang, P; Brusic, V; Georgiou, C A

2017-10-23

Accurate labelling of meat (e.g. wild versus farmed, geographical and genetic origin, organic versus conventional, processing treatment) is important to inform the consumers about the products they buy. Meat and meat products declared as game have higher commercial value making them target to fraudulent labelling practices and replacement with non-game meat. We have developed and validated a new method for authentication of wild rabbit meat using elemental metabolomics approach. Elemental analysis was performed using rapid ultra-trace multi-element measurement by inductively coupled plasma mass spectrometry (ICP-MS). Elemental signatures showed excellent ability to discriminate the wild rabbit from non-wild rabbit meat. Our results demonstrate the usefulness of metabolic markers -rare earth signatures, as well as other trace element signatures for game meat authentication. Copyright © 2017 Elsevier B.V. All rights reserved.

Usage monitoring of electrical devices in a smart home.

PubMed

Rahimi, Saba; Chan, Adrian D C; Goubran, Rafik A

2011-01-01

Profiling the usage of electrical devices within a smart home can be used as a method for determining an occupant's activities of daily living. A nonintrusive load monitoring system monitors the electrical consumption at a single electrical source (e.g., main electric utility service entry) and the operating schedules of individual devices are determined by disaggregating the composite electrical consumption waveforms. An electrical device's load signature plays a key role in nonintrusive load monitoring systems. A load signature is the unique electrical behaviour of an individual device when it is in operation. This paper proposes a feature-based model, using the real power and reactive power as features for describing the load signatures of individual devices. Experimental results for single device recognition for 7 devices show that the proposed approach can achieve 100% classification accuracy with discriminant analysis using Mahalanobis distances.

Adaptive Aft Signature Shaping of a Low-Boom Supersonic Aircraft Using Off-Body Pressures

NASA Technical Reports Server (NTRS)

Ordaz, Irian; Li, Wu

2012-01-01

The design and optimization of a low-boom supersonic aircraft using the state-of-the- art o -body aerodynamics and sonic boom analysis has long been a challenging problem. The focus of this paper is to demonstrate an e ective geometry parameterization scheme and a numerical optimization approach for the aft shaping of a low-boom supersonic aircraft using o -body pressure calculations. A gradient-based numerical optimization algorithm that models the objective and constraints as response surface equations is used to drive the aft ground signature toward a ramp shape. The design objective is the minimization of the variation between the ground signature and the target signature subject to several geometric and signature constraints. The target signature is computed by using a least-squares regression of the aft portion of the ground signature. The parameterization and the deformation of the geometry is performed with a NASA in- house shaping tool. The optimization algorithm uses the shaping tool to drive the geometric deformation of a horizontal tail with a parameterization scheme that consists of seven camber design variables and an additional design variable that describes the spanwise location of the midspan section. The demonstration cases show that numerical optimization using the state-of-the-art o -body aerodynamic calculations is not only feasible and repeatable but also allows the exploration of complex design spaces for which a knowledge-based design method becomes less effective.

Methane Emissions in the London Region: Deciphering Regional Sources with Mobile Measurements

NASA Astrophysics Data System (ADS)

Zazzeri, G.; Lowry, D.; Fisher, R. E.; France, J. L.; Lanoisellé, M.; Bjorkegren, A.; Nisbet, E. G.

2014-12-01

Methane stable isotope analysis, coupled with mole fraction measurement, has been used to link isotopic signature to methane emissions from the leading methane sources in the London region, such as landfills and gas leaks. A mobile Picarro G2301 CRDS analyser was installed in a vehicle, together with an anemometer and a Hemisphere GPS receiver, to measure atmospheric methane mole fractions and their relative location. When methane plumes were located and intercepted, air samples were collected in Tedlar bags, for δ13C-CH4 isotopic analysis by CF-GC-IRMS (Continous Flow-Gas Chromatography-Isotopic Ratio Mass Spectroscopy). This method provides high precision isotopic values, determining δ13C-CH4 to ±0.05 per mil. The bulk signature of the methane plume into the atmosphere from the whole source area was obtained by Keeling plot analysis, and a δ13C-CH4 signature, with the relative uncertainty, allocated to each methane source investigated. The averaged δ13C-CH4 signature for landfill sites around the London region is - 58 ± 3 ‰, whereas the δ13C-CH4 signature for gas leaks is fairly constant at -36 ± 2 ‰, a value characteristic of North Sea supply. The Picarro G2301 analyser was installed also on the roof of King's College London, located in the centre of the city, and connected to an air inlet located 7 meters above roof height. An auto-sampler was connected to the same air inlet and launched remotely when a high nocturnal build up was expected, allowing up to twenty air bags to be collected for methane isotopic analysis over a 24 hour period. The main source contributing to overnight methane build up in central London is fugitive gas, in agreement with inventories. From the isotopic characterisation of urban methane sources and the source mix in London, the contribution to the urban methane budget and the local distribution of the methane sources given in inventories can be validated.

DOE Office of Scientific and Technical Information (OSTI.GOV)

I. W. Ginsberg

Multiresolutional decompositions known as spectral fingerprints are often used to extract spectral features from multispectral/hyperspectral data. In this study, the authors investigate the use of wavelet-based algorithms for generating spectral fingerprints. The wavelet-based algorithms are compared to the currently used method, traditional convolution with first-derivative Gaussian filters. The comparison analyses consists of two parts: (a) the computational expense of the new method is compared with the computational costs of the current method and (b) the outputs of the wavelet-based methods are compared with those of the current method to determine any practical differences in the resulting spectral fingerprints. The resultsmore » show that the wavelet-based algorithms can greatly reduce the computational expense of generating spectral fingerprints, while practically no differences exist in the resulting fingerprints. The analysis is conducted on a database of hyperspectral signatures, namely, Hyperspectral Digital Image Collection Experiment (HYDICE) signatures. The reduction in computational expense is by a factor of about 30, and the average Euclidean distance between resulting fingerprints is on the order of 0.02.« less

Binary CFG Rebuilt of Self-Modifying Codes

DTIC Science & Technology

2016-10-03

ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      04-10-2016 2. REPORT TYPE Final 3. DATES COVERED (From - To) 12 May 2014 to 11 May 2016 4. TITLE ...industry to analyze malware is a dynamic analysis in a sand- box . Alternatively, we apply a hybrid method combining concolic testing (dynamic symbolic...virus software based on binary signatures. A popular method in industry to analyze malware is a dynamic analysis in a sand- box . Alternatively, we

Cancer Imaging Phenomics Toolkit (CaPTk) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

CaPTk is a software toolkit to facilitate translation of quantitative image analysis methods that help us obtain rich imaging phenotypic signatures of oncologic images and relate them to precision diagnostics and prediction of clinical outcomes, as well as to underlying molecular characteristics of cancer. The stand-alone graphical user interface of CaPTk brings analysis methods from the realm of medical imaging research to the clinic, and will be extended to use web-based services for computationally-demanding pipelines.

Multiscale moment-based technique for object matching and recognition

NASA Astrophysics Data System (ADS)

Thio, HweeLi; Chen, Liya; Teoh, Eam-Khwang

2000-03-01

A new method is proposed to extract features from an object for matching and recognition. The features proposed are a combination of local and global characteristics -- local characteristics from the 1-D signature function that is defined to each pixel on the object boundary, global characteristics from the moments that are generated from the signature function. The boundary of the object is first extracted, then the signature function is generated by computing the angle between two lines from every point on the boundary as a function of position along the boundary. This signature function is position, scale and rotation invariant (PSRI). The shape of the signature function is then described quantitatively by using moments. The moments of the signature function are the global characters of a local feature set. Using moments as the eventual features instead of the signature function reduces the time and complexity of an object matching application. Multiscale moments are implemented to produce several sets of moments that will generate more accurate matching. Basically multiscale technique is a coarse to fine procedure and makes the proposed method more robust to noise. This method is proposed to match and recognize objects under simple transformation, such as translation, scale changes, rotation and skewing. A simple logo indexing system is implemented to illustrate the performance of the proposed method.

Minimal methylation classifier (MIMIC): A novel method for derivation and rapid diagnostic detection of disease-associated DNA methylation signatures.

PubMed

Schwalbe, E C; Hicks, D; Rafiee, G; Bashton, M; Gohlke, H; Enshaei, A; Potluri, S; Matthiesen, J; Mather, M; Taleongpong, P; Chaston, R; Silmon, A; Curtis, A; Lindsey, J C; Crosier, S; Smith, A J; Goschzik, T; Doz, F; Rutkowski, S; Lannering, B; Pietsch, T; Bailey, S; Williamson, D; Clifford, S C

2017-10-18

Rapid and reliable detection of disease-associated DNA methylation patterns has major potential to advance molecular diagnostics and underpin research investigations. We describe the development and validation of minimal methylation classifier (MIMIC), combining CpG signature design from genome-wide datasets, multiplex-PCR and detection by single-base extension and MALDI-TOF mass spectrometry, in a novel method to assess multi-locus DNA methylation profiles within routine clinically-applicable assays. We illustrate the application of MIMIC to successfully identify the methylation-dependent diagnostic molecular subgroups of medulloblastoma (the most common malignant childhood brain tumour), using scant/low-quality samples remaining from the most recently completed pan-European medulloblastoma clinical trial, refractory to analysis by conventional genome-wide DNA methylation analysis. Using this approach, we identify critical DNA methylation patterns from previously inaccessible cohorts, and reveal novel survival differences between the medulloblastoma disease subgroups with significant potential for clinical exploitation.

Sequence signatures of allosteric proteins towards rational design.

PubMed

Namboodiri, Saritha; Verma, Chandra; Dhar, Pawan K; Giuliani, Alessandro; Nair, Achuthsankar S

2010-12-01

Allostery is the phenomenon of changes in the structure and activity of proteins that appear as a consequence of ligand binding at sites other than the active site. Studying mechanistic basis of allostery leading to protein design with predetermined functional endpoints is an important unmet need of synthetic biology. Here, we screened the amino acid sequence landscape in search of sequence-signatures of allostery using Recurrence Quantitative Analysis (RQA) method. A characteristic vector, comprised of 10 features extracted from RQA was defined for amino acid sequences. Using Principal Component Analysis, four factors were found to be important determinants of allosteric behavior. Our sequence-based predictor method shows 82.6% accuracy, 85.7% sensitivity and 77.9% specificity with the current dataset. Further, we show that Laminarity-Mean-hydrophobicity representing repeated hydrophobic patches is the most crucial indicator of allostery. To our best knowledge this is the first report that describes sequence determinants of allostery based on hydrophobicity. As an outcome of these findings, we plan to explore possibility of inducing allostery in proteins.

Fault detection and diagnosis of induction motors using motor current signature analysis and a hybrid FMM-CART model.

PubMed

Seera, Manjeevan; Lim, Chee Peng; Ishak, Dahaman; Singh, Harapajan

2012-01-01

In this paper, a novel approach to detect and classify comprehensive fault conditions of induction motors using a hybrid fuzzy min-max (FMM) neural network and classification and regression tree (CART) is proposed. The hybrid model, known as FMM-CART, exploits the advantages of both FMM and CART for undertaking data classification and rule extraction problems. A series of real experiments is conducted, whereby the motor current signature analysis method is applied to form a database comprising stator current signatures under different motor conditions. The signal harmonics from the power spectral density are extracted as discriminative input features for fault detection and classification with FMM-CART. A comprehensive list of induction motor fault conditions, viz., broken rotor bars, unbalanced voltages, stator winding faults, and eccentricity problems, has been successfully classified using FMM-CART with good accuracy rates. The results are comparable, if not better, than those reported in the literature. Useful explanatory rules in the form of a decision tree are also elicited from FMM-CART to analyze and understand different fault conditions of induction motors.

An improved procedure for detection and enumeration of walrus signatures in airborne thermal imagery

USGS Publications Warehouse

Burn, Douglas M.; Udevitz, Mark S.; Speckman, Suzann G.; Benter, R. Bradley

2009-01-01

In recent years, application of remote sensing to marine mammal surveys has been a promising area of investigation for wildlife managers and researchers. In April 2006, the United States and Russia conducted an aerial survey of Pacific walrus (Odobenus rosmarus divergens) using thermal infrared sensors to detect groups of animals resting on pack ice in the Bering Sea. The goal of this survey was to estimate the size of the Pacific walrus population. An initial analysis of the U.S. data using previously-established methods resulted in lower detectability of walrus groups in the imagery and higher variability in calibration models than was expected based on pilot studies. This paper describes an improved procedure for detection and enumeration of walrus groups in airborne thermal imagery. Thermal images were first subdivided into smaller 200 x 200 pixel "tiles." We calculated three statistics to represent characteristics of walrus signatures from the temperature histogram for each the. Tiles that exhibited one or more of these characteristics were examined further to determine if walrus signatures were present. We used cluster analysis on tiles that contained walrus signatures to determine which pixels belonged to each group. We then calculated a thermal index value for each walrus group in the imagery and used generalized linear models to estimate detection functions (the probability of a group having a positive index value) and calibration functions (the size of a group as a function of its index value) based on counts from matched digital aerial photographs. The new method described here improved our ability to detect walrus groups at both 2 m and 4 m spatial resolution. In addition, the resulting calibration models have lower variance than the original method. We anticipate that the use of this new procedure will greatly improve the quality of the population estimate derived from these data. This procedure may also have broader applicability to thermal infrared surveys of other wildlife species. Published by Elsevier B.V.

Multidimensional Raman spectroscopic signatures as a tool for forensic identification of body fluid traces: a review.

PubMed

Sikirzhytski, Vitali; Sikirzhytskaya, Aliaksandra; Lednev, Igor K

2011-11-01

The analysis of body fluid traces during forensic investigations is a critical step in determining the key details of a crime. Several confirmatory and presumptive biochemical tests are currently utilized. However, these tests are all destructive, and no single method can be used to analyze all body fluids. This review outlines recent progress in the development of a novel universal approach for the nondestructive, confirmatory identification of body fluid traces using Raman spectroscopy. The method is based on the use of multidimensional spectroscopic signatures of body fluids and accounts for the intrinsic heterogeneity of dry traces and donor variation. The results presented here demonstrate that Raman spectroscopy has potential for identifying traces of semen, blood, saliva, sweat, and vaginal fluid with high confidence.

40 CFR 262.25 - Electronic manifest signatures.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 26 2014-07-01 2014-07-01 false Electronic manifest signatures. 262.25... (CONTINUED) STANDARDS APPLICABLE TO GENERATORS OF HAZARDOUS WASTE The Manifest § 262.25 Electronic manifest signatures. Electronic signature methods for the e-Manifest system shall: (a) Be a legally valid and...

Air-gun signature modelling considering the influence of mechanical structure factors

NASA Astrophysics Data System (ADS)

Li, Guofa; Liu, Zhao; Wang, Jianhua; Cao, Mingqiang

2014-04-01

In marine seismic prospecting, as the air-gun array is usually composed of different types of air-guns, the signature modelling of different air-guns is particularly important to the array design. Different types of air-guns have different mechanical structures, which directly or indirectly affect the signatures. In order to simulate the influence of the mechanical structure, five parameters—the throttling constant, throttling power law exponent, mass release efficiency, fluid viscosity and heat transfer coefficient—are used in signature modelling. Through minimizing the energy relative error between the simulated and the measured signatures by the simulated annealing method, the five optimal parameters can be estimated. The method is tested in a field experiment, and the consistency between the simulated and the measured signatures is improved with the optimal parameters.

Longitudinal Analysis of Whole Blood Transcriptomes to Explore Molecular Signatures Associated With Acute Renal Allograft Rejection

PubMed Central

Shin, Heesun; Günther, Oliver; Hollander, Zsuzsanna; Wilson-McManus, Janet E.; Ng, Raymond T.; Balshaw, Robert; Keown, Paul A.; McMaster, Robert; McManus, Bruce M.; Isbel, Nicole M.; Knoll, Greg; Tebbutt, Scott J.

2014-01-01

In this study, we explored a time course of peripheral whole blood transcriptomes from kidney transplantation patients who either experienced an acute rejection episode or did not in order to better delineate the immunological and biological processes measureable in blood leukocytes that are associated with acute renal allograft rejection. Using microarrays, we generated gene expression data from 24 acute rejectors and 24 nonrejectors. We filtered the data to obtain the most unambiguous and robustly expressing probe sets and selected a subset of patients with the clearest phenotype. We then performed a data-driven exploratory analysis using data reduction and differential gene expression analysis tools in order to reveal gene expression signatures associated with acute allograft rejection. Using a template-matching algorithm, we then expanded our analysis to include time course data, identifying genes whose expression is modulated leading up to acute rejection. We have identified molecular phenotypes associated with acute renal allograft rejection, including a significantly upregulated signature of neutrophil activation and accumulation following transplant surgery that is common to both acute rejectors and nonrejectors. Our analysis shows that this expression signature appears to stabilize over time in nonrejectors but persists in patients who go on to reject the transplanted organ. In addition, we describe an expression signature characteristic of lymphocyte activity and proliferation. This lymphocyte signature is significantly downregulated in both acute rejectors and nonrejectors following surgery; however, patients who go on to reject the organ show a persistent downregulation of this signature relative to the neutrophil signature. PMID:24526836

Searching for evidence of quasi-periodic pulsations in solar flares using the AFINO code

NASA Astrophysics Data System (ADS)

Inglis, Andrew; Ireland, Jack; Dennis, Brian R.; Hayes, Laura Ann; Gallagher, Peter T.

2017-08-01

The AFINO (Automated Flare Inference of Oscillations) code is a new tool to allow analysis of temporal solar data in search of oscillatory signatures. Using AFINO, we carry out a large-scale search for evidence of signals consistent with quasi-periodic pulsations (QPP) in solar flares, focusing on the 1-300 s timescale. We analyze 675 M- and X-class flares observed by GOES in 1-8 Å soft X-rays between 2011 February 1 and 2015 December 31. Additionally, over the same era we analyze Fermi/GBM 15-25 keV X-ray data for each of these flares associated with a GBM solar flare trigger, a total of 261 events. Using a model comparison method and the Bayesian Information Criterion statistic, we determine whether there is evidence for a substantial enhancement in the Fourier power spectrum that may be consistent with a QPP-like signature.Quasi-steady periodic signatures appear more prevalently in thermal soft X-ray data than in the counterpart hard X-ray emission: according to AFINO ~30% of GOES flares but only ~8% of the same flares observed by GBM show strong signatures consistent with classical interpretations of QPP, which include MHD wave processes and oscillatory reconnection events. For both datasets, preferred characteristic timescales of ~5-30 s were found in the QPP-like events, with no clear dependence on flare magnitude. Individual events in the sample also show similar characteristic timescales in both GBM and GOES data sets, indicating that the same phenomenon is sometimes observed simultaneously in soft and hard X-rays. We discuss the implications of these survey results, and future developments of the analysis method. AFINO continues to run daily on new flares observed by GOES, and the full AFINO catalogue is made available online.

The effects of different representations on static structure analysis of computer malware signatures.

PubMed

Narayanan, Ajit; Chen, Yi; Pang, Shaoning; Tao, Ban

2013-01-01

The continuous growth of malware presents a problem for internet computing due to increasingly sophisticated techniques for disguising malicious code through mutation and the time required to identify signatures for use by antiviral software systems (AVS). Malware modelling has focused primarily on semantics due to the intended actions and behaviours of viral and worm code. The aim of this paper is to evaluate a static structure approach to malware modelling using the growing malware signature databases now available. We show that, if malware signatures are represented as artificial protein sequences, it is possible to apply standard sequence alignment techniques in bioinformatics to improve accuracy of distinguishing between worm and virus signatures. Moreover, aligned signature sequences can be mined through traditional data mining techniques to extract metasignatures that help to distinguish between viral and worm signatures. All bioinformatics and data mining analysis were performed on publicly available tools and Weka.

The Effects of Different Representations on Static Structure Analysis of Computer Malware Signatures

PubMed Central

Narayanan, Ajit; Chen, Yi; Pang, Shaoning; Tao, Ban

2013-01-01

The continuous growth of malware presents a problem for internet computing due to increasingly sophisticated techniques for disguising malicious code through mutation and the time required to identify signatures for use by antiviral software systems (AVS). Malware modelling has focused primarily on semantics due to the intended actions and behaviours of viral and worm code. The aim of this paper is to evaluate a static structure approach to malware modelling using the growing malware signature databases now available. We show that, if malware signatures are represented as artificial protein sequences, it is possible to apply standard sequence alignment techniques in bioinformatics to improve accuracy of distinguishing between worm and virus signatures. Moreover, aligned signature sequences can be mined through traditional data mining techniques to extract metasignatures that help to distinguish between viral and worm signatures. All bioinformatics and data mining analysis were performed on publicly available tools and Weka. PMID:23983644

A Dynamic Time Warping based covariance function for Gaussian Processes signature identification

NASA Astrophysics Data System (ADS)

Silversides, Katherine L.; Melkumyan, Arman

2016-11-01

Modelling stratiform deposits requires a detailed knowledge of the stratigraphic boundaries. In Banded Iron Formation (BIF) hosted ores of the Hamersley Group in Western Australia these boundaries are often identified using marker shales. Both Gaussian Processes (GP) and Dynamic Time Warping (DTW) have been previously proposed as methods to automatically identify marker shales in natural gamma logs. However, each method has different advantages and disadvantages. We propose a DTW based covariance function for the GP that combines the flexibility of the DTW with the probabilistic framework of the GP. The three methods are tested and compared on their ability to identify two natural gamma signatures from a Marra Mamba type iron ore deposit. These tests show that while all three methods can identify boundaries, the GP with the DTW covariance function combines and balances the strengths and weaknesses of the individual methods. This method identifies more positive signatures than the GP with the standard covariance function, and has a higher accuracy for identified signatures than the DTW. The combined method can handle larger variations in the signature without requiring multiple libraries, has a probabilistic output and does not require manual cut-off selections.

Analysis of Human Plasma Metabolites across Different Liquid Chromatography - Mass Spectrometry Platforms: Cross-platform Transferable Chemical Signatures

PubMed Central

Telu, Kelly H.; Yan, Xinjian; Wallace, William E.; Stein, Stephen E.; Simón-Manso, Yamil

2016-01-01

RATIONALE The metabolite profiling of a NIST plasma Standard Reference Material (SRM 1950) on different LC-MS platforms showed significant differences. Although these findings suggest caution when interpreting metabolomics results, the degree of overlap of both profiles allowed us to use tandem mass spectral libraries of recurrent spectra to evaluate to what extent these results are transferable across platforms and to develop cross-platform chemical signatures. METHODS Non-targeted global metabolite profiles of SRM 1950 were obtained on different LC-MS platforms using reversed phase chromatography and different chromatographic scales (nano, conventional and UHPLC). The data processing and the metabolite differential analysis were carried out using publically available (XCMS), proprietary (Mass Profiler Professional) and in-house software (NIST pipeline). RESULTS Repeatability and intermediate precision showed that the non-targeted SRM 1950 profiling was highly reproducible when working on the same platform (RSD < 2%); however, substantial differences were found in the LC-MS patterns originating on different platforms or even using different chromatographic scales (conventional HPLC, UHPLC and nanoLC) on the same platform. A substantial degree of overlap (common molecular features) was also found. A procedure to generate consistent chemical signatures using tandem mass spectral libraries of recurrent spectra is proposed. CONLUSIONS Different platforms rendered significantly different metabolite profiles, but the results were highly reproducible when working within one platform. Tandem mass spectral libraries of recurrent spectra are proposed to evaluate the degree of transferability of chemical signatures generated on different platforms. Chemical signatures based on our procedure are most likely cross-platform transferable. PMID:26842580

Third-Order Spectral Techniques for the Diagnosis of Motor Bearing Condition Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Yang, D.-M.; Stronach, A. F.; MacConnell, P.; Penman, J.

2002-03-01

This paper addresses the development of a novel condition monitoring procedure for rolling element bearings which involves a combination of signal processing, signal analysis and artificial intelligence methods. Seven approaches based on power spectrum, bispectral and bicoherence vibration analyses are investigated as signal pre-processing techniques for application in the diagnosis of a number of induction motor rolling element bearing conditions. The bearing conditions considered are a normal bearing and bearings with cage and inner and outer race faults. The vibration analysis methods investigated are based on the power spectrum, the bispectrum, the bicoherence, the bispectrum diagonal slice, the bicoherence diagonal slice, the summed bispectrum and the summed bicoherence. Selected features are extracted from the vibration signatures so obtained and these are used as inputs to an artificial neural network trained to identify the bearing conditions. Quadratic phase coupling (QPC), examined using the magnitude of bispectrum and bicoherence and biphase, is shown to be absent from the bearing system and it is therefore concluded that the structure of the bearing vibration signatures results from inter-modulation effects. In order to test the proposed procedure, experimental data from a bearing test rig are used to develop an example diagnostic system. Results show that the bearing conditions examined can be diagnosed with a high success rate, particularly when using the summed bispectrum signatures.

76 FR 31262 - Application for Annuity or Lump Sum

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-31

... regulations in order to allow signature alternatives to the traditional pen-and-ink (``wet'') signature. The.... SUMMARY: The Railroad Retirement Board (Board) proposes to amend its regulations to allow alternative signature methods in addition to the traditional pen-and-ink or '' wet'' signature in order to implement an...

Superpixel Based Factor Analysis and Target Transformation Method for Martian Minerals Detection

NASA Astrophysics Data System (ADS)

Wu, X.; Zhang, X.; Lin, H.

2018-04-01

The Factor analysis and target transformation (FATT) is an effective method to test for the presence of particular mineral on Martian surface. It has been used both in thermal infrared (Thermal Emission Spectrometer, TES) and near-infrared (Compact Reconnaissance Imaging Spectrometer for Mars, CRISM) hyperspectral data. FATT derived a set of orthogonal eigenvectors from a mixed system and typically selected first 10 eigenvectors to least square fit the library mineral spectra. However, minerals present only in a limited pixels will be ignored because its weak spectral features compared with full image signatures. Here, we proposed a superpixel based FATT method to detect the mineral distributions on Mars. The simple linear iterative clustering (SLIC) algorithm was used to partition the CRISM image into multiple connected image regions with spectral homogeneous to enhance the weak signatures by increasing their proportion in a mixed system. A least square fitting was used in target transformation and performed to each region iteratively. Finally, the distribution of the specific minerals in image was obtained, where fitting residual less than a threshold represent presence and otherwise absence. We validate our method by identifying carbonates in a well analysed CRISM image in Nili Fossae on Mars. Our experimental results indicate that the proposed method work well both in simulated and real data sets.

Gene-expression signature regulated by the KEAP1-NRF2-CUL3 axis is associated with a poor prognosis in head and neck squamous cell cancer.

PubMed

Namani, Akhileshwar; Matiur Rahaman, Md; Chen, Ming; Tang, Xiuwen

2018-01-06

NRF2 is the key regulator of oxidative stress in normal cells and aberrant expression of the NRF2 pathway due to genetic alterations in the KEAP1 (Kelch-like ECH-associated protein 1)-NRF2 (nuclear factor erythroid 2 like 2)-CUL3 (cullin 3) axis leads to tumorigenesis and drug resistance in many cancers including head and neck squamous cell cancer (HNSCC). The main goal of this study was to identify specific genes regulated by the KEAP1-NRF2-CUL3 axis in HNSCC patients, to assess the prognostic value of this gene signature in different cohorts, and to reveal potential biomarkers. RNA-Seq V2 level 3 data from 279 tumor samples along with 37 adjacent normal samples from patients enrolled in the The Cancer Genome Atlas (TCGA)-HNSCC study were used to identify upregulated genes using two methods (altered KEAP1-NRF2-CUL3 versus normal, and altered KEAP1-NRF2-CUL3 versus wild-type). We then used a new approach to identify the combined gene signature by integrating both datasets and subsequently tested this signature in 4 independent HNSCC datasets to assess its prognostic value. In addition, functional annotation using the DAVID v6.8 database and protein-protein interaction (PPI) analysis using the STRING v10 database were performed on the signature. A signature composed of a subset of 17 genes regulated by the KEAP1-NRF2-CUL3 axis was identified by overlapping both the upregulated genes of altered versus normal (251 genes) and altered versus wild-type (25 genes) datasets. We showed that increased expression was significantly associated with poor survival in 4 independent HNSCC datasets, including the TCGA-HNSCC dataset. Furthermore, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and PPI analysis revealed that most of the genes in this signature are associated with drug metabolism and glutathione metabolic pathways. Altogether, our study emphasizes the discovery of a gene signature regulated by the KEAP1-NRF2-CUL3 axis which is strongly associated with tumorigenesis and drug resistance in HNSCC. This 17-gene signature provides potential biomarkers and therapeutic targets for HNSCC cases in which the NRF2 pathway is activated.

Changes in Gene Expression Predicting Local Control in Cervical Cancer: Results from Radiation Therapy Oncology Group 0128

PubMed Central

Weidhaas, Joanne B.; Li, Shu-Xia; Winter, Kathryn; Ryu, Janice; Jhingran, Anuja; Miller, Bridgette; Dicker, Adam P.; Gaffney, David

2009-01-01

Purpose To evaluate the potential of gene expression signatures to predict response to treatment in locally advanced cervical cancer treated with definitive chemotherapy and radiation. Experimental Design Tissue biopsies were collected from patients participating in Radiation Therapy Oncology Group (RTOG) 0128, a phase II trial evaluating the benefit of celecoxib in addition to cisplatin chemotherapy and radiation for locally advanced cervical cancer. Gene expression profiling was done and signatures of pretreatment, mid-treatment (before the first implant), and “changed” gene expression patterns between pre- and mid-treatment samples were determined. The ability of the gene signatures to predict local control versus local failure was evaluated. Two-group t test was done to identify the initial gene set separating these end points. Supervised classification methods were used to enrich the gene sets. The results were further validated by leave-one-out and 2-fold cross-validation. Results Twenty-two patients had suitable material from pretreatment samples for analysis, and 13 paired pre- and mid-treatment samples were obtained. The changed gene expression signatures between the pre- and mid-treatment biopsies predicted response to treatment, separating patients with local failures from those who achieved local control with a seven-gene signature. The in-sample prediction rate, leave-one-out prediction rate, and 2-fold prediction rate are 100% for this seven-gene signature. This signature was enriched for cell cycle genes. Conclusions Changed gene expression signatures during therapy in cervical cancer can predict outcome as measured by local control. After further validation, such findings could be applied to direct additional therapy for cervical cancer patients treated with chemotherapy and radiation. PMID:19509178

Baseline shifts in coral skeletal oxygen isotopic composition: a signature of symbiont shuffling?

NASA Astrophysics Data System (ADS)

Carilli, J. E.; Charles, C. D.; Garren, M.; McField, M.; Norris, R. D.

2013-06-01

Decades-long records of the stable isotopic composition of coral skeletal cores were analyzed from four sites on the Mesoamerican Reef. Two of the sites exhibited baseline shifts in oxygen isotopic composition after known coral bleaching events. Changes in pH at the calcification site caused by a change in the associated symbiont community are invoked to explain the observed shift in the isotopic composition. To test the hypothesis that changes in symbiont clade could affect skeletal chemistry, additional coral samples were collected from Belize for paired Symbiodinium identification and skeletal stable isotopic analysis. We found some evidence that skeletal stable isotopic composition may be affected by symbiont clade and suggest this is an important topic for future investigation. If different Symbiodinium clades leave consistent signatures in skeletal geochemical composition, the signature will provide a method to quantify past symbiont shuffling events, important for understanding how corals are likely to respond to climate change.

Experimental statistical signature of many-body quantum interference

NASA Astrophysics Data System (ADS)

Giordani, Taira; Flamini, Fulvio; Pompili, Matteo; Viggianiello, Niko; Spagnolo, Nicolò; Crespi, Andrea; Osellame, Roberto; Wiebe, Nathan; Walschaers, Mattia; Buchleitner, Andreas; Sciarrino, Fabio

2018-03-01

Multi-particle interference is an essential ingredient for fundamental quantum mechanics phenomena and for quantum information processing to provide a computational advantage, as recently emphasized by boson sampling experiments. Hence, developing a reliable and efficient technique to witness its presence is pivotal in achieving the practical implementation of quantum technologies. Here, we experimentally identify genuine many-body quantum interference via a recent efficient protocol, which exploits statistical signatures at the output of a multimode quantum device. We successfully apply the test to validate three-photon experiments in an integrated photonic circuit, providing an extensive analysis on the resources required to perform it. Moreover, drawing upon established techniques of machine learning, we show how such tools help to identify the—a priori unknown—optimal features to witness these signatures. Our results provide evidence on the efficacy and feasibility of the method, paving the way for its adoption in large-scale implementations.

Research on Signature Verification Method Based on Discrete Fréchet Distance

NASA Astrophysics Data System (ADS)

Fang, J. L.; Wu, W.

2018-05-01

This paper proposes a multi-feature signature template based on discrete Fréchet distance, which breaks through the limitation of traditional signature authentication using a single signature feature. It solves the online handwritten signature authentication signature global feature template extraction calculation workload, signature feature selection unreasonable problem. In this experiment, the false recognition rate (FAR) and false rejection rate (FRR) of the statistical signature are calculated and the average equal error rate (AEER) is calculated. The feasibility of the combined template scheme is verified by comparing the average equal error rate of the combination template and the original template.

Testing for intracycle determinism in pseudoperiodic time series.

PubMed

Coelho, Mara C S; Mendes, Eduardo M A M; Aguirre, Luis A

2008-06-01

A determinism test is proposed based on the well-known method of the surrogate data. Assuming predictability to be a signature of determinism, the proposed method checks for intracycle (e.g., short-term) determinism in the pseudoperiodic time series for which standard methods of surrogate analysis do not apply. The approach presented is composed of two steps. First, the data are preprocessed to reduce the effects of seasonal and trend components. Second, standard tests of surrogate analysis can then be used. The determinism test is applied to simulated and experimental pseudoperiodic time series and the results show the applicability of the proposed test.

Copy number variation signature to predict human ancestry

PubMed Central

2012-01-01

Background Copy number variations (CNVs) are genomic structural variants that are found in healthy populations and have been observed to be associated with disease susceptibility. Existing methods for CNV detection are often performed on a sample-by-sample basis, which is not ideal for large datasets where common CNVs must be estimated by comparing the frequency of CNVs in the individual samples. Here we describe a simple and novel approach to locate genome-wide CNVs common to a specific population, using human ancestry as the phenotype. Results We utilized our previously published Genome Alteration Detection Analysis (GADA) algorithm to identify common ancestry CNVs (caCNVs) and built a caCNV model to predict population structure. We identified a 73 caCNV signature using a training set of 225 healthy individuals from European, Asian, and African ancestry. The signature was validated on an independent test set of 300 individuals with similar ancestral background. The error rate in predicting ancestry in this test set was 2% using the 73 caCNV signature. Among the caCNVs identified, several were previously confirmed experimentally to vary by ancestry. Our signature also contains a caCNV region with a single microRNA (MIR270), which represents the first reported variation of microRNA by ancestry. Conclusions We developed a new methodology to identify common CNVs and demonstrated its performance by building a caCNV signature to predict human ancestry with high accuracy. The utility of our approach could be extended to large case–control studies to identify CNV signatures for other phenotypes such as disease susceptibility and drug response. PMID:23270563

Method and system for evaluating integrity of adherence of a conductor bond to a mating surface of a substrate

DOEpatents

Telschow, K.L.; Siu, B.K.

1996-07-09

A method of evaluating integrity of adherence of a conductor bond to a substrate includes: (a) impinging a plurality of light sources onto a substrate; (b) detecting optical reflective signatures emanating from the substrate from the impinged light; (c) determining location of a selected conductor bond on the substrate from the detected reflective signatures; (d) determining a target site on the selected conductor bond from the detected reflective signatures; (e) optically imparting an elastic wave at the target site through the selected conductor bond and into the substrate; (f) optically detecting an elastic wave signature emanating from the substrate resulting from the optically imparting step; and (g) determining integrity of adherence of the selected conductor bond to the substrate from the detected elastic wave signature emanating from the substrate. A system is disclosed which is capable of conducting the method. 13 figs.

Method and system for evaluating integrity of adherence of a conductor bond to a mating surface of a substrate

DOEpatents

Telschow, Kenneth L.; Siu, Bernard K.

1996-01-01

A method of evaluating integrity of adherence of a conductor bond to a substrate includes: a) impinging a plurality of light sources onto a substrate; b) detecting optical reflective signatures emanating from the substrate from the impinged light; c) determining location of a selected conductor bond on the substrate from the detected reflective signatures; d) determining a target site on the selected conductor bond from the detected reflective signatures; e) optically imparting an elastic wave at the target site through the selected conductor bond and into the substrate; f) optically detecting an elastic wave signature emanating from the substrate resulting from the optically imparting step; and g) determining integrity of adherence of the selected conductor bond to the substrate from the detected elastic wave signature emanating from the substrate. A system is disclosed which is capable of conducting the method.

FIR signature verification system characterizing dynamics of handwriting features

NASA Astrophysics Data System (ADS)

Thumwarin, Pitak; Pernwong, Jitawat; Matsuura, Takenobu

2013-12-01

This paper proposes an online signature verification method based on the finite impulse response (FIR) system characterizing time-frequency characteristics of dynamic handwriting features. First, the barycenter determined from both the center point of signature and two adjacent pen-point positions in the signing process, instead of one pen-point position, is used to reduce the fluctuation of handwriting motion. In this paper, among the available dynamic handwriting features, motion pressure and area pressure are employed to investigate handwriting behavior. Thus, the stable dynamic handwriting features can be described by the relation of the time-frequency characteristics of the dynamic handwriting features. In this study, the aforesaid relation can be represented by the FIR system with the wavelet coefficients of the dynamic handwriting features as both input and output of the system. The impulse response of the FIR system is used as the individual feature for a particular signature. In short, the signature can be verified by evaluating the difference between the impulse responses of the FIR systems for a reference signature and the signature to be verified. The signature verification experiments in this paper were conducted using the SUBCORPUS MCYT-100 signature database consisting of 5,000 signatures from 100 signers. The proposed method yielded equal error rate (EER) of 3.21% on skilled forgeries.

MicroRNA meta-signature of oral cancer: evidence from a meta-analysis.

PubMed

Zeljic, Katarina; Jovanovic, Ivan; Jovanovic, Jasmina; Magic, Zvonko; Stankovic, Aleksandra; Supic, Gordana

2018-03-01

It was the aim of the study to identify commonly deregulated miRNAs in oral cancer patients by performing a meta-analysis of previously published miRNA expression profiles in cancer and matched normal non-cancerous tissue in such patients. Meta-analysis included seven independent studies analyzed by a vote-counting method followed by bioinformatic enrichment analysis. Amongst seven independent studies included in the meta-analysis, 20 miRNAs were found to be deregulated in oral cancer when compared with non-cancerous tissue. Eleven miRNAs were consistently up-regulated in three or more studies (miR-21-5p, miR-31-5p, miR-135b-5p, miR-31-3p, miR-93-5p, miR-34b-5p, miR-424-5p, miR-18a-5p, miR-455-3p, miR-450a-5p, miR-21-3p), and nine were down-regulated (miR-139-5p, miR-30a-3p, miR-376c-3p, miR-885-5p, miR-375, miR-486-5p, miR-411-5p, miR-133a-3p, miR-30a-5p). The meta-signature of identified miRNAs was functionally characterized by KEGG enrichment analysis. Twenty-four KEGG pathways were significantly enriched, and TGF-beta signaling was the most enriched signaling pathway. The highest number of meta-signature miRNAs was involved in the sphingolipid signaling pathway. Natural killer cell-mediated cytotoxicity was the pathway with most genes regulated by identified miRNAs. The rest of the enriched pathways in our miRNA list describe different malignancies and signaling. The identified miRNA meta-signature might be considered as a potential battery of biomarkers when distinguishing oral cancer tissue from normal, non-cancerous tissue. Further mechanistic studies are warranted in order to confirm and fully elucidate the role of deregulated miRNAs in oral cancer.

Fungicide residue identification and discrimination using a conducting polymer electronic-nose

Treesearch

Alphus D. Wilson

2013-01-01

The identification of fungicide residues on crop foliage is necessary to make periodic pest management decisions. The determination of fungicide residue identities currently is difficult and time consuming using conventional chemical analysis methods such as gas chromatography-mass spectroscopy. Different fungicide types produce unique electronic aroma signature...

Beef grading by ultrasound

NASA Technical Reports Server (NTRS)

Gammell, P. M.

1981-01-01

Reflections in ultrasonic A-scan signatures of beef carcasses indicate USDA grade. Since reflections from within muscle are determined primarily by fat/muscle interface, richness of signals is direct indication of degree of marbling and quality. Method replaces subjective sight and feel tests by individual graders and is applicable to grade analysis of live cattle.

Nearfield Summary and Statistical Analysis of the Second AIAA Sonic Boom Prediction Workshop

NASA Technical Reports Server (NTRS)

Park, Michael A.; Nemec, Marian

2017-01-01

A summary is provided for the Second AIAA Sonic Boom Workshop held 8-9 January 2017 in conjunction with AIAA SciTech 2017. The workshop used three required models of increasing complexity: an axisymmetric body, a wing body, and a complete configuration with flow-through nacelle. An optional complete configuration with propulsion boundary conditions is also provided. These models are designed with similar nearfield signatures to isolate geometry and shock/expansion interaction effects. Eleven international participant groups submitted nearfield signatures with forces, pitching moment, and iterative convergence norms. Statistics and grid convergence of these nearfield signatures are presented. These submissions are propagated to the ground, and noise levels are computed. This allows the grid convergence and the statistical distribution of a noise level to be computed. While progress is documented since the first workshop, improvement to the analysis methods for a possible subsequent workshop are provided. The complete configuration with flow-through nacelle showed the most dramatic improvement between the two workshops. The current workshop cases are more relevant to vehicles with lower loudness and have the potential for lower annoyance than the first workshop cases. The models for this workshop with quieter ground noise levels than the first workshop exposed weaknesses in analysis, particularly in convective discretization.

Built-in-test by signature inspection (bitsi)

DOEpatents

Bergeson, Gary C.; Morneau, Richard A.

1991-01-01

A system and method for fault detection for electronic circuits. A stimulus generator sends a signal to the input of the circuit under test. Signature inspection logic compares the resultant signal from test nodes on the circuit to an expected signal. If the signals do not match, the signature inspection logic sends a signal to the control logic for indication of fault detection in the circuit. A data input multiplexer between the test nodes of the circuit under test and the signature inspection logic can provide for identification of the specific node at fault by the signature inspection logic. Control logic responsive to the signature inspection logic conveys information about fault detection for use in determining the condition of the circuit. When used in conjunction with a system test controller, the built-in test by signature inspection system and method can be used to poll a plurality of circuits automatically and continuous for faults and record the results of such polling in the system test controller.

L1000CDS2: LINCS L1000 characteristic direction signatures search engine.

PubMed

Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma'ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS 2 . The L1000CDS 2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS 2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS 2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS 2 , we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS 2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS 2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource.

Loop-Mediated Isothermal Amplification (LAMP) Signature Identification Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Torres, C.

2009-03-17

This is an extendable open-source Loop-mediated isothermal AMPlification (LAMP) signature design program called LAVA (LAMP Assay Versatile Analysis). LAVA was created in response to limitations of existing LAMP signature programs.

Algorithms for Hyperspectral Endmember Extraction and Signature Classification with Morphological Dendritic Networks

NASA Astrophysics Data System (ADS)

Schmalz, M.; Ritter, G.

Accurate multispectral or hyperspectral signature classification is key to the nonimaging detection and recognition of space objects. Additionally, signature classification accuracy depends on accurate spectral endmember determination [1]. Previous approaches to endmember computation and signature classification were based on linear operators or neural networks (NNs) expressed in terms of the algebra (R, +, x) [1,2]. Unfortunately, class separation in these methods tends to be suboptimal, and the number of signatures that can be accurately classified often depends linearly on the number of NN inputs. This can lead to poor endmember distinction, as well as potentially significant classification errors in the presence of noise or densely interleaved signatures. In contrast to traditional CNNs, autoassociative morphological memories (AMM) are a construct similar to Hopfield autoassociatived memories defined on the (R, +, ?,?) lattice algebra [3]. Unlimited storage and perfect recall of noiseless real valued patterns has been proven for AMMs [4]. However, AMMs suffer from sensitivity to specific noise models, that can be characterized as erosive and dilative noise. On the other hand, the prior definition of a set of endmembers corresponds to material spectra lying on vertices of the minimum convex region covering the image data. These vertices can be characterized as morphologically independent patterns. It has further been shown that AMMs can be based on dendritic computation [3,6]. These techniques yield improved accuracy and class segmentation/separation ability in the presence of highly interleaved signature data. In this paper, we present a procedure for endmember determination based on AMM noise sensitivity, which employs morphological dendritic computation. We show that detected endmembers can be exploited by AMM based classification techniques, to achieve accurate signature classification in the presence of noise, closely spaced or interleaved signatures, and simulated camera optical distortions. In particular, we examine two critical cases: (1) classification of multiple closely spaced signatures that are difficult to separate using distance measures, and (2) classification of materials in simulated hyperspectral images of spaceborne satellites. In each case, test data are derived from a NASA database of space material signatures. Additional analysis pertains to computational complexity and noise sensitivity, which are superior to classical NN based techniques.

Automated analysis in generic groups

NASA Astrophysics Data System (ADS)

Fagerholm, Edvard

This thesis studies automated methods for analyzing hardness assumptions in generic group models, following ideas of symbolic cryptography. We define a broad class of generic and symbolic group models for different settings---symmetric or asymmetric (leveled) k-linear groups --- and prove ''computational soundness'' theorems for the symbolic models. Based on this result, we formulate a master theorem that relates the hardness of an assumption to solving problems in polynomial algebra. We systematically analyze these problems identifying different classes of assumptions and obtain decidability and undecidability results. Then, we develop automated procedures for verifying the conditions of our master theorems, and thus the validity of hardness assumptions in generic group models. The concrete outcome is an automated tool, the Generic Group Analyzer, which takes as input the statement of an assumption, and outputs either a proof of its generic hardness or shows an algebraic attack against the assumption. Structure-preserving signatures are signature schemes defined over bilinear groups in which messages, public keys and signatures are group elements, and the verification algorithm consists of evaluating ''pairing-product equations''. Recent work on structure-preserving signatures studies optimality of these schemes in terms of the number of group elements needed in the verification key and the signature, and the number of pairing-product equations in the verification algorithm. While the size of keys and signatures is crucial for many applications, another aspect of performance is the time it takes to verify a signature. The most expensive operation during verification is the computation of pairings. However, the concrete number of pairings is not captured by the number of pairing-product equations considered in earlier work. We consider the question of what is the minimal number of pairing computations needed to verify structure-preserving signatures. We build an automated tool to search for structure-preserving signatures matching a template. Through exhaustive search we conjecture lower bounds for the number of pairings required in the Type~II setting and prove our conjecture to be true. Finally, our tool exhibits examples of structure-preserving signatures matching the lower bounds, which proves tightness of our bounds, as well as improves on previously known structure-preserving signature schemes.

Phenotypic Signatures Arising from Unbalanced Bacterial Growth

PubMed Central

Tan, Cheemeng; Smith, Robert Phillip; Tsai, Ming-Chi; Schwartz, Russell; You, Lingchong

2014-01-01

Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth condition. Here, we present a method to identify “phenotypic signatures” by time-frequency analysis of unbalanced growth curves measured with high temporal resolution. The signatures are then applied to differentiate amongst different bacterial strains or the same strain under different growth conditions, and to identify the essential architecture of the gene network underlying the observed growth dynamics. Our method has implications for both basic understanding of bacterial physiology and for the classification of bacterial strains. PMID:25101949

Advances in biological dosimetry

NASA Astrophysics Data System (ADS)

Ivashkevich, A.; Ohnesorg, T.; Sparbier, C. E.; Elsaleh, H.

