Accurately estimating PSF with straight lines detected by Hough transform

NASA Astrophysics Data System (ADS)

Wang, Ruichen; Xu, Liangpeng; Fan, Chunxiao; Li, Yong

2018-04-01

This paper presents an approach to estimating point spread function (PSF) from low resolution (LR) images. Existing techniques usually rely on accurate detection of ending points of the profile normal to edges. In practice however, it is often a great challenge to accurately localize profiles of edges from a LR image, which hence leads to a poor PSF estimation of the lens taking the LR image. For precisely estimating the PSF, this paper proposes firstly estimating a 1-D PSF kernel with straight lines, and then robustly obtaining the 2-D PSF from the 1-D kernel by least squares techniques and random sample consensus. Canny operator is applied to the LR image for obtaining edges and then Hough transform is utilized to extract straight lines of all orientations. Estimating 1-D PSF kernel with straight lines effectively alleviates the influence of the inaccurate edge detection on PSF estimation. The proposed method is investigated on both natural and synthetic images for estimating PSF. Experimental results show that the proposed method outperforms the state-ofthe- art and does not rely on accurate edge detection.

Novel Methods at Molecular Level for Neurotoxicity Testing in 21st Century-Utility of Structure-Activity Relationship

EPA Science Inventory

Current neurotoxicity and developmental neurotoxicity testing methods for hazard identification rely on in vivo neurobehavior, neurophysiological, and gross pathology of the nervous system. These measures may not be sensitive enough to detect small changes caused by realistic ex...

Real time algorithms for sharp wave ripple detection.

PubMed

Sethi, Ankit; Kemere, Caleb

2014-01-01

Neural activity during sharp wave ripples (SWR), short bursts of co-ordinated oscillatory activity in the CA1 region of the rodent hippocampus, is implicated in a variety of memory functions from consolidation to recall. Detection of these events in an algorithmic framework, has thus far relied on simple thresholding techniques with heuristically derived parameters. This study is an investigation into testing and improving the current methods for detection of SWR events in neural recordings. We propose and profile methods to reduce latency in ripple detection. Proposed algorithms are tested on simulated ripple data. The findings show that simple realtime algorithms can improve upon existing power thresholding methods and can detect ripple activity with latencies in the range of 10-20 ms.

Novel Methods at Molecular Level for Developmental Neurotoxicity Testing in 21st Century-Utility of Structure-Activity Relationship

EPA Science Inventory

Current neurotoxicity and developmental neurotoxicity testing methods for hazard identification rely on in vivo neurobehavior, neurophysiological, and gross pathology of the nervous system. These measures may not be sensitive enough to detect small changes caused by realistic ex...

A scale-invariant change detection method for land use/cover change research

NASA Astrophysics Data System (ADS)

Xing, Jin; Sieber, Renee; Caelli, Terrence

2018-07-01

Land Use/Cover Change (LUCC) detection relies increasingly on comparing remote sensing images with different spatial and spectral scales. Based on scale-invariant image analysis algorithms in computer vision, we propose a scale-invariant LUCC detection method to identify changes from scale heterogeneous images. This method is composed of an entropy-based spatial decomposition, two scale-invariant feature extraction methods, Maximally Stable Extremal Region (MSER) and Scale-Invariant Feature Transformation (SIFT) algorithms, a spatial regression voting method to integrate MSER and SIFT results, a Markov Random Field-based smoothing method, and a support vector machine classification method to assign LUCC labels. We test the scale invariance of our new method with a LUCC case study in Montreal, Canada, 2005-2012. We found that the scale-invariant LUCC detection method provides similar accuracy compared with the resampling-based approach but this method avoids the LUCC distortion incurred by resampling.

Inter-observer variation in identifying mammals from their tracks at enclosed track plate stations

Treesearch

William J. Zielinski; Fredrick V. Schlexer

2009-01-01

Enclosed track plate stations are a common method to detect mammalian carnivores. Studies rely on these data to make inferences about geographic range, population status and detectability. Despite their popularity, there has been no effort to document inter-observer variation in identifying the species that leave their tracks. Four previous field crew leaders...

A Simple Method to Simultaneously Detect and Identify Spikes from Raw Extracellular Recordings.

PubMed

Petrantonakis, Panagiotis C; Poirazi, Panayiota

2015-01-01

The ability to track when and which neurons fire in the vicinity of an electrode, in an efficient and reliable manner can revolutionize the neuroscience field. The current bottleneck lies in spike sorting algorithms; existing methods for detecting and discriminating the activity of multiple neurons rely on inefficient, multi-step processing of extracellular recordings. In this work, we show that a single-step processing of raw (unfiltered) extracellular signals is sufficient for both the detection and identification of active neurons, thus greatly simplifying and optimizing the spike sorting approach. The efficiency and reliability of our method is demonstrated in both real and simulated data.

Detection of dopamine in dopaminergic cell using nanoparticles-based barcode DNA analysis.

PubMed

An, Jeung Hee; Kim, Tae-Hyung; Oh, Byung-Keun; Choi, Jeong Woo

2012-01-01

Nanotechnology-based bio-barcode-amplification analysis may be an innovative approach to dopamine detection. In this study, we evaluated the efficacy of this bio-barcode DNA method in detecting dopamine from dopaminergic cells. Herein, a combination DNA barcode and bead-based immunoassay for neurotransmitter detection with PCR-like sensitivity is described. This method relies on magnetic nanoparticles with antibodies and nanoparticles that are encoded with DNA, and antibodies that can sandwich the target protein captured by the nanoparticle-bound antibodies. The aggregate sandwich structures are magnetically separated from solution, and treated in order to remove the conjugated barcode DNA. The DNA barcodes were then identified via PCR analysis. The dopamine concentration in dopaminergic cells can be readily and rapidly detected via the bio-barcode assay method. The bio-barcode assay method is, therefore, a rapid and high-throughput screening tool for the detection of neurotransmitters such as dopamine.

In-situ trainable intrusion detection system

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

Symons, Christopher T.; Beaver, Justin M.; Gillen, Rob

A computer implemented method detects intrusions using a computer by analyzing network traffic. The method includes a semi-supervised learning module connected to a network node. The learning module uses labeled and unlabeled data to train a semi-supervised machine learning sensor. The method records events that include a feature set made up of unauthorized intrusions and benign computer requests. The method identifies at least some of the benign computer requests that occur during the recording of the events while treating the remainder of the data as unlabeled. The method trains the semi-supervised learning module at the network node in-situ, such thatmore » the semi-supervised learning modules may identify malicious traffic without relying on specific rules, signatures, or anomaly detection.« less

A review on detection methods used for foodborne pathogens

PubMed Central

Priyanka, B.; Patil, Rajashekhar K.; Dwarakanath, Sulatha

2016-01-01

Foodborne pathogens have been a cause of a large number of diseases worldwide and more so in developing countries. This has a major economic impact. It is important to contain them, and to do so, early detection is very crucial. Detection and diagnostics relied on culture-based methods to begin with and have developed in the recent past parallel to the developments towards immunological methods such as enzyme-linked immunosorbent assays (ELISA) and molecular biology-based methods such as polymerase chain reaction (PCR). The aim has always been to find a rapid, sensitive, specific and cost-effective method. Ranging from culturing of microbes to the futuristic biosensor technology, the methods have had this common goal. This review summarizes the recent trends and brings together methods that have been developed over the years. PMID:28139531

On detection of median filtering in digital images

NASA Astrophysics Data System (ADS)

Kirchner, Matthias; Fridrich, Jessica

2010-01-01

In digital image forensics, it is generally accepted that intentional manipulations of the image content are most critical and hence numerous forensic methods focus on the detection of such 'malicious' post-processing. However, it is also beneficial to know as much as possible about the general processing history of an image, including content-preserving operations, since they can affect the reliability of forensic methods in various ways. In this paper, we present a simple yet effective technique to detect median filtering in digital images-a widely used denoising and smoothing operator. As a great variety of forensic methods relies on some kind of a linearity assumption, a detection of non-linear median filtering is of particular interest. The effectiveness of our method is backed with experimental evidence on a large image database.

Batch methods for enriching trace impurities in hydrogen gas for their further analysis

DOEpatents

Ahmed, Shabbir; Lee, Sheldon H.D.; Kumar, Romesh; Papdias, Dionissios D.

2014-07-15

Provided herein are batch methods and devices for enriching trace quantities of impurities in gaseous mixtures, such as hydrogen fuel. The methods and devices rely on concentrating impurities using hydrogen transport membranes wherein the time period for concentrating the sample is calculated on the basis of optimized membrane characteristics, comprising its thickness and permeance, with optimization of temperature, and wherein the enrichment of trace impurities is proportional to the pressure ratio P.sub.hi/P.sub.lo and the volume ratio V.sub.1/V.sub.2, with following detection of the impurities using commonly-available detection methods.

Microbial Source Tracking Markers for Detection of Fecal Contamination in Environmental Waters: Relationships Between Pathogens and Human Health Outcomes

EPA Science Inventory

Microbial source tracking (MST) describes a suite of methods and an investigative strategy designed to identify the dominant sources of fecal pollution in environmental waters. The methods rely on the close association of certain fecal microorganisms with a particular host speci...

Figures of merit for detectors in digital radiography. II. Finite number of secondaries and structured backgrounds.

PubMed

Pineda, Angel R; Barrett, Harrison H

2004-02-01

The current paradigm for evaluating detectors in digital radiography relies on Fourier methods. Fourier methods rely on a shift-invariant and statistically stationary description of the imaging system. The theoretical justification for the use of Fourier methods is based on a uniform background fluence and an infinite detector. In practice, the background fluence is not uniform and detector size is finite. We study the effect of stochastic blurring and structured backgrounds on the correlation between Fourier-based figures of merit and Hotelling detectability. A stochastic model of the blurring leads to behavior similar to what is observed by adding electronic noise to the deterministic blurring model. Background structure does away with the shift invariance. Anatomical variation makes the covariance matrix of the data less amenable to Fourier methods by introducing long-range correlations. It is desirable to have figures of merit that can account for all the sources of variation, some of which are not stationary. For such cases, we show that the commonly used figures of merit based on the discrete Fourier transform can provide an inaccurate estimate of Hotelling detectability.

A Method of Face Detection with Bayesian Probability

NASA Astrophysics Data System (ADS)

Sarker, Goutam

2010-10-01

The objective of face detection is to identify all images which contain a face, irrespective of its orientation, illumination conditions etc. This is a hard problem, because the faces are highly variable in size, shape lighting conditions etc. Many methods have been designed and developed to detect faces in a single image. The present paper is based on one `Appearance Based Method' which relies on learning the facial and non facial features from image examples. This in its turn is based on statistical analysis of examples and counter examples of facial images and employs Bayesian Conditional Classification Rule to detect the probability of belongingness of a face (or non-face) within an image frame. The detection rate of the present system is very high and thereby the number of false positive and false negative detection is substantially low.

Detection of HIV-1 p24 Gag in plasma by a nanoparticle-based bio-barcode-amplification method.

PubMed

Kim, Eun-Young; Stanton, Jennifer; Korber, Bette T M; Krebs, Kendall; Bogdan, Derek; Kunstman, Kevin; Wu, Samuel; Phair, John P; Mirkin, Chad A; Wolinsky, Steven M

2008-06-01

Detection of HIV-1 in patients is limited by the sensitivity and selectivity of available tests. The nanotechnology-based bio-barcode-amplification method offers an innovative approach to detect specific HIV-1 antigens from diverse HIV-1 subtypes. We evaluated the efficacy of this protein-detection method in detecting HIV-1 in men enrolled in the Chicago component of the Multicenter AIDS Cohort Study (MACS). The method relies on magnetic microparticles with antibodies that specifically bind the HIV-1 p24 Gag protein and nanoparticles that are encoded with DNA and antibodies that can sandwich the target protein captured by the microparticle-bound antibodies. The aggregate sandwich structures are magnetically separated from solution, and treated to remove the conjugated barcode DNA. The DNA barcodes (hundreds per target) were identified by a nanoparticle-based detection method that does not rely on PCR. Of 112 plasma samples from HIV-1-infected subjects, 111 were positive for HIV-1 p24 Gag protein (range: 0.11-71.5 ng/ml of plasma) by the bio-barcode-amplification method. HIV-1 p24 Gag protein was detected in only 23 out of 112 men by the conventional ELISA. A total of 34 uninfected subjects were negative by both tests. Thus, the specificity of the bio-barcode-amplification method was 100% and the sensitivity 99%. The bio-barcode-amplification method detected HIV-1 p24 Gag protein in plasma from all study subjects with less than 200 CD4(+) T cells/microl of plasma (100%) and 19 out of 20 (95%) HIV-1-infected men who had less than 50 copies/ml of plasma of HIV-1 RNA. In a separate group of 60 diverse international isolates, representative of clades A, B, C and D and circulating recombinant forms CRF01_AE and CRF02_AG, the bio-barcode-amplification method identified the presence of virus correctly. The bio-barcode-amplification method was superior to the conventional ELISA assay for the detection of HIV-1 p24 Gag protein in plasma with a breadth of coverage for diverse HIV-1 subtypes. Because the bio-barcode-amplification method does not require enzymatic amplification, this method could be translated into a robust point-of-care test.

Distance-based microfluidic quantitative detection methods for point-of-care testing.

PubMed

Tian, Tian; Li, Jiuxing; Song, Yanling; Zhou, Leiji; Zhu, Zhi; Yang, Chaoyong James

2016-04-07

Equipment-free devices with quantitative readout are of great significance to point-of-care testing (POCT), which provides real-time readout to users and is especially important in low-resource settings. Among various equipment-free approaches, distance-based visual quantitative detection methods rely on reading the visual signal length for corresponding target concentrations, thus eliminating the need for sophisticated instruments. The distance-based methods are low-cost, user-friendly and can be integrated into portable analytical devices. Moreover, such methods enable quantitative detection of various targets by the naked eye. In this review, we first introduce the concept and history of distance-based visual quantitative detection methods. Then, we summarize the main methods for translation of molecular signals to distance-based readout and discuss different microfluidic platforms (glass, PDMS, paper and thread) in terms of applications in biomedical diagnostics, food safety monitoring, and environmental analysis. Finally, the potential and future perspectives are discussed.

A NEW SW-846 METHOD FOR THE ANALYSIS OF TOXAPHENE AND TOXAPHENE CONGENERS IN SOLID AND AQUEOUS SAMPLES USING GAS CHROMATOGRAPHY / NEGATIVE ION MASS SPECTROMETRY

EPA Science Inventory

US EPA SW-846 methods have typically relied on dual column gas chromatography coupled with electron capture detection (GC-ECD) for analysis of low concentrations of organochlorine pesticides, including toxaphene, in environmental samples. Toxaphene is one of the most widely appl...

Detection of Inter-chromosomal Stable Aberrations by Multiple Fluorescence In Situ Hybridization (mFISH) and Spectral Karyotyping (SKY) in Irradiated Mice

PubMed Central

Pathak, Rupak; Koturbash, Igor; Hauer-Jensen, Martin

2017-01-01

Ionizing radiation (IR) induces numerous stable and unstable chromosomal aberrations. Unstable aberrations, where chromosome morphology is substantially compromised, can easily be identified by conventional chromosome staining techniques. However, detection of stable aberrations, which involve exchange or translocation of genetic materials without considerable modification in the chromosome morphology, requires sophisticated chromosome painting techniques that rely on in situ hybridization of fluorescently labeled DNA probes, a chromosome painting technique popularly known as fluorescence in situ hybridization (FISH). FISH probes can be specific for whole chromosome/s or precise sub-region on chromosome/s. The method not only allows visualization of stable aberrations, but it can also allow detection of the chromosome/s or specific DNA sequence/s involved in a particular aberration formation. A variety of chromosome painting techniques are available in cytogenetics; here two highly sensitive methods, multiple fluorescence in situ hybridization (mFISH) and spectral karyotyping (SKY), are discussed to identify inter-chromosomal stable aberrations that form in the bone marrow cells of mice after exposure to total body irradiation. Although both techniques rely on fluorescent labeled DNA probes, the method of detection and the process of image acquisition of the fluorescent signals are different. These two techniques have been used in various research areas, such as radiation biology, cancer cytogenetics, retrospective radiation biodosimetry, clinical cytogenetics, evolutionary cytogenetics, and comparative cytogenetics. PMID:28117817

Traffic Sign Detection System for Locating Road Intersections and Roundabouts: The Chilean Case.

PubMed

Villalón-Sepúlveda, Gabriel; Torres-Torriti, Miguel; Flores-Calero, Marco

2017-05-25

This paper presents a traffic sign detection method for signs close to road intersections and roundabouts, such as stop and yield (give way) signs. The proposed method relies on statistical templates built using color information for both segmentation and classification. The segmentation method uses the RGB-normalized (ErEgEb) color space for ROIs (Regions of Interest) generation based on a chromaticity filter, where templates at 10 scales are applied to the entire image. Templates consider the mean and standard deviation of normalized color of the traffic signs to build thresholding intervals where the expected color should lie for a given sign. The classification stage employs the information of the statistical templates over YCbCr and ErEgEb color spaces, for which the background has been previously removed by using a probability function that models the probability that the pixel corresponds to a sign given its chromaticity values. This work includes an analysis of the detection rate as a function of the distance between the vehicle and the sign. Such information is useful to validate the robustness of the approach and is often not included in the existing literature. The detection rates, as a function of distance, are compared to those of the well-known Viola-Jones method. The results show that for distances less than 48 m, the proposed method achieves a detection rate of 87.5 % and 95.4 % for yield and stop signs, respectively. For distances less than 30 m, the detection rate is 100 % for both signs. The Viola-Jones approach has detection rates below 20 % for distances between 30 and 48 m, and barely improves in the 20-30 m range with detection rates of up to 60 % . Thus, the proposed method provides a robust alternative for intersection detection that relies on statistical color-based templates instead of shape information. The experiments employed videos of traffic signs taken in several streets of Santiago, Chile, using a research platform implemented at the Robotics and Automation Laboratory of PUC to develop driver assistance systems.

Traffic Sign Detection System for Locating Road Intersections and Roundabouts: The Chilean Case

PubMed Central

Villalón-Sepúlveda, Gabriel; Torres-Torriti, Miguel; Flores-Calero, Marco

2017-01-01

This paper presents a traffic sign detection method for signs close to road intersections and roundabouts, such as stop and yield (give way) signs. The proposed method relies on statistical templates built using color information for both segmentation and classification. The segmentation method uses the RGB-normalized (ErEgEb) color space for ROIs (Regions of Interest) generation based on a chromaticity filter, where templates at 10 scales are applied to the entire image. Templates consider the mean and standard deviation of normalized color of the traffic signs to build thresholding intervals where the expected color should lie for a given sign. The classification stage employs the information of the statistical templates over YCbCr and ErEgEb color spaces, for which the background has been previously removed by using a probability function that models the probability that the pixel corresponds to a sign given its chromaticity values. This work includes an analysis of the detection rate as a function of the distance between the vehicle and the sign. Such information is useful to validate the robustness of the approach and is often not included in the existing literature. The detection rates, as a function of distance, are compared to those of the well-known Viola–Jones method. The results show that for distances less than 48 m, the proposed method achieves a detection rate of 87.5% and 95.4% for yield and stop signs, respectively. For distances less than 30 m, the detection rate is 100% for both signs. The Viola–Jones approach has detection rates below 20% for distances between 30 and 48 m, and barely improves in the 20–30 m range with detection rates of up to 60%. Thus, the proposed method provides a robust alternative for intersection detection that relies on statistical color-based templates instead of shape information. The experiments employed videos of traffic signs taken in several streets of Santiago, Chile, using a research platform implemented at the Robotics and Automation Laboratory of PUC to develop driver assistance systems. PMID:28587071

A Multi-Receptor and Multi-Species Assay for Potential Endocrine Disruptor Targets (SLAS meeting)

EPA Science Inventory

Screening methods for detecting potential endocrine disrupting chemicals rely chiefly on transactivation assays targeting nuclear receptors such as the estrogen (ER) and androgen receptors (AR). These assays are predominately human-based; yet environmental exposure can affect div...

Asymmetry identification in rigid rotating bodies—Theory and experiment

NASA Astrophysics Data System (ADS)

Bucher, Izhak; Shomer, Ofer

2013-12-01

Asymmetry and anisotropy are important parameters in rotating devices that can cause instability; indicate a manufacturing defect or a developing fault. The present paper discusses an identification method capable of detecting minute levels of asymmetry by exploiting the unique dynamics of parametric excitation caused by asymmetry and rotation. The detection relies on rigid body dynamics without resorting to nonlinear vibration analysis, and the natural dynamics of elastically supported systems is exploited in order to increase the sensitivity to asymmetry. It is possible to isolate asymmetry from other rotation-induced phenomena like unbalance. An asymmetry detection machine which was built in the laboratory demonstrates the method alongside theoretical analysis.

Vessel network detection using contour evolution and color components

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

Ushizima, Daniela; Medeiros, Fatima; Cuadros, Jorge

2011-06-22

Automated retinal screening relies on vasculature segmentation before the identification of other anatomical structures of the retina. Vasculature extraction can also be input to image quality ranking, neovascularization detection and image registration, among other applications. There is an extensive literature related to this problem, often excluding the inherent heterogeneity of ophthalmic clinical images. The contribution of this paper relies on an algorithm using front propagation to segment the vessel network. The algorithm includes a penalty in the wait queue on the fast marching heap to minimize leakage of the evolving interface. The method requires no manual labeling, a minimum numbermore » of parameters and it is capable of segmenting color ocular fundus images in real scenarios, where multi-ethnicity and brightness variations are parts of the problem.« less

Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks

PubMed Central

Walsh, Aaron M.; Crispie, Fiona; Daari, Kareem; O'Sullivan, Orla; Martin, Jennifer C.; Arthur, Cornelius T.; Claesson, Marcus J.; Scott, Karen P.

2017-01-01

ABSTRACT The rapid detection of pathogenic strains in food products is essential for the prevention of disease outbreaks. It has already been demonstrated that whole-metagenome shotgun sequencing can be used to detect pathogens in food but, until recently, strain-level detection of pathogens has relied on whole-metagenome assembly, which is a computationally demanding process. Here we demonstrated that three short-read-alignment-based methods, i.e., MetaMLST, PanPhlAn, and StrainPhlAn, could accurately and rapidly identify pathogenic strains in spinach metagenomes that had been intentionally spiked with Shiga toxin-producing Escherichia coli in a previous study. Subsequently, we employed the methods, in combination with other metagenomics approaches, to assess the safety of nunu, a traditional Ghanaian fermented milk product that is produced by the spontaneous fermentation of raw cow milk. We showed that nunu samples were frequently contaminated with bacteria associated with the bovine gut and, worryingly, we detected putatively pathogenic E. coli and Klebsiella pneumoniae strains in a subset of nunu samples. Ultimately, our work establishes that short-read-alignment-based bioinformatics approaches are suitable food safety tools, and we describe a real-life example of their utilization. IMPORTANCE Foodborne pathogens are responsible for millions of illnesses each year. Here we demonstrate that short-read-alignment-based bioinformatics tools can accurately and rapidly detect pathogenic strains in food products by using shotgun metagenomics data. The methods used here are considerably faster than both traditional culturing methods and alternative bioinformatics approaches that rely on metagenome assembly; therefore, they can potentially be used for more high-throughput food safety testing. Overall, our results suggest that whole-metagenome sequencing can be used as a practical food safety tool to prevent diseases or to link outbreaks to specific food products. PMID:28625983

Scalable Track Detection in SAR CCD Images

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

Chow, James G; Quach, Tu-Thach

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988,more » up fr om 0.907 obtained by the current state-of-the-art method.« less

RAPID DETECTION METHOD FOR E.COLI, ENTEROCOCCI AND BACTEROIDES IN RECREATIONAL WATER

EPA Science Inventory

Current methodology for determining fecal contamination of drinking water sources and recreational waters rely on the time-consuming process of bacterial multiplication and require at least 24 hours from the time of sampling to the possible determination that the water is unsafe ...

DETECTION OF 2,4-DICHLOROPHENOXYACETIC ACID USING A FLUORESCENCE IMMUNOANALYZER

EPA Science Inventory

A flow immunoassay method for the measurement of 2,4-dichlorophenoxyacetic acid (2,4-D) was developed. The competitive fluorescence immunoassay relies on the use of antibody- or antigen-coated poly(methyl methacrylate) particles (98 um diameter) as a renewable solid phase. The as...

A novel method for resonant inelastic soft X-ray scattering via photoelectron spectroscopy detection

DOE PAGES

Dakovski, Georgi L.; Lin, Ming-Fu; Damiani, Daniel S.; ...

2017-10-05

A method for measuring resonant inelastic X-ray scattering based on the conversion of X-ray photons into photoelectrons is presented in this paper. The setup is compact, relies on commercially available detectors, and offers significant flexibility. Finally, this method is demonstrated at the Linac Coherent Light Source with ~0.5 eV resolution at the cobalt L 3-edge, with signal rates comparable with traditional grating spectrometers.

N-glycosylation of plant recombinant pharmaceuticals.

PubMed

Bardor, Muriel; Cabrera, Gleysin; Stadlmann, Johannes; Lerouge, Patrice; Cremata, José A; Gomord, Véronique; Fitchette, Anne-Catherine

2009-01-01

N-glycosylation is a maturation event necessary for the correct function, efficiency, and stability of a high number of biopharmaceuticals. This chapter presented here proposes various methods to determine whether, how, and where a plant pharmaceutical is N-glycosylated. These methods rely on blot detection with glycan-specific probes, specific deglycosylation of glycoproteins followed by mass spectrometry, N-glycan profile analysis, and glycopeptide identification by LC-MS.

Label-free SERS detection of Salmonella Typhimurium on DNA aptamer modified AgNR substrates

USDA-ARS?s Scientific Manuscript database

Salmonella Typhimurium is an important foodborne pathogen which causes gastroenteritis in both humans and animals. Currently available rapid methods have relied on antibodies to offer specific recognition of the pathogen from the background. As a substitute of antibodies, nucleic acid aptamers offer...

Differentiation of volatile profiles of stockpiled almonds at varying relative humidity levels using benchtop and portable GC-MS

USDA-ARS?s Scientific Manuscript database

Contamination by aflatoxin, a toxic metabolite produced by Aspergillus fungi ubiquitous in California almond and pistachio orchards, results in millions of dollars of lost product annually. Current detection of aflatoxin relies on destructive, expensive and time-intensive laboratory-based methods. T...

TCR-Vß8 as alternative to animal testing for quantifying active SEE

USDA-ARS?s Scientific Manuscript database

Staphylococcal food poisoning is a result of ingestion of Staphylococcal enterotoxins (SEs) produced by the bacterium Staphylococcus aureus. SEs cause gastroenteritis and also cause activation of T cells and massive cytokine release. A current method for the detection of active SEs relies on its eme...

Testing the Rotation Stage in the ARIADNE Axion Experiment

NASA Astrophysics Data System (ADS)

Dargert, Jordan; Lohmeyer, Chloe; Harkness, Mindy; Cunningham, Mark; Fosbinder-Elkins, Harry; Geraci, Andrew; Ariadne Collaboration

2017-04-01

The Axion Resonant InterAction Detection Experiment (ARIADNE) will search for the Peccei-Quinn (PQ) axion, a hypothetical particle that is a dark matter candidate. Using a new technique based on Nuclear Magnetic Resonance, this new method can probe well into the allowed PQ axion mass range. Additionally, it does not rely on cosmological assumptions, meaning that the PQ Axion would be sourced locally. Our project relies on the stability of a rotating segmented source mass and superconducting magnetic shielding. Superconducting shielding is essential for limiting magnetic noise, thus allowing a feasible level of sensitivity required for PQ Axion detection. Progress on testing the stability of the rotary mechanism will be reported, and the design for the superconducting shielding in the experiment will be discussed, along with plans for moving the experiment forward. NSF Grant PHY-1509176.

Comparison of real-time PCR methods for the detection of Naegleria fowleri in surface water and sediment.

PubMed

Streby, Ashleigh; Mull, Bonnie J; Levy, Karen; Hill, Vincent R

2015-05-01

Naegleria fowleri is a thermophilic free-living ameba found in freshwater environments worldwide. It is the cause of a rare but potentially fatal disease in humans known as primary amebic meningoencephalitis. Established N. fowleri detection methods rely on conventional culture techniques and morphological examination followed by molecular testing. Multiple alternative real-time PCR assays have been published for rapid detection of Naegleria spp. and N. fowleri. Foursuch assays were evaluated for the detection of N. fowleri from surface water and sediment. The assays were compared for thermodynamic stability, analytical sensitivity and specificity, detection limits, humic acid inhibition effects, and performance with seeded environmental matrices. Twenty-one ameba isolates were included in the DNA panel used for analytical sensitivity and specificity analyses. N. fowleri genotypes I and III were used for method performance testing. Two of the real-time PCR assays were determined to yield similar performance data for specificity and sensitivity for detecting N. fowleri in environmental matrices.

Comparison of real-time PCR methods for the detection of Naegleria fowleri in surface water and sediment

PubMed Central

Streby, Ashleigh; Mull, Bonnie J.; Levy, Karen

2015-01-01

Naegleria fowleri is a thermophilic free-living ameba found in freshwater environments worldwide. It is the cause of a rare but potentially fatal disease in humans known as primary amebic meningoencephalitis. Established N. fowleri detection methods rely on conventional culture techniques and morphological examination followed by molecular testing. Multiple alternative real-time PCR assays have been published for rapid detection of Naegleria spp. and N. fowleri. Four such assays were evaluated for the detection of N. fowleri from surface water and sediment. The assays were compared for thermodynamic stability, analytical sensitivity and specificity, detection limits, humic acid inhibition effects, and performance with seeded environmental matrices. Twenty-one ameba isolates were included in the DNA panel used for analytical sensitivity and specificity analyses. N. fowleri genotypes I and III were used for method performance testing. Two of the real-time PCR assays were determined to yield similar performance data for specificity and sensitivity for detecting N. fowleri in environmental matrices. PMID:25855343

A Novel Method for Block Size Forensics Based on Morphological Operations

NASA Astrophysics Data System (ADS)

Luo, Weiqi; Huang, Jiwu; Qiu, Guoping

Passive forensics analysis aims to find out how multimedia data is acquired and processed without relying on pre-embedded or pre-registered information. Since most existing compression schemes for digital images are based on block processing, one of the fundamental steps for subsequent forensics analysis is to detect the presence of block artifacts and estimate the block size for a given image. In this paper, we propose a novel method for blind block size estimation. A 2×2 cross-differential filter is first applied to detect all possible block artifact boundaries, morphological operations are then used to remove the boundary effects caused by the edges of the actual image contents, and finally maximum-likelihood estimation (MLE) is employed to estimate the block size. The experimental results evaluated on over 1300 nature images show the effectiveness of our proposed method. Compared with existing gradient-based detection method, our method achieves over 39% accuracy improvement on average.

Molecular Techniques for the Detection and Differentiation of Host and Parasitoid Species and the Implications for Fruit Fly Management

PubMed Central

Jenkins, Cheryl; Chapman, Toni A.; Micallef, Jessica L.; Reynolds, Olivia L.

2012-01-01

Parasitoid detection and identification is a necessary step in the development and implementation of fruit fly biological control strategies employing parasitoid augmentive release. In recent years, DNA-based methods have been used to identify natural enemies of pest species where morphological differentiation is problematic. Molecular techniques also offer a considerable advantage over traditional morphological methods of fruit fly and parasitoid discrimination as well as within-host parasitoid identification, which currently relies on dissection of immature parasitoids from the host, or lengthy and labour-intensive rearing methods. Here we review recent research focusing on the use of molecular strategies for fruit fly and parasitoid detection and differentiation and discuss the implications of these studies on fruit fly management. PMID:26466628

Facile Determination of Sodium Ion and Osmolarity in Artificial Tears by Sequential DNAzymes.

PubMed

Kim, Eun Hye; Lee, Eun-Song; Lee, Dong Yun; Kim, Young-Pil

2017-12-07

Despite high relevance of tear osmolarity and eye abnormality, numerous methods for detecting tear osmolarity rely upon expensive osmometers. We report a reliable method for simply determining sodium ion-based osmolarity in artificial tears using sequential DNAzymes. When sodium ion-specific DNAzyme and peroxidase-like DNAzyme were used as a sensing and detecting probe, respectively, the concentration of Na⁺ in artificial tears could be measured by absorbance or fluorescence intensity, which was highly correlated with osmolarity over the diagnostic range ( R ² > 0.98). Our approach is useful for studying eye diseases in relation to osmolarity.

Supercontinuum Fourier transform spectrometry with balanced detection on a single photodiode

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

Goncharov, Vasily; Hall, Gregory

Here, we have developed phase-sensitive signal detection and processing algorithms for Fourier transform spectrometers fitted with supercontinuum sources for applications requiring ultimate sensitivity. Similar to well-established approach of source noise cancellation through balanced detection of monochromatic light, our method is capable of reducing the relative intensity noise of polychromatic light by 40 dB. Unlike conventional balanced detection, which relies on differential absorption measured with a well matched pair of photo-detectors, our algorithm utilizes phase-sensitive differential detection on a single photodiode and is capable of the real-time correction for instabilities in supercontinuum spectral structure over a broad range of wavelengths. Inmore » the resulting method is universal in terms of applicable wavelengths and compatible with commercial spectrometers. We present a proof-of-principle experimental« less

Supercontinuum Fourier transform spectrometry with balanced detection on a single photodiode

DOE PAGES

Goncharov, Vasily; Hall, Gregory

2016-08-25

Here, we have developed phase-sensitive signal detection and processing algorithms for Fourier transform spectrometers fitted with supercontinuum sources for applications requiring ultimate sensitivity. Similar to well-established approach of source noise cancellation through balanced detection of monochromatic light, our method is capable of reducing the relative intensity noise of polychromatic light by 40 dB. Unlike conventional balanced detection, which relies on differential absorption measured with a well matched pair of photo-detectors, our algorithm utilizes phase-sensitive differential detection on a single photodiode and is capable of the real-time correction for instabilities in supercontinuum spectral structure over a broad range of wavelengths. Inmore » the resulting method is universal in terms of applicable wavelengths and compatible with commercial spectrometers. We present a proof-of-principle experimental« less

Extended linear detection range for optical tweezers using image-plane detection scheme

NASA Astrophysics Data System (ADS)

Hajizadeh, Faegheh; Masoumeh Mousavi, S.; Khaksar, Zeinab S.; Reihani, S. Nader S.

2014-10-01

Ability to measure pico- and femto-Newton range forces using optical tweezers (OT) strongly relies on the sensitivity of its detection system. We show that the commonly used back-focal-plane detection method provides a linear response range which is shorter than that of the restoring force of OT for large beads. This limits measurable force range of OT. We show, both theoretically and experimentally, that utilizing a second laser beam for tracking could solve the problem. We also propose a new detection scheme in which the quadrant photodiode is positioned at the plane optically conjugate to the object plane (image plane). This method solves the problem without need for a second laser beam for the bead sizes that are commonly used in force spectroscopy applications of OT, such as biopolymer stretching.

Gold Nanoparticles-Based Barcode Analysis for Detection of Norepinephrine.

PubMed

An, Jeung Hee; Lee, Kwon-Jai; Choi, Jeong-Woo

2016-02-01

Nanotechnology-based bio-barcode amplification analysis offers an innovative approach for detecting neurotransmitters. We evaluated the efficacy of this method for detecting norepinephrine in normal and oxidative-stress damaged dopaminergic cells. Our approach use a combination of DNA barcodes and bead-based immunoassays for detecting neurotransmitters with surface-enhanced Raman spectroscopy (SERS), and provides polymerase chain reaction (PCR)-like sensitivity. This method relies on magnetic Dynabeads containing antibodies and nanoparticles that are loaded both with DNA barcords and with antibodies that can sandwich the target protein captured by the Dynabead-bound antibodies. The aggregate sandwich structures are magnetically separated from the solution and treated to remove the conjugated barcode DNA. The DNA barcodes are then identified by SERS and PCR analysis. The concentration of norepinephrine in dopaminergic cells can be readily detected using the bio-barcode assay, which is a rapid, high-throughput screening tool for detecting neurotransmitters.

