Microarrays for Universal Detection and Identification of Phytoplasmas

DEFF Research Database (Denmark)

Nicolaisen, Mogens; Nyskjold, Henriette; Bertaccini, Assunta

2013-01-01

Detection and identification of phytoplasmas is a laborious process often involving nested PCR followed by restriction enzyme analysis and fine-resolution gel electrophoresis. To improve throughput, other methods are needed. Microarray technology offers a generic assay that can potentially detect...... and differentiate all types of phytoplasmas in one assay. The present protocol describes a microarray-based method for identification of phytoplasmas to 16Sr group level....

Improved method for rapid and accurate isolation and identification of Streptococcus mutans and Streptococcus sobrinus from human plaque samples.

Science.gov (United States)

Villhauer, Alissa L; Lynch, David J; Drake, David R

2017-08-01

Mutans streptococci (MS), specifically Streptococcus mutans (SM) and Streptococcus sobrinus (SS), are bacterial species frequently targeted for investigation due to their role in the etiology of dental caries. Differentiation of S. mutans and S. sobrinus is an essential part of exploring the role of these organisms in disease progression and the impact of the presence of either/both on a subject's caries experience. Of vital importance to the study of these organisms is an identification protocol that allows us to distinguish between the two species in an easy, accurate, and timely manner. While conducting a 5-year birth cohort study in a Northern Plains American Indian tribe, the need for a more rapid procedure for isolating and identifying high volumes of MS was recognized. We report here on the development of an accurate and rapid method for MS identification. Accuracy, ease of use, and material and time requirements for morphological differentiation on selective agar, biochemical tests, and various combinations of PCR primers were compared. The final protocol included preliminary identification based on colony morphology followed by PCR confirmation of species identification using primers targeting regions of the glucosyltransferase (gtf) genes of SM and SS. This method of isolation and identification was found to be highly accurate, more rapid than the previous methodology used, and easily learned. It resulted in more efficient use of both time and material resources. Copyright © 2017 Elsevier B.V. All rights reserved.

Camouflage, detection and identification of moving targets.

Science.gov (United States)

Hall, Joanna R; Cuthill, Innes C; Baddeley, Roland; Shohet, Adam J; Scott-Samuel, Nicholas E

2013-05-07

Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.

An Integrative Approach to Accurate Vehicle Logo Detection

Directory of Open Access Journals (Sweden)

Hao Pan

2013-01-01

required for many applications in intelligent transportation systems and automatic surveillance. The task is challenging considering the small target of logos and the wide range of variability in shape, color, and illumination. A fast and reliable vehicle logo detection approach is proposed following visual attention mechanism from the human vision. Two prelogo detection steps, that is, vehicle region detection and a small RoI segmentation, rapidly focalize a small logo target. An enhanced Adaboost algorithm, together with two types of features of Haar and HOG, is proposed to detect vehicles. An RoI that covers logos is segmented based on our prior knowledge about the logos’ position relative to license plates, which can be accurately localized from frontal vehicle images. A two-stage cascade classier proceeds with the segmented RoI, using a hybrid of Gentle Adaboost and Support Vector Machine (SVM, resulting in precise logo positioning. Extensive experiments were conducted to verify the efficiency of the proposed scheme.

Molecular identification of polydorid polychaetes (Annelida ...

African Journals Online (AJOL)

The early detection and correct identification of polydorid polychaete species is essential as they are often encountered as invasive alien pests in aquaculture facilities or the intertidal where they may modify the ecosystem. Accurate identification is, however, often hampered by high levels of morphological similarity among ...

The combined rapid detection and species-level identification of yeasts in simulated blood culture using a colorimetric sensor array.

Science.gov (United States)

Shrestha, Nabin K; Lim, Sung H; Wilson, Deborah A; SalasVargas, Ana Victoria; Churi, Yair S; Rhodes, Paul A; Mazzone, Peter J; Procop, Gary W

2017-01-01

A colorimetric sensor array (CSA) has been demonstrated to rapidly detect and identify bacteria growing in blood cultures by obtaining a species-specific "fingerprint" of the volatile organic compounds (VOCs) produced during growth. This capability has been demonstrated in prokaryotes, but has not been reported for eukaryotic cells growing in culture. The purpose of this study was to explore if a disposable CSA could differentially identify 7 species of pathogenic yeasts growing in blood culture. Culture trials of whole blood inoculated with a panel of clinically important pathogenic yeasts at four different microorganism loads were performed. Cultures were done in both standard BacT/Alert and CSA-embedded bottles, after adding 10 mL of spiked blood to each bottle. Color changes in the CSA were captured as images by an optical scanner at defined time intervals. The captured images were analyzed to identify the yeast species. Time to detection by the CSA was compared to that in the BacT/Alert system. One hundred sixty-two yeast culture trials were performed, including strains of several species of Candida (Ca. albicans, Ca. glabrata, Ca. parapsilosis, and Ca. tropicalis), Clavispora (synonym Candida) lusitaniae, Pichia kudriavzevii (synonym Candida krusei) and Cryptococcus neoformans, at loads of 8.2 × 105, 8.3 × 103, 8.5 × 101, and 1.7 CFU/mL. In addition, 8 negative trials (no yeast) were conducted. All negative trials were correctly identified as negative, and all positive trials were detected. Colorimetric responses were species-specific and did not vary by inoculum load over the 500000-fold range of loads tested, allowing for accurate species-level identification. The mean sensitivity for species-level identification by CSA was 74% at detection, and increased with time, reaching almost 95% at 4 hours after detection. At an inoculum load of 1.7 CFU/mL, mean time to detection with the CSA was 6.8 hours (17%) less than with the BacT/Alert platform. The CSA

Rapid identification of sequences for orphan enzymes to power accurate protein annotation.

Directory of Open Access Journals (Sweden)

Kevin R Ramkissoon

Full Text Available The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the "back catalog" of enzymology--"orphan enzymes," those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC database alone. In this study, we demonstrate how this orphan enzyme "back catalog" is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology's "back catalog" another powerful tool to drive accurate genome annotation.

Rapid Identification of Sequences for Orphan Enzymes to Power Accurate Protein Annotation

Science.gov (United States)

Ojha, Sunil; Watson, Douglas S.; Bomar, Martha G.; Galande, Amit K.; Shearer, Alexander G.

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the “back catalog” of enzymology – “orphan enzymes,” those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme “back catalog” is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology’s “back catalog” another powerful tool to drive accurate genome annotation. PMID:24386392

Detection and quantitation of trace phenolphthalein (in pharmaceutical preparations and in forensic exhibits) by liquid chromatography-tandem mass spectrometry, a sensitive and accurate method.

Science.gov (United States)

Sharma, Kakali; Sharma, Shiba P; Lahiri, Sujit C

2013-01-01

Phenolphthalein, an acid-base indicator and laxative, is important as a constituent of widely used weight-reducing multicomponent food formulations. Phenolphthalein is an useful reagent in forensic science for the identification of blood stains of suspected victims and for apprehending erring officials accepting bribes in graft or trap cases. The pink-colored alkaline hand washes originating from the phenolphthalein-smeared notes can easily be determined spectrophotometrically. But in many cases, colored solution turns colorless with time, which renders the genuineness of bribe cases doubtful to the judiciary. No method is known till now for the detection and identification of phenolphthalein in colorless forensic exhibits with positive proof. Liquid chromatography-tandem mass spectrometry had been found to be most sensitive, accurate method capable of detection and quantitation of trace phenolphthalein in commercial formulations and colorless forensic exhibits with positive proof. The detection limit of phenolphthalein was found to be 1.66 pg/L or ng/mL, and the calibration curve shows good linearity (r(2) = 0.9974). © 2012 American Academy of Forensic Sciences.

The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text

DEFF Research Database (Denmark)

Pafilis, Evangelos; Pletscher-Frankild, Sune; Fanini, Lucia

2013-01-01

The exponential growth of the biomedical literature is making the need for efficient, accurate text-mining tools increasingly clear. The identification of named biological entities in text is a central and difficult task. We have developed an efficient algorithm and implementation of a dictionary......-based approach to named entity recognition, which we here use to identify names of species and other taxa in text. The tool, SPECIES, is more than an order of magnitude faster and as accurate as existing tools. The precision and recall was assessed both on an existing gold-standard corpus and on a new corpus...

Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification

DEFF Research Database (Denmark)

Andreatta, Massimo; Karosiene, Edita; Rasmussen, Michael

2015-01-01

with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped...

Robust and accurate detection algorithm for multimode polymer optical FBG sensor system

DEFF Research Database (Denmark)

Ganziy, Denis; Jespersen, O.; Rose, B.

2015-01-01

We propose a novel dynamic gate algorithm (DGA) for robust and fast peak detection. The algorithm uses a threshold determined detection window and center of gravity algorithm with bias compensation. Our experiment demonstrates that the DGA method is fast and robust with better stability and accur...

Rapid and accurate identification by real-time PCR of biotoxin-producing dinoflagellates from the family gymnodiniaceae.

Science.gov (United States)

Smith, Kirsty F; de Salas, Miguel; Adamson, Janet; Rhodes, Lesley L

2014-03-07

The identification of toxin-producing dinoflagellates for monitoring programmes and bio-compound discovery requires considerable taxonomic expertise. It can also be difficult to morphologically differentiate toxic and non-toxic species or strains. Various molecular methods have been used for dinoflagellate identification and detection, and this study describes the development of eight real-time polymerase chain reaction (PCR) assays targeting the large subunit ribosomal RNA (LSU rRNA) gene of species from the genera Gymnodinium, Karenia, Karlodinium, and Takayama. Assays proved to be highly specific and sensitive, and the assay for G. catenatum was further developed for quantification in response to a bloom in Manukau Harbour, New Zealand. The assay estimated cell densities from environmental samples as low as 0.07 cells per PCR reaction, which equated to three cells per litre. This assay not only enabled conclusive species identification but also detected the presence of cells below the limit of detection for light microscopy. This study demonstrates the usefulness of real-time PCR as a sensitive and rapid molecular technique for the detection and quantification of micro-algae from environmental samples.

Accurate detection of carcinoma cells by use of a cell microarray chip.

Directory of Open Access Journals (Sweden)

Shohei Yamamura

Full Text Available BACKGROUND: Accurate detection and analysis of circulating tumor cells plays an important role in the diagnosis and treatment of metastatic cancer treatment. METHODS AND FINDINGS: A cell microarray chip was used to detect spiked carcinoma cells among leukocytes. The chip, with 20,944 microchambers (105 µm width and 50 µm depth, was made from polystyrene; and the formation of monolayers of leukocytes in the microchambers was observed. Cultured human T lymphoblastoid leukemia (CCRF-CEM cells were used to examine the potential of the cell microarray chip for the detection of spiked carcinoma cells. A T lymphoblastoid leukemia suspension was dispersed on the chip surface, followed by 15 min standing to allow the leukocytes to settle down into the microchambers. Approximately 29 leukocytes were found in each microchamber when about 600,000 leukocytes in total were dispersed onto a cell microarray chip. Similarly, when leukocytes isolated from human whole blood were used, approximately 89 leukocytes entered each microchamber when about 1,800,000 leukocytes in total were placed onto the cell microarray chip. After washing the chip surface, PE-labeled anti-cytokeratin monoclonal antibody and APC-labeled anti-CD326 (EpCAM monoclonal antibody solution were dispersed onto the chip surface and allowed to react for 15 min; and then a microarray scanner was employed to detect any fluorescence-positive cells within 20 min. In the experiments using spiked carcinoma cells (NCI-H1650, 0.01 to 0.0001%, accurate detection of carcinoma cells was achieved with PE-labeled anti-cytokeratin monoclonal antibody. Furthermore, verification of carcinoma cells in the microchambers was performed by double staining with the above monoclonal antibodies. CONCLUSION: The potential application of the cell microarray chip for the detection of CTCs was shown, thus demonstrating accurate detection by double staining for cytokeratin and EpCAM at the single carcinoma cell level.

Structural Acoustic UXO Detection and Identification in Marine Environments

Science.gov (United States)

2016-05-01

a thick steel wall, is cylindrical, and has an aspect ratio of about 5:1. Further, the interior water can support acoustic waves as does the epoxy...FINAL REPORT Structural Acoustic UXO Detection and Identification in Marine Environments SERDP Project MR-2103 MAY 2016 B. H...NUMBER Structural Acoustic UXO Detection and Identification in Marine Environments- Final report for Follow-on Work- MR-2103 Sb. GRANT NUMBER Sc

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.

Science.gov (United States)

Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried; De Vos, Winnok H

2017-01-01

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.

Directory of Open Access Journals (Sweden)

Marlies Verschuuren

Full Text Available A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND, which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.

The combined rapid detection and species-level identification of yeasts in simulated blood culture using a colorimetric sensor array.

Directory of Open Access Journals (Sweden)

Nabin K Shrestha

Full Text Available A colorimetric sensor array (CSA has been demonstrated to rapidly detect and identify bacteria growing in blood cultures by obtaining a species-specific "fingerprint" of the volatile organic compounds (VOCs produced during growth. This capability has been demonstrated in prokaryotes, but has not been reported for eukaryotic cells growing in culture. The purpose of this study was to explore if a disposable CSA could differentially identify 7 species of pathogenic yeasts growing in blood culture.Culture trials of whole blood inoculated with a panel of clinically important pathogenic yeasts at four different microorganism loads were performed. Cultures were done in both standard BacT/Alert and CSA-embedded bottles, after adding 10 mL of spiked blood to each bottle. Color changes in the CSA were captured as images by an optical scanner at defined time intervals. The captured images were analyzed to identify the yeast species. Time to detection by the CSA was compared to that in the BacT/Alert system.One hundred sixty-two yeast culture trials were performed, including strains of several species of Candida (Ca. albicans, Ca. glabrata, Ca. parapsilosis, and Ca. tropicalis, Clavispora (synonym Candida lusitaniae, Pichia kudriavzevii (synonym Candida krusei and Cryptococcus neoformans, at loads of 8.2 × 105, 8.3 × 103, 8.5 × 101, and 1.7 CFU/mL. In addition, 8 negative trials (no yeast were conducted. All negative trials were correctly identified as negative, and all positive trials were detected. Colorimetric responses were species-specific and did not vary by inoculum load over the 500000-fold range of loads tested, allowing for accurate species-level identification. The mean sensitivity for species-level identification by CSA was 74% at detection, and increased with time, reaching almost 95% at 4 hours after detection. At an inoculum load of 1.7 CFU/mL, mean time to detection with the CSA was 6.8 hours (17% less than with the BacT/Alert platform

Rapid and Accurate Identification by Real-Time PCR of Biotoxin-Producing Dinoflagellates from the Family Gymnodiniaceae

Directory of Open Access Journals (Sweden)

Kirsty F. Smith

2014-03-01

Full Text Available The identification of toxin-producing dinoflagellates for monitoring programmes and bio-compound discovery requires considerable taxonomic expertise. It can also be difficult to morphologically differentiate toxic and non-toxic species or strains. Various molecular methods have been used for dinoflagellate identification and detection, and this study describes the development of eight real-time polymerase chain reaction (PCR assays targeting the large subunit ribosomal RNA (LSU rRNA gene of species from the genera Gymnodinium, Karenia, Karlodinium, and Takayama. Assays proved to be highly specific and sensitive, and the assay for G. catenatum was further developed for quantification in response to a bloom in Manukau Harbour, New Zealand. The assay estimated cell densities from environmental samples as low as 0.07 cells per PCR reaction, which equated to three cells per litre. This assay not only enabled conclusive species identification but also detected the presence of cells below the limit of detection for light microscopy. This study demonstrates the usefulness of real-time PCR as a sensitive and rapid molecular technique for the detection and quantification of micro-algae from environmental samples.

Accurate mobile malware detection and classification in the cloud.

Science.gov (United States)

Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

2015-01-01

As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis. Our proposed system mainly consists of two parts: anomaly detection engine performing abnormal apps detection through dynamic analysis; signature detection engine performing known malware detection and classification with the combination of static and dynamic analysis. We evaluate our system using 5560 malware samples and 6000 benign samples. Experiments show that our anomaly detection engine with dynamic analysis is capable of detecting zero-day malware with a low false negative rate (1.16 %) and acceptable false positive rate (1.30 %); it is worth noting that our signature detection engine with hybrid analysis can accurately classify malware samples with an average positive rate 98.94 %. Considering the intensive computing resources required by the static and dynamic analysis, our proposed detection system should be deployed off-device, such as in the Cloud. The app store markets and the ordinary users can access our detection system for malware detection through cloud service.

A dual-process account of auditory change detection.

Science.gov (United States)

McAnally, Ken I; Martin, Russell L; Eramudugolla, Ranmalee; Stuart, Geoffrey W; Irvine, Dexter R F; Mattingley, Jason B

2010-08-01

Listeners can be "deaf" to a substantial change in a scene comprising multiple auditory objects unless their attention has been directed to the changed object. It is unclear whether auditory change detection relies on identification of the objects in pre- and post-change scenes. We compared the rates at which listeners correctly identify changed objects with those predicted by change-detection models based on signal detection theory (SDT) and high-threshold theory (HTT). Detected changes were not identified as accurately as predicted by models based on either theory, suggesting that some changes are detected by a process that does not support change identification. Undetected changes were identified as accurately as predicted by the HTT model but much less accurately than predicted by the SDT models. The process underlying change detection was investigated further by determining receiver-operating characteristics (ROCs). ROCs did not conform to those predicted by either a SDT or a HTT model but were well modeled by a dual-process that incorporated HTT and SDT components. The dual-process model also accurately predicted the rates at which detected and undetected changes were correctly identified.

Detection and identification of bio-threats using MALDI-TOF-MS

NARCIS (Netherlands)

Paauw, A.

2012-01-01

MALDI-TOF-MS emerged as a new diagnostic tool in established clinical laboratories. Advantages compared to conventional techniques are that it is a fast, cost-effective, accurate method, which is suitable for high-throughput identification of bacteria by less skilled laboratory personnel because

Detection and Identification of Loss of Efficiency Faults of Flight Actuators

Directory of Open Access Journals (Sweden)

Ossmann Daniel

2015-03-01

Full Text Available We propose linear parameter-varying (LPV model-based approaches to the synthesis of robust fault detection and diagnosis (FDD systems for loss of efficiency (LOE faults of flight actuators. The proposed methods are applicable to several types of parametric (or multiplicative LOE faults such as actuator disconnection, surface damage, actuator power loss or stall loads. For the detection of these parametric faults, advanced LPV-model detection techniques are proposed, which implicitly provide fault identification information. Fast detection of intermittent stall loads (seen as nuisances, rather than faults is important in enhancing the performance of various fault detection schemes dealing with large input signals. For this case, a dedicated fast identification algorithm is devised. The developed FDD systems are tested on a nonlinear actuator model which is implemented in a full nonlinear aircraft simulation model. This enables the validation of the FDD system’s detection and identification characteristics under realistic conditions.

Rapid detection and identification of four major Schistosoma species by high-resolution melt (HRM) analysis.

Science.gov (United States)

Li, Juan; Zhao, Guang-Hui; Lin, RuiQing; Blair, David; Sugiyama, Hiromu; Zhu, Xing-Quan

2015-11-01

Schistosomiasis, caused by blood flukes belonging to several species of the genus Schistosoma, is a serious and widespread parasitic disease. Accurate and rapid differentiation of these etiological agents of animal and human schistosomiasis to species level can be difficult. We report a real-time PCR assay coupled with a high-resolution melt (HRM) assay targeting a portion of the nuclear 18S rDNA to detect, identify, and distinguish between four major blood fluke species (Schistosoma japonicum, Schistosoma mansoni, Schistosoma haematobium, and Schistosoma mekongi). Using this system, the Schistosoma spp. was accurately identified and could also be distinguished from all other trematode species with which they were compared. As little as 10(-5) ng genomic DNA from a Schistosoma sp. could be detected. This process is inexpensive, easy, and can be completed within 3 h. Examination of 21 representative Schistosoma samples from 15 geographical localities in seven endemic countries validated the value of the HRM detection assay and proved its reliability. The melting curves were characterized by peaks of 83.65 °C for S. japonicum and S. mekongi, 85.65 °C for S. mansoni, and 85.85 °C for S. haematobium. The present study developed a real-time PCR coupled with HRM analysis assay for detection and differential identification of S. mansoni, S. haematobium, S. japonicum, and S. mekongi. This method is rapid, sensitive, and inexpensive. It has important implications for epidemiological studies of Schistosoma.

Comparison of methods for accurate end-point detection of potentiometric titrations

Science.gov (United States)

Villela, R. L. A.; Borges, P. P.; Vyskočil, L.

2015-01-01

Detection of the end point in potentiometric titrations has wide application on experiments that demand very low measurement uncertainties mainly for certifying reference materials. Simulations of experimental coulometric titration data and consequential error analysis of the end-point values were conducted using a programming code. These simulations revealed that the Levenberg-Marquardt method is in general more accurate than the traditional second derivative technique used currently as end-point detection for potentiometric titrations. Performance of the methods will be compared and presented in this paper.

Comparison of methods for accurate end-point detection of potentiometric titrations

International Nuclear Information System (INIS)

Villela, R L A; Borges, P P; Vyskočil, L

2015-01-01

Detection of the end point in potentiometric titrations has wide application on experiments that demand very low measurement uncertainties mainly for certifying reference materials. Simulations of experimental coulometric titration data and consequential error analysis of the end-point values were conducted using a programming code. These simulations revealed that the Levenberg-Marquardt method is in general more accurate than the traditional second derivative technique used currently as end-point detection for potentiometric titrations. Performance of the methods will be compared and presented in this paper

Final Progress Report: Isotope Identification Algorithm for Rapid and Accurate Determination of Radioisotopes Feasibility Study

International Nuclear Information System (INIS)

Rawool-Sullivan, Mohini; Bounds, John Alan; Brumby, Steven P.; Prasad, Lakshman; Sullivan, John P.

2012-01-01

This is the final report of the project titled, 'Isotope Identification Algorithm for Rapid and Accurate Determination of Radioisotopes,' PMIS project number LA10-HUMANID-PD03. The goal of the work was to demonstrate principles of emulating a human analysis approach towards the data collected using radiation isotope identification devices (RIIDs). It summarizes work performed over the FY10 time period. The goal of the work was to demonstrate principles of emulating a human analysis approach towards the data collected using radiation isotope identification devices (RIIDs). Human analysts begin analyzing a spectrum based on features in the spectrum - lines and shapes that are present in a given spectrum. The proposed work was to carry out a feasibility study that will pick out all gamma ray peaks and other features such as Compton edges, bremsstrahlung, presence/absence of shielding and presence of neutrons and escape peaks. Ultimately success of this feasibility study will allow us to collectively explain identified features and form a realistic scenario that produced a given spectrum in the future. We wanted to develop and demonstrate machine learning algorithms that will qualitatively enhance the automated identification capabilities of portable radiological sensors that are currently being used in the field.

Detection and identification of human targets in radar data

Science.gov (United States)

Gürbüz, Sevgi Z.; Melvin, William L.; Williams, Douglas B.

2007-04-01

Radar offers unique advantages over other sensors, such as visual or seismic sensors, for human target detection. Many situations, especially military applications, prevent the placement of video cameras or implantment seismic sensors in the area being observed, because of security or other threats. However, radar can operate far away from potential targets, and functions during daytime as well as nighttime, in virtually all weather conditions. In this paper, we examine the problem of human target detection and identification using single-channel, airborne, synthetic aperture radar (SAR). Human targets are differentiated from other detected slow-moving targets by analyzing the spectrogram of each potential target. Human spectrograms are unique, and can be used not just to identify targets as human, but also to determine features about the human target being observed, such as size, gender, action, and speed. A 12-point human model, together with kinematic equations of motion for each body part, is used to calculate the expected target return and spectrogram. A MATLAB simulation environment is developed including ground clutter, human and non-human targets for the testing of spectrogram-based detection and identification algorithms. Simulations show that spectrograms have some ability to detect and identify human targets in low noise. An example gender discrimination system correctly detected 83.97% of males and 91.11% of females. The problems and limitations of spectrogram-based methods in high clutter environments are discussed. The SNR loss inherent to spectrogram-based methods is quantified. An alternate detection and identification method that will be used as a basis for future work is proposed.

Robust and Accurate Anomaly Detection in ECG Artifacts Using Time Series Motif Discovery

Science.gov (United States)

Sivaraks, Haemwaan

2015-01-01

Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods. PMID:25688284

Detection and identification of unexploded ordnance (UXO) by neutron interrogation

International Nuclear Information System (INIS)

Caffrey, A.J.; Hartwell, J.K.; Krebs, K.M.; McLaughlin, G.D.

1998-01-01

This document reviews the principle of operation and unexploded ordnance (UXO) signatures of the PINS Chemical Assay System, a prompt-gamma-ray neutron activation analysis (PGNAA) for the identification of recovered UXO. Two related low cost methods for buried landmine detection are also suggested. Nuclear methods may compliment existing search techniques to improve the overall probability of detection and to reduce the false positive rate of other technologies. In addition, nuclear methods are a proven method for identification of UXO such as landmines

Parente2: a fast and accurate method for detecting identity by descent

KAUST Repository

Rodriguez, Jesse M.; Bercovici, Sivan; Huang, Lin; Frostig, Roy; Batzoglou, Serafim

2014-01-01

Identity-by-descent (IBD) inference is the problem of establishing a genetic connection between two individuals through a genomic segment that is inherited by both individuals from a recent common ancestor. IBD inference is an important preceding step in a variety of population genomic studies, ranging from demographic studies to linking genomic variation with phenotype and disease. The problem of accurate IBD detection has become increasingly challenging with the availability of large collections of human genotypes and genomes: Given a cohort's size, a quadratic number of pairwise genome comparisons must be performed. Therefore, computation time and the false discovery rate can also scale quadratically. To enable accurate and efficient large-scale IBD detection, we present Parente2, a novel method for detecting IBD segments. Parente2 is based on an embedded log-likelihood ratio and uses a model that accounts for linkage disequilibrium by explicitly modeling haplotype frequencies. Parente2 operates directly on genotype data without the need to phase data prior to IBD inference. We evaluate Parente2's performance through extensive simulations using real data, and we show that it provides substantially higher accuracy compared to previous state-of-the-art methods while maintaining high computational efficiency.

Breaking Snake Camouflage: Humans Detect Snakes More Accurately than Other Animals under Less Discernible Visual Conditions.

Science.gov (United States)

Kawai, Nobuyuki; He, Hongshen

2016-01-01

Humans and non-human primates are extremely sensitive to snakes as exemplified by their ability to detect pictures of snakes more quickly than those of other animals. These findings are consistent with the Snake Detection Theory, which hypothesizes that as predators, snakes were a major source of evolutionary selection that favored expansion of the visual system of primates for rapid snake detection. Many snakes use camouflage to conceal themselves from both prey and their own predators, making it very challenging to detect them. If snakes have acted as a selective pressure on primate visual systems, they should be more easily detected than other animals under difficult visual conditions. Here we tested whether humans discerned images of snakes more accurately than those of non-threatening animals (e.g., birds, cats, or fish) under conditions of less perceptual information by presenting a series of degraded images with the Random Image Structure Evolution technique (interpolation of random noise). We find that participants recognize mosaic images of snakes, which were regarded as functionally equivalent to camouflage, more accurately than those of other animals under dissolved conditions. The present study supports the Snake Detection Theory by showing that humans have a visual system that accurately recognizes snakes under less discernible visual conditions.

Breaking Snake Camouflage: Humans Detect Snakes More Accurately than Other Animals under Less Discernible Visual Conditions.

Directory of Open Access Journals (Sweden)

Nobuyuki Kawai

Full Text Available Humans and non-human primates are extremely sensitive to snakes as exemplified by their ability to detect pictures of snakes more quickly than those of other animals. These findings are consistent with the Snake Detection Theory, which hypothesizes that as predators, snakes were a major source of evolutionary selection that favored expansion of the visual system of primates for rapid snake detection. Many snakes use camouflage to conceal themselves from both prey and their own predators, making it very challenging to detect them. If snakes have acted as a selective pressure on primate visual systems, they should be more easily detected than other animals under difficult visual conditions. Here we tested whether humans discerned images of snakes more accurately than those of non-threatening animals (e.g., birds, cats, or fish under conditions of less perceptual information by presenting a series of degraded images with the Random Image Structure Evolution technique (interpolation of random noise. We find that participants recognize mosaic images of snakes, which were regarded as functionally equivalent to camouflage, more accurately than those of other animals under dissolved conditions. The present study supports the Snake Detection Theory by showing that humans have a visual system that accurately recognizes snakes under less discernible visual conditions.

Detection and identification of concealed weapons using matrix pencil

Science.gov (United States)

Adve, Raviraj S.; Thayaparan, Thayananthan

2011-06-01

The detection and identification of concealed weapons is an extremely hard problem due to the weak signature of the target buried within the much stronger signal from the human body. This paper furthers the automatic detection and identification of concealed weapons by proposing the use of an effective approach to obtain the resonant frequencies in a measurement. The technique, based on Matrix Pencil, a scheme for model based parameter estimation also provides amplitude information, hence providing a level of confidence in the results. Of specific interest is the fact that Matrix Pencil is based on a singular value decomposition, making the scheme robust against noise.

Multivariate algorithms for initiating event detection and identification in nuclear power plants

International Nuclear Information System (INIS)

Wu, Shun-Chi; Chen, Kuang-You; Lin, Ting-Han; Chou, Hwai-Pwu

2018-01-01

Highlights: •Multivariate algorithms for NPP initiating event detection and identification. •Recordings from multiple sensors are simultaneously considered for detection. •Both spatial and temporal information is used for event identification. •Untrained event isolation avoids falsely relating an untrained event. •Efficacy of the algorithms is verified with data from the Maanshan NPP simulator. -- Abstract: To prevent escalation of an initiating event into a severe accident, promptly detecting its occurrence and precisely identifying its type are essential. In this study, several multivariate algorithms for initiating event detection and identification are proposed to help maintain safe operations of nuclear power plants (NPPs). By monitoring changes in the NPP sensing variables, an event is detected when the preset thresholds are exceeded. Unlike existing approaches, recordings from sensors of the same type are simultaneously considered for detection, and no subjective reasoning is involved in setting these thresholds. To facilitate efficient event identification, a spatiotemporal feature extractor is proposed. The extracted features consist of the temporal traits used by existing techniques and the spatial signature of an event. Through an F-score-based feature ranking, only those that are most discriminant in classifying the events under consideration will be retained for identification. Moreover, an untrained event isolation scheme is introduced to avoid relating an untrained event to those in the event dataset so that improper recovery actions can be prevented. Results from experiments containing data of 12 event classes and a total of 125 events generated using a Taiwan’s Maanshan NPP simulator are provided to illustrate the efficacy of the proposed algorithms.

Sad people are more accurate at expression identification with a smaller own-ethnicity bias than happy people.

Science.gov (United States)

Hills, Peter J; Hill, Dominic M

2017-07-12

Sad individuals perform more accurately at face identity recognition (Hills, Werno, & Lewis, 2011), possibly because they scan more of the face during encoding. During expression identification tasks, sad individuals do not fixate on the eyes as much as happier individuals (Wu, Pu, Allen, & Pauli, 2012). Fixating on features other than the eyes leads to a reduced own-ethnicity bias (Hills & Lewis, 2006). This background indicates that sad individuals would not view the eyes as much as happy individuals and this would result in improved expression recognition and a reduced own-ethnicity bias. This prediction was tested using an expression identification task, with eye tracking. We demonstrate that sad-induced participants show enhanced expression recognition and a reduced own-ethnicity bias than happy-induced participants due to scanning more facial features. We conclude that mood affects eye movements and face encoding by causing a wider sampling strategy and deeper encoding of facial features diagnostic for expression identification.

Parente2: a fast and accurate method for detecting identity by descent

KAUST Repository

Rodriguez, Jesse M.

2014-10-01

Identity-by-descent (IBD) inference is the problem of establishing a genetic connection between two individuals through a genomic segment that is inherited by both individuals from a recent common ancestor. IBD inference is an important preceding step in a variety of population genomic studies, ranging from demographic studies to linking genomic variation with phenotype and disease. The problem of accurate IBD detection has become increasingly challenging with the availability of large collections of human genotypes and genomes: Given a cohort\\'s size, a quadratic number of pairwise genome comparisons must be performed. Therefore, computation time and the false discovery rate can also scale quadratically. To enable accurate and efficient large-scale IBD detection, we present Parente2, a novel method for detecting IBD segments. Parente2 is based on an embedded log-likelihood ratio and uses a model that accounts for linkage disequilibrium by explicitly modeling haplotype frequencies. Parente2 operates directly on genotype data without the need to phase data prior to IBD inference. We evaluate Parente2\\'s performance through extensive simulations using real data, and we show that it provides substantially higher accuracy compared to previous state-of-the-art methods while maintaining high computational efficiency.

A signal detection theory analysis of an unconscious perception effect.

Science.gov (United States)

Haase, S J; Theios, J; Jenison, R

1999-07-01

The independent observation model (Macmillan & Creelman, 1991) is fitted to detection-identification data collected under conditions of heavy masking. The model accurately predicts a quantitative relationship between stimulus detection and stimulus identification over a wide range of detection performance. This model can also be used to offer a signal detection interpretation of the common finding of above-chance identification following a missed signal. While our finding is not a new one, the stimuli used in this experiment (redundant three-letter strings) differ slightly from those used in traditional signal detection work. Also, the stimuli were presented very briefly and heavily masked, conditions typical in the study of unconscious perception effects.

Development and validation of a multiplex real-time PCR method to simultaneously detect 47 targets for the identification of genetically modified organisms.

Science.gov (United States)

Cottenet, Geoffrey; Blancpain, Carine; Sonnard, Véronique; Chuah, Poh Fong

2013-08-01

Considering the increase of the total cultivated land area dedicated to genetically modified organisms (GMO), the consumers' perception toward GMO and the need to comply with various local GMO legislations, efficient and accurate analytical methods are needed for their detection and identification. Considered as the gold standard for GMO analysis, the real-time polymerase chain reaction (RTi-PCR) technology was optimised to produce a high-throughput GMO screening method. Based on simultaneous 24 multiplex RTi-PCR running on a ready-to-use 384-well plate, this new procedure allows the detection and identification of 47 targets on seven samples in duplicate. To comply with GMO analytical quality requirements, a negative and a positive control were analysed in parallel. In addition, an internal positive control was also included in each reaction well for the detection of potential PCR inhibition. Tested on non-GM materials, on different GM events and on proficiency test samples, the method offered high specificity and sensitivity with an absolute limit of detection between 1 and 16 copies depending on the target. Easy to use, fast and cost efficient, this multiplex approach fits the purpose of GMO testing laboratories.

Rapid detection and identification of Bacillus anthracis in food using pyrosequencing technology.

Science.gov (United States)

Amoako, Kingsley K; Janzen, Timothy W; Shields, Michael J; Hahn, Kristen R; Thomas, Matthew C; Goji, Noriko

2013-08-01

The development of advanced methodologies for the detection of Bacillus anthracis has been evolving rapidly since the release of the anthrax spores in the mail in 2001. Recent advances in detection and identification techniques could prove to be an essential component in the defense against biological attacks. Sequence based such as pyrosequencing, which has the capability to determine short DNA stretches in real-time using biotinylated PCR amplicons, has potential biodefense applications. Using markers from the virulence plasmids (pXO1 and pXO2) and chromosomal regions, we have demonstrated the power of this technology in the rapid, specific and sensitive detection of B. anthracis spores in food matrices including milk, juice, bottled water, and processed meat. The combined use of immunomagnetic separation and pyrosequencing showed positive detection when liquid foods (bottled water, milk, juice), and processed meat were experimentally inoculated with 6CFU/mL and 6CFU/g, respectively, without an enrichment step. Pyrosequencing is completed in about 60min (following PCR amplification) and yields accurate and reliable results with an added layer of confidence. The entire assay (from sample preparation to sequencing information) can be completed in about 7.5h. A typical run on food samples yielded 67-80bp reads with 94-100% identity to the expected sequence. This sequence based approach is a novel application for the detection of anthrax spores in food with potential application in foodborne bioterrorism response and biodefense involving the use of anthrax spores. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Rapid identification and detection of pathogenic Fungi by padlock probes

NARCIS (Netherlands)

Tsui, C.K.M.; Wang, B.; Schoen, C.D.; Hamelin, R.C.

2013-01-01

Fungi are important pathogens of human diseases, as well as to agricultural crop and trees. Molecular diagnostics can detect diseases early, and improve identification accuracy and follow-up disease management. The use of padlock probe is effective to facilitate these detections and pathogen

On-line signal trend identification

International Nuclear Information System (INIS)

Tambouratzis, T.; Antonopoulos-Domis, M.

2004-01-01

An artificial neural network, based on the self-organizing map, is proposed for on-line signal trend identification. Trends are categorized at each incoming signal as steady-state, increasing and decreasing, while they are further classified according to characteristics such signal shape and rate of change. Tests with model-generated signals illustrate the ability of the self-organizing map to accurately and reliably perform on-line trend identification in terms of both detection and classification. The proposed methodology has been found robust to the presence of white noise

Accurate identification of layer number for few-layer WS2 and WSe2 via spectroscopic study.

Science.gov (United States)

Li, Yuanzheng; Li, Xinshu; Yu, Tong; Yang, Guochun; Chen, Heyu; Zhang, Cen; Feng, Qiushi; Ma, Jiangang; Liu, Weizhen; Xu, Haiyang; Liu, Yichun; Liu, Xinfeng

2018-03-23

Transition metal dichalcogenides (TMDs) with a typical layered structure are highly sensitive to their layer number in optical and electronic properties. Seeking a simple and effective method for layer number identification is very important to low-dimensional TMD samples. Herein, a rapid and accurate layer number identification of few-layer WS 2 and WSe 2 is proposed via locking their photoluminescence (PL) peak-positions. As the layer number of WS 2 /WSe 2 increases, it is found that indirect transition emission is more thickness-sensitive than direct transition emission, and the PL peak-position differences between the indirect and direct transitions can be regarded as fingerprints to identify their layer number. Theoretical calculation confirms that the notable thickness-sensitivity of indirect transition derives from the variations of electron density of states of W atom d-orbitals and chalcogen atom p-orbitals. Besides, the PL peak-position differences between the indirect and direct transitions are almost independent of different insulating substrates. This work not only proposes a new method for layer number identification via PL studies, but also provides a valuable insight into the thickness-dependent optical and electronic properties of W-based TMDs.

Parkinsonian rest tremor can be detected accurately based on neuronal oscillations recorded from the subthalamic nucleus.

Science.gov (United States)

Hirschmann, J; Schoffelen, J M; Schnitzler, A; van Gerven, M A J

2017-10-01

To investigate the possibility of tremor detection based on deep brain activity. We re-analyzed recordings of local field potentials (LFPs) from the subthalamic nucleus in 10 PD patients (12 body sides) with spontaneously fluctuating rest tremor. Power in several frequency bands was estimated and used as input to Hidden Markov Models (HMMs) which classified short data segments as either tremor-free rest or rest tremor. HMMs were compared to direct threshold application to individual power features. Applying a threshold directly to band-limited power was insufficient for tremor detection (mean area under the curve [AUC] of receiver operating characteristic: 0.64, STD: 0.19). Multi-feature HMMs, in contrast, allowed for accurate detection (mean AUC: 0.82, STD: 0.15), using four power features obtained from a single contact pair. Within-patient training yielded better accuracy than across-patient training (0.84vs. 0.78, p=0.03), yet tremor could often be detected accurately with either approach. High frequency oscillations (>200Hz) were the best performing individual feature. LFP-based markers of tremor are robust enough to allow for accurate tremor detection in short data segments, provided that appropriate statistical models are used. LFP-based markers of tremor could be useful control signals for closed-loop deep brain stimulation. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

SpotCaliper: fast wavelet-based spot detection with accurate size estimation.

Science.gov (United States)

Püspöki, Zsuzsanna; Sage, Daniel; Ward, John Paul; Unser, Michael

2016-04-15

SpotCaliper is a novel wavelet-based image-analysis software providing a fast automatic detection scheme for circular patterns (spots), combined with the precise estimation of their size. It is implemented as an ImageJ plugin with a friendly user interface. The user is allowed to edit the results by modifying the measurements (in a semi-automated way), extract data for further analysis. The fine tuning of the detections includes the possibility of adjusting or removing the original detections, as well as adding further spots. The main advantage of the software is its ability to capture the size of spots in a fast and accurate way. http://bigwww.epfl.ch/algorithms/spotcaliper/ zsuzsanna.puspoki@epfl.ch Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Fast and accurate spectral estimation for online detection of partial broken bar in induction motors

Science.gov (United States)

Samanta, Anik Kumar; Naha, Arunava; Routray, Aurobinda; Deb, Alok Kanti

2018-01-01

In this paper, an online and real-time system is presented for detecting partial broken rotor bar (BRB) of inverter-fed squirrel cage induction motors under light load condition. This system with minor modifications can detect any fault that affects the stator current. A fast and accurate spectral estimator based on the theory of Rayleigh quotient is proposed for detecting the spectral signature of BRB. The proposed spectral estimator can precisely determine the relative amplitude of fault sidebands and has low complexity compared to available high-resolution subspace-based spectral estimators. Detection of low-amplitude fault components has been improved by removing the high-amplitude fundamental frequency using an extended-Kalman based signal conditioner. Slip is estimated from the stator current spectrum for accurate localization of the fault component. Complexity and cost of sensors are minimal as only a single-phase stator current is required. The hardware implementation has been carried out on an Intel i7 based embedded target ported through the Simulink Real-Time. Evaluation of threshold and detectability of faults with different conditions of load and fault severity are carried out with empirical cumulative distribution function.

Accurate LC peak boundary detection for ¹⁶O/¹⁸O labeled LC-MS data.

Science.gov (United States)

Cui, Jian; Petritis, Konstantinos; Tegeler, Tony; Petritis, Brianne; Ma, Xuepo; Jin, Yufang; Gao, Shou-Jiang S J; Zhang, Jianqiu Michelle

2013-01-01

In liquid chromatography-mass spectrometry (LC-MS), parts of LC peaks are often corrupted by their co-eluting peptides, which results in increased quantification variance. In this paper, we propose to apply accurate LC peak boundary detection to remove the corrupted part of LC peaks. Accurate LC peak boundary detection is achieved by checking the consistency of intensity patterns within peptide elution time ranges. In addition, we remove peptides with erroneous mass assignment through model fitness check, which compares observed intensity patterns to theoretically constructed ones. The proposed algorithm can significantly improve the accuracy and precision of peptide ratio measurements.

Calibration experiments of neutron source identification and detection in soil

International Nuclear Information System (INIS)

Gorin, N. V.; Lipilina, E. N.; Rukavishnikov, G. V.; Shmakov, D. V.; Ulyanov, A. I.

2007-01-01

In the course of detection of fissile materials in soil, series of calibration experiments were carried out on in laboratory conditions on an experimental installation, presenting a mock-up of an endless soil with various heterogeneous bodies in it, fissile material, measuring boreholes. A design of detecting device, methods of neutrons detection are described. Conditions of neutron background measuring are given. Soil density, humidity, chemical composition of soil was measured. Sensitivity of methods of fissile materials detection and identification in soil was estimated in the calibration experiments. Minimal detectable activity and the distance at which it can be detected were defined. Characteristics of neutron radiation in a borehole mock-up were measured; dependences of method sensitivities from water content in soil, source-detector distance and presence of heterogeneous bodies were examined. Possibility of direction detection to a fissile material as neutron source from a borehole using a collimator is shown. Identification of fissile material was carried out by measuring the gamma-spectrum. Mathematical modeling was carried out using the PRIZMA code (Developed in RFNC-VNIITF) and MCNP code (Developed in LANL). Good correlation of calculational and experimental values was shown. The methodic were shown to be applicable in the field conditions

DIRADTM - a system for real time detection and identification of radioactive objects

International Nuclear Information System (INIS)

Guillot, L.; Reboli, A.

2009-01-01

The authors present the DIRAD system (DIRAD stands for Detection and Identification of Radionuclides), an automatic system for real time identification of a radioactive anomaly and its interpretation in terms of risk level. It can be adapted to different contexts: pedestrian control, parcel or luggage control, road traffic control, and so on. In case of risk detection, an alert is transmitted in real time to a supervision station along with the whole set of spectral data

Exploration of available feature detection and identification systems and their performance on radiographs

Science.gov (United States)

Wantuch, Andrew C.; Vita, Joshua A.; Jimenez, Edward S.; Bray, Iliana E.

2016-10-01

Despite object detection, recognition, and identification being very active areas of computer vision research, many of the available tools to aid in these processes are designed with only photographs in mind. Although some algorithms used specifically for feature detection and identification may not take explicit advantage of the colors available in the image, they still under-perform on radiographs, which are grayscale images. We are especially interested in the robustness of these algorithms, specifically their performance on a preexisting database of X-ray radiographs in compressed JPEG form, with multiple ways of describing pixel information. We will review various aspects of the performance of available feature detection and identification systems, including MATLABs Computer Vision toolbox, VLFeat, and OpenCV on our non-ideal database. In the process, we will explore possible reasons for the algorithms' lessened ability to detect and identify features from the X-ray radiographs.

Potential of MALDI-TOF mass spectrometry as a rapid detection technique in plant pathology: identification of plant-associated microorganisms.

Science.gov (United States)

Ahmad, Faheem; Babalola, Olubukola O; Tak, Hamid I

2012-09-01

Plant diseases caused by plant pathogens substantially reduce crop production every year, resulting in massive economic losses throughout the world. Accurate detection and identification of plant pathogens is fundamental to plant pathogen diagnostics and, thus, plant disease management. Diagnostics and disease-management strategies require techniques to enable simultaneous detection and quantification of a wide range of pathogenic and non-pathogenic microorganisms. Over the past decade, rapid development of matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) techniques for characterization of microorganisms has enabled substantially improved detection and identification of microorganisms. In the biological sciences, MALDI-TOF MS is used to analyze specific peptides or proteins directly desorbed from intact bacteria, fungal spores, nematodes, and other microorganisms. The ability to record biomarker ions, in a broad m/z range, which are unique to and representative of individual microorganisms, forms the basis of taxonomic identification of microorganisms by MALDI-TOF MS. Recent advances in mass spectrometry have initiated new research, i.e. analysis of more complex microbial communities. Such studies are just beginning but have great potential for elucidation not only of the interactions between microorganisms and their host plants but also those among different microbial taxa living in association with plants. There has been a recent effort by the mass spectrometry community to make data from large scale mass spectrometry experiments publicly available in the form of a centralized repository. Such a resource could enable the use of MALDI-TOF MS as a universal technique for detection of plant pathogens and non-pathogens. The effects of experimental conditions are sufficiently understood, reproducible spectra can be obtained from computational database search, and microorganisms can be rapidly characterized by genus, species

DNA barcode data accurately assign higher spider taxa

Directory of Open Access Journals (Sweden)

Jonathan A. Coddington

2016-07-01

Full Text Available The use of unique DNA sequences as a method for taxonomic identification is no longer fundamentally controversial, even though debate continues on the best markers, methods, and technology to use. Although both existing databanks such as GenBank and BOLD, as well as reference taxonomies, are imperfect, in best case scenarios “barcodes” (whether single or multiple, organelle or nuclear, loci clearly are an increasingly fast and inexpensive method of identification, especially as compared to manual identification of unknowns by increasingly rare expert taxonomists. Because most species on Earth are undescribed, a complete reference database at the species level is impractical in the near term. The question therefore arises whether unidentified species can, using DNA barcodes, be accurately assigned to more inclusive groups such as genera and families—taxonomic ranks of putatively monophyletic groups for which the global inventory is more complete and stable. We used a carefully chosen test library of CO1 sequences from 49 families, 313 genera, and 816 species of spiders to assess the accuracy of genus and family-level assignment. We used BLAST queries of each sequence against the entire library and got the top ten hits. The percent sequence identity was reported from these hits (PIdent, range 75–100%. Accurate assignment of higher taxa (PIdent above which errors totaled less than 5% occurred for genera at PIdent values >95 and families at PIdent values ≥ 91, suggesting these as heuristic thresholds for accurate generic and familial identifications in spiders. Accuracy of identification increases with numbers of species/genus and genera/family in the library; above five genera per family and fifteen species per genus all higher taxon assignments were correct. We propose that using percent sequence identity between conventional barcode sequences may be a feasible and reasonably accurate method to identify animals to family/genus. However

Signal trend identification with fuzzy methods

International Nuclear Information System (INIS)

Reifman, J.; Tsoukalas, L. H.; Wang, X.; Wei, T. Y. C.

1999-01-01

A fuzzy-logic-based methodology for on-line signal trend identification is introduced. Although signal trend identification is complicated by the presence of noise, fuzzy logic can help capture important features of on-line signals and classify incoming power plant signals into increasing, decreasing and steady-state trend categories. In order to verify the methodology, a code named PROTREN is developed and tested using plant data. The results indicate that the code is capable of detecting transients accurately, identifying trends reliably, and not misinterpreting a steady-state signal as a transient one

Event storm detection and identification in communication systems

International Nuclear Information System (INIS)

Albaghdadi, Mouayad; Briley, Bruce; Evens, Martha

2006-01-01

Event storms are the manifestation of an important class of abnormal behaviors in communication systems. They occur when a large number of nodes throughout the system generate a set of events within a small period of time. It is essential for network management systems to detect every event storm and identify its cause, in order to prevent and repair potential system faults. This paper presents a set of techniques for the effective detection and identification of event storms in communication systems. First, we introduce a new algorithm to synchronize events to a single node in the system. Second, the system's event log is modeled as a normally distributed random process. This is achieved by using data analysis techniques to explore and then model the statistical behavior of the event log. Third, event storm detection is proposed using a simple test statistic combined with an exponential smoothing technique to overcome the non-stationary behavior of event logs. Fourth, the system is divided into non-overlapping regions to locate the main contributing regions of a storm. We show that this technique provides us with a method for event storm identification. Finally, experimental results from a commercially deployed multimedia communication system that uses these techniques demonstrate their effectiveness

LocARNA-P: Accurate boundary prediction and improved detection of structural RNAs

DEFF Research Database (Denmark)

Will, Sebastian; Joshi, Tejal; Hofacker, Ivo L.

2012-01-01

Current genomic screens for noncoding RNAs (ncRNAs) predict a large number of genomic regions containing potential structural ncRNAs. The analysis of these data requires highly accurate prediction of ncRNA boundaries and discrimination of promising candidate ncRNAs from weak predictions. Existing...... methods struggle with these goals because they rely on sequence-based multiple sequence alignments, which regularly misalign RNA structure and therefore do not support identification of structural similarities. To overcome this limitation, we compute columnwise and global reliabilities of alignments based...... on sequence and structure similarity; we refer to these structure-based alignment reliabilities as STARs. The columnwise STARs of alignments, or STAR profiles, provide a versatile tool for the manual and automatic analysis of ncRNAs. In particular, we improve the boundary prediction of the widely used nc...

Large-Scale Off-Target Identification Using Fast and Accurate Dual Regularized One-Class Collaborative Filtering and Its Application to Drug Repurposing.

Directory of Open Access Journals (Sweden)

Hansaim Lim

2016-10-01

Full Text Available Target-based screening is one of the major approaches in drug discovery. Besides the intended target, unexpected drug off-target interactions often occur, and many of them have not been recognized and characterized. The off-target interactions can be responsible for either therapeutic or side effects. Thus, identifying the genome-wide off-targets of lead compounds or existing drugs will be critical for designing effective and safe drugs, and providing new opportunities for drug repurposing. Although many computational methods have been developed to predict drug-target interactions, they are either less accurate than the one that we are proposing here or computationally too intensive, thereby limiting their capability for large-scale off-target identification. In addition, the performances of most machine learning based algorithms have been mainly evaluated to predict off-target interactions in the same gene family for hundreds of chemicals. It is not clear how these algorithms perform in terms of detecting off-targets across gene families on a proteome scale. Here, we are presenting a fast and accurate off-target prediction method, REMAP, which is based on a dual regularized one-class collaborative filtering algorithm, to explore continuous chemical space, protein space, and their interactome on a large scale. When tested in a reliable, extensive, and cross-gene family benchmark, REMAP outperforms the state-of-the-art methods. Furthermore, REMAP is highly scalable. It can screen a dataset of 200 thousands chemicals against 20 thousands proteins within 2 hours. Using the reconstructed genome-wide target profile as the fingerprint of a chemical compound, we predicted that seven FDA-approved drugs can be repurposed as novel anti-cancer therapies. The anti-cancer activity of six of them is supported by experimental evidences. Thus, REMAP is a valuable addition to the existing in silico toolbox for drug target identification, drug repurposing

Large-Scale Off-Target Identification Using Fast and Accurate Dual Regularized One-Class Collaborative Filtering and Its Application to Drug Repurposing.

Science.gov (United States)

Lim, Hansaim; Poleksic, Aleksandar; Yao, Yuan; Tong, Hanghang; He, Di; Zhuang, Luke; Meng, Patrick; Xie, Lei

2016-10-01

Target-based screening is one of the major approaches in drug discovery. Besides the intended target, unexpected drug off-target interactions often occur, and many of them have not been recognized and characterized. The off-target interactions can be responsible for either therapeutic or side effects. Thus, identifying the genome-wide off-targets of lead compounds or existing drugs will be critical for designing effective and safe drugs, and providing new opportunities for drug repurposing. Although many computational methods have been developed to predict drug-target interactions, they are either less accurate than the one that we are proposing here or computationally too intensive, thereby limiting their capability for large-scale off-target identification. In addition, the performances of most machine learning based algorithms have been mainly evaluated to predict off-target interactions in the same gene family for hundreds of chemicals. It is not clear how these algorithms perform in terms of detecting off-targets across gene families on a proteome scale. Here, we are presenting a fast and accurate off-target prediction method, REMAP, which is based on a dual regularized one-class collaborative filtering algorithm, to explore continuous chemical space, protein space, and their interactome on a large scale. When tested in a reliable, extensive, and cross-gene family benchmark, REMAP outperforms the state-of-the-art methods. Furthermore, REMAP is highly scalable. It can screen a dataset of 200 thousands chemicals against 20 thousands proteins within 2 hours. Using the reconstructed genome-wide target profile as the fingerprint of a chemical compound, we predicted that seven FDA-approved drugs can be repurposed as novel anti-cancer therapies. The anti-cancer activity of six of them is supported by experimental evidences. Thus, REMAP is a valuable addition to the existing in silico toolbox for drug target identification, drug repurposing, phenotypic screening, and

Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.

Science.gov (United States)

Zhang, Jieru; Ju, Ying; Lu, Huijuan; Xuan, Ping; Zou, Quan

2016-01-01

Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.

Identification and accurate quantification of structurally related peptide impurities in synthetic human C-peptide by liquid chromatography-high resolution mass spectrometry.

Science.gov (United States)

Li, Ming; Josephs, Ralf D; Daireaux, Adeline; Choteau, Tiphaine; Westwood, Steven; Wielgosz, Robert I; Li, Hongmei

2018-06-04

Peptides are an increasingly important group of biomarkers and pharmaceuticals. The accurate purity characterization of peptide calibrators is critical for the development of reference measurement systems for laboratory medicine and quality control of pharmaceuticals. The peptides used for these purposes are increasingly produced through peptide synthesis. Various approaches (for example mass balance, amino acid analysis, qNMR, and nitrogen determination) can be applied to accurately value assign the purity of peptide calibrators. However, all purity assessment approaches require a correction for structurally related peptide impurities in order to avoid biases. Liquid chromatography coupled to high resolution mass spectrometry (LC-hrMS) has become the key technique for the identification and accurate quantification of structurally related peptide impurities in intact peptide calibrator materials. In this study, LC-hrMS-based methods were developed and validated in-house for the identification and quantification of structurally related peptide impurities in a synthetic human C-peptide (hCP) material, which served as a study material for an international comparison looking at the competencies of laboratories to perform peptide purity mass fraction assignments. More than 65 impurities were identified, confirmed, and accurately quantified by using LC-hrMS. The total mass fraction of all structurally related peptide impurities in the hCP study material was estimated to be 83.3 mg/g with an associated expanded uncertainty of 3.0 mg/g (k = 2). The calibration hierarchy concept used for the quantification of individual impurities is described in detail. Graphical abstract ᅟ.

Lung ultrasound accurately detects pneumothorax in a preterm newborn lamb model.

Science.gov (United States)

Blank, Douglas A; Hooper, Stuart B; Binder-Heschl, Corinna; Kluckow, Martin; Gill, Andrew W; LaRosa, Domenic A; Inocencio, Ishmael M; Moxham, Alison; Rodgers, Karyn; Zahra, Valerie A; Davis, Peter G; Polglase, Graeme R

2016-06-01

Pneumothorax is a common emergency affecting extremely preterm. In adult studies, lung ultrasound has performed better than chest x-ray in the diagnosis of pneumothorax. The purpose of this study was to determine the efficacy of lung ultrasound (LUS) examination to detect pneumothorax using a preterm animal model. This was a prospective, observational study using newborn Border-Leicester lambs at gestational age = 126 days (equivalent to gestational age = 26 weeks in humans) receiving mechanical ventilation from birth to 2 h of life. At the conclusion of the experiment, LUS was performed, the lambs were then euthanised and a post-mortem exam was immediately performed. We used previously published ultrasound techniques to identify pneumothorax. Test characteristics of LUS to detect pneumothorax were calculated, using the post-mortem exam as the 'gold standard' test. Nine lambs (18 lungs) were examined. Four lambs had a unilateral pneumothorax, all of which were identified by LUS with no false positives. This was the first study to use post-mortem findings to test the efficacy of LUS to detect pneumothorax in a newborn animal model. Lung ultrasound accurately detected pneumothorax, verified by post-mortem exam, in premature, newborn lambs. © 2016 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

Bacterial identification and subtyping using DNA microarray and DNA sequencing.

Science.gov (United States)

Al-Khaldi, Sufian F; Mossoba, Magdi M; Allard, Marc M; Lienau, E Kurt; Brown, Eric D

2012-01-01

The era of fast and accurate discovery of biological sequence motifs in prokaryotic and eukaryotic cells is here. The co-evolution of direct genome sequencing and DNA microarray strategies not only will identify, isotype, and serotype pathogenic bacteria, but also it will aid in the discovery of new gene functions by detecting gene expressions in different diseases and environmental conditions. Microarray bacterial identification has made great advances in working with pure and mixed bacterial samples. The technological advances have moved beyond bacterial gene expression to include bacterial identification and isotyping. Application of new tools such as mid-infrared chemical imaging improves detection of hybridization in DNA microarrays. The research in this field is promising and future work will reveal the potential of infrared technology in bacterial identification. On the other hand, DNA sequencing by using 454 pyrosequencing is so cost effective that the promise of $1,000 per bacterial genome sequence is becoming a reality. Pyrosequencing technology is a simple to use technique that can produce accurate and quantitative analysis of DNA sequences with a great speed. The deposition of massive amounts of bacterial genomic information in databanks is creating fingerprint phylogenetic analysis that will ultimately replace several technologies such as Pulsed Field Gel Electrophoresis. In this chapter, we will review (1) the use of DNA microarray using fluorescence and infrared imaging detection for identification of pathogenic bacteria, and (2) use of pyrosequencing in DNA cluster analysis to fingerprint bacterial phylogenetic trees.

Accurate Fall Detection in a Top View Privacy Preserving Configuration.

Science.gov (United States)

Ricciuti, Manola; Spinsante, Susanna; Gambi, Ennio

2018-05-29

Fall detection is one of the most investigated themes in the research on assistive solutions for aged people. In particular, a false-alarm-free discrimination between falls and non-falls is indispensable, especially to assist elderly people living alone. Current technological solutions designed to monitor several types of activities in indoor environments can guarantee absolute privacy to the people that decide to rely on them. Devices integrating RGB and depth cameras, such as the Microsoft Kinect, can ensure privacy and anonymity, since the depth information is considered to extract only meaningful information from video streams. In this paper, we propose an accurate fall detection method investigating the depth frames of the human body using a single device in a top-view configuration, with the subjects located under the device inside a room. Features extracted from depth frames train a classifier based on a binary support vector machine learning algorithm. The dataset includes 32 falls and 8 activities considered for comparison, for a total of 800 sequences performed by 20 adults. The system showed an accuracy of 98.6% and only one false positive.

