Intrusion detection using rough set classification.

PubMed

Zhang, Lian-hua; Zhang, Guan-hua; Zhang, Jie; Bai, Ying-cai

2004-09-01

Recently machine learning-based intrusion detection approaches have been subjected to extensive researches because they can detect both misuse and anomaly. In this paper, rough set classification (RSC), a modern learning algorithm, is used to rank the features extracted for detecting intrusions and generate intrusion detection models. Feature ranking is a very critical step when building the model. RSC performs feature ranking before generating rules, and converts the feature ranking to minimal hitting set problem addressed by using genetic algorithm (GA). This is done in classical approaches using Support Vector Machine (SVM) by executing many iterations, each of which removes one useless feature. Compared with those methods, our method can avoid many iterations. In addition, a hybrid genetic algorithm is proposed to increase the convergence speed and decrease the training time of RSC. The models generated by RSC take the form of "IF-THEN" rules, which have the advantage of explication. Tests and comparison of RSC with SVM on DARPA benchmark data showed that for Probe and DoS attacks both RSC and SVM yielded highly accurate results (greater than 99% accuracy on testing set).

New Algorithm to Enable Construction and Display of 3D Structures from Scanning Probe Microscopy Images Acquired Layer-by-Layer.

PubMed

Deng, William Nanqiao; Wang, Shuo; Ventrici de Souza, Joao; Kuhl, Tonya L; Liu, Gang-Yu

2018-06-25

Scanning probe microscopy (SPM), such as atomic force microscopy (AFM), is widely known for high-resolution imaging of surface structures and nanolithography in two dimensions (2D), providing important physical insights into surface science and material science. This work reports a new algorithm to enable construction and display of layer-by-layer 3D structures from SPM images. The algorithm enables alignment of SPM images acquired during layer-by-layer deposition and removal of redundant features and faithfully constructs the deposited 3D structures. The display uses a "see-through" strategy to enable the structure of each layer to be visible. The results demonstrate high spatial accuracy as well as algorithm versatility; users can set parameters for reconstruction and display as per image quality and research needs. To the best of our knowledge, this method represents the first report to enable SPM technology for 3D imaging construction and display. The detailed algorithm is provided to facilitate usage of the same approach in any SPM software. These new capabilities support wide applications of SPM that require 3D image reconstruction and display, such as 3D nanoprinting and 3D additive and subtractive manufacturing and imaging.

Research on Segmentation Monitoring Control of IA-RWA Algorithm with Probe Flow

NASA Astrophysics Data System (ADS)

Ren, Danping; Guo, Kun; Yao, Qiuyan; Zhao, Jijun

2018-04-01

The impairment-aware routing and wavelength assignment algorithm with probe flow (P-IA-RWA) can make an accurate estimation for the transmission quality of the link when the connection request comes. But it also causes some problems. The probe flow data introduced in the P-IA-RWA algorithm can result in the competition for wavelength resources. In order to reduce the competition and the blocking probability of the network, a new P-IA-RWA algorithm with segmentation monitoring-control mechanism (SMC-P-IA-RWA) is proposed. The algorithm would reduce the holding time of network resources for the probe flow. It segments the candidate path suitably for the data transmitting. And the transmission quality of the probe flow sent by the source node will be monitored in the endpoint of each segment. The transmission quality of data can also be monitored, so as to make the appropriate treatment to avoid the unnecessary probe flow. The simulation results show that the proposed SMC-P-IA-RWA algorithm can effectively reduce the blocking probability. It brings a better solution to the competition for resources between the probe flow and the main data to be transferred. And it is more suitable for scheduling control in the large-scale network.

Identification of genes and gene pathways associated with major depressive disorder by integrative brain analysis of rat and human prefrontal cortex transcriptomes

PubMed Central

Malki, K; Pain, O; Tosto, M G; Du Rietz, E; Carboni, L; Schalkwyk, L C

2015-01-01

Despite moderate heritability estimates, progress in uncovering the molecular substrate underpinning major depressive disorder (MDD) has been slow. In this study, we used prefrontal cortex (PFC) gene expression from a genetic rat model of MDD to inform probe set prioritization in PFC in a human post-mortem study to uncover genes and gene pathways associated with MDD. Gene expression differences between Flinders sensitive (FSL) and Flinders resistant (FRL) rat lines were statistically evaluated using the RankProd, non-parametric algorithm. Top ranking probe sets in the rat study were subsequently used to prioritize orthologous selection in a human PFC in a case–control post-mortem study on MDD from the Stanley Brain Consortium. Candidate genes in the human post-mortem study were then tested against a matched control sample using the RankProd method. A total of 1767 probe sets were differentially expressed in the PFC between FSL and FRL rat lines at (q⩽0.001). A total of 898 orthologous probe sets was found on Affymetrix's HG-U95A chip used in the human study. Correcting for the number of multiple, non-independent tests, 20 probe sets were found to be significantly dysregulated between human cases and controls at q⩽0.05. These probe sets tagged the expression profile of 18 human genes (11 upregulated and seven downregulated). Using an integrative rat–human study, a number of convergent genes that may have a role in pathogenesis of MDD were uncovered. Eighty percent of these genes were functionally associated with a key stress response signalling cascade, involving NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells), AP-1 (activator protein 1) and ERK/MAPK, which has been systematically associated with MDD, neuroplasticity and neurogenesis. PMID:25734512

Anopheles gambiae genome reannotation through synthesis of ab initio and comparative gene prediction algorithms

PubMed Central

Li, Jun; Riehle, Michelle M; Zhang, Yan; Xu, Jiannong; Oduol, Frederick; Gomez, Shawn M; Eiglmeier, Karin; Ueberheide, Beatrix M; Shabanowitz, Jeffrey; Hunt, Donald F; Ribeiro, José MC; Vernick, Kenneth D

2006-01-01

Background Complete genome annotation is a necessary tool as Anopheles gambiae researchers probe the biology of this potent malaria vector. Results We reannotate the A. gambiae genome by synthesizing comparative and ab initio sets of predicted coding sequences (CDSs) into a single set using an exon-gene-union algorithm followed by an open-reading-frame-selection algorithm. The reannotation predicts 20,970 CDSs supported by at least two lines of evidence, and it lowers the proportion of CDSs lacking start and/or stop codons to only approximately 4%. The reannotated CDS set includes a set of 4,681 novel CDSs not represented in the Ensembl annotation but with EST support, and another set of 4,031 Ensembl-supported genes that undergo major structural and, therefore, probably functional changes in the reannotated set. The quality and accuracy of the reannotation was assessed by comparison with end sequences from 20,249 full-length cDNA clones, and evaluation of mass spectrometry peptide hit rates from an A. gambiae shotgun proteomic dataset confirms that the reannotated CDSs offer a high quality protein database for proteomics. We provide a functional proteomics annotation, ReAnoXcel, obtained by analysis of the new CDSs through the AnoXcel pipeline, which allows functional comparisons of the CDS sets within the same bioinformatic platform. CDS data are available for download. Conclusion Comprehensive A. gambiae genome reannotation is achieved through a combination of comparative and ab initio gene prediction algorithms. PMID:16569258

Quantitative Electron Probe Microanalysis: State of the Art

NASA Technical Reports Server (NTRS)

Carpernter, P. K.

2005-01-01

Quantitative electron-probe microanalysis (EPMA) has improved due to better instrument design and X-ray correction methods. Design improvement of the electron column and X-ray spectrometer has resulted in measurement precision that exceeds analytical accuracy. Wavelength-dispersive spectrometer (WDS) have layered-dispersive diffraction crystals with improved light-element sensitivity. Newer energy-dispersive spectrometers (EDS) have Si-drift detector elements, thin window designs, and digital processing electronics with X-ray throughput approaching that of WDS Systems. Using these systems, digital X-ray mapping coupled with spectrum imaging is a powerful compositional mapping tool. Improvements in analytical accuracy are due to better X-ray correction algorithms, mass absorption coefficient data sets,and analysis method for complex geometries. ZAF algorithms have ban superceded by Phi(pz) algorithms that better model the depth distribution of primary X-ray production. Complex thin film and particle geometries are treated using Phi(pz) algorithms, end results agree well with Monte Carlo simulations. For geological materials, X-ray absorption dominates the corretions end depends on the accuracy of mass absorption coefficient (MAC) data sets. However, few MACs have been experimentally measured, and the use of fitted coefficients continues due to general success of the analytical technique. A polynomial formulation of the Bence-Albec alpha-factor technique, calibrated using Phi(pz) algorithms, is used to critically evaluate accuracy issues and can be also be used for high 2% relative and is limited by measurement precision for ideal cases, but for many elements the analytical accuracy is unproven. The EPMA technique has improved to the point where it is frequently used instead of the petrogaphic microscope for reconnaissance work. Examples of stagnant research areas are: WDS detector design characterization of calibration standards, and the need for more complete treatment of the continuum X-ray fluorescence correction.

Direct coupling of tomography and ptychography

DOE PAGES

Gürsoy, Doğa

2017-08-09

We present a generalization of the ptychographic phase problem for recovering refractive properties of a three-dimensional object in a tomography setting. Our approach, which ignores the lateral overlapping probe requirements in existing ptychography algorithms, can enable the reconstruction of objects using highly flexible acquisition patterns and pave the way for sparse and rapid data collection with lower radiation exposure.

Setting up a probe based, closed tube real-time PCR assay for focused detection of variable sequence alterations.

PubMed

Becságh, Péter; Szakács, Orsolya

2014-10-01

During diagnostic workflow when detecting sequence alterations, sometimes it is important to design an algorithm that includes screening and direct tests in combination. Normally the use of direct test, which is mainly sequencing, is limited. There is an increased need for effective screening tests, with "closed tube" during the whole process and therefore decreasing the risk of PCR product contamination. The aim of this study was to design such a closed tube, detection probe based screening assay to detect different kind of sequence alterations in the exon 11 of the human c-kit gene region. Inside this region there are variable possible deletions and single nucleotide changes. During assay setup, more probe chemistry formats were screened and tested. After some optimization steps the taqman probe format was selected.

Expanding probe repertoire and improving reproducibility in human genomic hybridization

PubMed Central

Dorman, Stephanie N.; Shirley, Ben C.; Knoll, Joan H. M.; Rogan, Peter K.

2013-01-01

Diagnostic DNA hybridization relies on probes composed of single copy (sc) genomic sequences. Sc sequences in probe design ensure high specificity and avoid cross-hybridization to other regions of the genome, which could lead to ambiguous results that are difficult to interpret. We examine how the distribution and composition of repetitive sequences in the genome affects sc probe performance. A divide and conquer algorithm was implemented to design sc probes. With this approach, sc probes can include divergent repetitive elements, which hybridize to unique genomic targets under higher stringency experimental conditions. Genome-wide custom probe sets were created for fluorescent in situ hybridization (FISH) and microarray genomic hybridization. The scFISH probes were developed for detection of copy number changes within small tumour suppressor genes and oncogenes. The microarrays demonstrated increased reproducibility by eliminating cross-hybridization to repetitive sequences adjacent to probe targets. The genome-wide microarrays exhibited lower median coefficients of variation (17.8%) for two HapMap family trios. The coefficients of variations of commercial probes within 300 nt of a repetitive element were 48.3% higher than the nearest custom probe. Furthermore, the custom microarray called a chromosome 15q11.2q13 deletion more consistently. This method for sc probe design increases probe coverage for FISH and lowers variability in genomic microarrays. PMID:23376933

Benchmarking Procedures for High-Throughput Context Specific Reconstruction Algorithms

PubMed Central

Pacheco, Maria P.; Pfau, Thomas; Sauter, Thomas

2016-01-01

Recent progress in high-throughput data acquisition has shifted the focus from data generation to processing and understanding of how to integrate collected information. Context specific reconstruction based on generic genome scale models like ReconX or HMR has the potential to become a diagnostic and treatment tool tailored to the analysis of specific individuals. The respective computational algorithms require a high level of predictive power, robustness and sensitivity. Although multiple context specific reconstruction algorithms were published in the last 10 years, only a fraction of them is suitable for model building based on human high-throughput data. Beside other reasons, this might be due to problems arising from the limitation to only one metabolic target function or arbitrary thresholding. This review describes and analyses common validation methods used for testing model building algorithms. Two major methods can be distinguished: consistency testing and comparison based testing. The first is concerned with robustness against noise, e.g., missing data due to the impossibility to distinguish between the signal and the background of non-specific binding of probes in a microarray experiment, and whether distinct sets of input expressed genes corresponding to i.e., different tissues yield distinct models. The latter covers methods comparing sets of functionalities, comparison with existing networks or additional databases. We test those methods on several available algorithms and deduce properties of these algorithms that can be compared with future developments. The set of tests performed, can therefore serve as a benchmarking procedure for future algorithms. PMID:26834640

A Feature Selection Algorithm to Compute Gene Centric Methylation from Probe Level Methylation Data.

PubMed

Baur, Brittany; Bozdag, Serdar

2016-01-01

DNA methylation is an important epigenetic event that effects gene expression during development and various diseases such as cancer. Understanding the mechanism of action of DNA methylation is important for downstream analysis. In the Illumina Infinium HumanMethylation 450K array, there are tens of probes associated with each gene. Given methylation intensities of all these probes, it is necessary to compute which of these probes are most representative of the gene centric methylation level. In this study, we developed a feature selection algorithm based on sequential forward selection that utilized different classification methods to compute gene centric DNA methylation using probe level DNA methylation data. We compared our algorithm to other feature selection algorithms such as support vector machines with recursive feature elimination, genetic algorithms and ReliefF. We evaluated all methods based on the predictive power of selected probes on their mRNA expression levels and found that a K-Nearest Neighbors classification using the sequential forward selection algorithm performed better than other algorithms based on all metrics. We also observed that transcriptional activities of certain genes were more sensitive to DNA methylation changes than transcriptional activities of other genes. Our algorithm was able to predict the expression of those genes with high accuracy using only DNA methylation data. Our results also showed that those DNA methylation-sensitive genes were enriched in Gene Ontology terms related to the regulation of various biological processes.

Quantum algorithm for solving some discrete mathematical problems by probing their energy spectra

NASA Astrophysics Data System (ADS)

Wang, Hefeng; Fan, Heng; Li, Fuli

2014-01-01

When a probe qubit is coupled to a quantum register that represents a physical system, the probe qubit will exhibit a dynamical response only when it is resonant with a transition in the system. Using this principle, we propose a quantum algorithm for solving discrete mathematical problems based on the circuit model. Our algorithm has favorable scaling properties in solving some discrete mathematical problems.

A Java-based tool for the design of classification microarrays.

PubMed

Meng, Da; Broschat, Shira L; Call, Douglas R

2008-08-04

Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for analysis of subsequent experimental data. Additionally, PLASMID can be used to construct virtual microarrays with genomes from public databases, which can then be used to identify an optimal set of probes.

An entangling-probe attack on Shor's algorithm for factorization

NASA Astrophysics Data System (ADS)

Azuma, Hiroo

2018-02-01

We investigate how to attack Shor's quantum algorithm for factorization with an entangling probe. We show that an attacker can steal an exact solution of Shor's algorithm outside an institute where the quantum computer is installed if he replaces its initialized quantum register with entangled qubits, namely the entangling probe. He can apply arbitrary local operations to his own probe. Moreover, we assume that there is an unauthorized person who helps the attacker to commit a crime inside the institute. He tells garbage data obtained from measurements of the quantum register to the attacker secretly behind a legitimate user's back. If the attacker succeeds in cracking Shor's algorithm, the legitimate user obtains a random answer and does not notice the attacker's illegal acts. We discuss how to detect the attacker. Finally, we estimate a probability that the quantum algorithm inevitably makes an error, of which the attacker can take advantage.

Genes@Work: an efficient algorithm for pattern discovery and multivariate feature selection in gene expression data.

PubMed

Lepre, Jorge; Rice, J Jeremy; Tu, Yuhai; Stolovitzky, Gustavo

2004-05-01

Despite the growing literature devoted to finding differentially expressed genes in assays probing different tissues types, little attention has been paid to the combinatorial nature of feature selection inherent to large, high-dimensional gene expression datasets. New flexible data analysis approaches capable of searching relevant subgroups of genes and experiments are needed to understand multivariate associations of gene expression patterns with observed phenotypes. We present in detail a deterministic algorithm to discover patterns of multivariate gene associations in gene expression data. The patterns discovered are differential with respect to a control dataset. The algorithm is exhaustive and efficient, reporting all existent patterns that fit a given input parameter set while avoiding enumeration of the entire pattern space. The value of the pattern discovery approach is demonstrated by finding a set of genes that differentiate between two types of lymphoma. Moreover, these genes are found to behave consistently in an independent dataset produced in a different laboratory using different arrays, thus validating the genes selected using our algorithm. We show that the genes deemed significant in terms of their multivariate statistics will be missed using other methods. Our set of pattern discovery algorithms including a user interface is distributed as a package called Genes@Work. This package is freely available to non-commercial users and can be downloaded from our website (http://www.research.ibm.com/FunGen).

Morphological spot counting from stacked images for automated analysis of gene copy numbers by fluorescence in situ hybridization.

PubMed

Grigoryan, Artyom M; Dougherty, Edward R; Kononen, Juha; Bubendorf, Lukas; Hostetter, Galen; Kallioniemi, Olli

2002-01-01

Fluorescence in situ hybridization (FISH) is a molecular diagnostic technique in which a fluorescent labeled probe hybridizes to a target nucleotide sequence of deoxyribose nucleic acid. Upon excitation, each chromosome containing the target sequence produces a fluorescent signal (spot). Because fluorescent spot counting is tedious and often subjective, automated digital algorithms to count spots are desirable. New technology provides a stack of images on multiple focal planes throughout a tissue sample. Multiple-focal-plane imaging helps overcome the biases and imprecision inherent in single-focal-plane methods. This paper proposes an algorithm for global spot counting in stacked three-dimensional slice FISH images without the necessity of nuclei segmentation. It is designed to work in complex backgrounds, when there are agglomerated nuclei, and in the presence of illumination gradients. It is based on the morphological top-hat transform, which locates intensity spikes on irregular backgrounds. After finding signals in the slice images, the algorithm groups these together to form three-dimensional spots. Filters are employed to separate legitimate spots from fluorescent noise. The algorithm is set in a comprehensive toolbox that provides visualization and analytic facilities. It includes simulation software that allows examination of algorithm performance for various image and algorithm parameter settings, including signal size, signal density, and the number of slices.

Clinical tests of an ultrasonic periodontal probe

NASA Astrophysics Data System (ADS)

Hinders, Mark K.; Lynch, John E.; McCombs, Gayle B.

2002-05-01

A new ultrasonic periodontal probe has been developed that offers the potential for earlier detection of periodontal disease activity, non-invasive diagnosis, and greater reliability of measurement. A comparison study of the ultrasonic probe to both a manual probe, and a controlled-force probe was conducted to evaluate its clinical effectiveness. Twelve patients enrolled into this study. Two half-month examinations were conducted on each patient, scheduled one hour apart. A one-way analysis of variance was performed to compare the results for the three sets of probing depth measurements, followed by a repeated measures analysis to assess the reproducibility of the different probing techniques. These preliminary findings indicate that manual and ultrasonic probing measure different features of the pocket. Therefore, it is not obvious how the two depth measurements correspond to each other. However, both methods exhibited a similar tendency toward increasing pocket depths as Gingival Index scores increased. Based on the small sample size, further studies need to be conducted using a larger population of patients exhibiting a wider range of disease activity. In addition, studies that allow histological examination of the pocket after probing will help further evaluate the clinical effectiveness the ultrasonic probe. Future studies will also aid in the development of more effective automated feature recognition algorithms that convert the ultrasonic echoes into pocket depth readings.

Standardless quantification by parameter optimization in electron probe microanalysis

NASA Astrophysics Data System (ADS)

Limandri, Silvina P.; Bonetto, Rita D.; Josa, Víctor Galván; Carreras, Alejo C.; Trincavelli, Jorge C.

2012-11-01

A method for standardless quantification by parameter optimization in electron probe microanalysis is presented. The method consists in minimizing the quadratic differences between an experimental spectrum and an analytical function proposed to describe it, by optimizing the parameters involved in the analytical prediction. This algorithm, implemented in the software POEMA (Parameter Optimization in Electron Probe Microanalysis), allows the determination of the elemental concentrations, along with their uncertainties. The method was tested in a set of 159 elemental constituents corresponding to 36 spectra of standards (mostly minerals) that include trace elements. The results were compared with those obtained with the commercial software GENESIS Spectrum® for standardless quantification. The quantifications performed with the method proposed here are better in the 74% of the cases studied. In addition, the performance of the method proposed is compared with the first principles standardless analysis procedure DTSA for a different data set, which excludes trace elements. The relative deviations with respect to the nominal concentrations are lower than 0.04, 0.08 and 0.35 for the 66% of the cases for POEMA, GENESIS and DTSA, respectively.

A parallel implementation of the Wuchty algorithm with additional experimental filters to more thoroughly explore RNA conformational space.

PubMed

Stone, Jonathan W; Bleckley, Samuel; Lavelle, Sean; Schroeder, Susan J

2015-01-01

We present new modifications to the Wuchty algorithm in order to better define and explore possible conformations for an RNA sequence. The new features, including parallelization, energy-independent lonely pair constraints, context-dependent chemical probing constraints, helix filters, and optional multibranch loops, provide useful tools for exploring the landscape of RNA folding. Chemical probing alone may not necessarily define a single unique structure. The helix filters and optional multibranch loops are global constraints on RNA structure that are an especially useful tool for generating models of encapsidated viral RNA for which cryoelectron microscopy or crystallography data may be available. The computations generate a combinatorially complete set of structures near a free energy minimum and thus provide data on the density and diversity of structures near the bottom of a folding funnel for an RNA sequence. The conformational landscapes for some RNA sequences may resemble a low, wide basin rather than a steep funnel that converges to a single structure.

A 2D range Hausdorff approach to 3D facial recognition.

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

Koch, Mark William; Russ, Trina Denise; Little, Charles Quentin

2004-11-01

This paper presents a 3D facial recognition algorithm based on the Hausdorff distance metric. The standard 3D formulation of the Hausdorff matching algorithm has been modified to operate on a 2D range image, enabling a reduction in computation from O(N2) to O(N) without large storage requirements. The Hausdorff distance is known for its robustness to data outliers and inconsistent data between two data sets, making it a suitable choice for dealing with the inherent problems in many 3D datasets due to sensor noise and object self-occlusion. For optimal performance, the algorithm assumes a good initial alignment between probe and templatemore » datasets. However, to minimize the error between two faces, the alignment can be iteratively refined. Results from the algorithm are presented using 3D face images from the Face Recognition Grand Challenge database version 1.0.« less

Personalized Medicine in Veterans with Traumatic Brain Injuries

DTIC Science & Technology

2014-07-01

9 control cases are subjected to unsupervised hierarchical clustering analysis using the UPGMA algorithm with cosine correlation as the similarity...in unsu- pervised hierarchical clustering by the Un- weighted Pair-Group Method using Arithmetic averages ( UPGMA ) based on cosine correlation of row...of log2 trans- formed MAS5.0 signal values; probe set cluster- ing was performed by the UPGMA method using Cosine correlation as the similarity

Using genic sequence capture in combination with a syntenic pseudo genome to map a deletion mutant in a wheat species.

PubMed

Gardiner, Laura-Jayne; Gawroński, Piotr; Olohan, Lisa; Schnurbusch, Thorsten; Hall, Neil; Hall, Anthony

2014-12-01

Mapping-by-sequencing analyses have largely required a complete reference sequence and employed whole genome re-sequencing. In species such as wheat, no finished genome reference sequence is available. Additionally, because of its large genome size (17 Gb), re-sequencing at sufficient depth of coverage is not practical. Here, we extend the utility of mapping by sequencing, developing a bespoke pipeline and algorithm to map an early-flowering locus in einkorn wheat (Triticum monococcum L.) that is closely related to the bread wheat genome A progenitor. We have developed a genomic enrichment approach using the gene-rich regions of hexaploid bread wheat to design a 110-Mbp NimbleGen SeqCap EZ in solution capture probe set, representing the majority of genes in wheat. Here, we use the capture probe set to enrich and sequence an F2 mapping population of the mutant. The mutant locus was identified in T. monococcum, which lacks a complete genome reference sequence, by mapping the enriched data set onto pseudo-chromosomes derived from the capture probe target sequence, with a long-range order of genes based on synteny of wheat with Brachypodium distachyon. Using this approach we are able to map the region and identify a set of deleted genes within the interval. © 2014 The Authors.The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

Quantitative Real-Time PCR using the Thermo Scientific Solaris qPCR Assay

PubMed Central

Ogrean, Christy; Jackson, Ben; Covino, James

2010-01-01

The Solaris qPCR Gene Expression Assay is a novel type of primer/probe set, designed to simplify the qPCR process while maintaining the sensitivity and accuracy of the assay. These primer/probe sets are pre-designed to >98% of the human and mouse genomes and feature significant improvements from previously available technologies. These improvements were made possible by virtue of a novel design algorithm, developed by Thermo Scientific bioinformatics experts. Several convenient features have been incorporated into the Solaris qPCR Assay to streamline the process of performing quantitative real-time PCR. First, the protocol is similar to commonly employed alternatives, so the methods used during qPCR are likely to be familiar. Second, the master mix is blue, which makes setting the qPCR reactions easier to track. Third, the thermal cycling conditions are the same for all assays (genes), making it possible to run many samples at a time and reducing the potential for error. Finally, the probe and primer sequence information are provided, simplifying the publication process. Here, we demonstrate how to obtain the appropriate Solaris reagents using the GENEius product search feature found on the ordering web site (www.thermo.com/solaris) and how to use the Solaris reagents for performing qPCR using the standard curve method. PMID:20567213

Methodology Development for the Reconstruction of the ESA Huygens Probe Entry and Descent Trajectory

NASA Astrophysics Data System (ADS)

Kazeminejad, B.

2005-01-01

The European Space Agency's (ESA) Huygens probe performed a successful entry and descent into Titan's atmosphere on January 14, 2005, and landed safely on the satellite's surface. A methodology was developed, implemented, and tested to reconstruct the Huygens probe trajectory from its various science and engineering measurements, which were performed during the probe's entry and descent to the surface of Titan, Saturn's largest moon. The probe trajectory reconstruction is an essential effort that has to be done as early as possible in the post-flight data analysis phase as it guarantees a correct and consistent interpretation of all the experiment data and furthermore provides a reference set of data for "ground-truthing" orbiter remote sensing measurements. The entry trajectory is reconstructed from the measured probe aerodynamic drag force, which also provides a means to derive the upper atmospheric properties like density, pressure, and temperature. The descent phase reconstruction is based upon a combination of various atmospheric measurements such as pressure, temperature, composition, speed of sound, and wind speed. A significant amount of effort was spent to outline and implement a least-squares trajectory estimation algorithm that provides a means to match the entry and descent trajectory portions in case of discontinuity. An extensive test campaign of the algorithm is presented which used the Huygens Synthetic Dataset (HSDS) developed by the Huygens Project Scientist Team at ESA/ESTEC as a test bed. This dataset comprises the simulated sensor output (and the corresponding measurement noise and uncertainty) of all the relevant probe instruments. The test campaign clearly showed that the proposed methodology is capable of utilizing all the relevant probe data, and will provide the best estimate of the probe trajectory once real instrument measurements from the actual probe mission are available. As a further test case using actual flight data the NASA Mars Pathfinder entry and descent trajectory and the space craft attitude was reconstructed from the 3-axis accelerometer measurements which are archived on the Planetary Data System. The results are consistent with previously published reconstruction efforts.

EvOligo: A Novel Software to Design and Group Libraries of Oligonucleotides Applicable for Nucleic Acid-Based Experiments.

PubMed

Milewski, Marek C; Kamel, Karol; Kurzynska-Kokorniak, Anna; Chmielewski, Marcin K; Figlerowicz, Marek

2017-10-01

Experimental methods based on DNA and RNA hybridization, such as multiplex polymerase chain reaction, multiplex ligation-dependent probe amplification, or microarray analysis, require the use of mixtures of multiple oligonucleotides (primers or probes) in a single test tube. To provide an optimal reaction environment, minimal self- and cross-hybridization must be achieved among these oligonucleotides. To address this problem, we developed EvOligo, which is a software package that provides the means to design and group DNA and RNA molecules with defined lengths. EvOligo combines two modules. The first module performs oligonucleotide design, and the second module performs oligonucleotide grouping. The software applies a nearest-neighbor model of nucleic acid interactions coupled with a parallel evolutionary algorithm to construct individual oligonucleotides, and to group the molecules that are characterized by the weakest possible cross-interactions. To provide optimal solutions, the evolutionary algorithm sorts oligonucleotides into sets, preserves preselected parts of the oligonucleotides, and shapes their remaining parts. In addition, the oligonucleotide sets can be designed and grouped based on their melting temperatures. For the user's convenience, EvOligo is provided with a user-friendly graphical interface. EvOligo was used to design individual oligonucleotides, oligonucleotide pairs, and groups of oligonucleotide pairs that are characterized by the following parameters: (1) weaker cross-interactions between the non-complementary oligonucleotides and (2) more uniform ranges of the oligonucleotide pair melting temperatures than other available software products. In addition, in contrast to other grouping algorithms, EvOligo offers time-efficient sorting of paired and unpaired oligonucleotides based on various parameters defined by the user.

Correction of Spatial Bias in Oligonucleotide Array Data

PubMed Central

Lemieux, Sébastien

2013-01-01

Background. Oligonucleotide microarrays allow for high-throughput gene expression profiling assays. The technology relies on the fundamental assumption that observed hybridization signal intensities (HSIs) for each intended target, on average, correlate with their target's true concentration in the sample. However, systematic, nonbiological variation from several sources undermines this hypothesis. Background hybridization signal has been previously identified as one such important source, one manifestation of which appears in the form of spatial autocorrelation. Results. We propose an algorithm, pyn, for the elimination of spatial autocorrelation in HSIs, exploiting the duality of desirable mutual information shared by probes in a common probe set and undesirable mutual information shared by spatially proximate probes. We show that this correction procedure reduces spatial autocorrelation in HSIs; increases HSI reproducibility across replicate arrays; increases differentially expressed gene detection power; and performs better than previously published methods. Conclusions. The proposed algorithm increases both precision and accuracy, while requiring virtually no changes to users' current analysis pipelines: the correction consists merely of a transformation of raw HSIs (e.g., CEL files for Affymetrix arrays). A free, open-source implementation is provided as an R package, compatible with standard Bioconductor tools. The approach may also be tailored to other platform types and other sources of bias. PMID:23573083

Down-Regulation of Olfactory Receptors in Response to Traumatic Brain Injury Promotes Risk for Alzheimers Disease

DTIC Science & Technology

2015-12-01

group assignment of samples in unsupervised hierarchical clustering by the Unweighted Pair-Group Method using Arithmetic averages ( UPGMA ) based on...log2 transformed MAS5.0 signal values; probe set clustering was performed by the UPGMA method using Cosine correlation as the similarity met- ric. For...differentially-regulated genes identified were subjected to unsupervised hierarchical clustering analysis using the UPGMA algorithm with cosine correlation as

TARGETED PRINCIPLE COMPONENT ANALYSIS: A NEW MOTION ARTIFACT CORRECTION APPROACH FOR NEAR-INFRARED SPECTROSCOPY

PubMed Central

YÜCEL, MERYEM A.; SELB, JULIETTE; COOPER, ROBERT J.; BOAS, DAVID A.

2014-01-01

As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation. Here, we introduce a new approach to motion artifact correction, targeted principle component analysis (tPCA), which incorporates a PCA filter only on the segments of data identified as motion artifacts. It is expected that this will overcome the issues of filtering desired signals that plagues standard PCA filtering of entire data sets. We compared the new approach with the most effective motion artifact correction algorithms on a set of data acquired simultaneously with a collodion-fixed probe (low motion artifact content) and a standard Velcro probe (high motion artifact content). Our results show that tPCA gives statistically better results in recovering hemodynamic response function (HRF) as compared to wavelet-based filtering and spline interpolation for the Velcro probe. It results in a significant reduction in mean-squared error (MSE) and significant enhancement in Pearson’s correlation coefficient to the true HRF. The collodion-fixed fiber probe with no motion correction performed better than the Velcro probe corrected for motion artifacts in terms of MSE and Pearson’s correlation coefficient. Thus, if the experimental study permits, the use of a collodion-fixed fiber probe may be desirable. If the use of a collodion-fixed probe is not feasible, then we suggest the use of tPCA in the processing of motion artifact contaminated data. PMID:25360181

Experimental testing of four correction algorithms for the forward scattering spectrometer probe

NASA Technical Reports Server (NTRS)

Hovenac, Edward A.; Oldenburg, John R.; Lock, James A.

1992-01-01

Three number density correction algorithms and one size distribution correction algorithm for the Forward Scattering Spectrometer Probe (FSSP) were compared with data taken by the Phase Doppler Particle Analyzer (PDPA) and an optical number density measuring instrument (NDMI). Of the three number density correction algorithms, the one that compared best to the PDPA and NDMI data was the algorithm developed by Baumgardner, Strapp, and Dye (1985). The algorithm that corrects sizing errors in the FSSP that was developed by Lock and Hovenac (1989) was shown to be within 25 percent of the Phase Doppler measurements at number densities as high as 3000/cc.

A Comparison of Experimental EPMA Data and Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Carpenter, P. K.

2004-01-01

Monte Carlo (MC) modeling shows excellent prospects for simulating electron scattering and x-ray emission from complex geometries, and can be compared to experimental measurements using electron-probe microanalysis (EPMA) and phi(rho z) correction algorithms. Experimental EPMA measurements made on NIST SRM 481 (AgAu) and 482 (CuAu) alloys, at a range of accelerating potential and instrument take-off angles, represent a formal microanalysis data set that has been used to develop phi(rho z) correction algorithms. The accuracy of MC calculations obtained using the NIST, WinCasino, WinXray, and Penelope MC packages will be evaluated relative to these experimental data. There is additional information contained in the extended abstract.

A robust multi-frequency mixing algorithm for suppression of rivet signal in GMR inspection of riveted structures

NASA Astrophysics Data System (ADS)

Safdernejad, Morteza S.; Karpenko, Oleksii; Ye, Chaofeng; Udpa, Lalita; Udpa, Satish

2016-02-01

The advent of Giant Magneto-Resistive (GMR) technology permits development of novel highly sensitive array probes for Eddy Current (EC) inspection of multi-layer riveted structures. Multi-frequency GMR measurements with different EC pene-tration depths show promise for detection of bottom layer notches at fastener sites. However, the distortion of the induced magnetic field due to flaws is dominated by the strong fastener signal, which makes defect detection and classification a challenging prob-lem. This issue is more pronounced for ferromagnetic fasteners that concentrate most of the magnetic flux. In the present work, a novel multi-frequency mixing algorithm is proposed to suppress rivet signal response and enhance defect detection capability of the GMR array probe. The algorithm is baseline-free and does not require any assumptions about the sample geometry being inspected. Fastener signal suppression is based upon the random sample consensus (RANSAC) method, which iteratively estimates parameters of a mathematical model from a set of observed data with outliers. Bottom layer defects at fastener site are simulated as EDM notches of different length. Performance of the proposed multi-frequency mixing approach is evaluated on finite element data and experimental GMR measurements obtained with unidirectional planar current excitation. Initial results are promising demonstrating the feasibility of the approach.

The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra.

PubMed

Shilov, Ignat V; Seymour, Sean L; Patel, Alpesh A; Loboda, Alex; Tang, Wilfred H; Keating, Sean P; Hunter, Christie L; Nuwaysir, Lydia M; Schaeffer, Daniel A

2007-09-01

The Paragon Algorithm, a novel database search engine for the identification of peptides from tandem mass spectrometry data, is presented. Sequence Temperature Values are computed using a sequence tag algorithm, allowing the degree of implication by an MS/MS spectrum of each region of a database to be determined on a continuum. Counter to conventional approaches, features such as modifications, substitutions, and cleavage events are modeled with probabilities rather than by discrete user-controlled settings to consider or not consider a feature. The use of feature probabilities in conjunction with Sequence Temperature Values allows for a very large increase in the effective search space with only a very small increase in the actual number of hypotheses that must be scored. The algorithm has a new kind of user interface that removes the user expertise requirement, presenting control settings in the language of the laboratory that are translated to optimal algorithmic settings. To validate this new algorithm, a comparison with Mascot is presented for a series of analogous searches to explore the relative impact of increasing search space probed with Mascot by relaxing the tryptic digestion conformance requirements from trypsin to semitrypsin to no enzyme and with the Paragon Algorithm using its Rapid mode and Thorough mode with and without tryptic specificity. Although they performed similarly for small search space, dramatic differences were observed in large search space. With the Paragon Algorithm, hundreds of biological and artifact modifications, all possible substitutions, and all levels of conformance to the expected digestion pattern can be searched in a single search step, yet the typical cost in search time is only 2-5 times that of conventional small search space. Despite this large increase in effective search space, there is no drastic loss of discrimination that typically accompanies the exploration of large search space.

Down-Regulation of Olfactory Receptors in Response to Traumatic Brain Injury Promotes Risk for Alzheimer’s Disease

DTIC Science & Technology

2013-10-01

correct group assignment of samples in unsupervised hierarchical clustering by the Unweighted Pair-Group Method using Arithmetic averages ( UPGMA ) based on...centering of log2 transformed MAS5.0 signal values; probe set clustering was performed by the UPGMA method using Cosine correlation as the similarity met...A) The 108 differentially-regulated genes identified were subjected to unsupervised hierarchical clustering analysis using the UPGMA algorithm with

ARTIST: A fully automated artifact rejection algorithm for single-pulse TMS-EEG data.

PubMed

Wu, Wei; Keller, Corey J; Rogasch, Nigel C; Longwell, Parker; Shpigel, Emmanuel; Rolle, Camarin E; Etkin, Amit

2018-04-01

Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings. © 2018 Wiley Periodicals, Inc.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements

NASA Astrophysics Data System (ADS)

Tsouri, Gill R.; Kyal, Survi; Dianat, Sohail; Mestha, Lalit K.

2012-07-01

Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements.

PubMed

Tsouri, Gill R; Kyal, Survi; Dianat, Sohail; Mestha, Lalit K

2012-07-01

Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.

System Design under Uncertainty: Evolutionary Optimization of the Gravity Probe-B Spacecraft

NASA Technical Reports Server (NTRS)

Pullen, Samuel P.; Parkinson, Bradford W.

1994-01-01

This paper discusses the application of evolutionary random-search algorithms (Simulated Annealing and Genetic Algorithms) to the problem of spacecraft design under performance uncertainty. Traditionally, spacecraft performance uncertainty has been measured by reliability. Published algorithms for reliability optimization are seldom used in practice because they oversimplify reality. The algorithm developed here uses random-search optimization to allow us to model the problem more realistically. Monte Carlo simulations are used to evaluate the objective function for each trial design solution. These methods have been applied to the Gravity Probe-B (GP-B) spacecraft being developed at Stanford University for launch in 1999, Results of the algorithm developed here for GP-13 are shown, and their implications for design optimization by evolutionary algorithms are discussed.

Simple Random Sampling-Based Probe Station Selection for Fault Detection in Wireless Sensor Networks

PubMed Central

Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

2011-01-01

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate. PMID:22163789

Simple random sampling-based probe station selection for fault detection in wireless sensor networks.

PubMed

Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

2011-01-01

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate.

Iterative methods for plasma sheath calculations: Application to spherical probe

NASA Technical Reports Server (NTRS)

Parker, L. W.; Sullivan, E. C.

1973-01-01

The computer cost of a Poisson-Vlasov iteration procedure for the numerical solution of a steady-state collisionless plasma-sheath problem depends on: (1) the nature of the chosen iterative algorithm, (2) the position of the outer boundary of the grid, and (3) the nature of the boundary condition applied to simulate a condition at infinity (as in three-dimensional probe or satellite-wake problems). Two iterative algorithms, in conjunction with three types of boundary conditions, are analyzed theoretically and applied to the computation of current-voltage characteristics of a spherical electrostatic probe. The first algorithm was commonly used by physicists, and its computer costs depend primarily on the boundary conditions and are only slightly affected by the mesh interval. The second algorithm is not commonly used, and its costs depend primarily on the mesh interval and slightly on the boundary conditions.

A model of binding on DNA microarrays: understanding the combined effect of probe synthesis failure, cross-hybridization, DNA fragmentation and other experimental details of affymetrix arrays

PubMed Central

2012-01-01

Background DNA microarrays are used both for research and for diagnostics. In research, Affymetrix arrays are commonly used for genome wide association studies, resequencing, and for gene expression analysis. These arrays provide large amounts of data. This data is analyzed using statistical methods that quite often discard a large portion of the information. Most of the information that is lost comes from probes that systematically fail across chips and from batch effects. The aim of this study was to develop a comprehensive model for hybridization that predicts probe intensities for Affymetrix arrays and that could provide a basis for improved microarray analysis and probe development. The first part of the model calculates probe binding affinities to all the possible targets in the hybridization solution using the Langmuir isotherm. In the second part of the model we integrate details that are specific to each experiment and contribute to the differences between hybridization in solution and on the microarray. These details include fragmentation, wash stringency, temperature, salt concentration, and scanner settings. Furthermore, the model fits probe synthesis efficiency and target concentration parameters directly to the data. All the parameters used in the model have a well-established physical origin. Results For the 302 chips that were analyzed the mean correlation between expected and observed probe intensities was 0.701 with a range of 0.88 to 0.55. All available chips were included in the analysis regardless of the data quality. Our results show that batch effects arise from differences in probe synthesis, scanner settings, wash strength, and target fragmentation. We also show that probe synthesis efficiencies for different nucleotides are not uniform. Conclusions To date this is the most complete model for binding on microarrays. This is the first model that includes both probe synthesis efficiency and hybridization kinetics/cross-hybridization. These two factors are sequence dependent and have a large impact on probe intensity. The results presented here provide novel insight into the effect of probe synthesis errors on Affymetrix microarrays; furthermore, the algorithms developed in this work provide useful tools for the analysis of cross-hybridization, probe synthesis efficiency, fragmentation, wash stringency, temperature, and salt concentration on microarray intensities. PMID:23270536

A diagnostic algorithm for atypical spitzoid tumors: guidelines for immunohistochemical and molecular assessment.

PubMed

Cho-Vega, Jeong Hee

2016-07-01

Atypical spitzoid tumors are a morphologically diverse group of rare melanocytic lesions most frequently seen in children and young adults. As atypical spitzoid tumors bear striking resemblance to Spitz nevus and spitzoid melanomas clinically and histopathologically, it is crucial to determine its malignant potential and predict its clinical behavior. To date, many researchers have attempted to differentiate atypical spitzoid tumors from unequivocal melanomas based on morphological, immonohistochemical, and molecular diagnostic differences. A diagnostic algorithm is proposed here to assess the malignant potential of atypical spitzoid tumors by using a combination of immunohistochemical and cytogenetic/molecular tests. Together with classical morphological evaluation, this algorithm includes a set of immunohistochemistry assays (p16(Ink4a), a dual-color Ki67/MART-1, and HMB45), fluorescence in situ hybridization (FISH) with five probes (6p25, 8q24, 11q13, CEN9, and 9p21), and an array-based comparative genomic hybridization. This review discusses details of the algorithm, the rationale of each test used in the algorithm, and utility of this algorithm in routine dermatopathology practice. This algorithmic approach will provide a comprehensive diagnostic tool that complements conventional histological criteria and will significantly contribute to improve the diagnosis and prediction of the clinical behavior of atypical spitzoid tumors.

Slingshot dynamics for self-replicating probes and the effect on exploration timescales

NASA Astrophysics Data System (ADS)

Nicholson, Arwen; Forgan, Duncan

2013-10-01

Interstellar probes can carry out slingshot manoeuvres around the stars they visit, gaining a boost in velocity by extracting energy from the star's motion around the Galactic Centre. These manoeuvres carry little to no extra energy cost, and in previous work it has been shown that a single Voyager-like probe exploring the Galaxy does so 100 times faster when carrying out these slingshots than when navigating purely by powered flight (Forgan et al. 2012). We expand on these results by repeating the experiment with self-replicating probes. The probes explore a box of stars representative of the local Solar neighbourhood, to investigate how self-replication affects exploration timescales when compared with a single non-replicating probe. We explore three different scenarios of probe behaviour: (i) standard powered flight to the nearest unvisited star (no slingshot techniques used), (ii) flight to the nearest unvisited star using slingshot techniques and (iii) flight to the next unvisited star that will give the maximum velocity boost under a slingshot trajectory. In all three scenarios, we find that as expected, using self-replicating probes greatly reduces the exploration time, by up to three orders of magnitude for scenarios (i) and (iii) and two orders of magnitude for (ii). The second case (i.e. nearest-star slingshots) remains the most time effective way to explore a population of stars. As the decision-making algorithms for the fleet are simple, unanticipated `race conditions' among probes are set up, causing the exploration time of the final stars to become much longer than necessary. From the scaling of the probes' performance with star number, we conclude that a fleet of self-replicating probes can indeed explore the Galaxy in a sufficiently short time to warrant the existence of the Fermi Paradox.

The Contribution of TOMS and UARS Data to Our Understanding of Ozone Change

NASA Technical Reports Server (NTRS)

Bhartia, Pawan K.; Einaudi, Franco (Technical Monitor)

2001-01-01

Both TOMS (Total Ozone Mapping Spectrometer) and UARS (Upper Atmosphere Research Satellite) have operated over an extended period, and generated data sets of sufficient accuracy to be of use in determining ozone change (TOMS) and some of the underlying causes (UARS). The basic scientific products have been used for model validation and assimilation to extend our understanding of stratospheric processes. TOMS on Nimbus-7, Earth-Probe, and QuikTOMS, and UARS have led to the next generation of instruments onboard the EOS platforms. Algorithms used for TOMS and UARS are being applied to the new data sets and extended to analysis of European satellite data (e.g., GOME)

Array of nucleic acid probes on biological chips for diagnosis of HIV and methods of using the same

DOEpatents

Chee, Mark; Gingeras, Thomas R.; Fodor, Stephen P. A.; Hubble, Earl A.; Morris, MacDonald S.

1999-01-19

The invention provides an array of oligonucleotide probes immobilized on a solid support for analysis of a target sequence from a human immunodeficiency virus. The array comprises at least four sets of oligonucleotide probes 9 to 21 nucleotides in length. A first probe set has a probe corresponding to each nucleotide in a reference sequence from a human immunodeficiency virus. A probe is related to its corresponding nucleotide by being exactly complementary to a subsequence of the reference sequence that includes the corresponding nucleotide. Thus, each probe has a position, designated an interrogation position, that is occupied by a complementary nucleotide to the corresponding nucleotide. The three additional probe sets each have a corresponding probe for each probe in the first probe set. Thus, for each nucleotide in the reference sequence, there are four corresponding probes, one from each of the probe sets. The three corresponding probes in the three additional probe sets are identical to the corresponding probe from the first probe or a subsequence thereof that includes the interrogation position, except that the interrogation position is occupied by a different nucleotide in each of the four corresponding probes.

PhylArray: phylogenetic probe design algorithm for microarray.

PubMed

Militon, Cécile; Rimour, Sébastien; Missaoui, Mohieddine; Biderre, Corinne; Barra, Vincent; Hill, David; Moné, Anne; Gagne, Geneviève; Meier, Harald; Peyretaillade, Eric; Peyret, Pierre

2007-10-01

Microbial diversity is still largely unknown in most environments, such as soils. In order to get access to this microbial 'black-box', the development of powerful tools such as microarrays are necessary. However, the reliability of this approach relies on probe efficiency, in particular sensitivity, specificity and explorative power, in order to obtain an image of the microbial communities that is close to reality. We propose a new probe design algorithm that is able to select microarray probes targeting SSU rRNA at any phylogenetic level. This original approach, implemented in a program called 'PhylArray', designs a combination of degenerate and non-degenerate probes for each target taxon. Comparative experimental evaluations indicate that probes designed with PhylArray yield a higher sensitivity and specificity than those designed by conventional approaches. Applying the combined PhyArray/GoArrays strategy helps to optimize the hybridization performance of short probes. Finally, hybridizations with environmental targets have shown that the use of the PhylArray strategy can draw attention to even previously unknown bacteria.

Accuracy Improvement for Light-Emitting-Diode-Based Colorimeter by Iterative Algorithm

NASA Astrophysics Data System (ADS)

Yang, Pao-Keng

2011-09-01

We present a simple algorithm, combining an interpolating method with an iterative calculation, to enhance the resolution of spectral reflectance by removing the spectral broadening effect due to the finite bandwidth of the light-emitting diode (LED) from it. The proposed algorithm can be used to improve the accuracy of a reflective colorimeter using multicolor LEDs as probing light sources and is also applicable to the case when the probing LEDs have different bandwidths in different spectral ranges, to which the powerful deconvolution method cannot be applied.

Asymmetric rotor-like probes to polarized fluorescence study of the macroscopically oriented uniaxial media: Model parameters recognition

NASA Astrophysics Data System (ADS)

Buczkowski, M.; Fisz, J. J.

2008-07-01

In this paper the possibility of the numerical data modelling in the case of angle- and time-resolved fluorescence spectroscopy is investigated. The asymmetric fluorescence probes are assumed to undergo the restricted rotational diffusion in a hosting medium. This process is described quantitatively by the diffusion tensor and the aligning potential. The evolution of the system is expressed in terms of the Smoluchowski equation with an appropriate time-developing operator. A matrix representation of this operator is calculated, then symmetrized and diagonalized. The resulting propagator is used to generate the synthetic noisy data set that imitates results of experimental measurements. The data set serves as a groundwork to the χ2 optimization, performed by the genetic algorithm followed by the gradient search, in order to recover model parameters, which are diagonal elements of the diffusion tensor, aligning potential expansion coefficients and directions of the electronic dipole moments. This whole procedure properly identifies model parameters, showing that the outlined formalism should be taken in the account in the case of analysing real experimental data.

An ultrashort-pulse reconstruction software: GROG, applied to the FLAME laser system

NASA Astrophysics Data System (ADS)

Galletti, Mario

2016-03-01

The GRENOUILLE traces of FLAME Probe line pulses (60mJ, 10mJ after compression, 70fs, 1cm FWHM, 10Hz) were acquired in the FLAME Front End Area (FFEA) at the Laboratori Nazionali di Frascati (LNF), Instituto Nazionale di Fisica Nucleare (INFN). The complete characterization of the laser pulse parameters was made using a new algorithm: GRenouille/FrOG (GROG). A characterization with a commercial algorithm, QUICKFrog, was also made. The temporal and spectral parameters came out to be in great agreement for the two kinds of algorithms. In this experimental campaign the Probe line of FLAME has been completely characterized and it has been showed how GROG, the developed algorithm, works as well as QuickFrog algorithm with this type of pulse class.

Measurements With a Split-Fiber Probe in Complex Unsteady Flows

NASA Technical Reports Server (NTRS)

Lepicovsky, Jan

2004-01-01

A split-fiber probe was used to acquire unsteady data in a research compressor. A calibration method was devised for a split-fiber probe, and a new algorithm was developed to decompose split-fiber probe signals into velocity magnitude and direction. The algorithm is based on the minimum value of a merit function that is built over the entire range of flow velocities for which the probe was calibrated. The split-fiber probe performance and signal decomposition was first verified in a free-jet facility by comparing the data from three thermo-anemometric probes, namely a single-wire, a single-fiber, and the split-fiber probe. All three probes performed extremely well as far as the velocity magnitude was concerned. However, there are differences in the peak values of measured velocity unsteadiness in the jet shear layer. The single-wire probe indicates the highest unsteadiness level, followed closely by the split-fiber probe. The single-fiber probe indicates a noticeably lower level of velocity unsteadiness. Experiments in the NASA Low Speed Axial Compressor facility revealed similar results. The mean velocities agreed well, and differences in the velocity unsteadiness are similar to the case of a free jet. A reason for these discrepancies is in the different frequency response characteristics of probes used. It follows that the single-fiber probe has the slowest frequency response. In summary, the split-fiber probe worked reliably during the entire program. The acquired data averaged in time followed closely data acquired by conventional pneumatic probes.

Estimating the similarity of alternative Affymetrix probe sets using transcriptional networks

PubMed Central

2013-01-01

Background The usefulness of the data from Affymetrix microarray analysis depends largely on the reliability of the files describing the correspondence between probe sets, genes and transcripts. Particularly, when a gene is targeted by several probe sets, these files should give information about the similarity of each alternative probe set pair. Transcriptional networks integrate the multiple correlations that exist between all probe sets and supply much more information than a simple correlation coefficient calculated for two series of signals. In this study, we used the PSAWN (Probe Set Assignment With Networks) programme we developed to investigate whether similarity of alternative probe sets resulted in some specific properties. Findings PSAWNpy delivered a full textual description of each probe set and information on the number and properties of secondary targets. PSAWNml calculated the similarity of each alternative probe set pair and allowed finding relationships between similarity and localisation of probes in common transcripts or exons. Similar alternative probe sets had very low negative correlation, high positive correlation and similar neighbourhood overlap. Using these properties, we devised a test that allowed grouping similar probe sets in a given network. By considering several networks, additional information concerning the similarity reproducibility was obtained, which allowed defining the actual similarity of alternative probe set pairs. In particular, we calculated the common localisation of probes in exons and in known transcripts and we showed that similarity was correctly correlated with them. The information collected on all pairs of alternative probe sets in the most popular 3’ IVT Affymetrix chips is available in tabular form at http://bns.crbm.cnrs.fr/download.html. Conclusions These processed data can be used to obtain a finer interpretation when comparing microarray data between biological conditions. They are particularly well adapted for searching 3’ alternative poly-adenylation events and can be also useful for studying the structure of transcriptional networks. The PSAWNpy, (in Python) and PSAWNml (in Matlab) programmes are freely available and can be downloaded at http://code.google.com/p/arraymatic. Tutorials and reference manuals are available at BMC Research Notes online (Additional file 1) or from http://bns.crbm.cnrs.fr/softwares.html. PMID:23517579

Hybridization properties of long nucleic acid probes for detection of variable target sequences, and development of a hybridization prediction algorithm

PubMed Central

Öhrmalm, Christina; Jobs, Magnus; Eriksson, Ronnie; Golbob, Sultan; Elfaitouri, Amal; Benachenhou, Farid; Strømme, Maria; Blomberg, Jonas

2010-01-01

One of the main problems in nucleic acid-based techniques for detection of infectious agents, such as influenza viruses, is that of nucleic acid sequence variation. DNA probes, 70-nt long, some including the nucleotide analog deoxyribose-Inosine (dInosine), were analyzed for hybridization tolerance to different amounts and distributions of mismatching bases, e.g. synonymous mutations, in target DNA. Microsphere-linked 70-mer probes were hybridized in 3M TMAC buffer to biotinylated single-stranded (ss) DNA for subsequent analysis in a Luminex® system. When mismatches interrupted contiguous matching stretches of 6 nt or longer, it had a strong impact on hybridization. Contiguous matching stretches are more important than the same number of matching nucleotides separated by mismatches into several regions. dInosine, but not 5-nitroindole, substitutions at mismatching positions stabilized hybridization remarkably well, comparable to N (4-fold) wobbles in the same positions. In contrast to shorter probes, 70-nt probes with judiciously placed dInosine substitutions and/or wobble positions were remarkably mismatch tolerant, with preserved specificity. An algorithm, NucZip, was constructed to model the nucleation and zipping phases of hybridization, integrating both local and distant binding contributions. It predicted hybridization more exactly than previous algorithms, and has the potential to guide the design of variation-tolerant yet specific probes. PMID:20864443

Leaving out control groups: an internal contrast analysis of gene expression profiles in atrial fibrillation patients--a systems biology approach to clinical categorization.

PubMed

Vanhoutte, Kurt; de Asmundis, Carlo; Francesconi, Anna; Figysl, Jurgen; Steurs, Griet; Boussy, Tim; Roos, Markus; Mueller, Andreas; Massimo, Lucio; Paparella, Gaetano; Van Caelenberg, Kristien; Chierchia, Gian Battista; Sarkozy, Andrea; Terradellas, Pedro Brugada Y; Zizi, Martin

2009-01-01

Atrial fibrillation (AF) is a frequent chronic dysrythmia with an incidence that increases with age (>40). Because of its medical and socio-economic impacts it is expected to become an increasing burden on most health care systems. AF is a multi-factorial disease for which the identification of subtypes is warranted. Novel approaches based on the broad concepts of systems biology may overcome the blurred notion of normal and pathological phenotype, which is inherent to high throughput molecular arrays analysis. Here we apply an internal contrast algorithm on AF patient data with an analytical focus on potential entry pathways into the disease. We used a RMA (Robust Multichip Average) normalized Affymetrix micro-array data set from 10 AF patients (geo_accession #GSE2240). Four series of probes were selected based on physiopathogenic links with AF entryways: apoptosis (remodeling), MAP kinase (cell remodeling), OXPHOS (ability to sustain hemodynamic workload) and glycolysis (ischemia). Annotated probe lists were polled with Bioconductor packages in R (version 2.7.1). Genetic profile contrasts were analysed with hierarchical clustering and principal component analysis. The analysis revealed distinct patient groups for all probe sets. A substantial part (54% till 67%) of the variance is explained in the first 2 principal components. Genes in PC1/2 with high discriminatory value were selected and analyzed in detail. We aim for reliable molecular stratification of AF. We show that stratification is possible based on physiologically relevant gene sets. Genes with high contrast value are likely to give pathophysiological insight into permanent AF subtypes.

Probing for quantum speedup in spin-glass problems with planted solutions

NASA Astrophysics Data System (ADS)

Hen, Itay; Job, Joshua; Albash, Tameem; Rønnow, Troels F.; Troyer, Matthias; Lidar, Daniel A.

2015-10-01

The availability of quantum annealing devices with hundreds of qubits has made the experimental demonstration of a quantum speedup for optimization problems a coveted, albeit elusive goal. Going beyond earlier studies of random Ising problems, here we introduce a method to construct a set of frustrated Ising-model optimization problems with tunable hardness. We study the performance of a D-Wave Two device (DW2) with up to 503 qubits on these problems and compare it to a suite of classical algorithms, including a highly optimized algorithm designed to compete directly with the DW2. The problems are generated around predetermined ground-state configurations, called planted solutions, which makes them particularly suitable for benchmarking purposes. The problem set exhibits properties familiar from constraint satisfaction (SAT) problems, such as a peak in the typical hardness of the problems, determined by a tunable clause density parameter. We bound the hardness regime where the DW2 device either does not or might exhibit a quantum speedup for our problem set. While we do not find evidence for a speedup for the hardest and most frustrated problems in our problem set, we cannot rule out that a speedup might exist for some of the easier, less frustrated problems. Our empirical findings pertain to the specific D-Wave processor and problem set we studied and leave open the possibility that future processors might exhibit a quantum speedup on the same problem set.

The instrument for investigating magnetic fields of isochronous cyclotrons

NASA Astrophysics Data System (ADS)

Avreline, N. V.

2017-12-01

A new instrument was designed and implemented in order to increase the measurement accuracy of magnetic field maps for isochronous Cyclotrons manufactured by Advanced Cyclotron Systems Inc. This instrument uses the Hall Probe (HP) from New Zealand manufacturer Group3. The specific probe used is MPT-141 HP and can measure magnetic field in the range from 2G to 21kG. Use of a fast ADC NI9239 module and error reduction algorithms, based on a polynomial regression method, allowed to reduce the noise to 0.2G. The design of this instrument allows to measure high gradient magnetic fields, as the resolution of the HP arm angle is within 0.0005° and the radial position resolution is within 25μm. A set of National Instrument interfaces connected to a desktop computer through a network are used as base control and data acquisition systems.

Design of a DNA chip for detection of unknown genetically modified organisms (GMOs).

PubMed

Nesvold, Håvard; Kristoffersen, Anja Bråthen; Holst-Jensen, Arne; Berdal, Knut G

2005-05-01

Unknown genetically modified organisms (GMOs) have not undergone a risk evaluation, and hence might pose a danger to health and environment. There are, today, no methods for detecting unknown GMOs. In this paper we propose a novel method intended as a first step in an approach for detecting unknown genetically modified (GM) material in a single plant. A model is designed where biological and combinatorial reduction rules are applied to a set of DNA chip probes containing all possible sequences of uniform length n, creating probes capable of detecting unknown GMOs. The model is theoretically tested for Arabidopsis thaliana Columbia, and the probabilities for detecting inserts and receiving false positives are assessed for various parameters for this organism. From a theoretical standpoint, the model looks very promising but should be tested further in the laboratory. The model and algorithms will be available upon request to the corresponding author.

Design and verification of a pangenome microarray oligonucleotide probe set for Dehalococcoides spp.

PubMed

Hug, Laura A; Salehi, Maryam; Nuin, Paulo; Tillier, Elisabeth R; Edwards, Elizabeth A

2011-08-01

Dehalococcoides spp. are an industrially relevant group of Chloroflexi bacteria capable of reductively dechlorinating contaminants in groundwater environments. Existing Dehalococcoides genomes revealed a high level of sequence identity within this group, including 98 to 100% 16S rRNA sequence identity between strains with diverse substrate specificities. Common molecular techniques for identification of microbial populations are often not applicable for distinguishing Dehalococcoides strains. Here we describe an oligonucleotide microarray probe set designed based on clustered Dehalococcoides genes from five different sources (strain DET195, CBDB1, BAV1, and VS genomes and the KB-1 metagenome). This "pangenome" probe set provides coverage of core Dehalococcoides genes as well as strain-specific genes while optimizing the potential for hybridization to closely related, previously unknown Dehalococcoides strains. The pangenome probe set was compared to probe sets designed independently for each of the five Dehalococcoides strains. The pangenome probe set demonstrated better predictability and higher detection of Dehalococcoides genes than strain-specific probe sets on nontarget strains with <99% average nucleotide identity. An in silico analysis of the expected probe hybridization against the recently released Dehalococcoides strain GT genome and additional KB-1 metagenome sequence data indicated that the pangenome probe set performs more robustly than the combined strain-specific probe sets in the detection of genes not included in the original design. The pangenome probe set represents a highly specific, universal tool for the detection and characterization of Dehalococcoides from contaminated sites. It has the potential to become a common platform for Dehalococcoides-focused research, allowing meaningful comparisons between microarray experiments regardless of the strain examined.

A Bayesian Estimate of the CMB-Large-scale Structure Cross-correlation

NASA Astrophysics Data System (ADS)

Moura-Santos, E.; Carvalho, F. C.; Penna-Lima, M.; Novaes, C. P.; Wuensche, C. A.

2016-08-01

Evidences for late-time acceleration of the universe are provided by multiple probes, such as Type Ia supernovae, the cosmic microwave background (CMB), and large-scale structure (LSS). In this work, we focus on the integrated Sachs-Wolfe (ISW) effect, I.e., secondary CMB fluctuations generated by evolving gravitational potentials due to the transition between, e.g., the matter and dark energy (DE) dominated phases. Therefore, assuming a flat universe, DE properties can be inferred from ISW detections. We present a Bayesian approach to compute the CMB-LSS cross-correlation signal. The method is based on the estimate of the likelihood for measuring a combined set consisting of a CMB temperature and galaxy contrast maps, provided that we have some information on the statistical properties of the fluctuations affecting these maps. The likelihood is estimated by a sampling algorithm, therefore avoiding the computationally demanding techniques of direct evaluation in either pixel or harmonic space. As local tracers of the matter distribution at large scales, we used the Two Micron All Sky Survey galaxy catalog and, for the CMB temperature fluctuations, the ninth-year data release of the Wilkinson Microwave Anisotropy Probe (WMAP9). The results show a dominance of cosmic variance over the weak recovered signal, due mainly to the shallowness of the catalog used, with systematics associated with the sampling algorithm playing a secondary role as sources of uncertainty. When combined with other complementary probes, the method presented in this paper is expected to be a useful tool to late-time acceleration studies in cosmology.

Calculated X-ray Intensities Using Monte Carlo Algorithms: A Comparison to Experimental EPMA Data

NASA Technical Reports Server (NTRS)

Carpenter, P. K.

2005-01-01

Monte Carlo (MC) modeling has been used extensively to simulate electron scattering and x-ray emission from complex geometries. Here are presented comparisons between MC results and experimental electron-probe microanalysis (EPMA) measurements as well as phi(rhoz) correction algorithms. Experimental EPMA measurements made on NIST SRM 481 (AgAu) and 482 (CuAu) alloys, at a range of accelerating potential and instrument take-off angles, represent a formal microanalysis data set that has been widely used to develop phi(rhoz) correction algorithms. X-ray intensity data produced by MC simulations represents an independent test of both experimental and phi(rhoz) correction algorithms. The alpha-factor method has previously been used to evaluate systematic errors in the analysis of semiconductor and silicate minerals, and is used here to compare the accuracy of experimental and MC-calculated x-ray data. X-ray intensities calculated by MC are used to generate a-factors using the certificated compositions in the CuAu binary relative to pure Cu and Au standards. MC simulations are obtained using the NIST, WinCasino, and WinXray algorithms; derived x-ray intensities have a built-in atomic number correction, and are further corrected for absorption and characteristic fluorescence using the PAP phi(rhoz) correction algorithm. The Penelope code additionally simulates both characteristic and continuum x-ray fluorescence and thus requires no further correction for use in calculating alpha-factors.

Pre-correction of distorted Bessel-Gauss beams without wavefront detection

NASA Astrophysics Data System (ADS)

Fu, Shiyao; Wang, Tonglu; Zhang, Zheyuan; Zhai, Yanwang; Gao, Chunqing

2017-12-01

By utilizing the property of the phase's rapid solution of the Gerchberg-Saxton algorithm, we experimentally demonstrate a scheme to correct distorted Bessel-Gauss beams resulting from inhomogeneous media as weak turbulent atmosphere with good performance. A probe Gaussian beam is employed and propagates coaxially with the Bessel-Gauss modes through the turbulence. No wavefront sensor but a matrix detector is used to capture the probe Gaussian beams, and then, the correction phase mask is computed through inputting such probe beam into the Gerchberg-Saxton algorithm. The experimental results indicate that both single and multiplexed BG beams can be corrected well, in terms of the improvement in mode purity and the mitigation of interchannel cross talk.

Methodology for Generating Conflict Scenarios by Time Shifting Recorded Traffic Data

NASA Technical Reports Server (NTRS)

Paglione, Mike; Oaks, Robert; Bilimoria, Karl D.

2003-01-01

A methodology is presented for generating conflict scenarios that can be used as test cases to estimate the operational performance of a conflict probe. Recorded air traffic data is time shifted to create traffic scenarios featuring conflicts with characteristic properties similar to those encountered in typical air traffic operations. First, a reference set of conflicts is obtained from trajectories that are computed using birth points and nominal flight plans extracted from recorded traffic data. Distributions are obtained for several primary properties (e.g., encounter angle) that are most likely to affect the performance of a conflict probe. A genetic algorithm is then utilized to determine the values of time shifts for the recorded track data so that the primary properties of conflicts generated by the time shifted data match those of the reference set. This methodology is successfully demonstrated using recorded traffic data for the Memphis Air Route Traffic Control Center; a key result is that the required time shifts are less than 5 min for 99% of the tracks. It is also observed that close matching of the primary properties used in this study additionally provides a good match for some other secondary properties.

Thickness Gauging of Single-Layer Conductive Materials with Two-Point Non Linear Calibration Algorithm

NASA Technical Reports Server (NTRS)

Fulton, James P. (Inventor); Namkung, Min (Inventor); Simpson, John W. (Inventor); Wincheski, Russell A. (Inventor); Nath, Shridhar C. (Inventor)

1998-01-01

A thickness gauging instrument uses a flux focusing eddy current probe and two-point nonlinear calibration algorithm. The instrument is small and portable due to the simple interpretation and operational characteristics of the probe. A nonlinear interpolation scheme incorporated into the instrument enables a user to make highly accurate thickness measurements over a fairly wide calibration range from a single side of nonferromagnetic conductive metals. The instrument is very easy to use and can be calibrated quickly.

PROcess Based Diagnostics PROBE

NASA Technical Reports Server (NTRS)

Clune, T.; Schmidt, G.; Kuo, K.; Bauer, M.; Oloso, H.