A parametric symmetry breaking transducer

NASA Astrophysics Data System (ADS)

Eichler, Alexander; Heugel, Toni L.; Leuch, Anina; Degen, Christian L.; Chitra, R.; Zilberberg, Oded

2018-06-01

Force detectors rely on resonators to transduce forces into a readable signal. Usually, these resonators operate in the linear regime and their signal appears amidst a competing background comprising thermal or quantum fluctuations as well as readout noise. Here, we demonstrate a parametric symmetry breaking transduction method that leads to a robust nonlinear force detection in the presence of noise. The force signal is encoded in the frequency at which the system jumps between two phase states which are inherently protected against phase noise. Consequently, the transduction effectively decouples from readout noise channels. For a controlled demonstration of the method, we experiment with a macroscopic doubly clamped string. Our method provides a promising paradigm for high-precision force detection.

Improving Control System Cyber-State Awareness using Known Secure Sensor Measurements

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

Ondrej Linda; Milos Manic; Miles McQueen

Abstract—This paper presents design and simulation of a low cost and low false alarm rate method for improved cyber-state awareness of critical control systems - the Known Secure Sensor Measurements (KSSM) method. The KSSM concept relies on physical measurements to detect malicious falsification of the control systems state. The KSSM method can be incrementally integrated with already installed control systems for enhanced resilience. This paper reviews the previously developed theoretical KSSM concept and then describes a simulation of the KSSM system. A simulated control system network is integrated with the KSSM components. The effectiveness of detection of various intrusion scenariosmore » is demonstrated on several control system network topologies.« less

Combining RTI and Psychoeducational Assessment: What We Must Assume to Do Otherwise

ERIC Educational Resources Information Center

Wodrich, David L.; Spencer, Marsha L. S.; Daley, Kelly B.

2006-01-01

The Individuals With Disabilities Education Improvement Act of 2004 (IDEA; 2004) permitted lack of students' response to intervention (RTI) to be considered as a basis for documenting specific learning disabilities (SLD). The previous method of detecting SLD, which relied on IQ and achievement testing, consequently is no longer mandatory.…

Highly Accurate Antibody Assays for Early and Rapid Detection of Tuberculosis in African and Asian Elephants

USDA-ARS?s Scientific Manuscript database

Tuberculosis (TB) in elephants is a re-emerging zoonotic disease caused primarily by Mycobacterium tuberculosis. Current methods for screening and diagnosis rely on trunk wash culture, which has serious limitations due to low test sensitivity, slow turn-around time, and variable sample quality. Inn...

A New Forensic Picture Polygraph Technique for Terrorist and Crime Deception System

ERIC Educational Resources Information Center

Costello, R. H. Brian; Axton, JoAnn; Gold, Karen L.

2006-01-01

The Forensic Terrorist Detection System called Pinocchio Assessment Profile (PAP) employs standard issue polygraphs for a non-verbal picture technique originated as a biofeedback careers interest instrument. The system can be integrated readily into airport screening protocols. However, the method does not rely on questioning or foreign language…

AN ENVIRONMENTAL TECHNOLOGY VERIFICATION (ETV) TESTING OF THREE IMMUNOASSAY TEST KITS FOR ANTHRAX, BOTULINUM TOXIN AND RICIN

EPA Science Inventory

Immunoassay test kits are based on immunoassay methods, where specific antibodies are used to detect and measure the contaminants of interest. Immunoassay test kits rely on the reaction of a contaminant or antigen with a selective antibody to give a product that can be measures....

Rapid detection of Naegleria fowleri in water distribution pipeline biofilms and drinking water samples.

PubMed

Puzon, Geoffrey J; Lancaster, James A; Wylie, Jason T; Plumb, Iason J

2009-09-01

Rapid detection of pathogenic Naegleria fowler in water distribution networks is critical for water utilities. Current detection methods rely on sampling drinking water followed by culturing and molecular identification of purified strains. This culture-based method takes an extended amount of time (days), detects both nonpathogenic and pathogenic species, and does not account for N. fowleri cells associated with pipe wall biofilms. In this study, a total DNA extraction technique coupled with a real-time PCR method using primers specific for N. fowleri was developed and validated. The method readily detected N. fowleri without preculturing with the lowest detection limit for N. fowleri cells spiked in biofilm being one cell (66% detection rate) and five cells (100% detection rate). For drinking water, the detection limit was five cells (66% detection rate) and 10 cells (100% detection rate). By comparison, culture-based methods were less sensitive for detection of cells spiked into both biofilm (66% detection for <10 cells) and drinking water (0% detection for <10 cells). In mixed cultures of N. fowleri and nonpathogenic Naegleria, the method identified N. fowleri in 100% of all replicates, whereastests with the current consensus primers detected N. fowleri in only 5% of all replicates. Application of the new method to drinking water and pipe wall biofilm samples obtained from a distribution network enabled the detection of N. fowleri in under 6 h, versus 3+ daysforthe culture based method. Further, comparison of the real-time PCR data from the field samples and the standard curves enabled an approximation of N. fowleri cells in the biofilm and drinking water. The use of such a method will further aid water utilities in detecting and managing the persistence of N. fowleri in water distribution networks.

Multi-Frame Convolutional Neural Networks for Object Detection in Temporal Data

DTIC Science & Technology

2017-03-01

maximum 200 words) Given the problem of detecting objects in video , existing neural-network solutions rely on a post-processing step to combine...information across frames and strengthen conclusions. This technique has been successful for videos with simple, dominant objects but it cannot detect objects...Computer Science iii THIS PAGE INTENTIONALLY LEFT BLANK iv ABSTRACT Given the problem of detecting objects in video , existing neural-network solutions rely

RETROSPECTIVE DETECTION OF INTERLEAVED SLICE ACQUISITION PARAMETERS FROM FMRI DATA

PubMed Central

Parker, David; Rotival, Georges; Laine, Andrew; Razlighi, Qolamreza R.

2015-01-01

To minimize slice excitation leakage to adjacent slices, interleaved slice acquisition is nowadays performed regularly in fMRI scanners. In interleaved slice acquisition, the number of slices skipped between two consecutive slice acquisitions is often referred to as the ‘interleave parameter’; the loss of this parameter can be catastrophic for the analysis of fMRI data. In this article we present a method to retrospectively detect the interleave parameter and the axis in which it is applied. Our method relies on the smoothness of the temporal-distance correlation function, which becomes disrupted along the axis on which interleaved slice acquisition is applied. We examined this method on simulated and real data in the presence of fMRI artifacts such as physiological noise, motion, etc. We also examined the reliability of this method in detecting different types of interleave parameters and demonstrated an accuracy of about 94% in more than 1000 real fMRI scans. PMID:26161244

Detection, identification and differentiation of Pectobacterium and Dickeya species causing potato blackleg and tuber soft rot: a review

PubMed Central

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. PMID:25684775

Radiative transfer modeling and analysis of spatially variant and coherent illumination for undersea object detection

NASA Astrophysics Data System (ADS)

Bailey, Bernard Charles

Increasing the optical range of target detection and recognition continues to be an area of great interest in the ocean environment. Light attenuation limits radiative and information transfer for image formation in water. These limitations are difficult to surmount in conventional underwater imaging system design. Methods for the formation of images in scattering media generally rely upon temporal or spatial methodologies. Some interesting designs have been developed in an attempt to circumvent or overcome the scattering problem. This document describes a variation of the spatial interferometric technique that relies upon projected spatial gratings with subsequent detection against a coherent return signal for the purpose of noise reduction and image enhancement. A model is developed that simulates the projected structured illumination through turbid water to a target and its return to a detector. The model shows an unstructured backscatter superimposed on a structured return signal. The model can predict the effect on received signal to noise of variations in the projected spatial frequency and turbidity. The model has been extended to predict what a camera would actually see so that various noise reduction schemes can be modeled. Finally, some water tank tests are presented validating original hypothesis and model predictions. The method is advantageous in not requiring temporal synchronization between reference and signal beams and may use a continuous illumination source. Spatial coherency of the beam allows detection of the direct return, while scattered light appears as a noncoherent noise term. Both model and illumination method should prove to be valuable tools in ocean research.

Geologic Carbon Sequestration Leakage Detection: A Physics-Guided Machine Learning Approach

NASA Astrophysics Data System (ADS)

Lin, Y.; Harp, D. R.; Chen, B.; Pawar, R.

2017-12-01

One of the risks of large-scale geologic carbon sequestration is the potential migration of fluids out of the storage formations. Accurate and fast detection of this fluids migration is not only important but also challenging, due to the large subsurface uncertainty and complex governing physics. Traditional leakage detection and monitoring techniques rely on geophysical observations including pressure. However, the resulting accuracy of these methods is limited because of indirect information they provide requiring expert interpretation, therefore yielding in-accurate estimates of leakage rates and locations. In this work, we develop a novel machine-learning technique based on support vector regression to effectively and efficiently predict the leakage locations and leakage rates based on limited number of pressure observations. Compared to the conventional data-driven approaches, which can be usually seem as a "black box" procedure, we develop a physics-guided machine learning method to incorporate the governing physics into the learning procedure. To validate the performance of our proposed leakage detection method, we employ our method to both 2D and 3D synthetic subsurface models. Our novel CO2 leakage detection method has shown high detection accuracy in the example problems.

Environmental Detection of Clandestine Nuclear Weapon Programs

NASA Astrophysics Data System (ADS)

Kemp, R. Scott

2016-06-01

Environmental sensing of nuclear activities has the potential to detect nuclear weapon programs at early stages, deter nuclear proliferation, and help verify nuclear accords. However, no robust system of detection has been deployed to date. This can be variously attributed to high costs, technical limitations in detector technology, simple countermeasures, and uncertainty about the magnitude or behavior of potential signals. In this article, current capabilities and promising opportunities are reviewed. Systematic research in a variety of areas could improve prospects for detecting covert nuclear programs, although the potential for countermeasures suggests long-term verification of nuclear agreements will need to rely on methods other than environmental sensing.

eMethylsorb: electrochemical quantification of DNA methylation at CpG resolution using DNA-gold affinity interactions.

PubMed

Sina, Abu Ali Ibn; Howell, Sidney; Carrascosa, Laura G; Rauf, Sakandar; Shiddiky, Muhammad J A; Trau, Matt

2014-11-07

We report a simple electrochemical method referred to as "eMethylsorb" for the detection of DNA methylation. The method relies on the base dependent affinity interaction of DNA with gold. The methylation status of DNA is quantified by monitoring the electrochemical current as a function of the relative adsorption level of bisulphite treated DNA samples onto a bare gold electrode. This method can successfully distinguish methylated and unmethylated epigenotypes at single CpG resolution.

Non-contact photoacoustic tomography and ultrasonography for tissue imaging

PubMed Central

Rousseau, Guy; Blouin, Alain; Monchalin, Jean-Pierre

2011-01-01

The detection of ultrasound in photoacoustic tomography (PAT) and ultrasonography (US) usually relies on ultrasonic transducers in contact with the biological tissue. This is a major drawback for important potential applications such as surgery and small animal imaging. Here we report the use of remote optical detection, as used in industrial laser-ultrasonics, to detect ultrasound in biological tissues. This strategy enables non-contact implementation of PAT and US without exceeding laser exposure safety limits. The method uses suitably shaped laser pulses and a confocal Fabry-Perot interferometer in differential configuration to reach quantum-limited sensitivity. Endogenous and exogenous inclusions exhibiting optical and acoustic contrasts were detected ex vivo in chicken breast and calf brain specimens. Inclusions down to 0.5 mm in size were detected at depths well exceeding 1 cm. The method could significantly expand the scope of applications of PAT and US in biomedical imaging. PMID:22254164

A Method for Automated Detection of Usability Problems from Client User Interface Events

PubMed Central

Saadawi, Gilan M.; Legowski, Elizabeth; Medvedeva, Olga; Chavan, Girish; Crowley, Rebecca S.

2005-01-01

Think-aloud usability analysis provides extremely useful data but is very time-consuming and expensive to perform because of the extensive manual video analysis that is required. We describe a simple method for automated detection of usability problems from client user interface events for a developing medical intelligent tutoring system. The method incorporates (1) an agent-based method for communication that funnels all interface events and system responses to a centralized database, (2) a simple schema for representing interface events and higher order subgoals, and (3) an algorithm that reproduces the criteria used for manual coding of usability problems. A correction factor was empirically determining to account for the slower task performance of users when thinking aloud. We tested the validity of the method by simultaneously identifying usability problems using TAU and manually computing them from stored interface event data using the proposed algorithm. All usability problems that did not rely on verbal utterances were detectable with the proposed method. PMID:16779121

Non-contact biomedical photoacoustic and ultrasound imaging

NASA Astrophysics Data System (ADS)

Rousseau, Guy; Gauthier, Bruno; Blouin, Alain; Monchalin, Jean-Pierre

2012-06-01

The detection of ultrasound in photoacoustic tomography (PAT) usually relies on ultrasonic transducers in contact with the biological tissue through a coupling medium. This is a major drawback for important potential applications such as surgery. Here we report the use of a remote optical method, derived from industrial laser-ultrasonics, to detect ultrasound in tissues. This approach enables non-contact PAT (NCPAT) without exceeding laser exposure safety limits. The sensitivity of the method is based on the use of suitably shaped detection laser pulses and a confocal Fabry-Perot interferometer in differential configuration. Reliable image reconstruction is obtained by measuring remotely the surface profile of the tissue with an optical coherence tomography system. The proposed method also allows non-contact ultrasound imaging (US) by applying a second reconstruction algorithm to the data acquired for NCPAT. Endogenous and exogenous inclusions exhibiting optical and acoustic contrasts were detected ex vivo in chicken breast and calf brain specimens. Inclusions down to 0.3 mm in size were detected at depths exceeding 1 cm. The method could expand the scope of photoacoustic and US to in-vivo biomedical applications where contact is impractical.

Signal and image processing for early detection of coronary artery diseases: A review

NASA Astrophysics Data System (ADS)

Mobssite, Youness; Samir, B. Belhaouari; Mohamad Hani, Ahmed Fadzil B.

2012-09-01

Today biomedical signals and image based detection are a basic step to diagnose heart diseases, in particular, coronary artery diseases. The goal of this work is to provide non-invasive early detection of Coronary Artery Diseases relying on analyzing images and ECG signals as a combined approach to extract features, further classify and quantify the severity of DCAD by using B-splines method. In an aim of creating a prototype of screening biomedical imaging for coronary arteries to help cardiologists to decide the kind of treatment needed to reduce or control the risk of heart attack.

Method and means for detecting optically transmitted signals and establishing optical interference pattern between electrodes

DOEpatents

Kostenbauder, Adnah G.

1988-01-01

A photodetector for detecting signal pulses transmitted in an optical carrier signal relies on the generation of electron-hole pairs and the diffusion of the generated electrons and holes to the electrodes on the surface of the semiconductor detector body for generating photovoltaic pulses. The detector utilizes the interference of optical waves for generating an electron-hole grating within the semiconductor body, and, by establishing an electron-hole pair maximum at one electrode and a minimum at the other electrode, a detectable voltaic pulse is generated across the electrode.

Method and means for detecting optically transmitted signals and establishing optical interference pattern between electrodes

DOEpatents

Kostenbauder, A.G.

1988-06-28

A photodetector for detecting signal pulses transmitted in an optical carrier signal relies on the generation of electron-hole pairs and the diffusion of the generated electrons and holes to the electrodes on the surface of the semiconductor detector body for generating photovoltaic pulses. The detector utilizes the interference of optical waves for generating an electron-hole grating within the semiconductor body, and, by establishing an electron-hole pair maximum at one electrode and a minimum at the other electrode, a detectable voltaic pulse is generated across the electrode. 4 figs.

Spectroscopic optical coherence tomography based on wavelength de-multiplexing and smart pixel array detection

NASA Astrophysics Data System (ADS)

Laubscher, Markus; Bourquin, Stéphane; Froehly, Luc; Karamata, Boris; Lasser, Theo

2004-07-01

Current spectroscopic optical coherence tomography (OCT) methods rely on a posteriori numerical calculation. We present an experimental alternative for accessing spectroscopic information in OCT without post-processing based on wavelength de-multiplexing and parallel detection using a diffraction grating and a smart pixel detector array. Both a conventional A-scan with high axial resolution and the spectrally resolved measurement are acquired simultaneously. A proof-of-principle demonstration is given on a dynamically changing absorbing sample. The method's potential for fast spectroscopic OCT imaging is discussed. The spectral measurements obtained with this approach are insensitive to scan non-linearities or sample movements.

Identification of faulty sensor using relative partial decomposition via independent component analysis

NASA Astrophysics Data System (ADS)

Wang, Z.; Quek, S. T.

2015-07-01

Performance of any structural health monitoring algorithm relies heavily on good measurement data. Hence, it is necessary to employ robust faulty sensor detection approaches to isolate sensors with abnormal behaviour and exclude the highly inaccurate data in the subsequent analysis. The independent component analysis (ICA) is implemented to detect the presence of sensors showing abnormal behaviour. A normalized form of the relative partial decomposition contribution (rPDC) is proposed to identify the faulty sensor. Both additive and multiplicative types of faults are addressed and the detectability illustrated using a numerical and an experimental example. An empirical method to establish control limits for detecting and identifying the type of fault is also proposed. The results show the effectiveness of the ICA and rPDC method in identifying faulty sensor assuming that baseline cases are available.

Interference and deception detection technology of satellite navigation based on deep learning

NASA Astrophysics Data System (ADS)

Chen, Weiyi; Deng, Pingke; Qu, Yi; Zhang, Xiaoguang; Li, Yaping

2017-10-01

Satellite navigation system plays an important role in people's daily life and war. The strategic position of satellite navigation system is prominent, so it is very important to ensure that the satellite navigation system is not disturbed or destroyed. It is a critical means to detect the jamming signal to avoid the accident in a navigation system. At present, the detection technology of jamming signal in satellite navigation system is not intelligent , mainly relying on artificial decision and experience. For this issue, the paper proposes a method based on deep learning to monitor the interference source in a satellite navigation. By training the interference signal data, and extracting the features of the interference signal, the detection sys tem model is constructed. The simulation results show that, the detection accuracy of our detection system can reach nearly 70%. The method in our paper provides a new idea for the research on intelligent detection of interference and deception signal in a satellite navigation system.

Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks.

PubMed

Walsh, Aaron M; Crispie, Fiona; Daari, Kareem; O'Sullivan, Orla; Martin, Jennifer C; Arthur, Cornelius T; Claesson, Marcus J; Scott, Karen P; Cotter, Paul D

2017-08-15

The rapid detection of pathogenic strains in food products is essential for the prevention of disease outbreaks. It has already been demonstrated that whole-metagenome shotgun sequencing can be used to detect pathogens in food but, until recently, strain-level detection of pathogens has relied on whole-metagenome assembly, which is a computationally demanding process. Here we demonstrated that three short-read-alignment-based methods, i.e., MetaMLST, PanPhlAn, and StrainPhlAn, could accurately and rapidly identify pathogenic strains in spinach metagenomes that had been intentionally spiked with Shiga toxin-producing Escherichia coli in a previous study. Subsequently, we employed the methods, in combination with other metagenomics approaches, to assess the safety of nunu, a traditional Ghanaian fermented milk product that is produced by the spontaneous fermentation of raw cow milk. We showed that nunu samples were frequently contaminated with bacteria associated with the bovine gut and, worryingly, we detected putatively pathogenic E. coli and Klebsiella pneumoniae strains in a subset of nunu samples. Ultimately, our work establishes that short-read-alignment-based bioinformatics approaches are suitable food safety tools, and we describe a real-life example of their utilization. IMPORTANCE Foodborne pathogens are responsible for millions of illnesses each year. Here we demonstrate that short-read-alignment-based bioinformatics tools can accurately and rapidly detect pathogenic strains in food products by using shotgun metagenomics data. The methods used here are considerably faster than both traditional culturing methods and alternative bioinformatics approaches that rely on metagenome assembly; therefore, they can potentially be used for more high-throughput food safety testing. Overall, our results suggest that whole-metagenome sequencing can be used as a practical food safety tool to prevent diseases or to link outbreaks to specific food products. Copyright © 2017 American Society for Microbiology.

Embedded Reasoning Supporting Aerospace IVHM

DTIC Science & Technology

2007-01-01

c method (BIT or health assessment algorithm) which the monitoring diagnostic relies on input information tics and Astronautics In the diagram...viewing of the current health state of all monitored subsystems, while also providing a means to probe deeper in the event anomalous operation is...seeks to integrate detection , diagnostic, and prognostic capabilities with a hierarchical diagnostic reasoning architecture into a single

DNA/RNA sequencing using a semiconducting nanopore

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

Fleharty, Mark; Petsev, Dimiter N.; Van Swol, Frank B.

The present disclosure provides novel apparatus including, though not necessarily limited to, biosensors utilizing semiconductor materials in electrolyte solutions and methods for using the same. The biosensors rely on a unique property wherein a charged body in the electrolyte solution produces a detectable change in the local conductivity of the semiconductor as the body approaches or travels near the semiconductor.

Enzyme-free detection and quantification of double-stranded nucleic acids.

PubMed

Feuillie, Cécile; Merheb, Maxime Mohamad; Gillet, Benjamin; Montagnac, Gilles; Hänni, Catherine; Daniel, Isabelle

2012-08-01

We have developed a fully enzyme-free SERRS hybridization assay for specific detection of double-stranded DNA sequences. Although all DNA detection methods ranging from PCR to high-throughput sequencing rely on enzymes, this method is unique for being totally non-enzymatic. The efficiency of enzymatic processes is affected by alterations, modifications, and/or quality of DNA. For instance, a limitation of most DNA polymerases is their inability to process DNA damaged by blocking lesions. As a result, enzymatic amplification and sequencing of degraded DNA often fail. In this study we succeeded in detecting and quantifying, within a mixture, relative amounts of closely related double-stranded DNA sequences from Rupicapra rupicapra (chamois) and Capra hircus (goat). The non-enzymatic SERRS assay presented here is the corner stone of a promising approach to overcome the failure of DNA polymerase when DNA is too degraded or when the concentration of polymerase inhibitors is too high. It is the first time double-stranded DNA has been detected with a truly non-enzymatic SERRS-based method. This non-enzymatic, inexpensive, rapid assay is therefore a breakthrough in nucleic acid detection.

Detecting and Analyzing Corrosion Spots on the Hull of Large Marine Vessels Using Colored 3d LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Aijazi, A. K.; Malaterre, L.; Tazir, M. L.; Trassoudaine, L.; Checchin, P.

2016-06-01

This work presents a new method that automatically detects and analyzes surface defects such as corrosion spots of different shapes and sizes, on large ship hulls. In the proposed method several scans from different positions and viewing angles around the ship are registered together to form a complete 3D point cloud. The R, G, B values associated with each scan, obtained with the help of an integrated camera are converted into HSV space to separate out the illumination invariant color component from the intensity. Using this color component, different surface defects such as corrosion spots of different shapes and sizes are automatically detected, within a selected zone, using two different methods depending upon the level of corrosion/defects. The first method relies on a histogram based distribution whereas the second on adaptive thresholds. The detected corrosion spots are then analyzed and quantified to help better plan and estimate the cost of repair and maintenance. Results are evaluated on real data using different standard evaluation metrics to demonstrate the efficacy as well as the technical strength of the proposed method.

Progress in the molecular diagnosis of Lyme disease.

PubMed

Ružić-Sabljić, Eva; Cerar, Tjaša

2017-01-01

Current laboratory testing of Lyme borreliosis mostly relies on serological methods with known limitations. Diagnostic modalities enabling direct detection of pathogen at the onset of the clinical signs could overcome some of the limitations. Molecular methods detecting borrelial DNA seem to be the ideal solution, although there are some aspects that need to be considered. Areas covered: This review represent summary and discussion of the published data obtained from literature searches from PubMed and The National Library of Medicine (USA) together with our own experience on molecular diagnosis of Lyme disease. Expert commentary: Molecular methods are promising and currently serve as supporting diagnostic testing in Lyme borreliosis. Since the field of molecular diagnostics is under rapid development, molecular testing could become an important diagnostic modality.

From thermometric to spectrophotometric kinetic-catalytic methods of analysis. A review.

PubMed

Cerdà, Víctor; González, Alba; Danchana, Kaewta

2017-05-15

Kinetic-catalytic analytical methods have proved to be very easy and highly sensitive strategies for chemical analysis, that rely on simple instrumentation [1,2]. Molecular absorption spectrophotometry is commonly used as the detection technique. However, other detection systems, like electrochemical or thermometric ones, offer some interesting possibilities since they are not affected by the color or turbidity of the samples. In this review some initial experience with thermometric kinetic-catalytic methods is described, up to our current experience exploiting spectrophotometric flow techniques to automate this kind of reactions, including the use of integrated chips. Procedures for determination of inorganic and organic species in organic and inorganic matrices are presented. Copyright © 2017 Elsevier B.V. All rights reserved.

SWT voting-based color reduction for text detection in natural scene images

NASA Astrophysics Data System (ADS)

Ikica, Andrej; Peer, Peter

2013-12-01

In this article, we propose a novel stroke width transform (SWT) voting-based color reduction method for detecting text in natural scene images. Unlike other text detection approaches that mostly rely on either text structure or color, the proposed method combines both by supervising text-oriented color reduction process with additional SWT information. SWT pixels mapped to color space vote in favor of the color they correspond to. Colors receiving high SWT vote most likely belong to text areas and are blocked from being mean-shifted away. Literature does not explicitly address SWT search direction issue; thus, we propose an adaptive sub-block method for determining correct SWT direction. Both SWT voting-based color reduction and SWT direction determination methods are evaluated on binary (text/non-text) images obtained from a challenging Computer Vision Lab optical character recognition database. SWT voting-based color reduction method outperforms the state-of-the-art text-oriented color reduction approach.

An efficient repeating signal detector to investigate earthquake swarms

NASA Astrophysics Data System (ADS)

Skoumal, Robert J.; Brudzinski, Michael R.; Currie, Brian S.

2016-08-01

Repetitive earthquake swarms have been recognized as key signatures in fluid injection induced seismicity, precursors to volcanic eruptions, and slow slip events preceding megathrust earthquakes. We investigate earthquake swarms by developing a Repeating Signal Detector (RSD), a computationally efficient algorithm utilizing agglomerative clustering to identify similar waveforms buried in years of seismic recordings using a single seismometer. Instead of relying on existing earthquake catalogs of larger earthquakes, RSD identifies characteristic repetitive waveforms by rapidly identifying signals of interest above a low signal-to-noise ratio and then grouping based on spectral and time domain characteristics, resulting in dramatically shorter processing time than more exhaustive autocorrelation approaches. We investigate seismicity in four regions using RSD: (1) volcanic seismicity at Mammoth Mountain, California, (2) subduction-related seismicity in Oaxaca, Mexico, (3) induced seismicity in Central Alberta, Canada, and (4) induced seismicity in Harrison County, Ohio. In each case, RSD detects a similar or larger number of earthquakes than existing catalogs created using more time intensive methods. In Harrison County, RSD identifies 18 seismic sequences that correlate temporally and spatially to separate hydraulic fracturing operations, 15 of which were previously unreported. RSD utilizes a single seismometer for earthquake detection which enables seismicity to be quickly identified in poorly instrumented regions at the expense of relying on another method to locate the new detections. Due to the smaller computation overhead and success at distances up to ~50 km, RSD is well suited for real-time detection of low-magnitude earthquake swarms with permanent regional networks.

Determination of acrylamide and methacrylamide by normal phase high performance liquid chromatography and UV detection.

PubMed

Paleologos, E K; Kontominas, M G

2005-06-10

A method using normal phase high performance liquid chromatography (NP-HPLC) with UV detection was developed for the analysis of acrylamide and methacrylamide. The method relies on the chromatographic separation of these analytes on a polar HPLC column designed for the separation of organic acids. Identification of acrylamide and methacrylamide is approached dually, that is directly in their protonated forms and as their hydrolysis products acrylic and methacrylic acid respectively, for confirmation. Detection and quantification is performed at 200 nm. The method is simple allowing for clear resolution of the target peaks from any interfering substances. Detection limits of 10 microg L(-1) were obtained for both analytes with the inter- and intra-day RSD for standard analysis lying below 1.0%. Use of acetonitrile in the elution solvent lowers detection limits and retention times, without impairing resolution of peaks. The method was applied for the determination of acrylamide and methacrylamide in spiked food samples without native acrylamide yielding recoveries between 95 and 103%. Finally, commercial samples of french and roasted fries, cookies, cocoa and coffee were analyzed to assess applicability of the method towards acrylamide, giving results similar with those reported in the literature.

Absolute quantification of DNA methylation using microfluidic chip-based digital PCR.

PubMed

Wu, Zhenhua; Bai, Yanan; Cheng, Zule; Liu, Fangming; Wang, Ping; Yang, Dawei; Li, Gang; Jin, Qinghui; Mao, Hongju; Zhao, Jianlong

2017-10-15

Hypermethylation of CpG islands in the promoter region of many tumor suppressor genes downregulates their expression and in a result promotes tumorigenesis. Therefore, detection of DNA methylation status is a convenient diagnostic tool for cancer detection. Here, we reported a novel method for the integrative detection of methylation by the microfluidic chip-based digital PCR. This method relies on methylation-sensitive restriction enzyme HpaII, which cleaves the unmethylated DNA strands while keeping the methylated ones intact. After HpaII treatment, the DNA methylation level is determined quantitatively by the microfluidic chip-based digital PCR with the lower limit of detection equal to 0.52%. To validate the applicability of this method, promoter methylation of two tumor suppressor genes (PCDHGB6 and HOXA9) was tested in 10 samples of early stage lung adenocarcinoma and their adjacent non-tumorous tissues. The consistency was observed in the analysis of these samples using our method and a conventional bisulfite pyrosequencing. Combining high sensitivity and low cost, the microfluidic chip-based digital PCR method might provide a promising alternative for the detection of DNA methylation and early diagnosis of epigenetics-related diseases. Copyright © 2017 Elsevier B.V. All rights reserved.

A real-time PCR diagnostic method for detection of Naegleria fowleri.

PubMed

Madarová, Lucia; Trnková, Katarína; Feiková, Sona; Klement, Cyril; Obernauerová, Margita

2010-09-01

Naegleria fowleri is a free-living amoeba that can cause primary amoebic meningoencephalitis (PAM). While, traditional methods for diagnosing PAM still rely on culture, more current laboratory diagnoses exist based on conventional PCR methods; however, only a few real-time PCR processes have been described as yet. Here, we describe a real-time PCR-based diagnostic method using hybridization fluorescent labelled probes, with a LightCycler instrument and accompanying software (Roche), targeting the Naegleria fowleriMp2Cl5 gene sequence. Using this method, no cross reactivity with other tested epidemiologically relevant prokaryotic and eukaryotic organisms was found. The reaction detection limit was 1 copy of the Mp2Cl5 DNA sequence. This assay could become useful in the rapid laboratory diagnostic assessment of the presence or absence of Naegleria fowleri. Copyright 2009 Elsevier Inc. All rights reserved.

Evaluation of coded aperture radiation detectors using a Bayesian approach

NASA Astrophysics Data System (ADS)

Miller, Kyle; Huggins, Peter; Labov, Simon; Nelson, Karl; Dubrawski, Artur

2016-12-01

We investigate tradeoffs arising from the use of coded aperture gamma-ray spectrometry to detect and localize sources of harmful radiation in the presence of noisy background. Using an example application scenario of area monitoring and search, we empirically evaluate weakly supervised spectral, spatial, and hybrid spatio-spectral algorithms for scoring individual observations, and two alternative methods of fusing evidence obtained from multiple observations. Results of our experiments confirm the intuition that directional information provided by spectrometers masked with coded aperture enables gains in source localization accuracy, but at the expense of reduced probability of detection. Losses in detection performance can however be to a substantial extent reclaimed by using our new spatial and spatio-spectral scoring methods which rely on realistic assumptions regarding masking and its impact on measured photon distributions.

A universal method for automated gene mapping

PubMed Central

Zipperlen, Peder; Nairz, Knud; Rimann, Ivo; Basler, Konrad; Hafen, Ernst; Hengartner, Michael; Hajnal, Alex

2005-01-01

Small insertions or deletions (InDels) constitute a ubiquituous class of sequence polymorphisms found in eukaryotic genomes. Here, we present an automated high-throughput genotyping method that relies on the detection of fragment-length polymorphisms (FLPs) caused by InDels. The protocol utilizes standard sequencers and genotyping software. We have established genome-wide FLP maps for both Caenorhabditis elegans and Drosophila melanogaster that facilitate genetic mapping with a minimum of manual input and at comparatively low cost. PMID:15693948

Direct Detection of Potential Pyrethroids in Yangtze River via an Imprinted Multilayer Phosphorescence Probe.

PubMed

Chen, Li; Lv, Xiaodong; Dai, Jiangdong; Sun, Lin; Huo, Pengwei; Li, Chunxiang; Yan, Yongsheng

2018-01-01

A novel tailored multilayer probe for monitoring potential pyrethroids in the Yangtze River was proposed. The room-temperature phosphorescence method was applied to realize a detection strategy that is superior to the fluorescence method. Efficient Mn-doped ZnS quantum dots with uniform size of 4.6 nm were firstly coated with a mesoporous silica to obtain a suitable intermediate transition layer, then an imprinted layer containing bifenthrin specific recognition sites was anchored. Characterizations verified the multilayer structure convincingly and the detection process relied on the electron transfer-induced fluorescence quenching mechanism. Optional detection time and standard detection curve were obtained within a concentration range from 5.0 to 50 μmol L -1 . The stability was verified to be good after 12 replicates. Feasibility of the probe was proved by monitoring water samples from the Zhenjiang reach of the Yangtze River. The probe offers promise for direct bifenthrin detection in unknown environmental water with an accurate and stable phosphorescence analysis strategy.

Detection of tyrosine hydroxylase in dopaminergic neuron cell using gold nanoparticles-based barcode DNA.

PubMed

An, Jeung Hee; Oh, Byung-Keun; Choi, Jeong Woo

2013-04-01

Tyrosine hydroxylase, the rate-limiting enzyme of catecholamine biosysthesis, is predominantly expressed in several cell groups within the brain, including the dopaminergic neurons of the substantia nigra and ventral tegmental area. We evaluated the efficacy of this protein-detection method in detecting tyrosine hydroxylase in normal and oxidative stress damaged dopaminergic cells. In this study, a coupling of DNA barcode and bead-based immnunoassay for detecting tyrosine hydroxylaser with PCR-like sensitivity is reported. The method relies on magnetic nanoparticles with antibodies and nanoparticles that are encoded with DNA and antibodies that can sandwich the target protein captured by the nanoparticle-bound antibodies. The aggregate sandwich structures are magnetically separated from solution, and treated to remove the conjugated barcode DNA. The DNA barcodes were identified by PCR analysis. The concentration of tyrosine hydroxylase in dopaminergic cell can be easily and rapidly detected using bio-barcode assay. The bio-barcode assay is a rapid and high-throughput screening tool to detect of neurotransmitter such as dopamine.

Detecting Visually Observable Disease Symptoms from Faces.