DeepBound: accurate identification of transcript boundaries via deep convolutional neural fields

KAUST Repository

Shao, Mingfu; Ma, Jianzhu; Wang, Sheng

2017-01-01

Motivation: Reconstructing the full- length expressed transcripts (a. k. a. the transcript assembly problem) from the short sequencing reads produced by RNA-seq protocol plays a central role in identifying novel genes and transcripts as well as in studying gene expressions and gene functions. A crucial step in transcript assembly is to accurately determine the splicing junctions and boundaries of the expressed transcripts from the reads alignment. In contrast to the splicing junctions that can be efficiently detected from spliced reads, the problem of identifying boundaries remains open and challenging, due to the fact that the signal related to boundaries is noisy and weak.

DeepBound: accurate identification of transcript boundaries via deep convolutional neural fields

KAUST Repository

Shao, Mingfu

2017-04-20

Motivation: Reconstructing the full- length expressed transcripts (a. k. a. the transcript assembly problem) from the short sequencing reads produced by RNA-seq protocol plays a central role in identifying novel genes and transcripts as well as in studying gene expressions and gene functions. A crucial step in transcript assembly is to accurately determine the splicing junctions and boundaries of the expressed transcripts from the reads alignment. In contrast to the splicing junctions that can be efficiently detected from spliced reads, the problem of identifying boundaries remains open and challenging, due to the fact that the signal related to boundaries is noisy and weak.

Encrypted data stream identification using randomness sparse representation and fuzzy Gaussian mixture model

Science.gov (United States)

Zhang, Hong; Hou, Rui; Yi, Lei; Meng, Juan; Pan, Zhisong; Zhou, Yuhuan

2016-07-01

The accurate identification of encrypted data stream helps to regulate illegal data, detect network attacks and protect users' information. In this paper, a novel encrypted data stream identification algorithm is introduced. The proposed method is based on randomness characteristics of encrypted data stream. We use a l1-norm regularized logistic regression to improve sparse representation of randomness features and Fuzzy Gaussian Mixture Model (FGMM) to improve identification accuracy. Experimental results demonstrate that the method can be adopted as an effective technique for encrypted data stream identification.

Enhanced statistical damage identification using frequency-shift information with tunable piezoelectric transducer circuitry

International Nuclear Information System (INIS)

Zhao, J; Tang, J; Wang, K W

2008-01-01

The frequency-shift-based damage detection method entertains advantages such as global detection capability and easy implementation, but also suffers from drawbacks that include low detection accuracy and sensitivity and the difficulty in identifying damage using a small number of measurable frequencies. Moreover, the damage detection/identification performance is inevitably affected by the uncertainty/variations in the baseline model. In this research, we investigate an enhanced statistical damage identification method using the tunable piezoelectric transducer circuitry. The tunable piezoelectric transducer circuitry can lead to much enriched information on frequency shift (before and after damage occurrence). The circuitry elements, meanwhile, can be directly and accurately measured and thus can be considered uncertainty-free. A statistical damage identification algorithm is formulated which can identify both the mean and variance of the elemental property change. Our analysis indicates that the integration of the tunable piezoelectric transducer circuitry can significantly enhance the robustness of the frequency-shift-based damage identification approach under uncertainty and noise

Identification of a 251 gene expression signature that can accurately detect M. tuberculosis in patients with and without HIV co-infection.

Directory of Open Access Journals (Sweden)

Noor Dawany

Full Text Available BACKGROUND: Co-infection with tuberculosis (TB is the leading cause of death in HIV-infected individuals. However, diagnosis of TB, especially in the presence of an HIV co-infection, can be limiting due to the high inaccuracy associated with the use of conventional diagnostic methods. Here we report a gene signature that can identify a tuberculosis infection in patients co-infected with HIV as well as in the absence of HIV. METHODS: We analyzed global gene expression data from peripheral blood mononuclear cell (PBMC samples of patients that were either mono-infected with HIV or co-infected with HIV/TB and used support vector machines to identify a gene signature that can distinguish between the two classes. We then validated our results using publically available gene expression data from patients mono-infected with TB. RESULTS: Our analysis successfully identified a 251-gene signature that accurately distinguishes patients co-infected with HIV/TB from those infected with HIV only, with an overall accuracy of 81.4% (sensitivity = 76.2%, specificity = 86.4%. Furthermore, we show that our 251-gene signature can also accurately distinguish patients with active TB in the absence of an HIV infection from both patients with a latent TB infection and healthy controls (88.9-94.7% accuracy; 69.2-90% sensitivity and 90.3-100% specificity. We also demonstrate that the expression levels of the 251-gene signature diminish as a correlate of the length of TB treatment. CONCLUSIONS: A 251-gene signature is described to (a detect TB in the presence or absence of an HIV co-infection, and (b assess response to treatment following anti-TB therapy.

Enhanced Isotopic Ratio Outlier Analysis (IROA Peak Detection and Identification with Ultra-High Resolution GC-Orbitrap/MS: Potential Application for Investigation of Model Organism Metabolomes

Directory of Open Access Journals (Sweden)

Yunping Qiu

2018-01-01

Full Text Available Identifying non-annotated peaks may have a significant impact on the understanding of biological systems. In silico methodologies have focused on ESI LC/MS/MS for identifying non-annotated MS peaks. In this study, we employed in silico methodology to develop an Isotopic Ratio Outlier Analysis (IROA workflow using enhanced mass spectrometric data acquired with the ultra-high resolution GC-Orbitrap/MS to determine the identity of non-annotated metabolites. The higher resolution of the GC-Orbitrap/MS, together with its wide dynamic range, resulted in more IROA peak pairs detected, and increased reliability of chemical formulae generation (CFG. IROA uses two different 13C-enriched carbon sources (randomized 95% 12C and 95% 13C to produce mirror image isotopologue pairs, whose mass difference reveals the carbon chain length (n, which aids in the identification of endogenous metabolites. Accurate m/z, n, and derivatization information are obtained from our GC/MS workflow for unknown metabolite identification, and aids in silico methodologies for identifying isomeric and non-annotated metabolites. We were able to mine more mass spectral information using the same Saccharomyces cerevisiae growth protocol (Qiu et al. Anal. Chem 2016 with the ultra-high resolution GC-Orbitrap/MS, using 10% ammonia in methane as the CI reagent gas. We identified 244 IROA peaks pairs, which significantly increased IROA detection capability compared with our previous report (126 IROA peak pairs using a GC-TOF/MS machine. For 55 selected metabolites identified from matched IROA CI and EI spectra, using the GC-Orbitrap/MS vs. GC-TOF/MS, the average mass deviation for GC-Orbitrap/MS was 1.48 ppm, however, the average mass deviation was 32.2 ppm for the GC-TOF/MS machine. In summary, the higher resolution and wider dynamic range of the GC-Orbitrap/MS enabled more accurate CFG, and the coupling of accurate mass GC/MS IROA methodology with in silico fragmentation has great

Enhanced Isotopic Ratio Outlier Analysis (IROA) Peak Detection and Identification with Ultra-High Resolution GC-Orbitrap/MS: Potential Application for Investigation of Model Organism Metabolomes.

Science.gov (United States)

Qiu, Yunping; Moir, Robyn D; Willis, Ian M; Seethapathy, Suresh; Biniakewitz, Robert C; Kurland, Irwin J

2018-01-18

Identifying non-annotated peaks may have a significant impact on the understanding of biological systems. In silico methodologies have focused on ESI LC/MS/MS for identifying non-annotated MS peaks. In this study, we employed in silico methodology to develop an Isotopic Ratio Outlier Analysis (IROA) workflow using enhanced mass spectrometric data acquired with the ultra-high resolution GC-Orbitrap/MS to determine the identity of non-annotated metabolites. The higher resolution of the GC-Orbitrap/MS, together with its wide dynamic range, resulted in more IROA peak pairs detected, and increased reliability of chemical formulae generation (CFG). IROA uses two different 13 C-enriched carbon sources (randomized 95% 12 C and 95% 13 C) to produce mirror image isotopologue pairs, whose mass difference reveals the carbon chain length (n), which aids in the identification of endogenous metabolites. Accurate m/z, n, and derivatization information are obtained from our GC/MS workflow for unknown metabolite identification, and aids in silico methodologies for identifying isomeric and non-annotated metabolites. We were able to mine more mass spectral information using the same Saccharomyces cerevisiae growth protocol (Qiu et al. Anal. Chem 2016) with the ultra-high resolution GC-Orbitrap/MS, using 10% ammonia in methane as the CI reagent gas. We identified 244 IROA peaks pairs, which significantly increased IROA detection capability compared with our previous report (126 IROA peak pairs using a GC-TOF/MS machine). For 55 selected metabolites identified from matched IROA CI and EI spectra, using the GC-Orbitrap/MS vs. GC-TOF/MS, the average mass deviation for GC-Orbitrap/MS was 1.48 ppm, however, the average mass deviation was 32.2 ppm for the GC-TOF/MS machine. In summary, the higher resolution and wider dynamic range of the GC-Orbitrap/MS enabled more accurate CFG, and the coupling of accurate mass GC/MS IROA methodology with in silico fragmentation has great potential in

Identification of mycobacterium tuberculosis in sputum smear slide using automatic scanning microscope

Science.gov (United States)

Rulaningtyas, Riries; Suksmono, Andriyan B.; Mengko, Tati L. R.; Saptawati, Putri

2015-04-01

Sputum smear observation has an important role in tuberculosis (TB) disease diagnosis, because it needs accurate identification to avoid high errors diagnosis. In development countries, sputum smear slide observation is commonly done with conventional light microscope from Ziehl-Neelsen stained tissue and it doesn't need high cost to maintain the microscope. The clinicians do manual screening process for sputum smear slide which is time consuming and needs highly training to detect the presence of TB bacilli (mycobacterium tuberculosis) accurately, especially for negative slide and slide with less number of TB bacilli. For helping the clinicians, we propose automatic scanning microscope with automatic identification of TB bacilli. The designed system modified the field movement of light microscope with stepper motor which was controlled by microcontroller. Every sputum smear field was captured by camera. After that some image processing techniques were done for the sputum smear images. The color threshold was used for background subtraction with hue canal in HSV color space. Sobel edge detection algorithm was used for TB bacilli image segmentation. We used feature extraction based on shape for bacilli analyzing and then neural network classified TB bacilli or not. The results indicated identification of TB bacilli that we have done worked well and detected TB bacilli accurately in sputum smear slide with normal staining, but not worked well in over staining and less staining tissue slide. However, overall the designed system can help the clinicians in sputum smear observation becomes more easily.

Detection system for the identification of heavy ions

International Nuclear Information System (INIS)

Abriola, Daniel H.; Arazi, Andres; Achterberg, Erhard; Capurro, Oscar A.; Fernandez Niello, Jorge O.; Ferrero, Armando M. J.; Liberman, Rosa G.; Marti, Guillermo V.; Pacheco, Alberto J.; Ramirez, Marcelo C.; Testoni, Jorge E.

1999-01-01

The TANDAR laboratory has a magnetic spectrometer as one of its detection facilities. This device allows the separation of incident particles according to the relation between their lineal momentum and their charge state. To complete this identification there are two alternatives: 1) A system of three detectors consisting of a multiwire detector, an ionization chamber and scintillators; 2) A segmented anode ionization chamber. (author)

Re-Ranking Sequencing Variants in the Post-GWAS Era for Accurate Causal Variant Identification

Science.gov (United States)

Faye, Laura L.; Machiela, Mitchell J.; Kraft, Peter; Bull, Shelley B.; Sun, Lei

2013-01-01

Next generation sequencing has dramatically increased our ability to localize disease-causing variants by providing base-pair level information at costs increasingly feasible for the large sample sizes required to detect complex-trait associations. Yet, identification of causal variants within an established region of association remains a challenge. Counter-intuitively, certain factors that increase power to detect an associated region can decrease power to localize the causal variant. First, combining GWAS with imputation or low coverage sequencing to achieve the large sample sizes required for high power can have the unintended effect of producing differential genotyping error among SNPs. This tends to bias the relative evidence for association toward better genotyped SNPs. Second, re-use of GWAS data for fine-mapping exploits previous findings to ensure genome-wide significance in GWAS-associated regions. However, using GWAS findings to inform fine-mapping analysis can bias evidence away from the causal SNP toward the tag SNP and SNPs in high LD with the tag. Together these factors can reduce power to localize the causal SNP by more than half. Other strategies commonly employed to increase power to detect association, namely increasing sample size and using higher density genotyping arrays, can, in certain common scenarios, actually exacerbate these effects and further decrease power to localize causal variants. We develop a re-ranking procedure that accounts for these adverse effects and substantially improves the accuracy of causal SNP identification, often doubling the probability that the causal SNP is top-ranked. Application to the NCI BPC3 aggressive prostate cancer GWAS with imputation meta-analysis identified a new top SNP at 2 of 3 associated loci and several additional possible causal SNPs at these loci that may have otherwise been overlooked. This method is simple to implement using R scripts provided on the author's website. PMID:23950724

Ship Detection in Optical Remote Sensing Images Based on Wavelet Transform and Multi-Level False Alarm Identification

Directory of Open Access Journals (Sweden)

Fang Xu

2017-09-01

Full Text Available Ship detection by Unmanned Airborne Vehicles (UAVs and satellites plays an important role in a spectrum of related military and civil applications. To improve the detection efficiency, accuracy, and speed, a novel ship detection method from coarse to fine is presented. Ship targets are viewed as uncommon regions in the sea background caused by the differences in colors, textures, shapes, or other factors. Inspired by this fact, a global saliency model is constructed based on high-frequency coefficients of the multi-scale and multi-direction wavelet decomposition, which can characterize different feature information from edge to texture of the input image. To further reduce the false alarms, a new and effective multi-level discrimination method is designed based on the improved entropy and pixel distribution, which is robust against the interferences introduced by islands, coastlines, clouds, and shadows. The experimental results on optical remote sensing images validate that the presented saliency model outperforms the comparative models in terms of the area under the receiver operating characteristic curves core and the accuracy in the images with different sizes. After the target identification, the locations and the number of the ships in various sizes and colors can be detected accurately and fast with high robustness.

Detection and Identification of Probiotic Lactobacillus plantarum Strains by Multiplex PCR Using RAPD-Derived Primers.

Science.gov (United States)

Galanis, Alex; Kourkoutas, Yiannis; Tassou, Chrysoula C; Chorianopoulos, Nikos

2015-10-22

Lactobacillus plantarum 2035 and Lactobacillus plantarum ACA-DC 2640 are two lactic acid bacteria (LAB) strains that have been isolated from Feta cheese. Both display significant potential for the production of novel probiotic food products. The aim of the present study was the development of an accurate and efficient method for the molecular detection and identification of the above strains in a single reaction. A multiplex PCR assay was designed for each strain, based on specific primers derived from Random Amplified Polymorphic DNA (RAPD) Sequenced Characterized Amplified Region (SCAR) analysis. The specificity of the assay was tested with a total of 23 different LAB strains, for L. plantarum 2035 and L. plantarum ACA-DC 2640. The multiplex PCR assay was also successfully applied for the detection of the above cultures in yogurt samples prepared in our lab. The proposed methodology may be applied for monitoring the presence of these strains in food products, thus evaluating their probiotic character. Moreover, our strategy may be adapted for other novel LAB strains with probiotic potential, thus providing a powerful tool for molecular discrimination that could be invaluable to the food industry.

Detection and Identification of Probiotic Lactobacillus plantarum Strains by Multiplex PCR Using RAPD-Derived Primers

Directory of Open Access Journals (Sweden)

Alex Galanis

2015-10-01

Full Text Available Lactobacillus plantarum 2035 and Lactobacillus plantarum ACA-DC 2640 are two lactic acid bacteria (LAB strains that have been isolated from Feta cheese. Both display significant potential for the production of novel probiotic food products. The aim of the present study was the development of an accurate and efficient method for the molecular detection and identification of the above strains in a single reaction. A multiplex PCR assay was designed for each strain, based on specific primers derived from Random Amplified Polymorphic DNA (RAPD Sequenced Characterized Amplified Region (SCAR analysis. The specificity of the assay was tested with a total of 23 different LAB strains, for L. plantarum 2035 and L. plantarum ACA-DC 2640. The multiplex PCR assay was also successfully applied for the detection of the above cultures in yogurt samples prepared in our lab. The proposed methodology may be applied for monitoring the presence of these strains in food products, thus evaluating their probiotic character. Moreover, our strategy may be adapted for other novel LAB strains with probiotic potential, thus providing a powerful tool for molecular discrimination that could be invaluable to the food industry.

Confidence in word detection predicts word identification: implications for an unconscious perception paradigm.

Science.gov (United States)

Haase, S J; Fisk, G

2001-01-01

The present experiments extend the scope of the independent observation model based on signal detection theory (Macmillan & Creelman, 1991) to complex (word) stimulus sets. In the first experiment, the model predicts the relationship between uncertain detection and subsequent correct identification, thereby providing an alternative interpretation to a phenomenon often described as unconscious perception. Our second experiment used an exclusion task (Jacoby, Toth, & Yonelinas, 1993), which, according to theories of unconscious perception, should show qualitative differences in performance based on stimulus detection accuracy and provide a relative measure of conscious versus unconscious influences (Merikle, Joordens, & Stoltz, 1995). Exclusion performance was also explained by the model, suggesting that undetected words did not unconsciously influence identification responses.

Detection and Identification of People at a Critical Infrastructure Facilities of Trafic Buildings

Directory of Open Access Journals (Sweden)

Rastislav PIRNÍK

2014-12-01

Full Text Available This paper focuses on identification of persons entering objects of crucial infrastructure and subsequent detection of movement in parts of objects. It explains some of the technologies and approaches to processing specific image information within existing building apparatus. The article describes the proposed algorithm for detection of persons. It brings a fresh approach to detection of moving objects (groups of persons involved in enclosed areas focusing on securing freely accessible places in buildings. Based on the designed algorithm of identification with presupposed utilisation of 3D application, motion trajectory of persons in delimited space can be automatically identified. The application was created in opensource software tool using the OpenCV library.

Target Detection, Identification, and Marksmanship Under Various Types of Physiological Strain

National Research Council Canada - National Science Library

Tikuisis, Peter

2006-01-01

.... Using a small arms trainer (SAT), target detection, identification, and engagement were tested under a variety of conditions including heat and cold exposure, fatiguing exercise, and sleep deprivation, with caffeine intervention...

Reliability of the MicroScan WalkAway PC21 panel in identifying and detecting oxacillin resistance in clinical coagulase-negative staphylococci strains.

Science.gov (United States)

Olendzki, A N; Barros, E M; Laport, M S; Dos Santos, K R N; Giambiagi-Demarval, M

2014-01-01

The purpose of this study was to determine the reliability of the MicroScan WalkAway PosCombo21 (PC21) system for the identification of coagulase-negative staphylococci (CNS) strains and the detection of oxacillin resistance. Using molecular and phenotypic methods, 196 clinical strains were evaluated. The automated system demonstrated 100 % reliability for the identification of the clinical strains Staphylococcus haemolyticus, Staphylococcus hominis and Staphylococcus cohnii; 98.03 % reliability for the identification of Staphylococcus epidermidis; 70 % reliability for the identification of Staphylococcus lugdunensis; 40 % reliability for the identification of Staphylococcus warneri; and 28.57 % reliability for the identification of Staphylococcus capitis, but no reliability for the identification of Staphylococcus auricularis, Staphylococcus simulans and Staphylococcus xylosus. We concluded that the automated system provides accurate results for the more common CNS species but often fails to accurately identify less prevalent species. For the detection of oxacillin resistance, the automated system showed 100 % specificity and 90.22 % sensitivity. Thus, the PC21 panel detects oxacillin-resistant strains, but is limited by the heteroresistance that is observed when using most phenotypic methods.

Multistage audiovisual integration of speech: dissociating identification and detection

DEFF Research Database (Denmark)

Eskelund, Kasper; Tuomainen, Jyrki; Andersen, Tobias

2011-01-01

Speech perception integrates auditory and visual information. This is evidenced by the McGurk illusion where seeing the talking face influences the auditory phonetic percept and by the audiovisual detection advantage where seeing the talking face influences the detectability of the acoustic speech...... signal. Here we show that identification of phonetic content and detection can be dissociated as speech-specific and non-specific audiovisual integration effects. To this end, we employed synthetically modified stimuli, sine wave speech (SWS), which is an impoverished speech signal that only observers...... informed of its speech-like nature recognize as speech. While the McGurk illusion only occurred for informed observers the audiovisual detection advantage occurred for naïve observers as well. This finding supports a multi-stage account of audiovisual integration of speech in which the many attributes...

Effect of Various Environmental Stressors on Target Detection, Identification, and Marksmanship

National Research Council Canada - National Science Library

Tikuisis, Peter; Keefe, Allan A

2007-01-01

.... Using a small arms trainer (SAT), the detection, identification, and engagement of targets were tested under a variety of environmentally stressful conditions including heat and cold exposure, noise, fatiguing exercise, and sleep...

PCR detection and identification of oral streptococci in saliva samples using gtf genes.

Science.gov (United States)

Hoshino, Tomonori; Kawaguchi, Mamoru; Shimizu, Noriko; Hoshino, Naoko; Ooshima, Takashi; Fujiwara, Taku

2004-03-01

Oral streptococci are major constituents of dental plaque, and their prevalence is implicated in various pathologies. Therefore, accurate identification of oral streptococci would be valuable for studies of cariogenic plaque and for diagnostic use in infective endocarditis. Many oral streptococci possess glucosyltransferase enzymes that synthesize glucan, which is an obligate component of dental plaque. We established a rapid and precise method to identify oral streptococci by PCR using the species-specific region from the glucosyltransferase gene. With the species-specific primers, Streptococcus mutans, S. sobrinus, S. salivarius, S. sanguinis, S. oralis, and S. gordonii could be successfully distinguished. Further, we developed a simple method to extract the bacterial DNA from saliva. Using the resultant DNA as a template, the proposed PCR detection was performed. Their distribution was in accord with results of conventional biochemical tests. These findings indicate that the present PCR method is useful for the analysis of oral streptococci and can be successfully used in clinical applications to identify pathogenic bacteria associated with oral infectious disease and/or endocarditis.

Rapid Detection and Identification of Human Hookworm Infections through High Resolution Melting (HRM) Analysis

Science.gov (United States)

Ngui, Romano; Lim, Yvonne A. L.; Chua, Kek Heng

2012-01-01

Background Hookworm infections are still endemic in low and middle income tropical countries with greater impact on the socioeconomic and public health of the bottom billion of the world's poorest people. In this study, a real-time polymerase chain reaction (PCR) coupled with high resolution melting-curve (HRM) analysis was evaluated for an accurate, rapid and sensitive tool for species identification focusing on the five human hookworm species. Methods Real-time PCR coupled with HRM analysis targeting the second internal transcribed spacer (ITS-2) of nuclear ribosomal DNA as the genetic marker was used to identify and distinguish hookworm species in human samples. Unique and distinct characteristics of HRM patterns were produced for each of the five hookworm species. The melting curves were characterized by peaks of 79.24±0.05°C and 83.00±0.04°C for Necator americanus, 79.12±0.10°C for Ancylostoma duodenale, 79.40±0.10°C for Ancylostoma ceylanicum, 79.63±0.05°C for Ancylostoma caninum and 79.70±0.14°C for Ancylostoma braziliense. An evaluation of the method's sensitivity and specificity revealed that this assay was able to detect as low as 0.01 ng/µl hookworm DNA and amplification was only recorded for hookworm positive samples. Conclusion The HRM assay developed in this study is a rapid and straightforward method for the diagnosis, identification and discrimination of five human hookworms. This assay is simple compared to other probe-based genotyping methods as it does not require multiplexing, DNA sequencing or post-PCR processing. Therefore, this method offers a new alternative for rapid detection of human hookworm species. PMID:22844538

Rapid detection and identification of human hookworm infections through high resolution melting (HRM analysis.

Directory of Open Access Journals (Sweden)

Romano Ngui

Full Text Available BACKGROUND: Hookworm infections are still endemic in low and middle income tropical countries with greater impact on the socioeconomic and public health of the bottom billion of the world's poorest people. In this study, a real-time polymerase chain reaction (PCR coupled with high resolution melting-curve (HRM analysis was evaluated for an accurate, rapid and sensitive tool for species identification focusing on the five human hookworm species. METHODS: Real-time PCR coupled with HRM analysis targeting the second internal transcribed spacer (ITS-2 of nuclear ribosomal DNA as the genetic marker was used to identify and distinguish hookworm species in human samples. Unique and distinct characteristics of HRM patterns were produced for each of the five hookworm species. The melting curves were characterized by peaks of 79.24±0.05°C and 83.00±0.04°C for Necator americanus, 79.12±0.10°C for Ancylostoma duodenale, 79.40±0.10°C for Ancylostoma ceylanicum, 79.63±0.05°C for Ancylostoma caninum and 79.70±0.14°C for Ancylostoma braziliense. An evaluation of the method's sensitivity and specificity revealed that this assay was able to detect as low as 0.01 ng/µl hookworm DNA and amplification was only recorded for hookworm positive samples. CONCLUSION: The HRM assay developed in this study is a rapid and straightforward method for the diagnosis, identification and discrimination of five human hookworms. This assay is simple compared to other probe-based genotyping methods as it does not require multiplexing, DNA sequencing or post-PCR processing. Therefore, this method offers a new alternative for rapid detection of human hookworm species.

Mass and charge identification of fragments detected with the Chimera Silicon-CsI(Tl) telescopes

Energy Technology Data Exchange (ETDEWEB)

Le Neindre, N.; Alderighi, M.; Anzalone, A.; Barna, R.; Bartolucci, M.; Berceanu, I.; Borderie, B.; Bougault, R.; Bruno, M.; Cardella, G.; Cavallaro, S.; D' Agostino, M. E-mail: dagostino@bo.infn.it; Dayras, R.; De Filippo, E.; De Pasquale, D.; Geraci, E.; Giustolisi, F.; Grzeszczuk, A.; Guazzoni, P.; Guinet, D.; Iacono-Manno, M.; Italiano, A.; Kowalski, S.; Lanchais, A.; Lanzano, G.; Lanzalone, G.; Li, S.; Lo Nigro, S.; Maiolino, C.; Manfredi, G.; Moisa, D.; Pagano, A.; Papa, M.; Paduszynski, T.; Petrovici, M.; Piasecki, E.; Pirrone, S.; Politi, G.; Pop, A.; Porto, F.; Rivet, M.F.; Rosato, E.; Russo, S.; Sambataro, S.; Sechi, G.; Simion, V.; Sperduto, M.L.; Steckmeyer, J.C.; Sutera, C.; Trifiro, A.; Tassan-Got, L.; Trimarchi, M.; Vannini, G.; Vigilante, M.; Wilczynski, J.; Wu, H.; Xiao, Z.; Zetta, L.; Zipper, W

2002-09-01

Mass and charge identification of charged products detected with Silicon-CsI(Tl) telescopes of the Chimera apparatus are presented. An identification function, based on the Bethe-Bloch formula, is used to fit empirical correlations between {delta}E and E ADC readings, in order to determine, event by event, the atomic and mass numbers of the detected charged reaction products prior to energy calibration.

EpHLA software: a timesaving and accurate tool for improving identification of acceptable mismatches for clinical purposes.

Science.gov (United States)

Filho, Herton Luiz Alves Sales; da Mata Sousa, Luiz Claudio Demes; von Glehn, Cristina de Queiroz Carrascosa; da Silva, Adalberto Socorro; dos Santos Neto, Pedro de Alcântara; do Nascimento, Ferraz; de Castro, Adail Fonseca; do Nascimento, Liliane Machado; Kneib, Carolina; Bianchi Cazarote, Helena; Mayumi Kitamura, Daniele; Torres, Juliane Roberta Dias; da Cruz Lopes, Laiane; Barros, Aryela Loureiro; da Silva Edlin, Evelin Nildiane; de Moura, Fernanda Sá Leal; Watanabe, Janine Midori Figueiredo; do Monte, Semiramis Jamil Hadad

2012-06-01

The HLAMatchmaker algorithm, which allows the identification of “safe” acceptable mismatches (AMMs) for recipients of solid organ and cell allografts, is rarely used in part due to the difficulty in using it in the current Excel format. The automation of this algorithm may universalize its use to benefit the allocation of allografts. Recently, we have developed a new software called EpHLA, which is the first computer program automating the use of the HLAMatchmaker algorithm. Herein, we present the experimental validation of the EpHLA program by showing the time efficiency and the quality of operation. The same results, obtained by a single antigen bead assay with sera from 10 sensitized patients waiting for kidney transplants, were analyzed either by conventional HLAMatchmaker or by automated EpHLA method. Users testing these two methods were asked to record: (i) time required for completion of the analysis (in minutes); (ii) number of eplets obtained for class I and class II HLA molecules; (iii) categorization of eplets as reactive or non-reactive based on the MFI cutoff value; and (iv) determination of AMMs based on eplets' reactivities. We showed that although both methods had similar accuracy, the automated EpHLA method was over 8 times faster in comparison to the conventional HLAMatchmaker method. In particular the EpHLA software was faster and more reliable but equally accurate as the conventional method to define AMMs for allografts. The EpHLA software is an accurate and quick method for the identification of AMMs and thus it may be a very useful tool in the decision-making process of organ allocation for highly sensitized patients as well as in many other applications.

Aircraft Abnormal Conditions Detection, Identification, and Evaluation Using Innate and Adaptive Immune Systems Interaction

Science.gov (United States)

Al Azzawi, Dia

Abnormal flight conditions play a major role in aircraft accidents frequently causing loss of control. To ensure aircraft operation safety in all situations, intelligent system monitoring and adaptation must rely on accurately detecting the presence of abnormal conditions as soon as they take place, identifying their root cause(s), estimating their nature and severity, and predicting their impact on the flight envelope. Due to the complexity and multidimensionality of the aircraft system under abnormal conditions, these requirements are extremely difficult to satisfy using existing analytical and/or statistical approaches. Moreover, current methodologies have addressed only isolated classes of abnormal conditions and a reduced number of aircraft dynamic parameters within a limited region of the flight envelope. This research effort aims at developing an integrated and comprehensive framework for the aircraft abnormal conditions detection, identification, and evaluation based on the artificial immune systems paradigm, which has the capability to address the complexity and multidimensionality issues related to aircraft systems. Within the proposed framework, a novel algorithm was developed for the abnormal conditions detection problem and extended to the abnormal conditions identification and evaluation. The algorithm and its extensions were inspired from the functionality of the biological dendritic cells (an important part of the innate immune system) and their interaction with the different components of the adaptive immune system. Immunity-based methodologies for re-assessing the flight envelope at post-failure and predicting the impact of the abnormal conditions on the performance and handling qualities are also proposed and investigated in this study. The generality of the approach makes it applicable to any system. Data for artificial immune system development were collected from flight tests of a supersonic research aircraft within a motion-based flight

Feasibility of Trace Alcohol Congener Detection and Identification Using Laser-Induced Breakdown Spectroscopy

International Nuclear Information System (INIS)

Zhang Jialiang; Wang Shangmin; Zhao Lixian; Liu Liying; Wang Dezhen

2014-01-01

In this paper, a feasible scheme is reported for the detection and identification of trace alcohol congeners that have identical elemental composition using laser-induced breakdown spectroscopy (LIBS). In the scheme, an intensive pulsed laser is used to break down trace alcohol samples and the optical emission spectra of the induced plasma are collected for the detection and identification of alcohol molecules. In order to prepare trace alcohol samples, pure ethanol or methanol is bubbled by argon carrier gas and then mixed into matrix gases. The key issue for the scheme is to constitute indices from the LIBS data of the alcohol samples. Two indices are found to be suitable for alcohol detection and identification. One is the emission intensity ratio (denoted as H/C) of the hydrogen line (653.3 nm) to the carbon line (247.9 nm) for identification and the other is the ratio of the carbon line (as C/Ar) or the hydrogen line (as H/Ar) to the argon lines (866.7 nm) for quantitative detection. The calibration experiment result shows that the index H/C is specific for alcohol congeners while almost being independent of alcohol concentration. In detail, the H/C keeps a specific constant of 34 and 23 respectively for ethanol and methanol. In the meanwhile, the C/Ar and H/Ar indices respond almost linearly to the alcohol concentration below 1300 ppm, and are therefore competent for concentration measurement. With the indices, trace alcohol concentration measurement achieves a limit of 140 ppm using a laser pulse energy of 300 mJ. (plasma technology)

Detection and identification of Staphylococcus aureus in raw milk by ...

African Journals Online (AJOL)

STORAGESEVER

2010-04-12

Apr 12, 2010 ... detection and identification of S. aureus in raw milk demonstrated high sensitivity and specificity. Key words: Microarray .... sterile after screening for S. aureus contamination according to the procedure described by Wang ... methods, the microarray method is high throughput, specific, and sensitive and also ...

The Performance of the Four Anaerobic Blood Culture Bottles BacT/ALERT-FN, -FN Plus, BACTEC-Plus and -Lytic in Detection of Anaerobic Bacteria and Identification by Direct MALDI-TOF MS.

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Mohammed Almuhayawi

Full Text Available Detection and identification of anaerobic bacteria in blood cultures (BC is a well-recognized challenge in clinical microbiology. We studied 100 clinical anaerobic BC isolates to evaluate the performance of BacT/ALERT-FN, -FN Plus (BioMérieux, BACTEC-Plus and -Lytic (Becton Dickinson BioSciences BC bottles in detection and time to detection (TTD of anaerobic bacteria. BACTEC Lytic had higher detection rate (94/100, 94% than BacT/ALERT FN Plus (80/100, 80% (p<0.01 in the studied material. There was no significant difference in detection of anaerobic bacteria among the remaining bottle types. The 67 anaerobic bacteria that signalled positive in all four bottle types were analyzed to compare the time to detection (TTD and isolates were directly identified by MALDI-TOF MS. There was a significant difference in TTD among the four bottle types (p<0.0001. The shortest median TTD was 18 h in BACTEC Lytic followed by BacT/ALERT FN (23.5 h, BACTEC Plus (27 h and finally BacT/ALERT FN Plus (38 h bottles. In contrast, MALDI-TOF MS performed similarly in all bottle types with accurate identification in 51/67 (76% BacT/ALERT FN, 51/67 (76% BacT/ALERT FN Plus, 53/67 (79% BACTEC Plus and 50/67 (75% BACTEC Lytic bottles. In conclusion, BACTEC Lytic bottles have significantly better detection rates and shorter TTD compared to the three other bottle types. The anaerobic BC bottles are equally suitable for direct MALDI-TOF MS for rapid and reliable identification of common anaerobic bacteria. Further clinical studies are warranted to investigate the performance of anaerobic BC bottles in detection of anaerobic bacteria and identification by direct MALDI-TOF MS.

Color-SIFT model: a robust and an accurate shot boundary detection algorithm

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Sharmila Kumari, M.; Shekar, B. H.

2010-02-01

In this paper, a new technique called color-SIFT model is devised for shot boundary detection. Unlike scale invariant feature transform model that uses only grayscale information and misses important visual information regarding color, here we have adopted different color planes to extract keypoints which are subsequently used to detect shot boundaries. The basic SIFT model has four stages namely scale-space peak selection, keypoint localization, orientation assignment and keypoint descriptor and all these four stages were employed to extract key descriptors in each color plane. The proposed model works on three different color planes and a fusion has been made to take a decision on number of keypoint matches for shot boundary identification and hence is different from the color global scale invariant feature transform that works on quantized images. In addition, the proposed algorithm possess invariance to linear transformation and robust to occlusion and noisy environment. Experiments have been conducted on the standard TRECVID video database to reveal the performance of the proposed model.

Detection and Identification of Arcobacter species in Poultry in Assiut Governorate, Upper Egypt

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Ahmed K. Hassan

2017-04-01

Full Text Available This work aimed to detect, identify and study the epidemiology of Arcobacter species in avian species in Upper Egypt. A total 600 samples, including cloacal swabs and intestinal samples were collected from chickens, turkeys and ducks in Assiut Governorate in Upper Egypt. Using conventional phenotypic methods for isolation and identification, Arcobacter species could be isolated and identified with percentage 25.5% in chickens, 9.5% in turkeys and 14% in ducks. Sixteen randomly selected phenotypically identified Arcobacter species isolates were confirmed using one step multiplex PCR assay. In conclusion, Arcobacter species could be detected and identified from various avian species with variable incidence. Conventional phenotypic methods for detection and differentiation of Arcobacter species are often hampered by many limitations, while molecular methods, and PCR, in particular can provide a sensitive and rapid alternative method for detection and identification of Arcobacter species in different domestic poultry species.

Tissue resonance interaction accurately detects colon lesions: A double-blind pilot study.

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Dore, Maria P; Tufano, Marcello O; Pes, Giovanni M; Cuccu, Marianna; Farina, Valentina; Manca, Alessandra; Graham, David Y

2015-07-07

To investigated the performance of the tissue resonance interaction method (TRIM) for the non-invasive detection of colon lesions. We performed a prospective single-center blinded pilot study of consecutive adults undergoing colonoscopy at the University Hospital in Sassari, Italy. Before patients underwent colonoscopy, they were examined by the TRIMprobe which detects differences in electromagnetic properties between pathological and normal tissues. All patients had completed the polyethylene glycol-containing bowel prep for the colonoscopy procedure before being screened. During the procedure the subjects remained fully dressed. A hand-held probe was moved over the abdomen and variations in electromagnetic signals were recorded for 3 spectral lines (462-465 MHz, 930 MHz, and 1395 MHz). A single investigator, blind to any clinical information, performed the test using the TRIMprob system. Abnormal signals were identified and recorded as malignant or benign (adenoma or hyperplastic polyps). Findings were compared with those from colonoscopy with histologic confirmation. Statistical analysis was performed by χ(2) test. A total of 305 consecutive patients fulfilling the inclusion criteria were enrolled over a period of 12 months. The most frequent indication for colonoscopy was abdominal pain (33%). The TRIMprob was well accepted by all patients; none spontaneously complained about the procedure, and no adverse effects were observed. TRIM proved inaccurate for polyp detection in patients with inflammatory bowel disease (IBD) and they were excluded leaving 281 subjects (mean age 59 ± 13 years; 107 males). The TRIM detected and accurately characterized all 12 adenocarcinomas and 135/137 polyps (98.5%) including 64 adenomatous (100%) found. The method identified cancers and polyps with 98.7% sensitivity, 96.2% specificity, and 97.5% diagnostic accuracy, compared to colonoscopy and histology analyses. The positive predictive value was 96.7% and the negative predictive

Accurate SERS detection of malachite green in aquatic products on basis of graphene wrapped flexible sensor.

Science.gov (United States)

Ouyang, Lei; Yao, Ling; Zhou, Taohong; Zhu, Lihua

2018-10-16

Malachite Green (MG) is a banned pesticide for aquaculture products. As a required inspection item, its fast and accurate determination before the products' accessing market is very important. Surface enhanced Raman scattering (SERS) is a promising tool for MG sensing, but it requires the overcoming of several problems such as fairly poor sensitivity and reproducibility, especially laser induced chemical conversion and photo-bleaching during SERS observation. By using a graphene wrapped Ag array based flexible membrane sensor, a modified SERS strategy was proposed for the sensitive and accurate detection of MG. The graphene layer functioned as an inert protector for impeding chemical transferring of the bioproduct Leucomalachite Green (LMG) to MG during the SERS detection, and as a heat transmitter for preventing laser induced photo-bleaching, which enables the separate detection of MG and LMG in fish extracts. The combination of the Ag array and the graphene cover also produced plentiful densely and uniformly distributed hot spots, leading to analytical enhancement factor up to 3.9 × 10 8 and excellent reproducibility (relative standard deviation low to 5.8% for 70 runs). The proposed method was easily used for MG detection with limit of detection (LOD) as low as 2.7 × 10 -11  mol L -1 . The flexibility of the sensor enable it have a merit for in-field fast detection of MG residues on the scale of a living fish through a surface extraction and paste transferring manner. The developed strategy was successfully applied in the analysis of real samples, showing good prospects for both the fast inspection and quantitative detection of MG. Copyright © 2018 Elsevier B.V. All rights reserved.

Multi-stage identification scheme for detecting damage in structures under ambient excitations

International Nuclear Information System (INIS)

Bao, Chunxiao; Li, Zhong-Xian; Hao, Hong

2013-01-01

Structural damage identification methods are critical to the successful application of structural health monitoring (SHM) systems to civil engineering structures. The dynamic response of civil engineering structures is usually characterized by high nonlinearity and non-stationarity. Accordingly, an improved Hilbert–Huang transform (HHT) method which is adaptive, output-only and applicable to system identification of in-service structures under ambient excitations is developed in this study. Based on this method, a multi-stage damage detection scheme including the detection of damage occurrence, damage existence, damage location and the estimation of damage severity is developed. In this scheme, the improved HHT method is used to analyse the structural acceleration response, the obtained instantaneous frequency detects the instant of damage occurrence, the instantaneous phase is sensitive to minor damage and provides reliable damage indication, and the damage indicator developed based on statistical analysis of the Hilbert marginal spectrum detects damage locations. Finally, the response sampled at the detected damage location is continuously analysed to estimate the damage severity. Numerical and experimental studies of frame structures under ambient excitations are performed. The results demonstrate that this scheme accomplishes the above damage detection functions within one flow. It is robust, time efficient, simply implemented and applicable to the real-time SHM of in-service structures. (paper)

Multistage audiovisual integration of speech: dissociating identification and detection.

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Eskelund, Kasper; Tuomainen, Jyrki; Andersen, Tobias S

2011-02-01

Speech perception integrates auditory and visual information. This is evidenced by the McGurk illusion where seeing the talking face influences the auditory phonetic percept and by the audiovisual detection advantage where seeing the talking face influences the detectability of the acoustic speech signal. Here, we show that identification of phonetic content and detection can be dissociated as speech-specific and non-specific audiovisual integration effects. To this end, we employed synthetically modified stimuli, sine wave speech (SWS), which is an impoverished speech signal that only observers informed of its speech-like nature recognize as speech. While the McGurk illusion only occurred for informed observers, the audiovisual detection advantage occurred for naïve observers as well. This finding supports a multistage account of audiovisual integration of speech in which the many attributes of the audiovisual speech signal are integrated by separate integration processes.

Immunity-based detection, identification, and evaluation of aircraft sub-system failures

Science.gov (United States)

Moncayo, Hever Y.

This thesis describes the design, development, and flight-simulation testing of an integrated Artificial Immune System (AIS) for detection, identification, and evaluation of a wide variety of sensor, actuator, propulsion, and structural failures/damages including the prediction of the achievable states and other limitations on performance and handling qualities. The AIS scheme achieves high detection rate and low number of false alarms for all the failure categories considered. Data collected using a motion-based flight simulator are used to define the self for an extended sub-region of the flight envelope. The NASA IFCS F-15 research aircraft model is used and represents a supersonic fighter which include model following adaptive control laws based on non-linear dynamic inversion and artificial neural network augmentation. The flight simulation tests are designed to analyze and demonstrate the performance of the immunity-based aircraft failure detection, identification and evaluation (FDIE) scheme. A general robustness analysis is also presented by determining the achievable limits for a desired performance in the presence of atmospheric perturbations. For the purpose of this work, the integrated AIS scheme is implemented based on three main components. The first component performs the detection when one of the considered failures is present in the system. The second component consists in the identification of the failure category and the classification according to the failed element. During the third phase a general evaluation of the failure is performed with the estimation of the magnitude/severity of the failure and the prediction of its effect on reducing the flight envelope of the aircraft system. Solutions and alternatives to specific design issues of the AIS scheme, such as data clustering and empty space optimization, data fusion and duplication removal, definition of features, dimensionality reduction, and selection of cluster/detector shape are also

Detection and identification of alkylating agents by using a bioinspired "chemical nose".

Science.gov (United States)

Hertzog-Ronen, Carmit; Borzin, Elena; Gerchikov, Yulia; Tessler, Nir; Eichen, Yoav

2009-10-12

Alkylating agents are simple and reactive molecules that are commonly used in many and diverse fields such as organic synthesis, medicine, and agriculture. Some highly reactive alkylating species are also being used as blister chemical-warfare agents. The detection and identification of alkylating agents is not a trivial issue because of their high reactivity and simple structure. Herein, we report on a new multispot luminescence-based approach to the detection and identification of alkylating agents. In order to demonstrate the potential of the approach, seven pi-conjugated oligomers and polymers bearing nucleophilic pyridine groups, 1-7, were adsorbed onto a solid support and exposed to vapors of alkylators 8-15. The alkylation-induced color-shift patterns of the seven-spot array allow clear discrimination of the different alkylators. The spots are sensitive to minute concentrations of alkylators and, because the detection is based on the formation of new covalent bonds, these spots saturate at about 50 ppb.

A novel RT-PCR for the detection of Helicobacter pylori and identification of clarithromycin resistance mediated by mutations in the 23S rRNA gene.

Science.gov (United States)

Redondo, Javier Jareño; Keller, Peter M; Zbinden, Reinhard; Wagner, Karoline

2018-01-01

In this study we evaluated the commercially available LightMix® RT-PCR assay for Helicobacter pylori detection and identification of clarithromycin (CLR) resistance in culture and clinical specimens (gastric biopsies and stool). The H. pylori LightMix® RT-PCR detects a 97bp long fragment of the 23S rRNA gene and allows the identification of 3 distinct point mutations conferring CLR resistance via melting curve analysis. The performance of the H. pylori LightMix® RT-PCR was evaluated using a set of 60 H. pylori strains showing phenotypical CLR susceptibility or CLR resistance (Minimum inhibitory concentrations from 0.016 to 256mg/L). We found high concordance (95%) between phenotypical CLR resistance screening by E-Test® and the Lightmix® RT-PCR. Discrepant results were verified by sequencing of the 23S rRNA gene that always confirmed the results obtained by Lightmix® RT-PCR. Furthermore, H. pylori was detected in clinical biopsy and stool specimens by Lightmix® RT-PCR that identified the correct H. pylori genotype. The LightMix® RT-PCR is an accurate, sensitive and easy to use test for H. pylori and CLR resistance detection and can therefore be readily implemented in any diagnostic laboratory. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Molecular detection and species-specific identification of medically important Aspergillus species by real-time PCR in experimental invasive pulmonary aspergillosis.

Science.gov (United States)

Walsh, Thomas J; Wissel, Mark C; Grantham, Kevin J; Petraitiene, Ruta; Petraitis, Vidmantas; Kasai, Miki; Francesconi, Andrea; Cotton, Margaret P; Hughes, Johanna E; Greene, Lora; Bacher, John D; Manna, Pradip; Salomoni, Martin; Kleiboeker, Steven B; Reddy, Sushruth K

2011-12-01

Diagnosis of invasive pulmonary aspergillosis (IPA) remains a major challenge to clinical microbiology laboratories. We developed rapid and sensitive quantitative PCR (qPCR) assays for genus- and species-specific identification of Aspergillus infections by use of TaqMan technology. In order to validate these assays and understand their potential diagnostic utility, we then performed a blinded study of bronchoalveolar lavage (BAL) fluid specimens from well-characterized models of IPA with the four medically important species. A set of real-time qPCR primers and probes was developed by utilizing unique ITS1 regions for genus- and species-specific detection of the four most common medically important Aspergillus species (Aspergillus fumigatus, A. flavus, A. niger, and A. terreus). Pan-Aspergillus and species-specific qPCRs with BAL fluid were more sensitive than culture for detection of IPA caused by A. fumigatus in untreated (P < 0.0007) and treated (P ≤ 0.008) animals, respectively. For infections caused by A. terreus and A. niger, culture and PCR amplification from BAL fluid yielded similar sensitivities for untreated and treated animals. Pan-Aspergillus PCR was more sensitive than culture for detection of A. flavus in treated animals (P = 0.002). BAL fluid pan-Aspergillus and species-specific PCRs were comparable in sensitivity to BAL fluid galactomannan (GM) assay. The copy numbers from the qPCR assays correlated with quantitative cultures to determine the pulmonary residual fungal burdens in lung tissue. Pan-Aspergillus and species-specific qPCR assays may improve the rapid and accurate identification of IPA in immunocompromised patients.

Fault Detection for Automotive Shock Absorber

Science.gov (United States)

Hernandez-Alcantara, Diana; Morales-Menendez, Ruben; Amezquita-Brooks, Luis

2015-11-01

Fault detection for automotive semi-active shock absorbers is a challenge due to the non-linear dynamics and the strong influence of the disturbances such as the road profile. First obstacle for this task, is the modeling of the fault, which has been shown to be of multiplicative nature. Many of the most widespread fault detection schemes consider additive faults. Two model-based fault algorithms for semiactive shock absorber are compared: an observer-based approach and a parameter identification approach. The performance of these schemes is validated and compared using a commercial vehicle model that was experimentally validated. Early results shows that a parameter identification approach is more accurate, whereas an observer-based approach is less sensible to parametric uncertainty.

Accurate identification of RNA editing sites from primitive sequence with deep neural networks.

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Ouyang, Zhangyi; Liu, Feng; Zhao, Chenghui; Ren, Chao; An, Gaole; Mei, Chuan; Bo, Xiaochen; Shu, Wenjie

2018-04-16

RNA editing is a post-transcriptional RNA sequence alteration. Current methods have identified editing sites and facilitated research but require sufficient genomic annotations and prior-knowledge-based filtering steps, resulting in a cumbersome, time-consuming identification process. Moreover, these methods have limited generalizability and applicability in species with insufficient genomic annotations or in conditions of limited prior knowledge. We developed DeepRed, a deep learning-based method that identifies RNA editing from primitive RNA sequences without prior-knowledge-based filtering steps or genomic annotations. DeepRed achieved 98.1% and 97.9% area under the curve (AUC) in training and test sets, respectively. We further validated DeepRed using experimentally verified U87 cell RNA-seq data, achieving 97.9% positive predictive value (PPV). We demonstrated that DeepRed offers better prediction accuracy and computational efficiency than current methods with large-scale, mass RNA-seq data. We used DeepRed to assess the impact of multiple factors on editing identification with RNA-seq data from the Association of Biomolecular Resource Facilities and Sequencing Quality Control projects. We explored developmental RNA editing pattern changes during human early embryogenesis and evolutionary patterns in Drosophila species and the primate lineage using DeepRed. Our work illustrates DeepRed's state-of-the-art performance; it may decipher the hidden principles behind RNA editing, making editing detection convenient and effective.

Spectroscopic confirmation of the optical identification of X-ray sources used to determine accurate positions for the anomalous X-ray pulsars 1E 2259+58.6 and 4U 0142+61

Science.gov (United States)

van den Berg, M.; Verbunt, F.

2001-03-01

Optical spectra show that two proposed counterparts for X-ray sources detected near 1E 2259+58.6 are late G stars, and a proposed counterpart for a source near 4U 0142+61 is a dMe star. The X-ray luminosities are as expected for such stars. We thus confirm the optical identification of the three X-ray objects, and thereby the correctness of the accurate positions for 1E 2259+58.6 and 4U 0142+61 based on them. Based on observations made with the William Herschel Telescope operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias.

Exploiting Multiple Detections for Person Re-Identification

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Amran Bhuiyan

2018-01-01

Full Text Available Re-identification systems aim at recognizing the same individuals in multiple cameras, and one of the most relevant problems is that the appearance of same individual varies across cameras due to illumination and viewpoint changes. This paper proposes the use of cumulative weighted brightness transfer functions (CWBTFs to model these appearance variations. Different from recently proposed methods which only consider pairs of images to learn a brightness transfer function, we exploit such a multiple-frame-based learning approach that leverages consecutive detections of each individual to transfer the appearance. We first present a CWBTF framework for the task of transforming appearance from one camera to another. We then present a re-identification framework where we segment the pedestrian images into meaningful parts and extract features from such parts, as well as from the whole body. Jointly, both of these frameworks contribute to model the appearance variations more robustly. We tested our approach on standard multi-camera surveillance datasets, showing consistent and significant improvements over existing methods on three different datasets without any other additional cost. Our approach is general and can be applied to any appearance-based method.

Identification of Importin 8 (IPO8 as the most accurate reference gene for the clinicopathological analysis of lung specimens

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Pio Ruben

2008-11-01

Full Text Available Abstract Background The accurate normalization of differentially expressed genes in lung cancer is essential for the identification of novel therapeutic targets and biomarkers by real time RT-PCR and microarrays. Although classical "housekeeping" genes, such as GAPDH, HPRT1, and beta-actin have been widely used in the past, their accuracy as reference genes for lung tissues has not been proven. Results We have conducted a thorough analysis of a panel of 16 candidate reference genes for lung specimens and lung cell lines. Gene expression was measured by quantitative real time RT-PCR and expression stability was analyzed with the softwares GeNorm and NormFinder, mean of |ΔCt| (= |Ct Normal-Ct tumor| ± SEM, and correlation coefficients among genes. Systematic comparison between candidates led us to the identification of a subset of suitable reference genes for clinical samples: IPO8, ACTB, POLR2A, 18S, and PPIA. Further analysis showed that IPO8 had a very low mean of |ΔCt| (0.70 ± 0.09, with no statistically significant differences between normal and malignant samples and with excellent expression stability. Conclusion Our data show that IPO8 is the most accurate reference gene for clinical lung specimens. In addition, we demonstrate that the commonly used genes GAPDH and HPRT1 are inappropriate to normalize data derived from lung biopsies, although they are suitable as reference genes for lung cell lines. We thus propose IPO8 as a novel reference gene for lung cancer samples.

HIPPI: highly accurate protein family classification with ensembles of HMMs

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Nam-phuong Nguyen

2016-11-01

Full Text Available Abstract Background Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics. Results We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification. HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy. Conclusion HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp .

Delamination Detection of Reinforced Concrete Decks Using Modal Identification

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Shutao Xing

2012-01-01

Full Text Available This study addressed delamination detection of concrete slabs by analyzing global dynamic responses of structures. Both numerical and experimental studies are presented. In the numerical examples, delaminations with different sizes and locations were introduced into a concrete slab; the effects of presence, sizes, and locations of delaminations on the modal frequencies and mode shapes of the concrete slab under various support conditions were studied. In the experimental study, four concrete deck specimens with different delamination sizes were constructed, and experimental tests were conducted. Traditional peak-picking, frequency domain decomposition, and stochastic subspace identification methods were applied to the modal identification from dynamic response measurements. The modal parameters identified by these three methods correlated well. The changes in modal frequencies, damping ratios, and mode shapes that were extracted from the dynamic measurements were investigated and correlated to the actual delaminations and can indicate presence and severity of delamination. Finite element (FE models of reinforced concrete decks with different delamination sizes and locations were established. The modal parameters computed from the FE models were compared to those obtained from the laboratory specimens, and the FE models were validated. The delamination detection approach was proved to be effective for concrete decks on beams.

The new generation of detection and identification equipment; Nouvelle generation de materiel de detection et d' identification

Energy Technology Data Exchange (ETDEWEB)

Schultz, F.; Guerin, M.; Fort, Ph. [Mirion technologies, division HPH, BPI - 13113 Lamanon (France)

2009-07-01

The authors address the highly sensitive detection issue with real time identification of the risk nature, a problem which occurs every time a source is only fleetingly present (a pedestrian, a vehicle or an object on a conveyor belt passing by). They briefly present a range of instruments specially designed for this purpose, the SPIR-Ident instruments. These equipment use one or several large sensors, digital multichannel analyzers (one per sensor) and neutron and gamma measurements. Spectra are continuously processed, stabilized, linearized and normalized, and finally analyzed by an algorithm. The authors evoke the performance characterization and a return on experience after a 6 month-use for the control of passengers and luggage in airport

Patient identification errors: the detective in the laboratory.

Science.gov (United States)

Salinas, Maria; López-Garrigós, Maite; Lillo, Rosa; Gutiérrez, Mercedes; Lugo, Javier; Leiva-Salinas, Carlos

2013-11-01

The eradication of errors regarding patients' identification is one of the main goals for safety improvement. As clinical laboratory intervenes in 70% of clinical decisions, laboratory safety is crucial in patient safety. We studied the number of Laboratory Information System (LIS) demographic data errors registered in our laboratory during one year. The laboratory attends a variety of inpatients and outpatients. The demographic data of outpatients is registered in the LIS, when they present to the laboratory front desk. The requests from the primary care centers (PCC) are made electronically by the general practitioner. A manual step is always done at the PCC to conciliate the patient identification number in the electronic request with the one in the LIS. Manual registration is done through hospital information system demographic data capture when patient's medical record number is registered in LIS. Laboratory report is always sent out electronically to the patient's electronic medical record. Daily, every demographic data in LIS is manually compared to the request form to detect potential errors. Fewer errors were committed when electronic order was used. There was great error variability between PCC when using the electronic order. LIS demographic data manual registration errors depended on patient origin and test requesting method. Even when using the electronic approach, errors were detected. There was a great variability between PCC even when using this electronic modality; this suggests that the number of errors is still dependent on the personnel in charge of the technology. © 2013.

Genome-Enhanced Detection and Identification (GEDI of plant pathogens

Directory of Open Access Journals (Sweden)

Nicolas Feau

2018-02-01

Full Text Available Plant diseases caused by fungi and Oomycetes represent worldwide threats to crops and forest ecosystems. Effective prevention and appropriate management of emerging diseases rely on rapid detection and identification of the causal pathogens. The increase in genomic resources makes it possible to generate novel genome-enhanced DNA detection assays that can exploit whole genomes to discover candidate genes for pathogen detection. A pipeline was developed to identify genome regions that discriminate taxa or groups of taxa and can be converted into PCR assays. The modular pipeline is comprised of four components: (1 selection and genome sequencing of phylogenetically related taxa, (2 identification of clusters of orthologous genes, (3 elimination of false positives by filtering, and (4 assay design. This pipeline was applied to some of the most important plant pathogens across three broad taxonomic groups: Phytophthoras (Stramenopiles, Oomycota, Dothideomycetes (Fungi, Ascomycota and Pucciniales (Fungi, Basidiomycota. Comparison of 73 fungal and Oomycete genomes led the discovery of 5,939 gene clusters that were unique to the targeted taxa and an additional 535 that were common at higher taxonomic levels. Approximately 28% of the 299 tested were converted into qPCR assays that met our set of specificity criteria. This work demonstrates that a genome-wide approach can efficiently identify multiple taxon-specific genome regions that can be converted into highly specific PCR assays. The possibility to easily obtain multiple alternative regions to design highly specific qPCR assays should be of great help in tackling challenging cases for which higher taxon-resolution is needed.

Medical isotope identification with large mobile detection systems

Science.gov (United States)

Mukhopadhyay, Sanjoy; Maurer, Richard

2012-10-01

The Remote Sensing laboratory (RSL) of National Security Technologies Inc. has built an array of large (5.08 - cm x 10.16 - cm x 40.6 - cm) thallium doped sodium iodide (NaI: Tl) scintillators to locate and screen gamma-ray emitting radioisotopes that are of interests to radiological emergency responders [1]. These vehicle mounted detectors provide the operators with rapid, simple, specific information for radiological threat assessment. Applications include large area inspection, customs inspection, border protection, emergency response, and monitoring of radiological facilities. These RSL mobile units are currently being upgraded to meet the Defense Threat Reduction Agency mission requirements for a next-generation system capable of detecting and identifying nuclear threat materials. One of the challenging problems faced by these gamma-ray detectors is the unambiguous identification of medical isotopes like 131I (364.49 keV [81.7%], 636.99 keV [7.17%]), 99Tcm (140.51 keV [89.1%]) and 67Ga (184.6 keV [19.7%], 300.2 [16.0%], 393.5 [4.5%] that are used in radionuclide therapy and often have overlapping gamma-ray energy regions of interest (ROI). The problem is made worse by short (about 5 seconds) acquisition time of the spectral data necessary for dynamic mobile detectors. This article describes attempts to identify medical isotopes from data collected from this mobile detection system in a short period of time (not exceeding 5 secs) and a large standoff distance (typically 10 meters) The mobile units offer identification capabilities that are based on hardware auto stabilization of the amplifier gain. The 1461 keV gamma-energy line from 40K is tracked. It uses gamma-ray energy windowing along with embedded mobile Gamma Detector Response and Analysis Software (GADRAS) [2] simultaneously to deconvolve any overlapping gamma-energy ROIs. These high sensitivity detectors are capable of resolving complex masking scenarios and exceed all ANSI N42.34 (2006) requirements

Cue combination in a combined feature contrast detection and figure identification task.