2017-01-01

Rapid retrospective biodosimetry methods are essential for the fast triage of persons occupationally or accidentally exposed to ionizing radiation. Identification and detection of a radiation specific molecular ‘footprint’ should provide a sensitive and reliable measurement of radiation exposure. Here we discuss conventional (cytogenetic) methods of detection and assessment of radiation exposure in comparison to emerging approaches such as gene expression signatures and DNA damage markers. Furthermore, we provide an overview of technical and logistic details such as type of sample required, time for sample preparation and analysis, ease of use and potential for a high throughput analysis.

Unconditionally Secure Blind Signatures

NASA Astrophysics Data System (ADS)

Hara, Yuki; Seito, Takenobu; Shikata, Junji; Matsumoto, Tsutomu

The blind signature scheme introduced by Chaum allows a user to obtain a valid signature for a message from a signer such that the message is kept secret for the signer. Blind signature schemes have mainly been studied from a viewpoint of computational security so far. In this paper, we study blind signatures in unconditional setting. Specifically, we newly introduce a model of unconditionally secure blind signature schemes (USBS, for short). Also, we propose security notions and their formalization in our model. Finally, we propose a construction method for USBS that is provably secure in our security notions.

GeneSigDB: a manually curated database and resource for analysis of gene expression signatures

PubMed Central

Culhane, Aedín C.; Schröder, Markus S.; Sultana, Razvan; Picard, Shaita C.; Martinelli, Enzo N.; Kelly, Caroline; Haibe-Kains, Benjamin; Kapushesky, Misha; St Pierre, Anne-Alyssa; Flahive, William; Picard, Kermshlise C.; Gusenleitner, Daniel; Papenhausen, Gerald; O'Connor, Niall; Correll, Mick; Quackenbush, John

2012-01-01

GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a database of gene signatures that have been extracted and manually curated from the published literature. It provides a standardized resource of published prognostic, diagnostic and other gene signatures of cancer and related disease to the community so they can compare the predictive power of gene signatures or use these in gene set enrichment analysis. Since GeneSigDB release 1.0, we have expanded from 575 to 3515 gene signatures, which were collected and transcribed from 1604 published articles largely focused on gene expression in cancer, stem cells, immune cells, development and lung disease. We have made substantial upgrades to the GeneSigDB website to improve accessibility and usability, including adding a tag cloud browse function, facetted navigation and a ‘basket’ feature to store genes or gene signatures of interest. Users can analyze GeneSigDB gene signatures, or upload their own gene list, to identify gene signatures with significant gene overlap and results can be viewed on a dynamic editable heatmap that can be downloaded as a publication quality image. All data in GeneSigDB can be downloaded in numerous formats including .gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb.org. PMID:22110038

Apparatuses and methods of determining if a person operating equipment is experiencing an elevated cognitive load

DOEpatents

Watkins, Michael L.; Keller, Paul Edwin; Amaya, Ivan A.

2015-06-16

A method of, and apparatus for, determining if a person operating equipment is experiencing an elevated cognitive load, wherein the person's use of a device at a first time is monitored so as to set a baseline signature. Then, at a later time, the person's use of the device is monitored to determine the person's performance at the second time, as represented by a performance signature. This performance signature can then be compared against the baseline signature to predict whether the person is experiencing an elevated cognitive load.

Chemical Signatures of and Precursors to Fractures Using Fluid Inclusion Stratigraphy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lorie M. Dilley

Enhanced Geothermal Systems (EGS) are designed to recover heat from the subsurface by mechanically creating fractures in subsurface rocks. Open or recently closed fractures would be more susceptible to enhancing the permeability of the system. Identifying dense fracture areas as well as large open fractures from small fracture systems will assist in fracture stimulation site selection. Geothermal systems are constantly generating fractures (Moore, Morrow et al. 1987), and fluids and gases passing through rocks in these systems leave small fluid and gas samples trapped in healed microfractures. These fluid inclusions are faithful records of pore fluid chemistry. Fluid inclusions trappedmore » in minerals as the fractures heal are characteristic of the fluids that formed them, and this signature can be seen in fluid inclusion gas analysis. This report presents the results of the project to determine fracture locations by the chemical signatures from gas analysis of fluid inclusions. With this project we hope to test our assumptions that gas chemistry can distinguish if the fractures are open and bearing production fluids or represent prior active fractures and whether there are chemical signs of open fracture systems in the wall rock above the fracture. Fluid Inclusion Stratigraphy (FIS) is a method developed for the geothermal industry which applies the mass quantification of fluid inclusion gas data from drill cuttings and applying known gas ratios and compositions to determine depth profiles of fluid barriers in a modern geothermal system (Dilley, 2009; Dilley et al., 2005; Norman et al., 2005). Identifying key gas signatures associated with fractures for isolating geothermal fluid production is the latest advancement in the application of FIS to geothermal systems (Dilley and Norman, 2005; Dilley and Norman, 2007). Our hypothesis is that peaks in FIS data are related to location of fractures. Previous work (DOE Grant DE-FG36-06GO16057) has indicated differences in the chemical signature of fluid inclusions between open and closed fractures as well as differences in the chemical signature of open fractures between geothermal systems. Our hypothesis is that open fracture systems can be identified by their FIS chemical signature; that there are differences based on the mineral assemblages and geology of the system; and that there are chemical precursors in the wall rock above open, large fractures. Specific goals for this project are: (1) To build on the preliminary results which indicate that there are differences in the FIS signatures between open and closed fractures by identifying which chemical species indicate open fractures in both active geothermal systems and in hot, dry rock; (2) To evaluate the FIS signatures based on the geology of the fields; (3) To evaluate the FIS signatures based on the mineral assemblages in the fracture; and (4) To determine if there are specific chemical signatures in the wall rock above open, large fractures. This method promises to lower the cost of geothermal energy production in several ways. Knowledge of productive fractures in the boreholes will allow engineers to optimize well production. This information can aid in well testing decisions, well completion strategies, and in resource calculations. It will assist in determining the areas for future fracture enhancement. This will develop into one of the techniques in the 'tool bag' for creating and managing Enhanced Geothermal Systems.« less

Offline signature verification using convolution Siamese network

NASA Astrophysics Data System (ADS)

Xing, Zi-Jian; Yin, Fei; Wu, Yi-Chao; Liu, Cheng-Lin

2018-04-01

This paper presents an offline signature verification approach using convolutional Siamese neural network. Unlike the existing methods which consider feature extraction and metric learning as two independent stages, we adopt a deepleaning based framework which combines the two stages together and can be trained end-to-end. The experimental results on two offline public databases (GPDSsynthetic and CEDAR) demonstrate the superiority of our method on the offline signature verification problem.

A comparison of robust principal component analysis techniques for buried object detection in downward looking GPR sensor data

NASA Astrophysics Data System (ADS)

Pinar, Anthony; Havens, Timothy C.; Rice, Joseph; Masarik, Matthew; Burns, Joseph; Thelen, Brian

2016-05-01

Explosive hazards are a deadly threat in modern conflicts; hence, detecting them before they cause injury or death is of paramount importance. One method of buried explosive hazard discovery relies on data collected from ground penetrating radar (GPR) sensors. Threat detection with downward looking GPR is challenging due to large returns from non-target objects and clutter. This leads to a large number of false alarms (FAs), and since the responses of clutter and targets can form very similar signatures, classifier design is not trivial. One approach to combat these issues uses robust principal component analysis (RPCA) to enhance target signatures while suppressing clutter and background responses, though there are many versions of RPCA. This work applies some of these RPCA techniques to GPR sensor data and evaluates their merit using the peak signal-to-clutter ratio (SCR) of the RPCA-processed B-scans. Experimental results on government furnished data show that while some of the RPCA methods yield similar results, there are indeed some methods that outperform others. Furthermore, we show that the computation time required by the different RPCA methods varies widely, and the selection of tuning parameters in the RPCA algorithms has a major effect on the peak SCR.

Output-Adaptive Tetrahedral Cut-Cell Validation for Sonic Boom Prediction

NASA Technical Reports Server (NTRS)

Park, Michael A.; Darmofal, David L.

2008-01-01

A cut-cell approach to Computational Fluid Dynamics (CFD) that utilizes the median dual of a tetrahedral background grid is described. The discrete adjoint is also calculated, which permits adaptation based on improving the calculation of a specified output (off-body pressure signature) in supersonic inviscid flow. These predicted signatures are compared to wind tunnel measurements on and off the configuration centerline 10 body lengths below the model to validate the method for sonic boom prediction. Accurate mid-field sonic boom pressure signatures are calculated with the Euler equations without the use of hybrid grid or signature propagation methods. Highly-refined, shock-aligned anisotropic grids were produced by this method from coarse isotropic grids created without prior knowledge of shock locations. A heuristic reconstruction limiter provided stable flow and adjoint solution schemes while producing similar signatures to Barth-Jespersen and Venkatakrishnan limiters. The use of cut-cells with an output-based adaptive scheme completely automated this accurate prediction capability after a triangular mesh is generated for the cut surface. This automation drastically reduces the manual intervention required by existing methods.

Determination of Extrapolation Distance with Measured Pressure Signatures from Two Low-Boom Models

NASA Technical Reports Server (NTRS)

Mack, Robert J.; Kuhn, Neil

2004-01-01

A study to determine a limiting distance to span ratio for the extrapolation of near-field pressure signatures is described and discussed. This study was to be done in two wind-tunnel facilities with two wind-tunnel models. At this time, only the first half had been completed, so the scope of this report is limited to the design of the models, and to an analysis of the first set of measured pressure signatures. The results from this analysis showed that the pressure signatures measured at separation distances of 2 to 5 span lengths did not show the desired low-boom shapes. However, there were indications that the pressure signature shapes were becoming 'flat-topped'. This trend toward a 'flat-top' pressure signatures shape was seen to be a gradual one at the distance ratios employed in this first series of wind-tunnel tests.

Evaluation of 4 years of continuous δ13C(CO2) data using a moving Keeling plot method

NASA Astrophysics Data System (ADS)

Vardag, Sanam Noreen; Hammer, Samuel; Levin, Ingeborg

2016-07-01

Different carbon dioxide (CO2) emitters can be distinguished by their carbon isotope ratios. Therefore measurements of atmospheric δ13C(CO2) and CO2 concentration contain information on the CO2 source mix in the catchment area of an atmospheric measurement site. This information may be illustratively presented as the mean isotopic source signature. Recently an increasing number of continuous measurements of δ13C(CO2) and CO2 have become available, opening the door to the quantification of CO2 shares from different sources at high temporal resolution. Here, we present a method to compute the CO2 source signature (δS) continuously and evaluate our result using model data from the Stochastic Time-Inverted Lagrangian Transport model. Only when we restrict the analysis to situations which fulfill the basic assumptions of the Keeling plot method does our approach provide correct results with minimal biases in δS. On average, this bias is 0.2 ‰ with an interquartile range of about 1.2 ‰ for hourly model data. As a consequence of applying the required strict filter criteria, 85 % of the data points - mainly daytime values - need to be discarded. Applying the method to a 4-year dataset of CO2 and δ13C(CO2) measured in Heidelberg, Germany, yields a distinct seasonal cycle of δS. Disentangling this seasonal source signature into shares of source components is, however, only possible if the isotopic end members of these sources - i.e., the biosphere, δbio, and the fuel mix, δF - are known. From the mean source signature record in 2012, δbio could be reliably estimated only for summer to (-25.0 ± 1.0) ‰ and δF only for winter to (-32.5 ± 2.5) ‰. As the isotopic end members δbio and δF were shown to change over the season, no year-round estimation of the fossil fuel or biosphere share is possible from the measured mean source signature record without additional information from emission inventories or other tracer measurements.

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

PubMed Central

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh; Webb-Robertson, Bobbie-Jo; Hafen, Ryan; Ramey, John; Rodland, Karin D.

2012-01-01

Introduction The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers. PMID:23335946

Cross-study projections of genomic biomarkers: an evaluation in cancer genomics.

PubMed

Lucas, Joseph E; Carvalho, Carlos M; Chen, Julia Ling-Yu; Chi, Jen-Tsan; West, Mike

2009-01-01

Human disease studies using DNA microarrays in both clinical/observational and experimental/controlled studies are having increasing impact on our understanding of the complexity of human diseases. A fundamental concept is the use of gene expression as a "common currency" that links the results of in vitro controlled experiments to in vivo observational human studies. Many studies--in cancer and other diseases--have shown promise in using in vitro cell manipulations to improve understanding of in vivo biology, but experiments often simply fail to reflect the enormous phenotypic variation seen in human diseases. We address this with a framework and methods to dissect, enhance and extend the in vivo utility of in vitro derived gene expression signatures. From an experimentally defined gene expression signature we use statistical factor analysis to generate multiple quantitative factors in human cancer gene expression data. These factors retain their relationship to the original, one-dimensional in vitro signature but better describe the diversity of in vivo biology. In a breast cancer analysis, we show that factors can reflect fundamentally different biological processes linked to molecular and clinical features of human cancers, and that in combination they can improve prediction of clinical outcomes.

ArrayVigil: a methodology for statistical comparison of gene signatures using segregated-one-tailed (SOT) Wilcoxon's signed-rank test.

PubMed

Khan, Haseeb Ahmad

2005-01-28

Due to versatile diagnostic and prognostic fidelity molecular signatures or fingerprints are anticipated as the most powerful tools for cancer management in the near future. Notwithstanding the experimental advancements in microarray technology, methods for analyzing either whole arrays or gene signatures have not been firmly established. Recently, an algorithm, ArraySolver has been reported by Khan for two-group comparison of microarray gene expression data using two-tailed Wilcoxon signed-rank test. Most of the molecular signatures are composed of two sets of genes (hybrid signatures) wherein up-regulation of one set and down-regulation of the other set collectively define the purpose of a gene signature. Since the direction of a selected gene's expression (positive or negative) with respect to a particular disease condition is known, application of one-tailed statistics could be a more relevant choice. A novel method, ArrayVigil, is described for comparing hybrid signatures using segregated-one-tailed (SOT) Wilcoxon signed-rank test and the results compared with integrated-two-tailed (ITT) procedures (SPSS and ArraySolver). ArrayVigil resulted in lower P values than those obtained from ITT statistics while comparing real data from four signatures.

Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

PubMed

Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

2018-04-23

Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis and benefit the therapy improvement.

Meta-analysis of gene expression patterns in animal models of prenatal alcohol exposure suggests role for protein synthesis inhibition and chromatin remodeling

PubMed Central

Rogic, Sanja; Wong, Albertina; Pavlidis, Paul

2017-01-01

Background Prenatal alcohol exposure (PAE) can result in an array of morphological, behavioural and neurobiological deficits that can range in their severity. Despite extensive research in the field and a significant progress made, especially in understanding the range of possible malformations and neurobehavioral abnormalities, the molecular mechanisms of alcohol responses in development are still not well understood. There have been multiple transcriptomic studies looking at the changes in gene expression after PAE in animal models, however there is a limited apparent consensus among the reported findings. In an effort to address this issue, we performed a comprehensive re-analysis and meta-analysis of all suitable, publically available expression data sets. Methods We assembled ten microarray data sets of gene expression after PAE in mouse and rat models consisting of samples from a total of 63 ethanol-exposed and 80 control animals. We re-analyzed each data set for differential expression and then used the results to perform meta-analyses considering all data sets together or grouping them by time or duration of exposure (pre- and post-natal, acute and chronic, respectively). We performed network and Gene Ontology enrichment analysis to further characterize the identified signatures. Results For each sub-analysis we identified signatures of differential expressed genes that show support from multiple studies. Overall, the changes in gene expression were more extensive after acute ethanol treatment during prenatal development than in other models. Considering the analysis of all the data together, we identified a robust core signature of 104 genes down-regulated after PAE, with no up-regulated genes. Functional analysis reveals over-representation of genes involved in protein synthesis, mRNA splicing and chromatin organization. Conclusions Our meta-analysis shows that existing studies, despite superficial dissimilarity in findings, share features that allow us to identify a common core signature set of transcriptome changes in PAE. This is an important step to identifying the biological processes that underlie the etiology of FASD. PMID:26996386

System and method of detecting cavitation in pumps

DOEpatents

Lu, Bin; Sharma, Santosh Kumar; Yan, Ting; Dimino, Steven A.

2017-10-03

A system and method for detecting cavitation in pumps for fixed and variable supply frequency applications is disclosed. The system includes a controller having a processor programmed to repeatedly receive real-time operating current data from a motor driving a pump, generate a current frequency spectrum from the current data, and analyze current data within a pair of signature frequency bands of the current frequency spectrum. The processor is further programmed to repeatedly determine fault signatures as a function of the current data within the pair of signature frequency bands, repeatedly determine fault indices based on the fault signatures and a dynamic reference signature, compare the fault indices to a reference index, and identify a cavitation condition in a pump based on a comparison between the reference index and a current fault index.

Application of the ToxMiner Database: Network Analysis Linking the ToxCast Chemicals to Known Disease-Gene Associations

EPA Science Inventory

The US EPA ToxCast program is using in vitro HTS (High-Throughput Screening) methods to profile and model bioactivity of environmental chemicals. The main goals of the ToxCast program are to generate predictive signatures of toxicity, and ultimately provide rapid and cost-effecti...

Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis

PubMed Central

Kim, David M.; Zhang, Hairong; Zhou, Haiying; Du, Tommy; Wu, Qian; Mockler, Todd C.; Berezin, Mikhail Y.

2015-01-01

The optical signature of leaves is an important monitoring and predictive parameter for a variety of biotic and abiotic stresses, including drought. Such signatures derived from spectroscopic measurements provide vegetation indices – a quantitative method for assessing plant health. However, the commonly used metrics suffer from low sensitivity. Relatively small changes in water content in moderately stressed plants demand high-contrast imaging to distinguish affected plants. We present a new approach in deriving sensitive indices using hyperspectral imaging in a short-wave infrared range from 800 nm to 1600 nm. Our method, based on high spectral resolution (1.56 nm) instrumentation and image processing algorithms (quantitative histogram analysis), enables us to distinguish a moderate water stress equivalent of 20% relative water content (RWC). The identified image-derived indices 15XX nm/14XX nm (i.e. 1529 nm/1416 nm) were superior to common vegetation indices, such as WBI, MSI, and NDWI, with significantly better sensitivity, enabling early diagnostics of plant health. PMID:26531782

Learning semantic and visual similarity for endomicroscopy video retrieval.

PubMed

Andre, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

2012-06-01

Content-based image retrieval (CBIR) is a valuable computer vision technique which is increasingly being applied in the medical community for diagnosis support. However, traditional CBIR systems only deliver visual outputs, i.e., images having a similar appearance to the query, which is not directly interpretable by the physicians. Our objective is to provide a system for endomicroscopy video retrieval which delivers both visual and semantic outputs that are consistent with each other. In a previous study, we developed an adapted bag-of-visual-words method for endomicroscopy retrieval, called "Dense-Sift," that computes a visual signature for each video. In this paper, we present a novel approach to complement visual similarity learning with semantic knowledge extraction, in the field of in vivo endomicroscopy. We first leverage a semantic ground truth based on eight binary concepts, in order to transform these visual signatures into semantic signatures that reflect how much the presence of each semantic concept is expressed by the visual words describing the videos. Using cross-validation, we demonstrate that, in terms of semantic detection, our intuitive Fisher-based method transforming visual-word histograms into semantic estimations outperforms support vector machine (SVM) methods with statistical significance. In a second step, we propose to improve retrieval relevance by learning an adjusted similarity distance from a perceived similarity ground truth. As a result, our distance learning method allows to statistically improve the correlation with the perceived similarity. We also demonstrate that, in terms of perceived similarity, the recall performance of the semantic signatures is close to that of visual signatures and significantly better than those of several state-of-the-art CBIR methods. The semantic signatures are thus able to communicate high-level medical knowledge while being consistent with the low-level visual signatures and much shorter than them. In our resulting retrieval system, we decide to use visual signatures for perceived similarity learning and retrieval, and semantic signatures for the output of an additional information, expressed in the endoscopist own language, which provides a relevant semantic translation of the visual retrieval outputs.

Authentication Based on Pole-zero Models of Signature Velocity

PubMed Central

Rashidi, Saeid; Fallah, Ali; Towhidkhah, Farzad

2013-01-01

With the increase of communication and financial transaction through internet, on-line signature verification is an accepted biometric technology for access control and plays a significant role in authenticity and authorization in modernized society. Therefore, fast and precise algorithms for the signature verification are very attractive. The goal of this paper is modeling of velocity signal that pattern and properties is stable for persons. With using pole-zero models based on discrete cosine transform, precise method is proposed for modeling and then features is founded from strokes. With using linear, parzen window and support vector machine classifiers, the signature verification technique was tested with a large number of authentic and forgery signatures and has demonstrated the good potential of this technique. The signatures are collected from three different database include a proprietary database, the SVC2004 and the Sabanci University signature database benchmark databases. Experimental results based on Persian, SVC2004 and SUSIG databases show that our method achieves an equal error rate of 5.91%, 5.62% and 3.91% in the skilled forgeries, respectively. PMID:24696797

Determination of impurities in uranium matrices by time-of-flight ICP-MS using matrix-matched method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buerger, Stefan; Riciputi, Lee R; Bostick, Debra A

2007-01-01

The analysis of impurities in uranium matrices is performed in a variety of fields, e.g. for quality control in the production stream converting uranium ores to fuels, as element signatures in nuclear forensics and safeguards, and for non-proliferation control. We have investigated the capabilities of time-of-flight ICP-MS for the analysis of impurities in uranium matrices using a matrix-matched method. The method was applied to the New Brunswick Laboratory CRM 124(1-7) series. For the seven certified reference materials, an overall precision and accuracy of approximately 5% and 14%, respectively, were obtained for 18 analyzed elements.

A static acoustic signature system for the analysis of dynamic flight information

NASA Technical Reports Server (NTRS)

Ramer, D. J.

1978-01-01

The Army family of helicopters was analyzed to measure the polar octave band acoustic signature in various modes of flight. A static array of calibrated microphones was used to simultaneously acquire the signature and differential times required to mathematically position the aircraft in space. The signature was then reconstructed, mathematically normalized to a fixed radius around the aircraft.

Additional studies of forest classification accuracy as influenced by multispectral scanner spatial resolution

NASA Technical Reports Server (NTRS)

Sadowski, F. E.; Sarno, J. E.

1976-01-01

First, an analysis of forest feature signatures was used to help explain the large variation in classification accuracy that can occur among individual forest features for any one case of spatial resolution and the inconsistent changes in classification accuracy that were demonstrated among features as spatial resolution was degraded. Second, the classification rejection threshold was varied in an effort to reduce the large proportion of unclassified resolution elements that previously appeared in the processing of coarse resolution data when a constant rejection threshold was used for all cases of spatial resolution. For the signature analysis, two-channel ellipse plots showing the feature signature distributions for several cases of spatial resolution indicated that the capability of signatures to correctly identify their respective features is dependent on the amount of statistical overlap among signatures. Reductions in signature variance that occur in data of degraded spatial resolution may not necessarily decrease the amount of statistical overlap among signatures having large variance and small mean separations. Features classified by such signatures may thus continue to have similar amounts of misclassified elements in coarser resolution data, and thus, not necessarily improve in classification accuracy.

A feature based comparison of pen and swipe based signature characteristics.

PubMed

Robertson, Joshua; Guest, Richard

2015-10-01

Dynamic Signature Verification (DSV) is a biometric modality that identifies anatomical and behavioral characteristics when an individual signs their name. Conventionally signature data has been captured using pen/tablet apparatus. However, the use of other devices such as the touch-screen tablets has expanded in recent years affording the possibility of assessing biometric interaction on this new technology. To explore the potential of employing DSV techniques when a user signs or swipes with their finger, we report a study to correlate pen and finger generated features. Investigating the stability and correlation between a set of characteristic features recorded in participant's signatures and touch-based swipe gestures, a statistical analysis was conducted to assess consistency between capture scenarios. The results indicate that there is a range of static and dynamic features such as the rate of jerk, size, duration and the distance the pen traveled that can lead to interoperability between these two systems for input methods for use within a potential biometric context. It can be concluded that this data indicates that a general principle is that the same underlying constructional mechanisms are evident. Copyright © 2015 Elsevier B.V. All rights reserved.

Extraction of human gait signatures: an inverse kinematic approach using Groebner basis theory applied to gait cycle analysis

NASA Astrophysics Data System (ADS)

Barki, Anum; Kendricks, Kimberly; Tuttle, Ronald F.; Bunker, David J.; Borel, Christoph C.

2013-05-01

This research highlights the results obtained from applying the method of inverse kinematics, using Groebner basis theory, to the human gait cycle to extract and identify lower extremity gait signatures. The increased threat from suicide bombers and the force protection issues of today have motivated a team at Air Force Institute of Technology (AFIT) to research pattern recognition in the human gait cycle. The purpose of this research is to identify gait signatures of human subjects and distinguish between subjects carrying a load to those subjects without a load. These signatures were investigated via a model of the lower extremities based on motion capture observations, in particular, foot placement and the joint angles for subjects affected by carrying extra load on the body. The human gait cycle was captured and analyzed using a developed toolkit consisting of an inverse kinematic motion model of the lower extremity and a graphical user interface. Hip, knee, and ankle angles were analyzed to identify gait angle variance and range of motion. Female subjects exhibited the most knee angle variance and produced a proportional correlation between knee flexion and load carriage.

FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data.

PubMed

Manijak, Mieszko P; Nielsen, Henrik B

2011-06-11

Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially circumvented by instead matching gene expression signatures to signatures of other experiments. To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700 Arabidopsis microarray experiments. Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/.

Geographic patterns of networks derived from extreme precipitation over the Indian subcontinent

NASA Astrophysics Data System (ADS)

Stolbova, Veronika; Bookhagen, Bodo; Marwan, Norbert; Kurths, Juergen

2014-05-01

Complex networks (CN) and event synchronization (ES) methods have been applied to study a number of climate phenomena such as Indian Summer Monsoon (ISM), South-American Monsoon, and African Monsoon. These methods proved to be powerful tools to infer interdependencies in climate dynamics between geographical sites, spatial structures, and key regions of the considered climate phenomenon. Here, we use these methods to study the spatial temporal variability of the extreme rainfall over the Indian subcontinent, in order to filter the data by coarse-graining the network, and to identify geographic patterns that are signature features (spatial signatures) of the ISM. We find four main geographic patterns of networks derived from extreme precipitation over the Indian subcontinent using up-to-date satellite-derived, and high temporal and spatial resolution rain-gauge interpolated daily rainfall datasets. In order to prove that our results are also relevant for other climatic variables like pressure and temperature, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). We find that two of the patterns revealed from the CN extreme rainfall analysis coincide with those obtained for the pressure and temperature fields, and all four above mentioned patterns can be explained by topography, winds, and monsoon circulation. CN and ES enable to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to infer geographic pattern that are spatial signatures of the ISM. These patterns deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

Determination of lateral size distribution of type-II ZnTe/ZnSe stacked submonolayer quantum dots via spectral analysis of optical signature of the Aharanov-Bohm excitons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ji, Haojie; Dhomkar, Siddharth; Roy, Bidisha

2014-10-28

For submonolayer quantum dot (QD) based photonic devices, size and density of QDs are critical parameters, the probing of which requires indirect methods. We report the determination of lateral size distribution of type-II ZnTe/ZnSe stacked submonolayer QDs, based on spectral analysis of the optical signature of Aharanov-Bohm (AB) excitons, complemented by photoluminescence studies, secondary-ion mass spectroscopy, and numerical calculations. Numerical calculations are employed to determine the AB transition magnetic field as a function of the type-II QD radius. The study of four samples grown with different tellurium fluxes shows that the lateral size of QDs increases by just 50%, evenmore » though tellurium concentration increases 25-fold. Detailed spectral analysis of the emission of the AB exciton shows that the QD radii take on only certain values due to vertical correlation and the stacked nature of the QDs.« less

L1000CDS2: LINCS L1000 characteristic direction signatures search engine

PubMed Central

Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma’ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS2. The L1000CDS2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS2, we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource. PMID:28413689

Statistical analysis of road-vehicle-driver interaction as an enabler to designing behavioural models

NASA Astrophysics Data System (ADS)

Chakravarty, T.; Chowdhury, A.; Ghose, A.; Bhaumik, C.; Balamuralidhar, P.

2014-03-01

Telematics form an important technology enabler for intelligent transportation systems. By deploying on-board diagnostic devices, the signatures of vehicle vibration along with its location and time are recorded. Detailed analyses of the collected signatures offer deep insights into the state of the objects under study. Towards that objective, we carried out experiments by deploying telematics device in one of the office bus that ferries employees to office and back. Data is being collected from 3-axis accelerometer, GPS, speed and the time for all the journeys. In this paper, we present initial results of the above exercise by applying statistical methods to derive information through systematic analysis of the data collected over four months. It is demonstrated that the higher order derivative of the measured Z axis acceleration samples display the properties Weibull distribution when the time axis is replaced by the amplitude of such processed acceleration data. Such an observation offers us a method to predict future behaviour where deviations from prediction are classified as context-based aberrations or progressive degradation of the system. In addition we capture the relationship between speed of the vehicle and median of the jerk energy samples using regression analysis. Such results offer an opportunity to develop a robust method to model road-vehicle interaction thereby enabling us to predict such like driving behaviour and condition based maintenance etc.

The Temporal Signature of Memories: Identification of a General Mechanism for Dynamic Memory Replay in Humans

PubMed Central

Michelmann, Sebastian; Bowman, Howard; Hanslmayr, Simon

2016-01-01

Reinstatement of dynamic memories requires the replay of neural patterns that unfold over time in a similar manner as during perception. However, little is known about the mechanisms that guide such a temporally structured replay in humans, because previous studies used either unsuitable methods or paradigms to address this question. Here, we overcome these limitations by developing a new analysis method to detect the replay of temporal patterns in a paradigm that requires participants to mentally replay short sound or video clips. We show that memory reinstatement is accompanied by a decrease of low-frequency (8 Hz) power, which carries a temporal phase signature of the replayed stimulus. These replay effects were evident in the visual as well as in the auditory domain and were localized to sensory-specific regions. These results suggest low-frequency phase to be a domain-general mechanism that orchestrates dynamic memory replay in humans. PMID:27494601

A new approach for SSVEP detection using PARAFAC and canonical correlation analysis.

PubMed

Tello, Richard; Pouryazdian, Saeed; Ferreira, Andre; Beheshti, Soosan; Krishnan, Sridhar; Bastos, Teodiano

2015-01-01

This paper presents a new way for automatic detection of SSVEPs through correlation analysis between tensor models. 3-way EEG tensor of channel × frequency × time is decomposed into constituting factor matrices using PARAFAC model. PARAFAC analysis of EEG tensor enables us to decompose multichannel EEG into constituting temporal, spectral and spatial signatures. SSVEPs characterized with localized spectral and spatial signatures are then detected exploiting a correlation analysis between extracted signatures of the EEG tensor and the corresponding simulated signatures of all target SSVEP signals. The SSVEP that has the highest correlation is selected as the intended target. Two flickers blinking at 8 and 13 Hz were used as visual stimuli and the detection was performed based on data packets of 1 second without overlapping. Five subjects participated in the experiments and the highest classification rate of 83.34% was achieved, leading to the Information Transfer Rate (ITR) of 21.01 bits/min.

Laser-induced breakdown spectroscopy for specimen analysis

DOEpatents

Kumar, Akshaya; Yu-Yueh, Fang; Burgess, Shane C.; Singh, Jagdish P.

2006-08-15

The present invention is directed to an apparatus, a system and a method for detecting the presence or absence of trace elements in a biological sample using Laser-Induced Breakdown Spectroscopy. The trace elements are used to develop a signature profile which is analyzed directly or compared with the known profile of a standard. In one aspect of the invention, the apparatus, system and method are used to detect malignant cancer cells in vivo.

Neuroelectrical Decomposition of Spontaneous Brain Activity Measured with Functional Magnetic Resonance Imaging

PubMed Central

Liu, Zhongming; de Zwart, Jacco A.; Chang, Catie; Duan, Qi; van Gelderen, Peter; Duyn, Jeff H.

2014-01-01

Spontaneous activity in the human brain occurs in complex spatiotemporal patterns that may reflect functionally specialized neural networks. Here, we propose a subspace analysis method to elucidate large-scale networks by the joint analysis of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data. The new approach is based on the notion that the neuroelectrical activity underlying the fMRI signal may have EEG spectral features that report on regional neuronal dynamics and interregional interactions. Applying this approach to resting healthy adults, we indeed found characteristic spectral signatures in the EEG correlates of spontaneous fMRI signals at individual brain regions as well as the temporal synchronization among widely distributed regions. These spectral signatures not only allowed us to parcel the brain into clusters that resembled the brain's established functional subdivision, but also offered important clues for disentangling the involvement of individual regions in fMRI network activity. PMID:23796947

Prediction of sonic boom from experimental near-field overpressure data. Volume 1: Method and results

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Hague, D. S.; Reiners, S. J.

1975-01-01

A computerized procedure for predicting sonic boom from experimental near-field overpressure data has been developed. The procedure extrapolates near-field pressure signatures for a specified flight condition to the ground by the Thomas method. Near-field pressure signatures are interpolated from a data base of experimental pressure signatures. The program is an independently operated ODIN (Optimal Design Integration) program which obtains flight path information from other ODIN programs or from input.

In Situ 3D Monitoring of Geometric Signatures in the Powder-Bed-Fusion Additive Manufacturing Process via Vision Sensing Methods.

PubMed

Li, Zhongwei; Liu, Xingjian; Wen, Shifeng; He, Piyao; Zhong, Kai; Wei, Qingsong; Shi, Yusheng; Liu, Sheng

2018-04-12

Lack of monitoring of the in situ process signatures is one of the challenges that has been restricting the improvement of Powder-Bed-Fusion Additive Manufacturing (PBF AM). Among various process signatures.

Experimental Measurements of Sonic Boom Signatures Using a Continuous Data Acquisition Technique

NASA Technical Reports Server (NTRS)

Wilcox, Floyd J.; Elmiligui, Alaa A.

2013-01-01

A wind tunnel investigation was conducted in the Langley Unitary Plan Wind Tunnel to determine the effectiveness of a technique to measure aircraft sonic boom signatures using a single conical survey probe while continuously moving the model past the probe. Sonic boom signatures were obtained using both move-pause and continuous data acquisition methods for comparison. The test was conducted using a generic business jet model at a constant angle of attack and a single model-to-survey-probe separation distance. The sonic boom signatures were obtained at a Mach number of 2.0 and a unit Reynolds number of 2 million per foot. The test results showed that it is possible to obtain sonic boom signatures while continuously moving the model and that the time required to acquire the signature is at least 10 times faster than the move-pause method. Data plots are presented with a discussion of the results. No tabulated data or flow visualization photographs are included.

Human relevance of an in vitro gene signature in HaCaT for skin sensitization.

PubMed

van der Veen, Jochem W; Hodemaekers, Henny; Reus, Astrid A; Maas, Wilfred J M; van Loveren, Henk; Ezendam, Janine

2015-02-01

The skin sensitizing potential of chemicals is mainly assessed using animal methods, such as the murine local lymph node assay. Recently, an in vitro assay based on a gene expression signature in the HaCaT keratinocyte cell line was proposed as an alternative to these animal methods. Here, the human relevance of this gene signature is assessed through exposure of freshly isolated human skin to the chemical allergens dinitrochlorobenzene (DNCB) and diphenylcyclopropenone (DCP). In human skin, the gene signature shows similar direction of regulation as was previously observed in vitro, suggesting that the molecular processes that drive expression of these genes are similar between the HaCaT cell line and freshly isolated skin, providing evidence for the human relevance of the gene signature. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning.

PubMed

Zhao, Jonathan Z L; Mucaki, Eliseos J; Rogan, Peter K

2018-01-01

Background: Gene signatures derived from transcriptomic data using machine learning methods have shown promise for biodosimetry testing. These signatures may not be sufficiently robust for large scale testing, as their performance has not been adequately validated on external, independent datasets. The present study develops human and murine signatures with biochemically-inspired machine learning that are strictly validated using k-fold and traditional approaches. Methods: Gene Expression Omnibus (GEO) datasets of exposed human and murine lymphocytes were preprocessed via nearest neighbor imputation and expression of genes implicated in the literature to be responsive to radiation exposure (n=998) were then ranked by Minimum Redundancy Maximum Relevance (mRMR). Optimal signatures were derived by backward, complete, and forward sequential feature selection using Support Vector Machines (SVM), and validated using k-fold or traditional validation on independent datasets. Results: The best human signatures we derived exhibit k-fold validation accuracies of up to 98% ( DDB2 ,  PRKDC , TPP2 , PTPRE , and GADD45A ) when validated over 209 samples and traditional validation accuracies of up to 92% ( DDB2 ,  CD8A ,  TALDO1 ,  PCNA ,  EIF4G2 ,  LCN2 ,  CDKN1A ,  PRKCH ,  ENO1 ,  and PPM1D ) when validated over 85 samples. Some human signatures are specific enough to differentiate between chemotherapy and radiotherapy. Certain multi-class murine signatures have sufficient granularity in dose estimation to inform eligibility for cytokine therapy (assuming these signatures could be translated to humans). We compiled a list of the most frequently appearing genes in the top 20 human and mouse signatures. More frequently appearing genes among an ensemble of signatures may indicate greater impact of these genes on the performance of individual signatures. Several genes in the signatures we derived are present in previously proposed signatures. Conclusions: Gene signatures for ionizing radiation exposure derived by machine learning have low error rates in externally validated, independent datasets, and exhibit high specificity and granularity for dose estimation.

Signature analysis of ballistic missile warhead with micro-nutation in terahertz band

NASA Astrophysics Data System (ADS)

Li, Ming; Jiang, Yue-song

2013-08-01

In recent years, the micro-Doppler effect has been proposed as a new technique for signature analysis and extraction of radar targets. The ballistic missile is known as a typical radar target and has been paid many attentions for the complexities of its motions in current researches. The trajectory of a ballistic missile can be generally divided into three stages: boost phase, midcourse phase and terminal phase. The midcourse phase is the most important phase for radar target recognition and interception. In this stage, the warhead forms a typical micro-motion called micro-nutation which consists of three basic micro-motions: spinning, coning and wiggle. This paper addresses the issue of signature analysis of ballistic missile warhead in terahertz band via discussing the micro-Doppler effect. We establish a simplified model (cone-shaped) for the missile warhead followed by the micro-motion models including of spinning, coning and wiggle. Based on the basic formulas of these typical micro-motions, we first derive the theoretical formula of micro-nutation which is the main micro-motion of the missile warhead. Then, we calculate the micro-Doppler frequency in both X band and terahertz band via these micro-Doppler formulas. The simulations are given to show the superiority of our proposed method for the recognition and detection of radar micro targets in terahertz band.

The technique of entropy optimization in motor current signature analysis and its application in the fault diagnosis of gear transmission

NASA Astrophysics Data System (ADS)

Chen, Xiaoguang; Liang, Lin; Liu, Fei; Xu, Guanghua; Luo, Ailing; Zhang, Sicong

2012-05-01

Nowadays, Motor Current Signature Analysis (MCSA) is widely used in the fault diagnosis and condition monitoring of machine tools. However, although the current signal has lower SNR (Signal Noise Ratio), it is difficult to identify the feature frequencies of machine tools from complex current spectrum that the feature frequencies are often dense and overlapping by traditional signal processing method such as FFT transformation. With the study in the Motor Current Signature Analysis (MCSA), it is found that the entropy is of importance for frequency identification, which is associated with the probability distribution of any random variable. Therefore, it plays an important role in the signal processing. In order to solve the problem that the feature frequencies are difficult to be identified, an entropy optimization technique based on motor current signal is presented in this paper for extracting the typical feature frequencies of machine tools which can effectively suppress the disturbances. Some simulated current signals were made by MATLAB, and a current signal was obtained from a complex gearbox of an iron works made in Luxembourg. In diagnosis the MCSA is combined with entropy optimization. Both simulated and experimental results show that this technique is efficient, accurate and reliable enough to extract the feature frequencies of current signal, which provides a new strategy for the fault diagnosis and the condition monitoring of machine tools.

Seismic attribute analysis for reservoir and fluid prediction, Malay Basin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mansor, M.N.; Rudolph, K.W.; Richards, F.B.

1994-07-01

The Malay Basin is characterized by excellent seismic data quality, but complex clastic reservoir architecture. With these characteristics, seismic attribute analysis is a very important tool in exploration and development geoscience and is routinely used for mapping fluids and reservoir, recognizing and risking traps, assessment, depth conversion, well placement, and field development planning. Attribute analysis can be successfully applied to both 2-D and 3-D data as demonstrated by comparisons of 2-D and 3-D amplitude maps of the same area. There are many different methods of extracting amplitude information from seismic data, including amplitude mapping, horizon slice, summed horizon slice, isochronmore » slice, and horizon slice from AVO (amplitude versus offset) cube. Within the Malay Basin, horizon/isochron slice techniques have several advantages over simply extracting amplitudes from a picked horizon: they are much faster, permit examination of the amplitude structure of the entire cube, yield better results for weak/variable signatures, and aid summation of amplitudes. Summation in itself often yields improved results because it incorporates the signature from the entire reservoir interval, reducing any effects due to noise, mispicking, or waveform variations. Dip and azimuth attributes have been widely applied by industry for fault identification. In addition, these attributes can also be used to map signature variations associated with hydrocarbon contacts or stratigraphic changes, and this must be considered when using these attributes for structural interpretation.« less

A Quantum Multi-proxy Blind Signature Scheme Based on Genuine Four-Qubit Entangled State

NASA Astrophysics Data System (ADS)

Tian, Juan-Hong; Zhang, Jian-Zhong; Li, Yan-Ping

2016-02-01

In this paper, we propose a multi-proxy blind signature scheme based on controlled teleportation. Genuine four-qubit entangled state functions as quantum channel. The scheme uses the physical characteristics of quantum mechanics to implement delegation, signature and verification. The security analysis shows the scheme satisfies the security features of multi-proxy signature, unforgeability, undeniability, blindness and unconditional security.

Analysis of dissolved organic carbon concentration and 13C isotopic signature by TOC-IRMS - assessment of analytical performance

NASA Astrophysics Data System (ADS)

Kirkels, Frédérique; Cerli, Chiara; Federherr, Eugen; Kalbitz, Karsten

2013-04-01

Stable carbon isotopes provide a powerful tool to assess carbon pools and their dynamics. Dissolved organic carbon (DOC) has been recognized to play an important role in ecosystem functioning and carbon cycling and has therefore gained increased research interest. However, direct measurement of 13C isotopic signature of carbon in the dissolved phase is technically challenging particularly using high temperature combustion. Until recently, mainly custom-made systems existed which were modified for coupling of TOC instruments with IRMS for simultaneous assessment of C content and isotopic signature. The variety of coupled systems showed differences in their analytical performances. For analysis of DOC high temperature combustion is recognized as best performing method, owing to its high efficiency of conversion to CO2 also for highly refractory components (e.g. humic, fulvic acids) present in DOC and soil extracts. Therefore, we tested high temperature combustion TOC coupled to IRMS (developed by Elementar Group) for bulk measurements of DOC concentration and 13C signature. The instruments are coupled via an Interface to exchange the carrier gas from O2 to He and to concentrate the derived CO2 for the isotope measurement. Analytical performance of the system was assessed for a variety of organic compounds characterized by different stability and complexity, including humic acid and DOM. We tested injection volumes between 0.2-3 ml, thereby enabling measurement of broad concentration ranges. With an injection volume of 0.5 ml (n=3, preceded by 1 discarded injection), DOC and 13C signatures for concentrations between 5-150 mg C/L were analyzed with high precision (standard deviation (SD) predominantly <0.1‰), good accuracy and linearity (overall SD <0.9‰). For the same settings, slightly higher variation in precision was observed among the lower concentration range and depending upon specific system conditions. Differences in 13C signatures of about 50‰ among samples did not affect the precision of the analysis of natural abundance and labeled samples. Natural DOM, derived from different soils and assessed at various concentrations, was measured with similar good analytical performance, and also tested for the effect of freezing and re-dissolving. We found good performance of TOC-IRMS in comparison with other systems capable of determining C concentration and isotopic signatures. We recognize the advantages of this system providing: - High sample throughput, short measurement time (15 minutes), flexible sample volume - Easy maintenance, handling, rapid sample preparation (no pretreatment) This preliminary assessment highlights wide-ranging opportunities for further research on concentrations and isotopic signatures by TOC-IRMS to elucidate the role of dissolved carbon in terrestrial and aquatic systems.

Modeling and analysis of LWIR signature variability associated with 3D and BRDF effects

NASA Astrophysics Data System (ADS)

Adler-Golden, Steven; Less, David; Jin, Xuemin; Rynes, Peter

2016-05-01

Algorithms for retrieval of surface reflectance, emissivity or temperature from a spectral image almost always assume uniform illumination across the scene and horizontal surfaces with Lambertian reflectance. When these algorithms are used to process real 3-D scenes, the retrieved "apparent" values contain the strong, spatially dependent variations in illumination as well as surface bidirectional reflectance distribution function (BRDF) effects. This is especially problematic with horizontal or near-horizontal viewing, where many observed surfaces are vertical, and where horizontal surfaces can show strong specularity. The goals of this study are to characterize long-wavelength infrared (LWIR) signature variability in a HSI 3-D scene and develop practical methods for estimating the true surface values. We take advantage of synthetic near-horizontal imagery generated with the high-fidelity MultiService Electro-optic Signature (MuSES) model, and compare retrievals of temperature and directional-hemispherical reflectance using standard sky downwelling illumination and MuSES-based non-uniform environmental illumination.

Theoretical Characterization of Visual Signatures and Calculation of Approximate Global Harmonic Frequency Scaling Factors

NASA Astrophysics Data System (ADS)

Kashinski, D. O.; Nelson, R. G.; Chase, G. M.; di Nallo, O. E.; Byrd, E. F. C.

2016-05-01

We are investigating the accuracy of theoretical models used to predict the visible, ultraviolet, and infrared spectra, as well as other properties, of product materials ejected from the muzzle of currently fielded systems. Recent advances in solid propellants has made the management of muzzle signature (flash) a principle issue in weapons development across the calibers. A priori prediction of the electromagnetic spectra of formulations will allow researchers to tailor blends that yield desired signatures and determine spectrographic detection ranges. Quantum chemistry methods at various levels of sophistication have been employed to optimize molecular geometries, compute unscaled harmonic frequencies, and determine the optical spectra of specific gas-phase species. Electronic excitations are being computed using Time Dependent Density Functional Theory (TD-DFT). Calculation of approximate global harmonic frequency scaling factors for specific DFT functionals is also in progress. A full statistical analysis and reliability assessment of computational results is currently underway. Work supported by the ARL, DoD-HPCMP, and USMA.