2013-01-01

Many of the aspects of the climate system that are of the greatest interest (e.g., the sensitivity of the system to external forcings) are emergent properties that arise via the complex interplay between disparate processes. This is also true for climate models most diagnostics are not a function of an isolated portion of source code, but rather are affected by multiple components and procedures. Thus any model-observation mismatch is hard to attribute to any specific piece of code or imperfection in a specific model assumption. An alternative approach is to identify diagnostics that are more closely tied to specific processes -- implying that if a mismatch is found, it should be much easier to identify and address specific algorithmic choices that will improve the simulation. However, this approach requires looking at model output and observational data in a more sophisticated way than the more traditional production of monthly or annual mean quantities. The data must instead be filtered in time and space for examples of the specific process being targeted.We are developing a data analysis environment called PROcess-Based Explorer (PROBE) that seeks to enable efficient and systematic computation of process-based diagnostics on very large sets of data. In this environment, investigators can define arbitrarily complex filters and then seamlessly perform computations in parallel on the filtered output from their model. The same analysis can be performed on additional related data sets (e.g., reanalyses) thereby enabling routine comparisons between model and observational data. PROBE also incorporates workflow technology to automatically update computed diagnostics for subsequent executions of a model. In this presentation, we will discuss the design and current status of PROBE as well as share results from some preliminary use cases.

Leaving out control groups: an internal contrast analysis of gene expression profiles in atrial fibrillation patients ‐ A systems biology approach to clinical categorization

PubMed Central

Vanhoutte, Kurt; de Asmundis, Carlo; Francesconi, Anna; Figys1, Jurgen; Steurs, Griet; Boussy, Tim; Roos, Markus; Mueller, Andreas; Massimo, Lucio; Paparella, Gaetano; Van Caelenberg, Kristien; Chierchia, Gian Battista; Sarkozy, Andrea; Y Terradellas, Pedro Brugada; Zizi, Martin

2009-01-01

Atrial fibrillation (AF) is a frequent chronic dysrythmia with an incidence that increases with age (>40). Because of its medical and socio-economic impacts it is expected to become an increasing burden on most health care systems. AF is a multi-factorial disease for which the identification of subtypes is warranted. Novel approaches based on the broad concepts of systems biology may overcome the blurred notion of normal and pathological phenotype, which is inherent to high throughput molecular arrays analysis. Here we apply an internal contrast algorithm on AF patient data with an analytical focus on potential entry pathways into the disease. We used a RMA (Robust Multichip Average) normalized Affymetrix micro-array data set from 10 AF patients (geo_accession #GSE2240). Four series of probes were selected based on physiopathogenic links with AF entryways: apoptosis (remodeling), MAP kinase (cell remodeling), OXPHOS (ability to sustain hemodynamic workload) and glycolysis (ischemia). Annotated probe lists were polled with Bioconductor packages in R (version 2.7.1). Genetic profile contrasts were analysed with hierarchical clustering and principal component analysis. The analysis revealed distinct patient groups for all probe sets. A substantial part (54% till 67%) of the variance is explained in the first 2 principal components. Genes in PC1/2 with high discriminatory value were selected and analyzed in detail. We aim for reliable molecular stratification of AF. We show that stratification is possible based on physiologically relevant gene sets. Genes with high contrast value are likely to give pathophysiological insight into permanent AF subtypes. PMID:19255648

A support vector machine designed to identify breasts at high risk using multi-probe generated REIS signals: a preliminary assessment

NASA Astrophysics Data System (ADS)

Gur, David; Zheng, Bin; Lederman, Dror; Dhurjaty, Sreeram; Sumkin, Jules; Zuley, Margarita

2010-02-01

A new resonance-frequency based electronic impedance spectroscopy (REIS) system with multi-probes, including one central probe and six external probes that are designed to contact the breast skin in a circular form with a radius of 60 millimeters to the central ("nipple") probe, has been assembled and installed in our breast imaging facility. We are conducting a prospective clinical study to test the performance of this REIS system in identifying younger women (< 50 years old) at higher risk for having or developing breast cancer. In this preliminary analysis, we selected a subset of 100 examinations. Among these, 50 examinations were recommended for a biopsy due to detection of a highly suspicious breast lesion and 50 were determined negative during mammography screening. REIS output signal sweeps that we used to compute an initial feature included both amplitude and phase information representing differences between corresponding (matched) EIS signal values acquired from the left and right breasts. A genetic algorithm was applied to reduce the feature set and optimize a support vector machine (SVM) to classify the REIS examinations into "biopsy recommended" and "non-biopsy" recommended groups. Using the leave-one-case-out testing method, the classification performance as measured by the area under the receiver operating characteristic (ROC) curve was 0.816 +/- 0.042. This pilot analysis suggests that the new multi-probe-based REIS system could potentially be used as a risk stratification tool to identify pre-screened young women who are at higher risk of having or developing breast cancer.

Floating Potential Probe Langmuir Probe Data Reduction Results

NASA Technical Reports Server (NTRS)

Morton, Thomas L.; Minow, Joseph I.

2002-01-01

During its first five months of operations, the Langmuir Probe on the Floating Potential Probe (FPP) obtained data on ionospheric electron densities and temperatures in the ISS orbit. In this paper, the algorithms for data reduction are presented, and comparisons are made of FPP data with ground-based ionosonde and Incoherent Scattering Radar (ISR) results. Implications for ISS operations are detailed, and the need for a permanent FPP on ISS is examined.

Automatic transperineal ultrasound probe positioning based on CT scan for image guided radiotherapy

NASA Astrophysics Data System (ADS)

Camps, S. M.; Verhaegen, F.; Paiva Fonesca, G.; de With, P. H. N.; Fontanarosa, D.

2017-03-01

Image interpretation is crucial during ultrasound image acquisition. A skilled operator is typically needed to verify if the correct anatomical structures are all visualized and with sufficient quality. The need for this operator is one of the major reasons why presently ultrasound is not widely used in radiotherapy workflows. To solve this issue, we introduce an algorithm that uses anatomical information derived from a CT scan to automatically provide the operator with a patient-specific ultrasound probe setup. The first application we investigated, for its relevance to radiotherapy, is 4D transperineal ultrasound image acquisition for prostate cancer patients. As initial test, the algorithm was applied on a CIRS multi-modality pelvic phantom. Probe setups were calculated in order to allow visualization of the prostate and adjacent edges of bladder and rectum, as clinically required. Five of the proposed setups were reproduced using a precision robotic arm and ultrasound volumes were acquired. A gel-filled probe cover was used to ensure proper acoustic coupling, while taking into account possible tilted positions of the probe with respect to the flat phantom surface. Visual inspection of the acquired volumes revealed that clinical requirements were fulfilled. Preliminary quantitative evaluation was also performed. The mean absolute distance (MAD) was calculated between actual anatomical structure positions and positions predicted by the CT-based algorithm. This resulted in a MAD of (2.8±0.4) mm for prostate, (2.5±0.6) mm for bladder and (2.8±0.6) mm for rectum. These results show that no significant systematic errors due to e.g. probe misplacement were introduced.

Resonant di-Higgs boson production in the b b ¯ W W channel: Probing the electroweak phase transition at the LHC

DOE PAGES

Huang, T.; No, J. M.; Pernié, L.; ...

2017-08-11

Here, we analyze the prospects for resonant di-Higgs production searches at the LHC in themore » $$b\\bar{b}$$W +W − (W +→ℓ +ν ℓ, W −→ℓ −$$\\bar{v}$$ ℓ) channel, as a probe of the nature of the electroweak phase transition in Higgs portal extensions of the Standard Model. In order to maximize the sensitivity in this final state, we develop a new algorithm for the reconstruction of the $$b\\bar{b}$$W +W − invariant mass in the presence of neutrinos from the W decays, building from a technique developed for the reconstruction of resonances decaying to τ +τ − pairs. We show that resonant di-Higgs production in the $$b\\bar{b}$$W +W − channel could be a competitive probe of the electroweak phase transition already with the data sets to be collected by the CMS and ATLAS experiments in run 2 of the LHC. The increase in sensitivity with larger amounts of data accumulated during the high-luminosity LHC phase can be sufficient to enable a potential discovery of the resonant di-Higgs production in this channel.« less

Semi-automatic 10/20 Identification Method for MRI-Free Probe Placement in Transcranial Brain Mapping Techniques.

PubMed

Xiao, Xiang; Zhu, Hao; Liu, Wei-Jie; Yu, Xiao-Ting; Duan, Lian; Li, Zheng; Zhu, Chao-Zhe

2017-01-01

The International 10/20 system is an important head-surface-based positioning system for transcranial brain mapping techniques, e.g., fNIRS and TMS. As guidance for probe placement, the 10/20 system permits both proper ROI coverage and spatial consistency among multiple subjects and experiments in a MRI-free context. However, the traditional manual approach to the identification of 10/20 landmarks faces problems in reliability and time cost. In this study, we propose a semi-automatic method to address these problems. First, a novel head surface reconstruction algorithm reconstructs head geometry from a set of points uniformly and sparsely sampled on the subject's head. Second, virtual 10/20 landmarks are determined on the reconstructed head surface in computational space. Finally, a visually-guided real-time navigation system guides the experimenter to each of the identified 10/20 landmarks on the physical head of the subject. Compared with the traditional manual approach, our proposed method provides a significant improvement both in reliability and time cost and thus could contribute to improving both the effectiveness and efficiency of 10/20-guided MRI-free probe placement.

Resonant di-Higgs boson production in the b b ¯ W W channel: Probing the electroweak phase transition at the LHC

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

Huang, T.; No, J. M.; Pernié, L.

Here, we analyze the prospects for resonant di-Higgs production searches at the LHC in themore » $$b\\bar{b}$$W +W − (W +→ℓ +ν ℓ, W −→ℓ −$$\\bar{v}$$ ℓ) channel, as a probe of the nature of the electroweak phase transition in Higgs portal extensions of the Standard Model. In order to maximize the sensitivity in this final state, we develop a new algorithm for the reconstruction of the $$b\\bar{b}$$W +W − invariant mass in the presence of neutrinos from the W decays, building from a technique developed for the reconstruction of resonances decaying to τ +τ − pairs. We show that resonant di-Higgs production in the $$b\\bar{b}$$W +W − channel could be a competitive probe of the electroweak phase transition already with the data sets to be collected by the CMS and ATLAS experiments in run 2 of the LHC. The increase in sensitivity with larger amounts of data accumulated during the high-luminosity LHC phase can be sufficient to enable a potential discovery of the resonant di-Higgs production in this channel.« less

Microphysics in West African squall line with an Xband polarimetric radar and an Hydrometeor Identification Scheme: comparison with in situ measurements

NASA Astrophysics Data System (ADS)

Cazenave, F.; Gosset, M.; Kacou, M.; Alcoba, M.; Fontaine, E.

2015-12-01

A better knowledge on the microphysics of tropical continental convective systems is needed in order to improve quantitative precipitation measurements in the Tropics. Satellite passive microwave estimation of tropical rainfall could be improved with a better parameterization of the icy hydrometeors in the Bayesian RAIN estimation algorithm (BRAIN, Viltard et al., 2006) used over continental tropics. To address this important issue specific campaigns that combine aircraft based in situ microphysics probing and polarimetric radar have been organized as part of the CNES/ISRO satellite mission Megha-Tropiques. The first microphysics validation campaign was set up in Niamey in August 2010. The field deployment included the AMMA-CATH 56 rain gages, 3 disdrometers, 2 meteorological radars including the C-band MIT and the Xport X-band dual polarisation radar, and a 4 weeks campaign with the instrumented Falcon 20 from the french operator for environmental research aircrafts equipped with several microphysics probes and the 94Ghz cloud radar RASTA. The objective is to combine scales and methods to converge towards a parameterization of the ice size, mass and density laws inside continental Mesoscale Convective System (MCS). The Particle IDentification algorithm (PID) developed by the Colorado State University (CSU) adapted to the band X by B. Dolan (Dolan et al. 2009) is used to classify seven kind of particles: drizzle or light rain, moderate to heavy rain, wet and dry graupel, wet and dry aggregates and ice crystals. On a limited number of systems, the airborne microphysics sensors provide a detailed in situ reference on the Particle Size Distribution (PSD) that can be compared with the radar PID in the radar pixels located along the flight trajectory. An original approach has been developed for the radar - in situ comparison: it consists in simulating synthetic radar variables from the microphysics probe information and compare the 2 data sets in a common 'radar space'. The consistency between the 2 types of observation is good considering the differences in sampling. The time evolution of the hydrometeor types and their relative proportion in the convective and stratiform regions are analyzed for the 13rd August 2010 MCS.

Performance of different reflectance and diffuse optical imaging tomographic approaches in fluorescence molecular imaging of small animals

NASA Astrophysics Data System (ADS)

Dinten, Jean-Marc; Petié, Philippe; da Silva, Anabela; Boutet, Jérôme; Koenig, Anne; Hervé, Lionel; Berger, Michel; Laidevant, Aurélie; Rizo, Philippe

2006-03-01

Optical imaging of fluorescent probes is an essential tool for investigation of molecular events in small animals for drug developments. In order to get localization and quantification information of fluorescent labels, CEA-LETI has developed efficient approaches in classical reflectance imaging as well as in diffuse optical tomographic imaging with continuous and temporal signals. This paper presents an overview of the different approaches investigated and their performances. High quality fluorescence reflectance imaging is obtained thanks to the development of an original "multiple wavelengths" system. The uniformity of the excitation light surface area is better than 15%. Combined with the use of adapted fluorescent probes, this system enables an accurate detection of pathological tissues, such as nodules, beneath the animal's observed area. Performances for the detection of ovarian nodules on a nude mouse are shown. In order to investigate deeper inside animals and get 3D localization, diffuse optical tomography systems are being developed for both slab and cylindrical geometries. For these two geometries, our reconstruction algorithms are based on analytical expression of light diffusion. Thanks to an accurate introduction of light/matter interaction process in the algorithms, high quality reconstructions of tumors in mice have been obtained. Reconstruction of lung tumors on mice are presented. By the use of temporal diffuse optical imaging, localization and quantification performances can be improved at the price of a more sophisticated acquisition system and more elaborate information processing methods. Such a system based on a pulsed laser diode and a time correlated single photon counting system has been set up. Performances of this system for localization and quantification of fluorescent probes are presented.

A Winner Determination Algorithm for Combinatorial Auctions Based on Hybrid Artificial Fish Swarm Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Genrang; Lin, ZhengChun

The problem of winner determination in combinatorial auctions is a hotspot electronic business, and a NP hard problem. A Hybrid Artificial Fish Swarm Algorithm(HAFSA), which is combined with First Suite Heuristic Algorithm (FSHA) and Artificial Fish Swarm Algorithm (AFSA), is proposed to solve the problem after probing it base on the theories of AFSA. Experiment results show that the HAFSA is a rapidly and efficient algorithm for The problem of winner determining. Compared with Ant colony Optimization Algorithm, it has a good performance with broad and prosperous application.

Characterization of Biofilm Community Structure by Ribosomal RNA sequences

DTIC Science & Technology

1989-12-01

for strains of Fibrobacter, 2) Desulfobacter genus-specific probe, 3) Desulfosarcina genus-specific probe, 4) archaebacterial kingdom -specific probes...and 5) eubacterial kingdom -specific probes 5) eukaryote kingdom -specific probe and 6) a general probe encompassing all characterized sulfate-reducing...sets have been fabricated. The group-specific primer sets selectively amplify either sulfate-reducing bacteria or archaebacteria . The SRB-specific

Bilevel thresholding of sliced image of sludge floc.

PubMed

Chu, C P; Lee, D J

2004-02-15

This work examined the feasibility of employing various thresholding algorithms to determining the optimal bilevel thresholding value for estimating the geometric parameters of sludge flocs from the microtome sliced images and from the confocal laser scanning microscope images. Morphological information extracted from images depends on the bilevel thresholding value. According to the evaluation on the luminescence-inverted images and fractal curves (quadric Koch curve and Sierpinski carpet), Otsu's method yields more stable performance than other histogram-based algorithms and is chosen to obtain the porosity. The maximum convex perimeter method, however, can probe the shapes and spatial distribution of the pores among the biomass granules in real sludge flocs. A combined algorithm is recommended for probing the sludge floc structure.

A novel interplanetary optical navigation algorithm based on Earth-Moon group photos by Chang'e-5T1 probe

NASA Astrophysics Data System (ADS)

Bu, Yanlong; Zhang, Qiang; Ding, Chibiao; Tang, Geshi; Wang, Hang; Qiu, Rujin; Liang, Libo; Yin, Hejun

2017-02-01

This paper presents an interplanetary optical navigation algorithm based on two spherical celestial bodies. The remarkable characteristic of the method is that key navigation parameters can be estimated depending entirely on known sizes and ephemerides of two celestial bodies, especially positioning is realized through a single image and does not rely on traditional terrestrial radio tracking any more. Actual Earth-Moon group photos captured by China's Chang'e-5T1 probe were used to verify the effectiveness of the algorithm. From 430,000 km away from the Earth, the camera pointing accuracy reaches 0.01° (one sigma) and the inertial positioning error is less than 200 km, respectively; meanwhile, the cost of the ground control and human resources are greatly reduced. The algorithm is flexible, easy to implement, and can provide reference to interplanetary autonomous navigation in the solar system.

Measuring graph similarity through continuous-time quantum walks and the quantum Jensen-Shannon divergence.

PubMed

Rossi, Luca; Torsello, Andrea; Hancock, Edwin R

2015-02-01

In this paper we propose a quantum algorithm to measure the similarity between a pair of unattributed graphs. We design an experiment where the two graphs are merged by establishing a complete set of connections between their nodes and the resulting structure is probed through the evolution of continuous-time quantum walks. In order to analyze the behavior of the walks without causing wave function collapse, we base our analysis on the recently introduced quantum Jensen-Shannon divergence. In particular, we show that the divergence between the evolution of two suitably initialized quantum walks over this structure is maximum when the original pair of graphs is isomorphic. We also prove that under special conditions the divergence is minimum when the sets of eigenvalues of the Hamiltonians associated with the two original graphs have an empty intersection.

Characterization of airborne transducers by optical tomography

PubMed

Bou Matar O; Pizarro; Certon; Remenieras; Patat

2000-03-01

This paper describes the application of an acousto-optic method to the measurement of airborne ultrasound. The method consists of a heterodyne interferometric probing of the pressure emitted by the transducer combined with a tomographic algorithm. The heterodyne interferometer measures the optical phase shift of the probe laser beam, proportional to the acoustic pressure integrated along the light path. A number of projections of the sound field, e.g. a set of ray integrals obtained along parallel paths, are made in moving the transducer to be tested. The main advantage of the method is its very high sensitivity in air (2 x 10(-4) Pa Hz-1/2), combined with a large bandwidth. Using the same principle as X-ray tomography the ultrasonic pressure in a plane perpendicular to the transducer axis can be reconstructed. Several ultrasonic fields emitted by wide-band home made electrostatic transducers, with operating frequencies between 200 and 700 kHz, have been measured. The sensitivities compared favorably with those of commercial airborne transducers.

Measurement of Air Flow Characteristics Using Seven-Hole Cone Probes

NASA Technical Reports Server (NTRS)

Takahashi, Timothy T.

1997-01-01

The motivation for this work has been the development of a wake survey system. A seven-hole probe can measure the distribution of static pressure, total pressure, and flow angularity in a wind tunnel environment. The author describes the development of a simple, very efficient algorithm to compute flow properties from probe tip pressures. Its accuracy and applicability to unsteady, turbulent flow are discussed.

A computer program for borehole compensation of dual-detector density well logs

USGS Publications Warehouse

Scott, James Henry

1978-01-01

The computer program described in this report was developed for applying a borehole-rugosity and mudcake compensation algorithm to dual-density logs using the following information: the water level in the drill hole, hole diameter (from a caliper log if available, or the nominal drill diameter if not), and the two gamma-ray count rate logs from the near and far detectors of the density probe. The equations that represent the compensation algorithm and the calibration of the two detectors (for converting countrate or density) were derived specifically for a probe manufactured by Comprobe Inc. (5.4 cm O.D. dual-density-caliper); they are not applicable to other probes. However, equivalent calibration and compensation equations can be empirically determined for any other similar two-detector density probes and substituted in the computer program listed in this report. * Use of brand names in this report does not necessarily constitute endorsement by the U.S. Geological Survey.

The changing landscape of dermatology practice: melanoma and pump-probe laser microscopy.

PubMed

Puza, Charles J; Mosca, Paul J

2017-11-01

To present current melanoma diagnosis, staging, prognosis, and treatment algorithms and how recent advances in laser pump-probe microscopy will fill in the gaps in our clinical understanding. Expert opinion and significantly cited articles identified in SCOPUS were used in conjunction with a pubmed database search on Melanoma practice guidelines from the last 10 years. Significant advances in melanoma treatment have been made over the last decade. However, proper treatment algorithm and prognostic information per melanoma stage remain controversial. The next step for providers will involve the identification of patient population(s) that can benefit from recent advances. One method of identifying potential patients is through new laser imaging techniques. Pump-probe laser microscopy has been shown to correctly identify nevi from melanoma and furthermore stratify melanoma by aggressiveness. The recent development of effective adjuvant therapies for melanoma is promising and should be utilized on appropriate patient populations that can potentially be identified using pump-probe laser microscopy.

Automated clustering of probe molecules from solvent mapping of protein surfaces: new algorithms applied to hot-spot mapping and structure-based drug design

NASA Astrophysics Data System (ADS)

Lerner, Michael G.; Meagher, Kristin L.; Carlson, Heather A.

2008-10-01

Use of solvent mapping, based on multiple-copy minimization (MCM) techniques, is common in structure-based drug discovery. The minima of small-molecule probes define locations for complementary interactions within a binding pocket. Here, we present improved methods for MCM. In particular, a Jarvis-Patrick (JP) method is outlined for grouping the final locations of minimized probes into physical clusters. This algorithm has been tested through a study of protein-protein interfaces, showing the process to be robust, deterministic, and fast in the mapping of protein "hot spots." Improvements in the initial placement of probe molecules are also described. A final application to HIV-1 protease shows how our automated technique can be used to partition data too complicated to analyze by hand. These new automated methods may be easily and quickly extended to other protein systems, and our clustering methodology may be readily incorporated into other clustering packages.

Respiratory rate estimation during triage of children in hospitals.

PubMed

Shah, Syed Ahmar; Fleming, Susannah; Thompson, Matthew; Tarassenko, Lionel

2015-01-01

Accurate assessment of a child's health is critical for appropriate allocation of medical resources and timely delivery of healthcare in Emergency Departments. The accurate measurement of vital signs is a key step in the determination of the severity of illness and respiratory rate is currently the most difficult vital sign to measure accurately. Several previous studies have attempted to extract respiratory rate from photoplethysmogram (PPG) recordings. However, the majority have been conducted in controlled settings using PPG recordings from healthy subjects. In many studies, manual selection of clean sections of PPG recordings was undertaken before assessing the accuracy of the signal processing algorithms developed. Such selection procedures are not appropriate in clinical settings. A major limitation of AR modelling, previously applied to respiratory rate estimation, is an appropriate selection of model order. This study developed a novel algorithm that automatically estimates respiratory rate from a median spectrum constructed applying multiple AR models to processed PPG segments acquired with pulse oximetry using a finger probe. Good-quality sections were identified using a dynamic template-matching technique to assess PPG signal quality. The algorithm was validated on 205 children presenting to the Emergency Department at the John Radcliffe Hospital, Oxford, UK, with reference respiratory rates up to 50 breaths per minute estimated by paediatric nurses. At the time of writing, the authors are not aware of any other study that has validated respiratory rate estimation using data collected from over 200 children in hospitals during routine triage.

[Effect of algorithms for calibration set selection on quantitatively determining asiaticoside content in Centella total glucosides by near infrared spectroscopy].

PubMed

Zhan, Xue-yan; Zhao, Na; Lin, Zhao-zhou; Wu, Zhi-sheng; Yuan, Rui-juan; Qiao, Yan-jiang

2014-12-01

The appropriate algorithm for calibration set selection was one of the key technologies for a good NIR quantitative model. There are different algorithms for calibration set selection, such as Random Sampling (RS) algorithm, Conventional Selection (CS) algorithm, Kennard-Stone(KS) algorithm and Sample set Portioning based on joint x-y distance (SPXY) algorithm, et al. However, there lack systematic comparisons between two algorithms of the above algorithms. The NIR quantitative models to determine the asiaticoside content in Centella total glucosides were established in the present paper, of which 7 indexes were classified and selected, and the effects of CS algorithm, KS algorithm and SPXY algorithm for calibration set selection on the accuracy and robustness of NIR quantitative models were investigated. The accuracy indexes of NIR quantitative models with calibration set selected by SPXY algorithm were significantly different from that with calibration set selected by CS algorithm or KS algorithm, while the robustness indexes, such as RMSECV and |RMSEP-RMSEC|, were not significantly different. Therefore, SPXY algorithm for calibration set selection could improve the predicative accuracy of NIR quantitative models to determine asiaticoside content in Centella total glucosides, and have no significant effect on the robustness of the models, which provides a reference to determine the appropriate algorithm for calibration set selection when NIR quantitative models are established for the solid system of traditional Chinese medcine.

Rapid polymerase chain reaction-based screening assay for bacterial biothreat agents.

PubMed

Yang, Samuel; Rothman, Richard E; Hardick, Justin; Kuroki, Marcos; Hardick, Andrew; Doshi, Vishal; Ramachandran, Padmini; Gaydos, Charlotte A

2008-04-01

To design and evaluate a rapid polymerase chain reaction (PCR)-based assay for detecting Eubacteria and performing early screening for selected Class A biothreat bacterial pathogens. The authors designed a two-step PCR-based algorithm consisting of an initial broad-based universal detection step, followed by specific pathogen identification targeted for identification of the Class A bacterial biothreat agents. A region in the bacterial 16S rRNA gene containing a highly variable sequence flanked by clusters of conserved sequences was chosen as the target for the PCR assay design. A previously described highly conserved region located within the 16S rRNA amplicon was selected as the universal probe (UniProbe, Integrated DNA Technology, Coralville, IA). Pathogen-specific TaqMan probes were designed for Bacillus anthracis, Yersinia pestis, and Francisella tularensis. Performance of the assay was assessed using genomic DNA extracted from the aforementioned biothreat-related organisms (inactivated or surrogate) and other common bacteria. The UniProbe detected the presence of all tested Eubacteria (31/31) with high analytical sensitivity. The biothreat-specific probes accurately identified organisms down to the closely related species and genus level, but were unable to discriminate between very close surrogates, such as Yersinia philomiragia and Bacillus cereus. A simple, two-step PCR-based assay proved capable of both universal bacterial detection and identification of select Class A bacterial biothreat and biothreat-related pathogens. Although this assay requires confirmatory testing for definitive species identification, the method has great potential for use in ED-based settings for rapid diagnosis in cases of suspected Category A bacterial biothreat agents.

SigReannot-mart: a query environment for expression microarray probe re-annotations.

PubMed

Moreews, François; Rauffet, Gaelle; Dehais, Patrice; Klopp, Christophe

2011-01-01

Expression microarrays are commonly used to study transcriptomes. Most of the arrays are now based on oligo-nucleotide probes. Probe design being a tedious task, it often takes place once at the beginning of the project. The oligo set is then used for several years. During this time period, the knowledge gathered by the community on the genome and the transcriptome increases and gets more precise. Therefore re-annotating the set is essential to supply the biologists with up-to-date annotations. SigReannot-mart is a query environment populated with regularly updated annotations for different oligo sets. It stores the results of the SigReannot pipeline that has mainly been used on farm and aquaculture species. It permits easy extraction in different formats using filters. It is used to compare probe sets on different criteria, to choose the set for a given experiment to mix probe sets in order to create a new one.

Retinal vessel segmentation on SLO image

PubMed Central

Xu, Juan; Ishikawa, Hiroshi; Wollstein, Gadi; Schuman, Joel S.

2010-01-01

A scanning laser ophthalmoscopy (SLO) image, taken from optical coherence tomography (OCT), usually has lower global/local contrast and more noise compared to the traditional retinal photograph, which makes the vessel segmentation challenging work. A hybrid algorithm is proposed to efficiently solve these problems by fusing several designed methods, taking the advantages of each method and reducing the error measurements. The algorithm has several steps consisting of image preprocessing, thresholding probe and weighted fusing. Four different methods are first designed to transform the SLO image into feature response images by taking different combinations of matched filter, contrast enhancement and mathematical morphology operators. A thresholding probe algorithm is then applied on those response images to obtain four vessel maps. Weighted majority opinion is used to fuse these vessel maps and generate a final vessel map. The experimental results showed that the proposed hybrid algorithm could successfully segment the blood vessels on SLO images, by detecting the major and small vessels and suppressing the noises. The algorithm showed substantial potential in various clinical applications. The use of this method can be also extended to medical image registration based on blood vessel location. PMID:19163149

Strawberry: Fast and accurate genome-guided transcript reconstruction and quantification from RNA-Seq.

PubMed

Liu, Ruolin; Dickerson, Julie

2017-11-01

We propose a novel method and software tool, Strawberry, for transcript reconstruction and quantification from RNA-Seq data under the guidance of genome alignment and independent of gene annotation. Strawberry consists of two modules: assembly and quantification. The novelty of Strawberry is that the two modules use different optimization frameworks but utilize the same data graph structure, which allows a highly efficient, expandable and accurate algorithm for dealing large data. The assembly module parses aligned reads into splicing graphs, and uses network flow algorithms to select the most likely transcripts. The quantification module uses a latent class model to assign read counts from the nodes of splicing graphs to transcripts. Strawberry simultaneously estimates the transcript abundances and corrects for sequencing bias through an EM algorithm. Based on simulations, Strawberry outperforms Cufflinks and StringTie in terms of both assembly and quantification accuracies. Under the evaluation of a real data set, the estimated transcript expression by Strawberry has the highest correlation with Nanostring probe counts, an independent experiment measure for transcript expression. Strawberry is written in C++14, and is available as open source software at https://github.com/ruolin/strawberry under the MIT license.

Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling.

PubMed

Perdikaris, P; Raissi, M; Damianou, A; Lawrence, N D; Karniadakis, G E

2017-02-01

Multi-fidelity modelling enables accurate inference of quantities of interest by synergistically combining realizations of low-cost/low-fidelity models with a small set of high-fidelity observations. This is particularly effective when the low- and high-fidelity models exhibit strong correlations, and can lead to significant computational gains over approaches that solely rely on high-fidelity models. However, in many cases of practical interest, low-fidelity models can only be well correlated to their high-fidelity counterparts for a specific range of input parameters, and potentially return wrong trends and erroneous predictions if probed outside of their validity regime. Here we put forth a probabilistic framework based on Gaussian process regression and nonlinear autoregressive schemes that is capable of learning complex nonlinear and space-dependent cross-correlations between models of variable fidelity, and can effectively safeguard against low-fidelity models that provide wrong trends. This introduces a new class of multi-fidelity information fusion algorithms that provide a fundamental extension to the existing linear autoregressive methodologies, while still maintaining the same algorithmic complexity and overall computational cost. The performance of the proposed methods is tested in several benchmark problems involving both synthetic and real multi-fidelity datasets from computational fluid dynamics simulations.

Performance Comparison of High-Speed Dual-Pneumatic Vitrectomy Cutters during Simulated Vitrectomy with Balanced Salt Solution.

PubMed

Abulon, Dina Joy K; Buboltz, David C

2015-02-01

To measure flow rate of balanced salt solution and IOP during simulated vitrectomy using two sets of high-speed dual-pneumatic probes. A closed-model eye system measured IOP and flow rate of a balanced salt solution through infusion cannula. The Constellation Vision System was tested with two sets of high-speed dual-pneumatic probes (UltraVit 23-gauge and enhanced 25+-gauge 5000-cpm probes; UltraVit 23-gauge and enhanced 25+-gauge 7500-cpm probes; n = 6 each) under different vacuum levels and cut rates in three duty cycle modes. In both probe sets, flow rates were dependent on cut rate with the biased open and biased closed duty cycles. Flow rates were highest with the biased open duty cycle, lower with the 50/50 duty cycle, and lowest with the biased closed duty cycle. IOP, as expected, was inversely associated with flow rate using both probe sets. The 7500-cpm probes offer greater control and customization compared with 5000-cpm probes under certain experimental conditions. At maximum cut rates, performance of 7500-cpm probes was similar to that of 5000-cpm probes, suggesting that 7500-cpm probes may be used without sacrifice of flow rate and IOP stability. Customization of vitrectomy parameters allows greater surgeon control during vitrectomy and may expand the usefulness of vitrectomy probes.

RUBIC identifies driver genes by detecting recurrent DNA copy number breaks

PubMed Central

van Dyk, Ewald; Hoogstraat, Marlous; ten Hoeve, Jelle; Reinders, Marcel J. T.; Wessels, Lodewyk F. A.

2016-01-01

The frequent recurrence of copy number aberrations across tumour samples is a reliable hallmark of certain cancer driver genes. However, state-of-the-art algorithms for detecting recurrent aberrations fail to detect several known drivers. In this study, we propose RUBIC, an approach that detects recurrent copy number breaks, rather than recurrently amplified or deleted regions. This change of perspective allows for a simplified approach as recursive peak splitting procedures and repeated re-estimation of the background model are avoided. Furthermore, we control the false discovery rate on the level of called regions, rather than at the probe level, as in competing algorithms. We benchmark RUBIC against GISTIC2 (a state-of-the-art approach) and RAIG (a recently proposed approach) on simulated copy number data and on three SNP6 and NGS copy number data sets from TCGA. We show that RUBIC calls more focal recurrent regions and identifies a much larger fraction of known cancer genes. PMID:27396759

Where do pulse oximeter probes break?

PubMed

Crede, S; Van der Merwe, G; Hutchinson, J; Woods, D; Karlen, W; Lawn, J

2014-06-01

Pulse oximetry, a non-invasive method for accurate assessment of blood oxygen saturation (SPO2), is an important monitoring tool in health care facilities. However, it is often not available in many low-resource settings, due to expense, overly sophisticated design, a lack of organised procurement systems and inadequate medical device management and maintenance structures. Furthermore medical devices are often fragile and not designed to withstand the conditions of low-resource settings. In order to design a probe, better suited to the needs of health care facilities in low-resource settings this study aimed to document the site and nature of pulse oximeter probe breakages in a range of different probe designs in a low to middle income country. A retrospective review of job cards relating to the assessment and repair of damaged or faulty pulse oximeter probes was conducted at a medical device repair company based in Cape Town, South Africa, specializing in pulse oximeter probe repairs. 1,840 job cards relating to the assessment and repair of pulse oximeter probes were reviewed. 60.2 % of probes sent for assessment were finger-clip probes. For all probes, excluding the neonatal wrap probes, the most common point of failure was the probe wiring (>50 %). The neonatal wrap most commonly failed at the strap (51.5 %). The total cost for quoting on the broken pulse oximeter probes and for the subsequent repair of devices, excluding replacement components, amounted to an estimated ZAR 738,810 (USD $98,508). Improving the probe wiring would increase the life span of pulse oximeter probes. Increasing the life span of probes will make pulse oximetry more affordable and accessible. This is of high priority in low-resource settings where frequent repair or replacement of probes is unaffordable or impossible.

OCaPPI-Db: an oligonucleotide probe database for pathogen identification through hybridization capture.

PubMed

Gasc, Cyrielle; Constantin, Antony; Jaziri, Faouzi; Peyret, Pierre

2017-01-01

The detection and identification of bacterial pathogens involved in acts of bio- and agroterrorism are essential to avoid pathogen dispersal in the environment and propagation within the population. Conventional molecular methods, such as PCR amplification, DNA microarrays or shotgun sequencing, are subject to various limitations when assessing environmental samples, which can lead to inaccurate findings. We developed a hybridization capture strategy that uses a set of oligonucleotide probes to target and enrich biomarkers of interest in environmental samples. Here, we present Oligonucleotide Capture Probes for Pathogen Identification Database (OCaPPI-Db), an online capture probe database containing a set of 1,685 oligonucleotide probes allowing for the detection and identification of 30 biothreat agents up to the species level. This probe set can be used in its entirety as a comprehensive diagnostic tool or can be restricted to a set of probes targeting a specific pathogen or virulence factor according to the user's needs. : http://ocappidb.uca.works. © The Author(s) 2017. Published by Oxford University Press.

Data compressive paradigm for multispectral sensing using tunable DWELL mid-infrared detectors.

PubMed

Jang, Woo-Yong; Hayat, Majeed M; Godoy, Sebastián E; Bender, Steven C; Zarkesh-Ha, Payman; Krishna, Sanjay

2011-09-26

While quantum dots-in-a-well (DWELL) infrared photodetectors have the feature that their spectral responses can be shifted continuously by varying the applied bias, the width of the spectral response at any applied bias is not sufficiently narrow for use in multispectral sensing without the aid of spectral filters. To achieve higher spectral resolutions without using physical spectral filters, algorithms have been developed for post-processing the DWELL's bias-dependent photocurrents resulting from probing an object of interest repeatedly over a wide range of applied biases. At the heart of these algorithms is the ability to approximate an arbitrary spectral filter, which we desire the DWELL-algorithm combination to mimic, by forming a weighted superposition of the DWELL's non-orthogonal spectral responses over a range of applied biases. However, these algorithms assume availability of abundant DWELL data over a large number of applied biases (>30), leading to large overall acquisition times in proportion with the number of biases. This paper reports a new multispectral sensing algorithm to substantially compress the number of necessary bias values subject to a prescribed performance level across multiple sensing applications. The algorithm identifies a minimal set of biases to be used in sensing only the relevant spectral information for remote-sensing applications of interest. Experimental results on target spectrometry and classification demonstrate a reduction in the number of required biases by a factor of 7 (e.g., from 30 to 4). The tradeoff between performance and bias compression is thoroughly investigated. © 2011 Optical Society of America

Window-based method for approximating the Hausdorff in three-dimensional range imagery

DOEpatents

Koch, Mark W [Albuquerque, NM

2009-06-02

One approach to pattern recognition is to use a template from a database of objects and match it to a probe image containing the unknown. Accordingly, the Hausdorff distance can be used to measure the similarity of two sets of points. In particular, the Hausdorff can measure the goodness of a match in the presence of occlusion, clutter, and noise. However, existing 3D algorithms for calculating the Hausdorff are computationally intensive, making them impractical for pattern recognition that requires scanning of large databases. The present invention is directed to a new method that can efficiently, in time and memory, compute the Hausdorff for 3D range imagery. The method uses a window-based approach.

General purpose graphics-processing-unit implementation of cosmological domain wall network evolution.

PubMed

Correia, J R C C C; Martins, C J A P

2017-10-01

Topological defects unavoidably form at symmetry breaking phase transitions in the early universe. To probe the parameter space of theoretical models and set tighter experimental constraints (exploiting the recent advances in astrophysical observations), one requires more and more demanding simulations, and therefore more hardware resources and computation time. Improving the speed and efficiency of existing codes is essential. Here we present a general purpose graphics-processing-unit implementation of the canonical Press-Ryden-Spergel algorithm for the evolution of cosmological domain wall networks. This is ported to the Open Computing Language standard, and as a consequence significant speedups are achieved both in two-dimensional (2D) and 3D simulations.

The Fragment Network: A Chemistry Recommendation Engine Built Using a Graph Database.

PubMed

Hall, Richard J; Murray, Christopher W; Verdonk, Marcel L

2017-07-27

The hit validation stage of a fragment-based drug discovery campaign involves probing the SAR around one or more fragment hits. This often requires a search for similar compounds in a corporate collection or from commercial suppliers. The Fragment Network is a graph database that allows a user to efficiently search chemical space around a compound of interest. The result set is chemically intuitive, naturally grouped by substitution pattern and meaningfully sorted according to the number of observations of each transformation in medicinal chemistry databases. This paper describes the algorithms used to construct and search the Fragment Network and provides examples of how it may be used in a drug discovery context.

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

Heredia-Langner, Alejandro; Amidan, Brett G.; Matzner, Shari

We present results from the optimization of a re-identification process using two sets of biometric data obtained from the Civilian American and European Surface Anthropometry Resource Project (CAESAR) database. The datasets contain real measurements of features for 2378 individuals in a standing (43 features) and seated (16 features) position. A genetic algorithm (GA) was used to search a large combinatorial space where different features are available between the probe (seated) and gallery (standing) datasets. Results show that optimized model predictions obtained using less than half of the 43 gallery features and data from roughly 16% of the individuals available producemore » better re-identification rates than two other approaches that use all the information available.« less

Spectral classifier design with ensemble classifiers and misclassification-rejection: application to elastic-scattering spectroscopy for detection of colonic neoplasia.

PubMed

Rodriguez-Diaz, Eladio; Castanon, David A; Singh, Satish K; Bigio, Irving J

2011-06-01

Optical spectroscopy has shown potential as a real-time, in vivo, diagnostic tool for identifying neoplasia during endoscopy. We present the development of a diagnostic algorithm to classify elastic-scattering spectroscopy (ESS) spectra as either neoplastic or non-neoplastic. The algorithm is based on pattern recognition methods, including ensemble classifiers, in which members of the ensemble are trained on different regions of the ESS spectrum, and misclassification-rejection, where the algorithm identifies and refrains from classifying samples that are at higher risk of being misclassified. These "rejected" samples can be reexamined by simply repositioning the probe to obtain additional optical readings or ultimately by sending the polyp for histopathological assessment, as per standard practice. Prospective validation using separate training and testing sets result in a baseline performance of sensitivity = .83, specificity = .79, using the standard framework of feature extraction (principal component analysis) followed by classification (with linear support vector machines). With the developed algorithm, performance improves to Se ∼ 0.90, Sp ∼ 0.90, at a cost of rejecting 20-33% of the samples. These results are on par with a panel of expert pathologists. For colonoscopic prevention of colorectal cancer, our system could reduce biopsy risk and cost, obviate retrieval of non-neoplastic polyps, decrease procedure time, and improve assessment of cancer risk.

Spectral classifier design with ensemble classifiers and misclassification-rejection: application to elastic-scattering spectroscopy for detection of colonic neoplasia

PubMed Central

Rodriguez-Diaz, Eladio; Castanon, David A.; Singh, Satish K.; Bigio, Irving J.

2011-01-01

Optical spectroscopy has shown potential as a real-time, in vivo, diagnostic tool for identifying neoplasia during endoscopy. We present the development of a diagnostic algorithm to classify elastic-scattering spectroscopy (ESS) spectra as either neoplastic or non-neoplastic. The algorithm is based on pattern recognition methods, including ensemble classifiers, in which members of the ensemble are trained on different regions of the ESS spectrum, and misclassification-rejection, where the algorithm identifies and refrains from classifying samples that are at higher risk of being misclassified. These “rejected” samples can be reexamined by simply repositioning the probe to obtain additional optical readings or ultimately by sending the polyp for histopathological assessment, as per standard practice. Prospective validation using separate training and testing sets result in a baseline performance of sensitivity = .83, specificity = .79, using the standard framework of feature extraction (principal component analysis) followed by classification (with linear support vector machines). With the developed algorithm, performance improves to Se ∼ 0.90, Sp ∼ 0.90, at a cost of rejecting 20–33% of the samples. These results are on par with a panel of expert pathologists. For colonoscopic prevention of colorectal cancer, our system could reduce biopsy risk and cost, obviate retrieval of non-neoplastic polyps, decrease procedure time, and improve assessment of cancer risk. PMID:21721830

An introduction to the theory of ptychographic phase retrieval methods

NASA Astrophysics Data System (ADS)

Konijnenberg, Sander

2017-12-01

An overview of several ptychographic phase retrieval methods and the theory behind them is presented. By looking into the theory behind more basic single-intensity pattern phase retrieval methods, a theoretical framework is provided for analyzing ptychographic algorithms. Extensions of ptychographic algorithms that deal with issues such as partial coherence, thick samples, or uncertainties of the probe or probe positions are also discussed. This introduction is intended for scientists and students without prior experience in the field of phase retrieval or ptychography to quickly get introduced to the theory, so that they can put the more specialized literature in context more easily.

High density DNA microarrays: algorithms and biomedical applications.

PubMed

Liu, Wei-Min

2004-08-01

DNA microarrays are devices capable of detecting the identity and abundance of numerous DNA or RNA segments in samples. They are used for analyzing gene expressions, identifying genetic markers and detecting mutations on a genomic scale. The fundamental chemical mechanism of DNA microarrays is the hybridization between probes and targets due to the hydrogen bonds of nucleotide base pairing. Since the cross hybridization is inevitable, and probes or targets may form undesirable secondary or tertiary structures, the microarray data contain noise and depend on experimental conditions. It is crucial to apply proper statistical algorithms to obtain useful signals from noisy data. After we obtained the signals of a large amount of probes, we need to derive the biomedical information such as the existence of a transcript in a cell, the difference of expression levels of a gene in multiple samples, and the type of a genetic marker. Furthermore, after the expression levels of thousands of genes or the genotypes of thousands of single nucleotide polymorphisms are determined, it is usually important to find a small number of genes or markers that are related to a disease, individual reactions to drugs, or other phenotypes. All these applications need careful data analyses and reliable algorithms.

Statistical analysis of an RNA titration series evaluates microarray precision and sensitivity on a whole-array basis

PubMed Central

Holloway, Andrew J; Oshlack, Alicia; Diyagama, Dileepa S; Bowtell, David DL; Smyth, Gordon K

2006-01-01

Background Concerns are often raised about the accuracy of microarray technologies and the degree of cross-platform agreement, but there are yet no methods which can unambiguously evaluate precision and sensitivity for these technologies on a whole-array basis. Results A methodology is described for evaluating the precision and sensitivity of whole-genome gene expression technologies such as microarrays. The method consists of an easy-to-construct titration series of RNA samples and an associated statistical analysis using non-linear regression. The method evaluates the precision and responsiveness of each microarray platform on a whole-array basis, i.e., using all the probes, without the need to match probes across platforms. An experiment is conducted to assess and compare four widely used microarray platforms. All four platforms are shown to have satisfactory precision but the commercial platforms are superior for resolving differential expression for genes at lower expression levels. The effective precision of the two-color platforms is improved by allowing for probe-specific dye-effects in the statistical model. The methodology is used to compare three data extraction algorithms for the Affymetrix platforms, demonstrating poor performance for the commonly used proprietary algorithm relative to the other algorithms. For probes which can be matched across platforms, the cross-platform variability is decomposed into within-platform and between-platform components, showing that platform disagreement is almost entirely systematic rather than due to measurement variability. Conclusion The results demonstrate good precision and sensitivity for all the platforms, but highlight the need for improved probe annotation. They quantify the extent to which cross-platform measures can be expected to be less accurate than within-platform comparisons for predicting disease progression or outcome. PMID:17118209

Dimensionality of Data Matrices with Applications to Gene Expression Profiles

ERIC Educational Resources Information Center

Feng, Xingdong

2009-01-01

Probe-level microarray data are usually stored in matrices. Take a given probe set (gene), for example, each row of the matrix corresponds to an array, and each column corresponds to a probe. Often, people summarize each array by the gene expression level. Is one number sufficient to summarize a whole probe set for a specific gene in an array?…

Robust non-rigid registration algorithm based on local affine registration

NASA Astrophysics Data System (ADS)

Wu, Liyang; Xiong, Lei; Du, Shaoyi; Bi, Duyan; Fang, Ting; Liu, Kun; Wu, Dongpeng

2018-04-01

Aiming at the problem that the traditional point set non-rigid registration algorithm has low precision and slow convergence speed for complex local deformation data, this paper proposes a robust non-rigid registration algorithm based on local affine registration. The algorithm uses a hierarchical iterative method to complete the point set non-rigid registration from coarse to fine. In each iteration, the sub data point sets and sub model point sets are divided and the shape control points of each sub point set are updated. Then we use the control point guided affine ICP algorithm to solve the local affine transformation between the corresponding sub point sets. Next, the local affine transformation obtained by the previous step is used to update the sub data point sets and their shape control point sets. When the algorithm reaches the maximum iteration layer K, the loop ends and outputs the updated sub data point sets. Experimental results demonstrate that the accuracy and convergence of our algorithm are greatly improved compared with the traditional point set non-rigid registration algorithms.

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

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

Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.

Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

DOE PAGES

Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.; ...

2016-06-24

Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

Mapping heritability and molecular genetic associations with cortical features using probabilistic brain atlases: methods and applications to schizophrenia.

PubMed

Cannon, Tyrone D; Thompson, Paul M; van Erp, Theo G M; Huttunen, Matti; Lonnqvist, Jouko; Kaprio, Jaakko; Toga, Arthur W

2006-01-01

There is an urgent need to decipher the complex nature of genotype-phenotype relationships within the multiple dimensions of brain structure and function that are compromised in neuropsychiatric syndromes such as schizophrenia. Doing so requires sophisticated methodologies to represent population variability in neural traits and to probe their heritable and molecular genetic bases. We have recently developed and applied computational algorithms to map the heritability of, as well as genetic linkage and association to, neural features encoded using brain imaging in the context of three-dimensional (3D), populationbased, statistical brain atlases. One set of algorithms builds on our prior work using classical twin study methods to estimate heritability by fitting biometrical models for additive genetic, unique, and common environmental influences. Another set of algorithms performs regression-based (Haseman-Elston) identical-bydescent linkage analysis and genetic association analysis of DNA polymorphisms in relation to neural traits of interest in the same 3D population-based brain atlas format. We demonstrate these approaches using samples of healthy monozygotic (MZ) and dizygotic (DZ) twin pairs, as well as MZ and DZ twin pairs discordant for schizophrenia, but the methods can be generalized to other classes of relatives and to other diseases. The results confirm prior evidence of genetic influences on gray matter density in frontal brain regions. They also provide converging evidence that the chromosome 1q42 region is relevant to schizophrenia by demonstrating linkage and association of markers of the Transelin-Associated-Factor-X and Disrupted-In- Schizophrenia-1 genes with prefrontal cortical gray matter deficits in twins discordant for schizophrenia.

Fusion of classifiers for REIS-based detection of suspicious breast lesions

NASA Astrophysics Data System (ADS)

Lederman, Dror; Wang, Xingwei; Zheng, Bin; Sumkin, Jules H.; Tublin, Mitchell; Gur, David

2011-03-01

After developing a multi-probe resonance-frequency electrical impedance spectroscopy (REIS) system aimed at detecting women with breast abnormalities that may indicate a developing breast cancer, we have been conducting a prospective clinical study to explore the feasibility of applying this REIS system to classify younger women (< 50 years old) into two groups of "higher-than-average risk" and "average risk" of having or developing breast cancer. The system comprises one central probe placed in contact with the nipple, and six additional probes uniformly distributed along an outside circle to be placed in contact with six points on the outer breast skin surface. In this preliminary study, we selected an initial set of 174 examinations on participants that have completed REIS examinations and have clinical status verification. Among these, 66 examinations were recommended for biopsy due to findings of a highly suspicious breast lesion ("positives"), and 108 were determined as negative during imaging based procedures ("negatives"). A set of REIS-based features, extracted using a mirror-matched approach, was computed and fed into five machine learning classifiers. A genetic algorithm was used to select an optimal subset of features for each of the five classifiers. Three fusion rules, namely sum rule, weighted sum rule and weighted median rule, were used to combine the results of the classifiers. Performance evaluation was performed using a leave-one-case-out cross-validation method. The results indicated that REIS may provide a new technology to identify younger women with higher than average risk of having or developing breast cancer. Furthermore, it was shown that fusion rule, such as a weighted median fusion rule and a weighted sum fusion rule may improve performance as compared with the highest performing single classifier.

Advanced Fast 3-D Electromagnetic Solver for Microwave Tomography Imaging.

PubMed

Simonov, Nikolai; Kim, Bo-Ra; Lee, Kwang-Jae; Jeon, Soon-Ik; Son, Seong-Ho

2017-10-01

This paper describes a fast-forward electromagnetic solver (FFS) for the image reconstruction algorithm of our microwave tomography system. Our apparatus is a preclinical prototype of a biomedical imaging system, designed for the purpose of early breast cancer detection. It operates in the 3-6-GHz frequency band using a circular array of probe antennas immersed in a matching liquid; it produces image reconstructions of the permittivity and conductivity profiles of the breast under examination. Our reconstruction algorithm solves the electromagnetic (EM) inverse problem and takes into account the real EM properties of the probe antenna array as well as the influence of the patient's body and that of the upper metal screen sheet. This FFS algorithm is much faster than conventional EM simulation solvers. In comparison, in the same PC, the CST solver takes ~45 min, while the FFS takes ~1 s of effective simulation time for the same EM model of a numerical breast phantom.

Pressure modulation algorithm to separate cerebral hemodynamic signals from extracerebral artifacts.

PubMed

Baker, Wesley B; Parthasarathy, Ashwin B; Ko, Tiffany S; Busch, David R; Abramson, Kenneth; Tzeng, Shih-Yu; Mesquita, Rickson C; Durduran, Turgut; Greenberg, Joel H; Kung, David K; Yodh, Arjun G

2015-07-01

We introduce and validate a pressure measurement paradigm that reduces extracerebral contamination from superficial tissues in optical monitoring of cerebral blood flow with diffuse correlation spectroscopy (DCS). The scheme determines subject-specific contributions of extracerebral and cerebral tissues to the DCS signal by utilizing probe pressure modulation to induce variations in extracerebral blood flow. For analysis, the head is modeled as a two-layer medium and is probed with long and short source-detector separations. Then a combination of pressure modulation and a modified Beer-Lambert law for flow enables experimenters to linearly relate differential DCS signals to cerebral and extracerebral blood flow variation without a priori anatomical information. We demonstrate the algorithm's ability to isolate cerebral blood flow during a finger-tapping task and during graded scalp ischemia in healthy adults. Finally, we adapt the pressure modulation algorithm to ameliorate extracerebral contamination in monitoring of cerebral blood oxygenation and blood volume by near-infrared spectroscopy.

A novel multisensor traffic state assessment system based on incomplete data.

PubMed

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Jiang, Yaoliang

2014-01-01

A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system.

A Novel Multisensor Traffic State Assessment System Based on Incomplete Data

PubMed Central

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Jiang, Yaoliang

2014-01-01

A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system. PMID:25162055

Parachute Dynamics Investigations Using a Sensor Package Airdropped from a Small-Scale Airplane

NASA Technical Reports Server (NTRS)

Dooley, Jessica; Lorenz, Ralph D.

2005-01-01

We explore the utility of various sensors by recovering parachute-probe dynamics information from a package released from a small-scale, remote-controlled airplane. The airdrops aid in the development of datasets for the exploration of planetary probe trajectory recovery algorithms, supplementing data collected from instrumented, full-scale tests and computer models.

Challenges in Analyzing and Representing Cloud Microphysical Data Measured with Airborne Cloud Probes

NASA Astrophysics Data System (ADS)

Baumgardner, D.; Freer, M.; McFarquhar, G. M.; Heymsfield, A.; Cziczo, D. J.

2014-12-01

There are a variety of in-situ instruments that are deployed on aircraft for measuring cloud properties, some of which provide data which are used to produce number and mass concentrations of water droplets and ice crystals and their size and shape distributions. Each of these instruments has its strengths and limitations that must be recognized and taken into account during analysis of the data. Various processing techniques have been developed by different groups and techniques implemented to partially correct for the known uncertainties and limitations. The cloud measurement community has in general acknowledged the various issues associated with these instruments and numerous studies have published processing algorithms that seek to improve data quality; however, there has not been a forum in which these various algorithms and processing techniques have been discussed and consensus reached both on optimum analysis strategy and on quantification of uncertainties on the derived data products. Prior to the 2014 AMS Cloud Physics Conference, a study was conducted in which many data sets taken from various aircraft (NCAR-130, North Dakota Citation, Wyoming King Air and FAAM BAE-146) and many instruments (FSSP, CDP, SID, 2D-C/P, CIP/PIP, 2D-S, CPI, Nevzorov Probe and King Hot-wire LWC sensor) were processed by more than 20 individuals or groups to produce a large number of derived products (size distributions, ice fraction, number and mass concentrations, CCN/IN concentrations and median volume diameter). Each person or group that processed a selected data set used their own software and algorithm to produce a secondary data file with derived parameters whose name was encoded to conceal the source of the file so that this was a blind comparison. The workshop that was convened July 5 and 6, 2014, presented the results of the evaluation of the derived products with respect to individual instruments as well as the types of conditions under which the measurements were made. This comparison will ultimately allow quantifying the error bars of derived parameters as a function of the conditions in which the observations are made. The results of this evaluation and the recommendations that evolved from the workshop will be summarized in this presentation.

Directional Histogram Ratio at Random Probes: A Local Thresholding Criterion for Capillary Images

PubMed Central

Lu, Na; Silva, Jharon; Gu, Yu; Gerber, Scott; Wu, Hulin; Gelbard, Harris; Dewhurst, Stephen; Miao, Hongyu

2013-01-01

With the development of micron-scale imaging techniques, capillaries can be conveniently visualized using methods such as two-photon and whole mount microscopy. However, the presence of background staining, leaky vessels and the diffusion of small fluorescent molecules can lead to significant complexity in image analysis and loss of information necessary to accurately quantify vascular metrics. One solution to this problem is the development of accurate thresholding algorithms that reliably distinguish blood vessels from surrounding tissue. Although various thresholding algorithms have been proposed, our results suggest that without appropriate pre- or post-processing, the existing approaches may fail to obtain satisfactory results for capillary images that include areas of contamination. In this study, we propose a novel local thresholding algorithm, called directional histogram ratio at random probes (DHR-RP). This method explicitly considers the geometric features of tube-like objects in conducting image binarization, and has a reliable performance in distinguishing small vessels from either clean or contaminated background. Experimental and simulation studies suggest that our DHR-RP algorithm is superior over existing thresholding methods. PMID:23525856

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Kokaly, Raymond F.; Sutley, Steve J.; Dalton, J. Brad; McDougal, Robert R.; Gent, Carol A.

2003-01-01

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

Algorithms for Disconnected Diagrams in Lattice QCD

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

Gambhir, Arjun Singh; Stathopoulos, Andreas; Orginos, Konstantinos

2016-11-01

Computing disconnected diagrams in Lattice QCD (operator insertion in a quark loop) entails the computationally demanding problem of taking the trace of the all to all quark propagator. We first outline the basic algorithm used to compute a quark loop as well as improvements to this method. Then, we motivate and introduce an algorithm based on the synergy between hierarchical probing and singular value deflation. We present results for the chiral condensate using a 2+1-flavor clover ensemble and compare estimates of the nucleon charges with the basic algorithm.

Are mind wandering rates an artifact of the probe-caught method? Using self-caught mind wandering in the classroom to test, and reject, this possibility.

PubMed

Varao-Sousa, Trish L; Kingstone, Alan

2018-06-26

Mind wandering (MW) reports often rely on individuals responding to specific external thought probes. Researchers have used this probe-caught method almost exclusively, due to its reliability across a wide range of testing situations. However, it remains an open question whether the probe-caught MW rates in more complex settings converge with those for simpler tasks, because of the rather artificial and controlled nature of the probe-caught methodology itself, which is shared across the different settings. To address this issue, we measured MW in a real-world lecture, during which students indicated whether they were mind wandering by simply catching themselves (as one would normally do in real life) or by catching themselves and responding to thought probes. Across three separate lectures, self-caught MW reports were stable and unaffected by the inclusion of MW probes. That the probe rates were similar to those found in prior classroom research and did not affect the self-caught MW rates strongly suggests that the past consistency of probe-caught MW rates across a range of different settings is not an artifact of the thought-probe method. Our study also indicates that the self-caught MW methodology is a reliable way to acquire MW data. The extension of measurement techniques to include students' self-caught reports provides valuable information about how to successfully and naturalistically monitor MW in lecture settings, outside the laboratory.

[Research progress of probe design software of oligonucleotide microarrays].

PubMed

Chen, Xi; Wu, Zaoquan; Liu, Zhengchun

2014-02-01

DNA microarray has become an essential medical genetic diagnostic tool for its high-throughput, miniaturization and automation. The design and selection of oligonucleotide probes are critical for preparing gene chips with high quality. Several sets of probe design software have been developed and are available to perform this work now. Every set of the software aims to different target sequences and shows different advantages and limitations. In this article, the research and development of these sets of software are reviewed in line with three main criteria, including specificity, sensitivity and melting temperature (Tm). In addition, based on the experimental results from literatures, these sets of software are classified according to their applications. This review will be helpful for users to choose an appropriate probe-design software. It will also reduce the costs of microarrays, improve the application efficiency of microarrays, and promote both the research and development (R&D) and commercialization of high-performance probe design software.

Focusing attention on objects of interest using multiple matched filters.

PubMed

Stough, T M; Brodley, C E

2001-01-01

In order to be of use to scientists, large image databases need to be analyzed to create a catalog of the objects of interest. One approach is to apply a multiple tiered search algorithm that uses reduction techniques of increasing computational complexity to select the desired objects from the database. The first tier of this type of algorithm, often called a focus of attention (FOA) algorithm, selects candidate regions from the image data and passes them to the next tier of the algorithm. In this paper we present a new approach to FOA that employs multiple matched filters (MMF), one for each object prototype, to detect the regions of interest. The MMFs are formed using k-means clustering on a set of image patches identified by domain experts as positive examples of objects of interest. An innovation of the approach is to radically reduce the dimensionality of the feature space, used by the k-means algorithm, by taking block averages (spoiling) the sample image patches. The process of spoiling is analyzed and its applicability to other domains is discussed. The combination of the output of the MMFs is achieved through the projection of the detections back into an empty image and then thresholding. This research was motivated by the need to detect small volcanos in the Magellan probe data from Venus. An empirical evaluation of the approach illustrates that a combination of the MMF plus the average filter results in a higher likelihood of 100% detection of the objects of interest at a lower false positive rate than a single matched filter alone.

An Ultrasonographic Periodontal Probe

NASA Astrophysics Data System (ADS)

Bertoncini, C. A.; Hinders, M. K.

2010-02-01

Periodontal disease, commonly known as gum disease, affects millions of people. The current method of detecting periodontal pocket depth is painful, invasive, and inaccurate. As an alternative to manual probing, an ultrasonographic periodontal probe is being developed to use ultrasound echo waveforms to measure periodontal pocket depth, which is the main measure of periodontal disease. Wavelet transforms and pattern classification techniques are implemented in artificial intelligence routines that can automatically detect pocket depth. The main pattern classification technique used here, called a binary classification algorithm, compares test objects with only two possible pocket depth measurements at a time and relies on dimensionality reduction for the final determination. This method correctly identifies up to 90% of the ultrasonographic probe measurements within the manual probe's tolerance.

2nd International Planetary Probe Workshop

NASA Technical Reports Server (NTRS)

Venkatapathy, Ethiraj; Martinez, Ed; Arcadi, Marla

2005-01-01

Included are presentations from the 2nd International Planetary Probe Workshop. The purpose of the second workshop was to continue to unite the community of planetary scientists, spacecraft engineers and mission designers and planners; whose expertise, experience and interests are in the areas of entry probe trajectory and attitude determination, and the aerodynamics/aerothermodynamics of planetary entry vehicles. Mars lander missions and the first probe mission to Titan made 2004 an exciting year for planetary exploration. The Workshop addressed entry probe science, engineering challenges, mission design and instruments, along with the challenges of reconstruction of the entry, descent and landing or the aerocapture phases. Topics addressed included methods, technologies, and algorithms currently employed; techniques and results from the rich history of entry probe science such as PAET, Venera/Vega, Pioneer Venus, Viking, Galileo, Mars Pathfinder and Mars MER; upcoming missions such as the imminent entry of Huygens and future Mars entry probes; and new and novel instrumentation and methodologies.

Determining the distribution of probes between different subcellular locations through automated unmixing of subcellular patterns.

PubMed

Peng, Tao; Bonamy, Ghislain M C; Glory-Afshar, Estelle; Rines, Daniel R; Chanda, Sumit K; Murphy, Robert F

2010-02-16

Many proteins or other biological macromolecules are localized to more than one subcellular structure. The fraction of a protein in different cellular compartments is often measured by colocalization with organelle-specific fluorescent markers, requiring availability of fluorescent probes for each compartment and acquisition of images for each in conjunction with the macromolecule of interest. Alternatively, tailored algorithms allow finding particular regions in images and quantifying the amount of fluorescence they contain. Unfortunately, this approach requires extensive hand-tuning of algorithms and is often cell type-dependent. Here we describe a machine-learning approach for estimating the amount of fluorescent signal in different subcellular compartments without hand tuning, requiring only the acquisition of separate training images of markers for each compartment. In testing on images of cells stained with mixtures of probes for different organelles, we achieved a 93% correlation between estimated and expected amounts of probes in each compartment. We also demonstrated that the method can be used to quantify drug-dependent protein translocations. The method enables automated and unbiased determination of the distributions of protein across cellular compartments, and will significantly improve imaging-based high-throughput assays and facilitate proteome-scale localization efforts.

Lung vasculature imaging using speckle variance optical coherence tomography

NASA Astrophysics Data System (ADS)

Cua, Michelle; Lee, Anthony M. D.; Lane, Pierre M.; McWilliams, Annette; Shaipanich, Tawimas; MacAulay, Calum E.; Yang, Victor X. D.; Lam, Stephen

2012-02-01

Architectural changes in and remodeling of the bronchial and pulmonary vasculature are important pathways in diseases such as asthma, chronic obstructive pulmonary disease (COPD), and lung cancer. However, there is a lack of methods that can find and examine small bronchial vasculature in vivo. Structural lung airway imaging using optical coherence tomography (OCT) has previously been shown to be of great utility in examining bronchial lesions during lung cancer screening under the guidance of autofluorescence bronchoscopy. Using a fiber optic endoscopic OCT probe, we acquire OCT images from in vivo human subjects. The side-looking, circumferentially-scanning probe is inserted down the instrument channel of a standard bronchoscope and manually guided to the imaging location. Multiple images are collected with the probe spinning proximally at 100Hz. Due to friction, the distal end of the probe does not spin perfectly synchronous with the proximal end, resulting in non-uniform rotational distortion (NURD) of the images. First, we apply a correction algorithm to remove NURD. We then use a speckle variance algorithm to identify vasculature. The initial data show a vascaulture density in small human airways similar to what would be expected.