Science.gov (United States)

Meinhardt, Günter; Persike, Malte; Mesenholl, Björn; Hagemann, Cordula

2006-11-01

Target figures defined by feature contrast in spatial frequency, orientation or both cues had to be detected in Gabor random fields and their shape had to be identified in a dual task paradigm. Performance improved with increasing feature contrast and was strongly correlated among both tasks. Subjects performed significantly better with combined cues than with single cues. The improvement due to cue summation was stronger than predicted by the assumption of independent feature specific mechanisms, and increased with the performance level achieved with single cues until it was limited by ceiling effects. Further, cue summation was also strongly correlated among tasks: when there was benefit due to the additional cue in feature contrast detection, there was also benefit in figure identification. For the same performance level achieved with single cues, cue summation was generally larger in figure identification than in feature contrast detection, indicating more benefit when processes of shape and surface formation are involved. Our results suggest that cue combination improves spatial form completion and figure-ground segregation in noisy environments, and therefore leads to more stable object vision.

The BaBar detector for muon identification and neutral hadron detection

International Nuclear Information System (INIS)

Paolucci, P.; Evangelista, C.; Palano, A.; Baldini, R.; Calcaterra, A.; De Sangro, R.; Piccolo, M.; Zallo, A.; Peruzzi, I.; Buzzo, A.; Contri, R.; Crosetti, G.; Monge, R.; Passaggio, S.; Patrignani, C.; Pia, M.G.; Santroni, A.; Bionta, R.M.; van Bibber, K.; Wenaus, T.J.; Wright, D.M.; Cavallo, N.; Carlino, G.; Lista, L.; Mele, S.; Parascandolo, P.; Piccolo, D.; Sciacca, C.; Johnson, J.R.

1996-01-01

The BaBar experiment is projected to study CP violation in B decays. Muon detection and K L 0 identification are achieved by an instrumented flux return (IFR) system based on resistive plate chamber detectors. In this paper the general layout of the IFR system will be described. (orig.)

A simple and accurate onset detection method for a measured bell-shaped speed profile

Directory of Open Access Journals (Sweden)

Lior Botzer

2009-06-01

Full Text Available Motor control neuroscientists measure limb trajectories and extract the onset of the movement for a variety of purposes. Such trajectories are often aligned relative to the onset of individual movement before the features of that movement are extracted and their properties are inspected. Onset detection is performed either manually or automatically, typically by selecting a velocity threshold. Here, we present a simple onset detection algorithm that is more accurate than the conventional velocity threshold technique. The proposed method is based on a simple regression and follows the minimum acceleration with constraints model, in which the initial phase of the bell-shaped movement is modeled by a cubic power of the time. We demonstrate the performance of the suggested method and compare it to the velocity threshold technique and to manual onset detection by a group of motor control experts. The database for this comparison consists of simulated minimum jerk trajectories and recorded reaching movements.

Molecular detection and species identification of Enterocytozoon bieneusi isolated from immunocompetent Orang Asli in Malaysia.

Science.gov (United States)

Ashikin, Azah; Al-Mekhlafi, Hesham M; Moktar, Norhayati; Anuar, Tengku Shahrul

2017-04-01

Most studies of opportunistic infections focus on immunocompromised patients. However, there is a lack of information on microsporidiosis in healthy people (immunocompetent) worldwide. This study aimed to detect and identify microsporidia species in immunocompetent Orang Asli living in Pahang, Malaysia. Orang Asli is a collective term for a group of indigenous people that usually reside in the interior regions of Peninsular Malaysia. They comprise about 0.7% of the total population in Malaysia and 76% of them lived below the poverty line i.e., poor housing conditions with the lack of access to safe drinking water and adequate sanitation, contaminated environment, high illiteracy rate and unhygienic practices by these people. Stool samples were collected from 209 Orang Asli and analyzed for detecting the presence of Enterocytozoon bieneusi and Encephalitozoon intestinalis by polymerase chain reaction assay targeting small subunit ribosomal RNA gene. E. bieneusi was detected in 8 individuals (3.83%). This infection was commonly found in males than females (5.2% vs. 2.7%). All infected Orang Asli were adults, with a mean age of 44years. Diarrhea and other gastrointestinal symptoms were reported in one case (12.5%) among individuals infected with this species. These findings clearly show that exposure to E. bieneusi may actually be common than reported. The accurate detection and identification of microsporidian species by molecular technique will improve therapy, clinical manifestations and prognosis of this infection, as no antiparasitic therapy has been approved for E. bieneusi. It is hoped that these findings will allow the formulation of better health management and disease prevention advisories, and improvement in the standards of health in similar communities. Copyright © 2017 Elsevier B.V. All rights reserved.

Automated Photoreceptor Cell Identification on Nonconfocal Adaptive Optics Images Using Multiscale Circular Voting.

Science.gov (United States)

Liu, Jianfei; Jung, HaeWon; Dubra, Alfredo; Tam, Johnny

2017-09-01

Adaptive optics scanning light ophthalmoscopy (AOSLO) has enabled quantification of the photoreceptor mosaic in the living human eye using metrics such as cell density and average spacing. These rely on the identification of individual cells. Here, we demonstrate a novel approach for computer-aided identification of cone photoreceptors on nonconfocal split detection AOSLO images. Algorithms for identification of cone photoreceptors were developed, based on multiscale circular voting (MSCV) in combination with a priori knowledge that split detection images resemble Nomarski differential interference contrast images, in which dark and bright regions are present on the two sides of each cell. The proposed algorithm locates dark and bright region pairs, iteratively refining the identification across multiple scales. Identification accuracy was assessed in data from 10 subjects by comparing automated identifications with manual labeling, followed by computation of density and spacing metrics for comparison to histology and published data. There was good agreement between manual and automated cone identifications with overall recall, precision, and F1 score of 92.9%, 90.8%, and 91.8%, respectively. On average, computed density and spacing values using automated identification were within 10.7% and 11.2% of the expected histology values across eccentricities ranging from 0.5 to 6.2 mm. There was no statistically significant difference between MSCV-based and histology-based density measurements (P = 0.96, Kolmogorov-Smirnov 2-sample test). MSCV can accurately detect cone photoreceptors on split detection images across a range of eccentricities, enabling quick, objective estimation of photoreceptor mosaic metrics, which will be important for future clinical trials utilizing adaptive optics.

Warnings to Counter Choice Blindness for Identification Decisions: Warnings Offer an Advantage in Time but Not in Rate of Detection

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Anna Sagana

2018-06-01

Full Text Available Choice blindness for identification decisions refers to the inability of eyewitnesses to detect that an originally recognized target was swapped for a non-identified lineup member. The robustness of the effect calls for measures that can prevent or reduce the negative consequences of choice blindness manipulations. Here, we investigated whether pre- and post-warnings given to participants about the possibility of mistakes reduces choice blindness for identification decisions. Participants (N = 119 were presented with identifications they never made and were asked to justify those decisions. Either before or after the presentation of the manipulated identification outcome, participants were or were not warned about the possibility of mistakes in the identification process. Although warnings were not sufficient to reduce choice blindness for identification decisions they provided a time-related detection advantage. Pre-warned participants questioned the legitimacy of the manipulated outcome sooner (i.e., concurrent detection than participants in other conditions. Hence, pre-warnings can help detect mistakes in the identification procedure at an earlier stage, before they contaminate the memory of the witness and other pieces of evidence. From a theoretical stance, our findings attest to the strength of self-suggestion and indicate that choice blindness effects are deeply rooted in cognition.

Identification of dental root canals and their medial line from micro-CT and cone-beam CT records

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Benyó Balázs

2012-10-01

Full Text Available Abstract Background Shape of the dental root canal is highly patient specific. Automated identification methods of the medial line of dental root canals and the reproduction of their 3D shape can be beneficial for planning endodontic interventions as severely curved root canals or multi-rooted teeth may pose treatment challenges. Accurate shape information of the root canals may also be used by manufacturers of endodontic instruments in order to make more efficient clinical tools. Method Novel image processing procedures dedicated to the automated detection of the medial axis of the root canal from dental micro-CT and cone-beam CT records are developed. For micro-CT, the 3D model of the root canal is built up from several hundred parallel cross sections, using image enhancement, histogram based fuzzy c-means clustering, center point detection in the segmented slice, three dimensional inner surface reconstruction, and potential field driven curve skeleton extraction in three dimensions. Cone-beam CT records are processed with image enhancement filters and fuzzy chain based regional segmentation, followed by the reconstruction of the root canal surface and detecting its skeleton via a mesh contraction algorithm. Results The proposed medial line identification and root canal detection algorithms are validated on clinical data sets. 25 micro-CT and 36 cone-beam-CT records are used in the validation procedure. The overall success rate of the automatic dental root canal identification was about 92% in both procedures. The algorithms proved to be accurate enough for endodontic therapy planning. Conclusions Accurate medial line identification and shape detection algorithms of dental root canal have been developed. Different procedures are defined for micro-CT and cone-beam CT records. The automated execution of the subsequent processing steps allows easy application of the algorithms in the dental care. The output data of the image processing procedures

Increased detection of mastitis pathogens by real-time PCR compared to bacterial culture.

Science.gov (United States)

Keane, O M; Budd, K E; Flynn, J; McCoy, F

2013-09-21

Rapid and accurate identification of mastitis pathogens is important for disease control. Bacterial culture and isolate identification is considered the gold standard in mastitis diagnosis but is time consuming and results in many culture-negative samples. Identification of mastitis pathogens by PCR has been proposed as a fast and sensitive alternative to bacterial culture. The results of bacterial culture and PCR for the identification of the aetiological agent of clinical mastitis were compared. The pathogen identified by traditional culture methods was also detected by PCR in 98 per cent of cases indicating good agreement between the positive results of bacterial culture and PCR. A mastitis pathogen could not be recovered from approximately 30 per cent of samples by bacterial culture, however, an aetiological agent was identified by PCR in 79 per cent of these samples. Therefore, a mastitis pathogen was detected in significantly more milk samples by PCR than by bacterial culture (92 per cent and 70 per cent, respectively) although the clinical relevance of PCR-positive culture-negative results remains controversial. A mixed infection of two or more mastitis pathogens was also detected more commonly by PCR. Culture-negative samples due to undetected Staphylococcus aureus infections were rare. The use of PCR technology may assist in rapid mastitis diagnosis, however, accurate interpretation of PCR results in the absence of bacterial culture remains problematic.

Chemical detection, identification, and analysis system

International Nuclear Information System (INIS)

Morel, R.S.; Gonzales, D.; Mniszewski, S.

1990-01-01

The chemical detection, identification, and analysis system (CDIAS) has three major goals. The first is to display safety information regarding chemical environment before personnel entry. The second is to archive personnel exposure to the environment. Third, the system assists users in identifying the stage of a chemical process in progress and suggests safety precautions associated with that process. In addition to these major goals, the system must be sufficiently compact to provide transportability, and it must be extremely simple to use in order to keep user interaction at a minimum. The system created to meet these goals includes several pieces of hardware and the integration of four software packages. The hardware consists of a low-oxygen, carbon monoxide, explosives, and hydrogen sulfide detector; an ion mobility spectrometer for airborne vapor detection; and a COMPAQ 386/20 portable computer. The software modules are a graphics kernel, an expert system shell, a data-base management system, and an interface management system. A supervisory module developed using the interface management system coordinates the interaction of the other software components. The system determines the safety of the environment using conventional data acquisition and analysis techniques. The low-oxygen, carbon monoxide, hydrogen sulfide, explosives, and vapor detectors are monitored for hazardous levels, and warnings are issued accordingly

Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms

Science.gov (United States)

Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid

2017-10-01

Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.

Embodied memory allows accurate and stable perception of hidden objects despite orientation change.

Science.gov (United States)

Pan, Jing Samantha; Bingham, Ned; Bingham, Geoffrey P

2017-07-01

Rotating a scene in a frontoparallel plane (rolling) yields a change in orientation of constituent images. When using only information provided by static images to perceive a scene after orientation change, identification performance typically decreases (Rock & Heimer, 1957). However, rolling generates optic flow information that relates the discrete, static images (before and after the change) and forms an embodied memory that aids recognition. The embodied memory hypothesis predicts that upon detecting a continuous spatial transformation of image structure, or in other words, seeing the continuous rolling process and objects undergoing rolling observers should accurately perceive objects during and after motion. Thus, in this case, orientation change should not affect performance. We tested this hypothesis in three experiments and found that (a) using combined optic flow and image structure, participants identified locations of previously perceived but currently occluded targets with great accuracy and stability (Experiment 1); (b) using combined optic flow and image structure information, participants identified hidden targets equally well with or without 30° orientation changes (Experiment 2); and (c) when the rolling was unseen, identification of hidden targets after orientation change became worse (Experiment 3). Furthermore, when rolling was unseen, although target identification was better when participants were told about the orientation change than when they were not told, performance was still worse than when there was no orientation change. Therefore, combined optic flow and image structure information, not mere knowledge about the rolling, enables accurate and stable perception despite orientation change. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Ultrasound detection and identification of cosmetic fillers in the skin

DEFF Research Database (Denmark)

Wortsman, X.; Wortsman, J.; Orlandi, C.

2012-01-01

Background While the incidence of cosmetic filler injections is rising world-wide, neither exact details of the procedure nor the agent used are always reported or remembered by the patients. Thus, although complications are reportedly rare, availability of a precise diagnostic tool to detect...... cutaneous filler deposits could help clarify the association between the procedure and the underlying pathology. Objectives The aim of this study was to evaluate cutaneous sonography in the detection and identification of cosmetic fillers deposits and, describe dermatological abnormalities found associated...... with the presence of those agents. Methods We used ultrasound in a porcine skin model to determine the sonographic characteristics of commonly available filler agents, and subsequently applied the analysis to detect and identify cosmetic fillers among patients referred for skin disorders. Results Fillers...

A transition radiation detector which features accurate tracking and dE/dx particle identification

International Nuclear Information System (INIS)

O'Brien, E.; Lissauer, D.; McCorkle, S.; Polychronakos, V.; Takai, H.; Chi, C.Y.; Nagamiya, S.; Sippach, W.; Toy, M.; Wang, D.; Wang, Y.F.; Wiggins, C.; Willis, W.; Cherniatin, V.; Dolgoshein, B.; Bennett, M.; Chikanian, A.; Kumar, S.; Mitchell, J.T.; Pope, K.

1991-01-01

We describe the results of a test run involving a Transition Radiation Detector that can both distinguish electrons from pions with momenta greater than 0.7 GeV/c and simultaneously track particles passing through the detector. The particle identification is accomplished through a combination of the detection of Transition Radiation from the electron and the differences in electron and pion energy loss (dE/dx) in the detector. The dE/dx particle separation is most efficient below 2 GeV/c while particle ID utilizing Transition Radiation is effective above 1.5 GeV/c. Combined, the electron-pion separation is better than 5 x l0 2 . The single-wire, track-position resolution for the TRD is ∼230μm

An OGA-Resistant Probe Allows Specific Visualization and Accurate Identification of O-GlcNAc-Modified Proteins in Cells.

Science.gov (United States)

Li, Jing; Wang, Jiajia; Wen, Liuqing; Zhu, He; Li, Shanshan; Huang, Kenneth; Jiang, Kuan; Li, Xu; Ma, Cheng; Qu, Jingyao; Parameswaran, Aishwarya; Song, Jing; Zhao, Wei; Wang, Peng George

2016-11-18

O-linked β-N-acetyl-glucosamine (O-GlcNAc) is an essential and ubiquitous post-translational modification present in nucleic and cytoplasmic proteins of multicellular eukaryotes. The metabolic chemical probes such as GlcNAc or GalNAc analogues bearing ketone or azide handles, in conjunction with bioorthogonal reactions, provide a powerful approach for detecting and identifying this modification. However, these chemical probes either enter multiple glycosylation pathways or have low labeling efficiency. Therefore, selective and potent probes are needed to assess this modification. We report here the development of a novel probe, 1,3,6-tri-O-acetyl-2-azidoacetamido-2,4-dideoxy-d-glucopyranose (Ac 3 4dGlcNAz), that can be processed by the GalNAc salvage pathway and transferred by O-GlcNAc transferase (OGT) to O-GlcNAc proteins. Due to the absence of a hydroxyl group at C4, this probe is less incorporated into α/β 4-GlcNAc or GalNAc containing glycoconjugates. Furthermore, the O-4dGlcNAz modification was resistant to the hydrolysis of O-GlcNAcase (OGA), which greatly enhanced the efficiency of incorporation for O-GlcNAcylation. Combined with a click reaction, Ac 3 4dGlcNAz allowed the selective visualization of O-GlcNAc in cells and accurate identification of O-GlcNAc-modified proteins with LC-MS/MS. This probe represents a more potent and selective tool in tracking, capturing, and identifying O-GlcNAc-modified proteins in cells and cell lysates.

An Innovative Fuzzy-Logic-Based Methodology for Trend Identification

International Nuclear Information System (INIS)

Wang Xin; Tsoukalas, Lefteri H.; Wei, Thomas Y.C.; Reifman, Jaques

2001-01-01

A new fuzzy-logic-based methodology for on-line signal trend identification is introduced. The methodology may be used for detecting the onset of nuclear power plant (NPP) transients at the earliest possible time and could be of great benefit to diagnostic, maintenance, and performance-monitoring programs. Although signal trend identification is complicated by the presence of noise, fuzzy methods can help capture important features of on-line signals, integrate the information included in these features, and classify incoming NPP signals into increasing, decreasing, and steady-state trend categories. A computer program named PROTREN is developed and tested for the purpose of verifying this methodology using NPP and simulation data. The results indicate that the new fuzzy-logic-based methodology is capable of detecting transients accurately, it identifies trends reliably and does not misinterpret a steady-state signal as a transient one

Rapid and accurate identification of Streptococcus equi subspecies by MALDI-TOF MS

DEFF Research Database (Denmark)

Kudirkiene, Egle; Welker, Martin; Knudsen, Nanna Reumert

2015-01-01

phenotypic and sequence similarity between three subspecies their discrimination remains difficult. In this study, we aimed to design and validate a novel, Superspectra based, MALDI-TOF MS approach for reliable, rapid and cost-effective identification of SEE and SEZ, the most frequent S. equi subspecies.......3±7.5%). This result may be attributed to the highly clonal population structure of SEE, as opposed to the diversity of SEZ seen in horses. Importantly strains with atypical colony appearance both within SEE and SEZ did not affect correct identification of the strains by MALDI-TOF MS. Atypical colony variants...... are often associated with a higher persistence or virulence of S. equi, thus their correct identification using the current method strengthens its potential use in routine clinical diagnostics. In conclusion, reliable identification of S. equi subspecies was achieved by combining a MALDI-TOF MS method...

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

Directory of Open Access Journals (Sweden)

Yang Zhang

2016-10-01

Full Text Available Ultra-wideband (UWB radar has been widely used for detecting human physiological signals (respiration, movement, etc. in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc., the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method.

Science.gov (United States)

Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

2016-10-27

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

The effect of texture on face identification and configural information processing

Directory of Open Access Journals (Sweden)

Tzschaschel Eva Alica

2014-01-01

Full Text Available Shape and texture are an integral part of face identity. In the present study, the importance of face texture for face identification and detection of configural manipulation (i.e., spatial relation among facial features was examined by comparing grayscale face photographs (i.e., real faces and line drawings of the same faces. Whereas real faces provide information about texture and shape of faces, line drawings are lacking texture cues. A change-detection task and a forced-choice identification task were used with both stimuli categories. Within the change detection task, participants had to decide whether the size of the eyes of two sequentially presented faces had changed or not. After having made this decision, three faces were shown to the subjects and they had to identify the previously shown face among them. Furthermore, context (full vs. cropped faces and orientation (upright vs. inverted were manipulated. The results obtained in the change detection task suggest that configural information was used in processing real faces, while part-based and featural information was used in processing line-drawings. Additionally, real faces were identified more accurately than line drawings, and identification was less context but more orientation sensitive than identification of line drawings. Taken together, the results of the present study provide new evidence stressing the importance of face texture for identity encoding and configural face processing.

BlueDetect: An iBeacon-Enabled Scheme for Accurate and Energy-Efficient Indoor-Outdoor Detection and Seamless Location-Based Service.

Science.gov (United States)

Zou, Han; Jiang, Hao; Luo, Yiwen; Zhu, Jianjie; Lu, Xiaoxuan; Xie, Lihua

2016-02-22

The location and contextual status (indoor or outdoor) is fundamental and critical information for upper-layer applications, such as activity recognition and location-based services (LBS) for individuals. In addition, optimizations of building management systems (BMS), such as the pre-cooling or heating process of the air-conditioning system according to the human traffic entering or exiting a building, can utilize the information, as well. The emerging mobile devices, which are equipped with various sensors, become a feasible and flexible platform to perform indoor-outdoor (IO) detection. However, power-hungry sensors, such as GPS and WiFi, should be used with caution due to the constrained battery storage on mobile device. We propose BlueDetect: an accurate, fast response and energy-efficient scheme for IO detection and seamless LBS running on the mobile device based on the emerging low-power iBeacon technology. By leveraging the on-broad Bluetooth module and our proposed algorithms, BlueDetect provides a precise IO detection service that can turn on/off on-board power-hungry sensors smartly and automatically, optimize their performances and reduce the power consumption of mobile devices simultaneously. Moreover, seamless positioning and navigation services can be realized by it, especially in a semi-outdoor environment, which cannot be achieved by GPS or an indoor positioning system (IPS) easily. We prototype BlueDetect on Android mobile devices and evaluate its performance comprehensively. The experimental results have validated the superiority of BlueDetect in terms of IO detection accuracy, localization accuracy and energy consumption.

BlueDetect: An iBeacon-Enabled Scheme for Accurate and Energy-Efficient Indoor-Outdoor Detection and Seamless Location-Based Service

Directory of Open Access Journals (Sweden)

Han Zou

2016-02-01

Full Text Available The location and contextual status (indoor or outdoor is fundamental and critical information for upper-layer applications, such as activity recognition and location-based services (LBS for individuals. In addition, optimizations of building management systems (BMS, such as the pre-cooling or heating process of the air-conditioning system according to the human traffic entering or exiting a building, can utilize the information, as well. The emerging mobile devices, which are equipped with various sensors, become a feasible and flexible platform to perform indoor-outdoor (IO detection. However, power-hungry sensors, such as GPS and WiFi, should be used with caution due to the constrained battery storage on mobile device. We propose BlueDetect: an accurate, fast response and energy-efficient scheme for IO detection and seamless LBS running on the mobile device based on the emerging low-power iBeacon technology. By leveraging the on-broad Bluetooth module and our proposed algorithms, BlueDetect provides a precise IO detection service that can turn on/off on-board power-hungry sensors smartly and automatically, optimize their performances and reduce the power consumption of mobile devices simultaneously. Moreover, seamless positioning and navigation services can be realized by it, especially in a semi-outdoor environment, which cannot be achieved by GPS or an indoor positioning system (IPS easily. We prototype BlueDetect on Android mobile devices and evaluate its performance comprehensively. The experimental results have validated the superiority of BlueDetect in terms of IO detection accuracy, localization accuracy and energy consumption.

Reproducible Molecularly Imprinted Piezoelectric Sensor for Accurate and Sensitive Detection of Ractopamine in Swine and Feed Products

Directory of Open Access Journals (Sweden)

Mingfei Pan

2018-06-01

Full Text Available This paper describes the development of a reproducible molecularly imprinted piezoelectric sensor for the accurate and sensitive detection of ractopamine (RAC in swine and feed products. The synthesized molecularly imprinted polymer (MIP was directly immobilized on the surface of a quartz crystal microbalance (QCM Au chip as the recognition element. The experimental parameters in the fabrication, measurement and regeneration process were evaluated in detail to produce an MIP-based piezoelectric sensor with high sensing capability. The developed piezoelectric sensor was verified to perform favorably in the RAC analysis of swine and feed products, with acceptable accuracy (recovery: 75.9–93.3%, precision [relative standard deviation (n = 3: 2.3–6.4%], and sensitivity [limit of detection: 0.46 ng g−1 (swine and 0.38 ng g−1 (feed]. This portable MIP-based chip for the piezoelectric sensing of RAC could be reused for at least 30 cycles and easily stored for a long time. These results demonstrated that the developed MIP-based piezoelectric sensor presents an accurate, sensitive and cost-effective method for the quantitative detection of RAC in complex samples. This research offers a promising strategy for the development of novel effective devices used for use in food safety analysis.

DNA barcoding and morphological identification of neotropical ichthyoplankton from the Upper Paraná and São Francisco.

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Becker, R A; Sales, N G; Santos, G M; Santos, G B; Carvalho, D C

2015-07-01

The identification of fish larvae from two neotropical hydrographic basins using traditional morphological taxonomy and DNA barcoding revealed no conflicting results between the morphological and barcode identification of larvae. A lower rate (25%) of correct morphological identification of eggs as belonging to migratory or non-migratory species was achieved. Accurate identification of ichthyoplankton by DNA barcoding is an important tool for fish reproductive behaviour studies, correct estimation of biodiversity by detecting eggs from rare species, as well as defining environmental and management strategies for fish conservation in the neotropics. © 2015 The Fisheries Society of the British Isles.

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry for fast and accurate identification of clinically relevant Aspergillus species.

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Alanio, A; Beretti, J-L; Dauphin, B; Mellado, E; Quesne, G; Lacroix, C; Amara, A; Berche, P; Nassif, X; Bougnoux, M-E

2011-05-01

New Aspergillus species have recently been described with the use of multilocus sequencing in refractory cases of invasive aspergillosis. The classical phenotypic identification methods routinely used in clinical laboratories failed to identify them adequately. Some of these Aspergillus species have specific patterns of susceptibility to antifungal agents, and misidentification may lead to inappropriate therapy. We developed a matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS)-based strategy to adequately identify Aspergillus species to the species level. A database including the reference spectra of 28 clinically relevant species from seven Aspergillus sections (five common and 23 unusual species) was engineered. The profiles of young and mature colonies were analysed for each reference strain, and species-specific spectral fingerprints were identified. The performance of the database was then tested on 124 clinical and 16 environmental isolates previously characterized by partial sequencing of the β-tubulin and calmodulin genes. One hundred and thirty-eight isolates of 140 (98.6%) were correctly identified. Two atypical isolates could not be identified, but no isolate was misidentified (specificity: 100%). The database, including species-specific spectral fingerprints of young and mature colonies of the reference strains, allowed identification regardless of the maturity of the clinical isolate. These results indicate that MALDI-TOF MS is a powerful tool for rapid and accurate identification of both common and unusual species of Aspergillus. It can give better results than morphological identification in clinical laboratories. © 2010 The Authors. Clinical Microbiology and Infection © 2010 European Society of Clinical Microbiology and Infectious Diseases.

Saliency Detection and Deep Learning-Based Wildfire Identification in UAV Imagery.

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Zhao, Yi; Ma, Jiale; Li, Xiaohui; Zhang, Jie

2018-02-27

An unmanned aerial vehicle (UAV) equipped with global positioning systems (GPS) can provide direct georeferenced imagery, mapping an area with high resolution. So far, the major difficulty in wildfire image classification is the lack of unified identification marks, the fire features of color, shape, texture (smoke, flame, or both) and background can vary significantly from one scene to another. Deep learning (e.g., DCNN for Deep Convolutional Neural Network) is very effective in high-level feature learning, however, a substantial amount of training images dataset is obligatory in optimizing its weights value and coefficients. In this work, we proposed a new saliency detection algorithm for fast location and segmentation of core fire area in aerial images. As the proposed method can effectively avoid feature loss caused by direct resizing; it is used in data augmentation and formation of a standard fire image dataset 'UAV_Fire'. A 15-layered self-learning DCNN architecture named 'Fire_Net' is then presented as a self-learning fire feature exactor and classifier. We evaluated different architectures and several key parameters (drop out ratio, batch size, etc.) of the DCNN model regarding its validation accuracy. The proposed architecture outperformed previous methods by achieving an overall accuracy of 98%. Furthermore, 'Fire_Net' guarantied an average processing speed of 41.5 ms per image for real-time wildfire inspection. To demonstrate its practical utility, Fire_Net is tested on 40 sampled images in wildfire news reports and all of them have been accurately identified.

A Novel Fault Identification Using WAMS/PMU

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ZHANG, Y.

2012-05-01

Full Text Available The important premise of the novel adaptive backup protection based on wide area information is to identify the fault in a real-time and on-line way. In this paper, the principal components analysis theory is introduced into the field of fault detection to locate precisely the fault by mean of the voltage and current phasor data from the PMUs. Massive simulation experiments have fully proven that the fault identification can be performed successfully by principal component analysis and calculation. Our researches indicate that the variable with the biggest coefficient in principal component usually corresponds to the fault. Under the influence of noise, the results are still accurate and reliable. So, the principal components fault identification has strong anti-interference ability and great redundancy.

Accuracy of using visual identification of white sharks to estimate residency patterns.

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David G Delaney

Full Text Available Determining the residency of an aquatic species is important but challenging and it remains unclear what is the best sampling methodology. Photo-identification has been used extensively to estimate patterns of animals' residency and is arguably the most common approach, but it may not be the most effective approach in marine environments. To examine this, in 2005, we deployed acoustic transmitters on 22 white sharks (Carcharodon carcharias in Mossel Bay, South Africa to quantify the probability of detecting these tagged sharks by photo-identification and different deployment strategies of acoustic telemetry equipment. Using the data collected by the different sampling approaches (detections from an acoustic listening station deployed under a chumming vessel versus those from visual sightings and photo-identification, we quantified the methodologies' probability of detection and determined if the sampling approaches, also including an acoustic telemetry array, produce comparable results for patterns of residency. Photo-identification had the lowest probability of detection and underestimated residency. The underestimation is driven by various factors primarily that acoustic telemetry monitors a large area and this reduces the occurrence of false negatives. Therefore, we propose that researchers need to use acoustic telemetry and also continue to develop new sampling approaches as photo-identification techniques are inadequate to determine residency. Using the methods presented in this paper will allow researchers to further refine sampling approaches that enable them to collect more accurate data that will result in better research and more informed management efforts and policy decisions.

DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

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Lawhern, Vernon; Hairston, W David; Robbins, Kay

2013-01-01

Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG) data as an additional illustration.

DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

Directory of Open Access Journals (Sweden)

Vernon Lawhern

Full Text Available Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG data as an additional illustration.

Identification of volatiles by headspace gas chromatography with simultaneous flame ionization and mass spectrometric detection.

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Tiscione, Nicholas B; Yeatman, Dustin Tate; Shan, Xiaoqin; Kahl, Joseph H

2013-10-01

Volatiles are frequently abused as inhalants. The methods used for identification are generally nonspecific if analyzed concurrently with ethanol or require an additional analytical procedure that employs mass spectrometry. A previously published technique utilizing a capillary flow technology splitter to simultaneously quantitate and confirm ethyl alcohol by flame ionization and mass spectrometric detection after headspace sampling and gas chromatographic separation was evaluated for the detection of inhalants. Methanol, isopropanol, acetone, acetaldehyde, toluene, methyl ethyl ketone, isoamyl alcohol, isobutyl alcohol, n-butyl alcohol, 1,1-difluoroethane, 1,1,1-trifluoroethane, 1,1,1,2-tetrafluoroethane (Norflurane, HFC-134a), chloroethane, trichlorofluoromethane (Freon®-11), dichlorodifluoromethane (Freon®-12), dichlorofluoromethane (Freon®-21), chlorodifluoromethane (Freon®-22) and 1,2-dichlorotetrafluoroethane (Freon®-114) were validated for qualitative identification by this method. The validation for qualitative identification included evaluation of matrix effects, sensitivity, carryover, specificity, repeatability and ruggedness/robustness.

Molecular-Based Identification and Detection of Salmonella in Food Production Systems: Current Perspectives.

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Ricke, Steven C; Kim, Sun Ae; Shi, Zhaohao; Park, Si Hong

2018-04-19

Salmonella remains a prominent cause of foodborne illnesses and can originate from a wide range of food products. Given the continued presence of pathogenic Salmonella in food production systems, there is a consistent need to improve identification and detection methods that can identify this pathogen at all stages in food systems. Methods for subtyping have evolved over the years, and the introduction of whole genome sequencing and advancements in PCR technologies has greatly improved the resolution for differentiating strains within a particular serovar. This, in turn, has led to the continued improvement in Salmonella detection technologies for utilization in food production systems. In this review, the focus will be on recent advancements in these technologies, as well as potential issues associated with the application of these tools in food production. In addition, the recent and emerging research developments on Salmonella detection and identification methodologies and their potential application in food production systems will be discussed. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

A portable neutron spectroscope (NSPECT) for detection, imaging and identification of nuclear material

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Ryan, James M.; Bancroft, Christopher; Bloser, Peter; Bravar, Ulisse; Fourguette, Dominique; Frost, Colin; Larocque, Liane; McConnell, Mark L.; Legere, Jason; Pavlich, Jane; Ritter, Greg; Wassick, Greg; Wood, Joshua; Woolf, Richard

2010-08-01

We have developed, fabricated and tested a prototype imaging neutron spectrometer designed for real-time neutron source location and identification. Real-time detection and identification is important for locating materials. These materials, specifically uranium and transuranics, emit neutrons via spontaneous or induced fission. Unlike other forms of radiation (e.g. gamma rays), penetrating neutron emission is very uncommon. The instrument detects these neutrons, constructs images of the emission pattern, and reports the neutron spectrum. The device will be useful for security and proliferation deterrence, as well as for nuclear waste characterization and monitoring. The instrument is optimized for imaging and spectroscopy in the 1-20 MeV range. The detection principle is based upon multiple elastic neutron-proton scatters in organic scintillator. Two detector panel layers are utilized. By measuring the recoil proton and scattered neutron locations and energies, the direction and energy spectrum of the incident neutrons can be determined and discrete and extended sources identified. Event reconstruction yields an image of the source and its location. The hardware is low power, low mass, and rugged. Its modular design allows the user to combine multiple units for increased sensitivity. We will report the results of laboratory testing of the instrument, including exposure to a calibrated Cf-252 source. Instrument parameters include energy and angular resolution, gamma rejection, minimum source identification distances and times, and projected effective area for a fully populated instrument.

Highly accurate fluorogenic DNA sequencing with information theory-based error correction.

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Chen, Zitian; Zhou, Wenxiong; Qiao, Shuo; Kang, Li; Duan, Haifeng; Xie, X Sunney; Huang, Yanyi

2017-12-01

Eliminating errors in next-generation DNA sequencing has proved challenging. Here we present error-correction code (ECC) sequencing, a method to greatly improve sequencing accuracy by combining fluorogenic sequencing-by-synthesis (SBS) with an information theory-based error-correction algorithm. ECC embeds redundancy in sequencing reads by creating three orthogonal degenerate sequences, generated by alternate dual-base reactions. This is similar to encoding and decoding strategies that have proved effective in detecting and correcting errors in information communication and storage. We show that, when combined with a fluorogenic SBS chemistry with raw accuracy of 98.1%, ECC sequencing provides single-end, error-free sequences up to 200 bp. ECC approaches should enable accurate identification of extremely rare genomic variations in various applications in biology and medicine.

[Evaluation of common commercial systems for the identification of yeast isolates in microbiology laboratories: a multicenter study].

Science.gov (United States)

Karabıçak, Nilgün; Uludağ Altun, Hatice; Karatuna, Onur; Hazırolan, Gülşen; Aksu, Neriman; Adiloğlu, Ali; Akyar, Işın

2015-04-01

Accurate and rapid identification of yeast isolates have become important in recent years for not only antifungal susceptibility testing due to the species-specific clinical resistance breakpoints but also early initiation of appropriate antifungal therapy. In clinical microbiology laboratories species identification of yeasts is often performed with several commercial systems based on biochemical properties and rarely according to the physiological and morphological characteristics. The aim of this study was to compare the two common commercial systems, VITEK 2 YST ID Card (Vitek; bioMérieux, France) and API 20C AUX (API; bioMérieux, France) with conventional mycological methods. A total of 473 clinical yeast strains isolated from clinical specimens in different university and training/research hospitals and identified by Vitek system were included in the study. The isolates were re-identified with API and conventional methods including morphological identification in the Mycology Reference Laboratory of the Public Health Institute of Turkey. Candida dubliniensis MYA 583, Candida krusei ATCC 6258, Candida parapsilosis ATCC 22019, Candida albicans ATCC 10231 and Cryptococcus neoformans ATCC 32268 were used as quality control strains and those standard strains were studied consecutively 10 days with both of the methods. The results of identification by Vitek and API were compared with the results of conventional methods for those 473 yeast isolates [6 genus (Candida, Cryptococcus, Blastoshizomyces, Rhodotorula, Saccharomyces, Trichosporon), 17 species (5 common and 12 rarely isolated)]. The performances of the systems were better (Vitek: 95%; API: 96%) for the commonly detected species (C.albicans, C.parapsilosis, C.glabrata, C.tropicalis and C.krusei) than those for rarely detected species (Vitek: 78.4%; API: 71.6%) (p= 0.155). Misidentification or unidentification were mostly detected for C.parapsilosis (Vitek: 6/87; API: 7/87) and C.glabrata (Vitek: 9/104; API

Methods of the Detection and Identification of Structural Defects in Saturated Metallic Composite Castings

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Gawdzińska K.

2017-09-01

Full Text Available Diagnostics of composite castings, due to their complex structure, requires that their characteristics are tested by an appropriate description method. Any deviation from the specific characteristic will be regarded as a material defect. The detection of defects in composite castings sometimes is not sufficient and the defects have to be identified. This study classifies defects found in the structures of saturated metallic composite castings and indicates those stages of the process where such defects are likely to be formed. Not only does the author determine the causes of structural defects, describe methods of their detection and identification, but also proposes a schematic procedure to be followed during detection and identification of structural defects of castings made from saturated reinforcement metallic composites. Alloys examination was conducted after technological process, while using destructive (macroscopic tests, light and scanning electron microscopy and non-destructive (ultrasonic and X-ray defectoscopy, tomography, gravimetric method methods. Research presented in this article are part of author’s work on castings quality.

Rapid identification of bacteria in positive blood culture broths by matrix-assisted laser desorption ionization-time of flight mass spectrometry.

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Stevenson, Lindsay G; Drake, Steven K; Murray, Patrick R

2010-02-01

Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry is a rapid, accurate method for identifying bacteria and fungi recovered on agar culture media. We report herein a method for the direct identification of bacteria in positive blood culture broths by MALDI-TOF mass spectrometry. A total of 212 positive cultures were examined, representing 32 genera and 60 species or groups. The identification of bacterial isolates by MALDI-TOF mass spectrometry was compared with biochemical testing, and discrepancies were resolved by gene sequencing. No identification (spectral score of blood culture broth. Of the bacteria with a spectral score of > or = 1.7, 162 (95.3%) of 170 isolates were correctly identified. All 8 isolates of Streptococcus mitis were misidentified as being Streptococcus pneumoniae isolates. This method provides a rapid, accurate, definitive identification of bacteria within 1 h of detection in positive blood cultures with the caveat that the identification of S. pneumoniae would have to be confirmed by an alternative test.

Spectroscopic methods for detection of impurities in water

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Strashnikova, Natalia V.; Papiashvili, Nona; Cohen-Luria, Rivka; Mark, Shlomo; Shilon, Guy; Khankin, Daniel; Kalisky, Yehoshua; Kalisky, Ofra; Parola, Abraham H.

2011-11-01

Optical photoluminescence spectroscopic method for detection of impurities, hazardous materials, pesticides, and pollutants in water resources, both qualitatively and quantitatively, is presented. The method is based on synchronous fluorescence spectroscopy (SFS) of organic aromatic compounds, or poly-aromatic hydrocarbons (PAH), and is carried out by following simultaneously their excitation and emission spectra. The full excitation emission matrix (EEM) generated in this way provides a 2-D and 3-D fluorescence map of the tested sample and the diagonals through the axes origin provide the synchronous fluorescence spectra at a constant wavelengths differences between the emission and excitation wavelengths, thus enabling multitude components identification. This map contains all the relevant spectroscopic information of the tested sample, and serves as a unique "fingerprint" with a very specific and accurate identification. When compared with pre-determined spectra and calibration curves from a "databank", there is a one-toone correspondence between the image and the specific compound, and it can be identified accurately both qualitatively and quantitatively. This method offers several significant advantages, and it provides a sensitive (ppm detection level), accurate and simple spectroscopic tool to monitor impurities and pollutants in water. The design and performance of the spectrofluorimeter prototype, as well as the software development and analysis of chemical organic compounds and mixtures in water will be discussed in this paper.

A Robust Motion Artifact Detection Algorithm for Accurate Detection of Heart Rates From Photoplethysmographic Signals Using Time-Frequency Spectral Features.

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Dao, Duy; Salehizadeh, S M A; Noh, Yeonsik; Chong, Jo Woon; Cho, Chae Ho; McManus, Dave; Darling, Chad E; Mendelson, Yitzhak; Chon, Ki H

2017-09-01

Motion and noise artifacts (MNAs) impose limits on the usability of the photoplethysmogram (PPG), particularly in the context of ambulatory monitoring. MNAs can distort PPG, causing erroneous estimation of physiological parameters such as heart rate (HR) and arterial oxygen saturation (SpO2). In this study, we present a novel approach, "TifMA," based on using the time-frequency spectrum of PPG to first detect the MNA-corrupted data and next discard the nonusable part of the corrupted data. The term "nonusable" refers to segments of PPG data from which the HR signal cannot be recovered accurately. Two sequential classification procedures were included in the TifMA algorithm. The first classifier distinguishes between MNA-corrupted and MNA-free PPG data. Once a segment of data is deemed MNA-corrupted, the next classifier determines whether the HR can be recovered from the corrupted segment or not. A support vector machine (SVM) classifier was used to build a decision boundary for the first classification task using data segments from a training dataset. Features from time-frequency spectra of PPG were extracted to build the detection model. Five datasets were considered for evaluating TifMA performance: (1) and (2) were laboratory-controlled PPG recordings from forehead and finger pulse oximeter sensors with subjects making random movements, (3) and (4) were actual patient PPG recordings from UMass Memorial Medical Center with random free movements and (5) was a laboratory-controlled PPG recording dataset measured at the forehead while the subjects ran on a treadmill. The first dataset was used to analyze the noise sensitivity of the algorithm. Datasets 2-4 were used to evaluate the MNA detection phase of the algorithm. The results from the first phase of the algorithm (MNA detection) were compared to results from three existing MNA detection algorithms: the Hjorth, kurtosis-Shannon entropy, and time-domain variability-SVM approaches. This last is an approach

Accurate detection of hierarchical communities in complex networks based on nonlinear dynamical evolution

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Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

2018-04-01

One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community

Autonomous system for pathogen detection and identification

International Nuclear Information System (INIS)

Belgrader, P.; Benett, W.; Langlois, R.; Long, G.; Mariella, R.; Milanovich, F.; Miles, R.; Nelson, W.; Venkateswaran, K.

1998-01-01

This purpose of this project is to build a prototype instrument that will, running unattended, detect, identify, and quantify BW agents. In order to accomplish this, we have chosen to start with the world s leading, proven, assays for pathogens: surface-molecular recognition assays, such as antibody-based assays, implemented on a high-performance, identification (ID)-capable flow cytometer, and the polymerase chain reaction (PCR) for nucleic-acid based assays. With these assays, we must integrate the capability to: l collect samples from aerosols, water, or surfaces; l perform sample preparation prior to the assays; l incubate the prepared samples, if necessary, for a period of time; l transport the prepared, incubated samples to the assays; l perform the assays; l interpret and report the results of the assays. Issues such as reliability, sensitivity and accuracy, quantity of consumables, maintenance schedule, etc. must be addressed satisfactorily to the end user. The highest possible sensitivity and specificity of the assay must be combined with no false alarms. Today, we have assays that can, in under 30 minutes, detect and identify stimulants for BW agents at concentrations of a few hundred colony-forming units per ml of solution. If the bio-aerosol sampler of this system collects 1000 Ymin and concentrates the respirable particles into 1 ml of solution with 70% processing efficiency over a period of 5 minutes, then this translates to a detection/ID capability of under 0.1 agent-containing particle/liter of air

Subtle pulmonary nodules: detection and identification with storage phosphor radiographs and conventional chest films

International Nuclear Information System (INIS)

Scheck, R.J.; Schaetzl, M.; Kandziora, C.; Panzer, M.; Rienmueller, R.

1994-01-01

To determine the value of digital storagephosphor radiography (SR) on the detection and identification of subtle lung nodules, postero-anterior (PA) and lateral (LAT) film-screen (FR) chest radiographs were compared with isodose SR images of 45 patients with metastatic malignancies. The SR postprocessing was done with a particular mode previously optimized for routine chest radiography. Pulmonary metastases were found in 34 patients and were proved or excluded by CT (n=28) or longterm follow-up FR (n=17). Chest images were divided into four regions for evaluation of image quality, number of lung nodules per region and marked pulmonary structures by receiver-operating characteristics (ROC) analysis (45 patients; 125 nodules; 2810 observations; five readers). Of the nodules selected for an ROC study 82% were 0.5-1.0 cm in diameter. Overall image quality was rated better for FR concerning lung fields (PA) and mediastinum/hilum (LAT). More lung-field nodules were detected on FR than on SR chest images. Use of FR was superior to SR in the general identification of nodules (PA chest), especially concerning intermediate and subtle abnormalities, whereas there was no significant difference for LAT chest images. Our results show, that currently FR still has advantages over SR in the detection and identification of subtle lung nodules in routine clinical radiography. (orig.)

Detection of biosurfactants in Bacillus species: genes and products identification.

Science.gov (United States)

Płaza, G; Chojniak, J; Rudnicka, K; Paraszkiewicz, K; Bernat, P

2015-10-01

To screen environmental Bacillus strains for detection of genes encoding the enzymes involved in biosurfactant synthesis and to evaluate their products e.g. surfactin, iturin and fengycin. The taxonomic identification of isolated from the environment Bacillus strains was performed by Microgene ID Bacillus panel and GEN III Biolog system. The polymerase chain reaction (PCR) strategy for screening of genes in Bacillus strains was set up. Liquid chromatography-mass spectrometry (LC-MS/MS) method was used for the identification of lipopeptides (LPs). All studied strains exhibited the presence of srfAA gene and produced surfactin mostly as four homologues (C13 to C16). Moreover, in 2 strains (KP7, T'-1) simultaneous co-production of 3 biosurfactants: surfactin, iturin and fengycin was observed. Additionally, it was found out that isolate identified as Bacillus subtilis ssp. subtilis (KP7), beside LPs co-production, synthesizes surfactin with the efficiency much higher than other studied strains (40·2 mg l(-1) ) and with the yield ranging from 0·8 to 8·3 mg l(-1) . We showed that the combined methodology based on PCR and LC-MS/MS technique is an optimal tool for the detection of genes encoding enzymes involved in biosurfactant synthesis as well as their products, e.g. surfactin, iturin and fengycin. This approach improves the screening and the identification of environmental Bacillus co-producing biosurfactants-stimulating and facilitating the development of this area of science. The findings of this work will help to improve screening of biosurfactant producers. Discovery of novel biosurfactants and biosurfactants co-production ability has shed light on their new application fields and for the understanding of their interactions and properties. © 2015 The Society for Applied Microbiology.

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

Science.gov (United States)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

Accurate, safe, and rapid method of intraoperative tumor identification for totally laparoscopic distal gastrectomy: injection of mixed fluid of sodium hyaluronate and patent blue.

Science.gov (United States)

Nakagawa, Masatoshi; Ehara, Kazuhisa; Ueno, Masaki; Tanaka, Tsuyoshi; Kaida, Sachiko; Udagawa, Harushi

2014-04-01

In totally laparoscopic distal gastrectomy, determining the resection line with safe proximal margins is often difficult, particularly for tumors located in a relatively upper area. This is because, in contrast to open surgery, identifying lesions by palpating or opening the stomach is essentially impossible. This study introduces a useful method of tumor identification that is accurate, safe, and rapid. On the operation day, after inducing general anesthesia, a mixture of sodium hyaluronate and patent blue is injected into the submucosal layer of the proximal margin. When resecting stomach, all marker spots should be on the resected side. In all cases, the proximal margin is examined histologically by using frozen sections during the operation. From October 2009 to September 2011, a prospective study that evaluated this method was performed. A total of 34 patients who underwent totally laparoscopic distal gastrectomy were enrolled in this study. Approximately 5 min was required to complete the procedure. Proximal margins were negative in all cases, and the mean ± standard deviation length of the proximal margin was 23.5 ± 12.8 mm. No side effects, such as allergy, were encountered. As a method of tumor identification for totally laparoscopic distal gastrectomy, this procedure appears accurate, safe, and rapid.

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

Science.gov (United States)

Pelletier, R. E.; Griffin, R. H.

1985-01-01

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

Rapid Electrochemical Detection and Identification of Microbiological and Chemical Contaminants for Manned Spaceflight Project

Science.gov (United States)

Pierson, Duane; Botkin, Douglas; Gazda, Daniel

2014-01-01

Microbial control in the spacecraft environment is a daunting task, especially in the presence of human crew members. Currently, assessing the potential crew health risk associated with a microbial contamination event requires return of representative environmental samples that are analyzed in a ground-based laboratory. It is therefore not currently possible to quickly identify microbes during spaceflight. This project addresses the unmet need for spaceflight-compatible microbial identification technology. The electrochemical detection and identification platform is expected to provide a sensitive, specific, and rapid sample-to-answer capability for in-flight microbial monitoring that can distinguish between related microorganisms (pathogens and non-pathogens) as well as chemical contaminants. This will dramatically enhance our ability to monitor the spacecraft environment and the health risk to the crew. Further, the project is expected to eliminate the need for sample return while significantly reducing crew time required for detection of multiple targets. Initial work will focus on the optimization of bacterial detection and identification. The platform is designed to release nucleic acids (DNA and RNA) from microorganisms without the use of harmful chemicals. Bacterial DNA or RNA is captured by bacteria-specific probe molecules that are bound to a microelectrode, and that capture event can generate a small change in the electrical current (Lam, et al. 2012. Anal. Chem. 84(1): 21-5.). This current is measured, and a determination is made whether a given microbe is present in the sample analyzed. Chemical detection can be accomplished by directly applying a sample to the microelectrode and measuring the resulting current change. This rapid microbial and chemical detection device is designed to be a low-cost, low-power platform anticipated to be operated independently of an external power source, characteristics optimal for manned spaceflight and areas where power

[Evaluation of a rapid trehalase test for the identification of Candida glabrata].

Science.gov (United States)

Kirdar, Sevin; Gültekin, Berna; Evcil, Gonca; Ozkütük, Aydan; Sener, Asli Gamze; Aydin, Neriman

2009-04-01

Candida species which cause local infections, may also lead to fatal systemic infections. The increasing incidence of non-albicans Candida, especially fluconazole susceptible or resistant dose-dependent C. glabrata, increased the importance of rapid and accurate species level identification for Candida. Rapid and correct identification of C. glabrata is essential for the initiation of the appropriate antifungal therapy. This study was conducted to evaluate the performance of the rapid trehalase test in the diagnosis of C. glabrata isolates. A total of 173 Candida strains isolated from various clinical specimens and identified according to germ tube test, growth on cornmeal Tween 80 agar and the colony morphologies on Mast-CHROMagar Candida medium (Mast Diagnostics, UK), were included to the study. The identification of non-albicans Candida species were also confirmed by API 20CAUX (BioMerieux, France) system. Accordingly 86 (50%) of the isolates were identified as C. glabrata, 48 (28%) C. albicans, 17 (10%) C. krusei, 13 (8%) C. tropicalis, 5 (3%) C. parapsilosis, 3 (2%) C. kefyr and 1 (1%) Cutilis. In order to detect the presence of trehalase enzyme in Condida strains, all isolates were grown on Sabouraud dextrose agar containing 4% glucose and then one yeast colony was emulsified in 50 microl of citrate buffer containing 4% (wt/vol) trehalose for 3 h at 37 degrees C. Presence of glucose which emerged after the action of trehalase on trehalose, was detected by a commercial "urinary glucose detection dipstick" (Spinreacta, Spain). All C. glabrata strains yielded positive result by trehalase test. None C. glabrata isolates were found negative by trehalase test except for one strain of C. tropicalis. In this study, the trehalase test allowed identification of C. globrata with 100% sensitivity and 98.9% specificity. It was concluded that trehalase test is a rapid, cost-effective and simple test that can be used for the accurate identification of C. glabrata.

Dynamic surface-enhanced Raman spectroscopy and Chemometric methods for fast detection and intelligent identification of methamphetamine and 3, 4-Methylenedioxy methamphetamine in human urine

Science.gov (United States)

Weng, Shizhuang; Dong, Ronglu; Zhu, Zede; Zhang, Dongyan; Zhao, Jinling; Huang, Linsheng; Liang, Dong

2018-01-01

Conventional Surface-Enhanced Raman Spectroscopy (SERS) for fast detection of drugs in urine on the portable Raman spectrometer remains challenges because of low sensitivity and unreliable Raman signal, and spectra process with manual intervention. Here, we develop a novel detection method of drugs in urine using chemometric methods and dynamic SERS (D-SERS) with mPEG-SH coated gold nanorods (GNRs). D-SERS combined with the uniform GNRs can obtain giant enhancement, and the signal is also of high reproducibility. On the basis of the above advantages, we obtained the spectra of urine, urine with methamphetamine (MAMP), urine with 3, 4-Methylenedioxy Methamphetamine (MDMA) using D-SERS. Simultaneously, some chemometric methods were introduced for the intelligent and automatic analysis of spectra. Firstly, the spectra at the critical state were selected through using K-means. Then, the spectra were proposed by random forest (RF) with feature selection and principal component analysis (PCA) to develop the recognition model. And the identification accuracy of model were 100%, 98.7% and 96.7%, respectively. To validate the effect in practical issue further, the drug abusers'urine samples with 0.4, 3, 30 ppm MAMP were detected using D-SERS and identified by the classification model. The high recognition accuracy of > 92.0% can meet the demand of practical application. Additionally, the parameter optimization of RF classification model was simple. Compared with the general laboratory method, the detection process of urine's spectra using D-SERS only need 2 mins and 2 μL samples volume, and the identification of spectra based on chemometric methods can be finish in seconds. It is verified that the proposed approach can provide the accurate, convenient and rapid detection of drugs in urine.

Accurate spectroscopic characterization of oxirane: A valuable route to its identification in Titan's atmosphere and the assignment of unidentified infrared bands

Energy Technology Data Exchange (ETDEWEB)

Puzzarini, Cristina [Dipartimento di Chimica " Giacomo Ciamician," Università di Bologna, Via Selmi 2, I-40126 Bologna (Italy); Biczysko, Malgorzata; Bloino, Julien; Barone, Vincenzo, E-mail: cristina.puzzarini@unibo.it [Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa (Italy)

2014-04-20

In an effort to provide an accurate spectroscopic characterization of oxirane, state-of-the-art computational methods and approaches have been employed to determine highly accurate fundamental vibrational frequencies and rotational parameters. Available experimental data were used to assess the reliability of our computations, and an accuracy on average of 10 cm{sup –1} for fundamental transitions as well as overtones and combination bands has been pointed out. Moving to rotational spectroscopy, relative discrepancies of 0.1%, 2%-3%, and 3%-4% were observed for rotational, quartic, and sextic centrifugal-distortion constants, respectively. We are therefore confident that the highly accurate spectroscopic data provided herein can be useful for identification of oxirane in Titan's atmosphere and the assignment of unidentified infrared bands. Since oxirane was already observed in the interstellar medium and some astronomical objects are characterized by very high D/H ratios, we also considered the accurate determination of the spectroscopic parameters for the mono-deuterated species, oxirane-d1. For the latter, an empirical scaling procedure allowed us to improve our computed data and to provide predictions for rotational transitions with a relative accuracy of about 0.02% (i.e., an uncertainty of about 40 MHz for a transition lying at 200 GHz).

Research on FBG-Based CFRP Structural Damage Identification Using BP Neural Network

Science.gov (United States)

Geng, Xiangyi; Lu, Shizeng; Jiang, Mingshun; Sui, Qingmei; Lv, Shanshan; Xiao, Hang; Jia, Yuxi; Jia, Lei

2018-06-01

A damage identification system of carbon fiber reinforced plastics (CFRP) structures is investigated using fiber Bragg grating (FBG) sensors and back propagation (BP) neural network. FBG sensors are applied to construct the sensing network to detect the structural dynamic response signals generated by active actuation. The damage identification model is built based on the BP neural network. The dynamic signal characteristics extracted by the Fourier transform are the inputs, and the damage states are the outputs of the model. Besides, damages are simulated by placing lumped masses with different weights instead of inducing real damages, which is confirmed to be feasible by finite element analysis (FEA). At last, the damage identification system is verified on a CFRP plate with 300 mm × 300 mm experimental area, with the accurate identification of varied damage states. The system provides a practical way for CFRP structural damage identification.

A transition radiation detector for RHIC featuring accurate tracking and dE/dx particle identification

Energy Technology Data Exchange (ETDEWEB)

O`Brien, E.; Lissauer, D.; McCorkle, S.; Polychronakos, V.; Takai, H. [Brookhaven National Lab., Upton, NY (United States); Chi, C.Y.; Nagamiya, S.; Sippach, W.; Toy, M.; Wang, D.; Wang, Y.F.; Wiggins, C.; Willis, W. [Columbia Univ., New York, NY (United States); Cherniatin, V.; Dolgoshein, B. [Moscow Institute of Physics and Engineering, (Russian Federation); Bennett, M.; Chikanian, A.; Kumar, S.; Mitchell, J.T.; Pope, K. [Yale Univ., New Haven, CT (United States)

1991-12-31

We describe the results of a test ran involving a Transition Radiation Detector that can both distinguish electrons from pions which momenta greater titan 0.7 GeV/c and simultaneously track particles passing through the detector. The particle identification is accomplished through a combination of the detection of Transition Radiation from the electron and the differences in electron and pion energy loss (dE/dx) in the detector. The dE/dx particle separation is most, efficient below 2 GeV/c while particle ID utilizing Transition Radiation effective above 1.5 GeV/c. Combined, the electron-pion separation is-better than 5 {times} 10{sup 2}. The single-wire, track-position resolution for the TRD is {approximately}230 {mu}m.

Simultaneous detection and identification of precursors, degradation and co-products of chemical warfare agents in drinking water by ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry.

Science.gov (United States)

Tak, Vijay; Purohit, Ajay; Pardasani, Deepak; Goud, D Raghavender; Jain, Rajeev; Dubey, D K

2014-11-28

Environmental markers of chemical warfare agents (CWAs) comprise millions of chemical structures. The simultaneous detection and identification of these environmental markers poses difficulty due to their diverse chemical properties. In this work, by using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF), a generic analytical method for the detection and identification of wide range of environmental markers of CWAs (including precursors, degradation and co-products of nerve agents and sesqui-mustards) in drinking water, was developed. The chromatographic analysis of 55 environmental markers of CWAs including isomeric and isobaric compounds was accomplished within 20 min, using 1.8 μm particle size column. Subsequent identification of the compounds was achieved by the accurate mass measurement of either protonated molecule [M+H](+) or ammonium adduct [M+NH4](+) and fragment ions. Isomeric and isobaric compounds were distinguished by chromatographic retention time, characteristic fragment ions generated by both in-source collision induced dissociation (CID) and CID in the collision cell by MS/MS experiments. The exact mass measurement errors for all ions were observed less than 3 ppm with internal calibration. The method limits of detection (LODs) and limits of quantification (LOQs) were determined in drinking water and found to be 1-50 ng mL(-1) and 5-125 ng mL(-1), respectively. Applicability of the proposed method was proved by determining the environmental markers of CWAs in aqueous samples provided by Organization for the Prohibition of Chemical Weapons during 34th official proficiency test. Copyright © 2014 Elsevier B.V. All rights reserved.