In Situ 3D Monitoring of Geometric Signatures in the Powder-Bed-Fusion Additive Manufacturing Process via Vision Sensing Methods

PubMed Central

Li, Zhongwei; Liu, Xingjian; Wen, Shifeng; He, Piyao; Zhong, Kai; Wei, Qingsong; Shi, Yusheng; Liu, Sheng

2018-01-01

Lack of monitoring of the in situ process signatures is one of the challenges that has been restricting the improvement of Powder-Bed-Fusion Additive Manufacturing (PBF AM). Among various process signatures, the monitoring of the geometric signatures is of high importance. This paper presents the use of vision sensing methods as a non-destructive in situ 3D measurement technique to monitor two main categories of geometric signatures: 3D surface topography and 3D contour data of the fusion area. To increase the efficiency and accuracy, an enhanced phase measuring profilometry (EPMP) is proposed to monitor the 3D surface topography of the powder bed and the fusion area reliably and rapidly. A slice model assisted contour detection method is developed to extract the contours of fusion area. The performance of the techniques is demonstrated with some selected measurements. Experimental results indicate that the proposed method can reveal irregularities caused by various defects and inspect the contour accuracy and surface quality. It holds the potential to be a powerful in situ 3D monitoring tool for manufacturing process optimization, close-loop control, and data visualization. PMID:29649171

Integrative Analysis to Identify Common Genetic Markers of Metabolic Syndrome, Dementia, and Diabetes

PubMed Central

Zhang, Weihong; Xin, Linlin; Lu, Ying

2017-01-01

Background Emerging data have established links between systemic metabolic dysfunction, such as diabetes and metabolic syndrome (MetS), with neurocognitive impairment, including dementia. The common gene signature and the associated signaling pathways of MetS, diabetes, and dementia have not been widely studied. Material/Methods We exploited the translational bioinformatics approach to choose the common gene signatures for both dementia and MetS. For this we employed “DisGeNET discovery platform”. Results Gene mining analysis revealed that a total of 173 genes (86 genes common to all three diseases) which comprised a proportion of 43% of the total genes associated with dementia. The gene enrichment analysis showed that these genes were involved in dysregulation in the neurological system (23.2%) and the central nervous system (20.8%) phenotype processes. The network analysis revealed APOE, APP, PARK2, CEPBP, PARP1, MT-CO2, CXCR4, IGFIR, CCR5, and PIK3CD as important nodes with significant interacting partners. The meta-regression analysis showed modest association of APOE with dementia and metabolic complications. The directionality of effects of the variants on Alzheimer disease is generally consistent with previous observations and did not differ by race/ethnicity (p>0.05), although our study had low power for this test. Conclusions Our novel approach showed APOE as a common gene signature with a link to dementia, MetS, and diabetes. Future gene association studies should focus on the association of gene polymorphisms with multiple disease models to identify novel putative drug targets. PMID:29229897

Did Shakespeare write double falsehood? Identifying individuals by creating psychological signatures with text analysis.

PubMed

Boyd, Ryan L; Pennebaker, James W

2015-05-01

More than 100 years after Shakespeare's death, Lewis Theobald published Double Falsehood, a play supposedly sourced from a lost play by Shakespeare and John Fletcher. Since its release, scholars have attempted to determine its true authorship. Using new approaches to language and psychological analysis, we examined Double Falsehood and the works of Theobald, Shakespeare, and Fletcher. Specifically, we created a psychological signature from each author's language and statistically compared the features of each signature with those of Double Falsehood's signature. Multiple analytic approaches converged in suggesting that Double Falsehood's psychological style and content architecture predominantly resemble those of Shakespeare, showing some similarity with Fletcher's signature and only traces of Theobald's. Closer inspection revealed that Shakespeare's influence is most apparent early in the play, whereas Fletcher's is most apparent in later acts. Double Falsehood has a psychological signature consistent with that expected to be present in the long-lost play The History of Cardenio, cowritten by Shakespeare and Fletcher. © The Author(s) 2015.

Acoustic emission from a growing crack

NASA Technical Reports Server (NTRS)

Jacobs, Laurence J.

1989-01-01

An analytical method is being developed to determine the signature of an acoustic emission waveform from a growing crack and the results of this analysis are compared to experimentally obtained values. Within the assumptions of linear elastic fracture mechanics, a two dimensional model is developed to examine a semi-infinite crack that, after propagating with a constant velocity, suddenly stops. The analytical model employs an integral equation method for the analysis of problems of dynamic fracture mechanics. The experimental procedure uses an interferometric apparatus that makes very localized absolute measurements with very high fidelity and without acoustically loading the specimen.

Application of the ToxMiner Database: Network Analysis of Linkage between ToxCast Phase I Chemicals and Thyroid Related Disease Outcomes

EPA Science Inventory

The US EPA ToxCast program is using in vitro HTS (High-Throughput Screening) methods to profile and model bioactivity of environmental chemicals. The main goals of the ToxCast program are to generate predictive signatures of toxicity, and ultimately provide rapid and cost-effecti...

Electrically tunable Dicke effect in a double-ring resonator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cetin, A. E.; Muestecaplioglu, Oe. E.; Department of Physics, Koc University, Sariyer, Istanbul 34450

We study the finite-element method analysis of the Dicke effect using numerical simulations in an all-optical system of an optical waveguide side-coupled to two interacting ring resonators in a liquid crystal environment. The system is shown to exhibit all the signatures of the Dicke effect under active and reversible control by an applied voltage.

Forensic assays of ricin: development of snp assays to generate precise genetic signatures for mixed genotypes found in ricin preparations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jackson, Paul J.; Hill, Karen K.

2009-11-09

The results outlined in this report provide the information for needed to apply a SNP-based forensic analysis to diverse ricin preparations. The same methods could be useful in castor breeding programs that seek to reduce or eliminate ricin in oil-producing R. communis cultivars.

The Peter Effect in Early Experimental Education Research

ERIC Educational Resources Information Center

Little, Joseph

2003-01-01

One of the signatures of scientific writing is its ability to present the claims of science as if they were "untouched by human hands." In the early years of experimental education, researchers achieved this by adopting a citational practice that led to the sedimentation of their cardinal method, the analysis of variance, and their standard for…

Secure and Efficient Signature Scheme Based on NTRU for Mobile Payment

NASA Astrophysics Data System (ADS)

Xia, Yunhao; You, Lirong; Sun, Zhe; Sun, Zhixin

2017-10-01

Mobile payment becomes more and more popular, however the traditional public-key encryption algorithm has higher requirements for hardware which is not suitable for mobile terminals of limited computing resources. In addition, these public-key encryption algorithms do not have the ability of anti-quantum computing. This paper researches public-key encryption algorithm NTRU for quantum computation through analyzing the influence of parameter q and k on the probability of generating reasonable signature value. Two methods are proposed to improve the probability of generating reasonable signature value. Firstly, increase the value of parameter q. Secondly, add the authentication condition that meet the reasonable signature requirements during the signature phase. Experimental results show that the proposed signature scheme can realize the zero leakage of the private key information of the signature value, and increase the probability of generating the reasonable signature value. It also improve rate of the signature, and avoid the invalid signature propagation in the network, but the scheme for parameter selection has certain restrictions.

Designing Dietary Recommendations Using System Level Interactomics Analysis and Network-Based Inference

PubMed Central

Zheng, Tingting; Ni, Yueqiong; Li, Jun; Chow, Billy K. C.; Panagiotou, Gianni

2017-01-01

Background: A range of computational methods that rely on the analysis of genome-wide expression datasets have been developed and successfully used for drug repositioning. The success of these methods is based on the hypothesis that introducing a factor (in this case, a drug molecule) that could reverse the disease gene expression signature will lead to a therapeutic effect. However, it has also been shown that globally reversing the disease expression signature is not a prerequisite for drug activity. On the other hand, the basic idea of significant anti-correlation in expression profiles could have great value for establishing diet-disease associations and could provide new insights into the role of dietary interventions in disease. Methods: We performed an integrated analysis of publicly available gene expression profiles for foods, diseases and drugs, by calculating pairwise similarity scores for diet and disease gene expression signatures and characterizing their topological features in protein-protein interaction networks. Results: We identified 485 diet-disease pairs where diet could positively influence disease development and 472 pairs where specific diets should be avoided in a disease state. Multiple evidence suggests that orange, whey and coconut fat could be beneficial for psoriasis, lung adenocarcinoma and macular degeneration, respectively. On the other hand, fructose-rich diet should be restricted in patients with chronic intermittent hypoxia and ovarian cancer. Since humans normally do not consume foods in isolation, we also applied different algorithms to predict synergism; as a result, 58 food pairs were predicted. Interestingly, the diets identified as anti-correlated with diseases showed a topological proximity to the disease proteins similar to that of the corresponding drugs. Conclusions: In conclusion, we provide a computational framework for establishing diet-disease associations and additional information on the role of diet in disease development. Due to the complexity of analyzing the food composition and eating patterns of individuals our in silico analysis, using large-scale gene expression datasets and network-based topological features, may serve as a proof-of-concept in nutritional systems biology for identifying diet-disease relationships and subsequently designing dietary recommendations. PMID:29033850

Study of recreational land and open space using Skylab imagery

NASA Technical Reports Server (NTRS)

Sattinger, I. J. (Principal Investigator)

1975-01-01

The author has identified the following significant results. An analysis of the statistical uniqueness of each of the signatures of the Gratiot-Saginaw State Game Area was made by computing a matrix of probabilities of misclassification for all possible signature pairs. Within each data set, the 35 signatures were then aggregated into a smaller set of composite signatures by combining groups of signatures having high probabilities of misclassification. Computer separation of forest denisty classes was poor with multispectral scanner data collected on 5 August 1973. Signatures from the scanner data were further analyzed to determine the ranking of spectral channels for computer separation of the scene classes. Probabilities of misclassification were computed for composite signatures using four separate combinations of data source and channel selection.

A Quantum Multi-Proxy Weak Blind Signature Scheme Based on Entanglement Swapping

NASA Astrophysics Data System (ADS)

Yan, LiLi; Chang, Yan; Zhang, ShiBin; Han, GuiHua; Sheng, ZhiWei

2017-02-01

In this paper, we present a multi-proxy weak blind signature scheme based on quantum entanglement swapping of Bell states. In the scheme, proxy signers can finish the signature instead of original singer with his/her authority. It can be applied to the electronic voting system, electronic paying system, etc. The scheme uses the physical characteristics of quantum mechanics to implement delegation, signature and verification. It could guarantee not only the unconditionally security but also the anonymity of the message owner. The security analysis shows the scheme satisfies the security features of multi-proxy weak signature, singers cannot disavowal his/her signature while the signature cannot be forged by others, and the message owner can be traced.

High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Musah, Rabi A.; Espinoza, Edgard O.; Cody, Robert B.

A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. Moreover, a range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. In this paper, we illustrate how the method can be used to: (1) distinguishmore » between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required.« less

High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

DOE PAGES

Musah, Rabi A.; Espinoza, Edgard O.; Cody, Robert B.; ...

2015-07-09

A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. Moreover, a range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. In this paper, we illustrate how the method can be used to: (1) distinguishmore » between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required.« less

A High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

PubMed Central

Musah, Rabi A.; Espinoza, Edgard O.; Cody, Robert B.; Lesiak, Ashton D.; Christensen, Earl D.; Moore, Hannah E.; Maleknia, Simin; Drijfhout, Falko P.

2015-01-01

A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. A range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. Here, we illustrate how the method can be used to: (1) distinguish between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required. PMID:26156000

A High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

NASA Astrophysics Data System (ADS)

Musah, Rabi A.; Espinoza, Edgard O.; Cody, Robert B.; Lesiak, Ashton D.; Christensen, Earl D.; Moore, Hannah E.; Maleknia, Simin; Drijfhout, Falko P.

2015-07-01

A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. A range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. Here, we illustrate how the method can be used to: (1) distinguish between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required.

High temperature polymer degradation: Rapid IR flow-through method for volatile quantification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giron, Nicholas H.; Celina, Mathew C.

Accelerated aging of polymers at elevated temperatures often involves the generation of volatiles. These can be formed as the products of oxidative degradation reactions or intrinsic pyrolytic decomposition as part of polymer scission reactions. A simple analytical method for the quantification of water, CO 2, and CO as fundamental signatures of degradation kinetics is required. Here, we describe an analytical framework and develops a rapid mid-IR based gas analysis methodology to quantify volatiles that are contained in small ampoules after aging exposures. The approach requires identification of unique spectral signatures, systematic calibration with known concentrations of volatiles, and a rapidmore » acquisition FTIR spectrometer for time resolved successive spectra. Furthermore, the volatiles are flushed out from the ampoule with dry N2 carrier gas and are then quantified through spectral and time integration. This method is sufficiently sensitive to determine absolute yields of ~50 μg water or CO 2, which relates to probing mass losses of less than 0.01% for a 1 g sample, i.e. the early stages in the degradation process. Such quantitative gas analysis is not easily achieved with other approaches. Our approach opens up the possibility of quantitative monitoring of volatile evolution as an avenue to explore polymer degradation kinetics and its dependence on time and temperature.« less

High temperature polymer degradation: Rapid IR flow-through method for volatile quantification

DOE PAGES

Giron, Nicholas H.; Celina, Mathew C.

2017-05-19

Accelerated aging of polymers at elevated temperatures often involves the generation of volatiles. These can be formed as the products of oxidative degradation reactions or intrinsic pyrolytic decomposition as part of polymer scission reactions. A simple analytical method for the quantification of water, CO 2, and CO as fundamental signatures of degradation kinetics is required. Here, we describe an analytical framework and develops a rapid mid-IR based gas analysis methodology to quantify volatiles that are contained in small ampoules after aging exposures. The approach requires identification of unique spectral signatures, systematic calibration with known concentrations of volatiles, and a rapidmore » acquisition FTIR spectrometer for time resolved successive spectra. Furthermore, the volatiles are flushed out from the ampoule with dry N2 carrier gas and are then quantified through spectral and time integration. This method is sufficiently sensitive to determine absolute yields of ~50 μg water or CO 2, which relates to probing mass losses of less than 0.01% for a 1 g sample, i.e. the early stages in the degradation process. Such quantitative gas analysis is not easily achieved with other approaches. Our approach opens up the possibility of quantitative monitoring of volatile evolution as an avenue to explore polymer degradation kinetics and its dependence on time and temperature.« less

Detecting of transient vibration signatures using an improved fast spatial-spectral ensemble kurtosis kurtogram and its applications to mechanical signature analysis of short duration data from rotating machinery

NASA Astrophysics Data System (ADS)

Chen, BinQiang; Zhang, ZhouSuo; Zi, YanYang; He, ZhengJia; Sun, Chuang

2013-10-01

Detecting transient vibration signatures is of vital importance for vibration-based condition monitoring and fault detection of the rotating machinery. However, raw mechanical signals collected by vibration sensors are generally mixtures of physical vibrations of the multiple mechanical components installed in the examined machinery. Fault-generated incipient vibration signatures masked by interfering contents are difficult to be identified. The fast kurtogram (FK) is a concise and smart gadget for characterizing these vibration features. The multi-rate filter-bank (MRFB) and the spectral kurtosis (SK) indicator of the FK are less powerful when strong interfering vibration contents exist, especially when the FK are applied to vibration signals of short duration. It is encountered that the impulsive interfering contents not authentically induced by mechanical faults complicate the optimal analyzing process and lead to incorrect choosing of the optimal analysis subband, therefore the original FK may leave out the essential fault signatures. To enhance the analyzing performance of FK for industrial applications, an improved version of fast kurtogram, named as "fast spatial-spectral ensemble kurtosis kurtogram", is presented. In the proposed technique, discrete quasi-analytic wavelet tight frame (QAWTF) expansion methods are incorporated as the detection filters. The QAWTF, constructed based on dual tree complex wavelet transform, possesses better vibration transient signature extracting ability and enhanced time-frequency localizability compared with conventional wavelet packet transforms (WPTs). Moreover, in the constructed QAWTF, a non-dyadic ensemble wavelet subband generating strategy is put forward to produce extra wavelet subbands that are capable of identifying fault features located in transition-band of WPT. On the other hand, an enhanced signal impulsiveness evaluating indicator, named "spatial-spectral ensemble kurtosis" (SSEK), is put forward and utilized as the quantitative measure to select optimal analyzing parameters. The SSEK indicator is robuster in evaluating the impulsiveness intensity of vibration signals due to its better suppressing ability of Gaussian noise, harmonics and sporadic impulsive shocks. Numerical validations, an experimental test and two engineering applications were used to verify the effectiveness of the proposed technique. The analyzing results of the numerical validations, experimental tests and engineering applications demonstrate that the proposed technique possesses robuster transient vibration content detecting performance in comparison with the original FK and the WPT-based FK method, especially when they are applied to the processing of vibration signals of relative limited duration.

A Real-Time Infrared Ultra-Spectral Signature Classification Method via Spatial Pyramid Matching

PubMed Central

Mei, Xiaoguang; Ma, Yong; Li, Chang; Fan, Fan; Huang, Jun; Ma, Jiayi

2015-01-01

The state-of-the-art ultra-spectral sensor technology brings new hope for high precision applications due to its high spectral resolution. However, it also comes with new challenges, such as the high data dimension and noise problems. In this paper, we propose a real-time method for infrared ultra-spectral signature classification via spatial pyramid matching (SPM), which includes two aspects. First, we introduce an infrared ultra-spectral signature similarity measure method via SPM, which is the foundation of the matching-based classification method. Second, we propose the classification method with reference spectral libraries, which utilizes the SPM-based similarity for the real-time infrared ultra-spectral signature classification with robustness performance. Specifically, instead of matching with each spectrum in the spectral library, our method is based on feature matching, which includes a feature library-generating phase. We calculate the SPM-based similarity between the feature of the spectrum and that of each spectrum of the reference feature library, then take the class index of the corresponding spectrum having the maximum similarity as the final result. Experimental comparisons on two publicly-available datasets demonstrate that the proposed method effectively improves the real-time classification performance and robustness to noise. PMID:26205263

Keystroke dynamics in the pre-touchscreen era

PubMed Central

Ahmad, Nasir; Szymkowiak, Andrea; Campbell, Paul A.

2013-01-01

Biometric authentication seeks to measure an individual’s unique physiological attributes for the purpose of identity verification. Conventionally, this task has been realized via analyses of fingerprints or signature iris patterns. However, whilst such methods effectively offer a superior security protocol compared with password-based approaches for example, their substantial infrastructure costs, and intrusive nature, make them undesirable and indeed impractical for many scenarios. An alternative approach seeks to develop similarly robust screening protocols through analysis of typing patterns, formally known as keystroke dynamics. Here, keystroke analysis methodologies can utilize multiple variables, and a range of mathematical techniques, in order to extract individuals’ typing signatures. Such variables may include measurement of the period between key presses, and/or releases, or even key-strike pressures. Statistical methods, neural networks, and fuzzy logic have often formed the basis for quantitative analysis on the data gathered, typically from conventional computer keyboards. Extension to more recent technologies such as numerical keypads and touch-screen devices is in its infancy, but obviously important as such devices grow in popularity. Here, we review the state of knowledge pertaining to authentication via conventional keyboards with a view toward indicating how this platform of knowledge can be exploited and extended into the newly emergent type-based technological contexts. PMID:24391568

Keystroke dynamics in the pre-touchscreen era.

PubMed

Ahmad, Nasir; Szymkowiak, Andrea; Campbell, Paul A

2013-12-19

Biometric authentication seeks to measure an individual's unique physiological attributes for the purpose of identity verification. Conventionally, this task has been realized via analyses of fingerprints or signature iris patterns. However, whilst such methods effectively offer a superior security protocol compared with password-based approaches for example, their substantial infrastructure costs, and intrusive nature, make them undesirable and indeed impractical for many scenarios. An alternative approach seeks to develop similarly robust screening protocols through analysis of typing patterns, formally known as keystroke dynamics. Here, keystroke analysis methodologies can utilize multiple variables, and a range of mathematical techniques, in order to extract individuals' typing signatures. Such variables may include measurement of the period between key presses, and/or releases, or even key-strike pressures. Statistical methods, neural networks, and fuzzy logic have often formed the basis for quantitative analysis on the data gathered, typically from conventional computer keyboards. Extension to more recent technologies such as numerical keypads and touch-screen devices is in its infancy, but obviously important as such devices grow in popularity. Here, we review the state of knowledge pertaining to authentication via conventional keyboards with a view toward indicating how this platform of knowledge can be exploited and extended into the newly emergent type-based technological contexts.

A Coincidence Signature Library for Multicoincidence Radionuclide Analysis Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Leon E.; Ellis, J E.; Valsan, Andrei B.

Pacific Northwest National Laboratory (PNNL) is currently developing multicoincidence systems to perform trace radionuclide analysis at or near the sample collection point, for applications that include emergency response, nuclear forensics, and environmental monitoring. Quantifying radionuclide concentrations with these systems requires a library of accurate emission intensities for each detected signature, for all candidate radionuclides. To meet this need, a Coincidence Lookup Library (CLL) is being developed to calculate the emission intensities of coincident signatures from a user-specified radionuclide, or conversely, to determine the radionuclides that may be responsible for a specific detected coincident signature. The algorithms used to generate absolutemore » emission intensities and various query modes for our developmental CLL are described.« less

Signature Peptide-Enabled Metagenomics (Seventh Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting 2012)

ScienceCinema

McMahon, Ben

2018-01-11

Ben McMahon of Los Alamos National Laboratory (LANL) presents "Signature Peptide-Enabled Metagenomics" at the 7th Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting held in June, 2012 in Santa Fe, NM.

Signature Peptide-Enabled Metagenomics (Seventh Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting 2012)

DOE Office of Scientific and Technical Information (OSTI.GOV)

McMahon, Ben

2012-06-01

Ben McMahon of Los Alamos National Laboratory (LANL) presents "Signature Peptide-Enabled Metagenomics" at the 7th Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting held in June, 2012 in Santa Fe, NM.

Predictions of runoff signatures in ungauged basins: Austrian case study

NASA Astrophysics Data System (ADS)

Viglione, A.; Parajka, J.; Salinas, J.; Rogger, M.; Sivapalan, M.; Bloeschl, G.

2012-12-01

Runoff variability can be broken up into several components, each of them meaningful of a certain class of applications of societal relevance: annual runoff, seasonal runoff, flow duration curve, low flows, floods and hydrographs. We call them runoff signatures and we view them as a manifestation of catchment functioning at different time scales, as emergent properties of the complex systems that catchments are. Just as a medical doctor has many different options for studying the state and functioning of a patient, we can infer the state and functioning of a catchment observing its runoff signatures. But what can we do in the absence of runoff data? This study aims to understand how well one can predict runoff signatures in ungauged catchments. The comparison across signatures is based on one consistent data set (Austria) and one regionalisation method (Top-Kriging) in order to explore the relative performance of the predictions of each of the signatures. Results indicate that the performance, assessed by cross-validation, is best for annual and seasonal runoff, it degrades as one moves to low flows and floods and goes up again to high values for runoff hydrographs. Also, dedicated regionalisation methods, i.e. focusing on particular signatures and their characteristics, provide better predictions of the signatures than regionalisation of the entire hydrograph. These results suggest that the use of signatures in the calibration or assessment of process models can be valuable, in that this can lead to models predicting runoff correctly for the right reasons.

Efficient Unstructured Grid Adaptation Methods for Sonic Boom Prediction

NASA Technical Reports Server (NTRS)

Campbell, Richard L.; Carter, Melissa B.; Deere, Karen A.; Waithe, Kenrick A.

2008-01-01

This paper examines the use of two grid adaptation methods to improve the accuracy of the near-to-mid field pressure signature prediction of supersonic aircraft computed using the USM3D unstructured grid flow solver. The first method (ADV) is an interactive adaptation process that uses grid movement rather than enrichment to more accurately resolve the expansion and compression waves. The second method (SSGRID) uses an a priori adaptation approach to stretch and shear the original unstructured grid to align the grid with the pressure waves and reduce the cell count required to achieve an accurate signature prediction at a given distance from the vehicle. Both methods initially create negative volume cells that are repaired in a module in the ADV code. While both approaches provide significant improvements in the near field signature (< 3 body lengths) relative to a baseline grid without increasing the number of grid points, only the SSGRID approach allows the details of the signature to be accurately computed at mid-field distances (3-10 body lengths) for direct use with mid-field-to-ground boom propagation codes.

Solution-grown crystals for neutron radiation detectors, and methods of solution growth

DOEpatents

Zaitseva, Natalia P; Hull, Giulia; Cherepy, Nerine J; Payne, Stephen A; Stoeffl, Wolfgang

2012-06-26

A method according to one embodiment includes growing an organic crystal from solution, the organic crystal exhibiting a signal response signature for neutrons from a radioactive source. A system according to one embodiment includes an organic crystal having physical characteristics of formation from solution, the organic crystal exhibiting a signal response signature for neutrons from a radioactive source; and a photodetector for detecting the signal response of the organic crystal. A method according to another embodiment includes growing an organic crystal from solution, the organic crystal being large enough to exhibit a detectable signal response signature for neutrons from a radioactive source. An organic crystal according to another embodiment includes an organic crystal having physical characteristics of formation from solution, the organic crystal exhibiting a signal response signature for neutrons from a radioactive source, wherein the organic crystal has a length of greater than about 1 mm in one dimension.

Probing multi-scale self-similarity of tissue structures using light scattering spectroscopy: prospects in pre-cancer detection

NASA Astrophysics Data System (ADS)

Chatterjee, Subhasri; Das, Nandan K.; Kumar, Satish; Mohapatra, Sonali; Pradhan, Asima; Panigrahi, Prasanta K.; Ghosh, Nirmalya

2013-02-01

Multi-resolution analysis on the spatial refractive index inhomogeneities in the connective tissue regions of human cervix reveals clear signature of multifractality. We have thus developed an inverse analysis strategy for extraction and quantification of the multifractality of spatial refractive index fluctuations from the recorded light scattering signal. The method is based on Fourier domain pre-processing of light scattering data using Born approximation, and its subsequent analysis through Multifractal Detrended Fluctuation Analysis model. The method has been validated on several mono- and multi-fractal scattering objects whose self-similar properties are user controlled and known a-priori. Following successful validation, this approach has initially been explored for differentiating between different grades of precancerous human cervical tissues.

GPU implementation of the simplex identification via split augmented Lagrangian

NASA Astrophysics Data System (ADS)

Sevilla, Jorge; Nascimento, José M. P.

2015-10-01

Hyperspectral imaging can be used for object detection and for discriminating between different objects based on their spectral characteristics. One of the main problems of hyperspectral data analysis is the presence of mixed pixels, due to the low spatial resolution of such images. This means that several spectrally pure signatures (endmembers) are combined into the same mixed pixel. Linear spectral unmixing follows an unsupervised approach which aims at inferring pure spectral signatures and their material fractions at each pixel of the scene. The huge data volumes acquired by such sensors put stringent requirements on processing and unmixing methods. This paper proposes an efficient implementation of a unsupervised linear unmixing method on GPUs using CUDA. The method finds the smallest simplex by solving a sequence of nonsmooth convex subproblems using variable splitting to obtain a constraint formulation, and then applying an augmented Lagrangian technique. The parallel implementation of SISAL presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory. The results herein presented indicate that the GPU implementation can significantly accelerate the method's execution over big datasets while maintaining the methods accuracy.

Inorganic optical taggant and method of making

DOEpatents

Lauf, Robert J.; Anderson, Kimberly K.; Montgomery, Frederick C.

2005-05-31

Sintered, translucent ceramic microbeads, preferably alumina, titania, zirconia, yttria, zirconium phosphate, or yttrium aluminum garnet (YAG) are doped with one or more optically active species. The beads may be added to substances such as explosives in order to create a distinctive optical signature that identifies a manufacturer, lot number, etc. in the event of the need for forensic analysis. Because the beads have a generally spherical surface, the radius of curvature provides an additional distinguishing characteristic by which a particular sample may be identified. The beads could also be formulated into paints if needed to create distinctive optical signatures for camouflage, decoys, or other countermeasures and could also be applied as a dust to track the movement of personnel, vehicles, etc.

The detection of global convection on the sun by an analysis of line shift data of the John M. Wilcox Solar Observatory at Stanford University

NASA Technical Reports Server (NTRS)

Yoshimura, Hirokazu

1987-01-01

Signatures of the existence of the global convection in the sun were found in the absorption line shift data of the John M. Wilcox Solar Observatory at Stanford University. The signatures are characterized by persistent periodic time variations in the east-west component of the velocity fields defined by fitting a slope to the line shift data in a certain longitude window at a specified latitude and longitude by a least square method. The variations indicate that the amplitude of the velocity fields is about 100 m/s. It is suggested that several modes of global convection are coexisting in the solar convection zone.

Integrative ChIP-seq/Microarray Analysis Identifies a CTNNB1 Target Signature Enriched in Intestinal Stem Cells and Colon Cancer

PubMed Central

Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L.; Roberts, Brian S.; Arthur, William T.; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

2014-01-01

Background Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. Results We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Conclusion Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells. PMID:24651522

Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

PubMed

Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L; Roberts, Brian S; Arthur, William T; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

2014-01-01

Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

Identification of forgeries in handwritten petitions for ballot propositions

NASA Astrophysics Data System (ADS)

Srihari, Sargur; Ramakrishnan, Veshnu; Malgireddy, Manavender; Ball, Gregory R.

2009-01-01

Many governments have some form of "direct democracy" legislation procedure whereby individual citizens can propose various measures creating or altering laws. Generally, such a process is started with the gathering of a large number of signatures. There is interest in whether or not there are fraudulent signatures present in such a petition, and if so what percentage of the signatures are indeed fraudulent. However, due to the large number of signatures (tens of thousands), it is not feasible to have a document examiner verify the signatures directly. Instead, there is interest in creating a subset of signatures where there is a high probability of fraud that can be verified. We present a method by which a pairwise comparison of signatures can be performed and subsequent sorting can generate such subsets.

Comparative of signal processing techniques for micro-Doppler signature extraction with automotive radar systems

NASA Astrophysics Data System (ADS)

Rodriguez-Hervas, Berta; Maile, Michael; Flores, Benjamin C.

2014-05-01

In recent years, the automotive industry has experienced an evolution toward more powerful driver assistance systems that provide enhanced vehicle safety. These systems typically operate in the optical and microwave regions of the electromagnetic spectrum and have demonstrated high efficiency in collision and risk avoidance. Microwave radar systems are particularly relevant due to their operational robustness under adverse weather or illumination conditions. Our objective is to study different signal processing techniques suitable for extraction of accurate micro-Doppler signatures of slow moving objects in dense urban environments. Selection of the appropriate signal processing technique is crucial for the extraction of accurate micro-Doppler signatures that will lead to better results in a radar classifier system. For this purpose, we perform simulations of typical radar detection responses in common driving situations and conduct the analysis with several signal processing algorithms, including short time Fourier Transform, continuous wavelet or Kernel based analysis methods. We take into account factors such as the relative movement between the host vehicle and the target, and the non-stationary nature of the target's movement. A comparison of results reveals that short time Fourier Transform would be the best approach for detection and tracking purposes, while the continuous wavelet would be the best suited for classification purposes.

A sensitive NanoString-based assay to score STK11 (LKB1) pathway disruption in lung adenocarcinoma

PubMed Central

Chen, Lu; Engel, Brienne E.; Welsh, Eric A.; Yoder, Sean J.; Brantley, Stephen G.; Chen, Dung-Tsa; Beg, Amer A.; Cao, Chunxia; Kaye, Frederic J.; Haura, Eric B.; Schabath, Matthew B.; Cress, W. Douglas

2016-01-01

Introduction Serine/threonine kinase 11 (STK11), better known as LKB1, is a tumor-suppressor commonly mutated in lung adenocarcinoma (LUAD). Previous work has shown that mutational inactivation of the STK11 pathway may serve as a predictive biomarker for cancer treatments including phenformin and COX-2 inhibition. Although immunohistochemistry and diagnostic sequencing are employed to measure STK11 pathway disruption, there are serious limitations to these methods emphasizing the importance to validate a clinically useful assay. Methods An initial STK11 mutation mRNA signature was generated using cell line data and refined using three large, independent patient databases. The signature was validated as a classifier using The Cancer Genome Anatomy Project (TCGA) LUAD cohort as well as a 442-patient LUAD cohort developed at Moffitt. Finally, the signature was adapted into a NanoString -based format and validated using RNA samples isolated from FFPE tissue blocks corresponding to a cohort of 150 LUAD patients. For comparison, STK11 immunochemistry was also performed. Results The STK11 signature was found to correlate with null mutations identified by exon sequencing in multiple cohorts using both microarray and NanoString formats. While there was a statistically significant correlation between reduced STK11 protein expression by IHC and mutation status, the NanoString-based assay showed superior overall performance with a −0.1588 improvement in area under the curve in receiver-operator characteristic curve analysis (p<0.012). Conclusion The described NanoString-based STK11 assay is a sensitive biomarker to study emerging therapeutic modalities in clinical trials. PMID:26917230

Design and Computational/Experimental Analysis of Low Sonic Boom Configurations

NASA Technical Reports Server (NTRS)

Cliff, Susan E.; Baker, Timothy J.; Hicks, Raymond M.

1999-01-01

Recent studies have shown that inviscid CFD codes combined with a planar extrapolation method give accurate sonic boom pressure signatures at distances greater than one body length from supersonic configurations if either adapted grids swept at the approximate Mach angle or very dense non-adapted grids are used. The validation of CFD for computing sonic boom pressure signatures provided the confidence needed to undertake the design of new supersonic transport configurations with low sonic boom characteristics. An aircraft synthesis code in combination with CFD and an extrapolation method were used to close the design. The principal configuration of this study is designated LBWT (Low Boom Wing Tail) and has a highly swept cranked arrow wing with conventional tails, and was designed to accommodate either 3 or 4 engines. The complete configuration including nacelles and boundary layer diverters was evaluated using the AIRPLANE code. This computer program solves the Euler equations on an unstructured tetrahedral mesh. Computations and wind tunnel data for the LBWT and two other low boom configurations designed at NASA Ames Research Center are presented. The two additional configurations are included to provide a basis for comparing the performance and sonic boom level of the LBWT with contemporary low boom designs and to give a broader experiment/CFD correlation study. The computational pressure signatures for the three configurations are contrasted with on-ground-track near-field experimental data from the NASA Ames 9x7 Foot Supersonic Wind Tunnel. Computed pressure signatures for the LBWT are also compared with experiment at approximately 15 degrees off ground track.

Ground signature extrapolation of three-dimensional near-field CFD predictions for several HSCT configurations

NASA Technical Reports Server (NTRS)

Siclari, M. J.

1992-01-01

A CFD analysis of the near-field sonic boom environment of several low boom High Speed Civilian Transport (HSCT) concepts is presented. The CFD method utilizes a multi-block Euler marching code within the context of an innovative mesh topology that allows for the resolution of shock waves several body lengths from the aircraft. Three-dimensional pressure footprints at one body length below three-different low boom aircraft concepts are presented. Models of two concepts designed by NASA to cruise at Mach 2 and Mach 3 were built and tested in the wind tunnel. The third concept was designed by Boeing to cruise at Mach 1.7. Centerline and sideline samples of these footprints are then extrapolated to the ground using a linear waveform parameter method to estimate the ground signatures or sonic boom ground overpressure levels. The Mach 2 concept achieved its centerline design signature but indicated higher sideline booms due to the outboard wing crank of the configuration. Nacelles are also included on two of NASA's low boom concepts. Computations are carried out for both flow-through nacelles and nacelles with engine exhaust simulation. The flow-through nacelles with the assumption of zero spillage and zero inlet lip radius showed very little effect on the sonic boom signatures. On the other hand, it was shown that the engine exhaust plumes can have an effect on the levels of overpressure reaching the ground depending on the engine operating conditions. The results of this study indicate that engine integration into a low boom design should be given some attention.

matK-QR classifier: a patterns based approach for plant species identification.

PubMed

More, Ravi Prabhakar; Mane, Rupali Chandrashekhar; Purohit, Hemant J

2016-01-01

DNA barcoding is widely used and most efficient approach that facilitates rapid and accurate identification of plant species based on the short standardized segment of the genome. The nucleotide sequences of maturaseK ( matK ) and ribulose-1, 5-bisphosphate carboxylase ( rbcL ) marker loci are commonly used in plant species identification. Here, we present a new and highly efficient approach for identifying a unique set of discriminating nucleotide patterns to generate a signature (i.e. regular expression) for plant species identification. In order to generate molecular signatures, we used matK and rbcL loci datasets, which encompass 125 plant species in 52 genera reported by the CBOL plant working group. Initially, we performed Multiple Sequence Alignment (MSA) of all species followed by Position Specific Scoring Matrix (PSSM) for both loci to achieve a percentage of discrimination among species. Further, we detected Discriminating Patterns (DP) at genus and species level using PSSM for the matK dataset. Combining DP and consecutive pattern distances, we generated molecular signatures for each species. Finally, we performed a comparative assessment of these signatures with the existing methods including BLASTn, Support Vector Machines (SVM), Jrip-RIPPER, J48 (C4.5 algorithm), and the Naïve Bayes (NB) methods against NCBI-GenBank matK dataset. Due to the higher discrimination success obtained with the matK as compared to the rbcL , we selected matK gene for signature generation. We generated signatures for 60 species based on identified discriminating patterns at genus and species level. Our comparative assessment results suggest that a total of 46 out of 60 species could be correctly identified using generated signatures, followed by BLASTn (34 species), SVM (18 species), C4.5 (7 species), NB (4 species) and RIPPER (3 species) methods As a final outcome of this study, we converted signatures into QR codes and developed a software matK -QR Classifier (http://www.neeri.res.in/matk_classifier/index.htm), which search signatures in the query matK gene sequences and predict corresponding plant species. This novel approach of employing pattern-based signatures opens new avenues for the classification of species. In addition to existing methods, we believe that matK -QR Classifier would be a valuable tool for molecular taxonomists enabling precise identification of plant species.

Restoration of the intrinsic properties of human dermal papilla in vitro.

PubMed

Ohyama, Manabu; Kobayashi, Tetsuro; Sasaki, Takashi; Shimizu, Atsushi; Amagai, Masayuki

2012-09-01

The dermal papilla (DP) plays pivotal roles in hair follicle morphogenesis and cycling. However, characterization and/or propagation of human DPs have been unsatisfactory because of the lack of efficient isolation methods and the loss of innate characteristics in vitro. We hypothesized that culture conditions sustaining the intrinsic molecular signature of the human DP could facilitate expansion of functional DP cells. To test this, we first characterized the global gene expression profile of microdissected, non-cultured human DPs. We performed a 'two-step' microarray analysis to exclude the influence of unwanted contaminants in isolated DPs and successfully identified 118 human DP signature genes, including 38 genes listed in the mouse DP signature. The bioinformatics analysis of the DP gene list revealed that WNT, BMP and FGF signaling pathways were upregulated in intact DPs and addition of 6-bromoindirubin-3'-oxime, recombinant BMP2 and basic FGF to stimulate these respective signaling pathways resulted in maintained expression of in situ DP signature genes in primarily cultured human DP cells. More importantly, the exposure to these stimulants restored normally reduced DP biomarker expression in conventionally cultured DP cells. Cell growth was moderate in the newly developed culture medium. However, rapid DP cell expansion by conventional culture followed by the restoration by defined activators provided a sufficient number of DP cells that demonstrated characteristic DP activities in functional assays. The study reported here revealed previously unreported molecular mechanisms contributing to human DP properties and describes a useful technique for the investigation of human DP biology and hair follicle bioengineering.

Detection of illegal transfer of videos over the Internet

NASA Astrophysics Data System (ADS)

Chaisorn, Lekha; Sainui, Janya; Manders, Corey

2010-07-01

In this paper, a method for detecting infringements or modifications of a video in real-time is proposed. The method first segments a video stream into shots, after which it extracts some reference frames as keyframes. This process is performed employing a Singular Value Decomposition (SVD) technique developed in this work. Next, for each input video (represented by its keyframes), ordinal-based signature and SIFT (Scale Invariant Feature Transform) descriptors are generated. The ordinal-based method employs a two-level bitmap indexing scheme to construct the index for each video signature. The first level clusters all input keyframes into k clusters while the second level converts the ordinal-based signatures into bitmap vectors. On the other hand, the SIFT-based method directly uses the descriptors as the index. Given a suspect video (being streamed or transferred on the Internet), we generate the signature (ordinal and SIFT descriptors) then we compute similarity between its signature and those signatures in the database based on ordinal signature and SIFT descriptors separately. For similarity measure, besides the Euclidean distance, Boolean operators are also utilized during the matching process. We have tested our system by performing several experiments on 50 videos (each about 1/2 hour in duration) obtained from the TRECVID 2006 data set. For experiments set up, we refer to the conditions provided by TRECVID 2009 on "Content-based copy detection" task. In addition, we also refer to the requirements issued in the call for proposals by MPEG standard on the similar task. Initial result shows that our framework is effective and robust. As compared to our previous work, on top of the achievement we obtained by reducing the storage space and time taken in the ordinal based method, by introducing the SIFT features, we could achieve an overall accuracy in F1 measure of about 96% (improved about 8%).

ERTS-1 imagery and native plant distributions

NASA Technical Reports Server (NTRS)

Musick, H. B.; Mcginnies, W.; Haase, E.; Lepley, L. K.

1974-01-01

A method is developed for using ERTS spectral signature data to determine plant community distribution and phenology without resolving individual plants. An Exotech ERTS radiometer was used near ground level to obtain spectral signatures for a desert plant community, including two shrub species, ground covered with live annuals in April and dead ones in June, and bare ground. It is shown that comparisons of scene types can be made when spectral signatures are expressed as a ratio of red reflectivity to IR reflectivity or when they are plotted as red reflectivity vs. IR reflectivity, in which case the signature clusters of each component are more distinct. A method for correcting and converting the ERTS radiance values to reflectivity values for comparison with ground truth data is appended.

RecceMan: an interactive recognition assistance for image-based reconnaissance: synergistic effects of human perception and computational methods for object recognition, identification, and infrastructure analysis

NASA Astrophysics Data System (ADS)

El Bekri, Nadia; Angele, Susanne; Ruckhäberle, Martin; Peinsipp-Byma, Elisabeth; Haelke, Bruno

2015-10-01

This paper introduces an interactive recognition assistance system for imaging reconnaissance. This system supports aerial image analysts on missions during two main tasks: Object recognition and infrastructure analysis. Object recognition concentrates on the classification of one single object. Infrastructure analysis deals with the description of the components of an infrastructure and the recognition of the infrastructure type (e.g. military airfield). Based on satellite or aerial images, aerial image analysts are able to extract single object features and thereby recognize different object types. It is one of the most challenging tasks in the imaging reconnaissance. Currently, there are no high potential ATR (automatic target recognition) applications available, as consequence the human observer cannot be replaced entirely. State-of-the-art ATR applications cannot assume in equal measure human perception and interpretation. Why is this still such a critical issue? First, cluttered and noisy images make it difficult to automatically extract, classify and identify object types. Second, due to the changed warfare and the rise of asymmetric threats it is nearly impossible to create an underlying data set containing all features, objects or infrastructure types. Many other reasons like environmental parameters or aspect angles compound the application of ATR supplementary. Due to the lack of suitable ATR procedures, the human factor is still important and so far irreplaceable. In order to use the potential benefits of the human perception and computational methods in a synergistic way, both are unified in an interactive assistance system. RecceMan® (Reconnaissance Manual) offers two different modes for aerial image analysts on missions: the object recognition mode and the infrastructure analysis mode. The aim of the object recognition mode is to recognize a certain object type based on the object features that originated from the image signatures. The infrastructure analysis mode pursues the goal to analyze the function of the infrastructure. The image analyst extracts visually certain target object signatures, assigns them to corresponding object features and is finally able to recognize the object type. The system offers him the possibility to assign the image signatures to features given by sample images. The underlying data set contains a wide range of objects features and object types for different domains like ships or land vehicles. Each domain has its own feature tree developed by aerial image analyst experts. By selecting the corresponding features, the possible solution set of objects is automatically reduced and matches only the objects that contain the selected features. Moreover, we give an outlook of current research in the field of ground target analysis in which we deal with partly automated methods to extract image signatures and assign them to the corresponding features. This research includes methods for automatically determining the orientation of an object and geometric features like width and length of the object. This step enables to reduce automatically the possible object types offered to the image analyst by the interactive recognition assistance system.

Novel algorithm to identify and differentiate specific digital signature of breath sound in patients with diffuse parenchymal lung disease.

PubMed

Bhattacharyya, Parthasarathi; Mondal, Ashok; Dey, Rana; Saha, Dipanjan; Saha, Goutam

2015-05-01

Auscultation is an important part of the clinical examination of different lung diseases. Objective analysis of lung sounds based on underlying characteristics and its subsequent automatic interpretations may help a clinical practice. We collected the breath sounds from 8 normal subjects and 20 diffuse parenchymal lung disease (DPLD) patients using a newly developed instrument and then filtered off the heart sounds using a novel technology. The collected sounds were thereafter analysed digitally on several characteristics as dynamical complexity, texture information and regularity index to find and define their unique digital signatures for differentiating normality and abnormality. For convenience of testing, these characteristic signatures of normal and DPLD lung sounds were transformed into coloured visual representations. The predictive power of these images has been validated by six independent observers that include three physicians. The proposed method gives a classification accuracy of 100% for composite features for both the normal as well as lung sound signals from DPLD patients. When tested by independent observers on the visually transformed images, the positive predictive value to diagnose the normality and DPLD remained 100%. The lung sounds from the normal and DPLD subjects could be differentiated and expressed according to their digital signatures. On visual transformation to coloured images, they retain 100% predictive power. This technique may assist physicians to diagnose DPLD from visual images bearing the digital signature of the condition. © 2015 Asian Pacific Society of Respirology.

Proton radiation-induced miRNA signatures in mouse blood: Characterization and comparison with 56Fe-ion and gamma radiation

PubMed Central

Templin, Thomas; Young, Erik F.; Smilenov, Lubomir B.

2013-01-01

Purpose Previously, we showed that microRNA (miRNA) signatures derived from the peripheral blood of mice are highly specific for both radiation energy (γ-rays or high linear energy transfer [LET] 56Fe ions) and radiation dose. Here, we investigate to what extent miRNA expression signatures derived from mouse blood can be used as biomarkers for exposure to 600 MeV proton radiation. Materials and methods We exposed mice to 600 MeV protons, using doses of 0.5 or 1.0 Gy, isolated total RNA at 6 h or 24 h after irradiation, and used quantitative real-time polymerase chain reaction (PCR) to determine the changes in miRNA expression. Results A total of 26 miRNA were differentially expressed after proton irradiation, in either one (77%) or multiple conditions (23%). Statistical classifiers based on proton, γ, and 56Fe-ion miRNA expression signatures predicted radiation type and proton dose with accuracies of 81% and 88%, respectively. Importantly, gene ontology analysis for proton-irradiated cells shows that genes targeted by radiation-induced miRNA are involved in biological processes and molecular functions similar to those controlled by miRNA in γ ray- and 56Fe-irradiated cells. Conclusions Mouse blood miRNA signatures induced by proton, γ, or 56Fe irradiation are radiation type- and dose-specific. These findings underline the complexity of the miRNA-mediated radiation response. PMID:22551419

A novel prognostic six-CpG signature in glioblastomas.

PubMed

Yin, An-An; Lu, Nan; Etcheverry, Amandine; Aubry, Marc; Barnholtz-Sloan, Jill; Zhang, Lu-Hua; Mosser, Jean; Zhang, Wei; Zhang, Xiang; Liu, Yu-He; He, Ya-Long

2018-03-01

We aimed to identify a clinically useful biomarker using DNA methylation-based information to optimize individual treatment of patients with glioblastoma (GBM). A six-CpG panel was identified by incorporating genome-wide DNA methylation data and clinical information of three distinct discovery sets and was combined using a risk-score model. Different validation sets of GBMs and lower-grade gliomas and different statistical methods were implemented for prognostic evaluation. An integrative analysis of multidimensional TCGA data was performed to molecularly characterize different risk tumors. The six-CpG risk-score signature robustly predicted overall survival (OS) in all discovery and validation cohorts and in a treatment-independent manner. It also predicted progression-free survival (PFS) in available patients. The multimarker epigenetic signature was demonstrated as an independent prognosticator and had better performance than known molecular indicators such as glioma-CpG island methylator phenotype (G-CIMP) and proneural subtype. The defined risk subgroups were molecularly distinct; high-risk tumors were biologically more aggressive with concordant activation of proangiogenic signaling at multimolecular levels. Accordingly, we observed better OS benefits of bevacizumab-contained therapy to high-risk patients in independent sets, supporting its implication in guiding usage of antiangiogenic therapy. Finally, the six-CpG signature refined the risk classification based on G-CIMP and MGMT methylation status. The novel six-CpG signature is a robust and independent prognostic indicator for GBMs and is of promising value to improve personalized management. © 2018 John Wiley & Sons Ltd.