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

Pierre, John W.; Wies, Richard; Trudnowski, Daniel

Time-synchronized measurements provide rich information for estimating a power-system's electromechanical modal properties via advanced signal processing. This information is becoming critical for the improved operational reliability of interconnected grids. A given mode's properties are described by its frequency, damping, and shape. Modal frequencies and damping are useful indicators of power-system stress, usually declining with increased load or reduced grid capacity. Mode shape provides critical information for operational control actions. This project investigated many advanced techniques for power system identification from measured data focusing on mode frequency and damping ratio estimation. Investigators from the three universities coordinated their effort with Pacificmore » Northwest National Laboratory (PNNL). Significant progress was made on developing appropriate techniques for system identification with confidence intervals and testing those techniques on field measured data and through simulation. Experimental data from the western area power system was provided by PNNL and Bonneville Power Administration (BPA) for both ambient conditions and for signal injection tests. Three large-scale tests were conducted for the western area in 2005 and 2006. Measured field PMU (Phasor Measurement Unit) data was provided to the three universities. A 19-machine simulation model was enhanced for testing the system identification algorithms. Extensive simulations were run with this model to test the performance of the algorithms. University of Wyoming researchers participated in four primary activities: (1) Block and adaptive processing techniques for mode estimation from ambient signals and probing signals, (2) confidence interval estimation, (3) probing signal design and injection method analysis, and (4) performance assessment and validation from simulated and field measured data. Subspace based methods have been use to improve previous results from block processing techniques. Bootstrap techniques have been developed to estimate confidence intervals for the electromechanical modes from field measured data. Results were obtained using injected signal data provided by BPA. A new probing signal was designed that puts more strength into the signal for a given maximum peak to peak swing. Further simulations were conducted on a model based on measured data and with the modifications of the 19-machine simulation model. Montana Tech researchers participated in two primary activities: (1) continued development of the 19-machine simulation test system to include a DC line; and (2) extensive simulation analysis of the various system identification algorithms and bootstrap techniques using the 19 machine model. Researchers at the University of Alaska-Fairbanks focused on the development and testing of adaptive filter algorithms for mode estimation using data generated from simulation models and on data provided in collaboration with BPA and PNNL. There efforts consist of pre-processing field data, testing and refining adaptive filter techniques (specifically the Least Mean Squares (LMS), the Adaptive Step-size LMS (ASLMS), and Error Tracking (ET) algorithms). They also improved convergence of the adaptive algorithms by using an initial estimate from block processing AR method to initialize the weight vector for LMS. Extensive testing was performed on simulated data from the 19 machine model. This project was also extensively involved in the WECC (Western Electricity Coordinating Council) system wide tests carried out in 2005 and 2006. These tests involved injecting known probing signals into the western power grid. One of the primary goals of these tests was the reliable estimation of electromechanical mode properties from measured PMU data. Applied to the system were three types of probing inputs: (1) activation of the Chief Joseph Dynamic Brake, (2) mid-level probing at the Pacific DC Intertie (PDCI), and (3) low-level probing on the PDCI. The Chief Joseph Dynamic Brake is a 1400 MW disturbance to the system and is injected for a half of a second. For the mid and low-level probing, the Celilo terminal of the PDCI is modulated with a known probing signal. Similar but less extensive tests were conducted in June of 2000. The low-level probing signals were designed at the University of Wyoming. A number of important design factors are considered. The designed low-level probing signal used in the tests is a multi-sine signal. Its frequency content is focused in the range of the inter-area electromechanical modes. The most frequently used of these low-level multi-sine signals had a period of over two minutes, a root-mean-square (rms) value of 14 MW, and a peak magnitude of 20 MW. Up to 15 cycles of this probing signal were injected into the system resulting in a processing gain of 15. The resulting measured response at points throughout the system was not much larger than the ambient noise present in the measurements.« less

Data-directed RNA secondary structure prediction using probabilistic modeling

PubMed Central

Deng, Fei; Ledda, Mirko; Vaziri, Sana; Aviran, Sharon

2016-01-01

Structure dictates the function of many RNAs, but secondary RNA structure analysis is either labor intensive and costly or relies on computational predictions that are often inaccurate. These limitations are alleviated by integration of structure probing data into prediction algorithms. However, existing algorithms are optimized for a specific type of probing data. Recently, new chemistries combined with advances in sequencing have facilitated structure probing at unprecedented scale and sensitivity. These novel technologies and anticipated wealth of data highlight a need for algorithms that readily accommodate more complex and diverse input sources. We implemented and investigated a recently outlined probabilistic framework for RNA secondary structure prediction and extended it to accommodate further refinement of structural information. This framework utilizes direct likelihood-based calculations of pseudo-energy terms per considered structural context and can readily accommodate diverse data types and complex data dependencies. We use real data in conjunction with simulations to evaluate performances of several implementations and to show that proper integration of structural contexts can lead to improvements. Our tests also reveal discrepancies between real data and simulations, which we show can be alleviated by refined modeling. We then propose statistical preprocessing approaches to standardize data interpretation and integration into such a generic framework. We further systematically quantify the information content of data subsets, demonstrating that high reactivities are major drivers of SHAPE-directed predictions and that better understanding of less informative reactivities is key to further improvements. Finally, we provide evidence for the adaptive capability of our framework using mock probe simulations. PMID:27251549

Comparative study of classification algorithms for immunosignaturing data

PubMed Central

2012-01-01

Background High-throughput technologies such as DNA, RNA, protein, antibody and peptide microarrays are often used to examine differences across drug treatments, diseases, transgenic animals, and others. Typically one trains a classification system by gathering large amounts of probe-level data, selecting informative features, and classifies test samples using a small number of features. As new microarrays are invented, classification systems that worked well for other array types may not be ideal. Expression microarrays, arguably one of the most prevalent array types, have been used for years to help develop classification algorithms. Many biological assumptions are built into classifiers that were designed for these types of data. One of the more problematic is the assumption of independence, both at the probe level and again at the biological level. Probes for RNA transcripts are designed to bind single transcripts. At the biological level, many genes have dependencies across transcriptional pathways where co-regulation of transcriptional units may make many genes appear as being completely dependent. Thus, algorithms that perform well for gene expression data may not be suitable when other technologies with different binding characteristics exist. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides. It relies on many-to-many binding of antibodies to the random sequence peptides. Each peptide can bind multiple antibodies and each antibody can bind multiple peptides. This technology has been shown to be highly reproducible and appears promising for diagnosing a variety of disease states. However, it is not clear what is the optimal classification algorithm for analyzing this new type of data. Results We characterized several classification algorithms to analyze immunosignaturing data. We selected several datasets that range from easy to difficult to classify, from simple monoclonal binding to complex binding patterns in asthma patients. We then classified the biological samples using 17 different classification algorithms. Using a wide variety of assessment criteria, we found ‘Naïve Bayes’ far more useful than other widely used methods due to its simplicity, robustness, speed and accuracy. Conclusions ‘Naïve Bayes’ algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties. PMID:22720696

Evaluation of ultrasonic array imaging algorithms for inspection of a coarse grained material

NASA Astrophysics Data System (ADS)

Van Pamel, A.; Lowe, M. J. S.; Brett, C. R.

2014-02-01

Improving the ultrasound inspection capability for coarse grain metals remains of longstanding interest to industry and the NDE research community and is expected to become increasingly important for next generation power plants. A test sample of coarse grained Inconel 625 which is representative of future power plant components has been manufactured to test the detectability of different inspection techniques. Conventional ultrasonic A, B, and C-scans showed the sample to be extraordinarily difficult to inspect due to its scattering behaviour. However, in recent years, array probes and Full Matrix Capture (FMC) imaging algorithms, which extract the maximum amount of information possible, have unlocked exciting possibilities for improvements. This article proposes a robust methodology to evaluate the detection performance of imaging algorithms, applying this to three FMC imaging algorithms; Total Focusing Method (TFM), Phase Coherent Imaging (PCI), and Decomposition of the Time Reversal Operator with Multiple Scattering (DORT MSF). The methodology considers the statistics of detection, presenting the detection performance as Probability of Detection (POD) and probability of False Alarm (PFA). The data is captured in pulse-echo mode using 64 element array probes at centre frequencies of 1MHz and 5MHz. All three algorithms are shown to perform very similarly when comparing their flaw detection capabilities on this particular case.

An exemplar-familiarity model predicts short-term and long-term probe recognition across diverse forms of memory search.

PubMed

Nosofsky, Robert M; Cox, Gregory E; Cao, Rui; Shiffrin, Richard M

2014-11-01

Experiments were conducted to test a modern exemplar-familiarity model on its ability to account for both short-term and long-term probe recognition within the same memory-search paradigm. Also, making connections to the literature on attention and visual search, the model was used to interpret differences in probe-recognition performance across diverse conditions that manipulated relations between targets and foils across trials. Subjects saw lists of from 1 to 16 items followed by a single item recognition probe. In a varied-mapping condition, targets and foils could switch roles across trials; in a consistent-mapping condition, targets and foils never switched roles; and in an all-new condition, on each trial a completely new set of items formed the memory set. In the varied-mapping and all-new conditions, mean correct response times (RTs) and error proportions were curvilinear increasing functions of memory set size, with the RT results closely resembling ones from hybrid visual-memory search experiments reported by Wolfe (2012). In the consistent-mapping condition, new-probe RTs were invariant with set size, whereas old-probe RTs increased slightly with increasing study-test lag. With appropriate choice of psychologically interpretable free parameters, the model accounted well for the complete set of results. The work provides support for the hypothesis that a common set of processes involving exemplar-based familiarity may govern long-term and short-term probe recognition across wide varieties of memory- search conditions. PsycINFO Database Record (c) 2014 APA, all rights reserved.

An Efficient Distributed Compressed Sensing Algorithm for Decentralized Sensor Network.

PubMed

Liu, Jing; Huang, Kaiyu; Zhang, Guoxian

2017-04-20

We consider the joint sparsity Model 1 (JSM-1) in a decentralized scenario, where a number of sensors are connected through a network and there is no fusion center. A novel algorithm, named distributed compact sensing matrix pursuit (DCSMP), is proposed to exploit the computational and communication capabilities of the sensor nodes. In contrast to the conventional distributed compressed sensing algorithms adopting a random sensing matrix, the proposed algorithm focuses on the deterministic sensing matrices built directly on the real acquisition systems. The proposed DCSMP algorithm can be divided into two independent parts, the common and innovation support set estimation processes. The goal of the common support set estimation process is to obtain an estimated common support set by fusing the candidate support set information from an individual node and its neighboring nodes. In the following innovation support set estimation process, the measurement vector is projected into a subspace that is perpendicular to the subspace spanned by the columns indexed by the estimated common support set, to remove the impact of the estimated common support set. We can then search the innovation support set using an orthogonal matching pursuit (OMP) algorithm based on the projected measurement vector and projected sensing matrix. In the proposed DCSMP algorithm, the process of estimating the common component/support set is decoupled with that of estimating the innovation component/support set. Thus, the inaccurately estimated common support set will have no impact on estimating the innovation support set. It is proven that under the condition the estimated common support set contains the true common support set, the proposed algorithm can find the true innovation set correctly. Moreover, since the innovation support set estimation process is independent of the common support set estimation process, there is no requirement for the cardinality of both sets; thus, the proposed DCSMP algorithm is capable of tackling the unknown sparsity problem successfully.

Correcting nonlinear drift distortion of scanning probe and scanning transmission electron microscopies from image pairs with orthogonal scan directions

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

Ophus, Colin; Ciston, Jim; Nelson, Chris T.

Unwanted motion of the probe with respect to the sample is a ubiquitous problem in scanning probe and scanning transmission electron microscopies, causing both linear and nonlinear artifacts in experimental images. We have designed a procedure to correct these artifacts by using orthogonal scan pairs to align each measurement line-by-line along the slow scan direction, by fitting contrast variation along the lines. We demonstrate the accuracy of our algorithm on both synthetic and experimental data and provide an implementation of our method.

Correcting nonlinear drift distortion of scanning probe and scanning transmission electron microscopies from image pairs with orthogonal scan directions

DOE PAGES

Ophus, Colin; Ciston, Jim; Nelson, Chris T.

2015-12-10

Unwanted motion of the probe with respect to the sample is a ubiquitous problem in scanning probe and scanning transmission electron microscopies, causing both linear and nonlinear artifacts in experimental images. We have designed a procedure to correct these artifacts by using orthogonal scan pairs to align each measurement line-by-line along the slow scan direction, by fitting contrast variation along the lines. We demonstrate the accuracy of our algorithm on both synthetic and experimental data and provide an implementation of our method.

miBLAST: scalable evaluation of a batch of nucleotide sequence queries with BLAST

PubMed Central

Kim, You Jung; Boyd, Andrew; Athey, Brian D.; Patel, Jignesh M.

2005-01-01

A common task in many modern bioinformatics applications is to match a set of nucleotide query sequences against a large sequence dataset. Exis-ting tools, such as BLAST, are designed to evaluate a single query at a time and can be unacceptably slow when the number of sequences in the query set is large. In this paper, we present a new algorithm, called miBLAST, that evaluates such batch workloads efficiently. At the core, miBLAST employs a q-gram filtering and an index join for efficiently detecting similarity between the query sequences and database sequences. This set-oriented technique, which indexes both the query and the database sets, results in substantial performance improvements over existing methods. Our results show that miBLAST is significantly faster than BLAST in many cases. For example, miBLAST aligned 247 965 oligonucleotide sequences in the Affymetrix probe set against the Human UniGene in 1.26 days, compared with 27.27 days with BLAST (an improvement by a factor of 22). The relative performance of miBLAST increases for larger word sizes; however, it decreases for longer queries. miBLAST employs the familiar BLAST statistical model and output format, guaranteeing the same accuracy as BLAST and facilitating a seamless transition for existing BLAST users. PMID:16061938

Structure and atomic correlations in molecular systems probed by XAS reverse Monte Carlo refinement

NASA Astrophysics Data System (ADS)

Di Cicco, Andrea; Iesari, Fabio; Trapananti, Angela; D'Angelo, Paola; Filipponi, Adriano

2018-03-01

The Reverse Monte Carlo (RMC) algorithm for structure refinement has been applied to x-ray absorption spectroscopy (XAS) multiple-edge data sets for six gas phase molecular systems (SnI2, CdI2, BBr3, GaI3, GeBr4, GeI4). Sets of thousands of molecular replicas were involved in the refinement process, driven by the XAS data and constrained by available electron diffraction results. The equilibrated configurations were analysed to determine the average tridimensional structure and obtain reliable bond and bond-angle distributions. Detectable deviations from Gaussian models were found in some cases. This work shows that a RMC refinement of XAS data is able to provide geometrical models for molecular structures compatible with present experimental evidence. The validation of this approach on simple molecular systems is particularly important in view of its possible simple extension to more complex and extended systems including metal-organic complexes, biomolecules, or nanocrystalline systems.

Can we match ultraviolet face images against their visible counterparts?

NASA Astrophysics Data System (ADS)

Narang, Neeru; Bourlai, Thirimachos; Hornak, Lawrence A.

2015-05-01

In law enforcement and security applications, the acquisition of face images is critical in producing key trace evidence for the successful identification of potential threats. However, face recognition (FR) for face images captured using different camera sensors, and under variable illumination conditions, and expressions is very challenging. In this paper, we investigate the advantages and limitations of the heterogeneous problem of matching ultra violet (from 100 nm to 400 nm in wavelength) or UV, face images against their visible (VIS) counterparts, when all face images are captured under controlled conditions. The contributions of our work are three-fold; (i) We used a camera sensor designed with the capability to acquire UV images at short-ranges, and generated a dual-band (VIS and UV) database that is composed of multiple, full frontal, face images of 50 subjects. Two sessions were collected that span over the period of 2 months. (ii) For each dataset, we determined which set of face image pre-processing algorithms are more suitable for face matching, and, finally, (iii) we determined which FR algorithm better matches cross-band face images, resulting in high rank-1 identification rates. Experimental results show that our cross spectral matching (the heterogeneous problem, where gallery and probe sets consist of face images acquired in different spectral bands) algorithms achieve sufficient identification performance. However, we also conclude that the problem under study, is very challenging, and it requires further investigation to address real-world law enforcement or military applications. To the best of our knowledge, this is first time in the open literature the problem of cross-spectral matching of UV against VIS band face images is being investigated.

Categorization of hyperspectral information (HSI) based on the distribution of spectra in hyperspace

NASA Astrophysics Data System (ADS)

Resmini, Ronald G.

2003-09-01

Hyperspectral information (HSI) data are commonly categorized by a description of the dominant physical geographic background captured in the image cube. In other words, HSI categorization is commonly based on a cursory, visual assessment of whether the data are of desert, forest, urban, littoral, jungle, alpine, etc., terrains. Additionally, often the design of HSI collection experiments is based on the acquisition of data of the various backgrounds or of objects of interest within the various terrain types. These data are for assessing and quantifying algorithm performance as well as for algorithm development activities. Here, results of an investigation into the validity of the backgrounds-driven mode of characterizing the diversity of hyperspectral data are presented. HSI data are described quantitatively, in the space where most algorithms operate: n-dimensional (n-D) hyperspace, where n is the number of bands in an HSI data cube. Nineteen metrics designed to probe hyperspace are applied to 14 HYDICE HSI data cubes that represent nine different backgrounds. Each of the 14 sets (one for each HYDICE cube) of 19 metric values was analyzed for clustering. With the present set of data and metrics, there is no clear, unambiguous break-out of metrics based on the nine different geographic backgrounds. The break-outs clump seemingly unrelated data types together; e.g., littoral and urban/residential. Most metrics are normally distributed and indicate no clustering; one metric is one outlier away from normal (i.e., two clusters); and five are comprised of two distributions (i.e., two clusters). Overall, there are three different break-outs that do not correspond to conventional background categories. Implications of these preliminary results are discussed as are recommendations for future work.

Comparison of Cloud and Aerosol Detection between CERES Edition 3 Cloud Mask and CALIPSO Version 2 Data Products

NASA Astrophysics Data System (ADS)

Trepte, Qing; Minnis, Patrick; Sun-Mack, Sunny; Trepte, Charles

Clouds and aerosol play important roles in the global climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a crucial first step in determining their influence on surface and top-of-atmosphere radiative fluxes. This paper presents a comparison analysis of a new version of the Clouds and Earth's Radiant Energy System (CERES) Edition 3 cloud detection algorithms using Aqua MODIS data with the recently released Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Version 2 Vertical Feature Mask (VFM). Improvements in CERES Edition 3 cloud mask include dust detection, thin cirrus tests, enhanced low cloud detection at night, and a smoother transition from mid-latitude to polar regions. For the CALIPSO Version 2 data set, changes to the lidar calibration can result in significant improvements to its identification of optically thick aerosol layers. The Aqua and CALIPSO satellites, part of the A-train satellite constellation, provide a unique opportunity for validating passive sensor cloud and aerosol detection using an active sensor. In this paper, individual comparison cases will be discussed for different types of clouds and aerosols over various surfaces, for daytime and nighttime conditions, and for regions ranging from the tropics to the poles. Examples will include an assessment of the CERES detection algorithm for optically thin cirrus, marine stratus, and polar night clouds as well as its ability to characterize Saharan dust plumes off the African coast. With the CALIPSO lidar's unique ability to probe the vertical structure of clouds and aerosol layers, it provides an excellent validation data set for cloud detection algorithms, especially for polar nighttime clouds.

3D-calibration of three- and four-sensor hot-film probes based on collocated sonic using neural networks

NASA Astrophysics Data System (ADS)

Kit, Eliezer; Liberzon, Dan

2016-09-01

High resolution measurements of turbulence in the atmospheric boundary layer (ABL) are critical to the understanding of physical processes and parameterization of important quantities, such as the turbulent kinetic energy dissipation. Low spatio-temporal resolution of standard atmospheric instruments, sonic anemometers and LIDARs, limits their suitability for fine-scale measurements of ABL. The use of miniature hot-films is an alternative technique, although such probes require frequent calibration, which is logistically untenable in field setups. Accurate and truthful calibration is crucial for the multi-hot-films applications in atmospheric studies, because the ability to conduct calibration in situ ultimately determines the turbulence measurements quality. Kit et al (2010 J. Atmos. Ocean. Technol. 27 23-41) described a novel methodology for calibration of hot-film probes using a collocated sonic anemometer combined with a neural network (NN) approach. An important step in the algorithm is the generation of a calibration set for NN training by an appropriate low-pass filtering of the high resolution voltages, measured by the hot-film-sensors and low resolution velocities acquired by the sonic. In Kit et al (2010 J. Atmos. Ocean. Technol. 27 23-41), Kit and Grits (2011 J. Atmos. Ocean. Technol. 28 104-10) and Vitkin et al (2014 Meas. Sci. Technol. 25 75801), the authors reported on successful use of this approach for in situ calibration, but also on the method’s limitations and restricted range of applicability. In their earlier work, a jet facility and a probe, comprised of two orthogonal x-hot-films, were used for calibration and for full dataset generation. In the current work, a comprehensive laboratory study of 3D-calibration of two multi-hot-film probes (triple- and four-sensor) using a grid flow was conducted. The probes were embedded in a collocated sonic, and their relative pitch and yaw orientation to the mean flow was changed by means of motorized traverses. The study demonstrated that NN-calibration is a powerful tool for calibration of multi-sensor 3D-hot film probes embedded in a collocated sonic, and can be employed in long-lasting field campaigns.

Efficient feature-based 2D/3D registration of transesophageal echocardiography to x-ray fluoroscopy for cardiac interventions

NASA Astrophysics Data System (ADS)

Hatt, Charles R.; Speidel, Michael A.; Raval, Amish N.

2014-03-01

We present a novel 2D/ 3D registration algorithm for fusion between transesophageal echocardiography (TEE) and X-ray fluoroscopy (XRF). The TEE probe is modeled as a subset of 3D gradient and intensity point features, which facilitates efficient 3D-to-2D perspective projection. A novel cost-function, based on a combination of intensity and edge features, evaluates the registration cost value without the need for time-consuming generation of digitally reconstructed radiographs (DRRs). Validation experiments were performed with simulations and phantom data. For simulations, in silica XRF images of a TEE probe were generated in a number of different pose configurations using a previously acquired CT image. Random misregistrations were applied and our method was used to recover the TEE probe pose and compare the result to the ground truth. Phantom experiments were performed by attaching fiducial markers externally to a TEE probe, imaging the probe with an interventional cardiac angiographic x-ray system, and comparing the pose estimated from the external markers to that estimated from the TEE probe using our algorithm. Simulations found a 3D target registration error of 1.08(1.92) mm for biplane (monoplane) geometries, while the phantom experiment found a 2D target registration error of 0.69mm. For phantom experiments, we demonstrated a monoplane tracking frame-rate of 1.38 fps. The proposed feature-based registration method is computationally efficient, resulting in near real-time, accurate image based registration between TEE and XRF.

Dual representation of item positions in verbal short-term memory: Evidence for two access modes.

PubMed

Lange, Elke B; Verhaeghen, Paul; Cerella, John

Memory sets of N = 1~5 digits were exposed sequentially from left-to-right across the screen, followed by N recognition probes. Probes had to be compared to memory list items on identity only (Sternberg task) or conditional on list position. Positions were probed randomly or in left-to-right order. Search functions related probe response times to set size. Random probing led to ramped, "Sternbergian" functions whose intercepts were elevated by the location requirement. Sequential probing led to flat search functions-fast responses unaffected by set size. These results suggested that items in STM could be accessed either by a slow search-on-identity followed by recovery of an associated location tag, or in a single step by following item-to-item links in study order. It is argued that this dual coding of location information occurs spontaneously at study, and that either code can be utilised at retrieval depending on test demands.

An Optimized Set of Fluorescence In Situ Hybridization Probes for Detection of Pancreatobiliary Tract Cancer in Cytology Brush Samples.

PubMed

Barr Fritcher, Emily G; Voss, Jesse S; Brankley, Shannon M; Campion, Michael B; Jenkins, Sarah M; Keeney, Matthew E; Henry, Michael R; Kerr, Sarah M; Chaiteerakij, Roongruedee; Pestova, Ekaterina V; Clayton, Amy C; Zhang, Jun; Roberts, Lewis R; Gores, Gregory J; Halling, Kevin C; Kipp, Benjamin R

2015-12-01

Pancreatobiliary cancer is detected by fluorescence in situ hybridization (FISH) of pancreatobiliary brush samples with UroVysion probes, originally designed to detect bladder cancer. We designed a set of new probes to detect pancreatobiliary cancer and compared its performance with that of UroVysion and routine cytology analysis. We tested a set of FISH probes on tumor tissues (cholangiocarcinoma or pancreatic carcinoma) and non-tumor tissues from 29 patients. We identified 4 probes that had high specificity for tumor vs non-tumor tissues; we called this set of probes pancreatobiliary FISH. We performed a retrospective analysis of brush samples from 272 patients who underwent endoscopic retrograde cholangiopancreatography for evaluation of malignancy at the Mayo Clinic; results were available from routine cytology and FISH with UroVysion probes. Archived residual specimens were retrieved and used to evaluate the pancreatobiliary FISH probes. Cutoff values for FISH with the pancreatobiliary probes were determined using 89 samples and validated in the remaining 183 samples. Clinical and pathologic evidence of malignancy in the pancreatobiliary tract within 2 years of brush sample collection was used as the standard; samples from patients without malignancies were used as negative controls. The validation cohort included 85 patients with malignancies (46.4%) and 114 patients with primary sclerosing cholangitis (62.3%). Samples containing cells above the cutoff for polysomy (copy number gain of ≥2 probes) were classified as positive in FISH with the UroVysion and pancreatobiliary probes. Multivariable logistic regression was used to estimate associations between clinical and pathology findings and results from FISH. The combination of FISH probes 1q21, 7p12, 8q24, and 9p21 identified cancer cells with 93% sensitivity and 100% specificity in pancreatobiliary tissue samples and were therefore included in the pancreatobiliary probe set. In the validation cohort of brush samples, pancreatobiliary FISH identified samples from patients with malignancy with a significantly higher level of sensitivity (64.7%) than the UroVysion probes (45.9%) (P < .001) or routine cytology analysis (18.8%) (P < .001), but similar specificity (92.9%, 90.8%, and 100.0% respectively). Factors significantly associated with detection of carcinoma, in adjusted analyses, included detection of polysomy by pancreatobiliary FISH (P < .001), a mass by cross-sectional imaging (P < .001), cancer cells by routine cytology (overall P = .003), as well as absence of primary sclerosing cholangitis (P = .011). We identified a set of FISH probes that detects cancer cells in pancreatobiliary brush samples from patients with and without primary sclerosing cholangitis with higher levels of sensitivity than UroVysion probes. Cytologic brushing test results and clinical features were independently associated with detection of cancer and might be used to identify patients with pancreatobiliary cancers. Copyright © 2015 AGA Institute. Published by Elsevier Inc. All rights reserved.

Comprehensive performance comparison of high-resolution array platforms for genome-wide Copy Number Variation (CNV) analysis in humans.

PubMed

Haraksingh, Rajini R; Abyzov, Alexej; Urban, Alexander Eckehart

2017-04-24

High-resolution microarray technology is routinely used in basic research and clinical practice to efficiently detect copy number variants (CNVs) across the entire human genome. A new generation of arrays combining high probe densities with optimized designs will comprise essential tools for genome analysis in the coming years. We systematically compared the genome-wide CNV detection power of all 17 available array designs from the Affymetrix, Agilent, and Illumina platforms by hybridizing the well-characterized genome of 1000 Genomes Project subject NA12878 to all arrays, and performing data analysis using both manufacturer-recommended and platform-independent software. We benchmarked the resulting CNV call sets from each array using a gold standard set of CNVs for this genome derived from 1000 Genomes Project whole genome sequencing data. The arrays tested comprise both SNP and aCGH platforms with varying designs and contain between ~0.5 to ~4.6 million probes. Across the arrays CNV detection varied widely in number of CNV calls (4-489), CNV size range (~40 bp to ~8 Mbp), and percentage of non-validated CNVs (0-86%). We discovered strikingly strong effects of specific array design principles on performance. For example, some SNP array designs with the largest numbers of probes and extensive exonic coverage produced a considerable number of CNV calls that could not be validated, compared to designs with probe numbers that are sometimes an order of magnitude smaller. This effect was only partially ameliorated using different analysis software and optimizing data analysis parameters. High-resolution microarrays will continue to be used as reliable, cost- and time-efficient tools for CNV analysis. However, different applications tolerate different limitations in CNV detection. Our study quantified how these arrays differ in total number and size range of detected CNVs as well as sensitivity, and determined how each array balances these attributes. This analysis will inform appropriate array selection for future CNV studies, and allow better assessment of the CNV-analytical power of both published and ongoing array-based genomics studies. Furthermore, our findings emphasize the importance of concurrent use of multiple analysis algorithms and independent experimental validation in array-based CNV detection studies.

A methodology for evaluating detection performance of ultrasonic array imaging algorithms for coarse-grained materials.

PubMed

Van Pamel, Anton; Brett, Colin R; Lowe, Michael J S

2014-12-01

Improving the ultrasound inspection capability for coarse-grained metals remains of longstanding interest and is expected to become increasingly important for next-generation electricity power plants. Conventional ultrasonic A-, B-, and C-scans have been found to suffer from strong background noise caused by grain scattering, which can severely limit the detection of defects. However, in recent years, array probes and full matrix capture (FMC) imaging algorithms have unlocked exciting possibilities for improvements. To improve and compare these algorithms, we must rely on robust methodologies to quantify their performance. This article proposes such a methodology to evaluate the detection performance of imaging algorithms. For illustration, the methodology is applied to some example data using three FMC imaging algorithms; total focusing method (TFM), phase-coherent imaging (PCI), and decomposition of the time-reversal operator with multiple scattering filter (DORT MSF). However, it is important to note that this is solely to illustrate the methodology; this article does not attempt the broader investigation of different cases that would be needed to compare the performance of these algorithms in general. The methodology considers the statistics of detection, presenting the detection performance as probability of detection (POD) and probability of false alarm (PFA). A test sample of coarse-grained nickel super alloy, manufactured to represent materials used for future power plant components and containing some simple artificial defects, is used to illustrate the method on the candidate algorithms. The data are captured in pulse-echo mode using 64-element array probes at center frequencies of 1 and 5 MHz. In this particular case, it turns out that all three algorithms are shown to perform very similarly when comparing their flaw detection capabilities.

Upgrading short-read animal genome assemblies to chromosome level using comparative genomics and a universal probe set.

PubMed

Damas, Joana; O'Connor, Rebecca; Farré, Marta; Lenis, Vasileios Panagiotis E; Martell, Henry J; Mandawala, Anjali; Fowler, Katie; Joseph, Sunitha; Swain, Martin T; Griffin, Darren K; Larkin, Denis M

2017-05-01

Most recent initiatives to sequence and assemble new species' genomes de novo fail to achieve the ultimate endpoint to produce contigs, each representing one whole chromosome. Even the best-assembled genomes (using contemporary technologies) consist of subchromosomal-sized scaffolds. To circumvent this problem, we developed a novel approach that combines computational algorithms to merge scaffolds into chromosomal fragments, PCR-based scaffold verification, and physical mapping to chromosomes. Multigenome-alignment-guided probe selection led to the development of a set of universal avian BAC clones that permit rapid anchoring of multiple scaffolds to chromosomes on all avian genomes. As proof of principle, we assembled genomes of the pigeon ( Columbia livia ) and peregrine falcon ( Falco peregrinus ) to chromosome levels comparable, in continuity, to avian reference genomes. Both species are of interest for breeding, cultural, food, and/or environmental reasons. Pigeon has a typical avian karyotype (2n = 80), while falcon (2n = 50) is highly rearranged compared to the avian ancestor. By using chromosome breakpoint data, we established that avian interchromosomal breakpoints appear in the regions of low density of conserved noncoding elements (CNEs) and that the chromosomal fission sites are further limited to long CNE "deserts." This corresponds with fission being the rarest type of rearrangement in avian genome evolution. High-throughput multiple hybridization and rapid capture strategies using the current BAC set provide the basis for assembling numerous avian (and possibly other reptilian) species, while the overall strategy for scaffold assembly and mapping provides the basis for an approach that (provided metaphases can be generated) could be applied to any animal genome. © 2017 Damas et al.; Published by Cold Spring Harbor Laboratory Press.

Upgrading short-read animal genome assemblies to chromosome level using comparative genomics and a universal probe set

PubMed Central

O'Connor, Rebecca; Lenis, Vasileios Panagiotis E.; Martell, Henry J.; Mandawala, Anjali; Fowler, Katie; Joseph, Sunitha; Swain, Martin T.; Griffin, Darren K.; Larkin, Denis M.

2017-01-01

Most recent initiatives to sequence and assemble new species’ genomes de novo fail to achieve the ultimate endpoint to produce contigs, each representing one whole chromosome. Even the best-assembled genomes (using contemporary technologies) consist of subchromosomal-sized scaffolds. To circumvent this problem, we developed a novel approach that combines computational algorithms to merge scaffolds into chromosomal fragments, PCR-based scaffold verification, and physical mapping to chromosomes. Multigenome-alignment-guided probe selection led to the development of a set of universal avian BAC clones that permit rapid anchoring of multiple scaffolds to chromosomes on all avian genomes. As proof of principle, we assembled genomes of the pigeon (Columbia livia) and peregrine falcon (Falco peregrinus) to chromosome levels comparable, in continuity, to avian reference genomes. Both species are of interest for breeding, cultural, food, and/or environmental reasons. Pigeon has a typical avian karyotype (2n = 80), while falcon (2n = 50) is highly rearranged compared to the avian ancestor. By using chromosome breakpoint data, we established that avian interchromosomal breakpoints appear in the regions of low density of conserved noncoding elements (CNEs) and that the chromosomal fission sites are further limited to long CNE “deserts.” This corresponds with fission being the rarest type of rearrangement in avian genome evolution. High-throughput multiple hybridization and rapid capture strategies using the current BAC set provide the basis for assembling numerous avian (and possibly other reptilian) species, while the overall strategy for scaffold assembly and mapping provides the basis for an approach that (provided metaphases can be generated) could be applied to any animal genome. PMID:27903645

Evaluation of the novel algorithm of flexible ligand docking with moveable target-protein atoms.

PubMed

Sulimov, Alexey V; Zheltkov, Dmitry A; Oferkin, Igor V; Kutov, Danil C; Katkova, Ekaterina V; Tyrtyshnikov, Eugene E; Sulimov, Vladimir B

2017-01-01

We present the novel docking algorithm based on the Tensor Train decomposition and the TT-Cross global optimization. The algorithm is applied to the docking problem with flexible ligand and moveable protein atoms. The energy of the protein-ligand complex is calculated in the frame of the MMFF94 force field in vacuum. The grid of precalculated energy potentials of probe ligand atoms in the field of the target protein atoms is not used. The energy of the protein-ligand complex for any given configuration is computed directly with the MMFF94 force field without any fitting parameters. The conformation space of the system coordinates is formed by translations and rotations of the ligand as a whole, by the ligand torsions and also by Cartesian coordinates of the selected target protein atoms. Mobility of protein and ligand atoms is taken into account in the docking process simultaneously and equally. The algorithm is realized in the novel parallel docking SOL-P program and results of its performance for a set of 30 protein-ligand complexes are presented. Dependence of the docking positioning accuracy is investigated as a function of parameters of the docking algorithm and the number of protein moveable atoms. It is shown that mobility of the protein atoms improves docking positioning accuracy. The SOL-P program is able to perform docking of a flexible ligand into the active site of the target protein with several dozens of protein moveable atoms: the native crystallized ligand pose is correctly found as the global energy minimum in the search space with 157 dimensions using 4700 CPU ∗ h at the Lomonosov supercomputer.

NADH-fluorescence scattering correction for absolute concentration determination in a liquid tissue phantom using a novel multispectral magnetic-resonance-imaging-compatible needle probe

NASA Astrophysics Data System (ADS)

Braun, Frank; Schalk, Robert; Heintz, Annabell; Feike, Patrick; Firmowski, Sebastian; Beuermann, Thomas; Methner, Frank-Jürgen; Kränzlin, Bettina; Gretz, Norbert; Rädle, Matthias

2017-07-01

In this report, a quantitative nicotinamide adenine dinucleotide hydrate (NADH) fluorescence measurement algorithm in a liquid tissue phantom using a fiber-optic needle probe is presented. To determine the absolute concentrations of NADH in this phantom, the fluorescence emission spectra at 465 nm were corrected using diffuse reflectance spectroscopy between 600 nm and 940 nm. The patented autoclavable Nitinol needle probe enables the acquisition of multispectral backscattering measurements of ultraviolet, visible, near-infrared and fluorescence spectra. As a phantom, a suspension of calcium carbonate (Calcilit) and water with physiological NADH concentrations between 0 mmol l-1 and 2.0 mmol l-1 were used to mimic human tissue. The light scattering characteristics were adjusted to match the backscattering attributes of human skin by modifying the concentration of Calcilit. To correct the scattering effects caused by the matrices of the samples, an algorithm based on the backscattered remission spectrum was employed to compensate the influence of multiscattering on the optical pathway through the dispersed phase. The monitored backscattered visible light was used to correct the fluorescence spectra and thereby to determine the true NADH concentrations at unknown Calcilit concentrations. Despite the simplicity of the presented algorithm, the root-mean-square error of prediction (RMSEP) was 0.093 mmol l-1.

Toward real-time quantification of fluorescence molecular probes using target/background ratio for guiding biopsy and endoscopic therapy of esophageal neoplasia.

PubMed

Jiang, Yang; Gong, Yuanzheng; Rubenstein, Joel H; Wang, Thomas D; Seibel, Eric J

2017-04-01

Multimodal endoscopy using fluorescence molecular probes is a promising method of surveying the entire esophagus to detect cancer progression. Using the fluorescence ratio of a target compared to a surrounding background, a quantitative value is diagnostic for progression from Barrett's esophagus to high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC). However, current quantification of fluorescent images is done only after the endoscopic procedure. We developed a Chan-Vese-based algorithm to segment fluorescence targets, and subsequent morphological operations to generate background, thus calculating target/background (T/B) ratios, potentially to provide real-time guidance for biopsy and endoscopic therapy. With an initial processing speed of 2 fps and by calculating the T/B ratio for each frame, our method provides quasireal-time quantification of the molecular probe labeling to the endoscopist. Furthermore, an automatic computer-aided diagnosis algorithm can be applied to the recorded endoscopic video, and the overall T/B ratio is calculated for each patient. The receiver operating characteristic curve was employed to determine the threshold for classification of HGD/EAC using leave-one-out cross-validation. With 92% sensitivity and 75% specificity to classify HGD/EAC, our automatic algorithm shows promising results for a surveillance procedure to help manage esophageal cancer and other cancers inspected by endoscopy.

LQTA-QSAR: a new 4D-QSAR methodology.

PubMed

Martins, João Paulo A; Barbosa, Euzébio G; Pasqualoto, Kerly F M; Ferreira, Márcia M C

2009-06-01

A novel 4D-QSAR approach which makes use of the molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package is presented in this study. This new methodology, named LQTA-QSAR (LQTA, Laboratório de Quimiometria Teórica e Aplicada), has a module (LQTAgrid) that calculates intermolecular interaction energies at each grid point considering probes and all aligned conformations resulting from MD simulations. These interaction energies are the independent variables or descriptors employed in a QSAR analysis. The comparison of the proposed methodology to other 4D-QSAR and CoMFA formalisms was performed using a set of forty-seven glycogen phosphorylase b inhibitors (data set 1) and a set of forty-four MAP p38 kinase inhibitors (data set 2). The QSAR models for both data sets were built using the ordered predictor selection (OPS) algorithm for variable selection. Model validation was carried out applying y-randomization and leave-N-out cross-validation in addition to the external validation. PLS models for data set 1 and 2 provided the following statistics: q(2) = 0.72, r(2) = 0.81 for 12 variables selected and 2 latent variables and q(2) = 0.82, r(2) = 0.90 for 10 variables selected and 5 latent variables, respectively. Visualization of the descriptors in 3D space was successfully interpreted from the chemical point of view, supporting the applicability of this new approach in rational drug design.

Pivot methods for global optimization

NASA Astrophysics Data System (ADS)

Stanton, Aaron Fletcher

A new algorithm is presented for the location of the global minimum of a multiple minima problem. It begins with a series of randomly placed probes in phase space, and then uses an iterative redistribution of the worst probes into better regions of phase space until a chosen convergence criterion is fulfilled. The method quickly converges, does not require derivatives, and is resistant to becoming trapped in local minima. Comparison of this algorithm with others using a standard test suite demonstrates that the number of function calls has been decreased conservatively by a factor of about three with the same degrees of accuracy. Two major variations of the method are presented, differing primarily in the method of choosing the probes that act as the basis for the new probes. The first variation, termed the lowest energy pivot method, ranks all probes by their energy and keeps the best probes. The probes being discarded select from those being kept as the basis for the new cycle. In the second variation, the nearest neighbor pivot method, all probes are paired with their nearest neighbor. The member of each pair with the higher energy is relocated in the vicinity of its neighbor. Both methods are tested against a standard test suite of functions to determine their relative efficiency, and the nearest neighbor pivot method is found to be the more efficient. A series of Lennard-Jones clusters is optimized with the nearest neighbor method, and a scaling law is found for cpu time versus the number of particles in the system. The two methods are then compared more explicitly, and finally a study in the use of the pivot method for solving the Schroedinger equation is presented. The nearest neighbor method is found to be able to solve the ground state of the quantum harmonic oscillator from a pure random initialization of the wavefunction.

Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics

PubMed Central

Prescott, Aaron M.; McCollough, Forest W.; Eldreth, Bryan L.; Binder, Brad M.; Abel, Steven M.

2016-01-01

Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. The dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i) whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii) what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB). In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB). Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations, and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms underlying ethylene signaling. Analysis of each network topology results in predictions about changes that occur in network components that can be experimentally tested to give insights into which, if either, network underlies ethylene responses. PMID:27625669

Relaxation dynamics of internal segments of DNA chains in nanochannels

NASA Astrophysics Data System (ADS)

Jain, Aashish; Muralidhar, Abhiram; Dorfman, Kevin; Dorfman Group Team

We will present relaxation dynamics of internal segments of a DNA chain confined in nanochannel. The results have direct application in genome mapping technology, where long DNA molecules containing sequence-specific fluorescent probes are passed through an array of nanochannels to linearize them, and then the distances between these probes (the so-called ``DNA barcode'') are measured. The relaxation dynamics of internal segments set the experimental error due to dynamic fluctuations. We developed a multi-scale simulation algorithm, combining a Pruned-Enriched Rosenbluth Method (PERM) simulation of a discrete wormlike chain model with hard spheres with Brownian dynamics (BD) simulations of a bead-spring chain. Realistic parameters such as the bead friction coefficient and spring force law parameters are obtained from PERM simulations and then mapped onto the bead-spring model. The BD simulations are carried out to obtain the extension autocorrelation functions of various segments, which furnish their relaxation times. Interestingly, we find that (i) corner segments relax faster than the center segments and (ii) relaxation times of corner segments do not depend on the contour length of DNA chain, whereas the relaxation times of center segments increase linearly with DNA chain size.

Correction of static pressure on a research aircraft in accelerated flight using differential pressure measurements

NASA Astrophysics Data System (ADS)

Rodi, A. R.; Leon, D. C.

2012-05-01

Geometric altitude data from a combined Global Navigation Satellite System (GNSS) and inertial measurement unit (IMU) system on the University of Wyoming King Air research aircraft are used to estimate acceleration effects on static pressure measurement. Using data collected during periods of accelerated flight, comparison of measured pressure with that derived from GNSS/IMU geometric altitude show that errors exceeding 150 Pa can occur which is significant in airspeed and atmospheric air motion determination. A method is developed to predict static pressure errors from analysis of differential pressure measurements from a Rosemount model 858 differential pressure air velocity probe. The method was evaluated with a carefully designed probe towed on connecting tubing behind the aircraft - a "trailing cone" - in steady flight, and shown to have a precision of about ±10 Pa over a wide range of conditions including various altitudes, power settings, and gear and flap extensions. Under accelerated flight conditions, compared to the GNSS/IMU data, this algorithm predicts corrections to a precision of better than ±20 Pa. Some limiting factors affecting the precision of static pressure measurement on a research aircraft are examined.

Oligonucleotide fingerprinting of rRNA genes for analysis of fungal community composition.

PubMed

Valinsky, Lea; Della Vedova, Gianluca; Jiang, Tao; Borneman, James

2002-12-01

Thorough assessments of fungal diversity are currently hindered by technological limitations. Here we describe a new method for identifying fungi, oligonucleotide fingerprinting of rRNA genes (OFRG). ORFG sorts arrayed rRNA gene (ribosomal DNA [rDNA]) clones into taxonomic clusters through a series of hybridization experiments, each using a single oligonucleotide probe. A simulated annealing algorithm was used to design an OFRG probe set for fungal rDNA. Analysis of 1,536 fungal rDNA clones derived from soil generated 455 clusters. A pairwise sequence analysis showed that clones with average sequence identities of 99.2% were grouped into the same cluster. To examine the accuracy of the taxonomic identities produced by this OFRG experiment, we determined the nucleotide sequences for 117 clones distributed throughout the tree. For all but two of these clones, the taxonomic identities generated by this OFRG experiment were consistent with those generated by a nucleotide sequence analysis. Eighty-eight percent of the clones were affiliated with Ascomycota, while 12% belonged to BASIDIOMYCOTA: A large fraction of the clones were affiliated with the genera Fusarium (404 clones) and Raciborskiomyces (176 clones). Smaller assemblages of clones had high sequence identities to the Alternaria, Ascobolus, Chaetomium, Cryptococcus, and Rhizoctonia clades.

Selection of optimal oligonucleotide probes for microarrays usingmultiple criteria, global alignment and parameter estimation.

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

Li, Xingyuan; He, Zhili; Zhou, Jizhong

2005-10-30

The oligonucleotide specificity for microarray hybridizationcan be predicted by its sequence identity to non-targets, continuousstretch to non-targets, and/or binding free energy to non-targets. Mostcurrently available programs only use one or two of these criteria, whichmay choose 'false' specific oligonucleotides or miss 'true' optimalprobes in a considerable proportion. We have developed a software tool,called CommOligo using new algorithms and all three criteria forselection of optimal oligonucleotide probes. A series of filters,including sequence identity, free energy, continuous stretch, GC content,self-annealing, distance to the 3'-untranslated region (3'-UTR) andmelting temperature (Tm), are used to check each possibleoligonucleotide. A sequence identity is calculated based onmore » gapped globalalignments. A traversal algorithm is used to generate alignments for freeenergy calculation. The optimal Tm interval is determined based on probecandidates that have passed all other filters. Final probes are pickedusing a combination of user-configurable piece-wise linear functions andan iterative process. The thresholds for identity, stretch and freeenergy filters are automatically determined from experimental data by anaccessory software tool, CommOligo_PE (CommOligo Parameter Estimator).The program was used to design probes for both whole-genome and highlyhomologous sequence data. CommOligo and CommOligo_PE are freely availableto academic users upon request.« less

2D-3D rigid registration to compensate for prostate motion during 3D TRUS-guided biopsy.

PubMed

De Silva, Tharindu; Fenster, Aaron; Cool, Derek W; Gardi, Lori; Romagnoli, Cesare; Samarabandu, Jagath; Ward, Aaron D

2013-02-01

Three-dimensional (3D) transrectal ultrasound (TRUS)-guided systems have been developed to improve targeting accuracy during prostate biopsy. However, prostate motion during the procedure is a potential source of error that can cause target misalignments. The authors present an image-based registration technique to compensate for prostate motion by registering the live two-dimensional (2D) TRUS images acquired during the biopsy procedure to a preacquired 3D TRUS image. The registration must be performed both accurately and quickly in order to be useful during the clinical procedure. The authors implemented an intensity-based 2D-3D rigid registration algorithm optimizing the normalized cross-correlation (NCC) metric using Powell's method. The 2D TRUS images acquired during the procedure prior to biopsy gun firing were registered to the baseline 3D TRUS image acquired at the beginning of the procedure. The accuracy was measured by calculating the target registration error (TRE) using manually identified fiducials within the prostate; these fiducials were used for validation only and were not provided as inputs to the registration algorithm. They also evaluated the accuracy when the registrations were performed continuously throughout the biopsy by acquiring and registering live 2D TRUS images every second. This measured the improvement in accuracy resulting from performing the registration, continuously compensating for motion during the procedure. To further validate the method using a more challenging data set, registrations were performed using 3D TRUS images acquired by intentionally exerting different levels of ultrasound probe pressures in order to measure the performance of our algorithm when the prostate tissue was intentionally deformed. In this data set, biopsy scenarios were simulated by extracting 2D frames from the 3D TRUS images and registering them to the baseline 3D image. A graphics processing unit (GPU)-based implementation was used to improve the registration speed. They also studied the correlation between NCC and TREs. The root-mean-square (RMS) TRE of registrations performed prior to biopsy gun firing was found to be 1.87 ± 0.81 mm. This was an improvement over 4.75 ± 2.62 mm before registration. When the registrations were performed every second during the biopsy, the RMS TRE was reduced to 1.63 ± 0.51 mm. For 3D data sets acquired under different probe pressures, the RMS TRE was found to be 3.18 ± 1.6 mm. This was an improvement from 6.89 ± 4.1 mm before registration. With the GPU based implementation, the registrations were performed with a mean time of 1.1 s. The TRE showed a weak correlation with the similarity metric. However, the authors measured a generally convex shape of the metric around the ground truth, which may explain the rapid convergence of their algorithm to accurate results. Registration to compensate for prostate motion during 3D TRUS-guided biopsy can be performed with a measured accuracy of less than 2 mm and a speed of 1.1 s, which is an important step toward improving the targeting accuracy of a 3D TRUS-guided biopsy system.

An image registration based ultrasound probe calibration

NASA Astrophysics Data System (ADS)

Li, Xin; Kumar, Dinesh; Sarkar, Saradwata; Narayanan, Ram

2012-02-01

Reconstructed 3D ultrasound of prostate gland finds application in several medical areas such as image guided biopsy, therapy planning and dose delivery. In our application, we use an end-fire probe rotated about its axis to acquire a sequence of rotational slices to reconstruct 3D TRUS (Transrectal Ultrasound) image. The image acquisition system consists of an ultrasound transducer situated on a cradle directly attached to a rotational sensor. However, due to system tolerances, axis of probe does not align exactly with the designed axis of rotation resulting in artifacts in the 3D reconstructed ultrasound volume. We present a rigid registration based automatic probe calibration approach. The method uses a sequence of phantom images, each pair acquired at angular separation of 180 degrees and registers corresponding image pairs to compute the deviation from designed axis. A modified shadow removal algorithm is applied for preprocessing. An attribute vector is constructed from image intensity and a speckle-insensitive information-theoretic feature. We compare registration between the presented method and expert-corrected images in 16 prostate phantom scans. Images were acquired at multiple resolutions, and different misalignment settings from two ultrasound machines. Screenshots from 3D reconstruction are shown before and after misalignment correction. Registration parameters from automatic and manual correction were found to be in good agreement. Average absolute differences of translation and rotation between automatic and manual methods were 0.27 mm and 0.65 degree, respectively. The registration parameters also showed lower variability for automatic registration (pooled standard deviation σtranslation = 0.50 mm, σrotation = 0.52 degree) compared to the manual approach (pooled standard deviation σtranslation = 0.62 mm, σrotation = 0.78 degree).

Probing numerical Laplace inversion methods for two and three-site molecular exchange between interconnected pore structures.

PubMed

Silletta, Emilia V; Franzoni, María B; Monti, Gustavo A; Acosta, Rodolfo H

2018-01-01

Two-dimension (2D) Nuclear Magnetic Resonance relaxometry experiments are a powerful tool extensively used to probe the interaction among different pore structures, mostly in inorganic systems. The analysis of the collected experimental data generally consists of a 2D numerical inversion of time-domain data where T 2 -T 2 maps are generated. Through the years, different algorithms for the numerical inversion have been proposed. In this paper, two different algorithms for numerical inversion are tested and compared under different conditions of exchange dynamics; the method based on Butler-Reeds-Dawson (BRD) algorithm and the fast-iterative shrinkage-thresholding algorithm (FISTA) method. By constructing a theoretical model, the algorithms were tested for a two- and three-site porous media, varying the exchange rates parameters, the pore sizes and the signal to noise ratio. In order to test the methods under realistic experimental conditions, a challenging organic system was chosen. The molecular exchange rates of water confined in hierarchical porous polymeric networks were obtained, for a two- and three-site porous media. Data processed with the BRD method was found to be accurate only under certain conditions of the exchange parameters, while data processed with the FISTA method is precise for all the studied parameters, except when SNR conditions are extreme. Copyright © 2017 Elsevier Inc. All rights reserved.

Accuracy of optical spectroscopy for the detection of cervical intraepithelial neoplasia without colposcopic tissue information; a step toward automation for low resource settings

PubMed Central

Zewdie, Getie A.; Cox, Dennis D.; Neely Atkinson, E.; Cantor, Scott B.; MacAulay, Calum; Davies, Kalatu; Adewole, Isaac; Buys, Timon P. H.; Follen, Michele

2012-01-01

Abstract. Optical spectroscopy has been proposed as an accurate and low-cost alternative for detection of cervical intraepithelial neoplasia. We previously published an algorithm using optical spectroscopy as an adjunct to colposcopy and found good accuracy (sensitivity=1.00 [95% confidence interval (CI)=0.92 to 1.00], specificity=0.71 [95% CI=0.62 to 0.79]). Those results used measurements taken by expert colposcopists as well as the colposcopy diagnosis. In this study, we trained and tested an algorithm for the detection of cervical intraepithelial neoplasia (i.e., identifying those patients who had histology reading CIN 2 or worse) that did not include the colposcopic diagnosis. Furthermore, we explored the interaction between spectroscopy and colposcopy, examining the importance of probe placement expertise. The colposcopic diagnosis-independent spectroscopy algorithm had a sensitivity of 0.98 (95% CI=0.89 to 1.00) and a specificity of 0.62 (95% CI=0.52 to 0.71). The difference in the partial area under the ROC curves between spectroscopy with and without the colposcopic diagnosis was statistically significant at the patient level (p=0.05) but not the site level (p=0.13). The results suggest that the device has high accuracy over a wide range of provider accuracy and hence could plausibly be implemented by providers with limited training. PMID:22559693

Design of primers and probes for quantitative real-time PCR methods.

PubMed

Rodríguez, Alicia; Rodríguez, Mar; Córdoba, Juan J; Andrade, María J

2015-01-01

Design of primers and probes is one of the most crucial factors affecting the success and quality of quantitative real-time PCR (qPCR) analyses, since an accurate and reliable quantification depends on using efficient primers and probes. Design of primers and probes should meet several criteria to find potential primers and probes for specific qPCR assays. The formation of primer-dimers and other non-specific products should be avoided or reduced. This factor is especially important when designing primers for SYBR(®) Green protocols but also in designing probes to ensure specificity of the developed qPCR protocol. To design primers and probes for qPCR, multiple software programs and websites are available being numerous of them free. These tools often consider the default requirements for primers and probes, although new research advances in primer and probe design should be progressively added to different algorithm programs. After a proper design, a precise validation of the primers and probes is necessary. Specific consideration should be taken into account when designing primers and probes for multiplex qPCR and reverse transcription qPCR (RT-qPCR). This chapter provides guidelines for the design of suitable primers and probes and their subsequent validation through the development of singlex qPCR, multiplex qPCR, and RT-qPCR protocols.

Measuring Constraint-Set Utility for Partitional Clustering Algorithms

NASA Technical Reports Server (NTRS)

Davidson, Ian; Wagstaff, Kiri L.; Basu, Sugato

2006-01-01

Clustering with constraints is an active area of machine learning and data mining research. Previous empirical work has convincingly shown that adding constraints to clustering improves the performance of a variety of algorithms. However, in most of these experiments, results are averaged over different randomly chosen constraint sets from a given set of labels, thereby masking interesting properties of individual sets. We demonstrate that constraint sets vary significantly in how useful they are for constrained clustering; some constraint sets can actually decrease algorithm performance. We create two quantitative measures, informativeness and coherence, that can be used to identify useful constraint sets. We show that these measures can also help explain differences in performance for four particular constrained clustering algorithms.

Comparing Cognitive Interviewing and Online Probing: Do They Find Similar Results?

ERIC Educational Resources Information Center

Meitinger, Katharina; Behr, Dorothée

2016-01-01

This study compares the application of probing techniques in cognitive interviewing (CI) and online probing (OP). Even though the probing is similar, the methods differ regarding typical mode setting, sample size, level of interactivity, and goals. We analyzed probing answers to the International Social Survey Programme item battery on specific…

Clinical utility of multiplex ligation-dependent probe amplification technique in identification of aetiology of unexplained mental retardation: a study in 203 Indian patients.

PubMed

Boggula, Vijay R; Shukla, Anju; Danda, Sumita; Hariharan, Sankar V; Nampoothiri, Sheela; Kumar, Rashmi; Phadke, Shubha R

2014-01-01

Developmental delay (DD)/mental retardation also described as intellectual disability (ID), is seen in 1-3 per cent of general population. Diagnosis continues to be a challenge at clinical level. With the advancement of new molecular cytogenetic techniques such as cytogenetic microarray (CMA), multiplex ligation-dependent probe amplification (MLPA) techniques, many microdeletion/microduplication syndromes with DD/ID are now delineated. MLPA technique can probe 40-50 genomic regions in a single reaction and is being used for evaluation of cases with DD/ID. In this study we evaluated the clinical utility of MLPA techniques with different probe sets to identify the aetiology of unexplained mental retardation in patients with ID/DD. A total of 203 randomly selected DD/ID cases with/without malformations were studied. MLPA probe sets for subtelomeric regions (P070/P036) and common microdeletions/microduplications (P245-A2) and X-chromosome (P106) were used. Positive cases with MLPA technique were confirmed using either fluorescence in situ hybridization (FISH) or follow up confirmatory MLPA probe sets. The overall detection rate was found to be 9.3 per cent (19 out of 203). The detection rates were 6.9 and 7.4 per cent for common microdeletion/microduplication and subtelomeric probe sets, respectively. No abnormality was detected with probe set for X-linked ID. The subtelomeric abnormalities detected included deletions of 1p36.33, 4p, 5p, 9p, 9q, 13q telomeric regions and duplication of 9pter. The deletions/duplications detected in non telomeric regions include regions for Prader Willi/Angelman regions, Williams syndrome, Smith Magenis syndrome and Velocardiofacial syndrome. Our results show that the use of P245-A2 and P070/P036-E1 probes gives good diagnostic yield. Though MLPA cannot probe the whole genome like cytogenetic microarray, due to its ease and relative low cost it is an important technique for evaluation of cases with DD/ID.

Gwyscan: a library to support non-equidistant scanning probe microscope measurements

NASA Astrophysics Data System (ADS)

Klapetek, Petr; Yacoot, Andrew; Grolich, Petr; Valtr, Miroslav; Nečas, David

2017-03-01

We present a software library and related methodology for enabling easy integration of adaptive step (non-equidistant) scanning techniques into metrological scanning probe microscopes or scanning probe microscopes where individual x, y position data are recorded during measurements. Scanning with adaptive steps can reduce the amount of data collected in SPM measurements thereby leading to faster data acquisition, a smaller amount of data collection required for a specific analytical task and less sensitivity to mechanical and thermal drift. Implementation of adaptive scanning routines into a custom built microscope is not normally an easy task: regular data are much easier to handle for previewing (e.g. levelling) and storage. We present an environment to make implementation of adaptive scanning easier for an instrument developer, specifically taking into account data acquisition approaches that are used in high accuracy microscopes as those developed by National Metrology Institutes. This includes a library with algorithms written in C and LabVIEW for handling data storage, regular mesh preview generation and planning the scan path on basis of different assumptions. A set of modules for Gwyddion open source software for handling these data and for their further analysis is presented. Using this combination of data acquisition and processing tools one can implement adaptive scanning in a relatively easy way into an instrument that was previously measuring on a regular grid. The performance of the presented approach is shown and general non-equidistant data processing steps are discussed.

Benchmarking Ligand-Based Virtual High-Throughput Screening with the PubChem Database

PubMed Central

Butkiewicz, Mariusz; Lowe, Edward W.; Mueller, Ralf; Mendenhall, Jeffrey L.; Teixeira, Pedro L.; Weaver, C. David; Meiler, Jens

2013-01-01

With the rapidly increasing availability of High-Throughput Screening (HTS) data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD) have the potential to accelerate and reduce the cost of probe development and drug discovery efforts in academia. We assemble nine data sets from realistic HTS campaigns representing major families of drug target proteins for benchmarking LB-CADD methods. Each data set is public domain through PubChem and carefully collated through confirmation screens validating active compounds. These data sets provide the foundation for benchmarking a new cheminformatics framework BCL::ChemInfo, which is freely available for non-commercial use. Quantitative structure activity relationship (QSAR) models are built using Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Decision Trees (DTs), and Kohonen networks (KNs). Problem-specific descriptor optimization protocols are assessed including Sequential Feature Forward Selection (SFFS) and various information content measures. Measures of predictive power and confidence are evaluated through cross-validation, and a consensus prediction scheme is tested that combines orthogonal machine learning algorithms into a single predictor. Enrichments ranging from 15 to 101 for a TPR cutoff of 25% are observed. PMID:23299552

Development and construction of a comprehensive set of research diagnostics for the FLARE user facility

NASA Astrophysics Data System (ADS)

Yoo, Jongsoo; Jara-Almonte, J.; Majeski, S.; Frank, S.; Ji, H.; Yamada, M.

2016-10-01

FLARE (Facility for Laboratory Reconnection Experiments) will be operated as a flexible user facility, and so a complete set of research diagnostics is under development, including magnetic probe arrays, Langmuir probes, Mach probes, spectroscopic probes, and a laser interferometer. In order to accommodate the various requirements of users, large-scale (1 m), variable resolution (0.5-4 cm) magnetic probes have been designed, and are currently being prototyped. Moreover, a fully fiber-coupled laser interferometer has been designed to measure the line-integrated electron density. This fiber-coupled interferometer system will reduce the complexity of alignment processes and minimize maintenance of the system. Finally, improvements to the electrostatic probes and spectroscopic probes currently used in the Magnetic Reconnection Experiment (MRX) are discussed. The specifications of other subsystems, such as integrators and digitizers, are also presented. This work is supported by DoE Contract No. DE-AC0209CH11466.

Development of a robust MRI fiducial system for automated fusion of MR-US abdominal images.

PubMed

Favazza, Christopher P; Gorny, Krzysztof R; Callstrom, Matthew R; Kurup, Anil N; Washburn, Michael; Trester, Pamela S; Fowler, Charles L; Hangiandreou, Nicholas J

2018-05-21

We present the development of a two-component magnetic resonance (MR) fiducial system, that is, a fiducial marker device combined with an auto-segmentation algorithm, designed to be paired with existing ultrasound probe tracking and image fusion technology to automatically fuse MR and ultrasound (US) images. The fiducial device consisted of four ~6.4 mL cylindrical wells filled with 1 g/L copper sulfate solution. The algorithm was designed to automatically segment the device in clinical abdominal MR images. The algorithm's detection rate and repeatability were investigated through a phantom study and in human volunteers. The detection rate was 100% in all phantom and human images. The center-of-mass of the fiducial device was robustly identified with maximum variations of 2.9 mm in position and 0.9° in angular orientation. In volunteer images, average differences between algorithm-measured inter-marker spacings and actual separation distances were 0.53 ± 0.36 mm. "Proof-of-concept" automatic MR-US fusions were conducted with sets of images from both a phantom and volunteer using a commercial prototype system, which was built based on the above findings. Image fusion accuracy was measured to be within 5 mm for breath-hold scanning. These results demonstrate the capability of this approach to automatically fuse US and MR images acquired across a wide range of clinical abdominal pulse sequences. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Tests of a Semi-Analytical Case 1 and Gelbstoff Case 2 SeaWiFS Algorithm with a Global Data Set

NASA Technical Reports Server (NTRS)

Carder, Kendall L.; Hawes, Steve K.; Lee, Zhongping

1997-01-01

A semi-analytical algorithm was tested with a total of 733 points of either unpackaged or packaged-pigment data, with corresponding algorithm parameters for each data type. The 'unpackaged' type consisted of data sets that were generally consistent with the Case 1 CZCS algorithm and other well calibrated data sets. The 'packaged' type consisted of data sets apparently containing somewhat more packaged pigments, requiring modification of the absorption parameters of the model consistent with the CalCOFI study area. This resulted in two equally divided data sets. A more thorough scrutiny of these and other data sets using a semianalytical model requires improved knowledge of the phytoplankton and gelbstoff of the specific environment studied. Since the semi-analytical algorithm is dependent upon 4 spectral channels including the 412 nm channel, while most other algorithms are not, a means of testing data sets for consistency was sought. A numerical filter was developed to classify data sets into the above classes. The filter uses reflectance ratios, which can be determined from space. The sensitivity of such numerical filters to measurement resulting from atmospheric correction and sensor noise errors requires further study. The semi-analytical algorithm performed superbly on each of the data sets after classification, resulting in RMS1 errors of 0.107 and 0.121, respectively, for the unpackaged and packaged data-set classes, with little bias and slopes near 1.0. In combination, the RMS1 performance was 0.114. While these numbers appear rather sterling, one must bear in mind what mis-classification does to the results. Using an average or compromise parameterization on the modified global data set yielded an RMS1 error of 0.171, while using the unpackaged parameterization on the global evaluation data set yielded an RMS1 error of 0.284. So, without classification, the algorithm performs better globally using the average parameters than it does using the unpackaged parameters. Finally, the effects of even more extreme pigment packaging must be examined in order to improve algorithm performance at high latitudes. Note, however, that the North Sea and Mississippi River plume studies contributed data to the packaged and unpackaged classess, respectively, with little effect on algorithm performance. This suggests that gelbstoff-rich Case 2 waters do not seriously degrade performance of the semi-analytical algorithm.

Optimization of pressure probe placement and data analysis of engine-inlet distortion

NASA Astrophysics Data System (ADS)

Walter, S. F.

The purpose of this research is to examine methods by which quantification of inlet flow distortion may be improved upon. Specifically, this research investigates how data interpolation effects results, optimizing sampling locations of the flow, and determining the sensitivity related to how many sample locations there are. The main parameters that are indicative of a "good" design are total pressure recovery, mass flow capture, and distortion. This work focuses on the total pressure distortion, which describes the amount of non-uniformity that exists in the flow as it enters the engine. All engines must tolerate some level of distortion, however too much distortion can cause the engine to stall or the inlet to unstart. Flow distortion is measured at the interface between the inlet and the engine. To determine inlet flow distortion, a combination of computational and experimental pressure data is generated and then collapsed into an index that indicates the amount of distortion. Computational simulations generate continuous contour maps, but experimental data is discrete. Researchers require continuous contour maps to evaluate the overall distortion pattern. There is no guidance on how to best manipulate discrete points into a continuous pattern. Using one experimental, 320 probe data set and one, 320 point computational data set with three test runs each, this work compares the pressure results obtained using all 320 points of data from the original sets, both quantitatively and qualitatively, with results derived from selecting 40 grid point subsets and interpolating to 320 grid points. Each of the two, 40 point sets were interpolated to 320 grid points using four different interpolation methods in an attempt to establish the best method for interpolating small sets of data into an accurate, continuous contour map. Interpolation methods investigated are bilinear, spline, and Kriging in Cartesian space, as well as angular in polar space. Spline interpolation methods should be used as they result in the most accurate, precise, and visually correct predictions when compared results achieved from the full data sets. Researchers were interested if fewer than the recommended 40 probes could be used - especially when placed in areas of high interest - but still obtain equivalent or better results. For this investigation, the computational results from a two-dimensional inlet and experimental results of an axisymmetric inlet were used. To find the areas of interest, a uniform sampling of all possible locations was run through a Monte Carlo simulation with a varying number of probes. A probability density function of the resultant distortion index was plotted. Certain probes are required to come within the desired accuracy level of the distortion index based on the full data set. For the experimental results, all three test cases could be characterized with 20 probes. For the axisymmetric inlet, placing 40 probes in select locations could get the results for parameters of interest within less than 10% of the exact solution for almost all cases. For the two dimensional inlet, the results were not as clear. 80 probes were required to get within 10% of the exact solution for all run numbers, although this is largely due to the small value of the exact result. The sensitivity of each probe added to the experiment was analyzed. Instead of looking at the overall pattern established by optimizing probe placements, the focus is on varying the number of sampled probes from 20 to 40. The number of points falling within a 1% tolerance band of the exact solution were counted as good points. The results were normalized for each data set and a general sensitivity function was found to determine the sensitivity of the results. A linear regression was used to generalize the results for all data sets used in this work. However, they can be used by directly comparing the number of good points obtained with various numbers of probes as well. The sensitivity in the results is higher when fewer probes are used and gradually tapers off near 40 probes. There is a bigger gain in good points when the number of probes is increased from 20 to 21 probes than from 39 to 40 probes.

An alternative view of protein fold space.

PubMed

Shindyalov, I N; Bourne, P E

2000-02-15

Comparing and subsequently classifying protein structures information has received significant attention concurrent with the increase in the number of experimentally derived 3-dimensional structures. Classification schemes have focused on biological function found within protein domains and on structure classification based on topology. Here an alternative view is presented that groups substructures. Substructures are long (50-150 residue) highly repetitive near-contiguous pieces of polypeptide chain that occur frequently in a set of proteins from the PDB defined as structurally non-redundant over the complete polypeptide chain. The substructure classification is based on a previously reported Combinatorial Extension (CE) algorithm that provides a significantly different set of structure alignments than those previously described, having, for example, only a 40% overlap with FSSP. Qualitatively the algorithm provides longer contiguous aligned segments at the price of a slightly higher root-mean-square deviation (rmsd). Clustering these alignments gives a discreet and highly repetitive set of substructures not detectable by sequence similarity alone. In some cases different substructures represent all or different parts of well known folds indicative of the Russian doll effect--the continuity of protein fold space. In other cases they fall into different structure and functional classifications. It is too early to determine whether these newly classified substructures represent new insights into the evolution of a structural framework important to many proteins. What is apparent from on-going work is that these substructures have the potential to be useful probes in finding remote sequence homology and in structure prediction studies. The characteristics of the complete all-by-all comparison of the polypeptide chains present in the PDB and details of the filtering procedure by pair-wise structure alignment that led to the emergent substructure gallery are discussed. Substructure classification, alignments, and tools to analyze them are available at http://cl.sdsc.edu/ce.html.