PubMed

Wang, Kuan; Luo, Jiebo

2016-12-01

Recent years have witnessed an increasing interest in the application of machine learning to clinical informatics and healthcare systems. A significant amount of research has been done on healthcare systems based on supervised learning. In this study, we present a generalized solution to detect visually observable symptoms on faces using semi-supervised anomaly detection combined with machine vision algorithms. We rely on the disease-related statistical facts to detect abnormalities and classify them into multiple categories to narrow down the possible medical reasons of detecting. Our method is in contrast with most existing approaches, which are limited by the availability of labeled training data required for supervised learning, and therefore offers the major advantage of flagging any unusual and visually observable symptoms.

Enhanced data validation strategy of air quality monitoring network.

PubMed

Harkat, Mohamed-Faouzi; Mansouri, Majdi; Nounou, Mohamed; Nounou, Hazem

2018-01-01

Quick validation and detection of faults in measured air quality data is a crucial step towards achieving the objectives of air quality networks. Therefore, the objectives of this paper are threefold: (i) to develop a modeling technique that can be used to predict the normal behavior of air quality variables and help provide accurate reference for monitoring purposes; (ii) to develop fault detection method that can effectively and quickly detect any anomalies in measured air quality data. For this purpose, a new fault detection method that is based on the combination of generalized likelihood ratio test (GLRT) and exponentially weighted moving average (EWMA) will be developed. GLRT is a well-known statistical fault detection method that relies on maximizing the detection probability for a given false alarm rate. In this paper, we propose to develop GLRT-based EWMA fault detection method that will be able to detect the changes in the values of certain air quality variables; (iii) to develop fault isolation and identification method that allows defining the fault source(s) in order to properly apply appropriate corrective actions. In this paper, reconstruction approach that is based on Midpoint-Radii Principal Component Analysis (MRPCA) model will be developed to handle the types of data and models associated with air quality monitoring networks. All air quality modeling, fault detection, fault isolation and reconstruction methods developed in this paper will be validated using real air quality data (such as particulate matter, ozone, nitrogen and carbon oxides measurement). Copyright © 2017 Elsevier Inc. All rights reserved.

Current Technical Approaches for the Early Detection of Foodborne Pathogens: Challenges and Opportunities.

PubMed

Cho, Il-Hoon; Ku, Seockmo

2017-09-30

The development of novel and high-tech solutions for rapid, accurate, and non-laborious microbial detection methods is imperative to improve the global food supply. Such solutions have begun to address the need for microbial detection that is faster and more sensitive than existing methodologies (e.g., classic culture enrichment methods). Multiple reviews report the technical functions and structures of conventional microbial detection tools. These tools, used to detect pathogens in food and food homogenates, were designed via qualitative analysis methods. The inherent disadvantage of these analytical methods is the necessity for specimen preparation, which is a time-consuming process. While some literature describes the challenges and opportunities to overcome the technical issues related to food industry legal guidelines, there is a lack of reviews of the current trials to overcome technological limitations related to sample preparation and microbial detection via nano and micro technologies. In this review, we primarily explore current analytical technologies, including metallic and magnetic nanomaterials, optics, electrochemistry, and spectroscopy. These techniques rely on the early detection of pathogens via enhanced analytical sensitivity and specificity. In order to introduce the potential combination and comparative analysis of various advanced methods, we also reference a novel sample preparation protocol that uses microbial concentration and recovery technologies. This technology has the potential to expedite the pre-enrichment step that precedes the detection process.

Differentiation of Volatile Profiles from Stockpiled Almonds at Varying Relative Humidity Levels Using Benchtop and Portable GC-MS.

PubMed

Beck, John J; Willett, Denis S; Gee, Wai S; Mahoney, Noreen E; Higbee, Bradley S

2016-12-14

Contamination by aflatoxin, a toxic metabolite produced by Aspergillus fungi ubiquitous in California almond and pistachio orchards, results in millions of dollars of lost product annually. Current detection of aflatoxin relies on destructive, expensive, and time-intensive laboratory-based methods. To explore an alternative method for the detection of general fungal growth, volatile emission profiles of almonds at varying humidities were sampled using both static SPME and dynamic needle-trap SPE followed by benchtop and portable GC-MS analysis. Despite the portable SPE/GC-MS system detecting fewer volatiles than the benchtop system, both systems resolved humidity treatments and identified potential fungal biomarkers at extremely low water activity levels. This ability to resolve humidity levels suggests that volatile profiles from germinating fungal spores could be used to create an early warning, nondestructive, portable detection system of fungal growth.

Automatic detection of spermatozoa for laser capture microdissection.

PubMed

Vandewoestyne, Mado; Van Hoofstat, David; Van Nieuwerburgh, Filip; Deforce, Dieter

2009-03-01

In sexual assault crimes, differential extraction of spermatozoa from vaginal swab smears is often ineffective, especially when only a few spermatozoa are present in an overwhelming amount of epithelial cells. Laser capture microdissection (LCM) enables the precise separation of spermatozoa and epithelial cells. However, standard sperm-staining techniques are non-specific and rely on sperm morphology for identification. Moreover, manual screening of the microscope slides is time-consuming and labor-intensive. Here, we describe an automated screening method to detect spermatozoa stained with Sperm HY-LITER. Different ratios of spermatozoa and epithelial cells were used to assess the automatic detection method. In addition, real postcoital samples were also screened. Detected spermatozoa were isolated using LCM and DNA analysis was performed. Robust DNA profiles without allelic dropout could be obtained from as little as 30 spermatozoa recovered from postcoital samples, showing that the staining had no significant influence on DNA recovery.

Simple colorimetric detection of doxycycline and oxytetracycline using unmodified gold nanoparticles

NASA Astrophysics Data System (ADS)

Li, Jie; Fan, Shumin; Li, Zhigang; Xie, Yuanzhe; Wang, Rui; Ge, Baoyu; Wu, Jing; Wang, Ruiyong

2014-08-01

The interaction between tetracycline antibiotics and gold nanoparticles was studied. With citrate-coated gold nanoparticles as colorimetric probe, a simple and rapid detection method for doxycycline and oxytetracycline has been developed. This method relies on the distance-dependent optical properties of gold nanoparticles. In weakly acidic buffer medium, doxycycline and oxytetracycline could rapidly induce the aggregation of gold nanoparticles, resulting in red-to-blue (or purple) colour change. The experimental parameters were optimized with regard to pH, the concentration of the gold nanoparticles and the reaction time. Under optimal experimental conditions, the linear range of the colorimetric sensor for doxycycline/oxytetracycline was 0.06-0.66 and 0.59-8.85 μg mL-1, respectively. The corresponding limit of detection for doxycycline and oxytetracycline was 0.0086 and 0.0838 μg mL-1, respectively. This assay was sensitive, selective, simple and readily used to detect tetracycline antibiotics in food products.

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

PubMed

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.

Making great leaps forward: Accounting for detectability in herpetological field studies

USGS Publications Warehouse

Mazerolle, Marc J.; Bailey, Larissa L.; Kendall, William L.; Royle, J. Andrew; Converse, Sarah J.; Nichols, James D.

2007-01-01

Detecting individuals of amphibian and reptile species can be a daunting task. Detection can be hindered by various factors such as cryptic behavior, color patterns, or observer experience. These factors complicate the estimation of state variables of interest (e.g., abundance, occupancy, species richness) as well as the vital rates that induce changes in these state variables (e.g., survival probabilities for abundance; extinction probabilities for occupancy). Although ad hoc methods (e.g., counts uncorrected for detection, return rates) typically perform poorly in the face of no detection, they continue to be used extensively in various fields, including herpetology. However, formal approaches that estimate and account for the probability of detection, such as capture-mark-recapture (CMR) methods and distance sampling, are available. In this paper, we present classical approaches and recent advances in methods accounting for detectability that are particularly pertinent for herpetological data sets. Through examples, we illustrate the use of several methods, discuss their performance compared to that of ad hoc methods, and we suggest available software to perform these analyses. The methods we discuss control for imperfect detection and reduce bias in estimates of demographic parameters such as population size, survival, or, at other levels of biological organization, species occurrence. Among these methods, recently developed approaches that no longer require marked or resighted individuals should be particularly of interest to field herpetologists. We hope that our effort will encourage practitioners to implement some of the estimation methods presented herein instead of relying on ad hoc methods that make more limiting assumptions.

Automated Detection of Atrial Fibrillation Based on Time-Frequency Analysis of Seismocardiograms.

PubMed

Hurnanen, Tero; Lehtonen, Eero; Tadi, Mojtaba Jafari; Kuusela, Tom; Kiviniemi, Tuomas; Saraste, Antti; Vasankari, Tuija; Airaksinen, Juhani; Koivisto, Tero; Pankaala, Mikko

2017-09-01

In this paper, a novel method to detect atrial fibrillation (AFib) from a seismocardiogram (SCG) is presented. The proposed method is based on linear classification of the spectral entropy and a heart rate variability index computed from the SCG. The performance of the developed algorithm is demonstrated on data gathered from 13 patients in clinical setting. After motion artifact removal, in total 119 min of AFib data and 126 min of sinus rhythm data were considered for automated AFib detection. No other arrhythmias were considered in this study. The proposed algorithm requires no direct heartbeat peak detection from the SCG data, which makes it tolerant against interpersonal variations in the SCG morphology, and noise. Furthermore, the proposed method relies solely on the SCG and needs no complementary electrocardiography to be functional. For the considered data, the detection method performs well even on relatively low quality SCG signals. Using a majority voting scheme that takes five randomly selected segments from a signal and classifies these segments using the proposed algorithm, we obtained an average true positive rate of [Formula: see text] and an average true negative rate of [Formula: see text] for detecting AFib in leave-one-out cross-validation. This paper facilitates adoption of microelectromechanical sensor based heart monitoring devices for arrhythmia detection.

Quantifying the momentum correlation between two light beams by detecting one

PubMed Central

Hochrainer, Armin; Lahiri, Mayukh; Lapkiewicz, Radek; Lemos, Gabriela Barreto; Zeilinger, Anton

2017-01-01

We report a measurement of the transverse momentum correlation between two photons by detecting only one of them. Our method uses two identical sources in an arrangement in which the phenomenon of induced coherence without induced emission is observed. In this way, we produce an interference pattern in the superposition of one beam from each source. We quantify the transverse momentum correlation by analyzing the visibility of this pattern. Our approach might be useful for the characterization of correlated photon pair sources and may lead to an experimental measure of continuous variable entanglement, which relies on the detection of only one of two entangled particles. PMID:28143940

Quantifying the momentum correlation between two light beams by detecting one.

PubMed

Hochrainer, Armin; Lahiri, Mayukh; Lapkiewicz, Radek; Lemos, Gabriela Barreto; Zeilinger, Anton

2017-02-14

We report a measurement of the transverse momentum correlation between two photons by detecting only one of them. Our method uses two identical sources in an arrangement in which the phenomenon of induced coherence without induced emission is observed. In this way, we produce an interference pattern in the superposition of one beam from each source. We quantify the transverse momentum correlation by analyzing the visibility of this pattern. Our approach might be useful for the characterization of correlated photon pair sources and may lead to an experimental measure of continuous variable entanglement, which relies on the detection of only one of two entangled particles.

Analysis of glycosaminoglycan-derived disaccharides by capillary electrophoresis using laser-induced fluorescence detection

PubMed Central

Chang, Yuqing; Yang, Bo; Zhao, Xue; Linhardt, Robert J.

2012-01-01

A quantitative and highly sensitive method for the analysis of glycosaminoglycan (GAG)-derived disaccharides is presented that relies on capillary electrophoresis (CE) with laser-induced fluorescence (LIF) detection. This method enables complete separation of seventeen GAG-derived disaccharides in a single run. Unsaturated disaccharides were derivatized with 2-aminoacridone (AMAC) to improve sensitivity. The limit of detection was at the attomole level and about 100-fold more sensitive than traditional CE-ultraviolet detection. A CE separation timetable was developed to achieve complete resolution and shorten analysis time. The RSD of migration time and peak areas at both low and high concentrations of unsaturated disaccharides are all less than 2.7% and 3.2%, respectively, demonstrating that this is a reproducible method. This analysis was successfully applied to cultured Chinese hamster ovary cell samples for determination of GAG disaccharides. The current method simplifies GAG extraction steps, and reduces inaccuracy in calculating ratios of heparin/heparan sulfate to chondroitin sulfate/dermatan sulfate, resulting from the separate analyses of a single sample. PMID:22609076

Current trends in endotoxin detection and analysis of endotoxin-protein interactions.

PubMed

Dullah, Elvina Clarie; Ongkudon, Clarence M

2017-03-01

Endotoxin is a type of pyrogen that can be found in Gram-negative bacteria. Endotoxin can form a stable interaction with other biomolecules thus making its removal difficult especially during the production of biopharmaceutical drugs. The prevention of endotoxins from contaminating biopharmaceutical products is paramount as endotoxin contamination, even in small quantities, can result in fever, inflammation, sepsis, tissue damage and even lead to death. Highly sensitive and accurate detection of endotoxins are keys in the development of biopharmaceutical products derived from Gram-negative bacteria. It will facilitate the study of the intermolecular interaction of an endotoxin with other biomolecules, hence the selection of appropriate endotoxin removal strategies. Currently, most researchers rely on the conventional LAL-based endotoxin detection method. However, new methods have been and are being developed to overcome the problems associated with the LAL-based method. This review paper highlights the current research trends in endotoxin detection from conventional methods to newly developed biosensors. Additionally, it also provides an overview of the use of electron microscopy, dynamic light scattering (DLS), fluorescence resonance energy transfer (FRET) and docking programs in the endotoxin-protein analysis.

A novel boundary layer sensor utilizing domain switching in ferroelectric liquid crystals

NASA Technical Reports Server (NTRS)

Parmar, D. S.

1991-01-01

This paper describes the design and the principles of operation of a novel sensor for the optical detection of a shear stress field induced by air or gas flow on a rigid surface. The detection relies on the effects of shear-induced optical switching in ferroelectric liquid crystals. It is shown that the method overcomes many of the limitations of similar measuring techniques including those using cholesteric liquid crystals. The present method offers a preferred alternative for flow visualization and skin friction measurements in wind-tunnel experiments on laminar boundary layer transition investigations. A theoretical model for the optical response to shear stress is presented together with a schematic diagram of the experimental setup.

An Amplitude-Based Estimation Method for International Space Station (ISS) Leak Detection and Localization Using Acoustic Sensor Networks

NASA Technical Reports Server (NTRS)

Tian, Jialin; Madaras, Eric I.

2009-01-01

The development of a robust and efficient leak detection and localization system within a space station environment presents a unique challenge. A plausible approach includes the implementation of an acoustic sensor network system that can successfully detect the presence of a leak and determine the location of the leak source. Traditional acoustic detection and localization schemes rely on the phase and amplitude information collected by the sensor array system. Furthermore, the acoustic source signals are assumed to be airborne and far-field. Likewise, there are similar applications in sonar. In solids, there are specialized methods for locating events that are used in geology and in acoustic emission testing that involve sensor arrays and depend on a discernable phase front to the received signal. These methods are ineffective if applied to a sensor detection system within the space station environment. In the case of acoustic signal location, there are significant baffling and structural impediments to the sound path and the source could be in the near-field of a sensor in this particular setting.

Highly sensitive detection of DNA methylation levels by using a quantum dot-based FRET method

NASA Astrophysics Data System (ADS)

Ma, Yunfei; Zhang, Honglian; Liu, Fangming; Wu, Zhenhua; Lu, Shaohua; Jin, Qinghui; Zhao, Jianlong; Zhong, Xinhua; Mao, Hongju

2015-10-01

DNA methylation is the most frequently studied epigenetic modification that is strongly involved in genomic stability and cellular plasticity. Aberrant changes in DNA methylation status are ubiquitous in human cancer and the detection of these changes can be informative for cancer diagnosis. Herein, we reported a facile quantum dot-based (QD-based) fluorescence resonance energy transfer (FRET) technique for the detection of DNA methylation. The method relies on methylation-sensitive restriction enzymes for the differential digestion of genomic DNA based on its methylation status. Digested DNA is then subjected to PCR amplification for the incorporation of Alexa Fluor-647 (A647) fluorophores. DNA methylation levels can be detected qualitatively through gel analysis and quantitatively by the signal amplification from QDs to A647 during FRET. Furthermore, the methylation levels of three tumor suppressor genes, PCDHGB6, HOXA9 and RASSF1A, in 20 lung adenocarcinoma and 20 corresponding adjacent nontumorous tissue (NT) samples were measured to verify the feasibility of the QD-based FRET method and a high sensitivity for cancer detection (up to 90%) was achieved. Our QD-based FRET method is a convenient, continuous and high-throughput method, and is expected to be an alternative for detecting DNA methylation as a biomarker for certain human cancers.DNA methylation is the most frequently studied epigenetic modification that is strongly involved in genomic stability and cellular plasticity. Aberrant changes in DNA methylation status are ubiquitous in human cancer and the detection of these changes can be informative for cancer diagnosis. Herein, we reported a facile quantum dot-based (QD-based) fluorescence resonance energy transfer (FRET) technique for the detection of DNA methylation. The method relies on methylation-sensitive restriction enzymes for the differential digestion of genomic DNA based on its methylation status. Digested DNA is then subjected to PCR amplification for the incorporation of Alexa Fluor-647 (A647) fluorophores. DNA methylation levels can be detected qualitatively through gel analysis and quantitatively by the signal amplification from QDs to A647 during FRET. Furthermore, the methylation levels of three tumor suppressor genes, PCDHGB6, HOXA9 and RASSF1A, in 20 lung adenocarcinoma and 20 corresponding adjacent nontumorous tissue (NT) samples were measured to verify the feasibility of the QD-based FRET method and a high sensitivity for cancer detection (up to 90%) was achieved. Our QD-based FRET method is a convenient, continuous and high-throughput method, and is expected to be an alternative for detecting DNA methylation as a biomarker for certain human cancers. Electronic supplementary information (ESI) available: Synthesis of CdSe/CdS/ZnS core/shell/shell QDs. Sequences of primers used for amplifying the promoter regions in bisulfate-modified DNA. Comparison of detected methylation levels in different gene promoters using the QD-based FRET method versus bisulfite pyrosequencing. Methylation levels of the RASSF1A gene in one pair of NT and cancer samples as indicated by pyrosequencing. Theoretical calculation of the Förster distance R0. See DOI: 10.1039/c5nr04956c

Bacteriophage Amplification-Coupled Detection and Identification of Bacterial Pathogens

NASA Astrophysics Data System (ADS)

Cox, Christopher R.; Voorhees, Kent J.

Current methods of species-specific bacterial detection and identification are complex, time-consuming, and often require expensive specialized equipment and highly trained personnel. Numerous biochemical and genotypic identification methods have been applied to bacterial characterization, but all rely on tedious microbiological culturing practices and/or costly sequencing protocols which render them impractical for deployment as rapid, cost-effective point-of-care or field detection and identification methods. With a view towards addressing these shortcomings, we have exploited the evolutionarily conserved interactions between a bacteriophage (phage) and its bacterial host to develop species-specific detection methods. Phage amplification-coupled matrix assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF-MS) was utilized to rapidly detect phage propagation resulting from species-specific in vitro bacterial infection. This novel signal amplification method allowed for bacterial detection and identification in as little as 2 h, and when combined with disulfide bond reduction methods developed in our laboratory to enhance MALDI-TOF-MS resolution, was observed to lower the limit of detection by several orders of magnitude over conventional spectroscopy and phage typing methods. Phage amplification has been combined with lateral flow immunochromatography (LFI) to develop rapid, easy-to-operate, portable, species-specific point-of-care (POC) detection devices. Prototype LFI detectors have been developed and characterized for Yersinia pestis and Bacillus anthracis, the etiologic agents of plague and anthrax, respectively. Comparable sensitivity and rapidity was observed when phage amplification was adapted to a species-specific handheld LFI detector, thus allowing for rapid, simple, POC bacterial detection and identification while eliminating the need for bacterial culturing or DNA isolation and amplification techniques.

Circulating tumor cell detection: A direct comparison between negative and unbiased enrichment in lung cancer.

PubMed

Xu, Yan; Liu, Biao; Ding, Fengan; Zhou, Xiaodie; Tu, Pin; Yu, Bo; He, Yan; Huang, Peilin

2017-06-01

Circulating tumor cells (CTCs), isolated as a 'liquid biopsy', may provide important diagnostic and prognostic information. Therefore, rapid, reliable and unbiased detection of CTCs are required for routine clinical analyses. It was demonstrated that negative enrichment, an epithelial marker-independent technique for isolating CTCs, exhibits a better efficiency in the detection of CTCs compared with positive enrichment techniques that only use specific anti-epithelial cell adhesion molecules. However, negative enrichment techniques incur significant cell loss during the isolation procedure, and as it is a method that uses only one type of antibody, it is inherently biased. The detection procedure and identification of cell types also relies on skilled and experienced technicians. In the present study, the detection sensitivity of using negative enrichment and a previously described unbiased detection method was compared. The results revealed that unbiased detection methods may efficiently detect >90% of cancer cells in blood samples containing CTCs. By contrast, only 40-60% of CTCs were detected by negative enrichment. Additionally, CTCs were identified in >65% of patients with stage I/II lung cancer. This simple yet efficient approach may achieve a high level of sensitivity. It demonstrates a potential for the large-scale clinical implementation of CTC-based diagnostic and prognostic strategies.

Potential mapping with charged-particle beams

NASA Technical Reports Server (NTRS)

Robinson, J. W.; Tillery, D. G.

1979-01-01

Experimental methods of mapping the equipotential surfaces near some structure of interest rely on the detection of charged particles which have traversed the regions of interest and are detected remotely. One method is the measurement of ion energies for ions created at a point of interest and expelled from the region by the fields. The ion energy at the detector in eV corresponds to the potential where the ion was created. An ionizing beam forms the ions from background neutrals. The other method is to inject charged particles into the region of interest and to locate their exit points. A set of several trajectories becomes a data base for a systematic mapping technique. An iterative solution of a boundary value problem establishes concepts and limitations pertaining to the mapping problem.

Identification of Successive ``Unobservable'' Cyber Data Attacks in Power Systems Through Matrix Decomposition

NASA Astrophysics Data System (ADS)

Gao, Pengzhi; Wang, Meng; Chow, Joe H.; Ghiocel, Scott G.; Fardanesh, Bruce; Stefopoulos, George; Razanousky, Michael P.

2016-11-01

This paper presents a new framework of identifying a series of cyber data attacks on power system synchrophasor measurements. We focus on detecting "unobservable" cyber data attacks that cannot be detected by any existing method that purely relies on measurements received at one time instant. Leveraging the approximate low-rank property of phasor measurement unit (PMU) data, we formulate the identification problem of successive unobservable cyber attacks as a matrix decomposition problem of a low-rank matrix plus a transformed column-sparse matrix. We propose a convex-optimization-based method and provide its theoretical guarantee in the data identification. Numerical experiments on actual PMU data from the Central New York power system and synthetic data are conducted to verify the effectiveness of the proposed method.

Torque-mixing magnetic resonance spectroscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Losby, Joseph; Fani Sani, Fatemeh; Grandmont, Dylan T.; Diao, Zhu; Belov, Miro; Burgess, Jacob A.; Compton, Shawn R.; Hiebert, Wayne K.; Vick, Doug; Mohammad, Kaveh; Salimi, Elham; Bridges, Gregory E.; Thomson, Douglas J.; Freeman, Mark R.

2016-10-01

An optomechanical platform for magnetic resonance spectroscopy will be presented. The method relies on frequency mixing of orthogonal RF fields to yield a torque amplitude (arising from the transverse component of a precessing dipole moment, in analogy to magnetic resonance detection by electromagnetic induction) on a miniaturized resonant mechanical torsion sensor. In contrast to induction, the method is fully broadband and allows for simultaneous observation of the equilibrium net magnetic moment alongside the associated magnetization dynamics. To illustrate the method, comprehensive electron spin resonance spectra of a mesoscopic, single-crystal YIG disk at room temperature will be presented, along with situations where torque spectroscopy can offer complimentary information to existing magnetic resonance detection techniques. The authors are very grateful for support from NSERC, CRC, AITF, and NINT. Reference: Science 350, 798 (2015).

Detecting SNPs and estimating allele frequencies in clonal bacterial populations by sequencing pooled DNA.

PubMed

Holt, Kathryn E; Teo, Yik Y; Li, Heng; Nair, Satheesh; Dougan, Gordon; Wain, John; Parkhill, Julian

2009-08-15

Here, we present a method for estimating the frequencies of SNP alleles present within pooled samples of DNA using high-throughput short-read sequencing. The method was tested on real data from six strains of the highly monomorphic pathogen Salmonella Paratyphi A, sequenced individually and in a pool. A variety of read mapping and quality-weighting procedures were tested to determine the optimal parameters, which afforded > or =80% sensitivity of SNP detection and strong correlation with true SNP frequency at poolwide read depth of 40x, declining only slightly at read depths 20-40x. The method was implemented in Perl and relies on the opensource software Maq for read mapping and SNP calling. The Perl script is freely available from ftp://ftp.sanger.ac.uk/pub/pathogens/pools/.

Semantic distance-based creation of clusters of pharmacovigilance terms and their evaluation.

PubMed

Dupuch, Marie; Grabar, Natalia

2015-04-01

Pharmacovigilance is the activity related to the collection, analysis and prevention of adverse drug reactions (ADRs) induced by drugs or biologics. The detection of adverse drug reactions is performed using statistical algorithms and groupings of ADR terms from the MedDRA (Medical Dictionary for Drug Regulatory Activities) terminology. Standardized MedDRA Queries (SMQs) are the groupings which become a standard for assisting the retrieval and evaluation of MedDRA-coded ADR reports worldwide. Currently 84 SMQs have been created, while several important safety topics are not yet covered. Creation of SMQs is a long and tedious process performed by the experts. It relies on manual analysis of MedDRA in order to find out all the relevant terms to be included in a SMQ. Our objective is to propose an automatic method for assisting the creation of SMQs using the clustering of terms which are semantically similar. The experimental method relies on a specific semantic resource, and also on the semantic distance algorithms and clustering approaches. We perform several experiments in order to define the optimal parameters. Our results show that the proposed method can assist the creation of SMQs and make this process faster and systematic. The average performance of the method is precision 59% and recall 26%. The correlation of the results obtained is 0.72 against the medical doctors judgments and 0.78 against the medical coders judgments. These results and additional evaluation indicate that the generated clusters can be efficiently used for the detection of pharmacovigilance signals, as they provide better signal detection than the existing SMQs. Copyright © 2014. Published by Elsevier Inc.

Cryo-balloon catheter localization in fluoroscopic images

NASA Astrophysics Data System (ADS)

Kurzendorfer, Tanja; Brost, Alexander; Jakob, Carolin; Mewes, Philip W.; Bourier, Felix; Koch, Martin; Kurzidim, Klaus; Hornegger, Joachim; Strobel, Norbert

2013-03-01

Minimally invasive catheter ablation has become the preferred treatment option for atrial fibrillation. Although the standard ablation procedure involves ablation points set by radio-frequency catheters, cryo-balloon catheters have even been reported to be more advantageous in certain cases. As electro-anatomical mapping systems do not support cryo-balloon ablation procedures, X-ray guidance is needed. However, current methods to provide support for cryo-balloon catheters in fluoroscopically guided ablation procedures rely heavily on manual user interaction. To improve this, we propose a first method for automatic cryo-balloon catheter localization in fluoroscopic images based on a blob detection algorithm. Our method is evaluated on 24 clinical images from 17 patients. The method successfully detected the cryoballoon in 22 out of 24 images, yielding a success rate of 91.6 %. The successful localization achieved an accuracy of 1.00 mm +/- 0.44 mm. Even though our methods currently fails in 8.4 % of the images available, it still offers a significant improvement over manual methods. Furthermore, detecting a landmark point along the cryo-balloon catheter can be a very important step for additional post-processing operations.

Improved Sensor Fault Detection, Isolation, and Mitigation Using Multiple Observers Approach

PubMed Central

Wang, Zheng; Anand, D. M.; Moyne, J.; Tilbury, D. M.

2017-01-01

Traditional Fault Detection and Isolation (FDI) methods analyze a residual signal to detect and isolate sensor faults. The residual signal is the difference between the sensor measurements and the estimated outputs of the system based on an observer. The traditional residual-based FDI methods, however, have some limitations. First, they require that the observer has reached its steady state. In addition, residual-based methods may not detect some sensor faults, such as faults on critical sensors that result in an unobservable system. Furthermore, the system may be in jeopardy if actions required for mitigating the impact of the faulty sensors are not taken before the faulty sensors are identified. The contribution of this paper is to propose three new methods to address these limitations. Faults that occur during the observers' transient state can be detected by analyzing the convergence rate of the estimation error. Open-loop observers, which do not rely on sensor information, are used to detect faults on critical sensors. By switching among different observers, we can potentially mitigate the impact of the faulty sensor during the FDI process. These three methods are systematically integrated with a previously developed residual-based method to provide an improved FDI and mitigation capability framework. The overall approach is validated mathematically, and the effectiveness of the overall approach is demonstrated through simulation on a 5-state suspension system. PMID:28924303

Behavior Based Social Dimensions Extraction for Multi-Label Classification

PubMed Central

Li, Le; Xu, Junyi; Xiao, Weidong; Ge, Bin

2016-01-01

Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when community detection algorithms fail. In this paper, we propose a novel behavior based social dimensions extraction method to improve the classification performance in multi-label heterogeneous networks. In our method, nodes’ behavior features, instead of community memberships, are used to extract social dimensions. By introducing Latent Dirichlet Allocation (LDA) to model the network generation process, nodes’ connection behaviors with different communities can be extracted accurately, which are applied as latent social dimensions for classification. Experiments on various public datasets reveal that the proposed method can obtain satisfactory classification results in comparison to other state-of-the-art methods on smaller social dimensions. PMID:27049849

Combining Radiography and Passive Measurements for Radiological Threat Detection in Cargo

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

Miller, Erin A.; White, Timothy A.; Jarman, Kenneth D.

Abstract Radiography is widely understood to provide information complimentary to passive detection: while not directly sensitive to radiological materials, radiography can reveal highly shielded regions which may mask a passive radiological signal. We present a method for combining radiographic and passive data which uses the radiograph to provide an estimate of scatter and attenuation for possible sources. This approach allows quantitative use of radiographic images without relying on image interpretation, and results in a probabilistic description of likely source locations and strengths. We present first results for this method for a simple modeled test case of a cargo container drivingmore » through a PVT portal. With this inversion approach, we address criteria for an integrated passive and radiographic screening system and how detection of SNM threats might be improved in such a system.« less

Highly selective colorimetric bacteria sensing based on protein-capped nanoparticles.

PubMed

Qiu, Suyan; Lin, Zhenyu; Zhou, Yaomin; Wang, Donggen; Yuan, Lijuan; Wei, Yihua; Dai, Tingcan; Luo, Linguang; Chen, Guonan

2015-02-21

A rapid and cost-effective colorimetric sensor has been developed for the detection of bacteria (Bacillus subtilis was selected as an example). The sensor was designed to rely on lysozyme-capped AuNPs with the advantages of effective amplification and high specificity. In the sensing system, lysozyme was able to bind strongly to Bacillus subtilis, which effectively induced a color change of the solution from light purple to purplish red. The lowest concentration of Bacillus subtilis detectable by the naked eye was 4.5 × 10(3) colony-forming units (CFU) mL(-1). Similar results were discernable from UV-Vis absorption measurements. A good specificity was observed through a statistical analysis method using the SPSS software (version 17.0). This simple colorimetric sensor may therefore be a rapid and specific method for a bacterial detection assay in complex samples.

An Automatic Segmentation Method Combining an Active Contour Model and a Classification Technique for Detecting Polycomb-group Proteinsin High-Throughput Microscopy Images.

PubMed

Gregoretti, Francesco; Cesarini, Elisa; Lanzuolo, Chiara; Oliva, Gennaro; Antonelli, Laura

2016-01-01

The large amount of data generated in biological experiments that rely on advanced microscopy can be handled only with automated image analysis. Most analyses require a reliable cell image segmentation eventually capable of detecting subcellular structures.We present an automatic segmentation method to detect Polycomb group (PcG) proteins areas isolated from nuclei regions in high-resolution fluorescent cell image stacks. It combines two segmentation algorithms that use an active contour model and a classification technique serving as a tool to better understand the subcellular three-dimensional distribution of PcG proteins in live cell image sequences. We obtained accurate results throughout several cell image datasets, coming from different cell types and corresponding to different fluorescent labels, without requiring elaborate adjustments to each dataset.

Specific and Sensitive Isothermal Electrochemical Biosensor for Plant Pathogen DNA Detection with Colloidal Gold Nanoparticles as Probes

NASA Astrophysics Data System (ADS)

Lau, Han Yih; Wu, Haoqi; Wee, Eugene J. H.; Trau, Matt; Wang, Yuling; Botella, Jose R.

2017-01-01

Developing quick and sensitive molecular diagnostics for plant pathogen detection is challenging. Herein, a nanoparticle based electrochemical biosensor was developed for rapid and sensitive detection of plant pathogen DNA on disposable screen-printed carbon electrodes. This 60 min assay relied on the rapid isothermal amplification of target pathogen DNA sequences by recombinase polymerase amplification (RPA) followed by gold nanoparticle-based electrochemical assessment with differential pulse voltammetry (DPV). Our method was 10,000 times more sensitive than conventional polymerase chain reaction (PCR)/gel electrophoresis and could readily identify P. syringae infected plant samples even before the disease symptoms were visible. On the basis of the speed, sensitivity, simplicity and portability of the approach, we believe the method has potential as a rapid disease management solution for applications in agriculture diagnostics.

Specific and Sensitive Isothermal Electrochemical Biosensor for Plant Pathogen DNA Detection with Colloidal Gold Nanoparticles as Probes.

PubMed

Lau, Han Yih; Wu, Haoqi; Wee, Eugene J H; Trau, Matt; Wang, Yuling; Botella, Jose R

2017-01-17

Developing quick and sensitive molecular diagnostics for plant pathogen detection is challenging. Herein, a nanoparticle based electrochemical biosensor was developed for rapid and sensitive detection of plant pathogen DNA on disposable screen-printed carbon electrodes. This 60 min assay relied on the rapid isothermal amplification of target pathogen DNA sequences by recombinase polymerase amplification (RPA) followed by gold nanoparticle-based electrochemical assessment with differential pulse voltammetry (DPV). Our method was 10,000 times more sensitive than conventional polymerase chain reaction (PCR)/gel electrophoresis and could readily identify P. syringae infected plant samples even before the disease symptoms were visible. On the basis of the speed, sensitivity, simplicity and portability of the approach, we believe the method has potential as a rapid disease management solution for applications in agriculture diagnostics.

Measuring the performance of two stationary interrogation systems for detecting downstream and upstream movement of PIT-tagged salmonids

USGS Publications Warehouse

Connolly, P.J.; Jezorek, I.G.; Martens, K.D.; Prentice, E.F.

2008-01-01

We tested the performance of two stationary interrogation systems designed for detecting the movement of fish with passive integrated transponder (PIT) tags. These systems allowed us to determine the direction of fish movement with high detection efficiency and high precision in a dynamic stream environment. We describe an indirect method for deriving an estimate for detection efficiency and the associated variance that does not rely on a known number of fish passing the system. By using six antennas arranged in a longitudinal series of three arrays, we attained detection efficiencies for downstream- and upstream-moving fish exceeding 96% during high-flow periods and approached 100% during low-flow periods for the two interrogation systems we tested. Because these systems did not rely on structural components, such as bridges or culverts, they were readily adaptable to remote, natural stream sites. Because of built-in redundancy, these systems were able to perform even with a loss of one or more antennas owing to dislodgement or electrical failure. However, the reduction in redundancy resulted in decreased efficiency and precision and the potential loss of ability to determine the direction of fish movement. What we learned about these systems should be applicable to a wide variety of other antenna configurations and to other types of PIT tags and transceivers.