Rapid detection and identification of viral and bacterial fish pathogens using a DNA array‐based multiplex assay

DEFF Research Database (Denmark)

Lievens, B.; Frans, I.; Heusdens, C.

2011-01-01

for the simultaneous detection and identification of all cyprinid herpesviruses (CyHV‐1, CyHV‐2 and CyHV‐3) and some of the most important fish pathogenic Flavobacterium species, including F. branchiophilum, F. columnare and F. psychrophilum. For virus identification, the DNA polymerase and helicase genes were...

A Pre-Detection Based Anti-Collision Algorithm with Adjustable Slot Size Scheme for Tag Identification

Directory of Open Access Journals (Sweden)

Chiu-Kuo LIANG

2015-06-01

Full Text Available One of the research areas in RFID systems is a tag anti-collision protocol; how to reduce identification time with a given number of tags in the field of an RFID reader. There are two types of tag anti-collision protocols for RFID systems: tree based algorithms and slotted aloha based algorithms. Many anti-collision algorithms have been proposed in recent years, especially in tree based protocols. However, there still have challenges on enhancing the system throughput and stability due to the underlying technologies had faced different limitation in system performance when network density is high. Particularly, the tree based protocols had faced the long identification delay. Recently, a Hybrid Hyper Query Tree (H2QT protocol, which is a tree based approach, was proposed and aiming to speedup tag identification in large scale RFID systems. The main idea of H2QT is to track the tag response and try to predict the distribution of tag IDs in order to reduce collisions. In this paper, we propose a pre-detection tree based algorithm, called the Adaptive Pre-Detection Broadcasting Query Tree algorithm (APDBQT, to avoid those unnecessary queries. Our proposed APDBQT protocol can reduce not only the collisions but the idle cycles as well by using pre-detection scheme and adjustable slot size mechanism. The simulation results show that our proposed technique provides superior performance in high density environments. It is shown that the APDBQT is effective in terms of increasing system throughput and minimizing identification delay.

Identification of Sarcosine as a Target Molecule for the Canine Olfactory Detection of Prostate Carcinoma.

Science.gov (United States)

Pacik, Dalibor; Plevova, Mariana; Urbanova, Lucie; Lackova, Zuzana; Strmiska, Vladislav; Necas, Alois; Heger, Zbynek; Adam, Vojtech

2018-03-21

The hypothesis that dogs can detect malignant tumours through the identification of specific molecules is nearly 30 years old. To date, several reports have described the successful detection of distinct types of cancer. However, is still a lack of data regarding the specific molecules that can be recognized by a dog's olfactory apparatus. Hence, we performed a study with artificially prepared, well-characterized urinary specimens that were enriched with sarcosine, a widely reported urinary biomarker for prostate cancer (PCa). For the purposes of the study, a German shepherd dog was utilized for analyses of 60 positive and 120 negative samples. Our study provides the first evidence that a sniffer dog specially trained for the olfactory detection of PCa can recognize sarcosine in artificial urine with a performance [sensitivity of 90%, specificity of 95%, and precision of 90% for the highest amount of sarcosine (10 µmol/L)] that is comparable to the identification of PCa-diagnosed subjects (sensitivity of 93.5% and specificity of 91.6%). This study casts light on the unrevealed phenomenon of PCa olfactory detection and opens the door for further studies with canine olfactory detection and cancer diagnostics.

The new generation of detection and identification equipment

International Nuclear Information System (INIS)

Schultz, F.; Guerin, M.; Fort, Ph.

2009-01-01

The authors address the highly sensitive detection issue with real time identification of the risk nature, a problem which occurs every time a source is only fleetingly present (a pedestrian, a vehicle or an object on a conveyor belt passing by). They briefly present a range of instruments specially designed for this purpose, the SPIR-Ident instruments. These equipment use one or several large sensors, digital multichannel analyzers (one per sensor) and neutron and gamma measurements. Spectra are continuously processed, stabilized, linearized and normalized, and finally analyzed by an algorithm. The authors evoke the performance characterization and a return on experience after a 6 month-use for the control of passengers and luggage in airport

An improved EMD method for modal identification and a combined static-dynamic method for damage detection

Science.gov (United States)

Yang, Jinping; Li, Peizhen; Yang, Youfa; Xu, Dian

2018-04-01

Empirical mode decomposition (EMD) is a highly adaptable signal processing method. However, the EMD approach has certain drawbacks, including distortions from end effects and mode mixing. In the present study, these two problems are addressed using an end extension method based on the support vector regression machine (SVRM) and a modal decomposition method based on the characteristics of the Hilbert transform. The algorithm includes two steps: using the SVRM, the time series data are extended at both endpoints to reduce the end effects, and then, a modified EMD method using the characteristics of the Hilbert transform is performed on the resulting signal to reduce mode mixing. A new combined static-dynamic method for identifying structural damage is presented. This method combines the static and dynamic information in an equilibrium equation that can be solved using the Moore-Penrose generalized matrix inverse. The combination method uses the differences in displacements of the structure with and without damage and variations in the modal force vector. Tests on a four-story, steel-frame structure were conducted to obtain static and dynamic responses of the structure. The modal parameters are identified using data from the dynamic tests and improved EMD method. The new method is shown to be more accurate and effective than the traditional EMD method. Through tests with a shear-type test frame, the higher performance of the proposed static-dynamic damage detection approach, which can detect both single and multiple damage locations and the degree of the damage, is demonstrated. For structures with multiple damage, the combined approach is more effective than either the static or dynamic method. The proposed EMD method and static-dynamic damage detection method offer improved modal identification and damage detection, respectively, in structures.

Saliency Detection and Deep Learning-Based Wildfire Identification in UAV Imagery

Directory of Open Access Journals (Sweden)

Yi Zhao

2018-02-01

Full Text Available An unmanned aerial vehicle (UAV equipped with global positioning systems (GPS can provide direct georeferenced imagery, mapping an area with high resolution. So far, the major difficulty in wildfire image classification is the lack of unified identification marks, the fire features of color, shape, texture (smoke, flame, or both and background can vary significantly from one scene to another. Deep learning (e.g., DCNN for Deep Convolutional Neural Network is very effective in high-level feature learning, however, a substantial amount of training images dataset is obligatory in optimizing its weights value and coefficients. In this work, we proposed a new saliency detection algorithm for fast location and segmentation of core fire area in aerial images. As the proposed method can effectively avoid feature loss caused by direct resizing; it is used in data augmentation and formation of a standard fire image dataset ‘UAV_Fire’. A 15-layered self-learning DCNN architecture named ‘Fire_Net’ is then presented as a self-learning fire feature exactor and classifier. We evaluated different architectures and several key parameters (drop out ratio, batch size, etc. of the DCNN model regarding its validation accuracy. The proposed architecture outperformed previous methods by achieving an overall accuracy of 98%. Furthermore, ‘Fire_Net’ guarantied an average processing speed of 41.5 ms per image for real-time wildfire inspection. To demonstrate its practical utility, Fire_Net is tested on 40 sampled images in wildfire news reports and all of them have been accurately identified.

A simplified and accurate detection of the genetically modified wheat MON71800 with one calibrator plasmid.

Science.gov (United States)

Kim, Jae-Hwan; Park, Saet-Byul; Roh, Hyo-Jeong; Park, Sunghoon; Shin, Min-Ki; Moon, Gui Im; Hong, Jin-Hwan; Kim, Hae-Yeong

2015-06-01

With the increasing number of genetically modified (GM) events, unauthorized GMO releases into the food market have increased dramatically, and many countries have developed detection tools for them. This study described the qualitative and quantitative detection methods of unauthorized the GM wheat MON71800 with a reference plasmid (pGEM-M71800). The wheat acetyl-CoA carboxylase (acc) gene was used as the endogenous gene. The plasmid pGEM-M71800, which contains both the acc gene and the event-specific target MON71800, was constructed as a positive control for the qualitative and quantitative analyses. The limit of detection in the qualitative PCR assay was approximately 10 copies. In the quantitative PCR assay, the standard deviation and relative standard deviation repeatability values ranged from 0.06 to 0.25 and from 0.23% to 1.12%, respectively. This study supplies a powerful and very simple but accurate detection strategy for unauthorized GM wheat MON71800 that utilizes a single calibrator plasmid. Copyright © 2014 Elsevier Ltd. All rights reserved.

SU-E-J-149: Secondary Emission Detection for Improved Proton Relative Stopping Power Identification

Energy Technology Data Exchange (ETDEWEB)

Saunders, J; Musall, B; Erickson, A [Georgia Institute of Technology, Atlanta, GA (Georgia)

2015-06-15

Purpose: This research investigates application of secondary prompt gamma (PG) emission spectra, resulting from nuclear reactions induced by protons, to characterize tissue composition along the particle path. The objective of utilizing the intensity of discrete high-energy peaks of PG is to improve the accuracy of relative stopping power (RSP) values available for proton therapy treatment planning on a patient specific basis and to reduce uncertainty in dose depth calculations. Methods: In this research, MCNP6 was used to simulate PG emission spectra generated from proton induced nuclear reactions in medium of varying composition of carbon, oxygen, calcium and nitrogen, the predominant elements found in human tissue. The relative peak intensities at discrete energies predicted by MCNP6 were compared to the corresponding atomic composition of the medium. Results: The results have shown a good general agreement with experimentally measured values reported by other investigators. Unexpected divergence from experimental spectra was noted in the peak intensities for some cases depending on the source of the cross-section data when using compiled proton table libraries vs. physics models built into MCNP6. While the use of proton cross-section libraries is generally recommended when available, these libraries lack data for several less abundant isotopes. This limits the range of their applicability and forces the simulations to rely on physics models for reactions with natural atomic compositions. Conclusion: Current end-of-range proton imaging provides an average RSP for the total estimated track length. The accurate identification of tissue composition along the incident particle path using PG detection and characterization allows for improved determination of the tissue RSP on the local level. While this would allow for more accurate depth calculations resulting in tighter treatment margins, precise understanding of proton beam behavior in tissue of various

Automated systems in the identification and determination of methicillin resistance among coagulase negative staphylococci

Directory of Open Access Journals (Sweden)

Juliana Caierão

2006-05-01

Full Text Available Coagulase-negative staphylococci (CoNS are an important cause of nosocomial bacteremia, specially in patients with indwelling devices or those submitted to invasive medical procedures. The identification of species and the accurate and rapid detection of methicillin resistance are directly dependent on the quality of the identification and susceptibility tests used, either manual or automated. The objective of this study was to evaluate the accuracy of two automated systems MicroScan and Vitek - in the identification of CoNS species and determination of susceptibility to methicillin, considering as gold standard the biochemical tests and the characterization of the mecA gene by polymerase chain reaction, respectively. MicroScan presented better results in the identification of CoNS species (accuracy of 96.8 vs 78.8%, respectively; isolates from the following species had no precise identification: Staphylococcus haemolyticus, S. simulans, and S. capitis. Both systems were similar in the characterization of methicillin resistance. The higher discrepancies for gene mec detection were observed among species other than S. epidermidis (S. hominis, S. saprophyticus, S. sciuri, S. haemolyticus, S. warneri, S. cohnii, and those with borderline MICs.

Genome-wide identification of coding and non-coding conserved sequence tags in human and mouse genomes

Directory of Open Access Journals (Sweden)

Maggi Giorgio P

2008-06-01

Full Text Available Abstract Background The accurate detection of genes and the identification of functional regions is still an open issue in the annotation of genomic sequences. This problem affects new genomes but also those of very well studied organisms such as human and mouse where, despite the great efforts, the inventory of genes and regulatory regions is far from complete. Comparative genomics is an effective approach to address this problem. Unfortunately it is limited by the computational requirements needed to perform genome-wide comparisons and by the problem of discriminating between conserved coding and non-coding sequences. This discrimination is often based (thus dependent on the availability of annotated proteins. Results In this paper we present the results of a comprehensive comparison of human and mouse genomes performed with a new high throughput grid-based system which allows the rapid detection of conserved sequences and accurate assessment of their coding potential. By detecting clusters of coding conserved sequences the system is also suitable to accurately identify potential gene loci. Following this analysis we created a collection of human-mouse conserved sequence tags and carefully compared our results to reliable annotations in order to benchmark the reliability of our classifications. Strikingly we were able to detect several potential gene loci supported by EST sequences but not corresponding to as yet annotated genes. Conclusion Here we present a new system which allows comprehensive comparison of genomes to detect conserved coding and non-coding sequences and the identification of potential gene loci. Our system does not require the availability of any annotated sequence thus is suitable for the analysis of new or poorly annotated genomes.

An intrusion detection system based on fiber hydrophone

Science.gov (United States)

Liu, Junrong; Qiu, Xiufen; Shen, Heping

2017-10-01

This paper provides a new intrusion detection system based on fiber hydrophone, focusing beam forming figure positioning according to the near field and high precision sound source location algorithm which can accurately position the intrusion; obtaining its behavior path , obtaining the intrusion events related information such as speed form tracking intrusion trace; And analyze identification the detected intrusion behavior. If the monitor area is larger, the algorithm will take too much time once, and influence the system response time, for reduce the calculating time. This paper provides way that coarse location first, and then scanned for accuracy, so as to realize the intrusion events (such as car, etc.) the remote monitoring of positioning. The system makes up the blank in process capture of the fiber optic intrusion detection technology, and improves the understanding of the invasion. Through the capture of the process of intrusion behavior, and the fusion detection of intrusion behavior itself, thus analysis, judgment, identification of the intrusion information can greatly reduce the rate of false positives, greatly improved the reliability and practicability of the perimeter security system.

Accurate, fully-automated NMR spectral profiling for metabolomics.

Directory of Open Access Journals (Sweden)

Siamak Ravanbakhsh

Full Text Available Many diseases cause significant changes to the concentrations of small molecules (a.k.a. metabolites that appear in a person's biofluids, which means such diseases can often be readily detected from a person's "metabolic profile"-i.e., the list of concentrations of those metabolites. This information can be extracted from a biofluids Nuclear Magnetic Resonance (NMR spectrum. However, due to its complexity, NMR spectral profiling has remained manual, resulting in slow, expensive and error-prone procedures that have hindered clinical and industrial adoption of metabolomics via NMR. This paper presents a system, BAYESIL, which can quickly, accurately, and autonomously produce a person's metabolic profile. Given a 1D 1H NMR spectrum of a complex biofluid (specifically serum or cerebrospinal fluid, BAYESIL can automatically determine the metabolic profile. This requires first performing several spectral processing steps, then matching the resulting spectrum against a reference compound library, which contains the "signatures" of each relevant metabolite. BAYESIL views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures including real biological samples (serum and CSF, defined mixtures and realistic computer generated spectra; involving > 50 compounds, show that BAYESIL can autonomously find the concentration of NMR-detectable metabolites accurately (~ 90% correct identification and ~ 10% quantification error, in less than 5 minutes on a single CPU. These results demonstrate that BAYESIL is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively-with an accuracy on these biofluids that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of

Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles.

Science.gov (United States)

Bisgin, Halil; Bera, Tanmay; Ding, Hongjian; Semey, Howard G; Wu, Leihong; Liu, Zhichao; Barnes, Amy E; Langley, Darryl A; Pava-Ripoll, Monica; Vyas, Himansu J; Tong, Weida; Xu, Joshua

2018-04-25

Insect pests, such as pantry beetles, are often associated with food contaminations and public health risks. Machine learning has the potential to provide a more accurate and efficient solution in detecting their presence in food products, which is currently done manually. In our previous research, we demonstrated such feasibility where Artificial Neural Network (ANN) based pattern recognition techniques could be implemented for species identification in the context of food safety. In this study, we present a Support Vector Machine (SVM) model which improved the average accuracy up to 85%. Contrary to this, the ANN method yielded ~80% accuracy after extensive parameter optimization. Both methods showed excellent genus level identification, but SVM showed slightly better accuracy  for most species. Highly accurate species level identification remains a challenge, especially in distinguishing between species from the same genus which may require improvements in both imaging and machine learning techniques. In summary, our work does illustrate a new SVM based technique and provides a good comparison with the ANN model in our context. We believe such insights will pave better way forward for the application of machine learning towards species identification and food safety.

Detecting Cancer Quickly and Accurately

Science.gov (United States)

Gourley, Paul; McDonald, Anthony; Hendricks, Judy; Copeland, Guild; Hunter, John; Akhil, Ohmar; Capps, Heather; Curry, Marc; Skirboll, Steve

2000-03-01

We present a new technique for high throughput screening of tumor cells in a sensitive nanodevice that has the potential to quickly identify a cell population that has begun the rapid protein synthesis and mitosis characteristic of cancer cell proliferation. Currently, pathologists rely on microscopic examination of cell morphology using century-old staining methods that are labor-intensive, time-consuming and frequently in error. New micro-analytical methods for automated, real time screening without chemical modification are critically needed to advance pathology and improve diagnoses. We have teamed scientists with physicians to create a microlaser biochip (based upon our R&D award winning bio-laser concept)1 which evaluates tumor cells by quantifying their growth kinetics. The key new discovery was demonstrating that the lasing spectra are sensitive to the biomolecular mass in the cell, which changes the speed of light in the laser microcavity. Initial results with normal and cancerous human brain cells show that only a few hundred cells -- the equivalent of a billionth of a liter -- are required to detect abnormal growth. The ability to detect cancer in such a minute tissue sample is crucial for resecting a tumor margin or grading highly localized tumor malignancy. 1. P. L. Gourley, NanoLasers, Scientific American, March 1998, pp. 56-61. This work supported under DOE contract DE-AC04-94AL85000 and the Office of Basic Energy Sciences.

Detection, Identification, Location, and Remote Sensing Using SAW RFID Sensor Tags

Science.gov (United States)

Barton, Richard J.; Kennedy, Timothy F.; Williams, Robert M.; Fink, Patrick W.; Ngo, Phong H.

2009-01-01

The Electromagnetic Systems Branch (EV4) of the Avionic Systems Division at NASA Johnson Space Center in Houston, TX is studying the utility of surface acoustic wave (SAW) radiofrequency identification (RFID) tags for multiple wireless applications including detection, identification, tracking, and remote sensing of objects on the lunar surface, monitoring of environmental test facilities, structural shape and health monitoring, and nondestructive test and evaluation of assets. For all of these applications, it is anticipated that the system utilized to interrogate the SAW RFID tags may need to operate at fairly long range and in the presence of considerable multipath and multiple-access interference. Towards that end, EV4 is developing a prototype SAW RFID wireless interrogation system for use in such environments called the Passive Adaptive RFID Sensor Equipment (PARSED) system. The system utilizes a digitally beam-formed planar receiving antenna array to extend range and provide direction-of-arrival information coupled with an approximate maximum-likelihood signal processing algorithm to provide near-optimal estimation of both range and temperature. The system is capable of forming a large number of beams within the field of view and resolving the information from several tags within each beam. The combination of both spatial and waveform discrimination provides the capability to track and monitor telemetry from a large number of objects appearing simultaneously within the field of view of the receiving array. In this paper, we will consider the application of the PARSEQ system to the problem of simultaneous detection, identification, localization, and temperature estimation for multiple objects. We will summarize the overall design of the PARSEQ system and present a detailed description of the design and performance of the signal detection and estimation algorithms incorporated in the system. The system is currently configured only to measure temperature

Molecular techniques for the identification and detection of microorganisms relevant for the food industry

NARCIS (Netherlands)

Klijn, N.

1996-01-01

The research described in this thesis concerns the development and application in food microbiology of molecular identification and detection techniques based on 16S rRNA sequences. The technologies developed were applied to study the microbial ecology of two groups of bacteria, namely

Detection and identification of explosives and illicit drugs using neutron based techniques

International Nuclear Information System (INIS)

Papp, A.; Csikai, J.; Debrecen University,

2011-01-01

Some methods developed in collaboration between the ATOMKI and IEP for bulk hydrogen analysis and for the detection and identification of illicit drugs are presented. Advantages and limitations of neutron techniques (reflection, transmission, elastic and inelastic scatterings, leakage spectra and angular yields of Be(d,n), Pu-Be, D-D, D-T and 252 Cf neutrons transmitted from thick samples, effects of hidden materials) are discussed. (author)

Vibrotactile Detection, Identification and Directional Perception of signal-Processed Sounds from Environmental Events: A Pilot Field Evaluation in Five Cases

Directory of Open Access Journals (Sweden)

Parivash Ranjbar

2008-09-01

Full Text Available Objectives: Conducting field tests of a vibrotactile aid for deaf/deafblind persons for detection, identification and directional perception of environmental sounds. Methods: Five deaf (3F/2M, 22–36 years individuals tested the aid separately in a home environment (kitchen and in a traffic environment. Their eyes were blindfolded and they wore a headband and holding a vibrator for sound identification. In the headband, three microphones were mounted and two vibrators for signalling direction of the sound source. The sounds originated from events typical for the home environment and traffic. The subjects were inexperienced (events unknown and experienced (events known. They identified the events in a home and traffic environment, but perceived sound source direction only in traffic. Results: The detection scores were higher than 98% both in the home and in the traffic environment. In the home environment, identification scores varied between 25%-58% when the subjects were inexperienced and between 33%-83% when they were experienced. In traffic, identification scores varied between 20%-40% when the subjects were inexperienced and between 22%-56% when they were experienced. The directional perception scores varied between 30%-60% when inexperienced and between 61%-83% when experienced. Discussion: The vibratory aid consistently improved all participants’ detection, identification and directional perception ability.

An accurate and efficient identification of children with psychosocial problems by means of computerized adaptive testing

Directory of Open Access Journals (Sweden)

Reijneveld Symen A

2011-08-01

Full Text Available Abstract Background Questionnaires used by health services to identify children with psychosocial problems are often rather short. The psychometric properties of such short questionnaires are mostly less than needed for an accurate distinction between children with and without problems. We aimed to assess whether a short Computerized Adaptive Test (CAT can overcome the weaknesses of short written questionnaires when identifying children with psychosocial problems. Method We used a Dutch national data set obtained from parents of children invited for a routine health examination by Preventive Child Healthcare with 205 items on behavioral and emotional problems (n = 2,041, response 84%. In a random subsample we determined which items met the requirements of an Item Response Theory (IRT model to a sufficient degree. Using those items, item parameters necessary for a CAT were calculated and a cut-off point was defined. In the remaining subsample we determined the validity and efficiency of a Computerized Adaptive Test using simulation techniques, with current treatment status and a clinical score on the Total Problem Scale (TPS of the Child Behavior Checklist as criteria. Results Out of 205 items available 190 sufficiently met the criteria of the underlying IRT model. For 90% of the children a score above or below cut-off point could be determined with 95% accuracy. The mean number of items needed to achieve this was 12. Sensitivity and specificity with the TPS as a criterion were 0.89 and 0.91, respectively. Conclusion An IRT-based CAT is a very promising option for the identification of psychosocial problems in children, as it can lead to an efficient, yet high-quality identification. The results of our simulation study need to be replicated in a real-life administration of this CAT.

Accurate Natural Trail Detection Using a Combination of a Deep Neural Network and Dynamic Programming.

Science.gov (United States)

Adhikari, Shyam Prasad; Yang, Changju; Slot, Krzysztof; Kim, Hyongsuk

2018-01-10

This paper presents a vision sensor-based solution to the challenging problem of detecting and following trails in highly unstructured natural environments like forests, rural areas and mountains, using a combination of a deep neural network and dynamic programming. The deep neural network (DNN) concept has recently emerged as a very effective tool for processing vision sensor signals. A patch-based DNN is trained with supervised data to classify fixed-size image patches into "trail" and "non-trail" categories, and reshaped to a fully convolutional architecture to produce trail segmentation map for arbitrary-sized input images. As trail and non-trail patches do not exhibit clearly defined shapes or forms, the patch-based classifier is prone to misclassification, and produces sub-optimal trail segmentation maps. Dynamic programming is introduced to find an optimal trail on the sub-optimal DNN output map. Experimental results showing accurate trail detection for real-world trail datasets captured with a head mounted vision system are presented.

Ulysses: accurate detection of low-frequency structural variations in large insert-size sequencing libraries.

Science.gov (United States)

Gillet-Markowska, Alexandre; Richard, Hugues; Fischer, Gilles; Lafontaine, Ingrid

2015-03-15

The detection of structural variations (SVs) in short-range Paired-End (PE) libraries remains challenging because SV breakpoints can involve large dispersed repeated sequences, or carry inherent complexity, hardly resolvable with classical PE sequencing data. In contrast, large insert-size sequencing libraries (Mate-Pair libraries) provide higher physical coverage of the genome and give access to repeat-containing regions. They can thus theoretically overcome previous limitations as they are becoming routinely accessible. Nevertheless, broad insert size distributions and high rates of chimerical sequences are usually associated to this type of libraries, which makes the accurate annotation of SV challenging. Here, we present Ulysses, a tool that achieves drastically higher detection accuracy than existing tools, both on simulated and real mate-pair sequencing datasets from the 1000 Human Genome project. Ulysses achieves high specificity over the complete spectrum of variants by assessing, in a principled manner, the statistical significance of each possible variant (duplications, deletions, translocations, insertions and inversions) against an explicit model for the generation of experimental noise. This statistical model proves particularly useful for the detection of low frequency variants. SV detection performed on a large insert Mate-Pair library from a breast cancer sample revealed a high level of somatic duplications in the tumor and, to a lesser extent, in the blood sample as well. Altogether, these results show that Ulysses is a valuable tool for the characterization of somatic mosaicism in human tissues and in cancer genomes. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Photogrammetry: an accurate and reliable tool to detect thoracic musculoskeletal abnormalities in preterm infants.

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Davidson, Josy; dos Santos, Amelia Miyashiro N; Garcia, Kessey Maria B; Yi, Liu C; João, Priscila C; Miyoshi, Milton H; Goulart, Ana Lucia

2012-09-01

To analyse the accuracy and reproducibility of photogrammetry in detecting thoracic abnormalities in infants born prematurely. Cross-sectional study. The Premature Clinic at the Federal University of São Paolo. Fifty-eight infants born prematurely in their first year of life. Measurement of the manubrium/acromion/trapezius angle (degrees) and the deepest thoracic retraction (cm). Digitised photographs were analysed by two blinded physiotherapists using a computer program (SAPO; http://SAPO.incubadora.fapesp.br) to detect shoulder elevation and thoracic retraction. Physical examinations performed independently by two physiotherapists were used to assess the accuracy of the new tool. Thoracic alterations were detected in 39 (67%) and in 40 (69%) infants by Physiotherapists 1 and 2, respectively (kappa coefficient=0.80). Using a receiver operating characteristic curve, measurement of the manubrium/acromion/trapezius angle and the deepest thoracic retraction indicated accuracy of 0.79 and 0.91, respectively. For measurement of the manubrium/acromion/trapezius angle, the Bland and Altman limits of agreement were -6.22 to 7.22° [mean difference (d)=0.5] for repeated measures by one physiotherapist, and -5.29 to 5.79° (d=0.75) between two physiotherapists. For thoracic retraction, the intra-rater limits of agreement were -0.14 to 0.18cm (d=0.02) and the inter-rater limits of agreement were -0.20 to -0.17cm (d=0.02). SAPO provided an accurate and reliable tool for the detection of thoracic abnormalities in preterm infants. Copyright © 2011 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

Accurate method for luminous transmittance and signal detection quotients measurements in sunglasses lenses

Science.gov (United States)

Loureiro, A. D.; Gomes, L. M.; Ventura, L.

2018-02-01

The international standard ISO 12312-1 proposes transmittance tests that quantify how dark sunglasses lenses are and whether or not they are suitable for driving. To perform these tests a spectrometer is required. In this study, we present and analyze theoretically an accurate alternative method for performing these measurements using simple components. Using three LEDs and a four-channel sensor we generated weighting functions similar to the standard ones for luminous and traffic lights transmittances. From 89 sunglasses lens spectroscopy data, we calculated luminous transmittance and signal detection quotients using our obtained weighting functions and the standard ones. Mean-difference Tukey plots were used to compare the results. All tested sunglasses lenses were classified in the right category and correctly as suitable or not for driving. The greatest absolute errors for luminous transmittance and red, yellow, green and blue signal detection quotients were 0.15%, 0.17, 0.06, 0.04 and 0.18, respectively. This method will be used in a device capable to perform transmittance tests (visible, traffic lights and ultraviolet (UV)) according to the standard. It is important to measure rightly luminous transmittance and relative visual attenuation quotients to report correctly whether or not sunglasses are suitable for driving. Moreover, standard UV requirements depend on luminous transmittance.

Maximized Inter-Class Weighted Mean for Fast and Accurate Mitosis Cells Detection in Breast Cancer Histopathology Images.

Science.gov (United States)

Nateghi, Ramin; Danyali, Habibollah; Helfroush, Mohammad Sadegh

2017-08-14

Based on the Nottingham criteria, the number of mitosis cells in histopathological slides is an important factor in diagnosis and grading of breast cancer. For manual grading of mitosis cells, histopathology slides of the tissue are examined by pathologists at 40× magnification for each patient. This task is very difficult and time-consuming even for experts. In this paper, a fully automated method is presented for accurate detection of mitosis cells in histopathology slide images. First a method based on maximum-likelihood is employed for segmentation and extraction of mitosis cell. Then a novel Maximized Inter-class Weighted Mean (MIWM) method is proposed that aims at reducing the number of extracted non-mitosis candidates that results in reducing the false positive mitosis detection rate. Finally, segmented candidates are classified into mitosis and non-mitosis classes by using a support vector machine (SVM) classifier. Experimental results demonstrate a significant improvement in accuracy of mitosis cells detection in different grades of breast cancer histopathological images.

Identification of southern radio sources

International Nuclear Information System (INIS)

Savage, A.; Bolton, J.G.; Wright, A.E.

1977-01-01

Identifications are suggested for 53 radio sources from the southern zones of the Parkes 2700-MHz survey, 32 with galaxies, 11 with suggested QSOs and 10 with confirmed QSOs. The identifications were made from the ESO quick blue survey plates, the SRC IIIa-J deep survey plates and the Palomar Sky Survey prints. Accurate optical positions have been measured for four of the new identifications and for two previously suggested identifications. A further nine previously suggested QSO identifications have also been confirmed by two-colour photography or spectroscopy. (author)

Accurate, rapid identification of dislocation lines in coherent diffractive imaging via a min-max optimization formulation

Energy Technology Data Exchange (ETDEWEB)

Ulvestad, A. [Materials Science Division, Argonne National Laboratory, Lemont, IL 60439, USA; Menickelly, M. [Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL 60439, USA; Wild, S. M. [Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL 60439, USA

2018-01-01

Defects such as dislocations impact materials properties and their response during external stimuli. Imaging these defects in their native operating conditions to establish the structure-function relationship and, ultimately, to improve performance via defect engineering has remained a considerable challenge for both electron-based and x-ray-based imaging techniques. While Bragg coherent x-ray diffractive imaging (BCDI) is successful in many cases, nuances in identifying the dislocations has left manual identification as the preferred method. Derivative-based methods are also used, but they can be inaccurate and are computationally inefficient. Here we demonstrate a derivative-free method that is both more accurate and more computationally efficient than either derivative-or human-based methods for identifying 3D dislocation lines in nanocrystal images produced by BCDI. We formulate the problem as a min-max optimization problem and show exceptional accuracy for experimental images. We demonstrate a 227x speedup for a typical experimental dataset with higher accuracy over current methods. We discuss the possibility of using this algorithm as part of a sparsity-based phase retrieval process. We also provide MATLAB code for use by other researchers.

Filtering technique for detection and identification of measurement failures in nuclear power plants

International Nuclear Information System (INIS)

Racz, A.

1989-11-01

The basic requirement of the safe operation of nuclear power plants (NPP) is to have reliable information on all quantities that can be measured, monitored or controlled during the operation. Kalman filtering techniques have been applied for prompt detection and identification of failures in the measurement systems used in NPPs. Mathematical basis of Kalman filtering and various models applied to failure detection are overviewed. The applicability of some models are evaluated by real results of NPP measurements. A sample system for an NPP is suggested, based on several numerical tests. (R.P.) 23 refs.; 40 figs.; 2 tabs

Hydrogen sulfide detection based on reflection: from a poison test approach of ancient China to single-cell accurate localization.

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Kong, Hao; Ma, Zhuoran; Wang, Song; Gong, Xiaoyun; Zhang, Sichun; Zhang, Xinrong

2014-08-05

With the inspiration of an ancient Chinese poison test approach, we report a rapid hydrogen sulfide detection strategy in specific areas of live cells using silver needles with good spatial resolution of 2 × 2 μm(2). Besides the accurate-localization ability, this reflection-based strategy also has attractive merits of convenience and robust response when free pretreatment and short detection time are concerned. The success of endogenous H2S level evaluation in cellular cytoplasm and nuclear of human A549 cells promises the application potential of our strategy in scientific research and medical diagnosis.

PCR methodology as a valuable tool for identification of endodontic pathogens.

Science.gov (United States)

Siqueira, José F; Rôças, Isabela N

2003-07-01

This paper reviews the principles of polymerase chain reaction (PCR) methodology, its application in identification of endodontic pathogens and the perspectives regarding the knowledge to be reached with the use of this highly sensitive, specific and accurate methodology as a microbial identification test. Studies published in the medical, dental and biological literature. Evaluation of published epidemiological studies examining the endodontic microbiota through PCR methodology. PCR technology has enabled the detection of bacterial species that are difficult or even impossible to culture as well as cultivable bacterial strains showing a phenotypically divergent or convergent behaviour. Moreover, PCR is more rapid, much more sensitive, and more accurate when compared with culture. Its use in endodontics to investigate the microbiota associated with infected root canals has expanded the knowledge on the bacteria involved in the pathogenesis of periradicular diseases. For instance, Tannerella forsythensis (formerly Bacteroides forsythus), Treponema denticola, other Treponema species, Dialister pneumosintes, and Prevotella tannerae were detected in infected root canals for the first time and in high prevalence when using PCR analysis. The diversity of endodontic microbiota has been demonstrated by studies using PCR amplification, cloning and sequencing of the PCR products. Moreover, other fastidious bacterial species, such as Porphyromonas endodontalis, Porphyromonas gingivalis and some Eubacterium spp., have been reported in endodontic infections at a higher prevalence than those reported by culture procedures.

Identification and Damage Detection on Structural Systems

DEFF Research Database (Denmark)

Brincker, Rune; Kirkegaard, Poul Henning; Andersen, Palle

1994-01-01

A short introduction is given to system identification and damage assessment in civil engineering structures. The most commonly used FFT-based techniques for system identification are mentioned, and the Random decrement technique and parametric methods based on ARMA models are introduced. Speed...

Universal Detection and Identification of Avian Influenza Virus by Use of Resequencing Microarrays

Science.gov (United States)

2009-04-01

Recent outbreaks of Nipah virus , severe acute respiratory syndrome virus , and avian influenza virus reiterate the impor- tance of zoonotic microbes as...Society for Microbiology. All Rights Reserved. Universal Detection and Identification of Avian Influenza Virus by Use of Resequencing Microarrays...been, and continue to emerge as, threats to human health. The recent outbreaks of highly pathogenic avian influenza virus in bird populations and the

Extraordinary tunable dynamic range of electrochemical aptasensor for accurate detection of ochratoxin A in food samples

Directory of Open Access Journals (Sweden)

Lin Cheng

2017-06-01

Full Text Available We report the design of a sensitive, electrochemical aptasensor for detection of ochratoxin A (OTA with an extraordinary tunable dynamic sensing range. This electrochemical aptasensor is constructed based on the target induced aptamer-folding detection mechanism and the recognition between OTA and its aptamers results in the conformational change of the aptamer probe and thus signal changes for measurement. The dynamic sensing range of the electrochemical aptasensor is successfully tuned by introduction of free assistant aptamer probes in the sensing system. Our electrochemical aptasensor shows an extraordinary dynamic sensing range of 11-order magnitude of OTA concentration from 10−8 to 102 ng/g. Of great significance, the signal response in all OTA concentration ranges is at the same current scale, demonstrating that our sensing protocol in this research could be applied for accurate detections of OTA in a broad range without using any complicated treatment of signal amplification. Finally, OTA spiked red wine and maize samples in different dynamic sensing ranges are determined with the electrochemical aptasensor under optimized sensing conditions. This tuning strategy of dynamic sensing range may offer a promising platform for electrochemical aptasensor optimizations in practical applications.

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

Science.gov (United States)

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-06-22

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

Identification of hare meat by a species-specific marker of mitochondrial origin.

Science.gov (United States)

Santos, Cristina G; Melo, Vitor S; Amaral, Joana S; Estevinho, Letícia; Oliveira, M Beatriz P P; Mafra, Isabel

2012-03-01

Meat species identification in food has gained increasing interest in recent years due to public health, economic and legal concerns. Following the consumer trend towards high quality products, game meat has earned much attention. The aim of the present work was to develop a DNA-based technique able to identify hare meat. Mitochondrial cytochrome b gene was used to design species-specific primers for hare detection. The new primers proved to be highly specific to Lepus species, allowing the detection of 0.01% of hare meat in pork meat by polymerase chain reaction (PCR). A real-time PCR assay with the new intercalating EvaGreen dye was further proposed as a specific and fast tool for hare identification with increased sensitivity (1pg) compared to end-point PCR (10pg). It can be concluded that the proposed new primers can be used by both species-specific end-point PCR or real-time PCR to accurately authenticate hare meat. Copyright © 2011 Elsevier Ltd. All rights reserved.

Identification of southern radio sources

International Nuclear Information System (INIS)

Savage, A.; Bolton, J.G.; Wright, A.E.

1976-01-01

Identifications are suggested for 36 radio sources from the southern zones of the Parkes 2700 MHz survey, 28 with galaxies, six with confirmed and two with suggested quasi-stellar objects. The identifications were made from the ESO quick blue survey plates, the SRC IIIa-J deep survey plates and the Palomar sky survey prints. Accurate optical positions have also been measured for nine of the objects and for five previously suggested identifications. (author)

A highly accurate wireless digital sun sensor based on profile detecting and detector multiplexing technologies

Science.gov (United States)

Wei, Minsong; Xing, Fei; You, Zheng

2017-01-01

The advancing growth of micro- and nano-satellites requires miniaturized sun sensors which could be conveniently applied in the attitude determination subsystem. In this work, a profile detecting technology based high accurate wireless digital sun sensor was proposed, which could transform a two-dimensional image into two-linear profile output so that it can realize a high update rate under a very low power consumption. A multiple spots recovery approach with an asymmetric mask pattern design principle was introduced to fit the multiplexing image detector method for accuracy improvement of the sun sensor within a large Field of View (FOV). A FOV determination principle based on the concept of FOV region was also proposed to facilitate both sub-FOV analysis and the whole FOV determination. A RF MCU, together with solar cells, was utilized to achieve the wireless and self-powered functionality. The prototype of the sun sensor is approximately 10 times lower in size and weight compared with the conventional digital sun sensor (DSS). Test results indicated that the accuracy of the prototype was 0.01° within a cone FOV of 100°. Such an autonomous DSS could be equipped flexibly on a micro- or nano-satellite, especially for highly accurate remote sensing applications.

Identification of anti-HPA-1a allo-antibodies using IgG platelet antibody detection and crossmatch system assay with Galileo Echo.

Science.gov (United States)

Di Cristofaro, Julie; Frassati, Coralie; Montagnie, Rolande; Basire, Agnes; Merieux, Yves; Picard, Christophe

2015-01-01

Fetal/neonatal allo-immune thrombocytopenia is the most frequent and the most dangerous clinical condition involving anti-human platelet antigens (HPA)-1a allo-antibodies. Anti-HPA-1a allo-immunization requires rapid and accurate diagnosis to determine appropriate treatment. The Capture-P Ready-Screen assay (C-PRS) is a new qualitative immunoassay to detect IgG anti-human leukocyte antigen (HLA) and anti-HPA allo-antibodies. The aim of this study is to assess the identification of anti-HPA-1a allo-antibodies using the C-PRS assay, associated with HLA class I stripping reagents, on the automated benchtop analyzer Galileo Echo. Forty-nine sera were analyzed: without anti-HLA class I or anti-HPA allo-antibodies, with anti-HLA class I allo-antibodies, with anti-HPA-1a allo-antibodies, among which with anti-HLA class I allo-antibodies. None of the samples without allo-antibodies were reactive. Only anti-HLA antibodies, detected by cytotoxicity-dependent complement and not by Luminex, remained positive before and after stripping reagents. Of the 13 samples, anti-HPA-1a allo-antibodies that were correctly identified before and after incubation with HLA assassin reagent were 70% and 85%, respectively. Anti-glycoprotein auto-antibodies and anti-HLA allo-antibodies do not interfere with the detection of anti-HPA-1a antibodies. This preliminary study indicates that further improvement of the test will be helpful in developing a clinically useful assay in the future.

OPTICAL correlation identification technology applied in underwater laser imaging target identification

Science.gov (United States)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve

Fast, accurate, and robust automatic marker detection for motion correction based on oblique kV or MV projection image pairs

International Nuclear Information System (INIS)

Slagmolen, Pieter; Hermans, Jeroen; Maes, Frederik; Budiharto, Tom; Haustermans, Karin; Heuvel, Frank van den

2010-01-01

Purpose: A robust and accurate method that allows the automatic detection of fiducial markers in MV and kV projection image pairs is proposed. The method allows to automatically correct for inter or intrafraction motion. Methods: Intratreatment MV projection images are acquired during each of five treatment beams of prostate cancer patients with four implanted fiducial markers. The projection images are first preprocessed using a series of marker enhancing filters. 2D candidate marker locations are generated for each of the filtered projection images and 3D candidate marker locations are reconstructed by pairing candidates in subsequent projection images. The correct marker positions are retrieved in 3D by the minimization of a cost function that combines 2D image intensity and 3D geometric or shape information for the entire marker configuration simultaneously. This optimization problem is solved using dynamic programming such that the globally optimal configuration for all markers is always found. Translational interfraction and intrafraction prostate motion and the required patient repositioning is assessed from the position of the centroid of the detected markers in different MV image pairs. The method was validated on a phantom using CT as ground-truth and on clinical data sets of 16 patients using manual marker annotations as ground-truth. Results: The entire setup was confirmed to be accurate to around 1 mm by the phantom measurements. The reproducibility of the manual marker selection was less than 3.5 pixels in the MV images. In patient images, markers were correctly identified in at least 99% of the cases for anterior projection images and 96% of the cases for oblique projection images. The average marker detection accuracy was 1.4±1.8 pixels in the projection images. The centroid of all four reconstructed marker positions in 3D was positioned within 2 mm of the ground-truth position in 99.73% of all cases. Detecting four markers in a pair of MV images

Environmental DNA (eDNA From the Wake of the Whales: Droplet Digital PCR for Detection and Species Identification

Directory of Open Access Journals (Sweden)

C. Scott Baker

2018-04-01

Full Text Available Genetic sampling for identification of species, subspecies or stock of whales, dolphins and porpoises at sea remains challenging. Most samples have been collected with some form of a biopsy dart requiring a close approach of a vessel while the individual is at the surface. Here we have adopted droplet digital (ddPCR technology for detection and species identification of cetaceans using environmental (eDNA collected from seawater. We conducted a series of eDNA sampling experiments during 25 encounters with killer whales, Orcinus orca, in Puget Sound (the Salish Sea. The regular habits of killer whales in these inshore waters allowed us to locate pods and collect seawater, at an initial distance of 200 m and at 15-min intervals, for up to 2 h after the passage of the whales. To optimize detection, we designed a set of oligonucleotide primers and probes to target short fragments of the mitochondrial (mtDNA control region, with a focus on identification of known killer whale ecotypes. We confirmed the potential to detect eDNA in the wake of the whales for up to 2 h, despite movement of the water mass by several kilometers due to tidal currents. Re-amplification and sequencing of the eDNA barcode confirmed that the ddPCR detection included the “southern resident community” of killer whales, consistent with the calls from hydrophone recordings and visual observations.

Nuclear Magnetic Resonance Spectroscopy-Based Identification of Yeast.

Science.gov (United States)

Himmelreich, Uwe; Sorrell, Tania C; Daniel, Heide-Marie

2017-01-01

Rapid and robust high-throughput identification of environmental, industrial, or clinical yeast isolates is important whenever relatively large numbers of samples need to be processed in a cost-efficient way. Nuclear magnetic resonance (NMR) spectroscopy generates complex data based on metabolite profiles, chemical composition and possibly on medium consumption, which can not only be used for the assessment of metabolic pathways but also for accurate identification of yeast down to the subspecies level. Initial results on NMR based yeast identification where comparable with conventional and DNA-based identification. Potential advantages of NMR spectroscopy in mycological laboratories include not only accurate identification but also the potential of automated sample delivery, automated analysis using computer-based methods, rapid turnaround time, high throughput, and low running costs.We describe here the sample preparation, data acquisition and analysis for NMR-based yeast identification. In addition, a roadmap for the development of classification strategies is given that will result in the acquisition of a database and analysis algorithms for yeast identification in different environments.

Fungal disease detection in plants: Traditional assays, novel diagnostic techniques and biosensors.

Science.gov (United States)

Ray, Monalisa; Ray, Asit; Dash, Swagatika; Mishra, Abtar; Achary, K Gopinath; Nayak, Sanghamitra; Singh, Shikha

2017-01-15

Fungal diseases in commercially important plants results in a significant reduction in both quality and yield, often leading to the loss of an entire plant. In order to minimize the losses, it is essential to detect and identify the pathogens at an early stage. Early detection and accurate identification of pathogens can control the spread of infection. The present article provides a comprehensive overview of conventional methods, current trends and advances in fungal pathogen detection with an emphasis on biosensors. Traditional techniques are the "gold standard" in fungal detection which relies on symptoms, culture-based, morphological observation and biochemical identifications. In recent times, with the advancement of biotechnology, molecular and immunological approaches have revolutionized fungal disease detection. But the drawback lies in the fact that these methods require specific and expensive equipments. Thus, there is an urgent need for rapid, reliable, sensitive, cost effective and easy to use diagnostic methods for fungal pathogen detection. Biosensors would become a promising and attractive alternative, but they still have to be subjected to some modifications, improvements and proper validation for on-field use. Copyright © 2016 Elsevier B.V. All rights reserved.

Development of an enzyme-linked-immunosorbent-assay technique for accurate identification of poorly preserved silks unearthed in ancient tombs.

Science.gov (United States)

Zheng, Qin; Wu, Xiaofeng; Zheng, Hailing; Zhou, Yang

2015-05-01

We report the preparation of a specific fibroin antibody and its use for the identification of unearthed ancient silk relics. Based on the 12-amino-acid repeat sequence "GAGAGSGAGAGS", which is found in fibroin of the silkworm Bombyx mori, a specific antibody against fibroin was prepared in rabbits through peptide synthesis and carrier-protein coupling. This antibody was highly specific for fibroin found in silk. Using this antibody we have successfully identified four silk samples from different time periods. Our results reveal, for the first time, a method capable of detecting silk from a few milligrams of archaeological fabric that has been buried for thousands of years, confirming that the ancient practice of wearing silk products while praying for rebirth dated back to at least 400 BCE. This method also complements current approaches in silk detection, especially for the characterization of poorly preserved silks, promoting the investigation of silk origins and of ancient clothing cultures.

Multi-gene detection and identification of mosquito-borne RNA viruses using an oligonucleotide microarray.

Directory of Open Access Journals (Sweden)

Nathan D Grubaugh

Full Text Available BACKGROUND: Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae, Alphavirus (Togaviridae, Orthobunyavirus (Bunyaviridae, and Phlebovirus (Bunyaviridae. METHODOLOGY/PRINCIPAL FINDINGS: The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. CONCLUSIONS/SIGNIFICANCE: We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish

Customized lifting multiwavelet packet information entropy for equipment condition identification

International Nuclear Information System (INIS)

Chen, Jinglong; Zi, Yanyang; He, Zhengjia; Chen, Xuefeng; Zuo, Ming J; Yuan, Jing

2013-01-01

Condition identification of mechanical equipment from vibration measurement data is significant to avoid economic loss caused by unscheduled breakdowns and catastrophic accidents. However, this task still faces challenges due to the complexity of equipment and the harsh environment. This paper provides a possibility for equipment condition identification by proposing a method called customized lifting multiwavelet packet information entropy. Benefiting from the properties of multi-resolution analysis and multiple wavelet basis functions, the multiwavelet method has advantages in characterizing non-stationary vibration signals. In order to realize the accurate detection and identification of the condition features, a customized lifting multiwavelet packet is constructed via a multiwavelet lifting scheme. Then the vibration signal from the mechanical equipment is processed by the customized lifting multiwavelet packet transform. The relative energy in each frequency band of the multiwavelet packet transform coefficients that equals a percentage of the whole signal energy is taken as the probability. The normalized information entropy is obtained based on the relative energy to describe the condition of a mechanical system. The proposed method is applied to the condition identification of a rolling mill and a demountable disk–drum aero-engine. The results support the feasibility of the proposed method in equipment condition identification. (paper)

Less accurate but more efficient family of search templates for detection of gravitational waves from inspiraling compact binaries

International Nuclear Information System (INIS)

Chronopoulos, Andreas E.; Apostolatos, Theocharis A.

2001-01-01

The network of interferometric detectors that is under construction at various locations on Earth is expected to start searching for gravitational waves in a few years. The number of search templates that is needed to be cross correlated with the noisy output of the detectors is a major issue since computing power capabilities are restricted. By choosing higher and higher post-Newtonian order expansions for the family of search templates we make sure that our filters are more accurate copies of the real waves that hit our detectors. However, this is not the only criterion for choosing a family of search templates. To make the process of detection as efficient as possible, one needs a family of templates with a relatively small number of members that manages to pick up any detectable signal with only a tiny reduction in signal-to-noise ratio. Evidently, one family is better than another if it accomplishes its goal with a smaller number of templates. Following the geometric language of Owen, we have studied the performance of the post 1.5 -Newtonian family of templates on detecting post 2 -Newtonian signals for binaries. Several technical issues arise from the fact that the two types of waveforms cannot be made to coincide by a suitable choice of parameters. In general, the parameter space of the signals is not identical with the parameter space of the templates, although in our case they are of the same dimension, and one has to take into account all such peculiarities before drawing any conclusion. An interesting result we have obtained is that the post 1.5 -Newtonian family of templates happens to be more economical for detecting post 2 -Newtonian signals than the perfectly accurate post 2 -Newtonian family of templates itself. The number of templates is reduced by 20-30%, depending on the acceptable level of reduction in signal-to-noise ratio due to discretization of the family of templates. This makes the post 1.5 -Newtonian family of templates more favorable

Duplex Identification of Staphylococcus aureus by Aptamer and Gold Nanoparticles.

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Chang, Tianjun; Wang, Libo; Zhao, Kexu; Ge, Yu; He, Meng; Li, Gang

2016-06-01

Staphylococcus aureus is the top common pathogen causing infections and food poisoning. Identification of S. aureus is crucial for the disease diagnosis and regulation of food hygiene. Herein, we report an aptamer-AuNPs based method for duplex identification of S. aureus. Using AuNPs as an indicator, SA23, an aptamer against S. aureus, can well identify its target from Escherichia coli, Listeria monocytogenes and Pseudomonas aeruginosa. Furthermore, we find citrate-coated AuNPs can strongly bind to S. aureus, but not bind to Salmonella enterica and Proteus mirabilis, which leads to different color changes in salt solution. This colorimetric response is capable of distinguishing S. aureus from S. enteritidis and P. mirabilis. Thus, using the aptasensor and AuNPs together, S. aureus can be accurately identified from the common pathogens. This duplex identification system is a promising platform for simple visual identification of S. aureus. Additionally, in the aptasensing process, bacteria are incubated with aptamers and then be removed before the aptamers adding to AuNPs, which may avoid the interactions between bacteria and AuNPs. This strategy can be potentially applied in principle to detect other cells by AuNPs-based aptasensors.

Location identification of closed crack based on Duffing oscillator transient transition

Science.gov (United States)

Liu, Xiaofeng; Bo, Lin; Liu, Yaolu; Zhao, Youxuan; Zhang, Jun; Deng, Mingxi; Hu, Ning

2018-02-01

The existence of a closed micro-crack in plates can be detected by using the nonlinear harmonic characteristics of the Lamb wave. However, its location identification is difficult. By considering the transient nonlinear Lamb under the noise interference, we proposed a location identification method for the closed crack based on the quantitative measurement of Duffing oscillator transient transfer in the phase space. The sliding short-time window was used to create a window truncation of to-be-detected signal. And then, the periodic extension processing for transient nonlinear Lamb wave was performed to ensure that the Duffing oscillator has adequate response time to reach a steady state. The transient autocorrelation method was used to reduce the occurrence of missed harmonic detection due to the random variable phase of nonlinear Lamb wave. Moreover, to overcome the deficiency in the quantitative analysis of Duffing system state by phase trajectory diagram and eliminate the misjudgment caused by harmonic frequency component contained in broadband noise, logic operation method of oscillator state transition function based on circular zone partition was adopted to establish the mapping relation between the oscillator transition state and the nonlinear harmonic time domain information. Final state transition discriminant function of Duffing oscillator was used as basis for identifying the reflected and transmitted harmonics from the crack. Chirplet time-frequency analysis was conducted to identify the mode of generated harmonics and determine the propagation speed. Through these steps, accurate position identification of the closed crack was achieved.

Identification of four squid species by quantitative real-time polymerase chain reaction.

Science.gov (United States)

Ye, Jian; Feng, Junli; Liu, Shasha; Zhang, Yanping; Jiang, Xiaona; Dai, Zhiyuan

2016-02-01

Squids are distributed worldwide, including many species of commercial importance, and they are often made into varieties of flavor foods. The rapid identification methods for squid species especially their processed products, however, have not been well developed. In this study, quantitative real-time PCR (qPCR) systems based on specific primers and TaqMan probes have been established for rapid and accurate identification of four common squid species (Ommastrephes bartramii, Dosidicus gigas, Illex argentinus, Todarodes pacificus) in Chinese domestic market. After analyzing mitochondrial genes reported in GenBank, the mitochondrial cytochrome b (Cytb) gene was selected for O. bartramii detection, cytochrome c oxidase subunit I (COI) gene for D. gigas and T. Pacificus detection, ATPase subunit 6 (ATPase 6) gene for I. Argentinus detection, and 12S ribosomal RNA (12S rDNA) gene for designing Ommastrephidae-specific primers and probe. As a result, all the TaqMan systems are of good performance, and efficiency of each reaction was calculated by making standard curves. This method could detect target species either in single or mixed squid specimen, and it was applied to identify 12 squid processed products successfully. Thus, it would play an important role in fulfilling labeling regulations and squid fishery control. Copyright © 2016 Elsevier Ltd. All rights reserved.

Forming and detection of digital watermarks in the System for Automatic Identification of VHF Transmissions

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О. В. Шишкін

2013-07-01

Full Text Available Forming and detection algorithms for digital watermarks are designed for automatic identification of VHF radiotelephone transmissions in the maritime and aeronautical mobile services. An audible insensitivity and interference resistance of embedded digital data are provided by means of OFDM technology jointly with normalized distortions distribution and data packet detection by the hash-function. Experiments were carried out on the base of ship’s radio station RT-2048 Sailor and USB ADC-DAC module of type Е14-140M L-CARD in the off-line processing regime in Matlab medium

Reliable identification at the species level of Brucella isolates with MALDI-TOF-MS

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Lista Florigio

2011-12-01

Full Text Available Abstract Background The genus Brucella contains highly infectious species that are classified as biological threat agents. The timely detection and identification of the microorganism involved is essential for an effective response not only to biological warfare attacks but also to natural outbreaks. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS is a rapid method for the analysis of biological samples. The advantages of this method, compared to conventional techniques, are rapidity, cost-effectiveness, accuracy and suitability for the high-throughput identification of bacteria. Discrepancies between taxonomy and genetic relatedness on the species and biovar level complicate the development of detection and identification assays. Results In this study, the accurate identification of Brucella species using MALDI-TOF-MS was achieved by constructing a Brucella reference library based on multilocus variable-number tandem repeat analysis (MLVA data. By comparing MS-spectra from Brucella species against a custom-made MALDI-TOF-MS reference library, MALDI-TOF-MS could be used as a rapid identification method for Brucella species. In this way, 99.3% of the 152 isolates tested were identified at the species level, and B. suis biovar 1 and 2 were identified at the level of their biovar. This result demonstrates that for Brucella, even minimal genomic differences between these serovars translate to specific proteomic differences. Conclusions MALDI-TOF-MS can be developed into a fast and reliable identification method for genetically highly related species when potential taxonomic and genetic inconsistencies are taken into consideration during the generation of the reference library.

A new diagnostic tool for rapid and accurate detection of Mycobacterium tuberculosis

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Ali Nour-Neamatollahi

2018-03-01

Full Text Available Mycobacterium tuberculosis, acid fast bacilli from the family of Mycobacteriaceae, is the causative agent of most cases of tuberculosis. Tuberculosis, as a communicable disease, remains a serious public health threat, killing more than one million people globally every year. Primary diagnosis of tuberculosis bacilli (TB relies mainly on microscopic detection of acid fast bacilli (AFB, but the method suffers from low sensitivity and the results largely depend on the technician’s skill. New diagnostic tools are necessary to be introduced for rapid and accurate detection of the bacilli in sputum samples. We, in collaboration with Anda Biologicals, have developed a new platform, named as “Patho-tb”, for rapid detection of AFB with high sensitivity and with low dependence on human skills. Evaluation of Patho-tb test performance was done in two settings: (1 primary field study conducted using 38 sputa from high TB prevalence area of Iran (Zabol city near to the Afghanistan border, and (2 main study conducted using 476 sputa from Tehran, capital of Iran. Patho-tb was applied for processed sputum samples in parallel with routine diagnostic methods (including AFB microscopy, culture and PCR. All test results were compared to final clinical diagnostic state of an individual and diagnostic sensitivity (DSe, specificity, positive predictive value, negative predictive value and accuracy of each test results were calculated using standard formulations. Analytical sensitivity and specificity of the Patho-tb test were also determined. Calculated values for five above mentioned parameters are as follows: for field study: AFB (DSe: 29.6, DSp: 81.8, PPV: 80, NPV: 23.1, AC: 44.7, Patho-tb (DSe: 63, DSp: 72.7, PPV: 85, NPV: 44.4, AC: 65.8, and for main study: AFB (DSe: 86.1, DSp: 99.4, PPV: 98.5, NPV: 93.9, AC: 95.2, Patho-tb (DSe: 97.4, DSp: 92.9, PPV: 86.5, NPV: 98.7, AC: 94.3. Reproducibility of Patho-tb test results were near to 100% (Cohen’s kappa value

Instrumentation measurement and testing complex for detection and identification of radioactive materials using the emitted radiation

International Nuclear Information System (INIS)

Samossadny, V.T.; Dmitrenko, V.V.; Kadlin, V.V.; Kolesnikov, S.V.; Ulin, S.E.; Grachev, V.M.; Vlasik, K.F.; Dedenko, G.L.; Novikov, D.V.; Uteshev, Z.M.

2006-01-01

Simultaneous measurement of neutron and gamma radiation is a very usefull method for effective nuclear materials identification and control. The gamma-ray-neutron complex described in the paper is based on two multi-layer 3 He neutrons detectors and two High Pressure Xenon gamma-ray spectrometers assembled in one unit. All these detectors were callibrated on neutron and gamma-ray sources. The main characteristics of the instrumentation , its testing results and gamma-ray and neutron radiation parameters, which have been measured are represented in the paper. The gamma-neutron sources and fissile materials reliable detection and identification capability was demonstrated

Discerning cultural identification from a thinly sliced behavioral sample.