PeakRanger: A cloud-enabled peak caller for ChIP-seq data

PubMed Central

2011-01-01

Background Chromatin immunoprecipitation (ChIP), coupled with massively parallel short-read sequencing (seq) is used to probe chromatin dynamics. Although there are many algorithms to call peaks from ChIP-seq datasets, most are tuned either to handle punctate sites, such as transcriptional factor binding sites, or broad regions, such as histone modification marks; few can do both. Other algorithms are limited in their configurability, performance on large data sets, and ability to distinguish closely-spaced peaks. Results In this paper, we introduce PeakRanger, a peak caller software package that works equally well on punctate and broad sites, can resolve closely-spaced peaks, has excellent performance, and is easily customized. In addition, PeakRanger can be run in a parallel cloud computing environment to obtain extremely high performance on very large data sets. We present a series of benchmarks to evaluate PeakRanger against 10 other peak callers, and demonstrate the performance of PeakRanger on both real and synthetic data sets. We also present real world usages of PeakRanger, including peak-calling in the modENCODE project. Conclusions Compared to other peak callers tested, PeakRanger offers improved resolution in distinguishing extremely closely-spaced peaks. PeakRanger has above-average spatial accuracy in terms of identifying the precise location of binding events. PeakRanger also has excellent sensitivity and specificity in all benchmarks evaluated. In addition, PeakRanger offers significant improvements in run time when running on a single processor system, and very marked improvements when allowed to take advantage of the MapReduce parallel environment offered by a cloud computing resource. PeakRanger can be downloaded at the official site of modENCODE project: http://www.modencode.org/software/ranger/ PMID:21554709

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.

Development of a group-specific 16S rRNA-targeted probe set for the identification of Marinobacter by fluorescence in situ hybridization

NASA Astrophysics Data System (ADS)

McKay, Luke J.; Gutierrez, Tony; Teske, Andreas P.

2016-07-01

Members of the Marinobacter genus play an important role in hydrocarbon degradation in the ocean - a topic of special significance in light of the recent Deepwater Horizon oil spill of 2010. The Marinobacter group has thus far lacked a genus level phylogenetic probe that would allow in situ identification of representative members. Here, we developed two new 16S rRNA-targeted oligonucleotide probes (Mrb-0625-a and Mrb-0625-b) to enumerate Marinobacter species by fluorescence in situ hybridization (FISH). In silico analysis of this probe set demonstrated 80% coverage of the Marinobacter genus. A competitor probe was developed to block hybridization by Mrb-0625-a to six Halomonas species with which it shared a one base pair mismatch. The probe set was optimized using pure cultures, and then used in an enrichment experiment with a deep sea oil plume water sample collected from the Deepwater Horizon oil spill. Marinobacter cells rapidly increased as a significant fraction of total microbial abundance in all incubations of original contaminated seawater as well as those amended with n-hexadecane, suggesting this group may be among the first microbial responders to oil pollution in the marine environment. The new probe set will provide a reliable tool for quantifying Marinobacter in the marine environment, particularly at contaminated sites where these organisms can play an important role in the biodegradation of oil pollutants.

AeroADL: applying the integration of the Suomi-NPP science algorithms with the Algorithm Development Library to the calibration and validation task

NASA Astrophysics Data System (ADS)

Houchin, J. S.

2014-09-01

A common problem for the off-line validation of the calibration algorithms and algorithm coefficients is being able to run science data through the exact same software used for on-line calibration of that data. The Joint Polar Satellite System (JPSS) program solved part of this problem by making the Algorithm Development Library (ADL) available, which allows the operational algorithm code to be compiled and run on a desktop Linux workstation using flat file input and output. However, this solved only part of the problem, as the toolkit and methods to initiate the processing of data through the algorithms were geared specifically toward the algorithm developer, not the calibration analyst. In algorithm development mode, a limited number of sets of test data are staged for the algorithm once, and then run through the algorithm over and over as the software is developed and debugged. In calibration analyst mode, we are continually running new data sets through the algorithm, which requires significant effort to stage each of those data sets for the algorithm without additional tools. AeroADL solves this second problem by providing a set of scripts that wrap the ADL tools, providing both efficient means to stage and process an input data set, to override static calibration coefficient look-up-tables (LUT) with experimental versions of those tables, and to manage a library containing multiple versions of each of the static LUT files in such a way that the correct set of LUTs required for each algorithm are automatically provided to the algorithm without analyst effort. Using AeroADL, The Aerospace Corporation's analyst team has demonstrated the ability to quickly and efficiently perform analysis tasks for both the VIIRS and OMPS sensors with minimal training on the software tools.

Nanohertz frequency determination for the gravity probe B high frequency superconducting quantum interference device signal.

PubMed

Salomon, M; Conklin, J W; Kozaczuk, J; Berberian, J E; Keiser, G M; Silbergleit, A S; Worden, P; Santiago, D I

2011-12-01

In this paper, we present a method to measure the frequency and the frequency change rate of a digital signal. This method consists of three consecutive algorithms: frequency interpolation, phase differencing, and a third algorithm specifically designed and tested by the authors. The succession of these three algorithms allowed a 5 parts in 10(10) resolution in frequency determination. The algorithm developed by the authors can be applied to a sampled scalar signal such that a model linking the harmonics of its main frequency to the underlying physical phenomenon is available. This method was developed in the framework of the gravity probe B (GP-B) mission. It was applied to the high frequency (HF) component of GP-B's superconducting quantum interference device signal, whose main frequency f(z) is close to the spin frequency of the gyroscopes used in the experiment. A 30 nHz resolution in signal frequency and a 0.1 pHz/s resolution in its decay rate were achieved out of a succession of 1.86 s-long stretches of signal sampled at 2200 Hz. This paper describes the underlying theory of the frequency measurement method as well as its application to GP-B's HF science signal.

Vision-based system for the control and measurement of wastewater flow rate in sewer systems.

PubMed

Nguyen, L S; Schaeli, B; Sage, D; Kayal, S; Jeanbourquin, D; Barry, D A; Rossi, L

2009-01-01

Combined sewer overflows and stormwater discharges represent an important source of contamination to the environment. However, the harsh environment inside sewers and particular hydraulic conditions during rain events reduce the reliability of traditional flow measurement probes. In the following, we present and evaluate an in situ system for the monitoring of water flow in sewers based on video images. This paper focuses on the measurement of the water level based on image-processing techniques. The developed image-based water level algorithms identify the wall/water interface from sewer images and measure its position with respect to real world coordinates. A web-based user interface and a 3-tier system architecture enable the remote configuration of the cameras and the image-processing algorithms. Images acquired and processed by our system were found to reliably measure water levels and thereby to provide crucial information leading to better understand particular hydraulic behaviors. In terms of robustness and accuracy, the water level algorithm provided equal or better results compared to traditional water level probes in three different in situ configurations.

Work on Planetary Atmospheres and Planetary Atmosphere Probes

NASA Technical Reports Server (NTRS)

Seiff, Alvin; Lester, Peter

1999-01-01

A major objective of the grant was to complete the fabrication, test, and evaluation of the atmosphere structure experiment on the Galileo Probe, and to receive, analyze, and interpret data received from the spacecraft. The grantee was competitively selected to be Principal Investigator of Jupiter's atmosphere structure on the Galileo Probe. His primary motivation was to learn as much as possible about Jupiter's atmosphere by means of a successful atmosphere structure experiment, and to support the needs and schedule of the Galileo Project. After a number of launch delays, the Flight instrument was shipped to Kennedy Space Center 2 years after the start of this collaboration, on April 14, 1989, at which time it was determined from System level tests of the ASI on the Probe that the instrument was in good working order and ready for flight. The spacecraft was launched on October 18, 1989. Data analysis of test and calibration data taken over a period of years of instrument testing was continued in preparation for the encounter. The initial instrument checkout in space was performed on October 26, 1989. The data set received by telemetry was thoroughly analyzed, and a report of the findings was transmitted to the Probe Operations Office on Feb. 28, 1990. Key findings reported were that the accelerometer biases had shifted by less than 1 mg through launch and since calibration at Bell Aerospace in 1983; accelerometer scale factors, evaluated by means of calibration currents, fell on lines of variation with temperature established in laboratory calibrations; pressure sensor offsets, correlated as a function of temperature, fell generally within the limits of several years of ground test data; atmospheric and engineering temperature sensor data were internally consistent within a few tenths of a degree; and the instrument electronics performed all expected functions without any observable fault. Altogether, this checkout was highly encouraging of the prospects of instrument performance, although performed greater than 5 years prior to Jupiter encounter. Capability of decoding the science data from the Experiment Data Record to be provided at encounter was developed and exercised using the tape recording of the first Cruise Checkout data. A team effort was organized to program the selection and combination of data words defining pressure, temperature, acceleration, turbulence, and engineering quantities; to apply decalibration algorithms to convert readings from digital numbers to physical quantities; and to organize the data into a suitable printout. A paper on the Galileo Atmosphere Structure Instrument was written and submitted for publication in a special issue of Space Science Reviews. At the Journal editor's request, the grantee reviewed other Probe instrument papers submitted for this special issue. Calibration data were carefully taken for all experiment sensors and accumulated over a period of 10 years. The data were analyzed, fitted with algorithms, and summarized in a calibration report for use in analyzing and interpreting data returned from Jupiter's atmosphere. The sensors included were the primary science pressure, temperature, and acceleration sensors, and the supporting engineering temperature sensors. This report was distributed to experiment coinvestigators and the Probe Project Office.

Surface topography acquisition method for double-sided near-right-angle structured surfaces based on dual-probe wavelength scanning interferometry.

PubMed

Zhang, Tao; Gao, Feng; Jiang, Xiangqian

2017-10-02

This paper proposes an approach to measure double-sided near-right-angle structured surfaces based on dual-probe wavelength scanning interferometry (DPWSI). The principle and mathematical model is discussed and the measurement system is calibrated with a combination of standard step-height samples for both probes vertical calibrations and a specially designed calibration artefact for building up the space coordinate relationship of the dual-probe measurement system. The topography of the specially designed artefact is acquired by combining the measurement results with white light scanning interferometer (WLSI) and scanning electron microscope (SEM) for reference. The relative location of the two probes is then determined with 3D registration algorithm. Experimental validation of the approach is provided and the results show that the method is able to measure double-sided near-right-angle structured surfaces with nanometer vertical resolution and micrometer lateral resolution.

Rutgers University Subcontract B611610 Final Report

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

Soundarajan, Sucheta; Eliassi-Rad, Tina; Gallagher, Brian

Given an incomplete (i.e., partially-observed) network, which nodes should we actively probe in order to achieve the highest accuracy for a given network feature? For example, consider a cyber-network administrator who observes only a portion of the network at time t and wants to accurately identify the most important (e.g., highest PageRank) nodes in the complete network. She has a limited budget for probing the network. Of all the nodes she has observed, which should she probe in order to most accurately identify the important nodes? We propose a novel and scalable algorithm, MaxOutProbe, and evaluate it w.r.t. four networkmore » features (largest connected component, PageRank, core-periphery, and community detection), five network sampling strategies, and seven network datasets from different domains. Across a range of conditions, MaxOutProbe demonstrates consistently high performance relative to several baseline strategies« less

High performance 3D adaptive filtering for DSP based portable medical imaging systems

NASA Astrophysics Data System (ADS)

Bockenbach, Olivier; Ali, Murtaza; Wainwright, Ian; Nadeski, Mark

2015-03-01

Portable medical imaging devices have proven valuable for emergency medical services both in the field and hospital environments and are becoming more prevalent in clinical settings where the use of larger imaging machines is impractical. Despite their constraints on power, size and cost, portable imaging devices must still deliver high quality images. 3D adaptive filtering is one of the most advanced techniques aimed at noise reduction and feature enhancement, but is computationally very demanding and hence often cannot be run with sufficient performance on a portable platform. In recent years, advanced multicore digital signal processors (DSP) have been developed that attain high processing performance while maintaining low levels of power dissipation. These processors enable the implementation of complex algorithms on a portable platform. In this study, the performance of a 3D adaptive filtering algorithm on a DSP is investigated. The performance is assessed by filtering a volume of size 512x256x128 voxels sampled at a pace of 10 MVoxels/sec with an Ultrasound 3D probe. Relative performance and power is addressed between a reference PC (Quad Core CPU) and a TMS320C6678 DSP from Texas Instruments.

Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots.

PubMed

Hajdin, Christine E; Bellaousov, Stanislav; Huggins, Wayne; Leonard, Christopher W; Mathews, David H; Weeks, Kevin M

2013-04-02

A pseudoknot forms in an RNA when nucleotides in a loop pair with a region outside the helices that close the loop. Pseudoknots occur relatively rarely in RNA but are highly overrepresented in functionally critical motifs in large catalytic RNAs, in riboswitches, and in regulatory elements of viruses. Pseudoknots are usually excluded from RNA structure prediction algorithms. When included, these pairings are difficult to model accurately, especially in large RNAs, because allowing this structure dramatically increases the number of possible incorrect folds and because it is difficult to search the fold space for an optimal structure. We have developed a concise secondary structure modeling approach that combines SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) experimental chemical probing information and a simple, but robust, energy model for the entropic cost of single pseudoknot formation. Structures are predicted with iterative refinement, using a dynamic programming algorithm. This melded experimental and thermodynamic energy function predicted the secondary structures and the pseudoknots for a set of 21 challenging RNAs of known structure ranging in size from 34 to 530 nt. On average, 93% of known base pairs were predicted, and all pseudoknots in well-folded RNAs were identified.

Iterative motion compensation approach for ultrasonic thermal imaging

NASA Astrophysics Data System (ADS)

Fleming, Ioana; Hager, Gregory; Guo, Xiaoyu; Kang, Hyun Jae; Boctor, Emad

2015-03-01

As thermal imaging attempts to estimate very small tissue motion (on the order of tens of microns), it can be negatively influenced by signal decorrelation. Patient's breathing and cardiac cycle generate shifts in the RF signal patterns. Other sources of movement could be found outside the patient's body, like transducer slippage or small vibrations due to environment factors like electronic noise. Here, we build upon a robust displacement estimation method for ultrasound elastography and we investigate an iterative motion compensation algorithm, which can detect and remove non-heat induced tissue motion at every step of the ablation procedure. The validation experiments are performed on laboratory induced ablation lesions in ex-vivo tissue. The ultrasound probe is either held by the operator's hand or supported by a robotic arm. We demonstrate the ability to detect and remove non-heat induced tissue motion in both settings. We show that removing extraneous motion helps unmask the effects of heating. Our strain estimation curves closely mirror the temperature changes within the tissue. While previous results in the area of motion compensation were reported for experiments lasting less than 10 seconds, our algorithm was tested on experiments that lasted close to 20 minutes.

Learning Instance-Specific Predictive Models

PubMed Central

Visweswaran, Shyam; Cooper, Gregory F.

2013-01-01

This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algorithm learns Markov blanket models, carries out Bayesian model averaging over a set of models to predict a target variable of the instance at hand, and employs an instance-specific heuristic to locate a set of suitable models to average over. We call this method the instance-specific Markov blanket (ISMB) algorithm. The ISMB algorithm was evaluated on 21 UCI data sets using five different performance measures and its performance was compared to that of several commonly used predictive algorithms, including nave Bayes, C4.5 decision tree, logistic regression, neural networks, k-Nearest Neighbor, Lazy Bayesian Rules, and AdaBoost. Over all the data sets, the ISMB algorithm performed better on average on all performance measures against all the comparison algorithms. PMID:25045325

CONEDEP: COnvolutional Neural network based Earthquake DEtection and Phase Picking

NASA Astrophysics Data System (ADS)

Zhou, Y.; Huang, Y.; Yue, H.; Zhou, S.; An, S.; Yun, N.

2017-12-01

We developed an automatic local earthquake detection and phase picking algorithm based on Fully Convolutional Neural network (FCN). The FCN algorithm detects and segments certain features (phases) in 3 component seismograms to realize efficient picking. We use STA/LTA algorithm and template matching algorithm to construct the training set from seismograms recorded 1 month before and after the Wenchuan earthquake. Precise P and S phases are identified and labeled to construct the training set. Noise data are produced by combining back-ground noise and artificial synthetic noise to form the equivalent scale of noise set as the signal set. Training is performed on GPUs to achieve efficient convergence. Our algorithm has significantly improved performance in terms of the detection rate and precision in comparison with STA/LTA and template matching algorithms.

ArrayInitiative - a tool that simplifies creating custom Affymetrix CDFs

PubMed Central

2011-01-01

Background Probes on a microarray represent a frozen view of a genome and are quickly outdated when new sequencing studies extend our knowledge, resulting in significant measurement error when analyzing any microarray experiment. There are several bioinformatics approaches to improve probe assignments, but without in-house programming expertise, standardizing these custom array specifications as a usable file (e.g. as Affymetrix CDFs) is difficult, owing mostly to the complexity of the specification file format. However, without correctly standardized files there is a significant barrier for testing competing analysis approaches since this file is one of the required inputs for many commonly used algorithms. The need to test combinations of probe assignments and analysis algorithms led us to develop ArrayInitiative, a tool for creating and managing custom array specifications. Results ArrayInitiative is a standalone, cross-platform, rich client desktop application for creating correctly formatted, custom versions of manufacturer-provided (default) array specifications, requiring only minimal knowledge of the array specification rules and file formats. Users can import default array specifications, import probe sequences for a default array specification, design and import a custom array specification, export any array specification to multiple output formats, export the probe sequences for any array specification and browse high-level information about the microarray, such as version and number of probes. The initial release of ArrayInitiative supports the Affymetrix 3' IVT expression arrays we currently analyze, but as an open source application, we hope that others will contribute modules for other platforms. Conclusions ArrayInitiative allows researchers to create new array specifications, in a standard format, based upon their own requirements. This makes it easier to test competing design and analysis strategies that depend on probe definitions. Since the custom array specifications are easily exported to the manufacturer's standard format, researchers can analyze these customized microarray experiments using established software tools, such as those available in Bioconductor. PMID:21548938

"Hook"-calibration of GeneChip-microarrays: theory and algorithm.

PubMed

Binder, Hans; Preibisch, Stephan

2008-08-29

: The improvement of microarray calibration methods is an essential prerequisite for quantitative expression analysis. This issue requires the formulation of an appropriate model describing the basic relationship between the probe intensity and the specific transcript concentration in a complex environment of competing interactions, the estimation of the magnitude these effects and their correction using the intensity information of a given chip and, finally the development of practicable algorithms which judge the quality of a particular hybridization and estimate the expression degree from the intensity values. : We present the so-called hook-calibration method which co-processes the log-difference (delta) and -sum (sigma) of the perfect match (PM) and mismatch (MM) probe-intensities. The MM probes are utilized as an internal reference which is subjected to the same hybridization law as the PM, however with modified characteristics. After sequence-specific affinity correction the method fits the Langmuir-adsorption model to the smoothed delta-versus-sigma plot. The geometrical dimensions of this so-called hook-curve characterize the particular hybridization in terms of simple geometric parameters which provide information about the mean non-specific background intensity, the saturation value, the mean PM/MM-sensitivity gain and the fraction of absent probes. This graphical summary spans a metrics system for expression estimates in natural units such as the mean binding constants and the occupancy of the probe spots. The method is single-chip based, i.e. it separately uses the intensities for each selected chip. : The hook-method corrects the raw intensities for the non-specific background hybridization in a sequence-specific manner, for the potential saturation of the probe-spots with bound transcripts and for the sequence-specific binding of specific transcripts. The obtained chip characteristics in combination with the sensitivity corrected probe-intensity values provide expression estimates scaled in natural units which are given by the binding constants of the particular hybridization.

Statistical Models for Averaging of the Pump–Probe Traces: Example of Denoising in Terahertz Time-Domain Spectroscopy

NASA Astrophysics Data System (ADS)

Skorobogatiy, Maksim; Sadasivan, Jayesh; Guerboukha, Hichem

2018-05-01

In this paper, we first discuss the main types of noise in a typical pump-probe system, and then focus specifically on terahertz time domain spectroscopy (THz-TDS) setups. We then introduce four statistical models for the noisy pulses obtained in such systems, and detail rigorous mathematical algorithms to de-noise such traces, find the proper averages and characterise various types of experimental noise. Finally, we perform a comparative analysis of the performance, advantages and limitations of the algorithms by testing them on the experimental data collected using a particular THz-TDS system available in our laboratories. We conclude that using advanced statistical models for trace averaging results in the fitting errors that are significantly smaller than those obtained when only a simple statistical average is used.

Automated bow shock and radiation belt edge identification methods and their application for Cluster, THEMIS/ARTEMIS and Van Allen Probes data

NASA Astrophysics Data System (ADS)

Facsko, Gabor; Sibeck, David; Balogh, Tamas; Kis, Arpad; Wesztergom, Viktor

2017-04-01

The bow shock and the outer rim of the outer radiation belt are detected automatically by our algorithm developed as a part of the Boundary Layer Identification Code Cluster Active Archive project. The radiation belt positions are determined from energized electron measurements working properly onboard all Cluster spacecraft. For bow shock identification we use magnetometer data and, when available, ion plasma instrument data. In addition, electrostatic wave instrument electron density, spacecraft potential measurements and wake indicator auxiliary data are also used so the events can be identified by all Cluster probes in highly redundant way, as the magnetometer and these instruments are still operational in all spacecraft. The capability and performance of the bow shock identification algorithm were tested using known bow shock crossing determined manually from January 29, 2002 to February 3,. The verification enabled 70% of the bow shock crossings to be identified automatically. The method shows high flexibility and it can be applied to observations from various spacecraft. Now these tools have been applied to Time History of Events and Macroscale Interactions during Substorms (THEMIS)/Acceleration, Reconnection, Turbulence, and Electrodynamics of the Moon's Interaction with the Sun (ARTEMIS) magnetic field, plasma and spacecraft potential observations to identify bow shock crossings; and to Van Allen Probes supra-thermal electron observations to identify the edges of the radiation belt. The outcomes of the algorithms are checked manually and the parameters used to search for bow shock identification are refined.

Application of the artificial bee colony algorithm for solving the set covering problem.

PubMed

Crawford, Broderick; Soto, Ricardo; Cuesta, Rodrigo; Paredes, Fernando

2014-01-01

The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show that our artificial bee colony algorithm is competitive in terms of solution quality with other recent metaheuristic approaches for the set covering problem.

Application of the Artificial Bee Colony Algorithm for Solving the Set Covering Problem

PubMed Central

Crawford, Broderick; Soto, Ricardo; Cuesta, Rodrigo; Paredes, Fernando

2014-01-01

The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show that our artificial bee colony algorithm is competitive in terms of solution quality with other recent metaheuristic approaches for the set covering problem. PMID:24883356

Public Data Set: Radially Scanning Magnetic Probes to Study Local Helicity Injection Dynamics

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

Richner, Nathan J; Bongard, Michael W; Fonck, Raymond J

This data set contains openly-documented, machine readable digital research data corresponding to figures published in N.J. Richner et al., 'Radially Scanning Magnetic Probes to Study Local Helicity Injection Dynamics,' accepted for publication in Rev. Sci. Instrum (2018).

A nested array of rRNA targeted probes for the detection and identification of enterococci by reverse hybridization.

PubMed

Behr, T; Koob, C; Schedl, M; Mehlen, A; Meier, H; Knopp, D; Frahm, E; Obst, U; Schleifer, K; Niessner, R; Ludwig, W

2000-12-01

Complete 23S and almost complete 16S rRNA gene sequences were determined for the type strains of the validly described Enterococcus species, Melissococcus pluton and Tetragenococcus halophilus. A comprehensive set of rRNA targeted specific oligonucleotide hybridization probes was designed according to the multiple probe concept. In silico probe design and evaluation was performed using the respective tools of the ARB program package in combination with the ARB databases comprising the currently available 16S as well as 23S rRNA primary structures. The probes were optimized with respect to their application for reverse hybridization in microplate format. The target comprising 16S and 23S rDNA was amplified and labeled by PCR (polymerase chain reaction) using general primers targeting a wide spectrum of bacteria. Alternatively, amplification of two adjacent rDNA fragments of enterococci was performed by using specific primers. In vitro evaluation of the probe set was done including all Enterococcus type strains, and a selection of other representatives of the gram-positive bacteria with a low genomic DNA G+C content. The optimized probe set was used to analyze enriched drinking water samples as well as original samples from waste water treatment plants.

Characterizing nanoscale scanning probes using electron microscopy: A novel fixture and a practical guide

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

Jacobs, Tevis D. B., E-mail: tjacobs@pitt.edu; Wabiszewski, Graham E.; Goodman, Alexander J.

2016-01-15

The nanoscale geometry of probe tips used for atomic force microscopy (AFM) measurements determines the lateral resolution, contributes to the strength of the tip-surface interaction, and can be a significant source of uncertainty in the quantitative analysis of results. While inverse imaging of the probe tip has been used successfully to determine probe tip geometry, direct observation of the tip profile using electron microscopy (EM) confers several advantages: it provides direct (rather than indirect) imaging, requires fewer algorithmic parameters, and does not require bringing the tip into contact with a sample. In the past, EM-based observation of the probe tipmore » has been achieved using ad hoc mounting methods that are constrained by low throughput, the risk of contamination, and repeatability issues. We report on a probe fixture designed for use in a commercial transmission electron microscope that enables repeatable mounting of multiple AFM probes as well as a reference grid for beam alignment. This communication describes the design, fabrication, and advantages of this probe fixture, including full technical drawings for machining. Further, best practices are discussed for repeatable, non-destructive probe imaging. Finally, examples of the fixture’s use are described, including characterization of common commercial AFM probes in their out-of-the-box condition.« less

Characterizing nanoscale scanning probes using electron microscopy: A novel fixture and a practical guide

NASA Astrophysics Data System (ADS)

Jacobs, Tevis D. B.; Wabiszewski, Graham E.; Goodman, Alexander J.; Carpick, Robert W.

2016-01-01

The nanoscale geometry of probe tips used for atomic force microscopy (AFM) measurements determines the lateral resolution, contributes to the strength of the tip-surface interaction, and can be a significant source of uncertainty in the quantitative analysis of results. While inverse imaging of the probe tip has been used successfully to determine probe tip geometry, direct observation of the tip profile using electron microscopy (EM) confers several advantages: it provides direct (rather than indirect) imaging, requires fewer algorithmic parameters, and does not require bringing the tip into contact with a sample. In the past, EM-based observation of the probe tip has been achieved using ad hoc mounting methods that are constrained by low throughput, the risk of contamination, and repeatability issues. We report on a probe fixture designed for use in a commercial transmission electron microscope that enables repeatable mounting of multiple AFM probes as well as a reference grid for beam alignment. This communication describes the design, fabrication, and advantages of this probe fixture, including full technical drawings for machining. Further, best practices are discussed for repeatable, non-destructive probe imaging. Finally, examples of the fixture's use are described, including characterization of common commercial AFM probes in their out-of-the-box condition.

Transverse vorticity measurements using an array of four hot-wire probes

NASA Technical Reports Server (NTRS)

Foss, J. F.; Klewickc, C. L.; Disimile, P. J.

1986-01-01

A comprehensive description of the technique used to obtain a time series of the quasi-instantaneous transverse vorticity from a four wire array of probes is presented. The algorithmic structure which supports the technique is described in detail and demonstration data, from a large plane shear layer, are presented to provide a specific utilization of the technique. Sensitivity calculations are provided which allow one contribution to the inherent uncertainty of the technique to be evaluated.

An efficient probe of the cosmological CPT violation

NASA Astrophysics Data System (ADS)

Zhao, Gong-Bo; Wang, Yuting; Xia, Jun-Qing; Li, Mingzhe; Zhang, Xinmin

2015-07-01

We develop an efficient method based on the linear regression algorithm to probe the cosmological CPT violation using the CMB polarisation data. We validate this method using simulated CMB data and apply it to recent CMB observations. We find that a combined data sample of BICEP1 and BOOMERanG 2003 favours a nonzero isotropic rotation angle at 2.3σ confidence level, i.e., bar alpha=-3.3o±1.4o (68% CL) with systematics included.

Adaptive optics compensation of orbital angular momentum beams with a modified Gerchberg-Saxton-based phase retrieval algorithm

NASA Astrophysics Data System (ADS)

Chang, Huan; Yin, Xiao-li; Cui, Xiao-zhou; Zhang, Zhi-chao; Ma, Jian-xin; Wu, Guo-hua; Zhang, Li-jia; Xin, Xiang-jun

2017-12-01

Practical orbital angular momentum (OAM)-based free-space optical (FSO) communications commonly experience serious performance degradation and crosstalk due to atmospheric turbulence. In this paper, we propose a wave-front sensorless adaptive optics (WSAO) system with a modified Gerchberg-Saxton (GS)-based phase retrieval algorithm to correct distorted OAM beams. We use the spatial phase perturbation (SPP) GS algorithm with a distorted probe Gaussian beam as the only input. The principle and parameter selections of the algorithm are analyzed, and the performance of the algorithm is discussed. The simulation results show that the proposed adaptive optics (AO) system can significantly compensate for distorted OAM beams in single-channel or multiplexed OAM systems, which provides new insights into adaptive correction systems using OAM beams.

Improved data reduction algorithm for the needle probe method applied to in-situ thermal conductivity measurements of lunar and planetary regoliths

NASA Astrophysics Data System (ADS)

Nagihara, Seiichi; Hedlund, Magnus; Zacny, Kris; Taylor, Patrick T.

2014-03-01

The needle probe method (also known as the ‘hot wire’ or ‘line heat source’ method) is widely used for in-situ thermal conductivity measurements on terrestrial soils and marine sediments. Variants of this method have also been used (or planned) for measuring regolith on the surfaces of extra-terrestrial bodies (e.g., the Moon, Mars, and comets). In the near-vacuum condition on the lunar and planetary surfaces, the measurement method used on the earth cannot be simply duplicated, because thermal conductivity of the regolith can be ~2 orders of magnitude lower. In addition, the planetary probes have much greater diameters, due to engineering requirements associated with the robotic deployment on extra-terrestrial bodies. All of these factors contribute to the planetary probes requiring a much longer time of measurement, several tens of (if not over a hundred) hours, while a conventional terrestrial needle probe needs only 1 to 2 min. The long measurement time complicates the surface operation logistics of the lander. It also negatively affects accuracy of the thermal conductivity measurement, because the cumulative heat loss along the probe is no longer negligible. The present study improves the data reduction algorithm of the needle probe method by shortening the measurement time on planetary surfaces by an order of magnitude. The main difference between the new scheme and the conventional one is that the former uses the exact mathematical solution to the thermal model on which the needle probe measurement theory is based, while the latter uses an approximate solution that is valid only for large times. The present study demonstrates the benefit of the new data reduction technique by applying it to data from a series of needle probe experiments carried out in a vacuum chamber on a lunar regolith simulant, JSC-1A. The use of the exact solution has some disadvantage, however, in requiring three additional parameters, but two of them (the diameter and the volumetric heat capacity of the probe) can be measured and the other (the volumetric heat capacity of the regolith/stimulant) may be estimated from the surface geologic observation and temperature measurements. Therefore, overall, the new data reduction scheme would make in-situ thermal conductivity measurement more practical on planetary missions.

Improved Data Reduction Algorithm for the Needle Probe Method Applied to In-Situ Thermal Conductivity Measurements of Lunar and Planetary Regoliths

NASA Technical Reports Server (NTRS)

Nagihara, S.; Hedlund, M.; Zacny, K.; Taylor, P. T.

2013-01-01

The needle probe method (also known as the' hot wire' or 'line heat source' method) is widely used for in-situ thermal conductivity measurements on soils and marine sediments on the earth. Variants of this method have also been used (or planned) for measuring regolith on the surfaces of extra-terrestrial bodies (e.g., the Moon, Mars, and comets). In the near-vacuum condition on the lunar and planetary surfaces, the measurement method used on the earth cannot be simply duplicated, because thermal conductivity of the regolith can be approximately 2 orders of magnitude lower. In addition, the planetary probes have much greater diameters, due to engineering requirements associated with the robotic deployment on extra-terrestrial bodies. All of these factors contribute to the planetary probes requiring much longer time of measurement, several tens of (if not over a hundred) hours, while a conventional terrestrial needle probe needs only 1 to 2 minutes. The long measurement time complicates the surface operation logistics of the lander. It also negatively affects accuracy of the thermal conductivity measurement, because the cumulative heat loss along the probe is no longer negligible. The present study improves the data reduction algorithm of the needle probe method by shortening the measurement time on planetary surfaces by an order of magnitude. The main difference between the new scheme and the conventional one is that the former uses the exact mathematical solution to the thermal model on which the needle probe measurement theory is based, while the latter uses an approximate solution that is valid only for large times. The present study demonstrates the benefit of the new data reduction technique by applying it to data from a series of needle probe experiments carried out in a vacuum chamber on JSC-1A lunar regolith stimulant. The use of the exact solution has some disadvantage, however, in requiring three additional parameters, but two of them (the diameter and the volumetric heat capacity of the probe) can be measured and the other (the volumetric heat capacity of the regolith/stimulant) may be estimated from the surface geologic observation and temperature measurements. Therefore, overall, the new data reduction scheme would make in-situ thermal conductivity measurement more practical on planetary missions.

Attentional bias to threat in the general population is contingent on target competition, not on attentional control settings.

PubMed

Wirth, Benedikt Emanuel; Wentura, Dirk

2018-04-01

Dot-probe studies usually find an attentional bias towards threatening stimuli only in anxious participants. Here, we investigated under what conditions such a bias occurs in unselected samples. According to contingent-capture theory, an irrelevant cue only captures attention if it matches an attentional control setting. Therefore, we first tested the hypothesis that an attentional control setting tuned to threat must be activated in (non-anxious) individuals. In Experiment 1, we used a dot-probe task with a manipulation of attentional control settings ('threat' - set vs. control set). Surprisingly, we found an (anxiety-independent) attentional bias to angry faces that was not moderated by attentional control settings. Since we presented two stimuli (i.e., a target and a distractor) on the target screen in Experiment 1 (a necessity to realise the test of contingent capture), but most dot-probe studies only employ a single target, we conducted Experiment 2 to test the hypothesis that attentional bias in the general population is contingent on target competition. Participants performed a dot-probe task, involving presentation of a stand-alone target or a target competing with a distractor. We found an (anxiety-independent) attentional bias towards angry faces in the latter but not the former condition. This suggests that attentional bias towards angry faces in unselected samples is not contingent on attentional control settings but on target competition.

The contour-buildup algorithm to calculate the analytical molecular surface.

PubMed

Totrov, M; Abagyan, R

1996-01-01

A new algorithm is presented to calculate the analytical molecular surface defined as a smooth envelope traced out by the surface of a probe sphere rolled over the molecule. The core of the algorithm is the sequential build up of multi-arc contours on the van der Waals spheres. This algorithm yields substantial reduction in both memory and time requirements of surface calculations. Further, the contour-buildup principle is intrinsically "local", which makes calculations of the partial molecular surfaces even more efficient. Additionally, the algorithm is equally applicable not only to convex patches, but also to concave triangular patches which may have complex multiple intersections. The algorithm permits the rigorous calculation of the full analytical molecular surface for a 100-residue protein in about 2 seconds on an SGI indigo with R4400++ processor at 150 Mhz, with the performance scaling almost linearly with the protein size. The contour-buildup algorithm is faster than the original Connolly algorithm an order of magnitude.

Comparison of sampling techniques for Bayesian parameter estimation

NASA Astrophysics Data System (ADS)

Allison, Rupert; Dunkley, Joanna

2014-02-01

The posterior probability distribution for a set of model parameters encodes all that the data have to tell us in the context of a given model; it is the fundamental quantity for Bayesian parameter estimation. In order to infer the posterior probability distribution we have to decide how to explore parameter space. Here we compare three prescriptions for how parameter space is navigated, discussing their relative merits. We consider Metropolis-Hasting sampling, nested sampling and affine-invariant ensemble Markov chain Monte Carlo (MCMC) sampling. We focus on their performance on toy-model Gaussian likelihoods and on a real-world cosmological data set. We outline the sampling algorithms themselves and elaborate on performance diagnostics such as convergence time, scope for parallelization, dimensional scaling, requisite tunings and suitability for non-Gaussian distributions. We find that nested sampling delivers high-fidelity estimates for posterior statistics at low computational cost, and should be adopted in favour of Metropolis-Hastings in many cases. Affine-invariant MCMC is competitive when computing clusters can be utilized for massive parallelization. Affine-invariant MCMC and existing extensions to nested sampling naturally probe multimodal and curving distributions.

Tissue Gene Expression Analysis Using Arrayed Normalized cDNA Libraries

PubMed Central

Eickhoff, Holger; Schuchhardt, Johannes; Ivanov, Igor; Meier-Ewert, Sebastian; O'Brien, John; Malik, Arif; Tandon, Neeraj; Wolski, Eryk-Witold; Rohlfs, Elke; Nyarsik, Lajos; Reinhardt, Richard; Nietfeld, Wilfried; Lehrach, Hans

2000-01-01

We have used oligonucleotide-fingerprinting data on 60,000 cDNA clones from two different mouse embryonic stages to establish a normalized cDNA clone set. The normalized set of 5,376 clones represents different clusters and therefore, in almost all cases, different genes. The inserts of the cDNA clones were amplified by PCR and spotted on glass slides. The resulting arrays were hybridized with mRNA probes prepared from six different adult mouse tissues. Expression profiles were analyzed by hierarchical clustering techniques. We have chosen radioactive detection because it combines robustness with sensitivity and allows the comparison of multiple normalized experiments. Sensitive detection combined with highly effective clustering algorithms allowed the identification of tissue-specific expression profiles and the detection of genes specifically expressed in the tissues investigated. The obtained results are publicly available (http://www.rzpd.de) and can be used by other researchers as a digital expression reference. [The sequence data described in this paper have been submitted to the EMBL data library under accession nos. AL360374–AL36537.] PMID:10958641

Universal Oligonucleotide Microarray for Sub-Typing of Influenza A Virus

PubMed Central

Ryabinin, Vladimir A.; Kostina, Elena V.; Maksakova, Galiya A.; Neverov, Alexander A.; Chumakov, Konstantin M.; Sinyakov, Alexander N.

2011-01-01

A universal microchip was developed for genotyping Influenza A viruses. It contains two sets of oligonucleotide probes allowing viruses to be classified by the subtypes of hemagglutinin (H1–H13, H15, H16) and neuraminidase (N1–N9). Additional sets of probes are used to detect H1N1 swine influenza viruses. Selection of probes was done in two steps. Initially, amino acid sequences specific to each subtype were identified, and then the most specific and representative oligonucleotide probes were selected. Overall, between 19 and 24 probes were used to identify each subtype of hemagglutinin (HA) and neuraminidase (NA). Genotyping included preparation of fluorescently labeled PCR amplicons of influenza virus cDNA and their hybridization to microarrays of specific oligonucleotide probes. Out of 40 samples tested, 36 unambiguously identified HA and NA subtypes of Influenza A virus. PMID:21559081

Difference in thermodynamics between two types of esophageal temperature probes: Insights from an experimental study.

PubMed

Gianni, Carola; Atoui, Moustapha; Mohanty, Sanghamitra; Trivedi, Chintan; Bai, Rong; Al-Ahmad, Amin; Burkhardt, J David; Gallinghouse, G Joseph; Hranitzky, Patrick M; Horton, Rodney P; Sanchez, Javier E; Di Biase, Luigi; Lakkireddy, Dhanunjaya R; Natale, Andrea

2016-11-01

Luminal esophageal temperature monitoring is performed with a variety of temperature probes, but little is known about the relationship between the structure of a given probe and its thermodynamic characteristics. The purpose of this study was to evaluate the difference in thermodynamics between a 9Fr standard esophageal probe and an 18Fr esophageal stethoscope. In the experimental setting, each probe was submerged in a constant temperature water bath maintained at 42°C; in the patient setting, we monitored the temperature with both probes at the same time. The time constant of the stethoscope was higher than that of the probe (33.5 vs 8.3 s). Compared to the probe, the mean temperature measured by the stethoscope at 10 seconds was significantly lower (22.5°C ± 0.4°C vs 33.5°C ± 0.3°C, P<.0001), whereas the time to reach the peak temperature was significantly longer (132.6 ± 5.9 s vs 38.8 ± 1.0 s, P<.0001). Even in the ablation cases we observed that when the esophageal probe reached a peak temperature of 39.6°C ± 0.3°C, the esophageal stethoscope still displayed a temperature of 37.3°C ± 0.2°C (a mean of 2.39°C ± 0.3°C lower, P<.0001), showing a <0.5°C increase in temperature half of the times. The 18Fr esophageal stethoscope has a significantly slower time response compared to the 9Fr esophageal probe. In the clinical setting, this might result in a considerable underestimation of the luminal esophageal temperature with potentially fatal consequences. Copyright © 2016 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Persistence of Microbial Contamination on Transvaginal Ultrasound Probes despite Low-Level Disinfection Procedure

PubMed Central

M'Zali, Fatima; Bounizra, Carole; Leroy, Sandrine; Mekki, Yahia; Quentin-Noury, Claudine; Kann, Michael

2014-01-01

Aim of the Study In many countries, Low Level Disinfection (LLD) of covered transvaginal ultrasound probes is recommended between patients' examinations. The aim of this study was to evaluate the antimicrobial efficacy of LLD under routine conditions on a range of microorganisms. Materials and Methods Samples were taken over a six month period in a private French Radiology Center. 300 specimens derived from endovaginal ultrasound probes were analyzed after disinfection of the probe with wipes impregnated with a quaternary ammonium compound and chlorhexidine. Human papillomavirus (HPV) was sought in the first set of s100 samples, Chlamydia trachomatis and mycoplasmas were searched in the second set of 100 samples, bacteria and fungi in the third 100 set samples. HPV, C. trachomatis and mycoplasmas were detected by PCR amplification. PCR positive samples were subjected to a nuclease treatment before an additional PCR assay to assess the likely viable microorganisms. Bacteria and fungi were investigated by conventional methods. Results A substantial persistence of microorganisms was observed on the disinfected probes: HPV DNA was found on 13% of the samples and 7% in nuclease-resistant form. C. trachomatis DNA was detected on 20% of the probes by primary PCR but only 2% after nuclease treatment, while mycoplasma DNA was amplified in 8% and 4%, respectively. Commensal and/or environmental bacterial flora was present on 86% of the probes, occasionally in mixed culture, and at various levels (10->3000 CFU/probe); Staphylococcus aureus was cultured from 4% of the probes (10-560 CFU/probe). No fungi were isolated. Conclusion Our findings raise concerns about the efficacy of impregnated towels as a sole mean for disinfection of ultrasound probes. Although the ultrasound probes are used with disposable covers, our results highlight the potential risk of cross contamination between patients during ultrasound examination and emphasize the need for reviewing the disinfection procedure. PMID:24695371

probeBase—an online resource for rRNA-targeted oligonucleotide probes and primers: new features 2016

PubMed Central

Greuter, Daniel; Loy, Alexander; Horn, Matthias; Rattei, Thomas

2016-01-01

probeBase http://www.probebase.net is a manually maintained and curated database of rRNA-targeted oligonucleotide probes and primers. Contextual information and multiple options for evaluating in silico hybridization performance against the most recent rRNA sequence databases are provided for each oligonucleotide entry, which makes probeBase an important and frequently used resource for microbiology research and diagnostics. Here we present a major update of probeBase, which was last featured in the NAR Database Issue 2007. This update describes a complete remodeling of the database architecture and environment to accommodate computationally efficient access. Improved search functions, sequence match tools and data output now extend the opportunities for finding suitable hierarchical probe sets that target an organism or taxon at different taxonomic levels. To facilitate the identification of complementary probe sets for organisms represented by short rRNA sequence reads generated by amplicon sequencing or metagenomic analysis with next generation sequencing technologies such as Illumina and IonTorrent, we introduce a novel tool that recovers surrogate near full-length rRNA sequences for short query sequences and finds matching oligonucleotides in probeBase. PMID:26586809

Parallel Clustering Algorithm for Large-Scale Biological Data Sets

PubMed Central

Wang, Minchao; Zhang, Wu; Ding, Wang; Dai, Dongbo; Zhang, Huiran; Xie, Hao; Chen, Luonan; Guo, Yike; Xie, Jiang

2014-01-01

Backgrounds Recent explosion of biological data brings a great challenge for the traditional clustering algorithms. With increasing scale of data sets, much larger memory and longer runtime are required for the cluster identification problems. The affinity propagation algorithm outperforms many other classical clustering algorithms and is widely applied into the biological researches. However, the time and space complexity become a great bottleneck when handling the large-scale data sets. Moreover, the similarity matrix, whose constructing procedure takes long runtime, is required before running the affinity propagation algorithm, since the algorithm clusters data sets based on the similarities between data pairs. Methods Two types of parallel architectures are proposed in this paper to accelerate the similarity matrix constructing procedure and the affinity propagation algorithm. The memory-shared architecture is used to construct the similarity matrix, and the distributed system is taken for the affinity propagation algorithm, because of its large memory size and great computing capacity. An appropriate way of data partition and reduction is designed in our method, in order to minimize the global communication cost among processes. Result A speedup of 100 is gained with 128 cores. The runtime is reduced from serval hours to a few seconds, which indicates that parallel algorithm is capable of handling large-scale data sets effectively. The parallel affinity propagation also achieves a good performance when clustering large-scale gene data (microarray) and detecting families in large protein superfamilies. PMID:24705246

Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

PubMed

Huang, Cai; Mezencev, Roman; McDonald, John F; Vannberg, Fredrik

2017-01-01

Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM) algorithm combined with a standard recursive feature elimination (RFE) approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60). The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be "drivers" of cancer onset/progression. Application of our models to publically available ovarian cancer (OC) patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm "open source", we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.

Drogue detection for vision-based autonomous aerial refueling via low rank and sparse decomposition with multiple features

NASA Astrophysics Data System (ADS)

Gao, Shibo; Cheng, Yongmei; Song, Chunhua

2013-09-01

The technology of vision-based probe-and-drogue autonomous aerial refueling is an amazing task in modern aviation for both manned and unmanned aircraft. A key issue is to determine the relative orientation and position of the drogue and the probe accurately for relative navigation system during the approach phase, which requires locating the drogue precisely. Drogue detection is a challenging task due to disorderly motion of drogue caused by both the tanker wake vortex and atmospheric turbulence. In this paper, the problem of drogue detection is considered as a problem of moving object detection. A drogue detection algorithm based on low rank and sparse decomposition with local multiple features is proposed. The global and local information of drogue is introduced into the detection model in a unified way. The experimental results on real autonomous aerial refueling videos show that the proposed drogue detection algorithm is effective.

Predicting DNA hybridization kinetics from sequence

NASA Astrophysics Data System (ADS)

Zhang, Jinny X.; Fang, John Z.; Duan, Wei; Wu, Lucia R.; Zhang, Angela W.; Dalchau, Neil; Yordanov, Boyan; Petersen, Rasmus; Phillips, Andrew; Zhang, David Yu

2018-01-01

Hybridization is a key molecular process in biology and biotechnology, but so far there is no predictive model for accurately determining hybridization rate constants based on sequence information. Here, we report a weighted neighbour voting (WNV) prediction algorithm, in which the hybridization rate constant of an unknown sequence is predicted based on similarity reactions with known rate constants. To construct this algorithm we first performed 210 fluorescence kinetics experiments to observe the hybridization kinetics of 100 different DNA target and probe pairs (36 nt sub-sequences of the CYCS and VEGF genes) at temperatures ranging from 28 to 55 °C. Automated feature selection and weighting optimization resulted in a final six-feature WNV model, which can predict hybridization rate constants of new sequences to within a factor of 3 with ∼91% accuracy, based on leave-one-out cross-validation. Accurate prediction of hybridization kinetics allows the design of efficient probe sequences for genomics research.

Accretion of satellites on to central galaxies in clusters: merger mass ratios and orbital parameters

NASA Astrophysics Data System (ADS)

Nipoti, Carlo; Giocoli, Carlo; Despali, Giulia

2018-05-01

We study the statistical properties of mergers between central and satellite galaxies in galaxy clusters in the redshift range 0 < z < 1, using a sample of dark-matter only cosmological N-body simulations from Le SBARBINE data set. Using a spherical overdensity algorithm to identify dark-matter haloes, we construct halo merger trees for different values of the overdensity Δc. While the virial overdensity definition allows us to probe the accretion of satellites at the cluster virial radius rvir, higher overdensities probe satellite mergers in the central region of the cluster, down to ≈0.06rvir, which can be considered a proxy for the accretion of satellite galaxies on to central galaxies. We find that the characteristic merger mass ratio increases for increasing values of Δc: more than 60 per cent of the mass accreted by central galaxies since z ≈ 1 comes from major mergers. The orbits of satellites accreting on to central galaxies tend to be more tangential and more bound than orbits of haloes accreting at the virial radius. The obtained distributions of merger mass ratios and orbital parameters are useful to model the evolution of the high-mass end of the galaxy scaling relations without resorting to hydrodynamic cosmological simulations.

Distributed shared memory for roaming large volumes.

PubMed

Castanié, Laurent; Mion, Christophe; Cavin, Xavier; Lévy, Bruno

2006-01-01

We present a cluster-based volume rendering system for roaming very large volumes. This system allows to move a gigabyte-sized probe inside a total volume of several tens or hundreds of gigabytes in real-time. While the size of the probe is limited by the total amount of texture memory on the cluster, the size of the total data set has no theoretical limit. The cluster is used as a distributed graphics processing unit that both aggregates graphics power and graphics memory. A hardware-accelerated volume renderer runs in parallel on the cluster nodes and the final image compositing is implemented using a pipelined sort-last rendering algorithm. Meanwhile, volume bricking and volume paging allow efficient data caching. On each rendering node, a distributed hierarchical cache system implements a global software-based distributed shared memory on the cluster. In case of a cache miss, this system first checks page residency on the other cluster nodes instead of directly accessing local disks. Using two Gigabit Ethernet network interfaces per node, we accelerate data fetching by a factor of 4 compared to directly accessing local disks. The system also implements asynchronous disk access and texture loading, which makes it possible to overlap data loading, volume slicing and rendering for optimal volume roaming.

ProbeDesigner: for the design of probesets for branched DNA (bDNA) signal amplification assays.

PubMed

Bushnell, S; Budde, J; Catino, T; Cole, J; Derti, A; Kelso, R; Collins, M L; Molino, G; Sheridan, P; Monahan, J; Urdea, M

1999-05-01

The sensitivity and specificity of branched DNA (bDNA) assays are derived in part through the judicious design of the capture and label extender probes. To minimize non-specific hybridization (NSH) events, which elevate assay background, candidate probes must be computer screened for complementarity with generic sequences present in the assay. We present a software application which allows for rapid and flexible design of bDNA probesets for novel targets. It includes an algorithm for estimating the magnitude of NSH contribution to background, a mechanism for removing probes with elevated contributions, a methodology for the simultaneous design of probesets for multiple targets, and a graphical user interface which guides the user through the design steps. The program is available as a commercial package through the Pharmaceutical Drug Discovery program at Chiron Diagnostics.

Restoring the lattice of Si-based atom probe reconstructions for enhanced information on dopant positioning.

PubMed

Breen, Andrew J; Moody, Michael P; Ceguerra, Anna V; Gault, Baptiste; Araullo-Peters, Vicente J; Ringer, Simon P

2015-12-01

The following manuscript presents a novel approach for creating lattice based models of Sb-doped Si directly from atom probe reconstructions for the purposes of improving information on dopant positioning and directly informing quantum mechanics based materials modeling approaches. Sophisticated crystallographic analysis techniques are used to detect latent crystal structure within the atom probe reconstructions with unprecedented accuracy. A distortion correction algorithm is then developed to precisely calibrate the detected crystal structure to the theoretically known diamond cubic lattice. The reconstructed atoms are then positioned on their most likely lattice positions. Simulations are then used to determine the accuracy of such an approach and show that improvements to short-range order measurements are possible for noise levels and detector efficiencies comparable with experimentally collected atom probe data. Copyright © 2015 Elsevier B.V. All rights reserved.

Use of molecular techniques to evaluate the survival of a microorganism injected into an aquifer

USGS Publications Warehouse

Thiem, S.M.; Krumme, M.L.; Smith, R.L.; Tiedje, J.M.

1994-01-01

A PCR primer set and an internal probe that are specific for Pseudomonas sp. strain B13, a 3-chlorobenzoate-metabolizing strain, were developed. Using this primer set and probe, we were able to detect Pseudomonas sp. strain B13 DNA sequences in DNA extracted from aquifer samples 14.5 months after Pseudomonas sp. strain B13 had been injected into a sand and gravel aquifer. This primer set and probe were also used to analyze isolates from 3-chlorobenzoate enrichments of the aquifer samples by Southern blot analysis. Hybridization of Southern blots with the Pseudomonas sp. strain B13-specific probe and a catabolic probe in conjunction with restriction fragment length polymorphism (RFLP) analysis of ribosome genes was used to determine that viable Pseudomonas sp. strain B13 persisted in this environment. We isolated a new 3-chlorobenzoate-degrading strain from one of these enrichment cultures. The B13-specific probe does not hybridize to DNA from this isolate. The new strain could be the result of gene exchange between Pseudomonas sp. strain B13 and an indigenous bacterium. This speculation is based on an RFLP pattern of ribosome genes that differs from that of Pseudomonas sp. strain B13, the fact that identically sized restriction fragments hybridized to the catabolic gene probe, and the absence of any enrichable 3-chlorobenzoate-degrading strains in the aquifer prior to inoculation.

Optimizing doped libraries by using genetic algorithms

NASA Astrophysics Data System (ADS)

Tomandl, Dirk; Schober, Andreas; Schwienhorst, Andreas

1997-01-01

The insertion of random sequences into protein-encoding genes in combination with biologicalselection techniques has become a valuable tool in the design of molecules that have usefuland possibly novel properties. By employing highly effective screening protocols, a functionaland unique structure that had not been anticipated can be distinguished among a hugecollection of inactive molecules that together represent all possible amino acid combinations.This technique is severely limited by its restriction to a library of manageable size. Oneapproach for limiting the size of a mutant library relies on `doping schemes', where subsetsof amino acids are generated that reveal only certain combinations of amino acids in a proteinsequence. Three mononucleotide mixtures for each codon concerned must be designed, suchthat the resulting codons that are assembled during chemical gene synthesis represent thedesired amino acid mixture on the level of the translated protein. In this paper we present adoping algorithm that `reverse translates' a desired mixture of certain amino acids into threemixtures of mononucleotides. The algorithm is designed to optimally bias these mixturestowards the codons of choice. This approach combines a genetic algorithm with localoptimization strategies based on the downhill simplex method. Disparate relativerepresentations of all amino acids (and stop codons) within a target set can be generated.Optional weighing factors are employed to emphasize the frequencies of certain amino acidsand their codon usage, and to compensate for reaction rates of different mononucleotidebuilding blocks (synthons) during chemical DNA synthesis. The effect of statistical errors thataccompany an experimental realization of calculated nucleotide mixtures on the generatedmixtures of amino acids is simulated. These simulations show that the robustness of differentoptima with respect to small deviations from calculated values depends on their concomitantfitness. Furthermore, the calculations probe the fitness landscape locally and allow apreliminary assessment of its structure.

Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm.

PubMed

Sharifahmadian, Ershad

2006-01-01

The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.

Mechanism-based biomarker gene sets for glutathione depletion-related hepatotoxicity in rats

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

Gao Weihua; Mizukawa, Yumiko; Nakatsu, Noriyuki

Chemical-induced glutathione depletion is thought to be caused by two types of toxicological mechanisms: PHO-type glutathione depletion [glutathione conjugated with chemicals such as phorone (PHO) or diethyl maleate (DEM)], and BSO-type glutathione depletion [i.e., glutathione synthesis inhibited by chemicals such as L-buthionine-sulfoximine (BSO)]. In order to identify mechanism-based biomarker gene sets for glutathione depletion in rat liver, male SD rats were treated with various chemicals including PHO (40, 120 and 400 mg/kg), DEM (80, 240 and 800 mg/kg), BSO (150, 450 and 1500 mg/kg), and bromobenzene (BBZ, 10, 100 and 300 mg/kg). Liver samples were taken 3, 6, 9 andmore » 24 h after administration and examined for hepatic glutathione content, physiological and pathological changes, and gene expression changes using Affymetrix GeneChip Arrays. To identify differentially expressed probe sets in response to glutathione depletion, we focused on the following two courses of events for the two types of mechanisms of glutathione depletion: a) gene expression changes occurring simultaneously in response to glutathione depletion, and b) gene expression changes after glutathione was depleted. The gene expression profiles of the identified probe sets for the two types of glutathione depletion differed markedly at times during and after glutathione depletion, whereas Srxn1 was markedly increased for both types as glutathione was depleted, suggesting that Srxn1 is a key molecule in oxidative stress related to glutathione. The extracted probe sets were refined and verified using various compounds including 13 additional positive or negative compounds, and they established two useful marker sets. One contained three probe sets (Akr7a3, Trib3 and Gstp1) that could detect conjugation-type glutathione depletors any time within 24 h after dosing, and the other contained 14 probe sets that could detect glutathione depletors by any mechanism. These two sets, with appropriate scoring systems, could be promising biomarkers for preclinical examination of hepatotoxicity.« less

"Gap hunting" to characterize clustered probe signals in Illumina methylation array data.

PubMed

Andrews, Shan V; Ladd-Acosta, Christine; Feinberg, Andrew P; Hansen, Kasper D; Fallin, M Daniele

2016-01-01

The Illumina 450k array has been widely used in epigenetic association studies. Current quality-control (QC) pipelines typically remove certain sets of probes, such as those containing a SNP or with multiple mapping locations. An additional set of potentially problematic probes are those with DNA methylation distributions characterized by two or more distinct clusters separated by gaps. Data-driven identification of such probes may offer additional insights for downstream analyses. We developed a procedure, termed "gap hunting," to identify probes showing clustered distributions. Among 590 peripheral blood samples from the Study to Explore Early Development, we identified 11,007 "gap probes." The vast majority (9199) are likely attributed to an underlying SNP(s) or other variant in the probe, although SNP-affected probes exist that do not produce a gap signals. Specific factors predict which SNPs lead to gap signals, including type of nucleotide change, probe type, DNA strand, and overall methylation state. These expected effects are demonstrated in paired genotype and 450k data on the same samples. Gap probes can also serve as a surrogate for the local genetic sequence on a haplotype scale and can be used to adjust for population stratification. The characteristics of gap probes reflect potentially informative biology. QC pipelines may benefit from an efficient data-driven approach that "flags" gap probes, rather than filtering such probes, followed by careful interpretation of downstream association analyses. Our results should translate directly to the recently released Illumina EPIC array given the similar chemistry and content design.

Efficient bulk-loading of gridfiles

NASA Technical Reports Server (NTRS)

Leutenegger, Scott T.; Nicol, David M.

1994-01-01

This paper considers the problem of bulk-loading large data sets for the gridfile multiattribute indexing technique. We propose a rectilinear partitioning algorithm that heuristically seeks to minimize the size of the gridfile needed to ensure no bucket overflows. Empirical studies on both synthetic data sets and on data sets drawn from computational fluid dynamics applications demonstrate that our algorithm is very efficient, and is able to handle large data sets. In addition, we present an algorithm for bulk-loading data sets too large to fit in main memory. Utilizing a sort of the entire data set it creates a gridfile without incurring any overflows.

Hybrid approach for detection of dental caries based on the methods FCM and level sets

NASA Astrophysics Data System (ADS)

Chaabene, Marwa; Ben Ali, Ramzi; Ejbali, Ridha; Zaied, Mourad

2017-03-01

This paper presents a new technique for detection of dental caries that is a bacterial disease that destroys the tooth structure. In our approach, we have achieved a new segmentation method that combines the advantages of fuzzy C mean algorithm and level set method. The results obtained by the FCM algorithm will be used by Level sets algorithm to reduce the influence of the noise effect on the working of each of these algorithms, to facilitate level sets manipulation and to lead to more robust segmentation. The sensitivity and specificity confirm the effectiveness of proposed method for caries detection.

The improved Apriori algorithm based on matrix pruning and weight analysis

NASA Astrophysics Data System (ADS)

Lang, Zhenhong

2018-04-01

This paper uses the matrix compression algorithm and weight analysis algorithm for reference and proposes an improved matrix pruning and weight analysis Apriori algorithm. After the transactional database is scanned for only once, the algorithm will construct the boolean transaction matrix. Through the calculation of one figure in the rows and columns of the matrix, the infrequent item set is pruned, and a new candidate item set is formed. Then, the item's weight and the transaction's weight as well as the weight support for items are calculated, thus the frequent item sets are gained. The experimental result shows that the improved Apriori algorithm not only reduces the number of repeated scans of the database, but also improves the efficiency of data correlation mining.

Multiplex real-time PCR assays for the identification of the potato cyst and tobacco cyst nematodes

USDA-ARS?s Scientific Manuscript database

TaqMan primer-probe sets were developed for the detection and identification of potato cyst nematodes (PCN) Globodera pallida and G. rostochiensis using two-tube, multiplex real-time PCR. One tube contained a primer-probe set specific for G. pallida (pale cyst nematode) multiplexed with another prim...

PROBES FOR THE SPECIFIC DETECTION OF CRYPTOSPORIDIUM PARVUM

EPA Science Inventory

A probe set, consisting of two synthetic oligonucleotides each tagged with a fluorescent reporter molecule, has been developed for specific detection of Cryptosporidium parvum.Each probe strand detects ribosomal RNA from a range of isolates of this species, and the combination is...

Model development and validation of geometrically complex eddy current coils using finite element methods

NASA Astrophysics Data System (ADS)

Brown, Alexander; Eviston, Connor

2017-02-01

Multiple FEM models of complex eddy current coil geometries were created and validated to calculate the change of impedance due to the presence of a notch. Capable realistic simulations of eddy current inspections are required for model assisted probability of detection (MAPOD) studies, inversion algorithms, experimental verification, and tailored probe design for NDE applications. An FEM solver was chosen to model complex real world situations including varying probe dimensions and orientations along with complex probe geometries. This will also enable creation of a probe model library database with variable parameters. Verification and validation was performed using other commercially available eddy current modeling software as well as experimentally collected benchmark data. Data analysis and comparison showed that the created models were able to correctly model the probe and conductor interactions and accurately calculate the change in impedance of several experimental scenarios with acceptable error. The promising results of the models enabled the start of an eddy current probe model library to give experimenters easy access to powerful parameter based eddy current models for alternate project applications.

Phase-Based Adaptive Estimation of Magnitude-Squared Coherence Between Turbofan Internal Sensors and Far-Field Microphone Signals

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2015-01-01

A cross-power spectrum phase based adaptive technique is discussed which iteratively determines the time delay between two digitized signals that are coherent. The adaptive delay algorithm belongs to a class of algorithms that identifies a minimum of a pattern matching function. The algorithm uses a gradient technique to find the value of the adaptive delay that minimizes a cost function based in part on the slope of a linear function that fits the measured cross power spectrum phase and in part on the standard error of the curve fit. This procedure is applied to data from a Honeywell TECH977 static-engine test. Data was obtained using a combustor probe, two turbine exit probes, and far-field microphones. Signals from this instrumentation are used estimate the post-combustion residence time in the combustor. Comparison with previous studies of the post-combustion residence time validates this approach. In addition, the procedure removes the bias due to misalignment of signals in the calculation of coherence which is a first step in applying array processing methods to the magnitude squared coherence data. The procedure also provides an estimate of the cross-spectrum phase-offset.

A background correction algorithm for Van Allen Probes MagEIS electron flux measurements

DOE PAGES

Claudepierre, S. G.; O'Brien, T. P.; Blake, J. B.; ...

2015-07-14

We describe an automated computer algorithm designed to remove background contamination from the Van Allen Probes Magnetic Electron Ion Spectrometer (MagEIS) electron flux measurements. We provide a detailed description of the algorithm with illustrative examples from on-orbit data. We find two primary sources of background contamination in the MagEIS electron data: inner zone protons and bremsstrahlung X-rays generated by energetic electrons interacting with the spacecraft material. Bremsstrahlung X-rays primarily produce contamination in the lower energy MagEIS electron channels (~30–500 keV) and in regions of geospace where multi-M eV electrons are present. Inner zone protons produce contamination in all MagEIS energymore » channels at roughly L < 2.5. The background-corrected MagEIS electron data produce a more accurate measurement of the electron radiation belts, as most earlier measurements suffer from unquantifiable and uncorrectable contamination in this harsh region of the near-Earth space environment. These background-corrected data will also be useful for spacecraft engineering purposes, providing ground truth for the near-Earth electron environment and informing the next generation of spacecraft design models (e.g., AE9).« less

A Compact VLSI System for Bio-Inspired Visual Motion Estimation.

PubMed

Shi, Cong; Luo, Gang

2018-04-01

This paper proposes a bio-inspired visual motion estimation algorithm based on motion energy, along with its compact very-large-scale integration (VLSI) architecture using low-cost embedded systems. The algorithm mimics motion perception functions of retina, V1, and MT neurons in a primate visual system. It involves operations of ternary edge extraction, spatiotemporal filtering, motion energy extraction, and velocity integration. Moreover, we propose the concept of confidence map to indicate the reliability of estimation results on each probing location. Our algorithm involves only additions and multiplications during runtime, which is suitable for low-cost hardware implementation. The proposed VLSI architecture employs multiple (frame, pixel, and operation) levels of pipeline and massively parallel processing arrays to boost the system performance. The array unit circuits are optimized to minimize hardware resource consumption. We have prototyped the proposed architecture on a low-cost field-programmable gate array platform (Zynq 7020) running at 53-MHz clock frequency. It achieved 30-frame/s real-time performance for velocity estimation on 160 × 120 probing locations. A comprehensive evaluation experiment showed that the estimated velocity by our prototype has relatively small errors (average endpoint error < 0.5 pixel and angular error < 10°) for most motion cases.

Human versus Robots in the Discovery and Crystallization of Gigantic Polyoxometalates.

PubMed

Duros, Vasilios; Grizou, Jonathan; Xuan, Weimin; Hosni, Zied; Long, De-Liang; Miras, Haralampos N; Cronin, Leroy

2017-08-28

The discovery of new gigantic molecules formed by self-assembly and crystal growth is challenging as it combines two contingent events; first is the formation of a new molecule, and second its crystallization. Herein, we construct a workflow that can be followed manually or by a robot to probe the envelope of both events and employ it for a new polyoxometalate cluster, Na 6 [Mo 120 Ce 6 O 366 H 12 (H 2 O) 78 ]⋅200 H 2 O (1) which has a trigonal-ring type architecture (yield 4.3 % based on Mo). Its synthesis and crystallization was probed using an active machine-learning algorithm developed by us to explore the crystallization space, the algorithm results were compared with those obtained by human experimenters. The algorithm-based search is able to cover ca. 9 times more crystallization space than a random search and ca. 6 times more than humans and increases the crystallization prediction accuracy to 82.4±0.7 % over 77.1±0.9 % from human experimenters. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Automated Non-Destructive Testing Array Evaluation System

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

Wei, T; Zavaljevski, N; Bakhtiari, S

2004-12-24

Automated Non-Destructive Testing Array Evaluation System (ANTARES) sofeware alogrithms were developed for use on X-probe(tm) data. Data used for algorithm development and preliminary perfomance determination was obtained for USNRC mock-up at Argone and data from EPRI.

Noniterative algorithm for improving the accuracy of a multicolor-light-emitting-diode-based colorimeter.

PubMed

Yang, Pao-Keng

2012-05-01

We present a noniterative algorithm to reliably reconstruct the spectral reflectance from discrete reflectance values measured by using multicolor light emitting diodes (LEDs) as probing light sources. The proposed algorithm estimates the spectral reflectance by a linear combination of product functions of the detector's responsivity function and the LEDs' line-shape functions. After introducing suitable correction, the resulting spectral reflectance was found to be free from the spectral-broadening effect due to the finite bandwidth of LED. We analyzed the data for a real sample and found that spectral reflectance with enhanced resolution gives a more accurate prediction in the color measurement.

Noniterative algorithm for improving the accuracy of a multicolor-light-emitting-diode-based colorimeter

NASA Astrophysics Data System (ADS)

Yang, Pao-Keng

2012-05-01

We present a noniterative algorithm to reliably reconstruct the spectral reflectance from discrete reflectance values measured by using multicolor light emitting diodes (LEDs) as probing light sources. The proposed algorithm estimates the spectral reflectance by a linear combination of product functions of the detector's responsivity function and the LEDs' line-shape functions. After introducing suitable correction, the resulting spectral reflectance was found to be free from the spectral-broadening effect due to the finite bandwidth of LED. We analyzed the data for a real sample and found that spectral reflectance with enhanced resolution gives a more accurate prediction in the color measurement.

PCR Amplicon Prediction from Multiplex Degenerate Primer and Probe Sets

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

Gardner, S. N.

2013-08-08

Assessing primer specificity and predicting both desired and off-target amplification products is an essential step for robust PCR assay design. Code is described to predict potential polymerase chain reaction (PCR) amplicons in a large sequence database such as NCBI nt from either singleplex or a large multiplexed set of primers, allowing degenerate primer and probe bases, with target mismatch annotates amplicons with gene information automatically downloaded from NCBI, and optionally it can predict whether there are also TaqMan/Luminex probe matches within predicted amplicons.