New set of design rules for resonant refractive index sensors enabled by FFT based processing of the measurement data.

PubMed

Gounaridis, Lefteris; Groumas, Panos; Schreuder, Erik; Heideman, Rene; Avramopoulos, Hercules; Kouloumentas, Christos

2016-04-04

It is still a common belief that ultra-high quality-factors (Q-factors) are a prerequisite in optical resonant cavities for high refractive index resolution and low detection limit in biosensing applications. In combination with the ultra-short steps that are necessary when the measurement of the resonance shift relies on the wavelength scanning of a laser source and conventional methods for data processing, the high Q-factor requirement makes these biosensors extremely impractical. In this work we analyze an alternative processing method based on the fast-Fourier transform, and show through Monte-Carlo simulations that improvement by 2-3 orders of magnitude can be achieved in the resolution and the detection limit of the system in the presence of amplitude and spectral noise. More significantly, this improvement is maximum for low Q-factors around 10⁴ and is present also for high intra-cavity losses and large scanning steps making the designs compatible with the low-cost aspect of lab-on-a-chip technology. Using a micro-ring resonator as model cavity and a system design with low Q-factor (10⁴), low amplitude transmission (0.85) and relatively large scanning step (0.25 pm), we show that resolution close to 0.01 pm and detection limit close to 10^-7 RIU can be achieved improving the sensing performance by more than 2 orders of magnitude compared to the performance of systems relying on a simple peak search processing method. The improvement in the limit of detection is present even when the simple method is combined with ultra-high Q-factors and ultra-short scanning steps due to the trade-off between the system resolution and sensitivity. Early experimental results are in agreement with the trends of the numerical studies.

Need for new caries detection methods

NASA Astrophysics Data System (ADS)

Young, Douglas A.; Featherstone, John D. B.

1999-05-01

Dental caries (tooth decay) continues to be a major problems for adults as well as children, even though great advances have been made in preventive methods in the last 20 years. New methods for the management of caries will work best if lesions can be detected at an early stage and chemical rather than physical intervention can take place, thereby preserving the natural tooth structure and helping the saliva to heal, or remineralize, the areas of early decay. Clinical detection of caries in the US relies on visual examination, tactile with hand held explorer, and conventional radiographs, all of which are inadequate for the occlusal (biting) surfaces of the teeth where most of the decay now occurs. The dentist often has to explore by drilling with a dental bur to confirm early decay in these areas. New method that can determine the extent and degree of subsurface lesions in these surfaces non-destructively are essential for further advances in the clinical management of dental caries. Optical methods, which exploit the differences between sound and carious enamel and dentin, show great promise for the accurate detection of these lesions. Two or three- dimensional images, which include a measure of severity will be needed.

Pothole Detection System Using a Black-box Camera.

PubMed

Jo, Youngtae; Ryu, Seungki

2015-11-19

Aging roads and poor road-maintenance systems result a large number of potholes, whose numbers increase over time. Potholes jeopardize road safety and transportation efficiency. Moreover, they are often a contributing factor to car accidents. To address the problems associated with potholes, the locations and size of potholes must be determined quickly. Sophisticated road-maintenance strategies can be developed using a pothole database, which requires a specific pothole-detection system that can collect pothole information at low cost and over a wide area. However, pothole repair has long relied on manual detection efforts. Recent automatic detection systems, such as those based on vibrations or laser scanning, are insufficient to detect potholes correctly and inexpensively owing to the unstable detection of vibration-based methods and high costs of laser scanning-based methods. Thus, in this paper, we introduce a new pothole-detection system using a commercial black-box camera. The proposed system detects potholes over a wide area and at low cost. We have developed a novel pothole-detection algorithm specifically designed to work with the embedded computing environments of black-box cameras. Experimental results are presented with our proposed system, showing that potholes can be detected accurately in real-time.

Hybrid online sensor error detection and functional redundancy for systems with time-varying parameters.

PubMed

Feng, Jianyuan; Turksoy, Kamuran; Samadi, Sediqeh; Hajizadeh, Iman; Littlejohn, Elizabeth; Cinar, Ali

2017-12-01

Supervision and control systems rely on signals from sensors to receive information to monitor the operation of a system and adjust manipulated variables to achieve the control objective. However, sensor performance is often limited by their working conditions and sensors may also be subjected to interference by other devices. Many different types of sensor errors such as outliers, missing values, drifts and corruption with noise may occur during process operation. A hybrid online sensor error detection and functional redundancy system is developed to detect errors in online signals, and replace erroneous or missing values detected with model-based estimates. The proposed hybrid system relies on two techniques, an outlier-robust Kalman filter (ORKF) and a locally-weighted partial least squares (LW-PLS) regression model, which leverage the advantages of automatic measurement error elimination with ORKF and data-driven prediction with LW-PLS. The system includes a nominal angle analysis (NAA) method to distinguish between signal faults and large changes in sensor values caused by real dynamic changes in process operation. The performance of the system is illustrated with clinical data continuous glucose monitoring (CGM) sensors from people with type 1 diabetes. More than 50,000 CGM sensor errors were added to original CGM signals from 25 clinical experiments, then the performance of error detection and functional redundancy algorithms were analyzed. The results indicate that the proposed system can successfully detect most of the erroneous signals and substitute them with reasonable estimated values computed by functional redundancy system.

An Unsupervised kNN Method to Systematically Detect Changes in Protein Localization in High-Throughput Microscopy Images.

PubMed

Lu, Alex Xijie; Moses, Alan M

2016-01-01

Despite the importance of characterizing genes that exhibit subcellular localization changes between conditions in proteome-wide imaging experiments, many recent studies still rely upon manual evaluation to assess the results of high-throughput imaging experiments. We describe and demonstrate an unsupervised k-nearest neighbours method for the detection of localization changes. Compared to previous classification-based supervised change detection methods, our method is much simpler and faster, and operates directly on the feature space to overcome limitations in needing to manually curate training sets that may not generalize well between screens. In addition, the output of our method is flexible in its utility, generating both a quantitatively ranked list of localization changes that permit user-defined cut-offs, and a vector for each gene describing feature-wise direction and magnitude of localization changes. We demonstrate that our method is effective at the detection of localization changes using the Δrpd3 perturbation in Saccharomyces cerevisiae, where we capture 71.4% of previously known changes within the top 10% of ranked genes, and find at least four new localization changes within the top 1% of ranked genes. The results of our analysis indicate that simple unsupervised methods may be able to identify localization changes in images without laborious manual image labelling steps.

Developing an Automated Method for Detection of Operationally Relevant Ocean Fronts and Eddies

NASA Astrophysics Data System (ADS)

Rogers-Cotrone, J. D.; Cadden, D. D. H.; Rivera, P.; Wynn, L. L.

2016-02-01

Since the early 90's, the U.S. Navy has utilized an observation-based process for identification of frontal systems and eddies. These Ocean Feature Assessments (OFA) rely on trained analysts to identify and position ocean features using satellite-observed sea surface temperatures. Meanwhile, as enhancements and expansion of the navy's Hybrid Coastal Ocean Model (HYCOM) and Regional Navy Coastal Ocean Model (RNCOM) domains have proceeded, the Naval Oceanographic Office (NAVO) has provided Tactical Oceanographic Feature Assessments (TOFA) that are based on data-validated model output but also rely on analyst identification of significant features. A recently completed project has migrated OFA production to the ArcGIS-based Acoustic Reach-back Cell Ocean Analysis Suite (ARCOAS), enabling use of additional observational datasets and significantly decreasing production time; however, it has highlighted inconsistencies inherent to this analyst-based identification process. Current efforts are focused on development of an automated method for detecting operationally significant fronts and eddies that integrates model output and observational data on a global scale. Previous attempts to employ techniques from the scientific community have been unable to meet the production tempo at NAVO. Thus, a system that incorporates existing techniques (Marr-Hildreth, Okubo-Weiss, etc.) with internally-developed feature identification methods (from model-derived physical and acoustic properties) is required. Ongoing expansions to the ARCOAS toolset have shown promising early results.

Evaluation of nearest-neighbor methods for detection of chimeric small-subunit rRNA sequences

NASA Technical Reports Server (NTRS)

Robison-Cox, J. F.; Bateson, M. M.; Ward, D. M.

1995-01-01

Detection of chimeric artifacts formed when PCR is used to retrieve naturally occurring small-subunit (SSU) rRNA sequences may rely on demonstrating that different sequence domains have different phylogenetic affiliations. We evaluated the CHECK_CHIMERA method of the Ribosomal Database Project and another method which we developed, both based on determining nearest neighbors of different sequence domains, for their ability to discern artificially generated SSU rRNA chimeras from authentic Ribosomal Database Project sequences. The reliability of both methods decreases when the parental sequences which contribute to chimera formation are more than 82 to 84% similar. Detection is also complicated by the occurrence of authentic SSU rRNA sequences that behave like chimeras. We developed a naive statistical test based on CHECK_CHIMERA output and used it to evaluate previously reported SSU rRNA chimeras. Application of this test also suggests that chimeras might be formed by retrieving SSU rRNAs as cDNA. The amount of uncertainty associated with nearest-neighbor analyses indicates that such tests alone are insufficient and that better methods are needed.

Identification of coliform genera recovered from water using different technologies.

PubMed

Fricker, C R; Eldred, B J

2009-12-01

Methods for the detection of coliforms in water have changed significantly in recent years with procedures incorporating substrates for the detection of beta-d-galactosidase becoming more widely used. This study was undertaken to determine the range of coliform genera detected with methods that rely on lactose fermentation and compare them to those recovered using methods based upon beta-d-galactosidase. Coliform isolates were recovered from sewage-polluted water using m-endo, membrane lauryl sulfate broth, tergitol TTC agar, Colilert-18, ChromoCult and ColiScan for primary isolation. Organisms were grouped according to whether they had been isolated based upon lactose fermentation or beta-d-galactosidase production. A wide range of coliform genera were detected using both types of methods. There was considerable overlap between the two groups, and whilst differences were seen between the genera isolated with the two method types, no clear pattern emerged. Substantial numbers of 'new' coliforms (e.g. Raoutella spp.) were recovered using both types of methods. The results presented here confirm that both methods based on lactose fermentation or detection of beta-d-galactosidase activity recover a range of coliform organisms. Any suggestion that only methods which are based upon fermentation of lactose recover organisms of public health or regulatory significance cannot be substantiated. Furthermore, the higher recovery of coliform organisms from sewage-polluted water using methods utilizing beta-d-galactosidase-based methods does not appear to be because of the recovery of substantially more 'new' coliforms.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits.

PubMed

Fu, Liya; Wang, You-Gan

2011-02-15

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which clearly demonstrates the advantages of the rank regression models.

Application of 3D Laser Scanning Technology in Inspection and Dynamic Reserves Detection of Open-Pit Mine

NASA Astrophysics Data System (ADS)

Hu, Zhumin; Wei, Shiyu; Jiang, Jun

2017-10-01

The traditional open-pit mine mining rights verification and dynamic reserve detection means rely on the total station and RTK to collect the results of the turning point coordinates of mining surface contours. It resulted in obtaining the results of low precision and large error in the means that is limited by the traditional measurement equipment accuracy and measurement methods. The three-dimensional scanning technology can obtain the three-dimensional coordinate data of the surface of the measured object in a large area at high resolution. This paper expounds the commonly used application of 3D scanning technology in the inspection and dynamic reserve detection of open mine mining rights.

An Ultrasonographic Periodontal Probe

NASA Astrophysics Data System (ADS)

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

2010-02-01

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

Robust image matching via ORB feature and VFC for mismatch removal

NASA Astrophysics Data System (ADS)

Ma, Tao; Fu, Wenxing; Fang, Bin; Hu, Fangyu; Quan, Siwen; Ma, Jie

2018-03-01

Image matching is at the base of many image processing and computer vision problems, such as object recognition or structure from motion. Current methods rely on good feature descriptors and mismatch removal strategies for detection and matching. In this paper, we proposed a robust image match approach based on ORB feature and VFC for mismatch removal. ORB (Oriented FAST and Rotated BRIEF) is an outstanding feature, it has the same performance as SIFT with lower cost. VFC (Vector Field Consensus) is a state-of-the-art mismatch removing method. The experiment results demonstrate that our method is efficient and robust.

Cosmic 21 cm delensing of microwave background polarization and the minimum detectable energy scale of inflation.

PubMed

Sigurdson, Kris; Cooray, Asantha

2005-11-18

We propose a new method for removing gravitational lensing from maps of cosmic microwave background (CMB) polarization anisotropies. Using observations of anisotropies or structures in the cosmic 21 cm radiation, emitted or absorbed by neutral hydrogen atoms at redshifts 10 to 200, the CMB can be delensed. We find this method could allow CMB experiments to have increased sensitivity to a background of inflationary gravitational waves (IGWs) compared to methods relying on the CMB alone and may constrain models of inflation which were heretofore considered to have undetectable IGW amplitudes.

[Assessment of lymph node metastasis in gastric cancer: status quo, recent advances and new perspectives].

PubMed

Tu, Min; Zhu, Zhen-shu; Shi, Lin-sen; Jiang, Xi-qun; Wang, Hao; Guan, Wen-xian

2012-02-01

The precondition of accurate gastric cancer surgery is precise assessment of lymph node metastasis. To date, no imaging modality achieves both high sensitivity and high specificity in detecting lymph node metastasis in gastric cancer. Intraoperative sentinel node tracing and biopsy are the most popular method to identify the localization of tumor cell, but is limited to early gastric cancer. Nano-composite materials, designed for tumor imaging and tracing, show us a newly emerging domain for tumor detection in gastric cancer. The function of these nano-composite materials to detect lymph node metastasis in gastric cancer relies on the effective backflow of lymph system. However, the lymph vessels can be obstructed by tumor cells in advanced gastric cancer, which may restrain the application of these nanoparticles. Therefore, more methods to detect lymph node metastasis in gastric cancer should be explored. This review summarizes the characteristic of the targeted nanosphere. Based on the reported studies, a novel idea is conceived that targeted multifunctional nanosphere may be a potential method to achieve precise assessment of lymph node metastasis in gastric cancer.

A rapid detection method for policy-sensitive amines real-time supervision.

PubMed

Zhang, Haixu; Shu, Jinian; Yang, Bo; Zhang, Peng; Ma, Pengkun

2018-02-01

Many organic amines that comprise a benzene ring are policy-sensitive because of their toxicity and links to social harm. However, to date, detection of such compounds mainly relies on offline methods. This study proposes an online pptv (parts per trillion by volume) level of detection method for amines, using the recently-built vacuum ultraviolet photoionization mass spectrometer (VUV-PIMS) combined with a new doping technique. Thus, the dichloromethane doping-assisted photoionization mass spectra of aniline, benzylamine, phenethylamine, amphetamine, and their structural isomers were recorded. The dominant characteristic mass peaks for all amines are those afforded by protonated amines and the amino radical-loss. The signal intensities of the amines were enhanced by 60-130 times compared to those recorded without doping assistance. Under 10s detection time, the sensitivities of aniline and benzylamine in the gas phase were determined as 4.0 and 2.7 countspptv -1 , with limits of detection (LODs) of 36 and 22 pptv, respectively. Notably, the detection efficiency of this method can be tenfold better in future applications since the ion transmission efficiency of the mass spectrometer was intentionally reduced to ~ 10% in this study. Therefore, dichloromethane doping-assisted photoionization mass spectrometry has proven to be a highly promising on-line approach to amine detection in environmental and judicial supervision and shows great potential for application in the biological field. Copyright © 2017 Elsevier B.V. All rights reserved.

Detection of Protein Interactions in T3S Systems Using Yeast Two-Hybrid Analysis.

PubMed

Nilles, Matthew L

2017-01-01

Two-hybrid systems, sometimes termed interaction traps, are genetic systems designed to find and analyze interactions between proteins. The most common systems are yeast based (commonly Saccharomyces cerevisae) and rely on the functional reconstitution of the GAL4 transcriptional activator. Reporter genes, such as the lacZ gene of Escherichia coli (encodes β-galactosidase), are placed under GAL4-dependent transcriptional control to provide quick and reliable detection of protein interactions. In this method the use of a yeast-based two-hybrid system is described to study protein interactions between components of type III secretion systems.

A challenging issue: Detection of white matter hyperintensities in neonatal brain MRI.

PubMed

Morel, Baptiste; Yongchao Xu; Virzi, Alessio; Geraud, Thierry; Adamsbaum, Catherine; Bloch, Isabelle

2016-08-01

The progress of magnetic resonance imaging (MRI) allows for a precise exploration of the brain of premature infants at term equivalent age. The so-called DEHSI (diffuse excessive high signal intensity) of the white matter of premature brains remains a challenging issue in terms of definition, and thus of interpretation. We propose a semi-automatic detection and quantification method of white matter hyperintensities in MRI relying on morphological operators and max-tree representations, which constitutes a powerful tool to help radiologists to improve their interpretation. Results show better reproducibility and robustness than interactive segmentation.

Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery

NASA Astrophysics Data System (ADS)

Kit, Oleksandr; Lüdeke, Matthias

2013-09-01

This paper presents an approach to automated identification of slum area change patterns in Hyderabad, India, using multi-year and multi-sensor very high resolution satellite imagery. It relies upon a lacunarity-based slum detection algorithm, combined with Canny- and LSD-based imagery pre-processing routines. This method outputs plausible and spatially explicit slum locations for the whole urban agglomeration of Hyderabad in years 2003 and 2010. The results indicate a considerable growth of area occupied by slums between these years and allow identification of trends in slum development in this urban agglomeration.

Shear wave induced resonance elastography of spherical masses with polarized torsional waves

NASA Astrophysics Data System (ADS)

Hadj Henni, Anis; Schmitt, Cédric; Trop, Isabelle; Cloutier, Guy

2012-03-01

Shear wave induced resonance (SWIR) is a technique for dynamic ultrasound elastography of confined mechanical inclusions. It was developed for breast tumor imaging and tissue characterization. This method relies on the polarization of torsional shear waves modeled with the Helmholtz equation in spherical coordinates. To validate modeling, an invitro set-up was used to measure and image the first three eigenfrequencies and eigenmodes of a soft sphere. A preliminary invivo SWIR measurement on a breast fibroadenoma is also reported. Results revealed the potential of SWIR elastography to detect and mechanically characterize breast lesions for early cancer detection.

Shear wave induced resonance elastography of spherical masses with polarized torsional waves.

PubMed

Henni, Anis Hadj; Schmitt, Cédric; Trop, Isabelle; Cloutier, Guy

2012-03-26

Shear Wave Induced Resonance (SWIR) is a technique for dynamic ultrasound elastography of confined mechanical inclusions. It was developed for breast tumor imaging and tissue characterization. This method relies on the polarization of torsional shear waves modeled with the Helmholtz equation in spherical coordinates. To validate modeling, an in vitro set-up was used to measure and image the first three eigenfrequencies and eigenmodes of a soft sphere. A preliminary in vivo SWIR measurement on a breast fibroadenoma is also reported. Results revealed the potential of SWIR elastography to detect and mechanically characterize breast lesions for early cancer detection.

Distance-Based Tear Lactoferrin Assay on Microfluidic Paper Device Using Interfacial Interactions on Surface-Modified Cellulose.

PubMed

Yamada, Kentaro; Henares, Terence G; Suzuki, Koji; Citterio, Daniel

2015-11-11

"Distance-based" detection motifs on microfluidic paper-based analytical devices (μPADs) allow quantitative analysis without using signal readout instruments in a similar manner to classical analogue thermometers. To realize a cost-effective and calibration-free distance-based assay of lactoferrin in human tear fluid on a μPAD not relying on antibodies or enzymes, we investigated the fluidic mobilities of the target protein and Tb(3+) cations used as the fluorescent detection reagent on surface-modified cellulosic filter papers. Chromatographic elution experiments in a tear-like sample matrix containing electrolytes and proteins revealed a collapse of attractive electrostatic interactions between lactoferrin or Tb(3+) and the cellulosic substrate, which was overcome by the modification of the paper surface with the sulfated polysaccharide ι-carrageenan. The resulting μPAD based on the fluorescence emission distance successfully analyzed 0-4 mg mL(-1) of lactoferrin in complex human tear matrix with a lower limit of detection of 0.1 mg mL(-1) by simple visual inspection. Assay results of 18 human tear samples including ocular disease patients and healthy volunteers showed good correlation to the reference ELISA method with a slope of 0.997 and a regression coefficient of 0.948. The distance-based quantitative signal and the good batch-to-batch fabrication reproducibility relying on printing methods enable quantitative analysis by simply reading out "concentration scale marks" printed on the μPAD without performing any calibration and using any signal readout instrument.

Non-radioactive detection of trinucleotide repeat size variability.

PubMed

Tomé, Stéphanie; Nicole, Annie; Gomes-Pereira, Mario; Gourdon, Genevieve

2014-03-06

Many human diseases are associated with the abnormal expansion of unstable trinucleotide repeat sequences. The mechanisms of trinucleotide repeat size mutation have not been fully dissected, and their understanding must be grounded on the detailed analysis of repeat size distributions in human tissues and animal models. Small-pool PCR (SP-PCR) is a robust, highly sensitive and efficient PCR-based approach to assess the levels of repeat size variation, providing both quantitative and qualitative data. The method relies on the amplification of a very low number of DNA molecules, through sucessive dilution of a stock genomic DNA solution. Radioactive Southern blot hybridization is sensitive enough to detect SP-PCR products derived from single template molecules, separated by agarose gel electrophoresis and transferred onto DNA membranes. We describe a variation of the detection method that uses digoxigenin-labelled locked nucleic acid probes. This protocol keeps the sensitivity of the original method, while eliminating the health risks associated with the manipulation of radiolabelled probes, and the burden associated with their regulation, manipulation and waste disposal.

Development of an Analytical Protocol for Determination of Cyanide in Human Biological Samples Based on Application of Ion Chromatography with Pulsed Amperometric Detection

PubMed Central

Ruman, Marek; Narkowicz, Sylwia; Namieśnik, Jacek

2017-01-01

A simple and accurate ion chromatography (IC) method with pulsed amperometric detection (PAD) was proposed for the determination of cyanide ion in urine, sweat, and saliva samples. The sample pretreatment relies on alkaline digestion and application of Dionex OnGuard II H cartridge. Under the optimized conditions, the method showed good linearity in the range of 1–100 μg/L for urine, 5–100 μg/L for saliva, and 3–100 μg/L for sweat samples with determination coefficients (R) > 0.992. Low detection limits (LODs) in the range of 1.8 μg/L, 5.1 μg/L, and 5.8 μg/L for urine, saliva, and sweat samples, respectively, and good repeatability (CV < 3%, n = 3) were obtained. The proposed method has been successfully applied to the analysis of human biological samples. PMID:29348966

Development of an Analytical Protocol for Determination of Cyanide in Human Biological Samples Based on Application of Ion Chromatography with Pulsed Amperometric Detection.

PubMed

Jaszczak, Ewa; Ruman, Marek; Narkowicz, Sylwia; Namieśnik, Jacek; Polkowska, Żaneta

2017-01-01

A simple and accurate ion chromatography (IC) method with pulsed amperometric detection (PAD) was proposed for the determination of cyanide ion in urine, sweat, and saliva samples. The sample pretreatment relies on alkaline digestion and application of Dionex OnGuard II H cartridge. Under the optimized conditions, the method showed good linearity in the range of 1-100  μ g/L for urine, 5-100  μ g/L for saliva, and 3-100  μ g/L for sweat samples with determination coefficients ( R ) > 0.992. Low detection limits (LODs) in the range of 1.8  μ g/L, 5.1  μ g/L, and 5.8  μ g/L for urine, saliva, and sweat samples, respectively, and good repeatability (CV < 3%, n = 3) were obtained. The proposed method has been successfully applied to the analysis of human biological samples.

Searching for co-orbital planets by combining transit and radial-velocity measurements

NASA Astrophysics Data System (ADS)

Robutel, p.; Leleu, A.; Correia, A.; Lillo-Box, J.

2017-09-01

Co-orbital planetary systems consist of two planets orbiting with the same period a central star. If co-orbital bodies are common in the solar system and are also a natural output of planetary formation models, so far none have been found in extrasolar systems. This lack may be due to observational biases, since the main detection methods are unable to spot co-orbital companions when they are small or near the Lagrangian equilibrium points. We propose a simple method, based on an idea from Ford & Gaudi (2006), that allows the detection of co-orbital companions, and relies on a single parameter proportional to the mass ratio of the two planets. This method is applied to archival radial velocity data of 46 close-in transiting planets among which a few are strong candidates to harbor a co-orbital companion.

A novel approach for food intake detection using electroglottography

PubMed Central

Farooq, Muhammad; Fontana, Juan M; Sazonov, Edward

2014-01-01

Many methods for monitoring diet and food intake rely on subjects self-reporting their daily intake. These methods are subjective, potentially inaccurate and need to be replaced by more accurate and objective methods. This paper presents a novel approach that uses an Electroglottograph (EGG) device for an objective and automatic detection of food intake. Thirty subjects participated in a 4-visit experiment involving the consumption of meals with self-selected content. Variations in the electrical impedance across the larynx caused by the passage of food during swallowing were captured by the EGG device. To compare performance of the proposed method with a well-established acoustical method, a throat microphone was used for monitoring swallowing sounds. Both signals were segmented into non-overlapping epochs of 30 s and processed to extract wavelet features. Subject-independent classifiers were trained using Artificial Neural Networks, to identify periods of food intake from the wavelet features. Results from leave-one-out cross-validation showed an average per-epoch classification accuracy of 90.1% for the EGG-based method and 83.1% for the acoustic-based method, demonstrating the feasibility of using an EGG for food intake detection. PMID:24671094

Novel approach for the simultaneous detection of DNA from different fish species based on a nuclear target: quantification potential.

PubMed

Prado, Marta; Boix, Ana; von Holst, Christoph

2012-07-01

The development of DNA-based methods for the identification and quantification of fish in food and feed samples is frequently focused on a specific fish species and/or on the detection of mitochondrial DNA of fish origin. However, a quantitative method for the most common fish species used by the food and feed industry is needed for official control purposes, and such a method should rely on the use of a single-copy nuclear DNA target owing to its more stable copy number in different tissues. In this article, we report on the development of a real-time PCR method based on the use of a nuclear gene as a target for the simultaneous detection of fish DNA from different species and on the evaluation of its quantification potential. The method was tested in 22 different fish species, including those most commonly used by the food and feed industry, and in negative control samples, which included 15 animal species and nine feed ingredients. The results show that the method reported here complies with the requirements concerning specificity and with the criteria required for real-time PCR methods with high sensitivity.

Acousto-optical assessment of skin viscoelasticity

NASA Astrophysics Data System (ADS)

Kirkpatrick, Sean J.; Duncan, Donald D.

2003-07-01

A multiphysics approach, combining acoustics, optics, and mechanics can be used to detect regions of skin with distinct mechanical behavior that may indicate a pathology, such as a cancerous skin lesion. Herein, an acousto-optical approach to evaluating the viscoelastic behavior of superficial skin layers will be presented. The method relies upon inducing low frequency guided surface waves in the skin and detecting these waves by monitoring the shift in the backscattered laser speckle pattern created by illuminating a small region of the skin with coherent light. Artificial lesions in the form of chemical cross-linking and chemical softening were induced in superficial porcine skin layers and detected based upon variations in local mechanical behavior. The lesions affect not only the time-of-flight of the guided surface waves, but also change the relative phase of the acoustic waves as determined optically. The method may be applicable in the study and diagnosis of superficial skin lesions.

Optical assessment of tissue mechanics: acousto-optical elastography of skin

NASA Astrophysics Data System (ADS)

Kirkpatrick, Sean J.

2003-10-01

A multiphysics approach, combining acoustics, optics, and mechanics can be used to detect regions of skin with distinct mechanical behavior that may indicate a pathology, such as a cancerous skin lesion. Herein, an acousto - optical approach to evaluating the viscoelastic behavior of superficial skin layers will be presented. The method relies upon inducing low frequency guided surface waves in the skin and detecting these waves by monitoring the shift in the backscattered laser speckle pattern created by illuminating a small region of the skin with coherent light. Artificial lesions in the form of chemical cross-linking and chemical softening were induced in superficial porcine skin layers and detected based upon variations in local mechanical behavior. The lesions affect not only the time-of-flight of the guided surface waves, but also change the relative phase of the acoustic waves as determined optically. The method may be applicable in the study and diagnosis of superficial skin lesions.

Video redaction: a survey and comparison of enabling technologies

NASA Astrophysics Data System (ADS)

Sah, Shagan; Shringi, Ameya; Ptucha, Raymond; Burry, Aaron; Loce, Robert

2017-09-01

With the prevalence of video recordings from smart phones, dash cams, body cams, and conventional surveillance cameras, privacy protection has become a major concern, especially in light of legislation such as the Freedom of Information Act. Video redaction is used to obfuscate sensitive and personally identifiable information. Today's typical workflow involves simple detection, tracking, and manual intervention. Automated methods rely on accurate detection mechanisms being paired with robust tracking methods across the video sequence to ensure the redaction of all sensitive information while minimizing spurious obfuscations. Recent studies have explored the use of convolution neural networks and recurrent neural networks for object detection and tracking. The present paper reviews the redaction problem and compares a few state-of-the-art detection, tracking, and obfuscation methods as they relate to redaction. The comparison introduces an evaluation metric that is specific to video redaction performance. The metric can be evaluated in a manner that allows balancing the penalty for false negatives and false positives according to the needs of particular application, thereby assisting in the selection of component methods and their associated hyperparameters such that the redacted video has fewer frames that require manual review.

Nonlinear vibrational microscopy

DOEpatents

Holtom, Gary R.; Xie, Xiaoliang Sunney; Zumbusch, Andreas

2000-01-01

The present invention is a method and apparatus for microscopic vibrational imaging using coherent Anti-Stokes Raman Scattering or Sum Frequency Generation. Microscopic imaging with a vibrational spectroscopic contrast is achieved by generating signals in a nonlinear optical process and spatially resolved detection of the signals. The spatial resolution is attained by minimizing the spot size of the optical interrogation beams on the sample. Minimizing the spot size relies upon a. directing at least two substantially co-axial laser beams (interrogation beams) through a microscope objective providing a focal spot on the sample; b. collecting a signal beam together with a residual beam from the at least two co-axial laser beams after passing through the sample; c. removing the residual beam; and d. detecting the signal beam thereby creating said pixel. The method has significantly higher spatial resolution then IR microscopy and higher sensitivity than spontaneous Raman microscopy with much lower average excitation powers. CARS and SFG microscopy does not rely on the presence of fluorophores, but retains the resolution and three-dimensional sectioning capability of confocal and two-photon fluorescence microscopy. Complementary to these techniques, CARS and SFG microscopy provides a contrast mechanism based on vibrational spectroscopy. This vibrational contrast mechanism, combined with an unprecedented high sensitivity at a tolerable laser power level, provides a new approach for microscopic investigations of chemical and biological samples.

Colorimetric Detection of Ehrlichia Canis via Nucleic Acid Hybridization in Gold Nano-Colloids

PubMed Central

Muangchuen, Ajima; Chaumpluk, Piyasak; Suriyasomboon, Annop; Ekgasit, Sanong

2014-01-01

Canine monocytic ehrlichiosis (CME) is a major thick-bone disease of dog caused by Ehrlichia canis. Detection of this causal agent outside the laboratory using conventional methods is not effective enough. Thus an assay for E. canis detection based on the p30 outer membrane protein gene was developed. It was based on the p30 gene amplification using loop-mediated isothermal DNA amplification (LAMP). The primer set specific to six areas within the target gene were designed and tested for their sensitivity and specificity. Detection of DNA signals was based on modulation of gold nanoparticles' surface properties and performing DNA/DNA hybridization using an oligonucleotide probe. Presence of target DNA affected the gold colloid nanoparticles in terms of particle aggregation with a plasmonic color change of the gold colloids from ruby red to purple, visible by the naked eye. All the assay steps were completed within 90 min including DNA extraction without relying on standard laboratory facilities. This method was very specific to target bacteria. Its sensitivity with probe hybridization was sufficient to detect 50 copies of target DNA. This method should provide an alternative choice for point of care control and management of the disease. PMID:25111239

Searching for exoplanets using artificial intelligence

NASA Astrophysics Data System (ADS)

Pearson, Kyle A.; Palafox, Leon; Griffith, Caitlin A.

2018-02-01

In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labor intensive and subject to human error, the results of which are difficult to quantify. Here we present a new method of detecting exoplanet candidates in large planetary search projects which, unlike current methods uses a neural network. Neural networks, also called "deep learning" or "deep nets" are designed to give a computer perception into a specific problem by training it to recognize patterns. Unlike past transit detection algorithms deep nets learn to recognize planet features instead of relying on hand-coded metrics that humans perceive as the most representative. Our convolutional neural network is capable of detecting Earth-like exoplanets in noisy time-series data with a greater accuracy than a least-squares method. Deep nets are highly generalizable allowing data to be evaluated from different time series after interpolation without compromising performance. As validated by our deep net analysis of Kepler light curves, we detect periodic transits consistent with the true period without any model fitting. Our study indicates that machine learning will facilitate the characterization of exoplanets in future analysis of large astronomy data sets.

Colorimetric detection of Ehrlichia canis via nucleic acid hybridization in gold nano-colloids.

PubMed

Muangchuen, Ajima; Chaumpluk, Piyasak; Suriyasomboon, Annop; Ekgasit, Sanong

2014-08-08

Canine monocytic ehrlichiosis (CME) is a major thick-bone disease of dog caused by Ehrlichia canis. Detection of this causal agent outside the laboratory using conventional methods is not effective enough. Thus an assay for E. canis detection based on the p30 outer membrane protein gene was developed. It was based on the p30 gene amplification using loop-mediated isothermal DNA amplification (LAMP). The primer set specific to six areas within the target gene were designed and tested for their sensitivity and specificity. Detection of DNA signals was based on modulation of gold nanoparticles' surface properties and performing DNA/DNA hybridization using an oligonucleotide probe. Presence of target DNA affected the gold colloid nanoparticles in terms of particle aggregation with a plasmonic color change of the gold colloids from ruby red to purple, visible by the naked eye. All the assay steps were completed within 90 min including DNA extraction without relying on standard laboratory facilities. This method was very specific to target bacteria. Its sensitivity with probe hybridization was sufficient to detect 50 copies of target DNA. This method should provide an alternative choice for point of care control and management of the disease.

Statistical approaches to account for false-positive errors in environmental DNA samples.

PubMed

Lahoz-Monfort, José J; Guillera-Arroita, Gurutzeta; Tingley, Reid

2016-05-01

Environmental DNA (eDNA) sampling is prone to both false-positive and false-negative errors. We review statistical methods to account for such errors in the analysis of eDNA data and use simulations to compare the performance of different modelling approaches. Our simulations illustrate that even low false-positive rates can produce biased estimates of occupancy and detectability. We further show that removing or classifying single PCR detections in an ad hoc manner under the suspicion that such records represent false positives, as sometimes advocated in the eDNA literature, also results in biased estimation of occupancy, detectability and false-positive rates. We advocate alternative approaches to account for false-positive errors that rely on prior information, or the collection of ancillary detection data at a subset of sites using a sampling method that is not prone to false-positive errors. We illustrate the advantages of these approaches over ad hoc classifications of detections and provide practical advice and code for fitting these models in maximum likelihood and Bayesian frameworks. Given the severe bias induced by false-negative and false-positive errors, the methods presented here should be more routinely adopted in eDNA studies. © 2015 John Wiley & Sons Ltd.

Multiplex hydrolysis probe real-time PCR for simultaneous detection of hepatitis A virus and hepatitis E virus.

PubMed

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.

Selective chromogenic detection of thiol-containing biomolecules using carbonaceous nanospheres loaded with silver nanoparticles as carrier.