Science.gov (United States)

Hamamura, Takeshi; Li, Liman Man Wai

2012-12-01

This research examined whether individual differences in cultural identification can be discerned at zero acquaintance. This issue was examined in Hong Kong, where the idiosyncrasy of cultural identification is a salient social-psychological issue. The participants were able to perceive accurately the targets' identification with Western culture from a video clip and from a still image. Findings also indicated that a stereotype of Western cultural identity (i.e., extraversion and particular hairstyle) facilitated these perceptions. Specifically, (a) the participants with a stronger stereotype were more accurate in perceiving Western cultural identification, (b) the targets who were experimentally manipulated to appear extraverted were rated as more strongly identifying with Western culture, and (c) the participants relatively unfamiliar with these stereotypes did not correctly perceive Western cultural identification. Implications of these findings on research on multiculturalism are also discussed.

Bistatic Forward Scattering Radar Detection and Imaging

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Hu Cheng

2016-06-01

Full Text Available Forward Scattering Radar (FSR is a special type of bistatic radar that can implement image detection, imaging, and identification using the forward scattering signals provided by the moving targets that cross the baseline between the transmitter and receiver. Because the forward scattering effect has a vital significance in increasing the targets’ Radar Cross Section (RCS, FSR is quite advantageous for use in counter stealth detection. This paper first introduces the front line technology used in forward scattering RCS, FSR detection, and Shadow Inverse Synthetic Aperture Radar (SISAR imaging and key problems such as the statistical characteristics of forward scattering clutter, accurate parameter estimation, and multitarget discrimination are then analyzed. Subsequently, the current research progress in FSR detection and SISAR imaging are described in detail, including the theories and experiments. In addition, with reference to the BeiDou navigation satellite, the results of forward scattering experiments in civil aircraft detection are shown. Finally, this paper considers future developments in FSR target detection and imaging and presents a new, promising technique for stealth target detection.

Direct identification of bacteria in positive blood culture bottles by matrix-assisted laser desorption ionisation time-of-flight mass spectrometry.

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Bernard La Scola

Full Text Available BACKGROUND: With long delays observed between sampling and availability of results, the usefulness of blood cultures in the context of emergency infectious diseases has recently been questioned. Among methods that allow quicker bacterial identification from growing colonies, matrix-assisted laser desorption ionisation time-of-flight (MALDI-TOF mass spectrometry was demonstrated to accurately identify bacteria routinely isolated in a clinical biology laboratory. In order to speed up the identification process, in the present work we attempted bacterial identification directly from blood culture bottles detected positive by the automate. METHODOLOGY/PRINCIPAL FINDINGS: We prospectively analysed routine MALDI-TOF identification of bacteria detected in blood culture by two different protocols involving successive centrifugations and then lysis by trifluoroacetic acid or formic acid. Of the 562 blood culture broths detected as positive by the automate and containing one bacterial species, 370 (66% were correctly identified. Changing the protocol from trifluoroacetic acid to formic acid improved identification of Staphylococci, and overall correct identification increased from 59% to 76%. Lack of identification was observed mostly with viridans streptococci, and only one false positive was observed. In the 22 positive blood culture broths that contained two or more different species, only one of the species was identified in 18 samples, no species were identified in two samples and false species identifications were obtained in two cases. The positive predictive value of bacterial identification using this procedure was 99.2%. CONCLUSIONS/SIGNIFICANCE: MALDI-TOF MS is an efficient method for direct routine identification of bacterial isolates in blood culture, with the exception of polymicrobial samples and viridans streptococci. It may replace routine identification performed on colonies, provided improvement for the specificity of blood culture

Direct identification of bacteria in positive blood culture bottles by matrix-assisted laser desorption ionisation time-of-flight mass spectrometry.

Science.gov (United States)

La Scola, Bernard; Raoult, Didier

2009-11-25

With long delays observed between sampling and availability of results, the usefulness of blood cultures in the context of emergency infectious diseases has recently been questioned. Among methods that allow quicker bacterial identification from growing colonies, matrix-assisted laser desorption ionisation time-of-flight (MALDI-TOF) mass spectrometry was demonstrated to accurately identify bacteria routinely isolated in a clinical biology laboratory. In order to speed up the identification process, in the present work we attempted bacterial identification directly from blood culture bottles detected positive by the automate. We prospectively analysed routine MALDI-TOF identification of bacteria detected in blood culture by two different protocols involving successive centrifugations and then lysis by trifluoroacetic acid or formic acid. Of the 562 blood culture broths detected as positive by the automate and containing one bacterial species, 370 (66%) were correctly identified. Changing the protocol from trifluoroacetic acid to formic acid improved identification of Staphylococci, and overall correct identification increased from 59% to 76%. Lack of identification was observed mostly with viridans streptococci, and only one false positive was observed. In the 22 positive blood culture broths that contained two or more different species, only one of the species was identified in 18 samples, no species were identified in two samples and false species identifications were obtained in two cases. The positive predictive value of bacterial identification using this procedure was 99.2%. MALDI-TOF MS is an efficient method for direct routine identification of bacterial isolates in blood culture, with the exception of polymicrobial samples and viridans streptococci. It may replace routine identification performed on colonies, provided improvement for the specificity of blood culture broths growing viridans streptococci is obtained in the near future.

Detection, Identification, Location, and Remote Sensing using SAW RFID Sensor Tags

Science.gov (United States)

Barton, Richard J.

2009-01-01

In this presentation, we will consider the problem of simultaneous detection, identification, location estimation, and remote sensing for multiple objects. In particular, we will describe the design and testing of a wireless system capable of simultaneously detecting the presence of multiple objects, identifying each object, and acquiring both a low-resolution estimate of location and a high-resolution estimate of temperature for each object based on wireless interrogation of passive surface acoustic wave (SAW) radiofrequency identification (RFID) sensor tags affixed to each object. The system is being studied for application on the lunar surface as well as for terrestrial remote sensing applications such as pre-launch monitoring and testing of spacecraft on the launch pad and monitoring of test facilities. The system utilizes a digitally beam-formed planar receiving antenna array to extend range and provide direction-of-arrival information coupled with an approximate maximum-likelihood signal processing algorithm to provide near-optimal estimation of both range and temperature. The system is capable of forming a large number of beams within the field of view and resolving the information from several tags within each beam. The combination of both spatial and waveform discrimination provides the capability to track and monitor telemetry from a large number of objects appearing simultaneously within the field of view of the receiving array. In the presentation, we will summarize the system design and illustrate several aspects of the operational characteristics and signal structure. We will examine the theoretical performance characteristics of the system and compare the theoretical results with results obtained from experiments in both controlled laboratory environments and in the field.

Fault detection and identification in missile system guidance and control: a filtering approach

Science.gov (United States)

Padgett, Mary Lou; Evers, Johnny; Karplus, Walter J.

1996-03-01

Real-world applications of computational intelligence can enhance the fault detection and identification capabilities of a missile guidance and control system. A simulation of a bank-to- turn missile demonstrates that actuator failure may cause the missile to roll and miss the target. Failure of one fin actuator can be detected using a filter and depicting the filter output as fuzzy numbers. The properties and limitations of artificial neural networks fed by these fuzzy numbers are explored. A suite of networks is constructed to (1) detect a fault and (2) determine which fin (if any) failed. Both the zero order moment term and the fin rate term show changes during actuator failure. Simulations address the following questions: (1) How bad does the actuator failure have to be for detection to occur, (2) How bad does the actuator failure have to be for fault detection and isolation to occur, (3) are both zero order moment and fine rate terms needed. A suite of target trajectories are simulated, and properties and limitations of the approach reported. In some cases, detection of the failed actuator occurs within 0.1 second, and isolation of the failure occurs 0.1 after that. Suggestions for further research are offered.

Direct spondylolisthesis identification and measurement in MR/CT using detectors trained by articulated parameterized spine model

Science.gov (United States)

Cai, Yunliang; Leung, Stephanie; Warrington, James; Pandey, Sachin; Shmuilovich, Olga; Li, Shuo

2017-02-01

The identification of spondylolysis and spondylolisthesis is important in spinal diagnosis, rehabilitation, and surgery planning. Accurate and automatic detection of spinal portion with spondylolisthesis problem will significantly reduce the manual work of physician and provide a more robust evaluation for the spine condition. Most existing automatic identification methods adopted the indirect approach which used vertebrae locations to measure the spondylolisthesis. However, these methods relied heavily on automatic vertebra detection which often suffered from the pool spatial accuracy and the lack of validated pathological training samples. In this study, we present a novel spondylolisthesis detection method which can directly locate the irregular spine portion and output the corresponding grading. The detection is done by a set of learning-based detectors which are discriminatively trained by synthesized spondylolisthesis image samples. To provide sufficient pathological training samples, we used a parameterized spine model to synthesize different types of spondylolysis images from real MR/CT scans. The parameterized model can automatically locate the vertebrae in spine images and estimate their pose orientations, and can inversely alter the vertebrae locations and poses by changing the corresponding parameters. Various training samples can then be generated from only a few spine MR/CT images. The preliminary results suggest great potential for the fast and efficient spondylolisthesis identification and measurement in both MR and CT spine images.

Detection and analysis of diamond fingerprinting feature and its application

Energy Technology Data Exchange (ETDEWEB)

Li Xin; Huang Guoliang; Li Qiang; Chen Shengyi, E-mail: tshgl@tsinghua.edu.cn [Department of Biomedical Engineering, the School of Medicine, Tsinghua University, Beijing, 100084 (China)

2011-01-01

Before becoming a jewelry diamonds need to be carved artistically with some special geometric features as the structure of the polyhedron. There are subtle differences in the structure of this polyhedron in each diamond. With the spatial frequency spectrum analysis of diamond surface structure, we can obtain the diamond fingerprint information which represents the 'Diamond ID' and has good specificity. Based on the optical Fourier Transform spatial spectrum analysis, the fingerprinting identification of surface structure of diamond in spatial frequency domain was studied in this paper. We constructed both the completely coherent diamond fingerprinting detection system illuminated by laser and the partially coherent diamond fingerprinting detection system illuminated by led, and analyzed the effect of the coherence of light source to the diamond fingerprinting feature. We studied rotation invariance and translation invariance of the diamond fingerprinting and verified the feasibility of real-time and accurate identification of diamond fingerprint. With the profit of this work, we can provide customs, jewelers and consumers with a real-time and reliable diamonds identification instrument, which will curb diamond smuggling, theft and other crimes, and ensure the healthy development of the diamond industry.

Assays for Detection and Identification of the Causative Agent of Mange in Free-Ranging Black Bears ( Ursus americanus).

Science.gov (United States)

Peltier, Sarah K; Brown, Justin D; Ternent, Mark A; Fenton, Heather; Niedringhaus, Kevin D; Yabsley, Michael J

2018-03-02

Three mite species ( Demodex ursi, Ursicoptes americanus, and Sarcoptes scabiei) have been associated with mange in black bears ( Ursus americanus). Since the early 1990s, the number and geographic distribution of mange cases in black bears in Pennsylvania has increased; however, the causative mites have yet to be completely defined. We evaluated several diagnostic approaches for detection and identification of mites in 72 black bears with severe lesions consistent with mange. Sarcoptes scabiei was morphologically identified in skin scrapes from 66 of the bears; no mites were identified in the remaining six. Histopathologic lesions consistent with sarcoptic mange were observed in 39 of 40 bear skin samples examined, and intralesional mites were observed in samples from 38 of these bears. Samples were collected from a subset of the 72 bears for PCR testing targeting both the internal transcribed spacer (ITS)-2 region and cytochrome c oxidase I ( cox1) gene including 69 skin scrapes ( ITS-2 only), 56 skin biopsies ( ITS-2 and cox1), and 36 fecal samples ( ITS-2 and cox1). Skin scrapes were a more sensitive sample for PCR detection than either skin biopsies or fecal samples, and the ITS-2 primers proved more sensitive than cox1. Using a commercial indirect enzyme-linked immunosorbent assay, antibodies to S. scabiei were detected in 45/49 (92%) black bears with confirmed mange and 0/62 (0%) cubs with no gross lesions suggestive of mange and which were born to seronegative sows. Sarcoptes scabiei was the predominant mite associated with mange in black bears in Pennsylvania. Diagnostically, cytologic examination of skin scrapes was the most effective approach for diagnosing active mite infestations in black bears. The evaluated serologic assay accurately detected antibodies to S. scabiei in most bears with confirmed S. scabiei infestations. Additional research is needed to determine the usefulness of this approach for larger scale surveys and for asymptomatic bears.

Gas detection by correlation spectroscopy employing a multimode diode laser.

Science.gov (United States)

Lou, Xiutao; Somesfalean, Gabriel; Zhang, Zhiguo

2008-05-01

A gas sensor based on the gas-correlation technique has been developed using a multimode diode laser (MDL) in a dual-beam detection scheme. Measurement of CO(2) mixed with CO as an interfering gas is successfully demonstrated using a 1570 nm tunable MDL. Despite overlapping absorption spectra and occasional mode hops, the interfering signals can be effectively excluded by a statistical procedure including correlation analysis and outlier identification. The gas concentration is retrieved from several pair-correlated signals by a linear-regression scheme, yielding a reliable and accurate measurement. This demonstrates the utility of the unsophisticated MDLs as novel light sources for gas detection applications.

Surface-enhanced Raman scattering detection of ammonium nitrate samples fabricated using drop-on-demand inkjet technology.

Science.gov (United States)

Farrell, Mikella E; Holthoff, Ellen L; Pellegrino, Paul M

2014-01-01

The United States Army and the first responder community are increasingly focusing efforts on energetic materials detection and identification. Main hazards encountered in theater include homemade explosives and improvised explosive devices, in part fabricated from simple components like ammonium nitrate (AN). In order to accurately detect and identify these unknowns (energetic or benign), fielded detection systems must be accurately trained using well-understood universal testing substrates. These training substrates must contain target species at known concentrations and recognized polymorphic phases. Ammonium nitrate is an explosive precursor material that demonstrates several different polymorphic phases dependent upon how the material is deposited onto testing substrates. In this paper, known concentrations of AN were uniformly deposited onto commercially available surface-enhanced Raman scattering (SERS) substrates using a drop-on-demand inkjet printing system. The phase changes observed after the deposition of AN under several solvent conditions are investigated. Characteristics of the collected SERS spectra of AN are discussed, and it is demonstrated that an understanding of the exact nature of the AN samples deposited will result in an increased ability to accurately and reliably "train" hazard detection systems.

Experimental Identification of Smartphones Using Fingerprints of Built-In Micro-Electro Mechanical Systems (MEMS

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Gianmarco Baldini

2016-06-01

Full Text Available The correct identification of smartphones has various applications in the field of security or the fight against counterfeiting. As the level of sophistication in counterfeit electronics increases, detection procedures must become more accurate but also not destructive for the smartphone under testing. Some components of the smartphone are more likely to reveal their authenticity even without a physical inspection, since they are characterized by hardware fingerprints detectable by simply examining the data they provide. This is the case of MEMS (Micro Electro-Mechanical Systems components like accelerometers and gyroscopes, where tiny differences and imprecisions in the manufacturing process determine unique patterns in the data output. In this paper, we present the experimental evaluation of the identification of smartphones through their built-in MEMS components. In our study, three different phones of the same model are subject to repeatable movements (composing a repeatable scenario using an high precision robotic arm. The measurements from MEMS for each repeatable scenario are collected and analyzed. The identification algorithm is based on the extraction of the statistical features of the collected data for each scenario. The features are used in a support vector machine (SVM classifier to identify the smartphone. The results of the evaluation are presented for different combinations of features and Inertial Measurement Unit (IMU outputs, which show that detection accuracy of higher than 90% is achievable.

Chemical warfare agents identification by thermal neutron detection

International Nuclear Information System (INIS)

Liu Boxue; Ai Xianyun; Tan Daoyuan; Zhang Dianqin

2000-01-01

The hydrogen concentration determination by thermal neutron detection is a non-destructive, fast and effective method to identify chemical warfare agents and TNT that contain different hydrogen fraction. When an isotropic neutron source is used to irradiate chemical ammunition, hydrogen atoms of the agent inside shell act as a moderator and slow down neutrons. The number of induced thermal neutrons depends mainly upon hydrogen content of the agent. Therefore measurement of thermal neutron influence can be used to determine hydrogen atom concentration, thereby to determine the chemical warfare agents. Under a certain geometry three calibration curves of count rate against hydrogen concentration were measured. According to the calibration curves, response of a chemical agent or TNT could be calculated. Differences of count rate among chemical agents and TNT for each kind of shells is greater than five times of standard deviations of count rate for any agent, so chemical agents or TNT could be identified correctly. Meanwhile, blast tube or liquid level of chemical warfare agent could affect the response of thermal neutron count rate, and thereby the result of identification. (author)

Detection and identification of Leishmania spp.: application of two hsp70-based PCR-RFLP protocols to clinical samples from the New World.

Science.gov (United States)

Montalvo, Ana M; Fraga, Jorge; Tirado, Dídier; Blandón, Gustavo; Alba, Annia; Van der Auwera, Gert; Vélez, Iván Darío; Muskus, Carlos

2017-07-01

Leishmaniasis is highly prevalent in New World countries, where several methods are available for detection and identification of Leishmania spp. Two hsp70-based PCR protocols (PCR-N and PCR-F) and their corresponding restriction fragment length polymorphisms (RFLP) were applied for detection and identification of Leishmania spp. in clinical samples recruited in Colombia, Guatemala, and Honduras. A total of 93 cases were studied. The samples were classified into positive or suspected of leishmaniasis according to parasitological criteria. Molecular amplification of two different hsp70 gene fragments and further RFLP analysis for identification of Leishmania species was done. The detection in parasitologically positive samples was higher using PCR-N than PCR-F. In the total of samples studied, the main species identified were Leishmania panamensis, Leishmania braziliensis, and Leishmania infantum (chagasi). Although RFLP-N was more efficient for the identification, RFLP-F is necessary for discrimination between L. panamensis and Leishmania guyanesis, of great importance in Colombia. Unexpectedly, one sample from this country revealed an RFLP pattern corresponding to Leishmania naiffi. Both molecular variants are applicable for the study of clinical samples originated in Colombia, Honduras, and Guatemala. Choosing the better tool for each setting depends on the species circulating. More studies are needed to confirm the presence of L. naiffi in Colombian territory.

IMAGE PROCESSING FOR DETECTION OF ORAL WHITE SPONGE NEVUS LESIONS

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Rajdeep Mitra

2016-12-01

Full Text Available White Sponge Nevus is a rear hereditary disease in human causes incurable white lesions in oral mucosa. Appropriate history, clinical examination along with biopsy and cytological studies are helpful for diagnosis of this disorder. Identification can also be made in alternative way by applying image processing technique using Watershed segmentation with MATLAB software. The applied techniques are effective and reliable for early accurate detection of the disease as alternative of expertise clinical and time taking laboratory investigations.

40 CFR Table 6 to Subpart IIIii of... - Examples of Techniques for Equipment Problem Identification, Leak Detection and Mercury Vapor

Science.gov (United States)

2010-07-01

... Problem Identification, Leak Detection and Mercury Vapor 6 Table 6 to Subpart IIIII of Part 63 Protection... Hazardous Air Pollutants: Mercury Emissions From Mercury Cell Chlor-Alkali Plants Pt. 63, Subpt. IIIII..., Leak Detection and Mercury Vapor As stated in Tables 1 and 2 of Subpart IIIII, examples of techniques...

Chromothripsis Detection and Characterization Using the CTLPScanner Web Server.

Science.gov (United States)

Yang, Jian; Liu, Bo; Cai, Haoyang

2018-01-01

Accurate detection of chromothripsis event is important to study the mechanisms underlying this phenomenon. CTLPScanner ( http://cgma.scu.edu.cn/CTLPScanner/ ) is a web-based tool for identification and annotation of chromothripsis-like pattern (CTLP) in genomic array data. In this chapter, we illustrate the utility of CTLPScanner for screening chromosome pulverization regions and give interpretation of the results. The web interface offers a set of parameters and thresholds for customized screening. We also provide practical recommendations for effective chromothripsis detection. In addition to the user data processing module, CTLPScanner contains more than 50,000 preprocessed oncogenomic arrays, which allow users to explore the presence of chromothripsis signatures from public data resources.

Implementation of Whole Genome Sequencing (WGS for Identification and Characterization of Shiga Toxin-Producing Escherichia coli (STEC in the United States

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Rebecca L Lindsey

2016-05-01

Full Text Available Shiga toxin-producing Escherichia coli (STEC is an important foodborne pathogen capable of causing severe disease in humans. Rapid and accurate identification and characterization techniques are essential during outbreak investigations. Current methods for characterization of STEC are expensive and time-consuming. With the advent of rapid and cheap whole genome sequencing (WGS benchtop sequencers, the potential exists to replace traditional workflows with WGS. The aim of this study was to validate tools to do reference identification and characterization from WGS for STEC in a single workflow within an easy to use commercially available software platform. Publically available serotype, virulence, and antimicrobial resistance databases were downloaded from the Center for Genomic Epidemiology (CGE (www.genomicepidemiology.org and integrated into a genotyping plug-in with in silico PCR tools to confirm some of the virulence genes detected from WGS data. Additionally, down sampling experiments on the WGS sequence data were performed to determine a threshold for sequence coverage needed to accurately predict serotype and virulence genes using the established workflow. The serotype database was tested on a total of 228 genomes and correctly predicted from WGS for 96.1% of O serogroups and 96.5% of H serogroups identified by conventional testing techniques. A total of 59 genomes were evaluated to determine the threshold of coverage to detect the different WGS targets, 40 were evaluated for serotype and virulence gene detection and 19 for the stx gene subtypes. For serotype, 95% of the O and 100% of the H serogroups were detected at > 40x and ≥ 30x coverage, respectively. For virulence targets and stx gene subtypes, nearly all genes were detected at > 40x, though some targets were 100% detectable from genomes with coverage ≥20x. The resistance detection tool was 97% concordant with phenotypic testing results. With isolates sequenced to > 40x

Implementation of Whole Genome Sequencing (WGS) for Identification and Characterization of Shiga Toxin-Producing Escherichia coli (STEC) in the United States

Science.gov (United States)

Lindsey, Rebecca L.; Pouseele, Hannes; Chen, Jessica C.; Strockbine, Nancy A.; Carleton, Heather A.

2016-01-01

Shiga toxin-producing Escherichia coli (STEC) is an important foodborne pathogen capable of causing severe disease in humans. Rapid and accurate identification and characterization techniques are essential during outbreak investigations. Current methods for characterization of STEC are expensive and time-consuming. With the advent of rapid and cheap whole genome sequencing (WGS) benchtop sequencers, the potential exists to replace traditional workflows with WGS. The aim of this study was to validate tools to do reference identification and characterization from WGS for STEC in a single workflow within an easy to use commercially available software platform. Publically available serotype, virulence, and antimicrobial resistance databases were downloaded from the Center for Genomic Epidemiology (CGE) (www.genomicepidemiology.org) and integrated into a genotyping plug-in with in silico PCR tools to confirm some of the virulence genes detected from WGS data. Additionally, down sampling experiments on the WGS sequence data were performed to determine a threshold for sequence coverage needed to accurately predict serotype and virulence genes using the established workflow. The serotype database was tested on a total of 228 genomes and correctly predicted from WGS for 96.1% of O serogroups and 96.5% of H serogroups identified by conventional testing techniques. A total of 59 genomes were evaluated to determine the threshold of coverage to detect the different WGS targets, 40 were evaluated for serotype and virulence gene detection and 19 for the stx gene subtypes. For serotype, 95% of the O and 100% of the H serogroups were detected at > 40x and ≥ 30x coverage, respectively. For virulence targets and stx gene subtypes, nearly all genes were detected at > 40x, though some targets were 100% detectable from genomes with coverage ≥20x. The resistance detection tool was 97% concordant with phenotypic testing results. With isolates sequenced to > 40x coverage, the different

A PCR detection method for rapid identification of Melissococcus pluton in honeybee larvae.

Science.gov (United States)

Govan, V A; Brözel, V; Allsopp, M H; Davison, S

1998-05-01

Melissococcus pluton is the causative agent of European foulbrood, a disease of honeybee larvae. This bacterium is particularly difficult to isolate because of its stringent growth requirements and competition from other bacteria. PCR was used selectively to amplify specific rRNA gene sequences of M. pluton from pure culture, from crude cell lysates, and directly from infected bee larvae. The PCR primers were designed from M. pluton 16S rRNA sequence data. The PCR products were visualized by agarose gel electrophoresis and confirmed as originating from M. pluton by sequencing in both directions. Detection was highly specific, and the probes did not hybridize with DNA from other bacterial species tested. This method enabled the rapid and specific detection and identification of M. pluton from pure cultures and infected bee larvae.

Development of Loop-Mediated Isothermal Amplification (LAMP) Assay for Rapid Detection of Cannabis sativa.

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Kitamura, Masashi; Aragane, Masako; Nakamura, Kou; Watanabe, Kazuhito; Sasaki, Yohei

2016-07-01

In many parts of the world, the possession and cultivation of Cannabis sativa L. are restricted by law. As chemical or morphological analyses cannot identify the plant in some cases, a simple yet accurate DNA-based method for identifying C. sativa is desired. We have developed a loop-mediated isothermal amplification (LAMP) assay for the rapid identification of C. sativa. By optimizing the conditions for the LAMP reaction that targets a highly conserved region of tetrahydrocannabinolic acid (THCA) synthase gene, C. sativa was identified within 50 min at 60-66°C. The detection limit was the same as or higher than that of conventional PCR. The LAMP assay detected all 21 specimens of C. sativa, showing high specificity. Using a simple protocol, the identification of C. sativa could be accomplished within 90 min from sample treatment to detection without use of special equipment. A rapid, sensitive, highly specific, and convenient method for detecting and identifying C. sativa has been developed and is applicable to forensic investigations and industrial quality control.

HybProbes-based real-time PCR assay for specific identification of Streptomyces scabies and Streptomyces europaeiscabiei, the potato common scab pathogens.

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Xu, R; Falardeau, J; Avis, T J; Tambong, J T

2016-02-01

The aim of this study was to develop and validate a HybProbes-based real-time PCR assay targeting the trpB gene for specific identification of Streptomyces scabies and Streptomyces europaeiscabiei. Four primer pairs and a fluorescent probe were designed and evaluated for specificity in identifying S. scabies and Streptomyces europaeiscabiei, the potato common scab pathogens. The specificity of the HybProbes-based real-time PCR assay was evaluated using 46 bacterial strains, 23 Streptomyces strains and 23 non-Streptomyces bacterial species. Specific and strong fluorescence signals were detected from all nine strains of S. scabies and Streptomyces europaeiscabiei. No fluorescence signal was detected from 14 strains of other Streptomyces species and all non-Streptomyces strains. The identification was corroborated by the melting curve analysis that was performed immediately after the amplification step. Eight of the nine S. scabies and S. europaeiscabiei strains exhibited a unique melting peak, at Tm of 69·1°C while one strain, Warba-6, had a melt peak at Tm of 65·4°C. This difference in Tm peaks could be attributed to a guanine to cytosine mutation in strain Warba-6 at the region spanning the donor HybProbe. The reported HybProbes assay provides a more specific tool for accurate identification of S. scabies and S. europaeiscabiei strains. This study reports a novel assay based on HybProbes chemistry for rapid and accurate identification of the potato common scab pathogens. Since the HybProbes chemistry requires two probes for positive identification, the assay is considered to be more specific than conventional PCR or TaqMan real-time PCR. The developed assay would be a useful tool with great potential in early diagnosis and detection of common scab pathogens of potatoes in infected plants or for surveillance of potatoes grown in soil environment. © 2015 Her Majesty the Queen in Right of Canada © 2015 The Society for Applied Microbiology.

Combined effects of expectations and visual uncertainty upon detection and identification of a target in the fog.

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Quétard, Boris; Quinton, Jean-Charles; Colomb, Michèle; Pezzulo, Giovanni; Barca, Laura; Izaute, Marie; Appadoo, Owen Kevin; Mermillod, Martial

2015-09-01

Detecting a pedestrian while driving in the fog is one situation where the prior expectation about the target presence is integrated with the noisy visual input. We focus on how these sources of information influence the oculomotor behavior and are integrated within an underlying decision-making process. The participants had to judge whether high-/low-density fog scenes displayed on a computer screen contained a pedestrian or a deer by executing a mouse movement toward the response button (mouse-tracking). A variable road sign was added on the scene to manipulate expectations about target identity. We then analyzed the timing and amplitude of the deviation of mouse trajectories toward the incorrect response and, using an eye tracker, the detection time (before fixating the target) and the identification time (fixations on the target). Results revealed that expectation of the correct target results in earlier decisions with less deviation toward the alternative response, this effect being partially explained by the facilitation of target identification.

 Methods of detection of selected respiratory viruses

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Ilona Stefańska

2012-06-01

Full Text Available  Respiratory viruses contribute to significant morbidity and mortality in healthy and immunocompromised individuals and are considered as a significant economic burden in the healthcare system. The similar clinical symptoms in the course of different viral and bacterial respiratory infections make the proper diagnosis difficult. An accurate and prompt diagnostics is crucial for infection control and patient management decisions, especially regarding the use of antibacterial or antiviral therapy and hospitalization. Moreover, the identification of the causative agent eliminates inappropriate use of antibiotics and may reduce the cost of healthcare.A wide variety of diagnostic procedures is applied for the detection of viral agents responsible for respiratory tract infections. For many years, the viral antigen detection and standard isolation technique in cell culture was the main method used in routine diagnostics. However, in recent years the nucleic acid amplification techniques have become widely used and have significantly improved the sensitivity of viral detection in clinical specimens. Molecular diagnostic assays have contributed to revealing high rates of co-infection (multiplex reactions and allow identification of agents that are difficult to culture.This paper discusses a number of technical aspects of the current most commonly used techniques, their general principles, main benefits and diagnostic value, but also some of their limitations.

Accurate Point-of-Care Detection of Ruptured Fetal Membranes: Improved Diagnostic Performance Characteristics with a Monoclonal/Polyclonal Immunoassay

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Linda C. Rogers

2016-01-01

Full Text Available Objective Accurate and timely diagnosis of rupture of membranes (ROM is imperative to allow for gestational age-specific interventions. This study compared the diagnostic performance characteristics between two methods used for the detection of ROM as measured in the same patient. Methods Vaginal secretions were evaluated using the conventional fern test as well as a point-of-care monoclonal/polyclonal immunoassay test (ROM Plus® in 75 pregnant patients who presented to labor and delivery with complaints of leaking amniotic fluid. Both tests were compared to analytical confirmation of ROM using three external laboratory tests. Diagnostic performance characteristics were calculated including sensitivity, specificity, positive predictive value (PPV, negative predictive value (NPV, and accuracy. Results Diagnostic performance characteristics uniformly favored ROM detection using the immunoassay test compared to the fern test: sensitivity (100% vs. 77.8%, specificity (94.8% vs. 79.3%, PPV (75% vs. 36.8%, NPV (100% vs. 95.8%, and accuracy (95.5% vs. 79.1%. Conclusions The point-of-care immunoassay test provides improved diagnostic accuracy for the detection of ROM compared to fern testing. It has the potential of improving patient management decisions, thereby minimizing serious complications and perinatal morbidity.

Creation of an Accurate Algorithm to Detect Snellen Best Documented Visual Acuity from Ophthalmology Electronic Health Record Notes.

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Mbagwu, Michael; French, Dustin D; Gill, Manjot; Mitchell, Christopher; Jackson, Kathryn; Kho, Abel; Bryar, Paul J

2016-05-04

Visual acuity is the primary measure used in ophthalmology to determine how well a patient can see. Visual acuity for a single eye may be recorded in multiple ways for a single patient visit (eg, Snellen vs. Jäger units vs. font print size), and be recorded for either distance or near vision. Capturing the best documented visual acuity (BDVA) of each eye in an individual patient visit is an important step for making electronic ophthalmology clinical notes useful in research. Currently, there is limited methodology for capturing BDVA in an efficient and accurate manner from electronic health record (EHR) notes. We developed an algorithm to detect BDVA for right and left eyes from defined fields within electronic ophthalmology clinical notes. We designed an algorithm to detect the BDVA from defined fields within 295,218 ophthalmology clinical notes with visual acuity data present. About 5668 unique responses were identified and an algorithm was developed to map all of the unique responses to a structured list of Snellen visual acuities. Visual acuity was captured from a total of 295,218 ophthalmology clinical notes during the study dates. The algorithm identified all visual acuities in the defined visual acuity section for each eye and returned a single BDVA for each eye. A clinician chart review of 100 random patient notes showed a 99% accuracy detecting BDVA from these records and 1% observed error. Our algorithm successfully captures best documented Snellen distance visual acuity from ophthalmology clinical notes and transforms a variety of inputs into a structured Snellen equivalent list. Our work, to the best of our knowledge, represents the first attempt at capturing visual acuity accurately from large numbers of electronic ophthalmology notes. Use of this algorithm can benefit research groups interested in assessing visual acuity for patient centered outcome. All codes used for this study are currently available, and will be made available online at https://phekb.org.

Fault detection and identification for a class of continuous piecewise affine systems with unknown subsystems and partitions

NARCIS (Netherlands)

Le quang, Thuan; Baldi, S.

2018-01-01

This paper establishes a novel online fault detection and identification strategy for a class of continuous piecewise affine (PWA) systems, namely, bimodal and trimodal PWA systems. The main contributions with respect to the state-of-the-art are the recursive nature of the proposed scheme and the

Remote spectroscopic identification of bloodstains

NARCIS (Netherlands)

Bremmer, Rolf H.; Edelman, Gerda; Vegter, Tessa Dijn; Bijvoets, Ted; Aalders, Maurice C. G.

2011-01-01

Blood detection and identification at crime scenes are crucial for harvesting forensic evidence. Unfortunately, most tests for the identification of blood are destructive and time consuming. We present a fast and nondestructive identification test for blood, using noncontact reflectance

Loop-Mediated Isothermal Amplification (LAMP): Emergence As an Alternative Technology for Herbal Medicine Identification.

Science.gov (United States)

Li, Jing-Jian; Xiong, Chao; Liu, Yue; Liang, Jun-Song; Zhou, Xing-Wen

2016-01-01

Correct identification of medicinal plant ingredients is essential for their safe use and for the regulation of herbal drug supply chain. Loop-mediated isothermal amplification (LAMP) is a recently developed approach to identify herbal medicine species. This novel molecular biology technique enables timely and accurate testing, especially in settings where infrastructures to support polymerase chain reaction facilities are lacking. Studies that used this method have altered our view on the extent and complexity of herbal medicine identification. In this review, we give an introduction into LAMP analysis, covers the basic principles and important aspects in the development of LAMP analysis method. Then we presented a critical review of the application of LAMP-based methods in detecting and identifying raw medicinal plant materials and their processed products. We also provide a practical standard operating procedure (SOP) for the utilization of the LAMP protocol in herbal authentication, and consider the prospects of LAMP technology in the future developments of herbal medicine identification and the challenges associated with its application.

Identification of novel autoantibodies for detection of malignant mesothelioma.

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Xufei Zhang

Full Text Available The malignant mesothelioma (MM survival rate has been hampered by the lack of efficient and accurate early detection methods. The immune system may detect the early changes of tumor progression by responding with tumor-associated autoantibody production. Hence, in this study, we translated the humoral immune response to cancer proteins into a potential blood test for MM.A T7 phage MM cDNA library was constructed using MM tumor tissues and biopanned for tumor-associated antigens (TAAs using pooled MM patient and normal serum samples. About 1008 individual phage TAA clones from the biopanned library were subjected to protein microarray construction and tested with 53 MM and 52 control serum samples as a training group. Nine candidate autoantibody markers were selected from the training group using Tclass system and logistic regression statistical analysis, which achieved 94.3% sensitivity and 90.4% specificity with an AUC value of 0.89 in receiver operating characteristic analysis. The classifier was further evaluated with 50 patient and 50 normal serum samples as an independent blind validation, and the sensitivity of 86.0% and the specificity of 86.0% were obtained with an AUC of 0.82. Sequencing and BLASTN analysis of the classifier revealed that five of these nine candidate markers were found to have strong homology to cancer related proteins (PDIA6, MEG3, SDCCAG3, IGHG3, IGHG1.Our results indicated that using a panel of 9 autoantibody markers presented a promising accuracy for MM detection. Although the results need further validation in high-risk groups, they provided the potentials in developing a serum-based assay for MM diagnosis.

Identification of quinone imine containing glutathione conjugates of diclofenac in rat bile.

Science.gov (United States)

Waldon, Daniel J; Teffera, Yohannes; Colletti, Adria E; Liu, Jingzhou; Zurcher, Danielle; Copeland, Katrina W; Zhao, Zhiyang

2010-12-20

High-resolution accurate MS with an LTQ-Orbitrap was used to identify quinone imine metabolites derived from the 5-hydroxy (5-OH) and 4 prime-hydroxy (4'-OH) glutathione conjugates of diclofenac in rat bile. The initial quinone imine metabolites formed by oxidation of diclofenac have been postulated to be reactive intermediates potentially involved in diclofenac-mediated hepatotoxicity; while these metabolites could be formed using in vitro systems, they have never been detected in vivo. This report describes the identification of secondary quinone imine metabolites derived from 5-OH and 4'-OH diclofenac glutathione conjugates in rat bile. To verify the proposed structures, the diclofenac quinone imine GSH conjugate standards were prepared synthetically and enzymatically. The novel metabolite peaks displayed the identical retention times, accurate mass MS/MS spectra, and the fragmentation patterns as the corresponding authentic standards. The formation of these secondary quinone metabolites occurs only under conditions where bile salt homeostasis was experimentally altered. Standard practice in biliary excretion experiments using bile duct-cannulated rats includes infusion of taurocholic acid and/or other bile acids to replace those lost due to continuous collection of bile; for this experiment, the rats received no replacement bile acid infusion. High-resolution accurate mass spectrometry data and comparison with chemically and enzymatically prepared quinone imines of diclofenac glutathione conjugates support the identification of these metabolites. A mechanism for the formation of these reactive quinone imine containing glutathione conjugates of diclofenac is proposed.

Detection and identification of Rift Valley fever virus in mosquito vectors by quantitative real-time PCR.

Science.gov (United States)

Mwaengo, D; Lorenzo, G; Iglesias, J; Warigia, M; Sang, R; Bishop, R P; Brun, A

2012-10-01

Diagnostic methods allowing for rapid identification of pathogens are crucial for controlling and preventing dissemination after disease outbreaks as well as for use in surveillance programs. For arboviruses, detection of the presence of virus in their arthropod hosts is important for monitoring of viral activity and quantitative information is useful for modeling of transmission dynamics. In this study, molecular detection of Rift Valley fever virus (RVFV) in mosquito samples from the 2006 to 2007 East African outbreaks was performed using quantitative real-time PCR assay (qRT-PCR). Specific RVFV sequence-based primer/fluorogenic (TaqMan) probe sets were derived from the L and S RNA segments of the virus. Both primer-probe L and S segment-based combinations detected genomic RVFV sequences, with generally comparable levels of sensitivity. Viral loads from three mosquito species, Aedes mcintoshi, Aedes ochraceus and Mansonia uniformis were estimated and significant differences of between 5- and 1000-fold were detected between Ae. mcintoshi and M. uniformis using both the L and S primer-probe-based assays. The genetic relationships of the viral sequences in mosquito samples were established by partial M segment sequencing and assigned to the two previously described viral lineages defined by analysis of livestock isolates obtained during the 2006-2007 outbreak, confirming that similar viruses were present in both the vector and mammalian host. The data confirms the utility of qRT-PCR for identification and initial quantification of virus in mosquito samples during RVFV outbreaks. Copyright © 2012 Elsevier B.V. All rights reserved.

Lightweight autonomous chemical identification system (LACIS)

Science.gov (United States)

Lozos, George; Lin, Hai; Burch, Timothy

2012-06-01

Smiths Detection and Intelligent Optical Systems have developed prototypes for the Lightweight Autonomous Chemical Identification System (LACIS) for the US Department of Homeland Security. LACIS is to be a handheld detection system for Chemical Warfare Agents (CWAs) and Toxic Industrial Chemicals (TICs). LACIS is designed to have a low limit of detection and rapid response time for use by emergency responders and could allow determination of areas having dangerous concentration levels and if protective garments will be required. Procedures for protection of responders from hazardous materials incidents require the use of protective equipment until such time as the hazard can be assessed. Such accurate analysis can accelerate operations and increase effectiveness. LACIS is to be an improved point detector employing novel CBRNE detection modalities that includes a militaryproven ruggedized ion mobility spectrometer (IMS) with an array of electro-resistive sensors to extend the range of chemical threats detected in a single device. It uses a novel sensor data fusion and threat classification architecture to interpret the independent sensor responses and provide robust detection at low levels in complex backgrounds with minimal false alarms. The performance of LACIS prototypes have been characterized in independent third party laboratory tests at the Battelle Memorial Institute (BMI, Columbus, OH) and indoor and outdoor field tests at the Nevada National Security Site (NNSS). LACIS prototypes will be entering operational assessment by key government emergency response groups to determine its capabilities versus requirements.

Detection and identification of intestinal pathogenic bacteria by hybridization to oligonucleotide microarrays

Science.gov (United States)

Jin, Lian-Qun; Li, Jun-Wen; Wang, Sheng-Qi; Chao, Fu-Huan; Wang, Xin-Wei; Yuan, Zheng-Quan

2005-01-01

AIM: To detect the common intestinal pathogenic bacteria quickly and accurately. METHODS: A rapid (<3 h) experimental procedure was set up based upon the gene chip technology. Target genes were amplified and hybridized by oligonucleotide microarrays. RESULTS: One hundred and seventy strains of bacteria in pure culture belonging to 11 genera were successfully discriminated under comparatively same conditions, and a series of specific hybridization maps corresponding to each kind of bacteria were obtained. When this method was applied to 26 divided cultures, 25 (96.2%) were identified. CONCLUSION: Salmonella sp., Escherichia coli, Shigella sp., Listeria monocytogenes, Vibrio parahaemolyticus, Staphylococcus aureus, Proteus sp., Bacillus cereus, Vibrio cholerae, Enterococcus faecalis, Yersinia enterocolitica, and Campylobacter jejuni can be detected and identified by our microarrays. The accuracy, range, and discrimination power of this assay can be continually improved by adding further oligonucleotides to the arrays without any significant increase of complexity or cost. PMID:16437687

Identification of antimycotic drugs transformation products upon UV exposure

Energy Technology Data Exchange (ETDEWEB)

Casado, Jorge; Rodríguez, Isaac, E-mail: isaac.rodriguez@usc.es; Ramil, María; Cela, Rafael

2015-05-30

Highlights: • Evaluation of antimycotic drugs UV stabilities in model supports. • Simultaneous detection of precursor drugs and transformation products. • Transformation products identification from their scan, accurate MS/MS spectra. • Directed search of identified transformation products in sand and soil samples. • Preliminary toxicity estimations. - Abstract: The reactivity of three imidazolic, environmental persistent antimycotic drugs (clotrimazole, CTZ; ketoconazole, KTZ; and miconazole, MCZ) upon exposure to ultraviolet (UV) radiation is discussed. First, precursor compounds were immobilized in a silicone support which was further exposed to UV light at two different wavelengths: 254 and 365 nm. After solvent desorption, degradation kinetics of the precursor pharmaceuticals, identification of the arising transformation products (TPs) and evaluation of their time-course were investigated by liquid chromatography (LC) with quadrupole time-of-flight (QTOF) mass spectrometry (MS) detection. The three antimycotics displayed similar stabilities when exposed to 254 nm light; however, CTZ was significantly more stable than MCZ and KTZ when irradiated with the 365 nm lamp. TPs identified in silicone supports resulted from de-chlorination, cleavage, intra-molecular cyclization and hydroxylation reactions. Many of these species were also detected when exposing other solid matrices, such as sand and agricultural soil, previously spiked with target compounds, to UV light. The 50% estimated lethal concentration, calculated using the 48-h Daphnia magna test, for the two main TPs of CTZ and MCZ, at both wavelengths, were lower than those corresponding to the precursor drugs.

Identification of antimycotic drugs transformation products upon UV exposure

International Nuclear Information System (INIS)

Casado, Jorge; Rodríguez, Isaac; Ramil, María; Cela, Rafael

2015-01-01

Highlights: • Evaluation of antimycotic drugs UV stabilities in model supports. • Simultaneous detection of precursor drugs and transformation products. • Transformation products identification from their scan, accurate MS/MS spectra. • Directed search of identified transformation products in sand and soil samples. • Preliminary toxicity estimations. - Abstract: The reactivity of three imidazolic, environmental persistent antimycotic drugs (clotrimazole, CTZ; ketoconazole, KTZ; and miconazole, MCZ) upon exposure to ultraviolet (UV) radiation is discussed. First, precursor compounds were immobilized in a silicone support which was further exposed to UV light at two different wavelengths: 254 and 365 nm. After solvent desorption, degradation kinetics of the precursor pharmaceuticals, identification of the arising transformation products (TPs) and evaluation of their time-course were investigated by liquid chromatography (LC) with quadrupole time-of-flight (QTOF) mass spectrometry (MS) detection. The three antimycotics displayed similar stabilities when exposed to 254 nm light; however, CTZ was significantly more stable than MCZ and KTZ when irradiated with the 365 nm lamp. TPs identified in silicone supports resulted from de-chlorination, cleavage, intra-molecular cyclization and hydroxylation reactions. Many of these species were also detected when exposing other solid matrices, such as sand and agricultural soil, previously spiked with target compounds, to UV light. The 50% estimated lethal concentration, calculated using the 48-h Daphnia magna test, for the two main TPs of CTZ and MCZ, at both wavelengths, were lower than those corresponding to the precursor drugs

Identification of microcystins from three collection strains of Microcystis aeruginosa

International Nuclear Information System (INIS)

Campo, Francisca F. del; Ouahid, Youness

2010-01-01

Microcystins (MCs) are toxic cyclic heptapeptides produced by various cyanobacteria genera, especially Microcystis. We identified 10 out of 12 MCs produced by three Microcystis aeruginosa strains from cyanobacteria collections, UTEX 2666, UTEX 2670 and UAM 1303, by using two analytical methods: Matrix-assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF/MS) and HPLC Photodiode Array Detector coupled to a hybrid Quadrupole Time of Flight Mass Spectrometry (HPLC-PDA-QTOF/MS). MALDI-TOF/MS failed to detect non-polar MCs, such as MC-LY and MC-LW. HPLC-QTOF/MS permitted the accurate identification of most MCs present in methanolic extracts. Besides, three new MCs, namely: [D-Glu(OCH 3 ) 6 , D-Asp 3 ] MC-LAba, MC-YL and MC-YM were detected by HPLC-QTOF/MS. - Three new microcystin variants identified by HPLC-QTOF/MS.

Vertebra identification using template matching modelmp and K-means clustering.

Science.gov (United States)

Larhmam, Mohamed Amine; Benjelloun, Mohammed; Mahmoudi, Saïd

2014-03-01

Accurate vertebra detection and segmentation are essential steps for automating the diagnosis of spinal disorders. This study is dedicated to vertebra alignment measurement, the first step in a computer-aided diagnosis tool for cervical spine trauma. Automated vertebral segment alignment determination is a challenging task due to low contrast imaging and noise. A software tool for segmenting vertebrae and detecting subluxations has clinical significance. A robust method was developed and tested for cervical vertebra identification and segmentation that extracts parameters used for vertebra alignment measurement. Our contribution involves a novel combination of a template matching method and an unsupervised clustering algorithm. In this method, we build a geometric vertebra mean model. To achieve vertebra detection, manual selection of the region of interest is performed initially on the input image. Subsequent preprocessing is done to enhance image contrast and detect edges. Candidate vertebra localization is then carried out by using a modified generalized Hough transform (GHT). Next, an adapted cost function is used to compute local voted centers and filter boundary data. Thereafter, a K-means clustering algorithm is applied to obtain clusters distribution corresponding to the targeted vertebrae. These clusters are combined with the vote parameters to detect vertebra centers. Rigid segmentation is then carried out by using GHT parameters. Finally, cervical spine curves are extracted to measure vertebra alignment. The proposed approach was successfully applied to a set of 66 high-resolution X-ray images. Robust detection was achieved in 97.5 % of the 330 tested cervical vertebrae. An automated vertebral identification method was developed and demonstrated to be robust to noise and occlusion. This work presents a first step toward an automated computer-aided diagnosis system for cervical spine trauma detection.

Easier detection of invertebrate "identification-key characters" with light of different wavelengths

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Koken Marcel HM

2011-10-01

Full Text Available Abstract The marine α-taxonomist often encounters two problems. Firstly, the "environmental dirt" that is frequently present on the specimens and secondly the difficulty in distinguishing key-features due to the uniform colours which fixed animals often adopt. Here we show that illuminating animals with deep-blue or ultraviolet light instead of the normal white-light abrogates both difficulties; dirt disappears and important details become clearly visible. This light regime has also two other advantages. It allows easy detection of very small, normally invisible, animals (0.1 μm range. And as these light wavelengths can induce fluorescence, new identification markers may be discovered by this approach.

Highly accurate determination of relative gamma-ray detection efficiency for Ge detector and its application

International Nuclear Information System (INIS)

Miyahara, H.; Mori, C.; Fleming, R.F.; Dewaraja, Y.K.

1997-01-01

When quantitative measurements of γ-rays using High-Purity Ge (HPGe) detectors are made for a variety of applications, accurate knowledge of oy-ray detection efficiency is required. The emission rates of γ-rays from sources can be determined quickly in the case that the absolute peak efficiency is calibrated. On the other hand, the relative peak efficiencies can be used for determination of intensity ratios for plural samples and for comparison to the standard source. Thus, both absolute and relative detection efficiencies are important in use of γ-ray detector. The objective of this work is to determine the relative gamma-ray peak detection efficiency for an HPGe detector with the uncertainty approaching 0.1% . We used some nuclides which emit at least two gamma-rays with energies from 700 to 2400 keV for which the relative emission probabilities are known with uncertainties much smaller than 0.1%. The relative peak detection efficiencies were calculated from the measurements of the nuclides, 46 Sc, 48 Sc, 60 Co and 94 Nb, emitting two γ- rays with the emission probabilities of almost unity. It is important that various corrections for the emission probabilities, the cascade summing effect, and the self-absorption are small. A third order polynomial function on both logarithmic scales of energy and efficiency was fitted to the data, and the peak efficiency predicted at certain energy from covariance matrix showed the uncertainty less than 0.5% except for near 700 keV. As an application, the emission probabilities of the 1037.5 and 1212.9 keV γ-rays for 48 Sc were determined using the function of the highly precise relative peak efficiency. Those were 0.9777+0,.00079 and 0.02345+0.00017 for the 1037.5 and 1212.9 keV γ-rays, respectively. The sum of these probabilities is close to unity within the uncertainty which means that the certainties of the results are high and the accuracy has been improved considerably

Enhanced detection method for corneal protein identification using shotgun proteomics

Directory of Open Access Journals (Sweden)

Schlager John J

2009-06-01

Full Text Available Abstract Background The cornea is a specialized transparent connective tissue responsible for the majority of light refraction and image focus for the retina. There are three main layers of the cornea: the epithelium that is exposed and acts as a protective barrier for the eye, the center stroma consisting of parallel collagen fibrils that refract light, and the endothelium that is responsible for hydration of the cornea from the aqueous humor. Normal cornea is an immunologically privileged tissue devoid of blood vessels, but injury can produce a loss of these conditions causing invasion of other processes that degrade the homeostatic properties resulting in a decrease in the amount of light refracted onto the retina. Determining a measure and drift of phenotypic cornea state from normal to an injured or diseased state requires knowledge of the existing protein signature within the tissue. In the study of corneal proteins, proteomics procedures have typically involved the pulverization of the entire cornea prior to analysis. Separation of the epithelium and endothelium from the core stroma and performing separate shotgun proteomics using liquid chromatography/mass spectrometry results in identification of many more proteins than previously employed methods using complete pulverized cornea. Results Rabbit corneas were purchased, the epithelium and endothelium regions were removed, proteins processed and separately analyzed using liquid chromatography/mass spectrometry. Proteins identified from separate layers were compared against results from complete corneal samples. Protein digests were separated using a six hour liquid chromatographic gradient and ion-trap mass spectrometry used for detection of eluted peptide fractions. The SEQUEST database search results were filtered to allow only proteins with match probabilities of equal or better than 10-3 and peptides with a probability of 10-2 or less with at least two unique peptides isolated within

HARDWARE TROJAN IDENTIFICATION AND DETECTION

OpenAIRE

Samer Moein; Fayez Gebali; T. Aaron Gulliver; Abdulrahman Alkandari

2017-01-01

ABSTRACT The majority of techniques developed to detect hardware trojans are based on specific attributes. Further, the ad hoc approaches employed to design methods for trojan detection are largely ineffective. Hardware trojans have a number of attributes which can be used to systematically develop detection techniques. Based on this concept, a detailed examination of current trojan detection techniques and the characteristics of existing hardware trojans is presented. This is used to dev...

On System Identification of Wind Turbines

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Perisic, Nevena; Pedersen, B.J.

Recently several methods have been proposed for the system identification of wind turbines which can be considered as a linear time-varying system due to the operating conditions. For the identification of linear wind turbine models, either black-box or grey-box identification can be used....... The operational model analysis (OMA) methodology can provide accurate estimates of the natural frequencies, damping ratios and mode shapes of the systems as long as the measurements have a low noise to signal ratio. However, in order to take information about the wind turbine into account a grey...

Substructure identification for shear structures: cross-power spectral density method

International Nuclear Information System (INIS)

Zhang, Dongyu; Johnson, Erik A

2012-01-01

In this paper, a substructure identification method for shear structures is proposed. A shear structure is divided into many small substructures; utilizing the dynamic equilibrium of a one-floor substructure, an inductive identification problem is formulated, using the cross-power spectral densities between structural floor accelerations and a reference response, to estimate the parameters of that one story. Repeating this procedure, all story parameters of the shear structure are identified from top to bottom recursively. An identification error analysis is performed for the proposed substructure method, revealing how uncertain factors (e.g. measurement noise) in the identification process affect the identification accuracy. According to the error analysis, a smart reference selection rule is designed to choose the optimal reference response that further enhances the identification accuracy. Moreover, based on the identification error analysis, explicit formulae are developed to calculate the variances of the parameter identification errors. A ten-story shear structure is used to illustrate the effectiveness of the proposed substructure method. The simulation results show that the method, combined with the reference selection rule, can very accurately identify structural parameters despite large measurement noise. Furthermore, the proposed formulae provide good predictions for the variances of the parameter identification errors, which are vital for providing accurate warnings of structural damage. (paper)

A New Algorithm for Radioisotope Identification of Shielded and Masked SNM/RDD Materials

International Nuclear Information System (INIS)

Jeffcoat, R.

2012-01-01

Detection and identification of shielded and masked nuclear materials is crucial to national security, but vast borders and high volumes of traffic impose stringent requirements for practical detection systems. Such tools must be be mobile, and hence low power, provide a low false alarm rate, and be sufficiently robust to be operable by non-technical personnel. Currently fielded systems have not achieved all of these requirements simultaneously. Transport modeling such as that done in GADRAS is able to predict observed spectra to a high degree of fidelity; our research is focusing on a radionuclide identification algorithm that inverts this modeling within the constraints imposed by a handheld device. Key components of this work include incorporation of uncertainty as a function of both the background radiation estimate and the hypothesized sources, dimensionality reduction, and nonnegative matrix factorization. We have partially evaluated performance of our algorithm on a third-party data collection made with two different sodium iodide detection devices. Initial results indicate, with caveats, that our algorithm performs as good as or better than the on-board identification algorithms. The system developed was based on a probabilistic approach with an improved approach to variance modeling relative to past work. This system was chosen based on technical innovation and system performance over algorithms developed at two competing research institutions. One key outcome of this probabilistic approach was the development of an intuitive measure of confidence which was indeed useful enough that a classification algorithm was developed based around alarming on high confidence targets. This paper will present and discuss results of this novel approach to accurately identifying shielded or masked radioisotopes with radiation detection systems.

Rapid and Accurate Molecular Identification of the Emerging Multidrug-Resistant Pathogen Candida auris.

Science.gov (United States)

Kordalewska, Milena; Zhao, Yanan; Lockhart, Shawn R; Chowdhary, Anuradha; Berrio, Indira; Perlin, David S

2017-08-01

Candida auris is an emerging multidrug-resistant fungal pathogen causing nosocomial and invasive infections associated with high mortality. C. auris is commonly misidentified as several different yeast species by commercially available phenotypic identification platforms. Thus, there is an urgent need for a reliable diagnostic method. In this paper, we present fast, robust, easy-to-perform and interpret PCR and real-time PCR assays to identify C. auris and related species: Candida duobushaemulonii , Candida haemulonii , and Candida lusitaniae Targeting rDNA region nucleotide sequences, primers specific for C. auris only or C. auris and related species were designed. A panel of 140 clinical fungal isolates was used in both PCR and real-time PCR assays followed by electrophoresis or melting temperature analysis, respectively. The identification results from the assays were 100% concordant with DNA sequencing results. These molecular assays overcome the deficiencies of existing phenotypic tests to identify C. auris and related species. Copyright © 2017 Kordalewska et al.

Performance Assessment of the CapitalBio Mycobacterium Identification Array System for Identification of Mycobacteria

Science.gov (United States)

Liu, Jingbo; Yan, Zihe; Han, Min; Han, Zhijun; Jin, Lingjie; Zhao, Yanlin

2012-01-01

The CapitalBio Mycobacterium identification microarray system is a rapid system for the detection of Mycobacterium tuberculosis. The performance of this system was assessed with 24 reference strains, 486 Mycobacterium tuberculosis clinical isolates, and 40 clinical samples and then compared to the “gold standard” of DNA sequencing. The CapitalBio Mycobacterium identification microarray system showed highly concordant identification results of 100% and 98.4% for Mycobacterium tuberculosis complex (MTC) and nontuberculous mycobacteria (NTM), respectively. The sensitivity and specificity of the CapitalBio Mycobacterium identification array for identification of Mycobacterium tuberculosis isolates were 99.6% and 100%, respectively, for direct detection and identification of clinical samples, and the overall sensitivity was 52.5%. It was 100% for sputum, 16.7% for pleural fluid, and 10% for bronchoalveolar lavage fluid, respectively. The total assay was completed in 6 h, including DNA extraction, PCR, and hybridization. The results of this study confirm the utility of this system for the rapid identification of mycobacteria and suggest that the CapitalBio Mycobacterium identification array is a molecular diagnostic technique with high sensitivity and specificity that has the capacity to quickly identify most mycobacteria. PMID:22090408

A Survey and Proposed Framework on the Soft Biometrics Technique for Human Identification in Intelligent Video Surveillance System

Directory of Open Access Journals (Sweden)

Min-Gu Kim

2012-01-01

Full Text Available Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing.

A Survey and Proposed Framework on the Soft Biometrics Technique for Human Identification in Intelligent Video Surveillance System

Science.gov (United States)

Kim, Min-Gu; Moon, Hae-Min; Chung, Yongwha; Pan, Sung Bum

2012-01-01

Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing. PMID:22919273

A survey and proposed framework on the soft biometrics technique for human identification in intelligent video surveillance system.

Science.gov (United States)

Kim, Min-Gu; Moon, Hae-Min; Chung, Yongwha; Pan, Sung Bum

2012-01-01

Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing.

Retrival experience as an accurate indicator of person identification in line-ups

Directory of Open Access Journals (Sweden)

María José Contreras

2011-07-01

Full Text Available Responses in eyewitness identification of a person in a line-up may be based on two types of recovery experiences, remember and know experiences. Remember responses involve eyewitness identification of the target person as an episodic memory task, because it implies retrieving information about the target person in the place and at the time of the event. Know responses, in contrast, engage recognition based on familiarity or perceptual facilitation, that is, as a semantic memory task. To explore the relation between retrieval experiences and recognition accuracy, 86 participants took part in a recognition task with two conditions: one with an interpolated target absent line-up and the other only with the target present line-up. Accuracy of recognition and retrieval experience was measured. The results showed that, having previously participated in a target-absent line-up, increased omissions, while the number of hits decreased. Furthermore, participants’ know responses were associated to false recognition, whilst remember responses were associated to hits in recognition. Thus, asking eyewitnesses to inform about the kind of retrieval experience in which they based their recognition responses, may serve as a reliable indicator of accuracy in recognition. Future studies are needed to investigate whether this is also the case in natural settings.