Hierarchical Order Parameters for Macromolecular Assembly Simulations I: Construction and Dynamical Properties of Order Parameters

PubMed Central

Singharoy, Abhishek; Sereda, Yuriy

2012-01-01

Macromolecular assemblies often display a hierarchical organization of macromolecules or their sub-assemblies. To model this, we have formulated a space warping method that enables capturing overall macromolecular structure and dynamics via a set of coarse-grained order parameters (OPs). This article is the first of two describing the construction and computational implementation of an additional class of OPs that has built into them the hierarchical architecture of macromolecular assemblies. To accomplish this, first, the system is divided into subsystems, each of which is described via a representative set of OPs. Then, a global set of variables is constructed from these subsystem-centered OPs to capture overall system organization. Dynamical properties of the resulting OPs are compared to those of our previous nonhierarchical ones, and implied conceptual and computational advantages are discussed for a 100ns, 2 million atom solvated Human Papillomavirus-like particle simulation. In the second article, the hierarchical OPs are shown to enable a multiscale analysis that starts with the N-atom Liouville equation and yields rigorous Langevin equations of stochastic OP dynamics. The latter is demonstrated via a force-field based simulation algorithm that probes key structural transition pathways, simultaneously accounting for all-atom details and overall structure. PMID:22661911

Solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators.

PubMed

Zhao, Jing; Zong, Haili

2018-01-01

In this paper, we propose parallel and cyclic iterative algorithms for solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators. We also combine the process of cyclic and parallel iterative methods and propose two mixed iterative algorithms. Our several algorithms do not need any prior information about the operator norms. Under mild assumptions, we prove weak convergence of the proposed iterative sequences in Hilbert spaces. As applications, we obtain several iterative algorithms to solve the multiple-set split equality problem.

Probing Reliability of Transport Phenomena Based Heat Transfer and Fluid Flow Analysis in Autogeneous Fusion Welding Process

NASA Astrophysics Data System (ADS)

Bag, S.; de, A.

2010-09-01

The transport phenomena based heat transfer and fluid flow calculations in weld pool require a number of input parameters. Arc efficiency, effective thermal conductivity, and viscosity in weld pool are some of these parameters, values of which are rarely known and difficult to assign a priori based on the scientific principles alone. The present work reports a bi-directional three-dimensional (3-D) heat transfer and fluid flow model, which is integrated with a real number based genetic algorithm. The bi-directional feature of the integrated model allows the identification of the values of a required set of uncertain model input parameters and, next, the design of process parameters to achieve a target weld pool dimension. The computed values are validated with measured results in linear gas-tungsten-arc (GTA) weld samples. Furthermore, a novel methodology to estimate the overall reliability of the computed solutions is also presented.

Bayesian Analysis of the Power Spectrum of the Cosmic Microwave Background

NASA Technical Reports Server (NTRS)

Jewell, Jeffrey B.; Eriksen, H. K.; O'Dwyer, I. J.; Wandelt, B. D.

2005-01-01

There is a wealth of cosmological information encoded in the spatial power spectrum of temperature anisotropies of the cosmic microwave background. The sky, when viewed in the microwave, is very uniform, with a nearly perfect blackbody spectrum at 2.7 degrees. Very small amplitude brightness fluctuations (to one part in a million!!) trace small density perturbations in the early universe (roughly 300,000 years after the Big Bang), which later grow through gravitational instability to the large-scale structure seen in redshift surveys... In this talk, I will discuss a Bayesian formulation of this problem; discuss a Gibbs sampling approach to numerically sampling from the Bayesian posterior, and the application of this approach to the first-year data from the Wilkinson Microwave Anisotropy Probe. I will also comment on recent algorithmic developments for this approach to be tractable for the even more massive data set to be returned from the Planck satellite.

Quantum algorithm for linear regression

NASA Astrophysics Data System (ADS)

Wang, Guoming

2017-07-01

We present a quantum algorithm for fitting a linear regression model to a given data set using the least-squares approach. Differently from previous algorithms which yield a quantum state encoding the optimal parameters, our algorithm outputs these numbers in the classical form. So by running it once, one completely determines the fitted model and then can use it to make predictions on new data at little cost. Moreover, our algorithm works in the standard oracle model, and can handle data sets with nonsparse design matrices. It runs in time poly( log2(N ) ,d ,κ ,1 /ɛ ) , where N is the size of the data set, d is the number of adjustable parameters, κ is the condition number of the design matrix, and ɛ is the desired precision in the output. We also show that the polynomial dependence on d and κ is necessary. Thus, our algorithm cannot be significantly improved. Furthermore, we also give a quantum algorithm that estimates the quality of the least-squares fit (without computing its parameters explicitly). This algorithm runs faster than the one for finding this fit, and can be used to check whether the given data set qualifies for linear regression in the first place.

[Multi-Target Recognition of Internal and External Defects of Potato by Semi-Transmission Hyperspectral Imaging and Manifold Learning Algorithm].

PubMed

Huang, Tao; Li, Xiao-yu; Jin, Rui; Ku, Jing; Xu, Sen-miao; Xu, Meng-ling; Wu, Zhen-zhong; Kong, De-guo

2015-04-01

The present paper put forward a non-destructive detection method which combines semi-transmission hyperspectral imaging technology with manifold learning dimension reduction algorithm and least squares support vector machine (LSSVM) to recognize internal and external defects in potatoes simultaneously. Three hundred fifteen potatoes were bought in farmers market as research object, and semi-transmission hyperspectral image acquisition system was constructed to acquire the hyperspectral images of normal external defects (bud and green rind) and internal defect (hollow heart) potatoes. In order to conform to the actual production, defect part is randomly put right, side and back to the acquisition probe when the hyperspectral images of external defects potatoes are acquired. The average spectrums (390-1,040 nm) were extracted from the region of interests for spectral preprocessing. Then three kinds of manifold learning algorithm were respectively utilized to reduce the dimension of spectrum data, including supervised locally linear embedding (SLLE), locally linear embedding (LLE) and isometric mapping (ISOMAP), the low-dimensional data gotten by manifold learning algorithms is used as model input, Error Correcting Output Code (ECOC) and LSSVM were combined to develop the multi-target classification model. By comparing and analyzing results of the three models, we concluded that SLLE is the optimal manifold learning dimension reduction algorithm, and the SLLE-LSSVM model is determined to get the best recognition rate for recognizing internal and external defects potatoes. For test set data, the single recognition rate of normal, bud, green rind and hollow heart potato reached 96.83%, 86.96%, 86.96% and 95% respectively, and he hybrid recognition rate was 93.02%. The results indicate that combining the semi-transmission hyperspectral imaging technology with SLLE-LSSVM is a feasible qualitative analytical method which can simultaneously recognize the internal and external defects potatoes and also provide technical reference for rapid on-line non-destructive detecting of the internal and external defects potatoes.

Electrophysiological correlates of proactive interference in the 'Recent Probes' verbal working memory task.

PubMed

Zhang, John X; Wu, Renhua; Kong, Lingyue; Weng, Xuchu; Du, Yingchun

2010-06-01

Using event-related potentials (ERPs), the present study examined the temporal dynamics of proactive interference in working memory using a recent probes task. Participants memorized and retained a target set of four letters over a short retention interval. They then responded to a recognition probe by judging whether it was from the memory set. ERP waveforms elicited by positive probes compared to those from negative probes showed positive shifts in a fronto-central early N2 component and a parietal late positive component (LPC). The LPC was identified as the electrophysiological signature of proactive interference, as it differentiated between two types of negative probes defined based on whether they were recently encountered. These results indicate that the proactive interference we observed arises from a mismatch between familiarity and contextual information during recognition memory. When considered together with related studies in the literature, the results also suggest that there are different forms of proactive interference associated with different neural correlates. Copyright 2010 Elsevier Ltd. All rights reserved.

Probabilistic Common Spatial Patterns for Multichannel EEG Analysis

PubMed Central

Chen, Zhe; Gao, Xiaorong; Li, Yuanqing; Brown, Emery N.; Gao, Shangkai

2015-01-01

Common spatial patterns (CSP) is a well-known spatial filtering algorithm for multichannel electroencephalogram (EEG) analysis. In this paper, we cast the CSP algorithm in a probabilistic modeling setting. Specifically, probabilistic CSP (P-CSP) is proposed as a generic EEG spatio-temporal modeling framework that subsumes the CSP and regularized CSP algorithms. The proposed framework enables us to resolve the overfitting issue of CSP in a principled manner. We derive statistical inference algorithms that can alleviate the issue of local optima. In particular, an efficient algorithm based on eigendecomposition is developed for maximum a posteriori (MAP) estimation in the case of isotropic noise. For more general cases, a variational algorithm is developed for group-wise sparse Bayesian learning for the P-CSP model and for automatically determining the model size. The two proposed algorithms are validated on a simulated data set. Their practical efficacy is also demonstrated by successful applications to single-trial classifications of three motor imagery EEG data sets and by the spatio-temporal pattern analysis of one EEG data set recorded in a Stroop color naming task. PMID:26005228

Diffraction modeling of finite subband EFC probing on dark hole contrast with WFIRST-CGI shaped pupil coronagraph

NASA Astrophysics Data System (ADS)

Zhou, Hanying; Krist, John; Nemati, Bijan

2016-08-01

Current coronagraph instrument design (CGI), as a part of a proposed NASA WFIRST (Wide-Field InfraRed Survey Telescope) mission, allocates two subband filters per full science band in order to contain system complexity and cost. We present our detailed investigation results on the adequacy of such limited number of finite subband filters in achieving full band dark hole contrast with shaped pupil coronagraph. The study is based on diffraction propagation modeling with realistic WFIRST optics, where each subband's complex field estimation is obtained, using Electric Field Conjugation (EFC) wavefront sensing / control algorithm, from pairwise pupil plane deformable mirror (DM) probing and image plane intensity averaging of the resulting fields of multiple (subband) wavelengths. Multiple subband choices and probing and control strategies are explored, including standard subband probing; mixed wavelength and/or weighted Jacobian matrix; subband probing with intensity subtraction; and extended subband probing with intensity subtraction. Overall, the investigation shows that the achievable contrast with limited number of finite subband EFC probing is about 2 2.5x worse than the designed post-EFC contrast for current SPC design. The result suggests that for future shaped pupil design, slightly larger over intended full bandwidth should be considered if it will be used with limited subbands for probing.

Analysis of an Optimized MLOS Tomographic Reconstruction Algorithm and Comparison to the MART Reconstruction Algorithm

NASA Astrophysics Data System (ADS)

La Foy, Roderick; Vlachos, Pavlos

2011-11-01

An optimally designed MLOS tomographic reconstruction algorithm for use in 3D PIV and PTV applications is analyzed. Using a set of optimized reconstruction parameters, the reconstructions produced by the MLOS algorithm are shown to be comparable to reconstructions produced by the MART algorithm for a range of camera geometries, camera numbers, and particle seeding densities. The resultant velocity field error calculated using PIV and PTV algorithms is further minimized by applying both pre and post processing to the reconstructed data sets.

Scalable Nearest Neighbor Algorithms for High Dimensional Data.

PubMed

Muja, Marius; Lowe, David G

2014-11-01

For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

MPAI (mass probes aided ionization) method for total analysis of biomolecules by mass spectrometry.

PubMed

Honda, Aki; Hayashi, Shinichiro; Hifumi, Hiroki; Honma, Yuya; Tanji, Noriyuki; Iwasawa, Naoko; Suzuki, Yoshio; Suzuki, Koji

2007-01-01

We have designed and synthesized various mass probes, which enable us to effectively ionize various molecules to be detected with mass spectrometry. We call the ionization method using mass probes the "MPAI (mass probes aided ionization)" method. We aim at the sensitive detection of various biological molecules, and also the detection of bio-molecules by a single mass spectrometry serially without changing the mechanical settings. Here, we review mass probes for small molecules with various functional groups and mass probes for proteins. Further, we introduce newly developed mass probes for proteins for highly sensitive detection.

Stride search: A general algorithm for storm detection in high resolution climate data

DOE PAGES

Bosler, Peter Andrew; Roesler, Erika Louise; Taylor, Mark A.; ...

2015-09-08

This article discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared. The commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. Stride Search is designed to work at all latitudes, while grid point searches may fail in polar regions. Results from the two algorithms are compared for the application of tropicalmore » cyclone detection, and shown to produce similar results for the same set of storm identification criteria. The time required for both algorithms to search the same data set is compared. Furthermore, Stride Search's ability to search extreme latitudes is demonstrated for the case of polar low detection.« less

Fuzzy automata and pattern matching

NASA Technical Reports Server (NTRS)

Setzer, C. B.; Warsi, N. A.

1986-01-01

A wide-ranging search for articles and books concerned with fuzzy automata and syntactic pattern recognition is presented. A number of survey articles on image processing and feature detection were included. Hough's algorithm is presented to illustrate the way in which knowledge about an image can be used to interpret the details of the image. It was found that in hand generated pictures, the algorithm worked well on following the straight lines, but had great difficulty turning corners. An algorithm was developed which produces a minimal finite automaton recognizing a given finite set of strings. One difficulty of the construction is that, in some cases, this minimal automaton is not unique for a given set of strings and a given maximum length. This algorithm compares favorably with other inference algorithms. More importantly, the algorithm produces an automaton with a rigorously described relationship to the original set of strings that does not depend on the algorithm itself.

Distributed Sleep Scheduling in Wireless Sensor Networks via Fractional Domatic Partitioning

NASA Astrophysics Data System (ADS)

Schumacher, André; Haanpää, Harri

We consider setting up sleep scheduling in sensor networks. We formulate the problem as an instance of the fractional domatic partition problem and obtain a distributed approximation algorithm by applying linear programming approximation techniques. Our algorithm is an application of the Garg-Könemann (GK) scheme that requires solving an instance of the minimum weight dominating set (MWDS) problem as a subroutine. Our two main contributions are a distributed implementation of the GK scheme for the sleep-scheduling problem and a novel asynchronous distributed algorithm for approximating MWDS based on a primal-dual analysis of Chvátal's set-cover algorithm. We evaluate our algorithm with ns2 simulations.

Effective traffic features selection algorithm for cyber-attacks samples

NASA Astrophysics Data System (ADS)

Li, Yihong; Liu, Fangzheng; Du, Zhenyu

2018-05-01

By studying the defense scheme of Network attacks, this paper propose an effective traffic features selection algorithm based on k-means++ clustering to deal with the problem of high dimensionality of traffic features which extracted from cyber-attacks samples. Firstly, this algorithm divide the original feature set into attack traffic feature set and background traffic feature set by the clustering. Then, we calculates the variation of clustering performance after removing a certain feature. Finally, evaluating the degree of distinctiveness of the feature vector according to the result. Among them, the effective feature vector is whose degree of distinctiveness exceeds the set threshold. The purpose of this paper is to select out the effective features from the extracted original feature set. In this way, it can reduce the dimensionality of the features so as to reduce the space-time overhead of subsequent detection. The experimental results show that the proposed algorithm is feasible and it has some advantages over other selection algorithms.

Reference set design for relational modeling of fuzzy systems

NASA Astrophysics Data System (ADS)

Lapohos, Tibor; Buchal, Ralph O.

1994-10-01

One of the keys to the successful relational modeling of fuzzy systems is the proper design of fuzzy reference sets. This has been discussed throughout the literature. In the frame of modeling a stochastic system, we analyze the problem numerically. First, we briefly describe the relational model and present the performance of the modeling in the most trivial case: the reference sets are triangle shaped. Next, we present a known fuzzy reference set generator algorithm (FRSGA) which is based on the fuzzy c-means (Fc-M) clustering algorithm. In the second section of this chapter we improve the previous FRSGA by adding a constraint to the Fc-M algorithm (modified Fc-M or MFc-M): two cluster centers are forced to coincide with the domain limits. This is needed to obtain properly shaped extreme linguistic reference values. We apply this algorithm to uniformly discretized domains of the variables involved. The fuzziness of the reference sets produced by both Fc-M and MFc-M is determined by a parameter, which in our experiments is modified iteratively. Each time, a new model is created and its performance analyzed. For certain algorithm parameter values both of these two algorithms have shortcomings. To eliminate the drawbacks of these two approaches, we develop a completely new generator algorithm for reference sets which we call Polyline. This algorithm and its performance are described in the last section. In all three cases, the modeling is performed for a variety of operators used in the inference engine and two defuzzification methods. Therefore our results depend neither on the system model order nor the experimental setup.

Ionosphere Plasma State Determination in Low Earth Orbit from International Space Station Plasma Monitor

NASA Technical Reports Server (NTRS)

Kramer, Leonard

2014-01-01

A plasma diagnostic package is deployed on the International Space Station (ISS). The system - a Floating Potential Measurement Unit (FPMU) - is used by NASA to monitor the electrical floating potential of the vehicle to assure astronaut safety during extravehicular activity. However, data from the unit also reflects the ionosphere state and seems to represent an unutilized scientific resource in the form of an archive of scientific plasma state data. The unit comprises a Floating Potential probe and two Langmuir probes. There is also an unused but active plasma impedance probe. The data, at one second cadence, are collected, typically for a two week period surrounding extravehicular activity events. Data is also collected any time a visiting vehicle docks with ISS and also when any large solar events occur. The telemetry system is unusual because the package is mounted on a television camera stanchion and its data is impressed on a video signal that is transmitted to the ground and streamed by internet to two off center laboratory locations. The data quality has in the past been challenged by weaknesses in the integrated ground station and distribution systems. These issues, since mid-2010, have been largely resolved and the ground stations have been upgraded. Downstream data reduction has been developed using physics based modeling of the electron and ion collecting character in the plasma. Recursive algorithms determine plasma density and temperature from the raw Langmuir probe current voltage sweeps and this is made available in real time for situational awareness. The purpose of this paper is to describe and record the algorithm for data reduction and to show that the Floating probe and Langmuir probes are capable of providing long term plasma state measurement in the ionosphere. Geophysical features such as the Appleton anomaly and high latitude modulation at the edge of the Auroral zones are regularly observed in the nearly circular, 51 deg inclined, 400 km altitude ISS orbit. Evidence of waves in the ion collection current data is seen in geographic zones known to exhibit the spread-F phenomenon. An anomaly in the current collection characteristic of the cylindrical probe appears also too be organized by the geomagnetic field.

Accuracy enhancement of point triangulation probes for linear displacement measurement

NASA Astrophysics Data System (ADS)

Kim, Kyung-Chan; Kim, Jong-Ahn; Oh, SeBaek; Kim, Soo Hyun; Kwak, Yoon Keun

2000-03-01

Point triangulation probes (PTBs) fall into a general category of noncontact height or displacement measurement devices. PTBs are widely used for their simple structure, high resolution, and long operating range. However, there are several factors that must be taken into account in order to obtain high accuracy and reliability; measurement errors from inclinations of an object surface, probe signal fluctuations generated by speckle effects, power variation of a light source, electronic noises, and so on. In this paper, we propose a novel signal processing algorithm, named as EASDF (expanded average square difference function), for a newly designed PTB which is composed of an incoherent source (LED), a line scan array detector, a specially selected diffuse reflecting surface, and several optical components. The EASDF, which is a modified correlation function, is able to calculate displacement between the probe and the object surface effectively even if there are inclinations, power fluctuations, and noises.

Generalization of some hidden subgroup algorithms for input sets of arbitrary size

NASA Astrophysics Data System (ADS)

Poslu, Damla; Say, A. C. Cem

2006-05-01

We consider the problem of generalizing some quantum algorithms so that they will work on input domains whose cardinalities are not necessarily powers of two. When analyzing the algorithms we assume that generating superpositions of arbitrary subsets of basis states whose cardinalities are not necessarily powers of two perfectly is possible. We have taken Ballhysa's model as a template and have extended it to Chi, Kim and Lee's generalizations of the Deutsch-Jozsa algorithm and to Simon's algorithm. With perfectly equal superpositions of input sets of arbitrary size, Chi, Kim and Lee's generalized Deutsch-Jozsa algorithms, both for evenly-distributed and evenly-balanced functions, worked with one-sided error property. For Simon's algorithm the success probability of the generalized algorithm is the same as that of the original for input sets of arbitrary cardinalities with equiprobable superpositions, since the property that the measured strings are all those which have dot product zero with the string we search, for the case where the function is 2-to-1, is not lost.

Ensemble of hybrid genetic algorithm for two-dimensional phase unwrapping

NASA Astrophysics Data System (ADS)

Balakrishnan, D.; Quan, C.; Tay, C. J.

2013-06-01

The phase unwrapping is the final and trickiest step in any phase retrieval technique. Phase unwrapping by artificial intelligence methods (optimization algorithms) such as hybrid genetic algorithm, reverse simulated annealing, particle swarm optimization, minimum cost matching showed better results than conventional phase unwrapping methods. In this paper, Ensemble of hybrid genetic algorithm with parallel populations is proposed to solve the branch-cut phase unwrapping problem. In a single populated hybrid genetic algorithm, the selection, cross-over and mutation operators are applied to obtain new population in every generation. The parameters and choice of operators will affect the performance of the hybrid genetic algorithm. The ensemble of hybrid genetic algorithm will facilitate to have different parameters set and different choice of operators simultaneously. Each population will use different set of parameters and the offspring of each population will compete against the offspring of all other populations, which use different set of parameters. The effectiveness of proposed algorithm is demonstrated by phase unwrapping examples and advantages of the proposed method are discussed.

Ensemble stump classifiers and gene expression signatures in lung cancer.

PubMed

Frey, Lewis; Edgerton, Mary; Fisher, Douglas; Levy, Shawn

2007-01-01

Microarray data sets for cancer tumor tissue generally have very few samples, each sample having thousands of probes (i.e., continuous variables). The sparsity of samples makes it difficult for machine learning techniques to discover probes relevant to the classification of tumor tissue. By combining data from different platforms (i.e., data sources), data sparsity is reduced, but this typically requires normalizing data from the different platforms, which can be non-trivial. This paper proposes a variant on the idea of ensemble learners to circumvent the need for normalization. To facilitate comprehension we build ensembles of very simple classifiers known as decision stumps--decision trees of one test each. The Ensemble Stump Classifier (ESC) identifies an mRNA signature having three probes and high accuracy for distinguishing between adenocarcinoma and squamous cell carcinoma of the lung across four data sets. In terms of accuracy, ESC outperforms a decision tree classifier on all four data sets, outperforms ensemble decision trees on three data sets, and simple stump classifiers on two data sets.

Tomography by iterative convolution - Empirical study and application to interferometry

NASA Technical Reports Server (NTRS)

Vest, C. M.; Prikryl, I.

1984-01-01

An algorithm for computer tomography has been developed that is applicable to reconstruction from data having incomplete projections because an opaque object blocks some of the probing radiation as it passes through the object field. The algorithm is based on iteration between the object domain and the projection (Radon transform) domain. Reconstructions are computed during each iteration by the well-known convolution method. Although it is demonstrated that this algorithm does not converge, an empirically justified criterion for terminating the iteration when the most accurate estimate has been computed is presented. The algorithm has been studied by using it to reconstruct several different object fields with several different opaque regions. It also has been used to reconstruct aerodynamic density fields from interferometric data recorded in wind tunnel tests.

Restoration of high-resolution AFM images captured with broken probes

NASA Astrophysics Data System (ADS)

Wang, Y. F.; Corrigan, D.; Forman, C.; Jarvis, S.; Kokaram, A.

2012-03-01

A type of artefact is induced by damage of the scanning probe when the Atomic Force Microscope (AFM) captures a material surface structure with nanoscale resolution. This artefact has a dramatic form of distortion rather than the traditional blurring artefacts. Practically, it is not easy to prevent the damage of the scanning probe. However, by using natural image deblurring techniques in image processing domain, a comparatively reliable estimation of the real sample surface structure can be generated. This paper introduces a novel Hough Transform technique as well as a Bayesian deblurring algorithm to remove this type of artefact. The deblurring result is successful at removing blur artefacts in the AFM artefact images. And the details of the fibril surface topography are well preserved.

SCENERY: a web application for (causal) network reconstruction from cytometry data

PubMed Central

Papoutsoglou, Georgios; Athineou, Giorgos; Lagani, Vincenzo; Xanthopoulos, Iordanis; Schmidt, Angelika; Éliás, Szabolcs; Tegnér, Jesper

2017-01-01

Abstract Flow and mass cytometry technologies can probe proteins as biological markers in thousands of individual cells simultaneously, providing unprecedented opportunities for reconstructing networks of protein interactions through machine learning algorithms. The network reconstruction (NR) problem has been well-studied by the machine learning community. However, the potentials of available methods remain largely unknown to the cytometry community, mainly due to their intrinsic complexity and the lack of comprehensive, powerful and easy-to-use NR software implementations specific for cytometry data. To bridge this gap, we present Single CEll NEtwork Reconstruction sYstem (SCENERY), a web server featuring several standard and advanced cytometry data analysis methods coupled with NR algorithms in a user-friendly, on-line environment. In SCENERY, users may upload their data and set their own study design. The server offers several data analysis options categorized into three classes of methods: data (pre)processing, statistical analysis and NR. The server also provides interactive visualization and download of results as ready-to-publish images or multimedia reports. Its core is modular and based on the widely-used and robust R platform allowing power users to extend its functionalities by submitting their own NR methods. SCENERY is available at scenery.csd.uoc.gr or http://mensxmachina.org/en/software/. PMID:28525568

The Tropical Rainfall Measuring Mission (TRMM) Progress Report

NASA Technical Reports Server (NTRS)

Simpson, Joanne; Meneghini, Robert; Kummerow, Christian D.; Meneghini, Robert; Hou, Arthur; Adler, Robert F.; Huffman, George; Barkstrom, Bruce; Wielicki, Bruce; Goodman, Steve

1999-01-01

Recognizing the importance of rain in the tropics and the accompanying latent heat release, NASA for the U.S. and NASDA for Japan have partnered in the design, construction and flight of an Earth Probe satellite to measure tropical rainfall and calculate the associated heating. Primary mission goals are 1) the understanding of crucial links in climate variability by the hydrological cycle, 2) improvement in the large-scale models of weather and climate 3) Improvement in understanding cloud ensembles and their impacts on larger scale circulations. The linkage with the tropical oceans and landmasses are also emphasized. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched in November 1997 with fuel enough to obtain a four to five year data set of rainfall over the global tropics from 37'N to 37'S. This paper reports progress from launch date through the spring of 1999. The data system and its products and their access is described, as are the algorithms used to obtain the data. Some exciting early results from TRMM are described. Some important algorithm improvements are shown. These will be used in the first total data reprocessing, scheduled to be complete in early 2000. The reader is given information on how to access and use the data.

The Tropical Rainfall Measuring Mission (TRMM)

NASA Technical Reports Server (NTRS)

Simpson, Joanne; Kummerow, Christian D.; Meneghini, Robert; Hou, Arthur; Adler, Robert F.; Huffman, George; Barkstrom, Bruce; Wielicki, Bruce; Goodman, Steven J.; Christian, Hugh;

CEM-designer: design of custom expression microarrays in the post-ENCODE Era.

PubMed

Arnold, Christian; Externbrink, Fabian; Hackermüller, Jörg; Reiche, Kristin

2014-11-10

Microarrays are widely used in gene expression studies, and custom expression microarrays are popular to monitor expression changes of a customer-defined set of genes. However, the complexity of transcriptomes uncovered recently make custom expression microarray design a non-trivial task. Pervasive transcription and alternative processing of transcripts generate a wealth of interweaved transcripts that requires well-considered probe design strategies and is largely neglected in existing approaches. We developed the web server CEM-Designer that facilitates microarray platform independent design of custom expression microarrays for complex transcriptomes. CEM-Designer covers (i) the collection and generation of a set of unique target sequences from different sources and (ii) the selection of a set of sensitive and specific probes that optimally represents the target sequences. Probe design itself is left to third party software to ensure that probes meet provider-specific constraints. CEM-Designer is available at http://designpipeline.bioinf.uni-leipzig.de. Copyright © 2014 Elsevier B.V. All rights reserved.

One cutting plane algorithm using auxiliary functions

NASA Astrophysics Data System (ADS)

Zabotin, I. Ya; Kazaeva, K. E.

2016-11-01

We propose an algorithm for solving a convex programming problem from the class of cutting methods. The algorithm is characterized by the construction of approximations using some auxiliary functions, instead of the objective function. Each auxiliary function bases on the exterior penalty function. In proposed algorithm the admissible set and the epigraph of each auxiliary function are embedded into polyhedral sets. In connection with the above, the iteration points are found by solving linear programming problems. We discuss the implementation of the algorithm and prove its convergence.

Application of a Split-Fiber Probe to Velocity Measurement in the NASA Research Compressor

NASA Technical Reports Server (NTRS)

Lepicovsky, Jan

2003-01-01

A split-fiber probe was used to acquire unsteady data in a research compressor. The probe has two thin films deposited on a quartz cylinder 200 microns in diameter. A split-fiber probe allows simultaneous measurement of velocity magnitude and direction in a plane that is perpendicular to the sensing cylinder, because it has its circumference divided into two independent parts. Local heat transfer considerations indicated that the probe direction characteristic is linear in the range of flow incidence angles of +/- 35. Calibration tests confirmed this assumption. Of course, the velocity characteristic is nonlinear as is typical in thermal anemometry. The probe was used extensively in the NASA Glenn Research Center (GRC) low-speed, multistage axial compressor, and worked reliably during a test program of several months duration. The velocity and direction characteristics of the probe showed only minute changes during the entire test program. An algorithm was developed to decompose the probe signals into velocity magnitude and velocity direction. The averaged unsteady data were compared with data acquired by pneumatic probes. An overall excellent agreement between the averaged data acquired by a split-fiber probe and a pneumatic probe boosts confidence in the reliability of the unsteady content of the split-fiber probe data. To investigate the features of unsteady data, two methods were used: ensemble averaging and frequency analysis. The velocity distribution in a rotor blade passage was retrieved using the ensemble averaging method. Frequencies of excitation forces that may contribute to high cycle fatigue problems were identified by applying a fast Fourier transform to the absolute velocity data.

On a programming language for graph algorithms

NASA Technical Reports Server (NTRS)

Rheinboldt, W. C.; Basili, V. R.; Mesztenyi, C. K.

1971-01-01

An algorithmic language, GRAAL, is presented for describing and implementing graph algorithms of the type primarily arising in applications. The language is based on a set algebraic model of graph theory which defines the graph structure in terms of morphisms between certain set algebraic structures over the node set and arc set. GRAAL is modular in the sense that the user specifies which of these mappings are available with any graph. This allows flexibility in the selection of the storage representation for different graph structures. In line with its set theoretic foundation, the language introduces sets as a basic data type and provides for the efficient execution of all set and graph operators. At present, GRAAL is defined as an extension of ALGOL 60 (revised) and its formal description is given as a supplement to the syntactic and semantic definition of ALGOL. Several typical graph algorithms are written in GRAAL to illustrate various features of the language and to show its applicability.

Automatic characterization and segmentation of human skin using three-dimensional optical coherence tomography

NASA Astrophysics Data System (ADS)

Hori, Yasuaki; Yasuno, Yoshiaki; Sakai, Shingo; Matsumoto, Masayuki; Sugawara, Tomoko; Madjarova, Violeta; Yamanari, Masahiro; Makita, Shuichi; Yasui, Takeshi; Araki, Tsutomu; Itoh, Masahide; Yatagai, Toyohiko

2006-03-01

A set of fully automated algorithms that is specialized for analyzing a three-dimensional optical coherence tomography (OCT) volume of human skin is reported. The algorithm set first determines the skin surface of the OCT volume, and a depth-oriented algorithm provides the mean epidermal thickness, distribution map of the epidermis, and a segmented volume of the epidermis. Subsequently, an en face shadowgram is produced by an algorithm to visualize the infundibula in the skin with high contrast. The population and occupation ratio of the infundibula are provided by a histogram-based thresholding algorithm and a distance mapping algorithm. En face OCT slices at constant depths from the sample surface are extracted, and the histogram-based thresholding algorithm is again applied to these slices, yielding a three-dimensional segmented volume of the infundibula. The dermal attenuation coefficient is also calculated from the OCT volume in order to evaluate the skin texture. The algorithm set examines swept-source OCT volumes of the skins of several volunteers, and the results show the high stability, portability and reproducibility of the algorithm.

The truth will out: interrogative polygraphy ("lie detection") with event-related brain potentials.

PubMed

Farwell, L A; Donchin, E

1991-09-01

The feasibility of using Event Related Brain Potentials (ERPs) in Interrogative Polygraphy ("Lie Detection") was tested by examining the effectiveness of the Guilty Knowledge Test designed by Farwell and Donchin (1986, 1988). The subject is assigned an arbitrary task requiring discrimination between experimenter-designated targets and other, irrelevant stimuli. A group of diagnostic items ("probes"), which to the unwitting are indistinguishable from the irrelevant items, are embedded among the irrelevant. For subjects who possess "guilty knowledge" these probes are distinct from the irrelevants and are likely to elicit a P300, thus revealing their possessing the special knowledge that allows them to differentiate the probes from the irrelevants. We report two experiments in which this paradigm was tested. In Experiment 1, 20 subjects participated in one of two mock espionage scenarios and were tested for their knowledge of both scenarios. All stimuli consisted of short phrases presented for 300 ms each at an interstimulus interval of 1550 ms. A set of items were designated as "targets" and appeared on 17% of the trials. Probes related to the scenarios also appeared on 17% of the trials. The rest of the items were irrelevants. Subjects responded by pressing one switch following targets, and the other following irrelevants (and, of course, probes). ERPs were recorded from FZ, CZ, and PZ. As predicted, targets elicited large P300s in all subjects. Probes associated with a given scenario elicited a P300 in subjects who participated in that scenario. A bootstrapping method was used to assess the quality of the decision for each subject. The algorithm declared the decision indeterminate in 12.5% of the cases. In all other cases a decision was made. There were no false positives and no false negatives: whenever a determination was made it was accurate. The second experiment was virtually identical to the first, with identical results, except that this time 4 subjects were tested, each of which had a minor brush with the law. Subjects were tested to determine whether they possessed information on their own "crimes." The results were as expected; the Guilty Knowledge Test determined correctly which subject possessed which information. The implications of these data both for the practice of Interrogative Polygraphy and the interpretation of the P300 are discussed.

An extended affinity propagation clustering method based on different data density types.

PubMed

Zhao, XiuLi; Xu, WeiXiang

2015-01-01

Affinity propagation (AP) algorithm, as a novel clustering method, does not require the users to specify the initial cluster centers in advance, which regards all data points as potential exemplars (cluster centers) equally and groups the clusters totally by the similar degree among the data points. But in many cases there exist some different intensive areas within the same data set, which means that the data set does not distribute homogeneously. In such situation the AP algorithm cannot group the data points into ideal clusters. In this paper, we proposed an extended AP clustering algorithm to deal with such a problem. There are two steps in our method: firstly the data set is partitioned into several data density types according to the nearest distances of each data point; and then the AP clustering method is, respectively, used to group the data points into clusters in each data density type. Two experiments are carried out to evaluate the performance of our algorithm: one utilizes an artificial data set and the other uses a real seismic data set. The experiment results show that groups are obtained more accurately by our algorithm than OPTICS and AP clustering algorithm itself.

Procedure of Partitioning Data Into Number of Data Sets or Data Group - A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

The goal of clustering is to decompose a dataset into similar groups based on a objective function. Some already well established clustering algorithms are there for data clustering. Objective of these data clustering algorithms are to divide the data points of the feature space into a number of groups (or classes) so that a predefined set of criteria are satisfied. The article considers the comparative study about the effectiveness and efficiency of traditional data clustering algorithms. For evaluating the performance of the clustering algorithms, Minkowski score is used here for different data sets.

Computationally efficient algorithm for Gaussian Process regression in case of structured samples

NASA Astrophysics Data System (ADS)

Belyaev, M.; Burnaev, E.; Kapushev, Y.

2016-04-01

Surrogate modeling is widely used in many engineering problems. Data sets often have Cartesian product structure (for instance factorial design of experiments with missing points). In such case the size of the data set can be very large. Therefore, one of the most popular algorithms for approximation-Gaussian Process regression-can be hardly applied due to its computational complexity. In this paper a computationally efficient approach for constructing Gaussian Process regression in case of data sets with Cartesian product structure is presented. Efficiency is achieved by using a special structure of the data set and operations with tensors. Proposed algorithm has low computational as well as memory complexity compared to existing algorithms. In this work we also introduce a regularization procedure allowing to take into account anisotropy of the data set and avoid degeneracy of regression model.

Pattern-set generation algorithm for the one-dimensional multiple stock sizes cutting stock problem

NASA Astrophysics Data System (ADS)

Cui, Yaodong; Cui, Yi-Ping; Zhao, Zhigang

2015-09-01

A pattern-set generation algorithm (PSG) for the one-dimensional multiple stock sizes cutting stock problem (1DMSSCSP) is presented. The solution process contains two stages. In the first stage, the PSG solves the residual problems repeatedly to generate the patterns in the pattern set, where each residual problem is solved by the column-generation approach, and each pattern is generated by solving a single large object placement problem. In the second stage, the integer linear programming model of the 1DMSSCSP is solved using a commercial solver, where only the patterns in the pattern set are considered. The computational results of benchmark instances indicate that the PSG outperforms existing heuristic algorithms and rivals the exact algorithm in solution quality.

Probe-And-Socket Fasteners For Robotic Assembly

NASA Technical Reports Server (NTRS)

Nyberg, Karen

1995-01-01

Self-alignment and simplicity of actuation make mechanism amenable to robotic assembly. Includes socket, mounted on structure at worksite, and probe, mounted on piece of equipment to be attached to structure at socket. Probe-and-socket mechanism used in conjunction with fixed target aiding in placement of end effector of robot during grasping, and with handle or handles on structure. Intended to enable robot to set up workstation in hostile environment. Workstation then used by astronaut, aquanaut, or other human, spending minimum time in environment. Human concentrates on performing quality work rather than on setting up equipment, with consequent reduction of risk.

Method of identifying hairpin DNA probes by partial fold analysis

DOEpatents

Miller, Benjamin L [Penfield, NY; Strohsahl, Christopher M [Saugerties, NY

2009-10-06

Method of identifying molecular beacons in which a secondary structure prediction algorithm is employed to identify oligonucleotide sequences within a target gene having the requisite hairpin structure. Isolated oligonucleotides, molecular beacons prepared from those oligonucleotides, and their use are also disclosed.

Method of identifying hairpin DNA probes by partial fold analysis

DOEpatents

Miller, Benjamin L.; Strohsahl, Christopher M.

2008-10-28

Methods of identifying molecular beacons in which a secondary structure prediction algorithm is employed to identify oligonucleotide sequences within a target gene having the requisite hairpin structure. Isolated oligonucleotides, molecular beacons prepared from those oligonucleotides, and their use are also disclosed.

Set covering algorithm, a subprogram of the scheduling algorithm for mission planning and logistic evaluation

NASA Technical Reports Server (NTRS)

Chang, H.

1976-01-01

A computer program using Lemke, Salkin and Spielberg's Set Covering Algorithm (SCA) to optimize a traffic model problem in the Scheduling Algorithm for Mission Planning and Logistics Evaluation (SAMPLE) was documented. SCA forms a submodule of SAMPLE and provides for input and output, subroutines, and an interactive feature for performing the optimization and arranging the results in a readily understandable form for output.

SymDex: increasing the efficiency of chemical fingerprint similarity searches for comparing large chemical libraries by using query set indexing.

PubMed

Tai, David; Fang, Jianwen

2012-08-27

The large sizes of today's chemical databases require efficient algorithms to perform similarity searches. It can be very time consuming to compare two large chemical databases. This paper seeks to build upon existing research efforts by describing a novel strategy for accelerating existing search algorithms for comparing large chemical collections. The quest for efficiency has focused on developing better indexing algorithms by creating heuristics for searching individual chemical against a chemical library by detecting and eliminating needless similarity calculations. For comparing two chemical collections, these algorithms simply execute searches for each chemical in the query set sequentially. The strategy presented in this paper achieves a speedup upon these algorithms by indexing the set of all query chemicals so redundant calculations that arise in the case of sequential searches are eliminated. We implement this novel algorithm by developing a similarity search program called Symmetric inDexing or SymDex. SymDex shows over a 232% maximum speedup compared to the state-of-the-art single query search algorithm over real data for various fingerprint lengths. Considerable speedup is even seen for batch searches where query set sizes are relatively small compared to typical database sizes. To the best of our knowledge, SymDex is the first search algorithm designed specifically for comparing chemical libraries. It can be adapted to most, if not all, existing indexing algorithms and shows potential for accelerating future similarity search algorithms for comparing chemical databases.

Molecular beacon sequence design algorithm.

PubMed

Monroe, W Todd; Haselton, Frederick R

2003-01-01

A method based on Web-based tools is presented to design optimally functioning molecular beacons. Molecular beacons, fluorogenic hybridization probes, are a powerful tool for the rapid and specific detection of a particular nucleic acid sequence. However, their synthesis costs can be considerable. Since molecular beacon performance is based on its sequence, it is imperative to rationally design an optimal sequence before synthesis. The algorithm presented here uses simple Microsoft Excel formulas and macros to rank candidate sequences. This analysis is carried out using mfold structural predictions along with other free Web-based tools. For smaller laboratories where molecular beacons are not the focus of research, the public domain algorithm described here may be usefully employed to aid in molecular beacon design.

Muon tomography imaging algorithms for nuclear threat detection inside large volume containers with the Muon Portal detector

NASA Astrophysics Data System (ADS)

Riggi, S.; Antonuccio-Delogu, V.; Bandieramonte, M.; Becciani, U.; Costa, A.; La Rocca, P.; Massimino, P.; Petta, C.; Pistagna, C.; Riggi, F.; Sciacca, E.; Vitello, F.

2013-11-01

Muon tomographic visualization techniques try to reconstruct a 3D image as close as possible to the real localization of the objects being probed. Statistical algorithms under test for the reconstruction of muon tomographic images in the Muon Portal Project are discussed here. Autocorrelation analysis and clustering algorithms have been employed within the context of methods based on the Point Of Closest Approach (POCA) reconstruction tool. An iterative method based on the log-likelihood approach was also implemented. Relative merits of all such methods are discussed, with reference to full GEANT4 simulations of different scenarios, incorporating medium and high-Z objects inside a container.

GeneChip{sup {trademark}} screening assay for cystic fibrosis mutations

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

Cronn, M.T.; Miyada, C.G.; Fucini, R.V.

1994-09-01

GeneChip{sup {trademark}} assays are based on high density, carefully designed arrays of short oligonucleotide probes (13-16 bases) built directly on derivatized silica substrates. DNA target sequence analysis is achieved by hybridizing fluorescently labeled amplification products to these arrays. Fluorescent hybridization signals located within the probe array are translated into target sequence information using the known probe sequence at each array feature. The mutation screening assay for cystic fibrosis includes sets of oligonucleotide probes designed to detect numerous different mutations that have been described in 14 exons and one intron of the CFTR gene. Each mutation site is addressed by amore » sub-array of at least 40 probe sequences, half designed to detect the wild type gene sequence and half designed to detect the reported mutant sequence. Hybridization with homozygous mutant, homozygous wild type or heterozygous targets results in distinctive hybridization patterns within a sub-array, permitting specific discrimination of each mutation. The GeneChip probe arrays are very small (approximately 1 cm{sup 2}). There miniature size coupled with their high information content make GeneChip probe arrays a useful and practical means for providing CF mutation analysis in a clinical setting.« less

Measurement of Flow Pattern Within a Rotating Stall Cell in an Axial Compressor

NASA Technical Reports Server (NTRS)

Lepicovsky, Jan; Braunscheidel, Edward P.

2006-01-01

Effective active control of rotating stall in axial compressors requires detailed understanding of flow instabilities associated with this compressor regime. Newly designed miniature high frequency response total and static pressure probes as well as commercial thermoanemometric probes are suitable tools for this task. However, during the rotating stall cycle the probes are subjected to flow direction changes that are far larger than the range of probe incidence acceptance, and therefore probe data without a proper correction would misrepresent unsteady variations of flow parameters. A methodology, based on ensemble averaging, is proposed to circumvent this problem. In this approach the ensemble averaged signals acquired for various probe setting angles are segmented, and only the sections for probe setting angles close to the actual flow angle are used for signal recombination. The methodology was verified by excellent agreement between velocity distributions obtained from pressure probe data, and data measured with thermoanemometric probes. Vector plots of unsteady flow behavior during the rotating stall regime indicate reversed flow within the rotating stall cell that spreads over to adjacent rotor blade channels. Results of this study confirmed that the NASA Low Speed Axial Compressor (LSAC) while in a rotating stall regime at rotor design speed exhibits one stall cell that rotates at a speed equal to 50.6 percent of the rotor shaft speed.

Uprobe: a genome-wide universal probe resource for comparative physical mapping in vertebrates.

PubMed

Kellner, Wendy A; Sullivan, Robert T; Carlson, Brian H; Thomas, James W

2005-01-01

Interspecies comparisons are important for deciphering the functional content and evolution of genomes. The expansive array of >70 public vertebrate genomic bacterial artificial chromosome (BAC) libraries can provide a means of comparative mapping, sequencing, and functional analysis of targeted chromosomal segments that is independent and complementary to whole-genome sequencing. However, at the present time, no complementary resource exists for the efficient targeted physical mapping of the majority of these BAC libraries. Universal overgo-hybridization probes, designed from regions of sequenced genomes that are highly conserved between species, have been demonstrated to be an effective resource for the isolation of orthologous regions from multiple BAC libraries in parallel. Here we report the application of the universal probe design principal across entire genomes, and the subsequent creation of a complementary probe resource, Uprobe, for screening vertebrate BAC libraries. Uprobe currently consists of whole-genome sets of universal overgo-hybridization probes designed for screening mammalian or avian/reptilian libraries. Retrospective analysis, experimental validation of the probe design process on a panel of representative BAC libraries, and estimates of probe coverage across the genome indicate that the majority of all eutherian and avian/reptilian genes or regions of interest can be isolated using Uprobe. Future implementation of the universal probe design strategy will be used to create an expanded number of whole-genome probe sets that will encompass all vertebrate genomes.

Inverse consistent non-rigid image registration based on robust point set matching

PubMed Central

2014-01-01

Background Robust point matching (RPM) has been extensively used in non-rigid registration of images to robustly register two sets of image points. However, except for the location at control points, RPM cannot estimate the consistent correspondence between two images because RPM is a unidirectional image matching approach. Therefore, it is an important issue to make an improvement in image registration based on RPM. Methods In our work, a consistent image registration approach based on the point sets matching is proposed to incorporate the property of inverse consistency and improve registration accuracy. Instead of only estimating the forward transformation between the source point sets and the target point sets in state-of-the-art RPM algorithms, the forward and backward transformations between two point sets are estimated concurrently in our algorithm. The inverse consistency constraints are introduced to the cost function of RPM and the fuzzy correspondences between two point sets are estimated based on both the forward and backward transformations simultaneously. A modified consistent landmark thin-plate spline registration is discussed in detail to find the forward and backward transformations during the optimization of RPM. The similarity of image content is also incorporated into point matching in order to improve image matching. Results Synthetic data sets, medical images are employed to demonstrate and validate the performance of our approach. The inverse consistent errors of our algorithm are smaller than RPM. Especially, the topology of transformations is preserved well for our algorithm for the large deformation between point sets. Moreover, the distance errors of our algorithm are similar to that of RPM, and they maintain a downward trend as whole, which demonstrates the convergence of our algorithm. The registration errors for image registrations are evaluated also. Again, our algorithm achieves the lower registration errors in same iteration number. The determinant of the Jacobian matrix of the deformation field is used to analyse the smoothness of the forward and backward transformations. The forward and backward transformations estimated by our algorithm are smooth for small deformation. For registration of lung slices and individual brain slices, large or small determinant of the Jacobian matrix of the deformation fields are observed. Conclusions Results indicate the improvement of the proposed algorithm in bi-directional image registration and the decrease of the inverse consistent errors of the forward and the reverse transformations between two images. PMID:25559889

Analysis of miRNA expression profile based on SVM algorithm

NASA Astrophysics Data System (ADS)

Ting-ting, Dai; Chang-ji, Shan; Yan-shou, Dong; Yi-duo, Bian

2018-05-01

Based on mirna expression spectrum data set, a new data mining algorithm - tSVM - KNN (t statistic with support vector machine - k nearest neighbor) is proposed. the idea of the algorithm is: firstly, the feature selection of the data set is carried out by the unified measurement method; Secondly, SVM - KNN algorithm, which combines support vector machine (SVM) and k - nearest neighbor (k - nearest neighbor) is used as classifier. Simulation results show that SVM - KNN algorithm has better classification ability than SVM and KNN alone. Tsvm - KNN algorithm only needs 5 mirnas to obtain 96.08 % classification accuracy in terms of the number of mirna " tags" and recognition accuracy. compared with similar algorithms, tsvm - KNN algorithm has obvious advantages.

Continuous Glucose Monitoring Enables the Detection of Losses in Infusion Set Actuation (LISAs)

PubMed Central

Howsmon, Daniel P.; Cameron, Faye; Baysal, Nihat; Ly, Trang T.; Forlenza, Gregory P.; Maahs, David M.; Buckingham, Bruce A.; Hahn, Juergen; Bequette, B. Wayne

2017-01-01

Reliable continuous glucose monitoring (CGM) enables a variety of advanced technology for the treatment of type 1 diabetes. In addition to artificial pancreas algorithms that use CGM to automate continuous subcutaneous insulin infusion (CSII), CGM can also inform fault detection algorithms that alert patients to problems in CGM or CSII. Losses in infusion set actuation (LISAs) can adversely affect clinical outcomes, resulting in hyperglycemia due to impaired insulin delivery. Prolonged hyperglycemia may lead to diabetic ketoacidosis—a serious metabolic complication in type 1 diabetes. Therefore, an algorithm for the detection of LISAs based on CGM and CSII signals was developed to improve patient safety. The LISA detection algorithm is trained retrospectively on data from 62 infusion set insertions from 20 patients. The algorithm collects glucose and insulin data, and computes relevant fault metrics over two different sliding windows; an alarm sounds when these fault metrics are exceeded. With the chosen algorithm parameters, the LISA detection strategy achieved a sensitivity of 71.8% and issued 0.28 false positives per day on the training data. Validation on two independent data sets confirmed that similar performance is seen on data that was not used for training. The developed algorithm is able to effectively alert patients to possible infusion set failures in open-loop scenarios, with limited evidence of its extension to closed-loop scenarios. PMID:28098839

Continuous Glucose Monitoring Enables the Detection of Losses in Infusion Set Actuation (LISAs).

PubMed

Howsmon, Daniel P; Cameron, Faye; Baysal, Nihat; Ly, Trang T; Forlenza, Gregory P; Maahs, David M; Buckingham, Bruce A; Hahn, Juergen; Bequette, B Wayne

2017-01-15

Reliable continuous glucose monitoring (CGM) enables a variety of advanced technology for the treatment of type 1 diabetes. In addition to artificial pancreas algorithms that use CGM to automate continuous subcutaneous insulin infusion (CSII), CGM can also inform fault detection algorithms that alert patients to problems in CGM or CSII. Losses in infusion set actuation (LISAs) can adversely affect clinical outcomes, resulting in hyperglycemia due to impaired insulin delivery. Prolonged hyperglycemia may lead to diabetic ketoacidosis-a serious metabolic complication in type 1 diabetes. Therefore, an algorithm for the detection of LISAs based on CGM and CSII signals was developed to improve patient safety. The LISA detection algorithm is trained retrospectively on data from 62 infusion set insertions from 20 patients. The algorithm collects glucose and insulin data, and computes relevant fault metrics over two different sliding windows; an alarm sounds when these fault metrics are exceeded. With the chosen algorithm parameters, the LISA detection strategy achieved a sensitivity of 71.8% and issued 0.28 false positives per day on the training data. Validation on two independent data sets confirmed that similar performance is seen on data that was not used for training. The developed algorithm is able to effectively alert patients to possible infusion set failures in open-loop scenarios, with limited evidence of its extension to closed-loop scenarios.

Decreased rates of hypoglycemia following implementation of a comprehensive computerized insulin order set and titration algorithm in the inpatient setting.

PubMed

Sinha Gregory, Naina; Seley, Jane Jeffrie; Gerber, Linda M; Tang, Chin; Brillon, David

2016-12-01

More than one-third of hospitalized patients have hyperglycemia. Despite evidence that improving glycemic control leads to better outcomes, achieving recognized targets remains a challenge. The objective of this study was to evaluate the implementation of a computerized insulin order set and titration algorithm on rates of hypoglycemia and overall inpatient glycemic control. A prospective observational study evaluating the impact of a glycemic order set and titration algorithm in an academic medical center in non-critical care medical and surgical inpatients. The initial intervention was hospital-wide implementation of a comprehensive insulin order set. The secondary intervention was initiation of an insulin titration algorithm in two pilot medicine inpatient units. Point of care testing blood glucose reports were analyzed. These reports included rates of hypoglycemia (BG < 70 mg/dL) and hyperglycemia (BG >200 mg/dL in phase 1, BG > 180 mg/dL in phase 2). In the first phase of the study, implementation of the insulin order set was associated with decreased rates of hypoglycemia (1.92% vs 1.61%; p < 0.001) and increased rates of hyperglycemia (24.02% vs 27.27%; p < 0.001) from 2010 to 2011. In the second phase, addition of a titration algorithm was associated with decreased rates of hypoglycemia (2.57% vs 1.82%; p = 0.039) and increased rates of hyperglycemia (31.76% vs 41.33%; p < 0.001) from 2012 to 2013. A comprehensive computerized insulin order set and titration algorithm significantly decreased rates of hypoglycemia. This significant reduction in hypoglycemia was associated with increased rates of hyperglycemia. Hardwiring the algorithm into the electronic medical record may foster adoption.

Modeling of skin cancer dermatoscopy images

NASA Astrophysics Data System (ADS)

Iralieva, Malica B.; Myakinin, Oleg O.; Bratchenko, Ivan A.; Zakharov, Valery P.

2018-04-01

An early identified cancer is more likely to effective respond to treatment and has a less expensive treatment as well. Dermatoscopy is one of general diagnostic techniques for skin cancer early detection that allows us in vivo evaluation of colors and microstructures on skin lesions. Digital phantoms with known properties are required during new instrument developing to compare sample's features with data from the instrument. An algorithm for image modeling of skin cancer is proposed in the paper. Steps of the algorithm include setting shape, texture generation, adding texture and normal skin background setting. The Gaussian represents the shape, and then the texture generation based on a fractal noise algorithm is responsible for spatial chromophores distributions, while the colormap applied to the values corresponds to spectral properties. Finally, a normal skin image simulated by mixed Monte Carlo method using a special online tool is added as a background. Varying of Asymmetry, Borders, Colors and Diameter settings is shown to be fully matched to the ABCD clinical recognition algorithm. The asymmetry is specified by setting different standard deviation values of Gaussian in different parts of image. The noise amplitude is increased to set the irregular borders score. Standard deviation is changed to determine size of the lesion. Colors are set by colormap changing. The algorithm for simulating different structural elements is required to match with others recognition algorithms.

Association of a cytarabine chemosensitivity related gene expression signature with survival in cytogenetically normal acute myeloid leukemia.

PubMed

Yan, Han; Wen, Lu; Tan, Dan; Xie, Pan; Pang, Feng-Mei; Zhou, Hong-Hao; Zhang, Wei; Liu, Zhao-Qian; Tang, Jie; Li, Xi; Chen, Xiao-Ping

2017-01-03

The prognosis of cytogenetically normal acute myeloid leukemia (CN-AML) varies greatly among patients. Achievement of complete remission (CR) after chemotherapy is indispensable for a better prognosis. To develop a gene signature predicting overall survival (OS) in CN-AML, we performed data mining procedure based on whole genome expression data of both blood cancer cell lines and AML patients from open access database. A gene expression signature including 42 probes was derived. These probes were significantly associated with both cytarabine half maximal inhibitory concentration values in blood cancer cell lines and OS in CN-AML patients. By using cox regression analysis and linear regression analysis, a chemo-sensitive score calculated algorithm based on mRNA expression levels of the 42 probes was established. The scores were associated with OS in both the training sample (p=5.13 × 10-4, HR=2.040, 95% CI: 1.364-3.051) and the validation sample (p=0.002, HR=2.528, 95% CI: 1.393-4.591) of the GSE12417 dataset from Gene Expression Omnibus. In The Cancer Genome Atlas (TCGA) CN-AML patients, higher scores were found to be associated with both worse OS (p=0.013, HR=2.442, 95% CI: 1.205-4.950) and DFS (p=0.015, HR=2.376, 95% CI: 1.181-4.779). Results of gene ontology (GO) analysis showed that all the significant GO Terms were correlated with cellular component of mitochondrion. In summary, a novel gene set that could predict prognosis of CN-AML was identified presently, which provided a new way to identify genes impacting AML chemo-sensitivity and prognosis.

Association of a cytarabine chemosensitivity related gene expression signature with survival in cytogenetically normal acute myeloid leukemia

PubMed Central

Yan, Han; Wen, Lu; Tan, Dan; Xie, Pan; Pang, Feng-mei; Zhou, Hong-hao; Zhang, Wei; Liu, Zhao-qian; Tang, Jie; Li, Xi; Chen, Xiao-ping

2017-01-01

The prognosis of cytogenetically normal acute myeloid leukemia (CN-AML) varies greatly among patients. Achievement of complete remission (CR) after chemotherapy is indispensable for a better prognosis. To develop a gene signature predicting overall survival (OS) in CN-AML, we performed data mining procedure based on whole genome expression data of both blood cancer cell lines and AML patients from open access database. A gene expression signature including 42 probes was derived. These probes were significantly associated with both cytarabine half maximal inhibitory concentration values in blood cancer cell lines and OS in CN-AML patients. By using cox regression analysis and linear regression analysis, a chemo-sensitive score calculated algorithm based on mRNA expression levels of the 42 probes was established. The scores were associated with OS in both the training sample (p=5.13 × 10−4, HR=2.040, 95% CI: 1.364-3.051) and the validation sample (p=0.002, HR=2.528, 95% CI: 1.393-4.591) of the GSE12417 dataset from Gene Expression Omnibus. In The Cancer Genome Atlas (TCGA) CN-AML patients, higher scores were found to be associated with both worse OS (p=0.013, HR=2.442, 95% CI: 1.205-4.950) and DFS (p=0.015, HR=2.376, 95% CI: 1.181-4.779). Results of gene ontology (GO) analysis showed that all the significant GO Terms were correlated with cellular component of mitochondrion. In summary, a novel gene set that could predict prognosis of CN-AML was identified presently, which provided a new way to identify genes impacting AML chemo-sensitivity and prognosis. PMID:27903973

Bayesian Atmospheric Radiative Transfer (BART): Model, Statistics Driver, and Application to HD 209458b

NASA Astrophysics Data System (ADS)

Cubillos, Patricio; Harrington, Joseph; Blecic, Jasmina; Stemm, Madison M.; Lust, Nate B.; Foster, Andrew S.; Rojo, Patricio M.; Loredo, Thomas J.

2014-11-01

Multi-wavelength secondary-eclipse and transit depths probe the thermo-chemical properties of exoplanets. In recent years, several research groups have developed retrieval codes to analyze the existing data and study the prospects of future facilities. However, the scientific community has limited access to these packages. Here we premiere the open-source Bayesian Atmospheric Radiative Transfer (BART) code. We discuss the key aspects of the radiative-transfer algorithm and the statistical package. The radiation code includes line databases for all HITRAN molecules, high-temperature H2O, TiO, and VO, and includes a preprocessor for adding additional line databases without recompiling the radiation code. Collision-induced absorption lines are available for H2-H2 and H2-He. The parameterized thermal and molecular abundance profiles can be modified arbitrarily without recompilation. The generated spectra are integrated over arbitrary bandpasses for comparison to data. BART's statistical package, Multi-core Markov-chain Monte Carlo (MC3), is a general-purpose MCMC module. MC3 implements the Differental-evolution Markov-chain Monte Carlo algorithm (ter Braak 2006, 2009). MC3 converges 20-400 times faster than the usual Metropolis-Hastings MCMC algorithm, and in addition uses the Message Passing Interface (MPI) to parallelize the MCMC chains. We apply the BART retrieval code to the HD 209458b data set to estimate the planet's temperature profile and molecular abundances. This work was supported by NASA Planetary Atmospheres grant NNX12AI69G and NASA Astrophysics Data Analysis Program grant NNX13AF38G. JB holds a NASA Earth and Space Science Fellowship.

Strong convergence of an extragradient-type algorithm for the multiple-sets split equality problem.

PubMed

Zhao, Ying; Shi, Luoyi

2017-01-01

This paper introduces a new extragradient-type method to solve the multiple-sets split equality problem (MSSEP). Under some suitable conditions, the strong convergence of an algorithm can be verified in the infinite-dimensional Hilbert spaces. Moreover, several numerical results are given to show the effectiveness of our algorithm.

Cone-Probe Rake Design and Calibration for Supersonic Wind Tunnel Models

NASA Technical Reports Server (NTRS)

Won, Mark J.

1999-01-01

A series of experimental investigations were conducted at the NASA Langley Unitary Plan Wind Tunnel (UPWT) to calibrate cone-probe rakes designed to measure the flow field on 1-2% scale, high-speed wind tunnel models from Mach 2.15 to 2.4. The rakes were developed from a previous design that exhibited unfavorable measurement characteristics caused by a high probe spatial density and flow blockage from the rake body. Calibration parameters included Mach number, total pressure recovery, and flow angularity. Reference conditions were determined from a localized UPWT test section flow survey using a 10deg supersonic wedge probe. Test section Mach number and total pressure were determined using a novel iterative technique that accounted for boundary layer effects on the wedge surface. Cone-probe measurements were correlated to the surveyed flow conditions using analytical functions and recursive algorithms that resolved Mach number, pressure recovery, and flow angle to within +/-0.01, +/-1% and +/-0.1deg , respectively, for angles of attack and sideslip between +/-8deg. Uncertainty estimates indicated the overall cone-probe calibration accuracy was strongly influenced by the propagation of measurement error into the calculated results.

Image-processing algorithms for inspecting characteristics of hybrid rice seed

NASA Astrophysics Data System (ADS)

Cheng, Fang; Ying, Yibin

2004-03-01

Incompletely closed glumes, germ and disease are three characteristics of hybrid rice seed. Image-processing algorithms developed to detect these seed characteristics were presented in this paper. The rice seed used for this study involved five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou and IIyou. The algorithms were implemented with a 5*600 images set, a 4*400 images set and the other 5*600 images set respectively. The image sets included black background images, white background images and both sides images of rice seed. Results show that the algorithm for inspecting seeds with incompletely closed glumes based on Radon Transform achieved an accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with unclosed glumes, the algorithm for inspecting germinated seeds on panicle based on PCA and ANN achieved n average accuracy of 98% for normal seeds, 88% for germinated seeds on panicle and the algorithm for inspecting diseased seeds based on color features achieved an accuracy of 92% for normal and healthy seeds, 95% for spot diseased seeds and 83% for severe diseased seeds.

The Impact of a Line Probe Assay Based Diagnostic Algorithm on Time to Treatment Initiation and Treatment Outcomes for Multidrug Resistant TB Patients in Arkhangelsk Region, Russia.

PubMed

Eliseev, Platon; Balantcev, Grigory; Nikishova, Elena; Gaida, Anastasia; Bogdanova, Elena; Enarson, Donald; Ornstein, Tara; Detjen, Anne; Dacombe, Russell; Gospodarevskaya, Elena; Phillips, Patrick P J; Mann, Gillian; Squire, Stephen Bertel; Mariandyshev, Andrei

2016-01-01

In the Arkhangelsk region of Northern Russia, multidrug-resistant (MDR) tuberculosis (TB) rates in new cases are amongst the highest in the world. In 2014, MDR-TB rates reached 31.7% among new cases and 56.9% among retreatment cases. The development of new diagnostic tools allows for faster detection of both TB and MDR-TB and should lead to reduced transmission by earlier initiation of anti-TB therapy. The PROVE-IT (Policy Relevant Outcomes from Validating Evidence on Impact) Russia study aimed to assess the impact of the implementation of line probe assay (LPA) as part of an LPA-based diagnostic algorithm for patients with presumptive MDR-TB focusing on time to treatment initiation with time from first-care seeking visit to the initiation of MDR-TB treatment rather than diagnostic accuracy as the primary outcome, and to assess treatment outcomes. We hypothesized that the implementation of LPA would result in faster time to treatment initiation and better treatment outcomes. A culture-based diagnostic algorithm used prior to LPA implementation was compared to an LPA-based algorithm that replaced BacTAlert and Löwenstein Jensen (LJ) for drug sensitivity testing. A total of 295 MDR-TB patients were included in the study, 163 diagnosed with the culture-based algorithm, 132 with the LPA-based algorithm. Among smear positive patients, the implementation of the LPA-based algorithm was associated with a median decrease in time to MDR-TB treatment initiation of 50 and 66 days compared to the culture-based algorithm (BacTAlert and LJ respectively, p<0.001). In smear negative patients, the LPA-based algorithm was associated with a median decrease in time to MDR-TB treatment initiation of 78 days when compared to the culture-based algorithm (LJ, p<0.001). However, several weeks were still needed for treatment initiation in LPA-based algorithm, 24 days in smear positive, and 62 days in smear negative patients. Overall treatment outcomes were better in LPA-based algorithm compared to culture-based algorithm (p = 0.003). Treatment success rates at 20 months of treatment were higher in patients diagnosed with the LPA-based algorithm (65.2%) as compared to those diagnosed with the culture-based algorithm (44.8%). Mortality was also lower in the LPA-based algorithm group (7.6%) compared to the culture-based algorithm group (15.9%). There was no statistically significant difference in smear and culture conversion rates between the two algorithms. The results of the study suggest that the introduction of LPA leads to faster time to MDR diagnosis and earlier treatment initiation as well as better treatment outcomes for patients with MDR-TB. These findings also highlight the need for further improvements within the health system to reduce both patient and diagnostic delays to truly optimize the impact of new, rapid diagnostics.

Final Report: Sampling-Based Algorithms for Estimating Structure in Big Data.

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

Matulef, Kevin Michael

The purpose of this project was to develop sampling-based algorithms to discover hidden struc- ture in massive data sets. Inferring structure in large data sets is an increasingly common task in many critical national security applications. These data sets come from myriad sources, such as network traffic, sensor data, and data generated by large-scale simulations. They are often so large that traditional data mining techniques are time consuming or even infeasible. To address this problem, we focus on a class of algorithms that do not compute an exact answer, but instead use sampling to compute an approximate answer using fewermore » resources. The particular class of algorithms that we focus on are streaming algorithms , so called because they are designed to handle high-throughput streams of data. Streaming algorithms have only a small amount of working storage - much less than the size of the full data stream - so they must necessarily use sampling to approximate the correct answer. We present two results: * A streaming algorithm called HyperHeadTail , that estimates the degree distribution of a graph (i.e., the distribution of the number of connections for each node in a network). The degree distribution is a fundamental graph property, but prior work on estimating the degree distribution in a streaming setting was impractical for many real-world application. We improve upon prior work by developing an algorithm that can handle streams with repeated edges, and graph structures that evolve over time. * An algorithm for the task of maintaining a weighted subsample of items in a stream, when the items must be sampled according to their weight, and the weights are dynamically changing. To our knowledge, this is the first such algorithm designed for dynamically evolving weights. We expect it may be useful as a building block for other streaming algorithms on dynamic data sets.« less

Rapid real-time diagnostic PCR for Trichophyton rubrum and Trichophyton mentagrophytes in patients with tinea unguium and tinea pedis using specific fluorescent probes.

PubMed

Miyajima, Yoshiharu; Satoh, Kazuo; Uchida, Takao; Yamada, Tsuyoshi; Abe, Michiko; Watanabe, Shin-ichi; Makimura, Miho; Makimura, Koichi

2013-03-01

Trichophyton rubrum and Trichophyton mentagrophytes human-type (synonym, Trichophyton interdigitale (anthropophilic)) are major causative pathogens of tinea unguium. For suitable diagnosis and treatment, rapid and accurate identification of etiologic agents in clinical samples using reliable molecular based method is required. For identification of organisms causing tinea unguium, we developed a new real-time polymerase chain reaction (PCR) with a pan-fungal primer set and probe, as well as specific primer sets and probes for T. rubrum and T. mentagrophytes human-type. We designed two sets of primers from the internal transcribed spacer 1 (ITS1) region of fungal ribosomal DNA (rDNA) and three quadruple fluorescent probes, one for detection wide range pathogenic fungi and two for classification of T. rubrum and T. mentagrophytes by specific binding to different sites in the ITS1 region. We investigated the specificity of these primer sets and probes using fungal genomic DNA, and also examined 42 clinical specimens with our real-time PCR. The primers and probes specifically detected T. rubrum, T. mentagrophytes, and a wide range of pathogenic fungi. The causative pathogens were identified in 42 nail and skin samples from 32 patients. The total time required for identification of fungal species in each clinical specimen was about 3h. The copy number of each fungal DNA in the clinical specimens was estimated from the intensity of fluorescence simultaneously. This PCR system is one of the most rapid and sensitive methods available for diagnosing dermatophytosis, including tinea unguium and tinea pedis. Copyright © 2012 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.