PubMed

Hu, Bo; Zhao, Yang; Zhu, Hai-Zhou; Yu, Shu-Hong

2011-04-26

Thiol-containing biomolecules show strong affinity with noble metal nanostructures and could not only stably protect them but also control the self-assembly process of these special nanostructures. A highly selective and sensitive chromogenic detection method has been designed for the low and high molecular weight thiol-containing biomolecules, including cysteine, glutathione, dithiothreitol, and bovine serum albumin, using a new type of carbonaceous nanospheres loaded with silver nanoparticles (Ag NPs) as carrier. This strategy relies upon the place-exchange process between the reporter dyes on the surface of Ag NPs and the thiol groups of thiol-containing biomolecules. The concentration of biomolecules can be determined by monitoring with the fluorescence intensity of reporter dyes dispersed in solution. This new chromogenic assay method could selectively detect these biomolecules in the presence of various other amino acids and monosaccharides and even sensitively detect the thiol-containing biomolecules with different molecular weight, even including proteins.

The gravitational wave stress–energy (pseudo)-tensor in modified gravity

NASA Astrophysics Data System (ADS)

Saffer, Alexander; Yunes, Nicolás; Yagi, Kent

2018-03-01

The recent detections of gravitational waves by the advanced LIGO and Virgo detectors open up new tests of modified gravity theories in the strong-field and dynamical, extreme gravity regime. Such tests rely sensitively on the phase evolution of the gravitational waves, which is controlled by the energy–momentum carried by such waves out of the system. We here study four different methods for finding the gravitational wave stress–energy pseudo-tensor in gravity theories with any combination of scalar, vector, or tensor degrees of freedom. These methods rely on the second variation of the action under short-wavelength averaging, the second perturbation of the field equations in the short-wavelength approximation, the construction of an energy complex leading to a Landau–Lifshitz tensor, and the use of Noether’s theorem in field theories about a flat background. We apply these methods in general relativity, Jordan–Fierz–Brans–Dicky theoy, and Einstein-Æther theory to find the gravitational wave stress–energy pseudo-tensor and calculate the rate at which energy and linear momentum is carried away from the system. The stress–energy tensor and the rate of linear momentum loss in Einstein-Æther theory are presented here for the first time. We find that all methods yield the same rate of energy loss, although the stress–energy pseudo-tensor can be functionally different. We also find that the Noether method yields a stress–energy tensor that is not symmetric or gauge-invariant, and symmetrization via the Belinfante procedure does not fix these problems because this procedure relies on Lorentz invariance, which is spontaneously broken in Einstein-Æther theory. The methods and results found here will be useful for the calculation of predictions in modified gravity theories that can then be contrasted with observations.

Heart rate detection from an electronic weighing scale.

PubMed

González-Landaeta, R; Casas, O; Pallàs-Areny, R

2007-01-01

We propose a novel technique for heart rate detection on a subject that stands on a common electronic weighing scale. The detection relies on sensing force variations related to the blood acceleration in the aorta, works even if wearing footwear, and does not require any sensors attached to the body. We have applied our method to three different weighing scales, and estimated whether their sensitivity and frequency response suited heart rate detection. Scale sensitivities were from 490 nV/V/N to 1670 nV/V/N, all had an underdamped transient response and their dynamic gain error was below 19% at 10 Hz, which are acceptable values for heart rate estimation. We also designed a pulse detection system based on off-the-shelf integrated circuits, whose gain was about 70x10(3) and able to sense force variations about 240 mN. The signal-to-noise ratio (SNR) of the main peaks of the pulse signal detected was higher than 48 dB, which is large enough to estimate the heart rate by simple signal processing methods. To validate the method, the ECG and the force signal were simultaneously recorded on 12 volunteers. The maximal error obtained from heart rates determined from these two signals was +/-0.6 beats/minute.

Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach

NASA Astrophysics Data System (ADS)

Schulz, Hans Martin; Thies, Boris; Chang, Shih-Chieh; Bendix, Jörg

2016-03-01

The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of ≈ 40, classification errors significantly increase.

A flow-cytometry-based method for detecting simultaneously five allergens in a complex food matrix.

PubMed

Otto, Gaetan; Lamote, Amandine; Deckers, Elise; Dumont, Valery; Delahaut, Philippe; Scippo, Marie-Louise; Pleck, Jessica; Hillairet, Caroline; Gillard, Nathalie

2016-12-01

To avoid carry-over contamination with allergens, food manufacturers implement quality control strategies relying primarily on detection of allergenic proteins by ELISA. Although sensitive and specific, this method allowed detection of only one allergen per analysis and effective control policies were thus based on multiplying the number of tests done in order to cover the whole range of allergens. We present in this work an immunoassay for the simultaneous detection of milk, egg, peanut, mustard and crustaceans in cookies samples. The method was based on a combination of flow cytometry with competitive ELISA where microbeads were used as sorbent surface. The test was able to detect the presence of the five allergens with median inhibitory concentrations (IC50) ranging from 2.5 to 15 mg/kg according to the allergen to be detected. The lowest concentrations of contaminants inducing a significant difference of signal between non-contaminated controls and test samples were 2 mg/kg of peanut, 5 mg/kg of crustaceans, 5 mg/kg of milk, 5 mg/kg of mustard and 10 mg/kg of egg. Assay sensitivity was influenced by the concentration of primary antibodies added to the sample extract for the competition and by the concentration of allergenic proteins bound to the surface of the microbeads.

SQUID-detected FMR: Resonance in single crystalline and polycrystalline yttrium iron garnet

NASA Astrophysics Data System (ADS)

O'Reilly, J. M.; Stamenov, P.

2018-04-01

Here two new techniques for the detection of broadband (100 MHz-20 GHz) ferromagnetic resonance (FMR)/ferrimagnetic resonance in single and poly-crystalline materials, which rely on SQUID-based gradiometry detection of small changes in the magnetisation, are developed. In the first method, small changes in the along-the-applied-field projection of the coupled magnetic moment (Δmz) are detected as the material is driven into resonance. Absolute measurement of the longitudinal component of the magnetisation and the resonance induced lowering of this moment makes estimation of the precession cone angle accessible, which is typically difficult to extract using conventional cavity or stripline based detection methods. The second method invokes the change in Δmz with the resonance-induced thermal heating (d/mz d T ). Magnetisation dynamics in bulk Y3Fe5O12 are observed over a broad range of experimental temperatures (4 K-400 K) and fields (10-500 mT). The inhomogeneous microwave excitation allows for the observation of higher magnetostatic modes and the convenient tracking of very broad resonances. The two SQUID-detection techniques when combined with conventional broadband vector network analyser-FMR, low-frequency magnetic susceptibility, and DC magnetometry, all easily realised, essentially concurrently, using the same module, greatly expand the amount of static and dynamic information accessible.

Multiview face detection based on position estimation over multicamera surveillance system

NASA Astrophysics Data System (ADS)

Huang, Ching-chun; Chou, Jay; Shiu, Jia-Hou; Wang, Sheng-Jyh

2012-02-01

In this paper, we propose a multi-view face detection system that locates head positions and indicates the direction of each face in 3-D space over a multi-camera surveillance system. To locate 3-D head positions, conventional methods relied on face detection in 2-D images and projected the face regions back to 3-D space for correspondence. However, the inevitable false face detection and rejection usually degrades the system performance. Instead, our system searches for the heads and face directions over the 3-D space using a sliding cube. Each searched 3-D cube is projected onto the 2-D camera views to determine the existence and direction of human faces. Moreover, a pre-process to estimate the locations of candidate targets is illustrated to speed-up the searching process over the 3-D space. In summary, our proposed method can efficiently fuse multi-camera information and suppress the ambiguity caused by detection errors. Our evaluation shows that the proposed approach can efficiently indicate the head position and face direction on real video sequences even under serious occlusion.

Residual pesticide detection on food with particle-enhanced Raman scattering

NASA Astrophysics Data System (ADS)

Ranjan, Bikas; Huang, LiChuan; Masui, Kyoko; Saito, Yuika; Verma, Prabhat

2014-08-01

Modern farming relies highly on pesticides to protect agricultural food items from insects for high yield and better quality. Increasing use of pesticide has raised concern about its harmful effects on human health and hence it has become very important to detect even small amount of pesticide residues. Raman spectroscopy is a suitable nondestructive method for pesticide detection, however, it is not very effective for low concentration of pesticide molecules. Here, we report an approach based on plasmonic enhancement, namely, particle enhanced Raman spectroscopy (PERS), which is rapid, nondestructive and sensitive. In this technique, Raman signals are enhanced via the resonance excitation of localized plasmons in metallic nanoparticles. Gold nanostructures are promising materials that have ability to tune surface plasmon resonance frequency in visible to near-IR, which depends on shape and size of nanostructures. We synthesized gold nanorods (GNRs) with desired shape and size by seed mediated growth method, and successfully detected very tiny amount of pesticide present on food items. We also conformed that the detection of pesticide was not possible by usual Raman spectroscopy.

SuBSENSE: a universal change detection method with local adaptive sensitivity.

PubMed

St-Charles, Pierre-Luc; Bilodeau, Guillaume-Alexandre; Bergevin, Robert

2015-01-01

Foreground/background segmentation via change detection in video sequences is often used as a stepping stone in high-level analytics and applications. Despite the wide variety of methods that have been proposed for this problem, none has been able to fully address the complex nature of dynamic scenes in real surveillance tasks. In this paper, we present a universal pixel-level segmentation method that relies on spatiotemporal binary features as well as color information to detect changes. This allows camouflaged foreground objects to be detected more easily while most illumination variations are ignored. Besides, instead of using manually set, frame-wide constants to dictate model sensitivity and adaptation speed, we use pixel-level feedback loops to dynamically adjust our method's internal parameters without user intervention. These adjustments are based on the continuous monitoring of model fidelity and local segmentation noise levels. This new approach enables us to outperform all 32 previously tested state-of-the-art methods on the 2012 and 2014 versions of the ChangeDetection.net dataset in terms of overall F-Measure. The use of local binary image descriptors for pixel-level modeling also facilitates high-speed parallel implementations: our own version, which used no low-level or architecture-specific instruction, reached real-time processing speed on a midlevel desktop CPU. A complete C++ implementation based on OpenCV is available online.

An autonomous surface discontinuity detection and quantification method by digital image correlation and phase congruency

NASA Astrophysics Data System (ADS)

Cinar, A. F.; Barhli, S. M.; Hollis, D.; Flansbjer, M.; Tomlinson, R. A.; Marrow, T. J.; Mostafavi, M.

2017-09-01

Digital image correlation has been routinely used to measure full-field displacements in many areas of solid mechanics, including fracture mechanics. Accurate segmentation of the crack path is needed to study its interaction with the microstructure and stress fields, and studies of crack behaviour, such as the effect of closure or residual stress in fatigue, require data on its opening displacement. Such information can be obtained from any digital image correlation analysis of cracked components, but it collection by manual methods is quite onerous, particularly for massive amounts of data. We introduce the novel application of Phase Congruency to detect and quantify cracks and their opening. Unlike other crack detection techniques, Phase Congruency does not rely on adjustable threshold values that require user interaction, and so allows large datasets to be treated autonomously. The accuracy of the Phase Congruency based algorithm in detecting cracks is evaluated and compared with conventional methods such as Heaviside function fitting. As Phase Congruency is a displacement-based method, it does not suffer from the noise intensification to which gradient-based methods (e.g. strain thresholding) are susceptible. Its application is demonstrated to experimental data for cracks in quasi-brittle (Granitic rock) and ductile (Aluminium alloy) materials.

Markov Chain Monte Carlo estimation of species distributions: a case study of the swift fox in western Kansas

USGS Publications Warehouse

Sargeant, Glen A.; Sovada, Marsha A.; Slivinski, Christiane C.; Johnson, Douglas H.

2005-01-01

Accurate maps of species distributions are essential tools for wildlife research and conservation. Unfortunately, biologists often are forced to rely on maps derived from observed occurrences recorded opportunistically during observation periods of variable length. Spurious inferences are likely to result because such maps are profoundly affected by the duration and intensity of observation and by methods used to delineate distributions, especially when detection is uncertain. We conducted a systematic survey of swift fox (Vulpes velox) distribution in western Kansas, USA, and used Markov chain Monte Carlo (MCMC) image restoration to rectify these problems. During 1997–1999, we searched 355 townships (ca. 93 km) 1–3 times each for an average cost of $7,315 per year and achieved a detection rate (probability of detecting swift foxes, if present, during a single search) of = 0.69 (95% Bayesian confidence interval [BCI] = [0.60, 0.77]). Our analysis produced an estimate of the underlying distribution, rather than a map of observed occurrences, that reflected the uncertainty associated with estimates of model parameters. To evaluate our results, we analyzed simulated data with similar properties. Results of our simulations suggest negligible bias and good precision when probabilities of detection on ≥1 survey occasions (cumulative probabilities of detection) exceed 0.65. Although the use of MCMC image restoration has been limited by theoretical and computational complexities, alternatives do not possess the same advantages. Image models accommodate uncertain detection, do not require spatially independent data or a census of map units, and can be used to estimate species distributions directly from observations without relying on habitat covariates or parameters that must be estimated subjectively. These features facilitate economical surveys of large regions, the detection of temporal trends in distribution, and assessments of landscape-level relations between species and habitats. Requirements for the use of MCMC image restoration include study areas that can be partitioned into regular grids of mapping units, spatially contagious species distributions, reliable methods for identifying target species, and cumulative probabilities of detection ≥0.65.

Markov chain Monte Carlo estimation of species distributions: A case study of the swift fox in western Kansas

USGS Publications Warehouse

Sargeant, G.A.; Sovada, M.A.; Slivinski, C.C.; Johnson, D.H.

2005-01-01

Accurate maps of species distributions are essential tools for wildlife research and conservation. Unfortunately, biologists often are forced to rely on maps derived from observed occurrences recorded opportunistically during observation periods of variable length. Spurious inferences are likely to result because such maps are profoundly affected by the duration and intensity of observation and by methods used to delineate distributions, especially when detection is uncertain. We conducted a systematic survey of swift fox (Vulpes velox) distribution in western Kansas, USA, and used Markov chain Monte Carlo (MCMC) image restoration to rectify these problems. During 1997-1999, we searched 355 townships (ca. 93 km2) 1-3 times each for an average cost of $7,315 per year and achieved a detection rate (probability of detecting swift foxes, if present, during a single search) of ?? = 0.69 (95% Bayesian confidence interval [BCI] = [0.60, 0.77]). Our analysis produced an estimate of the underlying distribution, rather than a map of observed occurrences, that reflected the uncertainty associated with estimates of model parameters. To evaluate our results, we analyzed simulated data with similar properties. Results of our simulations suggest negligible bias and good precision when probabilities of detection on ???1 survey occasions (cumulative probabilities of detection) exceed 0.65. Although the use of MCMC image restoration has been limited by theoretical and computational complexities, alternatives do not possess the same advantages. Image models accommodate uncertain detection, do not require spatially independent data or a census of map units, and can be used to estimate species distributions directly from observations without relying on habitat covariates or parameters that must be estimated subjectively. These features facilitate economical surveys of large regions, the detection of temporal trends in distribution, and assessments of landscape-level relations between species and habitats. Requirements for the use of MCMC image restoration include study areas that can be partitioned into regular grids of mapping units, spatially contagious species distributions, reliable methods for identifying target species, and cumulative probabilities of detection ???0.65.

Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru

USGS Publications Warehouse

Shermeyer, Jacob S.; Haack, Barry N.

2015-01-01

Two forestry-change detection methods are described, compared, and contrasted for estimating deforestation and growth in threatened forests in southern Peru from 2000 to 2010. The methods used in this study rely on freely available data, including atmospherically corrected Landsat 5 Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF). The two methods include a conventional supervised signature extraction method and a unique self-calibrating method called MODIS VCF guided forest/nonforest (FNF) masking. The process chain for each of these methods includes a threshold classification of MODIS VCF, training data or signature extraction, signature evaluation, k-nearest neighbor classification, analyst-guided reclassification, and postclassification image differencing to generate forest change maps. Comparisons of all methods were based on an accuracy assessment using 500 validation pixels. Results of this accuracy assessment indicate that FNF masking had a 5% higher overall accuracy and was superior to conventional supervised classification when estimating forest change. Both methods succeeded in classifying persistently forested and nonforested areas, and both had limitations when classifying forest change.

Detection of entanglement in asymmetric quantum networks and multipartite quantum steering.

PubMed

Cavalcanti, D; Skrzypczyk, P; Aguilar, G H; Nery, R V; Ribeiro, P H Souto; Walborn, S P

2015-08-03

The future of quantum communication relies on quantum networks composed by observers sharing multipartite quantum states. The certification of multipartite entanglement will be crucial to the usefulness of these networks. In many real situations it is natural to assume that some observers are more trusted than others in the sense that they have more knowledge of their measurement apparatuses. Here we propose a general method to certify all kinds of multipartite entanglement in this asymmetric scenario and experimentally demonstrate it in an optical experiment. Our results, which can be seen as a definition of genuine multipartite quantum steering, give a method to detect entanglement in a scenario in between the standard entanglement and fully device-independent scenarios, and provide a basis for semi-device-independent cryptographic applications in quantum networks.

Estimating Divergence Parameters With Small Samples From a Large Number of Loci

PubMed Central

Wang, Yong; Hey, Jody

2010-01-01

Most methods for studying divergence with gene flow rely upon data from many individuals at few loci. Such data can be useful for inferring recent population history but they are unlikely to contain sufficient information about older events. However, the growing availability of genome sequences suggests a different kind of sampling scheme, one that may be more suited to studying relatively ancient divergence. Data sets extracted from whole-genome alignments may represent very few individuals but contain a very large number of loci. To take advantage of such data we developed a new maximum-likelihood method for genomic data under the isolation-with-migration model. Unlike many coalescent-based likelihood methods, our method does not rely on Monte Carlo sampling of genealogies, but rather provides a precise calculation of the likelihood by numerical integration over all genealogies. We demonstrate that the method works well on simulated data sets. We also consider two models for accommodating mutation rate variation among loci and find that the model that treats mutation rates as random variables leads to better estimates. We applied the method to the divergence of Drosophila melanogaster and D. simulans and detected a low, but statistically significant, signal of gene flow from D. simulans to D. melanogaster. PMID:19917765

Searching for disease-susceptibility loci by testing for Hardy-Weinberg disequilibrium in a gene bank of affected individuals.

PubMed

Lee, Wen-Chung

2003-09-01

The future of genetic studies of complex human diseases will rely more and more on the epidemiologic association paradigm. The author proposes to scan the genome for disease-susceptibility gene(s) by testing for deviation from Hardy-Weinberg equilibrium in a gene bank of affected individuals. A power formula is presented, which is very accurate as revealed by Monte Carlo simulations. If the disease-susceptibility gene is recessive with an allele frequency of < or = 0.5 or dominant with an allele frequency of > or = 0.5, the number of subjects needed by the present method is smaller than that needed by using a case-parents design (using either the transmission/disequilibrium test or the 2-df likelihood ratio test). However, the method cannot detect genes with a multiplicative mode of inheritance, and the validity of the method relies on the assumption that the source population from which the cases arise is in Hardy-Weinberg equilibrium. Thus, it is prone to produce false positive and false negative results. Nevertheless, the method enables rapid gene hunting in an existing gene bank of affected individuals with no extra effort beyond simple calculations.

Research Advances: Pacific Northwest National Laboratory Finds New Way to Detect Destructive Enzyme Activity--Hair Dye Relies on Nanotechnology--Ways to Increase Shelf Life of Milk

ERIC Educational Resources Information Center

King, Angela G.

2007-01-01

Recent advances in various research fields are described. Scientists at the Pacific Northwest National Laboratory have found a new way to detect destructive enzyme activity, scientists in France have found that an ancient hair dye used by ancient people in Greece and Rome relied on nanotechnology and in the U.S. scientists are developing new…

Molecular methods for pathogen and microbial community detection and characterization: current and potential application in diagnostic microbiology.

PubMed

Sibley, Christopher D; Peirano, Gisele; Church, Deirdre L

2012-04-01

Clinical microbiology laboratories worldwide have historically relied on phenotypic methods (i.e., culture and biochemical tests) for detection, identification and characterization of virulence traits (e.g., antibiotic resistance genes, toxins) of human pathogens. However, limitations to implementation of molecular methods for human infectious diseases testing are being rapidly overcome allowing for the clinical evaluation and implementation of diverse technologies with expanding diagnostic capabilities. The advantages and limitation of molecular techniques including real-time polymerase chain reaction, partial or whole genome sequencing, molecular typing, microarrays, broad-range PCR and multiplexing will be discussed. Finally, terminal restriction fragment length polymorphism (T-RFLP) and deep sequencing are introduced as technologies at the clinical interface with the potential to dramatically enhance our ability to diagnose infectious diseases and better define the epidemiology and microbial ecology of a wide range of complex infections. Copyright © 2012 Elsevier B.V. All rights reserved.

An efficient method for facial component detection in thermal images

NASA Astrophysics Data System (ADS)

Paul, Michael; Blanik, Nikolai; Blazek, Vladimir; Leonhardt, Steffen

2015-04-01

A method to detect certain regions in thermal images of human faces is presented. In this approach, the following steps are necessary to locate the periorbital and the nose regions: First, the face is segmented from the background by thresholding and morphological filtering. Subsequently, a search region within the face, around its center of mass, is evaluated. Automatically computed temperature thresholds are used per subject and image or image sequence to generate binary images, in which the periorbital regions are located by integral projections. Then, the located positions are used to approximate the nose position. It is possible to track features in the located regions. Therefore, these regions are interesting for different applications like human-machine interaction, biometrics and biomedical imaging. The method is easy to implement and does not rely on any training images or templates. Furthermore, the approach saves processing resources due to simple computations and restricted search regions.

Molecular dispersion spectroscopy for chemical sensing using chirped mid-infrared quantum cascade laser.

PubMed

Wysocki, Gerard; Weidmann, Damien

2010-12-06

A spectroscopic method of molecular detection based on dispersion measurements using a frequency-chirped laser source is presented. An infrared quantum cascade laser emitting around 1912 cm(-1) is used as a tunable spectroscopic source to measure dispersion that occurs in the vicinity of molecular ro-vibrational transitions. The sample under study is a mixture of nitric oxide in dry nitrogen. Two experimental configurations based on a coherent detection scheme are investigated and discussed. The theoretical models, which describe the observed spectral signals, are developed and verified experimentally. The method is particularly relevant to optical sensing based on mid-infrared quantum cascade lasers as the high chirp rates available with those sources can significantly enhance the magnitude of the measured dispersion signals. The method relies on heterodyne beatnote frequency measurements and shows high immunity to variations in the optical power received by the photodetector.

Diagnostic testing for Giardia infections.

PubMed

Heyworth, Martin F

2014-03-01

The traditional method for diagnosing Giardia infections involves microscopic examination of faecal specimens for Giardia cysts. This method is subjective and relies on observer experience. From the 1980s onwards, objective techniques have been developed for diagnosing Giardia infections, and are superseding diagnostic techniques reliant on microscopy. Detection of Giardia antigen(s) by immunoassay is the basis of commercially available diagnostic kits. Various nucleic acid amplification techniques (NAATs) can demonstrate DNA of Giardia intestinalis, and have the potential to become standard approaches for diagnosing Giardia infections. Of such techniques, methods involving either fluorescent microspheres (Luminex) or isothermal amplification of DNA (loop-mediated isothermal amplification; LAMP) are especially promising.

Passive quantum error correction of linear optics networks through error averaging

NASA Astrophysics Data System (ADS)

Marshman, Ryan J.; Lund, Austin P.; Rohde, Peter P.; Ralph, Timothy C.

2018-02-01

We propose and investigate a method of error detection and noise correction for bosonic linear networks using a method of unitary averaging. The proposed error averaging does not rely on ancillary photons or control and feedforward correction circuits, remaining entirely passive in its operation. We construct a general mathematical framework for this technique and then give a series of proof of principle examples including numerical analysis. Two methods for the construction of averaging are then compared to determine the most effective manner of implementation and probe the related error thresholds. Finally we discuss some of the potential uses of this scheme.

Multiplex Hydrolysis Probe Real-Time PCR for Simultaneous Detection of Hepatitis A Virus and Hepatitis E Virus

PubMed Central

Qiu, Feng; Cao, Jingyuan; Su, Qiudong; Yi, Yao; Bi, Shengli

2014-01-01

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. PMID:24886818

Direct Detection of Hardly Detectable Hidden Chirality of Hydrocarbons and Deuterated Isotopomers by a Helical Polyacetylene through Chiral Amplification and Memory.

PubMed

Maeda, Katsuhiro; Hirose, Daisuke; Okoshi, Natsuki; Shimomura, Kouhei; Wada, Yuya; Ikai, Tomoyuki; Kanoh, Shigeyoshi; Yashima, Eiji

2018-03-07

We report the first direct chirality sensing of a series of chiral hydrocarbons and isotopically chiral compounds (deuterated isotopomers), which are almost impossible to detect by conventional optical spectroscopic methods, by a stereoregular polyacetylene bearing 2,2'-biphenol-derived pendants. The polyacetylene showed a circular dichroism due to a preferred-handed helix formation in response to the hardly detectable hidden chirality of saturated tertiary or chiroptical quaternary hydrocarbons, and deuterated isotopomers. In sharp contrast to the previously reported sensory systems, the chirality detection by the polyacetylene relies on an excess one-handed helix formation induced by the chiral hydrocarbons and deuterated isotopomers via significant amplification of the chirality followed by its static memory, through which chiral information on the minute and hidden chirality can be stored as an excess of a single-handed helix memory for a long time.

Strategies and limitations for fluorescence detection of XAFS at high flux beamlines

DOE PAGES

Heald, Steve M.

2015-02-17

The issue of detecting the XAFS signal from dilute samples is discussed in detail with the aim of making best use of high flux beamlines that provide up to 10 13 photons -1. Various detection methods are compared, including filters with slits, solid state detectors, crystal analyzers and combinations of these. These comparisons rely on simulations that use experimentally determined parameters. It is found that inelastic scattering places a fundamental limit on detection, and that it is important to take proper account of the polarization dependence of the signals. The combination of a filter–slit system with a solid state detectormore » is a promising approach. With an optimized system good performance can be obtained even if the total count rate is limited to 10 7 Hz. Detection schemes with better energy resolution can help at the largest dilutions if their collection efficiency and count rate limits can be improved.« less

Strategies and limitations for fluorescence detection of XAFS at high flux beamlines

PubMed Central

Heald, Steve M.

2015-01-01

The issue of detecting the XAFS signal from dilute samples is discussed in detail with the aim of making best use of high flux beamlines that provide up to 1013 photons s−1. Various detection methods are compared, including filters with slits, solid state detectors, crystal analyzers and combinations of these. These comparisons rely on simulations that use experimentally determined parameters. It is found that inelastic scattering places a fundamental limit on detection, and that it is important to take proper account of the polarization dependence of the signals. The combination of a filter–slit system with a solid state detector is a promising approach. With an optimized system good performance can be obtained even if the total count rate is limited to 107 Hz. Detection schemes with better energy resolution can help at the largest dilutions if their collection efficiency and count rate limits can be improved. PMID:25723945

Towards a magnetoresistive platform for neural signal recording

NASA Astrophysics Data System (ADS)

Sharma, P. P.; Gervasoni, G.; Albisetti, E.; D'Ercoli, F.; Monticelli, M.; Moretti, D.; Forte, N.; Rocchi, A.; Ferrari, G.; Baldelli, P.; Sampietro, M.; Benfenati, F.; Bertacco, R.; Petti, D.

2017-05-01

A promising strategy to get deeper insight on brain functionalities relies on the investigation of neural activities at the cellular and sub-cellular level. In this framework, methods for recording neuron electrical activity have gained interest over the years. Main technological challenges are associated to finding highly sensitive detection schemes, providing considerable spatial and temporal resolution. Moreover, the possibility to perform non-invasive assays would constitute a noteworthy benefit. In this work, we present a magnetoresistive platform for the detection of the action potential propagation in neural cells. Such platform allows, in perspective, the in vitro recording of neural signals arising from single neurons, neural networks and brain slices.

Studies on protozoa in ancient remains - A Review

PubMed Central

Frías, Liesbeth; Leles, Daniela; Araújo, Adauto

2013-01-01

Paleoparasitological research has made important contributions to the understanding of parasite evolution and ecology. Although parasitic protozoa exhibit a worldwide distribution, recovering these organisms from an archaeological context is still exceptional and relies on the availability and distribution of evidence, the ecology of infectious diseases and adequate detection techniques. Here, we present a review of the findings related to protozoa in ancient remains, with an emphasis on their geographical distribution in the past and the methodologies used for their retrieval. The development of more sensitive detection methods has increased the number of identified parasitic species, promising interesting insights from research in the future. PMID:23440107

Automated muscle wrapping using finite element contact detection.

PubMed

Favre, Philippe; Gerber, Christian; Snedeker, Jess G

2010-07-20

Realistic muscle path representation is essential to musculoskeletal modeling of joint function. Algorithms predicting these muscle paths typically rely on a labor intensive predefinition of via points or underlying geometries to guide wrapping for given joint positions. While muscle wrapping using anatomically precise three-dimensional (3D) finite element (FE) models of bone and muscle has been achieved, computational expense and pre-processing associated with this approach exclude its use in applications such as subject-specific modeling. With the intention of combining advantageous features of both approaches, an intermediate technique relying on contact detection capabilities of commercial FE packages is presented. We applied the approach to the glenohumeral joint, and validated the method by comparison against existing experimental data. Individual muscles were modeled as a straight series of deformable beam elements and bones as anatomically precise 3D rigid bodies. Only the attachment locations and a default orientation of the undeformed muscle segment were pre-defined. The joint was then oriented in a static position of interest. The muscle segment free end was then moved along the shortest Euclidean path to its origin on the scapula, wrapping the muscle along bone surfaces by relying on software contact detection. After wrapping for a given position, the resulting moment arm was computed as the perpendicular distance from the line of action vector to the humeral head center of rotation. This approach reasonably predicted muscle length and moment arm for 27 muscle segments when compared to experimental measurements over a wide range of shoulder motion. Artificial via points or underlying contact geometries were avoided, contact detection and multiobject wrapping on the bone surfaces were automatic, and low computational cost permitted wrapping of individual muscles within seconds on a standard desktop PC. These advantages may be valuable for both general and subject-specific musculoskeletal modeling. 2010 Elsevier Ltd. All rights reserved.

Extraction and analysis of neuron firing signals from deep cortical video microscopy

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

Kerekes, Ryan A; Blundon, Jay

We introduce a method for extracting and analyzing neuronal activity time signals from video of the cortex of a live animal. The signals correspond to the firing activity of individual cortical neurons. Activity signals are based on the changing fluorescence of calcium indicators in the cells over time. We propose a cell segmentation method that relies on a user-specified center point, from which the signal extraction method proceeds. A stabilization approach is used to reduce tissue motion in the video. The extracted signal is then processed to flatten the baseline and detect action potentials. We show results from applying themore » method to a cortical video of a live mouse.« less

Multidrug-resistant tuberculosis treatment failure detection depends on monitoring interval and microbiological method

PubMed Central

White, Richard A.; Lu, Chunling; Rodriguez, Carly A.; Bayona, Jaime; Becerra, Mercedes C.; Burgos, Marcos; Centis, Rosella; Cohen, Theodore; Cox, Helen; D'Ambrosio, Lia; Danilovitz, Manfred; Falzon, Dennis; Gelmanova, Irina Y.; Gler, Maria T.; Grinsdale, Jennifer A.; Holtz, Timothy H.; Keshavjee, Salmaan; Leimane, Vaira; Menzies, Dick; Milstein, Meredith B.; Mishustin, Sergey P.; Pagano, Marcello; Quelapio, Maria I.; Shean, Karen; Shin, Sonya S.; Tolman, Arielle W.; van der Walt, Martha L.; Van Deun, Armand; Viiklepp, Piret

2016-01-01

Debate persists about monitoring method (culture or smear) and interval (monthly or less frequently) during treatment for multidrug-resistant tuberculosis (MDR-TB). We analysed existing data and estimated the effect of monitoring strategies on timing of failure detection. We identified studies reporting microbiological response to MDR-TB treatment and solicited individual patient data from authors. Frailty survival models were used to estimate pooled relative risk of failure detection in the last 12 months of treatment; hazard of failure using monthly culture was the reference. Data were obtained for 5410 patients across 12 observational studies. During the last 12 months of treatment, failure detection occurred in a median of 3 months by monthly culture; failure detection was delayed by 2, 7, and 9 months relying on bimonthly culture, monthly smear and bimonthly smear, respectively. Risk (95% CI) of failure detection delay resulting from monthly smear relative to culture is 0.38 (0.34–0.42) for all patients and 0.33 (0.25–0.42) for HIV-co-infected patients. Failure detection is delayed by reducing the sensitivity and frequency of the monitoring method. Monthly monitoring of sputum cultures from patients receiving MDR-TB treatment is recommended. Expanded laboratory capacity is needed for high-quality culture, and for smear microscopy and rapid molecular tests. PMID:27587552

A universal TaqMan-based RT-PCR protocol for cost-efficient detection of small noncoding RNA.

PubMed

Jung, Ulrike; Jiang, Xiaoou; Kaufmann, Stefan H E; Patzel, Volker

2013-12-01

Several methods for the detection of RNA have been developed over time. For small RNA detection, a stem-loop reverse primer-based protocol relying on TaqMan RT-PCR has been described. This protocol requires an individual specific TaqMan probe for each target RNA and, hence, is highly cost-intensive for experiments with small sample sizes or large numbers of different samples. We describe a universal TaqMan-based probe protocol which can be used to detect any target sequence and demonstrate its applicability for the detection of endogenous as well as artificial eukaryotic and bacterial small RNAs. While the specific and the universal probe-based protocol showed the same sensitivity, the absolute sensitivity of detection was found to be more than 100-fold lower for both than previously reported. In subsequent experiments, we found previously unknown limitations intrinsic to the method affecting its feasibility in determination of mature template RISC incorporation as well as in multiplexing. Both protocols were equally specific in discriminating between correct and incorrect small RNA targets or between mature miRNA and its unprocessed RNA precursor, indicating the stem-loop RT-primer, but not the TaqMan probe, triggers target specificity. The presented universal TaqMan-based RT-PCR protocol represents a cost-efficient method for the detection of small RNAs.

Automated detection of pain from facial expressions: a rule-based approach using AAM

NASA Astrophysics Data System (ADS)

Chen, Zhanli; Ansari, Rashid; Wilkie, Diana J.

2012-02-01

In this paper, we examine the problem of using video analysis to assess pain, an important problem especially for critically ill, non-communicative patients, and people with dementia. We propose and evaluate an automated method to detect the presence of pain manifested in patient videos using a unique and large collection of cancer patient videos captured in patient homes. The method is based on detecting pain-related facial action units defined in the Facial Action Coding System (FACS) that is widely used for objective assessment in pain analysis. In our research, a person-specific Active Appearance Model (AAM) based on Project-Out Inverse Compositional Method is trained for each patient individually for the modeling purpose. A flexible representation of the shape model is used in a rule-based method that is better suited than the more commonly used classifier-based methods for application to the cancer patient videos in which pain-related facial actions occur infrequently and more subtly. The rule-based method relies on the feature points that provide facial action cues and is extracted from the shape vertices of AAM, which have a natural correspondence to face muscular movement. In this paper, we investigate the detection of a commonly used set of pain-related action units in both the upper and lower face. Our detection results show good agreement with the results obtained by three trained FACS coders who independently reviewed and scored the action units in the cancer patient videos.