A 15-gene signature for prediction of colon cancer recurrence and prognosis based on SVM.

PubMed

Xu, Guangru; Zhang, Minghui; Zhu, Hongxing; Xu, Jinhua

2017-03-10

To screen the gene signature for distinguishing patients with high risks from those with low-risks for colon cancer recurrence and predicting their prognosis. Five microarray datasets of colon cancer samples were collected from Gene Expression Omnibus database and one was obtained from The Cancer Genome Atlas (TCGA). After preprocessing, data in GSE17537 were analyzed using the Linear Models for Microarray data (LIMMA) method to identify the differentially expressed genes (DEGs). The DEGs further underwent PPI network-based neighborhood scoring and support vector machine (SVM) analyses to screen the feature genes associated with recurrence and prognosis, which were then validated by four datasets GSE38832, GSE17538, GSE28814 and TCGA using SVM and Cox regression analyses. A total of 1207 genes were identified as DEGs between recurrence and no-recurrence samples, including 726 downregulated and 481 upregulated genes. Using SVM analysis and five gene expression profile data confirmation, a 15-gene signature (HES5, ZNF417, GLRA2, OR8D2, HOXA7, FABP6, MUSK, HTR6, GRIP2, KLRK1, VEGFA, AKAP12, RHEB, NCRNA00152 and PMEPA1) were identified as a predictor of recurrence risk and prognosis for colon cancer patients. Our identified 15-gene signature may be useful to classify colon cancer patients with different prognosis and some genes in this signature may represent new therapeutic targets. Copyright © 2016. Published by Elsevier B.V.

A signature inferred from Drosophila mitotic genes predicts survival of breast cancer patients.

PubMed

Damasco, Christian; Lembo, Antonio; Somma, Maria Patrizia; Gatti, Maurizio; Di Cunto, Ferdinando; Provero, Paolo

2011-02-28

The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures. We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes). The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis. This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies.

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kulkarni, Shilpa; Koller, Antonius; Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York

Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24more » and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes. Together, these data showed the feasibility of defining biomarkers that could elucidate tissue-associated and systemic response caused by high-dose ionizing radiation. This is the first report using an exosome proteomics approach to identify radiation signatures.« less

A New Method to Quantify the Isotopic Signature of Leaf Transpiration: Implications for Landscape-Scale Evapotranspiration Partitioning Studies

NASA Astrophysics Data System (ADS)

Wang, L.; Good, S. P.; Caylor, K. K.

2010-12-01

Characterizing the constituent components of evapotranspiration is crucial to better understand ecosystem-level water budgets and water use dynamics. Isotope based evapotranspiration partitioning methods are promising but their utility lies in the accurate estimation of the isotopic composition of underlying transpiration and evaporation. Here we report a new method to quantify the isotopic signature of leaf transpiration under field conditions. This method utilizes a commercially available laser-based isotope analyzer and a transparent leaf chamber, modified from Licor conifer leaf chamber. The method is based on the water mass balance in ambient air and leaf transpired air. We verified the method using “artificial leaves” and glassline extracted samples. The method provides a new and direct way to estimate leaf transpiration isotopic signatures and it has wide applications in ecology, hydrology and plant physiology.

Chemical Attribution of Fentanyl Using Multivariate Statistical Analysis of Orthogonal Mass Spectral Data

DOE PAGES

Mayer, Brian P.; DeHope, Alan J.; Mew, Daniel A.; ...

2016-03-24

Attribution of the origin of an illicit drug relies on identification of compounds indicative of its clandestine production and is a key component of many modern forensic investigations. Here, the results of these studies can yield detailed information on method of manufacture, starting material source, and final product, all critical forensic evidence. In the present work, chemical attribution signatures (CAS) associated with the synthesis of the analgesic fentanyl, N-(1-phenylethylpiperidin-4-yl)-N-phenylpropanamide, were investigated. Six synthesis methods, all previously published fentanyl synthetic routes or hybrid versions thereof, were studied in an effort to identify and classify route-specific signatures. A total of 160 distinctmore » compounds and inorganic species were identified using gas and liquid chromatographies combined with mass spectrometric methods (gas chromatography/mass spectrometry (GC/MS) and liquid chromatography–tandem mass spectrometry-time of-flight (LC–MS/MS-TOF)) in conjunction with inductively coupled plasma mass spectrometry (ICPMS). The complexity of the resultant data matrix urged the use of multivariate statistical analysis. Using partial least-squares-discriminant analysis (PLS-DA), 87 route-specific CAS were classified and a statistical model capable of predicting the method of fentanyl synthesis was validated and tested against CAS profiles from crude fentanyl products deposited and later extracted from two operationally relevant surfaces: stainless steel and vinyl tile. Finally, this work provides the most detailed fentanyl CAS investigation to date by using orthogonal mass spectral data to identify CAS of forensic significance for illicit drug detection, profiling, and attribution.« less

Chemical Attribution of Fentanyl Using Multivariate Statistical Analysis of Orthogonal Mass Spectral Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayer, Brian P.; DeHope, Alan J.; Mew, Daniel A.

Attribution of the origin of an illicit drug relies on identification of compounds indicative of its clandestine production and is a key component of many modern forensic investigations. Here, the results of these studies can yield detailed information on method of manufacture, starting material source, and final product, all critical forensic evidence. In the present work, chemical attribution signatures (CAS) associated with the synthesis of the analgesic fentanyl, N-(1-phenylethylpiperidin-4-yl)-N-phenylpropanamide, were investigated. Six synthesis methods, all previously published fentanyl synthetic routes or hybrid versions thereof, were studied in an effort to identify and classify route-specific signatures. A total of 160 distinctmore » compounds and inorganic species were identified using gas and liquid chromatographies combined with mass spectrometric methods (gas chromatography/mass spectrometry (GC/MS) and liquid chromatography–tandem mass spectrometry-time of-flight (LC–MS/MS-TOF)) in conjunction with inductively coupled plasma mass spectrometry (ICPMS). The complexity of the resultant data matrix urged the use of multivariate statistical analysis. Using partial least-squares-discriminant analysis (PLS-DA), 87 route-specific CAS were classified and a statistical model capable of predicting the method of fentanyl synthesis was validated and tested against CAS profiles from crude fentanyl products deposited and later extracted from two operationally relevant surfaces: stainless steel and vinyl tile. Finally, this work provides the most detailed fentanyl CAS investigation to date by using orthogonal mass spectral data to identify CAS of forensic significance for illicit drug detection, profiling, and attribution.« less

Identification of contemporary selection signatures using composite log likelihood and their associations with marbling score in Korean cattle.

PubMed

Ryu, Jihye; Lee, Chaeyoung

2014-12-01

Positive selection not only increases beneficial allele frequency but also causes augmentation of allele frequencies of sequence variants in close proximity. Signals for positive selection were detected by the statistical differences in subsequent allele frequencies. To identify selection signatures in Korean cattle, we applied a composite log-likelihood (CLL)-based method, which calculates a composite likelihood of the allelic frequencies observed across sliding windows of five adjacent loci and compares the value with the critical statistic estimated by 50,000 permutations. Data for a total of 11,799 nucleotide polymorphisms were used with 71 Korean cattle and 209 foreign beef cattle. As a result, 147 signals were identified for Korean cattle based on CLL estimates (P < 0.01). The signals might be candidate genetic factors for meat quality by which the Korean cattle have been selected. Further genetic association analysis with 41 intragenic variants in the selection signatures with the greatest CLL for each chromosome revealed that marbling score was associated with five variants. Intensive association studies with all the selection signatures identified in this study are required to exclude signals associated with other phenotypes or signals falsely detected and thus to identify genetic markers for meat quality. © 2014 Stichting International Foundation for Animal Genetics.

Forensic Signature Detection of Yersinia Pestis Culturing Practices Across Institutions Using a Bayesian Network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webb-Robertson, Bobbie-Jo M.; Corley, Courtney D.; McCue, Lee Ann

The field of bioforensics is focused on the analysis of evidence from a biocrime. Existing laboratory analyses can identify the specific strain of an organism in the evidence, as well signatures of the specific culture batch of organisms, such as low-frequency contaminants or indicators of growth and processing methods. To link these disparate types of physical data to potential suspects, investigators may need to identify institutions or individuals whose access to strains and culturing practices match those identified from the evidence. In this work we present a Bayesian statistical network to fuse different types of analytical measurements that predict themore » production environment of a Yersinia pestis sample under investigation with automated test processing of scientific publications to identify institutions with a history of growing Y. pestis under similar conditions. Furthermore, the textual and experimental signatures were evaluated recursively to determine the overall sensitivity of the network across all levels of false positives. We illustrate that institutions associated with several specific culturing practices can be accurately selected based on the experimental signature from only a few analytical measurements. These findings demonstrate that similar Bayesian networks can be generated generically for many organisms of interest and their deployment is not prohibitive due to either computational or experimental factors.« less

The LncRNA Connectivity Map: Using LncRNA Signatures to Connect Small Molecules, LncRNAs, and Diseases.

PubMed

Yang, Haixiu; Shang, Desi; Xu, Yanjun; Zhang, Chunlong; Feng, Li; Sun, Zeguo; Shi, Xinrui; Zhang, Yunpeng; Han, Junwei; Su, Fei; Li, Chunquan; Li, Xia

2017-07-27

Well characterized the connections among diseases, long non-coding RNAs (lncRNAs) and drugs are important for elucidating the key roles of lncRNAs in biological mechanisms in various biological states. In this study, we constructed a database called LNCmap (LncRNA Connectivity Map), available at http://www.bio-bigdata.com/LNCmap/ , to establish the correlations among diseases, physiological processes, and the action of small molecule therapeutics by attempting to describe all biological states in terms of lncRNA signatures. By reannotating the microarray data from the Connectivity Map database, the LNCmap obtained 237 lncRNA signatures of 5916 instances corresponding to 1262 small molecular drugs. We provided a user-friendly interface for the convenient browsing, retrieval and download of the database, including detailed information and the associations of drugs and corresponding affected lncRNAs. Additionally, we developed two enrichment analysis methods for users to identify candidate drugs for a particular disease by inputting the corresponding lncRNA expression profiles or an associated lncRNA list and then comparing them to the lncRNA signatures in our database. Overall, LNCmap could significantly improve our understanding of the biological roles of lncRNAs and provide a unique resource to reveal the connections among drugs, lncRNAs and diseases.

A Patient-Derived, Pan-Cancer EMT Signature Identifies Global Molecular Alterations and Immune Target Enrichment Following Epithelial-to-Mesenchymal Transition.

PubMed

Mak, Milena P; Tong, Pan; Diao, Lixia; Cardnell, Robert J; Gibbons, Don L; William, William N; Skoulidis, Ferdinandos; Parra, Edwin R; Rodriguez-Canales, Jaime; Wistuba, Ignacio I; Heymach, John V; Weinstein, John N; Coombes, Kevin R; Wang, Jing; Byers, Lauren Averett

2016-02-01

We previously demonstrated the association between epithelial-to-mesenchymal transition (EMT) and drug response in lung cancer using an EMT signature derived in cancer cell lines. Given the contribution of tumor microenvironments to EMT, we extended our investigation of EMT to patient tumors from 11 cancer types to develop a pan-cancer EMT signature. Using the pan-cancer EMT signature, we conducted an integrated, global analysis of genomic and proteomic profiles associated with EMT across 1,934 tumors including breast, lung, colon, ovarian, and bladder cancers. Differences in outcome and in vitro drug response corresponding to expression of the pan-cancer EMT signature were also investigated. Compared with the lung cancer EMT signature, the patient-derived, pan-cancer EMT signature encompasses a set of core EMT genes that correlate even more strongly with known EMT markers across diverse tumor types and identifies differences in drug sensitivity and global molecular alterations at the DNA, RNA, and protein levels. Among those changes associated with EMT, pathway analysis revealed a strong correlation between EMT and immune activation. Further supervised analysis demonstrated high expression of immune checkpoints and other druggable immune targets, such as PD1, PD-L1, CTLA4, OX40L, and PD-L2, in tumors with the most mesenchymal EMT scores. Elevated PD-L1 protein expression in mesenchymal tumors was confirmed by IHC in an independent lung cancer cohort. This new signature provides a novel, patient-based, histology-independent tool for the investigation of EMT and offers insights into potential novel therapeutic targets for mesenchymal tumors, independent of cancer type, including immune checkpoints. ©2015 American Association for Cancer Research.

Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors.

PubMed

Lamas-Seco, José J; Castro, Paula M; Dapena, Adriana; Vazquez-Araujo, Francisco J

2015-10-26

Inductive Loop Detectors (ILDs) are the most commonly used sensors in traffic management systems. This paper shows that some spectral features extracted from the Fourier Transform (FT) of inductive signatures do not depend on the vehicle speed. Such a property is used to propose a novel method for vehicle classification based on only one signature acquired from a sensor single-loop, in contrast to standard methods using two sensor loops. Our proposal will be evaluated by means of real inductive signatures captured with our hardware prototype.

Multiparty Quantum Blind Signature Scheme Based on Graph States

NASA Astrophysics Data System (ADS)

Jian-Wu, Liang; Xiao-Shu, Liu; Jin-Jing, Shi; Ying, Guo

2018-05-01

A multiparty quantum blind signature scheme is proposed based on the principle of graph state, in which the unitary operations of graph state particles can be applied to generate the quantum blind signature and achieve verification. Different from the classical blind signature based on the mathematical difficulty, the scheme could guarantee not only the anonymity but also the unconditionally security. The analysis shows that the length of the signature generated in our scheme does not become longer as the number of signers increases, and it is easy to increase or decrease the number of signers.

PlasFlow: predicting plasmid sequences in metagenomic data using genome signatures

PubMed Central

Lipinski, Leszek; Dziembowski, Andrzej

2018-01-01

Abstract Plasmids are mobile genetics elements that play an important role in the environmental adaptation of microorganisms. Although plasmids are usually analyzed in cultured microorganisms, there is a need for methods that allow for the analysis of pools of plasmids (plasmidomes) in environmental samples. To that end, several molecular biology and bioinformatics methods have been developed; however, they are limited to environments with low diversity and cannot recover large plasmids. Here, we present PlasFlow, a novel tool based on genomic signatures that employs a neural network approach for identification of bacterial plasmid sequences in environmental samples. PlasFlow can recover plasmid sequences from assembled metagenomes without any prior knowledge of the taxonomical or functional composition of samples with an accuracy up to 96%. It can also recover sequences of both circular and linear plasmids and can perform initial taxonomical classification of sequences. Compared to other currently available tools, PlasFlow demonstrated significantly better performance on test datasets. Analysis of two samples from heavy metal-contaminated microbial mats revealed that plasmids may constitute an important fraction of their metagenomes and carry genes involved in heavy-metal homeostasis, proving the pivotal role of plasmids in microorganism adaptation to environmental conditions. PMID:29346586

The Mimas ghost revisited: An analysis of the electron flux and electron microsignatures observed in the vicinity of Mimas at Saturn

NASA Technical Reports Server (NTRS)

Chenette, D. L.; Stone, E. C.

1983-01-01

An analysis of the electron absorption signature observed by the Cosmic Ray System (CRS) on Voyage 2 near the orbit of Mimas is presented. We find that these observations cannot be explained as the absorption signature of Mimas. Combing Pioneer 11 and Voyager 2 measurements of the electron flux at Mimas's orbit (L=3.1), we find an electron spectrum where most of the flux above approx 100 keV is concentrated near 1 to 3 MeV. The expected Mimas absorption signature is calculated from this spectrum neglecting radial diffusion. A lower limit on the diffusion coefficient for MeV electrons is obtained. With a diffusion coefficient this large, both the Voyager 2 and the Pioneer 11 small-scale electron absorption signature observations in Mimas's orbit are enigmatic. Thus we refer to the mechanism for producing these signatures as the Mimas ghost. A cloud of material in orbit with Mimas may account for the observed electron signature if the cloud is at least 1% opaque to electrons across a region extending over a few hundred kilometers.

A Quantum Proxy Blind Signature Scheme Based on Genuine Five-Qubit Entangled State

NASA Astrophysics Data System (ADS)

Zeng, Chuan; Zhang, Jian-Zhong; Xie, Shu-Cui

2017-06-01

In this paper, a quantum proxy blind signature scheme based on controlled quantum teleportation is proposed. This scheme uses a genuine five-qubit entangled state as quantum channel and adopts the classical Vernam algorithm to blind message. We use the physical characteristics of quantum mechanics to implement delegation, signature and verification. Security analysis shows that our scheme is valid and satisfy the properties of a proxy blind signature, such as blindness, verifiability, unforgeability, undeniability.

Exploring internal features of 16S rRNA gene for identification of clinically relevant species of the genus Streptococcus

PubMed Central

2011-01-01

Background Streptococcus is an economically important genus as a number of species belonging to this genus are human and animal pathogens. The genus has been divided into different groups based on 16S rRNA gene sequence similarity. The variability observed among the members of these groups is low and it is difficult to distinguish them. The present study was taken up to explore 16S rRNA gene sequence to develop methods that can be used for preliminary identification and can supplement the existing methods for identification of clinically-relevant isolates of the genus Streptococcus. Methods 16S rRNA gene sequences belonging to the isolates of S. dysgalactiae, S. equi, S. pyogenes, S. agalactiae, S. bovis, S. gallolyticus, S. mutans, S. sobrinus, S. mitis, S. pneumoniae, S. thermophilus and S. anginosus were analyzed with the purpose to define genetic variability within each species to generate a phylogenetic framework, to identify species-specific signatures and in-silico restriction enzyme analysis. Results The framework based analysis was used to segregate Streptococcus spp. previously identified upto genus level. This segregation was validated using species-specific signatures and in-silico restriction enzyme analysis. 43 uncharacterized Streptococcus spp. could be identified using this approach. Conclusions The markers generated exploring 16S rRNA gene sequences provided useful tool that can be further used for identification of different species of the genus Streptococcus. PMID:21702978

Plant seed species identification from chemical fingerprints: a high-throughput application of direct analysis in real time mass spectrometry.

PubMed

Lesiak, Ashton D; Cody, Robert B; Dane, A John; Musah, Rabi A

2015-09-01

Plant species identification based on the morphological features of plant parts is a well-established science in botany. However, species identification from seeds has largely been unexplored, despite the fact that the seeds contain all of the genetic information that distinguishes one plant from another. Using seeds of genus Datura plants, we show here that the mass spectrum-derived chemical fingerprints for seeds of the same species are similar. On the other hand, seeds from different species within the same genus display distinct chemical signatures, even though they may contain similar characteristic biomarkers. The intraspecies chemical signature similarities on the one hand, and interspecies fingerprint differences on the other, can be processed by multivariate statistical analysis methods to enable rapid species-level identification and differentiation. The chemical fingerprints can be acquired rapidly and in a high-throughput manner by direct analysis in real time mass spectrometry (DART-MS) analysis of the seeds in their native form, without use of a solvent extract. Importantly, knowledge of the identity of the detected molecules is not required for species level identification. However, confirmation of the presence within the seeds of various characteristic tropane and other alkaloids, including atropine, scopolamine, scopoline, tropine, tropinone, and tyramine, was accomplished by comparison of the in-source collision-induced dissociation (CID) fragmentation patterns of authentic standards, to the fragmentation patterns observed in the seeds when analyzed under similar in-source CID conditions. The advantages, applications, and implications of the chemometric processing of DART-MS derived seed chemical signatures for species level identification and differentiation are discussed.

Metabolomic analysis of insulin resistance across different mouse strains and diets.

PubMed

Stöckli, Jacqueline; Fisher-Wellman, Kelsey H; Chaudhuri, Rima; Zeng, Xiao-Yi; Fazakerley, Daniel J; Meoli, Christopher C; Thomas, Kristen C; Hoffman, Nolan J; Mangiafico, Salvatore P; Xirouchaki, Chrysovalantou E; Yang, Chieh-Hsin; Ilkayeva, Olga; Wong, Kari; Cooney, Gregory J; Andrikopoulos, Sofianos; Muoio, Deborah M; James, David E

2017-11-24

Insulin resistance is a major risk factor for many diseases. However, its underlying mechanism remains unclear in part because it is triggered by a complex relationship between multiple factors, including genes and the environment. Here, we used metabolomics combined with computational methods to identify factors that classified insulin resistance across individual mice derived from three different mouse strains fed two different diets. Three inbred ILSXISS strains were fed high-fat or chow diets and subjected to metabolic phenotyping and metabolomics analysis of skeletal muscle. There was significant metabolic heterogeneity between strains, diets, and individual animals. Distinct metabolites were changed with insulin resistance, diet, and between strains. Computational analysis revealed 113 metabolites that were correlated with metabolic phenotypes. Using these 113 metabolites, combined with machine learning to segregate mice based on insulin sensitivity, we identified C22:1-CoA, C2-carnitine, and C16-ceramide as the best classifiers. Strikingly, when these three metabolites were combined into one signature, they classified mice based on insulin sensitivity more accurately than each metabolite on its own or other published metabolic signatures. Furthermore, C22:1-CoA was 2.3-fold higher in insulin-resistant mice and correlated significantly with insulin resistance. We have identified a metabolomic signature composed of three functionally unrelated metabolites that accurately predicts whole-body insulin sensitivity across three mouse strains. These data indicate the power of simultaneous analysis of individual, genetic, and environmental variance in mice for identifying novel factors that accurately predict metabolic phenotypes like whole-body insulin sensitivity. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Acousto-optic signature analysis for inspection of the orbiter thermal protection tile bonds

NASA Technical Reports Server (NTRS)

Rodriguez, Julio G.; Tow, D. M.; Barna, B. A.

1990-01-01

The goal of this research is to develop a viable NDE technique for the inspection of orbiter thermal protection system (TPS) tile bonds. Phase 2, discussed here, concentrated on developing an empirical understanding of the bonded and unbonded vibration signatures of acreage tiles. Controlled experiments in the laboratory have provided useful information on the dynamic response of TPS tiles. It has been shown that several signatures are common to all the pedigree tiles. This degree of consistency in the tile-SIP (strain isolation pad) dynamic response proves that an unbond can be detected for a known tile and establish the basis for extending the analysis capability to arbitrary tiles for which there are no historical data. The field tests of the noncontacting laser acoustic sensor system, conducted at the Kennedy Space Center (KSC), investigated the vibrational environment of the Orbiter Processing Facility (OPF) and its effect on the measurement and analysis techniques being developed. The data collected showed that for orbiter locations, such as the body flap and elevon, the data analysis scheme, and/or the sensor, will require modification to accommodate the ambient motion. Several methods were identified for accomplishing this, and a solution is seen as readily achievable. It was established that the tile response was similar to that observed in the laboratory. Of most importance, however, is that the field environment will not affect the physics of the dynamic response that is related to bond condition. All of this information is fundamental to any future design and development of a prototype system.

Mapping target signatures via partial unmixing of AVIRIS data

NASA Technical Reports Server (NTRS)

Boardman, Joseph W.; Kruse, Fred A.; Green, Robert O.

1995-01-01

A complete spectral unmixing of a complicated AVIRIS scene may not always be possible or even desired. High quality data of spectrally complex areas are very high dimensional and are consequently difficult to fully unravel. Partial unmixing provides a method of solving only that fraction of the data inversion problem that directly relates to the specific goals of the investigation. Many applications of imaging spectrometry can be cast in the form of the following question: 'Are my target signatures present in the scene, and if so, how much of each target material is present in each pixel?' This is a partial unmixing problem. The number of unmixing endmembers is one greater than the number of spectrally defined target materials. The one additional endmember can be thought of as the composite of all the other scene materials, or 'everything else'. Several workers have proposed partial unmixing schemes for imaging spectrometry data, but each has significant limitations for operational application. The low probability detection methods described by Farrand and Harsanyi and the foreground-background method of Smith et al are both examples of such partial unmixing strategies. The new method presented here builds on these innovative analysis concepts, combining their different positive attributes while attempting to circumvent their limitations. This new method partially unmixes AVIRIS data, mapping apparent target abundances, in the presence of an arbitrary and unknown spectrally mixed background. It permits the target materials to be present in abundances that drive significant portions of the scene covariance. Furthermore it does not require a priori knowledge of the background material spectral signatures. The challenge is to find the proper projection of the data that hides the background variance while simultaneously maximizing the variance amongst the targets.

Comprehensive study of solid pharmaceutical tablets in visible, near infrared (NIR), and longwave infrared (LWIR) spectral regions using a rapid simultaneous ultraviolet/visible/NIR (UVN) + LWIR laser-induced breakdown spectroscopy linear arrays detection system and a fast acousto-optic tunable filter NIR spectrometer.

PubMed

Yang, Clayton S C; Jin, Feng; Swaminathan, Siva R; Patel, Sita; Ramer, Evan D; Trivedi, Sudhir B; Brown, Ei E; Hommerich, Uwe; Samuels, Alan C

2017-10-30

This is the first report of a simultaneous ultraviolet/visible/NIR and longwave infrared laser-induced breakdown spectroscopy (UVN + LWIR LIBS) measurement. In our attempt to study the feasibility of combining the newly developed rapid LWIR LIBS linear array detection system to existing rapid analytical techniques for a wide range of chemical analysis applications, two different solid pharmaceutical tablets, Tylenol arthritis pain and Bufferin, were studied using both a recently designed simultaneous UVN + LWIR LIBS detection system and a fast AOTF NIR (1200 to 2200 nm) spectrometer. Every simultaneous UVN + LWIR LIBS emission spectrum in this work was initiated by one single laser pulse-induced micro-plasma in the ambient air atmosphere. Distinct atomic and molecular LIBS emission signatures of the target compounds measured simultaneously in UVN (200 to 1100 nm) and LWIR (5.6 to 10 µm) spectral regions are readily detected and identified without the need to employ complex data processing. In depth profiling studies of these two pharmaceutical tablets without any sample preparation, one can easily monitor the transition of the dominant LWIR emission signatures from coating ingredients gradually to the pharmaceutical ingredients underneath the coating. The observed LWIR LIBS emission signatures provide complementary molecular information to the UVN LIBS signatures, thus adding robustness to identification procedures. LIBS techniques are more surface specific while NIR spectroscopy has the capability to probe more bulk materials with its greater penetration depth. Both UVN + LWIR LIBS and NIR absorption spectroscopy have shown the capabilities of acquiring useful target analyte spectral signatures in comparable short time scales. The addition of a rapid LWIR spectroscopic probe to these widely used optical analytical methods, such as NIR spectroscopy and UVN LIBS, may greatly enhance the capability and accuracy of the combined system for a comprehensive analysis.

Microarray Meta-Analysis Identifies Acute Lung Injury Biomarkers in Donor Lungs That Predict Development of Primary Graft Failure in Recipients

PubMed Central

Haitsma, Jack J.; Furmli, Suleiman; Masoom, Hussain; Liu, Mingyao; Imai, Yumiko; Slutsky, Arthur S.; Beyene, Joseph; Greenwood, Celia M. T.; dos Santos, Claudia

2012-01-01

Objectives To perform a meta-analysis of gene expression microarray data from animal studies of lung injury, and to identify an injury-specific gene expression signature capable of predicting the development of lung injury in humans. Methods We performed a microarray meta-analysis using 77 microarray chips across six platforms, two species and different animal lung injury models exposed to lung injury with or/and without mechanical ventilation. Individual gene chips were classified and grouped based on the strategy used to induce lung injury. Effect size (change in gene expression) was calculated between non-injurious and injurious conditions comparing two main strategies to pool chips: (1) one-hit and (2) two-hit lung injury models. A random effects model was used to integrate individual effect sizes calculated from each experiment. Classification models were built using the gene expression signatures generated by the meta-analysis to predict the development of lung injury in human lung transplant recipients. Results Two injury-specific lists of differentially expressed genes generated from our meta-analysis of lung injury models were validated using external data sets and prospective data from animal models of ventilator-induced lung injury (VILI). Pathway analysis of gene sets revealed that both new and previously implicated VILI-related pathways are enriched with differentially regulated genes. Classification model based on gene expression signatures identified in animal models of lung injury predicted development of primary graft failure (PGF) in lung transplant recipients with larger than 80% accuracy based upon injury profiles from transplant donors. We also found that better classifier performance can be achieved by using meta-analysis to identify differentially-expressed genes than using single study-based differential analysis. Conclusion Taken together, our data suggests that microarray analysis of gene expression data allows for the detection of “injury" gene predictors that can classify lung injury samples and identify patients at risk for clinically relevant lung injury complications. PMID:23071521

In-situ Condition Monitoring of Components in Small Modular Reactors Using Process and Electrical Signature Analysis. Final report, volume 1. Development of experimental flow control loop, data analysis and plant monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Upadhyaya, Belle; Hines, J. Wesley; Damiano, Brian

The research and development under this project was focused on the following three major objectives: Objective 1: Identification of critical in-vessel SMR components for remote monitoring and development of their low-order dynamic models, along with a simulation model of an integral pressurized water reactor (iPWR). Objective 2: Development of an experimental flow control loop with motor-driven valves and pumps, incorporating data acquisition and on-line monitoring interface. Objective 3: Development of stationary and transient signal processing methods for electrical signatures, machinery vibration, and for characterizing process variables for equipment monitoring. This objective includes the development of a data analysis toolbox. Themore » following is a summary of the technical accomplishments under this project: - A detailed literature review of various SMR types and electrical signature analysis of motor-driven systems was completed. A bibliography of literature is provided at the end of this report. Assistance was provided by ORNL in identifying some key references. - A review of literature on pump-motor modeling and digital signal processing methods was performed. - An existing flow control loop was upgraded with new instrumentation, data acquisition hardware and software. The upgrading of the experimental loop included the installation of a new submersible pump driven by a three-phase induction motor. All the sensors were calibrated before full-scale experimental runs were performed. - MATLAB-Simulink model of a three-phase induction motor and pump system was completed. The model was used to simulate normal operation and fault conditions in the motor-pump system, and to identify changes in the electrical signatures. - A simulation model of an integral PWR (iPWR) was updated and the MATLAB-Simulink model was validated for known transients. The pump-motor model was interfaced with the iPWR model for testing the impact of primary flow perturbations (upsets) on plant parameters and the pump electrical signatures. Additionally, the reactor simulation is being used to generate normal operation data and data with instrumentation faults and process anomalies. A frequency controller was interfaced with the motor power supply in order to vary the electrical supply frequency. The experimental flow control loop was used to generate operational data under varying motor performance characteristics. Coolant leakage events were simulated by varying the bypass loop flow rate. The accuracy of motor power calculation was improved by incorporating the power factor, computed from motor current and voltage in each phase of the induction motor.- A variety of experimental runs were made for steady-state and transient pump operating conditions. Process, vibration, and electrical signatures were measured using a submersible pump with variable supply frequency. High correlation was seen between motor current and pump discharge pressure signal; similar high correlation was exhibited between pump motor power and flow rate. Wide-band analysis indicated high coherence (in the frequency domain) between motor current and vibration signals. - Wide-band operational data from a PWR were acquired from AMS Corporation and used to develop time-series models, and to estimate signal spectrum and sensor time constant. All the data were from different pressure transmitters in the system, including primary and secondary loops. These signals were pre-processed using the wavelet transform for filtering both low-frequency and high-frequency bands. This technique of signal pre-processing provides minimum distortion of the data, and results in a more optimal estimation of time constants of plant sensors using time-series modeling techniques.« less

Discriminative Features Mining for Offline Handwritten Signature Verification

NASA Astrophysics Data System (ADS)

Neamah, Karrar; Mohamad, Dzulkifli; Saba, Tanzila; Rehman, Amjad

2014-03-01

Signature verification is an active research area in the field of pattern recognition. It is employed to identify the particular person with the help of his/her signature's characteristics such as pen pressure, loops shape, speed of writing and up down motion of pen, writing speed, pen pressure, shape of loops, etc. in order to identify that person. However, in the entire process, features extraction and selection stage is of prime importance. Since several signatures have similar strokes, characteristics and sizes. Accordingly, this paper presents combination of orientation of the skeleton and gravity centre point to extract accurate pattern features of signature data in offline signature verification system. Promising results have proved the success of the integration of the two methods.

Age and gender-invariant features of handwritten signatures for verification systems

NASA Astrophysics Data System (ADS)

AbdAli, Sura; Putz-Leszczynska, Joanna

2014-11-01

Handwritten signature is one of the most natural biometrics, the study of human physiological and behavioral patterns. Behavioral biometrics includes signatures that may be different due to its owner gender or age because of intrinsic or extrinsic factors. This paper presents the results of the author's research on age and gender influence on verification factors. The experiments in this research were conducted using a database that contains signatures and their associated metadata. The used algorithm is based on the universal forgery feature idea, where the global classifier is able to classify a signature as a genuine one or, as a forgery, without the actual knowledge of the signature template and its owner. Additionally, the reduction of the dimensionality with the MRMR method is discussed.

Standoff spectroscopic interrogation of samples irradiated by high energy lasers

NASA Astrophysics Data System (ADS)

Daigle, Jean-François; Pudo, Dominik; Théberge, Francis

2017-10-01

We report on a novel method that shows the potential to provide real-time, standoff forensic analysis of samples being irradiated by a high energy laser (HEL). The interaction of the HEL beam with matter produces specific optical signatures that can be detected from the location of the HEL system. A spectroscopic analysis of these signals can then provide useful information to the operator including the impact the laser has on the sample as well as providing data about the its structure and composition.

Wetlands delineation by spectral signature analysis and legal implications

NASA Technical Reports Server (NTRS)

Anderon, R. R.; Carter, V.

1972-01-01

High altitude analysis of wetland resources and the use of such information in an operational mode to address specific problems of wetland preservation at a state level are discussed. Work efforts were directed toward: (1) developing techniques for using large scale color IR photography in state wetlands mapping program, (2) developing methods for obtaining wetlands ecology information from high altitude photography, (3) developing means by which spectral data can be more accurately analyzed visually, and (4) developing spectral data for automatic mapping of wetlands.

Diagnostic value of microRNAs in asbestos exposure and malignant mesothelioma: systematic review and qualitative meta-analysis.

PubMed

Micolucci, Luigina; Akhtar, Most Mauluda; Olivieri, Fabiola; Rippo, Maria Rita; Procopio, Antonio Domenico

2016-09-06

Asbestos is a harmful and exceptionally persistent natural material. Malignant mesothelioma (MM), an asbestos-related disease, is an insidious, lethal cancer that is poorly responsive to current treatments. Minimally invasive, specific, and sensitive biomarkers providing early and effective diagnosis in high-risk patients are urgently needed. MicroRNAs (miRNAs, miRs) are endogenous, non-coding, small RNAs with established diagnostic value in cancer and pollution exposure. A systematic review and a qualitative meta-analysis were conducted to identify high-confidence miRNAs that can serve as biomarkers of asbestos exposure and MM. The major biomedical databases were systematically searched for miRNA expression signatures related to asbestos exposure and MM. The qualitative meta-analysis applied a novel vote-counting method that takes into account multiple parameters. The most significant miRNAs thus identified were then subjected to functional and bioinformatic analysis to assess their biomarker potential. A pool of deregulated circulating and tissue miRNAs with biomarker potential for MM was identified and designated as "mesomiRs" (MM-associated miRNAs). Comparison of data from asbestos-exposed and MM subjects found that the most promising candidates for a multimarker signature were circulating miR-126-3p, miR-103a-3p, and miR-625-3p in combination with mesothelin. The most consistently described tissue miRNAs, miR-16-5p, miR-126-3p, miR-143-3p, miR-145-5p, miR-192-5p, miR-193a-3p, miR-200b-3p, miR-203a-3p, and miR-652-3p, were also found to provide a diagnostic signature and should be further investigated as possible therapeutic targets. The qualitative meta-analysis and functional investigation confirmed the early diagnostic value of two miRNA signatures for MM. Large-scale, standardized validation studies are needed to assess their clinical relevance, so as to move from the workbench to the clinic.

Knowledge Driven Variable Selection (KDVS) – a new approach to enrichment analysis of gene signatures obtained from high–throughput data

PubMed Central

2013-01-01

Background High–throughput (HT) technologies provide huge amount of gene expression data that can be used to identify biomarkers useful in the clinical practice. The most frequently used approaches first select a set of genes (i.e. gene signature) able to characterize differences between two or more phenotypical conditions, and then provide a functional assessment of the selected genes with an a posteriori enrichment analysis, based on biological knowledge. However, this approach comes with some drawbacks. First, gene selection procedure often requires tunable parameters that affect the outcome, typically producing many false hits. Second, a posteriori enrichment analysis is based on mapping between biological concepts and gene expression measurements, which is hard to compute because of constant changes in biological knowledge and genome analysis. Third, such mapping is typically used in the assessment of the coverage of gene signature by biological concepts, that is either score–based or requires tunable parameters as well, limiting its power. Results We present Knowledge Driven Variable Selection (KDVS), a framework that uses a priori biological knowledge in HT data analysis. The expression data matrix is transformed, according to prior knowledge, into smaller matrices, easier to analyze and to interpret from both computational and biological viewpoints. Therefore KDVS, unlike most approaches, does not exclude a priori any function or process potentially relevant for the biological question under investigation. Differently from the standard approach where gene selection and functional assessment are applied independently, KDVS embeds these two steps into a unified statistical framework, decreasing the variability derived from the threshold–dependent selection, the mapping to the biological concepts, and the signature coverage. We present three case studies to assess the usefulness of the method. Conclusions We showed that KDVS not only enables the selection of known biological functionalities with accuracy, but also identification of new ones. An efficient implementation of KDVS was devised to obtain results in a fast and robust way. Computing time is drastically reduced by the effective use of distributed resources. Finally, integrated visualization techniques immediately increase the interpretability of results. Overall, KDVS approach can be considered as a viable alternative to enrichment–based approaches. PMID:23302187

Mal-Xtract: Hidden Code Extraction using Memory Analysis

NASA Astrophysics Data System (ADS)

Lim, Charles; Syailendra Kotualubun, Yohanes; Suryadi; Ramli, Kalamullah

2017-01-01

Software packer has been used effectively to hide the original code inside a binary executable, making it more difficult for existing signature based anti malware software to detect malicious code inside the executable. A new method of written and rewritten memory section is introduced to to detect the exact end time of unpacking routine and extract original code from packed binary executable using Memory Analysis running in an software emulated environment. Our experiment results show that at least 97% of the original code from the various binary executable packed with different software packers could be extracted. The proposed method has also been successfully extracted hidden code from recent malware family samples.

[Study of automatic marine oil spills detection using imaging spectroscopy].

PubMed

Liu, De-Lian; Han, Liang; Zhang, Jian-Qi

2013-11-01

To reduce artificial auxiliary works in oil spills detection process, an automatic oil spill detection method based on adaptive matched filter is presented. Firstly, the characteristics of reflectance spectral signature of C-H bond in oil spill are analyzed. And an oil spill spectral signature extraction model is designed by using the spectral feature of C-H bond. It is then used to obtain the reference spectral signature for the following oil spill detection step. Secondly, the characteristics of reflectance spectral signature of sea water, clouds, and oil spill are compared. The bands which have large difference in reflectance spectral signatures of the sea water, clouds, and oil spill are selected. By using these bands, the sea water pixels are segmented. And the background parameters are then calculated. Finally, the classical adaptive matched filter from target detection algorithms is improved and introduced for oil spill detection. The proposed method is applied to the real airborne visible infrared imaging spectrometer (AVIRIS) hyperspectral image captured during the deepwater horizon oil spill in the Gulf of Mexico for oil spill detection. The results show that the proposed method has, high efficiency, does not need artificial auxiliary work, and can be used for automatic detection of marine oil spill.

FAVR (Filtering and Annotation of Variants that are Rare): methods to facilitate the analysis of rare germline genetic variants from massively parallel sequencing datasets

PubMed Central

2013-01-01

Background Characterising genetic diversity through the analysis of massively parallel sequencing (MPS) data offers enormous potential to significantly improve our understanding of the genetic basis for observed phenotypes, including predisposition to and progression of complex human disease. Great challenges remain in resolving genetic variants that are genuine from the millions of artefactual signals. Results FAVR is a suite of new methods designed to work with commonly used MPS analysis pipelines to assist in the resolution of some of the issues related to the analysis of the vast amount of resulting data, with a focus on relatively rare genetic variants. To the best of our knowledge, no equivalent method has previously been described. The most important and novel aspect of FAVR is the use of signatures in comparator sequence alignment files during variant filtering, and annotation of variants potentially shared between individuals. The FAVR methods use these signatures to facilitate filtering of (i) platform and/or mapping-specific artefacts, (ii) common genetic variants, and, where relevant, (iii) artefacts derived from imbalanced paired-end sequencing, as well as annotation of genetic variants based on evidence of co-occurrence in individuals. We applied conventional variant calling applied to whole-exome sequencing datasets, produced using both SOLiD and TruSeq chemistries, with or without downstream processing by FAVR methods. We demonstrate a 3-fold smaller rare single nucleotide variant shortlist with no detected reduction in sensitivity. This analysis included Sanger sequencing of rare variant signals not evident in dbSNP131, assessment of known variant signal preservation, and comparison of observed and expected rare variant numbers across a range of first cousin pairs. The principles described herein were applied in our recent publication identifying XRCC2 as a new breast cancer risk gene and have been made publically available as a suite of software tools. Conclusions FAVR is a platform-agnostic suite of methods that significantly enhances the analysis of large volumes of sequencing data for the study of rare genetic variants and their influence on phenotypes. PMID:23441864

Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, Ju; Chang, Hang; Giricz, Orsi

Correlative analysis of molecular markers with phenotypic signatures is the simplest model for hypothesis generation. In this paper, a panel of 24 breast cell lines was grown in 3D culture, their morphology was imaged through phase contrast microscopy, and computational methods were developed to segment and represent each colony at multiple dimensions. Subsequently, subpopulations from these morphological responses were identified through consensus clustering to reveal three clusters of round, grape-like, and stellate phenotypes. In some cases, cell lines with particular pathobiological phenotypes clustered together (e.g., ERBB2 amplified cell lines sharing the same morphometric properties as the grape-like phenotype). Next, associationsmore » with molecular features were realized through (i) differential analysis within each morphological cluster, and (ii) regression analysis across the entire panel of cell lines. In both cases, the dominant genes that are predictive of the morphological signatures were identified. Specifically, PPAR? has been associated with the invasive stellate morphological phenotype, which corresponds to triple-negative pathobiology. PPAR? has been validated through two supporting biological assays.« less

Detection and discrimination of microorganisms on various substrates with quantum cascade laser spectroscopy

NASA Astrophysics Data System (ADS)

Padilla-Jiménez, Amira C.; Ortiz-Rivera, William; Rios-Velazquez, Carlos; Vazquez-Ayala, Iris; Hernández-Rivera, Samuel P.

2014-06-01

Investigations focusing on devising rapid and accurate methods for developing signatures for microorganisms that could be used as biological warfare agents' detection, identification, and discrimination have recently increased significantly. Quantum cascade laser (QCL)-based spectroscopic systems have revolutionized many areas of defense and security including this area of research. In this contribution, infrared spectroscopy detection based on QCL was used to obtain the mid-infrared (MIR) spectral signatures of Bacillus thuringiensis, Escherichia coli, and Staphylococcus epidermidis. These bacteria were used as microorganisms that simulate biothreats (biosimulants) very truthfully. The experiments were conducted in reflection mode with biosimulants deposited on various substrates including cardboard, glass, travel bags, wood, and stainless steel. Chemometrics multivariate statistical routines, such as principal component analysis regression and partial least squares coupled to discriminant analysis, were used to analyze the MIR spectra. Overall, the investigated infrared vibrational techniques were useful for detecting target microorganisms on the studied substrates, and the multivariate data analysis techniques proved to be very efficient for classifying the bacteria and discriminating them in the presence of highly IR-interfering media.

Properties and behaviour of FAC currents in the inner magnetosphere

NASA Astrophysics Data System (ADS)

Yang, Junying; Dunlop, Malcolm; Yang, Yanyan; Xiong, Chao; Lühr, Hermann; Cao, Jinbin; Li, Liuyuan; Ma, Yuduan; Shen, Chao

2017-04-01

Cusp, region 1 and 2, and other large scale field-aligned currents (FACs), are sampled in situ by both the four Cluster spacecraft and by the three Swarm spacecraft at different altitudes, separated by a few to several Earth radii, and sometimes simultaneously. Here, the capability of Swarm-Cluster coordination for probing the behaviour of the field aligned currents (FACs) at medium and low orbits is explored. Joint signatures of R1 and R2 FACs (as well as cusp, R0 and NBZ currents) can be found and compared in terms of the magnetic signatures, using multi-spacecraft analysis where possible. Using the Swarm configuration, statistical correlation analysis of the local time variation of R1/R2 FACs can be shown and compared to standard MVA analysis. For context, we identify the associated auroral boundaries through application of a method to determine the FAC intensity gradients in order to interpret and resolve the R1 and R2 FACs. We also explore the relation of R2 FACs to the ring current properties measured in situ.

Shape Analysis of Planar Multiply-Connected Objects Using Conformal Welding.

PubMed

Lok Ming Lui; Wei Zeng; Shing-Tung Yau; Xianfeng Gu

2014-07-01

Shape analysis is a central problem in the field of computer vision. In 2D shape analysis, classification and recognition of objects from their observed silhouettes are extremely crucial but difficult. It usually involves an efficient representation of 2D shape space with a metric, so that its mathematical structure can be used for further analysis. Although the study of 2D simply-connected shapes has been subject to a corpus of literatures, the analysis of multiply-connected shapes is comparatively less studied. In this work, we propose a representation for general 2D multiply-connected domains with arbitrary topologies using conformal welding. A metric can be defined on the proposed representation space, which gives a metric to measure dissimilarities between objects. The main idea is to map the exterior and interior of the domain conformally to unit disks and circle domains (unit disk with several inner disks removed), using holomorphic 1-forms. A set of diffeomorphisms of the unit circle S(1) can be obtained, which together with the conformal modules are used to define the shape signature. A shape distance between shape signatures can be defined to measure dissimilarities between shapes. We prove theoretically that the proposed shape signature uniquely determines the multiply-connected objects under suitable normalization. We also introduce a reconstruction algorithm to obtain shapes from their signatures. This completes our framework and allows us to move back and forth between shapes and signatures. With that, a morphing algorithm between shapes can be developed through the interpolation of the Beltrami coefficients associated with the signatures. Experiments have been carried out on shapes extracted from real images. Results demonstrate the efficacy of our proposed algorithm as a stable shape representation scheme.

Unsupervised Bayesian linear unmixing of gene expression microarrays.

PubMed

Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O

2013-03-19

This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores collected during the study. Using a constrained model allows recovery of all the inflammatory genes in a single factor.

Is the Alzheimer's disease cortical thickness signature a biological marker for memory?