[Study on the Identification of Geographical Indication Wuchang Rice Based on the Content of Inorganic Elements].

Science.gov (United States)

Li, Yong-le; Zheng, Yan-jie; Tang, Lu; Su, Zhi-yi; Xiong, Cen

2016-03-01

Wuchang rice is a geographical indication product in China. Due to its high quality and low production, the phenome- non of fake is more and more serious. An effective identification method of Wuchang rice is urgent needed, for the maintenance of its brand image and interest of consumers. Base on the content of inorganic elements which are analyzed by ICP-AES and ICP-MS in rice, the identification model of Wuchang rice is studied combining with principal component analysis (PCA), Fisher discrimination and artificial neural network (ANN) in this paper. The effect on the identification of samples is poor through PCA, while the samples from Wuchang area and other areas can be identified accurately through Fisher discrimination and ANN. The average accurate identification ratio of training and verification set through Fisher discrimination is 93.5%, while the average accurate identification ratio through ANN is 96.4%. The ability to identify of ANN is better than Fisher discrimination. Wuchang rice can be identified accurately through the result of this research which provides a technology for the protection of geographical indications of this product.

Functional neuroimaging of visuospatial working memory tasks enables accurate detection of attention deficit and hyperactivity disorder

Directory of Open Access Journals (Sweden)

Rubi Hammer

2015-01-01

Full Text Available Finding neurobiological markers for neurodevelopmental disorders, such as attention deficit and hyperactivity disorder (ADHD, is a major objective of clinicians and neuroscientists. We examined if functional Magnetic Resonance Imaging (fMRI data from a few distinct visuospatial working memory (VSWM tasks enables accurately detecting cases with ADHD. We tested 20 boys with ADHD combined type and 20 typically developed (TD boys in four VSWM tasks that differed in feedback availability (feedback, no-feedback and reward size (large, small. We used a multimodal analysis based on brain activity in 16 regions of interest, significantly activated or deactivated in the four VSWM tasks (based on the entire participants' sample. Dimensionality of the data was reduced into 10 principal components that were used as the input variables to a logistic regression classifier. fMRI data from the four VSWM tasks enabled a classification accuracy of 92.5%, with high predicted ADHD probability values for most clinical cases, and low predicted ADHD probabilities for most TDs. This accuracy level was higher than those achieved by using the fMRI data of any single task, or the respective behavioral data. This indicates that task-based fMRI data acquired while participants perform a few distinct VSWM tasks enables improved detection of clinical cases.

An effective approach for identification of in vivo protein-DNA binding sites from paired-end ChIP-Seq data

Directory of Open Access Journals (Sweden)

Wilson Zoe A

2010-02-01

Full Text Available Abstract Background ChIP-Seq, which combines chromatin immunoprecipitation (ChIP with high-throughput massively parallel sequencing, is increasingly being used for identification of protein-DNA interactions in vivo in the genome. However, to maximize the effectiveness of data analysis of such sequences requires the development of new algorithms that are able to accurately predict DNA-protein binding sites. Results Here, we present SIPeS (Site Identification from Paired-end Sequencing, a novel algorithm for precise identification of binding sites from short reads generated by paired-end solexa ChIP-Seq technology. In this paper we used ChIP-Seq data from the Arabidopsis basic helix-loop-helix transcription factor ABORTED MICROSPORES (AMS, which is expressed within the anther during pollen development, the results show that SIPeS has better resolution for binding site identification compared to two existing ChIP-Seq peak detection algorithms, Cisgenome and MACS. Conclusions When compared to Cisgenome and MACS, SIPeS shows better resolution for binding site discovery. Moreover, SIPeS is designed to calculate the mappable genome length accurately with the fragment length based on the paired-end reads. Dynamic baselines are also employed to effectively discriminate closely adjacent binding sites, for effective binding sites discovery, which is of particular value when working with high-density genomes.

Automatic reference selection for quantitative EEG interpretation: identification of diffuse/localised activity and the active earlobe reference, iterative detection of the distribution of EEG rhythms.

Science.gov (United States)

Wang, Bei; Wang, Xingyu; Ikeda, Akio; Nagamine, Takashi; Shibasaki, Hiroshi; Nakamura, Masatoshi

2014-01-01

EEG (Electroencephalograph) interpretation is important for the diagnosis of neurological disorders. The proper adjustment of the montage can highlight the EEG rhythm of interest and avoid false interpretation. The aim of this study was to develop an automatic reference selection method to identify a suitable reference. The results may contribute to the accurate inspection of the distribution of EEG rhythms for quantitative EEG interpretation. The method includes two pre-judgements and one iterative detection module. The diffuse case is initially identified by pre-judgement 1 when intermittent rhythmic waveforms occur over large areas along the scalp. The earlobe reference or averaged reference is adopted for the diffuse case due to the effect of the earlobe reference depending on pre-judgement 2. An iterative detection algorithm is developed for the localised case when the signal is distributed in a small area of the brain. The suitable averaged reference is finally determined based on the detected focal and distributed electrodes. The presented technique was applied to the pathological EEG recordings of nine patients. One example of the diffuse case is introduced by illustrating the results of the pre-judgements. The diffusely intermittent rhythmic slow wave is identified. The effect of active earlobe reference is analysed. Two examples of the localised case are presented, indicating the results of the iterative detection module. The focal and distributed electrodes are detected automatically during the repeating algorithm. The identification of diffuse and localised activity was satisfactory compared with the visual inspection. The EEG rhythm of interest can be highlighted using a suitable selected reference. The implementation of an automatic reference selection method is helpful to detect the distribution of an EEG rhythm, which can improve the accuracy of EEG interpretation during both visual inspection and automatic interpretation. Copyright © 2013 IPEM

Prevalence and Identification of Burkholderia pseudomallei and Near-Neighbor Species in the Malabar Coastal Region of India

Science.gov (United States)

Peddayelachagiri, Bhavani V.; Paul, Soumya; Nagaraj, Sowmya; Gogoi, Madhurjya; Sripathy, Murali H.; Batra, Harsh V.

2016-01-01

Accurate identification of pathogens with biowarfare importance requires detection tools that specifically differentiate them from near-neighbor species. Burkholderia pseudomallei, the causative agent of a fatal disease melioidosis, is one such biothreat agent whose differentiation from its near-neighbor species is always a challenge. This is because of its phenotypic similarity with other Burkholderia species which have a wide spread geographical distribution with shared environmental niches. Melioidosis is a major public health concern in endemic regions including Southeast Asia and northern Australia. In India, the disease is still considered to be emerging. Prevalence surveys of this saprophytic bacterium in environment are under-reported in the country. A major challenge in this case is the specific identification and differentiation of B. pseudomallei from the growing list of species of Burkholderia genus. The objectives of this study included examining the prevalence of B. pseudomallei and near-neighbor species in coastal region of South India and development of a novel detection tool for specific identification and differentiation of Burkholderia species. Briefly, we analyzed soil and water samples collected from Malabar coastal region of Kerala, South India for prevalence of B. pseudomallei. The presumptive Burkholderia isolates were identified using recA PCR assay. The recA PCR assay identified 22 of the total 40 presumptive isolates as Burkholderia strains (22.72% and 77.27% B. pseudomallei and non-pseudomallei Burkholderia respectively). In order to identify each isolate screened, we performed recA and 16S rDNA sequencing. This two genes sequencing revealed that the presumptive isolates included B. pseudomallei, non-pseudomallei Burkholderia as well as non-Burkholderia strains. Furthermore, a gene termed D-beta hydroxybutyrate dehydrogenase (bdha) was studied both in silico and in vitro for accurate detection of Burkholderia genus. The optimized bdha

Accurately bearing measurement in non-cooperative passive location system

International Nuclear Information System (INIS)

Liu Zhiqiang; Ma Hongguang; Yang Lifeng

2007-01-01

The system of non-cooperative passive location based on array is proposed. In the system, target is detected by beamforming and Doppler matched filtering; and bearing is measured by a long-base-ling interferometer which is composed of long distance sub-arrays. For the interferometer with long-base-line, the bearing is measured accurately but ambiguously. To realize unambiguous accurately bearing measurement, beam width and multiple constraint adoptive beamforming technique is used to resolve azimuth ambiguous. Theory and simulation result shows this method is effective to realize accurately bearing measurement in no-cooperate passive location system. (authors)

Residual signal feature extraction for gearbox planetary stage fault detection

DEFF Research Database (Denmark)

Skrimpas, Georgios Alexandros; Ursin, Thomas; Sweeney, Christian Walsted

2017-01-01

Faults in planetary gears and related bearings, e.g. planet bearings and planet carrier bearings, pose inherent difficulties on their accurate and consistent detection associated mainly to the low energy in slow rotating stages and the operating complexity of planetary gearboxes. In this work......, identification of the expected spectral signature for proper residual signal calculation and filtering of any frequency component not related to the planetary stage. Two field cases of planet carrier bearing defect and planet wheel spalling are presented and discussed, showing the efficiency of the followed...

Detection Identification and Quantification of Keto-Hydroperoxides in Low-Temperature Oxidation.

Energy Technology Data Exchange (ETDEWEB)

Hansen, Nils; Moshammer, Kai; Jasper, Ahren W.

2017-07-01

Keto-hydroperoxides are reactive partially oxidized intermediates that play a central role in chain-branching reactions during the low-temperature oxidation of hydrocarbons. In this Perspective, we outline how these short lived species can be detected, identified, and quantified using integrated experimental and theoretical approaches. The procedures are based on direct molecular-beam sampling from reactive environments, followed by mass spectrometry with single-photon ionization, identification of fragmentation patterns, and theoretical calculations of ionization thresholds, fragment appearance energies, and photoionization cross sections. Using the oxidation of neo-pentane and tetrahydrofuran as examples, the individual steps of the experimental approaches are described in depth together with a detailed description of the theoretical efforts. For neo-pentane, the experimental data are consistent with the calculated ionization and fragment appearance energies of the keto-hydroperoxide, thus adding confidence to the analysis routines and the employed levels of theory. For tetrahydrofuran, multiple keto-hydroperoxide isomers are possible due to the presence of nonequivalent O₂ addition sites. Despite this additional complexity, the experimental data allow for the identification of two to four keto-hydroperoxides. Mole fraction profiles of the keto-hydroperoxides, which are quantified using calculated photoionization cross sections, are provided together with estimated uncertainties as function of the temperature of the reactive mixture and can serve as validation targets for chemically detailed mechanisms.

A rapid method of accurate detection and differentiation of Newcastle disease virus pathotypes by demonstrating multiple bands in degenerate primer based nested RT-PCR.

Science.gov (United States)

Desingu, P A; Singh, S D; Dhama, K; Kumar, O R Vinodh; Singh, R; Singh, R K

2015-02-01

A rapid and accurate method of detection and differentiation of virulent and avirulent Newcastle disease virus (NDV) pathotypes was developed. The NDV detection was carried out for different domestic avian field isolates and pigeon paramyxo virus-1 (25 field isolates and 9 vaccine strains) by using APMV-I "fusion" (F) gene Class II specific external primer A and B (535bp), internal primer C and D (238bp) based reverses transcriptase PCR (RT-PCR). The internal degenerative reverse primer D is specific for F gene cleavage position of virulent strain of NDV. The nested RT-PCR products of avirulent strains showed two bands (535bp and 424bp) while virulent strains showed four bands (535bp, 424bp, 349bp and 238bp) on agar gel electrophoresis. This is the first report regarding development and use of degenerate primer based nested RT-PCR for accurate detection and differentiation of NDV pathotypes by demonstrating multiple PCR band patterns. Being a rapid, simple, and economical test, the developed method could serve as a valuable alternate diagnostic tool for characterizing NDV isolates and carrying out molecular epidemiological surveillance studies for this important pathogen of poultry. Copyright © 2014 Elsevier B.V. All rights reserved.

Spatial-Temporal Synchrophasor Data Characterization and Analytics in Smart Grid Fault Detection, Identification, and Impact Causal Analysis

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang; Dai, Xiaoxiao; Gao, David Wenzhong; Zhang, Jun Jason; Zhang, Yingchen; Muljadi, Eduard

2016-09-01

An approach of big data characterization for smart grids (SGs) and its applications in fault detection, identification, and causal impact analysis is proposed in this paper, which aims to provide substantial data volume reduction while keeping comprehensive information from synchrophasor measurements in spatial and temporal domains. Especially, based on secondary voltage control (SVC) and local SG observation algorithm, a two-layer dynamic optimal synchrophasor measurement devices selection algorithm (OSMDSA) is proposed to determine SVC zones, their corresponding pilot buses, and the optimal synchrophasor measurement devices. Combining the two-layer dynamic OSMDSA and matching pursuit decomposition, the synchrophasor data is completely characterized in the spatial-temporal domain. To demonstrate the effectiveness of the proposed characterization approach, SG situational awareness is investigated based on hidden Markov model based fault detection and identification using the spatial-temporal characteristics generated from the reduced data. To identify the major impact buses, the weighted Granger causality for SGs is proposed to investigate the causal relationship of buses during system disturbance. The IEEE 39-bus system and IEEE 118-bus system are employed to validate and evaluate the proposed approach.

High-Speed Target Identification System Based on the Plume’s Spectral Distribution

Directory of Open Access Journals (Sweden)

Wenjie Lang

2015-01-01

Full Text Available In order to recognize the target of high speed quickly and accurately, an identification system was designed based on analysis of the distribution characteristics of the plume spectrum. In the system, the target was aligned with visible light tracking module, and the spectral analysis of the target’s plume radiation was achieved by interference module. The distinguishing factor recognition algorithm was designed on basis of ratio of multifeature band peaks and valley mean values. Effective recognition of the high speed moving target could be achieved after partition of the active region and the influence of target motion on spectral acquisition was analyzed. In the experiment the small rocket combustion was used as the target. The spectral detection experiment was conducted at different speeds 2.0 km away from the detection system. Experimental results showed that spectral distribution had significant spectral offset in the same sampling period for the target with different speeds, but the spectral distribution was basically consistent. Through calculation of the inclusion relationship between distinguishing factor and distinction interval of the peak value and the valley value at the corresponding wave-bands, effective identification of target could be achieved.

Simultaneous detection and identification of Aspergillus and mucorales species in tissues collected from patients with fungal rhinosinusitis.

Science.gov (United States)

Zhao, Zuotao; Li, Lili; Wan, Zhe; Chen, Wei; Liu, Honggang; Li, Ruoyu

2011-04-01

Rapid detection and differentiation of Aspergillus and Mucorales species in fungal rhinosinusitis diagnosis are desirable, since the clinical management and prognosis associated with the two taxa are fundamentally different. We describe an assay based on a combination of broad-range PCR amplification and reverse line blot hybridization (PCR/RLB) to detect and differentiate the pathogens causing fungal rhinosinusitis, which include five Aspergillus species (A. fumigatus, A. flavus, A. niger, A. terreus, and A. nidulans) and seven Mucorales species (Mucor heimalis, Mucor racemosus, Mucor cercinelloidea, Rhizopus arrhizus, Rhizopus microsporus, Rhizomucor pusillus, and Absidia corymbifera). The assay was validated with 98 well-characterized clinical isolates and 41 clinical tissue specimens. PCR/RLB showed high sensitivity and specificity, with 100% correct identifications of 98 clinical isolates and no cross-hybridization between the species-specific probes. Results for five control isolates, Candida albicans, Fusarium solani, Scedosporium apiospermum, Penicillium marneffei, and Exophiala verrucosa, were negative as judged by PCR/RLB. The analytical sensitivity of PCR/RLB was found to be 1.8 × 10(-3) ng/μl by 10-fold serial dilution of Aspergillus genomic DNA. The assay identified 35 of 41 (85.4%) clinical specimens, exhibiting a higher sensitivity than fungal culture (22 of 41; 53.7%) and direct sequencing (18 of 41; 43.9%). PCR/RLB similarly showed high specificity, with correct identification 16 of 18 specimens detected by internal transcribed spacer (ITS) sequencing and 16 of 22 detected by fungal culture, but it also has the additional advantage of being able to detect mixed infection in a single clinical specimen. The PCR/RLB assay thus provides a rapid and reliable option for laboratory diagnosis of fungal rhinosinusitis.

Simultaneous Detection and Identification of Aspergillus and Mucorales Species in Tissues Collected from Patients with Fungal Rhinosinusitis▿

Science.gov (United States)

Zhao, Zuotao; Li, Lili; Wan, Zhe; Chen, Wei; Liu, Honggang; Li, Ruoyu

2011-01-01

Rapid detection and differentiation of Aspergillus and Mucorales species in fungal rhinosinusitis diagnosis are desirable, since the clinical management and prognosis associated with the two taxa are fundamentally different. We describe an assay based on a combination of broad-range PCR amplification and reverse line blot hybridization (PCR/RLB) to detect and differentiate the pathogens causing fungal rhinosinusitis, which include five Aspergillus species (A. fumigatus, A. flavus, A. niger, A. terreus, and A. nidulans) and seven Mucorales species (Mucor heimalis, Mucor racemosus, Mucor cercinelloidea, Rhizopus arrhizus, Rhizopus microsporus, Rhizomucor pusillus, and Absidia corymbifera). The assay was validated with 98 well-characterized clinical isolates and 41 clinical tissue specimens. PCR/RLB showed high sensitivity and specificity, with 100% correct identifications of 98 clinical isolates and no cross-hybridization between the species-specific probes. Results for five control isolates, Candida albicans, Fusarium solani, Scedosporium apiospermum, Penicillium marneffei, and Exophiala verrucosa, were negative as judged by PCR/RLB. The analytical sensitivity of PCR/RLB was found to be 1.8 × 10−3 ng/μl by 10-fold serial dilution of Aspergillus genomic DNA. The assay identified 35 of 41 (85.4%) clinical specimens, exhibiting a higher sensitivity than fungal culture (22 of 41; 53.7%) and direct sequencing (18 of 41; 43.9%). PCR/RLB similarly showed high specificity, with correct identification 16 of 18 specimens detected by internal transcribed spacer (ITS) sequencing and 16 of 22 detected by fungal culture, but it also has the additional advantage of being able to detect mixed infection in a single clinical specimen. The PCR/RLB assay thus provides a rapid and reliable option for laboratory diagnosis of fungal rhinosinusitis. PMID:21325541

A multiplex nested PCR for the detection and identification of Candida species in blood samples of critically ill paediatric patients.

Science.gov (United States)

Taira, Cleison Ledesma; Okay, Thelma Suely; Delgado, Artur Figueiredo; Ceccon, Maria Esther Jurfest Rivero; de Almeida, Margarete Teresa Gottardo; Del Negro, Gilda Maria Barbaro

2014-07-21

Nosocomial candidaemia is associated with high mortality rates in critically ill paediatric patients; thus, the early detection and identification of the infectious agent is crucial for successful medical intervention. The PCR-based techniques have significantly increased the detection of Candida species in bloodstream infections. In this study, a multiplex nested PCR approach was developed for candidaemia detection in neonatal and paediatric intensive care patients. DNA samples from the blood of 54 neonates and children hospitalised in intensive care units with suspected candidaemia were evaluated by multiplex nested PCR with specific primers designed to identify seven Candida species, and the results were compared with those obtained from blood cultures. The multiplex nested PCR had a detection limit of four Candida genomes/mL of blood for all Candida species. Blood cultures were positive in 14.8% of patients, whereas the multiplex nested PCR was positive in 24.0% of patients, including all culture-positive patients. The results obtained with the molecular technique were available within 24 hours, and the assay was able to identify Candida species with 100% of concordance with blood cultures. Additionally, the multiplex nested PCR detected dual candidaemia in three patients. Our proposed PCR method may represent an effective tool for the detection and identification of Candida species in the context of candidaemia diagnosis in children, showing highly sensitive detection and the ability to identify the major species involved in this infection.

Early Detection and Identification of Anomalies in Chemical Regime

International Nuclear Information System (INIS)

Figedy, Stefan; Smiesko, Ivan

2011-01-01

This paper provides a brief information about the basic features of a newly developed diagnostic system for early detection and identification of anomalies incoming in the water chemistry regime of the primary and secondary circuit of VVER-440 reactor. This system, called SACHER (System of Analysis of CHEmical Regime) is being installed within the major modernization project at the NPP-V2 Bohunice in the Slovak Republic. System SACHER has been developed fully in MATLAB environment. The availability of prompt information about the chemical conditions of the primary and secondary circuit is very important to prevent the undue corrosion and deposit build-up. The typical chemical information systems that exist and work at the NPPs give the user values of the measured quantities together with their time trends and other derived values. It is then the experienced user's role to recognize the situation the monitored process is in and make the subsequent decisions and take the measures. The SACHER system, based on the computational intelligence techniques, inserts the elements of intelligence into the overall chemical information system. It has the modular structure with the following most important modules: normality module- its aim is to recognize that the process starts to deviate from the normal one and serves as the early warning to the staff to take the adequate measures, fuzzy identification module- its aim is to identify the anomaly on the basis of a set of fuzzy rules, time-prediction module- its aim is to predict the behavior/trend of selected chemical quantities 8 hours ahead in 15 min step from the moment of request, validation module- its aim is to validate the measured quantities, trend module- this module serves for showing the trends of the acquired quantities

Towards accurate detection of obfuscated web tracking

OpenAIRE

Le, Hoan; Fallace, Federico; Barlet Ros, Pere

2017-01-01

Web tracking is currently recognized as one of the most important privacy threats on the Internet. Over the last years, many methodologies have been developed to uncover web trackers. Most of them are based on static code analysis and the use of predefined blacklists. However, our main hypothesis is that web tracking has started to use obfuscated programming, a transformation of code that renders previous detection methodologies ineffective and easy to evade. In this paper, we propose a new m...

A colorimetric method for highly sensitive and accurate detection of iodide by finding the critical color in a color change process using silver triangular nanoplates

Energy Technology Data Exchange (ETDEWEB)

Yang, Xiu-Hua; Ling, Jian, E-mail: lingjian@ynu.edu.cn; Peng, Jun; Cao, Qiu-E., E-mail: qecao@ynu.edu.cn; Ding, Zhong-Tao; Bian, Long-Chun

2013-10-10

Graphical abstract: -- Highlights: •Demonstrated a new colorimetric strategy for iodide detection by silver nanoplates. •The colorimetric strategy is to find the critical color in a color change process. •The colorimetric strategy is more accurate and sensitive than common colorimetry. •Discovered a new morphological transformation phenomenon of silver nanoplates. -- Abstract: In this contribution, we demonstrated a novel colorimetric method for highly sensitive and accurate detection of iodide using citrate-stabilized silver triangular nanoplates (silver TNPs). Very lower concentration of iodide can induce an appreciable color change of silver TNPs solution from blue to yellow by fusing of silver TNPs to nanoparticles, as confirmed by UV–vis absorption spectroscopy and transmission electron microscopy (TEM). The principle of this colorimetric assay is not an ordinary colorimetry, but a new colorimetric strategy by finding the critical color in a color change process. With this strategy, 0.1 μM of iodide can be recognized within 30 min by naked-eyes observation, and lower concentration of iodide down to 8.8 nM can be detected using a spectrophotometer. Furthermore, this high sensitive colorimetric assay has good accuracy, stability and reproducibility comparing with other ordinary colorimetry. We believe this new colorimetric method will open up a fresh insight of simple, rapid and reliable detection of iodide and can find its future application in the biochemical analysis or clinical diagnosis.

A colorimetric method for highly sensitive and accurate detection of iodide by finding the critical color in a color change process using silver triangular nanoplates

International Nuclear Information System (INIS)

Yang, Xiu-Hua; Ling, Jian; Peng, Jun; Cao, Qiu-E.; Ding, Zhong-Tao; Bian, Long-Chun

2013-01-01

Graphical abstract: -- Highlights: •Demonstrated a new colorimetric strategy for iodide detection by silver nanoplates. •The colorimetric strategy is to find the critical color in a color change process. •The colorimetric strategy is more accurate and sensitive than common colorimetry. •Discovered a new morphological transformation phenomenon of silver nanoplates. -- Abstract: In this contribution, we demonstrated a novel colorimetric method for highly sensitive and accurate detection of iodide using citrate-stabilized silver triangular nanoplates (silver TNPs). Very lower concentration of iodide can induce an appreciable color change of silver TNPs solution from blue to yellow by fusing of silver TNPs to nanoparticles, as confirmed by UV–vis absorption spectroscopy and transmission electron microscopy (TEM). The principle of this colorimetric assay is not an ordinary colorimetry, but a new colorimetric strategy by finding the critical color in a color change process. With this strategy, 0.1 μM of iodide can be recognized within 30 min by naked-eyes observation, and lower concentration of iodide down to 8.8 nM can be detected using a spectrophotometer. Furthermore, this high sensitive colorimetric assay has good accuracy, stability and reproducibility comparing with other ordinary colorimetry. We believe this new colorimetric method will open up a fresh insight of simple, rapid and reliable detection of iodide and can find its future application in the biochemical analysis or clinical diagnosis

Performance of computer-aided diagnosis for detection of lacunar infarcts on brain MR images: ROC analysis of radiologists' detection

International Nuclear Information System (INIS)

Uchiyama, Y.; Yokoyama, R.; Hara, T.; Fujita, H.; Asano, T.; Kato, H.; Hoshi, H.; Yamakawa, H.; Iwama, T.; Ando, H.; Yamakawa, H.

2007-01-01

The detection and management of asymptomatic lacunar infarcts on magnetic resonance (MR) images are important tasks for radiologists to ensure the prevention of sever cerebral infarctions. However, accurate identification of lacunar infarcts is a difficult. Therefore, we developed a computer-aided diagnosis (CAD) scheme for detection of lacunar infarcts. The purpose of this study was to evaluate radiologists' performance in detection of lacunar infarcts without and with use of CAD scheme. 30 T1- and 30 T2- weighted images obtained from 30 patients were used for an observer study, which were consisted of 15 cases with a single lacunar infarct and 15 cases without any lacunar infarct. Six radiologists participated in the observer study. They interpreted lacunar infarcts first without and then with use of the scheme. For all six observers, average area under the receiver operating characteristic curve value was increased from 0.920 to 0.965 when they used the computer output. This CAD scheme might have the potential to improve the accuracy of radiologists' performance in the detection of lacunar infarcts on MR images. (orig.)

An Accurate Method for Inferring Relatedness in Large Datasets of Unphased Genotypes via an Embedded Likelihood-Ratio Test

KAUST Repository

Rodriguez, Jesse M.; Batzoglou, Serafim; Bercovici, Sivan

2013-01-01

, accurate and efficient detection of hidden relatedness becomes a challenge. To enable disease-mapping studies of increasingly large cohorts, a fast and accurate method to detect IBD segments is required. We present PARENTE, a novel method for detecting

CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation

Directory of Open Access Journals (Sweden)

Li Gong-Hua

2010-08-01

Full Text Available Abstract Background The rapid development of structural genomics has resulted in many "unknown function" proteins being deposited in Protein Data Bank (PDB, thus, the functional prediction of these proteins has become a challenge for structural bioinformatics. Several sequence-based and structure-based methods have been developed to predict protein function, but these methods need to be improved further, such as, enhancing the accuracy, sensitivity, and the computational speed. Here, an accurate algorithm, the CMASA (Contact MAtrix based local Structural Alignment algorithm, has been developed to predict unknown functions of proteins based on the local protein structural similarity. This algorithm has been evaluated by building a test set including 164 enzyme families, and also been compared to other methods. Results The evaluation of CMASA shows that the CMASA is highly accurate (0.96, sensitive (0.86, and fast enough to be used in the large-scale functional annotation. Comparing to both sequence-based and global structure-based methods, not only the CMASA can find remote homologous proteins, but also can find the active site convergence. Comparing to other local structure comparison-based methods, the CMASA can obtain the better performance than both FFF (a method using geometry to predict protein function and SPASM (a local structure alignment method; and the CMASA is more sensitive than PINTS and is more accurate than JESS (both are local structure alignment methods. The CMASA was applied to annotate the enzyme catalytic sites of the non-redundant PDB, and at least 166 putative catalytic sites have been suggested, these sites can not be observed by the Catalytic Site Atlas (CSA. Conclusions The CMASA is an accurate algorithm for detecting local protein structural similarity, and it holds several advantages in predicting enzyme active sites. The CMASA can be used in large-scale enzyme active site annotation. The CMASA can be available by the

Detection of Food Spoilage and Pathogenic Bacteria Based on Ligation Detection Reaction Coupled to Flow-Through Hybridization on Membranes

Directory of Open Access Journals (Sweden)

K. Böhme

2014-01-01

Full Text Available Traditional culturing methods are still commonly applied for bacterial identification in the food control sector, despite being time and labor intensive. Microarray technologies represent an interesting alternative. However, they require higher costs and technical expertise, making them still inappropriate for microbial routine analysis. The present study describes the development of an efficient method for bacterial identification based on flow-through reverse dot-blot (FT-RDB hybridization on membranes, coupled to the high specific ligation detection reaction (LDR. First, the methodology was optimized by testing different types of ligase enzymes, labeling, and membranes. Furthermore, specific oligonucleotide probes were designed based on the 16S rRNA gene, using the bioinformatic tool Oligonucleotide Retrieving for Molecular Applications (ORMA. Four probes were selected and synthesized, being specific for Aeromonas spp., Pseudomonas spp., Shewanella spp., and Morganella morganii, respectively. For the validation of the probes, 16 reference strains from type culture collections were tested by LDR and FT-RDB hybridization using universal arrays spotted onto membranes. In conclusion, the described methodology could be applied for the rapid, accurate, and cost-effective identification of bacterial species, exhibiting special relevance in food safety and quality.

Verification of protein biomarker specificity for the identification of biological stains by quadrupole time-of-flight mass spectrometry.

Science.gov (United States)

Legg, Kevin M; Powell, Roger; Reisdorph, Nichole; Reisdorph, Rick; Danielson, Phillip B

2017-03-01

Advances in proteomics technology over the past decade offer forensic serologists a greatly improved opportunity to accurately characterize the tissue source from which a DNA profile has been developed. Such information can provide critical context to evidence and can help to prioritize downstream DNA analyses. Previous proteome studies compiled panels of "candidate biomarkers" specific to each of five body fluids (i.e., peripheral blood, vaginal/menstrual fluid, seminal fluid, urine, and saliva). Here, a multiplex quadrupole time-of-flight mass spectrometry assay has been developed in order to verify the tissue/body fluid specificity the 23 protein biomarkers that comprise these panels and the consistency with which they can be detected across a sample population of 50 humans. Single-source samples of these human body fluids were accurately identified by the detection of one or more high-specificity biomarkers. Recovery of body fluid samples from a variety of substrates did not impede accurate characterization and, of the potential inhibitors assayed, only chewing tobacco juice appeared to preclude the identification of a target body fluid. Using a series of 2-component mixtures of human body fluids, the multiplex assay accurately identified both components in a single-pass. Only in the case of saliva and peripheral blood did matrix effects appear to impede the detection of salivary proteins. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detecting and Identifying Industrial Gases by a Method Based on Olfactory Machine at Different Concentrations

Directory of Open Access Journals (Sweden)

Yunlong Sun

2018-01-01

Full Text Available Gas sensors have been widely reported for industrial gas detection and monitoring. However, the rapid detection and identification of industrial gases are still a challenge. In this work, we measure four typical industrial gases including CO2, CH4, NH3, and volatile organic compounds (VOCs based on electronic nose (EN at different concentrations. To solve the problem of effective classification and identification of different industrial gases, we propose an algorithm based on the selective local linear embedding (SLLE to reduce the dimensionality and extract the features of high-dimensional data. Combining the Euclidean distance (ED formula with the proposed algorithm, we can achieve better classification and identification of four kinds of gases. We compared the classification and recognition results of classical principal component analysis (PCA, linear discriminate analysis (LDA, and PCA + LDA algorithms with the proposed SLLE algorithm after selecting the original data and performing feature extraction. The experimental results show that the recognition accuracy rate of the SLLE reaches 91.36%, which is better than the other three algorithms. In addition, the SLLE algorithm provides more efficient and accurate responses to high-dimensional industrial gas data. It can be used in real-time industrial gas detection and monitoring combined with gas sensor networks.

DNA detection and single nucleotide mutation identification using SERS for molecular diagnostics and global health

Science.gov (United States)

Ngo, Hoan T.; Gandra, Naveen; Fales, Andrew M.; Taylor, Steve M.; Vo-Dinh, Tuan

2017-02-01

Nucleic acid-based molecular diagnostics at the point-of-care (POC) and in resource-limited settings is still a challenge. We present a sensitive yet simple DNA detection method with single nucleotide polymorphism (SNP) identification capability. The detection scheme involves sandwich hybridization of magnetic beads conjugated with capture probes, target sequences, and ultrabright surface-enhanced Raman Scattering (SERS) nanorattles conjugated with reporter probes. Upon hybridization, the sandwich probes are concentrated at the detection focus controlled by a magnetic system for SERS measurements. The ultrabright SERS nanorattles, consisting of a core and a shell with resonance Raman reporters loaded in the gap space between the core and the shell, serve as SERS tags for ultrasensitive signal detection. Specific DNA sequences of the malaria parasite Plasmodium falciparum and dengue virus 1 (DENV1) were used as the model marker system. Detection limit of approximately 100 attomoles was achieved. Single nucleotide polymorphism (SNP) discrimination of wild type malaria DNA and mutant malaria DNA, which confers resistance to artemisinin drugs, was also demonstrated. The results demonstrate the molecular diagnostic potential of the nanorattle-based method to both detect and genotype infectious pathogens. The method's simplicity makes it a suitable candidate for molecular diagnosis at the POC and in resource-limited settings.

Identification of beer spoilage microorganisms using the MALDI Biotyper platform.

Science.gov (United States)

Turvey, Michelle Elizabeth; Weiland, Florian; Meneses, Jon; Sterenberg, Nick; Hoffmann, Peter

2016-03-01

Beer spoilage microorganisms present a major risk for the brewing industry and can lead to cost-intensive recall of contaminated products and damage to brand reputation. The applicability of molecular profiling using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) in combination with Biotyper software was investigated for the identification of beer spoilage microorganisms from routine brewery quality control samples. Reference mass spectrum profiles for three of the most common bacterial beer spoilage microorganisms (Lactobacillus lindneri, Lactobacillus brevis and Pediococcus damnosus), four commercially available brewing yeast strains (top- and bottom-fermenting) and Dekkera/Brettanomyces bruxellensis wild yeast were established, incorporated into the Biotyper reference library and validated by successful identification after inoculation into beer. Each bacterial species could be accurately identified and distinguished from one another and from over 5600 other microorganisms present in the Biotyper database. In addition, wild yeast contaminations were rapidly detected and distinguished from top- and bottom-fermenting brewing strains. The applicability and integration of mass spectrometry profiling using the Biotyper platform into existing brewery quality assurance practices within industry were assessed by analysing routine microbiology control samples from a local brewery, where contaminating microorganisms could be reliably identified. Brewery-isolated microorganisms not present in the Biotyper database were further analysed for identification using LC-MS/MS methods. This renders the Biotyper platform a promising candidate for biological quality control testing within the brewing industry as a more rapid, high-throughput and cost-effective technology that can be tailored for the detection of brewery-specific spoilage organisms from the local environment.

A novel copro-diagnostic molecular method for qualitative detection and identification of parasitic nematodes in amphibians and reptiles.

Directory of Open Access Journals (Sweden)

Lucas G Huggins

Full Text Available Anthropogenic disturbance via resource acquisition, habitat fragmentation and climate change, amongst other factors, has led to catastrophic global biodiversity losses and species extinctions at an accelerating rate. Amphibians are currently one of the worst affected classes with at least a third of species categorised as being threatened with extinction. At the same time, they are also critically important for many habitats and provide man with a powerful proxy for ecosystem health by acting as a bioindicator group. Whilst the causes of synchronised amphibian losses are varied recent research has begun to highlight a growing role that macroparasites are playing in amphibian declines. However, diagnosing parasite infection in the field can be problematic, principally relying on collection and euthanasia of hosts, followed by necropsy and morphological identification of parasites in situ. The current study developed a non-invasive PCR-based methodology for sensitive detection and identification of parasitic nematode DNA released in the faeces of infected amphibians as egg or tissue fragments (environmental DNA. A DNA extraction protocol optimised for liberation of DNA from resilient parasite eggs was developed alongside the design of a novel, nematode universal, degenerate primer pair, thus avoiding the difficulties of using species specific primers in situations where common parasite species are unknown. Used in conjunction this protocol and primer pair was tested on a wide range of faecal samples from captive and wild amphibians. The primers and protocol were validated and detected infections, including a Railletnema nematode infection in poison dart frogs from ZSL London Zoo and Mantella cowani frogs in the wild. Furthermore, we demonstrate the efficacy of our PCR-based protocol for detecting nematode infection in other hosts, such as the presence of pinworm (Aspiculuris in two tortoise species and whipworm (Trichuris muris in mice. Our

A novel copro-diagnostic molecular method for qualitative detection and identification of parasitic nematodes in amphibians and reptiles.

Science.gov (United States)

Huggins, Lucas G; Michaels, Christopher J; Cruickshank, Sheena M; Preziosi, Richard F; Else, Kathryn J

2017-01-01

Anthropogenic disturbance via resource acquisition, habitat fragmentation and climate change, amongst other factors, has led to catastrophic global biodiversity losses and species extinctions at an accelerating rate. Amphibians are currently one of the worst affected classes with at least a third of species categorised as being threatened with extinction. At the same time, they are also critically important for many habitats and provide man with a powerful proxy for ecosystem health by acting as a bioindicator group. Whilst the causes of synchronised amphibian losses are varied recent research has begun to highlight a growing role that macroparasites are playing in amphibian declines. However, diagnosing parasite infection in the field can be problematic, principally relying on collection and euthanasia of hosts, followed by necropsy and morphological identification of parasites in situ. The current study developed a non-invasive PCR-based methodology for sensitive detection and identification of parasitic nematode DNA released in the faeces of infected amphibians as egg or tissue fragments (environmental DNA). A DNA extraction protocol optimised for liberation of DNA from resilient parasite eggs was developed alongside the design of a novel, nematode universal, degenerate primer pair, thus avoiding the difficulties of using species specific primers in situations where common parasite species are unknown. Used in conjunction this protocol and primer pair was tested on a wide range of faecal samples from captive and wild amphibians. The primers and protocol were validated and detected infections, including a Railletnema nematode infection in poison dart frogs from ZSL London Zoo and Mantella cowani frogs in the wild. Furthermore, we demonstrate the efficacy of our PCR-based protocol for detecting nematode infection in other hosts, such as the presence of pinworm (Aspiculuris) in two tortoise species and whipworm (Trichuris muris) in mice. Our environmental DNA

Vulnerability Identification Errors in Security Risk Assessments

OpenAIRE

Taubenberger, Stefan

2014-01-01

At present, companies rely on information technology systems to achieve their business objectives, making them vulnerable to cybersecurity threats. Information security risk assessments help organisations to identify their risks and vulnerabilities. An accurate identification of risks and vulnerabilities is a challenge, because the input data is uncertain. So-called ’vulnerability identification errors‘ can occur if false positive vulnerabilities are identified, or if vulnerabilities remain u...

Combined, solid-state molecular property and gamma spectrometers for CBRNE detection

Science.gov (United States)

Rogers, Ben; Grate, Jay; Pearson, Brett; Gallagher, Neal; Wise, Barry; Whitten, Ralph; Adams, Jesse

2013-05-01

Nevada Nanotech Systems, Inc. (Nevada Nano) has developed a multi-sensor solution to Chemical, Biological, Radiological, Nuclear and Explosives (CBRNE) detection that combines the Molecular Property Spectrometer™ (MPS™)—a micro-electro-mechanical chip-based technology capable of measuring a variety of thermodynamic and electrostatic molecular properties of sampled vapors and particles—and a compact, high-resolution, solid-state gamma spectrometer module for identifying radioactive materials, including isotopes used in dirty bombs and nuclear weapons. By conducting multiple measurements, the system can provide a more complete characterization of an unknown sample, leading to a more accurate identification. Positive identifications of threats are communicated using an integrated wireless module. Currently, system development is focused on detection of commercial, military and improvised explosives, radioactive materials, and chemical threats. The system can be configured for a variety of CBRNE applications, including handheld wands and swab-type threat detectors requiring short sample times, and ultra-high sensitivity detectors in which longer sampling times are used. Here we provide an overview of the system design and operation and present results from preliminary testing.

Eyewitness Identification Accuracy and Response Latency: The Unruly 10-12-Second Rule

Science.gov (United States)

Weber, Nathan; Brewer, Neil; Wells, Gary L.; Semmler, Carolyn; Keast, Amber

2004-01-01

Data are reported from 3,213 research eyewitnesses confirming that accurate eyewitness identifications from lineups are made faster than are inaccurate identifications. However, consistent with predictions from the recognition and search literatures, the authors did not find support for the "10-12-s rule" in which lineup identifications faster…

Performance of computer-aided diagnosis for detection of lacunar infarcts on brain MR images: ROC analysis of radiologists' detection

Energy Technology Data Exchange (ETDEWEB)

Uchiyama, Y.; Yokoyama, R.; Hara, T.; Fujita, H. [Dept. of Intelligent Image Information, Graduate Scholl of Medicine, Gifu Univ. (Japan); Asano, T.; Kato, H.; Hoshi, H. [Dept. of Radiology, Graduate Scholl of Medicine, Gifu Univ. (Japan); Yamakawa, H.; Iwama, T. [Dept. of Neurosurgery, Graduate Scholl of Medicine, Gifu Univ. (Japan); Ando, H. [Dept. of Neurosurgery, Gifu Municipal Hospital (Japan); Yamakawa, H. [Dept. of Emergency and Critical Care Medicine, Chuno-Kousei Hospital (Japan)

2007-06-15

The detection and management of asymptomatic lacunar infarcts on magnetic resonance (MR) images are important tasks for radiologists to ensure the prevention of sever cerebral infarctions. However, accurate identification of lacunar infarcts is a difficult. Therefore, we developed a computer-aided diagnosis (CAD) scheme for detection of lacunar infarcts. The purpose of this study was to evaluate radiologists' performance in detection of lacunar infarcts without and with use of CAD scheme. 30 T1- and 30 T2- weighted images obtained from 30 patients were used for an observer study, which were consisted of 15 cases with a single lacunar infarct and 15 cases without any lacunar infarct. Six radiologists participated in the observer study. They interpreted lacunar infarcts first without and then with use of the scheme. For all six observers, average area under the receiver operating characteristic curve value was increased from 0.920 to 0.965 when they used the computer output. This CAD scheme might have the potential to improve the accuracy of radiologists' performance in the detection of lacunar infarcts on MR images. (orig.)

Identification of southern radio sources

International Nuclear Information System (INIS)

Savage, A.

1976-01-01

Identifications are suggested for 32 radio sources from the southern zones of the Parkes 2700 MHz survey, 18 with galaxies, one with a confirmed and 12 with possible quasistellar objects, and one with a supernova remnant in the Large Magellanic Cloud. The identifications were made from the ESO IIa-O quick blue survey plates, the SRC IIIa-J deep survey plates and the Palomar sky survey prints. Accurate optical positions have also been measured for 10 of the objects and for five previously suggested QSOs. (author)

Lymphoscintigraphic sentinel node identification in patients with breast cancer: the role of SPECT-CT

International Nuclear Information System (INIS)

Lerman, H.; Metser, U.; Lievshitz, G.; Sperber, F.; Shneebaum, S.; Even-Sapir, E.

2006-01-01

Lymph node status is a major factor in determining the stage, appropriate therapy and outcome in patients with breast cancer. It is therefore of clinical importance to accurately identify all sentinel nodes (SNs) for each individual tumour before surgery. The purpose of this study was to assess the role of SPECT-CT lymphoscintigraphy in SN identification in patients with breast cancer. Lymphoscintigraphy comprising planar and SPECT-CT acquisition was performed in 157 consecutive patients with breast cancer (mean age 54.7±10.6, range 27-81 years) with a palpable mass (n=100), with a non-palpable mass (n=52) or post lumpectomy (n=5). Planar and SPECT-CT images were interpreted separately and the two imaging techniques were compared with respect to their ability to identify hot nodes. Planar imaging alone was negative for identification of hot nodes in 15% of the patients. SPECT-CT alone was negative in 10% and both techniques were negative in 9% of the patients. Forty-six of the total of 361 (13%) hot nodes identified by lymphoscintigraphy were detected only on SPECT-CT, including 21 nodes obscured by the scattered radiation from the injection site, nine adjacent nodes misinterpreted on planar images as a single node and 16 nodes which were missed on planar images and detected on SPECT data. SPECT-CT detected additional sites of drainage unexpected on planar images, including axillary (n=23 patients), internal mammary (n=5 patients), interpectoral (n=3 patients) and intramammary (n=2 patients) lymph node sites. Fourteen of the 329 (4%) hot lesions seen on planar images were false positive non-nodal sites of uptake that were accurately assessed by SPECT-CT and further validated by surgery. In a single patient, SPECT-CT was negative while planar images identified the SN. (orig.)

Detection and identification of extra virgin olive oil adulteration by GC-MS combined with chemometrics.

Science.gov (United States)

Yang, Yang; Ferro, Miguel Duarte; Cavaco, Isabel; Liang, Yizeng

2013-04-17

In this study, an analytical method for the detection and identification of extra virgin olive oil adulteration with four types of oils (corn, peanut, rapeseed, and sunflower oils) was proposed. The variables under evaluation included 22 fatty acids and 6 other significant parameters (the ratio of linoleic/linolenic acid, oleic/linoleic acid, total saturated fatty acids (SFAs), polyunsaturated fatty acids (PUFAs), monounsaturated fatty acids (MUFAs), MUFAs/PUFAs). Univariate analyses followed by multivariate analyses were applied to the adulteration investigation. As a result, the univariate analyses demonstrated that higher contents of eicosanoic acid, docosanoic acid, tetracosanoic acid, and SFAs were the peculiarities of peanut adulteration and higher levels of linolenic acid, 11-eicosenoic acid, erucic acid, and nervonic acid the characteristics of rapeseed adulteration. Then, PLS-LDA made the detection of adulteration effective with a 1% detection limit and 90% prediction ability; a Monte Carlo tree identified the type of adulteration with 85% prediction ability.

Fusion of an Ensemble of Augmented Image Detectors for Robust Object Detection.

Science.gov (United States)

Wei, Pan; Ball, John E; Anderson, Derek T

2018-03-17

A significant challenge in object detection is accurate identification of an object's position in image space, whereas one algorithm with one set of parameters is usually not enough, and the fusion of multiple algorithms and/or parameters can lead to more robust results. Herein, a new computational intelligence fusion approach based on the dynamic analysis of agreement among object detection outputs is proposed. Furthermore, we propose an online versus just in training image augmentation strategy. Experiments comparing the results both with and without fusion are presented. We demonstrate that the augmented and fused combination results are the best, with respect to higher accuracy rates and reduction of outlier influences. The approach is demonstrated in the context of cone, pedestrian and box detection for Advanced Driver Assistance Systems (ADAS) applications.

Fusion of an Ensemble of Augmented Image Detectors for Robust Object Detection

Directory of Open Access Journals (Sweden)

Pan Wei

2018-03-01

Full Text Available A significant challenge in object detection is accurate identification of an object’s position in image space, whereas one algorithm with one set of parameters is usually not enough, and the fusion of multiple algorithms and/or parameters can lead to more robust results. Herein, a new computational intelligence fusion approach based on the dynamic analysis of agreement among object detection outputs is proposed. Furthermore, we propose an online versus just in training image augmentation strategy. Experiments comparing the results both with and without fusion are presented. We demonstrate that the augmented and fused combination results are the best, with respect to higher accuracy rates and reduction of outlier influences. The approach is demonstrated in the context of cone, pedestrian and box detection for Advanced Driver Assistance Systems (ADAS applications.

A very accurate method for sentinel lymph node investigation: Gamma detecting probe associated with SPECT examination for depth

International Nuclear Information System (INIS)

Ascoli, G.; Cinti, P.; Nonni, M.; Rossi, B.

2002-01-01

Aim: aim of this study is to magnify the lymphoscintigraphy examination by gamma probe with SPECT acquisition for very accurate detection of depth of axilla node in patients affected by melanoma. Methods: according to physiological peculiarities the lymphatic system plays a very important role and represents the most important barrier to neoplastic cells spreading. The 'sentinel node' is the first lymph node draining the affected area. The tendency for surgery is a 'preventive' axillary dissection, even in presence of a clinically negative examination. In fact a high percentage of clinically negative lymph node shows a positive histology (presence of metastatic cells). The nuclear medicine method for researching 'sentinel node' is represented by a regional lymphoscintigraphy with normal gamma camera with a large field of view followed by examination with gamma detecting probe and, in following day, controlled in operating room to confirm the presence of the node early identified. We have completed this protocol with SPECT examination of affected axilla by use of injected laboratory capillary around axilla to perform an exact investigation of node depth. Discussion: Our experience in 150 cases in 18 months shows 100% of axilla 'sentinel node' detection, 25 cases with positive histologic examination and subsequently axillary dissection. Conclusions: In conclusion the scintigraphic examination with lymphoscintigraphy represents a good tool for management of patient with melanoma and the use of ''targeting' with collimated SPECT represent a very aid for the surgeon in reduction time for detection and dissection of lymph node, with high reduction of anesthesia duration

Development of electrochemical biosensors and solid-phase amplification methods for the detection of human papillomavirus genes

OpenAIRE

Civit Pitarch, Laia

2012-01-01

A rapid, accurate and reliable diagnosis is crucial for the identification of a disease, like cancer, where an early detection can improve patient survival outcomes. Cervical cancer is the third most commonly diagnosed and the fourth leading cause of cancer death in women. It is well known that persistent infections with high-risk human papillomaviruses (HPV) are the primary cause of cervical cancer. Electrochemical DNA biosensors have received important attention owing to their characterist...

Real-time whole-genome sequencing for routine typing, surveillance, and outbreak detection of verotoxigenic Escherichia coli.

OpenAIRE

Joensen, Katrine Grimstrup; Scheutz, Flemming; Lund, Ole; Hasman, Henrik; Kaas, Rolf Sommer; Nielsen, Eva M.; Aarestrup, Frank Møller

2014-01-01

Fast and accurate identification and typing of pathogens are essential for effective surveillance and outbreak detection. The current routine procedure is based on a variety of techniques, making the procedure laborious, time-consuming, and expensive. With whole-genome sequencing (WGS) becoming cheaper, it has huge potential in both diagnostics and routine surveillance. The aim of this study was to perform a real-time evaluation of WGS for routine typing and surveillance of verocytotoxin-prod...

Real-Time Whole-Genome Sequencing for Routine Typing, Surveillance, and Outbreak Detection of Verotoxigenic Escherichia coli

OpenAIRE

Joensen, Katrine Grimstrup; Scheutz, Flemming; Lund, Ole; Hasman, Henrik; Kaas, Rolf S.; Nielsen, Eva M.; Aarestrup, Frank M.

2014-01-01

Fast and accurate identification and typing of pathogens are essential for effective surveillance and outbreak detection. The current routine procedure is based on a variety of techniques, making the procedure laborious, time-consuming, and expensive. With whole-genome sequencing (WGS) becoming cheaper, it has huge potential in both diagnostics and routine surveillance. The aim of this study was to perform a real-time evaluation of WGS for routine typing and surveillance of verocytotoxin-prod...

Multimodal Person Re-identification Using RGB-D Sensors and a Transient Identification Database

DEFF Research Database (Denmark)

Møgelmose, Andreas; Moeslund, Thomas B.; Nasrollahi, Kamal

2013-01-01

This paper describes a system for person re-identification using RGB-D sensors. The system covers the full flow, from detection of subjects, over contour extraction, to re-identification using soft biometrics. The biometrics in question are part-based color histograms and the subjects height...

Field Test Kit for Gun Residue Detection; TOPICAL

International Nuclear Information System (INIS)

WALKER, PAMELA K.; RODACY, PHILIP J.

2002-01-01

One of the major needs of the law enforcement field is a product that quickly, accurately, and inexpensively identifies whether a person has recently fired a gun--even if the suspect has attempted to wash the traces of gunpowder off. The Field Test Kit for Gunshot Residue Identification based on Sandia National Laboratories technology works with a wide variety of handguns and other weaponry using gunpowder. There are several organic chemicals in small arms propellants such as nitrocellulose, nitroglycerine, dinitrotoluene, and nitrites left behind after the firing of a gun that result from the incomplete combustion of the gunpowder. Sandia has developed a colorimetric shooter identification kit for in situ detection of gunshot residue (GSR) from a suspect. The test kit is the first of its kind and is small, inexpensive, and easily transported by individual law enforcement personnel requiring minimal training for effective use. It will provide immediate information identifying gunshot residue

Identification of soft drinks using MEMS-IDT microsensors

Science.gov (United States)

Abraham, Jose K.; Karjathkar, Sonal; Jacesko, Stefany; Varadan, Vijay K.; Gardner, Julian W.

2005-05-01

Development of a taste sensor with high sensitivity, stability and selectivity is highly desirable for the food and beverage industries. The main goal of a taste sensor is to reproduce five kinds of senses of humans, which is quite difficult. The importance of knowing quality of beverages and drinking water has been recognized as a result of increase in concern in environmental pollution issues. However, no accurate measuring system appropriate for quality evaluation of beverages is available. A highly sensitive microsensor using horizontally polarized Surface Acoustic Waves (SH-SAW) for the detection and identification of soft drinks is presented in this paper. Different soft drinks were tested using this sensor and the results which could distinguish between two popular soft drinks like Pepsi and Coca cola is presented in this paper. The SH-SAW microsensors are fabricated on 36°-rotated Y cut X propagating LiTaO3 (36YX.LT) substrate. This design consists of a dual delay line configuration in which one line is free and other one is metallized and shielded. Due to high electromechanical coupling of 36YX.LT, it could detect difference in electrical properties and hence to distinguish different soft drinks. Measured electrical characteristics of these soft drinks at X-band frequency using free space system show distinguishable results. It is clear from these results that the microsensor based on 36YX.LT is an effective liquid identification system for quantifying human sensory expressions.

Proteome-based bacterial identification using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS): A revolutionary shift in clinical diagnostic microbiology.

Science.gov (United States)

Nomura, Fumio

2015-06-01

Rapid and accurate identification of microorganisms, a prerequisite for appropriate patient care and infection control, is a critical function of any clinical microbiology laboratory. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is a quick and reliable method for identification of microorganisms, including bacteria, yeast, molds, and mycobacteria. Indeed, there has been a revolutionary shift in clinical diagnostic microbiology. In the present review, the state of the art and advantages of MALDI-TOF MS-based bacterial identification are described. The potential of this innovative technology for use in strain typing and detection of antibiotic resistance is also discussed. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

Detection of the cyanobacterial hepatotoxins microcystins

International Nuclear Information System (INIS)

McElhiney, Jacqui; Lawton, Linda A.

2005-01-01

Concern regarding the presence of microcystins in drinking water and their possible contamination in food (e.g., salad vegetables, fish, shellfish) has resulted in the need for reliable methods for the detection and accurate quantification of this class of toxins. Currently, routine analysis of microcystins is most commonly carried out using high-performance liquid chromatography with photodiode array detection (HPLC-PDA), although more sensitive biological assays such as antibody-based ELISAs and protein phosphatase inhibition assays have also proven useful. However, many of these methods have been hindered by the availability of a wide range of purified microcystins. Although over 60 variants have now been reported, only a very small number are commercially available and calibrated standards are not yet obtainable. This has led to the common practice of reporting microcystin-LR equivalence regardless of which variant is present. The increased availability of HPLC with online mass spectral analysis (HPLC-MS) may facilitate more accurate detection of toxin variants but as several microcystins share the same molecular mass, definitive identification can be difficult. A further difficulty in analyzing microcystins is the requirement for sample processing before analysis. Solid phase extraction (SPE) is typically used to enrich environmental concentrations of microcystins, or to eliminate contaminants from complex samples such as animal and plant tissues. Recently, new technologies employing recombinant antibodies and molecularly imprinted polymers have been exploited to develop assays and biosensors for microcystins. These novel detection systems are highly sensitive, often do not require sample processing, and offer a simpler, less expensive alternative to analytical techniques. They have also been successfully employed in solid phase extraction formats for the concentration and clean up of environmental samples before HPLC analysis

Instant detection and identification of concealed explosive-related compounds: Induced Stokes Raman versus infrared.

Science.gov (United States)

Elbasuney, Sherif; El-Sherif, Ashraf F

2017-01-01

The instant detection of explosives and explosive-related compounds has become an urgent priority in recent years for homeland security and counter-terrorism applications. Modern techniques should offer enhancement in selectivity, sensitivity, and standoff distances. Miniaturisation, portability, and field-ruggedisation are crucial requirements. This study reports on instant and standoff identification of concealed explosive-related compounds using customized Raman technique. Stokes Raman spectra of common explosive-related compounds were generated and spectrally resolved to create characteristic finger print spectra. The scattered Raman emissions over the band 400:2000cm -1 were compared to infrared absorption using FTIR. It has been demonstrated that the two vibrational spectroscopic techniques were opposite and completing each other. Molecular vibrations with strong absorption in infrared (those involve strong change in dipole moments) induced weak signals in Raman and vice versa. The tailored Raman offered instant detection, high sensitivity, and standoff detection capabilities. Raman demonstrated characteristic fingerprint spectra with stable baseline and sharp intense peaks. Complete correlations of absorption/scattered signals to certain molecular vibrations were conducted to generate an entire spectroscopic profile of explosive-related compounds. This manuscript shades the light on Raman as one of the prevailing technologies for instantaneous detection of explosive-related compounds. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Rapid sample preparation for detection and identification of avian influenza virus from chicken faecal samples using magnetic bead microsystem

DEFF Research Database (Denmark)

Dhumpa, Raghuram; Bu, Minqiang; Handberg, Kurt

2010-01-01

Avian influenza virus (AIV) is an infectious agent of birds and mammals. AIV is causing huge economic loss and can be a threat to human health. Reverse transcriptase polymerase chain reaction (RT-PCR) has been used as a method for the detection and identification of AIV virus. Although RT...

Specific Detection and Identification of American Mulberry-Infecting and Italian Olive-Associated Strains of Xylella fastidiosa by Polymerase Chain Reaction.

Science.gov (United States)

Guan, Wei; Shao, Jonathan; Elbeaino, Toufic; Davis, Robert E; Zhao, Tingchang; Huang, Qi

2015-01-01

Xylella fastidiosa causes bacterial leaf scorch in many landscape trees including elm, oak, sycamore and mulberry, but methods for specific identification of a particular tree host species-limited strain or differentiation of tree-specific strains are lacking. It is also unknown whether a particular landscape tree-infecting X. fastidiosa strain is capable of infecting multiple landscape tree species in an urban environment. We developed two PCR primers specific for mulberry-infecting strains of X. fastidiosa based on the nucleotide sequence of a unique open reading frame identified only in mulberry-infecting strains among all the North and South American strains of X. fastidiosa sequenced to date. PCR using the primers allowed for detection and identification of mulberry-infecting X. fastidiosa strains in cultures and in samples collected from naturally infected mulberry trees. In addition, no mixed infections with or non-specific detections of the mulberry-infecting strains of X. fastidiosa were found in naturally X. fastidiosa-infected oak, elm and sycamore trees growing in the same region where naturally infected mulberry trees were grown. This genotype-specific PCR assay will be valuable for disease diagnosis, studies of strain-specific infections in insects and plant hosts, and management of diseases caused by X. fastidiosa. Unexpectedly but interestingly, the unique open reading frame conserved in the mulberry-infecting strains in the U. S. was also identified in the recently sequenced olive-associated strain CoDiRO isolated in Italy. When the primer set was tested against naturally infected olive plant samples collected in Italy, it allowed for detection of olive-associated strains of X. fastidiosa in Italy. This PCR assay, therefore, will also be useful for detection and identification of the Italian group of X. fastidiosa strains to aid understanding of the occurrence, evolution and biology of this new group of X. fastidiosa strains.