Biosensing Using Magnetic Particle Detection Techniques

PubMed Central

Chen, Yi-Ting; Kolhatkar, Arati G.; Zenasni, Oussama; Xu, Shoujun

2017-01-01

Magnetic particles are widely used as signal labels in a variety of biological sensing applications, such as molecular detection and related strategies that rely on ligand-receptor binding. In this review, we explore the fundamental concepts involved in designing magnetic particles for biosensing applications and the techniques used to detect them. First, we briefly describe the magnetic properties that are important for bio-sensing applications and highlight the associated key parameters (such as the starting materials, size, functionalization methods, and bio-conjugation strategies). Subsequently, we focus on magnetic sensing applications that utilize several types of magnetic detection techniques: spintronic sensors, nuclear magnetic resonance (NMR) sensors, superconducting quantum interference devices (SQUIDs), sensors based on the atomic magnetometer (AM), and others. From the studies reported, we note that the size of the MPs is one of the most important factors in choosing a sensing technique. PMID:28994727

Recent advances in rapid pathogen detection method based on biosensors.

PubMed

Chen, Ying; Wang, Zhenzhen; Liu, Yingxun; Wang, Xin; Li, Ying; Ma, Ping; Gu, Bing; Li, Hongchun

2018-06-01

As strain variation and drug resistance become more pervasive, the prevention and control of infection have been a serious problem in recent years. The detection of pathogen is one of the most important parts of the process of diagnosis. Having a series of advantages, such as rapid response, high sensitivity, ease of use, and low cost, biosensors have received much attention and been studied deeply. Moreover, relying on its characteristics of small size, real time, and multiple analyses, biosensors have developed rapidly and used widely and are expected to be applied for microbiological detection in order to meet higher accuracy required by clinical diagnosis. The main goal of this contribution is not to simply collect and list all papers related to pathogen detection based on biosensors published recently, but to discuss critically the development and application of many kinds of biosensors such as electrochemical (amperometric, impedimetric, potentiometric, and conductometric), optical (fluorescent, fibre optic and surface plasmon resonance), and piezoelectric (quartz crystal microbalances and atomic force microscopy) biosensors in pathogen detection as well as the comparisons with the existing clinical detection methods (traditional culture, enzyme-linked immunosorbent assay, polymerase chain reaction, and mass spectrometry).

Biosensor UUV payload for underwater detection

NASA Astrophysics Data System (ADS)

Kusterbeck, Anne W.; Charles, Paul T.; Melde, Brian J.; Trammell, Scott A.; Adams, André A.; Deschamps, Jeffrey R.

2010-04-01

Increased emphasis on maritime domain awareness and port security has led to the development of unmanned underwater vehicles (UUVs) capable of extended missions. These systems rely most frequently on well-developed side scan sonar and acoustic methods to locate potential targets. The Naval Research Laboratory (NRL) is developing biosensors for underwater explosives detection that complement acoustic sensors and can be used as UUV payloads to monitor areas for port and harbor security or in detection of underwater unexploded ordnance (UXO) and biochemical threats. The prototype sensor has recently been demonstrated to detect explosives in seawater at trace levels when run in a continuous sampling mode. To overcome ongoing issues with sample preparation and facilitate rapid detection at trace levels in a marine environment, we have been developing new mesoporous materials for in-line preconcentration of explosives and other small molecules, engineering microfluidic components to improve the signal, and testing alternative signal transduction methods. Additional work is being done to optimize the optical components and sensor response time. Highlights of these current studies and our ongoing efforts to integrate the biosensor with existing detection technologies to reduce false positives are described. In addition, we present the results of field tests that demonstrate the prototype biosensor performance as a UUV payload.

Molecular diagnostics for human leptospirosis.

PubMed

Waggoner, Jesse J; Pinsky, Benjamin A

2016-10-01

The definitive diagnosis of leptospirosis, which results from infection with spirochetes of the genus Leptospira, currently relies on the use of culture, serological testing (microscopic agglutination testing), and molecular detection. The purpose of this review is to describe new molecular diagnostics for Leptospira and discuss advancements in the use of available methods. Efforts have been focused on improving the clinical sensitivity of Leptospira detection using molecular methods. In this review, we describe a reoptimized pathogenic species-specific real-time PCR (targeting lipL32) that has demonstrated improved sensitivity, findings by two groups that real-time reverse-transcription PCR assays targeting the 16S rrs gene can improve detection, and two new loop-mediated amplification techniques. Quantitation of leptospiremia, detection in different specimen types, and the complementary roles played by molecular detection and microscopic agglutination testing will be discussed. Finally, a protocol for Leptospira strain subtyping using variable number tandem repeat targets and high-resolution melting will be described. Molecular diagnostics have an established role for the diagnosis of leptospirosis and provide an actionable diagnosis in the acute setting. The use of real-time reverse-transcription PCR for testing serum/plasma and cerebrospinal fluid, when available, may improve the detection of Leptospira without decreasing clinical specificity.

Multicentric Comparative Analytical Performance Study for Molecular Detection of Low Amounts of Toxoplasma gondii from Simulated Specimens▿ †

PubMed Central

Sterkers, Yvon; Varlet-Marie, Emmanuelle; Cassaing, Sophie; Brenier-Pinchart, Marie-Pierre; Brun, Sophie; Dalle, Frédéric; Delhaes, Laurence; Filisetti, Denis; Pelloux, Hervé; Yera, Hélène; Bastien, Patrick

2010-01-01

Although screening for maternal toxoplasmic seroconversion during pregnancy is based on immunodiagnostic assays, the diagnosis of clinically relevant toxoplasmosis greatly relies upon molecular methods. A problem is that this molecular diagnosis is subject to variation of performances, mainly due to a large diversity of PCR methods and primers and the lack of standardization. The present multicentric prospective study, involving eight laboratories proficient in the molecular prenatal diagnosis of toxoplasmosis, was a first step toward the harmonization of this diagnosis among university hospitals in France. Its aim was to compare the analytical performances of different PCR protocols used for Toxoplasma detection. Each center extracted the same concentrated Toxoplasma gondii suspension and tested serial dilutions of the DNA using its own assays. Differences in analytical sensitivities were observed between assays, particularly at low parasite concentrations (≤2 T. gondii genomes per reaction tube), with “performance scores” differing by a 20-fold factor among laboratories. Our data stress the fact that differences do exist in the performances of molecular assays in spite of expertise in the matter; we propose that laboratories work toward a detection threshold defined for a best sensitivity of this diagnosis. Moreover, on the one hand, intralaboratory comparisons confirmed previous studies showing that rep529 is a more adequate DNA target for this diagnosis than the widely used B1 gene. But, on the other hand, interlaboratory comparisons showed differences that appear independent of the target, primers, or technology and that hence rely essentially on proficiency and care in the optimization of PCR conditions. PMID:20610670

A method for detecting IBD regions simultaneously in multiple individuals—with applications to disease genetics

PubMed Central

Moltke, Ida; Albrechtsen, Anders; Hansen, Thomas v.O.; Nielsen, Finn C.; Nielsen, Rasmus

2011-01-01

All individuals in a finite population are related if traced back long enough and will, therefore, share regions of their genomes identical by descent (IBD). Detection of such regions has several important applications—from answering questions about human evolution to locating regions in the human genome containing disease-causing variants. However, IBD regions can be difficult to detect, especially in the common case where no pedigree information is available. In particular, all existing non-pedigree based methods can only infer IBD sharing between two individuals. Here, we present a new Markov Chain Monte Carlo method for detection of IBD regions, which does not rely on any pedigree information. It is based on a probabilistic model applicable to unphased SNP data. It can take inbreeding, allele frequencies, genotyping errors, and genomic distances into account. And most importantly, it can simultaneously infer IBD sharing among multiple individuals. Through simulations, we show that the simultaneous modeling of multiple individuals makes the method more powerful and accurate than several other non-pedigree based methods. We illustrate the potential of the method by applying it to data from individuals with breast and/or ovarian cancer, and show that a known disease-causing mutation can be mapped to a 2.2-Mb region using SNP data from only five seemingly unrelated affected individuals. This would not be possible using classical linkage mapping or association mapping. PMID:21493780

A novel spatial-temporal detection method of dim infrared moving small target

NASA Astrophysics Data System (ADS)

Chen, Zhong; Deng, Tao; Gao, Lei; Zhou, Heng; Luo, Song

2014-09-01

Moving small target detection under complex background in infrared image sequence is one of the major challenges of modern military in Early Warning Systems (EWS) and the use of Long-Range Strike (LRS). However, because of the low SNR and undulating background, the infrared moving small target detection is a difficult problem in a long time. To solve this problem, a novel spatial-temporal detection method based on bi-dimensional empirical mode decomposition (EMD) and time-domain difference is proposed in this paper. This method is downright self-data decomposition and do not rely on any transition kernel function, so it has a strong adaptive capacity. Firstly, we generalized the 1D EMD algorithm to the 2D case. In this process, the project has solved serial issues in 2D EMD, such as large amount of data operations, define and identify extrema in 2D case, and two-dimensional signal boundary corrosion. The EMD algorithm studied in this project can be well adapted to the automatic detection of small targets under low SNR and complex background. Secondly, considering the characteristics of moving target, we proposed an improved filtering method based on three-frame difference on basis of the original difference filtering in time-domain, which greatly improves the ability of anti-jamming algorithm. Finally, we proposed a new time-space fusion method based on a combined processing of 2D EMD and improved time-domain differential filtering. And, experimental results show that this method works well in infrared small moving target detection under low SNR and complex background.

Development of a fast and efficient method for hepatitis A virus concentration from green onion.

PubMed

Zheng, Yan; Hu, Yuan

2017-11-01

Hepatitis A virus (HAV) can cause serious liver disease and even death. HAV outbreaks are associated with the consumption of raw or minimally processed produce, making it a major public health concern. Infections have occurred despite the fact that effective HAV vaccine has been available. Development of a rapid and sensitive HAV detection method is necessary for an investigation of an HAV outbreak. Detection of HAV is complicated by the lack of a reliable culture method. In addition, due to the low infectious dose of HAV, these methods must be very sensitive. Current methods rely on efficient sample preparation and concentration steps followed by sensitive molecular detection techniques. Using green onions which was involved in most recent HAV outbreaks as a representative produce, a method of capturing virus particles was developed using carboxyl-derivatized magnetic beads in this study. Carboxyl beads, like antibody-coated beads or cationic beads, detect HAV at a level as low as 100 pfu/25g of green onions. RNA from virus concentrated in this manner can be released by heat-shock (98°C 5min) for molecular detection without sacrificing sensitivity. Bypassing the RNA extraction procedure saves time and removes multiple manipulation steps, which makes large scale HAV screening possible. In addition, the inclusion of beef extract and pectinase rather than NP40 in the elution buffer improved the HAV liberation from the food matrix over current methods by nearly 10 fold. The method proposed in this study provides a promising tool to improve food risk assessment and protect public health. Published by Elsevier B.V.

Detect2Rank: Combining Object Detectors Using Learning to Rank.

PubMed

Karaoglu, Sezer; Yang Liu; Gevers, Theo

2016-01-01

Object detection is an important research area in the field of computer vision. Many detection algorithms have been proposed. However, each object detector relies on specific assumptions of the object appearance and imaging conditions. As a consequence, no algorithm can be considered universal. With the large variety of object detectors, the subsequent question is how to select and combine them. In this paper, we propose a framework to learn how to combine object detectors. The proposed method uses (single) detectors like Deformable Part Models, Color Names and Ensemble of Exemplar-SVMs, and exploits their correlation by high-level contextual features to yield a combined detection list. Experiments on the PASCAL VOC07 and VOC10 data sets show that the proposed method significantly outperforms single object detectors, DPM (8.4%), CN (6.8%) and EES (17.0%) on VOC07 and DPM (6.5%), CN (5.5%) and EES (16.2%) on VOC10. We show with an experiment that there are no constraints on the type of the detector. The proposed method outperforms (2.4%) the state-of-the-art object detector (RCNN) on VOC07 when Regions with Convolutional Neural Network is combined with other detectors used in this paper.

Nanoparticle based bio-bar code technology for trace analysis of aflatoxin B1 in Chinese herbs.

PubMed

Yu, Yu-Yan; Chen, Yuan-Yuan; Gao, Xuan; Liu, Yuan-Yuan; Zhang, Hong-Yan; Wang, Tong-Ying

2018-04-01

A novel and sensitive assay for aflatoxin B1 (AFB1) detection has been developed by using bio-bar code assay (BCA). The method that relies on polyclonal antibodies encoded with DNA modified gold nanoparticle (NP) and monoclonal antibodies modified magnetic microparticle (MMP), and subsequent detection of amplified target in the form of bio-bar code using a fluorescent quantitative polymerase chain reaction (FQ-PCR) detection method. First, NP probes encoded with DNA that was unique to AFB1, MMP probes with monoclonal antibodies that bind AFB1 specifically were prepared. Then, the MMP-AFB1-NP sandwich compounds were acquired, dehybridization of the oligonucleotides on the nanoparticle surface allows the determination of the presence of AFB1 by identifying the oligonucleotide sequence released from the NP through FQ-PCR detection. The bio-bar code techniques system for detecting AFB1 was established, and the sensitivity limit was about 10 -8  ng/mL, comparable ELISA assays for detecting the same target, it showed that we can detect AFB1 at low attomolar levels with the bio-bar-code amplification approach. This is also the first demonstration of a bio-bar code type assay for the detection of AFB1 in Chinese herbs. Copyright © 2017. Published by Elsevier B.V.

Evaluation of volatile organic emissions from hazardous waste incinerators.

PubMed Central

Sedman, R M; Esparza, J R

1991-01-01

Conventional methods of risk assessment typically employed to evaluate the impact of hazardous waste incinerators on public health must rely on somewhat speculative emissions estimates or on complicated and expensive sampling and analytical methods. The limited amount of toxicological information concerning many of the compounds detected in stack emissions also complicates the evaluation of the public health impacts of these facilities. An alternative approach aimed at evaluating the public health impacts associated with volatile organic stack emissions is presented that relies on a screening criterion to evaluate total stack hydrocarbon emissions. If the concentration of hydrocarbons in ambient air is below the screening criterion, volatile emissions from the incinerator are judged not to pose a significant threat to public health. Both the screening criterion and a conventional method of risk assessment were employed to evaluate the emissions from 20 incinerators. Use of the screening criterion always yielded a substantially greater estimate of risk than that derived by the conventional method. Since the use of the screening criterion always yielded estimates of risk that were greater than that determined by conventional methods and measuring total hydrocarbon emissions is a relatively simple analytical procedure, the use of the screening criterion would appear to facilitate the evaluation of operating hazardous waste incinerators. PMID:1954928

Detection of goal events in soccer videos

NASA Astrophysics Data System (ADS)

Kim, Hyoung-Gook; Roeber, Steffen; Samour, Amjad; Sikora, Thomas

2005-01-01

In this paper, we present an automatic extraction of goal events in soccer videos by using audio track features alone without relying on expensive-to-compute video track features. The extracted goal events can be used for high-level indexing and selective browsing of soccer videos. The detection of soccer video highlights using audio contents comprises three steps: 1) extraction of audio features from a video sequence, 2) event candidate detection of highlight events based on the information provided by the feature extraction Methods and the Hidden Markov Model (HMM), 3) goal event selection to finally determine the video intervals to be included in the summary. For this purpose we compared the performance of the well known Mel-scale Frequency Cepstral Coefficients (MFCC) feature extraction method vs. MPEG-7 Audio Spectrum Projection feature (ASP) extraction method based on three different decomposition methods namely Principal Component Analysis( PCA), Independent Component Analysis (ICA) and Non-Negative Matrix Factorization (NMF). To evaluate our system we collected five soccer game videos from various sources. In total we have seven hours of soccer games consisting of eight gigabytes of data. One of five soccer games is used as the training data (e.g., announcers' excited speech, audience ambient speech noise, audience clapping, environmental sounds). Our goal event detection results are encouraging.

Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps.

PubMed

Fernández-Esparrach, Glòria; Bernal, Jorge; López-Cerón, Maria; Córdova, Henry; Sánchez-Montes, Cristina; Rodríguez de Miguel, Cristina; Sánchez, Francisco Javier

2016-09-01

Polyp miss-rate is a drawback of colonoscopy that increases significantly for small polyps. We explored the efficacy of an automatic computer-vision method for polyp detection. Our method relies on a model that defines polyp boundaries as valleys of image intensity. Valley information is integrated into energy maps that represent the likelihood of the presence of a polyp. In 24 videos containing polyps from routine colonoscopies, all polyps were detected in at least one frame. The mean of the maximum values on the energy map was higher for frames with polyps than without (P < 0.001). Performance improved in high quality frames (AUC = 0.79 [95 %CI 0.70 - 0.87] vs. 0.75 [95 %CI 0.66 - 0.83]). With 3.75 set as the maximum threshold value, sensitivity and specificity for the detection of polyps were 70.4 % (95 %CI 60.3 % - 80.8 %) and 72.4 % (95 %CI 61.6 % - 84.6 %), respectively. Energy maps performed well for colonic polyp detection, indicating their potential applicability in clinical practice. © Georg Thieme Verlag KG Stuttgart · New York.

Detection of material property errors in handbooks and databases using artificial neural networks with hidden correlations

NASA Astrophysics Data System (ADS)

Zhang, Y. M.; Evans, J. R. G.; Yang, S. F.

2010-11-01

The authors have discovered a systematic, intelligent and potentially automatic method to detect errors in handbooks and stop their transmission using unrecognised relationships between materials properties. The scientific community relies on the veracity of scientific data in handbooks and databases, some of which have a long pedigree covering several decades. Although various outlier-detection procedures are employed to detect and, where appropriate, remove contaminated data, errors, which had not been discovered by established methods, were easily detected by our artificial neural network in tables of properties of the elements. We started using neural networks to discover unrecognised relationships between materials properties and quickly found that they were very good at finding inconsistencies in groups of data. They reveal variations from 10 to 900% in tables of property data for the elements and point out those that are most probably correct. Compared with the statistical method adopted by Ashby and co-workers [Proc. R. Soc. Lond. Ser. A 454 (1998) p. 1301, 1323], this method locates more inconsistencies and could be embedded in database software for automatic self-checking. We anticipate that our suggestion will be a starting point to deal with this basic problem that affects researchers in every field. The authors believe it may eventually moderate the current expectation that data field error rates will persist at between 1 and 5%.

Optical Biopsy: A New Frontier in Endoscopic Detection and Diagnosis

PubMed Central

WANG, THOMAS D.; VAN DAM, JACQUES

2007-01-01

Endoscopic diagnosis currently relies on the ability of the operator to visualize abnormal patterns in the image created by light reflected from the mucosal surface of the gastrointestinal tract. Advances in fiber optics, light sources, detectors, and molecular biology have led to the development of several novel methods for tissue evaluation in situ. The term “optical biopsy” refers to methods that use the properties of light to enable the operator to make an instant diagnosis at endoscopy, previously possible only by using histological or cytological analysis. Promising imaging techniques include fluorescence endoscopy, optical coherence tomography, confocal microendoscopy, and molecular imaging. Point detection schemes under development include light scattering and Raman spectroscopy. Such advanced diagnostic methods go beyond standard endoscopic techniques by offering improved image resolution, contrast, and tissue penetration and providing biochemical and molecular information about mucosal disease. This review describes the basic biophysics of light-tissue interactions, assesses the strengths and weaknesses of each method, and examines clinical and preclinical evidence for each approach. PMID:15354274

A SVM-based quantitative fMRI method for resting-state functional network detection.

PubMed

Song, Xiaomu; Chen, Nan-kuei

2014-09-01

Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Guided wave imaging of oblique reflecting interfaces in pipes using common-source synthetic focusing

NASA Astrophysics Data System (ADS)

Sun, Zeqing; Sun, Anyu; Ju, Bing-Feng

2018-04-01

Cross-mode-family mode conversion and secondary reflection of guided waves in pipes complicate the processing of guided waves signals, and can cause false detection. In this paper, filters operating in the spectral domain of wavenumber, circumferential order and frequency are designed to suppress the signal components of unwanted mode-family and unwanted traveling direction. Common-source synthetic focusing is used to reconstruct defect images from the guided wave signals. Simulations of the reflections from linear oblique defects and a semicircle defect are separately implemented. Defect images, which are reconstructed from the simulation results under different excitation conditions, are comparatively studied in terms of axial resolution, reflection amplitude, detectable oblique angle and so on. Further, the proposed method is experimentally validated by detecting linear cracks with various oblique angles (10-40°). The proposed method relies on the guided wave signals that are captured during 2-D scanning of a cylindrical area on the pipe. The redundancy of the signals is analyzed to reduce the time-consumption of the scanning process and to enhance the practicability of the proposed method.

A magnetic nanobead-based bioassay provides sensitive detection of single- and biplex bacterial DNA using a portable AC susceptometer

PubMed Central

Strömberg, Mattias; Zardán Gómez de la Torre, Teresa; Nilsson, Mats; Svedlindh, Peter; Strømme, Maria

2014-01-01

Bioassays relying on magnetic read-out using probe-tagged magnetic nanobeads are potential platforms for low-cost biodiagnostic devices for pathogen detection. For optimal assay performance it is crucial to apply an easy, efficient and robust bead-probe conjugation protocol. In this paper, sensitive (1.5 pM) singleplex detection of bacterial DNA sequences is demonstrated in a portable AC susceptometer by a magnetic nanobead-based bioassay principle; the volume-amplified magnetic nanobead detection assay (VAM-NDA). Two bead sizes, 100 and 250 nm, are investigated along with a highly efficient, rapid, robust, and stable conjugation chemistry relying on the avidin–biotin interaction for bead-probe attachment. Avidin-biotin conjugation gives easy control of the number of detection probes per bead; thus allowing for systematic investigation of the impact of varying the detection probe surface coverage upon bead immobilization in rolling circle amplified DNA-coils. The existence of an optimal surface coverage is discussed. Biplex VAM-NDA detection is for the first time demonstrated in the susceptometer: Semi-quantitative results are obtained and it is concluded that the concentration of DNA-coils in the incubation volume is of crucial importance for target quantification. The present findings bring the development of commercial biodiagnostic devices relying on the VAM–NDA further towards implementation in point-of-care and outpatient settings. PMID:24174315

Rapid Detection and Enumeration of Giardia lamblia Cysts in Water Samples by Immunomagnetic Separation and Flow Cytometric Analysis ▿ †

PubMed Central

Keserue, Hans-Anton; Füchslin, Hans Peter; Egli, Thomas

2011-01-01

Giardia lamblia is an important waterborne pathogen and is among the most common intestinal parasites of humans worldwide. Its fecal-oral transmission leads to the presence of cysts of this pathogen in the environment, and so far, quantitative rapid screening methods are not available for various matrices, such as surface waters, wastewater, or food. Thus, it is necessary to establish methods that enable reliable rapid detection of a single cyst in 10 to 100 liters of drinking water. Conventional detection relies on cyst concentration, isolation, and confirmation by immunofluorescence microscopy (IFM), resulting in low recoveries and high detection limits. Many different immunomagnetic separation (IMS) procedures have been developed for separation and cyst purification, so far with variable but high losses of cysts. A method was developed that requires less than 100 min and consists of filtration, resuspension, IMS, and flow cytometric (FCM) detection. MACS MicroBeads were used for IMS, and a reliable flow cytometric detection approach was established employing 3 different parameters for discrimination from background signals, i.e., green and red fluorescence (resulting from the distinct pattern emitted by the fluorescein dye) and sideward scatter for size discrimination. With spiked samples, recoveries exceeding 90% were obtained, and false-positive results were never encountered for negative samples. Additionally, the method was applicable to naturally occurring cysts in wastewater and has the potential to be automated. PMID:21685159

Genomic Data Quality Impacts Automated Detection of Lateral Gene Transfer in Fungi

PubMed Central

Dupont, Pierre-Yves; Cox, Murray P.

2017-01-01

Lateral gene transfer (LGT, also known as horizontal gene transfer), an atypical mechanism of transferring genes between species, has almost become the default explanation for genes that display an unexpected composition or phylogeny. Numerous methods of detecting LGT events all rely on two fundamental strategies: primary structure composition or gene tree/species tree comparisons. Discouragingly, the results of these different approaches rarely coincide. With the wealth of genome data now available, detection of laterally transferred genes is increasingly being attempted in large uncurated eukaryotic datasets. However, detection methods depend greatly on the quality of the underlying genomic data, which are typically complex for eukaryotes. Furthermore, given the automated nature of genomic data collection, it is typically impractical to manually verify all protein or gene models, orthology predictions, and multiple sequence alignments, requiring researchers to accept a substantial margin of error in their datasets. Using a test case comprising plant-associated genomes across the fungal kingdom, this study reveals that composition- and phylogeny-based methods have little statistical power to detect laterally transferred genes. In particular, phylogenetic methods reveal extreme levels of topological variation in fungal gene trees, the vast majority of which show departures from the canonical species tree. Therefore, it is inherently challenging to detect LGT events in typical eukaryotic genomes. This finding is in striking contrast to the large number of claims for laterally transferred genes in eukaryotic species that routinely appear in the literature, and questions how many of these proposed examples are statistically well supported. PMID:28235827

Developing the Cleanliness Requirements for an Organic-detection Instrument MOMA-MS

NASA Technical Reports Server (NTRS)

Perry, Radford; Canham, John; Lalime, Erin

2015-01-01

The cleanliness requirements for an organic-detection instrument, like the Mars Organic Molecule Analyzer Mass Spectrometer (MOMA-MS), on a Planetary Protection Class IVb mission can be extremely stringent. These include surface molecular and particulate, outgassing, and bioburden. The prime contractor for the European Space Agencys ExoMars 2018 project, Thales Alenia Space Italy, provided requirements based on a standard, conservative approach of defining limits which yielded levels that are unverifiable by standard cleanliness verification methods. Additionally, the conservative method for determining contamination surface area uses underestimation while conservative bioburden surface area relies on overestimation, which results in inconsistencies for the normalized reporting. This presentation will provide a survey of the challenge to define requirements that can be reasonably verified and still remain appropriate to the core science of the ExoMars mission.

Plasmonic biosensor for label-free G-quadruplexes detection

NASA Astrophysics Data System (ADS)

Qiu, Suyan; Zhao, Fusheng; Santos, Greggy M.; Shih, Wei-Chuan

2016-03-01

G-quadruplex, readily formed by the G-rich sequence, potentially distributes in over 40 % of all human genes, such as the telomeric DNA with the G-rich sequence found at the end of the chromosome. The G-quadruplex structure is supposed to possess a diverse set of critical functions in the mammalian genome for transcriptional regulation, DNA replication and genome stability. However, most of the currently available methods for G-quadruplex identification are restricted to fluorescence techniques susceptible to poor sensitivity. It is essential to propose methods with higher sensitivity to specifically recognize the G-quadruplexes. In this study, we demonstrate a label-free plasmonic biosensor for G-quadruplex detection by relying on the advantages of nanoporous gold (NPG) disks that provide high-density plasmonic hot spots, suitable for molecular recognition capability without the requirement for labeling processes.

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

PubMed

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

PubMed Central

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

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. PMID:28125723

Toward Failure Modeling In Complex Dynamic Systems: Impact of Design and Manufacturing Variations

NASA Technical Reports Server (NTRS)

Tumer, Irem Y.; McAdams, Daniel A.; Clancy, Daniel (Technical Monitor)

2001-01-01

When designing vehicle vibration monitoring systems for aerospace devices, it is common to use well-established models of vibration features to determine whether failures or defects exist. Most of the algorithms used for failure detection rely on these models to detect significant changes during a flight environment. In actual practice, however, most vehicle vibration monitoring systems are corrupted by high rates of false alarms and missed detections. Research conducted at the NASA Ames Research Center has determined that a major reason for the high rates of false alarms and missed detections is the numerous sources of statistical variations that are not taken into account in the. modeling assumptions. In this paper, we address one such source of variations, namely, those caused during the design and manufacturing of rotating machinery components that make up aerospace systems. We present a novel way of modeling the vibration response by including design variations via probabilistic methods. The results demonstrate initial feasibility of the method, showing great promise in developing a general methodology for designing more accurate aerospace vehicle vibration monitoring systems.

Detection and characterization of pulses in broadband seismometers

USGS Publications Warehouse

Wilson, David; Ringler, Adam; Hutt, Charles R.

2017-01-01

Pulsing - caused either by mechanical or electrical glitches, or by microtilt local to a seismometer - can significantly compromise the long‐period noise performance of broadband seismometers. High‐fidelity long‐period recordings are needed for accurate calculation of quantities such as moment tensors, fault‐slip models, and normal‐mode measurements. Such pulses have long been recognized in accelerometers, and methods have been developed to correct these acceleration steps, but considerable work remains to be done in order to detect and correct similar pulses in broadband seismic data. We present a method for detecting and characterizing the pulses using data from a range of broadband sensor types installed in the Global Seismographic Network. The technique relies on accurate instrument response removal and employs a moving‐window approach looking for acceleration baseline shifts. We find that pulses are present at varying levels in all sensor types studied. Pulse‐detection results compared with average daily station noise values are consistent with predicted noise levels of acceleration steps. This indicates that we can calculate maximum pulse amplitude allowed per time window that would be acceptable without compromising long‐period data analysis.

1 km fog and low stratus detection using pan-sharpened MSG SEVIRI data

NASA Astrophysics Data System (ADS)

Schulz, H. M.; Thies, B.; Cermak, J.; Bendix, J.

2012-06-01

In this paper a new technique for the detection of fog and low stratus in 1 km resolution from MSG SEVIRI data is presented. The method relies on the pan-sharpening of 3 km narrow-band channels using the 1 km high-resolution visible (HRV) channel. As solar and thermal channels had to be sharpened for the technique, a new approach based on an existing pan-sharpening method was developed using local regressions. A fog and low stratus detection scheme originally developed for 3 km SEVIRI data was used as the basis to derive 1 km resolution fog and low stratus masks from the sharpened channels. The sharpened channels and the fog and low stratus masks based on them were evaluated visually and by various statistical measures. The sharpened channels deviate only slightly from reference images regarding their pixel values as well as spatial features. The 1 km fog and low stratus masks are therefore deemed of high quality. They contain many details, especially where fog is restricted by complex terrain in its extent, that cannot be detected in the 3 km resolution.

1 km fog and low stratus detection using pan-sharpened MSG SEVIRI data

NASA Astrophysics Data System (ADS)

Schulz, H. M.; Thies, B.; Cermak, J.; Bendix, J.

2012-10-01

In this paper a new technique for the detection of fog and low stratus in 1 km resolution from MSG SEVIRI data is presented. The method relies on the pan-sharpening of 3 km narrow-band channels using the 1 km high-resolution visible (HRV) channel. As solar and thermal channels had to be sharpened for the technique, a new approach based on an existing pan-sharpening method was developed using local regressions. A fog and low stratus detection scheme originally developed for 3 km SEVIRI data was used as the basis to derive 1 km resolution fog and low stratus masks from the sharpened channels. The sharpened channels and the fog and low stratus masks based on them were evaluated visually and by various statistical measures. The sharpened channels deviate only slightly from reference images regarding their pixel values as well as spatial features. The 1 km fog and low stratus masks are therefore deemed of high quality. They contain many details, especially where fog is restricted by complex terrain in its extent, that cannot be detected in the 3 km resolution.

Detection of the Spermicide Nonoxynol-9 Via GC-MS

NASA Astrophysics Data System (ADS)

Musah, Rabi A.; Vuong, Angela L.; Henck, Colin; Shepard, Jason R. E.

2012-05-01

The spermicide nonoxynol-9 is actually a complex mixture of dozens of closely related amphiphilic compounds, and the chemical properties of this assortment significantly hamper its characterization by GC-MS. The inability to perform routine GC-MS testing on nonoxynol-9 has limited its evidentiary value in forensic casework, which relies heavily on this technique for analysis. A disturbing trend in sexual assault is the use of condoms by assailants, to avoid leaving behind DNA evidence that can connect a perpetrator to a victim. This observation necessitates the development of alternative methods for the analysis of trace evidence that can show causal links between a victim and a suspect. Detection of lubricants associated with sexual assault is one such way to establish this connection. The development of GC-MS methods that permit facile detection of both nonoxynol-9 alone and nonoxynol-9 extracted from other complex matrices that have potential as trace evidence in sexual assault is reported. A detection limit of 2.14 μg of nonoxynol-9 is demonstrated, and a detailed mass spectral profile that elaborates on what is known of its structure is provided.

Vortex flows in the solar chromosphere. I. Automatic detection method

NASA Astrophysics Data System (ADS)

Kato, Y.; Wedemeyer, S.

2017-05-01

Solar "magnetic tornadoes" are produced by rotating magnetic field structures that extend from the upper convection zone and the photosphere to the corona of the Sun. Recent studies show that these kinds of rotating features are an integral part of atmospheric dynamics and occur on a large range of spatial scales. A systematic statistical study of magnetic tornadoes is a necessary next step towards understanding their formation and their role in mass and energy transport in the solar atmosphere. For this purpose, we develop a new automatic detection method for chromospheric swirls, meaning the observable signature of solar tornadoes or, more generally, chromospheric vortex flows and rotating motions. Unlike existing studies that rely on visual inspections, our new method combines a line integral convolution (LIC) imaging technique and a scalar quantity that represents a vortex flow on a two-dimensional plane. We have tested two detection algorithms, based on the enhanced vorticity and vorticity strength quantities, by applying them to three-dimensional numerical simulations of the solar atmosphere with CO5BOLD. We conclude that the vorticity strength method is superior compared to the enhanced vorticity method in all aspects. Applying the method to a numerical simulation of the solar atmosphere reveals very abundant small-scale, short-lived chromospheric vortex flows that have not been found previously by visual inspection.

Online boosting for vehicle detection.

PubMed

Chang, Wen-Chung; Cho, Chih-Wei

2010-06-01

This paper presents a real-time vision-based vehicle detection system employing an online boosting algorithm. It is an online AdaBoost approach for a cascade of strong classifiers instead of a single strong classifier. Most existing cascades of classifiers must be trained offline and cannot effectively be updated when online tuning is required. The idea is to develop a cascade of strong classifiers for vehicle detection that is capable of being online trained in response to changing traffic environments. To make the online algorithm tractable, the proposed system must efficiently tune parameters based on incoming images and up-to-date performance of each weak classifier. The proposed online boosting method can improve system adaptability and accuracy to deal with novel types of vehicles and unfamiliar environments, whereas existing offline methods rely much more on extensive training processes to reach comparable results and cannot further be updated online. Our approach has been successfully validated in real traffic environments by performing experiments with an onboard charge-coupled-device camera in a roadway vehicle.

Harnessing Aptamers to Overcome Challenges in Gluten Detection

PubMed Central

Miranda-Castro, Rebeca; de-los-Santos-Álvarez, Noemí; Miranda-Ordieres, Arturo J.; Lobo-Castañón, María Jesús

2016-01-01

Celiac disease is a lifelong autoimmune disorder triggered by foods containing gluten, the storage protein in wheat, rye, and barley. The rapidly escalating number of patients diagnosed with this disease poses a great challenge to both food industry and authorities to guarantee food safety for all. Therefore, intensive efforts are being made to establish minimal disease-eliciting doses of gluten and consequently to improve gluten-free labeling. These efforts depend to a high degree on the availability of methods capable of detecting the protein in food samples at levels as low as possible. Current analytical approaches rely on the use of antibodies as selective recognition elements. With limited sensitivity, these methods exhibit some deficiencies that compromise the accuracy of the obtained results. Aptamers provide an ideal alternative for designing biosensors for fast and selective measurement of gluten in foods. This article highlights the challenges in gluten detection, the current status of the use of aptamers for solving this problem, and what remains to be done to move these systems into commercial applications. PMID:27104578

Triple-helix molecular switch-based aptasensors and DNA sensors.