PubMed

Busovaca, Edgar; Zimmerman, Molly E; Meier, Irene B; Griffith, Erica Y; Grieve, Stuart M; Korgaonkar, Mayuresh S; Williams, Leanne M; Brickman, Adam M

2016-06-01

Recent work suggests that analysis of the cortical thickness in key brain regions can be used to identify individuals at greatest risk for development of Alzheimer's disease (AD). It is unclear to what extent this "signature" is a biological marker of normal memory function - the primary cognitive domain affected by AD. We examined the relationship between the AD signature biomarker and memory functioning in a group of neurologically healthy young and older adults. Cortical thickness measurements and neuropsychological evaluations were obtained in 110 adults (age range 21-78, mean = 46) drawn from the Brain Resource International Database. The cohort was divided into young adult (n = 64, age 21-50) and older adult (n = 46, age 51-78) groups. Cortical thickness analysis was performed with FreeSurfer, and the average cortical thickness extracted from the eight regions that comprise the AD signature. Mean AD-signature cortical thickness was positively associated with performance on the delayed free recall trial of a list learning task and this relationship did not differ between younger and older adults. Mean AD-signature cortical thickness was not associated with performance on a test of psychomotor speed, as a control task, in either group. The results suggest that the AD signature cortical thickness is a marker for memory functioning across the adult lifespan.

Security of a sessional blind signature based on quantum cryptograph

NASA Astrophysics Data System (ADS)

Wang, Tian-Yin; Cai, Xiao-Qiu; Zhang, Rui-Ling

2014-08-01

We analyze the security of a sessional blind signature protocol based on quantum cryptograph and show that there are two security leaks in this protocol. One is that the legal user Alice can change the signed message after she gets a valid blind signature from the signatory Bob, and the other is that an external opponent Eve also can forge a valid blind message by a special attack, which are not permitted for blind signature. Therefore, this protocol is not secure in the sense that it does not satisfy the non-forgeability of blind signatures. We also discuss the methods to prevent the attack strategies in the end.

Improvement of a Quantum Proxy Blind Signature Scheme

NASA Astrophysics Data System (ADS)

Zhang, Jia-Lei; Zhang, Jian-Zhong; Xie, Shu-Cui

2018-02-01

Improvement of a quantum proxy blind signature scheme is proposed in this paper. Six-qubit entangled state functions as quantum channel. In our scheme, a trust party Trent is introduced so as to avoid David's dishonest behavior. The receiver David verifies the signature with the help of Trent in our scheme. The scheme uses the physical characteristics of quantum mechanics to implement message blinding, delegation, signature and verification. Security analysis proves that our scheme has the properties of undeniability, unforgeability, anonymity and can resist some common attacks.

Improvement of a Quantum Proxy Blind Signature Scheme

NASA Astrophysics Data System (ADS)

Zhang, Jia-Lei; Zhang, Jian-Zhong; Xie, Shu-Cui

2018-06-01

Improvement of a quantum proxy blind signature scheme is proposed in this paper. Six-qubit entangled state functions as quantum channel. In our scheme, a trust party Trent is introduced so as to avoid David's dishonest behavior. The receiver David verifies the signature with the help of Trent in our scheme. The scheme uses the physical characteristics of quantum mechanics to implement message blinding, delegation, signature and verification. Security analysis proves that our scheme has the properties of undeniability, unforgeability, anonymity and can resist some common attacks.

Vibration Sensor Data Denoising Using a Time-Frequency Manifold for Machinery Fault Diagnosis

PubMed Central

He, Qingbo; Wang, Xiangxiang; Zhou, Qiang

2014-01-01

Vibration sensor data from a mechanical system are often associated with important measurement information useful for machinery fault diagnosis. However, in practice the existence of background noise makes it difficult to identify the fault signature from the sensing data. This paper introduces the time-frequency manifold (TFM) concept into sensor data denoising and proposes a novel denoising method for reliable machinery fault diagnosis. The TFM signature reflects the intrinsic time-frequency structure of a non-stationary signal. The proposed method intends to realize data denoising by synthesizing the TFM using time-frequency synthesis and phase space reconstruction (PSR) synthesis. Due to the merits of the TFM in noise suppression and resolution enhancement, the denoised signal would have satisfactory denoising effects, as well as inherent time-frequency structure keeping. Moreover, this paper presents a clustering-based statistical parameter to evaluate the proposed method, and also presents a new diagnostic approach, called frequency probability time series (FPTS) spectral analysis, to show its effectiveness in fault diagnosis. The proposed TFM-based data denoising method has been employed to deal with a set of vibration sensor data from defective bearings, and the results verify that for machinery fault diagnosis the method is superior to two traditional denoising methods. PMID:24379045

Methods for analyzing optical observations of tsunami-induced signatures in airglow emissions from ground-based and space-based platforms

NASA Astrophysics Data System (ADS)

Grawe, M.; Makela, J. J.

2016-12-01

Airglow imaging of the 630.0-nm redline emission has emerged as a useful tool for studying the properties of tsunami-ionospheric coupling in recent years, offering spatially continuous coverage of the sky with a single instrument. Past studies have shown that airglow signatures induced by tsunamis are inherently anisotropic due to the observation geometry and effects from the geomagnetic field. Here, we present details behind the techniques used to determine the parameters of the signature (orientation, wavelength, etc) with potential extensions to real or quasi-real time and a tool for interpreting the location and strength of the signatures in the field of view. We demonstrate application of the techniques to ground-based optical measurements of several tsunami-induced signatures taking place over the past five years from an imaging system in Hawaii. Additionally, these methods are extended for use on space-based observation platforms, offering advantages over ground-based installations.

A covert authentication and security solution for GMOs.

PubMed

Mueller, Siguna; Jafari, Farhad; Roth, Don

2016-09-21

Proliferation and expansion of security risks necessitates new measures to ensure authenticity and validation of GMOs. Watermarking and other cryptographic methods are available which conceal and recover the original signature, but in the process reveal the authentication information. In many scenarios watermarking and standard cryptographic methods are necessary but not sufficient and new, more advanced, cryptographic protocols are necessary. Herein, we present a new crypto protocol, that is applicable in broader settings, and embeds the authentication string indistinguishably from a random element in the signature space and the string is verified or denied without disclosing the actual signature. Results show that in a nucleotide string of 1000, the algorithm gives a correlation of 0.98 or higher between the distribution of the codon and that of E. coli, making the signature virtually invisible. This algorithm may be used to securely authenticate and validate GMOs without disclosing the actual signature. While this protocol uses watermarking, its novelty is in use of more complex cryptographic techniques based on zero knowledge proofs to encode information.

Analysis of blood-based gene expression in idiopathic Parkinson disease.

PubMed

Shamir, Ron; Klein, Christine; Amar, David; Vollstedt, Eva-Juliane; Bonin, Michael; Usenovic, Marija; Wong, Yvette C; Maver, Ales; Poths, Sven; Safer, Hershel; Corvol, Jean-Christophe; Lesage, Suzanne; Lavi, Ofer; Deuschl, Günther; Kuhlenbaeumer, Gregor; Pawlack, Heike; Ulitsky, Igor; Kasten, Meike; Riess, Olaf; Brice, Alexis; Peterlin, Borut; Krainc, Dimitri

2017-10-17

To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220 samples). Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks. A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was identified with the training cohort and successfully replicated in both an independent validation cohort (area under the curve [AUC] = 0.79, p = 7.13E-6) and a subsequent independent test cohort (AUC = 0.74, p = 4.2E-4). Network analysis of the signature revealed gene enrichment in pathways, including metabolism, oxidation, and ubiquitination/proteasomal activity, and misregulation of mitochondria-localized genes, including downregulation of COX4I1 , ATP5A1 , and VDAC3 . We present a large-scale study of PD gene expression profiling. This work identifies a reliable blood-based PD signature and highlights the importance of large-scale patient cohorts in developing potential PD biomarkers. © 2017 American Academy of Neurology.

Fruit and Juice Epigenetic Signatures Are Associated with Independent Immunoregulatory Pathways.

PubMed

Nicodemus-Johnson, Jessie; Sinnott, Robert A

2017-07-14

Epidemiological evidence strongly suggests that fruit consumption promotes many health benefits. Despite the general consensus that fruit and juice are nutritionally similar, epidemiological results for juice consumption are conflicting. Our objective was to use DNA methylation marks to characterize fruit and juice epigenetic signatures within PBMCs and identify shared and independent signatures associated with these groups. Genome-wide DNA methylation marks (Illumina Human Methylation 450k chip) for 2,148 individuals that participated in the Framingham Offspring exam 8 were analyzed for correlations between fruit or juice consumption using standard linear regression. CpG sites with low P -values ( P < 0.01) were characterized using Gene Set Enrichment Analysis (GSEA), Ingenuity Pathway Analysis (IPA), and epigenetic Functional element Overlap analysis of the Results of Genome Wide Association Study Experiments (eFORGE). Fruit and juice-specific low P -value epigenetic signatures were largely independent. Genes near the fruit-specific epigenetic signature were enriched among pathways associated with antigen presentation and chromosome or telomere maintenance, while the juice-specific epigenetic signature was enriched for proinflammatory pathways. IPA and eFORGE analyses implicate fruit and juice-specific epigenetic signatures in the modulation of macrophage (fruit) and B or T cell (juice) activities. These data suggest a role for epigenetic regulation in fruit and juice-specific health benefits and demonstrate independent associations with distinct immune functions and cell types, suggesting that these groups may not confer the same health benefits. Identification of such differences between foods is the first step toward personalized nutrition and ultimately the improvement of human health and longevity.

Fruit and Juice Epigenetic Signatures Are Associated with Independent Immunoregulatory Pathways

PubMed Central

Nicodemus-Johnson, Jessie; Sinnott, Robert A.

2017-01-01

Epidemiological evidence strongly suggests that fruit consumption promotes many health benefits. Despite the general consensus that fruit and juice are nutritionally similar, epidemiological results for juice consumption are conflicting. Our objective was to use DNA methylation marks to characterize fruit and juice epigenetic signatures within PBMCs and identify shared and independent signatures associated with these groups. Genome-wide DNA methylation marks (Illumina Human Methylation 450k chip) for 2,148 individuals that participated in the Framingham Offspring exam 8 were analyzed for correlations between fruit or juice consumption using standard linear regression. CpG sites with low P-values (P < 0.01) were characterized using Gene Set Enrichment Analysis (GSEA), Ingenuity Pathway Analysis (IPA), and epigenetic Functional element Overlap analysis of the Results of Genome Wide Association Study Experiments (eFORGE). Fruit and juice-specific low P-value epigenetic signatures were largely independent. Genes near the fruit-specific epigenetic signature were enriched among pathways associated with antigen presentation and chromosome or telomere maintenance, while the juice-specific epigenetic signature was enriched for proinflammatory pathways. IPA and eFORGE analyses implicate fruit and juice-specific epigenetic signatures in the modulation of macrophage (fruit) and B or T cell (juice) activities. These data suggest a role for epigenetic regulation in fruit and juice-specific health benefits and demonstrate independent associations with distinct immune functions and cell types, suggesting that these groups may not confer the same health benefits. Identification of such differences between foods is the first step toward personalized nutrition and ultimately the improvement of human health and longevity. PMID:28708104

Excitation-emission matrix fluorescence spectroscopy in conjunction with multiway analysis for PAH detection in complex matrices.

PubMed

Nahorniak, Michelle L; Booksh, Karl S

2006-12-01

A field portable, single exposure excitation-emission matrix (EEM) fluorometer has been constructed and used in conjunction with parallel factor analysis (PARAFAC) to determine the sub part per billion (ppb) concentrations of several aqueous polycyclic aromatic hydrocarbons (PAHs), such as benzo(k)fluoranthene and benzo(a)pyrene, in various matrices including aqueous motor oil extract and asphalt leachate. Multiway methods like PARAFAC are essential to resolve the analyte signature from the ubiquitous background in environmental samples. With multiway data and PARAFAC analysis it is shown that reliable concentration determinations can be achieved with minimal standards in spite of the large convoluting fluorescence background signal. Thus, rapid fieldable EEM analyses may prove to be a good screening method for tracking pollutants and prioritizing sampling and analysis by more complete but time consuming and labor intensive EPA methods.

Vibration Signature Analysis of a Faulted Gear Transmission System

NASA Technical Reports Server (NTRS)

Choy, F. K.; Huang, S.; Zakrajsek, J. J.; Handschuh, R. F.; Townsend, D. P.

1994-01-01

A comprehensive procedure in predicting faults in gear transmission systems under normal operating conditions is presented. Experimental data was obtained from a spiral bevel gear fatigue test rig at NASA Lewis Research Center. Time synchronous averaged vibration data was recorded throughout the test as the fault progressed from a small single pit to severe pitting over several teeth, and finally tooth fracture. A numerical procedure based on the Winger-Ville distribution was used to examine the time averaged vibration data. Results from the Wigner-Ville procedure are compared to results from a variety of signal analysis techniques which include time domain analysis methods and frequency analysis methods. Using photographs of the gear tooth at various stages of damage, the limitations and accuracy of the various techniques are compared and discussed. Conclusions are drawn from the comparison of the different approaches as well as the applicability of the Wigner-Ville method in predicting gear faults.

An Iterative Time Windowed Signature Algorithm for Time Dependent Transcription Module Discovery

PubMed Central

Meng, Jia; Gao, Shou-Jiang; Huang, Yufei

2010-01-01

An algorithm for the discovery of time varying modules using genome-wide expression data is present here. When applied to large-scale time serious data, our method is designed to discover not only the transcription modules but also their timing information, which is rarely annotated by the existing approaches. Rather than assuming commonly defined time constant transcription modules, a module is depicted as a set of genes that are co-regulated during a specific period of time, i.e., a time dependent transcription module (TDTM). A rigorous mathematical definition of TDTM is provided, which is serve as an objective function for retrieving modules. Based on the definition, an effective signature algorithm is proposed that iteratively searches the transcription modules from the time series data. The proposed method was tested on the simulated systems and applied to the human time series microarray data during Kaposi's sarcoma-associated herpesvirus (KSHV) infection. The result has been verified by Expression Analysis Systematic Explorer. PMID:21552463

Clinical and multiple gene expression variables in survival analysis of breast cancer: Analysis with the hypertabastic survival model

PubMed Central

2012-01-01

Background We explore the benefits of applying a new proportional hazard model to analyze survival of breast cancer patients. As a parametric model, the hypertabastic survival model offers a closer fit to experimental data than Cox regression, and furthermore provides explicit survival and hazard functions which can be used as additional tools in the survival analysis. In addition, one of our main concerns is utilization of multiple gene expression variables. Our analysis treats the important issue of interaction of different gene signatures in the survival analysis. Methods The hypertabastic proportional hazards model was applied in survival analysis of breast cancer patients. This model was compared, using statistical measures of goodness of fit, with models based on the semi-parametric Cox proportional hazards model and the parametric log-logistic and Weibull models. The explicit functions for hazard and survival were then used to analyze the dynamic behavior of hazard and survival functions. Results The hypertabastic model provided the best fit among all the models considered. Use of multiple gene expression variables also provided a considerable improvement in the goodness of fit of the model, as compared to use of only one. By utilizing the explicit survival and hazard functions provided by the model, we were able to determine the magnitude of the maximum rate of increase in hazard, and the maximum rate of decrease in survival, as well as the times when these occurred. We explore the influence of each gene expression variable on these extrema. Furthermore, in the cases of continuous gene expression variables, represented by a measure of correlation, we were able to investigate the dynamics with respect to changes in gene expression. Conclusions We observed that use of three different gene signatures in the model provided a greater combined effect and allowed us to assess the relative importance of each in determination of outcome in this data set. These results point to the potential to combine gene signatures to a greater effect in cases where each gene signature represents some distinct aspect of the cancer biology. Furthermore we conclude that the hypertabastic survival models can be an effective survival analysis tool for breast cancer patients. PMID:23241496

Multivariate Protein Signatures of Pre-Clinical Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative (ADNI) Plasma Proteome Dataset

PubMed Central

Johnstone, Daniel; Milward, Elizabeth A.; Berretta, Regina; Moscato, Pablo

2012-01-01

Background Recent Alzheimer's disease (AD) research has focused on finding biomarkers to identify disease at the pre-clinical stage of mild cognitive impairment (MCI), allowing treatment to be initiated before irreversible damage occurs. Many studies have examined brain imaging or cerebrospinal fluid but there is also growing interest in blood biomarkers. The Alzheimer's Disease Neuroimaging Initiative (ADNI) has generated data on 190 plasma analytes in 566 individuals with MCI, AD or normal cognition. We conducted independent analyses of this dataset to identify plasma protein signatures predicting pre-clinical AD. Methods and Findings We focused on identifying signatures that discriminate cognitively normal controls (n = 54) from individuals with MCI who subsequently progress to AD (n = 163). Based on p value, apolipoprotein E (APOE) showed the strongest difference between these groups (p = 2.3×10−13). We applied a multivariate approach based on combinatorial optimization ((α,β)-k Feature Set Selection), which retains information about individual participants and maintains the context of interrelationships between different analytes, to identify the optimal set of analytes (signature) to discriminate these two groups. We identified 11-analyte signatures achieving values of sensitivity and specificity between 65% and 86% for both MCI and AD groups, depending on whether APOE was included and other factors. Classification accuracy was improved by considering “meta-features,” representing the difference in relative abundance of two analytes, with an 8-meta-feature signature consistently achieving sensitivity and specificity both over 85%. Generating signatures based on longitudinal rather than cross-sectional data further improved classification accuracy, returning sensitivities and specificities of approximately 90%. Conclusions Applying these novel analysis approaches to the powerful and well-characterized ADNI dataset has identified sets of plasma biomarkers for pre-clinical AD. While studies of independent test sets are required to validate the signatures, these analyses provide a starting point for developing a cost-effective and minimally invasive test capable of diagnosing AD in its pre-clinical stages. PMID:22485168

CFD Predictions of Sonic-Boom Characteristics for Unmodified and Modified SR-71 Configurations

NASA Technical Reports Server (NTRS)

Fouladi, Kamran

1999-01-01

Shaped sonic-boom signatures refer to signatures that look something other than the typical N-waves. Shaped sonic-boom signatures such as "flat-top," "ramp-type," or "hybrid-type" waveforms have been shown to reduce the subjective loudness without requiring reductions in overpressure peaks. The shaping of sonic-boom signatures requires increasing the shock rise time and changes in frequency spectra. So far, a flat-top waveform was shown to be achievable in wind tunnels; however, the influence of long propagation distance and real atmosphere on shaped signatures should be addressed using flight tests. Two different approaches have been proposed for sonic-boom minimization flight tests. The first approach, proposed by Eagle Aerospace, is for a flight test using a modified BQM-34 "FIREBEE" remotely piloted vehicle. The 30-foot long FIREBEE has a steady state flight condition at the Mach number and altitude of interest, and it can be recovered by helicopter from the water. As an alternative approach, a modified SR-71 vehicle has been proposed by the McDonnell Douglas Corporation. Benefits of the SR-71 include its variable geometry supersonic inlets, small cockpit bulge, higher Mach number capabilities, slender design, and longer length (105 foot). The present investigation addresses the sonic-boom analysis for the second vehicle.The objective of the current investigation is to assess the feasibility of a modified SR-71 configuration, with McDonnell Douglas-designed fuselage modifications, intended to produce shaped sonic-boom signatures on the ground. The present study describes the use of a higher-order computational fluid dynamics (CFD) method to predict the sonic-boom characteristics for both unmodified and modified SR-71 configurations. An Euler unstructured grid methodology is used to predict the near-field, three-dimensional pressure patterns generated by both SR-71 models. The computed near-field pressure signatures are extrapolated to specified distances below the aircraft down to impingement on the ground using the code MDBOOM. Comparisons of the near-field pressure signatures with available flight-test data are presented in the current paper.

Direct modeling parameter signature analysis and failure mode prediction of physical systems using hybrid computer optimization

NASA Technical Reports Server (NTRS)

Drake, R. L.; Duvoisin, P. F.; Asthana, A.; Mather, T. W.

1971-01-01

High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.

Search for Electronic Recoil Event Rate Modulation with 4 Years of XENON100 Data

NASA Astrophysics Data System (ADS)

Aprile, E.; Aalbers, J.; Agostini, F.; Alfonsi, M.; Amaro, F. D.; Anthony, M.; Arneodo, F.; Barrow, P.; Baudis, L.; Bauermeister, B.; Benabderrahmane, M. L.; Berger, T.; Breur, P. A.; Brown, A.; Brown, E.; Bruenner, S.; Bruno, G.; Budnik, R.; Bütikofer, L.; Calvén, J.; Cardoso, J. M. R.; Cervantes, M.; Cichon, D.; Coderre, D.; Colijn, A. P.; Conrad, J.; Cussonneau, J. P.; Decowski, M. P.; de Perio, P.; di Gangi, P.; di Giovanni, A.; Diglio, S.; Eurin, G.; Fei, J.; Ferella, A. D.; Fieguth, A.; Franco, D.; Fulgione, W.; Gallo Rosso, A.; Galloway, M.; Gao, F.; Garbini, M.; Geis, C.; Goetzke, L. W.; Greene, Z.; Grignon, C.; Hasterok, C.; Hogenbirk, E.; Itay, R.; Kaminsky, B.; Kessler, G.; Kish, A.; Landsman, H.; Lang, R. F.; Lellouch, D.; Levinson, L.; Lin, Q.; Lindemann, S.; Lindner, M.; Lopes, J. A. M.; Manfredini, A.; Maris, I.; Marrodán Undagoitia, T.; Masbou, J.; Massoli, F. V.; Masson, D.; Mayani, D.; Messina, M.; Micheneau, K.; Miguez, B.; Molinario, A.; Murra, M.; Naganoma, J.; Ni, K.; Oberlack, U.; Pakarha, P.; Pelssers, B.; Persiani, R.; Piastra, F.; Pienaar, J.; Pizzella, V.; Piro, M.-C.; Plante, G.; Priel, N.; Rauch, L.; Reichard, S.; Reuter, C.; Rizzo, A.; Rosendahl, S.; Rupp, N.; Dos Santos, J. M. F.; Sartorelli, G.; Scheibelhut, M.; Schindler, S.; Schreiner, J.; Schumann, M.; Scotto Lavina, L.; Selvi, M.; Shagin, P.; Silva, M.; Simgen, H.; Sivers, M. V.; Stein, A.; Thers, D.; Tiseni, A.; Trinchero, G.; Tunnell, C.; Wang, H.; Wei, Y.; Weinheimer, C.; Wulf, J.; Ye, J.; Zhang, Y.; Xenon Collaboration

2017-03-01

We report on a search for electronic recoil event rate modulation signatures in the XENON100 data accumulated over a period of 4 yr, from January 2010 to January 2014. A profile likelihood method, which incorporates the stability of the XENON100 detector and the known electronic recoil background model, is used to quantify the significance of periodicity in the time distribution of events. There is a weak modulation signature at a period of 43 1-14+16 day in the low energy region of (2.0-5.8) keV in the single scatter event sample, with a global significance of 1.9 σ ; however, no other more significant modulation is observed. The significance of an annual modulation signature drops from 2.8 σ , from a previous analysis of a subset of this data, to 1.8 σ with all data combined. Single scatter events in the low energy region are thus used to exclude the DAMA/LIBRA annual modulation as being due to dark matter electron interactions via axial vector coupling at 5.7 σ .

Investigating isotopic signatures of atmospheric nitrous acid (HONO)

NASA Astrophysics Data System (ADS)

Chai, J.; Miller, D. J.; Hastings, M. G.

2016-12-01

Nitrous acid (HONO) is an important reactive nitrogen species that can be easily photolyzed to nitrogen oxide and hydroxyl radical in the troposphere. HONO greatly influences atmospheric oxidation capacity, affecting the formation of tropospheric ozone (O3) and secondary aerosol. Recent studies have indicated that in addition to heterogeneous NOx reactions, biomass burning, soil emission and photolysis of nitric acid (HNO3) on surfaces (e.g. aerosol particles and soot) are also important sources of HONO. However, these sources have not yet been well constrained. The stable isotope ratios in nitrate have been successfully used to trace NOx sources and oxidation chemistry in the atmosphere. Can the isotopic signatures of HONO be used to trace NOx oxidation and renoxification pathways? For this purpose, we have built an annular denuder HONO collection system for the stable isotope study of HONO. Preliminary tests show successful collection and recovery of HONO synthesized in our lab. Nitrogen and oxygen isotopic analysis of the recovered HONO also shows consistent isotopic signatures. Results from field applications of this method in near road and on road environments, agricultural settings, and laboratory based biomass burns will be presented.

Theoretical Characterizaiton of Visual Signatures

NASA Astrophysics Data System (ADS)

Kashinski, D. O.; Chase, G. M.; di Nallo, O. E.; Scales, A. N.; Vanderley, D. L.; Byrd, E. F. C.

2015-05-01

We are investigating the accuracy of theoretical models used to predict the visible, ultraviolet, and infrared spectra, as well as other properties, of product materials ejected from the muzzle of currently fielded systems. Recent advances in solid propellants has made the management of muzzle signature (flash) a principle issue in weapons development across the calibers. A priori prediction of the electromagnetic spectra of formulations will allow researchers to tailor blends that yield desired signatures and determine spectrographic detection ranges. Quantum chemistry methods at various levels of sophistication have been employed to optimize molecular geometries, compute unscaled vibrational frequencies, and determine the optical spectra of specific gas-phase species. Electronic excitations are being computed using Time Dependent Density Functional Theory (TD-DFT). A full statistical analysis and reliability assessment of computational results is currently underway. A comparison of theoretical results to experimental values found in the literature is used to assess any affects of functional choice and basis set on calculation accuracy. The status of this work will be presented at the conference. Work supported by the ARL, DoD HPCMP, and USMA.

Compound-Specific Isotope Analysis of Amino Acids for Stardust-Returned Samples

NASA Technical Reports Server (NTRS)

Cook, Jamie; Elsila, Jamie E.; Stern J. C.; Glavin, D. P.; Dworkin, J. P.

2008-01-01

Significant portions of the early Earth's prebiotic organic inventory , including amino acids, could have been delivered to the Earth's sur face by comets and their fragments. Analysis of comets via spectrosc opic observations has identified many organic molecules, including me thane, ethane, arnmonia, cyanic acid, formaldehyde, formamide, acetal ehyde, acetonitrile, and methanol. Reactions between these identifie d molecules could allow the formation of more complex organics such a s amino acids. Isotopic analysis could reveal whether an extraterrest rial signature is present in the Stardust-exposed amines and amino ac ids. Although bulk isotopic analysis would be dominated by the EACA contaminant's terrestrial signature, compoundspecific isotope analysi s (CSIA) could determine the signature of each of the other individua l amines. Here, we report on progress made towards CSIA of the amino acids glycine and EACA in Stardustreturned samples.

Suspect Screening Analysis of Chemicals in Consumer Products.

PubMed

Phillips, Katherine A; Yau, Alice; Favela, Kristin A; Isaacs, Kristin K; McEachran, Andrew; Grulke, Christopher; Richard, Ann M; Williams, Antony J; Sobus, Jon R; Thomas, Russell S; Wambaugh, John F

2018-03-06

A two-dimensional gas chromatography-time-of-flight/mass spectrometry (GC×GC-TOF/MS) suspect screening analysis method was used to rapidly characterize chemicals in 100 consumer products-which included formulations (e.g., shampoos, paints), articles (e.g., upholsteries, shower curtains), and foods (cereals)-and therefore supports broader efforts to prioritize chemicals based on potential human health risks. Analyses yielded 4270 unique chemical signatures across the products, with 1602 signatures tentatively identified using the National Institute of Standards and Technology 2008 spectral database. Chemical standards confirmed the presence of 119 compounds. Of the 1602 tentatively identified chemicals, 1404 were not present in a public database of known consumer product chemicals. Reported data and model predictions of chemical functional use were applied to evaluate the tentative chemical identifications. Estimated chemical concentrations were compared to manufacturer-reported values and other measured data. Chemical presence and concentration data can now be used to improve estimates of chemical exposure, and refine estimates of risk posed to human health and the environment.

Computer-aided, multi-modal, and compression diffuse optical studies of breast tissue

NASA Astrophysics Data System (ADS)

Busch, David Richard, Jr.

Diffuse Optical Tomography and Spectroscopy permit measurement of important physiological parameters non-invasively through ˜10 cm of tissue. I have applied these techniques in measurements of human breast and breast cancer. My thesis integrates three loosely connected themes in this context: multi-modal breast cancer imaging, automated data analysis of breast cancer images, and microvascular hemodynamics of breast under compression. As per the first theme, I describe construction, testing, and the initial clinical usage of two generations of imaging systems for simultaneous diffuse optical and magnetic resonance imaging. The second project develops a statistical analysis of optical breast data from many spatial locations in a population of cancers to derive a novel optical signature of malignancy; I then apply this data-derived signature for localization of cancer in additional subjects. Finally, I construct and deploy diffuse optical instrumentation to measure blood content and blood flow during breast compression; besides optics, this research has implications for any method employing breast compression, e.g., mammography.

Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemia.

PubMed

Giustacchini, Alice; Thongjuea, Supat; Barkas, Nikolaos; Woll, Petter S; Povinelli, Benjamin J; Booth, Christopher A G; Sopp, Paul; Norfo, Ruggiero; Rodriguez-Meira, Alba; Ashley, Neil; Jamieson, Lauren; Vyas, Paresh; Anderson, Kristina; Segerstolpe, Åsa; Qian, Hong; Olsson-Strömberg, Ulla; Mustjoki, Satu; Sandberg, Rickard; Jacobsen, Sten Eirik W; Mead, Adam J

2017-06-01

Recent advances in single-cell transcriptomics are ideally placed to unravel intratumoral heterogeneity and selective resistance of cancer stem cell (SC) subpopulations to molecularly targeted cancer therapies. However, current single-cell RNA-sequencing approaches lack the sensitivity required to reliably detect somatic mutations. We developed a method that combines high-sensitivity mutation detection with whole-transcriptome analysis of the same single cell. We applied this technique to analyze more than 2,000 SCs from patients with chronic myeloid leukemia (CML) throughout the disease course, revealing heterogeneity of CML-SCs, including the identification of a subgroup of CML-SCs with a distinct molecular signature that selectively persisted during prolonged therapy. Analysis of nonleukemic SCs from patients with CML also provided new insights into cell-extrinsic disruption of hematopoiesis in CML associated with clinical outcome. Furthermore, we used this single-cell approach to identify a blast-crisis-specific SC population, which was also present in a subclone of CML-SCs during the chronic phase in a patient who subsequently developed blast crisis. This approach, which might be broadly applied to any malignancy, illustrates how single-cell analysis can identify subpopulations of therapy-resistant SCs that are not apparent through cell-population analysis.

Signature-based store checking buffer

DOEpatents

Sridharan, Vilas; Gurumurthi, Sudhanva

2015-06-02

A system and method for optimizing redundant output verification, are provided. A hardware-based store fingerprint buffer receives multiple instances of output from multiple instances of computation. The store fingerprint buffer generates a signature from the content included in the multiple instances of output. When a barrier is reached, the store fingerprint buffer uses the signature to verify the content is error-free.

A Sense of Embodiment Is Reflected in People's Signature Size

PubMed Central

Rawal, Adhip; Harmer, Catherine J.; Park, Rebecca J.; O'Sullivan, Ursula D.; Williams, J. Mark G.

2014-01-01

Background The size of a person's signature may reveal implicit information about how the self is perceived although this has not been closely examined. Methods/Results We conducted three experiments to test whether increases in signature size can be induced. Specifically, the aim of these experiments was to test whether changes in signature size reflect a person's current implicit sense of embodiment. Experiment 1 showed that an implicit affect task (positive subliminal evaluative conditioning) led to increases in signature size relative to an affectively neutral task, showing that implicit affective cues alter signature size. Experiments 2 and 3 demonstrated increases in signature size following experiential self-focus on sensory and affective stimuli relative to both conceptual self-focus and external (non-self-focus) in both healthy participants and patients with anorexia nervosa, a disorder associated with self-evaluation and a sense of disembodiment. In all three experiments, increases in signature size were unrelated to changes in self-reported mood and larger than manipulation unrelated variations. Conclusions Together, these findings suggest that a person's sense of embodiment is reflected in their signature size. PMID:24533088

[Molecular characterization of breast cancer in clinical practice].

PubMed

Zemmouri, Y; De Croze, D; Vincent Salomon, A; Rouzier, R; Bonneau, C

2016-05-01

Breast cancer involves various types of tumors. The objective of this review was to provide a summary of the main methods currently available in clinical practice to characterize breast cancers at a molecular level and to discuss their prognostic and predictive values. Hormonal receptors expression and the HER2 status are prognostic markers and can also predict the response to targeted therapies. Their analysis through immunohistochemistry is systematical. Ki67 is an effective prognostic marker, but its reliability is debated because of its low reproducibility between laboratories and between pathologists. Commercial genomic signatures are all considered valid prognostic tools and may guide physicians to make therapeutic choices. These signatures are costly and should therefore be restricted to situations in which the use of chemotherapy remains equivocal. Copyright © 2016. Published by Elsevier SAS.

Method and device for identifying different species of honeybees

DOEpatents

Kerr, Howard T.; Buchanan, Michael E.; Valentine, Kenneth H.

1989-01-01

A method and device have been provided for distinguishing Africanized honeybees from European honeybees. The method is based on the discovery of a distinct difference in the acoustical signatures of these two species of honeybees in flight. The European honeybee signature has a fundamental power peak in the 210 to 240 Hz range while the Africanized honeybee signature has a fundamental power peak in the 260 to 290 Hz range. The acoustic signal produced by honeybees is analyzed by means of a detecting device to quickly determine the honeybee species through the detection of the presence of frequencies in one of these distinct ranges. The device includes a microphone for acoustical signal detection which feeds the detected signal into a frequency analyzer which is designed to detect the presence of either of the known fundamental wingbeat frequencies unique to the acoustical signatures of these species as an indication of the identity of the species and indicate the species identity on a readout device.

Signatures of positive selection in East African Shorthorn Zebu: a genome-wide SNP analysis

USDA-ARS?s Scientific Manuscript database

The small East African Shorthorn Zebu is the main indigenous cattle across East Africa. A recent genome wide SNPs analysis has revealed their ancient stable African taurine x Asian zebu admixture. Here, we assess the presence of candidate signature of positive selection in their genome, with the aim...

Non-Linear Acoustic Concealed Weapons Detector

DTIC Science & Technology

2006-05-01

signature analysis 8 the interactions of the beams with concealed objects. The Khokhlov- Zabolotskaya-Kuznetsov ( KZK ) equation is the most widely used...Hamilton developed a finite difference method based on the KZK equation to model pulsed acoustic emissions from axial symmetric sources. Using a...College of William & Mary, we have developed a simulation code using the KZK equation to model non-linear acoustic beams and visualize beam patterns

Basic principles, methodology, and applications of remote sensing in agriculture

NASA Technical Reports Server (NTRS)

Moreira, M. A. (Principal Investigator); Deassuncao, G. V.

1984-01-01

The basic principles of remote sensing applied to agriculture and the methods used in data analysis are described. Emphasis is placed on the importance of developing a methodology that may help crop forecast, basic concepts of spectral signatures of vegetation, the methodology of the LANDSAT data utilization in agriculture, and the remote sensing program application of INPE (Institute for Space Research) in agriculture.

Laser Capture Microdissection Assisted Identification of Epithelial MicroRNA Expression Signatures for Prognosis of Stage I NSCLC

DTIC Science & Technology

2011-10-01

SiC  relativ stains (B) are p tandard error 0 ng of RN on of a muc , a finding s measured crease in t dissection l, given tha of total RN ummary o...the yield and quality of microRNAs from LMD microdissectates of FFPE tissues for downstream analysis. Materials and Methods Ethics statement

Modeling the Lexical Morphology of Western Handwritten Signatures

PubMed Central

Diaz-Cabrera, Moises; Ferrer, Miguel A.; Morales, Aythami

2015-01-01

A handwritten signature is the final response to a complex cognitive and neuromuscular process which is the result of the learning process. Because of the many factors involved in signing, it is possible to study the signature from many points of view: graphologists, forensic experts, neurologists and computer vision experts have all examined them. Researchers study written signatures for psychiatric, penal, health and automatic verification purposes. As a potentially useful, multi-purpose study, this paper is focused on the lexical morphology of handwritten signatures. This we understand to mean the identification, analysis, and description of the signature structures of a given signer. In this work we analyze different public datasets involving 1533 signers from different Western geographical areas. Some relevant characteristics of signature lexical morphology have been selected, examined in terms of their probability distribution functions and modeled through a General Extreme Value distribution. This study suggests some useful models for multi-disciplinary sciences which depend on handwriting signatures. PMID:25860942

Public-key quantum digital signature scheme with one-time pad private-key

NASA Astrophysics Data System (ADS)

Chen, Feng-Lin; Liu, Wan-Fang; Chen, Su-Gen; Wang, Zhi-Hua

2018-01-01

A quantum digital signature scheme is firstly proposed based on public-key quantum cryptosystem. In the scheme, the verification public-key is derived from the signer's identity information (such as e-mail) on the foundation of identity-based encryption, and the signature private-key is generated by one-time pad (OTP) protocol. The public-key and private-key pair belongs to classical bits, but the signature cipher belongs to quantum qubits. After the signer announces the public-key and generates the final quantum signature, each verifier can verify publicly whether the signature is valid or not with the public-key and quantum digital digest. Analysis results show that the proposed scheme satisfies non-repudiation and unforgeability. Information-theoretic security of the scheme is ensured by quantum indistinguishability mechanics and OTP protocol. Based on the public-key cryptosystem, the proposed scheme is easier to be realized compared with other quantum signature schemes under current technical conditions.

Degradation and Volatilization of Chlorofluorocarbons in Contaminated Groundwater Explored by Stable Carbon Isotope Analysis

NASA Astrophysics Data System (ADS)

Horst, A.; Lacrampe-Couloume, G.; Sherwood Lollar, B.

2015-12-01

Chlorofluorocarbons (CFCs) are ozone depleting compounds whose production was phased out by the regulations of the Montreal Protocol (1987). Accidental release and disposal also led to contamination of groundwater at many locations, however, and this legacy persists. Although very stable, CFCs may degrade via abiotic and biotic pathways. Quantification of the degree of transformation of CFCs has been challenging due to other processes such as dilution, sorption and volatilization. Compound specific stable carbon isotope analysis (CSIA) has been successfully applied for a variety of priority pollutants to distinguish degradation from other processes and to quantify transformation rates. A Purge & Trap - CSIA method developed in our lab was applied to determine the stable carbon isotopic signature of CFCs and HCFCs (hydrochlorofluorocarbons) in groundwater samples from a contaminated site. Preliminary results suggest that degradation of CFCs and HCFCs may result in enriched δ13C values, consistent with fractionation during bond breakage as has been reported for many other hydrocarbon pollutants. The effect of volatile loss during sampling on the isotopic signatures of CFCs was examined in laboratory experiments. Volatilization from pure phase CFCs showed a small inverse isotope effect during open system volatilization, opposite to the normal isotope effect generally observed during biodegradation. For volatilization of CFCs dissolved in water a much smaller isotope effect was observed. An important result from this work is that any volatile loss may introduce only a small change in CFC isotopic signatures in groundwater, and importantly, due to the opposite direction of isotope effects associated with volatilization versus degradation, any effects of volatile loss on the isotopic signatures cannot be confused with transformation of CFCs. At most, volatilization might contribute to a conservative estimate of the extent of degradation.

Signatures of tumour immunity distinguish Asian and non-Asian gastric adenocarcinomas

PubMed Central

Lin, Suling J; Gagnon-Bartsch, Johann A; Tan, Iain Beehuat; Earle, Sophie; Ruff, Louise; Pettinger, Katherine; Ylstra, Bauke; van Grieken, Nicole; Rha, Sun Young; Chung, Hyun Cheol; Lee, Ju-Seog; Cheong, Jae Ho; Noh, Sung Hoon; Aoyama, Toru; Miyagi, Yohei; Tsuburaya, Akira; Yoshikawa, Takaki; Ajani, Jaffer A; Boussioutas, Alex; Yeoh, Khay Guan; Yong, Wei Peng; So, Jimmy; Lee, Jeeyun; Kang, Won Ki; Kim, Sung; Kameda, Yoichi; Arai, Tomio; zur Hausen, Axel; Speed, Terence P; Grabsch, Heike I; Tan, Patrick

2015-01-01

Objective Differences in gastric cancer (GC) clinical outcomes between patients in Asian and non-Asian countries has been historically attributed to variability in clinical management. However, recent international Phase III trials suggest that even with standardised treatments, GC outcomes differ by geography. Here, we investigated gene expression differences between Asian and non-Asian GCs, and if these molecular differences might influence clinical outcome. Design We compared gene expression profiles of 1016 GCs from six Asian and three non-Asian GC cohorts, using a two-stage meta-analysis design and a novel biostatistical method (RUV-4) to adjust for technical variation between cohorts. We further validated our findings by computerised immunohistochemical analysis on two independent tissue microarray (TMA) cohorts from Asian and non-Asian localities (n=665). Results Gene signatures differentially expressed between Asians and non-Asian GCs were related to immune function and inflammation. Non-Asian GCs were significantly enriched in signatures related to T-cell biology, including CTLA-4 signalling. Similarly, in the TMA cohorts, non-Asian GCs showed significantly higher expression of T-cell markers (CD3, CD45R0, CD8) and lower expression of the immunosuppressive T-regulatory cell marker FOXP3 compared to Asian GCs (p<0.05). Inflammatory cell markers CD66b and CD68 also exhibited significant cohort differences (p<0.05). Exploratory analyses revealed a significant relationship between tumour immunity factors, geographic locality-specific prognosis, and postchemotherapy outcomes. Conclusions Analyses of >1600 GCs suggest that Asian and non-Asian GCs exhibit distinct tumour immunity signatures related to T-cell function. These differences may influence geographical differences in clinical outcome, and the design of future trials particularly in immuno-oncology. PMID:25385008

ARMOR Dual-Polarimetric Radar Observations of Tornadic Debris Signatures

NASA Technical Reports Server (NTRS)

Petersen, W. A,; Carey, L. D.; Knupp, K. R.; Schultz, C.; Johnson, E.

2008-01-01

During the Super-Tuesday tornado outbreak of 5-6 February 2008, two EF-4 tornadoes occurred in Northern Alabama within 75 km range of the University of Alabama in Huntsville (UAH) Advanced Radar for Meteorological and Operational Research (ARMOR, C-band dual-polarimetric). This study will present an analysis of ARMOR radar-indicated dual-polarimetric tornadic debris signatures. The debris signatures were associated with spatially-confined large decreases in the copolar correlation coefficient (rho(hv)hv) that were embedded within broader mesocyclone "hook" signatures. These debris signatures were most obviously manifest during the F-3 to F-4 intensity stages of the tornado(s) and extended to altitudes of approximately 3 km. The rho(hv) signatures of the tornadic debris were the most easily distinguished relative to other polarimetric and radial velocity parameters (e.g., associated with large hail and/or the incipient mesocyclone). Based on our analysis, and consistent with the small number of studies found in the literature, we conclude that dual-polarimetric radar data offer at least the possibility for enhancing specificity and confidence in the process of issuing tornado warnings based only on radar detection of threatening circulation features.

Uncertainty in hydrological signatures

NASA Astrophysics Data System (ADS)

McMillan, Hilary; Westerberg, Ida

2015-04-01

Information that summarises the hydrological behaviour or flow regime of a catchment is essential for comparing responses of different catchments to understand catchment organisation and similarity, and for many other modelling and water-management applications. Such information types derived as an index value from observed data are known as hydrological signatures, and can include descriptors of high flows (e.g. mean annual flood), low flows (e.g. mean annual low flow, recession shape), the flow variability, flow duration curve, and runoff ratio. Because the hydrological signatures are calculated from observed data such as rainfall and flow records, they are affected by uncertainty in those data. Subjective choices in the method used to calculate the signatures create a further source of uncertainty. Uncertainties in the signatures may affect our ability to compare different locations, to detect changes, or to compare future water resource management scenarios. The aim of this study was to contribute to the hydrological community's awareness and knowledge of data uncertainty in hydrological signatures, including typical sources, magnitude and methods for its assessment. We proposed a generally applicable method to calculate these uncertainties based on Monte Carlo sampling and demonstrated it for a variety of commonly used signatures. The study was made for two data rich catchments, the 50 km2 Mahurangi catchment in New Zealand and the 135 km2 Brue catchment in the UK. For rainfall data the uncertainty sources included point measurement uncertainty, the number of gauges used in calculation of the catchment spatial average, and uncertainties relating to lack of quality control. For flow data the uncertainty sources included uncertainties in stage/discharge measurement and in the approximation of the true stage-discharge relation by a rating curve. The resulting uncertainties were compared across the different signatures and catchments, to quantify uncertainty magnitude and bias, and to test how uncertainty depended on the density of the raingauge network and flow gauging station characteristics. The uncertainties were sometimes large (i.e. typical intervals of ±10-40% relative uncertainty) and highly variable between signatures. Uncertainty in the mean discharge was around ±10% for both catchments, while signatures describing the flow variability had much higher uncertainties in the Mahurangi where there was a fast rainfall-runoff response and greater high-flow rating uncertainty. Event and total runoff ratios had uncertainties from ±10% to ±15% depending on the number of rain gauges used; precipitation uncertainty was related to interpolation rather than point uncertainty. Uncertainty distributions in these signatures were skewed, and meant that differences in signature values between these catchments were often not significant. We hope that this study encourages others to use signatures in a way that is robust to data uncertainty.

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tholouli, Eleni; MacDermott, Sarah; Hoyland, Judith

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection inmore » archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.« less

A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions

PubMed Central

Iorio, Francesco; Shrestha, Roshan L.; Levin, Nicolas; Boilot, Viviane; Garnett, Mathew J.; Saez-Rodriguez, Julio; Draviam, Viji M.

2015-01-01

We present a novel strategy to identify drug-repositioning opportunities. The starting point of our method is the generation of a signature summarising the consensual transcriptional response of multiple human cell lines to a compound of interest (namely the seed compound). This signature can be derived from data in existing databases, such as the connectivity-map, and it is used at first instance to query a network interlinking all the connectivity-map compounds, based on the similarity of their transcriptional responses. This provides a drug neighbourhood, composed of compounds predicted to share some effects with the seed one. The original signature is then refined by systematically reducing its overlap with the transcriptional responses induced by drugs in this neighbourhood that are known to share a secondary effect with the seed compound. Finally, the drug network is queried again with the resulting refined signatures and the whole process is carried on for a number of iterations. Drugs in the final refined neighbourhood are then predicted to exert the principal mode of action of the seed compound. We illustrate our approach using paclitaxel (a microtubule stabilising agent) as seed compound. Our method predicts that glipizide and splitomicin perturb microtubule function in human cells: a result that could not be obtained through standard signature matching methods. In agreement, we find that glipizide and splitomicin reduce interphase microtubule growth rates and transiently increase the percentage of mitotic cells–consistent with our prediction. Finally, we validated the refined signatures of paclitaxel response by mining a large drug screening dataset, showing that human cancer cell lines whose basal transcriptional profile is anti-correlated to them are significantly more sensitive to paclitaxel and docetaxel. PMID:26452147

Case Writing as a Signature Pedagogy in Education Leadership

ERIC Educational Resources Information Center

Meyer, Heinz-Dieter; Shannon, Brenda

2010-01-01

Purpose: The purpose of this paper is to propose, as a candidate for a signature pedagogy, a method centered on case writing and peer review. Design/methodology/approach: In this method, aspiring education leaders use the writing of case studies--frequently featuring themselves as an actor in a narrative of organizational development or change--to…

36 CFR 218.8 - Filing an objection.

Code of Federal Regulations, 2014 CFR

2014-07-01

...) Signature or other verification of authorship upon request (a scanned signature for electronic mail may be... related to the proposed project; if applicable, how the objector believes the environmental analysis or...

36 CFR 218.8 - Filing an objection.

Code of Federal Regulations, 2013 CFR

2013-07-01

...) Signature or other verification of authorship upon request (a scanned signature for electronic mail may be... related to the proposed project; if applicable, how the objector believes the environmental analysis or...