Vector Quantization Algorithm Based on Associative Memories

NASA Astrophysics Data System (ADS)

Guzmán, Enrique; Pogrebnyak, Oleksiy; Yáñez, Cornelio; Manrique, Pablo

This paper presents a vector quantization algorithm for image compression based on extended associative memories. The proposed algorithm is divided in two stages. First, an associative network is generated applying the learning phase of the extended associative memories between a codebook generated by the LBG algorithm and a training set. This associative network is named EAM-codebook and represents a new codebook which is used in the next stage. The EAM-codebook establishes a relation between training set and the LBG codebook. Second, the vector quantization process is performed by means of the recalling stage of EAM using as associative memory the EAM-codebook. This process generates a set of the class indices to which each input vector belongs. With respect to the LBG algorithm, the main advantages offered by the proposed algorithm is high processing speed and low demand of resources (system memory); results of image compression and quality are presented.

Determining open cluster membership. A Bayesian framework for quantitative member classification

NASA Astrophysics Data System (ADS)

Stott, Jonathan J.

2018-01-01

Aims: My goal is to develop a quantitative algorithm for assessing open cluster membership probabilities. The algorithm is designed to work with single-epoch observations. In its simplest form, only one set of program images and one set of reference images are required. Methods: The algorithm is based on a two-stage joint astrometric and photometric assessment of cluster membership probabilities. The probabilities were computed within a Bayesian framework using any available prior information. Where possible, the algorithm emphasizes simplicity over mathematical sophistication. Results: The algorithm was implemented and tested against three observational fields using published survey data. M 67 and NGC 654 were selected as cluster examples while a third, cluster-free, field was used for the final test data set. The algorithm shows good quantitative agreement with the existing surveys and has a false-positive rate significantly lower than the astrometric or photometric methods used individually.

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

Bosler, Peter Andrew; Roesler, Erika Louise; Taylor, Mark A.

This article discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared. The commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. Stride Search is designed to work at all latitudes, while grid point searches may fail in polar regions. Results from the two algorithms are compared for the application of tropicalmore » cyclone detection, and shown to produce similar results for the same set of storm identification criteria. The time required for both algorithms to search the same data set is compared. Furthermore, Stride Search's ability to search extreme latitudes is demonstrated for the case of polar low detection.« less

Optic disc segmentation: level set methods and blood vessels inpainting

NASA Astrophysics Data System (ADS)

Almazroa, A.; Sun, Weiwei; Alodhayb, Sami; Raahemifar, Kaamran; Lakshminarayanan, Vasudevan

2017-03-01

Segmenting the optic disc (OD) is an important and essential step in creating a frame of reference for diagnosing optic nerve head (ONH) pathology such as glaucoma. Therefore, a reliable OD segmentation technique is necessary for automatic screening of ONH abnormalities. The main contribution of this paper is in presenting a novel OD segmentation algorithm based on applying a level set method on a localized OD image. To prevent the blood vessels from interfering with the level set process, an inpainting technique is applied. The algorithm is evaluated using a new retinal fundus image dataset called RIGA (Retinal Images for Glaucoma Analysis). In the case of low quality images, a double level set is applied in which the first level set is considered to be a localization for the OD. Five hundred and fifty images are used to test the algorithm accuracy as well as its agreement with manual markings by six ophthalmologists. The accuracy of the algorithm in marking the optic disc area and centroid is 83.9%, and the best agreement is observed between the results of the algorithm and manual markings in 379 images.

Calibration and Sediment Load Algorithms for an Acoustic Sediment Flux Probe

DTIC Science & Technology

1994-06-01

Office of Management and Budget, Paperwork Reduction Project (0704-0118) Washington DC 20503. 1 . AGENCY USE ONLY (Leave blank) 2. REPORT DATE 3. REPORT... 1 IL BACKGROUND THEORY...BACKSCATITER TESTS ........................ 32 1 . EVaimental Tank and Tst V smd ..................................................... 32 2. Sdiment Collection

A Review on Real-Time 3D Ultrasound Imaging Technology

PubMed Central

Zeng, Zhaozheng

2017-01-01

Real-time three-dimensional (3D) ultrasound (US) has attracted much more attention in medical researches because it provides interactive feedback to help clinicians acquire high-quality images as well as timely spatial information of the scanned area and hence is necessary in intraoperative ultrasound examinations. Plenty of publications have been declared to complete the real-time or near real-time visualization of 3D ultrasound using volumetric probes or the routinely used two-dimensional (2D) probes. So far, a review on how to design an interactive system with appropriate processing algorithms remains missing, resulting in the lack of systematic understanding of the relevant technology. In this article, previous and the latest work on designing a real-time or near real-time 3D ultrasound imaging system are reviewed. Specifically, the data acquisition techniques, reconstruction algorithms, volume rendering methods, and clinical applications are presented. Moreover, the advantages and disadvantages of state-of-the-art approaches are discussed in detail. PMID:28459067

Probing optimal measurement configuration for optical scatterometry by the multi-objective genetic algorithm

NASA Astrophysics Data System (ADS)

Chen, Xiuguo; Gu, Honggang; Jiang, Hao; Zhang, Chuanwei; Liu, Shiyuan

2018-04-01

Measurement configuration optimization (MCO) is a ubiquitous and important issue in optical scatterometry, whose aim is to probe the optimal combination of measurement conditions, such as wavelength, incidence angle, azimuthal angle, and/or polarization directions, to achieve a higher measurement precision for a given measuring instrument. In this paper, the MCO problem is investigated and formulated as a multi-objective optimization problem, which is then solved by the multi-objective genetic algorithm (MOGA). The case study on the Mueller matrix scatterometry for the measurement of a Si grating verifies the feasibility of the MOGA in handling the MCO problem in optical scatterometry by making a comparison with the Monte Carlo simulations. Experiments performed at the achieved optimal measurement configuration also show good agreement between the measured and calculated best-fit Mueller matrix spectra. The proposed MCO method based on MOGA is expected to provide a more general and practical means to solve the MCO problem in the state-of-the-art optical scatterometry.

Spatiotemporal matrix image formation for programmable ultrasound scanners

NASA Astrophysics Data System (ADS)

Berthon, Beatrice; Morichau-Beauchant, Pierre; Porée, Jonathan; Garofalakis, Anikitos; Tavitian, Bertrand; Tanter, Mickael; Provost, Jean

2018-02-01

As programmable ultrasound scanners become more common in research laboratories, it is increasingly important to develop robust software-based image formation algorithms that can be obtained in a straightforward fashion for different types of probes and sequences with a small risk of error during implementation. In this work, we argue that as the computational power keeps increasing, it is becoming practical to directly implement an approximation to the matrix operator linking reflector point targets to the corresponding radiofrequency signals via thoroughly validated and widely available simulations software. Once such a spatiotemporal forward-problem matrix is constructed, standard and thus highly optimized inversion procedures can be leveraged to achieve very high quality images in real time. Specifically, we show that spatiotemporal matrix image formation produces images of similar or enhanced quality when compared against standard delay-and-sum approaches in phantoms and in vivo, and show that this approach can be used to form images even when using non-conventional probe designs for which adapted image formation algorithms are not readily available.

A Review on Real-Time 3D Ultrasound Imaging Technology.

PubMed

Huang, Qinghua; Zeng, Zhaozheng

2017-01-01

Real-time three-dimensional (3D) ultrasound (US) has attracted much more attention in medical researches because it provides interactive feedback to help clinicians acquire high-quality images as well as timely spatial information of the scanned area and hence is necessary in intraoperative ultrasound examinations. Plenty of publications have been declared to complete the real-time or near real-time visualization of 3D ultrasound using volumetric probes or the routinely used two-dimensional (2D) probes. So far, a review on how to design an interactive system with appropriate processing algorithms remains missing, resulting in the lack of systematic understanding of the relevant technology. In this article, previous and the latest work on designing a real-time or near real-time 3D ultrasound imaging system are reviewed. Specifically, the data acquisition techniques, reconstruction algorithms, volume rendering methods, and clinical applications are presented. Moreover, the advantages and disadvantages of state-of-the-art approaches are discussed in detail.

3D ultrasound image guidance system used in RF uterine adenoma and uterine bleeding ablation system

NASA Astrophysics Data System (ADS)

Ding, Mingyue; Luo, Xiaoan; Cai, Chao; Zhou, Chengping; Fenster, Aaron

2006-03-01

Uterine adenoma and uterine bleeding are the two most prevalent diseases in Chinese women. Many women lose their fertility from these diseases. Currently, a minimally invasive ablation system using an RF button electrode is being used in Chinese hospitals to destroy tumor cells or stop bleeding. In this paper, we report on a 3D US guidance system developed to avoid accidents or death of the patient by inaccurate localization of the tumor position during treatment. A 3D US imaging system using a rotational scanning approach of an abdominal probe was built. In order to reduce the distortion produced when the rotational axis is not collinear with the central beam of the probe, a new 3D reconstruction algorithm is used. Then, a fast 3D needle segmentation algorithm is used to find the electrode. Finally, the tip of electrode is determined along the segmented 3D needle and the whole electrode is displayed. Experiments with a water phantom demonstrated the feasibility of our approach.

In vivo light scattering for the detection of cancerous and precancerous lesions of the cervix

PubMed Central

Mourant, Judith R.; Powers, Tamara M.; Bocklage, Thérese J.; Greene, Heather M.; Dorin, Maxine H.; Waxman, Alan G.; Zsemlye, Meggan M.; Smith, Harriet O.

2009-01-01

A non-invasive optical diagnostic system for detection of cancerous and precancerous lesions of the cervix was evaluated, in vivo. The optical system included a fiber optic probe designed to measure polarized and unpolarized light transport properties of a small volume of tissue. An algorithm for diagnosing tissue based on the optical measurements was developed which used four optical properties, three of which were related to light scattering properties and the fourth of which was related to hemoglobin concentration. A sensitivity of ∼77% and specificities in the mid 60's were obtained for separating high grade squamous intraepithelial lesions and cancer from other pathologies and normal tissue. The use of different cross-validation methods in algorithm development is analyzed and the relative difficulties of diagnosing certain pathologies is assessed. Furthermore, the robustness of the optical system for use by different doctors and to changes in fiber optic probe were also assessed and potential improvements in the optical system are discussed. PMID:19340117

Pressure modulation algorithm to separate cerebral hemodynamic signals from extracerebral artifacts

PubMed Central

Baker, Wesley B.; Parthasarathy, Ashwin B.; Ko, Tiffany S.; Busch, David R.; Abramson, Kenneth; Tzeng, Shih-Yu; Mesquita, Rickson C.; Durduran, Turgut; Greenberg, Joel H.; Kung, David K.; Yodh, Arjun G.

2015-01-01

Abstract. We introduce and validate a pressure measurement paradigm that reduces extracerebral contamination from superficial tissues in optical monitoring of cerebral blood flow with diffuse correlation spectroscopy (DCS). The scheme determines subject-specific contributions of extracerebral and cerebral tissues to the DCS signal by utilizing probe pressure modulation to induce variations in extracerebral blood flow. For analysis, the head is modeled as a two-layer medium and is probed with long and short source-detector separations. Then a combination of pressure modulation and a modified Beer-Lambert law for flow enables experimenters to linearly relate differential DCS signals to cerebral and extracerebral blood flow variation without a priori anatomical information. We demonstrate the algorithm’s ability to isolate cerebral blood flow during a finger-tapping task and during graded scalp ischemia in healthy adults. Finally, we adapt the pressure modulation algorithm to ameliorate extracerebral contamination in monitoring of cerebral blood oxygenation and blood volume by near-infrared spectroscopy. PMID:26301255

A Modified MinMax k-Means Algorithm Based on PSO.

PubMed

Wang, Xiaoyan; Bai, Yanping

The MinMax k -means algorithm is widely used to tackle the effect of bad initialization by minimizing the maximum intraclustering errors. Two parameters, including the exponent parameter and memory parameter, are involved in the executive process. Since different parameters have different clustering errors, it is crucial to choose appropriate parameters. In the original algorithm, a practical framework is given. Such framework extends the MinMax k -means to automatically adapt the exponent parameter to the data set. It has been believed that if the maximum exponent parameter has been set, then the programme can reach the lowest intraclustering errors. However, our experiments show that this is not always correct. In this paper, we modified the MinMax k -means algorithm by PSO to determine the proper values of parameters which can subject the algorithm to attain the lowest clustering errors. The proposed clustering method is tested on some favorite data sets in several different initial situations and is compared to the k -means algorithm and the original MinMax k -means algorithm. The experimental results indicate that our proposed algorithm can reach the lowest clustering errors automatically.

A comprehensive performance evaluation on the prediction results of existing cooperative transcription factors identification algorithms.

PubMed

Lai, Fu-Jou; Chang, Hong-Tsun; Huang, Yueh-Min; Wu, Wei-Sheng

2014-01-01

Eukaryotic transcriptional regulation is known to be highly connected through the networks of cooperative transcription factors (TFs). Measuring the cooperativity of TFs is helpful for understanding the biological relevance of these TFs in regulating genes. The recent advances in computational techniques led to various predictions of cooperative TF pairs in yeast. As each algorithm integrated different data resources and was developed based on different rationales, it possessed its own merit and claimed outperforming others. However, the claim was prone to subjectivity because each algorithm compared with only a few other algorithms and only used a small set of performance indices for comparison. This motivated us to propose a series of indices to objectively evaluate the prediction performance of existing algorithms. And based on the proposed performance indices, we conducted a comprehensive performance evaluation. We collected 14 sets of predicted cooperative TF pairs (PCTFPs) in yeast from 14 existing algorithms in the literature. Using the eight performance indices we adopted/proposed, the cooperativity of each PCTFP was measured and a ranking score according to the mean cooperativity of the set was given to each set of PCTFPs under evaluation for each performance index. It was seen that the ranking scores of a set of PCTFPs vary with different performance indices, implying that an algorithm used in predicting cooperative TF pairs is of strength somewhere but may be of weakness elsewhere. We finally made a comprehensive ranking for these 14 sets. The results showed that Wang J's study obtained the best performance evaluation on the prediction of cooperative TF pairs in yeast. In this study, we adopted/proposed eight performance indices to make a comprehensive performance evaluation on the prediction results of 14 existing cooperative TFs identification algorithms. Most importantly, these proposed indices can be easily applied to measure the performance of new algorithms developed in the future, thus expedite progress in this research field.

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

NASA Astrophysics Data System (ADS)

Min, Junhong; Vonesch, Cédric; Kirshner, Hagai; Carlini, Lina; Olivier, Nicolas; Holden, Seamus; Manley, Suliana; Ye, Jong Chul; Unser, Michael

2014-04-01

Super resolution microscopy such as STORM and (F)PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow temporal resolution which is a serious limitation when investigating live-cell dynamics. Here, we present an algorithm for high-density super-resolution microscopy which combines a sparsity-promoting formulation with a Taylor series approximation of the PSF. Our algorithm is designed to provide unbiased localization on continuous space and high recall rates for high-density imaging, and to have orders-of-magnitude shorter run times compared to previous high-density algorithms. We validated our algorithm on both simulated and experimental data, and demonstrated live-cell imaging with temporal resolution of 2.5 seconds by recovering fast ER dynamics.

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

PubMed Central

Min, Junhong; Vonesch, Cédric; Kirshner, Hagai; Carlini, Lina; Olivier, Nicolas; Holden, Seamus; Manley, Suliana; Ye, Jong Chul; Unser, Michael

2014-01-01

Super resolution microscopy such as STORM and (F)PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow temporal resolution which is a serious limitation when investigating live-cell dynamics. Here, we present an algorithm for high-density super-resolution microscopy which combines a sparsity-promoting formulation with a Taylor series approximation of the PSF. Our algorithm is designed to provide unbiased localization on continuous space and high recall rates for high-density imaging, and to have orders-of-magnitude shorter run times compared to previous high-density algorithms. We validated our algorithm on both simulated and experimental data, and demonstrated live-cell imaging with temporal resolution of 2.5 seconds by recovering fast ER dynamics. PMID:24694686

Accessing primary care Big Data: the development of a software algorithm to explore the rich content of consultation records.

PubMed

MacRae, J; Darlow, B; McBain, L; Jones, O; Stubbe, M; Turner, N; Dowell, A

2015-08-21

To develop a natural language processing software inference algorithm to classify the content of primary care consultations using electronic health record Big Data and subsequently test the algorithm's ability to estimate the prevalence and burden of childhood respiratory illness in primary care. Algorithm development and validation study. To classify consultations, the algorithm is designed to interrogate clinical narrative entered as free text, diagnostic (Read) codes created and medications prescribed on the day of the consultation. Thirty-six consenting primary care practices from a mixed urban and semirural region of New Zealand. Three independent sets of 1200 child consultation records were randomly extracted from a data set of all general practitioner consultations in participating practices between 1 January 2008-31 December 2013 for children under 18 years of age (n=754,242). Each consultation record within these sets was independently classified by two expert clinicians as respiratory or non-respiratory, and subclassified according to respiratory diagnostic categories to create three 'gold standard' sets of classified records. These three gold standard record sets were used to train, test and validate the algorithm. Sensitivity, specificity, positive predictive value and F-measure were calculated to illustrate the algorithm's ability to replicate judgements of expert clinicians within the 1200 record gold standard validation set. The algorithm was able to identify respiratory consultations in the 1200 record validation set with a sensitivity of 0.72 (95% CI 0.67 to 0.78) and a specificity of 0.95 (95% CI 0.93 to 0.98). The positive predictive value of algorithm respiratory classification was 0.93 (95% CI 0.89 to 0.97). The positive predictive value of the algorithm classifying consultations as being related to specific respiratory diagnostic categories ranged from 0.68 (95% CI 0.40 to 1.00; other respiratory conditions) to 0.91 (95% CI 0.79 to 1.00; throat infections). A software inference algorithm that uses primary care Big Data can accurately classify the content of clinical consultations. This algorithm will enable accurate estimation of the prevalence of childhood respiratory illness in primary care and resultant service utilisation. The methodology can also be applied to other areas of clinical care. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Framework for reanalysis of publicly available Affymetrix® GeneChip® data sets based on functional regions of interest.

PubMed

Saka, Ernur; Harrison, Benjamin J; West, Kirk; Petruska, Jeffrey C; Rouchka, Eric C

2017-12-06

Since the introduction of microarrays in 1995, researchers world-wide have used both commercial and custom-designed microarrays for understanding differential expression of transcribed genes. Public databases such as ArrayExpress and the Gene Expression Omnibus (GEO) have made millions of samples readily available. One main drawback to microarray data analysis involves the selection of probes to represent a specific transcript of interest, particularly in light of the fact that transcript-specific knowledge (notably alternative splicing) is dynamic in nature. We therefore developed a framework for reannotating and reassigning probe groups for Affymetrix® GeneChip® technology based on functional regions of interest. This framework addresses three issues of Affymetrix® GeneChip® data analyses: removing nonspecific probes, updating probe target mapping based on the latest genome knowledge and grouping probes into gene, transcript and region-based (UTR, individual exon, CDS) probe sets. Updated gene and transcript probe sets provide more specific analysis results based on current genomic and transcriptomic knowledge. The framework selects unique probes, aligns them to gene annotations and generates a custom Chip Description File (CDF). The analysis reveals only 87% of the Affymetrix® GeneChip® HG-U133 Plus 2 probes uniquely align to the current hg38 human assembly without mismatches. We also tested new mappings on the publicly available data series using rat and human data from GSE48611 and GSE72551 obtained from GEO, and illustrate that functional grouping allows for the subtle detection of regions of interest likely to have phenotypical consequences. Through reanalysis of the publicly available data series GSE48611 and GSE72551, we profiled the contribution of UTR and CDS regions to the gene expression levels globally. The comparison between region and gene based results indicated that the detected expressed genes by gene-based and region-based CDFs show high consistency and regions based results allows us to detection of changes in transcript formation.

Delaunay based algorithm for finding polygonal voids in planar point sets

NASA Astrophysics Data System (ADS)

Alonso, R.; Ojeda, J.; Hitschfeld, N.; Hervías, C.; Campusano, L. E.

2018-01-01

This paper presents a new algorithm to find under-dense regions called voids inside a 2D point set. The algorithm starts from terminal-edges (local longest-edges) in a Delaunay triangulation and builds the largest possible low density terminal-edge regions around them. A terminal-edge region can represent either an entire void or part of a void (subvoid). Using artificial data sets, the case of voids that are detected as several adjacent subvoids is analyzed and four subvoid joining criteria are proposed and evaluated. Since this work is inspired on searches of a more robust, effective and efficient algorithm to find 3D cosmological voids the evaluation of the joining criteria considers this context. However, the design of the algorithm permits its adaption to the requirements of any similar application.

Rough sets and Laplacian score based cost-sensitive feature selection

PubMed Central

Yu, Shenglong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of “good” features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms. PMID:29912884

Rough sets and Laplacian score based cost-sensitive feature selection.

PubMed

Yu, Shenglong; Zhao, Hong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of "good" features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms.

Mismatch and G-Stack Modulated Probe Signals on SNP Microarrays

PubMed Central

Binder, Hans; Fasold, Mario; Glomb, Torsten

2009-01-01

Background Single nucleotide polymorphism (SNP) arrays are important tools widely used for genotyping and copy number estimation. This technology utilizes the specific affinity of fragmented DNA for binding to surface-attached oligonucleotide DNA probes. We analyze the variability of the probe signals of Affymetrix GeneChip SNP arrays as a function of the probe sequence to identify relevant sequence motifs which potentially cause systematic biases of genotyping and copy number estimates. Methodology/Principal Findings The probe design of GeneChip SNP arrays enables us to disentangle different sources of intensity modulations such as the number of mismatches per duplex, matched and mismatched base pairings including nearest and next-nearest neighbors and their position along the probe sequence. The effect of probe sequence was estimated in terms of triple-motifs with central matches and mismatches which include all 256 combinations of possible base pairings. The probe/target interactions on the chip can be decomposed into nearest neighbor contributions which correlate well with free energy terms of DNA/DNA-interactions in solution. The effect of mismatches is about twice as large as that of canonical pairings. Runs of guanines (G) and the particular type of mismatched pairings formed in cross-allelic probe/target duplexes constitute sources of systematic biases of the probe signals with consequences for genotyping and copy number estimates. The poly-G effect seems to be related to the crowded arrangement of probes which facilitates complex formation of neighboring probes with at minimum three adjacent G's in their sequence. Conclusions The applied method of “triple-averaging” represents a model-free approach to estimate the mean intensity contributions of different sequence motifs which can be applied in calibration algorithms to correct signal values for sequence effects. Rules for appropriate sequence corrections are suggested. PMID:19924253

A new probe using hybrid virus-dye nanoparticles for near-infrared fluorescence tomography

NASA Astrophysics Data System (ADS)

Wu, Changfeng; Barnhill, Hannah; Liang, Xiaoping; Wang, Qian; Jiang, Huabei

2005-11-01

A fluorescent probe based on bionanoparticle cowpea mosaic virus has been developed for near-infrared fluorescence tomography. A unique advantage of this probe is that over 30 dye molecules can be loaded onto each viral nanoparticle with an average diameter of 30 nm, making high local dye concentration (∼1.8 mM) possible without significant fluorescence quenching. This ability of high loading of local dye concentration would increase the signal-to-noise ratio considerably, thus sensitivity for detection. We demonstrate successful tomographic fluorescence imaging of a target containing the virus-dye nanoparticles embedded in a tissue-like phantom. Tomographic fluorescence data were obtained through a multi-channel frequency-domain system and the spatial maps of fluorescence quantum yield were recovered with a finite-element-based reconstruction algorithm.

Frequency-Domain Streak Camera and Tomography for Ultrafast Imaging of Evolving and Channeled Plasma Accelerator Structures

NASA Astrophysics Data System (ADS)

Li, Zhengyan; Zgadzaj, Rafal; Wang, Xiaoming; Reed, Stephen; Dong, Peng; Downer, Michael C.

2010-11-01

We demonstrate a prototype Frequency Domain Streak Camera (FDSC) that can capture the picosecond time evolution of the plasma accelerator structure in a single shot. In our prototype Frequency-Domain Streak Camera, a probe pulse propagates obliquely to a sub-picosecond pump pulse that creates an evolving nonlinear index "bubble" in fused silica glass, supplementing a conventional Frequency Domain Holographic (FDH) probe-reference pair that co-propagates with the "bubble". Frequency Domain Tomography (FDT) generalizes Frequency-Domain Streak Camera by probing the "bubble" from multiple angles and reconstructing its morphology and evolution using algorithms similar to those used in medical CAT scans. Multiplexing methods (Temporal Multiplexing and Angular Multiplexing) improve data storage and processing capability, demonstrating a compact Frequency Domain Tomography system with a single spectrometer.

Oligo Design: a computer program for development of probes for oligonucleotide microarrays.

PubMed

Herold, Keith E; Rasooly, Avraham

2003-12-01

Oligonucleotide microarrays have demonstrated potential for the analysis of gene expression, genotyping, and mutational analysis. Our work focuses primarily on the detection and identification of bacteria based on known short sequences of DNA. Oligo Design, the software described here, automates several design aspects that enable the improved selection of oligonucleotides for use with microarrays for these applications. Two major features of the program are: (i) a tiling algorithm for the design of short overlapping temperature-matched oligonucleotides of variable length, which are useful for the analysis of single nucleotide polymorphisms and (ii) a set of tools for the analysis of multiple alignments of gene families and related short DNA sequences, which allow for the identification of conserved DNA sequences for PCR primer selection and variable DNA sequences for the selection of unique probes for identification. Note that the program does not address the full genome perspective but, instead, is focused on the genetic analysis of short segments of DNA. The program is Internet-enabled and includes a built-in browser and the automated ability to download sequences from GenBank by specifying the GI number. The program also includes several utilities, including audio recital of a DNA sequence (useful for verifying sequences against a written document), a random sequence generator that provides insight into the relationship between melting temperature and GC content, and a PCR calculator.

Molecular dynamics force-field refinement against quasi-elastic neutron scattering data

DOE PAGES

Borreguero Calvo, Jose M.; Lynch, Vickie E.

2015-11-23

Quasi-elastic neutron scattering (QENS) is one of the experimental techniques of choice for probing the dynamics at length and time scales that are also in the realm of full-atom molecular dynamics (MD) simulations. This overlap enables extension of current fitting methods that use time-independent equilibrium measurements to new methods fitting against dynamics data. We present an algorithm that fits simulation-derived incoherent dynamical structure factors against QENS data probing the diffusive dynamics of the system. We showcase the difficulties inherent to this type of fitting problem, namely, the disparity between simulation and experiment environment, as well as limitations in the simulationmore » due to incomplete sampling of phase space. We discuss a methodology to overcome these difficulties and apply it to a set of full-atom MD simulations for the purpose of refining the force-field parameter governing the activation energy of methyl rotation in the octa-methyl polyhedral oligomeric silsesquioxane molecule. Our optimal simulated activation energy agrees with the experimentally derived value up to a 5% difference, well within experimental error. We believe the method will find applicability to other types of diffusive motions and other representation of the systems such as coarse-grain models where empirical fitting is essential. In addition, the refinement method can be extended to the coherent dynamic structure factor with no additional effort.« less

MRPrimerW: a tool for rapid design of valid high-quality primers for multiple target qPCR experiments

PubMed Central

Kim, Hyerin; Kang, NaNa; An, KyuHyeon; Koo, JaeHyung; Kim, Min-Soo

2016-01-01

Design of high-quality primers for multiple target sequences is essential for qPCR experiments, but is challenging due to the need to consider both homology tests on off-target sequences and the same stringent filtering constraints on the primers. Existing web servers for primer design have major drawbacks, including requiring the use of BLAST-like tools for homology tests, lack of support for ranking of primers, TaqMan probes and simultaneous design of primers against multiple targets. Due to the large-scale computational overhead, the few web servers supporting homology tests use heuristic approaches or perform homology tests within a limited scope. Here, we describe the MRPrimerW, which performs complete homology testing, supports batch design of primers for multi-target qPCR experiments, supports design of TaqMan probes and ranks the resulting primers to return the top-1 best primers to the user. To ensure high accuracy, we adopted the core algorithm of a previously reported MapReduce-based method, MRPrimer, but completely redesigned it to allow users to receive query results quickly in a web interface, without requiring a MapReduce cluster or a long computation. MRPrimerW provides primer design services and a complete set of 341 963 135 in silico validated primers covering 99% of human and mouse genes. Free access: http://MRPrimerW.com. PMID:27154272

CHILES Con Pol: Probing galaxy evolution, the dark Universe, and cosmic magnetism with a deep 1000 hour Jansky VLA survey

NASA Astrophysics Data System (ADS)

Hales, Christopher A.; Chiles Con Pol Collaboration

2014-04-01

We recently started a 1000 hour campaign to observe 0.2 square degrees of the COSMOS field in full polarization continuum at 1.4 GHz with the Jansky VLA, as part of a joint program with the spectral line COSMOS HI Large Extragalactic Survey (CHILES). When complete, we expect our CHILES Continuum Polarization (CHILES Con Pol) survey to reach an unprecedented SKA-era sensitivity of 0.7 uJy per 4 arcsecond FWHM beam. Here we present the key goals of CHILES Con Pol, which are to (i) produce a source catalog of legacy value to the astronomical community, (ii) measure differential source counts in total intensity, linear polarization, and circular polarization in order to constrain the redshift and luminosity distributions of source populations, (iii) perform a novel weak lensing study using radio polarization as an indicator of intrinsic alignment to better study dark energy and dark matter, and (iv) probe the unknown origin of cosmic magnetism by measuring the strength and structure of intergalactic magnetic fields in the filaments of large scale structure. The CHILES Con Pol source catalog will be a useful resource for upcoming wide-field surveys by acting as a training set for machine learning algorithms, which can then be used to identify and classify radio sources in regions lacking deep multiwavelength coverage.

Earth Probe Total Ozone Mapping Spectrometer (TOMS) Data Product User's Guide

NASA Technical Reports Server (NTRS)

McPeters, R.; Bhartia, P. K.; Krueger, A.; Herman, J.; Wellemeyer, C.; Seftor, C.; Jaross, G.; Torres, O.; Moy, L.; Labow, G.;

Development and Validation of Various Phenotyping Algorithms for Diabetes Mellitus Using Data from Electronic Health Records.

PubMed

Esteban, Santiago; Rodríguez Tablado, Manuel; Peper, Francisco; Mahumud, Yamila S; Ricci, Ricardo I; Kopitowski, Karin; Terrasa, Sergio

2017-01-01

Precision medicine requires extremely large samples. Electronic health records (EHR) are thought to be a cost-effective source of data for that purpose. Phenotyping algorithms help reduce classification errors, making EHR a more reliable source of information for research. Four algorithm development strategies for classifying patients according to their diabetes status (diabetics; non-diabetics; inconclusive) were tested (one codes-only algorithm; one boolean algorithm, four statistical learning algorithms and six stacked generalization meta-learners). The best performing algorithms within each strategy were tested on the validation set. The stacked generalization algorithm yielded the highest Kappa coefficient value in the validation set (0.95 95% CI 0.91, 0.98). The implementation of these algorithms allows for the exploitation of data from thousands of patients accurately, greatly reducing the costs of constructing retrospective cohorts for research.

An Evaluation of an Algorithm for Linear Inequalities and Its Applications

NASA Technical Reports Server (NTRS)

Jurgensen, J.

1973-01-01

An algorithm is presented for obtaining a solution alpha to a set of inequalities (A alpha) 0 where A is an N x m-matrix and alpha is an m-vector. If the set of inequalities is consistant, then the algorithm is guaranteed to arrive at a solution in a finite number of steps. Also, if in the iteration, a negative vector is obtained, then the initial set of inequalities is inconsistant, and the iteration is terminated.

Probing the space of toric quiver theories

NASA Astrophysics Data System (ADS)

Hewlett, Joseph; He, Yang-Hui

2010-03-01

We demonstrate a practical and efficient method for generating toric Calabi-Yau quiver theories, applicable to both D3 and M2 brane world-volume physics. A new analytic method is presented at low order parametres and an algorithm for the general case is developed which has polynomial complexity in the number of edges in the quiver. Using this algorithm, carefully implemented, we classify the quiver diagram and assign possible superpotentials for various small values of the number of edges and nodes. We examine some preliminary statistics on this space of toric quiver theories.

Efficient quantum algorithm for computing n-time correlation functions.

PubMed

Pedernales, J S; Di Candia, R; Egusquiza, I L; Casanova, J; Solano, E

2014-07-11

We propose a method for computing n-time correlation functions of arbitrary spinorial, fermionic, and bosonic operators, consisting of an efficient quantum algorithm that encodes these correlations in an initially added ancillary qubit for probe and control tasks. For spinorial and fermionic systems, the reconstruction of arbitrary n-time correlation functions requires the measurement of two ancilla observables, while for bosonic variables time derivatives of the same observables are needed. Finally, we provide examples applicable to different quantum platforms in the frame of the linear response theory.

HECLIB. Volume 2: HECDSS Subroutines Programmer’s Manual

DTIC Science & Technology

1991-05-01

algorithm and hierarchical design for database accesses. This algorithm provides quick access to data sets and an efficient means of adding new data set...Description of How DSS Works DSS version 6 utilizes a modified hash algorithm based upon the pathname to store and retrieve data. This structure allows...balancing disk space and record access times. A variation in this algorithm is for "stable" files. In a stable file, a hash table is not utilized

Finite Set Control Transcription for Optimal Control Applications

DTIC Science & Technology

2009-05-01

Figures 1.1 The Parameters of x . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.1 Categories of Optimization Algorithms ...Programming (NLP) algorithm , such as SNOPT2 (hereafter, called the optimizer). The Finite Set Control Transcription (FSCT) method is essentially a...artificial neural networks, ge- netic algorithms , or combinations thereof for analysis.4,5 Indeed, an actual biological neural network is an example of

Influenza Risk Management: Lessons Learned from an A(H1N1) pdm09 Outbreak Investigation in an Operational Military Setting

DTIC Science & Technology

2013-07-10

of the virus in Spain was detected during an outbreak investigation of influenza -like illness (ILI) in soldiers from an engineering military academy...SwInfA primer and probe set) and specific A(H1N1) pdm09 influenza A viruses using SwH1 primer and probe set developed by CDC, Atlanta (WHO...CY062374, CY062375 and CY062376. Viral culture Influenza viruses were isolated from clinical samples by infecting Madin Darby Canine Kidney (MDCK

Sampling solution traces for the problem of sorting permutations by signed reversals

PubMed Central

2012-01-01

Background Traditional algorithms to solve the problem of sorting by signed reversals output just one optimal solution while the space of all optimal solutions can be huge. A so-called trace represents a group of solutions which share the same set of reversals that must be applied to sort the original permutation following a partial ordering. By using traces, we therefore can represent the set of optimal solutions in a more compact way. Algorithms for enumerating the complete set of traces of solutions were developed. However, due to their exponential complexity, their practical use is limited to small permutations. A partial enumeration of traces is a sampling of the complete set of traces and can be an alternative for the study of distinct evolutionary scenarios of big permutations. Ideally, the sampling should be done uniformly from the space of all optimal solutions. This is however conjectured to be ♯P-complete. Results We propose and evaluate three algorithms for producing a sampling of the complete set of traces that instead can be shown in practice to preserve some of the characteristics of the space of all solutions. The first algorithm (RA) performs the construction of traces through a random selection of reversals on the list of optimal 1-sequences. The second algorithm (DFALT) consists in a slight modification of an algorithm that performs the complete enumeration of traces. Finally, the third algorithm (SWA) is based on a sliding window strategy to improve the enumeration of traces. All proposed algorithms were able to enumerate traces for permutations with up to 200 elements. Conclusions We analysed the distribution of the enumerated traces with respect to their height and average reversal length. Various works indicate that the reversal length can be an important aspect in genome rearrangements. The algorithms RA and SWA show a tendency to lose traces with high average reversal length. Such traces are however rare, and qualitatively our results show that, for testable-sized permutations, the algorithms DFALT and SWA produce distributions which approximate the reversal length distributions observed with a complete enumeration of the set of traces. PMID:22704580

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

Hirode, Mitsuhiro; Ono, Atsushi; Miyagishima, Toshikazu

We have constructed a large-scale transcriptome database of rat liver treated with various drugs. In an effort to identify a biomarker for diagnosis of hepatic phospholipidosis, we extracted 78 probe sets of rat hepatic genes from data of 5 drugs, amiodarone, amitriptyline, clomipramine, imipramine, and ketoconazole, which actually induced this phenotype. Principal component analysis (PCA) using these probes clearly separated dose- and time-dependent clusters of treated groups from their controls. Moreover, 6 drugs (chloramphenicol, chlorpromazine, gentamicin, perhexiline, promethazine, and tamoxifen), which were reported to cause phospholipidosis but judged as negative by histopathological examination, were designated as positive by PCA usingmore » these probe sets. Eight drugs (carbon tetrachloride, coumarin, tetracycline, metformin, hydroxyzine, diltiazem, 2-bromoethylamine, and ethionamide), which showed phospholipidosis-like vacuolar formation in the histopathology, could be distinguished from the typical drugs causing phospholipidosis. Moreover, the possible induction of phospholipidosis was predictable by the expression of these genes 24 h after single administration in some of the drugs. We conclude that these identified 78 probe sets could be useful for diagnosis of phospholipidosis, and that toxicogenomics would be a promising approach for prediction of this type of toxicity.« less

Mapping-by-sequencing in complex polyploid genomes using genic sequence capture: a case study to map yellow rust resistance in hexaploid wheat.

PubMed

Gardiner, Laura-Jayne; Bansept-Basler, Pauline; Olohan, Lisa; Joynson, Ryan; Brenchley, Rachel; Hall, Neil; O'Sullivan, Donal M; Hall, Anthony

2016-08-01

Previously we extended the utility of mapping-by-sequencing by combining it with sequence capture and mapping sequence data to pseudo-chromosomes that were organized using wheat-Brachypodium synteny. This, with a bespoke haplotyping algorithm, enabled us to map the flowering time locus in the diploid wheat Triticum monococcum L. identifying a set of deleted genes (Gardiner et al., 2014). Here, we develop this combination of gene enrichment and sliding window mapping-by-synteny analysis to map the Yr6 locus for yellow stripe rust resistance in hexaploid wheat. A 110 MB NimbleGen capture probe set was used to enrich and sequence a doubled haploid mapping population of hexaploid wheat derived from an Avalon and Cadenza cross. The Yr6 locus was identified by mapping to the POPSEQ chromosomal pseudomolecules using a bespoke pipeline and algorithm (Chapman et al., 2015). Furthermore the same locus was identified using newly developed pseudo-chromosome sequences as a mapping reference that are based on the genic sequence used for sequence enrichment. The pseudo-chromosomes allow us to demonstrate the application of mapping-by-sequencing to even poorly defined polyploidy genomes where chromosomes are incomplete and sub-genome assemblies are collapsed. This analysis uniquely enabled us to: compare wheat genome annotations; identify the Yr6 locus - defining a smaller genic region than was previously possible; associate the interval with one wheat sub-genome and increase the density of SNP markers associated. Finally, we built the pipeline in iPlant, making it a user-friendly community resource for phenotype mapping. © 2016 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

Electromagnetic microscope compared with a conventional pulsed eddy-current probe

NASA Astrophysics Data System (ADS)

Podney, Walter N.

1998-03-01

A superconductive probe presently can detect a crack at a rivet hole that is two to three times smaller than the smallest crack detectable by a conventional probe. As the technology matures and noise resolution approaches a limit set by SQUIDS, approximately 1 fH, it will enable detecting submillimeter cracks down to approximately 15 mm.

Using phylogenetic probes for quantification of stable isotope labeling and microbial community analysis

DOEpatents

Brodie, Eoin L; DeSantis, Todd Z; Karaoz, Ulas; Andersen, Gary L

2014-12-09

Herein is described methods for a high-sensitivity means to measure the incorporation of stable isotope labeled substrates into RNA following stable isotope probing experiments (SIP). RNA is hybridized to a set of probes such as phylogenetic microarrays and isotope incorporation is quantified such as by secondary ion mass spectrometer imaging (NanoSIMS).

Expanded Processing Techniques for EMI Systems

DTIC Science & Technology

2012-07-01

possible to perform better target detection using physics-based algorithms and the entire data set, rather than simulating a simpler data set and mapping...possible to perform better target detection using physics-based algorithms and the entire data set, rather than simulating a simpler data set and...54! Figure 4.25: Plots of simulated MetalMapper data for two oblate spheroidal targets

Using linear polarization for LWIR hyperspectral sensing of liquid contaminants

NASA Astrophysics Data System (ADS)

Thériault, Jean-Marc; Fortin, Gilles; Lacasse, Paul; Bouffard, François; Lavoie, Hugo

2013-09-01

We report and analyze recent results obtained with the MoDDIFS sensor (Multi-option Differential Detection and Imaging Fourier Spectrometer) for the passive polarization sensing of liquid contaminants in the long wave infrared (LWIR). Field measurements of polarized spectral radiance done on ethylene glycol and SF96 probed at distances of 6.5 and 450 meters, respectively, have been used to develop and test a GLRT-type detection algorithm adapted for liquid contaminants. The GLRT detection results serve to establish the potential and advantage of probing the vertical and horizontal linear hyperspectral polarization components for improving liquid contaminants detection.

SamSelect: a sample sequence selection algorithm for quorum planted motif search on large DNA datasets.

PubMed

Yu, Qiang; Wei, Dingbang; Huo, Hongwei

2018-06-18

Given a set of t n-length DNA sequences, q satisfying 0 < q ≤ 1, and l and d satisfying 0 ≤ d < l < n, the quorum planted motif search (qPMS) finds l-length strings that occur in at least qt input sequences with up to d mismatches and is mainly used to locate transcription factor binding sites in DNA sequences. Existing qPMS algorithms have been able to efficiently process small standard datasets (e.g., t = 20 and n = 600), but they are too time consuming to process large DNA datasets, such as ChIP-seq datasets that contain thousands of sequences or more. We analyze the effects of t and q on the time performance of qPMS algorithms and find that a large t or a small q causes a longer computation time. Based on this information, we improve the time performance of existing qPMS algorithms by selecting a sample sequence set D' with a small t and a large q from the large input dataset D and then executing qPMS algorithms on D'. A sample sequence selection algorithm named SamSelect is proposed. The experimental results on both simulated and real data show (1) that SamSelect can select D' efficiently and (2) that the qPMS algorithms executed on D' can find implanted or real motifs in a significantly shorter time than when executed on D. We improve the ability of existing qPMS algorithms to process large DNA datasets from the perspective of selecting high-quality sample sequence sets so that the qPMS algorithms can find motifs in a short time in the selected sample sequence set D', rather than take an unfeasibly long time to search the original sequence set D. Our motif discovery method is an approximate algorithm.

Sparse sampling and reconstruction for electron and scanning probe microscope imaging

DOEpatents

Anderson, Hyrum; Helms, Jovana; Wheeler, Jason W.; Larson, Kurt W.; Rohrer, Brandon R.

2015-07-28

Systems and methods for conducting electron or scanning probe microscopy are provided herein. In a general embodiment, the systems and methods for conducting electron or scanning probe microscopy with an undersampled data set include: driving an electron beam or probe to scan across a sample and visit a subset of pixel locations of the sample that are randomly or pseudo-randomly designated; determining actual pixel locations on the sample that are visited by the electron beam or probe; and processing data collected by detectors from the visits of the electron beam or probe at the actual pixel locations and recovering a reconstructed image of the sample.

Automated video-based detection of nocturnal convulsive seizures in a residential care setting.

PubMed

Geertsema, Evelien E; Thijs, Roland D; Gutter, Therese; Vledder, Ben; Arends, Johan B; Leijten, Frans S; Visser, Gerhard H; Kalitzin, Stiliyan N

2018-06-01

People with epilepsy need assistance and are at risk of sudden death when having convulsive seizures (CS). Automated real-time seizure detection systems can help alert caregivers, but wearable sensors are not always tolerated. We determined algorithm settings and investigated detection performance of a video algorithm to detect CS in a residential care setting. The algorithm calculates power in the 2-6 Hz range relative to 0.5-12.5 Hz range in group velocity signals derived from video-sequence optical flow. A detection threshold was found using a training set consisting of video-electroencephalogaphy (EEG) recordings of 72 CS. A test set consisting of 24 full nights of 12 new subjects in residential care and additional recordings of 50 CS selected randomly was used to estimate performance. All data were analyzed retrospectively. The start and end of CS (generalized clonic and tonic-clonic seizures) and other seizures considered desirable to detect (long generalized tonic, hyperkinetic, and other major seizures) were annotated. The detection threshold was set to the value that obtained 97% sensitivity in the training set. Sensitivity, latency, and false detection rate (FDR) per night were calculated in the test set. A seizure was detected when the algorithm output exceeded the threshold continuously for 2 seconds. With the detection threshold determined in the training set, all CS were detected in the test set (100% sensitivity). Latency was ≤10 seconds in 78% of detections. Three/five hyperkinetic and 6/9 other major seizures were detected. Median FDR was 0.78 per night and no false detections occurred in 9/24 nights. Our algorithm could improve safety unobtrusively by automated real-time detection of CS in video registrations, with an acceptable latency and FDR. The algorithm can also detect some other motor seizures requiring assistance. © 2018 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.

Current algorithmic solutions for peptide-based proteomics data generation and identification.

PubMed

Hoopmann, Michael R; Moritz, Robert L

2013-02-01

Peptide-based proteomic data sets are ever increasing in size and complexity. These data sets provide computational challenges when attempting to quickly analyze spectra and obtain correct protein identifications. Database search and de novo algorithms must consider high-resolution MS/MS spectra and alternative fragmentation methods. Protein inference is a tricky problem when analyzing large data sets of degenerate peptide identifications. Combining multiple algorithms for improved peptide identification puts significant strain on computational systems when investigating large data sets. This review highlights some of the recent developments in peptide and protein identification algorithms for analyzing shotgun mass spectrometry data when encountering the aforementioned hurdles. Also explored are the roles that analytical pipelines, public spectral libraries, and cloud computing play in the evolution of peptide-based proteomics. Copyright © 2012 Elsevier Ltd. All rights reserved.

Community Analysis of Biofilters Using Fluorescence In Situ Hybridization Including a New Probe for the Xanthomonas Branch of the Class Proteobacteria

PubMed Central

Friedrich, Udo; Naismith, Michèle M.; Altendorf, Karlheinz; Lipski, André

1999-01-01

Domain-, class-, and subclass-specific rRNA-targeted probes were applied to investigate the microbial communities of three industrial and three laboratory-scale biofilters. The set of probes also included a new probe (named XAN818) specific for the Xanthomonas branch of the class Proteobacteria; this probe is described in this study. The members of the Xanthomonas branch do not hybridize with previously developed rRNA-targeted oligonucleotide probes for the α-, β-, and γ-Proteobacteria. Bacteria of the Xanthomonas branch accounted for up to 4.5% of total direct counts obtained with 4′,6-diamidino-2-phenylindole. In biofilter samples, the relative abundance of these bacteria was similar to that of the γ-Proteobacteria. Actinobacteria (gram-positive bacteria with a high G+C DNA content) and α-Proteobacteria were the most dominant groups. Detection rates obtained with probe EUB338 varied between about 40 and 70%. For samples with high contents of gram-positive bacteria, these percentages were substantially improved when the calculations were corrected for the reduced permeability of gram-positive bacteria when formaldehyde was used as a fixative. The set of applied bacterial class- and subclass-specific probes yielded, on average, 58.5% (± a standard deviation of 23.0%) of the corrected eubacterial detection rates, thus indicating the necessity of additional probes for studies of biofilter communities. The Xanthomonas-specific probe presented here may serve as an efficient tool for identifying potential phytopathogens. In situ hybridization proved to be a practical tool for microbiological studies of biofiltration systems. PMID:10427047

Microarray missing data imputation based on a set theoretic framework and biological knowledge.

PubMed

Gan, Xiangchao; Liew, Alan Wee-Chung; Yan, Hong

2006-01-01

Gene expressions measured using microarrays usually suffer from the missing value problem. However, in many data analysis methods, a complete data matrix is required. Although existing missing value imputation algorithms have shown good performance to deal with missing values, they also have their limitations. For example, some algorithms have good performance only when strong local correlation exists in data while some provide the best estimate when data is dominated by global structure. In addition, these algorithms do not take into account any biological constraint in their imputation. In this paper, we propose a set theoretic framework based on projection onto convex sets (POCS) for missing data imputation. POCS allows us to incorporate different types of a priori knowledge about missing values into the estimation process. The main idea of POCS is to formulate every piece of prior knowledge into a corresponding convex set and then use a convergence-guaranteed iterative procedure to obtain a solution in the intersection of all these sets. In this work, we design several convex sets, taking into consideration the biological characteristic of the data: the first set mainly exploit the local correlation structure among genes in microarray data, while the second set captures the global correlation structure among arrays. The third set (actually a series of sets) exploits the biological phenomenon of synchronization loss in microarray experiments. In cyclic systems, synchronization loss is a common phenomenon and we construct a series of sets based on this phenomenon for our POCS imputation algorithm. Experiments show that our algorithm can achieve a significant reduction of error compared to the KNNimpute, SVDimpute and LSimpute methods.

Direct comparison of the FibroScan XL and M probes for assessment of liver fibrosis in obese and nonobese patients.

PubMed

Durango, Esteban; Dietrich, Christian; Seitz, Helmut Karl; Kunz, Cornelia Ursula; Pomier-Layrargues, Gilles T; Duarte-Rojo, Andres; Beaton, Melanie; Elkhashab, Magdy; Myers, Robert P; Mueller, Sebastian

2013-01-01

A novel Fibroscan XL probe has recently been introduced and validated for obese patients, and has a diagnostic accuracy comparable with that of the standard M probe. The aim of this study was to analyze and understand the differences between these two probes in nonobese patients, to identify underlying causes for these differences, and to develop a practical algorithm to translate results for the XL probe to those for the M probe. Both probes were directly compared first in copolymer phantoms of varying stiffness (4.8, 11, and 40 kPa) and then in 371 obese and nonobese patients (body mass index, range 17.2-72.4) from German (n = 129) and Canadian (n = 242) centers. Liver stiffness values for both probes correlated better in phantoms than in patients (r = 0.98 versus 0.82, P < 0.001). Significantly more patients could be measured successfully using the XL probe than the M probe (98.4% versus 85.2%, respectively, P < 0.001) while the M probe produced a smaller interquartile range (21% versus 32%). Failure of the M probe to measure liver stiffness was not only observed in patients with a high body mass index and long skin-liver capsule distance but also in some nonobese patients (n = 10) due to quenching of the signal from subcutaneous fat tissue. In contrast with the phantoms, the XL probe consistently produced approximately 20% lower liver stiffness values in humans compared with the M probe. A long skin-liver capsule distance and a high degree of steatosis were responsible for this discordance. Adjustment of cutoff values for the XL probe (<5.5, 5.5-7, 7-10, and >10 kPa for F0, F1-2, F3, and F4 fibrosis, respectively) significantly improved agreement between the two probes from r = 0.655 to 0.679. Liver stiffness can be measured in significantly more obese and nonobese patients using the XL probe than the M probe. However, the XL probe is less accurate and adjusted cutoff values are required.

Direct comparison of the FibroScan XL and M probes for assessment of liver fibrosis in obese and nonobese patients

PubMed Central

Durango, Esteban; Dietrich, Christian; Seitz, Helmut Karl; Kunz, Cornelia Ursula; Pomier-Layrargues, Gilles T; Duarte-Rojo, Andres; Beaton, Melanie; Elkhashab, Magdy; Myers, Robert P; Mueller, Sebastian

2013-01-01

Background A novel Fibroscan XL probe has recently been introduced and validated for obese patients, and has a diagnostic accuracy comparable with that of the standard M probe. The aim of this study was to analyze and understand the differences between these two probes in nonobese patients, to identify underlying causes for these differences, and to develop a practical algorithm to translate results for the XL probe to those for the M probe. Methods and results Both probes were directly compared first in copolymer phantoms of varying stiffness (4.8, 11, and 40 kPa) and then in 371 obese and nonobese patients (body mass index, range 17.2–72.4) from German (n = 129) and Canadian (n = 242) centers. Liver stiffness values for both probes correlated better in phantoms than in patients (r = 0.98 versus 0.82, P < 0.001). Significantly more patients could be measured successfully using the XL probe than the M probe (98.4% versus 85.2%, respectively, P < 0.001) while the M probe produced a smaller interquartile range (21% versus 32%). Failure of the M probe to measure liver stiffness was not only observed in patients with a high body mass index and long skin-liver capsule distance but also in some nonobese patients (n = 10) due to quenching of the signal from subcutaneous fat tissue. In contrast with the phantoms, the XL probe consistently produced approximately 20% lower liver stiffness values in humans compared with the M probe. A long skin-liver capsule distance and a high degree of steatosis were responsible for this discordance. Adjustment of cutoff values for the XL probe (<5.5, 5.5–7, 7–10, and >10 kPa for F0, F1–2, F3, and F4 fibrosis, respectively) significantly improved agreement between the two probes from r = 0.655 to 0.679. Conclusion Liver stiffness can be measured in significantly more obese and nonobese patients using the XL probe than the M probe. However, the XL probe is less accurate and adjusted cutoff values are required. PMID:24696623

Data reduction using cubic rational B-splines

NASA Technical Reports Server (NTRS)

Chou, Jin J.; Piegl, Les A.

1992-01-01

A geometric method is proposed for fitting rational cubic B-spline curves to data that represent smooth curves including intersection or silhouette lines. The algorithm is based on the convex hull and the variation diminishing properties of Bezier/B-spline curves. The algorithm has the following structure: it tries to fit one Bezier segment to the entire data set and if it is impossible it subdivides the data set and reconsiders the subset. After accepting the subset the algorithm tries to find the longest run of points within a tolerance and then approximates this set with a Bezier cubic segment. The algorithm uses this procedure repeatedly to the rest of the data points until all points are fitted. It is concluded that the algorithm delivers fitting curves which approximate the data with high accuracy even in cases with large tolerances.

Four-probe measurements with a three-probe scanning tunneling microscope.

PubMed

Salomons, Mark; Martins, Bruno V C; Zikovsky, Janik; Wolkow, Robert A

2014-04-01

We present an ultrahigh vacuum (UHV) three-probe scanning tunneling microscope in which each probe is capable of atomic resolution. A UHV JEOL scanning electron microscope aids in the placement of the probes on the sample. The machine also has a field ion microscope to clean, atomically image, and shape the probe tips. The machine uses bare conductive samples and tips with a homebuilt set of pliers for heating and loading. Automated feedback controlled tip-surface contacts allow for electrical stability and reproducibility while also greatly reducing tip and surface damage due to contact formation. The ability to register inter-tip position by imaging of a single surface feature by multiple tips is demonstrated. Four-probe material characterization is achieved by deploying two tips as fixed current probes and the third tip as a movable voltage probe.

Feasibility of a GNSS-Probe for Creating Digital Maps of High Accuracy and Integrity

NASA Astrophysics Data System (ADS)

Vartziotis, Dimitris; Poulis, Alkis; Minogiannis, Alexandros; Siozos, Panayiotis; Goudas, Iraklis; Samson, Jaron; Tossaint, Michel

The “ROADSCANNER” project addresses the need for increased accuracy and integrity Digital Maps (DM) utilizing the latest developments in GNSS, in order to provide the required datasets for novel applications, such as navigation based Safety Applications, Advanced Driver Assistance Systems (ADAS) and Digital Automotive Simulations. The activity covered in the current paper is the feasibility study, preliminary tests, initial product design and development plan for an EGNOS enabled vehicle probe. The vehicle probe will be used for generating high accuracy, high integrity and ADAS compatible digital maps of roads, employing a multiple passes methodology supported by sophisticated refinement algorithms. Furthermore, the vehicle probe will be equipped with pavement scanning and other data fusion equipment, in order to produce 3D road surface models compatible with standards of road-tire simulation applications. The project was assigned to NIKI Ltd under the 1st Call for Ideas in the frame of the ESA - Greece Task Force.

Data Analysis of the Floating Potential Measurement Unit aboard the International Space Station

NASA Technical Reports Server (NTRS)

Barjatya, Aroh; Swenson, Charles M.; Thompson, Donald C.; Wright, Kenneth H., Jr.

2009-01-01

We present data from the Floating Potential Measurement Unit (FPMU), that is deployed on the starboard (S1) truss of the International Space Station. The FPMU is a suite of instruments capable of redundant measurements of various plasma parameters. The instrument suite consists of: a Floating Potential Probe, a Wide-sweeping spherical Langmuir probe, a Narrow-sweeping cylindrical Langmuir Probe, and a Plasma Impedance Probe. This paper gives a brief overview of the instrumentation and the received data quality, and then presents the algorithm used to reduce I-V curves to plasma parameters. Several hours of data is presented from August 5th, 2006 and March 3rd, 2007. The FPMU derived plasma density and temperatures are compared with the International Reference Ionosphere (IRI) and USU-Global Assimilation of Ionospheric Measurement (USU-GAIM) models. Our results show that the derived in-situ density matches the USU-GAIM model better than the IRI, and the derived in-situ temperatures are comparable to the average temperatures given by the IRI.

Greedy Algorithms for Nonnegativity-Constrained Simultaneous Sparse Recovery

PubMed Central

Kim, Daeun; Haldar, Justin P.

2016-01-01

This work proposes a family of greedy algorithms to jointly reconstruct a set of vectors that are (i) nonnegative and (ii) simultaneously sparse with a shared support set. The proposed algorithms generalize previous approaches that were designed to impose these constraints individually. Similar to previous greedy algorithms for sparse recovery, the proposed algorithms iteratively identify promising support indices. In contrast to previous approaches, the support index selection procedure has been adapted to prioritize indices that are consistent with both the nonnegativity and shared support constraints. Empirical results demonstrate for the first time that the combined use of simultaneous sparsity and nonnegativity constraints can substantially improve recovery performance relative to existing greedy algorithms that impose less signal structure. PMID:26973368

Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)

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

The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.

The MAP Spacecraft Angular State Estimation After Sensor Failure

NASA Technical Reports Server (NTRS)

Bar-Itzhack, Itzhack Y.; Harman, Richard R.

2003-01-01

This work describes two algorithms for computing the angular rate and attitude in case of a gyro and a Star Tracker failure in the Microwave Anisotropy Probe (MAP) satellite, which was placed in the L2 parking point from where it collects data to determine the origin of the universe. The nature of the problem is described, two algorithms are suggested, an observability study is carried out and real MAP data are used to determine the merit of the algorithms. It is shown that one of the algorithms yields a good estimate of the rates but not of the attitude whereas the other algorithm yields a good estimate of the rate as well as two of the three attitude angles. The estimation of the third angle depends on the initial state estimate. There is a contradiction between this result and the outcome of the observability analysis. An explanation of this contradiction is given in the paper. Although this work treats a particular spacecraft, the conclusions have a far reaching consequence.

Community-based benchmarking improves spike rate inference from two-photon calcium imaging data.

PubMed

Berens, Philipp; Freeman, Jeremy; Deneux, Thomas; Chenkov, Nikolay; McColgan, Thomas; Speiser, Artur; Macke, Jakob H; Turaga, Srinivas C; Mineault, Patrick; Rupprecht, Peter; Gerhard, Stephan; Friedrich, Rainer W; Friedrich, Johannes; Paninski, Liam; Pachitariu, Marius; Harris, Kenneth D; Bolte, Ben; Machado, Timothy A; Ringach, Dario; Stone, Jasmine; Rogerson, Luke E; Sofroniew, Nicolas J; Reimer, Jacob; Froudarakis, Emmanouil; Euler, Thomas; Román Rosón, Miroslav; Theis, Lucas; Tolias, Andreas S; Bethge, Matthias

2018-05-01

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.

The Effect of Sensor Failure on the Attitude and Rate Estimation of MAP Spacecraft

NASA Technical Reports Server (NTRS)

Bar-Itzhack, Itzhack Y.; Harman, Richard R.

2003-01-01

This work describes two algorithms for computing the angular rate and attitude in case of a gyro and a Star Tracker failure in the Microwave Anisotropy Probe (MAP) satellite, which was placed in the L2 parking point from where it collects data to determine the origin of the universe. The nature of the problem is described, two algorithms are suggested, an observability study is carried out and real MAP data are used to determine the merit of the algorithms. It is shown that one of the algorithms yields a good estimate of the rates but not of the attitude whereas the other algorithm yields a good estimate of the rate as well as two of the three attitude angles. The estimation of the third angle depends on the initial state estimate. There is a contradiction between this result and the outcome of the observability analysis. An explanation of this contradiction is given in the paper. Although this work treats a particular spacecraft, its conclusions are more general.

A Semisupervised Support Vector Machines Algorithm for BCI Systems

PubMed Central

Qin, Jianzhao; Li, Yuanqing; Sun, Wei

2007-01-01

As an emerging technology, brain-computer interfaces (BCIs) bring us new communication interfaces which translate brain activities into control signals for devices like computers, robots, and so forth. In this study, we propose a semisupervised support vector machine (SVM) algorithm for brain-computer interface (BCI) systems, aiming at reducing the time-consuming training process. In this algorithm, we apply a semisupervised SVM for translating the features extracted from the electrical recordings of brain into control signals. This SVM classifier is built from a small labeled data set and a large unlabeled data set. Meanwhile, to reduce the time for training semisupervised SVM, we propose a batch-mode incremental learning method, which can also be easily applied to the online BCI systems. Additionally, it is suggested in many studies that common spatial pattern (CSP) is very effective in discriminating two different brain states. However, CSP needs a sufficient labeled data set. In order to overcome the drawback of CSP, we suggest a two-stage feature extraction method for the semisupervised learning algorithm. We apply our algorithm to two BCI experimental data sets. The offline data analysis results demonstrate the effectiveness of our algorithm. PMID:18368141

Improving depth maps of plants by using a set of five cameras

NASA Astrophysics Data System (ADS)

Kaczmarek, Adam L.

2015-03-01

Obtaining high-quality depth maps and disparity maps with the use of a stereo camera is a challenging task for some kinds of objects. The quality of these maps can be improved by taking advantage of a larger number of cameras. The research on the usage of a set of five cameras to obtain disparity maps is presented. The set consists of a central camera and four side cameras. An algorithm for making disparity maps called multiple similar areas (MSA) is introduced. The algorithm was specially designed for the set of five cameras. Experiments were performed with the MSA algorithm and the stereo matching algorithm based on the sum of sum of squared differences (sum of SSD, SSSD) measure. Moreover, the following measures were included in the experiments: sum of absolute differences (SAD), zero-mean SAD (ZSAD), zero-mean SSD (ZSSD), locally scaled SAD (LSAD), locally scaled SSD (LSSD), normalized cross correlation (NCC), and zero-mean NCC (ZNCC). Algorithms presented were applied to images of plants. Making depth maps of plants is difficult because parts of leaves are similar to each other. The potential usability of the described algorithms is especially high in agricultural applications such as robotic fruit harvesting.

Quantum Algorithm for K-Nearest Neighbors Classification Based on the Metric of Hamming Distance

NASA Astrophysics Data System (ADS)

Ruan, Yue; Xue, Xiling; Liu, Heng; Tan, Jianing; Li, Xi

2017-11-01

K-nearest neighbors (KNN) algorithm is a common algorithm used for classification, and also a sub-routine in various complicated machine learning tasks. In this paper, we presented a quantum algorithm (QKNN) for implementing this algorithm based on the metric of Hamming distance. We put forward a quantum circuit for computing Hamming distance between testing sample and each feature vector in the training set. Taking advantage of this method, we realized a good analog for classical KNN algorithm by setting a distance threshold value t to select k - n e a r e s t neighbors. As a result, QKNN achieves O( n 3) performance which is only relevant to the dimension of feature vectors and high classification accuracy, outperforms Llyod's algorithm (Lloyd et al. 2013) and Wiebe's algorithm (Wiebe et al. 2014).

The implementation of contour-based object orientation estimation algorithm in FPGA-based on-board vision system

NASA Astrophysics Data System (ADS)

Alpatov, Boris; Babayan, Pavel; Ershov, Maksim; Strotov, Valery

2016-10-01

This paper describes the implementation of the orientation estimation algorithm in FPGA-based vision system. An approach to estimate an orientation of objects lacking axial symmetry is proposed. Suggested algorithm is intended to estimate orientation of a specific known 3D object based on object 3D model. The proposed orientation estimation algorithm consists of two stages: learning and estimation. Learning stage is devoted to the exploring of studied object. Using 3D model we can gather set of training images by capturing 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. Gathered training image set is used for calculating descriptors, which will be used in the estimation stage of the algorithm. The estimation stage is focusing on matching process between an observed image descriptor and the training image descriptors. The experimental research was performed using a set of images of Airbus A380. The proposed orientation estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.

Algorithms for Discovery of Multiple Markov Boundaries

PubMed Central

Statnikov, Alexander; Lytkin, Nikita I.; Lemeire, Jan; Aliferis, Constantin F.

2013-01-01

Algorithms for Markov boundary discovery from data constitute an important recent development in machine learning, primarily because they offer a principled solution to the variable/feature selection problem and give insight on local causal structure. Over the last decade many sound algorithms have been proposed to identify a single Markov boundary of the response variable. Even though faithful distributions and, more broadly, distributions that satisfy the intersection property always have a single Markov boundary, other distributions/data sets may have multiple Markov boundaries of the response variable. The latter distributions/data sets are common in practical data-analytic applications, and there are several reasons why it is important to induce multiple Markov boundaries from such data. However, there are currently no sound and efficient algorithms that can accomplish this task. This paper describes a family of algorithms TIE* that can discover all Markov boundaries in a distribution. The broad applicability as well as efficiency of the new algorithmic family is demonstrated in an extensive benchmarking study that involved comparison with 26 state-of-the-art algorithms/variants in 15 data sets from a diversity of application domains. PMID:25285052

Nonrigid Image Registration in Digital Subtraction Angiography Using Multilevel B-Spline

PubMed Central

2013-01-01

We address the problem of motion artifact reduction in digital subtraction angiography (DSA) using image registration techniques. Most of registration algorithms proposed for application in DSA, have been designed for peripheral and cerebral angiography images in which we mainly deal with global rigid motions. These algorithms did not yield good results when applied to coronary angiography images because of complex nonrigid motions that exist in this type of angiography images. Multiresolution and iterative algorithms are proposed to cope with this problem, but these algorithms are associated with high computational cost which makes them not acceptable for real-time clinical applications. In this paper we propose a nonrigid image registration algorithm for coronary angiography images that is significantly faster than multiresolution and iterative blocking methods and outperforms competing algorithms evaluated on the same data sets. This algorithm is based on a sparse set of matched feature point pairs and the elastic registration is performed by means of multilevel B-spline image warping. Experimental results with several clinical data sets demonstrate the effectiveness of our approach. PMID:23971026

A GENERAL ALGORITHM FOR THE CONSTRUCTION OF CONTOUR PLOTS

NASA Technical Reports Server (NTRS)

Johnson, W.

1994-01-01

The graphical presentation of experimentally or theoretically generated data sets frequently involves the construction of contour plots. A general computer algorithm has been developed for the construction of contour plots. The algorithm provides for efficient and accurate contouring with a modular approach which allows flexibility in modifying the algorithm for special applications. The algorithm accepts as input data values at a set of points irregularly distributed over a plane. The algorithm is based on an interpolation scheme in which the points in the plane are connected by straight line segments to form a set of triangles. In general, the data is smoothed using a least-squares-error fit of the data to a bivariate polynomial. To construct the contours, interpolation along the edges of the triangles is performed, using the bivariable polynomial if data smoothing was performed. Once the contour points have been located, the contour may be drawn. This program is written in FORTRAN IV for batch execution and has been implemented on an IBM 360 series computer with a central memory requirement of approximately 100K of 8-bit bytes. This computer algorithm was developed in 1981.