PubMed

Bagheri, Elnaz; Abnous, Khalil; Alibolandi, Mona; Ramezani, Mohammad; Taghdisi, Seyed Mohammad

2018-07-15

Utilization of traditional analytical techniques is limited because they are generally time-consuming and require high consumption of reagents, complicated sample preparation and expensive equipment. Therefore, it is of great interest to achieve sensitive, rapid and simple detection methods. It is believed that nucleic acids assays, especially aptamers, are very important in modern life sciences for target detection and biological analysis. Aptamers and DNA-based sensors have been widely used for the design of various sensors owing to their unique features. In recent years, triple-helix molecular switch (THMS)-based aptasensors and DNA sensors have been broadly utilized for the detection and analysis of different targets. The THMS relies on the formation of DNA triplex via Watson-Crick and Hoogsteen base pairings under optimal conditions. This review focuses on recent progresses in the development and applications of electrochemical, colorimetric, fluorescence and SERS aptasensors and DNA sensors, which are based on THMS. Also, the advantages and drawbacks of these methods are discussed. Copyright © 2018 Elsevier B.V. All rights reserved.

Impulse Testing of Corporate-Fed Patch Array Antennas

NASA Technical Reports Server (NTRS)

Chamberlain, Neil F.

2011-01-01

This paper discusses a novel method for detecting faults in antenna arrays. The method, termed Impulse Testing, was developed for corporate-fed patch arrays where the element is fed by a probe and is shorted at its center. Impulse Testing was devised to supplement conventional microwave measurements in order to quickly verify antenna integrity. The technique relies on exciting each antenna element in turn with a fast pulse (or impulse) that propagates through the feed network to the output port of the antenna. The resulting impulse response is characteristic of the path through the feed network. Using an oscilloscope, a simple amplitude measurement can be made to detect faults. A circuit model of the antenna elements and feed network was constructed to assess various fault scenarios and determine fault-detection thresholds. The experimental setup and impulse measurements for two patch array antennas are presented. Advantages and limitations of the technique are discussed along with applications to other antenna array topologies

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry applied to virus identification

PubMed Central

Calderaro, Adriana; Arcangeletti, Maria-Cristina; Rodighiero, Isabella; Buttrini, Mirko; Gorrini, Chiara; Motta, Federica; Germini, Diego; Medici, Maria-Cristina; Chezzi, Carlo; De Conto, Flora

2014-01-01

Virus detection and/or identification traditionally rely on methods based on cell culture, electron microscopy and antigen or nucleic acid detection. These techniques are good, but often expensive and/or time-consuming; furthermore, they not always lead to virus identification at the species and/or type level. In this study, Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) was tested as an innovative tool to identify human polioviruses and to identify specific viral protein biomarkers in infected cells. The results revealed MALDI-TOF MS to be an effective and inexpensive tool for the identification of the three poliovirus serotypes. The method was firstly applied to Sabin reference strains, and then to isolates from different clinical samples, highlighting its value as a time-saving, sensitive and specific technique when compared to the gold standard neutralization assay and casting new light on its possible application to virus detection and/or identification. PMID:25354905

Circulating tumor cells in lung cancer.

PubMed

Young, Rachel; Pailler, Emma; Billiot, Fanny; Drusch, Françoise; Barthelemy, Amélie; Oulhen, Marianne; Besse, Benjamin; Soria, Jean-Charles; Farace, Françoise; Vielh, Philippe

2012-01-01

Circulating tumor cells (CTCs) have emerged as potential biomarkers in several cancers such as colon, prostate, and breast carcinomas, with a correlation between CTC number and patient prognosis being established by independent research groups. The detection and enumeration of CTCs, however, is still a developing field, with no universal method of detection suitable for all types of cancer. CTC detection in lung cancer in particular has proven difficult to perform, as CTCs in this type of cancer often present with nonepithelial characteristics. Moreover, as many detection methods rely on the use of epithelial markers to identify CTCs, the loss of these markers during epithelial-to-mesenchymal transition in certain metastatic cancers can render these methods ineffective. The development of personalized medicine has led to an increase in the advancement of molecular characterization of CTCs. The application of techniques such as FISH and RT-PCR to detect EGFR, HER2, and KRAS abnormalities in lung, breast, and colon cancer, for example, could be used to characterize CTCs in real time. The use of CTCs as a 'liquid biopsy' is therefore an exciting possibility providing information on patient prognosis and treatment efficacy. This review summarizes the state of CTC detection today, with particular emphasis on lung cancer, and discusses the future applications of CTCs in helping the clinician to develop new strategies in patient treatment. Copyright © 2012 S. Karger AG, Basel.

Calculation of the detection limit in radiation measurements with systematic uncertainties

NASA Astrophysics Data System (ADS)

Kirkpatrick, J. M.; Russ, W.; Venkataraman, R.; Young, B. M.

2015-06-01

The detection limit (LD) or Minimum Detectable Activity (MDA) is an a priori evaluation of assay sensitivity intended to quantify the suitability of an instrument or measurement arrangement for the needs of a given application. Traditional approaches as pioneered by Currie rely on Gaussian approximations to yield simple, closed-form solutions, and neglect the effects of systematic uncertainties in the instrument calibration. These approximations are applicable over a wide range of applications, but are of limited use in low-count applications, when high confidence values are required, or when systematic uncertainties are significant. One proposed modification to the Currie formulation attempts account for systematic uncertainties within a Gaussian framework. We have previously shown that this approach results in an approximation formula that works best only for small values of the relative systematic uncertainty, for which the modification of Currie's method is the least necessary, and that it significantly overestimates the detection limit or gives infinite or otherwise non-physical results for larger systematic uncertainties where such a correction would be the most useful. We have developed an alternative approach for calculating detection limits based on realistic statistical modeling of the counting distributions which accurately represents statistical and systematic uncertainties. Instead of a closed form solution, numerical and iterative methods are used to evaluate the result. Accurate detection limits can be obtained by this method for the general case.

Optimized approach for Ion Proton RNA sequencing reveals details of RNA splicing and editing features of the transcriptome.

PubMed

Brown, Roger B; Madrid, Nathaniel J; Suzuki, Hideaki; Ness, Scott A

2017-01-01

RNA-sequencing (RNA-seq) has become the standard method for unbiased analysis of gene expression but also provides access to more complex transcriptome features, including alternative RNA splicing, RNA editing, and even detection of fusion transcripts formed through chromosomal translocations. However, differences in library methods can adversely affect the ability to recover these different types of transcriptome data. For example, some methods have bias for one end of transcripts or rely on low-efficiency steps that limit the complexity of the resulting library, making detection of rare transcripts less likely. We tested several commonly used methods of RNA-seq library preparation and found vast differences in the detection of advanced transcriptome features, such as alternatively spliced isoforms and RNA editing sites. By comparing several different protocols available for the Ion Proton sequencer and by utilizing detailed bioinformatics analysis tools, we were able to develop an optimized random primer based RNA-seq technique that is reliable at uncovering rare transcript isoforms and RNA editing features, as well as fusion reads from oncogenic chromosome rearrangements. The combination of optimized libraries and rapid Ion Proton sequencing provides a powerful platform for the transcriptome analysis of research and clinical samples.

Border preserving skin lesion segmentation

NASA Astrophysics Data System (ADS)

Kamali, Mostafa; Samei, Golnoosh

2008-03-01

Melanoma is a fatal cancer with a growing incident rate. However it could be cured if diagnosed in early stages. The first step in detecting melanoma is the separation of skin lesion from healthy skin. There are particular features associated with a malignant lesion whose successful detection relies upon accurately extracted borders. We propose a two step approach. First, we apply K-means clustering method (to 3D RGB space) that extracts relatively accurate borders. In the second step we perform an extra refining step for detecting the fading area around some lesions as accurately as possible. Our method has a number of novelties. Firstly as the clustering method is directly applied to the 3D color space, we do not overlook the dependencies between different color channels. In addition, it is capable of extracting fine lesion borders up to pixel level in spite of the difficulties associated with fading areas around the lesion. Performing clustering in different color spaces reveals that 3D RGB color space is preferred. The application of the proposed algorithm to an extensive data-base of skin lesions shows that its performance is superior to that of existing methods both in terms of accuracy and computational complexity.

Facile and rapid DNA extraction and purification from food matrices using IFAST (immiscible filtration assisted by surface tension).

PubMed

Strotman, Lindsay N; Lin, Guangyun; Berry, Scott M; Johnson, Eric A; Beebe, David J

2012-09-07

Extraction and purification of DNA is a prerequisite to detection and analytical techniques. While DNA sample preparation methods have improved over the last few decades, current methods are still time consuming and labor intensive. Here we demonstrate a technology termed IFAST (Immiscible Filtration Assisted by Surface Tension), that relies on immiscible phase filtration to reduce the time and effort required to purify DNA. IFAST replaces the multiple wash and centrifugation steps required by traditional DNA sample preparation methods with a single step. To operate, DNA from lysed cells is bound to paramagnetic particles (PMPs) and drawn through an immiscible fluid phase barrier (i.e. oil) by an external handheld magnet. Purified DNA is then eluted from the PMPs. Here, detection of Clostridium botulinum type A (BoNT/A) in food matrices (milk, orange juice), a bioterrorism concern, was used as a model system to establish IFAST's utility in detection assays. Data validated that the DNA purified by IFAST was functional as a qPCR template to amplify the bont/A gene. The sensitivity limit of IFAST was comparable to the commercially available Invitrogen ChargeSwitch® method. Notably, pathogen detection via IFAST required only 8.5 μL of sample and was accomplished in five-fold less time. The simplicity, rapidity and portability of IFAST offer significant advantages when compared to existing DNA sample preparation methods.

Fuzzy-logic detection and probability of hail exploiting short-range X-band weather radar

NASA Astrophysics Data System (ADS)

Capozzi, Vincenzo; Picciotti, Errico; Mazzarella, Vincenzo; Marzano, Frank Silvio; Budillon, Giorgio

2018-03-01

This work proposes a new method for hail precipitation detection and probability, based on single-polarization X-band radar measurements. Using a dataset consisting of reflectivity volumes, ground truth observations and atmospheric sounding data, a probability of hail index, which provides a simple estimate of the hail potential, has been trained and adapted within Naples metropolitan environment study area. The probability of hail has been calculated starting by four different hail detection methods. The first two, based on (1) reflectivity data and temperature measurements and (2) on vertically-integrated liquid density product, respectively, have been selected from the available literature. The other two techniques are based on combined criteria of the above mentioned methods: the first one (3) is based on the linear discriminant analysis, whereas the other one (4) relies on the fuzzy-logic approach. The latter is an innovative criterion based on a fuzzyfication step performed through ramp membership functions. The performances of the four methods have been tested using an independent dataset: the results highlight that the fuzzy-oriented combined method performs slightly better in terms of false alarm ratio, critical success index and area under the relative operating characteristic. An example of application of the proposed hail detection and probability products is also presented for a relevant hail event, occurred on 21 July 2014.

A comparison of line enhancement techniques: applications to guide-wire detection and respiratory motion tracking

NASA Astrophysics Data System (ADS)

Bismuth, Vincent; Vancamberg, Laurence; Gorges, Sébastien

2009-02-01

During interventional radiology procedures, guide-wires are usually inserted into the patients vascular tree for diagnosis or healing purpose. These procedures are monitored with an Xray interventional system providing images of the interventional devices navigating through the patient's body. The automatic detection of such tools by image processing means has gained maturity over the past years and enables applications ranging from image enhancement to multimodal image fusion. Sophisticated detection methods are emerging, which rely on a variety of device enhancement techniques. In this article we reviewed and classified these techniques into three families. We chose a state of the art approach in each of them and built a rigorous framework to compare their detection capability and their computational complexity. Through simulations and the intensive use of ROC curves we demonstrated that the Hessian based methods are the most robust to strong curvature of the devices and that the family of rotated filters technique is the most suited for detecting low CNR and low curvature devices. The steerable filter approach demonstrated less interesting detection capabilities and appears to be the most expensive one to compute. Finally we demonstrated the interest of automatic guide-wire detection on a clinical topic: the compensation of respiratory motion in multimodal image fusion.

Addressing multi-label imbalance problem of surgical tool detection using CNN.

PubMed

Sahu, Manish; Mukhopadhyay, Anirban; Szengel, Angelika; Zachow, Stefan

2017-06-01

A fully automated surgical tool detection framework is proposed for endoscopic video streams. State-of-the-art surgical tool detection methods rely on supervised one-vs-all or multi-class classification techniques, completely ignoring the co-occurrence relationship of the tools and the associated class imbalance. In this paper, we formulate tool detection as a multi-label classification task where tool co-occurrences are treated as separate classes. In addition, imbalance on tool co-occurrences is analyzed and stratification techniques are employed to address the imbalance during convolutional neural network (CNN) training. Moreover, temporal smoothing is introduced as an online post-processing step to enhance runtime prediction. Quantitative analysis is performed on the M2CAI16 tool detection dataset to highlight the importance of stratification, temporal smoothing and the overall framework for tool detection. The analysis on tool imbalance, backed by the empirical results, indicates the need and superiority of the proposed framework over state-of-the-art techniques.

Modified use of methylene blue in the tissue compression technique to detect sarcocysts in meat-producing animals.

PubMed

Ng, Yit Han; Subramaniam, Vellayan; Lau, Yee Ling

2015-11-30

Sarcocystosis in meat-producing animals is a major cause of reduced productivity in many countries, especially those that rely on agriculture. Although several diagnostic methods are available to detect sarcocystosis, many are too time-consuming for routine use in abattoirs and meat inspection centers, where large numbers of samples need to be tested. This study aimed to compare the sensitivity of the methylene blue tissue preparation, unstained tissue preparation and nested PCR in the detection of sarcocysts in tissue samples. Approximately three-fold more sarcocysts were detected in methylene blue-stained tissue compared to unstained controls (McNemar's test: P<0.01). Test sensitivity was comparable to that of the gold standard for sarcocyst detection, nested polymerase chain reaction. These results suggest that methylene blue can be used in tissue compression as a rapid, safe, and inexpensive technique for the detection of ruminant sarcocystosis in abattoirs. Copyright © 2015 Elsevier B.V. All rights reserved.

Detection of common diarrhea-causing pathogens in Northern Taiwan by multiplex polymerase chain reaction.

PubMed

Huang, Shu-Huan; Lin, Yi-Fang; Tsai, Ming-Han; Yang, Shuan; Liao, Mei-Ling; Chao, Shao-Wen; Hwang, Cheng-Cheng

2018-06-01

Conventional methods for identifying gastroenteritis pathogens are time consuming, more likely to result in a false-negative, rely on personnel with diagnostic expertise, and are dependent on the specimen status. Alternatively, molecular diagnostic methods permit the rapid, simultaneous detection of multiple pathogens with high sensitivity and specificity. The present study compared conventional methods with the Luminex xTAG Gastrointestinal Pathogen Panel (xTAG GPP) for the diagnosis of infectious gastroenteritis in northern Taiwan. From July 2015 to April 2016, 217 clinical fecal samples were collected from patients with suspected infectious gastroenteritis. All specimens were tested using conventional diagnostic techniques following physicians' orders as well as with the xTAG GPP. The multiplex polymerase chain reaction (PCR) approach detected significantly more positive samples with bacterial, viral, and/or parasitic infections as compared to conventional analysis (55.8% vs 40.1%, respectively; P < .001). Moreover, multiplex PCR could detect Escherichia coli O157, enterotoxigenic E coli, Shiga-like toxin-producing E coli, Cryptosporidium, and Giardia, which were undetectable by conventional methods. Furthermore, 48 pathogens in 23 patients (10.6%) with coinfections were identified only using the multiplex PCR approach. Of which, 82.6% were from pediatric patients. Because the detection rates using multiplex PCR are higher than conventional methods, and some pediatric pathogens could only be detected by multiplex PCR, this approach may be useful in rapidly diagnosing diarrheal disease in children and facilitating treatment initiation. Further studies are necessary to determine if multiplex PCR improves patient outcomes and reduces costs.

Detection of common diarrhea-causing pathogens in Northern Taiwan by multiplex polymerase chain reaction

PubMed Central

Huang, Shu-Huan; Lin, Yi-Fang; Tsai, Ming-Han; Yang, Shuan; Liao, Mei-Ling; Chao, Shao-Wen; Hwang, Cheng-Cheng

2018-01-01

Abstract Conventional methods for identifying gastroenteritis pathogens are time consuming, more likely to result in a false-negative, rely on personnel with diagnostic expertise, and are dependent on the specimen status. Alternatively, molecular diagnostic methods permit the rapid, simultaneous detection of multiple pathogens with high sensitivity and specificity. The present study compared conventional methods with the Luminex xTAG Gastrointestinal Pathogen Panel (xTAG GPP) for the diagnosis of infectious gastroenteritis in northern Taiwan. From July 2015 to April 2016, 217 clinical fecal samples were collected from patients with suspected infectious gastroenteritis. All specimens were tested using conventional diagnostic techniques following physicians’ orders as well as with the xTAG GPP. The multiplex polymerase chain reaction (PCR) approach detected significantly more positive samples with bacterial, viral, and/or parasitic infections as compared to conventional analysis (55.8% vs 40.1%, respectively; P < .001). Moreover, multiplex PCR could detect Escherichia coli O157, enterotoxigenic E coli, Shiga-like toxin-producing E coli, Cryptosporidium, and Giardia, which were undetectable by conventional methods. Furthermore, 48 pathogens in 23 patients (10.6%) with coinfections were identified only using the multiplex PCR approach. Of which, 82.6% were from pediatric patients. Because the detection rates using multiplex PCR are higher than conventional methods, and some pediatric pathogens could only be detected by multiplex PCR, this approach may be useful in rapidly diagnosing diarrheal disease in children and facilitating treatment initiation. Further studies are necessary to determine if multiplex PCR improves patient outcomes and reduces costs. PMID:29879060

Attomolar quantitation of Mycobacterium tuberculosis by asymmetric helicase-dependent isothermal DNA-amplification and electrochemical detection.

PubMed

Barreda-García, Susana; González-Álvarez, María José; de-Los-Santos-Álvarez, Noemí; Palacios-Gutiérrez, Juan José; Miranda-Ordieres, Arturo J; Lobo-Castañón, María Jesús

2015-06-15

A highly sensitive and robust method for the quantification of specific DNA sequences based on coupling asymmetric helicase-dependent DNA amplification to electrochemical detection is described. This method relies on the entrapment of the amplified ssDNA sequences on magnetic beads followed by a post-amplification hybridization assay to provide an added degree of specificity. As a proof-of-concept a 84-bases long sequence specific of Mycobacterium tuberculosis is amplified at 65°C, providing 3×10(6) amplification after 90 min. Using this system 0.5 aM, corresponding to 15 copies of the target gene in 50 µL of sample, can be successfully detected and reliably quantified under isothermal conditions in less than 4h. The assay has been applied to the detection of M. tuberculosis in sputum, pleural fluid and urine samples. Besides this application, the proposed assays is a powerful and general tool for molecular diagnostic that can be applied to the detection of other specific DNA sequences, taking full advantage of the plethora of genomic information now available. Copyright © 2014 Elsevier B.V. All rights reserved.

Detection of Streptococcus pyogenes using rapid visual molecular assay.

PubMed

Zhao, Xiangna; He, Xiaoming; Li, Huan; Zhao, Jiangtao; Huang, Simo; Liu, Wei; Wei, Xiao; Ding, Yiwei; Wang, Zhaoyan; Zou, Dayang; Wang, Xuesong; Dong, Derong; Yang, Zhan; Yan, Xiabei; Huang, Liuyu; Du, Shuangkui; Yuan, Jing

2015-09-01

Streptococcus pyogenes is an increasingly important pathogen in many parts of the world. Rapid and accurate detection of S. pyogenes aids in the control of the infection. In this study, a loop-mediated isothermal amplification (LAMP) assay was developed and validated for the specific detection of S. pyogenes. The assay incorporates two methods: a chromogenic analysis using a calcein/Mn(2+) complex and real-time turbidity monitoring to assess the reaction. Both methods detected the target DNA within 60 min under 64°C isothermal conditions. The assay used specifically designed primers to target spy1258, and correctly identified 111 strains of S. pyogenes and 32 non-S. pyogenes strains, including other species of the genus Streptococcus. Tests using reference strains showed that the LAMP assay was highly specific. The sensitivity of the assay, with a detection limit of 1.49 pg DNA, was 10-fold greater than that of PCR. The LAMP assay established in this study is simple, fast and sensitive, and does not rely upon any special equipment; thus, it could be employed in clinical diagnosis. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.

Baseline-free damage detection in composite plates based on the reciprocity principle

NASA Astrophysics Data System (ADS)

Huang, Liping; Zeng, Liang; Lin, Jing

2018-01-01

Lamb wave based damage detection techniques have been widely used in composite structures. In particular, these techniques usually rely on reference signals, which are significantly influenced by the operational and environmental conditions. To solve this issue, this paper presents a baseline-free damage inspection method based on the reciprocity principle. If a localized nonlinear scatterer exists along the wave path, the reciprocity breaks down. Through estimating the loss of reciprocity, the delamination could be detected. A reciprocity index (RI), which compares the discrepancy between the signal received in transducer B when emitting from transducer A and the signal received in A when the same source is located in B, is established to quantitatively analyze the reciprocity. Experimental results show that the RI value of a damaged path is much higher than that of a healthy path. In addition, the effects of the parameters of excitation signal (i.e., central frequency and bandwidth) and the position of delamination on the RI value are discussed. Furthermore, a RI based probabilistic imaging algorithm is proposed for detecting delamination damage of composite plates without reference signals. Finally, the effectiveness of this baseline-free damage detection method is validated by an experimental example.

Change detection of medical images using dictionary learning techniques and PCA

NASA Astrophysics Data System (ADS)

Nika, Varvara; Babyn, Paul; Zhu, Hongmei

2014-03-01

Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of MRI scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. In this paper we present the Eigen-Block Change Detection algorithm (EigenBlockCD). It performs local registration and identifies the changes between consecutive MR images of the brain. Blocks of pixels from baseline scan are used to train local dictionaries that are then used to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between L1 and L2 norms as two possible similarity measures in the EigenBlockCD. We show the advantages of L2 norm over L1 norm theoretically and numerically. We also demonstrate the performance of the EigenBlockCD algorithm for detecting changes of MR images and compare our results with those provided in recent literature. Experimental results with both simulated and real MRI scans show that the EigenBlockCD outperforms the previous methods. It detects clinical changes while ignoring the changes due to patient's position and other acquisition artifacts.

Procedures for the interpretation and use of elevation scanning laser/multi-sensor data for short range hazard detection and avoidance for an autonomous planetary rover

NASA Technical Reports Server (NTRS)

Troiani, N.; Yerazunis, S. W.

1978-01-01

An autonomous roving science vehicle that relies on terrain data acquired by a hierarchy of sensors for navigation was one method of carrying out such a mission. The hierarchy of sensors included a short range sensor with sufficient resolution to detect every possible obstacle and with the ability to make fast and reliable terrain characterizations. A multilaser, multidetector triangulation system was proposed as a short range sensor. The general system was studied to determine its perception capabilities and limitations. A specific rover and low resolution sensor system was then considered. After studying the data obtained, a hazard detection algorithm was developed that accounts for all possible terrains given the sensor resolution. Computer simulation of the rover on various terrains was used to test the entire hazard detection system.

Bacteriophages of lactic acid bacteria and their impact on milk fermentations

PubMed Central

2011-01-01

Every biotechnology process that relies on the use of bacteria to make a product or to overproduce a molecule may, at some time, struggle with the presence of virulent phages. For example, phages are the primary cause of fermentation failure in the milk transformation industry. This review focuses on the recent scientific advances in the field of lactic acid bacteria phage research. Three specific topics, namely, the sources of contamination, the detection methods and the control procedures will be discussed. PMID:21995802

A Fe K Line in GRB 970508

NASA Astrophysics Data System (ADS)

Protassov, R.; van Dyk, D.; Connors, A.; Kashyap, V.; Siemiginowska, A.

2000-12-01

We examine the x-ray spectrum of the afterglow of GRB 970508, analyzed for Fe line emission by Piro et al (1999, ApJL, 514, L73). This is a difficult and extremely important measurement: the detection of x-ray afterglows from γ -ray bursts is at best a tricky business, relying on near-real satellite time response to unpredictable events; and a great deal of luck in catching a burst bright enough for a useful spectral analysis. Detecting a clear atomic (or cyclotron) line in the generally smooth and featureless afterglow (or burst) emission not only gives one of the few very specific keys to the physics local to the emission region, but also provides clues or confirmation of its distance (via redshift). Unfortunately, neither the likelihood ratio test or the related F-statistic commonly used to detect spectral lines adhere to their nominal Chi square and F-distributions. Thus we begin by calibrating the F-statistic used in Piro et al (1999, ApJL, 514, L73) via a simulation study. The simulation study relies on a completely specified source model, i.e. we do Monte Carlo simulations with all model parameters fixed (so--called ``parametric bootstrapping''). Second, we employ the method of posterior predictive p-values to calibrate a LRT statistic while accounting for the uncertainty in the parameters of the source model. Our analysis reveals evidence for the Fe K line.

High sensitive and direct fluorescence detection of single viral DNA sequences by integration of double strand probes onto microgels particles.

PubMed

Aliberti, A; Cusano, A M; Battista, E; Causa, F; Netti, P A

2016-02-21

A novel class of probes for fluorescence detection was developed and combined to microgel particles for a high sensitive fluorescence detection of nucleic acids. A double strand probe with an optimized fluorescent-quencher couple was designed for the detection of different lengths of nucleic acids (39 nt and 100 nt). Such probe proved efficient in target detection in different contests and specific even in presence of serum proteins. The conjugation of double strand probes onto polymeric microgels allows for a sensitive detection of DNA sequences from HIV, HCV and SARS corona viruses with a LOD of 1.4 fM, 3.7 fM and 1.4 fM, respectively, and with a dynamic range of 10(-9)-10(-15) M. Such combination enhances the sensitivity of the detection of almost five orders of magnitude when compared to the only probe. The proposed platform based on the integration of innovative double strand probe into microgels particles represents an attractive alternative to conventional sensitive DNA detection technologies that rely on amplifications methods.

A Novel Approach to Rotorcraft Damage Tolerance

NASA Technical Reports Server (NTRS)

Forth, Scott C.; Everett, Richard A.; Newman, John A.

2002-01-01

Damage-tolerance methodology is positioned to replace safe-life methodologies for designing rotorcraft structures. The argument for implementing a damage-tolerance method comes from the fundamental fact that rotorcraft structures typically fail by fatigue cracking. Therefore, if technology permits prediction of fatigue-crack growth in structures, a damage-tolerance method should deliver the most accurate prediction of component life. Implementing damage-tolerance (DT) into high-cycle-fatigue (HCF) components will require a shift from traditional DT methods that rely on detecting an initial flaw with nondestructive inspection (NDI) methods. The rapid accumulation of cycles in a HCF component will result in a design based on a traditional DT method that is either impractical because of frequent inspections, or because the design will be too heavy to operate efficiently. Furthermore, once a HCF component develops a detectable propagating crack, the remaining fatigue life is short, sometimes less than one flight hour, which does not leave sufficient time for inspection. Therefore, designing a HCF component will require basing the life analysis on an initial flaw that is undetectable with current NDI technology.

Resolving the depth of fluorescent light by structured illumination and shearing interferometry

NASA Astrophysics Data System (ADS)

Schindler, Johannes; Elmaklizi, Ahmed; Voit, Florian; Hohmann, Ansgar; Schau, Philipp; Brodhag, Nicole; Krauter, Philipp; Frenner, Karsten; Kienle, Alwin; Osten, Wolfgang

2016-03-01

A method for the depth-sensitive detection of fluorescent light is presented. It relies on a structured illumination restricting the excitation volume and on an interferometric detection of the wave front curvature. The illumination with two intersecting beams of a white-light laser separated in a Sagnac interferometer coupled to the microscope provides a coarse confinement in lateral and axial direction. The depth reconstruction is carried out by evaluating shearing interferograms produced with a Michelson interferometer. This setup can also be used with spatially and temporally incoherent light as emitted by fluorophores. A simulation workflow of the method was developed using a combination of a solution of Maxwell's equations with the Monte Carlo method. These simulations showed the principal feasibility of the method. The method is validated by measurements at reference samples with characterized material properties, locations and sizes of fluorescent regions. It is demonstrated that sufficient signal quality can be obtained for materials with scattering properties comparable to dental enamel while maintaining moderate illumination powers in the milliwatt range. The depth reconstruction is demonstrated for a range of distances and penetration depths of several hundred micrometers.

A non-radioisotopic quantitative competitive polymerase chain reaction method: application in measurement of human herpesvirus 7 load.

PubMed

Kidd, I M; Clark, D A; Emery, V C

2000-06-01

Quantitative-competitive polymerase chain reaction (QCPCR) is a well-optimised and objective methodology for the determination of viral load in clinical specimens. A major advantage of QCPCR is the ability to control for the differential modulation of the PCR process in the presence of potentially inhibitory material. QCPCR protocols were developed previously for CMV, HHV-6, HHV-7 and HHV-8 and relied upon radioactively labelled primers, followed by autoradiography of the separated and digested PCR products to quantify viral load. Whilst this approach offers high accuracy and dynamic range, non-radioactive approaches would be attractive. Here, an alternative detection system is reported, based on simple ethidium bromide staining and computer analysis of the separated reaction products, which enables its adoption in the analysis of a large number of samples. In calibration experiments using cloned HHV-7 DNA, the ethidium bromide detection method showed an improved correlation with known copy number over that obtained with the isotopic method. In addition, 67 HHV-7 PCR positive blood samples, derived from immunocompromised patients, were quantified using both detection techniques. The results showed a highly significant correlation with no significant difference between the two methods. The applicability of the computerised densitometry method in the routine laboratory is discussed.

Detecting Smoking Events Using Accelerometer Data Collected Via Smartwatch Technology: Validation Study

PubMed Central

Cole, Casey A; Anshari, Dien; Lambert, Victoria; Thrasher, James F

2017-01-01

Background Smoking is the leading cause of preventable death in the world today. Ecological research on smoking in context currently relies on self-reported smoking behavior. Emerging smartwatch technology may more objectively measure smoking behavior by automatically detecting smoking sessions using robust machine learning models. Objective This study aimed to examine the feasibility of detecting smoking behavior using smartwatches. The second aim of this study was to compare the success of observing smoking behavior with smartwatches to that of conventional self-reporting. Methods A convenience sample of smokers was recruited for this study. Participants (N=10) recorded 12 hours of accelerometer data using a mobile phone and smartwatch. During these 12 hours, they engaged in various daily activities, including smoking, for which they logged the beginning and end of each smoking session. Raw data were classified as either smoking or nonsmoking using a machine learning model for pattern recognition. The accuracy of the model was evaluated by comparing the output with a detailed description of a modeled smoking session. Results In total, 120 hours of data were collected from participants and analyzed. The accuracy of self-reported smoking was approximately 78% (96/123). Our model was successful in detecting 100 of 123 (81%) smoking sessions recorded by participants. After eliminating sessions from the participants that did not adhere to study protocols, the true positive detection rate of the smartwatch based-detection increased to more than 90%. During the 120 hours of combined observation time, only 22 false positive smoking sessions were detected resulting in a 2.8% false positive rate. Conclusions Smartwatch technology can provide an accurate, nonintrusive means of monitoring smoking behavior in natural contexts. The use of machine learning algorithms for passively detecting smoking sessions may enrich ecological momentary assessment protocols and cessation intervention studies that often rely on self-reported behaviors and may not allow for targeted data collection and communications around smoking events. PMID:29237580

A universal approach to determine footfall timings from kinematics of a single foot marker in hoofed animals

PubMed Central

Clayton, Hilary M.

2015-01-01

The study of animal movement commonly requires the segmentation of continuous data streams into individual strides. The use of forceplates and foot-mounted accelerometers readily allows the detection of the foot-on and foot-off events that define a stride. However, when relying on optical methods such as motion capture, there is lack of validated robust, universally applicable stride event detection methods. To date, no method has been validated for movement on a circle, while algorithms are commonly specific to front/hind limbs or gait. In this study, we aimed to develop and validate kinematic stride segmentation methods applicable to movement on straight line and circle at walk and trot, which exclusively rely on a single, dorsal hoof marker. The advantage of such marker placement is the robustness to marker loss and occlusion. Eight horses walked and trotted on a straight line and in a circle over an array of multiple forceplates. Kinetic events were detected based on the vertical force profile and used as the reference values. Kinematic events were detected based on displacement, velocity or acceleration signals of the dorsal hoof marker depending on the algorithm using (i) defined thresholds associated with derived movement signals and (ii) specific events in the derived movement signals. Method comparison was performed by calculating limits of agreement, accuracy, between-horse precision and within-horse precision based on differences between kinetic and kinematic event. In addition, we examined the effect of force thresholds ranging from 50 to 150 N on the timings of kinetic events. The two approaches resulted in very good and comparable performance: of the 3,074 processed footfall events, 95% of individual foot on and foot off events differed by no more than 26 ms from the kinetic event, with average accuracy between −11 and 10 ms and average within- and between horse precision ≤8 ms. While the event-based method may be less likely to suffer from scaling effects, on soft ground the threshold-based method may prove more valuable. While we found that use of velocity thresholds for foot on detection results in biased event estimates for the foot on the inside of the circle at trot, adjusting thresholds for this condition negated the effect. For the final four algorithms, we found no noteworthy bias between conditions or between front- and hind-foot timings. Different force thresholds in the range of 50 to 150 N had the greatest systematic effect on foot-off estimates in the hind limbs (up to on average 16 ms per condition), being greater than the effect on foot-on estimates or foot-off estimates in the forelimbs (up to on average ±7 ms per condition). PMID:26157641

Optical detection of special nuclear materials: an alternative approach for standoff and remote sensing

NASA Astrophysics Data System (ADS)

Johnson, J. Bruce; Reeve, S. W.; Burns, W. A.; Allen, Susan D.

2010-04-01

Termed Special Nuclear Material (SNM) by the Atomic Energy Act of 1954, fissile materials, such as 235U and 239Pu, are the primary components used to construct modern nuclear weapons. Detecting the clandestine presence of SNM represents an important capability for Homeland Security. An ideal SNM sensor must be able to detect fissile materials present at ppb levels, be able to distinguish between the source of the detected fissile material, i.e., 235U, 239Pu, 233U or other fission source, and be able to perform the discrimination in near real time. A sensor with such capabilities would provide not only rapid identification of a threat but, ultimately, information on the potential source of the threat. For example, current detection schemes for monitoring clandestine nuclear testing and nuclear fuel reprocessing to provide weapons grade fissile material rely largely on passive air sampling combined with a subsequent instrumental analysis or some type of wet chemical analysis of the collected material. It would be highly useful to have a noncontact method of measuring isotopes capable of providing forensic information rapidly at ppb levels of detection. Here we compare the use of Kr, Xe and I as "canary" species for distinguishing between 235U and 239Pu fission sources by spectroscopic methods.

Chemiluminescent labels released from long spacer arm-functionalized magnetic particles: a novel strategy for ultrasensitive and highly selective detection of pathogen infections.