Nuclear Forensic Inferences Using Iterative Multidimensional Statistics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robel, M; Kristo, M J; Heller, M A

2009-06-09

Nuclear forensics involves the analysis of interdicted nuclear material for specific material characteristics (referred to as 'signatures') that imply specific geographical locations, production processes, culprit intentions, etc. Predictive signatures rely on expert knowledge of physics, chemistry, and engineering to develop inferences from these material characteristics. Comparative signatures, on the other hand, rely on comparison of the material characteristics of the interdicted sample (the 'questioned sample' in FBI parlance) with those of a set of known samples. In the ideal case, the set of known samples would be a comprehensive nuclear forensics database, a database which does not currently exist. Inmore » fact, our ability to analyze interdicted samples and produce an extensive list of precise materials characteristics far exceeds our ability to interpret the results. Therefore, as we seek to develop the extensive databases necessary for nuclear forensics, we must also develop the methods necessary to produce the necessary inferences from comparison of our analytical results with these large, multidimensional sets of data. In the work reported here, we used a large, multidimensional dataset of results from quality control analyses of uranium ore concentrate (UOC, sometimes called 'yellowcake'). We have found that traditional multidimensional techniques, such as principal components analysis (PCA), are especially useful for understanding such datasets and drawing relevant conclusions. In particular, we have developed an iterative partial least squares-discriminant analysis (PLS-DA) procedure that has proven especially adept at identifying the production location of unknown UOC samples. By removing classes which fell far outside the initial decision boundary, and then rebuilding the PLS-DA model, we have consistently produced better and more definitive attributions than with a single pass classification approach. Performance of the iterative PLS-DA method compared favorably to that of classification and regression tree (CART) and k nearest neighbor (KNN) algorithms, with the best combination of accuracy and robustness, as tested by classifying samples measured independently in our laboratories against the vendor QC based reference set.« less

The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression.

PubMed

Catto, James W F; Abbod, Maysam F; Wild, Peter J; Linkens, Derek A; Pilarsky, Christian; Rehman, Ishtiaq; Rosario, Derek J; Denzinger, Stefan; Burger, Maximilian; Stoehr, Robert; Knuechel, Ruth; Hartmann, Arndt; Hamdy, Freddie C

2010-03-01

New methods for identifying bladder cancer (BCa) progression are required. Gene expression microarrays can reveal insights into disease biology and identify novel biomarkers. However, these experiments produce large datasets that are difficult to interpret. To develop a novel method of microarray analysis combining two forms of artificial intelligence (AI): neurofuzzy modelling (NFM) and artificial neural networks (ANN) and validate it in a BCa cohort. We used AI and statistical analyses to identify progression-related genes in a microarray dataset (n=66 tumours, n=2800 genes). The AI-selected genes were then investigated in a second cohort (n=262 tumours) using immunohistochemistry. We compared the accuracy of AI and statistical approaches to identify tumour progression. AI identified 11 progression-associated genes (odds ratio [OR]: 0.70; 95% confidence interval [CI], 0.56-0.87; p=0.0004), and these were more discriminate than genes chosen using statistical analyses (OR: 1.24; 95% CI, 0.96-1.60; p=0.09). The expression of six AI-selected genes (LIG3, FAS, KRT18, ICAM1, DSG2, and BRCA2) was determined using commercial antibodies and successfully identified tumour progression (concordance index: 0.66; log-rank test: p=0.01). AI-selected genes were more discriminate than pathologic criteria at determining progression (Cox multivariate analysis: p=0.01). Limitations include the use of statistical correlation to identify 200 genes for AI analysis and that we did not compare regression identified genes with immunohistochemistry. AI and statistical analyses use different techniques of inference to determine gene-phenotype associations and identify distinct prognostic gene signatures that are equally valid. We have identified a prognostic gene signature whose members reflect a variety of carcinogenic pathways that could identify progression in non-muscle-invasive BCa. 2009 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Fission Signatures for Nuclear Material Detection

NASA Astrophysics Data System (ADS)

Gozani, Tsahi

2009-06-01

Detection and interdiction of nuclear materials in all forms of transport is one of the most critical security issues facing the United States and the rest of the civilized world. Naturally emitted gamma rays by these materials, while abundant and detectable when unshielded, are low in energy and readily shielded. X-ray radiography is useful in detecting the possible presence of shielding material. Positive detection of concealed nuclear materials requires methods which unequivocally detect specific attributes of the materials. These methods typically involve active interrogation by penetrating radiation of neutrons, photons or other particles. Fortunately, nuclear materials, probed by various types of radiation, yield very unique and often strong signatures. Paramount among them are the detectable fission signatures, namely prompt neutrons and gamma rays, and delayed neutrons gamma rays. Other useful signatures are the nuclear states excited by neutrons, via inelastic scattering, or photons, via nuclear resonance fluorescence and absorption. The signatures are very different in magnitude, level of specificity, ease of excitation and detection, signal to background ratios, etc. For example, delayed neutrons are very unique to the fission process, but are scarce, have low energy, and hence are easily absorbed. Delayed gamma rays are more abundant but "featureless", and have a higher background from natural sources and more importantly, from activation due to the interrogation sources. The prompt fission signatures need to be measured in the presence of the much higher levels of probing radiation. This requires taking special measures to look for the signatures, sometimes leading to a significant sensitivity loss or a complete inability to detect them. Characteristic gamma rays induced in nuclear materials reflecting their nuclear structure, while rather unique, require very high intensity of interrogation radiation and very high resolution in energy and/or time. The trade off of signatures, their means of stimulation, and methods of detection, will be reviewed.

Towards the implementation of a spectral database for the detection of biological warfare agents

NASA Astrophysics Data System (ADS)

Carestia, M.; Pizzoferrato, R.; Gelfusa, M.; Cenciarelli, O.; D'Amico, F.; Malizia, A.; Scarpellini, D.; Murari, A.; Vega, J.; Gaudio, P.

2014-10-01

The deliberate use of biological warfare agents (BWA) and other pathogens can jeopardize the safety of population, fauna and flora, and represents a concrete concern from the military and civil perspective. At present, the only commercially available tools for fast warning of a biological attack can perform point detection and require active or passive sampling collection. The development of a stand-off detection system would be extremely valuable to minimize the risk and the possible consequences of the release of biological aerosols in the atmosphere. Biological samples can be analyzed by means of several optical techniques, covering a broad region of the electromagnetic spectrum. Strong evidence proved that the informative content of fluorescence spectra could provide good preliminary discrimination among those agents and it can also be obtained through stand-off measurements. Such a system necessitates a database and a mathematical method for the discrimination of the spectral signatures. In this work, we collected fluorescence emission spectra of the main BWA simulants, to implement a spectral signature database and apply the Universal Multi Event Locator (UMEL) statistical method. Our preliminary analysis, conducted in laboratory conditions with a standard UV lamp source, considers the main experimental setups influencing the fluorescence signature of some of the most commonly used BWA simulants. Our work represents a first step towards the implementation of a spectral database and a laser-based biological stand-off detection and identification technique.

Identifying Time Periods of Minimal Thermal Gradient for Temperature-Driven Structural Health Monitoring

PubMed Central

Reilly, John; Glisic, Branko

2018-01-01

Temperature changes play a large role in the day to day structural behavior of structures, but a smaller direct role in most contemporary Structural Health Monitoring (SHM) analyses. Temperature-Driven SHM will consider temperature as the principal driving force in SHM, relating a measurable input temperature to measurable output generalized strain (strain, curvature, etc.) and generalized displacement (deflection, rotation, etc.) to create three-dimensional signatures descriptive of the structural behavior. Identifying time periods of minimal thermal gradient provides the foundation for the formulation of the temperature–deformation–displacement model. Thermal gradients in a structure can cause curvature in multiple directions, as well as non-linear strain and stress distributions within the cross-sections, which significantly complicates data analysis and interpretation, distorts the signatures, and may lead to unreliable conclusions regarding structural behavior and condition. These adverse effects can be minimized if the signatures are evaluated at times when thermal gradients in the structure are minimal. This paper proposes two classes of methods based on the following two metrics: (i) the range of raw temperatures on the structure, and (ii) the distribution of the local thermal gradients, for identifying time periods of minimal thermal gradient on a structure with the ability to vary the tolerance of acceptable thermal gradients. The methods are tested and validated with data collected from the Streicker Bridge on campus at Princeton University. PMID:29494496

Identifying Time Periods of Minimal Thermal Gradient for Temperature-Driven Structural Health Monitoring.

PubMed

Reilly, John; Glisic, Branko

2018-03-01

Temperature changes play a large role in the day to day structural behavior of structures, but a smaller direct role in most contemporary Structural Health Monitoring (SHM) analyses. Temperature-Driven SHM will consider temperature as the principal driving force in SHM, relating a measurable input temperature to measurable output generalized strain (strain, curvature, etc.) and generalized displacement (deflection, rotation, etc.) to create three-dimensional signatures descriptive of the structural behavior. Identifying time periods of minimal thermal gradient provides the foundation for the formulation of the temperature-deformation-displacement model. Thermal gradients in a structure can cause curvature in multiple directions, as well as non-linear strain and stress distributions within the cross-sections, which significantly complicates data analysis and interpretation, distorts the signatures, and may lead to unreliable conclusions regarding structural behavior and condition. These adverse effects can be minimized if the signatures are evaluated at times when thermal gradients in the structure are minimal. This paper proposes two classes of methods based on the following two metrics: (i) the range of raw temperatures on the structure, and (ii) the distribution of the local thermal gradients, for identifying time periods of minimal thermal gradient on a structure with the ability to vary the tolerance of acceptable thermal gradients. The methods are tested and validated with data collected from the Streicker Bridge on campus at Princeton University.

Linguistic Analysis of the Human Heartbeat Using Frequency and Rank Order Statistics

NASA Astrophysics Data System (ADS)

Yang, Albert C.-C.; Hseu, Shu-Shya; Yien, Huey-Wen; Goldberger, Ary L.; Peng, C.-K.

2003-03-01

Complex physiologic signals may carry unique dynamical signatures that are related to their underlying mechanisms. We present a method based on rank order statistics of symbolic sequences to investigate the profile of different types of physiologic dynamics. We apply this method to heart rate fluctuations, the output of a central physiologic control system. The method robustly discriminates patterns generated from healthy and pathologic states, as well as aging. Furthermore, we observe increased randomness in the heartbeat time series with physiologic aging and pathologic states and also uncover nonrandom patterns in the ventricular response to atrial fibrillation.

Apparatus and method for non-invasive diagnosis and control of motor operated valve condition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lyon, R.H.; Chai, J.; Lang, J.H.

1997-01-14

An apparatus compares the torque from an MOV motor with the valve displacement, and from the comparison assesses MOV operating condition. A transducer measures the vibration of the housing of an MOV. The vibrations are due to the motions of the rotating elements within the housing, which motions are directly related to the motion of the valve relative to its seat. Signal processing apparatus analyzes the vibrations to recover the rotations of the rotating elements and thus the motion of the valve plug. Lost motion can also be determined (if a lost motion connection exists) by demodulating the vibration signalmore » and thus taking into account also the lost motion. Simultaneously, the forces applied to the valve are estimated by estimating the torque between the stator and the rotor of the motor. Such torque can be estimated from measuring the input current and voltage alone, using a forgetting factor and a correction for the forgetting factor. A signature derived from relating the torque to the valve position can be used to assess the condition of the MOV, by comparing the signature to signatures for MOVs of known conditions. The vibration analysis components generate signals that relate to the position of elements in the operator. Similarly, the torque estimator estimates the torque output by any type of electric motor, whether or not part of an MOV analysis unit. 28 figs.« less

Apparatus and method for non-invasive diagnosis and control of motor operated valve condition

DOEpatents

Lyon, R.H.; Chai, J.; Lang, J.H.; Hagman, W.H.; Umans, S.D.; Saarela, O.J.

1997-01-14

An apparatus compares the torque from an MOV motor with the valve displacement, and from the comparison assesses MOV operating condition. A transducer measures the vibration of the housing of an MOV. The vibrations are due to the motions of the rotating elements within the housing, which motions are directly related to the motion of the valve relative to its seat. Signal processing apparatus analyzes the vibrations to recover the rotations of the rotating elements and thus the motion of the valve plug. Lost motion can also be determined (if a lost motion connection exists) by demodulating the vibration signal and thus taking into account also the lost motion. Simultaneously, the forces applied to the valve are estimated by estimating the torque between the stator and the rotor of the motor. Such torque can be estimated from measuring the input current and voltage alone, using a forgetting factor and a correction for the forgetting factor. A signature derived from relating the torque to the valve position can be used to assess the condition of the MOV, by comparing the signature to signatures for MOVs of known conditions. The vibration analysis components generate signals that relate to the position of elements in the operator. Similarly, the torque estimator estimates the torque output by any type of electric motor, whether or not part of an MOV analysis unit. 28 figs.

Apparatus and method for non-invasive diagnosis and control of motor operated valve condition

DOEpatents

Lyon, Richard H.; Chai, Jangbom; Lang, Jeffrey H.; Hagman, Wayne H.; Umans, Stephen D.; Saarela, Olli J.

1997-01-01

An apparatus compares the torque from an MOV motor with the valve displacement, and from the comparison assesses MOV operating condition. A transducer measures the vibration of the housing of an MOV. The vibrations are due to the motions of the rotating elements within the housing, which motions are directly related to the motion of the valve relative to its seat. Signal processing apparatus analyzes the vibrations to recover the rotations of the rotating elements and thus the motion of the valve plug. Lost motion can also be determined (if a lost motion connection exists) by demodulating the vibration signal and thus taking into account also the lost motion. Simultaneously, the forces applied to the valve are estimated by estimating the torque between the stator and the rotor of the motor. Such torque can be estimated from measuring the input current and voltage alone, using a forgetting factor and a correction for the forgetting factor. A signature derived from relating the torque to the valve position can be used to assess the condition of the MOV, by comparing the signature to signatures for MOVs of known conditions. The vibration analysis components generate signals that relate to the position of elements in the operator. Similarly, the torque estimator estimates the torque output by any type of electric motor, whether or not part of an MOV analysis unit.

Character Recognition Method by Time-Frequency Analyses Using Writing Pressure

NASA Astrophysics Data System (ADS)

Watanabe, Tatsuhito; Katsura, Seiichiro

With the development of information and communication technology, personal verification becomes more and more important. In the future ubiquitous society, the development of terminals handling personal information requires the personal verification technology. The signature is one of the personal verification methods; however, the number of characters is limited in the case of the signature and therefore false signature is used easily. Thus, personal identification is difficult from handwriting. This paper proposes a “haptic pen” that extracts the writing pressure, and shows a character recognition method by time-frequency analyses. Although the figures of characters written by different amanuenses are similar, the differences appear in the time-frequency domain. As a result, it is possible to use the proposed character recognition for personal identification more exactly. The experimental results showed the viability of the proposed method.

Thermal stress characterization using the electro-mechanical impedance method

NASA Astrophysics Data System (ADS)

Zhu, Xuan; Lanza di Scalea, Francesco; Fateh, Mahmood

2017-04-01

This study examines the potential of the Electro-Mechanical Impedance (EMI) method to provide an estimation of the developed thermal stress in constrained bar-like structures. This non-invasive method features the easiness of implementation and interpretation, while it is notoriously known for being vulnerable to environmental variability. A comprehensive analytical model is proposed to relate the measured electric admittance signatures of the PZT element to temperature and uniaxial stress applied to the underlying structure. The model results compare favorably to the experimental ones, where the sensitivities of features extracted from the admittance signatures to the varying stress levels and temperatures are determined. Two temperature compensation frameworks are proposed to characterize the thermal stress states: (a) a regression model is established based on temperature-only tests, and the residuals from the thermal stress tests are then used to isolate the stress measurand; (b) the temperature-only tests are decomposed by Principle Components Analysis (PCA) and the feature vectors of the thermal stress tests are reconstructed after removal of the temperaturesensitive components. For both methods, the features were selected based on their performance in Receiver Operating Characteristic (ROC) curves. Experimental results on the Continuous Welded Rails (CWR) are shown to demonstrate the effectiveness of these temperature compensation methods.

Group Key Agreement Efficient in Communication

DTIC Science & Technology

2003-10-14

Selected Areas in Communications, 17(9), September 1999. [13] David Chaum . Zero-knowledge undeniable signatures . In I.B. Damgard, editor, Advances in...sender with some sufficiently strong public key signature method such as DSA or RSA (and using a long-term private key).1 All receivers are required...to verify signatures on all received messages and check the aforementioned fields. Consequently, our security model is different from some recent

Methods of extending signatures and training without ground information. [data processing, pattern recognition

NASA Technical Reports Server (NTRS)

Henderson, R. G.; Thomas, G. S.; Nalepka, R. F.

1975-01-01

Methods of performing signature extension, using LANDSAT-1 data, are explored. The emphasis is on improving the performance and cost-effectiveness of large area wheat surveys. Two methods were developed: ASC, and MASC. Two methods, Ratio, and RADIFF, previously used with aircraft data were adapted to and tested on LANDSAT-1 data. An investigation into the sources and nature of between scene data variations was included. Initial investigations into the selection of training fields without in situ ground truth were undertaken.

Specialized CFD Grid Generation Methods for Near-Field Sonic Boom Prediction

NASA Technical Reports Server (NTRS)

Park, Michael A.; Campbell, Richard L.; Elmiligui, Alaa; Cliff, Susan E.; Nayani, Sudheer N.

2014-01-01

Ongoing interest in analysis and design of low sonic boom supersonic transports re- quires accurate and ecient Computational Fluid Dynamics (CFD) tools. Specialized grid generation techniques are employed to predict near- eld acoustic signatures of these con- gurations. A fundamental examination of grid properties is performed including grid alignment with ow characteristics and element type. The issues a ecting the robustness of cylindrical surface extrusion are illustrated. This study will compare three methods in the extrusion family of grid generation methods that produce grids aligned with the freestream Mach angle. These methods are applied to con gurations from the First AIAA Sonic Boom Prediction Workshop.

Non-Invasive Survey of Old Paintings Using Vnir Hyperspectral Sensor

NASA Astrophysics Data System (ADS)

Matouskova, E.; Pavelka, K.; Svadlenkova, Z.

2013-07-01

Hyperspectral imaging is relatively new method developed primarily for army applications with respect to detection of possible chemical weapon existence and as an efficient assistant for a geological survey. The method is based on recording spectral profile for many hundreds of narrow spectral band. The technique gives full spectral curve of explored pixel which is an unparalleled signature of pixels material. Spectral signatures can then be compared with pre-defined spectral libraries or they can be created with respect to application. A new project named "New Modern Methods of Non-invasive Survey of Historical Site Objects" started at CTU in Prague with the New Year. The project is designed for 4 years and is funded by the Ministry of Culture in the Czech Republic. It is focused on material and chemical composition, damage diagnostics, condition description of paintings, images, construction components and whole structure object analysis in cultural heritage domain. This paper shows first results of the project on painting documentation field as well as used instrument. Hyperspec VNIR by Headwall Photonics was used for this analysis. It operates in the spectral range between 400 and 1000 nm. Comparison with infrared photography is discussed. The goal of this contribution is a non-destructive deep exploration of specific paintings. Two original 17th century paintings by Flemish authors Thomas van Apshoven ("On the Road") and David Teniers the Younger ("The Interior of a Mill") were chosen for the first analysis with a kind permission of academic painter Mr. M. Martan. Both paintings oil painted on wooden panel. This combination was chosen because of the possibility of underdrawing visualization which is supposed to be the most uncomplicated painting combination for this type of analysis.

A 16-Gene Signature Distinguishes Anaplastic Astrocytoma from Glioblastoma

PubMed Central

Rao, Soumya Alige Mahabala; Srinivasan, Sujaya; Patric, Irene Rosita Pia; Hegde, Alangar Sathyaranjandas; Chandramouli, Bangalore Ashwathnarayanara; Arimappamagan, Arivazhagan; Santosh, Vani; Kondaiah, Paturu; Rao, Manchanahalli R. Sathyanarayana; Somasundaram, Kumaravel

2014-01-01

Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; Grade IV) are diffusely infiltrating tumors and are called malignant astrocytomas. The treatment regimen and prognosis are distinctly different between anaplastic astrocytoma and glioblastoma patients. Although histopathology based current grading system is well accepted and largely reproducible, intratumoral histologic variations often lead to difficulties in classification of malignant astrocytoma samples. In order to obtain a more robust molecular classifier, we analysed RT-qPCR expression data of 175 differentially regulated genes across astrocytoma using Prediction Analysis of Microarrays (PAM) and found the most discriminatory 16-gene expression signature for the classification of anaplastic astrocytoma and glioblastoma. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. Additionally, validation of the 16-gene signature in multiple independent cohorts revealed that the signature predicted anaplastic astrocytoma and glioblastoma samples with accuracy rates of 99%, 88%, and 92% in TCGA, GSE1993 and GSE4422 datasets, respectively. The protein-protein interaction network and pathway analysis suggested that the 16-genes of the signature identified epithelial-mesenchymal transition (EMT) pathway as the most differentially regulated pathway in glioblastoma compared to anaplastic astrocytoma. In addition to identifying 16 gene classification signature, we also demonstrated that genes involved in epithelial-mesenchymal transition may play an important role in distinguishing glioblastoma from anaplastic astrocytoma. PMID:24475040

Twenty-four signature genes predict the prognosis of oral squamous cell carcinoma with high accuracy and repeatability

PubMed Central

Gao, Jianyong; Tian, Gang; Han, Xu; Zhu, Qiang

2018-01-01

Oral squamous cell carcinoma (OSCC) is the sixth most common type cancer worldwide, with poor prognosis. The present study aimed to identify gene signatures that could classify OSCC and predict prognosis in different stages. A training data set (GSE41613) and two validation data sets (GSE42743 and GSE26549) were acquired from the online Gene Expression Omnibus database. In the training data set, patients were classified based on the tumor-node-metastasis staging system, and subsequently grouped into low stage (L) or high stage (H). Signature genes between L and H stages were selected by disparity index analysis, and classification was performed by the expression of these signature genes. The established classification was compared with the L and H classification, and fivefold cross validation was used to evaluate the stability. Enrichment analysis for the signature genes was implemented by the Database for Annotation, Visualization and Integration Discovery. Two validation data sets were used to determine the precise of classification. Survival analysis was conducted followed each classification using the package ‘survival’ in R software. A set of 24 signature genes was identified based on the classification model with the Fi value of 0.47, which was used to distinguish OSCC samples in two different stages. Overall survival of patients in the H stage was higher than those in the L stage. Signature genes were primarily enriched in ‘ether lipid metabolism’ pathway and biological processes such as ‘positive regulation of adaptive immune response’ and ‘apoptotic cell clearance’. The results provided a novel 24-gene set that may be used as biomarkers to predict OSCC prognosis with high accuracy, which may be used to determine an appropriate treatment program for patients with OSCC in addition to the traditional evaluation index. PMID:29257303

Quantum blind dual-signature scheme without arbitrator

NASA Astrophysics Data System (ADS)

Li, Wei; Shi, Ronghua; Huang, Dazu; Shi, Jinjing; Guo, Ying

2016-03-01

Motivated by the elegant features of a bind signature, we suggest the design of a quantum blind dual-signature scheme with three phases, i.e., initial phase, signing phase and verification phase. Different from conventional schemes, legal messages are signed not only by the blind signatory but also by the sender in the signing phase. It does not rely much on an arbitrator in the verification phase as the previous quantum signature schemes usually do. The security is guaranteed by entanglement in quantum information processing. Security analysis demonstrates that the signature can be neither forged nor disavowed by illegal participants or attacker. It provides a potential application for e-commerce or e-payment systems with the current technology.

An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer

PubMed Central

2010-01-01

Background Gene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse. Methods We included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed were those included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Index. The association among gene expression, clinical variables and distant metastasis-free survival was analyzed using Cox regression models. Results An 8-gene prognostic score was defined. Distant metastasis-free survival at 5 years was 97% for patients defined as low-risk by the prognostic score versus 60% for patients defined as high-risk. The 8-gene score remained a significant factor in multivariate analysis and its performance was similar to that of two validated gene profiles: the 70-Gene Signature and the Recurrence Score. The validity of the signature was verified in independent cohorts obtained from the GEO database. Conclusions This study identifies a simple gene expression score that complements histopathological prognostic factors in breast cancer, and can be determined in paraffin-embedded samples. PMID:20584321

A novel RNA-sequencing-based miRNA signature predicts with recurrence and outcome of hepatocellular carcinoma.

PubMed

Fumao, Bai; Zhou, Huaibin; Ma, Mengni; Guan, Chen; Lyu, Jianxin; Meng, Qing H

2018-05-02

Hepatocellular carcinoma (HCC) is the fifth most common type of cancer and the second leading cause of cancer-related deaths worldwide. Given that the rate of HCC recurrence 5 years after liver resection is as high as 70%, patient with HCC typically have a poor outcome. A biomarker or set of biomarkers that could predict disease recurrence would have a substantial clinical impact, allowing earlier detection of recurrence and more effective treatment. With the aim of identifying a new microRNA (miRNA) signature associated with HCC recurrence, we analyzed data on 306 HCC patients for whom both miRNA expression profiles and complete clinical information were available from The Cancer Genome Atlas (TCGA) database. Through this analysis, we identified a six-miRNA signature that could effectively predict patients' recurrence risk; the high-risk and low-risk groups had significantly different recurrence-free survival rates. Time-dependent receiver operating characteristic analysis indicated that this signature had a good predictive performance. Multivariable Cox regression and stratified analyses demonstrated that the six-miRNA signature was independent of other clinical features. Functional enrichment analysis of the gene targets of the six prognostic miRNAs indicated enrichment mainly in cancer-related pathways and important cell biological processes. Our results support use of this six-miRNA signature as an independent factor for predicting recurrence and outcome of patients with HCC. Molecular Oncology (2018) © 2018 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru

USGS Publications Warehouse

Shermeyer, Jacob S.; Haack, Barry N.

2015-01-01

Two forestry-change detection methods are described, compared, and contrasted for estimating deforestation and growth in threatened forests in southern Peru from 2000 to 2010. The methods used in this study rely on freely available data, including atmospherically corrected Landsat 5 Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF). The two methods include a conventional supervised signature extraction method and a unique self-calibrating method called MODIS VCF guided forest/nonforest (FNF) masking. The process chain for each of these methods includes a threshold classification of MODIS VCF, training data or signature extraction, signature evaluation, k-nearest neighbor classification, analyst-guided reclassification, and postclassification image differencing to generate forest change maps. Comparisons of all methods were based on an accuracy assessment using 500 validation pixels. Results of this accuracy assessment indicate that FNF masking had a 5% higher overall accuracy and was superior to conventional supervised classification when estimating forest change. Both methods succeeded in classifying persistently forested and nonforested areas, and both had limitations when classifying forest change.

Unmixing the Materials and Mechanics Contributions in Non-resolved Object Signatures

DTIC Science & Technology

2008-09-01

abundances from hyperspectral or multi-spectral time - resolved signatures. A Fourier analysis of temporal variation of material abundance provides...factorization technique to extract the temporal variation of material abundances from hyperspectral or multi-spectral time - resolved signatures. A Fourier...approximately one hundred wavelengths in the visible spectrum. The frame rate for the instrument was not large enough to collect time resolved data. However

Signature simulation of mixed materials

NASA Astrophysics Data System (ADS)

Carson, Tyler D.; Salvaggio, Carl

2015-05-01

Soil target signatures vary due to geometry, chemical composition, and scene radiometry. Although radiative transfer models and function-fit physical models may describe certain targets in limited depth, the ability to incorporate all three signature variables is difficult. This work describes a method to simulate the transient signatures of soil by first considering scene geometry synthetically created using 3D physics engines. Through the assignment of spectral data from the Nonconventional Exploitation Factors Data System (NEFDS), the synthetic scene is represented as a physical mixture of particles. Finally, first principles radiometry is modeled using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. With DIRSIG, radiometric and sensing conditions were systematically manipulated to produce and record goniometric signatures. The implementation of this virtual goniometer allows users to examine how a target bidirectional reflectance distribution function (BRDF) will change with geometry, composition, and illumination direction. By using 3D computer graphics models, this process does not require geometric assumptions that are native to many radiative transfer models. It delivers a discrete method to circumnavigate the significant cost of time and treasure associated with hardware-based goniometric data collections.

Comparing synthetic imagery with real imagery for visible signature analysis: human observer results

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.; Richards, Noel; Madden, Christopher S.; Winter, Neal; Wheaton, Vivienne C.

2017-10-01

Synthetic imagery could potentially enhance visible signature analysis by providing a wider range of target images in differing environmental conditions than would be feasible to collect in field trials. Achieving this requires a method for generating synthetic imagery that is both verified to be realistic and produces the same visible signature analysis results as real images. Is target detectability as measured by image metrics the same for real images and synthetic images of the same scene? Is target detectability as measured by human observer trials the same for real images and synthetic images of the same scene, and how realistic do the synthetic images need to be? In this paper we present the results of a small scale exploratory study on the second question: a photosimulation experiment conducted using digital photographs and synthetic images generated of the same scene. Two sets of synthetic images were created: a high fidelity set created using an image generation tool, E-on Vue, and a low fidelity set created using a gaming engine, Unity 3D. The target detection results obtained using digital photographs were compared with those obtained using the two sets of synthetic images. There was a moderate correlation between the high fidelity synthetic image set and the real images in both the probability of correct detection (Pd: PCC = 0.58, SCC = 0.57) and mean search time (MST: PCC = 0.63, SCC = 0.61). There was no correlation between the low fidelity synthetic image set and the real images for the Pd, but a moderate correlation for MST (PCC = 0.67, SCC = 0.55).

Micro-Doppler analysis of multiple frequency continuous wave radar signatures

NASA Astrophysics Data System (ADS)

Anderson, Michael G.; Rogers, Robert L.

2007-04-01

Micro-Doppler refers to Doppler scattering returns produced by non rigid-body motion. Micro-Doppler gives rise to many detailed radar image features in addition to those associated with bulk target motion. Targets of different classes (for example, humans, animals, and vehicles) produce micro-Doppler images that are often distinguishable even by nonexpert observers. Micro-Doppler features have great potential for use in automatic target classification algorithms. Although the potential benefit of using micro-Doppler in classification algorithms is high, relatively little experimental (non-synthetic) micro-Doppler data exists. Much of the existing experimental data comes from highly cooperative targets (human or vehicle targets directly approaching the radar). This research involved field data collection and analysis of micro-Doppler radar signatures from non-cooperative targets. The data was collected using a low cost Xband multiple frequency continuous wave (MFCW) radar with three transmit frequencies. The collected MFCW radar signatures contain data from humans, vehicles, and animals. The presented data includes micro-Doppler signatures previously unavailable in the literature such as crawling humans and various animal species. The animal micro-Doppler signatures include deer, dog, and goat datasets. This research focuses on the analysis of micro-Doppler from noncooperative targets approaching the radar at various angles, maneuvers, and postures.

In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer.

PubMed

Abu-Jamous, Basel; Buffa, Francesca M; Harris, Adrian L; Nandi, Asoke K

2017-06-15

Hypoxia is a characteristic of breast tumours indicating poor prognosis. Based on the assumption that those genes which are up-regulated under hypoxia in cell-lines are expected to be predictors of poor prognosis in clinical data, many signatures of poor prognosis were identified. However, it was observed that cell line data do not always concur with clinical data, and therefore conclusions from cell line analysis should be considered with caution. As many transcriptomic cell-line datasets from hypoxia related contexts are available, integrative approaches which investigate these datasets collectively, while not ignoring clinical data, are required. We analyse sixteen heterogeneous breast cancer cell-line transcriptomic datasets in hypoxia-related conditions collectively by employing the unique capabilities of the method, UNCLES, which integrates clustering results from multiple datasets and can address questions that cannot be answered by existing methods. This has been demonstrated by comparison with the state-of-the-art iCluster method. From this collection of genome-wide datasets include 15,588 genes, UNCLES identified a relatively high number of genes (>1000 overall) which are consistently co-regulated over all of the datasets, and some of which are still poorly understood and represent new potential HIF targets, such as RSBN1 and KIAA0195. Two main, anti-correlated, clusters were identified; the first is enriched with MYC targets participating in growth and proliferation, while the other is enriched with HIF targets directly participating in the hypoxia response. Surprisingly, in six clinical datasets, some sub-clusters of growth genes are found consistently positively correlated with hypoxia response genes, unlike the observation in cell lines. Moreover, the ability to predict bad prognosis by a combined signature of one sub-cluster of growth genes and one sub-cluster of hypoxia-induced genes appears to be comparable and perhaps greater than that of known hypoxia signatures. We present a clustering approach suitable to integrate data from diverse experimental set-ups. Its application to breast cancer cell line datasets reveals new hypoxia-regulated signatures of genes which behave differently when in vitro (cell-line) data is compared with in vivo (clinical) data, and are of a prognostic value comparable or exceeding the state-of-the-art hypoxia signatures.

Dual function seal: visualized digital signature for electronic medical record systems.

PubMed

Yu, Yao-Chang; Hou, Ting-Wei; Chiang, Tzu-Chiang

2012-10-01

Digital signature is an important cryptography technology to be used to provide integrity and non-repudiation in electronic medical record systems (EMRS) and it is required by law. However, digital signatures normally appear in forms unrecognizable to medical staff, this may reduce the trust from medical staff that is used to the handwritten signatures or seals. Therefore, in this paper we propose a dual function seal to extend user trust from a traditional seal to a digital signature. The proposed dual function seal is a prototype that combines the traditional seal and digital seal. With this prototype, medical personnel are not just can put a seal on paper but also generate a visualized digital signature for electronic medical records. Medical Personnel can then look at the visualized digital signature and directly know which medical personnel generated it, just like with a traditional seal. Discrete wavelet transform (DWT) is used as an image processing method to generate a visualized digital signature, and the peak signal to noise ratio (PSNR) is calculated to verify that distortions of all converted images are beyond human recognition, and the results of our converted images are from 70 dB to 80 dB. The signature recoverability is also tested in this proposed paper to ensure that the visualized digital signature is verifiable. A simulated EMRS is implemented to show how the visualized digital signature can be integrity into EMRS.

Characterization of Relatively Large Track Geometry Variations

DOT National Transportation Integrated Search

1982-03-01

An analysis of existing track geometry data is described from which the signatures of key track geometry variations related to severe track-train dynamic interaction are identified and quantified. Mathematical representations of these signatures are ...

Single-cell multimodal profiling reveals cellular epigenetic heterogeneity.

PubMed

Cheow, Lih Feng; Courtois, Elise T; Tan, Yuliana; Viswanathan, Ramya; Xing, Qiaorui; Tan, Rui Zhen; Tan, Daniel S W; Robson, Paul; Loh, Yuin-Han; Quake, Stephen R; Burkholder, William F

2016-10-01

Sample heterogeneity often masks DNA methylation signatures in subpopulations of cells. Here, we present a method to genotype single cells while simultaneously interrogating gene expression and DNA methylation at multiple loci. We used this targeted multimodal approach, implemented on an automated, high-throughput microfluidic platform, to assess primary lung adenocarcinomas and human fibroblasts undergoing reprogramming by profiling epigenetic variation among cell types identified through genotyping and transcriptional analysis.

Estimating physiological skin parameters from hyperspectral signatures

NASA Astrophysics Data System (ADS)

Vyas, Saurabh; Banerjee, Amit; Burlina, Philippe

2013-05-01

We describe an approach for estimating human skin parameters, such as melanosome concentration, collagen concentration, oxygen saturation, and blood volume, using hyperspectral radiometric measurements (signatures) obtained from in vivo skin. We use a computational model based on Kubelka-Munk theory and the Fresnel equations. This model forward maps the skin parameters to a corresponding multiband reflectance spectra. Machine-learning-based regression is used to generate the inverse map, and hence estimate skin parameters from hyperspectral signatures. We test our methods using synthetic and in vivo skin signatures obtained in the visible through the short wave infrared domains from 24 patients of both genders and Caucasian, Asian, and African American ethnicities. Performance validation shows promising results: good agreement with the ground truth and well-established physiological precepts. These methods have potential use in the characterization of skin abnormalities and in minimally-invasive prescreening of malignant skin cancers.

Bearing defect signature analysis using advanced nonlinear signal analysis in a controlled environment

NASA Technical Reports Server (NTRS)

Zoladz, T.; Earhart, E.; Fiorucci, T.

1995-01-01

Utilizing high-frequency data from a highly instrumented rotor assembly, seeded bearing defect signatures are characterized using both conventional linear approaches, such as power spectral density analysis, and recently developed nonlinear techniques such as bicoherence analysis. Traditional low-frequency (less than 20 kHz) analysis and high-frequency envelope analysis of both accelerometer and acoustic emission data are used to recover characteristic bearing distress information buried deeply in acquired data. The successful coupling of newly developed nonlinear signal analysis with recovered wideband envelope data from accelerometers and acoustic emission sensors is the innovative focus of this research.

Automatic removal of cosmic ray signatures in Deep Impact images

NASA Astrophysics Data System (ADS)

Ipatov, S. I.; A'Hearn, M. F.; Klaasen, K. P.

The results of recognition of cosmic ray (CR) signatures on single images made during the Deep Impact mission were analyzed for several codes written by several authors. For automatic removal of CR signatures on many images, we suggest using the code imgclean ( http://pdssbn.astro.umd.edu/volume/didoc_0001/document/calibration_software/dical_v5/) written by E. Deutsch as other codes considered do not work properly automatically with a large number of images and do not run to completion for some images; however, other codes can be better for analysis of certain specific images. Sometimes imgclean detects false CR signatures near the edge of a comet nucleus, and it often does not recognize all pixels of long CR signatures. Our code rmcr is the only code among those considered that allows one to work with raw images. For most visual images made during low solar activity at exposure time t > 4 s, the number of clusters of bright pixels on an image per second per sq. cm of CCD was about 2-4, both for dark and normal sky images. At high solar activity, it sometimes exceeded 10. The ratio of the number of CR signatures consisting of n pixels obtained at high solar activity to that at low solar activity was greater for greater n. The number of clusters detected as CR signatures on a single infrared image is by at least a factor of several greater than the actual number of CR signatures; the number of clusters based on analysis of two successive dark infrared frames is in agreement with an expected number of CR signatures. Some glitches of false CR signatures include bright pixels repeatedly present on different infrared images. Our interactive code imr allows a user to choose the regions on a considered image where glitches detected by imgclean as CR signatures are ignored. In other regions chosen by the user, the brightness of some pixels is replaced by the local median brightness if the brightness of these pixels is greater by some factor than the median brightness. The interactive code allows one to delete long CR signatures and prevents removal of false CR signatures near the edge of the nucleus of the comet. The interactive code can be applied to editing any digital images. Results obtained can be used for other missions to comets.

U.S. Army Research Laboratory (ARL) multimodal signatures database

NASA Astrophysics Data System (ADS)

Bennett, Kelly

2008-04-01

The U.S. Army Research Laboratory (ARL) Multimodal Signatures Database (MMSDB) is a centralized collection of sensor data of various modalities that are co-located and co-registered. The signatures include ground and air vehicles, personnel, mortar, artillery, small arms gunfire from potential sniper weapons, explosives, and many other high value targets. This data is made available to Department of Defense (DoD) and DoD contractors, Intel agencies, other government agencies (OGA), and academia for use in developing target detection, tracking, and classification algorithms and systems to protect our Soldiers. A platform independent Web interface disseminates the signatures to researchers and engineers within the scientific community. Hierarchical Data Format 5 (HDF5) signature models provide an excellent solution for the sharing of complex multimodal signature data for algorithmic development and database requirements. Many open source tools for viewing and plotting HDF5 signatures are available over the Web. Seamless integration of HDF5 signatures is possible in both proprietary computational environments, such as MATLAB, and Free and Open Source Software (FOSS) computational environments, such as Octave and Python, for performing signal processing, analysis, and algorithm development. Future developments include extending the Web interface into a portal system for accessing ARL algorithms and signatures, High Performance Computing (HPC) resources, and integrating existing database and signature architectures into sensor networking environments.

False alarm recognition in hyperspectral gas plume identification

DOEpatents

Conger, James L [San Ramon, CA; Lawson, Janice K [Tracy, CA; Aimonetti, William D [Livermore, CA

2011-03-29

According to one embodiment, a method for analyzing hyperspectral data includes collecting first hyperspectral data of a scene using a hyperspectral imager during a no-gas period and analyzing the first hyperspectral data using one or more gas plume detection logics. The gas plume detection logic is executed using a low detection threshold, and detects each occurrence of an observed hyperspectral signature. The method also includes generating a histogram for all occurrences of each observed hyperspectral signature which is detected using the gas plume detection logic, and determining a probability of false alarm (PFA) for all occurrences of each observed hyperspectral signature based on the histogram. Possibly at some other time, the method includes collecting second hyperspectral data, and analyzing the second hyperspectral data using the one or more gas plume detection logics and the PFA to determine if any gas is present. Other systems and methods are also included.

Signature of Microbial Dysbiosis in Periodontitis.

PubMed

Meuric, Vincent; Le Gall-David, Sandrine; Boyer, Emile; Acuña-Amador, Luis; Martin, Bénédicte; Fong, Shao Bing; Barloy-Hubler, Frederique; Bonnaure-Mallet, Martine

2017-07-15

Periodontitis is driven by disproportionate host inflammatory immune responses induced by an imbalance in the composition of oral bacteria; this instigates microbial dysbiosis, along with failed resolution of the chronic destructive inflammation. The objectives of this study were to identify microbial signatures for health and chronic periodontitis at the genus level and to propose a model of dysbiosis, including the calculation of bacterial ratios. Published sequencing data obtained from several different studies (196 subgingival samples from patients with chronic periodontitis and 422 subgingival samples from healthy subjects) were pooled and subjected to a new microbiota analysis using the same Visualization and Analysis of Microbial Population Structures (VAMPS) pipeline, to identify microbiota specific to health and disease. Microbiota were visualized using CoNet and Cytoscape. Dysbiosis ratios, defined as the percentage of genera associated with disease relative to the percentage of genera associated with health, were calculated to distinguish disease from health. Correlations between the proposed dysbiosis ratio and the periodontal pocket depth were tested with a different set of data obtained from a recent study, to confirm the relevance of the ratio as a potential indicator of dysbiosis. Beta diversity showed significant clustering of periodontitis-associated microbiota, at the genus level, according to the clinical status and independent of the methods used. Specific genera ( Veillonella , Neisseria , Rothia , Corynebacterium , and Actinomyces ) were highly prevalent (>95%) in health, while other genera ( Eubacterium , Campylobacter , Treponema , and Tannerella ) were associated with chronic periodontitis. The calculation of dysbiosis ratios based on the relative abundance of the genera found in health versus periodontitis was tested. Nonperiodontitis samples were significantly identifiable by low ratios, compared to chronic periodontitis samples. When applied to a subgingival sample set with well-defined clinical data, the method showed a strong correlation between the dysbiosis ratio, as well as a simplified ratio ( Porphyromonas , Treponema , and Tannerella to Rothia and Corynebacterium ), and pocket depth. Microbial analysis of chronic periodontitis can be correlated with the pocket depth through specific signatures for microbial dysbiosis. IMPORTANCE Defining microbiota typical of oral health or chronic periodontitis is difficult. The evaluation of periodontal disease is currently based on probing of the periodontal pocket. However, the status of pockets "on the mend" or sulci at risk of periodontitis cannot be addressed solely through pocket depth measurements or current microbiological tests available for practitioners. Thus, a more specific microbiological measure of dysbiosis could help in future diagnoses of periodontitis. In this work, data from different studies were pooled, to improve the accuracy of the results. However, analysis of multiple species from different studies intensified the bacterial network and complicated the search for reproducible microbial signatures. Despite the use of different methods in each study, investigation of the microbiota at the genus level showed that some genera were prevalent (up to 95% of the samples) in health or disease, allowing the calculation of bacterial ratios (i.e., dysbiosis ratios). The correlation between the proposed ratios and the periodontal pocket depth was tested, which confirmed the link between dysbiosis ratios and the severity of the disease. The results of this work are promising, but longitudinal studies will be required to improve the ratios and to define the microbial signatures of the disease, which will allow monitoring of periodontal pocket recovery and, conceivably, determination of the potential risk of periodontitis among healthy patients. Copyright © 2017 American Society for Microbiology.

A Potential Biofilm Metabolite Signature for Caries Activity - A Pilot Clinical Study

PubMed Central

Zandona, F; Soini, HA; Novotny, MV; Santiago, E; Eckert, GJ; Preisser, JS; Benecha, HK; Arthur, RA; Zero, DT

2016-01-01

Background This study's aim was to compare the dental biofilm metabolite-profile of caries-active (N=11) or caries-free (N=4) children by gas chromatography-mass spectrometry (GC/MS) analyses. Methods Samples collected after overnight fasting, with or without a previous glucose rinse, were combined for each child based on the caries status of the site, re-suspended in ethanol and analyzed by GC/MS. Results Biofilm from caries-active sites exhibited a different chromatographic profile compared to caries-free sites. Qualitative and quantitative analysis suggested a special cluster of branched alcohols and esters present at substantially higher intensity in biofilms of caries-active sites. Conclusions This pilot study indicates that there are metabolites present in the biofilm which have the potential to provide a characteristic metabolomics signature for caries activity. PMID:27885354

Model of lidar range-Doppler signatures of solid rocket fuel plumes

NASA Astrophysics Data System (ADS)

Bankman, Isaac N.; Giles, John W.; Chan, Stephen C.; Reed, Robert A.

2004-09-01

The analysis of particles produced by solid rocket motor fuels relates to two types of studies: the effect of these particles on the Earth's ozone layer, and the dynamic flight behavior of solid fuel boosters used by the NASA Space Shuttle. Since laser backscatter depends on the particle size and concentration, a lidar system can be used to analyze the particle distributions inside a solid rocket plume in flight. We present an analytical model that simulates the lidar returns from solid rocket plumes including effects of beam profile, spot size, polarization and sensing geometry. The backscatter and extinction coefficients of alumina particles are computed with the T-matrix method that can address non-spherical particles. The outputs of the model include time-resolved return pulses and range-Doppler signatures. Presented examples illustrate the effects of sensing geometry.

Imaging-based molecular barcoding with pixelated dielectric metasurfaces

NASA Astrophysics Data System (ADS)

Tittl, Andreas; Leitis, Aleksandrs; Liu, Mingkai; Yesilkoy, Filiz; Choi, Duk-Yong; Neshev, Dragomir N.; Kivshar, Yuri S.; Altug, Hatice

2018-06-01

Metasurfaces provide opportunities for wavefront control, flat optics, and subwavelength light focusing. We developed an imaging-based nanophotonic method for detecting mid-infrared molecular fingerprints and implemented it for the chemical identification and compositional analysis of surface-bound analytes. Our technique features a two-dimensional pixelated dielectric metasurface with a range of ultrasharp resonances, each tuned to a discrete frequency; this enables molecular absorption signatures to be read out at multiple spectral points, and the resulting information is then translated into a barcode-like spatial absorption map for imaging. The signatures of biological, polymer, and pesticide molecules can be detected with high sensitivity, covering applications such as biosensing and environmental monitoring. Our chemically specific technique can resolve absorption fingerprints without the need for spectrometry, frequency scanning, or moving mechanical parts, thereby paving the way toward sensitive and versatile miniaturized mid-infrared spectroscopy devices.

Statistical analysis and machine learning algorithms for optical biopsy

NASA Astrophysics Data System (ADS)

Wu, Binlin; Liu, Cheng-hui; Boydston-White, Susie; Beckman, Hugh; Sriramoju, Vidyasagar; Sordillo, Laura; Zhang, Chunyuan; Zhang, Lin; Shi, Lingyan; Smith, Jason; Bailin, Jacob; Alfano, Robert R.