Pruning Rogue Taxa Improves Phylogenetic Accuracy: An Efficient Algorithm and Webservice

PubMed Central

Aberer, Andre J.; Krompass, Denis; Stamatakis, Alexandros

2013-01-01

Abstract The presence of rogue taxa (rogues) in a set of trees can frequently have a negative impact on the results of a bootstrap analysis (e.g., the overall support in consensus trees). We introduce an efficient graph-based algorithm for rogue taxon identification as well as an interactive webservice implementing this algorithm. Compared with our previous method, the new algorithm is up to 4 orders of magnitude faster, while returning qualitatively identical results. Because of this significant improvement in scalability, the new algorithm can now identify substantially more complex and compute-intensive rogue taxon constellations. On a large and diverse collection of real-world data sets, we show that our method yields better supported reduced/pruned consensus trees than any competing rogue taxon identification method. Using the parallel version of our open-source code, we successfully identified rogue taxa in a set of 100 trees with 116 334 taxa each. For simulated data sets, we show that when removing/pruning rogue taxa with our method from a tree set, we consistently obtain bootstrap consensus trees as well as maximum-likelihood trees that are topologically closer to the respective true trees. PMID:22962004

Pruning rogue taxa improves phylogenetic accuracy: an efficient algorithm and webservice.

PubMed

Aberer, Andre J; Krompass, Denis; Stamatakis, Alexandros

2013-01-01

The presence of rogue taxa (rogues) in a set of trees can frequently have a negative impact on the results of a bootstrap analysis (e.g., the overall support in consensus trees). We introduce an efficient graph-based algorithm for rogue taxon identification as well as an interactive webservice implementing this algorithm. Compared with our previous method, the new algorithm is up to 4 orders of magnitude faster, while returning qualitatively identical results. Because of this significant improvement in scalability, the new algorithm can now identify substantially more complex and compute-intensive rogue taxon constellations. On a large and diverse collection of real-world data sets, we show that our method yields better supported reduced/pruned consensus trees than any competing rogue taxon identification method. Using the parallel version of our open-source code, we successfully identified rogue taxa in a set of 100 trees with 116 334 taxa each. For simulated data sets, we show that when removing/pruning rogue taxa with our method from a tree set, we consistently obtain bootstrap consensus trees as well as maximum-likelihood trees that are topologically closer to the respective true trees.

The implementation of aerial object recognition algorithm based on contour descriptor in FPGA-based on-board vision system

NASA Astrophysics Data System (ADS)

Babayan, Pavel; Smirnov, Sergey; Strotov, Valery

2017-10-01

This paper describes the aerial object recognition algorithm for on-board and stationary vision system. Suggested algorithm is intended to recognize the objects of a specific kind using the set of the reference objects defined by 3D models. The proposed algorithm based on the outer contour descriptor building. The algorithm consists of two stages: learning and recognition. Learning stage is devoted to the exploring of reference objects. Using 3D models we can build the database containing training images by rendering the 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. Gathered training image set is used for calculating descriptors, which will be used in the recognition stage of the algorithm. The recognition stage is focusing on estimating the similarity of the captured object and the reference objects by matching an observed image descriptor and the reference object descriptors. The experimental research was performed using a set of the models of the aircraft of the different types (airplanes, helicopters, UAVs). The proposed orientation estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.

A Modified MinMax k-Means Algorithm Based on PSO

PubMed Central

2016-01-01

The MinMax k-means algorithm is widely used to tackle the effect of bad initialization by minimizing the maximum intraclustering errors. Two parameters, including the exponent parameter and memory parameter, are involved in the executive process. Since different parameters have different clustering errors, it is crucial to choose appropriate parameters. In the original algorithm, a practical framework is given. Such framework extends the MinMax k-means to automatically adapt the exponent parameter to the data set. It has been believed that if the maximum exponent parameter has been set, then the programme can reach the lowest intraclustering errors. However, our experiments show that this is not always correct. In this paper, we modified the MinMax k-means algorithm by PSO to determine the proper values of parameters which can subject the algorithm to attain the lowest clustering errors. The proposed clustering method is tested on some favorite data sets in several different initial situations and is compared to the k-means algorithm and the original MinMax k-means algorithm. The experimental results indicate that our proposed algorithm can reach the lowest clustering errors automatically. PMID:27656201

Single-step reinitialization and extending algorithms for level-set based multi-phase flow simulations

NASA Astrophysics Data System (ADS)

Fu, Lin; Hu, Xiangyu Y.; Adams, Nikolaus A.

2017-12-01

We propose efficient single-step formulations for reinitialization and extending algorithms, which are critical components of level-set based interface-tracking methods. The level-set field is reinitialized with a single-step (non iterative) "forward tracing" algorithm. A minimum set of cells is defined that describes the interface, and reinitialization employs only data from these cells. Fluid states are extrapolated or extended across the interface by a single-step "backward tracing" algorithm. Both algorithms, which are motivated by analogy to ray-tracing, avoid multiple block-boundary data exchanges that are inevitable for iterative reinitialization and extending approaches within a parallel-computing environment. The single-step algorithms are combined with a multi-resolution conservative sharp-interface method and validated by a wide range of benchmark test cases. We demonstrate that the proposed reinitialization method achieves second-order accuracy in conserving the volume of each phase. The interface location is invariant to reapplication of the single-step reinitialization. Generally, we observe smaller absolute errors than for standard iterative reinitialization on the same grid. The computational efficiency is higher than for the standard and typical high-order iterative reinitialization methods. We observe a 2- to 6-times efficiency improvement over the standard method for serial execution. The proposed single-step extending algorithm, which is commonly employed for assigning data to ghost cells with ghost-fluid or conservative interface interaction methods, shows about 10-times efficiency improvement over the standard method while maintaining same accuracy. Despite their simplicity, the proposed algorithms offer an efficient and robust alternative to iterative reinitialization and extending methods for level-set based multi-phase simulations.

Accelerated Dimension-Independent Adaptive Metropolis

DOE PAGES

Chen, Yuxin; Keyes, David E.; Law, Kody J.; ...

2016-10-27

This work describes improvements from algorithmic and architectural means to black-box Bayesian inference over high-dimensional parameter spaces. The well-known adaptive Metropolis (AM) algorithm [33] is extended herein to scale asymptotically uniformly with respect to the underlying parameter dimension for Gaussian targets, by respecting the variance of the target. The resulting algorithm, referred to as the dimension-independent adaptive Metropolis (DIAM) algorithm, also shows improved performance with respect to adaptive Metropolis on non-Gaussian targets. This algorithm is further improved, and the possibility of probing high-dimensional (with dimension d 1000) targets is enabled, via GPU-accelerated numerical libraries and periodically synchronized concurrent chains (justimore » ed a posteriori). Asymptotically in dimension, this GPU implementation exhibits a factor of four improvement versus a competitive CPU-based Intel MKL parallel version alone. Strong scaling to concurrent chains is exhibited, through a combination of longer time per sample batch (weak scaling) and yet fewer necessary samples to convergence. The algorithm performance is illustrated on several Gaussian and non-Gaussian target examples, in which the dimension may be in excess of one thousand.« less

Accelerated Dimension-Independent Adaptive Metropolis

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

Chen, Yuxin; Keyes, David E.; Law, Kody J.

This work describes improvements from algorithmic and architectural means to black-box Bayesian inference over high-dimensional parameter spaces. The well-known adaptive Metropolis (AM) algorithm [33] is extended herein to scale asymptotically uniformly with respect to the underlying parameter dimension for Gaussian targets, by respecting the variance of the target. The resulting algorithm, referred to as the dimension-independent adaptive Metropolis (DIAM) algorithm, also shows improved performance with respect to adaptive Metropolis on non-Gaussian targets. This algorithm is further improved, and the possibility of probing high-dimensional (with dimension d 1000) targets is enabled, via GPU-accelerated numerical libraries and periodically synchronized concurrent chains (justimore » ed a posteriori). Asymptotically in dimension, this GPU implementation exhibits a factor of four improvement versus a competitive CPU-based Intel MKL parallel version alone. Strong scaling to concurrent chains is exhibited, through a combination of longer time per sample batch (weak scaling) and yet fewer necessary samples to convergence. The algorithm performance is illustrated on several Gaussian and non-Gaussian target examples, in which the dimension may be in excess of one thousand.« less

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks.

PubMed

Ma, Junjie; Meng, Fansheng; Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-02-16

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks

PubMed Central

Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-01-01

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths. PMID:29462929

Implications of Version 8 TOMS and SBUV Data for Long-Term Trend Analysis

NASA Technical Reports Server (NTRS)

Frith, Stacey M.

2004-01-01

Total ozone data from the Total Ozone Mapping Spectrometer (TOMS) and profile/total ozone data from the Solar Backscatter Ultraviolet (SBUV; SBW/2) series of instruments have recently been reprocessed using new retrieval algorithms (referred to as Version 8 for both) and updated calibrations. In this paper, we incorporate the Version 8 data into a TOMS/SBW merged total ozone data set and an S B W merged profile ozone data set. The Total Merged Ozone Data (Total MOD) combines data from multiple TOMS and SBW instruments to form an internally consistent global data set with virtually complete time coverage from October 1978 through December 2003. Calibration differences between instruments are accounted for using external adjustments based on instrument intercomparisons during overlap periods. Previous results showed errors due to aerosol loading and sea glint are significantly reduced in the V8 TOMS retrievals. Using SBW as a transfer standard, calibration differences between V8 Nimbus 7 and Earth Probe TOMS data are approx. 1.3%, suggesting small errors in calibration remain. We will present updated total ozone long-term trends based on the Version 8 data. The Profile Merged Ozone Data (Profile MOD) data set is constructed using data from the SBUV series of instruments. In previous versions, SAGE data were used to establish the long-term external calibration of the combined data set. The SBW Version 8 we assess the V8 profile data through comparisons with SAGE and between SBW instruments in overlap periods. We then construct a consistently-calibrated long term time series. Updated zonal mean trends as a function of altitude and season from the new profile data set will be shown, and uncertainties in determining the best long-term calibration will be discussed.

No drive line, no seal, no bearing and no wear: magnetics for impeller suspension and flow assessment in a new VAD.

PubMed

Huber, Christoph H; Tozzi, Piergiorgio; Hurni, Michel; von Segesser, Ludwig K

2004-06-01

The new magnetically suspended axial pump is free of seals, bearings, mechanical friction and wear. In the absence of a drive shaft or flow meter, pump flow assessment is made with an algorithm based on currents required for impeller rotation and stabilization. The aim of this study is to validate pump performance, algorithm-based flow and effective flow. A series of bovine experiments was realized after equipment with pressure transducers, continuous-cardiac-output-catheter, intracardiac ultrasound (AcuNav) over 6 h. Pump implantation was through a median sternotomy (LV-->VAD-->calibrated transonic-flow-probe-->aorta). A transonic-HT311-flow-probe was fixed onto the outflow cannula for flow comparison. Animals were electively sacrificed and at necropsy systematic pump inspection and renal embolus score was realized. Observation period was 340+/-62.4 min. The axial pump generated a mean arterial pressure of 58.8+/-14.3 mmHg (max 117 mmHg) running at a speed of 6591.3+/-1395.4 rev./min (min 5000/max 8500 rev./min) and generating 2.5+/-1.0 l/min (min 1.4/max 6.0 l/min) of flow. Correlation between the results of the pump flow algorithm and measured pump flow was linear (y=1.0339x, R2=0.9357). VAD explants were free of macroscopic thrombi. Renal embolus score was 0+/-0. The magnetically suspended axial flow pump provides excellent left ventricular support. The pump flow algorithm used is accurate and reliable. Therefore, there is no need for direct flow measurement.

Fast and accurate face recognition based on image compression

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Blasch, Erik

2017-05-01

Image compression is desired for many image-related applications especially for network-based applications with bandwidth and storage constraints. The face recognition community typical reports concentrate on the maximal compression rate that would not decrease the recognition accuracy. In general, the wavelet-based face recognition methods such as EBGM (elastic bunch graph matching) and FPB (face pattern byte) are of high performance but run slowly due to their high computation demands. The PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) algorithms run fast but perform poorly in face recognition. In this paper, we propose a novel face recognition method based on standard image compression algorithm, which is termed as compression-based (CPB) face recognition. First, all gallery images are compressed by the selected compression algorithm. Second, a mixed image is formed with the probe and gallery images and then compressed. Third, a composite compression ratio (CCR) is computed with three compression ratios calculated from: probe, gallery and mixed images. Finally, the CCR values are compared and the largest CCR corresponds to the matched face. The time cost of each face matching is about the time of compressing the mixed face image. We tested the proposed CPB method on the "ASUMSS face database" (visible and thermal images) from 105 subjects. The face recognition accuracy with visible images is 94.76% when using JPEG compression. On the same face dataset, the accuracy of FPB algorithm was reported as 91.43%. The JPEG-compressionbased (JPEG-CPB) face recognition is standard and fast, which may be integrated into a real-time imaging device.

Temporally separating Cherenkov radiation in a scintillator probe exposed to a pulsed X-ray beam.

PubMed

Archer, James; Madden, Levi; Li, Enbang; Carolan, Martin; Petasecca, Marco; Metcalfe, Peter; Rosenfeld, Anatoly

2017-10-01

Cherenkov radiation is generated in optical systems exposed to ionising radiation. In water or plastic devices, if the incident radiation has components with high enough energy (for example, electrons or positrons with energy greater than 175keV), Cherenkov radiation will be generated. A scintillator dosimeter that collects optical light, guided by optical fibre, will have Cherenkov radiation generated throughout the length of fibre exposed to the radiation field and compromise the signal. We present a novel algorithm to separate Cherenkov radiation signal that requires only a single probe, provided the radiation source is pulsed, such as a linear accelerator in external beam radiation therapy. We use a slow scintillator (BC-444) that, in a constant beam of radiation, reaches peak light output after 1 microsecond, while the Cherenkov signal is detected nearly instantly. This allows our algorithm to separate the scintillator signal from the Cherenkov signal. The relative beam profile and depth dose of a linear accelerator 6MV X-ray field were reconstructed using the algorithm. The optimisation method improved the fit to the ionisation chamber data and improved the reliability of the measurements. The algorithm was able to remove 74% of the Cherenkov light, at the expense of only 1.5% scintillation light. Further characterisation of the Cherenkov radiation signal has the potential to improve the results and allow this method to be used as a simpler optical fibre dosimeter for quality assurance in external beam therapy. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

The genetic algorithm: A robust method for stress inversion

NASA Astrophysics Data System (ADS)

Thakur, Prithvi; Srivastava, Deepak C.; Gupta, Pravin K.

2017-01-01

The stress inversion of geological or geophysical observations is a nonlinear problem. In most existing methods, it is solved by linearization, under certain assumptions. These linear algorithms not only oversimplify the problem but also are vulnerable to entrapment of the solution in a local optimum. We propose the use of a nonlinear heuristic technique, the genetic algorithm, which searches the global optimum without making any linearizing assumption or simplification. The algorithm mimics the natural evolutionary processes of selection, crossover and mutation and, minimizes a composite misfit function for searching the global optimum, the fittest stress tensor. The validity and efficacy of the algorithm are demonstrated by a series of tests on synthetic and natural fault-slip observations in different tectonic settings and also in situations where the observations are noisy. It is shown that the genetic algorithm is superior to other commonly practised methods, in particular, in those tectonic settings where none of the principal stresses is directed vertically and/or the given data set is noisy.

Optimization of genomic selection training populations with a genetic algorithm

USDA-ARS?s Scientific Manuscript database

In this article, we derive a computationally efficient statistic to measure the reliability of estimates of genetic breeding values for a fixed set of genotypes based on a given training set of genotypes and phenotypes. We adopt a genetic algorithm scheme to find a training set of certain size from ...

Advancements to the planogram frequency–distance rebinning algorithm

PubMed Central

Champley, Kyle M; Raylman, Raymond R; Kinahan, Paul E

2010-01-01

In this paper we consider the task of image reconstruction in positron emission tomography (PET) with the planogram frequency–distance rebinning (PFDR) algorithm. The PFDR algorithm is a rebinning algorithm for PET systems with panel detectors. The algorithm is derived in the planogram coordinate system which is a native data format for PET systems with panel detectors. A rebinning algorithm averages over the redundant four-dimensional set of PET data to produce a three-dimensional set of data. Images can be reconstructed from this rebinned three-dimensional set of data. This process enables one to reconstruct PET images more quickly than reconstructing directly from the four-dimensional PET data. The PFDR algorithm is an approximate rebinning algorithm. We show that implementing the PFDR algorithm followed by the (ramp) filtered backprojection (FBP) algorithm in linogram coordinates from multiple views reconstructs a filtered version of our image. We develop an explicit formula for this filter which can be used to achieve exact reconstruction by means of a modified FBP algorithm applied to the stack of rebinned linograms and can also be used to quantify the errors introduced by the PFDR algorithm. This filter is similar to the filter in the planogram filtered backprojection algorithm derived by Brasse et al. The planogram filtered backprojection and exact reconstruction with the PFDR algorithm require complete projections which can be completed with a reprojection algorithm. The PFDR algorithm is similar to the rebinning algorithm developed by Kao et al. By expressing the PFDR algorithm in detector coordinates, we provide a comparative analysis between the two algorithms. Numerical experiments using both simulated data and measured data from a positron emission mammography/tomography (PEM/PET) system are performed. Images are reconstructed by PFDR+FBP (PFDR followed by 2D FBP reconstruction), PFDRX (PFDR followed by the modified FBP algorithm for exact reconstruction) and planogram filtered backprojection image reconstruction algorithms. We show that the PFDRX algorithm produces images that are nearly as accurate as images reconstructed with the planogram filtered backprojection algorithm and more accurate than images reconstructed with the PFDR+FBP algorithm. Both the PFDR+FBP and PFDRX algorithms provide a dramatic improvement in computation time over the planogram filtered backprojection algorithm. PMID:20436790

Fast detection of vascular plaque in optical coherence tomography images using a reduced feature set

NASA Astrophysics Data System (ADS)

Prakash, Ammu; Ocana Macias, Mariano; Hewko, Mark; Sowa, Michael; Sherif, Sherif

2018-03-01

Optical coherence tomography (OCT) images are capable of detecting vascular plaque by using the full set of 26 Haralick textural features and a standard K-means clustering algorithm. However, the use of the full set of 26 textural features is computationally expensive and may not be feasible for real time implementation. In this work, we identified a reduced set of 3 textural feature which characterizes vascular plaque and used a generalized Fuzzy C-means clustering algorithm. Our work involves three steps: 1) the reduction of a full set 26 textural feature to a reduced set of 3 textural features by using genetic algorithm (GA) optimization method 2) the implementation of an unsupervised generalized clustering algorithm (Fuzzy C-means) on the reduced feature space, and 3) the validation of our results using histology and actual photographic images of vascular plaque. Our results show an excellent match with histology and actual photographic images of vascular tissue. Therefore, our results could provide an efficient pre-clinical tool for the detection of vascular plaque in real time OCT imaging.

Expectation-maximization algorithms for learning a finite mixture of univariate survival time distributions from partially specified class values

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

Lee, Youngrok

2013-05-15

Heterogeneity exists on a data set when samples from di erent classes are merged into the data set. Finite mixture models can be used to represent a survival time distribution on heterogeneous patient group by the proportions of each class and by the survival time distribution within each class as well. The heterogeneous data set cannot be explicitly decomposed to homogeneous subgroups unless all the samples are precisely labeled by their origin classes; such impossibility of decomposition is a barrier to overcome for estimating nite mixture models. The expectation-maximization (EM) algorithm has been used to obtain maximum likelihood estimates ofmore » nite mixture models by soft-decomposition of heterogeneous samples without labels for a subset or the entire set of data. In medical surveillance databases we can find partially labeled data, that is, while not completely unlabeled there is only imprecise information about class values. In this study we propose new EM algorithms that take advantages of using such partial labels, and thus incorporate more information than traditional EM algorithms. We particularly propose four variants of the EM algorithm named EM-OCML, EM-PCML, EM-HCML and EM-CPCML, each of which assumes a specific mechanism of missing class values. We conducted a simulation study on exponential survival trees with five classes and showed that the advantages of incorporating substantial amount of partially labeled data can be highly signi cant. We also showed model selection based on AIC values fairly works to select the best proposed algorithm on each specific data set. A case study on a real-world data set of gastric cancer provided by Surveillance, Epidemiology and End Results (SEER) program showed a superiority of EM-CPCML to not only the other proposed EM algorithms but also conventional supervised, unsupervised and semi-supervised learning algorithms.« less

An OMIC biomarker detection algorithm TriVote and its application in methylomic biomarker detection.

PubMed

Xu, Cheng; Liu, Jiamei; Yang, Weifeng; Shu, Yayun; Wei, Zhipeng; Zheng, Weiwei; Feng, Xin; Zhou, Fengfeng

2018-04-01

Transcriptomic and methylomic patterns represent two major OMIC data sources impacted by both inheritable genetic information and environmental factors, and have been widely used as disease diagnosis and prognosis biomarkers. Modern transcriptomic and methylomic profiling technologies detect the status of tens of thousands or even millions of probing residues in the human genome, and introduce a major computational challenge for the existing feature selection algorithms. This study proposes a three-step feature selection algorithm, TriVote, to detect a subset of transcriptomic or methylomic residues with highly accurate binary classification performance. TriVote outperforms both filter and wrapper feature selection algorithms with both higher classification accuracy and smaller feature number on 17 transcriptomes and two methylomes. Biological functions of the methylome biomarkers detected by TriVote were discussed for their disease associations. An easy-to-use Python package is also released to facilitate the further applications.

Dynamic phasing of multichannel cw laser radiation by means of a stochastic gradient algorithm

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

Volkov, V A; Volkov, M V; Garanin, S G

2013-09-30

The phasing of a multichannel laser beam by means of an iterative stochastic parallel gradient (SPG) algorithm has been numerically and experimentally investigated. The operation of the SPG algorithm is simulated, the acceptable range of amplitudes of probe phase shifts is found, and the algorithm parameters at which the desired Strehl number can be obtained with a minimum number of iterations are determined. An experimental bench with phase modulators based on lithium niobate, which are controlled by a multichannel electronic unit with a real-time microcontroller, has been designed. Phasing of 16 cw laser beams at a system response bandwidth ofmore » 3.7 kHz and phase thermal distortions in a frequency band of about 10 Hz is experimentally demonstrated. The experimental data are in complete agreement with the calculation results. (control of laser radiation parameters)« less

Improving Electronic Sensor Reliability by Robust Outlier Screening

PubMed Central

Moreno-Lizaranzu, Manuel J.; Cuesta, Federico

2013-01-01

Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount. Outlier detection algorithms are a key component in screening latent defects and decreasing the number of customer quality incidents (CQIs). This paper focuses on new spatial algorithms (Good Die in a Bad Cluster with Statistical Bins (GDBC SB) and Bad Bin in a Bad Cluster (BBBC)) and an advanced outlier screening method, called Robust Dynamic Part Averaging Testing (RDPAT), as well as two practical improvements, which significantly enhance existing algorithms. Those methods have been used in production in Freescale® Semiconductor probe factories around the world for several years. Moreover, a study was conducted with production data of 289,080 dice with 26 CQIs to determine and compare the efficiency and effectiveness of all these algorithms in identifying CQIs. PMID:24113682

Improving electronic sensor reliability by robust outlier screening.

PubMed

Moreno-Lizaranzu, Manuel J; Cuesta, Federico

2013-10-09

Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount. Outlier detection algorithms are a key component in screening latent defects and decreasing the number of customer quality incidents (CQIs). This paper focuses on new spatial algorithms (Good Die in a Bad Cluster with Statistical Bins (GDBC SB) and Bad Bin in a Bad Cluster (BBBC)) and an advanced outlier screening method, called Robust Dynamic Part Averaging Testing (RDPAT), as well as two practical improvements, which significantly enhance existing algorithms. Those methods have been used in production in Freescale® Semiconductor probe factories around the world for several years. Moreover, a study was conducted with production data of 289,080 dice with 26 CQIs to determine and compare the efficiency and effectiveness of all these algorithms in identifying CQIs.

Flow measurements in sewers based on image analysis: automatic flow velocity algorithm.

PubMed

Jeanbourquin, D; Sage, D; Nguyen, L; Schaeli, B; Kayal, S; Barry, D A; Rossi, L

2011-01-01

Discharges of combined sewer overflows (CSOs) and stormwater are recognized as an important source of environmental contamination. However, the harsh sewer environment and particular hydraulic conditions during rain events reduce the reliability of traditional flow measurement probes. An in situ system for sewer water flow monitoring based on video images was evaluated. Algorithms to determine water velocities were developed based on image-processing techniques. The image-based water velocity algorithm identifies surface features and measures their positions with respect to real world coordinates. A web-based user interface and a three-tier system architecture enable remote configuration of the cameras and the image-processing algorithms in order to calculate automatically flow velocity on-line. Results of investigations conducted in a CSO are presented. The system was found to measure reliably water velocities, thereby providing the means to understand particular hydraulic behaviors.

Leveraging Python Interoperability Tools to Improve Sapphire's Usability

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

Gezahegne, A; Love, N S

2007-12-10

The Sapphire project at the Center for Applied Scientific Computing (CASC) develops and applies an extensive set of data mining algorithms for the analysis of large data sets. Sapphire's algorithms are currently available as a set of C++ libraries. However many users prefer higher level scripting languages such as Python for their ease of use and flexibility. In this report, we evaluate four interoperability tools for the purpose of wrapping Sapphire's core functionality with Python. Exposing Sapphire's functionality through a Python interface would increase its usability and connect its algorithms to existing Python tools.

A novel dicyanoisophorone based red-emitting fluorescent probe with a large Stokes shift for detection of hydrazine in solution and living cells

NASA Astrophysics Data System (ADS)

Lv, Hongshui; Sun, Haiyan; Wang, Shoujuan; Kong, Fangong

2018-05-01

A novel dicyanoisophorone based fluorescent probe HP was developed to detect hydrazine. Upon the addition of hydrazine, probe HP displayed turn-on fluorescence in the red region with a large Stokes shift (180 nm). This probe exhibited high selectivity and high sensitivity to hydrazine in solution. The detection limit of HP was found to be 3.26 ppb, which was lower than the threshold limit value set by USEPA (10 ppb). Moreover, the probe was successfully applied to detect hydrazine in different water samples and living cells.

Comparison of the structure function F 2 as measured by charged lepton and neutrino scattering from iron targets

DOE PAGES

Kalantarians, N.; Keppel, C.; Christy, M. E.

2017-09-12

A comparison study of world data for the structure function F 2 for Iron, as measured by both charged lepton and neutrino scattering experiments, is presented. Consistency of results for both charged lepton and neutrino scattering is observed for the full global data set in the valence regime. Consistency is also observed at low x for the various neutrino data sets, as well as for the charged lepton data sets, independently. However, data from the two probes exhibit differences on the order of 15% in the shadowing/anti-shadowing transition region where the Bjorken scaling variable x is < 0.15. This observationmore » is indicative that neutrino probes of nucleon structure might be sensitive to different nuclear effects than charged lepton probes. Details and results of the data comparison are here presented.« less

Comparison of the structure function F 2 as measured by charged lepton and neutrino scattering from iron targets

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

Kalantarians, N.; Keppel, C.; Christy, M. E.

A comparison study of world data for the structure function F 2 for Iron, as measured by both charged lepton and neutrino scattering experiments, is presented. Consistency of results for both charged lepton and neutrino scattering is observed for the full global data set in the valence regime. Consistency is also observed at low x for the various neutrino data sets, as well as for the charged lepton data sets, independently. However, data from the two probes exhibit differences on the order of 15% in the shadowing/anti-shadowing transition region where the Bjorken scaling variable x is < 0.15. This observationmore » is indicative that neutrino probes of nucleon structure might be sensitive to different nuclear effects than charged lepton probes. Details and results of the data comparison are here presented.« less

High-throughput microarray technology in diagnostics of enterobacteria based on genome-wide probe selection and regression analysis.

PubMed

Friedrich, Torben; Rahmann, Sven; Weigel, Wilfried; Rabsch, Wolfgang; Fruth, Angelika; Ron, Eliora; Gunzer, Florian; Dandekar, Thomas; Hacker, Jörg; Müller, Tobias; Dobrindt, Ulrich

2010-10-21

The Enterobacteriaceae comprise a large number of clinically relevant species with several individual subspecies. Overlapping virulence-associated gene pools and the high overall genome plasticity often interferes with correct enterobacterial strain typing and risk assessment. Array technology offers a fast, reproducible and standardisable means for bacterial typing and thus provides many advantages for bacterial diagnostics, risk assessment and surveillance. The development of highly discriminative broad-range microbial diagnostic microarrays remains a challenge, because of marked genome plasticity of many bacterial pathogens. We developed a DNA microarray for strain typing and detection of major antimicrobial resistance genes of clinically relevant enterobacteria. For this purpose, we applied a global genome-wide probe selection strategy on 32 available complete enterobacterial genomes combined with a regression model for pathogen classification. The discriminative power of the probe set was further tested in silico on 15 additional complete enterobacterial genome sequences. DNA microarrays based on the selected probes were used to type 92 clinical enterobacterial isolates. Phenotypic tests confirmed the array-based typing results and corroborate that the selected probes allowed correct typing and prediction of major antibiotic resistances of clinically relevant Enterobacteriaceae, including the subspecies level, e.g. the reliable distinction of different E. coli pathotypes. Our results demonstrate that the global probe selection approach based on longest common factor statistics as well as the design of a DNA microarray with a restricted set of discriminative probes enables robust discrimination of different enterobacterial variants and represents a proof of concept that can be adopted for diagnostics of a wide range of microbial pathogens. Our approach circumvents misclassifications arising from the application of virulence markers, which are highly affected by horizontal gene transfer. Moreover, a broad range of pathogens have been covered by an efficient probe set size enabling the design of high-throughput diagnostics.

Real-time PCR detection of Vibrio vulnificus in oysters: comparison of oligonucleotide primers and probes targeting vvhA.

PubMed

Panicker, Gitika; Bej, Asim K

2005-10-01

We compared three sets of oligonucleotide primers and two probes designed for Vibrio vulnificus hemolysin A gene (vvhA) for TaqMan-based real-time PCR method enabling specific detection of Vibrio vulnificus in oysters. Two of three sets of primers with a probe were specific for the detection of all 81 V. vulnificus isolates by TaqMan PCR. The 25 nonvibrio and 12 other vibrio isolates tested were negative. However, the third set of primers, F-vvh1059 and R-vvh1159, with the P-vvh1109 probe, although positive for all V. vulnificus isolates, also exhibited positive cycle threshold (C(T)) values for other Vibrio spp. Optimization of the TaqMan PCR assay using F-vvh785/R-vvh990 or F-vvh731/R-vvh1113 primers and the P-vvh874 probe detected 1 pg of purified DNA and 10(3) V. vulnificus CFU/ml in pure cultures. The enriched oyster tissue homogenate did not exhibit detectable inhibition to the TaqMan PCR amplification of vvhA. Detection of 3 x 10(3) CFU V. vulnificus, resulting from a 5-h enrichment of an initial inoculum of 1 CFU/g of oyster tissue homogenate, was achieved with F-vvh785/R-vvh990 or F-vvh731/R-vvh1113 primers and P-vvh875 probe. The application of the TaqMan PCR using these primers and probe, exhibited detection of V. vulnificus on 5-h-enriched natural oysters harvested from the Gulf of Mexico. Selection of appropriate primers and a probe on vvhA for TaqMan-PCR-based detection of V. vulnificus in post-harvest-treated oysters would help avoid false-positive results, thus ensuring a steady supply of safe oysters to consumers and reducing V. vulnificus-related illnesses and deaths.

Measurement of locus copy number by hybridisation with amplifiable probes

PubMed Central

Armour, John A. L.; Sismani, Carolina; Patsalis, Philippos C.; Cross, Gareth

2000-01-01

Despite its fundamental importance in genome analysis, it is only recently that systematic approaches have been developed to assess copy number at specific genetic loci, or to examine genomic DNA for submicroscopic deletions of unknown location. In this report we show that short probes can be recovered and amplified quantitatively following hybridisation to genomic DNA. This simple observation forms the basis of a new approach to determining locus copy number in complex genomes. The power and specificity of multiplex amplifiable probe hybridisation is demonstrated by the simultaneous assessment of copy number at a set of 40 human loci, including detection of deletions causing Duchenne muscular dystrophy and Prader–Willi/Angelman syndromes. Assembly of other probe sets will allow novel, technically simple approaches to a wide variety of genetic analyses, including the potential for extension to high resolution genome-wide screens for deletions and amplifications. PMID:10606661

Measurement of locus copy number by hybridisation with amplifiable probes.

PubMed

Armour, J A; Sismani, C; Patsalis, P C; Cross, G

2000-01-15

Despite its fundamental importance in genome analysis, it is only recently that systematic approaches have been developed to assess copy number at specific genetic loci, or to examine genomic DNA for submicro-scopic deletions of unknown location. In this report we show that short probes can be recovered and amplified quantitatively following hybridisation to genomic DNA. This simple observation forms the basis of a new approach to determining locus copy number in complex genomes. The power and specificity of multiplex amplifiable probe hybridisation is demonstrated by the simultaneous assessment of copy number at a set of 40 human loci, including detection of deletions causing Duchenne muscular dystrophy and Prader-Willi/Angelman syndromes. Assembly of other probe sets will allow novel, technically simple approaches to a wide variety of genetic analyses, including the potential for extension to high resolution genome-wide screens for deletions and amplifications.

An early-biomarker algorithm predicts lethal graft-versus-host disease and survival

PubMed Central

Hartwell, Matthew J.; Özbek, Umut; Holler, Ernst; Major-Monfried, Hannah; Reddy, Pavan; Aziz, Mina; Hogan, William J.; Ayuk, Francis; Efebera, Yvonne A.; Hexner, Elizabeth O.; Bunworasate, Udomsak; Qayed, Muna; Ordemann, Rainer; Wölfl, Matthias; Mielke, Stephan; Chen, Yi-Bin; Devine, Steven; Jagasia, Madan; Kitko, Carrie L.; Litzow, Mark R.; Kröger, Nicolaus; Locatelli, Franco; Morales, George; Nakamura, Ryotaro; Reshef, Ran; Rösler, Wolf; Weber, Daniela; Yanik, Gregory A.; Levine, John E.; Ferrara, James L.M.

2017-01-01

BACKGROUND. No laboratory test can predict the risk of nonrelapse mortality (NRM) or severe graft-versus-host disease (GVHD) after hematopoietic cellular transplantation (HCT) prior to the onset of GVHD symptoms. METHODS. Patient blood samples on day 7 after HCT were obtained from a multicenter set of 1,287 patients, and 620 samples were assigned to a training set. We measured the concentrations of 4 GVHD biomarkers (ST2, REG3α, TNFR1, and IL-2Rα) and used them to model 6-month NRM using rigorous cross-validation strategies to identify the best algorithm that defined 2 distinct risk groups. We then applied the final algorithm in an independent test set (n = 309) and validation set (n = 358). RESULTS. A 2-biomarker model using ST2 and REG3α concentrations identified patients with a cumulative incidence of 6-month NRM of 28% in the high-risk group and 7% in the low-risk group (P < 0.001). The algorithm performed equally well in the test set (33% vs. 7%, P < 0.001) and the multicenter validation set (26% vs. 10%, P < 0.001). Sixteen percent, 17%, and 20% of patients were at high risk in the training, test, and validation sets, respectively. GVHD-related mortality was greater in high-risk patients (18% vs. 4%, P < 0.001), as was severe gastrointestinal GVHD (17% vs. 8%, P < 0.001). The same algorithm can be successfully adapted to define 3 distinct risk groups at GVHD onset. CONCLUSION. A biomarker algorithm based on a blood sample taken 7 days after HCT can consistently identify a group of patients at high risk for lethal GVHD and NRM. FUNDING. The National Cancer Institute, American Cancer Society, and the Doris Duke Charitable Foundation. PMID:28194439

Frequency-Domain Streak Camera and Tomography for Ultrafast Imaging of Evolving and Channeled Plasma Accelerator Structures

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

Li Zhengyan; Zgadzaj, Rafal; Wang Xiaoming

2010-11-04

We demonstrate a prototype Frequency Domain Streak Camera (FDSC) that can capture the picosecond time evolution of the plasma accelerator structure in a single shot. In our prototype Frequency-Domain Streak Camera, a probe pulse propagates obliquely to a sub-picosecond pump pulse that creates an evolving nonlinear index 'bubble' in fused silica glass, supplementing a conventional Frequency Domain Holographic (FDH) probe-reference pair that co-propagates with the 'bubble'. Frequency Domain Tomography (FDT) generalizes Frequency-Domain Streak Camera by probing the 'bubble' from multiple angles and reconstructing its morphology and evolution using algorithms similar to those used in medical CAT scans. Multiplexing methods (Temporalmore » Multiplexing and Angular Multiplexing) improve data storage and processing capability, demonstrating a compact Frequency Domain Tomography system with a single spectrometer.« less

Comparison of chirped-probe-pulse and hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering for combustion thermometry.

PubMed

Richardson, Daniel R; Stauffer, Hans U; Roy, Sukesh; Gord, James R

2017-04-10

A comparison is made between two ultrashort-pulse coherent anti-Stokes Raman scattering (CARS) thermometry techniques-hybrid femtosecond/picosecond (fs/ps) CARS and chirped-probe-pulse (CPP) fs-CARS-that have become standards for high-repetition-rate thermometry in the combustion diagnostics community. These two variants of fs-CARS differ only in the characteristics of the ps-duration probe pulse; in hybrid fs/ps CARS a spectrally narrow, time-asymmetric probe pulse is used, whereas a highly chirped, spectrally broad probe pulse is used in CPP fs-CARS. Temperature measurements were performed using both techniques in near-adiabatic flames in the temperature range 1600-2400 K and for probe time delays of 0-30 ps. Under these conditions, both techniques are shown to exhibit similar temperature measurement accuracies and precisions to previously reported values and to each other. However, it is observed that initial calibration fits to the spectrally broad CPP results require more fitting parameters and a more robust optimization algorithm and therefore significantly increased computational cost and complexity compared to the fitting of hybrid fs/ps CARS data. The optimized model parameters varied more for the CPP measurements than for the hybrid fs/ps measurements for different experimental conditions.

Machine learning aided diagnosis of hepatic malignancies through in vivo dielectric measurements with microwaves.

PubMed

Yilmaz, Tuba; Kılıç, Mahmut Alp; Erdoğan, Melike; Çayören, Mehmet; Tunaoğlu, Doruk; Kurtoğlu, İsmail; Yaslan, Yusuf; Çayören, Hüseyin; Arkan, Akif Enes; Teksöz, Serkan; Cancan, Gülden; Kepil, Nuray; Erdamar, Sibel; Özcan, Murat; Akduman, İbrahim; Kalkan, Tunaya

2016-06-20

In the past decade, extensive research on dielectric properties of biological tissues led to characterization of dielectric property discrepancy between the malignant and healthy tissues. Such discrepancy enabled the development of microwave therapeutic and diagnostic technologies. Traditionally, dielectric property measurements of biological tissues is performed with the well-known contact probe (open-ended coaxial probe) technique. However, the technique suffers from limited accuracy and low loss resolution for permittivity and conductivity measurements, respectively. Therefore, despite the inherent dielectric property discrepancy, a rigorous measurement routine with open-ended coaxial probes is required for accurate differentiation of malignant and healthy tissues. In this paper, we propose to eliminate the need for multiple measurements with open-ended coaxial probe for malignant and healthy tissue differentiation by applying support vector machine (SVM) classification algorithm to the dielectric measurement data. To do so, first, in vivo malignant and healthy rat liver tissue dielectric property measurements are collected with open-ended coaxial probe technique between 500 MHz to 6 GHz. Cole-Cole functions are fitted to the measured dielectric properties and measurement data is verified with the literature. Malign tissue classification is realized by applying SVM to the open-ended coaxial probe measurements where as high as 99.2% accuracy (F1 Score) is obtained.

Quantitative dual-probe microdialysis: mathematical model and analysis.

PubMed

Chen, Kevin C; Höistad, Malin; Kehr, Jan; Fuxe, Kjell; Nicholson, Charles

2002-04-01

Steady-state microdialysis is a widely used technique to monitor the concentration changes and distributions of substances in tissues. To obtain more information about brain tissue properties from microdialysis, a dual-probe approach was applied to infuse and sample the radiotracer, [3H]mannitol, simultaneously both in agar gel and in the rat striatum. Because the molecules released by one probe and collected by the other must diffuse through the interstitial space, the concentration profile exhibits dynamic behavior that permits the assessment of the diffusion characteristics in the brain extracellular space and the clearance characteristics. In this paper a mathematical model for dual-probe microdialysis was developed to study brain interstitial diffusion and clearance processes. Theoretical expressions for the spatial distribution of the infused tracer in the brain extracellular space and the temporal concentration at the probe outlet were derived. A fitting program was developed using the simplex algorithm, which finds local minima of the standard deviations between experiments and theory by adjusting the relevant parameters. The theoretical curves accurately fitted the experimental data and generated realistic diffusion parameters, implying that the mathematical model is capable of predicting the interstitial diffusion behavior of [3H]mannitol and that it will be a valuable quantitative tool in dual-probe microdialysis.

The gradient boosting algorithm and random boosting for genome-assisted evaluation in large data sets.

PubMed

González-Recio, O; Jiménez-Montero, J A; Alenda, R

2013-01-01

In the next few years, with the advent of high-density single nucleotide polymorphism (SNP) arrays and genome sequencing, genomic evaluation methods will need to deal with a large number of genetic variants and an increasing sample size. The boosting algorithm is a machine-learning technique that may alleviate the drawbacks of dealing with such large data sets. This algorithm combines different predictors in a sequential manner with some shrinkage on them; each predictor is applied consecutively to the residuals from the committee formed by the previous ones to form a final prediction based on a subset of covariates. Here, a detailed description is provided and examples using a toy data set are included. A modification of the algorithm called "random boosting" was proposed to increase predictive ability and decrease computation time of genome-assisted evaluation in large data sets. Random boosting uses a random selection of markers to add a subsequent weak learner to the predictive model. These modifications were applied to a real data set composed of 1,797 bulls genotyped for 39,714 SNP. Deregressed proofs of 4 yield traits and 1 type trait from January 2009 routine evaluations were used as dependent variables. A 2-fold cross-validation scenario was implemented. Sires born before 2005 were used as a training sample (1,576 and 1,562 for production and type traits, respectively), whereas younger sires were used as a testing sample to evaluate predictive ability of the algorithm on yet-to-be-observed phenotypes. Comparison with the original algorithm was provided. The predictive ability of the algorithm was measured as Pearson correlations between observed and predicted responses. Further, estimated bias was computed as the average difference between observed and predicted phenotypes. The results showed that the modification of the original boosting algorithm could be run in 1% of the time used with the original algorithm and with negligible differences in accuracy and bias. This modification may be used to speed the calculus of genome-assisted evaluation in large data sets such us those obtained from consortiums. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Learning overcomplete representations from distributed data: a brief review

NASA Astrophysics Data System (ADS)

Raja, Haroon; Bajwa, Waheed U.

2016-05-01

Most of the research on dictionary learning has focused on developing algorithms under the assumption that data is available at a centralized location. But often the data is not available at a centralized location due to practical constraints like data aggregation costs, privacy concerns, etc. Using centralized dictionary learning algorithms may not be the optimal choice in such settings. This motivates the design of dictionary learning algorithms that consider distributed nature of data as one of the problem variables. Just like centralized settings, distributed dictionary learning problem can be posed in more than one way depending on the problem setup. Most notable distinguishing features are the online versus batch nature of data and the representative versus discriminative nature of the dictionaries. In this paper, several distributed dictionary learning algorithms that are designed to tackle different problem setups are reviewed. One of these algorithms is cloud K-SVD, which solves the dictionary learning problem for batch data in distributed settings. One distinguishing feature of cloud K-SVD is that it has been shown to converge to its centralized counterpart, namely, the K-SVD solution. On the other hand, no such guarantees are provided for other distributed dictionary learning algorithms. Convergence of cloud K-SVD to the centralized K-SVD solution means problems that are solvable by K-SVD in centralized settings can now be solved in distributed settings with similar performance. Finally, cloud K-SVD is used as an example to show the advantages that are attainable by deploying distributed dictionary algorithms for real world distributed datasets.

Feasibility of pulse wave velocity estimation from low frame rate US sequences in vivo

NASA Astrophysics Data System (ADS)

Zontak, Maria; Bruce, Matthew; Hippke, Michelle; Schwartz, Alan; O'Donnell, Matthew

2017-03-01

The pulse wave velocity (PWV) is considered one of the most important clinical parameters to evaluate CV risk, vascular adaptation, etc. There has been substantial work attempting to measure the PWV in peripheral vessels using ultrasound (US). This paper presents a fully automatic algorithm for PWV estimation from the human carotid using US sequences acquired with a Logic E9 scanner (modified for RF data capture) and a 9L probe. Our algorithm samples the pressure wave in time by tracking wall displacements over the sequence, and estimates the PWV by calculating the temporal shift between two sampled waves at two distinct locations. Several recent studies have utilized similar ideas along with speckle tracking tools and high frame rate (above 1 KHz) sequences to estimate the PWV. To explore PWV estimation in a more typical clinical setting, we used focused-beam scanning, which yields relatively low frame rates and small fields of view (e.g., 200 Hz for 16.7 mm filed of view). For our application, a 200 Hz frame rate is low. In particular, the sub-frame temporal accuracy required for PWV estimation between locations 16.7 mm apart, ranges from 0.82 of a frame for 4m/s, to 0.33 for 10m/s. When the distance is further reduced (to 0.28 mm between two beams), the sub-frame precision is in parts per thousand (ppt) of the frame (5 ppt for 10m/s). As such, the contributions of our algorithm and this paper are: 1. Ability to work with low frame-rate ( 200Hz) and decreased lateral field of view. 2. Fully automatic segmentation of the wall intima (using raw RF images). 3. Collaborative Speckle Tracking of 2D axial and lateral carotid wall motion. 4. Outlier robust PWV calculation from multiple votes using RANSAC. 5. Algorithm evaluation on volunteers of different ages and health conditions.

Density-based cluster algorithms for the identification of core sets

NASA Astrophysics Data System (ADS)

Lemke, Oliver; Keller, Bettina G.

2016-10-01

The core-set approach is a discretization method for Markov state models of complex molecular dynamics. Core sets are disjoint metastable regions in the conformational space, which need to be known prior to the construction of the core-set model. We propose to use density-based cluster algorithms to identify the cores. We compare three different density-based cluster algorithms: the CNN, the DBSCAN, and the Jarvis-Patrick algorithm. While the core-set models based on the CNN and DBSCAN clustering are well-converged, constructing core-set models based on the Jarvis-Patrick clustering cannot be recommended. In a well-converged core-set model, the number of core sets is up to an order of magnitude smaller than the number of states in a conventional Markov state model with comparable approximation error. Moreover, using the density-based clustering one can extend the core-set method to systems which are not strongly metastable. This is important for the practical application of the core-set method because most biologically interesting systems are only marginally metastable. The key point is to perform a hierarchical density-based clustering while monitoring the structure of the metric matrix which appears in the core-set method. We test this approach on a molecular-dynamics simulation of a highly flexible 14-residue peptide. The resulting core-set models have a high spatial resolution and can distinguish between conformationally similar yet chemically different structures, such as register-shifted hairpin structures.

Stacked Denoising Autoencoders Applied to Star/Galaxy Classification

NASA Astrophysics Data System (ADS)

Qin, Hao-ran; Lin, Ji-ming; Wang, Jun-yi

2017-04-01

In recent years, the deep learning algorithm, with the characteristics of strong adaptability, high accuracy, and structural complexity, has become more and more popular, but it has not yet been used in astronomy. In order to solve the problem that the star/galaxy classification accuracy is high for the bright source set, but low for the faint source set of the Sloan Digital Sky Survey (SDSS) data, we introduced the new deep learning algorithm, namely the SDA (stacked denoising autoencoder) neural network and the dropout fine-tuning technique, which can greatly improve the robustness and antinoise performance. We randomly selected respectively the bright source sets and faint source sets from the SDSS DR12 and DR7 data with spectroscopic measurements, and made preprocessing on them. Then, we randomly selected respectively the training sets and testing sets without replacement from the bright source sets and faint source sets. At last, using these training sets we made the training to obtain the SDA models of the bright sources and faint sources in the SDSS DR7 and DR12, respectively. We compared the test result of the SDA model on the DR12 testing set with the test results of the Library for Support Vector Machines (LibSVM), J48 decision tree, Logistic Model Tree (LMT), Support Vector Machine (SVM), Logistic Regression, and Decision Stump algorithm, and compared the test result of the SDA model on the DR7 testing set with the test results of six kinds of decision trees. The experiments show that the SDA has a better classification accuracy than other machine learning algorithms for the faint source sets of DR7 and DR12. Especially, when the completeness function is used as the evaluation index, compared with the decision tree algorithms, the correctness rate of SDA has improved about 15% for the faint source set of SDSS-DR7.

Developing an Enhanced Lightning Jump Algorithm for Operational Use

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Petersen, Walter A.; Carey, Lawrence D.

2009-01-01

Overall Goals: 1. Build on the lightning jump framework set through previous studies. 2. Understand what typically occurs in nonsevere convection with respect to increases in lightning. 3. Ultimately develop a lightning jump algorithm for use on the Geostationary Lightning Mapper (GLM). 4 Lightning jump algorithm configurations were developed (2(sigma), 3(sigma), Threshold 10 and Threshold 8). 5 algorithms were tested on a population of 47 nonsevere and 38 severe thunderstorms. Results indicate that the 2(sigma) algorithm performed best over the entire thunderstorm sample set with a POD of 87%, a far of 35%, a CSI of 59% and a HSS of 75%.

System and method for resolving gamma-ray spectra

DOEpatents

Gentile, Charles A.; Perry, Jason; Langish, Stephen W.; Silber, Kenneth; Davis, William M.; Mastrovito, Dana

2010-05-04

A system for identifying radionuclide emissions is described. The system includes at least one processor for processing output signals from a radionuclide detecting device, at least one training algorithm run by the at least one processor for analyzing data derived from at least one set of known sample data from the output signals, at least one classification algorithm derived from the training algorithm for classifying unknown sample data, wherein the at least one training algorithm analyzes the at least one sample data set to derive at least one rule used by said classification algorithm for identifying at least one radionuclide emission detected by the detecting device.

Self-Nulling Eddy Current Probe for Surface and Subsurface Flaw Detection

NASA Technical Reports Server (NTRS)

Wincheski, B.; Fulton, J. P.; Nath, S.; Namkung, M.; Simpson, J. W.

1994-01-01

An eddy current probe which provides a null-signal in the presence of unflawed material without the need for any balancing circuitry has been developed at NASA Langley Research Center. Such a unique capability of the probe reduces set-up time, eliminates tester configuration errors, and decreases instrumentation requirements. The probe is highly sensitive to surface breaking fatigue cracks, and shows excellent resolution for the measurement of material thickness, including material loss due to corrosion damage. The presence of flaws in the material under test causes an increase in the extremely stable and reproducible output voltage of the probe. The design of the probe and some examples illustrating its flaw detection capabilities are presented.

Measurement of non-sugar solids content in Chinese rice wine using near infrared spectroscopy combined with an efficient characteristic variables selection algorithm.

PubMed

Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng

2015-01-01

The non-sugar solids (NSS) content is one of the most important nutrition indicators of Chinese rice wine. This study proposed a rapid method for the measurement of NSS content in Chinese rice wine using near infrared (NIR) spectroscopy. We also systemically studied the efficient spectral variables selection algorithms that have to go through modeling. A new algorithm of synergy interval partial least square with competitive adaptive reweighted sampling (Si-CARS-PLS) was proposed for modeling. The performance of the final model was back-evaluated using root mean square error of calibration (RMSEC) and correlation coefficient (Rc) in calibration set and similarly tested by mean square error of prediction (RMSEP) and correlation coefficient (Rp) in prediction set. The optimum model by Si-CARS-PLS algorithm was achieved when 7 PLS factors and 18 variables were included, and the results were as follows: Rc=0.95 and RMSEC=1.12 in the calibration set, Rp=0.95 and RMSEP=1.22 in the prediction set. In addition, Si-CARS-PLS algorithm showed its superiority when compared with the commonly used algorithms in multivariate calibration. This work demonstrated that NIR spectroscopy technique combined with a suitable multivariate calibration algorithm has a high potential in rapid measurement of NSS content in Chinese rice wine. Copyright © 2015 Elsevier B.V. All rights reserved.

A practical model for pressure probe system response estimation (with review of existing models)

NASA Astrophysics Data System (ADS)

Hall, B. F.; Povey, T.

2018-04-01

The accurate estimation of the unsteady response (bandwidth) of pneumatic pressure probe systems (probe, line and transducer volume) is a common practical problem encountered in the design of aerodynamic experiments. Understanding the bandwidth of the probe system is necessary to capture unsteady flow features accurately. Where traversing probes are used, the desired traverse speed and spatial gradients in the flow dictate the minimum probe system bandwidth required to resolve the flow. Existing approaches for bandwidth estimation are either complex or inaccurate in implementation, so probes are often designed based on experience. Where probe system bandwidth is characterized, it is often done experimentally, requiring careful experimental set-up and analysis. There is a need for a relatively simple but accurate model for estimation of probe system bandwidth. A new model is presented for the accurate estimation of pressure probe bandwidth for simple probes commonly used in wind tunnel environments; experimental validation is provided. An additional, simple graphical method for air is included for convenience.

Four-probe measurements with a three-probe scanning tunneling microscope

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

Salomons, Mark; Martins, Bruno V. C.; Zikovsky, Janik

2014-04-15

We present an ultrahigh vacuum (UHV) three-probe scanning tunneling microscope in which each probe is capable of atomic resolution. A UHV JEOL scanning electron microscope aids in the placement of the probes on the sample. The machine also has a field ion microscope to clean, atomically image, and shape the probe tips. The machine uses bare conductive samples and tips with a homebuilt set of pliers for heating and loading. Automated feedback controlled tip-surface contacts allow for electrical stability and reproducibility while also greatly reducing tip and surface damage due to contact formation. The ability to register inter-tip position bymore » imaging of a single surface feature by multiple tips is demonstrated. Four-probe material characterization is achieved by deploying two tips as fixed current probes and the third tip as a movable voltage probe.« less

SCENERY: a web application for (causal) network reconstruction from cytometry data.

PubMed

Papoutsoglou, Georgios; Athineou, Giorgos; Lagani, Vincenzo; Xanthopoulos, Iordanis; Schmidt, Angelika; Éliás, Szabolcs; Tegnér, Jesper; Tsamardinos, Ioannis

2017-07-03

Flow and mass cytometry technologies can probe proteins as biological markers in thousands of individual cells simultaneously, providing unprecedented opportunities for reconstructing networks of protein interactions through machine learning algorithms. The network reconstruction (NR) problem has been well-studied by the machine learning community. However, the potentials of available methods remain largely unknown to the cytometry community, mainly due to their intrinsic complexity and the lack of comprehensive, powerful and easy-to-use NR software implementations specific for cytometry data. To bridge this gap, we present Single CEll NEtwork Reconstruction sYstem (SCENERY), a web server featuring several standard and advanced cytometry data analysis methods coupled with NR algorithms in a user-friendly, on-line environment. In SCENERY, users may upload their data and set their own study design. The server offers several data analysis options categorized into three classes of methods: data (pre)processing, statistical analysis and NR. The server also provides interactive visualization and download of results as ready-to-publish images or multimedia reports. Its core is modular and based on the widely-used and robust R platform allowing power users to extend its functionalities by submitting their own NR methods. SCENERY is available at scenery.csd.uoc.gr or http://mensxmachina.org/en/software/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Algorithm That Synthesizes Other Algorithms for Hashing

NASA Technical Reports Server (NTRS)

James, Mark

2010-01-01

An algorithm that includes a collection of several subalgorithms has been devised as a means of synthesizing still other algorithms (which could include computer code) that utilize hashing to determine whether an element (typically, a number or other datum) is a member of a set (typically, a list of numbers). Each subalgorithm synthesizes an algorithm (e.g., a block of code) that maps a static set of key hashes to a somewhat linear monotonically increasing sequence of integers. The goal in formulating this mapping is to cause the length of the sequence thus generated to be as close as practicable to the original length of the set and thus to minimize gaps between the elements. The advantage of the approach embodied in this algorithm is that it completely avoids the traditional approach of hash-key look-ups that involve either secondary hash generation and look-up or further searching of a hash table for a desired key in the event of collisions. This algorithm guarantees that it will never be necessary to perform a search or to generate a secondary key in order to determine whether an element is a member of a set. This algorithm further guarantees that any algorithm that it synthesizes can be executed in constant time. To enforce these guarantees, the subalgorithms are formulated to employ a set of techniques, each of which works very effectively covering a certain class of hash-key values. These subalgorithms are of two types, summarized as follows: Given a list of numbers, try to find one or more solutions in which, if each number is shifted to the right by a constant number of bits and then masked with a rotating mask that isolates a set of bits, a unique number is thereby generated. In a variant of the foregoing procedure, omit the masking. Try various combinations of shifting, masking, and/or offsets until the solutions are found. From the set of solutions, select the one that provides the greatest compression for the representation and is executable in the minimum amount of time. Given a list of numbers, try to find one or more solutions in which, if each number is compressed by use of the modulo function by some value, then a unique value is generated.

A study on the application of topic models to motif finding algorithms.

PubMed

Basha Gutierrez, Josep; Nakai, Kenta

2016-12-22

Topic models are statistical algorithms which try to discover the structure of a set of documents according to the abstract topics contained in them. Here we try to apply this approach to the discovery of the structure of the transcription factor binding sites (TFBS) contained in a set of biological sequences, which is a fundamental problem in molecular biology research for the understanding of transcriptional regulation. Here we present two methods that make use of topic models for motif finding. First, we developed an algorithm in which first a set of biological sequences are treated as text documents, and the k-mers contained in them as words, to then build a correlated topic model (CTM) and iteratively reduce its perplexity. We also used the perplexity measurement of CTMs to improve our previous algorithm based on a genetic algorithm and several statistical coefficients. The algorithms were tested with 56 data sets from four different species and compared to 14 other methods by the use of several coefficients both at nucleotide and site level. The results of our first approach showed a performance comparable to the other methods studied, especially at site level and in sensitivity scores, in which it scored better than any of the 14 existing tools. In the case of our previous algorithm, the new approach with the addition of the perplexity measurement clearly outperformed all of the other methods in sensitivity, both at nucleotide and site level, and in overall performance at site level. The statistics obtained show that the performance of a motif finding method based on the use of a CTM is satisfying enough to conclude that the application of topic models is a valid method for developing motif finding algorithms. Moreover, the addition of topic models to a previously developed method dramatically increased its performance, suggesting that this combined algorithm can be a useful tool to successfully predict motifs in different kinds of sets of DNA sequences.

Support for the Harvard University Water Vapor and Total Water Instruments for the 2004 NASA WB57 Middle Latitude Cirrus Experiment

NASA Technical Reports Server (NTRS)

Anderson, James G.

2005-01-01

In order to improve our understanding of the role clouds play in the climate system, NASA is investing considerable effort in characterizing clouds with instruments ranging from passive remote sensors on board the EOS platforms, to the forthcoming active remote sensors on Cloudsat and Calipso. These missions, when taken together, have the capacity to advance our understanding of the coupling between various components of the hydrologic cycle and the atmospheric circulation, and hold the additional potential of leading to significant improvements in the characterization of cloud feedbacks in global models. This is especially true considering that several of these platforms will be flown in an identical orbit within several minutes of one another-a constellation of satellites known as the A-Train. The algorithms that are being implemented and developed to convert these new data streams from radiance and reflectivity measurements into geophysical parameters invariably rely on some set of simplifymg assumptions and empirical constants. Uncertainties in these relationships lead to poorly understood random and systematic errors in the retrieved properties. This lack of understanding introduces ambiguity in interpreting the data and in using the global data sets for their intended purposes. In light of this, a series of flights with the W57F was proposed to address certain specific issues related to the basic properties of mid latitude cirrus clouds: the NASA WE357 Middle Latitude Cirrus Experiment ("MidCiX"). The science questions addressed are: 1) Can cloud property retrieval algorithms developed for A-Train active and passive remote sensing measurements accurately characterize the microphysical properties of synoptic and convectively generated cirrus cloud systems? 2) What are the relationships between the cirrus particle mass, projected area, and particle size spectrum in various genre of cirrus clouds? 3) Does the present compliment of state of the art in situ cloud probes provide the level of precision and accuracy needed to develop and validate algorithms and to contribute to our understanding of the characteristics and microphysical processes operating in cirrus clouds?

Contour-based object orientation estimation

NASA Astrophysics Data System (ADS)

Alpatov, Boris; Babayan, Pavel

2016-04-01

Real-time object orientation estimation is an actual problem of computer vision nowadays. In this paper we propose an approach to estimate an orientation of objects lacking axial symmetry. Proposed algorithm is intended to estimate orientation of a specific known 3D object, so 3D model is required for learning. The proposed orientation estimation algorithm consists of 2 stages: learning and estimation. Learning stage is devoted to the exploring of studied object. Using 3D model we can gather set of training images by capturing 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. It minimizes the training image set. Gathered training image set is used for calculating descriptors, which will be used in the estimation stage of the algorithm. The estimation stage is focusing on matching process between an observed image descriptor and the training image descriptors. The experimental research was performed using a set of images of Airbus A380. The proposed orientation estimation algorithm showed good accuracy (mean error value less than 6°) in all case studies. The real-time performance of the algorithm was also demonstrated.

Designing Waveform Sets with Good Correlation and Stopband Properties for MIMO Radar via the Gradient-Based Method

PubMed Central

Tang, Liang; Zhu, Yongfeng; Fu, Qiang

2017-01-01

Waveform sets with good correlation and/or stopband properties have received extensive attention and been widely used in multiple-input multiple-output (MIMO) radar. In this paper, we aim at designing unimodular waveform sets with good correlation and stopband properties. To formulate the problem, we construct two criteria to measure the correlation and stopband properties and then establish an unconstrained problem in the frequency domain. After deducing the phase gradient and the step size, an efficient gradient-based algorithm with monotonicity is proposed to minimize the objective function directly. For the design problem without considering the correlation weights, we develop a simplified algorithm, which only requires a few fast Fourier transform (FFT) operations and is more efficient. Because both of the algorithms can be implemented via the FFT operations and the Hadamard product, they are computationally efficient and can be used to design waveform sets with a large waveform number and waveform length. Numerical experiments show that the proposed algorithms can provide better performance than the state-of-the-art algorithms in terms of the computational complexity. PMID:28468308

Designing Waveform Sets with Good Correlation and Stopband Properties for MIMO Radar via the Gradient-Based Method.

PubMed

Tang, Liang; Zhu, Yongfeng; Fu, Qiang

2017-05-01

Waveform sets with good correlation and/or stopband properties have received extensive attention and been widely used in multiple-input multiple-output (MIMO) radar. In this paper, we aim at designing unimodular waveform sets with good correlation and stopband properties. To formulate the problem, we construct two criteria to measure the correlation and stopband properties and then establish an unconstrained problem in the frequency domain. After deducing the phase gradient and the step size, an efficient gradient-based algorithm with monotonicity is proposed to minimize the objective function directly. For the design problem without considering the correlation weights, we develop a simplified algorithm, which only requires a few fast Fourier transform (FFT) operations and is more efficient. Because both of the algorithms can be implemented via the FFT operations and the Hadamard product, they are computationally efficient and can be used to design waveform sets with a large waveform number and waveform length. Numerical experiments show that the proposed algorithms can provide better performance than the state-of-the-art algorithms in terms of the computational complexity.

A new improved artificial bee colony algorithm for ship hull form optimization

NASA Astrophysics Data System (ADS)

Huang, Fuxin; Wang, Lijue; Yang, Chi

2016-04-01

The artificial bee colony (ABC) algorithm is a relatively new swarm intelligence-based optimization algorithm. Its simplicity of implementation, relatively few parameter settings and promising optimization capability make it widely used in different fields. However, it has problems of slow convergence due to its solution search equation. Here, a new solution search equation based on a combination of the elite solution pool and the block perturbation scheme is proposed to improve the performance of the algorithm. In addition, two different solution search equations are used by employed bees and onlooker bees to balance the exploration and exploitation of the algorithm. The developed algorithm is validated by a set of well-known numerical benchmark functions. It is then applied to optimize two ship hull forms with minimum resistance. The tested results show that the proposed new improved ABC algorithm can outperform the ABC algorithm in most of the tested problems.

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer

PubMed Central

Veta, Mitko; Johannes van Diest, Paul; van Ginneken, Bram; Karssemeijer, Nico; Litjens, Geert; van der Laak, Jeroen A. W. M.; Hermsen, Meyke; Manson, Quirine F; Balkenhol, Maschenka; Geessink, Oscar; Stathonikos, Nikolaos; van Dijk, Marcory CRF; Bult, Peter; Beca, Francisco; Beck, Andrew H; Wang, Dayong; Khosla, Aditya; Gargeya, Rishab; Irshad, Humayun; Zhong, Aoxiao; Dou, Qi; Li, Quanzheng; Chen, Hao; Lin, Huang-Jing; Heng, Pheng-Ann; Haß, Christian; Bruni, Elia; Wong, Quincy; Halici, Ugur; Öner, Mustafa Ümit; Cetin-Atalay, Rengul; Berseth, Matt; Khvatkov, Vitali; Vylegzhanin, Alexei; Kraus, Oren; Shaban, Muhammad; Rajpoot, Nasir; Awan, Ruqayya; Sirinukunwattana, Korsuk; Qaiser, Talha; Tsang, Yee-Wah; Tellez, David; Annuscheit, Jonas; Hufnagl, Peter; Valkonen, Mira; Kartasalo, Kimmo; Latonen, Leena; Ruusuvuori, Pekka; Liimatainen, Kaisa; Albarqouni, Shadi; Mungal, Bharti; George, Ami; Demirci, Stefanie; Navab, Nassir; Watanabe, Seiryo; Seno, Shigeto; Takenaka, Yoichi; Matsuda, Hideo; Ahmady Phoulady, Hady; Kovalev, Vassili; Kalinovsky, Alexander; Liauchuk, Vitali; Bueno, Gloria; Fernandez-Carrobles, M. Milagro; Serrano, Ismael; Deniz, Oscar; Racoceanu, Daniel; Venâncio, Rui

2017-01-01

Importance Application of deep learning algorithms to whole-slide pathology images can potentially improve diagnostic accuracy and efficiency. Objective Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin–stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists’ diagnoses in a diagnostic setting. Design, Setting, and Participants Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC). Exposures Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation. Main Outcomes and Measures The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor. Results The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4% [95% CI, 64.3%-80.4%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P < .001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95% CI, 0.927-0.998] for the pathologist WOTC). Conclusions and Relevance In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting. PMID:29234806

Multiwaveguide implantable probe for light delivery to sets of distributed brain targets.

PubMed

Zorzos, Anthony N; Boyden, Edward S; Fonstad, Clifton G

2010-12-15

Optical fibers are commonly inserted into living tissues such as the brain in order to deliver light to deep targets for neuroscientific and neuroengineering applications such as optogenetics, in which light is used to activate or silence neurons expressing specific photosensitive proteins. However, an optical fiber is limited to delivering light to a single target within the three-dimensional structure of the brain. We here demonstrate a multiwaveguide probe capable of independently delivering light to multiple targets along the probe axis, thus enabling versatile optical control of sets of distributed brain targets. The 1.45-cm-long probe is microfabricated in the form of a 360-μm-wide array of 12 parallel silicon oxynitride (SiON) multimode waveguides clad with SiO(2) and coated with aluminum; probes of custom dimensions are easily created as well. The waveguide array accepts light from a set of sources at the input end and guides the light down each waveguide to an aluminum corner mirror that efficiently deflects light away from the probe axis. Light losses at each stage are small (input coupling loss, 0.4 ± 0.3 dB; bend loss, negligible; propagation loss, 3.1 ± 1 dB/cm using the outscattering method and 3.2 ± 0.4 dB/cm using the cutback method; corner mirror loss, 1.5 ± 0.4 dB); a waveguide coupled, for example, to a 5 mW source will deliver over 1.5 mW to a target at a depth of 1 cm.

Clustering algorithms for identifying core atom sets and for assessing the precision of protein structure ensembles.