Specific Detection and Identification of American Mulberry-Infecting and Italian Olive-Associated Strains of Xylella fastidiosa by Polymerase Chain Reaction.

Directory of Open Access Journals (Sweden)

Wei Guan

Full Text Available Xylella fastidiosa causes bacterial leaf scorch in many landscape trees including elm, oak, sycamore and mulberry, but methods for specific identification of a particular tree host species-limited strain or differentiation of tree-specific strains are lacking. It is also unknown whether a particular landscape tree-infecting X. fastidiosa strain is capable of infecting multiple landscape tree species in an urban environment. We developed two PCR primers specific for mulberry-infecting strains of X. fastidiosa based on the nucleotide sequence of a unique open reading frame identified only in mulberry-infecting strains among all the North and South American strains of X. fastidiosa sequenced to date. PCR using the primers allowed for detection and identification of mulberry-infecting X. fastidiosa strains in cultures and in samples collected from naturally infected mulberry trees. In addition, no mixed infections with or non-specific detections of the mulberry-infecting strains of X. fastidiosa were found in naturally X. fastidiosa-infected oak, elm and sycamore trees growing in the same region where naturally infected mulberry trees were grown. This genotype-specific PCR assay will be valuable for disease diagnosis, studies of strain-specific infections in insects and plant hosts, and management of diseases caused by X. fastidiosa. Unexpectedly but interestingly, the unique open reading frame conserved in the mulberry-infecting strains in the U. S. was also identified in the recently sequenced olive-associated strain CoDiRO isolated in Italy. When the primer set was tested against naturally infected olive plant samples collected in Italy, it allowed for detection of olive-associated strains of X. fastidiosa in Italy. This PCR assay, therefore, will also be useful for detection and identification of the Italian group of X. fastidiosa strains to aid understanding of the occurrence, evolution and biology of this new group of X. fastidiosa strains.

Towards Accurate Node-Based Detection of P2P Botnets

Directory of Open Access Journals (Sweden)

Chunyong Yin

2014-01-01

Full Text Available Botnets are a serious security threat to the current Internet infrastructure. In this paper, we propose a novel direction for P2P botnet detection called node-based detection. This approach focuses on the network characteristics of individual nodes. Based on our model, we examine node’s flows and extract the useful features over a given time period. We have tested our approach on real-life data sets and achieved detection rates of 99-100% and low false positives rates of 0–2%. Comparison with other similar approaches on the same data sets shows that our approach outperforms the existing approaches.

Identification of impact force acting on composite laminated plates using the radiated sound measured with microphones

Science.gov (United States)

Atobe, Satoshi; Nonami, Shunsuke; Hu, Ning; Fukunaga, Hisao

2017-09-01

Foreign object impact events are serious threats to composite laminates because impact damage leads to significant degradation of the mechanical properties of the structure. Identification of the location and force history of the impact that was applied to the structure can provide useful information for assessing the structural integrity. This study proposes a method for identifying impact forces acting on CFRP (carbon fiber reinforced plastic) laminated plates on the basis of the sound radiated from the impacted structure. Identification of the impact location and force history is performed using the sound pressure measured with microphones. To devise a method for identifying the impact location from the difference in the arrival times of the sound wave detected with the microphones, the propagation path of the sound wave from the impacted point to the sensor is examined. For the identification of the force history, an experimentally constructed transfer matrix is employed to relate the force history to the corresponding sound pressure. To verify the validity of the proposed method, impact tests are conducted by using a CFRP cross-ply laminate as the specimen, and an impulse hammer as the impactor. The experimental results confirm the validity of the present method for identifying the impact location from the arrival time of the sound wave detected with the microphones. Moreover, the results of force history identification show the feasibility of identifying the force history accurately from the measured sound pressure using the experimental transfer matrix.

Multiplex PCR Assay for Identification of Six Different Staphylococcus spp. and Simultaneous Detection of Methicillin and Mupirocin Resistance

OpenAIRE

Campos-Peña, E.; Martín-Nuñez, E.; Pulido-Reyes, G.; Martín-Padrón, J.; Caro-Carrillo, E.; Donate-Correa, J.; Lorenzo-Castrillejo, I.; Alcoba-Flórez, J.; Machín, F.; Méndez-Alvarez, S.

2014-01-01

We describe a new, efficient, sensitive, and fast single-tube multiple-PCR protocol for the identification of the most clinically significant Staphylococcus spp. and the simultaneous detection of the methicillin and mupirocin resistance loci. The protocol identifies at the species level isolates belonging to S. aureus, S. epidermidis, S. haemolyticus, S. hominis, S. lugdunensis, and S. saprophyticus.

Quasi-closed phase forward-backward linear prediction analysis of speech for accurate formant detection and estimation.

Science.gov (United States)

Gowda, Dhananjaya; Airaksinen, Manu; Alku, Paavo

2017-09-01

Recently, a quasi-closed phase (QCP) analysis of speech signals for accurate glottal inverse filtering was proposed. However, the QCP analysis which belongs to the family of temporally weighted linear prediction (WLP) methods uses the conventional forward type of sample prediction. This may not be the best choice especially in computing WLP models with a hard-limiting weighting function. A sample selective minimization of the prediction error in WLP reduces the effective number of samples available within a given window frame. To counter this problem, a modified quasi-closed phase forward-backward (QCP-FB) analysis is proposed, wherein each sample is predicted based on its past as well as future samples thereby utilizing the available number of samples more effectively. Formant detection and estimation experiments on synthetic vowels generated using a physical modeling approach as well as natural speech utterances show that the proposed QCP-FB method yields statistically significant improvements over the conventional linear prediction and QCP methods.

Detection of Sensor Faults in Small Helicopter UAVs Using Observer/Kalman Filter Identification

Directory of Open Access Journals (Sweden)

Guillermo Heredia

2011-01-01

Full Text Available Reliability is a critical issue in navigation of unmanned aerial vehicles (UAVs since there is no human pilot that can react to any abnormal situation. Due to size and cost limitations, redundant sensor schemes and aeronautical-grade navigation sensors used in large aircrafts cannot be installed in small UAVs. Therefore, other approaches like analytical redundancy should be used to detect faults in navigation sensors and increase reliability. This paper presents a sensor fault detection and diagnosis system for small autonomous helicopters based on analytical redundancy. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The observer is obtained from input-output experimental data with the Observer/Kalman Filter Identification (OKID method. The OKID method is able to identify the system and an observer with properties similar to a Kalman filter, directly from input-output experimental data. Results are similar to the Kalman filter, but, with the proposed method, there is no need to estimate neither system matrices nor sensor and process noise covariance matrices. The system has been tested with real helicopter flight data, and the results compared with other methods.

[Identification of Circulating Tumor Cell（CTC）in Breast Cancer Patients Using a Newly Established CTC Detecting System].

Science.gov (United States)

Nagata, Takuya; Ohnaga, Takashi; Lu, Xiao Long; Watanabe, Toru; Hirano, Katsuhisa; Okumura, Tomoyuki; Tsukada, Kazuhiro

2015-10-01

We developed a new circulating tumor cell (CTC) chip in order to identify CTCs in the peripheral blood of cancer patients. In this study, we aimed to identify CTCs in the blood of breast cancer patients by using this CTC detecting system. In addition, we used this system to evaluate the response to anticancer agents. We were able to identify CTCs in 5 of 6 patients. In addition, the system showed that the number of CTCs had decreased after chemotherapy. Thus, the CTC detecting system was useful in the identification of CTCs in the breast cancer patients and in the early prediction of response to anticancer agents.

Automatic detection of patient identification and positioning errors in radiation therapy treatment using 3-dimensional setup images.

Science.gov (United States)

Jani, Shyam S; Low, Daniel A; Lamb, James M

2015-01-01

To develop an automated system that detects patient identification and positioning errors between 3-dimensional computed tomography (CT) and kilovoltage CT planning images. Planning kilovoltage CT images were collected for head and neck (H&N), pelvis, and spine treatments with corresponding 3-dimensional cone beam CT and megavoltage CT setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. For positioning errors, setup and planning images were misaligned by 1 to 5 cm in the 6 anatomical directions for H&N and pelvis patients. Spinal misalignments were simulated by misaligning to adjacent vertebral bodies. Image pairs were assessed using commonly used image similarity metrics as well as custom-designed metrics. Linear discriminant analysis classification models were trained and tested on the imaging datasets, and misclassification error (MCE), sensitivity, and specificity parameters were estimated using 10-fold cross-validation. For patient identification, our workflow produced MCE estimates of 0.66%, 1.67%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivity and specificity ranged from 97.5% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 95.4% and 97.7%. MCEs for 1-cm H&N/pelvis misalignments were 1.3%/5.1% and 9.1%/8.6% for TomoTherapy and TrueBeam images, respectively. Two-centimeter MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. MCEs for vertebral body misalignments were 4.8% and 3.6% for TomoTherapy and TrueBeam images, respectively. Patient identification and gross misalignment errors can be robustly and automatically detected using 3-dimensional setup images of different energies across 3 commonly treated anatomical sites. Copyright © 2015 American Society for Radiation Oncology. Published by

Eyewitness confidence in simultaneous and sequential lineups: a criterion shift account for sequential mistaken identification overconfidence.

Science.gov (United States)

Dobolyi, David G; Dodson, Chad S

2013-12-01

Confidence judgments for eyewitness identifications play an integral role in determining guilt during legal proceedings. Past research has shown that confidence in positive identifications is strongly associated with accuracy. Using a standard lineup recognition paradigm, we investigated accuracy using signal detection and ROC analyses, along with the tendency to choose a face with both simultaneous and sequential lineups. We replicated past findings of reduced rates of choosing with sequential as compared to simultaneous lineups, but notably found an accuracy advantage in favor of simultaneous lineups. Moreover, our analysis of the confidence-accuracy relationship revealed two key findings. First, we observed a sequential mistaken identification overconfidence effect: despite an overall reduction in false alarms, confidence for false alarms that did occur was higher with sequential lineups than with simultaneous lineups, with no differences in confidence for correct identifications. This sequential mistaken identification overconfidence effect is an expected byproduct of the use of a more conservative identification criterion with sequential than with simultaneous lineups. Second, we found a steady drop in confidence for mistaken identifications (i.e., foil identifications and false alarms) from the first to the last face in sequential lineups, whereas confidence in and accuracy of correct identifications remained relatively stable. Overall, we observed that sequential lineups are both less accurate and produce higher confidence false identifications than do simultaneous lineups. Given the increasing prominence of sequential lineups in our legal system, our data argue for increased scrutiny and possibly a wholesale reevaluation of this lineup format. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Section-Based Tree Species Identification Using Airborne LIDAR Point Cloud

Science.gov (United States)

Yao, C.; Zhang, X.; Liu, H.

2017-09-01

The application of LiDAR data in forestry initially focused on mapping forest community, particularly and primarily intended for largescale forest management and planning. Then with the smaller footprint and higher sampling density LiDAR data available, detecting individual tree overstory, estimating crowns parameters and identifying tree species are demonstrated practicable. This paper proposes a section-based protocol of tree species identification taking palm tree as an example. Section-based method is to detect objects through certain profile among different direction, basically along X-axis or Y-axis. And this method improve the utilization of spatial information to generate accurate results. Firstly, separate the tree points from manmade-object points by decision-tree-based rules, and create Crown Height Mode (CHM) by subtracting the Digital Terrain Model (DTM) from the digital surface model (DSM). Then calculate and extract key points to locate individual trees, thus estimate specific tree parameters related to species information, such as crown height, crown radius, and cross point etc. Finally, with parameters we are able to identify certain tree species. Comparing to species information measured on ground, the portion correctly identified trees on all plots could reach up to 90.65 %. The identification result in this research demonstrate the ability to distinguish palm tree using LiDAR point cloud. Furthermore, with more prior knowledge, section-based method enable the process to classify trees into different classes.

Mode identification using stochastic hybrid models with applications to conflict detection and resolution

Science.gov (United States)

Naseri Kouzehgarani, Asal

2009-12-01

Most models of aircraft trajectories are non-linear and stochastic in nature; and their internal parameters are often poorly defined. The ability to model, simulate and analyze realistic air traffic management conflict detection scenarios in a scalable, composable, multi-aircraft fashion is an extremely difficult endeavor. Accurate techniques for aircraft mode detection are critical in order to enable the precise projection of aircraft conflicts, and for the enactment of altitude separation resolution strategies. Conflict detection is an inherently probabilistic endeavor; our ability to detect conflicts in a timely and accurate manner over a fixed time horizon is traded off against the increased human workload created by false alarms---that is, situations that would not develop into an actual conflict, or would resolve naturally in the appropriate time horizon-thereby introducing a measure of probabilistic uncertainty in any decision aid fashioned to assist air traffic controllers. The interaction of the continuous dynamics of the aircraft, used for prediction purposes, with the discrete conflict detection logic gives rise to the hybrid nature of the overall system. The introduction of the probabilistic element, common to decision alerting and aiding devices, places the conflict detection and resolution problem in the domain of probabilistic hybrid phenomena. A hidden Markov model (HMM) has two stochastic components: a finite-state Markov chain and a finite set of output probability distributions. In other words an unobservable stochastic process (hidden) that can only be observed through another set of stochastic processes that generate the sequence of observations. The problem of self separation in distributed air traffic management reduces to the ability of aircraft to communicate state information to neighboring aircraft, as well as model the evolution of aircraft trajectories between communications, in the presence of probabilistic uncertain dynamics as well

Expanded envelope concepts for aircraft control-element failure detection and identification

Science.gov (United States)

Weiss, Jerold L.; Hsu, John Y.

1988-01-01

The purpose of this effort was to develop and demonstrate concepts for expanding the envelope of failure detection and isolation (FDI) algorithms for aircraft-path failures. An algorithm which uses analytic-redundancy in the form of aerodynamic force and moment balance equations was used. Because aircraft-path FDI uses analytical models, there is a tradeoff between accuracy and the ability to detect and isolate failures. For single flight condition operation, design and analysis methods are developed to deal with this robustness problem. When the departure from the single flight condition is significant, algorithm adaptation is necessary. Adaptation requirements for the residual generation portion of the FDI algorithm are interpreted as the need for accurate, large-motion aero-models, over a broad range of velocity and altitude conditions. For the decision-making part of the algorithm, adaptation may require modifications to filtering operations, thresholds, and projection vectors that define the various hypothesis tests performed in the decision mechanism. Methods of obtaining and evaluating adequate residual generation and decision-making designs have been developed. The application of the residual generation ideas to a high-performance fighter is demonstrated by developing adaptive residuals for the AFTI-F-16 and simulating their behavior under a variety of maneuvers using the results of a NASA F-16 simulation.

The rapid identification for the unaware radioactive material

International Nuclear Information System (INIS)

Jin Yuren; Cheng Zhiwei; Xu Hui; Wang Jiang; Han Xiaoyuan; Long Bin

2010-01-01

The unaware radioactive material(URM) appeared in the society may induce serious deterministic effect, even result in havoc and instability of the society. The rapid and accurate identification for URM is the premise for its reasonable treatment. In this paper, an identification procedure for URM was developed and which was successfully implemented in the identification of an URM. The In-situ HPGe gamma spectrometry etc was employed for the rapid preliminary identification, and the laboratory HPGe gamma spectrometry and ICP-MS as well as the density measurement were used for its final identification. One unaware radioactive material was assayed, and the results indicate that it is a kind of high pure depleted uranium metal with the 235 U/ 238 U atomic ratio of 0.454%. (authors)

Identification of Polish cochineal (Porphyrophora polonica L.) in historical textiles by high-performance liquid chromatography coupled with spectrophotometric and tandem mass spectrometric detection.

Science.gov (United States)

Lech, Katarzyna; Jarosz, Maciej

2016-05-01

The present work reports a method for identification of Polish cochineal (Porphyrophora polonica L.) in historical fabrics by the use of high-performance liquid chromatography coupled with diode array and tandem mass spectrometric detection with electrospray ionization (HPLC-DAD-ESI MS/MS). This hyphened technique allows detection and identification of 16 new minor colorants present in the discussed scale insect (including two previously observed by Wouters and Verhecken (Ann Soc Entomol Fr. 1989;25:393-410), but specified only as compounds of unknown structures) that do not occur (e.g., in American cochineal). The MS/MS experiments, complemented with UV-VIS data, enable identification of mono- and di-, C- and O-hexosides of kermesic and flavokermesic acids or their derivatives. The present paper introduces a fingerprint of color compounds present in Polish cochineal and defines them, particularly pp6 (ppI, O-hexoside of flavokermesic acid), as its markers allow distinguishing of Polish-cochineal reds from the American ones. Usefulness of the selected set of markers for identification of Polish cochineal has been demonstrated in the examination of textiles from the collection of the National Museum in Warsaw using the multiple reaction monitoring (MRM) method, originally elaborated on the basis of this study.

MIDAS robust trend estimator for accurate GPS station velocities without step detection

Science.gov (United States)

Blewitt, Geoffrey; Kreemer, Corné; Hammond, William C.; Gazeaux, Julien

2016-03-01

Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil-Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj-xi)/(tj-ti) computed between all data pairs i > j. For normally distributed data, Theil-Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil-Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one-sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root-mean-square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences.

Early identification of microorganisms in blood culture prior to the detection of a positive signal in the BACTEC FX system using matrix-assisted laser desorption/ionization-time of flight mass spectrometry.

Science.gov (United States)

Wang, Ming-Cheng; Lin, Wei-Hung; Yan, Jing-Jou; Fang, Hsin-Yi; Kuo, Te-Hui; Tseng, Chin-Chung; Wu, Jiunn-Jong

2015-08-01

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) is a valuable method for rapid identification of blood stream infection (BSI) pathogens. Integration of MALDI-TOF MS and blood culture system can speed the identification of causative BSI microorganisms. We investigated the minimal microorganism concentrations of common BSI pathogens required for positive blood culture using BACTEC FX and for positive identification using MALDI-TOF MS. The time to detection with positive BACTEC FX and minimal incubation time with positive MALDI-TOF MS identification were determined for earlier identification of common BSI pathogens. The minimal microorganism concentrations required for positive blood culture using BACTEC FX were >10(7)-10(8) colony forming units/mL for most of the BSI pathogens. The minimal microorganism concentrations required for identification using MALDI-TOF MS were > 10(7) colony forming units/mL. Using simulated BSI models, one can obtain enough bacterial concentration from blood culture bottles for successful identification of five common Gram-positive and Gram-negative bacteria using MALDI-TOF MS 1.7-2.3 hours earlier than the usual time to detection in blood culture systems. This study provides an approach to earlier identification of BSI pathogens prior to the detection of a positive signal in the blood culture system using MALDI-TOF MS, compared to current methods. It can speed the time for identification of BSI pathogens and may have benefits of earlier therapy choice and on patient outcome. Copyright © 2013. Published by Elsevier B.V.

Identification of children with reading difficulties: Cheap can be adequate

DEFF Research Database (Denmark)

Poulsen, Mads; Nielsen, Anne-Mette Veber

Classification of reading difficulties: Cheap screening can be accurate Purpose: Three factors are important for identification of students in need of remedial instruction: accuracy, timeliness, and cost. The identification has to be accurate to be of any use, the identification has to be timely......, inexpensive testing. The present study investigated the classification accuracy of three screening models varying in timeliness and cost. Method: We compared the ROC statistics of three logistic models for predicting end of Grade 2 reading difficulties in a sample of 164 students: 1) an early, comprehensive...... model using a battery of Grade 0 tests, including phoneme awareness, rapid naming, and paired associate learning, 2) a late, comprehensive model adding reading measures from January of Grade 1, and 3) a late, inexpensive model using only group-administered reading measures from January of Grade 1...

Rapid identification of ascomycetous yeasts from clinical specimens by a molecular method based on flow cytometry and comparison with identifications from phenotypic assays.

Science.gov (United States)

Page, Brent T; Shields, Christine E; Merz, William G; Kurtzman, Cletus P

2006-09-01

This study was designed to compare the identification of ascomycetous yeasts recovered from clinical specimens by using phenotypic assays (PA) and a molecular flow cytometric (FC) method. Large-subunit rRNA domains 1 and 2 (D1/D2) gene sequence analysis was also performed and served as the reference for correct strain identification. A panel of 88 clinical isolates was tested that included representatives of nine commonly encountered species and six infrequently encountered species. The PA included germ tube production, fermentation of seven carbohydrates, morphology on corn meal agar, urease and phenoloxidase activities, and carbohydrate assimilation tests when needed. The FC method (Luminex) employed species-specific oligonucleotides attached to polystyrene beads, which were hybridized with D1/D2 amplicons from the unidentified isolates. The PA identified 81 of 88 strains correctly but misidentified 4 of Candida dubliniensis, 1 of C. bovina, 1 of C. palmioleophila, and 1 of C. bracarensis. The FC method correctly identified 79 of 88 strains and did not misidentify any isolate but did not identify nine isolates because oligonucleotide probes were not available in the current library. The FC assay takes approximately 5 h, whereas the PA takes from 2 h to 5 days for identification. In conclusion, PA did well with the commonly encountered species, was not accurate for uncommon species, and takes significantly longer than the FC method. These data strongly support the potential of FC technology for rapid and accurate identification of medically important yeasts. With the introduction of new antifungals, rapid, accurate identification of pathogenic yeasts is more important than ever for guiding antifungal chemotherapy.

Rapid detection and identification of pathogenic mycobacteria by combining radiometric and nucleic acid probe methods

International Nuclear Information System (INIS)

Ellner, P.D.; Kiehn, T.E.; Cammarata, R.; Hosmer, M.

1988-01-01

The combination of radiometric methodology (BACTEC 12B) and probe technology for recovery and identification of mycobacteria was studied in two large hospital laboratories. The sediment from vials with positive growth indices was tested with DNA probes specific for Mycobacterium tuberculosis, Mycobacterium avium, and Mycobacterium intracellulare. The sensitivity of the radiometric method and the specificity of the probes resulted in a marked reduction in the time to the final report. Biochemical testing could be eliminated on isolates giving a positive reaction with one of the probes. Some 176 isolates of M. tuberculosis, 110 of M. avium, and 5 of M. intracellulare were recovered. Two-thirds of these isolates were detected and identified within 2 weeks of inoculation and the remainder was detected by 4 weeks, a reduction of 5 to 7 weeks to the final report

Rapid identification of Enterobacter hormaechei and Enterobacter cloacae genetic cluster III.

Science.gov (United States)

Ohad, S; Block, C; Kravitz, V; Farber, A; Pilo, S; Breuer, R; Rorman, E

2014-05-01

Enterobacter cloacae complex bacteria are of both clinical and environmental importance. Phenotypic methods are unable to distinguish between some of the species in this complex, which often renders their identification incomplete. The goal of this study was to develop molecular assays to identify Enterobacter hormaechei and Ent. cloacae genetic cluster III which are relatively frequently encountered in clinical material. The molecular assays developed in this study are qPCR technology based and served to identify both Ent. hormaechei and Ent. cloacae genetic cluster III. qPCR results were compared to hsp60 sequence analysis. Most clinical isolates were assigned to Ent. hormaechei subsp. steigerwaltii and Ent. cloacae genetic cluster III. The latter was proportionately more frequently isolated from bloodstream infections than from other material (P < 0·05). The qPCR assays detecting Ent. hormaechei and Ent. cloacae genetic cluster III demonstrated high sensitivity and specificity. The presented qPCR assays allow accurate and rapid identification of clinical isolates of the Ent. cloacae complex. The improved identifications obtained can specifically assist analysis of Ent. hormaechei and Ent. cloacae genetic cluster III in nosocomial outbreaks and can promote rapid environmental monitoring. An association was observed between Ent. cloacae cluster III and systemic infection that deserves further attention. © 2014 The Society for Applied Microbiology.

Multilevel Thresholding Method Based on Electromagnetism for Accurate Brain MRI Segmentation to Detect White Matter, Gray Matter, and CSF

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G. Sandhya

2017-01-01

Full Text Available This work explains an advanced and accurate brain MRI segmentation method. MR brain image segmentation is to know the anatomical structure, to identify the abnormalities, and to detect various tissues which help in treatment planning prior to radiation therapy. This proposed technique is a Multilevel Thresholding (MT method based on the phenomenon of Electromagnetism and it segments the image into three tissues such as White Matter (WM, Gray Matter (GM, and CSF. The approach incorporates skull stripping and filtering using anisotropic diffusion filter in the preprocessing stage. This thresholding method uses the force of attraction-repulsion between the charged particles to increase the population. It is the combination of Electromagnetism-Like optimization algorithm with the Otsu and Kapur objective functions. The results obtained by using the proposed method are compared with the ground-truth images and have given best values for the measures sensitivity, specificity, and segmentation accuracy. The results using 10 MR brain images proved that the proposed method has accurately segmented the three brain tissues compared to the existing segmentation methods such as K-means, fuzzy C-means, OTSU MT, Particle Swarm Optimization (PSO, Bacterial Foraging Algorithm (BFA, Genetic Algorithm (GA, and Fuzzy Local Gaussian Mixture Model (FLGMM.

The Performance of the Four Anaerobic Blood Culture Bottles BacT/ALERT-FN, -FN Plus, BACTEC-Plus and -Lytic in Detection of Anaerobic Bacteria and Identification by Direct MALDI-TOF MS.

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Almuhayawi, Mohammed; Altun, Osman; Abdulmajeed, Adam Dilshad; Ullberg, Måns; Özenci, Volkan

2015-01-01

Detection and identification of anaerobic bacteria in blood cultures (BC) is a well-recognized challenge in clinical microbiology. We studied 100 clinical anaerobic BC isolates to evaluate the performance of BacT/ALERT-FN, -FN Plus (BioMérieux), BACTEC-Plus and -Lytic (Becton Dickinson BioSciences) BC bottles in detection and time to detection (TTD) of anaerobic bacteria. BACTEC Lytic had higher detection rate (94/100, 94%) than BacT/ALERT FN Plus (80/100, 80%) (panaerobic bacteria among the remaining bottle types. The 67 anaerobic bacteria that signalled positive in all four bottle types were analyzed to compare the time to detection (TTD) and isolates were directly identified by MALDI-TOF MS. There was a significant difference in TTD among the four bottle types (panaerobic BC bottles are equally suitable for direct MALDI-TOF MS for rapid and reliable identification of common anaerobic bacteria. Further clinical studies are warranted to investigate the performance of anaerobic BC bottles in detection of anaerobic bacteria and identification by direct MALDI-TOF MS.

Space-time clusters for early detection of grizzly bear predation.

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Kermish-Wells, Joseph; Massolo, Alessandro; Stenhouse, Gordon B; Larsen, Terrence A; Musiani, Marco

2018-01-01

Accurate detection and classification of predation events is important to determine predation and consumption rates by predators. However, obtaining this information for large predators is constrained by the speed at which carcasses disappear and the cost of field data collection. To accurately detect predation events, researchers have used GPS collar technology combined with targeted site visits. However, kill sites are often investigated well after the predation event due to limited data retrieval options on GPS collars (VHF or UHF downloading) and to ensure crew safety when working with large predators. This can lead to missing information from small-prey (including young ungulates) kill sites due to scavenging and general site deterioration (e.g., vegetation growth). We used a space-time permutation scan statistic (STPSS) clustering method (SaTScan) to detect predation events of grizzly bears ( Ursus arctos ) fitted with satellite transmitting GPS collars. We used generalized linear mixed models to verify predation events and the size of carcasses using spatiotemporal characteristics as predictors. STPSS uses a probability model to compare expected cluster size (space and time) with the observed size. We applied this method retrospectively to data from 2006 to 2007 to compare our method to random GPS site selection. In 2013-2014, we applied our detection method to visit sites one week after their occupation. Both datasets were collected in the same study area. Our approach detected 23 of 27 predation sites verified by visiting 464 random grizzly bear locations in 2006-2007, 187 of which were within space-time clusters and 277 outside. Predation site detection increased by 2.75 times (54 predation events of 335 visited clusters) using 2013-2014 data. Our GLMMs showed that cluster size and duration predicted predation events and carcass size with high sensitivity (0.72 and 0.94, respectively). Coupling GPS satellite technology with clusters using a program based

SPERM HY-LITER™ for the identification of spermatozoa from sexual assault evidence

DEFF Research Database (Denmark)

Westring, Christian Gustav; Wiuf, Morten; Nielsen, S Jock

2014-01-01

Accurate microscopic identification of human spermatozoa is important in sexual assault cases. We have compared the results of examinations with (1) a fluorescent microscopy method, SPERM HY-LITER™, and (2) Baecchi's method for identification of human spermatozoa. In 35 artificial, forensic type...

Evaluation of amplified rDNA restriction analysis (ARDRA for the identification of cultured mycobacteria in a diagnostic laboratory

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Rottiers Sylvianne

2002-03-01

Full Text Available Abstract Background The development of DNA amplification for the direct detection of M. tuberculosis from clinical samples has been a major goal of clinical microbiology during the last ten years. However, the limited sensitivity of most DNA amplification techniques restricts their use to smear positive samples. On the other hand, the development of automated liquid culture has increased the speed and sensitivity of cultivation of mycobacteria. We have opted to combine automated culture with rapid genotypic identification (ARDRA: amplified rDNA restriction analysis for the detection resp. identification of all mycobacterial species at once, instead of attempting direct PCR based detection from clinical samples of M. tuberculosis only. Results During 1998–2000 a total of approx. 3500 clinical samples was screened for the presence of M. tuberculosis. Of the 151 culture positive samples, 61 were M. tuberculosis culture positive. Of the 30 smear positive samples, 26 were M. tuberculosis positive. All but three of these 151 mycobacterial isolates could be identified with ARDRA within on average 36 hours. The three isolates that could not be identified belonged to rare species not yet included in our ARDRA fingerprint library or were isolates with an aberrant pattern. Conclusions In our hands, automated culture in combination with ARDRA provides with accurate, practically applicable, wide range identification of mycobacterial species. The existing identification library covers most species, and can be easily updated when new species are studied or described. The drawback is that ARDRA is culture-dependent, since automated culture of M. tuberculosis takes on average 16.7 days (range 6 to 29 days. However, culture is needed after all to assess the antibiotic susceptibility of the strains.

Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively.

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Shimamoto, Shoichi; Waldman, Zachary J; Orosz, Iren; Song, Inkyung; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard; Sharan, Ashwini; Wu, Chengyuan; Sperling, Michael R; Weiss, Shennan A

2018-01-01

To develop and validate a detector that identifies ripple (80-200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). iEEG recordings from 16 patients were first band-pass filtered (80-600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of

Compression ultrasonography of the lower extremity with portable vascular ultrasonography can accurately detect deep venous thrombosis in the emergency department.

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Crisp, Jonathan G; Lovato, Luis M; Jang, Timothy B

2010-12-01

Compression ultrasonography of the lower extremity is an established method of detecting proximal lower extremity deep venous thrombosis when performed by a certified operator in a vascular laboratory. Our objective is to determine the sensitivity and specificity of bedside 2-point compression ultrasonography performed in the emergency department (ED) with portable vascular ultrasonography for the detection of proximal lower extremity deep venous thrombosis. We did this by directly comparing emergency physician-performed ultrasonography to lower extremity duplex ultrasonography performed by the Department of Radiology. This was a prospective, cross-sectional study and diagnostic test assessment of a convenience sample of ED patients with a suspected lower extremity deep venous thrombosis, conducted at a single-center, urban, academic ED. All physicians had a 10-minute training session before enrolling patients. ED compression ultrasonography occurred before Department of Radiology ultrasonography and involved identification of 2 specific points: the common femoral and popliteal vessels, with subsequent compression of the common femoral and popliteal veins. The study result was considered positive for proximal lower extremity deep venous thrombosis if either vein was incompressible or a thrombus was visualized. Sensitivity and specificity were calculated with the final radiologist interpretation of the Department of Radiology ultrasonography as the criterion standard. A total of 47 physicians performed 199 2-point compression ultrasonographic examinations in the ED. Median number of examinations per physician was 2 (range 1 to 29 examinations; interquartile range 1 to 5 examinations). There were 45 proximal lower extremity deep venous thromboses observed on Department of Radiology evaluation, all correctly identified by ED 2-point compression ultrasonography. The 153 patients without proximal lower extremity deep venous thrombosis all had a negative ED compression

CYP450 phenotyping and accurate mass identification of metabolites of the 8-aminoquinoline, anti-malarial drug primaquine

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Pybus Brandon S

2012-08-01

Full Text Available Abstract Background The 8-aminoquinoline (8AQ drug primaquine (PQ is currently the only approved drug effective against the persistent liver stage of the hypnozoite forming strains Plasmodium vivax and Plasmodium ovale as well as Stage V gametocytes of Plasmodium falciparum. To date, several groups have investigated the toxicity observed in the 8AQ class, however, exact mechanisms and/or metabolic species responsible for PQ’s haemotoxic and anti-malarial properties are not fully understood. Methods In the present study, the metabolism of PQ was evaluated using in vitro recombinant metabolic enzymes from the cytochrome P450 (CYP and mono-amine oxidase (MAO families. Based on this information, metabolite identification experiments were performed using nominal and accurate mass measurements. Results Relative activity factor (RAF-weighted intrinsic clearance values show the relative role of each enzyme to be MAO-A, 2C19, 3A4, and 2D6, with 76.1, 17.0, 5.2, and 1.7% contributions to PQ metabolism, respectively. CYP 2D6 was shown to produce at least six different oxidative metabolites along with demethylations, while MAO-A products derived from the PQ aldehyde, a pre-cursor to carboxy PQ. CYPs 2C19 and 3A4 produced only trace levels of hydroxylated species. Conclusions As a result of this work, CYP 2D6 and MAO-A have been implicated as the key enzymes associated with PQ metabolism, and metabolites previously identified as potentially playing a role in efficacy and haemolytic toxicity have been attributed to production via CYP 2D6 mediated pathways.

Wide-scope analysis of pesticide and veterinary drug residues in meat matrices by high resolution MS: detection and identification using Exactive-Orbitrap.

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Gómez-Pérez, María Luz; Romero-González, Roberto; Plaza-Bolaños, Patricia; Génin, Eric; Martínez Vidal, José Luis; Garrido Frenich, Antonia

2014-01-01

A multiresidue and multiclass method for the simultaneous determination of more than 350 compounds including pesticides, biopesticides and veterinary drugs in different meat matrices (beef, pork and chicken) by ultra-high performance liquid chromatography coupled to Orbitrap MS has been developed. In the present study, the determination of fragments was accomplished as an essential tool for a reliable identification of compounds using high resolution MS. To obtain these fragments, different strategies have been carried out in order to ensure an appropriate fragment assignment and identification. The analytical method is suitable for qualitative analysis, and it was also evaluated for quantitative analysis. Generic extraction conditions were optimized, obtaining adequate recovery and precision values for most of the studied analytes (>290). The limits of detection ranged from 2 to 16 µg kg(-1). Limits of quantification were 10 µg kg(-1) with the exception of few compounds with a higher value (50 or 100 µg kg(-1)). Limits of identification were also established, and they ranged from 2 to 150 µg kg(-1). This method was applied to the analysis of 18 meat samples and some veterinary drugs as enrofloxacin and sulfadiazine were detected and further identified/quantified (with triple quadrupole) in two different samples at 33 µg kg(-1) and trace levels, respectively. No pesticides were detected in the analyzed samples. Copyright © 2014 John Wiley & Sons, Ltd.

Multiplex hydrolysis probe real-time PCR for simultaneous detection of hepatitis A virus and hepatitis E virus.

Science.gov (United States)

Qiu, Feng; Cao, Jingyuan; Su, Qiudong; Yi, Yao; Bi, Shengli

2014-05-30

Detection of hepatitis viral infections has traditionally relied on the circulating antibody test using the enzyme-linked immunosorbent assay. However, multiplex real-time PCR has been increasingly used for a variety of viral nucleic acid detections and has proven to be superior to traditional methods. Hepatitis A virus (HAV) and hepatitis E virus (HEV) are the major causes of acute hepatitis worldwide; both HAV and HEV infection are a main public health problem. In the present study, a one-step multiplex reverse transcriptase quantitative polymerase chain reaction assay using hydrolysis probes was developed for simultaneously detecting HAV and HEV. This novel detection system proved specific to the target viruses, to be highly sensitive and to be applicable to clinical sera samples, making it useful for rapid, accurate and feasible identification of HAV and HEV.

Generic detection and identification of pospiviroids.

Science.gov (United States)

Olivier, Thibaut; Demonty, Elisabeth; Fauche, Frédéric; Steyer, Stéphan

2014-08-01

A multiplex one-step RT-PCR aiming at detecting all pospiviroids known to be harmful to cultivated plants has been developed. Specificity, sensitivity, selectivity, repeatability and reproducibility of this test have been assessed in order to fulfill the recommendations of the EPPO standard PM7/98 and provide routine detection laboratories with a cost-effective, easy-to-use and robust pospiviroid detection test. To further understand the epidemiology and ease the management of pospiviroid outbreaks, this RT-PCR diagnostic test can be followed by direct sequencing of the amplicons to identify and characterize the detected pospiviroid isolates.

TALENT IDENTIFICATION IN FOOTBALL

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Bojan Rakojević

2008-08-01

Full Text Available There is incerasing emphasis on clubs to detect players and nurture and guide them throught the talent identification proces. More over, different factors may contribute to performance prediction at different ages. Thus any such model would need to be agespecific (Reilly et al, 2000. The aim of this paper was to determine essential principles of proces talent identification and determine antropometric, physiological and psychological profile and football-specifc skills that could be used for talent identification in players aged 10-12 years.

Detection of undeclared animal by-products in commercial canine canned foods: Comparative analyses by ELISA and PCR-RFLP coupled with slab gel electrophoresis or capillary gel electrophoresis.

Science.gov (United States)

Hsieh, Ming-Kun; Shih, Pei-Yin; Wei, Chia-Fong; Vickroy, Thomas W; Chou, Chi-Chung

2016-03-30

The potential presence of undeclared animal by-products in pet foods is not subject to routine examination. Previously published methods for species-based identification of animal by-products have not been used routinely owing to inconsistent results. The present study evaluated the utility of several approaches for accurate identification of animal by-products in 11 commercial brands of canine canned foods. Canine canned foods from several countries were analysed by ELISA, PCR-RFLP coupled with slab-gel electrophoresis (SGE) and capillary gel electrophoresis (CGE) to test for evidence of by-products derived from cattle, chicken, sheep or pig. While CGE-based analysis detected all (24) animal-derived by-products that were reported for the 11 test samples, SGE and ELISA detected only 22/24 (92%) and 14/24 (58%) of labelled by-products, respectively. In addition, undeclared animal by-products were found using all three analytical approaches with CGE detecting more positives (19) than SGE (17) or ELISA (5). Significant disparities were evident between the labelled contents and the detected content of animal by-products. CGE-based testing for PCR products appears to provide greater sensitivity and accuracy than either SGE or ELISA-based methods. As testing of commercial products becomes more reliable and mainstream, manufacturers will need to develop more thorough and accurate labelling protocols. © 2015 Society of Chemical Industry.

Detection and identification of dyes in blue writing inks by LC-DAD-orbitrap MS.

Science.gov (United States)

Sun, Qiran; Luo, Yiwen; Yang, Xu; Xiang, Ping; Shen, Min

2016-04-01

In the field of forensic questioned document examination, to identify dyes detected in inks not only provides a solid foundation for ink discrimination in forged contents identification, but also facilitates the investigation of ink origin or the study regarding ink dating. To detect and identify potential acid and basic dyes in blue writing inks, a liquid chromatography-diode array detection-Orbitrap mass spectrometry (LC-DAD-Orbitrap MS) method was established. Three sulfonic acid dyes (Acid blue 1, Acid blue 9 and Acid red 52) and six triphenylmethane basic dyes (Ethyl violet, Crystal violet, Methyl violet 2B, Basic blue 7, Victoria blue B and Victoria blue R) were employed as reference dyes for method development. Determination of the nine dyes was validated to evaluate the instrument performance, and it turned out to be sensitive and stable enough for quantification. The method was then applied in the screening analysis of ten blue roller ball pen inks and twenty blue ballpoint pen inks. As a result, including TPR (a de-methylated product of Crystal violet), ten known dyes and four unknown dyes were detected in the inks. The latter were further identified as a de-methylated product of Victoria blue B, Acid blue 104, Acid violet 49 and Acid blue 90, through analyzing their characteristic precursor and product ions acquired by Orbitrap MS with good mass accuracy. The results showed that the established method is capable of detecting and identifying potential dyes in blue writing inks. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

COMPARATIVE ANALYSIS OF METHODS FOR IDENTIFICATION OF NONTUBERCULOUS MYCOBACTERIA ISOLATED FROM CLINICAL MATERIAL

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A. V. Lyamin

2017-01-01

Full Text Available Recently there has been a significant increase in the incidence of mycobacteriosis, which is due to an increase in the proportion of immunosuppressed patients, the presence of these various comorbid conditions, as well as the improvement of diagnostic methods. Selecting the most accurate method of identification is extremely important in determining treatment strategy of patients. The aim of the study was to conduct a comparative analysis of modern methods of identification NTMB isolated from clinical specimens in 2015 in the Samara region. The work was carried out identification of 78 strains of microorganisms. Laboratory diagnosis was carried out using the DNA hybridization method and MALDI-ToF mass spectrometry. When microbial identification using MALDI-ToF mass spectrometry was isolated 16 strains (20.5% M. kansasii; 11 strains (14.1% M. avium and M. fortuitum; 9 strains (11.5% M. gordonae; strain 3 (3.8% M. peregrinum, M. szulgai, M. chimera intracellulare group, strain 2 (2.6% M. abscessus, M. septicum, M. paragordonae, M. senegalence, 1 strain (1.3% M. chelonae, M. frederiksbergense, M. monacense, M. lentiflavum. By using mass spectrometry, it was identified 15 types NTMB compared with 9 types — by DNA hybridization. Full match identification results was observed only in 45 (57.7% strains of divergent strains were found in 16 (20.5%. Most often when using the DNA hybridization method, discrepancy was detected in slow-growing cultures (9 strains with a predominance of microorganisms identified as M. gordonae. Among the representatives of fast-growing NTMB, seven investigations were identified in the identification, more often among representatives of the M. fortuitum and M. peregrinum groups. Particular attention should be paid to the identification of the M. kansasii strain by a molecular genetic method, which mass spectrometry was defined as M. bovis. Both cultures of M. tuberculosis complex, which were identified by MALDI

Extra pulmonary tuberculosis: Rapid identification of Mycobacterium tuberculosis grown in Mycobacterium growth indicator tube 960 and Lowenstein-Jensen media, employing Standard diagnostics Bioline Mycobacterium tuberculosis protein 64 antigen detection kit

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G Kandhakumari

2015-01-01

Full Text Available Background: Investigation of extra pulmonary tuberculosis (EPTB in and around Pondicherry is being carried out since August 2011 in our tertiary care super specialty hospital. Objectives: To compare the rapid Kit SD Bio-Line MPT 64 Ag with conventional and time consuming biochemical tests. Confirmation of Mycobacterium tuberculosis at a reasonable time frame is the main thrust. Materials and Methods: Thirty three Mycobacterium tuberculosis and four Non-Tuberculous Mycobacteria (NTM grown in MGIT960 system/Lowenstein-Jensen media (LJ were examined by the rapid MPT 64 antigen detection as well as a battery of conventional tests like niacin, nitrate reduction, paraminobenzoic acid susceptibility and cord formation. Results and Conclusion: . Both the rapid kit and conventional tests correctly identified 33 M.tuberculosis isolates. Keeping conventional identification as reference, sensitivity and specificity for rapid kit was 100%. Rapid kit which takes only 15 minutes is accurate, cost effective, and facilitates early treatment for these EPTB patients, whose clinical specimens are paucibacillary.

Probabilistic structural damage identification based on vibration data

International Nuclear Information System (INIS)

Hao, H.; Xia, Y.

2001-01-01

Vibration-based methods are being rapidly developed and applied to detect structural damage in civil, mechanical and aerospace engineering communities in the last two decades. But uncertainties existing in the structural model and measured vibration data might lead to unreliable results. This paper will present some recent research results to tackle the above mentioned uncertainty problems. By assuming each of the FE model parameters and measured vibration data as a normally distributed random variable, a probabilistic damage detection procedure is developed based on perturbation method and validated by Monte Carlo simulation technique. With this technique, the damage probability of each structural element can be determined. The method developed has been verified by applying it to identify the damages of laboratory tested structures. It was proven that, as compared to the deterministic damage identification method, the present method can not only reduce the possibility of false identification, but also give the identification results in terms of probability. which is deemed more realistic and practical in detecting possible damages in a structure. It has also been found that the modal data included in damage identification analysis have a great influence on the identification results. With a sensitivity study, an optimal measurement set for damage detection is determined. This set includes the optimal measurement locations and the most appropriate modes that should be used in the damage identification analysis. Numerical results indicated that if the optimal set determined in a pre-analysis is used in the damage detection better results will be achieved. (author)

An Accurate Framework for Arbitrary View Pedestrian Detection in Images

Science.gov (United States)

Fan, Y.; Wen, G.; Qiu, S.

2018-01-01

We consider the problem of detect pedestrian under from images collected under various viewpoints. This paper utilizes a novel framework called locality-constrained affine subspace coding (LASC). Firstly, the positive training samples are clustered into similar entities which represent similar viewpoint. Then Principal Component Analysis (PCA) is used to obtain the shared feature of each viewpoint. Finally, the samples that can be reconstructed by linear approximation using their top- k nearest shared feature with a small error are regarded as a correct detection. No negative samples are required for our method. Histograms of orientated gradient (HOG) features are used as the feature descriptors, and the sliding window scheme is adopted to detect humans in images. The proposed method exploits the sparse property of intrinsic information and the correlations among the multiple-views samples. Experimental results on the INRIA and SDL human datasets show that the proposed method achieves a higher performance than the state-of-the-art methods in form of effect and efficiency.

Detection of Dendritic Spines Using Wavelet-Based Conditional Symmetric Analysis and Regularized Morphological Shared-Weight Neural Networks

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Shuihua Wang

2015-01-01

Full Text Available Identification and detection of dendritic spines in neuron images are of high interest in diagnosis and treatment of neurological and psychiatric disorders (e.g., Alzheimer’s disease, Parkinson’s diseases, and autism. In this paper, we have proposed a novel automatic approach using wavelet-based conditional symmetric analysis and regularized morphological shared-weight neural networks (RMSNN for dendritic spine identification involving the following steps: backbone extraction, localization of dendritic spines, and classification. First, a new algorithm based on wavelet transform and conditional symmetric analysis has been developed to extract backbone and locate the dendrite boundary. Then, the RMSNN has been proposed to classify the spines into three predefined categories (mushroom, thin, and stubby. We have compared our proposed approach against the existing methods. The experimental result demonstrates that the proposed approach can accurately locate the dendrite and accurately classify the spines into three categories with the accuracy of 99.1% for “mushroom” spines, 97.6% for “stubby” spines, and 98.6% for “thin” spines.

Soft Biometrics; Human Identification Using Comparative Descriptions.

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Reid, Daniel A; Nixon, Mark S; Stevenage, Sarah V

2014-06-01

Soft biometrics are a new form of biometric identification which use physical or behavioral traits that can be naturally described by humans. Unlike other biometric approaches, this allows identification based solely on verbal descriptions, bridging the semantic gap between biometrics and human description. To permit soft biometric identification the description must be accurate, yet conventional human descriptions comprising of absolute labels and estimations are often unreliable. A novel method of obtaining human descriptions will be introduced which utilizes comparative categorical labels to describe differences between subjects. This innovative approach has been shown to address many problems associated with absolute categorical labels-most critically, the descriptions contain more objective information and have increased discriminatory capabilities. Relative measurements of the subjects' traits can be inferred from comparative human descriptions using the Elo rating system. The resulting soft biometric signatures have been demonstrated to be robust and allow accurate recognition of subjects. Relative measurements can also be obtained from other forms of human representation. This is demonstrated using a support vector machine to determine relative measurements from gait biometric signatures-allowing retrieval of subjects from video footage by using human comparisons, bridging the semantic gap.

Accurate location estimation of moving object In Wireless Sensor network

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Vinay Bhaskar Semwal

2011-12-01

Full Text Available One of the central issues in wirless sensor networks is track the location, of moving object which have overhead of saving data, an accurate estimation of the target location of object with energy constraint .We do not have any mechanism which control and maintain data .The wireless communication bandwidth is also very limited. Some field which is using this technique are flood and typhoon detection, forest fire detection, temperature and humidity and ones we have these information use these information back to a central air conditioning and ventilation.In this research paper, we propose protocol based on the prediction and adaptive based algorithm which is using less sensor node reduced by an accurate estimation of the target location. We had shown that our tracking method performs well in terms of energy saving regardless of mobility pattern of the mobile target. We extends the life time of network with less sensor node. Once a new object is detected, a mobile agent will be initiated to track the roaming path of the object.

Pyrosequencing as a tool for the detection of Phytophthora species: error rate and risk of false Molecular Operational Taxonomic Units.

Science.gov (United States)

Vettraino, A M; Bonants, P; Tomassini, A; Bruni, N; Vannini, A

2012-11-01

To evaluate the accuracy of pyrosequencing for the description of Phytophthora communities in terms of taxa identification and risk of assignment for false Molecular Operational Taxonomic Units (MOTUs). Pyrosequencing of Internal Transcribed Spacer 1 (ITS1) amplicons was used to describe the structure of a DNA mixture comprising eight Phytophthora spp. and Pythium vexans. Pyrosequencing resulted in 16 965 reads, detecting all species in the template DNA mixture. Reducing the ITS1 sequence identity threshold resulted in a decrease in numbers of unmatched reads but a concomitant increase in the numbers of false MOTUs. The total error rate was 0·63% and comprised mainly mismatches (0·25%) Pyrosequencing of ITS1 region is an efficient and accurate technique for the detection and identification of Phytophthora spp. in environmental samples. However, the risk of allocating false MOTUs, even when demonstrated to be low, may require additional validation with alternative detection methods. Phytophthora spp. are considered among the most destructive groups of invasive plant pathogens, affecting thousands of cultivated and wild plants worldwide. Simultaneous early detection of Phytophthora complexes in environmental samples offers an unique opportunity for the interception of known and unknown species along pathways of introduction, along with the identification of these organisms in invaded environments. © 2012 The Authors Letters in Applied Microbiology © 2012 The Society for Applied Microbiology.

Real-time contaminant detection and classification in a drinking water pipe using conventional water quality sensors: techniques and experimental results.

Science.gov (United States)

Jeffrey Yang, Y; Haught, Roy C; Goodrich, James A

2009-06-01

Accurate detection and identification of natural or intentional contamination events in a drinking water pipe is critical to drinking water supply security and health risk management. To use conventional water quality sensors for the purpose, we have explored a real-time event adaptive detection, identification and warning (READiw) methodology and examined it using pilot-scale pipe flow experiments of 11 chemical and biological contaminants each at three concentration levels. The tested contaminants include pesticide and herbicides (aldicarb, glyphosate and dicamba), alkaloids (nicotine and colchicine), E. coli in terrific broth, biological growth media (nutrient broth, terrific broth, tryptic soy broth), and inorganic chemical compounds (mercuric chloride and potassium ferricyanide). First, through adaptive transformation of the sensor outputs, contaminant signals were enhanced and background noise was reduced in time-series plots leading to detection and identification of all simulated contamination events. The improved sensor detection threshold was 0.1% of the background for pH and oxidation-reduction potential (ORP), 0.9% for free chlorine, 1.6% for total chlorine, and 0.9% for chloride. Second, the relative changes calculated from adaptively transformed residual chlorine measurements were quantitatively related to contaminant-chlorine reactivity in drinking water. We have shown that based on these kinetic and chemical differences, the tested contaminants were distinguishable in forensic discrimination diagrams made of adaptively transformed sensor measurements.

Detection and identification of bacteria in a juice matrix with Fourier transform-near infrared spectroscopy and multivariiate analysis.

Science.gov (United States)

Rodriguez-Saona, L E; Khambaty, F M; Fry, F S; Dubois, J; Calvey, E M

2004-11-01

The use of Fourier transform-near infrared (FT-NIR) spectroscopy combined with multivariate pattern recognition techniques was evaluated to address the need for a fast and senisitive method for the detection of bacterial contamination in liquids. The complex cellular composition of bacteria produces FT-NIR vibrational transitions (overtone and combination bands), forming the basis for identification and subtyping. A database including strains of Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, Bacillus cereus, and Bacillus thuringiensis was built, with special care taken to optimize sample preparation. The bacterial cells were treated with 70% (vol/vol) ethanolto enhance safe handling of pathogenic strains and then concentrated on an aluminum oxide membrane to obtain a thin bacterial film. This simple membrane filtration procedure generated reproducible FT-NIR spectra that allowed for the rapid discrimination among closely related strains. Principal component analysis and soft independent modeling of class analogy of transformed spectra in the region 5,100 to 4,400 cm(-1) were able to discriminate between bacterial species. Spectroscopic analysis of apple juices inoculated with different strains of E. coli at approximately 10(5) CFU/ml showed that FT-NIR spectralfeatures are consistent with bacterial contamination and soft independent modeling of class analogy correctly predicted the identity of the contaminant as strains of E. coli. FT-NIR in conjunction with multivariate techniques can be used for the rapid and accurate evaluation of potential bacterial contamination in liquids with minimal sample manipulation, and hence limited exposure of the laboratory worker to the agents.

Accurate Sybil Attack Detection Based on Fine-Grained Physical Channel Information

Directory of Open Access Journals (Sweden)

Chundong Wang

2018-03-01

Full Text Available With the development of the Internet-of-Things (IoT, wireless network security has more and more attention paid to it. The Sybil attack is one of the famous wireless attacks that can forge wireless devices to steal information from clients. These forged devices may constantly attack target access points to crush the wireless network. In this paper, we propose a novel Sybil attack detection based on Channel State Information (CSI. This detection algorithm can tell whether the static devices are Sybil attackers by combining a self-adaptive multiple signal classification algorithm with the Received Signal Strength Indicator (RSSI. Moreover, we develop a novel tracing scheme to cluster the channel characteristics of mobile devices and detect dynamic attackers that change their channel characteristics in an error area. Finally, we experiment on mobile and commercial WiFi devices. Our algorithm can effectively distinguish the Sybil devices. The experimental results show that our Sybil attack detection system achieves high accuracy for both static and dynamic scenarios. Therefore, combining the phase and similarity of channel features, the multi-dimensional analysis of CSI can effectively detect Sybil nodes and improve the security of wireless networks.

Accurate Sybil Attack Detection Based on Fine-Grained Physical Channel Information.

Science.gov (United States)

Wang, Chundong; Zhu, Likun; Gong, Liangyi; Zhao, Zhentang; Yang, Lei; Liu, Zheli; Cheng, Xiaochun

2018-03-15

With the development of the Internet-of-Things (IoT), wireless network security has more and more attention paid to it. The Sybil attack is one of the famous wireless attacks that can forge wireless devices to steal information from clients. These forged devices may constantly attack target access points to crush the wireless network. In this paper, we propose a novel Sybil attack detection based on Channel State Information (CSI). This detection algorithm can tell whether the static devices are Sybil attackers by combining a self-adaptive multiple signal classification algorithm with the Received Signal Strength Indicator (RSSI). Moreover, we develop a novel tracing scheme to cluster the channel characteristics of mobile devices and detect dynamic attackers that change their channel characteristics in an error area. Finally, we experiment on mobile and commercial WiFi devices. Our algorithm can effectively distinguish the Sybil devices. The experimental results show that our Sybil attack detection system achieves high accuracy for both static and dynamic scenarios. Therefore, combining the phase and similarity of channel features, the multi-dimensional analysis of CSI can effectively detect Sybil nodes and improve the security of wireless networks.

Facial expressions of emotion (KDEF): identification under different display-duration conditions.

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Calvo, Manuel G; Lundqvist, Daniel

2008-02-01

Participants judged which of seven facial expressions (neutrality, happiness, anger, sadness, surprise, fear, and disgust) were displayed by a set of 280 faces corresponding to 20 female and 20 male models of the Karolinska Directed Emotional Faces database (Lundqvist, Flykt, & Ohman, 1998). Each face was presented under free-viewing conditions (to 63 participants) and also for 25, 50, 100, 250, and 500 msec (to 160 participants), to examine identification thresholds. Measures of identification accuracy, types of errors, and reaction times were obtained for each expression. In general, happy faces were identified more accurately, earlier, and faster than other faces, whereas judgments of fearful faces were the least accurate, the latest, and the slowest. Norms for each face and expression regarding level of identification accuracy, errors, and reaction times may be downloaded from www.psychonomic.org/archive/.

Integrating early detection with DNA barcoding: species identification of a non-native monitor lizard (Squamata: Varanidae) carcass in Mississippi, U.S.A.

Science.gov (United States)

Reed, Robert N.; Hopken, Matthew W.; Steen, David A.; Falk, Bryan G.; Piaggio, Antoinette J.

2016-01-01

Early detection of invasive species is critical to increasing the probability of successful management. At the primary stage of an invasion, invasive species are easier to control as the population is likely represented by just a few individuals. Detection of these first few individuals can be challenging, particularly if they are cryptic or otherwise characterized by low detectability. The engagement of members of the public may be critical to early detection as there are far more citizen s on the landscape than trained biologists. However, it can be difficult to assess the credibility of public reporting, especially when a diagnostic digital image or a physical specimen in good condition are lacking. DNA barcoding can be used for verification when morphological identification of a specimen is not possible or uncertain (i.e., degraded or partial specimen). DNA barcoding relies on obtaining a DNA sequence from a relatively small fragment of mitochondrial DNA and comparing it to a database of sequences containing a variety of expertly identified species. He rein we report the successful identification of a degraded specimen of a non-native, potentially invasive reptile species (Varanus niloticus) via DNA barcoding, after discovery and reporting by a member of the public.

Accurate RNA consensus sequencing for high-fidelity detection of transcriptional mutagenesis-induced epimutations.

Science.gov (United States)

Reid-Bayliss, Kate S; Loeb, Lawrence A

2017-08-29

Transcriptional mutagenesis (TM) due to misincorporation during RNA transcription can result in mutant RNAs, or epimutations, that generate proteins with altered properties. TM has long been hypothesized to play a role in aging, cancer, and viral and bacterial evolution. However, inadequate methodologies have limited progress in elucidating a causal association. We present a high-throughput, highly accurate RNA sequencing method to measure epimutations with single-molecule sensitivity. Accurate RNA consensus sequencing (ARC-seq) uniquely combines RNA barcoding and generation of multiple cDNA copies per RNA molecule to eliminate errors introduced during cDNA synthesis, PCR, and sequencing. The stringency of ARC-seq can be scaled to accommodate the quality of input RNAs. We apply ARC-seq to directly assess transcriptome-wide epimutations resulting from RNA polymerase mutants and oxidative stress.

Supporting child witnesses during identification lineups: Exploring the effectiveness of registered intermediaries.

Science.gov (United States)

Wilcock, Rachel; Crane, Laura; Hobson, Zoe; Nash, Gilly; Kirke-Smith, Mimi; Henry, Lucy A

2018-01-01

Performance at identification lineup was assessed in eighty-five 6- to 11-year-old typically developing children. Children viewed a live staged event involving 2 male actors, and were asked to identify the perpetrators from 2 separate lineups (one perpetrator-present lineup and one perpetrator-absent lineup). Half the children took part in lineups adapted by a registered intermediary (an impartial, trained professional who facilitates understanding and communication between vulnerable witnesses and members of the justice system), and half took part in "best-practice" lineups, according to the current guidance for eyewitness identification in England and Wales. Children receiving assistance from a registered intermediary (relative to children who received best-practice lineups) were more accurate in their identifications for perpetrator-present lineups, and there was some evidence that they were also more accurate for perpetrator-absent lineups. This provides the first empirical evidence for the effectiveness of registered intermediary support during identification lineups.