2018-02-01

Analyzing spectral or imaging data collected with various optical biopsy methods is often times difficult due to the complexity of the biological basis. Robust methods that can utilize the spectral or imaging data and detect the characteristic spectral or spatial signatures for different types of tissue is challenging but highly desired. In this study, we used various machine learning algorithms to analyze a spectral dataset acquired from human skin normal and cancerous tissue samples using resonance Raman spectroscopy with 532nm excitation. The algorithms including principal component analysis, nonnegative matrix factorization, and autoencoder artificial neural network are used to reduce dimension of the dataset and detect features. A support vector machine with a linear kernel is used to classify the normal tissue and cancerous tissue samples. The efficacies of the methods are compared.

High order statistical signatures from source-driven measurements of subcritical fissile systems

NASA Astrophysics Data System (ADS)

Mattingly, John Kelly

1998-11-01

This research focuses on the development and application of high order statistical analyses applied to measurements performed with subcritical fissile systems driven by an introduced neutron source. The signatures presented are derived from counting statistics of the introduced source and radiation detectors that observe the response of the fissile system. It is demonstrated that successively higher order counting statistics possess progressively higher sensitivity to reactivity. Consequently, these signatures are more sensitive to changes in the composition, fissile mass, and configuration of the fissile assembly. Furthermore, it is shown that these techniques are capable of distinguishing the response of the fissile system to the introduced source from its response to any internal or inherent sources. This ability combined with the enhanced sensitivity of higher order signatures indicates that these techniques will be of significant utility in a variety of applications. Potential applications include enhanced radiation signature identification of weapons components for nuclear disarmament and safeguards applications and augmented nondestructive analysis of spent nuclear fuel. In general, these techniques expand present capabilities in the analysis of subcritical measurements.

S100A9 and EGFR gene signatures predict disease progression in muscle invasive bladder cancer patients after chemotherapy.

PubMed

Kim, W T; Kim, J; Yan, C; Jeong, P; Choi, S Y; Lee, O J; Chae, Y B; Yun, S J; Lee, S C; Kim, W J

2014-05-01

In our previous gene expression profile analysis, IL1B, S100A8, S100A9, and EGFR were shown to be important mediators of muscle invasive bladder cancer (MIBC) progression. The aim of the present study was to investigate the ability of these gene signatures to predict disease progression after chemotherapy in patients with locally recurrent or metastatic MIBC. Patients with locally advanced MIBC who received chemotherapy were enrolled. The expression signatures of four genes were measured and carried out further functional analysis to confirm our findings. Two of the four genes, S100A9 and EGFR, were determined to significantly influence disease progression (P = 0.023, 0.045, respectively). Based on a receiver operating characteristic curve, a cut-off value for disease progression was determined. Patients with the good-prognostic signature group had a significantly longer time to progression and cancer-specific survival time than those with the poor-prognostic signature group (P < 0.001, 0.042, respectively). In the multivariate Cox regression analysis, gene signature was the only factor that significantly influenced disease progression [hazard ratio: 4.726, confidence interval: 1.623-13.763, P = 0.004]. In immunohistochemical analysis, S100A9 and EGFR positivity were associated with disease progression after chemotherapy. Protein expression of S100A9/EGFR showed modest correlation with gene expression of S100A9/EGFR (r = 0.395, P = 0.014 and r = 0.453, P = 0.004). Our functional analysis provided the evidence demonstrating that expression of S100A9 and EGFR closely associated chemoresistance, and that inhibition of S100A9 and EGFR may sensitize bladder tumor cells to the cisplatin-based chemotherapy. The S100A9/EGFR level is a novel prognostic marker to predict the chemoresponsiveness of patients with locally recurrent or metastatic MIBC.

Unsupervised color normalisation for H and E stained histopathology image analysis

NASA Astrophysics Data System (ADS)

Celis, Raúl; Romero, Eduardo

2015-12-01

In histology, each dye component attempts to specifically characterise different microscopic structures. In the case of the Hematoxylin-Eosin (H&E) stain, universally used for routine examination, quantitative analysis may often require the inspection of different morphological signatures related mainly to nuclei patterns, but also to stroma distribution. Nevertheless, computer systems for automatic diagnosis are often fraught by color variations ranging from the capturing device to the laboratory specific staining protocol and stains. This paper presents a novel colour normalisation method for H&E stained histopathology images. This method is based upon the opponent process theory and blindly estimates the best color basis for the Hematoxylin and Eosin stains without relying on prior knowledge. Stain Normalisation and Color Separation are transversal to any Framework of Histopathology Image Analysis.

An Android malware detection system based on machine learning

NASA Astrophysics Data System (ADS)

Wen, Long; Yu, Haiyang

2017-08-01

The Android smartphone, with its open source character and excellent performance, has attracted many users. However, the convenience of the Android platform also has motivated the development of malware. The traditional method which detects the malware based on the signature is unable to detect unknown applications. The article proposes a machine learning-based lightweight system that is capable of identifying malware on Android devices. In this system we extract features based on the static analysis and the dynamitic analysis, then a new feature selection approach based on principle component analysis (PCA) and relief are presented in the article to decrease the dimensions of the features. After that, a model will be constructed with support vector machine (SVM) for classification. Experimental results show that our system provides an effective method in Android malware detection.

Aging-dependent alterations in gene expression and a mitochondrial signature of responsiveness to human influenza vaccination.

PubMed

Thakar, Juilee; Mohanty, Subhasis; West, A Phillip; Joshi, Samit R; Ueda, Ikuyo; Wilson, Jean; Meng, Hailong; Blevins, Tamara P; Tsang, Sui; Trentalange, Mark; Siconolfi, Barbara; Park, Koonam; Gill, Thomas M; Belshe, Robert B; Kaech, Susan M; Shadel, Gerald S; Kleinstein, Steven H; Shaw, Albert C

2015-01-01

To elucidate gene expression pathways underlying age-associated impairment in influenza vaccine response, we screened young (age 21-30) and older (age≥65) adults receiving influenza vaccine in two consecutive seasons and identified those with strong or absent response to vaccine, including a subset of older adults meeting criteria for frailty. PBMCs obtained prior to vaccination (Day 0) and at day 2 or 4, day 7 and day 28 post-vaccine were subjected to gene expression microarray analysis. We defined a response signature and also detected induction of a type I interferon response at day 2 and a plasma cell signature at day 7 post-vaccine in young responders. The response signature was dysregulated in older adults, with the plasma cell signature induced at day 2, and was never induced in frail subjects (who were all non-responders). We also identified a mitochondrial signature in young vaccine responders containing genes mediating mitochondrial biogenesis and oxidative phosphorylation that was consistent in two different vaccine seasons and verified by analyses of mitochondrial content and protein expression. These results represent the first genome-wide transcriptional profiling analysis of age-associated dynamics following influenza vaccination, and implicate changes in mitochondrial biogenesis and function as a critical factor in human vaccine responsiveness.

Development of a rapid method for the automatic classification of biological agents' fluorescence spectral signatures

NASA Astrophysics Data System (ADS)

Carestia, Mariachiara; Pizzoferrato, Roberto; Gelfusa, Michela; Cenciarelli, Orlando; Ludovici, Gian Marco; Gabriele, Jessica; Malizia, Andrea; Murari, Andrea; Vega, Jesus; Gaudio, Pasquale

2015-11-01

Biosecurity and biosafety are key concerns of modern society. Although nanomaterials are improving the capacities of point detectors, standoff detection still appears to be an open issue. Laser-induced fluorescence of biological agents (BAs) has proved to be one of the most promising optical techniques to achieve early standoff detection, but its strengths and weaknesses are still to be fully investigated. In particular, different BAs tend to have similar fluorescence spectra due to the ubiquity of biological endogenous fluorophores producing a signal in the UV range, making data analysis extremely challenging. The Universal Multi Event Locator (UMEL), a general method based on support vector regression, is commonly used to identify characteristic structures in arrays of data. In the first part of this work, we investigate fluorescence emission spectra of different simulants of BAs and apply UMEL for their automatic classification. In the second part of this work, we elaborate a strategy for the application of UMEL to the discrimination of different BAs' simulants spectra. Through this strategy, it has been possible to discriminate between these BAs' simulants despite the high similarity of their fluorescence spectra. These preliminary results support the use of SVR methods to classify BAs' spectral signatures.

Second trimester maternal urine for the diagnosis of trisomy 21 and prediction of poor pregnancy outcomes.

PubMed

Diaz, Sílvia O; Barros, António S; Goodfellow, Brian J; Duarte, Iola F; Galhano, Eulália; Pita, Cristina; Almeida, Maria do Céu; Carreira, Isabel M; Gil, Ana M

2013-06-07

Given the recognized lack of prenatal clinical methods for the early diagnosis of preterm delivery, intrauterine growth restriction, preeclampsia and gestational diabetes mellitus, and the continuing need for optimized diagnosis methods for specific chromosomal disorders (e.g., trisomy 21) and fetal malformations, this work sought specific metabolic signatures of these conditions in second trimester maternal urine, using (1)H Nuclear Magnetic Resonance ((1)H NMR) metabolomics. Several variable importance to the projection (VIP)- and b-coefficient-based variable selection methods were tested, both individually and through their intersection, and the resulting data sets were analyzed by partial least-squares discriminant analysis (PLS-DA) and submitted to Monte Carlo cross validation (MCCV) and permutation tests to evaluate model predictive power. The NMR data subsets produced significantly improved PLS-DA models for all conditions except for pre-premature rupture of membranes. Specific urinary metabolic signatures were unveiled for central nervous system malformations, trisomy 21, preterm delivery, gestational diabetes, intrauterine growth restriction and preeclampsia, and biochemical interpretations were proposed. This work demonstrated, for the first time, the value of maternal urine profiling as a complementary means of prenatal diagnostics and early prediction of several poor pregnancy outcomes.

On the security of a novel probabilistic signature based on bilinear square Diffie-Hellman problem and its extension.

PubMed

Zhao, Zhenguo; Shi, Wenbo

2014-01-01

Probabilistic signature scheme has been widely used in modern electronic commerce since it could provide integrity, authenticity, and nonrepudiation. Recently, Wu and Lin proposed a novel probabilistic signature (PS) scheme using the bilinear square Diffie-Hellman (BSDH) problem. They also extended it to a universal designated verifier signature (UDVS) scheme. In this paper, we analyze the security of Wu et al.'s PS scheme and UDVS scheme. Through concrete attacks, we demonstrate both of their schemes are not unforgeable. The security analysis shows that their schemes are not suitable for practical applications.

Determination of spectral signatures of substances in natural waters

NASA Technical Reports Server (NTRS)

Klemas, V.; Philpot, W. D.; Davis, G.

1978-01-01

Optical remote sensing of water pollution offers the possibility of fast, large scale coverage at a relatively low cost. The possibility of using the spectral characteristics of the upwelling light from water for the purpose of ocean water quality monitoring was explained. The work was broken into several broad tasks as follows: (1) definition of a remotely measured spectral signature of water, (2) collection of field data and testing of the signature analysis, and (3) the possibility of using LANDSAT data for the identification of substances in water. An attempt to extract spectral signatures of acid waste and sediment was successful.

Shell Buckling Design Criteria Based on Manufacturing Imperfection Signatures

NASA Technical Reports Server (NTRS)

Hilburger, Mark W.; Nemeth, Michael P.; Starnes, James H., Jr.

2004-01-01

An analysis-based approach .for developing shell-buckling design criteria for laminated-composite cylindrical shells that accurately accounts for the effects of initial geometric imperfections is presented. With this approach, measured initial geometric imperfection data from six graphite-epoxy shells are used to determine a manufacturing-process-specific imperfection signature for these shells. This imperfection signature is then used as input into nonlinear finite-element analyses. The imperfection signature represents a "first-approximation" mean imperfection shape that is suitable for developing preliminary-design data. Comparisons of test data and analytical results obtained by using several different imperfection shapes are presented for selected shells. Overall, the results indicate that the analysis-based approach presented for developing reliable preliminary-design criteria has the potential to provide improved, less conservative buckling-load estimates, and to reduce the weight and cost of developing buckling-resistant shell structures.

Statistical Methods for Passive Vehicle Classification in Urban Traffic Surveillance and Control

DOT National Transportation Integrated Search

1980-01-01

A statistical approach to passive vehicle classification using the phase-shift signature from electromagnetic presence-type vehicle detectors is developed with digitized samples of the analog phase-shift signature, the problem of classifying vehicle ...

Novel Molecular Method for Identification of Streptococcus pneumoniae Applicable to Clinical Microbiology and 16S rRNA Sequence-Based Microbiome Studies

PubMed Central

Scholz, Christian F. P.; Poulsen, Knud

2012-01-01

The close phylogenetic relationship of the important pathogen Streptococcus pneumoniae and several species of commensal streptococci, particularly Streptococcus mitis and Streptococcus pseudopneumoniae, and the recently demonstrated sharing of genes and phenotypic traits previously considered specific for S. pneumoniae hamper the exact identification of S. pneumoniae. Based on sequence analysis of 16S rRNA genes of a collection of 634 streptococcal strains, identified by multilocus sequence analysis, we detected a cytosine at position 203 present in all 440 strains of S. pneumoniae but replaced by an adenosine residue in all strains representing other species of mitis group streptococci. The S. pneumoniae-specific sequence signature could be demonstrated by sequence analysis or indirectly by restriction endonuclease digestion of a PCR amplicon covering the site. The S. pneumoniae-specific signature offers an inexpensive means for validation of the identity of clinical isolates and should be used as an integrated marker in the annotation procedure employed in 16S rRNA-based molecular studies of complex human microbiotas. This may avoid frequent misidentifications such as those we demonstrate to have occurred in previous reports and in reference sequence databases. PMID:22442329

The Mimas ghost revisited - An analysis of the electron flux and electron microsignatures observed in the vicinity of Mimas at Saturn

NASA Technical Reports Server (NTRS)

Chenette, D. L.; Stone, E. C.

1983-01-01

An analysis of the electron-absorption signature observed by the cosmic-ray system on Voyager 2 near the orbit of Mimas is presented. It is found that these observations cannot be explained as the absorption signature of Mimas. By combining Pioneer 11 and Voyager 2 measurements of the electron flux at Mimas's orbit (L = 3.1), an electron spectrum is found in which most of the flux above about 100 keV is concentrated near 1 to 3 MeV. This spectral form is qualitatively consistent with the bandpass filter model of Van Allen et al. (1980). The expected Mimas absorption signature is calculated from this spectrum neglecting radial diffusion. Since no Mimas absorption signature was observed in the inbound Voyager 2 data, a lower limit on the diffusion coefficient for MeV electrons at L = 3.1 of D greater than 10 to the -8th sq Saturn radii/sec is obtained. With a diffusion coefficient this large, both the Voyager 2 and the Pioneer 11 small-scale electron-absorption-signature observations in Mimas's orbit are enigmatic. Thus the mechanism for producing these signatures is referred to as the Mimas ghost. A cloud of material in orbit with Mimas may account for the observed electron signature if the cloud is at least 1-percent opaque to electrons across a region extending over a few hundred kilometers.

Identifying prognostic signature in ovarian cancer using DirGenerank

PubMed Central

Wang, Jian-Yong; Chen, Ling-Ling; Zhou, Xiong-Hui

2017-01-01

Identifying the prognostic genes in cancer is essential not only for the treatment of cancer patients, but also for drug discovery. However, it's still a big challenge to select the prognostic genes that can distinguish the risk of cancer patients across various data sets because of tumor heterogeneity. In this situation, the selected genes whose expression levels are statistically related to prognostic risks may be passengers. In this paper, based on gene expression data and prognostic data of ovarian cancer patients, we used conditional mutual information to construct gene dependency network in which the nodes (genes) with more out-degrees have more chances to be the modulators of cancer prognosis. After that, we proposed DirGenerank (Generank in direct netowrk) algorithm, which concerns both the gene dependency network and genes’ correlations to prognostic risks, to identify the gene signature that can predict the prognostic risks of ovarian cancer patients. Using ovarian cancer data set from TCGA (The Cancer Genome Atlas) as training data set, 40 genes with the highest importance were selected as prognostic signature. Survival analysis of these patients divided by the prognostic signature in testing data set and four independent data sets showed the signature can distinguish the prognostic risks of cancer patients significantly. Enrichment analysis of the signature with curated cancer genes and the drugs selected by CMAP showed the genes in the signature may be drug targets for therapy. In summary, we have proposed a useful pipeline to identify prognostic genes of cancer patients. PMID:28615526

Current status of the real-time processing of complex radar signatures

NASA Astrophysics Data System (ADS)

Clay, E.

The real-time processing technique developed by ONERA to characterize radar signatures at the Brahms station is described. This technique is used for the real-time analysis of the RCS of airframes and rotating parts, the one-dimensional tomography of aircraft, and the RCS of electromagnetic decoys. Using this technique, it is also possible to optimize the experimental parameters, i.e., the analysis band, the microwave-network gain, and the electromagnetic window of the analysis.

Analysis of Forgery Attack on One-Time Proxy Signature and the Improvement

NASA Astrophysics Data System (ADS)

Wang, Tian-Yin; Wei, Zong-Li

2016-02-01

In a recent paper, Yang et al. (Quant. Inf. Process. 13(9), 2007-2016, 2014) analyzed the security of one-time proxy signature scheme Wang and Wei (Quant. Inf. Process. 11(2), 455-463, 2012) and pointed out that it cannot satisfy the security requirements of unforgeability and undeniability because an eavesdropper Eve can forge a valid proxy signature on a message chosen by herself. However, we find that the so-called proxy message-signature pair forged by Eve is issued by the proxy signer in fact, and anybody can obtain it as a requester, which means that the forgery attack is not considered as a successful attack. Therefore, the conclusion that this scheme cannot satisfy the security requirements of proxy signature against forging and denying is not appropriate in this sense. Finally, we study the reason for the misunderstanding and clarify the security requirements for proxy signatures.

A Robust Unified Approach to Analyzing Methylation and Gene Expression Data

PubMed Central

Khalili, Abbas; Huang, Tim; Lin, Shili

2009-01-01

Microarray technology has made it possible to investigate expression levels, and more recently methylation signatures, of thousands of genes simultaneously, in a biological sample. Since more and more data from different biological systems or technological platforms are being generated at an incredible rate, there is an increasing need to develop statistical methods that are applicable to multiple data types and platforms. Motivated by such a need, a flexible finite mixture model that is applicable to methylation, gene expression, and potentially data from other biological systems, is proposed. Two major thrusts of this approach are to allow for a variable number of components in the mixture to capture non-biological variation and small biases, and to use a robust procedure for parameter estimation and probe classification. The method was applied to the analysis of methylation signatures of three breast cancer cell lines. It was also tested on three sets of expression microarray data to study its power and type I error rates. Comparison with a number of existing methods in the literature yielded very encouraging results; lower type I error rates and comparable/better power were achieved based on the limited study. Furthermore, the method also leads to more biologically interpretable results for the three breast cancer cell lines. PMID:20161265

New method for the measurement of osmium isotopes applied to a New Zealand Cretaceous/Tertiary boundary shale

USGS Publications Warehouse

Lichte, F.E.; Wilson, S.M.; Brooks, R.R.; Reeves, R.D.; Holzbecher, J.; Ryan, D.E.

1986-01-01

The determination of osmium content and isotopic abundances in geological materials has received increasing attention in recent years following the proposal of Alvarez et al.1 that mass extinctions at the end of the Cretaceous period were caused by the impact of a large (???10km) meteorite which left anomalously high iridium levels as a geochemical signature in the boundary shales. Here we report a new and simple method for measuring osmium in geological materials, involving fusion of the sample with sodium peroxide, distillation of the osmium as the tetroxide using perchloric acid, extraction into chloroform, and absorption of the chloroform extract onto graphite powder before instrumental neutron activation analysis. In a variant of this technique, the chloroform extract is back-extracted into an aqueous phase and the osmium isotopes are determined by plasma-source mass spectrometry (ICPMS). We have used this method on the Woodside Creek (New Zealand) Cretaceous/Tertiary boundary clay and have obtained the first osmium content (6g ng g-1) for this material. The 187Os/186Os ratio is 1.12??0.16, showing a typical non-crustal signature. This combined distillation-extraction- ICPMS method will prove to be useful for measuring osmium isotopes in other geological materials. ?? 1986 Nature Publishing Group.

NMR ({sup 1}H and {sup 13}C) based signatures of abnormal choline metabolism in oral squamous cell carcinoma with no prominent Warburg effect

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bag, Swarnendu, E-mail: Swarna.bag@gmail.com; Banerjee, Deb Ranjan, E-mail: debranjan2@gmail.com; Basak, Amit, E-mail: absk@chem.iitkgp.ernet.in

At functional levels, besides genes and proteins, changes in metabolome profiles are instructive for a biological system in health and disease including malignancy. It is understood that metabolomic alterations in association with proteomic and transcriptomic aberrations are very fundamental to unravel malignant micro-ambient criticality and oral cancer is no exception. Hence deciphering intricate dimensions of oral cancer metabolism may be contributory both for integrated appreciation of its pathogenesis and to identify any critical but yet unexplored dimension of this malignancy with high mortality rate. Although several methods do exist, NMR provides higher analytical precision in identification of cancer metabolomic signature.more » Present study explored abnormal signatures in choline metabolism in oral squamous cell carcinoma (OSCC) using {sup 1}H and {sup 13}C NMR analysis of serum. It has demonstrated down-regulation of choline with concomitant up-regulation of its break-down product in the form of trimethylamine N-oxide in OSCC compared to normal counterpart. Further, no significant change in lactate profile in OSCC possibly indicated that well-known Warburg effect was not a prominent phenomenon in such malignancy. Amongst other important metabolites, malonate has shown up-regulation but D-glucose, saturated fatty acids, acetate and threonine did not show any significant change. Analyzing these metabolomic findings present study proposed trimethyl amine N-oxide and malonate as important metabolic signature for oral cancer with no prominent Warburg effect. - Highlights: • NMR ({sup 1}H and {sup 13}C) study of Oral Squamous cell Carcinoma Serum. • Abnormal Choline metabolomic signatures. • Up-regulation of Trimethylamine N-oxide. • Unchanged lactate profile indicates no prominent Warburg effect. • Proposed alternative glucose metabolism path through up-regulation of malonate.« less

Serum microRNAs as biomarkers for recurrence in melanoma

PubMed Central

2012-01-01

Background Identification of melanoma patients at high risk for recurrence and monitoring for recurrence are critical for informed management decisions. We hypothesized that serum microRNAs (miRNAs) could provide prognostic information at the time of diagnosis unaccounted for by the current staging system and could be useful in detecting recurrence after resection. Methods We screened 355 miRNAs in sera from 80 melanoma patients at primary diagnosis (discovery cohort) using a unique quantitative reverse transcription-PCR (qRT-PCR) panel. Cox proportional hazard models and Kaplan-Meier recurrence-free survival (RFS) curves were used to identify a miRNA signature with prognostic potential adjusting for stage. We then tested the miRNA signature in an independent cohort of 50 primary melanoma patients (validation cohort). Logistic regression analysis was performed to determine if the miRNA signature can determine risk of recurrence in both cohorts. Selected miRNAs were measured longitudinally in subsets of patients pre-/post-operatively and pre-/post-recurrence. Results A signature of 5 miRNAs successfully classified melanoma patients into high and low recurrence risk groups with significant separation of RFS in both discovery and validation cohorts (p = 0.0036, p = 0.0093, respectively). Significant separation of RFS was maintained when a logistic model containing the same signature set was used to predict recurrence risk in both discovery and validation cohorts (p < 0.0001, p = 0.033, respectively). Longitudinal expression of 4 miRNAs in a subset of patients was dynamic, suggesting miRNAs can be associated with tumor burden. Conclusion Our data demonstrate that serum miRNAs can improve accuracy in identifying primary melanoma patients with high recurrence risk and in monitoring melanoma tumor burden over time. PMID:22857597

Revealing the selection history of adaptive loci using genome-wide scans for selection: an example from domestic sheep.

PubMed

Rochus, Christina Marie; Tortereau, Flavie; Plisson-Petit, Florence; Restoux, Gwendal; Moreno-Romieux, Carole; Tosser-Klopp, Gwenola; Servin, Bertrand

2018-01-23

One of the approaches to detect genetics variants affecting fitness traits is to identify their surrounding genomic signatures of past selection. With established methods for detecting selection signatures and the current and future availability of large datasets, such studies should have the power to not only detect these signatures but also to infer their selective histories. Domesticated animals offer a powerful model for these approaches as they adapted rapidly to environmental and human-mediated constraints in a relatively short time. We investigated this question by studying a large dataset of 542 individuals from 27 domestic sheep populations raised in France, genotyped for more than 500,000 SNPs. Population structure analysis revealed that this set of populations harbour a large part of European sheep diversity in a small geographical area, offering a powerful model for the study of adaptation. Identification of extreme SNP and haplotype frequency differences between populations listed 126 genomic regions likely affected by selection. These signatures revealed selection at loci commonly identified as selection targets in many species ("selection hotspots") including ABCG2, LCORL/NCAPG, MSTN, and coat colour genes such as ASIP, MC1R, MITF, and TYRP1. For one of these regions (ABCG2, LCORL/NCAPG), we could propose a historical scenario leading to the introgression of an adaptive allele into a new genetic background. Among selection signatures, we found clear evidence for parallel selection events in different genetic backgrounds, most likely for different mutations. We confirmed this allelic heterogeneity in one case by resequencing the MC1R gene in three black-faced breeds. Our study illustrates how dense genetic data in multiple populations allows the deciphering of evolutionary history of populations and of their adaptive mutations.

Measurement of microbial activity in soil by colorimetric observation of in situ dye reduction: an approach to detection of extraterrestrial life

PubMed Central

Crawford, Ronald L; Paszczynski, Andrzej; Lang, Qingyong; Erwin, Daniel P; Allenbach, Lisa; Corti, Giancarlo; Anderson, Tony J; Cheng, I Francis; Wai, Chien; Barnes, Bruce; Wells, Richard; Assefi, Touraj; Mojarradi, Mohammad

2002-01-01

Background Detecting microbial life in extraterrestrial locations is a goal of space exploration because of ecological and health concerns about possible contamination of other planets with earthly organisms, and vice versa. Previously we suggested a method for life detection based on the fact that living entities require a continual input of energy accessed through coupled oxidations and reductions (an electron transport chain). We demonstrated using earthly soils that the identification of extracted components of electron transport chains is useful for remote detection of a chemical signature of life. The instrument package developed used supercritical carbon dioxide for soil extraction, followed by chromatography or electrophoresis to separate extracted compounds, with final detection by voltammetry and tandem mass-spectrometry. Results Here we used Earth-derived soils to develop a related life detection system based on direct observation of a biological redox signature. We measured the ability of soil microbial communities to reduce artificial electron acceptors. Living organisms in pure culture and those naturally found in soil were shown to reduce 2,3-dichlorophenol indophenol (DCIP) and the tetrazolium dye 2,3-bis(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide inner salt (XTT). Uninoculated or sterilized controls did not reduce the dyes. A soil from Antarctica that was determined by chemical signature and DNA analysis to be sterile also did not reduce the dyes. Conclusion Observation of dye reduction, supplemented with extraction and identification of only a few specific signature redox-active biochemicals such as porphyrins or quinones, provides a simplified means to detect a signature of life in the soils of other planets or their moons. PMID:12150716

Method for obtaining chromosome painting probes

DOEpatents

Lucas, Joe N.

2000-01-01

A method is provided for determining a clastogenic signature of a sample of chromosomes by quantifying a frequency of a first type of chromosome aberration present in the sample; quantifying a frequency of a second, different type of chromosome aberration present in the sample; and comparing the frequency of the first type of chromosome aberration to the frequency of the second type of chromosome aberration. A method is also provided for using that clastogenic signature to identify a clastogenic agent or dosage to which the cells were exposed.

Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle

PubMed Central

2014-01-01

Background Signatures of selection are regions in the genome that have been preferentially increased in frequency and fixed in a population because of their functional importance in specific processes. These regions can be detected because of their lower genetic variability and specific regional linkage disequilibrium (LD) patterns. Methods By comparing the differences in regional LD variation between dairy and beef cattle types, and between indicine and taurine subspecies, we aim at finding signatures of selection for production and adaptation in cattle breeds. The VarLD method was applied to compare the LD variation in the autosomal genome between breeds, including Angus and Brown Swiss, representing taurine breeds, and Nelore and Gir, representing indicine breeds. Genomic regions containing the top 0.01 and 0.1 percentile of signals were characterized using the UMD3.1 Bos taurus genome assembly to identify genes in those regions and compared with previously reported selection signatures and regions with copy number variation. Results For all comparisons, the top 0.01 and 0.1 percentile included 26 and 165 signals and 17 and 125 genes, respectively, including TECRL, BT.23182 or FPPS, CAST, MYOM1, UVRAG and DNAJA1. Conclusions The VarLD method is a powerful tool to identify differences in linkage disequilibrium between cattle populations and putative signatures of selection with potential adaptive and productive importance. PMID:24592996

Are Metabolic Signatures Mediating the Relationship between Lifestyle Factors and Hepatocellular Carcinoma Risk? Results from a Nested Case-Control Study in EPIC.

PubMed

Assi, Nada; Thomas, Duncan C; Leitzmann, Michael; Stepien, Magdalena; Chajès, Véronique; Philip, Thierry; Vineis, Paolo; Bamia, Christina; Boutron-Ruault, Marie-Christine; Sandanger, Torkjel M; Molinuevo, Amaia; Boshuizen, Hendriek C; Sundkvist, Anneli; Kühn, Tilman; Travis, Ruth C; Overvad, Kim; Riboli, Elio; Gunter, Marc J; Scalbert, Augustin; Jenab, Mazda; Ferrari, Pietro; Viallon, Vivian

2018-05-01

Background: The "meeting-in-the-middle" (MITM) is a principle to identify exposure biomarkers that are also predictors of disease. The MITM statistical framework was applied in a nested case-control study of hepatocellular carcinoma (HCC) within European Prospective Investigation into Cancer and Nutrition (EPIC), where healthy lifestyle index (HLI) variables were related to targeted serum metabolites. Methods: Lifestyle and targeted metabolomic data were available from 147 incident HCC cases and 147 matched controls. Partial least squares analysis related 7 lifestyle variables from a modified HLI to a set of 132 serum-measured metabolites and a liver function score. Mediation analysis evaluated whether metabolic profiles mediated the relationship between each lifestyle exposure and HCC risk. Results: Exposure-related metabolic signatures were identified. Particularly, the body mass index (BMI)-associated metabolic component was positively related to glutamic acid, tyrosine, PC aaC38:3, and liver function score and negatively to lysoPC aC17:0 and aC18:2. The lifetime alcohol-specific signature had negative loadings on sphingomyelins (SM C16:1, C18:1, SM(OH) C14:1, C16:1 and C22:2). Both exposures were associated with increased HCC with total effects (TE) = 1.23 (95% confidence interval = 0.93-1.62) and 1.40 (1.14-1.72), respectively, for BMI and alcohol consumption. Both metabolic signatures mediated the association between BMI and lifetime alcohol consumption and HCC with natural indirect effects, respectively, equal to 1.56 (1.24-1.96) and 1.09 (1.03-1.15), accounting for a proportion mediated of 100% and 24%. Conclusions: In a refined MITM framework, relevant metabolic signatures were identified as mediators in the relationship between lifestyle exposures and HCC risk. Impact: The understanding of the biological basis for the relationship between modifiable exposures and cancer would pave avenues for clinical and public health interventions on metabolic mediators. Cancer Epidemiol Biomarkers Prev; 27(5); 531-40. ©2018 AACR . ©2018 American Association for Cancer Research.

Ontology based molecular signatures for immune cell types via gene expression analysis

PubMed Central

2013-01-01

Background New technologies are focusing on characterizing cell types to better understand their heterogeneity. With large volumes of cellular data being generated, innovative methods are needed to structure the resulting data analyses. Here, we describe an ‘Ontologically BAsed Molecular Signature’ (OBAMS) method that identifies novel cellular biomarkers and infers biological functions as characteristics of particular cell types. This method finds molecular signatures for immune cell types based on mapping biological samples to the Cell Ontology (CL) and navigating the space of all possible pairwise comparisons between cell types to find genes whose expression is core to a particular cell type’s identity. Results We illustrate this ontological approach by evaluating expression data available from the Immunological Genome project (IGP) to identify unique biomarkers of mature B cell subtypes. We find that using OBAMS, candidate biomarkers can be identified at every strata of cellular identity from broad classifications to very granular. Furthermore, we show that Gene Ontology can be used to cluster cell types by shared biological processes in order to find candidate genes responsible for somatic hypermutation in germinal center B cells. Moreover, through in silico experiments based on this approach, we have identified genes sets that represent genes overexpressed in germinal center B cells and identify genes uniquely expressed in these B cells compared to other B cell types. Conclusions This work demonstrates the utility of incorporating structured ontological knowledge into biological data analysis – providing a new method for defining novel biomarkers and providing an opportunity for new biological insights. PMID:24004649

CHEMINFORMATICS TOOLS FOR TOXICANT CHARACTERIZATION

EPA Science Inventory

• Continued development of the Shape Signatures method is planed.  This effort will include further development of the Shape Signatures database of PDB-extracted ligands and of the clustering algorithm.

• In addition, we plan to develop an...

• Harvest locations of goose barnacles can be successfully discriminated using trace elemental signatures

  NASA Astrophysics Data System (ADS)

  Albuquerque, Rui; Queiroga, Henrique; Swearer, Stephen E.; Calado, Ricardo; Leandro, Sérgio M.

  2016-06-01

  European Union regulations state that consumers must be rightfully informed about the provenance of fishery products to prevent fraudulent practices. However, mislabeling of the geographical origin is a common practice. It is therefore paramount to develop forensic methods that allow all players involved in the supply chain to accurately trace the origin of seafood. In this study, trace elemental signatures (TES) of the goose barnacle Pollicipes pollicipes, collected from ten sites along the Portuguese coast, were employed to discriminate individual’s origin. Barium (Ba), boron (B), cadmium (Cd), chromium (Cr), lithium (Li), magnesium (Mg), manganese (Mn), phosphorous (P), lead (Pb), strontium (Sr) and zinc (Zn) - were quantified using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Significant differences were recorded among locations for all elements. A regularized discriminant analysis (RDA) revealed that 83% of all individuals were correctly assigned. This study shows TES can be a reliable tool to confirm the geographic origin of goose barnacles at fine spatial resolution. Although additional studies are required to ascertain the reliability of TES on cooked specimens and the temporal stability of the signature, the approach holds great promise for the management of goose barnacles fisheries, enforcement of conservation policies and assurance in accurate labeling.

• miRNA signature associated with outcome of gastric cancer patients following chemotherapy

  PubMed Central

  2011-01-01

  Background Identification of patients who likely will or will not benefit from cytotoxic chemotherapy through the use of biomarkers could greatly improve clinical management by better defining appropriate treatment options for patients. microRNAs may be potentially useful biomarkers that help guide individualized therapy for cancer because microRNA expression is dysregulated in cancer. In order to identify miRNA signatures for gastric cancer and for predicting clinical resistance to cisplatin/fluorouracil (CF) chemotherapy, a comprehensive miRNA microarray analysis was performed using endoscopic biopsy samples. Methods Biopsy samples were collected prior to chemotherapy from 90 gastric cancer patients treated with CF and from 34 healthy volunteers. At the time of disease progression, post-treatment samples were additionally collected from 8 clinical responders. miRNA expression was determined using a custom-designed Agilent microarray. In order to identify a miRNA signature for chemotherapy resistance, we correlated miRNA expression levels with the time to progression (TTP) of disease after CF therapy. Results A miRNA signature distinguishing gastric cancer from normal stomach epithelium was identified. 30 miRNAs were significantly inversely correlated with TTP whereas 28 miRNAs were significantly positively correlated with TTP of 82 cancer patients (P<0.05). Prominent among the upregulated miRNAs associated with chemosensitivity were miRNAs known to regulate apoptosis, including let-7g, miR-342, miR-16, miR-181, miR-1, and miR-34. When this 58-miRNA predictor was applied to a separate set of pre- and post-treatment tumor samples from the 8 clinical responders, all of the 8 pre-treatment samples were correctly predicted as low-risk, whereas samples from the post-treatment tumors that developed chemoresistance were predicted to be in the high-risk category by the 58 miRNA signature, suggesting that selection for the expression of these miRNAs occurred as chemoresistance arose. Conclusions We have identified 1) a miRNA expression signature that distinguishes gastric cancer from normal stomach epithelium from healthy volunteers, and 2) a chemoreresistance miRNA expression signature that is correlated with TTP after CF therapy. The chemoresistance miRNA expression signature includes several miRNAs previously shown to regulate apoptosis in vitro, and warrants further validation. PMID:22112324

• Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

  PubMed Central

  Tsai, Yu-Shuen; Aguan, Kripamoy; Pal, Nikhil R.; Chung, I-Fang

  2011-01-01

  Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases. PMID:21909426

• Numerical Predictions of Sonic Boom Signatures for a Straight Line Segmented Leading Edge Model

  NASA Technical Reports Server (NTRS)

  Elmiligui, Alaa A.; Wilcox, Floyd J.; Cliff, Susan; Thomas, Scott

  2012-01-01

  A sonic boom wind tunnel test was conducted on a straight-line segmented leading edge (SLSLE) model in the NASA Langley 4- by 4- Foot Unitary Plan Wind Tunnel (UPWT). The purpose of the test was to determine whether accurate sonic boom measurements could be obtained while continuously moving the SLSLE model past a conical pressure probe. Sonic boom signatures were also obtained using the conventional move-pause data acquisition method for comparison. The continuous data acquisition approach allows for accurate signatures approximately 15 times faster than a move-pause technique. These successful results provide an incentive for future testing with greatly increased efficiency using the continuous model translation technique with the single probe to measure sonic boom signatures. Two widely used NASA codes, USM3D (Navier-Stokes) and CART3D-AERO (Euler, adjoint-based adaptive mesh), were used to compute off-body sonic boom pressure signatures of the SLSLE model at several different altitudes below the model at Mach 2.0. The computed pressure signatures compared well with wind tunnel data. The effect of the different altitude for signature extraction was evaluated by extrapolating the near field signatures to the ground and comparing pressure signatures and sonic boom loudness levels.

• An Improved Quantum Proxy Blind Signature Scheme Based on Genuine Seven-Qubit Entangled State

  NASA Astrophysics Data System (ADS)

  Yang, Yuan-Yuan; Xie, Shu-Cui; Zhang, Jian-Zhong

  2017-07-01

  An improved quantum proxy blind signature scheme based on controlled teleportation is proposed in this paper. Genuine seven-qubit entangled state functions as quantum channel. We use the physical characteristics of quantum mechanics to implement delegation, signature and verification. Security analysis shows that our scheme is unforgeability, undeniability, blind and unconditionally secure. Meanwhile, we propose a trust party to provide higher security, the trust party is costless.

• VIPER: Chronic Pain after Amputation: Inflammatory Mechanisms, Novel Analgesic Pathways, and Improved Patient Safety

  DTIC Science & Technology

  2017-10-01

  Through analysis of data obtained in the Molecular Signatures of Chronic Pain Subtypes study termed Veterans Integrated Pain Evaluation Research...immune cells (macrophages) to chronic pain while also evaluating novel analgesics in relevant animal models. The current proposal also attempts to...analysis of data obtained in the Molecular Signatures of Chronic Pain Subtypes study termed Veterans Integrated Pain Evaluation Research (VIPER

• Energy performance assessment with empirical methods: application of energy signature

  NASA Astrophysics Data System (ADS)

  Belussi, L.; Danza, L.; Meroni, I.; Salamone, F.

  2015-03-01

  Energy efficiency and reduction of building consumption are deeply felt issues both at Italian and international level. The recent regulatory framework sets stringent limits on energy performance of buildings. Awaiting the adoption of these principles, several methods have been developed to solve the problem of energy consumption of buildings, among which the simplified energy audit is intended to identify any anomalies in the building system, to provide helpful tips for energy refurbishments and to raise end users' awareness. The Energy Signature is an operational tool of these methodologies, an evaluation method in which energy consumption is correlated with climatic variables, representing the actual energy behaviour of the building. In addition to that purpose, the Energy Signature can be used as an empirical tool to determine the real performances of the technical elements. The latter aspect is illustrated in this article.

• Finding the patterns in complex specimens by improving the acquisition and analysis of x-ray spectromicroscopy data

  NASA Astrophysics Data System (ADS)

  Lerotic, Mirna

  Soft x-ray spectromicroscopy provides spectral data on the chemical speciation of light elements at sub-100 nanometer spatial resolution. The high resolution imaging places a strong demand on the microscope stability and on the reproducibility of the scanned image field, and the volume of data necessitates the need for improved data analysis methods. This dissertation concerns two developments in extending the capability of soft x-ray transmission microscopes to carry out studies of chemical speciation at high spatial resolution. One development involves an improvement in x-ray microscope instrumentation: a new Stony Brook scanning transmission x-ray microscope which incorporates laser interferometer feedback in scanning stage positions. The interferometer is used to control the position between the sample and focusing optics, and thus improve the stability of the system. A second development concerns new analysis methods for the study of chemical speciation of complex specimens, such as those in biological and environmental science studies. When all chemical species in a specimen are known and separately characterized, existing approaches can be used to measure the concentration of each component at each pixel. In other cases (such as often occur in biology or environmental science), where the specimen may be too complicated or provide at least some unknown spectral signatures, other approaches must be used. We describe here an approach that uses principal component analysis (similar to factor analysis) to orthogonalize and noise-filter spectromicroscopy data. We then use cluster analysis (a form of unsupervised pattern matching) to classify pixels according to spectral similarity, to extract representative, cluster-averaged spectra with good signal-to-noise ratio, and to obtain gradations of concentration of these representative spectra at each pixel. The method is illustrated with a simulated data set of organic compounds, and a mixture of lutetium in hematite used to understand colloidal transport properties of radionuclides. Also, we describe here an extension of that work employing an angle distance measure; this measure provides better classification based on spectral signatures alone in specimens with significant thickness variations. The method is illustrated using simulated data, and also to examine sporulation in the bacterium Clostridium sp.

• A novel genome signature based on inter-nucleotide distances profiles for visualization of metagenomic data

  NASA Astrophysics Data System (ADS)

  Xie, Xian-Hua; Yu, Zu-Guo; Ma, Yuan-Lin; Han, Guo-Sheng; Anh, Vo

  2017-09-01

  There has been a growing interest in visualization of metagenomic data. The present study focuses on the visualization of metagenomic data using inter-nucleotide distances profile. We first convert the fragment sequences into inter-nucleotide distances profiles. Then we analyze these profiles by principal component analysis. Finally the principal components are used to obtain the 2-D scattered plot according to their source of species. We name our method as inter-nucleotide distances profiles (INP) method. Our method is evaluated on three benchmark data sets used in previous published papers. Our results demonstrate that the INP method is good, alternative and efficient for visualization of metagenomic data.

• A signature correlation study of ground target VHF/UHF ISAR imagery

  NASA Astrophysics Data System (ADS)

  Gatesman, Andrew J.; Beaudoin, Christopher J.; Giles, Robert H.; Kersey, William T.; Waldman, Jerry; Carter, Steve; Nixon, William E.

  2003-09-01

  VV and HH-polarized radar signatures of several ground targets were acquired in the VHF/UHF band (171-342 MHz) by using 1/35th scale models and an indoor radar range operating from 6 to 12 GHz. Data were processed into medianized radar cross sections as well as focused, ISAR imagery. Measurement validation was confirmed by comparing the radar cross section of a test object with a method of moments radar cross section prediction code. The signatures of several vehicles from three vehicle classes (tanks, trunks, and TELs) were measured and a signature cross-correlation study was performed. The VHF/UHF band is currently being exploited for its foliage penetration ability, however, the coarse image resolution which results from the relatively long radar wavelengths suggests a more challenging target recognition problem. One of the study's goals was to determine the amount of unique signature content in VHF/UHF ISAR imagery of military ground vehicles. Open-field signatures are compared with each other as well as with simplified shapes of similar size. Signatures were also acquired on one vehicle in a variety of configurations to determine the impact of monitor target variations on the signature content at these frequencies.

• Discrimination Between Child and Adult Forms Using Radar Frequency Signature Analysis

  DTIC Science & Technology

  2013-03-14

  Distances. This sensor poses no risk to human subjects or persons operating the equipment. The 88 th Medical Group Bio -Environmental Safety...method of remotely characterizing human activity. Unlike optical sensors , radar systems need not rely upon line-of-sight or good weather to perform well...and in monitoring vital signs through chemical or bio - logical protection suits. These military applications have seen research as early as the mid

• Using Functional Signature Ontology (FUSION) to Identify Mechanisms of Action for Natural Products

  PubMed Central

  Potts, Malia B.; Kim, Hyun Seok; Fisher, Kurt W.; Hu, Youcai; Carrasco, Yazmin P.; Bulut, Gamze Betul; Ou, Yi-Hung; Herrera-Herrera, Mireya L.; Cubillos, Federico; Mendiratta, Saurabh; Xiao, Guanghua; Hofree, Matan; Ideker, Trey; Xie, Yang; Huang, Lily Jun-shen; Lewis, Robert E.; MacMillan, John B.; White, Michael A.

  2014-01-01

  A challenge for biomedical research is the development of pharmaceuticals that appropriately target disease mechanisms. Natural products can be a rich source of bioactive chemicals for medicinal applications but can act through unknown mechanisms and can be difficult to produce or obtain. To address these challenges, we developed a new marine-derived, renewable natural products resource and a method for linking bioactive derivatives of this library to the proteins and biological processes that they target in cells. We used cell-based screening and computational analysis to match gene expression signatures produced by natural products to those produced by siRNA and synthetic microRNA libraries. With this strategy, we matched proteins and microRNAs with diverse biological processes and also identified putative protein targets and mechanisms of action for several previously undescribed marine-derived natural products. We confirmed mechanistic relationships for selected short-interfering RNAs, microRNAs, and compounds with functional roles in autophagy, chemotaxis mediated by discoidin domain receptor 2, or activation of the kinase AKT. Thus, this approach may be an effective method for screening new drugs while simultaneously identifying their targets. PMID:24129700

• Quantification of 235U and 238U activity concentrations for undeclared nuclear materials by a digital gamma-gamma coincidence spectroscopy.

  PubMed

  Zhang, Weihua; Yi, Jing; Mekarski, Pawel; Ungar, Kurt; Hauck, Barry; Kramer, Gary H

  2011-06-01

  The purpose of this study is to investigate the possibility of verifying depleted uranium (DU), natural uranium (NU), low enriched uranium (LEU) and high enriched uranium (HEU) by a developed digital gamma-gamma coincidence spectroscopy. The spectroscopy consists of two NaI(Tl) scintillators and XIA LLC Digital Gamma Finder (DGF)/Pixie-4 software and card package. The results demonstrate that the spectroscopy provides an effective method of (235)U and (238)U quantification based on the count rate of their gamma-gamma coincidence counting signatures. The main advantages of this approach over the conventional gamma spectrometry include the facts of low background continuum near coincident signatures of (235)U and (238)U, less interference from other radionuclides by the gamma-gamma coincidence counting, and region-of-interest (ROI) imagine analysis for uranium enrichment determination. Compared to conventional gamma spectrometry, the method offers additional advantage of requiring minimal calibrations for (235)U and (238)U quantification at different sample geometries. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

• Early forest fire detection using principal component analysis of infrared video

  NASA Astrophysics Data System (ADS)

  Saghri, John A.; Radjabi, Ryan; Jacobs, John T.