PubMed

Snyder, David A; Montelione, Gaetano T

2005-06-01

An important open question in the field of NMR-based biomolecular structure determination is how best to characterize the precision of the resulting ensemble of structures. Typically, the RMSD, as minimized in superimposing the ensemble of structures, is the preferred measure of precision. However, the presence of poorly determined atomic coordinates and multiple "RMSD-stable domains"--locally well-defined regions that are not aligned in global superimpositions--complicate RMSD calculations. In this paper, we present a method, based on a novel, structurally defined order parameter, for identifying a set of core atoms to use in determining superimpositions for RMSD calculations. In addition we present a method for deciding whether to partition that core atom set into "RMSD-stable domains" and, if so, how to determine partitioning of the core atom set. We demonstrate our algorithm and its application in calculating statistically sound RMSD values by applying it to a set of NMR-derived structural ensembles, superimposing each RMSD-stable domain (or the entire core atom set, where appropriate) found in each protein structure under consideration. A parameter calculated by our algorithm using a novel, kurtosis-based criterion, the epsilon-value, is a measure of precision of the superimposition that complements the RMSD. In addition, we compare our algorithm with previously described algorithms for determining core atom sets. The methods presented in this paper for biomolecular structure superimposition are quite general, and have application in many areas of structural bioinformatics and structural biology.

Clustering Binary Data in the Presence of Masking Variables

ERIC Educational Resources Information Center

Brusco, Michael J.

2004-01-01

A number of important applications require the clustering of binary data sets. Traditional nonhierarchical cluster analysis techniques, such as the popular K-means algorithm, can often be successfully applied to these data sets. However, the presence of masking variables in a data set can impede the ability of the K-means algorithm to recover the…

Research on distributed heterogeneous data PCA algorithm based on cloud platform

NASA Astrophysics Data System (ADS)

Zhang, Jin; Huang, Gang

2018-05-01

Principal component analysis (PCA) of heterogeneous data sets can solve the problem that centralized data scalability is limited. In order to reduce the generation of intermediate data and error components of distributed heterogeneous data sets, a principal component analysis algorithm based on heterogeneous data sets under cloud platform is proposed. The algorithm performs eigenvalue processing by using Householder tridiagonalization and QR factorization to calculate the error component of the heterogeneous database associated with the public key to obtain the intermediate data set and the lost information. Experiments on distributed DBM heterogeneous datasets show that the model method has the feasibility and reliability in terms of execution time and accuracy.

Circular dichroism in photoelectron images from aligned nitric oxide molecules

DOE PAGES

Sen, Ananya; Pratt, S. T.; Reid, K. L.

2017-05-03

We have used velocity map photoelectron imaging to study circular dichroism of the photoelectron angular distributions (PADs) of nitric oxide following two-color resonanceenhanced two-photon ionization via selected rotational levels of the A 2Σ +, v' = 0 state. By using a circularly polarized pump beam and a counter-propagating, circularly polarized probe beam, cylindrical symmetry is preserved in the ionization process, and the images can be reconstructed using standard algorithms. The VMI set up enables individual ion rotational states to be resolved with excellent collection efficiency, rendering the measurements considerably simpler to perform than previous measurements conducted with a conventional photoelectronmore » spectrometer. The results demonstrate that circular dichroism is observed even when cylindrical symmetry is maintained, and serve as a reminder that dichroism is a general feature of the multiphoton ionization of atoms and molecules. Furthermore, the observed PADs are in good agreement with calculations based on parameters extracted from previous experimental results obtained by using a time-offlight electron spectrometer.« less

Measuring mRNA copy-number in individual Escherichia coli cells using single-molecule fluorescent in situ hybridization (smFISH)

PubMed Central

Skinner, Samuel O.; Sepúlveda, Leonardo A.; Xu, Heng; Golding, Ido

2014-01-01

We present a method for measuring the absolute number of mRNA molecules from a gene of interest in individual, chemically fixed Escherichia coli cells. A set of fluorescently-labeled oligonucleotide probes are hybridized to the target mRNA, so that each mRNA molecule is decorated by a known number of fluorescent dyes. Cells are then imaged using fluorescence microscopy. The number of target mRNA is estimated from the total intensity of fluorescent foci in the cell, rather than from counting discrete “spots” as in other currently available protocols. Image analysis is performed using an automated algorithm. The measured mRNA copy-number distribution obtained from many individual cells can be used to extract the parameters of stochastic gene activity, namely the frequency and size of transcription bursts from the gene of interest. The experimental procedure takes 2 days, with another 2-3 days typically required for image and data analysis. PMID:23680982

Influence of Ionization and Beam Quality on Interaction of TW-Peak CO2 Laser with Hydrogen Plasma

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

Samulyak, Roman

3D numerical simulations of the interaction of a powerful CO2 laser with hydrogen jets demonstrating the role of ionization and laser beam quality are presented. Simulations are performed in support of the plasma wakefield accelerator experiments being conducted at the BNL Accelerator Test Facility (ATF). The CO2 laser at BNL ATF has several potential advantages for laser wakefield acceleration compared to widely used solid-state lasers. SPACE, a parallel relativistic Particle-in-Cell code, developed at SBU and BNL, has been used in these studies. A novelty of the code is its set of efficient atomic physics algorithms that compute ionization and recombinationmore » rates on the grid and transfer them to particles. The primary goal of the initial BNL experiments was to characterize the plasma density by measuring the sidebands in the spectrum of the probe laser. Simulations, that resolve hydrogen ionization and laser spectra, help explain several trends that were observed in the experiments.« less

MARTINI: An event generator for relativistic heavy-ion collisions

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

Schenke, Bjoern; Gale, Charles; Jeon, Sangyong

2009-11-15

We introduce the modular algorithm for relativistic treatment of heavy ion interactions (MARTINI), a comprehensive event generator for the hard and penetrating probes in high-energy nucleus-nucleus collisions. Its main components are a time-evolution model for the soft background, PYTHIA 8.1, and the McGill-Arnold, Moore, and Yaffe (AMY) parton-evolution scheme, including radiative as well as elastic processes. This allows us to generate full event configurations in the high p{sub T} region that take into account thermal quantum chromodynamic (QCD) and quantum electrodynamic (QED) effects as well as effects of the evolving medium. We present results for the neutral pion nuclear modificationmore » factor in Au+Au collisions at the BNL Relativistic Heavy Ion Collider as a function of p{sub T} for different centralities and also as a function of the angle with respect to the reaction plane for noncentral collisions. Furthermore, we study the production of high-transverse-momentum photons, incorporating a complete set of photon-production channels.« less

In vivo quantitative bioluminescence tomography using heterogeneous and homogeneous mouse models.

PubMed

Liu, Junting; Wang, Yabin; Qu, Xiaochao; Li, Xiangsi; Ma, Xiaopeng; Han, Runqiang; Hu, Zhenhua; Chen, Xueli; Sun, Dongdong; Zhang, Rongqing; Chen, Duofang; Chen, Dan; Chen, Xiaoyuan; Liang, Jimin; Cao, Feng; Tian, Jie

2010-06-07

Bioluminescence tomography (BLT) is a new optical molecular imaging modality, which can monitor both physiological and pathological processes by using bioluminescent light-emitting probes in small living animal. Especially, this technology possesses great potential in drug development, early detection, and therapy monitoring in preclinical settings. In the present study, we developed a dual modality BLT prototype system with Micro-computed tomography (MicroCT) registration approach, and improved the quantitative reconstruction algorithm based on adaptive hp finite element method (hp-FEM). Detailed comparisons of source reconstruction between the heterogeneous and homogeneous mouse models were performed. The models include mice with implanted luminescence source and tumor-bearing mice with firefly luciferase report gene. Our data suggest that the reconstruction based on heterogeneous mouse model is more accurate in localization and quantification than the homogeneous mouse model with appropriate optical parameters and that BLT allows super-early tumor detection in vivo based on tomographic reconstruction of heterogeneous mouse model signal.

Circular dichroism in photoelectron images from aligned nitric oxide molecules

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

Sen, Ananya; Pratt, S. T.; Reid, K. L.

We have used velocity map photoelectron imaging to study circular dichroism of the photoelectron angular distributions (PADs) of nitric oxide following two-color resonanceenhanced two-photon ionization via selected rotational levels of the A 2Σ +, v' = 0 state. By using a circularly polarized pump beam and a counter-propagating, circularly polarized probe beam, cylindrical symmetry is preserved in the ionization process, and the images can be reconstructed using standard algorithms. The VMI set up enables individual ion rotational states to be resolved with excellent collection efficiency, rendering the measurements considerably simpler to perform than previous measurements conducted with a conventional photoelectronmore » spectrometer. The results demonstrate that circular dichroism is observed even when cylindrical symmetry is maintained, and serve as a reminder that dichroism is a general feature of the multiphoton ionization of atoms and molecules. Furthermore, the observed PADs are in good agreement with calculations based on parameters extracted from previous experimental results obtained by using a time-offlight electron spectrometer.« less

Array magnetics modal analysis for the DIII-D tokamak based on localized time-series modelling

DOE PAGES

Olofsson, K. Erik J.; Hanson, Jeremy M.; Shiraki, Daisuke; ...

2014-07-14

Here, time-series analysis of magnetics data in tokamaks is typically done using block-based fast Fourier transform methods. This work presents the development and deployment of a new set of algorithms for magnetic probe array analysis. The method is based on an estimation technique known as stochastic subspace identification (SSI). Compared with the standard coherence approach or the direct singular value decomposition approach, the new technique exhibits several beneficial properties. For example, the SSI method does not require that frequencies are orthogonal with respect to the timeframe used in the analysis. Frequencies are obtained directly as parameters of localized time-series models.more » The parameters are extracted by solving small-scale eigenvalue problems. Applications include maximum-likelihood regularized eigenmode pattern estimation, detection of neoclassical tearing modes, including locked mode precursors, and automatic clustering of modes, and magnetics-pattern characterization of sawtooth pre- and postcursors, edge harmonic oscillations and fishbones.« less

Magnetic resonance fingerprinting.

PubMed

Ma, Dan; Gulani, Vikas; Seiberlich, Nicole; Liu, Kecheng; Sunshine, Jeffrey L; Duerk, Jeffrey L; Griswold, Mark A

2013-03-14

Magnetic resonance is an exceptionally powerful and versatile measurement technique. The basic structure of a magnetic resonance experiment has remained largely unchanged for almost 50 years, being mainly restricted to the qualitative probing of only a limited set of the properties that can in principle be accessed by this technique. Here we introduce an approach to data acquisition, post-processing and visualization--which we term 'magnetic resonance fingerprinting' (MRF)--that permits the simultaneous non-invasive quantification of multiple important properties of a material or tissue. MRF thus provides an alternative way to quantitatively detect and analyse complex changes that can represent physical alterations of a substance or early indicators of disease. MRF can also be used to identify the presence of a specific target material or tissue, which will increase the sensitivity, specificity and speed of a magnetic resonance study, and potentially lead to new diagnostic testing methodologies. When paired with an appropriate pattern-recognition algorithm, MRF inherently suppresses measurement errors and can thus improve measurement accuracy.

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

PubMed

Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean

2017-12-04

Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further using multiple metrics with much larger scale comparisons, prospective testing as well as assessment of different fingerprints and DNN architectures beyond those used.

Sparse representation and Bayesian detection of genome copy number alterations from microarray data.

PubMed

Pique-Regi, Roger; Monso-Varona, Jordi; Ortega, Antonio; Seeger, Robert C; Triche, Timothy J; Asgharzadeh, Shahab

2008-02-01

Genomic instability in cancer leads to abnormal genome copy number alterations (CNA) that are associated with the development and behavior of tumors. Advances in microarray technology have allowed for greater resolution in detection of DNA copy number changes (amplifications or deletions) across the genome. However, the increase in number of measured signals and accompanying noise from the array probes present a challenge in accurate and fast identification of breakpoints that define CNA. This article proposes a novel detection technique that exploits the use of piece wise constant (PWC) vectors to represent genome copy number and sparse Bayesian learning (SBL) to detect CNA breakpoints. First, a compact linear algebra representation for the genome copy number is developed from normalized probe intensities. Second, SBL is applied and optimized to infer locations where copy number changes occur. Third, a backward elimination (BE) procedure is used to rank the inferred breakpoints; and a cut-off point can be efficiently adjusted in this procedure to control for the false discovery rate (FDR). The performance of our algorithm is evaluated using simulated and real genome datasets and compared to other existing techniques. Our approach achieves the highest accuracy and lowest FDR while improving computational speed by several orders of magnitude. The proposed algorithm has been developed into a free standing software application (GADA, Genome Alteration Detection Algorithm). http://biron.usc.edu/~piquereg/GADA

A learning approach to the bandwidth multicolouring problem

NASA Astrophysics Data System (ADS)

Akbari Torkestani, Javad

2016-05-01

In this article, a generalisation of the vertex colouring problem known as bandwidth multicolouring problem (BMCP), in which a set of colours is assigned to each vertex such that the difference between the colours, assigned to each vertex and its neighbours, is by no means less than a predefined threshold, is considered. It is shown that the proposed method can be applied to solve the bandwidth colouring problem (BCP) as well. BMCP is known to be NP-hard in graph theory, and so a large number of approximation solutions, as well as exact algorithms, have been proposed to solve it. In this article, two learning automata-based approximation algorithms are proposed for estimating a near-optimal solution to the BMCP. We show, for the first proposed algorithm, that by choosing a proper learning rate, the algorithm finds the optimal solution with a probability close enough to unity. Moreover, we compute the worst-case time complexity of the first algorithm for finding a 1/(1-ɛ) optimal solution to the given problem. The main advantage of this method is that a trade-off between the running time of algorithm and the colour set size (colouring optimality) can be made, by a proper choice of the learning rate also. Finally, it is shown that the running time of the proposed algorithm is independent of the graph size, and so it is a scalable algorithm for large graphs. The second proposed algorithm is compared with some well-known colouring algorithms and the results show the efficiency of the proposed algorithm in terms of the colour set size and running time of algorithm.

Method for determining thermal conductivity and thermal capacity per unit volume of earth in situ

DOEpatents

Poppendiek, Heinz F.

1982-01-01

A method for determining the thermal conductivity of the earth in situ is based upon a cylindrical probe (10) having a thermopile (16) for measuring the temperature gradient between sets of thermocouple junctions (18 and 20) of the probe after it has been positioned in a borehole and has reached thermal equilibrium with its surroundings, and having means (14) for heating one set of thermocouple junctions (20) of the probe at a constant rate while the temperature gradient of the probe is recorded as a rise in temperature over several hours (more than about 3 hours). A fluid annulus thermally couples the probe to the surrounding earth. The recorded temperature curves are related to the earth's thermal conductivity, k.sub..infin., and to the thermal capacity per unit volume, (.gamma.c.sub.p).sub..infin., by comparison with calculated curves using estimates of k.sub..infin. and (.gamma.c.sub.p).sub..infin. in an equation which relates these parameters to a rise in the earth's temperature for a known and constant heating rate.

A refraction-corrected tomographic algorithm for immersion laser-ultrasonic imaging of solids with piecewise linear surface profile

NASA Astrophysics Data System (ADS)

Zarubin, V.; Bychkov, A.; Simonova, V.; Zhigarkov, V.; Karabutov, A.; Cherepetskaya, E.

2018-05-01

In this paper, a technique for reflection mode immersion 2D laser-ultrasound tomography of solid objects with piecewise linear 2D surface profiles is presented. Pulsed laser radiation was used for generation of short ultrasonic probe pulses, providing high spatial resolution. A piezofilm sensor array was used for detection of the waves reflected by the surface and internal inhomogeneities of the object. The original ultrasonic image reconstruction algorithm accounting for refraction of acoustic waves at the liquid-solid interface provided longitudinal resolution better than 100 μm in the polymethyl methacrylate sample object.

The Wide-Field Imaging Interferometry Testbed: Recent Results

NASA Technical Reports Server (NTRS)

Rinehart, Stephen

2006-01-01

We present recent results from the Wide-Field Imaging Interferometry Testbed (WIIT). The data acquired with the WIIT is "double Fourier" data, including both spatial and spectral information within each data cube. We have been working with this data, and starting to develop algorithms, implementations, and techniques for reducing this data. Such algorithms and tools are of great importance for a number of proposed future missions, including the Space Infrared Interferometric Telescope (SPIRIT), the Submillimeter Probe of the Evolution of Cosmic Structure (SPECS), and the Terrestrial Planet Finder Interferometer (TPF-I)/Darwin. Recent results are discussed and future study directions are described.

Use of Fuzzycones for Sun-Only Attitude Determination: THEMIS Becomes ARTEMIS

NASA Technical Reports Server (NTRS)

Hashmall, Joseph A.; Felikson, Denis; Sedlak, Joseph E.

2009-01-01

In order for two THEMIS probes to successfully transition to ARTEMIS it will be necessary to determine attitudes with moderate accuracy using Sun sensor data only. To accomplish this requirement, an implementation of the Fuzzycones maximum likelihood algorithm was developed. The effect of different measurement uncertainty models on Fuzzycones attitude accuracy was investigated and a bin-transition technique was introduced to improve attitude accuracy using data with uniform error distributions. The algorithm was tested with THEMIS data and in simulations. The analysis results show that the attitude requirements can be met using Fuzzycones and data containing two bin-transitions.

Pulse-Shaping-Based Nonlinear Microscopy: Development and Applications

NASA Astrophysics Data System (ADS)

Flynn, Daniel Christopher

The combination of optical microscopy and ultrafast spectroscopy make the spatial characterization of chemical kinetics on the femtosecond time scale possible. Commercially available octave-spanning Ti:Sapphire oscillators with sub-8 fs pulse durations can drive a multitude of nonlinear transitions across a significant portion of the visible spectrum with minimal average power. Unfortunately, dispersion from microscope objectives broadens pulse durations, decreases temporal resolution and lowers the peak intensities required for driving nonlinear transitions. In this dissertation, pulse shaping is used to compress laser pulses after the microscope objective. By using a binary genetic algorithm, pulse-shapes are designed to enable selective two-photon excitation. The pulse-shapes are demonstrated in two-photon fluorescence of live COS-7 cells expressing GFP-variants mAmetrine and tdTomato. The pulse-shaping approach is applied to a new multiphoton fluorescence resonance energy transfer (FRET) stoichiometry method that quantifies donor and acceptor molecules in complex, as well as the ratio of total donor to acceptor molecules. Compared to conventional multi-photon imaging techniques that require laser tuning or multiple laser systems to selectively excite individual fluorophores, the pulse-shaping approach offers rapid selective multifluorphore imaging at biologically relevant time scales. By splitting the laser beam into two beams and building a second pulse shaper, a pulse-shaping-based pump-probe microscope is developed. The technique offers multiple imaging modalities, such as excited state absorption (ESA), ground state bleach (GSB), and stimulated emission (SE), enhancing contrast of structures via their unique quantum pathways without the addition of contrast agents. Pulse-shaping based pump-probe microscopy is demonstrated for endogenous chemical-contrast imaging of red blood cells. In the second section of this dissertation, ultrafast spectroscopic techniques are used to characterize structure-function relationships of two-photon absorbing GFP-type probes and optical limiting materials. Fluorescence lifetimes of GFP-type probes are shown to depend on functional group substitution position, therefore, enabling the synthesis of designer probes for the possible study of conformation changes and aggregation in biological systems. Similarly, it is determined that small differences in the structure and dimensionality of organometallic macrocycles result in a diverse set of optical properties, which serves as a basis for the molecular level design of nonlinear optical materials.

Depth-resolved registration of transesophageal echo to x-ray fluoroscopy using an inverse geometry fluoroscopy system

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

Hatt, Charles R.; Tomkowiak, Michael T.; Dunkerley, David A. P.

2015-12-15

Purpose: Image registration between standard x-ray fluoroscopy and transesophageal echocardiography (TEE) has recently been proposed. Scanning-beam digital x-ray (SBDX) is an inverse geometry fluoroscopy system designed for cardiac procedures. This study presents a method for 3D registration of SBDX and TEE images based on the tomosynthesis and 3D tracking capabilities of SBDX. Methods: The registration algorithm utilizes the stack of tomosynthetic planes produced by the SBDX system to estimate the physical 3D coordinates of salient key-points on the TEE probe. The key-points are used to arrive at an initial estimate of the probe pose, which is then refined using amore » 2D/3D registration method adapted for inverse geometry fluoroscopy. A phantom study was conducted to evaluate probe pose estimation accuracy relative to the ground truth, as defined by a set of coregistered fiducial markers. This experiment was conducted with varying probe poses and levels of signal difference-to-noise ratio (SDNR). Additional phantom and in vivo studies were performed to evaluate the correspondence of catheter tip positions in TEE and x-ray images following registration of the two modalities. Results: Target registration error (TRE) was used to characterize both pose estimation and registration accuracy. In the study of pose estimation accuracy, successful pose estimates (3D TRE < 5.0 mm) were obtained in 97% of cases when the SDNR was 5.9 or higher in seven out of eight poses. Under these conditions, 3D TRE was 2.32 ± 1.88 mm, and 2D (projection) TRE was 1.61 ± 1.36 mm. Probe localization error along the source-detector axis was 0.87 ± 1.31 mm. For the in vivo experiments, mean 3D TRE ranged from 2.6 to 4.6 mm and mean 2D TRE ranged from 1.1 to 1.6 mm. Anatomy extracted from the echo images appeared well aligned when projected onto the SBDX images. Conclusions: Full 6 DOF image registration between SBDX and TEE is feasible and accurate to within 5 mm. Future studies will focus on real-time implementation and application-specific analysis.« less

Spectral Kinetic Simulation of the Ideal Multipole Resonance Probe

NASA Astrophysics Data System (ADS)

Gong, Junbo; Wilczek, Sebastian; Szeremley, Daniel; Oberrath, Jens; Eremin, Denis; Dobrygin, Wladislaw; Schilling, Christian; Friedrichs, Michael; Brinkmann, Ralf Peter

2015-09-01

The term Active Plasma Resonance Spectroscopy (APRS) denotes a class of diagnostic techniques which utilize the natural ability of plasmas to resonate on or near the electron plasma frequency ωpe: An RF signal in the GHz range is coupled into the plasma via an electric probe; the spectral response of the plasma is recorded, and a mathematical model is used to determine plasma parameters such as the electron density ne or the electron temperature Te. One particular realization of the method is the Multipole Resonance Probe (MRP). The ideal MRP is a geometrically simplified version of that probe; it consists of two dielectrically shielded, hemispherical electrodes to which the RF signal is applied. A particle-based numerical algorithm is described which enables a kinetic simulation of the interaction of the probe with the plasma. Similar to the well-known particle-in-cell (PIC), it contains of two modules, a particle pusher and a field solver. The Poisson solver determines, with the help of a truncated expansion into spherical harmonics, the new electric field at each particle position directly without invoking a numerical grid. The effort of the scheme scales linearly with the ensemble size N.

A broad range assay for rapid detection and etiologic characterization of bacterial meningitis: performance testing in samples from sub-Sahara.

PubMed

Won, Helen; Yang, Samuel; Gaydos, Charlotte; Hardick, Justin; Ramachandran, Padmini; Hsieh, Yu-Hsiang; Kecojevic, Alexander; Njanpop-Lafourcade, Berthe-Marie; Mueller, Judith E; Tameklo, Tsidi Agbeko; Badziklou, Kossi; Gessner, Bradford D; Rothman, Richard E

2012-09-01

This study aimed to conduct a pilot evaluation of broad-based multiprobe polymerase chain reaction (PCR) in clinical cerebrospinal fluid (CSF) samples compared to local conventional PCR/culture methods used for bacterial meningitis surveillance. A previously described PCR consisting of initial broad-based detection of Eubacteriales by a universal probe, followed by Gram typing, and pathogen-specific probes was designed targeting variable regions of the 16S rRNA gene. The diagnostic performance of the 16S rRNA assay in "127 CSF samples was evaluated in samples from patients from Togo, Africa, by comparison to conventional PCR/culture methods. Our probes detected Neisseria meningitidis, Streptococcus pneumoniae, and Haemophilus influenzae. Uniprobe sensitivity and specificity versus conventional PCR were 100% and 54.6%, respectively. Sensitivity and specificity of uniprobe versus culture methods were 96.5% and 52.5%, respectively. Gram-typing probes correctly typed 98.8% (82/83) and pathogen-specific probes identified 96.4% (80/83) of the positives. This broad-based PCR algorithm successfully detected and provided species level information for multiple bacterial meningitis agents in clinical samples. Copyright © 2012 Elsevier Inc. All rights reserved.

A broad range assay for rapid detection and etiologic characterization of bacterial meningitis: performance testing in samples from sub-Sahara☆, ☆☆,★

PubMed Central

Won, Helen; Yang, Samuel; Gaydos, Charlotte; Hardick, Justin; Ramachandran, Padmini; Hsieh, Yu-Hsiang; Kecojevic, Alexander; Njanpop-Lafourcade, Berthe-Marie; Mueller, Judith E.; Tameklo, Tsidi Agbeko; Badziklou, Kossi; Gessner, Bradford D.; Rothman, Richard E.

2012-01-01

This study aimed to conduct a pilot evaluation of broad-based multiprobe polymerase chain reaction (PCR) in clinical cerebrospinal fluid (CSF) samples compared to local conventional PCR/culture methods used for bacterial meningitis surveillance. A previously described PCR consisting of initial broad-based detection of Eubacteriales by a universal probe, followed by Gram typing, and pathogen-specific probes was designed targeting variable regions of the 16S rRNA gene. The diagnostic performance of the 16S rRNA assay in “”127 CSF samples was evaluated in samples from patients from Togo, Africa, by comparison to conventional PCR/culture methods. Our probes detected Neisseria meningitidis, Streptococcus pneumoniae, and Haemophilus influenzae. Uniprobe sensitivity and specificity versus conventional PCR were 100% and 54.6%, respectively. Sensitivity and specificity of uniprobe versus culture methods were 96.5% and 52.5%, respectively. Gram-typing probes correctly typed 98.8% (82/83) and pathogen-specific probes identified 96.4% (80/83) of the positives. This broad-based PCR algorithm successfully detected and provided species level information for multiple bacterial meningitis agents in clinical samples. PMID:22809694

The genomic response of skeletal muscle to methylprednisolone using microarrays: tailoring data mining to the structure of the pharmacogenomic time series

PubMed Central

DuBois, Debra C; Piel, William H; Jusko, William J

2008-01-01

High-throughput data collection using gene microarrays has great potential as a method for addressing the pharmacogenomics of complex biological systems. Similarly, mechanism-based pharmacokinetic/pharmacodynamic modeling provides a tool for formulating quantitative testable hypotheses concerning the responses of complex biological systems. As the response of such systems to drugs generally entails cascades of molecular events in time, a time series design provides the best approach to capturing the full scope of drug effects. A major problem in using microarrays for high-throughput data collection is sorting through the massive amount of data in order to identify probe sets and genes of interest. Due to its inherent redundancy, a rich time series containing many time points and multiple samples per time point allows for the use of less stringent criteria of expression, expression change and data quality for initial filtering of unwanted probe sets. The remaining probe sets can then become the focus of more intense scrutiny by other methods, including temporal clustering, functional clustering and pharmacokinetic/pharmacodynamic modeling, which provide additional ways of identifying the probes and genes of pharmacological interest. PMID:15212590

Improvements to direct quantitative analysis of multiple microRNAs facilitating faster analysis.

PubMed

Ghasemi, Farhad; Wegman, David W; Kanoatov, Mirzo; Yang, Burton B; Liu, Stanley K; Yousef, George M; Krylov, Sergey N

2013-11-05

Studies suggest that patterns of deregulation in sets of microRNA (miRNA) can be used as cancer diagnostic and prognostic biomarkers. Establishing a "miRNA fingerprint"-based diagnostic technique requires a suitable miRNA quantitation method. The appropriate method must be direct, sensitive, capable of simultaneous analysis of multiple miRNAs, rapid, and robust. Direct quantitative analysis of multiple microRNAs (DQAMmiR) is a recently introduced capillary electrophoresis-based hybridization assay that satisfies most of these criteria. Previous implementations of the method suffered, however, from slow analysis time and required lengthy and stringent purification of hybridization probes. Here, we introduce a set of critical improvements to DQAMmiR that address these technical limitations. First, we have devised an efficient purification procedure that achieves the required purity of the hybridization probe in a fast and simple fashion. Second, we have optimized the concentrations of the DNA probe to decrease the hybridization time to 10 min. Lastly, we have demonstrated that the increased probe concentrations and decreased incubation time removed the need for masking DNA, further simplifying the method and increasing its robustness. The presented improvements bring DQAMmiR closer to use in a clinical setting.

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.

PubMed

Ehteshami Bejnordi, Babak; Veta, Mitko; Johannes van Diest, Paul; van Ginneken, Bram; Karssemeijer, Nico; Litjens, Geert; van der Laak, Jeroen A W M; Hermsen, Meyke; Manson, Quirine F; Balkenhol, Maschenka; Geessink, Oscar; Stathonikos, Nikolaos; van Dijk, Marcory Crf; Bult, Peter; Beca, Francisco; Beck, Andrew H; Wang, Dayong; Khosla, Aditya; Gargeya, Rishab; Irshad, Humayun; Zhong, Aoxiao; Dou, Qi; Li, Quanzheng; Chen, Hao; Lin, Huang-Jing; Heng, Pheng-Ann; Haß, Christian; Bruni, Elia; Wong, Quincy; Halici, Ugur; Öner, Mustafa Ümit; Cetin-Atalay, Rengul; Berseth, Matt; Khvatkov, Vitali; Vylegzhanin, Alexei; Kraus, Oren; Shaban, Muhammad; Rajpoot, Nasir; Awan, Ruqayya; Sirinukunwattana, Korsuk; Qaiser, Talha; Tsang, Yee-Wah; Tellez, David; Annuscheit, Jonas; Hufnagl, Peter; Valkonen, Mira; Kartasalo, Kimmo; Latonen, Leena; Ruusuvuori, Pekka; Liimatainen, Kaisa; Albarqouni, Shadi; Mungal, Bharti; George, Ami; Demirci, Stefanie; Navab, Nassir; Watanabe, Seiryo; Seno, Shigeto; Takenaka, Yoichi; Matsuda, Hideo; Ahmady Phoulady, Hady; Kovalev, Vassili; Kalinovsky, Alexander; Liauchuk, Vitali; Bueno, Gloria; Fernandez-Carrobles, M Milagro; Serrano, Ismael; Deniz, Oscar; Racoceanu, Daniel; Venâncio, Rui

2017-12-12

Application of deep learning algorithms to whole-slide pathology images can potentially improve diagnostic accuracy and efficiency. Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin-stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists' diagnoses in a diagnostic setting. Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC). Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation. The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor. The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4% [95% CI, 64.3%-80.4%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P < .001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95% CI, 0.927-0.998] for the pathologist WOTC). In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting.

Investigation into the efficiency of different bionic algorithm combinations for a COBRA meta-heuristic

NASA Astrophysics Data System (ADS)

Akhmedova, Sh; Semenkin, E.

2017-02-01

Previously, a meta-heuristic approach, called Co-Operation of Biology-Related Algorithms or COBRA, for solving real-parameter optimization problems was introduced and described. COBRA’s basic idea consists of a cooperative work of five well-known bionic algorithms such as Particle Swarm Optimization, the Wolf Pack Search, the Firefly Algorithm, the Cuckoo Search Algorithm and the Bat Algorithm, which were chosen due to the similarity of their schemes. The performance of this meta-heuristic was evaluated on a set of test functions and its workability was demonstrated. Thus it was established that the idea of the algorithms’ cooperative work is useful. However, it is unclear which bionic algorithms should be included in this cooperation and how many of them. Therefore, the five above-listed algorithms and additionally the Fish School Search algorithm were used for the development of five different modifications of COBRA by varying the number of component-algorithms. These modifications were tested on the same set of functions and the best of them was found. Ways of further improving the COBRA algorithm are then discussed.

Solving LP Relaxations of Large-Scale Precedence Constrained Problems

NASA Astrophysics Data System (ADS)

Bienstock, Daniel; Zuckerberg, Mark

We describe new algorithms for solving linear programming relaxations of very large precedence constrained production scheduling problems. We present theory that motivates a new set of algorithmic ideas that can be employed on a wide range of problems; on data sets arising in the mining industry our algorithms prove effective on problems with many millions of variables and constraints, obtaining provably optimal solutions in a few minutes of computation.

LiveWire interactive boundary extraction algorithm based on Haar wavelet transform and control point set direction search

NASA Astrophysics Data System (ADS)

Cheng, Jun; Zhang, Jun; Tian, Jinwen

2015-12-01

Based on deep analysis of the LiveWire interactive boundary extraction algorithm, a new algorithm focusing on improving the speed of LiveWire algorithm is proposed in this paper. Firstly, the Haar wavelet transform is carried on the input image, and the boundary is extracted on the low resolution image obtained by the wavelet transform of the input image. Secondly, calculating LiveWire shortest path is based on the control point set direction search by utilizing the spatial relationship between the two control points users provide in real time. Thirdly, the search order of the adjacent points of the starting node is set in advance. An ordinary queue instead of a priority queue is taken as the storage pool of the points when optimizing their shortest path value, thus reducing the complexity of the algorithm from O[n2] to O[n]. Finally, A region iterative backward projection method based on neighborhood pixel polling has been used to convert dual-pixel boundary of the reconstructed image to single-pixel boundary after Haar wavelet inverse transform. The algorithm proposed in this paper combines the advantage of the Haar wavelet transform and the advantage of the optimal path searching method based on control point set direction search. The former has fast speed of image decomposition and reconstruction and is more consistent with the texture features of the image and the latter can reduce the time complexity of the original algorithm. So that the algorithm can improve the speed in interactive boundary extraction as well as reflect the boundary information of the image more comprehensively. All methods mentioned above have a big role in improving the execution efficiency and the robustness of the algorithm.

Identification of random nucleic acid sequence aberrations using dual capture probes which hybridize to different chromosome regions

DOEpatents

Lucas, J.N.; Straume, T.; Bogen, K.T.

1998-03-24

A method is provided for detecting nucleic acid sequence aberrations using two immobilization steps. According to the method, a nucleic acid sequence aberration is detected by detecting nucleic acid sequences having both a first nucleic acid sequence type (e.g., from a first chromosome) and a second nucleic acid sequence type (e.g., from a second chromosome), the presence of the first and the second nucleic acid sequence type on the same nucleic acid sequence indicating the presence of a nucleic acid sequence aberration. In the method, immobilization of a first hybridization probe is used to isolate a first set of nucleic acids in the sample which contain the first nucleic acid sequence type. Immobilization of a second hybridization probe is then used to isolate a second set of nucleic acids from within the first set of nucleic acids which contain the second nucleic acid sequence type. The second set of nucleic acids are then detected, their presence indicating the presence of a nucleic acid sequence aberration. 14 figs.

Identification of random nucleic acid sequence aberrations using dual capture probes which hybridize to different chromosome regions

DOEpatents

Lucas, Joe N.; Straume, Tore; Bogen, Kenneth T.

1998-01-01

A method is provided for detecting nucleic acid sequence aberrations using two immobilization steps. According to the method, a nucleic acid sequence aberration is detected by detecting nucleic acid sequences having both a first nucleic acid sequence type (e.g., from a first chromosome) and a second nucleic acid sequence type (e.g., from a second chromosome), the presence of the first and the second nucleic acid sequence type on the same nucleic acid sequence indicating the presence of a nucleic acid sequence aberration. In the method, immobilization of a first hybridization probe is used to isolate a first set of nucleic acids in the sample which contain the first nucleic acid sequence type. Immobilization of a second hybridization probe is then used to isolate a second set of nucleic acids from within the first set of nucleic acids which contain the second nucleic acid sequence type. The second set of nucleic acids are then detected, their presence indicating the presence of a nucleic acid sequence aberration.

Double-labeled donor probe can enhance the signal of fluorescence resonance energy transfer (FRET) in detection of nucleic acid hybridization

PubMed Central

Okamura, Yukio; Kondo, Satoshi; Sase, Ichiro; Suga, Takayuki; Mise, Kazuyuki; Furusawa, Iwao; Kawakami, Shigeki; Watanabe, Yuichiro

2000-01-01

A set of fluorescently-labeled DNA probes that hybridize with the target RNA and produce fluorescence resonance energy transfer (FRET) signals can be utilized for the detection of specific RNA. We have developed probe sets to detect and discriminate single-strand RNA molecules of plant viral genome, and sought a method to improve the FRET signals to handle in vivo applications. Consequently, we found that a double-labeled donor probe labeled with Bodipy dye yielded a remarkable increase in fluorescence intensity compared to a single-labeled donor probe used in an ordinary FRET. This double-labeled donor system can be easily applied to improve various FRET probes since the dependence upon sequence and label position in enhancement is not as strict. Furthermore this method could be applied to other nucleic acid substances, such as oligo RNA and phosphorothioate oligonucleotides (S-oligos) to enhance FRET signal. Although the double-labeled donor probes labeled with a variety of fluorophores had unexpected properties (strange UV-visible absorption spectra, decrease of intensity and decay of donor fluorescence) compared with single-labeled ones, they had no relation to FRET enhancement. This signal amplification mechanism cannot be explained simply based on our current results and knowledge of FRET. Yet it is possible to utilize this double-labeled donor system in various applications of FRET as a simple signal-enhancement method. PMID:11121494

Screening for specific chromosome involvement in hematological malignancies using a set of seven chromosome painting probes. An alternative approach for chromosome analysis using standard FISH instrumentation.

PubMed

Nacheva, E P; Gribble, S; Andrews, K; Wienberg, J; Grace, C D

2000-10-15

We report the application of multi-color fluorescence in situ hydribidization (FISH) for bone marrow metaphase cell analysis of hematological malignancies using a sub-set of the human karyotype for chromosome painting. A combination of chromosome probes labeled with three haptens enabled the construction of a "painting probe" which detects seven different chromosomes. The probe was used to screen three chronic myeloid leukemia (CML) derived cell lines and ten CML patient bone marrow samples for aberrations, additional to the Ph rearrangement, that are associated with the onset of blast crisis of CML. This approach was shown to identify karyotype changes commonly seen by conventional karyotyping, and in addition revealed chromosome changes unresolved or undetected by conventional cytogenetic analysis. The seven-color painting probe provides a useful, fast, and reliable complementary tool for chromosome analysis, especially in cases with poor chromosome morphology. This is a simple approach, since the probes can be displayed in a standard red/green/blue format accessible to standard fluorescence microscopes and image-processing software. The proposed approach using panels of locus-specific probes as well as chromosome paints will be useful in all diagnostic routine environments where analysis is directed towards screening for genetic rearrangements and/or specific patterns of chromosome involvement with diagnostic/prognostic value.

Robust algorithm for aligning two-dimensional chromatograms.

PubMed

Gros, Jonas; Nabi, Deedar; Dimitriou-Christidis, Petros; Rutler, Rebecca; Arey, J Samuel

2012-11-06

Comprehensive two-dimensional gas chromatography (GC × GC) chromatograms typically exhibit run-to-run retention time variability. Chromatogram alignment is often a desirable step prior to further analysis of the data, for example, in studies of environmental forensics or weathering of complex mixtures. We present a new algorithm for aligning whole GC × GC chromatograms. This technique is based on alignment points that have locations indicated by the user both in a target chromatogram and in a reference chromatogram. We applied the algorithm to two sets of samples. First, we aligned the chromatograms of twelve compositionally distinct oil spill samples, all analyzed using the same instrument parameters. Second, we applied the algorithm to two compositionally distinct wastewater extracts analyzed using two different instrument temperature programs, thus involving larger retention time shifts than the first sample set. For both sample sets, the new algorithm performed favorably compared to two other available alignment algorithms: that of Pierce, K. M.; Wood, Lianna F.; Wright, B. W.; Synovec, R. E. Anal. Chem.2005, 77, 7735-7743 and 2-D COW from Zhang, D.; Huang, X.; Regnier, F. E.; Zhang, M. Anal. Chem.2008, 80, 2664-2671. The new algorithm achieves the best matches of retention times for test analytes, avoids some artifacts which result from the other alignment algorithms, and incurs the least modification of quantitative signal information.

Data depth based clustering analysis

DOE PAGES

Jeong, Myeong -Hun; Cai, Yaping; Sullivan, Clair J.; ...

2016-01-01

Here, this paper proposes a new algorithm for identifying patterns within data, based on data depth. Such a clustering analysis has an enormous potential to discover previously unknown insights from existing data sets. Many clustering algorithms already exist for this purpose. However, most algorithms are not affine invariant. Therefore, they must operate with different parameters after the data sets are rotated, scaled, or translated. Further, most clustering algorithms, based on Euclidean distance, can be sensitive to noises because they have no global perspective. Parameter selection also significantly affects the clustering results of each algorithm. Unlike many existing clustering algorithms, themore » proposed algorithm, called data depth based clustering analysis (DBCA), is able to detect coherent clusters after the data sets are affine transformed without changing a parameter. It is also robust to noises because using data depth can measure centrality and outlyingness of the underlying data. Further, it can generate relatively stable clusters by varying the parameter. The experimental comparison with the leading state-of-the-art alternatives demonstrates that the proposed algorithm outperforms DBSCAN and HDBSCAN in terms of affine invariance, and exceeds or matches the ro-bustness to noises of DBSCAN or HDBSCAN. The robust-ness to parameter selection is also demonstrated through the case study of clustering twitter data.« less

The Maximum Likelihood Estimation of Signature Transformation /MLEST/ algorithm. [for affine transformation of crop inventory data

NASA Technical Reports Server (NTRS)

Thadani, S. G.

1977-01-01

The Maximum Likelihood Estimation of Signature Transformation (MLEST) algorithm is used to obtain maximum likelihood estimates (MLE) of affine transformation. The algorithm has been evaluated for three sets of data: simulated (training and recognition segment pairs), consecutive-day (data gathered from Landsat images), and geographical-extension (large-area crop inventory experiment) data sets. For each set, MLEST signature extension runs were made to determine MLE values and the affine-transformed training segment signatures were used to classify the recognition segments. The classification results were used to estimate wheat proportions at 0 and 1% threshold values.

Directly Reconstructing Principal Components of Heterogeneous Particles from Cryo-EM Images

PubMed Central

Tagare, Hemant D.; Kucukelbir, Alp; Sigworth, Fred J.; Wang, Hongwei; Rao, Murali

2015-01-01

Structural heterogeneity of particles can be investigated by their three-dimensional principal components. This paper addresses the question of whether, and with what algorithm, the three-dimensional principal components can be directly recovered from cryo-EM images. The first part of the paper extends the Fourier slice theorem to covariance functions showing that the three-dimensional covariance, and hence the principal components, of a heterogeneous particle can indeed be recovered from two-dimensional cryo-EM images. The second part of the paper proposes a practical algorithm for reconstructing the principal components directly from cryo-EM images without the intermediate step of calculating covariances. This algorithm is based on maximizing the (posterior) likelihood using the Expectation-Maximization algorithm. The last part of the paper applies this algorithm to simulated data and to two real cryo-EM data sets: a data set of the 70S ribosome with and without Elongation Factor-G (EF-G), and a data set of the inluenza virus RNA dependent RNA Polymerase (RdRP). The first principal component of the 70S ribosome data set reveals the expected conformational changes of the ribosome as the EF-G binds and unbinds. The first principal component of the RdRP data set reveals a conformational change in the two dimers of the RdRP. PMID:26049077

Genetic algorithm applied to the selection of factors in principal component-artificial neural networks: application to QSAR study of calcium channel antagonist activity of 1,4-dihydropyridines (nifedipine analogous).

PubMed

Hemmateenejad, Bahram; Akhond, Morteza; Miri, Ramin; Shamsipur, Mojtaba

2003-01-01

A QSAR algorithm, principal component-genetic algorithm-artificial neural network (PC-GA-ANN), has been applied to a set of newly synthesized calcium channel blockers, which are of special interest because of their role in cardiac diseases. A data set of 124 1,4-dihydropyridines bearing different ester substituents at the C-3 and C-5 positions of the dihydropyridine ring and nitroimidazolyl, phenylimidazolyl, and methylsulfonylimidazolyl groups at the C-4 position with known Ca(2+) channel binding affinities was employed in this study. Ten different sets of descriptors (837 descriptors) were calculated for each molecule. The principal component analysis was used to compress the descriptor groups into principal components. The most significant descriptors of each set were selected and used as input for the ANN. The genetic algorithm (GA) was used for the selection of the best set of extracted principal components. A feed forward artificial neural network with a back-propagation of error algorithm was used to process the nonlinear relationship between the selected principal components and biological activity of the dihydropyridines. A comparison between PC-GA-ANN and routine PC-ANN shows that the first model yields better prediction ability.

High-NA metrology and sensing on Berkeley MET5

NASA Astrophysics Data System (ADS)

Miyakawa, Ryan; Anderson, Chris; Naulleau, Patrick

2017-03-01

In this paper we compare two non-interferometric wavefront sensors suitable for in-situ high-NA EUV optical testing. The first is the AIS sensor, which has been deployed in both inspection and exposure tools. AIS is a compact, optical test that directly measures a wavefront by probing various parts of the imaging optic pupil and measuring localized wavefront curvature. The second is an image-based technique that uses an iterative algorithm based on simulated annealing to reconstruct a wavefront based on matching aerial images through focus. In this technique, customized illumination is used to probe the pupil at specific points to optimize differences in aberration signatures.

An Advanced Approach to Simultaneous Monitoring of Multiple Bacteria in Space

NASA Technical Reports Server (NTRS)

Eggers, M.

1998-01-01

The utility of a novel microarray-based microbial analyzer was demonstrated by the rapid detection, imaging, and identification of a mixture of microorganisms found in a waste water sample from the Lunar-Mars Life Support Test Project through the synergistic combination of: (1) judicious RNA probe selection via algorithms developed by University of Houston scientists; (2) tuned surface chemistries developed by Baylor College of Medicine scientists to facilitate hybridization of rRNA targets to DNA probes under very low salt conditions, thereby minimizing secondary structure; and (3) integration of the microarray printing and detection/imaging instrumentation by Genometrix to complete the quantitative analysis of microorganism mixtures.

Use of the MATRIXx Integrated Toolkit on the Microwave Anisotropy Probe Attitude Control System

NASA Technical Reports Server (NTRS)

Ward, David K.; Andrews, Stephen F.; McComas, David C.; ODonnell, James R., Jr.

1999-01-01

Recent advances in analytical software tools allow the analysis, simulation, flight code, and documentation of an algorithm to be generated from a single source, all within one integrated analytical design package. NASA's Microwave Anisotropy Probe project has used one such package, Integrated Systems' MATRIXx suite, in the design of the spacecraft's Attitude Control System. The project's experience with the linear analysis, simulation, code generation, and documentation tools will be presented and compared with more traditional development tools. In particular, the quality of the flight software generated will be examined in detail. Finally, lessons learned on each of the tools will be shared.

Screening prostate cancer using a portable near infrared scanning imaging unit with an optical fiber-based rectal probe

NASA Astrophysics Data System (ADS)

Pu, Yang; Wang, Wubao; Tang, Guichen; Budansky, Yury; Sharonov, Mikhail; Xu, Min; Achilefu, Samuel; Eastham, James A.; Alfano, Robert R.

2012-01-01

A portable near infrared scanning polarization imaging unit with an optical fiber-based rectal probe, namely Photonic Finger, was designed and developed o locate the 3D position of abnormal prostate site inside normal prostate tissue. An inverse algorithm, Optical Tomography using Independent Component Analysis (OPTICA) was improved particularly to unmix the signal from targets (cancerous tissue) embedded in a turbid medium (normal tissue) in the backscattering imaging geometry. Photonic Finger combined with OPTICA was tested to characterize different target(s) inside different tissue medium, including cancerous prostate tissue embedded by large piece of normal tissue.

Face recognition from unconstrained three-dimensional face images using multitask sparse representation

NASA Astrophysics Data System (ADS)

Bentaieb, Samia; Ouamri, Abdelaziz; Nait-Ali, Amine; Keche, Mokhtar

2018-01-01

We propose and evaluate a three-dimensional (3D) face recognition approach that applies the speeded up robust feature (SURF) algorithm to the depth representation of shape index map, under real-world conditions, using only a single gallery sample for each subject. First, the 3D scans are preprocessed, then SURF is applied on the shape index map to find interest points and their descriptors. Each 3D face scan is represented by keypoints descriptors, and a large dictionary is built from all the gallery descriptors. At the recognition step, descriptors of a probe face scan are sparsely represented by the dictionary. A multitask sparse representation classification is used to determine the identity of each probe face. The feasibility of the approach that uses the SURF algorithm on the shape index map for face identification/authentication is checked through an experimental investigation conducted on Bosphorus, University of Milano Bicocca, and CASIA 3D datasets. It achieves an overall rank one recognition rate of 97.75%, 80.85%, and 95.12%, respectively, on these datasets.

Revisiting Mitochondrial pH with an Improved Algorithm for Calibration of the Ratiometric 5(6)-carboxy-SNARF-1 Probe Reveals Anticooperative Reaction with H+ Ions and Warrants Further Studies of Organellar pH

PubMed Central

Żurawik, Tomasz Michał; Pomorski, Adam; Belczyk-Ciesielska, Agnieszka; Goch, Grażyna; Niedźwiedzka, Katarzyna; Kucharczyk, Róża; Krężel, Artur; Bal, Wojciech

2016-01-01

Fluorescence measurements of pH and other analytes in the cell rely on accurate calibrations, but these have routinely used algorithms that inadequately describe the properties of indicators. Here, we have established a more accurate method for calibrating and analyzing data obtained using the ratiometric probe 5(6)-carboxy-SNARF-1. We tested the implications of novel approach to measurements of pH in yeast mitochondria, a compartment containing a small number of free H+ ions. Our findings demonstrate that 5(6)-carboxy-SNARF-1 interacts with H+ ions inside the mitochondria in an anticooperative manner (Hill coefficient n of 0.5) and the apparent pH inside the mitochondria is ~0.5 unit lower than had been generally assumed. This result, at odds with the current consensus on the mechanism of energy generation in the mitochondria, is in better agreement with theoretical considerations and warrants further studies of organellar pH. PMID:27557123

Drogue pose estimation for unmanned aerial vehicle autonomous aerial refueling system based on infrared vision sensor

NASA Astrophysics Data System (ADS)

Chen, Shanjun; Duan, Haibin; Deng, Yimin; Li, Cong; Zhao, Guozhi; Xu, Yan

2017-12-01

Autonomous aerial refueling is a significant technology that can significantly extend the endurance of unmanned aerial vehicles. A reliable method that can accurately estimate the position and attitude of the probe relative to the drogue is the key to such a capability. A drogue pose estimation method based on infrared vision sensor is introduced with the general goal of yielding an accurate and reliable drogue state estimate. First, by employing direct least squares ellipse fitting and convex hull in OpenCV, a feature point matching and interference point elimination method is proposed. In addition, considering the conditions that some infrared LEDs are damaged or occluded, a missing point estimation method based on perspective transformation and affine transformation is designed. Finally, an accurate and robust pose estimation algorithm improved by the runner-root algorithm is proposed. The feasibility of the designed visual measurement system is demonstrated by flight test, and the results indicate that our proposed method enables precise and reliable pose estimation of the probe relative to the drogue, even in some poor conditions.

Precise algorithm to generate random sequential adsorption of hard polygons at saturation

NASA Astrophysics Data System (ADS)

Zhang, G.

2018-04-01

Random sequential adsorption (RSA) is a time-dependent packing process, in which particles of certain shapes are randomly and sequentially placed into an empty space without overlap. In the infinite-time limit, the density approaches a "saturation" limit. Although this limit has attracted particular research interest, the majority of past studies could only probe this limit by extrapolation. We have previously found an algorithm to reach this limit using finite computational time for spherical particles and could thus determine the saturation density of spheres with high accuracy. In this paper, we generalize this algorithm to generate saturated RSA packings of two-dimensional polygons. We also calculate the saturation density for regular polygons of three to ten sides and obtain results that are consistent with previous, extrapolation-based studies.

Precise algorithm to generate random sequential adsorption of hard polygons at saturation.

PubMed

Zhang, G

2018-04-01

Random sequential adsorption (RSA) is a time-dependent packing process, in which particles of certain shapes are randomly and sequentially placed into an empty space without overlap. In the infinite-time limit, the density approaches a "saturation" limit. Although this limit has attracted particular research interest, the majority of past studies could only probe this limit by extrapolation. We have previously found an algorithm to reach this limit using finite computational time for spherical particles and could thus determine the saturation density of spheres with high accuracy. In this paper, we generalize this algorithm to generate saturated RSA packings of two-dimensional polygons. We also calculate the saturation density for regular polygons of three to ten sides and obtain results that are consistent with previous, extrapolation-based studies.

Parallel fuzzy connected image segmentation on GPU

PubMed Central

Zhuge, Ying; Cao, Yong; Udupa, Jayaram K.; Miller, Robert W.

2011-01-01

Purpose: Image segmentation techniques using fuzzy connectedness (FC) principles have shown their effectiveness in segmenting a variety of objects in several large applications. However, one challenge in these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays, commodity graphics hardware provides a highly parallel computing environment. In this paper, the authors present a parallel fuzzy connected image segmentation algorithm implementation on NVIDIA’s compute unified device Architecture (cuda) platform for segmenting medical image data sets. Methods: In the FC algorithm, there are two major computational tasks: (i) computing the fuzzy affinity relations and (ii) computing the fuzzy connectedness relations. These two tasks are implemented as cuda kernels and executed on GPU. A dramatic improvement in speed for both tasks is achieved as a result. Results: Our experiments based on three data sets of small, medium, and large data size demonstrate the efficiency of the parallel algorithm, which achieves a speed-up factor of 24.4x, 18.1x, and 10.3x, correspondingly, for the three data sets on the NVIDIA Tesla C1060 over the implementation of the algorithm on CPU, and takes 0.25, 0.72, and 15.04 s, correspondingly, for the three data sets. Conclusions: The authors developed a parallel algorithm of the widely used fuzzy connected image segmentation method on the NVIDIA GPUs, which are far more cost- and speed-effective than both cluster of workstations and multiprocessing systems. A near-interactive speed of segmentation has been achieved, even for the large data set. PMID:21859037

Parallel fuzzy connected image segmentation on GPU.

PubMed

Zhuge, Ying; Cao, Yong; Udupa, Jayaram K; Miller, Robert W

2011-07-01

Image segmentation techniques using fuzzy connectedness (FC) principles have shown their effectiveness in segmenting a variety of objects in several large applications. However, one challenge in these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays, commodity graphics hardware provides a highly parallel computing environment. In this paper, the authors present a parallel fuzzy connected image segmentation algorithm implementation on NVIDIA's compute unified device Architecture (CUDA) platform for segmenting medical image data sets. In the FC algorithm, there are two major computational tasks: (i) computing the fuzzy affinity relations and (ii) computing the fuzzy connectedness relations. These two tasks are implemented as CUDA kernels and executed on GPU. A dramatic improvement in speed for both tasks is achieved as a result. Our experiments based on three data sets of small, medium, and large data size demonstrate the efficiency of the parallel algorithm, which achieves a speed-up factor of 24.4x, 18.1x, and 10.3x, correspondingly, for the three data sets on the NVIDIA Tesla C1060 over the implementation of the algorithm on CPU, and takes 0.25, 0.72, and 15.04 s, correspondingly, for the three data sets. The authors developed a parallel algorithm of the widely used fuzzy connected image segmentation method on the NVIDIA GPUs, which are far more cost- and speed-effective than both cluster of workstations and multiprocessing systems. A near-interactive speed of segmentation has been achieved, even for the large data set.

Three-dimensional wide-field pump-probe structured illumination microscopy

PubMed Central

Kim, Yang-Hyo; So, Peter T.C.

2017-01-01

We propose a new structured illumination scheme for achieving depth resolved wide-field pump-probe microscopy with sub-diffraction limit resolution. By acquiring coherent pump-probe images using a set of 3D structured light illumination patterns, a 3D super-resolution pump-probe image can be reconstructed. We derive the theoretical framework to describe the coherent image formation and reconstruction scheme for this structured illumination pump-probe imaging system and carry out numerical simulations to investigate its imaging performance. The results demonstrate a lateral resolution improvement by a factor of three and providing 0.5 µm level axial optical sectioning. PMID:28380860

GPU accelerated fuzzy connected image segmentation by using CUDA.

PubMed

Zhuge, Ying; Cao, Yong; Miller, Robert W

2009-01-01

Image segmentation techniques using fuzzy connectedness principles have shown their effectiveness in segmenting a variety of objects in several large applications in recent years. However, one problem of these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays commodity graphics hardware provides high parallel computing power. In this paper, we present a parallel fuzzy connected image segmentation algorithm on Nvidia's Compute Unified Device Architecture (CUDA) platform for segmenting large medical image data sets. Our experiments based on three data sets with small, medium, and large data size demonstrate the efficiency of the parallel algorithm, which achieves a speed-up factor of 7.2x, 7.3x, and 14.4x, correspondingly, for the three data sets over the sequential implementation of fuzzy connected image segmentation algorithm on CPU.

A Review On Missing Value Estimation Using Imputation Algorithm

NASA Astrophysics Data System (ADS)

Armina, Roslan; Zain, Azlan Mohd; Azizah Ali, Nor; Sallehuddin, Roselina

2017-09-01

The presence of the missing value in the data set has always been a major problem for precise prediction. The method for imputing missing value needs to minimize the effect of incomplete data sets for the prediction model. Many algorithms have been proposed for countermeasure of missing value problem. In this review, we provide a comprehensive analysis of existing imputation algorithm, focusing on the technique used and the implementation of global or local information of data sets for missing value estimation. In addition validation method for imputation result and way to measure the performance of imputation algorithm also described. The objective of this review is to highlight possible improvement on existing method and it is hoped that this review gives reader better understanding of imputation method trend.

Transcriptomic Analysis of Grape (Vitis vinifera L.) Leaves after Exposure to Ultraviolet C Irradiation

PubMed Central

Xi, Huifen; Ma, Ling; Liu, Guotian; Wang, Nian; Wang, Junfang; Wang, Lina; Dai, Zhanwu; Li, Shaohua; Wang, Lijun

2014-01-01

Background Only a small amount of solar ultraviolet C (UV-C) radiation reaches the Earth's surface. This is because of the filtering effects of the stratospheric ozone layer. Artificial UV-C irradiation is used on leaves and fruits to stimulate different biological processes in plants. Grapes are a major fruit crop and are grown in many parts of the world. Research has shown that UV-C irradiation induces the biosynthesis of phenols in grape leaves. However, few studies have analyzed the overall changes in gene expression in grape leaves exposed to UV-C. Methodology/Principal Findings In the present study, transcriptional responses were investigated in grape (Vitis vinifera L.) leaves before and after exposure to UV-C irradiation (6 W·m−2 for 10 min) using an Affymetrix Vitis vinifera (Grape) Genome Array (15,700 transcripts). A total of 5274 differentially expressed probe sets were defined, including 3564 (67.58%) probe sets that appeared at both 6 and 12 h after exposure to UV-C irradiation but not before exposure. A total of 468 (8.87%) probe sets and 1242 (23.55%) probe sets were specifically expressed at these times. The probe sets were associated with a large number of important traits and biological pathways, including cell rescue (i.e., antioxidant enzymes), protein fate (i.e., HSPs), primary and secondary metabolism, and transcription factors. Interestingly, some of the genes involved in secondary metabolism, such as stilbene synthase, responded intensely to irradiation. Some of the MYB and WRKY family transcription factors, such as VvMYBPA1, VvMYB14, VvMYB4, WRKY57-like, and WRKY 65, were also strongly up-regulated (about 100 to 200 fold). Conclusions UV-C irridiation has an important role in some biology processes, especially cell rescue, protein fate, secondary metabolism, and regulation of transcription.These results opened up ways of exploring the molecular mechanisms underlying the effects of UV-C irradiation on grape leaves and have great implications for further studies. PMID:25464056

Transcriptomic analysis of grape (Vitis vinifera L.) leaves after exposure to ultraviolet C irradiation.

PubMed

Xi, Huifen; Ma, Ling; Liu, Guotian; Wang, Nian; Wang, Junfang; Wang, Lina; Dai, Zhanwu; Li, Shaohua; Wang, Lijun

2014-01-01

Only a small amount of solar ultraviolet C (UV-C) radiation reaches the Earth's surface. This is because of the filtering effects of the stratospheric ozone layer. Artificial UV-C irradiation is used on leaves and fruits to stimulate different biological processes in plants. Grapes are a major fruit crop and are grown in many parts of the world. Research has shown that UV-C irradiation induces the biosynthesis of phenols in grape leaves. However, few studies have analyzed the overall changes in gene expression in grape leaves exposed to UV-C. In the present study, transcriptional responses were investigated in grape (Vitis vinifera L.) leaves before and after exposure to UV-C irradiation (6 W·m-2 for 10 min) using an Affymetrix Vitis vinifera (Grape) Genome Array (15,700 transcripts). A total of 5274 differentially expressed probe sets were defined, including 3564 (67.58%) probe sets that appeared at both 6 and 12 h after exposure to UV-C irradiation but not before exposure. A total of 468 (8.87%) probe sets and 1242 (23.55%) probe sets were specifically expressed at these times. The probe sets were associated with a large number of important traits and biological pathways, including cell rescue (i.e., antioxidant enzymes), protein fate (i.e., HSPs), primary and secondary metabolism, and transcription factors. Interestingly, some of the genes involved in secondary metabolism, such as stilbene synthase, responded intensely to irradiation. Some of the MYB and WRKY family transcription factors, such as VvMYBPA1, VvMYB14, VvMYB4, WRKY57-like, and WRKY 65, were also strongly up-regulated (about 100 to 200 fold). UV-C irridiation has an important role in some biology processes, especially cell rescue, protein fate, secondary metabolism, and regulation of transcription.These results opened up ways of exploring the molecular mechanisms underlying the effects of UV-C irradiation on grape leaves and have great implications for further studies.

Reconstructing liver shape and position from MR image slices using an active shape model

NASA Astrophysics Data System (ADS)

Fenchel, Matthias; Thesen, Stefan; Schilling, Andreas

2008-03-01

We present an algorithm for fully automatic reconstruction of 3D position, orientation and shape of the human liver from a sparsely covering set of n 2D MR slice images. Reconstructing the shape of an organ from slice images can be used for scan planning, for surgical planning or other purposes where 3D anatomical knowledge has to be inferred from sparse slices. The algorithm is based on adapting an active shape model of the liver surface to a given set of slice images. The active shape model is created from a training set of liver segmentations from a group of volunteers. The training set is set up with semi-manual segmentations of T1-weighted volumetric MR images. Searching for the optimal shape model that best fits to the image data is done by maximizing a similarity measure based on local appearance at the surface. Two different algorithms for the active shape model search are proposed and compared: both algorithms seek to maximize the a-posteriori probability of the grey level appearance around the surface while constraining the surface to the space of valid shapes. The first algorithm works by using grey value profile statistics in normal direction. The second algorithm uses average and variance images to calculate the local surface appearance on the fly. Both algorithms are validated by fitting the active shape model to abdominal 2D slice images and comparing the shapes, which have been reconstructed, to the manual segmentations and to the results of active shape model searches from 3D image data. The results turn out to be promising and competitive to active shape model segmentations from 3D data.

Noise-enhanced convolutional neural networks.

PubMed

Audhkhasi, Kartik; Osoba, Osonde; Kosko, Bart

2016-06-01

Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generalized expectation-maximization (EM) algorithm and because such carefully chosen noise always speeds up the EM algorithm on average. The CNN framework gives a practical way to learn and recognize images because backpropagation scales with training data. It has only linear time complexity in the number of training samples. The Noisy CNN algorithm finds a special separating hyperplane in the network's noise space. The hyperplane arises from the likelihood-based positivity condition that noise-boosts the EM algorithm. The hyperplane cuts through a uniform-noise hypercube or Gaussian ball in the noise space depending on the type of noise used. Noise chosen from above the hyperplane speeds training on average. Noise chosen from below slows it on average. The algorithm can inject noise anywhere in the multilayered network. Adding noise to the output neurons reduced the average per-iteration training-set cross entropy by 39% on a standard MNIST image test set of handwritten digits. It also reduced the average per-iteration training-set classification error by 47%. Adding noise to the hidden layers can also reduce these performance measures. The noise benefit is most pronounced for smaller data sets because the largest EM hill-climbing gains tend to occur in the first few iterations. This noise effect can assist random sampling from large data sets because it allows a smaller random sample to give the same or better performance than a noiseless sample gives. Copyright © 2015 Elsevier Ltd. All rights reserved.

The centroidal algorithm in molecular similarity and diversity calculations on confidential datasets.

PubMed

Trepalin, Sergey; Osadchiy, Nikolay

2005-01-01

Chemical structure provides exhaustive description of a compound, but it is often proprietary and thus an impediment in the exchange of information. For example, structure disclosure is often needed for the selection of most similar or dissimilar compounds. Authors propose a centroidal algorithm based on structural fragments (screens) that can be efficiently used for the similarity and diversity selections without disclosing structures from the reference set. For an increased security purposes, authors recommend that such set contains at least some tens of structures. Analysis of reverse engineering feasibility showed that the problem difficulty grows with decrease of the screen's radius. The algorithm is illustrated with concrete calculations on known steroidal, quinoline, and quinazoline drugs. We also investigate a problem of scaffold identification in combinatorial library dataset. The results show that relatively small screens of radius equal to 2 bond lengths perform well in the similarity sorting, while radius 4 screens yield better results in diversity sorting. The software implementation of the algorithm taking SDF file with a reference set generates screens of various radii which are subsequently used for the similarity and diversity sorting of external SDFs. Since the reverse engineering of the reference set molecules from their screens has the same difficulty as the RSA asymmetric encryption algorithm, generated screens can be stored openly without further encryption. This approach ensures an end user transfers only a set of structural fragments and no other data. Like other algorithms of encryption, the centroid algorithm cannot give 100% guarantee of protecting a chemical structure from dataset, but probability of initial structure identification is very small-order of 10(-40) in typical cases.

The centroidal algorithm in molecular similarity and diversity calculations on confidential datasets

NASA Astrophysics Data System (ADS)

Trepalin, Sergey; Osadchiy, Nikolay

2005-09-01

Chemical structure provides exhaustive description of a compound, but it is often proprietary and thus an impediment in the exchange of information. For example, structure disclosure is often needed for the selection of most similar or dissimilar compounds. Authors propose a centroidal algorithm based on structural fragments (screens) that can be efficiently used for the similarity and diversity selections without disclosing structures from the reference set. For an increased security purposes, authors recommend that such set contains at least some tens of structures. Analysis of reverse engineering feasibility showed that the problem difficulty grows with decrease of the screen's radius. The algorithm is illustrated with concrete calculations on known steroidal, quinoline, and quinazoline drugs. We also investigate a problem of scaffold identification in combinatorial library dataset. The results show that relatively small screens of radius equal to 2 bond lengths perform well in the similarity sorting, while radius 4 screens yield better results in diversity sorting. The software implementation of the algorithm taking SDF file with a reference set generates screens of various radii which are subsequently used for the similarity and diversity sorting of external SDFs. Since the reverse engineering of the reference set molecules from their screens has the same difficulty as the RSA asymmetric encryption algorithm, generated screens can be stored openly without further encryption. This approach ensures an end user transfers only a set of structural fragments and no other data. Like other algorithms of encryption, the centroid algorithm cannot give 100% guarantee of protecting a chemical structure from dataset, but probability of initial structure identification is very small-order of 10-40 in typical cases.

Angle Statistics Reconstruction: a robust reconstruction algorithm for Muon Scattering Tomography

NASA Astrophysics Data System (ADS)

Stapleton, M.; Burns, J.; Quillin, S.; Steer, C.

2014-11-01

Muon Scattering Tomography (MST) is a technique for using the scattering of cosmic ray muons to probe the contents of enclosed volumes. As a muon passes through material it undergoes multiple Coulomb scattering, where the amount of scattering is dependent on the density and atomic number of the material as well as the path length. Hence, MST has been proposed as a means of imaging dense materials, for instance to detect special nuclear material in cargo containers. Algorithms are required to generate an accurate reconstruction of the material density inside the volume from the muon scattering information and some have already been proposed, most notably the Point of Closest Approach (PoCA) and Maximum Likelihood/Expectation Maximisation (MLEM) algorithms. However, whilst PoCA-based algorithms are easy to implement, they perform rather poorly in practice. Conversely, MLEM is a complicated algorithm to implement and computationally intensive and there is currently no published, fast and easily-implementable algorithm that performs well in practice. In this paper, we first provide a detailed analysis of the source of inaccuracy in PoCA-based algorithms. We then motivate an alternative method, based on ideas first laid out by Morris et al, presenting and fully specifying an algorithm that performs well against simulations of realistic scenarios. We argue this new algorithm should be adopted by developers of Muon Scattering Tomography as an alternative to PoCA.