DB2: a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads.

Science.gov (United States)

Yavaş, Gökhan; Koyutürk, Mehmet; Gould, Meetha P; McMahon, Sarah; LaFramboise, Thomas

2014-03-05

With the advent of paired-end high throughput sequencing, it is now possible to identify various types of structural variation on a genome-wide scale. Although many methods have been proposed for structural variation detection, most do not provide precise boundaries for identified variants. In this paper, we propose a new method, Distribution Based detection of Duplication Boundaries (DB2), for accurate detection of tandem duplication breakpoints, an important class of structural variation, with high precision and recall. Our computational experiments on simulated data show that DB2 outperforms state-of-the-art methods in terms of finding breakpoints of tandem duplications, with a higher positive predictive value (precision) in calling the duplications' presence. In particular, DB2's prediction of tandem duplications is correct 99% of the time even for very noisy data, while narrowing down the space of possible breakpoints within a margin of 15 to 20 bps on the average. Most of the existing methods provide boundaries in ranges that extend to hundreds of bases with lower precision values. Our method is also highly robust to varying properties of the sequencing library and to the sizes of the tandem duplications, as shown by its stable precision, recall and mean boundary mismatch performance. We demonstrate our method's efficacy using both simulated paired-end reads, and those generated from a melanoma sample and two ovarian cancer samples. Newly discovered tandem duplications are validated using PCR and Sanger sequencing. Our method, DB2, uses discordantly aligned reads, taking into account the distribution of fragment length to predict tandem duplications along with their breakpoints on a donor genome. The proposed method fine tunes the breakpoint calls by applying a novel probabilistic framework that incorporates the empirical fragment length distribution to score each feasible breakpoint. DB2 is implemented in Java programming language and is freely available

HeurAA: accurate and fast detection of genetic variations with a novel heuristic amplicon aligner program for next generation sequencing.

Directory of Open Access Journals (Sweden)

Lőrinc S Pongor

Full Text Available Next generation sequencing (NGS of PCR amplicons is a standard approach to detect genetic variations in personalized medicine such as cancer diagnostics. Computer programs used in the NGS community often miss insertions and deletions (indels that constitute a large part of known human mutations. We have developed HeurAA, an open source, heuristic amplicon aligner program. We tested the program on simulated datasets as well as experimental data from multiplex sequencing of 40 amplicons in 12 oncogenes collected on a 454 Genome Sequencer from lung cancer cell lines. We found that HeurAA can accurately detect all indels, and is more than an order of magnitude faster than previous programs. HeurAA can compare reads and reference sequences up to several thousand base pairs in length, and it can evaluate data from complex mixtures containing reads of different gene-segments from different samples. HeurAA is written in C and Perl for Linux operating systems, the code and the documentation are available for research applications at http://sourceforge.net/projects/heuraa/

Knowledge of damage identification about tensegrities via flexibility disassembly

Science.gov (United States)

Jiang, Ge; Feng, Xiaodong; Du, Shigui

2017-12-01

Tensegrity structures composing of continuous cables and discrete struts are under tension and compression, respectively. In order to determine the damage extents of tensegrity structures, a new method for tensegrity structural damage identification is presented based on flexibility disassembly. To decompose a tensegrity structural flexibility matrix into the matrix represention of the connectivity between degress-of-freedoms and the diagonal matrix comprising of magnitude informations. Step 1: Calculate perturbation flexibility; Step 2: Compute the flexibility connectivity matrix and perturbation flexibility parameters; Step 3: Calculate the perturbation stiffness parameters. The efficiency of the proposed method is demonstrated by a numeical example comprising of 12 cables and 4 struts with pretensioned. Accurate identification of local damage depends on the availability of good measured data, an accurate and reasonable algorithm.

Detection and identification of Toscana and other phleboviruses by RT-nested-PCR assays with degenerated primers.

Science.gov (United States)

Sánchez-Seco, María-Paz; Echevarría, José-Manuel; Hernández, Lourdes; Estévez, Domingo; Navarro-Marí, José-María; Tenorio, Antonio

2003-09-01

Phleboviruses are a large and widespread group of viruses that are transmitted by arthropods. Toscana virus is one of the principal agents that causes meningitis in humans during the summer in Italy and, possibly, in other Mediterranean countries. Rift Valley Fever virus can cause serious illness in both animals and humans, leading to high morbidity and mortality, and is considered to be a potential agent for epizootics and human epidemics. Since information on this group of viruses is still scant, reliable laboratory tools for diagnosis and epidemiological surveillance must be developed, in order to ascertain their real impact on Public Health. Sequence data obtained from Spanish isolates of Toscana virus and other phleboviruses confirmed that natural genome variability may hamper the diagnosis of these agents by molecular methods, so this must be borne in mind when developing reliable assays. In view of the above, a novel and useful protocol has been developed for the detection and specific identification of every member of the phlebovirus genus present in a sample, including Toscana virus, based on a generic RT-nested-PCR, followed by sequencing of the amplified fragment. A change in this method also allowed specific direct detection and identification of wild isolates of Toscana virus of different geographical origin, using newly designed primers. Testing clinical samples with these assays confirmed the role of Toscana virus as an agent that causes acute aseptic meningitis in the central region of Spain. Copyright 2003 Wiley-Liss, Inc.

morphological identification of malaria vectors within anopheles

African Journals Online (AJOL)

DR. AMIN

Africa among the human population. Determination of risk of malaria transmission requires quick and accurate methods of identification of Anopheles mosquitoes especially when targeting vector control. (Maxwell, et al., 2003). Anopheles mosquito transmits malaria. The most important vectors of malaria are members of.

Automated Detection of Knickpoints and Knickzones Across Transient Landscapes

Science.gov (United States)

Gailleton, B.; Mudd, S. M.; Clubb, F. J.

2017-12-01

Mountainous regions are ubiquitously dissected by river channels, which transmit climate and tectonic signals to the rest of the landscape by adjusting their long profiles. Fluvial response to allogenic forcing is often expressed through the upstream propagation of steepened reaches, referred to as knickpoints or knickzones. The identification and analysis of these steepened reaches has numerous applications in geomorphology, such as modelling long-term landscape evolution, understanding controls on fluvial incision, and constraining tectonic uplift histories. Traditionally, the identification of knickpoints or knickzones from fluvial profiles requires manual selection or calibration. This process is both time-consuming and subjective, as different workers may select different steepened reaches within the profile. We propose an objective, statistically-based method to systematically pick knickpoints/knickzones on a landscape scale using an outlier-detection algorithm. Our method integrates river profiles normalised by drainage area (Chi, using the approach of Perron and Royden, 2013), then separates the chi-elevation plots into a series of transient segments using the method of Mudd et al. (2014). This method allows the systematic detection of knickpoints across a DEM, regardless of size, using a high-performance algorithm implemented in the open-source Edinburgh Land Surface Dynamics Topographic Tools (LSDTopoTools) software package. After initial knickpoint identification, outliers are selected using several sorting and binning methods based on the Median Absolute Deviation, to avoid the influence sample size. We test our method on a series of DEMs and grid resolutions, and show that our method consistently identifies accurate knickpoint locations across each landscape tested.

Detection and identification of drugs and toxicants in human body fluids by liquid chromatography-tandem mass spectrometry under data-dependent acquisition control and automated database search.

Science.gov (United States)

Oberacher, Herbert; Schubert, Birthe; Libiseller, Kathrin; Schweissgut, Anna

2013-04-03

Systematic toxicological analysis (STA) is aimed at detecting and identifying all substances of toxicological relevance (i.e. drugs, drugs of abuse, poisons and/or their metabolites) in biological material. Particularly, gas chromatography-mass spectrometry (GC/MS) represents a competent and commonly applied screening and confirmation tool. Herein, we present an untargeted liquid chromatography-tandem mass spectrometry (LC/MS/MS) assay aimed to complement existing GC/MS screening for the detection and identification of drugs in blood, plasma and urine samples. Solid-phase extraction was accomplished on mixed-mode cartridges. LC was based on gradient elution in a miniaturized C18 column. High resolution electrospray ionization-MS/MS in positive ion mode with data-dependent acquisition control was used to generate tandem mass spectral information that enabled compound identification via automated library search in the "Wiley Registry of Tandem Mass Spectral Data, MSforID". Fitness of the developed LC/MS/MS method for application in STA in terms of selectivity, detection capability and reliability of identification (sensitivity/specificity) was demonstrated with blank samples, certified reference materials, proficiency test samples, and authentic casework samples. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluation of Rapid Stain IDentification (RSID™ Reader System for Analysis and Documentation of RSID™ Tests

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Pravatchai W. Boonlayangoor

2013-08-01

Full Text Available The ability to detect the presence of body fluids is a crucial first step in documenting and processing forensic evidence. The Rapid Stain IDentification (RSID™ tests for blood, saliva, semen and urine are lateral flow immunochromatographic strip tests specifically designed for forensic use. Like most lateral flow strips, the membrane components of the test are enclosed in a molded plastic cassette with a sample well and an observation window. No specialized equipment is required to use these tests or to score the results seen in the observation window; however, the utility of these tests can be enhanced if an electronic record of the test results can be obtained, preferably by a small hand-held device that could be used in the field under low light conditions. Such a device should also be able to “read” the lateral flow strips and accurately record the results of the test as either positive, i.e., the body fluid was detected, or negative, i.e., the body fluid was not detected. Here we describe the RSID™ Reader System—a ruggedized strip test reader unit that allows analysis and documentation of RSID™ lateral flow strip tests using pre-configured settings, and show that the RSID™ Reader can accurately and reproducibly report and record correct results from RSID™ blood, saliva, semen, and urine tests.

Performance of a veterinary urine dipstick paddle system for diagnosis and identification of urinary tract infections in dogs and cats.

Science.gov (United States)

Ybarra, Winnie L; Sykes, Jane E; Wang, Yenlie; Byrne, Barbara A; Westropp, Jodi L

2014-04-01

To evaluate the performance of a veterinary urine dipstick paddle (UDP) for diagnosis and identification of urinary tract infection (UTI) in dogs and cats. Prospective, randomized, blinded study. 207 urine specimens. UDPs were inoculated by 2 investigators and incubated according to manufacturer's instructions. Results, including presence or absence of bacterial growth, organism counts, and identification of uropathogens, were compared between investigators and with microbiology laboratory results. A subset of UDPs with bacterial growth was submitted to the laboratory for confirmation. The laboratory reported 64 (30.9%) specimens had growth of bacteria. Bacterial growth was reported for 63 (30.4%) and 58 (28.0%) of the UDPs by investigators 1 and 2, respectively. Sensitivity and specificity of the UDP for detection of bacterial growth were 97.3% and 98.6%, respectively, for investigator 1 and 89.1% and 99.3%, respectively, for investigator 2. For UPDs with ≥ 10(5) colony-forming units/mL, organism counts correlated well between the laboratory and investigators 1 (r = 0.95) and 2 (r = 0.89). Pathogen identification was not always accurate. Only 25 of 33 (75.8%) UDPs submitted for confirmation yielded bacteria consistent with those isolated from the original bacterial culture of urine. The veterinary UDP system was a sensitive test for screening patients for bacterial UTI, but uropathogen identification was not always accurate. When UDPs have bacterial growth, a fresh urine specimen should be submitted to the laboratory to confirm the identity of the organisms and to permit antimicrobial susceptibility testing.

Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology

Directory of Open Access Journals (Sweden)

Andrea Loddo

2018-02-01

Full Text Available Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis. Nevertheless, this kind of visual inspection is subjective, error-prone and time-consuming. In order to overcome the issues, numerous methods of automatic malaria diagnosis have been proposed so far. In particular, many researchers have used mathematical morphology as a powerful tool for computer aided malaria detection and classification. Mathematical morphology is not only a theory for the analysis of spatial structures, but also a very powerful technique widely used for image processing purposes and employed successfully in biomedical image analysis, especially in preprocessing and segmentation tasks. Microscopic image analysis and particularly malaria detection and classification can greatly benefit from the use of morphological operators. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection and identification in stained blood smears images.

Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology.

Science.gov (United States)

Loddo, Andrea; Di Ruberto, Cecilia; Kocher, Michel

2018-02-08

Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis. Nevertheless, this kind of visual inspection is subjective, error-prone and time-consuming. In order to overcome the issues, numerous methods of automatic malaria diagnosis have been proposed so far. In particular, many researchers have used mathematical morphology as a powerful tool for computer aided malaria detection and classification. Mathematical morphology is not only a theory for the analysis of spatial structures, but also a very powerful technique widely used for image processing purposes and employed successfully in biomedical image analysis, especially in preprocessing and segmentation tasks. Microscopic image analysis and particularly malaria detection and classification can greatly benefit from the use of morphological operators. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection and identification in stained blood smears images.

Surface-enhanced Raman scattering based nonfluorescent probe for multiplex DNA detection.

Science.gov (United States)

Sun, Lan; Yu, Chenxu; Irudayaraj, Joseph

2007-06-01

To provide rapid and accurate detection of DNA markers in a straightforward, inexpensive, and multiplex format, an alternative surface-enhanced Raman scattering based probe was designed and fabricated to covalently attach both DNA probing sequence and nonfluorescent Raman tags to the surface of gold nanoparticles (DNA-AuP-RTag). The intensity of Raman signal of the probes could be controlled through the surface coverage of the nonfluorescent Raman tags (RTags). Detection sensitivity of these probes could be optimized by fine-tuning the amount of DNA molecules and RTags on the probes. Long-term stability of the DNA-AuP-RTag probes was found to be good (over 3 months). Excellent multiplexing capability of the DNA-AuP-RTag scheme was demonstrated by simultaneous identification of up to eight probes in a mixture. Detection of hybridization of single-stranded DNA to its complementary targets was successfully accomplished with a long-term goal to use nonfluorescent RTags in a Raman-based DNA microarray platform.

Real-time PCR assays for detection of Brucella spp. and the identification of genotype ST27 in bottlenose dolphins (Tursiops truncatus).

Science.gov (United States)

Wu, Qingzhong; McFee, Wayne E; Goldstein, Tracey; Tiller, Rebekah V; Schwacke, Lori

2014-05-01

Rapid detection of Brucella spp. in marine mammals is challenging. Microbiologic culture is used for definitive diagnosis of brucellosis, but is time consuming, has low sensitivity and can be hazardous to laboratory personnel. Serological methods can aid in diagnosis, but may not differentiate prior exposure versus current active infection and may cross-react with unrelated Gram-negative bacteria. This study reports a real-time PCR assay for the detection of Brucella spp. and application to screen clinical samples from bottlenose dolphins stranded along the coast of South Carolina, USA. The assay was found to be 100% sensitive for the Brucella strains tested, and the limit of detection was 0.27fg of genomic DNA from Brucella ceti B1/94 per PCR volume. No amplification was detected for the non-Brucella pathogens tested. Brucella DNA was detected in 31% (55/178) of clinical samples tested. These studies indicate that the real-time PCR assay is highly sensitive and specific for the detection of Brucella spp. in bottlenose dolphins. We also developed a second real-time PCR assay for rapid identification of Brucella ST27, a genotype that is associated with human zoonotic infection. Positive results were obtained for Brucella strains which had been identified as ST27 by multilocus sequence typing. No amplification was found for other Brucella strains included in this study. ST27 was identified in 33% (18/54) of Brucella spp. DNA-positive clinical samples. To our knowledge, this is the first report on the use of a real-time PCR assay for identification of Brucella genotype ST27 in marine mammals. Copyright © 2014 Elsevier B.V. All rights reserved.

Rapid and reliable detection and identification of GM events using multiplex PCR coupled with oligonucleotide microarray.

Science.gov (United States)

Xu, Xiaodan; Li, Yingcong; Zhao, Heng; Wen, Si-yuan; Wang, Sheng-qi; Huang, Jian; Huang, Kun-lun; Luo, Yun-bo

2005-05-18

To devise a rapid and reliable method for the detection and identification of genetically modified (GM) events, we developed a multiplex polymerase chain reaction (PCR) coupled with a DNA microarray system simultaneously aiming at many targets in a single reaction. The system included probes for screening gene, species reference gene, specific gene, construct-specific gene, event-specific gene, and internal and negative control genes. 18S rRNA was combined with species reference genes as internal controls to assess the efficiency of all reactions and to eliminate false negatives. Two sets of the multiplex PCR system were used to amplify four and five targets, respectively. Eight different structure genes could be detected and identified simultaneously for Roundup Ready soybean in a single microarray. The microarray specificity was validated by its ability to discriminate two GM maizes Bt176 and Bt11. The advantages of this method are its high specificity and greatly reduced false-positives and -negatives. The multiplex PCR coupled with microarray technology presented here is a rapid and reliable tool for the simultaneous detection of GM organism ingredients.

An integrated tool to study MHC region: accurate SNV detection and HLA genes typing in human MHC region using targeted high-throughput sequencing.

Directory of Open Access Journals (Sweden)

Hongzhi Cao

Full Text Available The major histocompatibility complex (MHC is one of the most variable and gene-dense regions of the human genome. Most studies of the MHC, and associated regions, focus on minor variants and HLA typing, many of which have been demonstrated to be associated with human disease susceptibility and metabolic pathways. However, the detection of variants in the MHC region, and diagnostic HLA typing, still lacks a coherent, standardized, cost effective and high coverage protocol of clinical quality and reliability. In this paper, we presented such a method for the accurate detection of minor variants and HLA types in the human MHC region, using high-throughput, high-coverage sequencing of target regions. A probe set was designed to template upon the 8 annotated human MHC haplotypes, and to encompass the 5 megabases (Mb of the extended MHC region. We deployed our probes upon three, genetically diverse human samples for probe set evaluation, and sequencing data show that ∼97% of the MHC region, and over 99% of the genes in MHC region, are covered with sufficient depth and good evenness. 98% of genotypes called by this capture sequencing prove consistent with established HapMap genotypes. We have concurrently developed a one-step pipeline for calling any HLA type referenced in the IMGT/HLA database from this target capture sequencing data, which shows over 96% typing accuracy when deployed at 4 digital resolution. This cost-effective and highly accurate approach for variant detection and HLA typing in the MHC region may lend further insight into immune-mediated diseases studies, and may find clinical utility in transplantation medicine research. This one-step pipeline is released for general evaluation and use by the scientific community.

A Parameter Identification Method for Helicopter Noise Source Identification and Physics-Based Semi-Empirical Modeling

Science.gov (United States)

Greenwood, Eric, II; Schmitz, Fredric H.

2010-01-01

A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.

Mining social media and web searches for disease detection.

Science.gov (United States)

Yang, Y Tony; Horneffer, Michael; DiLisio, Nicole

2013-04-28

Web-based social media is increasingly being used across different settings in the health care industry. The increased frequency in the use of the Internet via computer or mobile devices provides an opportunity for social media to be the medium through which people can be provided with valuable health information quickly and directly. While traditional methods of detection relied predominately on hierarchical or bureaucratic lines of communication, these often failed to yield timely and accurate epidemiological intelligence. New web-based platforms promise increased opportunities for a more timely and accurate spreading of information and analysis. This article aims to provide an overview and discussion of the availability of timely and accurate information. It is especially useful for the rapid identification of an outbreak of an infectious disease that is necessary to promptly and effectively develop public health responses. These web-based platforms include search queries, data mining of web and social media, process and analysis of blogs containing epidemic key words, text mining, and geographical information system data analyses. These new sources of analysis and information are intended to complement traditional sources of epidemic intelligence. Despite the attractiveness of these new approaches, further study is needed to determine the accuracy of blogger statements, as increases in public participation may not necessarily mean the information provided is more accurate.

Mining social media and web searches for disease detection

Directory of Open Access Journals (Sweden)

Y. Tony Yang

2013-05-01

Full Text Available Web-based social media is increasingly being used across different settings in the health care industry. The increased frequency in the use of the Internet via computer or mobile devices provides an opportunity for social media to be the medium through which people can be provided with valuable health information quickly and directly. While traditional methods of detection relied predominately on hierarchical or bureaucratic lines of communication, these often failed to yield timely and accurate epidemiological intelligence. New web-based platforms promise increased opportunities for a more timely and accurate spreading of information and analysis. This article aims to provide an overview and discussion of the availability of timely and accurate information. It is especially useful for the rapid identification of an outbreak of an infectious disease that is necessary to promptly and effectively develop public health responses. These web-based platforms include search queries, data mining of web and social media, process and analysis of blogs containing epidemic key words, text mining, and geographical information system data analyses. These new sources of analysis and information are intended to complement traditional sources of epidemic intelligence. Despite the attractiveness of these new approaches, further study is needed to determine the accuracy of blogger statements, as increases in public participation may not necessarily mean the information provided is more accurate.

Incipient fault detection and identification in process systems using accelerating neural network learning

International Nuclear Information System (INIS)

Parlos, A.G.; Muthusami, J.; Atiya, A.F.

1994-01-01

The objective of this paper is to present the development and numerical testing of a robust fault detection and identification (FDI) system using artificial neural networks (ANNs), for incipient (slowly developing) faults occurring in process systems. The challenge in using ANNs in FDI systems arises because of one's desire to detect faults of varying severity, faults from noisy sensors, and multiple simultaneous faults. To address these issues, it becomes essential to have a learning algorithm that ensures quick convergence to a high level of accuracy. A recently developed accelerated learning algorithm, namely a form of an adaptive back propagation (ABP) algorithm, is used for this purpose. The ABP algorithm is used for the development of an FDI system for a process composed of a direct current motor, a centrifugal pump, and the associated piping system. Simulation studies indicate that the FDI system has significantly high sensitivity to incipient fault severity, while exhibiting insensitivity to sensor noise. For multiple simultaneous faults, the FDI system detects the fault with the predominant signature. The major limitation of the developed FDI system is encountered when it is subjected to simultaneous faults with similar signatures. During such faults, the inherent limitation of pattern-recognition-based FDI methods becomes apparent. Thus, alternate, more sophisticated FDI methods become necessary to address such problems. Even though the effectiveness of pattern-recognition-based FDI methods using ANNs has been demonstrated, further testing using real-world data is necessary

Demographic Factors Associated with the Early Identification of Children with Special Needs

Science.gov (United States)

Guarino, Cassandra M.; Buddin, Richard; Pham, Chung; Cho, Michelle

2010-01-01

Early and accurate identification of special needs, coupled with an appropriate course of treatment and educational plan, is important to academic progress, in particular for economically disadvantaged children with fewer family resources to catch up if they fall behind. A first step in improving mechanisms to promote early identification is to…

Highly sensitive capillary electrophoresis-mass spectrometry for rapid screening and accurate quantitation of drugs of abuse in urine.

Science.gov (United States)

Kohler, Isabelle; Schappler, Julie; Rudaz, Serge

2013-05-30

The combination of capillary electrophoresis (CE) and mass spectrometry (MS) is particularly well adapted to bioanalysis due to its high separation efficiency, selectivity, and sensitivity; its short analytical time; and its low solvent and sample consumption. For clinical and forensic toxicology, a two-step analysis is usually performed: first, a screening step for compound identification, and second, confirmation and/or accurate quantitation in cases of presumed positive results. In this study, a fast and sensitive CE-MS workflow was developed for the screening and quantitation of drugs of abuse in urine samples. A CE with a time-of-flight MS (CE-TOF/MS) screening method was developed using a simple urine dilution and on-line sample preconcentration with pH-mediated stacking. The sample stacking allowed for a high loading capacity (20.5% of the capillary length), leading to limits of detection as low as 2 ng mL(-1) for drugs of abuse. Compound quantitation of positive samples was performed by CE-MS/MS with a triple quadrupole MS equipped with an adapted triple-tube sprayer and an electrospray ionization (ESI) source. The CE-ESI-MS/MS method was validated for two model compounds, cocaine (COC) and methadone (MTD), according to the Guidance of the Food and Drug Administration. The quantitative performance was evaluated for selectivity, response function, the lower limit of quantitation, trueness, precision, and accuracy. COC and MTD detection in urine samples was determined to be accurate over the range of 10-1000 ng mL(-1) and 21-1000 ng mL(-1), respectively. Copyright © 2013 Elsevier B.V. All rights reserved.

Fault Detection for a Diesel Engine Actuator

DEFF Research Database (Denmark)

Blanke, M.; Bøgh, S.A.; Jørgensen, R.B.

1995-01-01

An electro-mechanical position servo is introduced as a benchmark for mode-based Fault Detection and Identification (FDI).......An electro-mechanical position servo is introduced as a benchmark for mode-based Fault Detection and Identification (FDI)....

A novel multiplex PCR for the simultaneous detection of Salmonella enterica and Shigella species.

Science.gov (United States)

Radhika, M; Saugata, Majumder; Murali, H S; Batra, H V

2014-01-01

Salmonella enterica and Shigella species are commonly associated with food and water borne infections leading to gastrointestinal diseases. The present work was undertaken to develop a sensitive and reliable PCR based detection system for simultaneous detection of Salmonella enterica and Shigella at species level. For this the conserved regions of specific genes namely ipaH1, ipaH, wbgZ, wzy and invA were targeted for detection of Shigella genus, S. flexneri, S. sonnei, S. boydii and Salmonella enterica respectively along with an internal amplification control (IAC). The results showed that twenty Salmonella and eleven Shigella spp., were accurately identified by the assay without showing non-specificity against closely related other Enterobacteriaceae organisms and also against other pathogens. Further evaluation of multiplex PCR was undertaken on 50 natural samples of chicken, eggs and poultry litter and results compared with conventional culture isolation and identification procedure. The multiplex PCR identified the presence of Salmonella and Shigella strains with a short pre-enrichment step of 5 h in peptone water and the same samples were processed by conventional procedures for comparison. Therefore, this reported multiplex PCR can serve as an alternative to the tedious time-consuming procedure of culture and identification in food safety laboratories.

3D ear identification based on sparse representation.

Directory of Open Access Journals (Sweden)

Lin Zhang

Full Text Available Biometrics based personal authentication is an effective way for automatically recognizing, with a high confidence, a person's identity. Recently, 3D ear shape has attracted tremendous interests in research field due to its richness of feature and ease of acquisition. However, the existing ICP (Iterative Closet Point-based 3D ear matching methods prevalent in the literature are not quite efficient to cope with the one-to-many identification case. In this paper, we aim to fill this gap by proposing a novel effective fully automatic 3D ear identification system. We at first propose an accurate and efficient template-based ear detection method. By utilizing such a method, the extracted ear regions are represented in a common canonical coordinate system determined by the ear contour template, which facilitates much the following stages of feature extraction and classification. For each extracted 3D ear, a feature vector is generated as its representation by making use of a PCA-based local feature descriptor. At the stage of classification, we resort to the sparse representation based classification approach, which actually solves an l1-minimization problem. To the best of our knowledge, this is the first work introducing the sparse representation framework into the field of 3D ear identification. Extensive experiments conducted on a benchmark dataset corroborate the effectiveness and efficiency of the proposed approach. The associated Matlab source code and the evaluation results have been made publicly online available at http://sse.tongji.edu.cn/linzhang/ear/srcear/srcear.htm.

Crack identification by artificial neural network

Energy Technology Data Exchange (ETDEWEB)

Hwu, C.B.; Liang, Y.C. [National Cheng Kung Univ., Tainan (Taiwan, Province of China). Inst. of Aeronaut. and Astronaut.

1998-04-01

In this paper, a most popular artificial neural network called the back propagation neural network (BPN) is employed to achieve an ideal on-line identification of the crack embedded in a composite plate. Different from the usual dynamic estimate, the parameters used for the present crack identification are the strains of static deformation. It is known that the crack effects are localized which may not be clearly reflected from the boundary information especially when the data is from static deformation only. To remedy this, we use data from multiple-loading modes in which the loading modes may include the opening, shearing and tearing modes. The results show that our method for crack identification is always stable and accurate no matter how far-away of the test data from its training set. (orig.) 8 refs.

Study on Material Parameters Identification of Brain Tissue Considering Uncertainty of Friction Coefficient

Science.gov (United States)

Guan, Fengjiao; Zhang, Guanjun; Liu, Jie; Wang, Shujing; Luo, Xu; Zhu, Feng

2017-10-01

Accurate material parameters are critical to construct the high biofidelity finite element (FE) models. However, it is hard to obtain the brain tissue parameters accurately because of the effects of irregular geometry and uncertain boundary conditions. Considering the complexity of material test and the uncertainty of friction coefficient, a computational inverse method for viscoelastic material parameters identification of brain tissue is presented based on the interval analysis method. Firstly, the intervals are used to quantify the friction coefficient in the boundary condition. And then the inverse problem of material parameters identification under uncertain friction coefficient is transformed into two types of deterministic inverse problem. Finally the intelligent optimization algorithm is used to solve the two types of deterministic inverse problems quickly and accurately, and the range of material parameters can be easily acquired with no need of a variety of samples. The efficiency and convergence of this method are demonstrated by the material parameters identification of thalamus. The proposed method provides a potential effective tool for building high biofidelity human finite element model in the study of traffic accident injury.

Molecular formula and METLIN Personal Metabolite Database matching applied to the identification of compounds generated by LC/TOF-MS.

Science.gov (United States)

Sana, Theodore R; Roark, Joseph C; Li, Xiangdong; Waddell, Keith; Fischer, Steven M

2008-09-01

In an effort to simplify and streamline compound identification from metabolomics data generated by liquid chromatography time-of-flight mass spectrometry, we have created software for constructing Personalized Metabolite Databases with content from over 15,000 compounds pulled from the public METLIN database (http://metlin.scripps.edu/). Moreover, we have added extra functionalities to the database that (a) permit the addition of user-defined retention times as an orthogonal searchable parameter to complement accurate mass data; and (b) allow interfacing to separate software, a Molecular Formula Generator (MFG), that facilitates reliable interpretation of any database matches from the accurate mass spectral data. To test the utility of this identification strategy, we added retention times to a subset of masses in this database, representing a mixture of 78 synthetic urine standards. The synthetic mixture was analyzed and screened against this METLIN urine database, resulting in 46 accurate mass and retention time matches. Human urine samples were subsequently analyzed under the same analytical conditions and screened against this database. A total of 1387 ions were detected in human urine; 16 of these ions matched both accurate mass and retention time parameters for the 78 urine standards in the database. Another 374 had only an accurate mass match to the database, with 163 of those masses also having the highest MFG score. Furthermore, MFG calculated a formula for a further 849 ions that had no match to the database. Taken together, these results suggest that the METLIN Personal Metabolite database and MFG software offer a robust strategy for confirming the formula of database matches. In the event of no database match, it also suggests possible formulas that may be helpful in interpreting the experimental results.

Application of Modal Parameter Estimation Methods for Continuous Wavelet Transform-Based Damage Detection for Beam-Like Structures

Directory of Open Access Journals (Sweden)

Zhi Qiu

2015-02-01

Full Text Available This paper presents a hybrid damage detection method based on continuous wavelet transform (CWT and modal parameter identification techniques for beam-like structures. First, two kinds of mode shape estimation methods, herein referred to as the quadrature peaks picking (QPP and rational fraction polynomial (RFP methods, are used to identify the first four mode shapes of an intact beam-like structure based on the hammer/accelerometer modal experiment. The results are compared and validated using a numerical simulation with ABAQUS software. In order to determine the damage detection effectiveness between the QPP-based method and the RFP-based method when applying the CWT technique, the first two mode shapes calculated by the QPP and RFP methods are analyzed using CWT. The experiment, performed on different damage scenarios involving beam-like structures, shows that, due to the outstanding advantage of the denoising characteristic of the RFP-based (RFP-CWT technique, the RFP-CWT method gives a clearer indication of the damage location than the conventionally used QPP-based (QPP-CWT method. Finally, an overall evaluation of the damage detection is outlined, as the identification results suggest that the newly proposed RFP-CWT method is accurate and reliable in terms of detection of damage locations on beam-like structures.

In vivo tumor detection with combined MR–Photoacoustic-Thermoacoustic imaging

Directory of Open Access Journals (Sweden)

Lin Huang

2016-09-01

Full Text Available Here, we report a new method using combined magnetic resonance (MR–Photoacoustic (PA–Thermoacoustic (TA imaging techniques, and demonstrate its unique ability for in vivo cancer detection using tumor-bearing mice. Circular scanning TA and PA imaging systems were used to recover the dielectric and optical property distributions of three colon carcinoma bearing mice While a 7.0-T magnetic resonance imaging (MRI unit with a mouse body volume coil was utilized for high resolution structural imaging of the same mice. Three plastic tubes filled with soybean sauce were used as fiducial markers for the co-registration of MR, PA and TA images. The resulting fused images provided both enhanced tumor margin and contrast relative to the surrounding normal tissues. In particular, some finger-like protrusions extending into the surrounding tissues were revealed in the MR/TA infused images. These results show that the tissue functional optical and dielectric properties provided by PA and TA images along with the anatomical structure by MRI in one picture make accurate tumor identification easier. This combined MR–PA–TA-imaging strategy has the potential to offer a clinically useful triple-modality tool for accurate cancer detection and for intraoperative surgical navigation.

Alternative SNP detection platforms, HRM and biosensors, for varietal identification in Vitis vinifera L. using F3H and LDOX genes.

Science.gov (United States)

Gomes, Sónia; Castro, Cláudia; Barrias, Sara; Pereira, Leonor; Jorge, Pedro; Fernandes, José R; Martins-Lopes, Paula

2018-04-11

The wine sector requires quick and reliable methods for Vitis vinifera L. varietal identification. The number of V. vinifera varieties is estimated in about 5,000 worldwide. Single Nucleotide Polymorphisms (SNPs) represent the most basic and abundant form of genetic sequence variation, being adequate for varietal discrimination. The aim of this work was to develop DNA-based assays suitable to detect SNP variation in V. vinifera, allowing varietal discrimination. Genotyping by sequencing allowed the detection of eleven SNPs on two genes of the anthocyanin pathway, the flavanone 3-hydroxylase (F3H, EC: 1.14.11.9), and the leucoanthocyanidin dioxygenase (LDOX, EC 1.14.11.19; synonym anthocyanidin synthase, ANS) in twenty V. vinifera varieties. Three High Resolution Melting (HRM) assays were designed based on the sequencing information, discriminating five of the 20 varieties: Alicante Bouschet, Donzelinho Tinto, Merlot, Moscatel Galego and Tinta Roriz. Sanger sequencing of the HRM assay products confirmed the HRM profiles. Three probes, with different lengths and sequences, were used as bio-recognition elements in an optical biosensor platform based on a long period grating (LPG) fiber optic sensor. The label free platform detected a difference of a single SNP using genomic DNA samples. The two different platforms were successfully applied for grapevine varietal identification.

Biometric identification based on feature fusion with PCA and SVM

Science.gov (United States)

Lefkovits, László; Lefkovits, Szidónia; Emerich, Simina

2018-04-01

Biometric identification is gaining ground compared to traditional identification methods. Many biometric measurements may be used for secure human identification. The most reliable among them is the iris pattern because of its uniqueness, stability, unforgeability and inalterability over time. The approach presented in this paper is a fusion of different feature descriptor methods such as HOG, LIOP, LBP, used for extracting iris texture information. The classifiers obtained through the SVM and PCA methods demonstrate the effectiveness of our system applied to one and both irises. The performances measured are highly accurate and foreshadow a fusion system with a rate of identification approaching 100% on the UPOL database.

Induced Voltages Ratio-Based Algorithm for Fault Detection, and Faulted Phase and Winding Identification of a Three-Winding Power Transformer

Directory of Open Access Journals (Sweden)

Byung Eun Lee

2014-09-01

Full Text Available This paper proposes an algorithm for fault detection, faulted phase and winding identification of a three-winding power transformer based on the induced voltages in the electrical power system. The ratio of the induced voltages of the primary-secondary, primary-tertiary and secondary-tertiary windings is the same as the corresponding turns ratio during normal operating conditions, magnetic inrush, and over-excitation. It differs from the turns ratio during an internal fault. For a single phase and a three-phase power transformer with wye-connected windings, the induced voltages of each pair of windings are estimated. For a three-phase power transformer with delta-connected windings, the induced voltage differences are estimated to use the line currents, because the delta winding currents are practically unavailable. Six detectors are suggested for fault detection. An additional three detectors and a rule for faulted phase and winding identification are presented as well. The proposed algorithm can not only detect an internal fault, but also identify the faulted phase and winding of a three-winding power transformer. The various test results with Electromagnetic Transients Program (EMTP-generated data show that the proposed algorithm successfully discriminates internal faults from normal operating conditions including magnetic inrush and over-excitation. This paper concludes by implementing the algorithm into a prototype relay based on a digital signal processor.

A practical approach to tramway track condition monitoring: vertical track defects detection and identification using time-frequency processing technique

Directory of Open Access Journals (Sweden)

Bocz Péter

2018-03-01

Full Text Available This paper presents an automatic method for detecting vertical track irregularities on tramway operation using acceleration measurements on trams. For monitoring of tramway tracks, an unconventional measurement setup is developed, which records the data of 3-axes wireless accelerometers mounted on wheel discs. Accelerations are processed to obtain the vertical track irregularities to determine whether the track needs to be repaired. The automatic detection algorithm is based on time–frequency distribution analysis and determines the defect locations. Admissible limits (thresholds are given for detecting moderate and severe defects using statistical analysis. The method was validated on frequented tram lines in Budapest and accurately detected severe defects with a hit rate of 100%, with no false alarms. The methodology is also sensitive to moderate and small rail surface defects at the low operational speed.

Laboratory evaluation of a quantitative real-time reverse transcription PCR assay for the detection and identification of the four subgroups of avian metapneumovirus.

Science.gov (United States)

Guionie, O; Toquin, D; Sellal, E; Bouley, S; Zwingelstein, F; Allée, C; Bougeard, S; Lemière, S; Eterradossi, N

2007-02-01

Avian metapneumovirus (AMPV) is an important pathogen causing respiratory diseases and egg drops in several avian species. Four AMPV subgroups have been identified. The laboratory diagnosis of AMPV infections relies on serological methods, on labour-intensive virus isolation procedures, and on recently developed subgroup specific reverse transcription PCR (RT-PCR) protocols. In the present study, both the specificity and sensitivity of a commercial real-time reverse transcription PCR (RRT-PCR) for the detection and identification of the four AMPV subgroups were evaluated. Fifteen non-AMPV avian viruses belonging to 7 genera and 32 AMPV belonging to the 4 subgroups were tested. No non-AMPV virus was detected, whereas all AMPV viruses were identified in agreement with their previous molecular and antigenic subgroup assignment. The sensitivity and quantitating ability of the RRT-PCR assay were determined using serial dilutions of RNA derived either from AMPV virus stocks or from runoff transcripts. In all cases, linear dose/responses were observed. The detection limits of the different subgroups ranged from 500 to 5000 RNA copies and from 0.03 to 3.16TCID50/ml. The results were reproducible under laboratory conditions, thus showing that quantitative RRT-PCR is a new and powerful tool for the rapid and sensitive detection, identification and quantitation of AMPVs.

Optical identifications of radio sources in the 5C 7 survey

International Nuclear Information System (INIS)

Perryman, M.A.C.

1979-01-01

An identification procedure developed for the deep radio survey 5C 6 has been refined and applied to the 5C 7 survey. Positions and finding charts are presented for candidate identifications from deep plates taken with the Palomar 48-inch Schmidt telescope. The identification statistics are in good agreement with the 5C 6 results, the accurate radio positions obtained at 1407 MHz defining a reasonably reliable and complete sample of associations with an identification rate of about 40 per cent. At 408 MHz the positional uncertainties are larger and the identifications are thus of lower reliability; the identification rate is about 20 per cent. The results are in good agreement with the assumptions that the optical identifications are coincident with the radio centroids, and that the identifications are not preferentially associated with faint clusters. (author)

Accurate 3D Mapping Algorithm for Flexible Antennas

Directory of Open Access Journals (Sweden)

Saed Asaly

2018-01-01

Full Text Available This work addresses the problem of performing an accurate 3D mapping of a flexible antenna surface. Consider a high-gain satellite flexible antenna; even a submillimeter change in the antenna surface may lead to a considerable loss in the antenna gain. Using a robotic subreflector, such changes can be compensated for. Yet, in order to perform such tuning, an accurate 3D mapping of the main antenna is required. This paper presents a general method for performing an accurate 3D mapping of marked surfaces such as satellite dish antennas. Motivated by the novel technology for nanosatellites with flexible high-gain antennas, we propose a new accurate mapping framework which requires a small-sized monocamera and known patterns on the antenna surface. The experimental result shows that the presented mapping method can detect changes up to 0.1-millimeter accuracy, while the camera is located 1 meter away from the dish, allowing an RF antenna optimization for Ka and Ku frequencies. Such optimization process can improve the gain of the flexible antennas and allow an adaptive beam shaping. The presented method is currently being implemented on a nanosatellite which is scheduled to be launched at the end of 2018.

Detection, identification and differentiation of Pectobacterium and Dickeya species causing potato blackleg and tuber soft rot: a review.

Science.gov (United States)

Czajkowski, R; Pérombelon, McM; Jafra, S; Lojkowska, E; Potrykus, M; van der Wolf, Jm; Sledz, W

2015-01-01

The soft rot Enterobacteriaceae (SRE) Pectobacterium and Dickeya species (formerly classified as pectinolytic Erwinia spp.) cause important diseases on potato and other arable and horticultural crops. They may affect the growing potato plant causing blackleg and are responsible for tuber soft rot in storage thereby reducing yield and quality. Efficient and cost-effective detection and identification methods are essential to investigate the ecology and pathogenesis of the SRE as well as in seed certification programmes. The aim of this review was to collect all existing information on methods available for SRE detection. The review reports on the sampling and preparation of plant material for testing and on over thirty methods to detect, identify and differentiate the soft rot and blackleg causing bacteria to species and subspecies level. These include methods based on biochemical characters, serology, molecular techniques which rely on DNA sequence amplification as well as several less-investigated ones.

Molecular identification of nematode larvae different from those of the Trichinella genus detected by muscle digestion.

Science.gov (United States)

Marucci, Gianluca; Interisano, Maria; La Rosa, Giuseppe; Pozio, Edoardo

2013-05-20

Although larvae of the genus Trichinella are the most common parasite species detected in vertebrate muscles using artificial digestion, nematode larvae belonging to other genera are sometimes detected and incorrectly identified as Trichinella. However, it is often very difficult to identify these larvae at the species, genus or family level using microscopy because of the absence of specific morphological characters or cuticle damage, and the only means of identification is PCR and sequencing of specific molecular markers (12S mtDNA; COI; 18S rDNA; and ITS1). From 2008 to 2011, 18 nematode isolates not belonging to the genus Trichinella were collected from different host species. Eleven of these isolates were successfully identified at the species, genus or superfamily level: larvae from two common kestrels, three hooded crows, a hen harrier and a domestic pig were identified as Toxocara cati; larvae from a badger were identified as Toxocara canis; larvae from a domestic pig were identified as a free-living nematode of the genus Panagrolaimus; larvae from a wild boar were identified as belonging to the Metastrongylus genus; and larvae from a rough-legged buzzard were identified as belonging to the superfamily Filarioidea. The recovery of nematodes belonging to genera other than Trichinella during routine meat inspection suggests that the persons performing the analyses need to be informed of the possibility of false positives and that a molecular-based identification system that allows for a rapid and reliable response must be adopted (i.e., a DNA barcoding-like system). Copyright © 2013 Elsevier B.V. All rights reserved.

RareVar: A Framework for Detecting Low-Frequency Single-Nucleotide Variants.

Science.gov (United States)

Hao, Yangyang; Xuei, Xiaoling; Li, Lang; Nakshatri, Harikrishna; Edenberg, Howard J; Liu, Yunlong

2017-07-01

Accurate identification of low-frequency somatic point mutations in tumor samples has important clinical utilities. Although high-throughput sequencing technology enables capturing such variants while sequencing primary tumor samples, our ability for accurate detection is compromised when the variant frequency is close to the sequencer error rate. Most current experimental and bioinformatic strategies target mutations with ≥5% allele frequency, which limits our ability to understand the cancer etiology and tumor evolution. We present an experimental and computational modeling framework, RareVar, to reliably identify low-frequency single-nucleotide variants from high-throughput sequencing data under standard experimental protocols. RareVar protocol includes a benchmark design by pooling DNAs from already sequenced individuals at various concentrations to target variants at desired frequencies, 0.5%-3% in our case. By applying a generalized, linear model-based, position-specific error model, followed by machine-learning-based variant calibration, our approach outperforms existing methods. Our method can be applied on most capture and sequencing platforms without modifying the experimental protocol.

[Development and application of real-time PCR for identification and detection of horse meat in animal-origin products].

Science.gov (United States)

Li, Nan; Wang, Jiahui; Shen, Qing; Han, Chunhui; Zhang, Jing; Li, Fengqin; Xu, Jin; Jiang, Tao

2013-11-01

To develop a real-time PCR method for identification and detection of domestic horse meat (Equus caballus) in animal-origin products. The primer and TaqMan-probe was designed and synthesized according to the EU reference laboratory and 87 bp fragments was amplified for horse ingredients. The specificity and sensitivity was tested by artificially spiked horse meat into other domestic meat, such as cattle, sheep, pork, chicken, duck and rabbit. 122 samples of cattle and sheep products were random collected in Beijing market and the detection of horse meat was carried out. The real-time PCR in this study has high specificity and sensitivity for horse meat. No cross-reaction was observed between the horse and sheep, pork, chicken, duck and rabbit meat. There was little cross reaction between horse and cattle when the CT value reach 33. 81. The method can detect 0.1% of horse meat mixed with other domestic animal-origin products. No horse meat ingredients were detected in 122 samples in this survey. There was no horse meat mixed into cattle and sheep products in Beijing marked.

Complete Hexose Isomer Identification with Mass Spectrometry

Science.gov (United States)

Nagy, Gabe; Pohl, Nicola L. B.

2015-04-01

The first analytical method is presented for the identification and absolute configuration determination of all 24 aldohexose and 2-ketohexose isomers, including the D and L enantiomers for allose, altrose, galactose, glucose, gulose, idose, mannose, talose, fructose, psicose, sorbose, and tagatose. Two unique fixed ligand kinetic method combinations were discovered to create significant enough energetic differences to achieve chiral discrimination among all 24 hexoses. Each of these 24 hexoses yields unique ratios of a specific pair of fragment ions that allows for simultaneous determination of identification and absolute configuration. This mass spectrometric-based methodology can be readily employed for accurate identification of any isolated monosaccharide from an unknown biological source. This work provides a key step towards the goal of complete de novo carbohydrate analysis.

Estimating spatial travel times using automatic vehicle identification data

Science.gov (United States)

2001-01-01

Prepared ca. 2001. The paper describes an algorithm that was developed for estimating reliable and accurate average roadway link travel times using Automatic Vehicle Identification (AVI) data. The algorithm presented is unique in two aspects. First, ...

Identification and evaluation of new reference genes in Gossypium hirsutum for accurate normalization of real-time quantitative RT-PCR data

Directory of Open Access Journals (Sweden)

Alves-Ferreira Marcio

2010-03-01

Full Text Available Abstract Background Normalizing through reference genes, or housekeeping genes, can make more accurate and reliable results from reverse transcription real-time quantitative polymerase chain reaction (qPCR. Recent studies have shown that no single housekeeping gene is universal for all experiments. Thus, suitable reference genes should be the first step of any qPCR analysis. Only a few studies on the identification of housekeeping gene have been carried on plants. Therefore qPCR studies on important crops such as cotton has been hampered by the lack of suitable reference genes. Results By the use of two distinct algorithms, implemented by geNorm and NormFinder, we have assessed the gene expression of nine candidate reference genes in cotton: GhACT4, GhEF1α5, GhFBX6, GhPP2A1, GhMZA, GhPTB, GhGAPC2, GhβTUB3 and GhUBQ14. The candidate reference genes were evaluated in 23 experimental samples consisting of six distinct plant organs, eight stages of flower development, four stages of fruit development and in flower verticils. The expression of GhPP2A1 and GhUBQ14 genes were the most stable across all samples and also when distinct plants organs are examined. GhACT4 and GhUBQ14 present more stable expression during flower development, GhACT4 and GhFBX6 in the floral verticils and GhMZA and GhPTB during fruit development. Our analysis provided the most suitable combination of reference genes for each experimental set tested as internal control for reliable qPCR data normalization. In addition, to illustrate the use of cotton reference genes we checked the expression of two cotton MADS-box genes in distinct plant and floral organs and also during flower development. Conclusion We have tested the expression stabilities of nine candidate genes in a set of 23 tissue samples from cotton plants divided into five different experimental sets. As a result of this evaluation, we recommend the use of GhUBQ14 and GhPP2A1 housekeeping genes as superior references

Identification and evaluation of new reference genes in Gossypium hirsutum for accurate normalization of real-time quantitative RT-PCR data.

Science.gov (United States)

Artico, Sinara; Nardeli, Sarah M; Brilhante, Osmundo; Grossi-de-Sa, Maria Fátima; Alves-Ferreira, Marcio

2010-03-21

Normalizing through reference genes, or housekeeping genes, can make more accurate and reliable results from reverse transcription real-time quantitative polymerase chain reaction (qPCR). Recent studies have shown that no single housekeeping gene is universal for all experiments. Thus, suitable reference genes should be the first step of any qPCR analysis. Only a few studies on the identification of housekeeping gene have been carried on plants. Therefore qPCR studies on important crops such as cotton has been hampered by the lack of suitable reference genes. By the use of two distinct algorithms, implemented by geNorm and NormFinder, we have assessed the gene expression of nine candidate reference genes in cotton: GhACT4, GhEF1alpha5, GhFBX6, GhPP2A1, GhMZA, GhPTB, GhGAPC2, GhbetaTUB3 and GhUBQ14. The candidate reference genes were evaluated in 23 experimental samples consisting of six distinct plant organs, eight stages of flower development, four stages of fruit development and in flower verticils. The expression of GhPP2A1 and GhUBQ14 genes were the most stable across all samples and also when distinct plants organs are examined. GhACT4 and GhUBQ14 present more stable expression during flower development, GhACT4 and GhFBX6 in the floral verticils and GhMZA and GhPTB during fruit development. Our analysis provided the most suitable combination of reference genes for each experimental set tested as internal control for reliable qPCR data normalization. In addition, to illustrate the use of cotton reference genes we checked the expression of two cotton MADS-box genes in distinct plant and floral organs and also during flower development. We have tested the expression stabilities of nine candidate genes in a set of 23 tissue samples from cotton plants divided into five different experimental sets. As a result of this evaluation, we recommend the use of GhUBQ14 and GhPP2A1 housekeeping genes as superior references for normalization of gene expression measures in

A study on association and correlation of lip and finger print pattern analysis for gender identification

Directory of Open Access Journals (Sweden)

Surapaneni Ratheesh Kumar Nandan

2015-01-01

Conclusion: Lip print analysis is a challenging area in the personal identification during forensic dentistry examination. The study revealed the weaker correlation and approachable significance of lip and finger print pattern in gender identification. Future studies should be encouraged in the direction of software based identification for lip and finger print analysis in gender identification. Such studies may benefit this study pattern in more accurate way.

Low Power, Room Temperature Systems for the Detection and Identification of Radionuclides from Atmospheric Nuclear Test

Science.gov (United States)

2013-07-01

DTRA-TR-13-48 Low Power, Room Temperature Systems for the Detection and Identification of Radionuclides from Atmospheric Nuclear Test Approved for...01-C-0071 Radionuclides from Atmospheric Nuclear Tests 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Muren Chu...I IIlIl4eI ilf "tt""f;lk~ l).t::l’e.do)- mllin:: in an n-t~’J𔃻f mlllril.: II!’ ,-kll ~".r’I::!, ..... ·hkh j,-, .:auI,,·d br thP . la-ek f.r ·;IIff

Adaptive Ridge Point Refinement for Seeds Detection in X-Ray Coronary Angiogram

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Ruoxiu Xiao

2015-01-01

Full Text Available Seed point is prerequired condition for tracking based method for extracting centerline or vascular structures from the angiogram. In this paper, a novel seed point detection method for coronary artery segmentation is proposed. Vessels on the image are first enhanced according to the distribution of Hessian eigenvalue in multiscale space; consequently, centerlines of tubular vessels are also enhanced. Ridge point is extracted as candidate seed point, which is then refined according to its mathematical definition. The theoretical feasibility of this method is also proven. Finally, all the detected ridge points are checked using a self-adaptive threshold to improve the robustness of results. Clinical angiograms are used to evaluate the performance of the proposed algorithm, and the results show that the proposed algorithm can detect a large set of true seed points located on most branches of vessels. Compared with traditional seed point detection algorithms, the proposed method can detect a larger number of seed points with higher precision. Considering that the proposed method can achieve accurate seed detection without any human interaction, it can be utilized for several clinical applications, such as vessel segmentation, centerline extraction, and topological identification.

Experiment design for identification of structured linear systems

NARCIS (Netherlands)

Potters, M.G.

2016-01-01

Experiment Design for system identification involves the design of an optimal input signal with the purpose of accurately estimating unknown parameters in a system. Specifically, in the Least-Costly Experiment Design (LCED) framework, the optimal input signal results from an optimisation problem in

Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent

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Cruz-Roa, Angel; Gilmore, Hannah; Basavanhally, Ajay; Feldman, Michael; Ganesan, Shridar; Shih, Natalie N. C.; Tomaszewski, John; González, Fabio A.; Madabhushi, Anant

2017-04-01

With the increasing ability to routinely and rapidly digitize whole slide images with slide scanners, there has been interest in developing computerized image analysis algorithms for automated detection of disease extent from digital pathology images. The manual identification of presence and extent of breast cancer by a pathologist is critical for patient management for tumor staging and assessing treatment response. However, this process is tedious and subject to inter- and intra-reader variability. For computerized methods to be useful as decision support tools, they need to be resilient to data acquired from different sources, different staining and cutting protocols and different scanners. The objective of this study was to evaluate the accuracy and robustness of a deep learning-based method to automatically identify the extent of invasive tumor on digitized images. Here, we present a new method that employs a convolutional neural network for detecting presence of invasive tumor on whole slide images. Our approach involves training the classifier on nearly 400 exemplars from multiple different sites, and scanners, and then independently validating on almost 200 cases from The Cancer Genome Atlas. Our approach yielded a Dice coefficient of 75.86%, a positive predictive value of 71.62% and a negative predictive value of 96.77% in terms of pixel-by-pixel evaluation compared to manually annotated regions of invasive ductal carcinoma.

Performance metrics for the evaluation of hyperspectral chemical identification systems

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Truslow, Eric; Golowich, Steven; Manolakis, Dimitris; Ingle, Vinay

2016-02-01

Remote sensing of chemical vapor plumes is a difficult but important task for many military and civilian applications. Hyperspectral sensors operating in the long-wave infrared regime have well-demonstrated detection capabilities. However, the identification of a plume's chemical constituents, based on a chemical library, is a multiple hypothesis testing problem which standard detection metrics do not fully describe. We propose using an additional performance metric for identification based on the so-called Dice index. Our approach partitions and weights a confusion matrix to develop both the standard detection metrics and identification metric. Using the proposed metrics, we demonstrate that the intuitive system design of a detector bank followed by an identifier is indeed justified when incorporating performance information beyond the standard detection metrics.

An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1.

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Sergei L Kosakovsky Pond

2009-11-01

Full Text Available Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1 are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (approximately 5% fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance

Stress, interviewer support, and children's eyewitness identification accuracy.

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Rush, Elizabeth B; Quas, Jodi A; Yim, Ilona S; Nikolayev, Mariya; Clark, Steven E; Larson, Rakel P

2014-01-01

Few studies have investigated how stress affects eyewitness identification capabilities across development, and no studies have investigated whether retrieval context in conjunction with stress affects accuracy. In this study, one hundred fifty-nine 7- to 8- and 12- to 14-year-olds completed a high- or low-stress laboratory protocol during which they interacted with a confederate. Two weeks later, they attempted to identify the confederate in a photographic lineup. The lineup administrator behaved in either a supportive or a nonsupportive manner. Participants who experienced the high-stress event and were questioned by a supportive interviewer were most accurate in rejecting target-absent lineups. Results have implications for debates about effects of stress on eyewitness recall, how best to elicit accurate identifications in children, and developmental changes in episodic mnemonic processes. © 2013 The Authors. Child Development © 2013 Society for Research in Child Development, Inc.

Genetic species identification in weatherfish and first molecular confirmation of Oriental Weatherfish Misgurnus anguillicaudatus (Cantor, 1842 in Central Europe

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Belle Christina C.

2017-01-01

Full Text Available The Oriental Weatherfish is considered a globally invasive fish species. In Europe, several reported feral populations of Oriental Weatherfish display an overlapping distribution range with native weatherfish Misgurnus fossilis, a declining species of international conservation and aquatic management concern. Morphologically distinguishing the different weatherfish species can be difficult, as their coloration is highly variable, many species reveal high phenotypic plasticity, and morphological traits like coloration might be not obvious or might be degraded during field sampling and after preservation. Herein, we analysed suspicious weatherfish specimens from southern Germany, demonstrating the usefulness of molecular genetic species identifications in this genus. We present the first molecular genetic species record of Misgurnus anguillicaudatus in Central Europe, and confirm the range expansion of Oriental Weatherfish into the river Inn catchment in southern Germany. As accurate species identification is crucial both in the context of monitoring and conserving native endangered species, and in early detection and prevention of biological invasion, we suggest the standard use of genetic species identification if morphological traits are not obvious.

Correlation dynamics and enhanced signals for the identification of serial biomolecules and DNA bases

International Nuclear Information System (INIS)

Ahmed, Towfiq; Haraldsen, Jason T; Balatsky, Alexander V; Rehr, John J; Di Ventra, Massimiliano; Schuller, Ivan

2014-01-01

Nanopore-based sequencing has demonstrated a significant potential for the development of fast, accurate, and cost-efficient fingerprinting techniques for next generation molecular detection and sequencing. We propose a specific multilayered graphene-based nanopore device architecture for the recognition of single biomolecules. Molecular detection and analysis can be accomplished through the detection of transverse currents as the molecule or DNA base translocates through the nanopore. To increase the overall signal-to-noise ratio and the accuracy, we implement a new ‘multi-point cross-correlation’ technique for identification of DNA bases or other molecules on the single molecular level. We demonstrate that the cross-correlations between each nanopore will greatly enhance the transverse current signal for each molecule. We implement first-principles transport calculations for DNA bases surveyed across a multilayered graphene nanopore system to illustrate the advantages of the proposed geometry. A time-series analysis of the cross-correlation functions illustrates the potential of this method for enhancing the signal-to-noise ratio. This work constitutes a significant step forward in facilitating fingerprinting of single biomolecules using solid state technology. (paper)

Correlation dynamics and enhanced signals for the identification of serial biomolecules and DNA bases

Science.gov (United States)

Ahmed, Towfiq; Haraldsen, Jason T.; Rehr, John J.; Di Ventra, Massimiliano; Schuller, Ivan; Balatsky, Alexander V.

2014-03-01

Nanopore-based sequencing has demonstrated a significant potential for the development of fast, accurate, and cost-efficient fingerprinting techniques for next generation molecular detection and sequencing. We propose a specific multilayered graphene-based nanopore device architecture for the recognition of single biomolecules. Molecular detection and analysis can be accomplished through the detection of transverse currents as the molecule or DNA base translocates through the nanopore. To increase the overall signal-to-noise ratio and the accuracy, we implement a new ‘multi-point cross-correlation’ technique for identification of DNA bases or other molecules on the single molecular level. We demonstrate that the cross-correlations between each nanopore will greatly enhance the transverse current signal for each molecule. We implement first-principles transport calculations for DNA bases surveyed across a multilayered graphene nanopore system to illustrate the advantages of the proposed geometry. A time-series analysis of the cross-correlation functions illustrates the potential of this method for enhancing the signal-to-noise ratio. This work constitutes a significant step forward in facilitating fingerprinting of single biomolecules using solid state technology.