  2011-09-01

  A land-based early forest fire detection scheme which exploits the infrared (IR) temporal signature of fire plume is described. Unlike common land-based and/or satellite-based techniques which rely on measurement and discrimination of fire plume directly from its infrared and/or visible reflectance imagery, this scheme is based on exploitation of fire plume temporal signature, i.e., temperature fluctuations over the observation period. The method is simple and relatively inexpensive to implement. The false alarm rate is expected to be lower that of the existing methods. Land-based infrared (IR) cameras are installed in a step-stare-mode configuration in potential fire-prone areas. The sequence of IR video frames from each camera is digitally processed to determine if there is a fire within camera's field of view (FOV). The process involves applying a principal component transformation (PCT) to each nonoverlapping sequence of video frames from the camera to produce a corresponding sequence of temporally-uncorrelated principal component (PC) images. Since pixels that form a fire plume exhibit statistically similar temporal variation (i.e., have a unique temporal signature), PCT conveniently renders the footprint/trace of the fire plume in low-order PC images. The PC image which best reveals the trace of the fire plume is then selected and spatially filtered via simple threshold and median filter operations to remove the background clutter, such as traces of moving tree branches due to wind.

• Network information improves cancer outcome prediction.

  PubMed

  Roy, Janine; Winter, Christof; Isik, Zerrin; Schroeder, Michael

  2014-07-01

  Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression. © The Author 2012. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Quantum dual signature scheme based on coherent states with entanglement swapping

NASA Astrophysics Data System (ADS)

Liu, Jia-Li; Shi, Rong-Hua; Shi, Jin-Jing; Lv, Ge-Li; Guo, Ying

2016-08-01

A novel quantum dual signature scheme, which combines two signed messages expected to be sent to two diverse receivers Bob and Charlie, is designed by applying entanglement swapping with coherent states. The signatory Alice signs two different messages with unitary operations (corresponding to the secret keys) and applies entanglement swapping to generate a quantum dual signature. The dual signature is firstly sent to the verifier Bob who extracts and verifies the signature of one message and transmits the rest of the dual signature to the verifier Charlie who verifies the signature of the other message. The transmission of the dual signature is realized with quantum teleportation of coherent states. The analysis shows that the security of secret keys and the security criteria of the signature protocol can be greatly guaranteed. An extensional multi-party quantum dual signature scheme which considers the case with more than three participants is also proposed in this paper and this scheme can remain secure. The proposed schemes are completely suited for the quantum communication network including multiple participants and can be applied to the e-commerce system which requires a secure payment among the customer, business and bank. Project supported by the National Natural Science Foundation of China (Grant Nos. 61272495, 61379153, and 61401519) and the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20130162110012).

Superboom Caustic Analysis and Measurement Program (SCAMP) Final Report

NASA Technical Reports Server (NTRS)

Page, Juliet; Plotkin, Ken; Hobbs, Chris; Sparrow, Vic; Salamone, Joe; Cowart, Robbie; Elmer, Kevin; Welge, H. Robert; Ladd, John; Maglieri, Domenic;

RNA-Seq-based toxicogenomic assessment of fresh frozen and formalin-fixed tissues yields similar mechanistic insights.

PubMed

Auerbach, Scott S; Phadke, Dhiral P; Mav, Deepak; Holmgren, Stephanie; Gao, Yuan; Xie, Bin; Shin, Joo Heon; Shah, Ruchir R; Merrick, B Alex; Tice, Raymond R

2015-07-01

Formalin-fixed, paraffin-embedded (FFPE) pathology specimens represent a potentially vast resource for transcriptomic-based biomarker discovery. We present here a comparison of results from a whole transcriptome RNA-Seq analysis of RNA extracted from fresh frozen and FFPE livers. The samples were derived from rats exposed to aflatoxin B1 (AFB1 ) and a corresponding set of control animals. Principal components analysis indicated that samples were separated in the two groups representing presence or absence of chemical exposure, both in fresh frozen and FFPE sample types. Sixty-five percent of the differentially expressed transcripts (AFB1 vs. controls) in fresh frozen samples were also differentially expressed in FFPE samples (overlap significance: P < 0.0001). Genomic signature and gene set analysis of AFB1 differentially expressed transcript lists indicated highly similar results between fresh frozen and FFPE at the level of chemogenomic signatures (i.e., single chemical/dose/duration elicited transcriptomic signatures), mechanistic and pathology signatures, biological processes, canonical pathways and transcription factor networks. Overall, our results suggest that similar hypotheses about the biological mechanism of toxicity would be formulated from fresh frozen and FFPE samples. These results indicate that phenotypically anchored archival specimens represent a potentially informative resource for signature-based biomarker discovery and mechanistic characterization of toxicity. Copyright © 2014 John Wiley & Sons, Ltd.

Infrared spectroscopy as a screening technique for colitis

NASA Astrophysics Data System (ADS)

Titus, Jitto; Ghimire, Hemendra; Viennois, Emilie; Merlin, Didier; Perera, A. G. Unil

2017-05-01

There remains a great need for diagnosis of inflammatory bowel disease (IBD), for which the current technique, colonoscopy, is not cost-effective and presents a non-negligible risk for complications. Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy is a new screening technique to evaluate colitis. Comparing infrared spectra of sera to study the differences between them can prove challenging due to the complexity of its biological constituents giving rise to a plethora of vibrational modes. Overcoming these inherent infrared spectral analysis difficulties involving highly overlapping absorbance peaks and the analysis of the data by curve fitting to improve the resolution is discussed. The proposed technique uses colitic and normal wild type mice dried serum to obtain ATR/FTIR spectra to effectively differentiate colitic mice from normal mice. Using this method, Amide I group frequency (specifically, alpha helix to beta sheet ratio of the protein secondary structure) was identified as disease associated spectral signature in addition to the previously reported glucose and mannose signatures in sera of chronic and acute mice models of colitis. Hence, this technique will be able to identify changes in the sera due to various diseases.

Technical note: Headspace analysis of explosive compounds using a novel sampling chamber.

PubMed

DeGreeff, Lauryn; Rogers, Duane A; Katilie, Christopher; Johnson, Kevin; Rose-Pehrsson, Susan

2015-03-01

The development of instruments and methods for explosive vapor detection is a continually evolving field of interest. A thorough understanding of the characteristic vapor signatures of explosive material is imperative for the development and testing of new and current detectors. In this research a headspace sampling chamber was designed to contain explosive materials for the controlled, reproducible sampling and characterization of vapors associated with these materials. In a detonation test, the chamber was shown to contain an explosion equivalent to three grams of trinitrotoluene (TNT) without damage to the chamber. The efficacy of the chamber in controlled headspace sampling was evaluated in laboratory tests with bulk explosive materials. Small quantities of TNT, triacetone triperoxide (TATP) and hexamethylene triperoxide diamine (HMTD) were separately placed in the sampling chamber, and the headspace of each material was analyzed by gas chromatography/mass spectrometry (GC/MS) with online cryogenic trapping to yield characteristic vapor signatures for each explosive compound. Chamber sampling conditions, temperature and sampling time, were varied to demonstrate suitability for precise headspace analysis. Published by Elsevier Ireland Ltd.

Proteomics goes forensic: Detection and mapping of blood signatures in fingermarks.

PubMed

Deininger, Lisa; Patel, Ekta; Clench, Malcolm R; Sears, Vaughn; Sammon, Chris; Francese, Simona

2016-06-01

A bottom up in situ proteomic method has been developed enabling the mapping of multiple blood signatures on the intact ridges of blood fingermarks by Matrix Assisted Laser Desorption Mass Spectrometry Imaging (MALDI-MSI). This method, at a proof of concept stage, builds upon recently published work demonstrating the opportunity to profile and identify multiple blood signatures in bloodstains via a bottom up proteomic approach. The present protocol addresses the limitation of the previously developed profiling method with respect to destructivity; destructivity should be avoided for evidence such as blood fingermarks, where the ridge detail must be preserved in order to provide the associative link between the biometric information and the events of bloodshed. Using a blood mark reference model, trypsin concentration and spraying conditions have been optimised within the technical constraints of the depositor eventually employed; the application of MALDI-MSI and Ion Mobility MS have enabled the detection, confirmation and visualisation of blood signatures directly onto the ridge pattern. These results are to be considered a first insight into a method eventually informing investigations (and judicial debates) of violent crimes in which the reliable and non-destructive detection and mapping of blood in fingermarks is paramount to reconstruct the events of bloodshed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Secure Hashing of Dynamic Hand Signatures Using Wavelet-Fourier Compression with BioPhasor Mixing and [InlineEquation not available: see fulltext.] Discretization

NASA Astrophysics Data System (ADS)

Wai Kuan, Yip; Teoh, Andrew B. J.; Ngo, David C. L.

2006-12-01

We introduce a novel method for secure computation of biometric hash on dynamic hand signatures using BioPhasor mixing and[InlineEquation not available: see fulltext.] discretization. The use of BioPhasor as the mixing process provides a one-way transformation that precludes exact recovery of the biometric vector from compromised hashes and stolen tokens. In addition, our user-specific[InlineEquation not available: see fulltext.] discretization acts both as an error correction step as well as a real-to-binary space converter. We also propose a new method of extracting compressed representation of dynamic hand signatures using discrete wavelet transform (DWT) and discrete fourier transform (DFT). Without the conventional use of dynamic time warping, the proposed method avoids storage of user's hand signature template. This is an important consideration for protecting the privacy of the biometric owner. Our results show that the proposed method could produce stable and distinguishable bit strings with equal error rates (EERs) of[InlineEquation not available: see fulltext.] and[InlineEquation not available: see fulltext.] for random and skilled forgeries for stolen token (worst case) scenario, and[InlineEquation not available: see fulltext.] for both forgeries in the genuine token (optimal) scenario.

Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma.

PubMed

Chen, Ming-Huang; Yang, Wu-Lung R; Lin, Kuan-Ting; Liu, Chia-Hung; Liu, Yu-Wen; Huang, Kai-Wen; Chang, Peter Mu-Hsin; Lai, Jin-Mei; Hsu, Chun-Nan; Chao, Kun-Mao; Kao, Cheng-Yan; Huang, Chi-Ying F

2011-01-01

Hepatocellular carcinoma (HCC) is an aggressive tumor with a poor prognosis. Currently, only sorafenib is approved by the FDA for advanced HCC treatment; therefore, there is an urgent need to discover candidate therapeutic drugs for HCC. We hypothesized that if a drug signature could reverse, at least in part, the gene expression signature of HCC, it might have the potential to inhibit HCC-related pathways and thereby treat HCC. To test this hypothesis, we first built an integrative platform, the "Encyclopedia of Hepatocellular Carcinoma genes Online 2", dubbed EHCO2, to systematically collect, organize and compare the publicly available data from HCC studies. The resulting collection includes a total of 4,020 genes. To systematically query the Connectivity Map (CMap), which includes 6,100 drug-mediated expression profiles, we further designed various gene signature selection and enrichment methods, including a randomization technique, majority vote, and clique analysis. Subsequently, 28 out of 50 prioritized drugs, including tanespimycin, trichostatin A, thioguanosine, and several anti-psychotic drugs with anti-tumor activities, were validated via MTT cell viability assays and clonogenic assays in HCC cell lines. To accelerate their future clinical use, possibly through drug-repurposing, we selected two well-established drugs to test in mice, chlorpromazine and trifluoperazine. Both drugs inhibited orthotopic liver tumor growth. In conclusion, we successfully discovered and validated existing drugs for potential HCC therapeutic use with the pipeline of Connectivity Map analysis and lab verification, thereby suggesting the usefulness of this procedure to accelerate drug repurposing for HCC treatment.

Signature-Discovery Approach for Sample Matching of a Nerve-Agent Precursor using Liquid Chromatography–Mass Spectrometry, XCMS, and Chemometrics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fraga, Carlos G.; Clowers, Brian H.; Moore, Ronald J.

2010-05-15

This report demonstrates the use of bioinformatic and chemometric tools on liquid chromatography mass spectrometry (LC-MS) data for the discovery of ultra-trace forensic signatures for sample matching of various stocks of the nerve-agent precursor known as methylphosphonic dichloride (dichlor). The use of the bioinformatic tool known as XCMS was used to comprehensively search and find candidate LC-MS peaks in a known set of dichlor samples. These candidate peaks were down selected to a group of 34 impurity peaks. Hierarchal cluster analysis and factor analysis demonstrated the potential of these 34 impurities peaks for matching samples based on their stock source.more » Only one pair of dichlor stocks was not differentiated from one another. An acceptable chemometric approach for sample matching was determined to be variance scaling and signal averaging of normalized duplicate impurity profiles prior to classification by k-nearest neighbors. Using this approach, a test set of dichlor samples were all correctly matched to their source stock. The sample preparation and LC-MS method permitted the detection of dichlor impurities presumably in the parts-per-trillion (w/w). The detection of a common impurity in all dichlor stocks that were synthesized over a 14-year period and by different manufacturers was an unexpected discovery. Our described signature-discovery approach should be useful in the development of a forensic capability to help in criminal investigations following chemical attacks.« less

IPRStats: visualization of the functional potential of an InterProScan run.

PubMed

Kelly, Ryan J; Vincent, David E; Friedberg, Iddo

2010-12-21

InterPro is a collection of protein signatures for the classification and automated annotation of proteins. Interproscan is a software tool that scans protein sequences against Interpro member databases using a variety of profile-based, hidden markov model and positional specific score matrix methods. It not only combines a set of analysis tools, but also performs data look-up from various sources, as well as some redundancy removal. Interproscan is robust and scalable, able to perform on any machine from a netbook to a large cluster. However, when performing whole-genome or metagenome analysis, there is a need for a fast statistical visualization of the results to have good initial grasp on the functional potential of the sequences in the analyzed data set. This is especially important when analyzing and comparing metagenomic or metaproteomic data-sets. IPRStats is a tool for the visualization of Interproscan results. Interproscan results are parsed from the Interproscan XML or EBIXML file into an SQLite or MySQL database. The results for each signature database scan are read and displayed as pie-charts or bar charts as summary statistics. A table is also provided, where each entry is a signature (e.g. a Pfam entry) accompanied by one or more Gene Ontology terms, if Interproscan was run using the Gene Ontology option. We present an platform-independent, open source licensed tool that is useful for Interproscan users who wish to view the summary of their results in a rapid and concise fashion.

On the Statistical Analysis of the Radar Signature of the MQM-34D

DTIC Science & Technology

1975-01-31

target drone for aspect angles near normal to the roll axis for a vertically polarized measurements system. The radar cross section and glint are... drone . The raw data from RATSCAT are reported in graphical form in an AFSWC three-volume report.. The results reported here are a statistical analysis of...Ta1get Drones , AFSWC-rR.74-0l, January 1974. 2James W. Wright, On the Statistical Analysis of the Radar Signature of the MQM-34D, Interim Report

Security analysis of boolean algebra based on Zhang-Wang digital signature scheme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Jinbin, E-mail: jbzheng518@163.com

2014-10-06

In 2005, Zhang and Wang proposed an improvement signature scheme without using one-way hash function and message redundancy. In this paper, we show that this scheme exits potential safety concerns through the analysis of boolean algebra, such as bitwise exclusive-or, and point out that mapping is not one to one between assembly instructions and machine code actually by means of the analysis of the result of the assembly program segment, and which possibly causes safety problems unknown to the software.

A wall interference assessment/correction system

NASA Technical Reports Server (NTRS)

Lo, Ching F.; Ulbrich, N.; Sickles, W. L.; Qian, Cathy X.

1992-01-01

A Wall Signature method, the Hackett method, has been selected to be adapted for the 12-ft Wind Tunnel wall interference assessment/correction (WIAC) system in the present phase. This method uses limited measurements of the static pressure at the wall, in conjunction with the solid wall boundary condition, to determine the strength and distribution of singularities representing the test article. The singularities are used in turn for estimating wall interferences at the model location. The Wall Signature method will be formulated for application to the unique geometry of the 12-ft Tunnel. The development and implementation of a working prototype will be completed, delivered and documented with a software manual. The WIAC code will be validated by conducting numerically simulated experiments rather than actual wind tunnel experiments. The simulations will be used to generate both free-air and confined wind-tunnel flow fields for each of the test articles over a range of test configurations. Specifically, the pressure signature at the test section wall will be computed for the tunnel case to provide the simulated 'measured' data. These data will serve as the input for the WIAC method-Wall Signature method. The performance of the WIAC method then may be evaluated by comparing the corrected parameters with those for the free-air simulation. Each set of wind tunnel/test article numerical simulations provides data to validate the WIAC method. A numerical wind tunnel test simulation is initiated to validate the WIAC methods developed in the project. In the present reported period, the blockage correction has been developed and implemented for a rectangular tunnel as well as the 12-ft Pressure Tunnel. An improved wall interference assessment and correction method for three-dimensional wind tunnel testing is presented in the appendix.

LINEBACkER: Bio-inspired Data Reduction Toward Real Time Network Traffic Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teuton, Jeremy R.; Peterson, Elena S.; Nordwall, Douglas J.

Abstract—One essential component of resilient cyber applications is the ability to detect adversaries and protect systems with the same flexibility adversaries will use to achieve their goals. Current detection techniques do not enable this degree of flexibility because most existing applications are built using exact or regular-expression matching to libraries of rule sets. Further, network traffic defies traditional cyber security approaches that focus on limiting access based on the use of passwords and examination of lists of installed or downloaded programs. These approaches do not readily apply to network traffic occurring beyond the access control point, and when the datamore » in question are combined control and payload data of ever increasing speed and volume. Manual analysis of network traffic is not normally possible because of the magnitude of the data that is being exchanged and the length of time that this analysis takes. At the same time, using an exact matching scheme to identify malicious traffic in real time often fails because the lists against which such searches must operate grow too large. In this work, we introduce an alternative method for cyber network detection based on similarity-measuring algorithms for gene sequence analysis. These methods are ideal because they were designed to identify similar but nonidentical sequences. We demonstrate that our method is generally applicable to the problem of network traffic analysis by illustrating its use in two different areas both based on different attributes of network traffic. Our approach provides a logical framework for organizing large collections of network data, prioritizing traffic of interest to human analysts, and makes it possible to discover traffic signatures without the bias introduced by expert-directed signature generation. Pattern recognition on reduced representations of network traffic offers a fast, efficient, and more robust way to detect anomalies.« less

Fault detection of gearbox using time-frequency method

NASA Astrophysics Data System (ADS)

Widodo, A.; Satrijo, Dj.; Prahasto, T.; Haryanto, I.

2017-04-01

This research deals with fault detection and diagnosis of gearbox by using vibration signature. In this work, fault detection and diagnosis are approached by employing time-frequency method, and then the results are compared with cepstrum analysis. Experimental work has been conducted for data acquisition of vibration signal thru self-designed gearbox test rig. This test-rig is able to demonstrate normal and faulty gearbox i.e., wears and tooth breakage. Three accelerometers were used for vibration signal acquisition from gearbox, and optical tachometer was used for shaft rotation speed measurement. The results show that frequency domain analysis using fast-fourier transform was less sensitive to wears and tooth breakage condition. However, the method of short-time fourier transform was able to monitor the faults in gearbox. Wavelet Transform (WT) method also showed good performance in gearbox fault detection using vibration signal after employing time synchronous averaging (TSA).

A Fast, Open EEG Classification Framework Based on Feature Compression and Channel Ranking

PubMed Central

Han, Jiuqi; Zhao, Yuwei; Sun, Hongji; Chen, Jiayun; Ke, Ang; Xu, Gesen; Zhang, Hualiang; Zhou, Jin; Wang, Changyong

2018-01-01

Superior feature extraction, channel selection and classification methods are essential for designing electroencephalography (EEG) classification frameworks. However, the performance of most frameworks is limited by their improper channel selection methods and too specifical design, leading to high computational complexity, non-convergent procedure and narrow expansibility. In this paper, to remedy these drawbacks, we propose a fast, open EEG classification framework centralized by EEG feature compression, low-dimensional representation, and convergent iterative channel ranking. First, to reduce the complexity, we use data clustering to compress the EEG features channel-wise, packing the high-dimensional EEG signal, and endowing them with numerical signatures. Second, to provide easy access to alternative superior methods, we structurally represent each EEG trial in a feature vector with its corresponding numerical signature. Thus, the recorded signals of many trials shrink to a low-dimensional structural matrix compatible with most pattern recognition methods. Third, a series of effective iterative feature selection approaches with theoretical convergence is introduced to rank the EEG channels and remove redundant ones, further accelerating the EEG classification process and ensuring its stability. Finally, a classical linear discriminant analysis (LDA) model is employed to classify a single EEG trial with selected channels. Experimental results on two real world brain-computer interface (BCI) competition datasets demonstrate the promising performance of the proposed framework over state-of-the-art methods. PMID:29713262

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors

PubMed Central

2010-01-01

Background Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. Methods We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. Results The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. Conclusions These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast tumors. PMID:20591134

Jet engine noise and infrared plume correlation field campaign

NASA Astrophysics Data System (ADS)

Cunio, Phillip M.; Weber, Reed A.; Knobel, Kimberly R.; Smith, Christine; Draudt, Andy

2015-09-01

Jet engine noise can be a health hazard and environmental pollutant, particularly affecting personnel working in close proximity to jet engines, such as airline mechanics. Mitigating noise could reduce the potential for hearing loss in runway workers; however, there exists a very complex relationship between jet engine design parameters, operating conditions, and resultant noise power levels, and understanding and characterizing this relationship is a key step in mitigating jet engine noise effects. We demonstrate initial results highlighting the utility of high-speed imaging (hypertemporal imaging) in correlating the infrared signatures of jet engines with acoustic noise. This paper builds on prior theoretical analysis of jet engine infrared signatures and their potential relationships to jet engine acoustic emissions. This previous work identified the region of the jet plume most likely to emit both in infrared and in acoustic domains, and it prompted the investigation of wave packets as a physical construct tying together acoustic and infrared energy emissions. As a means of verifying these assertions, a field campaign to collect relevant data was proposed, and data collection was carried out with a bank of infrared instruments imaging a T700 turboshaft engine undergoing routine operational testing. The detection of hypertemporal signatures in association with acoustic signatures of jet engines enables the use of a new domain in characterizing jet engine noise. This may in turn enable new methods of predicting or mitigating jet engine noise, which could lead to socioeconomic benefits for airlines and other operators of large numbers of jet engines.

A Comparative Analysis of the Influence of Surface Mining on Hydrological and Geochemical Response of Selected Headwater Streams in the Elk Valley, British Columbia, Canada.

NASA Astrophysics Data System (ADS)

Carey, S. K.; Shatilla, N. J.; Szmudrowska, B.; Rastelli, J.; Wellen, C.

2014-12-01

Surface mining is a common method of accessing coal. Blasting of overburden rock allows access to mineable ore. In high-elevation environments, the removed overburden rock is deposited in adjacent valleys as waste rock spoils. As part of a multi-year R&D program examining the influence of surface mining on watershed hydrological and water quality responses in the Elk Valley, British Columbia, this study reports on how surface mining affects streamflow hydrological and geochemical response at four reference and four mine-influenced catchments. The hydrology of this environment is dominated by snowmelt and steep topographic gradients. Flows were attenuated in mine-influenced catchments, with spring freshet delayed and more muted responses to precipitation events observed. Dissolved ions were an order of magnitude greater in mine-influenced streams, with more dilution-based responses to flows compared with chemostatic behavior observed in reference streams. Stable isotope signatures in stream water suggested that in both mine-influenced and reference watersheds, stream water was derived from well mixed groundwater as annual variability of stream isotope signatures was dampened compared with precipitation signatures. However, deflection of stream isotopes in response to precipitation were more apparent in reference watersheds. As a group, mine influenced catchments had a heavier isotope signature than reference watersheds, suggesting an enhanced influence of rainfall on recharge. Transit time distributions indicate existing waste rock spoils increase the average time water takes to move through the catchment.

Mitigating flood exposure: Reducing disaster risk and trauma signature.

PubMed

Shultz, James M; McLean, Andrew; Herberman Mash, Holly B; Rosen, Alexa; Kelly, Fiona; Solo-Gabriele, Helena M; Youngs, Georgia A; Jensen, Jessica; Bernal, Oscar; Neria, Yuval

2013-01-01

Introduction. In 2011, following heavy winter snowfall, two cities bordering two rivers in North Dakota, USA faced major flood threats. Flooding was foreseeable and predictable although the extent of risk was uncertain. One community, Fargo, situated in a shallow river basin, successfully mitigated and prevented flooding. For the other community, Minot, located in a deep river valley, prevention was not possible and downtown businesses and one-quarter of the homes were inundated, in the city's worst flood on record. We aimed at contrasting the respective hazards, vulnerabilities, stressors, psychological risk factors, psychosocial consequences, and disaster risk reduction strategies under conditions where flood prevention was, and was not, possible. Methods . We applied the "trauma signature analysis" (TSIG) approach to compare the hazard profiles, identify salient disaster stressors, document the key components of disaster risk reduction response, and examine indicators of community resilience. Results . Two demographically-comparable communities, Fargo and Minot, faced challenging river flood threats and exhibited effective coordination across community sectors. We examined the implementation of disaster risk reduction strategies in situations where coordinated citizen action was able to prevent disaster impact (hazard avoidance) compared to the more common scenario when unpreventable disaster strikes, causing destruction, harm, and distress. Across a range of indicators, it is clear that successful mitigation diminishes both physical and psychological impact, thereby reducing the trauma signature of the event. Conclusion . In contrast to experience of historic flooding in Minot, the city of Fargo succeeded in reducing the trauma signature by way of reducing risk through mitigation.

On the Security of a Novel Probabilistic Signature Based on Bilinear Square Diffie-Hellman Problem and Its Extension

PubMed Central

Zhao, Zhenguo; Shi, Wenbo

2014-01-01

Probabilistic signature scheme has been widely used in modern electronic commerce since it could provide integrity, authenticity, and nonrepudiation. Recently, Wu and Lin proposed a novel probabilistic signature (PS) scheme using the bilinear square Diffie-Hellman (BSDH) problem. They also extended it to a universal designated verifier signature (UDVS) scheme. In this paper, we analyze the security of Wu et al.'s PS scheme and UDVS scheme. Through concrete attacks, we demonstrate both of their schemes are not unforgeable. The security analysis shows that their schemes are not suitable for practical applications. PMID:25025083

Analysis of suspended solids by single-particle scattering. [for Lake Superior pollution monitoring

NASA Technical Reports Server (NTRS)

Diehl, S. R.; Smith, D. T.; Sydor, M.

1979-01-01

Light scattering by individual particulates is used in a multiple-detector system to categorize the composition of suspended solids in terms of broad particulate categories. The scattering signatures of red clay and taconite tailings, the two primary particulate contaminants in western Lake Superior, along with two types of asbestiform fibers, amphibole and chrysolite, were studied in detail. A method was developed to predict the concentration of asbestiform fibers in filtration plant samples for which electron microscope analysis was done concurrently. Fiber levels as low as 50,000 fibers/liter were optically detectable. The method has application in optical categorization of samples for remote sensing purposes and offers a fast, inexpensive means for analyzing water samples from filtration plants for specific particulate contaminants.

Literature Review of the Extraction and Analysis of Trace Contaminants in Food

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Audrey Martin; Alcaraz, Armando

2010-06-15

There exists a serious concern that chemical warfare agents (CWA) may be used in a terrorist attack against military or civilian populations. While many precautions have been taken on the military front (e.g. protective clothing, gas masks), such precautions are not suited for the widespread application to civilian populations. Thus, defense of the civilian population, and applicable to the military population, has focused on prevention and early detection. Early detection relies on accurate and sensitive analytical methods to detect and identify CWA in a variety of matrices. Once a CWA is detected, the analytical needs take on a forensic applicationmore » – are there any chemical signatures present in the sample that could indicate its source? These signatures could include byproducts of the reaction, unreacted starting materials, degradation products, or impurities. Therefore, it is important that the analytical method used can accurately identify such signatures, as well as the CWA itself. Contained herein is a review of the open literature describing the detection of CWA in various matrices and the detection of trace toxic chemicals in food. Several relevant reviews have been published in the literature,1-5 including a review of analytical separation techniques for CWA by Hooijschuur et al.1 The current review is not meant to reiterate the published manuscripts; is focused mainly on extraction procedures, as well as the detection of VX and its hydrolysis products, as it is closely related to Russian VX, which is not prevalent in the literature. It is divided by the detection technique used, as such; extraction techniques are included with each detection method.« less

Label-Free Raman Imaging to Monitor Breast Tumor Signatures.

PubMed

Manciu, Felicia S; Ciubuc, John D; Parra, Karla; Manciu, Marian; Bennet, Kevin E; Valenzuela, Paloma; Sundin, Emma M; Durrer, William G; Reza, Luis; Francia, Giulio

2017-08-01

Although not yet ready for clinical application, methods based on Raman spectroscopy have shown significant potential in identifying, characterizing, and discriminating between noncancerous and cancerous specimens. Real-time and accurate medical diagnosis achievable through this vibrational optical method largely benefits from improvements in current technological and software capabilities. Not only is the acquisition of spectral information now possible in milliseconds and analysis of hundreds of thousands of data points achieved in minutes, but Raman spectroscopy also allows simultaneous detection and monitoring of several biological components. Besides demonstrating a significant Raman signature distinction between nontumorigenic (MCF-10A) and tumorigenic (MCF-7) breast epithelial cells, our study demonstrates that Raman can be used as a label-free method to evaluate epidermal growth factor activity in tumor cells. Comparative Raman profiles and images of specimens in the presence or absence of epidermal growth factor show important differences in regions attributed to lipid, protein, and nucleic acid vibrations. The occurrence, which is dependent on the presence of epidermal growth factor, of new Raman features associated with the appearance of phosphothreonine and phosphoserine residues reflects a signal transduction from the membrane to the nucleus, with concomitant modification of DNA/RNA structural characteristics. Parallel Western blotting analysis reveals an epidermal growth factor induction of phosphorylated Akt protein, corroborating the Raman results. The analysis presented in this work is an important step toward Raman-based evaluation of biological activity of epidermal growth factor receptors on the surfaces of breast cancer cells. With the ultimate future goal of clinically implementing Raman-guided techniques for the diagnosis of breast tumors (e.g., with regard to specific receptor activity), the current results just lay the foundation for further label-free optical tools to diagnose the disease.

Imaging Surrogates of Infiltration Obtained Via Multiparametric Imaging Pattern Analysis Predict Subsequent Location of Recurrence of Glioblastoma

PubMed Central

Akbari, Hamed; Macyszyn, Luke; Da, Xiao; Bilello, Michel; Wolf, Ronald L.; Martinez-Lage, Maria; Biros, George; Alonso-Basanta, Michelle; O’Rourke, Donald M.; Davatzikos, Christos

2016-01-01

Background Glioblastoma is an aggressive and highly infiltrative brain cancer. Standard surgical resection is guided by enhancement on postcontrast T1-weighted (T1) magnetic resonance imaging (MRI), which is insufficient for delineating surrounding infiltrating tumor. Objective To develop imaging biomarkers that delineate areas of tumor infiltration and predict early recurrence in peritumoral tissue. Such markers would enable intensive, yet targeted, surgery and radiotherapy, thereby potentially delaying recurrence and prolonging survival. Methods Preoperative multiparametric MRIs (T1, T1-Gad, T2-weighted [T2], T2-fluid-attenuated inversion recovery [FLAIR], diffusion tensor imaging (DTI), and dynamic susceptibility contrast-enhanced [DSC]-MRI) from 31 patients were combined using machine learning methods, thereby creating predictive spatial maps of infiltrated peritumoral tissue. Cross validation was used in the retrospective cohort to achieve generalizable biomarkers. Subsequently, the imaging signatures learned from the retrospective study were used in a replication cohort of 34 new patients. Spatial maps representing likelihood of tumor infiltration and future early recurrence were compared to regions of recurrence on postresection follow-up studies with pathology confirmation. Results This technique produced predictions of early recurrence with a mean area under the curve (AUC) of 0.84, sensitivity of 91%, specificity of 93%, and odds ratio estimates of 9.29 (99% CI, 8.95–9.65) for tissue predicted to be heavily infiltrated in the replication study. Regions of tumor recurrence were found to have subtle, yet fairly distinctive multiparametric imaging signatures when analyzed quantitatively by pattern analysis and machine learning. Conclusion Visually imperceptible imaging patterns discovered via multiparametric pattern analysis methods were found to estimate the extent of infiltration and location of future tumor recurrence, paving the way for improved targeted treatment. PMID:26813856

Characteristics of genomic signatures derived using univariate methods and mechanistically anchored functional descriptors for predicting drug- and xenobiotic-induced nephrotoxicity.

PubMed

Shi, Weiwei; Bugrim, Andrej; Nikolsky, Yuri; Nikolskya, Tatiana; Brennan, Richard J

2008-01-01

ABSTRACT The ideal toxicity biomarker is composed of the properties of prediction (is detected prior to traditional pathological signs of injury), accuracy (high sensitivity and specificity), and mechanistic relationships to the endpoint measured (biological relevance). Gene expression-based toxicity biomarkers ("signatures") have shown good predictive power and accuracy, but are difficult to interpret biologically. We have compared different statistical methods of feature selection with knowledge-based approaches, using GeneGo's database of canonical pathway maps, to generate gene sets for the classification of renal tubule toxicity. The gene set selection algorithms include four univariate analyses: t-statistics, fold-change, B-statistics, and RankProd, and their combination and overlap for the identification of differentially expressed probes. Enrichment analysis following the results of the four univariate analyses, Hotelling T-square test, and, finally out-of-bag selection, a variant of cross-validation, were used to identify canonical pathway maps-sets of genes coordinately involved in key biological processes-with classification power. Differentially expressed genes identified by the different statistical univariate analyses all generated reasonably performing classifiers of tubule toxicity. Maps identified by enrichment analysis or Hotelling T-square had lower classification power, but highlighted perturbed lipid homeostasis as a common discriminator of nephrotoxic treatments. The out-of-bag method yielded the best functionally integrated classifier. The map "ephrins signaling" performed comparably to a classifier derived using sparse linear programming, a machine learning algorithm, and represents a signaling network specifically involved in renal tubule development and integrity. Such functional descriptors of toxicity promise to better integrate predictive toxicogenomics with mechanistic analysis, facilitating the interpretation and risk assessment of predictive genomic investigations.

Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer.

PubMed

Tamez-Peña, Jose-Gerardo; Rodriguez-Rojas, Juan-Andrés; Gomez-Rueda, Hugo; Celaya-Padilla, Jose-Maria; Rivera-Prieto, Roxana-Alicia; Palacios-Corona, Rebeca; Garza-Montemayor, Margarita; Cardona-Huerta, Servando; Treviño, Victor

2018-01-01

In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies. From digital mammograms, a semi-automated radiogenomics analysis generated 1,078 features describing the shape, signal distribution, and texture of tumors along their contralateral image used as control. From tumor biopsy, we estimated the OncotypeDX and PAM50 recurrence scores using gene expression microarrays. Then, we used multivariate analysis under stringent cross-validation to train models predicting recurrence scores. Few univariate features reached Spearman correlation coefficients above 0.4. Nevertheless, multivariate analysis yielded significantly correlated models for both signatures (correlation of OncotypeDX = 0.49 ± 0.07 and PAM50 = 0.32 ± 0.10 in stringent cross-validation and OncotypeDX = 0.83 and PAM50 = 0.78 for a unique model). Equivalent models trained from the unaffected contralateral breast were not correlated suggesting that the image signatures were tumor-specific and that overfitting was not a considerable issue. We also noted that models were improved by combining clinical information (triple negative status and progesterone receptor). The models used mostly wavelets and fractal features suggesting their importance to capture tumor information. Our results suggest that molecular-based recurrence risk and breast cancer subtypes have observable radiographic phenotypes. To our knowledge, this is the first study associating mammographic information to gene expression recurrence signatures.

Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer

PubMed Central

Tamez-Peña, Jose-Gerardo; Rodriguez-Rojas, Juan-Andrés; Gomez-Rueda, Hugo; Celaya-Padilla, Jose-Maria; Rivera-Prieto, Roxana-Alicia; Palacios-Corona, Rebeca; Garza-Montemayor, Margarita; Cardona-Huerta, Servando

2018-01-01

In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies. From digital mammograms, a semi-automated radiogenomics analysis generated 1,078 features describing the shape, signal distribution, and texture of tumors along their contralateral image used as control. From tumor biopsy, we estimated the OncotypeDX and PAM50 recurrence scores using gene expression microarrays. Then, we used multivariate analysis under stringent cross-validation to train models predicting recurrence scores. Few univariate features reached Spearman correlation coefficients above 0.4. Nevertheless, multivariate analysis yielded significantly correlated models for both signatures (correlation of OncotypeDX = 0.49 ± 0.07 and PAM50 = 0.32 ± 0.10 in stringent cross-validation and OncotypeDX = 0.83 and PAM50 = 0.78 for a unique model). Equivalent models trained from the unaffected contralateral breast were not correlated suggesting that the image signatures were tumor-specific and that overfitting was not a considerable issue. We also noted that models were improved by combining clinical information (triple negative status and progesterone receptor). The models used mostly wavelets and fractal features suggesting their importance to capture tumor information. Our results suggest that molecular-based recurrence risk and breast cancer subtypes have observable radiographic phenotypes. To our knowledge, this is the first study associating mammographic information to gene expression recurrence signatures. PMID:29596496

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer

PubMed Central

Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-01-01

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies. PMID:26397224

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer.

PubMed

Nguyen, Minh Nam; Choi, Tae Gyu; Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-10-13

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

Fire Signatures of Materials Used in Spacecraft Construction

NASA Technical Reports Server (NTRS)

Taylor, Christina

2003-01-01

The focus of my work this summer was fire safety, specifically determining fire signatures from the combustion of materials commonly found in the construction of spacecraft. This project was undertaken with the aim of addressing concerns for health and safety onboard spacecraft. Under certain conditions, burning electronics produce surprisingly large amounts of acrid smoke, release fine airborne particles and expel condensable aerosols. Similarly, some wire insulation and packing material evolves smoke when in contact with a hot surface. In the limited, enclosed space available on spacecraft, these combustion products may pose a nuisance at the very least - at worst, a hazard to health or equipment. There is also a concern for fire safety in early detection on spacecraft. Our goal for the summer was to determine the most effective methods to test the materials, develop a protocol for sampling, and generate samples for analysis. We restricted our testing to electronic components, packaging and insulation materials, and wire insulation materials.

Prediction of sonic boom at a focus

NASA Technical Reports Server (NTRS)

Plotkin, K. J.; Cantril, J. M.

1976-01-01

The behavior of sonic boom at a focus has been reviewed for the purpose of extending present sonic boom computational methods to include focal zones. The geometry of a focal zone - whether a smooth caustic, a cusped caustic, or a perfect focus to a point - determines the character of focused signatures. The seeming contradiction of various experimental data can be resolved by noting these differences. A ray acoustic analysis has been developed for quantitative determination of caustic geometry. The only reliable theory presently available for signatures at a focus is for a smooth caustic. There has been some controversy between theoretical and experimental values of a constant in the scaling law for this case. It has been found that this discrepancy can be resolved by accounting for the finite thickness of real sonic boom shock waves. These findings have been incorporated into an existing sonic boom computer program.

Current Trends in the Detection of Sociocultural Signatures: Data-Driven Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanfilippo, Antonio P.; Bell, Eric B.; Corley, Courtney D.

The harvesting of behavioral data and their analysis through evidence-based reasoning enable the detection of sociocultural signatures in their context to support situation awareness and decision making. Harvested data are used as training materials from which to infer computational models of sociocultural behaviors or calibrate parameters for such models. Harvested data also serve as evidence input that the models use to provide insights about observed and future behaviors for targets of interest. The harvested data is often the result of assembling diverse data types and aggregating them into a form suitable for analysis. Data need to be analyzed to bringmore » out the categories of content that are relevant to the domain being addressed in order to train or run a model. If, for example, we are modeling the intent of a group to engage in violent behavior using messages that the group has broadcasted, then these messages need to be processed to extract and measure indicators of violent intent. The extracted indicators and the associated measurements (e.g. rates or counts of occurrence) can then be used to train/calibrate and run computational models that assess the propensity for violence expressed in the source message. Ubiquitous access to the Internet, mobile telephony and technologies such as digital photography and digital video have enabled social media application platforms such as Facebook, YouTube, and Twitter that are altering the nature of human social interaction. The fast increasing pace of online social interaction introduces new challenges and opportunities for gathering sociocultural data. Challenges include the development of harvesting and processing techniques tailored to new data environments and formats (e.g. Twitter, Facebook), the integration of social media content with traditional media content, and the protection of personal privacy. As these and other challenges are addressed, a new wealth of behavioral data and data analysis methods becomes available that are shaping social computing as a strongly data-driven experimental discipline with an increasingly stronger impact on the decision-making process of groups and individuals alike. In this chapter, we review current advances and trends in the detection of sociocultural signatures. Specific embodiments of the issues discussed are provided with respect to the assessment of violent intent and sociopolitical contention. We begin by reviewing current approaches to the detection of sociocultural signatures in these domains. Next, we turn to the review of novel data harvesting methods for social media content. Finally, we discuss the application of sociocultural models to social media content, and conclude by commenting on current challenges and future developments.« less

MutSpec: a Galaxy toolbox for streamlined analyses of somatic mutation spectra in human and mouse cancer genomes.

PubMed

Ardin, Maude; Cahais, Vincent; Castells, Xavier; Bouaoun, Liacine; Byrnes, Graham; Herceg, Zdenko; Zavadil, Jiri; Olivier, Magali

2016-04-18

The nature of somatic mutations observed in human tumors at single gene or genome-wide levels can reveal information on past carcinogenic exposures and mutational processes contributing to tumor development. While large amounts of sequencing data are being generated, the associated analysis and interpretation of mutation patterns that may reveal clues about the natural history of cancer present complex and challenging tasks that require advanced bioinformatics skills. To make such analyses accessible to a wider community of researchers with no programming expertise, we have developed within the web-based user-friendly platform Galaxy a first-of-its-kind package called MutSpec. MutSpec includes a set of tools that perform variant annotation and use advanced statistics for the identification of mutation signatures present in cancer genomes and for comparing the obtained signatures with those published in the COSMIC database and other sources. MutSpec offers an accessible framework for building reproducible analysis pipelines, integrating existing methods and scripts developed in-house with publicly available R packages. MutSpec may be used to analyse data from whole-exome, whole-genome or targeted sequencing experiments performed on human or mouse genomes. Results are provided in various formats including rich graphical outputs. An example is presented to illustrate the package functionalities, the straightforward workflow analysis and the richness of the statistics and publication-grade graphics produced by the tool. MutSpec offers an easy-to-use graphical interface embedded in the popular Galaxy platform that can be used by researchers with limited programming or bioinformatics expertise to analyse mutation signatures present in cancer genomes. MutSpec can thus effectively assist in the discovery of complex mutational processes resulting from exogenous and endogenous carcinogenic insults.

Statistical analysis of the magnetization signatures of impact basins

NASA Astrophysics Data System (ADS)

Gabasova, L. R.; Wieczorek, M. A.

2017-09-01

We quantify the magnetic signatures of the largest lunar impact basins using recent mission data and robust statistical bounds, and obtain an early activity timeline for the lunar core dynamo which appears to peak earlier than indicated by Apollo paleointensity measurements.

Repliscan: a tool for classifying replication timing regions.

PubMed

Zynda, Gregory J; Song, Jawon; Concia, Lorenzo; Wear, Emily E; Hanley-Bowdoin, Linda; Thompson, William F; Vaughn, Matthew W

2017-08-07

Replication timing experiments that use label incorporation and high throughput sequencing produce peaked data similar to ChIP-Seq experiments. However, the differences in experimental design, coverage density, and possible results make traditional ChIP-Seq analysis methods inappropriate for use with replication timing. To accurately detect and classify regions of replication across the genome, we present Repliscan. Repliscan robustly normalizes, automatically removes outlying and uninformative data points, and classifies Repli-seq signals into discrete combinations of replication signatures. The quality control steps and self-fitting methods make Repliscan generally applicable and more robust than previous methods that classify regions based on thresholds. Repliscan is simple and effective to use on organisms with different genome sizes. Even with analysis window sizes as small as 1 kilobase, reliable profiles can be generated with as little as 2.4x coverage.

ToxCast: Developing Predictive Signatures of Chemically Induced Toxicity (Developing Predictive Bioactivity Signatures from ToxCasts HTS Data)

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry, bioactivity profiling and toxicogenomic data to predict potential for toxicity and prioritize limited testing resour...

Ensemble analyses improve signatures of tumour hypoxia and reveal inter-platform differences

PubMed Central

2014-01-01

Background The reproducibility of transcriptomic biomarkers across datasets remains poor, limiting clinical application. We and others have suggested that this is in-part caused by differential error-structure between datasets, and their incomplete removal by pre-processing algorithms. Methods To test this hypothesis, we systematically assessed the effects of pre-processing on biomarker classification using 24 different pre-processing methods and 15 distinct signatures of tumour hypoxia in 10 datasets (2,143 patients). Results We confirm strong pre-processing effects for all datasets and signatures, and find that these differ between microarray versions. Importantly, exploiting different pre-processing techniques in an ensemble technique improved classification for a majority of signatures. Conclusions Assessing biomarkers using an ensemble of pre-processing techniques shows clear value across multiple diseases, datasets and biomarkers. Importantly, ensemble classification improves biomarkers with initially good results but does not result in spuriously improved performance for poor biomarkers. While further research is required, this approach has the potential to become a standard for transcriptomic biomarkers. PMID:24902696

Investigation on the kurtosis filter and the derivation of convolutional sparse filter for impulsive signature enhancement

NASA Astrophysics Data System (ADS)

Jia, Xiaodong; Zhao, Ming; Di, Yuan; Jin, Chao; Lee, Jay

2017-01-01

Minimum Entropy Deconvolution (MED) filter, which is a non-parametric approach for impulsive signature detection, has been widely studied recently. Although the merits of the MED filter are manifold, this method tends to over highlight the dominant peaks and its performance becomes less stable when strong noise exists. In order to better understand the behavior of the MED filter, this study first investigated the mathematical fundamentals of the MED filter and then explained the reason why the MED filter tends to over highlight the dominant peaks. In order to pursue finer solutions for weak impulsive signature enhancement, the Convolutional Sparse Filter (CSF) is originally proposed in this work and the derivation of the CSF is presented in details. The superiority of the proposed CSF over the MED filter is validated by both simulated data and experimental data. The results demonstrate that CSF is an effective method for impulsive signature enhancement that could be applied in rotating machines for incipient fault detection.

Fuzzy Intervals for Designing Structural Signature: An Application to Graphic Symbol Recognition

NASA Astrophysics Data System (ADS)

Luqman, Muhammad Muzzamil; Delalandre, Mathieu; Brouard, Thierry; Ramel, Jean-Yves; Lladós, Josep

The motivation behind our work is to present a new methodology for symbol recognition. The proposed method employs a structural approach for representing visual associations in symbols and a statistical classifier for recognition. We vectorize a graphic symbol, encode its topological and geometrical information by an attributed relational graph and compute a signature from this structural graph. We have addressed the sensitivity of structural representations to noise, by using data adapted fuzzy intervals. The joint probability distribution of signatures is encoded by a Bayesian network, which serves as a mechanism for pruning irrelevant features and choosing a subset of interesting features from structural signatures of underlying symbol set. The Bayesian network is deployed in a supervised learning scenario for recognizing query symbols. The method has been evaluated for robustness against degradations & deformations on pre-segmented 2D linear architectural & electronic symbols from GREC databases, and for its recognition abilities on symbols with context noise i.e. cropped symbols.