PubMed

Yang, Haowen; Liang, Wenbiao; He, Nongyue; Deng, Yan; Li, Zhiyang

2015-01-14

Previously, the unique advantages provided by chemiluminescence (CL) and magnetic particles (MPs) have resulted in the development of many useful nucleic acid detection methods. CL is highly sensitive, but when applied to MPs, its intensity is limited by the inner filter-like effect arising from excess dark MPs. Herein, we describe a modified strategy whereby CL labels are released from MPs to eliminate this negative effect. This approach relies on (1) the magnetic capture of target molecules on long spacer arm-functionalized magnetic particles (LSA-MPs), (2) the conjugation of streptavidin-alkaline phosphatase (SA-AP) to biotinylated amplicons of target pathogens, (3) the release of CL labels (specifically, AP tags), and (4) the detection of the released labels. CL labels were released from LSA-MPs through LSA ultrasonication or DNA enzymolysis, which proved to be the superior method. In contrast to conventional MPs, LSA-MPs exhibited significantly improved CL detection, because of the introduction of LSA, which was made of water-soluble carboxymethylated β-1,3-glucan. Detection of hepatitis B virus with this technique revealed a low detection limit of 50 fM, high selectivity, and excellent reproducibility. Thus, this approach may hold great potential for early stage clinical diagnosis of infectious diseases.

Detection of interaction articles and experimental methods in biomedical literature.

PubMed

Schneider, Gerold; Clematide, Simon; Rinaldi, Fabio

2011-10-03

This article describes the approaches taken by the OntoGene group at the University of Zurich in dealing with two tasks of the BioCreative III competition: classification of articles which contain curatable protein-protein interactions (PPI-ACT) and extraction of experimental methods (PPI-IMT). Two main achievements are described in this paper: (a) a system for document classification which crucially relies on the results of an advanced pipeline of natural language processing tools; (b) a system which is capable of detecting all experimental methods mentioned in scientific literature, and listing them with a competitive ranking (AUC iP/R > 0.5). The results of the BioCreative III shared evaluation clearly demonstrate that significant progress has been achieved in the domain of biomedical text mining in the past few years. Our own contribution, together with the results of other participants, provides evidence that natural language processing techniques have become by now an integral part of advanced text mining approaches.

Invasive candidiasis: future directions in non-culture based diagnosis.

PubMed

Posch, Wilfried; Heimdörfer, David; Wilflingseder, Doris; Lass-Flörl, Cornelia

2017-09-01

Delayed initial antifungal therapy is associated with high mortality rates caused by invasive candida infections, since accurate detection of the opportunistic pathogenic yeast and its identification display a diagnostic challenge. diagnosis of candida infections relies on time-consuming methods such as blood cultures, serologic and histopathologic examination. to allow for fast detection and characterization of invasive candidiasis, there is a need to improve diagnostic tools. trends in diagnostics switch to non-culture-based methods, which allow specified diagnosis within significantly shorter periods of time in order to provide early and appropriate antifungal treatment. Areas covered: within this review comprise novel pathogen- and host-related testing methods, e.g. multiplex-PCR analyses, T2 magnetic resonance, fungus-specific DNA microarrays, microRNA characterization or analyses of IL-17 as biomarker for early detection of invasive candidiasis. Expert commentary: Early recognition and diagnosis of fungal infections is a key issue for improved patient management. As shown in this review, a broad range of novel molecular based tests for the detection and identification of Candida species is available. However, several assays are in-house assays and lack standardization, clinical validation as well as data on sensitivity and specificity. This underscores the need for the development of faster and more accurate diagnostic tests.

AEG-1 promoter-mediated imaging of prostate cancer

PubMed Central

Bhatnagar, Akrita; Wang, Yuchuan; Mease, Ronnie C.; Gabrielson, Matthew; Sysa, Polina; Minn, Il; Green, Gilbert; Simmons, Brian; Gabrielson, Kathleen; Sarkar, Siddik; Fisher, Paul B.; Pomper, Martin G.

2014-01-01

We describe a new imaging method for detecting prostate cancer, whether localized or disseminated and metastatic to soft tissues and bone. The method relies on the use of imaging reporter genes under the control of the promoter of AEG-1 (MTDH), which is selectively active only in malignant cells. Through systemic, nanoparticle-based delivery of the imaging construct, lesions can be identified through bioluminescence imaging and single photon emission-computed tomography in the PC3-ML murine model of prostate cancer at high sensitivity. This approach is applicable for the detection of prostate cancer metastases, including bone lesions for which there is no current reliable agent for non-invasive clinical imaging. Further, the approach compares favorably to accepted and emerging clinical standards, including positron emission tomography with [18F]fluorodeoxyglucose and [18F]sodium fluoride. Our results offer a preclinical proof of concept that rationalizes clinical evaluation in patients with advanced prostate cancer. PMID:25145668

Semantic Segmentation and Unregistered Building Detection from Uav Images Using a Deconvolutional Network

NASA Astrophysics Data System (ADS)

Ham, S.; Oh, Y.; Choi, K.; Lee, I.

2018-05-01

Detecting unregistered buildings from aerial images is an important task for urban management such as inspection of illegal buildings in green belt or update of GIS database. Moreover, the data acquisition platform of photogrammetry is evolving from manned aircraft to UAVs (Unmanned Aerial Vehicles). However, it is very costly and time-consuming to detect unregistered buildings from UAV images since the interpretation of aerial images still relies on manual efforts. To overcome this problem, we propose a system which automatically detects unregistered buildings from UAV images based on deep learning methods. Specifically, we train a deconvolutional network with publicly opened geospatial data, semantically segment a given UAV image into a building probability map and compare the building map with existing GIS data. Through this procedure, we could detect unregistered buildings from UAV images automatically and efficiently. We expect that the proposed system can be applied for various urban management tasks such as monitoring illegal buildings or illegal land-use change.

A technique for simultaneous detection of individual vortex states of Laguerre-Gaussian beams transmitted through an aqueous suspension of microparticles

NASA Astrophysics Data System (ADS)

Khonina, S. N.; Karpeev, S. V.; Paranin, V. D.

2018-06-01

A technique for simultaneous detection of individual vortex states of the beams propagating in a randomly inhomogeneous medium is proposed. The developed optical system relies on the correlation method that is invariant to the beam wandering. The intensity distribution formed at the optical system output does not require digital processing. The proposed technique based on a multi-order phase diffractive optical element (DOE) is studied numerically and experimentally. The developed detection technique is used for the analysis of Laguerre-Gaussian vortex beams propagating under conditions of intense absorption, reflection, and scattering in transparent and opaque microparticles in aqueous suspensions. The performed experimental studies confirm the relevance of the vortex phase dependence of a laser beam under conditions of significant absorption, reflection, and scattering of the light.

Development and evaluation of a blocking enzyme-linked immunosorbent assay and virus neutralization assay to detect antibodies to viral hemorrhagic septicemia virus

USGS Publications Warehouse

Wilson, Anna; Goldberg, Tony; Marcquenski, Susan; Olson, Wendy; Goetz, Frederick; Hershberger, Paul; Hart, Lucas M.; Toohey-Kurth, Kathy

2014-01-01

Viral hemorrhagic septicemia virus (VHSV) is a target of surveillance by many state and federal agencies in the United States. Currently, the detection of VHSV relies on virus isolation, which is lethal to fish and indicates only the current infection status. A serological method is required to ascertain prior exposure. Here, we report two serologic tests for VHSV that are nonlethal, rapid, and species independent, a virus neutralization (VN) assay and a blocking enzyme-linked immunosorbent assay (ELISA). The results show that the VN assay had a specificity of 100% and sensitivity of 42.9%; the anti-nucleocapsid-blocking ELISA detected nonneutralizing VHSV antibodies at a specificity of 88.2% and a sensitivity of 96.4%. The VN assay and ELISA are valuable tools for assessing exposure to VHSV.

Defect Detection and Segmentation Framework for Remote Field Eddy Current Sensor Data

PubMed Central

2017-01-01

Remote-Field Eddy-Current (RFEC) technology is often used as a Non-Destructive Evaluation (NDE) method to prevent water pipe failures. By analyzing the RFEC data, it is possible to quantify the corrosion present in pipes. Quantifying the corrosion involves detecting defects and extracting their depth and shape. For large sections of pipelines, this can be extremely time-consuming if performed manually. Automated approaches are therefore well motivated. In this article, we propose an automated framework to locate and segment defects in individual pipe segments, starting from raw RFEC measurements taken over large pipelines. The framework relies on a novel feature to robustly detect these defects and a segmentation algorithm applied to the deconvolved RFEC signal. The framework is evaluated using both simulated and real datasets, demonstrating its ability to efficiently segment the shape of corrosion defects. PMID:28984823

Defect Detection and Segmentation Framework for Remote Field Eddy Current Sensor Data.

PubMed

Falque, Raphael; Vidal-Calleja, Teresa; Miro, Jaime Valls

2017-10-06

Remote-Field Eddy-Current (RFEC) technology is often used as a Non-Destructive Evaluation (NDE) method to prevent water pipe failures. By analyzing the RFEC data, it is possible to quantify the corrosion present in pipes. Quantifying the corrosion involves detecting defects and extracting their depth and shape. For large sections of pipelines, this can be extremely time-consuming if performed manually. Automated approaches are therefore well motivated. In this article, we propose an automated framework to locate and segment defects in individual pipe segments, starting from raw RFEC measurements taken over large pipelines. The framework relies on a novel feature to robustly detect these defects and a segmentation algorithm applied to the deconvolved RFEC signal. The framework is evaluated using both simulated and real datasets, demonstrating its ability to efficiently segment the shape of corrosion defects.

Automated segmentation and tracking of non-rigid objects in time-lapse microscopy videos of polymorphonuclear neutrophils.

PubMed

Brandes, Susanne; Mokhtari, Zeinab; Essig, Fabian; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-02-01

Time-lapse microscopy is an important technique to study the dynamics of various biological processes. The labor-intensive manual analysis of microscopy videos is increasingly replaced by automated segmentation and tracking methods. These methods are often limited to certain cell morphologies and/or cell stainings. In this paper, we present an automated segmentation and tracking framework that does not have these restrictions. In particular, our framework handles highly variable cell shapes and does not rely on any cell stainings. Our segmentation approach is based on a combination of spatial and temporal image variations to detect moving cells in microscopy videos. This method yields a sensitivity of 99% and a precision of 95% in object detection. The tracking of cells consists of different steps, starting from single-cell tracking based on a nearest-neighbor-approach, detection of cell-cell interactions and splitting of cell clusters, and finally combining tracklets using methods from graph theory. The segmentation and tracking framework was applied to synthetic as well as experimental datasets with varying cell densities implying different numbers of cell-cell interactions. We established a validation framework to measure the performance of our tracking technique. The cell tracking accuracy was found to be >99% for all datasets indicating a high accuracy for connecting the detected cells between different time points. Copyright © 2014 Elsevier B.V. All rights reserved.

Inductance and resistance measurement method for vessel detection and coil powering in all-surface inductive heating systems composed of outer squircle coils

NASA Astrophysics Data System (ADS)

Kilic, Veli Tayfun; Unal, Emre; Demir, Hilmi Volkan

2017-05-01

In this work, we investigate a method proposed for vessel detection and coil powering in an all-surface inductive heating system composed of outer squircle coils. Besides conventional circular coils, coils with different shapes such as outer squircle coils are used for and enable efficient all-surface inductive heating. Validity of the method, which relies on measuring inductance and resistance values of a loaded coil at different frequencies, is experimentally demonstrated for a coil with shape different from conventional circular coil. Simple setup was constructed with a small coil to model an all-surface inductive heating system. Inductance and resistance maps were generated by measuring coil's inductance and resistance values at different frequencies loaded by a plate made of different materials and located at various positions. Results show that in an induction hob for various coil geometries it is possible to detect a vessel's presence, to identify its material type and to specify its position on the hob surface by considering inductance and resistance of the coil measured on at least two different frequencies. The studied method is important in terms of enabling safe, efficient and user flexible heating in an all-surface inductive heating system by automatically detecting the vessel's presence and powering on only the coils that are loaded by the vessel with predetermined current levels.

Mechanical properties of resin cements with different activation modes.

PubMed

Braga, R R; Cesar, P F; Gonzaga, C C

2002-03-01

Dual-cured cements have been studied in terms of the hardness or degree of conversion achieved with different curing modes. However, little emphasis is given to the influence of the curing method on other mechanical properties. This study investigated the flexural strength, flexural modulus and hardness of four proprietary resin cements. Materials tested were: Enforce and Variolink II (light-, self- and dual-cured), RelyX ARC (self- and dual-cured) and C & B (self-cured). Specimens were fractured using a three-point bending test. Pre-failure loads corresponding to specific displacements of the cross-head were used for flexural modulus calculation. Knoop hardness (KHN) was measured on fragments obtained after the flexural test. Tests were performed after 24 h storage at 37 degrees C. RelyX ARC dual-cured showed higher flexural strength than the other groups. RelyX ARC and Variolink II depended upon photo-activation to achieve higher hardness values. Enforce showed similar hardness for dual- and self-curing modes. No correlation was found between flexural strength and hardness, indicating that other factors besides the degree of cure (e.g. filler content and monomer type) affect the flexural strength of composites. No statistical difference was detected in the flexural modulus among the different groups.

A brief review on recent developments of electrochemical sensors in environmental application for PGMs.

PubMed

Silwana, Bongiwe; Van Der Horst, Charlton; Iwuoha, Emmanuel; Somerset, Vernon

2016-12-05

This study offers a brief review of the latest developments and applications of electrochemical sensors for the detection of Platinum Group Metals (PGMs) using electrochemical sensors. In particular, significant advances in electrochemical sensors made over the past decade and sensing methodologies associated with the introduction of nanostructures are highlighted. Amongst a variety of detection methods that have been developed for PGMs, nanoparticles offer the unrivaled merits of high sensitivity. Rapid detection of PGMs is a key step to promote improvement of the public health and individual quality of life. Conventional methods to detect PGMs rely on time-consuming and labor intensive procedures such as extraction, isolation, enrichment, counting, etc., prior to measurement. This results in laborious sample preparation and testing over several days. This study reviewed the state-of-the-art application of nanoparticles (NPs) in electrochemical analysis of environmental pollutants. This review is intended to provide environmental scientists and engineers an overview of current rapid detection methods, a close look at the nanoparticles based electrodes and identification of knowledge gaps and future research needs. We summarize electrodes that have been used in the past for detection of PGMs. We describe several examples of applications in environmental electrochemical sensors and performance in terms of sensitivity and selectivity for all the sensors utilized for PGMs detection. NPs have promising potential to increase competitiveness of electrochemical sensors in environmental monitoring, though this review has focused mainly on sensors used in the past decade for PGMs detection. This review therefore provides a synthesis of outstanding performances in recent advances in the nanosensor application for PGMs determination.

Automated Detection of Salt Marsh Platforms : a Topographic Method

NASA Astrophysics Data System (ADS)

Goodwin, G.; Mudd, S. M.; Clubb, F. J.

2017-12-01

Monitoring the topographic evolution of coastal marshes is a crucial step toward improving the management of these valuable landscapes under the pressure of relative sea level rise and anthropogenic modification. However, determining their geometrically complex boundaries currently relies on spectral vegetation detection methods or requires labour-intensive field surveys and digitisation.We propose a novel method to reproducibly isolate saltmarsh scarps and platforms from a DEM. Field observations and numerical models show that saltmarshes mature into sub-horizontal platforms delineated by sub-vertical scarps: based on this premise, we identify scarps as lines of local maxima on a slope*relief raster, then fill landmasses from the scarps upward, thus isolating mature marsh platforms. Non-dimensional search parameters allow batch-processing of data without recalibration. We test our method using lidar-derived DEMs of six saltmarshes in England with varying tidal ranges and geometries, for which topographic platforms were manually isolated from tidal flats. Agreement between manual and automatic segregation exceeds 90% for resolutions of 1m, with all but one sites maintaining this performance for resolutions up to 3.5m. For resolutions of 1m, automatically detected platforms are comparable in surface area and elevation distribution to digitised platforms. We also find that our method allows the accurate detection of local bloc failures 3 times larger than the DEM resolution.Detailed inspection reveals that although tidal creeks were digitised as part of the marsh platform, automatic detection classifies them as part of the tidal flat, causing an increase in false negatives and overall platform perimeter. This suggests our method would benefit from a combination with existing creek detection algorithms. Fallen blocs and pioneer zones are inconsistently identified, particularly in macro-tidal marshes, leading to differences between digitisation and the automated method: this also suggests that these areas must be carefully considered when analysing erosion and accretion processes. Ultimately, we have shown that automatic detection of marsh platforms from high-resolution topography is possible and sufficient to monitor and analyse topographic evolution.

Detecting bacteria and Determining Their Susceptibility to Antibiotics by Stochastic Confinement in Nanoliter Droplets using Plug-Based Microfluidics

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

Boedicker, J.; Li, L; Kline, T

2008-01-01

This article describes plug-based microfluidic technology that enables rapid detection and drug susceptibility screening of bacteria in samples, including complex biological matrices, without pre-incubation. Unlike conventional bacterial culture and detection methods, which rely on incubation of a sample to increase the concentration of bacteria to detectable levels, this method confines individual bacteria into droplets nanoliters in volume. When single cells are confined into plugs of small volume such that the loading is less than one bacterium per plug, the detection time is proportional to plug volume. Confinement increases cell density and allows released molecules to accumulate around the cell, eliminatingmore » the pre-incubation step and reducing the time required to detect the bacteria. We refer to this approach as stochastic confinement. Using the microfluidic hybrid method, this technology was used to determine the antibiogram - or chart of antibiotic sensitivity - of methicillin-resistant Staphylococcus aureus (MRSA) to many antibiotics in a single experiment and to measure the minimal inhibitory concentration (MIC) of the drug cefoxitin (CFX) against this strain. In addition, this technology was used to distinguish between sensitive and resistant strains of S. aureus in samples of human blood plasma. High-throughput microfluidic techniques combined with single-cell measurements also enable multiple tests to be performed simultaneously on a single sample containing bacteria. This technology may provide a method of rapid and effective patient-specific treatment of bacterial infections and could be extended to a variety of applications that require multiple functional tests of bacterial samples on reduced timescales.« less

Impact detection method for composite winglets based on neural network implementation

NASA Astrophysics Data System (ADS)

Viscardi, Massimo; Arena, Maurizio; Napolitano, Pasquale

2018-03-01

Maintenance tasks and safety aspects represent a strategic role in the managing of the modern aircraft fleets. The demand for reliable techniques for structural health monitoring represent so a key aspect looking forward to new generation aircraft. In particular, the use of more technologically complex materials and manufacturing methods requires anyway more efficient as well as rapid application processes to improve the design strength and service life. Actually, it is necessary to rely on survey instruments, which allow for safeguarding the structural integrity of the aircraft, especially after the wide use of composite structures highly susceptible to non-detected damages as delamination of the ply. In this paper, the authors have investigated the feasibility to implement a neural network-based algorithm to predict the impact event at low frequency, typically due to the bird collision. Relying upon a numerical model, representative of a composite flat panel, the approach has been also experimentally validated. The purpose of the work is therefore the presentation of an innovative application within the Non Destructive Testing field based upon vibration measurements. The aim of the research has been the development of a Non Destructive Test which meets most of the mandatory requirements for effective health monitoring systems while, at the same time, reducing as much as possible the complexity of the data analysis algorithm and the experimental acquisition instrumentation. Future activities will be addressed to test such technique on a more complex aeronautical system.

Toward multimodal signal detection of adverse drug reactions.

PubMed

Harpaz, Rave; DuMouchel, William; Schuemie, Martijn; Bodenreider, Olivier; Friedman, Carol; Horvitz, Eric; Ripple, Anna; Sorbello, Alfred; White, Ryen W; Winnenburg, Rainer; Shah, Nigam H

2017-12-01

Improving mechanisms to detect adverse drug reactions (ADRs) is key to strengthening post-marketing drug safety surveillance. Signal detection is presently unimodal, relying on a single information source. Multimodal signal detection is based on jointly analyzing multiple information sources. Building on, and expanding the work done in prior studies, the aim of the article is to further research on multimodal signal detection, explore its potential benefits, and propose methods for its construction and evaluation. Four data sources are investigated; FDA's adverse event reporting system, insurance claims, the MEDLINE citation database, and the logs of major Web search engines. Published methods are used to generate and combine signals from each data source. Two distinct reference benchmarks corresponding to well-established and recently labeled ADRs respectively are used to evaluate the performance of multimodal signal detection in terms of area under the ROC curve (AUC) and lead-time-to-detection, with the latter relative to labeling revision dates. Limited to our reference benchmarks, multimodal signal detection provides AUC improvements ranging from 0.04 to 0.09 based on a widely used evaluation benchmark, and a comparative added lead-time of 7-22 months relative to labeling revision dates from a time-indexed benchmark. The results support the notion that utilizing and jointly analyzing multiple data sources may lead to improved signal detection. Given certain data and benchmark limitations, the early stage of development, and the complexity of ADRs, it is currently not possible to make definitive statements about the ultimate utility of the concept. Continued development of multimodal signal detection requires a deeper understanding the data sources used, additional benchmarks, and further research on methods to generate and synthesize signals. Copyright © 2017 Elsevier Inc. All rights reserved.

Methodological Guidelines for Accurate Detection of Viruses in Wild Plant Species

PubMed Central

Renner, Kurra; Cole, Ellen; Seabloom, Eric W.; Borer, Elizabeth T.; Malmstrom, Carolyn M.

2016-01-01

Ecological understanding of disease risk, emergence, and dynamics and of the efficacy of control strategies relies heavily on efficient tools for microorganism identification and characterization. Misdetection, such as the misclassification of infected hosts as healthy, can strongly bias estimates of disease prevalence and lead to inaccurate conclusions. In natural plant ecosystems, interest in assessing microbial dynamics is increasing exponentially, but guidelines for detection of microorganisms in wild plants remain limited, particularly so for plant viruses. To address this gap, we explored issues and solutions associated with virus detection by serological and molecular methods in noncrop plant species as applied to the globally important Barley yellow dwarf virus PAV (Luteoviridae), which infects wild native plants as well as crops. With enzyme-linked immunosorbent assays (ELISA), we demonstrate how virus detection in a perennial wild plant species may be much greater in stems than in leaves, although leaves are most commonly sampled, and may also vary among tillers within an individual, thereby highlighting the importance of designing effective sampling strategies. With reverse transcription-PCR (RT-PCR), we demonstrate how inhibitors in tissues of perennial wild hosts can suppress virus detection but can be overcome with methods and products that improve isolation and amplification of nucleic acids. These examples demonstrate the paramount importance of testing and validating survey designs and virus detection methods for noncrop plant communities to ensure accurate ecological surveys and reliable assumptions about virus dynamics in wild hosts. PMID:26773088

Methodological Guidelines for Accurate Detection of Viruses in Wild Plant Species.

PubMed

Lacroix, Christelle; Renner, Kurra; Cole, Ellen; Seabloom, Eric W; Borer, Elizabeth T; Malmstrom, Carolyn M

2016-01-15

Ecological understanding of disease risk, emergence, and dynamics and of the efficacy of control strategies relies heavily on efficient tools for microorganism identification and characterization. Misdetection, such as the misclassification of infected hosts as healthy, can strongly bias estimates of disease prevalence and lead to inaccurate conclusions. In natural plant ecosystems, interest in assessing microbial dynamics is increasing exponentially, but guidelines for detection of microorganisms in wild plants remain limited, particularly so for plant viruses. To address this gap, we explored issues and solutions associated with virus detection by serological and molecular methods in noncrop plant species as applied to the globally important Barley yellow dwarf virus PAV (Luteoviridae), which infects wild native plants as well as crops. With enzyme-linked immunosorbent assays (ELISA), we demonstrate how virus detection in a perennial wild plant species may be much greater in stems than in leaves, although leaves are most commonly sampled, and may also vary among tillers within an individual, thereby highlighting the importance of designing effective sampling strategies. With reverse transcription-PCR (RT-PCR), we demonstrate how inhibitors in tissues of perennial wild hosts can suppress virus detection but can be overcome with methods and products that improve isolation and amplification of nucleic acids. These examples demonstrate the paramount importance of testing and validating survey designs and virus detection methods for noncrop plant communities to ensure accurate ecological surveys and reliable assumptions about virus dynamics in wild hosts. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Next day Salmonella spp. detection method based on real-time PCR for meat, dairy and vegetable food products.

PubMed

Rodriguez-Lazaro, David; Gonzalez-García, Patricia; Delibato, Elisabetta; De Medici, Dario; García-Gimeno, Rosa Maria; Valero, Antonio; Hernandez, Marta

2014-08-01

The microbiological standard for detection of Salmonella relies on several cultural steps and requires more than 5 days for final confirmation, and as consequence there is a need for an alternative rapid methodology for its detection. The aim of this study was to compare different detection strategies based on real-time PCR for a rapid and sensitive detection in an ample range of food products: raw pork and poultry meat, ready to eat lettuce salad and raw sheep milk cured cheese. Three main parameters were evaluated to reduce the time and cost for final results: the initial sample size (25 and 50 g), the incubation times (6, 10 and 18 h) and the bacterial DNA extraction (simple boiling of the culture after washing the bacterial pellet, the use of the Chelex resin, and a commercial silica column). The results obtained demonstrate that a combination of an incubation in buffered peptone water for 18 h of a 25 g-sample coupled to a DNA extraction by boiling and a real-time PCR assay detected down to 2-4 Salmonella spp.CFU per sample in less than 21 h in different types of food products. This RTi-PCR-based method is fully compatible with the ISO standard, providing results more rapidly and cost-effectively. The results were confirmed in a large number of naturally contaminated food samples with at least the same analytical performance as the reference method. Copyright © 2014 Elsevier B.V. All rights reserved.

Flaws detection and localization in weld structure using the topological energy method

NASA Astrophysics Data System (ADS)

Lubeigt, Emma; Mensah, Serge; Rakotonarivo, Sandrine; Chaix, Jean-François; Gobillot, Gilles; Baqué, François

2017-02-01

The non-destructive testing of austenitic welds using ultrasound plays an important role in the assessment of the structural integrity and safety of critical structures in a nuclear reactor. The bedspring and the deck are complex welded structures of very restricted access; the ability to reliably detect and locate defects like cracks is therefore a difficult challenge. Ultrasonic testing is a well-recognized non-invasive technique which exhibits high characterization performances in homogeneous media (steel). However, its capabilities are hampered when operating in heterogeneous and anisotropic austenitic welds because of deviation and splitting of the ultrasonic beam. In order to rise to this important challenge, a model-based method is proposed, which takes into account a prior knowledge corresponding to the welding procedure specifications that condition the austenitic grains orientation within the weld and thus the wave propagation. The topological imaging method implemented is a differential approach which, compares signals from the reference defect-free medium to the inspected medium. It relies on combinations of two computed ultrasonic fields, one forward and one adjoint. Numerical simulations and experiments have been carried out to validate the practical relevance of this approach to detect and locate a flaw in a weld.

Automated determination of arterial input function for DCE-MRI of the prostate

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Chang, Ming-Ching; Gupta, Sandeep

2011-03-01

Prostate cancer is one of the commonest cancers in the world. Dynamic contrast enhanced MRI (DCE-MRI) provides an opportunity for non-invasive diagnosis, staging, and treatment monitoring. Quantitative analysis of DCE-MRI relies on determination of an accurate arterial input function (AIF). Although several methods for automated AIF detection have been proposed in literature, none are optimized for use in prostate DCE-MRI, which is particularly challenging due to large spatial signal inhomogeneity. In this paper, we propose a fully automated method for determining the AIF from prostate DCE-MRI. Our method is based on modeling pixel uptake curves as gamma variate functions (GVF). First, we analytically compute bounds on GVF parameters for more robust fitting. Next, we approximate a GVF for each pixel based on local time domain information, and eliminate the pixels with false estimated AIFs using the deduced upper and lower bounds. This makes the algorithm robust to signal inhomogeneity. After that, according to spatial information such as similarity and distance between pixels, we formulate the global AIF selection as an energy minimization problem and solve it using a message passing algorithm to further rule out the weak pixels and optimize the detected AIF. Our method is fully automated without training or a priori setting of parameters. Experimental results on clinical data have shown that our method obtained promising detection accuracy (all detected pixels inside major arteries), and a very good match with expert traced manual AIF.

Optimal filtering and Bayesian detection for friction-based diagnostics in machines.

PubMed

Ray, L R; Townsend, J R; Ramasubramanian, A

2001-01-01

Non-model-based diagnostic methods typically rely on measured signals that must be empirically related to process behavior or incipient faults. The difficulty in interpreting a signal that is indirectly related to the fundamental process behavior is significant. This paper presents an integrated non-model and model-based approach to detecting when process behavior varies from a proposed model. The method, which is based on nonlinear filtering combined with maximum likelihood hypothesis testing, is applicable to dynamic systems whose constitutive model is well known, and whose process inputs are poorly known. Here, the method is applied to friction estimation and diagnosis during motion control in a rotating machine. A nonlinear observer estimates friction torque in a machine from shaft angular position measurements and the known input voltage to the motor. The resulting friction torque estimate can be analyzed directly for statistical abnormalities, or it can be directly compared to friction torque outputs of an applicable friction process model in order to diagnose faults or model variations. Nonlinear estimation of friction torque provides a variable on which to apply diagnostic methods that is directly related to model variations or faults. The method is evaluated experimentally by its ability to detect normal load variations in a closed-loop controlled motor driven inertia with bearing friction and an artificially-induced external line contact. Results show an ability to detect statistically significant changes in friction characteristics induced by normal load variations over a wide range of underlying friction behaviors.

Probabilistic detection of volcanic ash using a Bayesian approach

NASA Astrophysics Data System (ADS)

Mackie, Shona; Watson, Matthew

2014-03-01

Airborne volcanic ash can pose a hazard to aviation, agriculture, and both human and animal health. It is therefore important that ash clouds are monitored both day and night, even when they travel far from their source. Infrared satellite data provide perhaps the only means of doing this, and since the hugely expensive ash crisis that followed the 2010 Eyjafjalljökull eruption, much research has been carried out into techniques for discriminating ash in such data and for deriving key properties. Such techniques are generally specific to data from particular sensors, and most approaches result in a binary classification of pixels into "ash" and "ash free" classes with no indication of the classification certainty for individual pixels. Furthermore, almost all operational methods rely on expert-set thresholds to determine what constitutes "ash" and can therefore be criticized for being subjective and dependent on expertise that may not remain with an institution. Very few existing methods exploit available contemporaneous atmospheric data to inform the detection, despite the sensitivity of most techniques to atmospheric parameters. The Bayesian method proposed here does exploit such data and gives a probabilistic, physically based classification. We provide an example of the method's implementation for a scene containing both land and sea observations, and a large area of desert dust (often misidentified as ash by other methods). The technique has already been successfully applied to other detection problems in remote sensing, and this work shows that it will be a useful and effective tool for ash detection.

Dot enzyme-linked immunosorbent assay (ELISA) for the detection of Toxocara infection using a rat model.

PubMed

Paller, Vachel Gay V; Besana, Cyrelle M; Valdez, Isabel Kristine M

2017-12-01

Toxocariasis is a zoonotic disease usually caused by dog and cat roundworms, Toxocara canis and T. cati. Detection and diagnosis is difficult in paratenic and accidental hosts, including humans, as they cannot be detected through conventional methods such as fecal examination. Diagnosis therefore relies on immunological methods and molecular methods such as enzyme-linked immunosorbent assay (ELISA) and Western Blot, which are both time-consuming and requires sophisticated equipment. In the Philippines, only a few studies are available on Toxocara seroprevalence. Therefore, there is a need to adapt methods for serodiagnosis of Toxocara infection in humans for the Philippine setting. A dot enzyme linked immunosorbent assay (dot-ELISA) was standardized using T. canis excretory-secretory antigens. Test sera were collected from laboratory rats (Sprague-Dawley strain) experimentally infected with embryonated eggs of T. canis and Ascaris suum as well as rice field rats naturally infected with Taenia taeniaeformis and Nippostrongylus sp. Optimum conditions used were 20 µg/ml antigen concentration and 1:10 serum dilution. The sensitivity, specificity, positive, and negative predictive values were 90% (95% CI 55.5-99.7%), 100% (95% CI 69.2-100.0%), 100% (95% CI 66.4-100%), and 90.9% (95% CI 58.7-99.8%), respectively. Dot-ELISA has the potential to be developed as a cheaper, simpler, and more practical method for detection of anti- Toxocara antibodies on accidental hosts. This is a preliminary study conducted on experimental animals before optimization and standardization for human serum samples.

Detection of Orbital Debris Collision Risks for the Automated Transfer Vehicle

NASA Technical Reports Server (NTRS)

Peret, L.; Legendre, P.; Delavault, S.; Martin, T.

2007-01-01

In this paper, we present a general collision risk assessment method, which has been applied through numerical simulations to the Automated Transfer Vehicle (ATV) case. During ATV ascent towards the International Space Station, close approaches between the ATV and objects of the USSTRACOM catalog will be monitored through collision rosk assessment. Usually, collision risk assessment relies on an exclusion volume or a probability threshold method. Probability methods are more effective than exclusion volumes but require accurate covariance data. In this work, we propose to use a criterion defined by an adaptive exclusion area. This criterion does not require any probability calculation but is more effective than exclusion volume methods as demonstrated by our numerical experiments. The results of these studies, when confirmed and finalized, will be used for the ATV operations.

Understanding reliance on automation: effects of error type, error distribution, age and experience

PubMed Central

Sanchez, Julian; Rogers, Wendy A.; Fisk, Arthur D.; Rovira, Ericka

2015-01-01

An obstacle detection task supported by “imperfect” automation was used with the goal of understanding the effects of automation error types and age on automation reliance. Sixty younger and sixty older adults interacted with a multi-task simulation of an agricultural vehicle (i.e. a virtual harvesting combine). The simulator included an obstacle detection task and a fully manual tracking task. A micro-level analysis provided insight into the way reliance patterns change over time. The results indicated that there are distinct patterns of reliance that develop as a function of error type. A prevalence of automation false alarms led participants to under-rely on the automation during alarm states while over relying on it during non-alarms states. Conversely, a prevalence of automation misses led participants to over-rely on automated alarms and under-rely on the automation during non-alarm states. Older adults adjusted their behavior according to the characteristics of the automation similarly to younger adults, although it took them longer to do so. The results of this study suggest the relationship between automation reliability and reliance depends on the prevalence of specific errors and on the state of the system. Understanding the effects of automation detection criterion settings on human-automation interaction can help designers of automated systems make predictions about human behavior and system performance as a function of the characteristics of the automation. PMID:25642142

Understanding reliance on automation: effects of error type, error distribution, age and experience.

PubMed

Sanchez, Julian; Rogers, Wendy A; Fisk, Arthur D; Rovira, Ericka

2014-03-01

An obstacle detection task supported by "imperfect" automation was used with the goal of understanding the effects of automation error types and age on automation reliance. Sixty younger and sixty older adults interacted with a multi-task simulation of an agricultural vehicle (i.e. a virtual harvesting combine). The simulator included an obstacle detection task and a fully manual tracking task. A micro-level analysis provided insight into the way reliance patterns change over time. The results indicated that there are distinct patterns of reliance that develop as a function of error type. A prevalence of automation false alarms led participants to under-rely on the automation during alarm states while over relying on it during non-alarms states. Conversely, a prevalence of automation misses led participants to over-rely on automated alarms and under-rely on the automation during non-alarm states. Older adults adjusted their behavior according to the characteristics of the automation similarly to younger adults, although it took them longer to do so. The results of this study suggest the relationship between automation reliability and reliance depends on the prevalence of specific errors and on the state of the system. Understanding the effects of automation detection criterion settings on human-automation interaction can help designers of automated systems make predictions about human behavior and system performance as a function of the characteristics of the automation.

Autonomous Scanning Probe Microscopy in Situ Tip Conditioning through Machine Learning.

PubMed

Rashidi, Mohammad; Wolkow, Robert A

2018-05-23

Atomic-scale characterization and manipulation with scanning probe microscopy rely upon the use of an atomically sharp probe. Here we present automated methods based on machine learning to automatically detect and recondition the quality of the probe of a scanning tunneling microscope. As a model system, we employ these techniques on the technologically relevant hydrogen-terminated silicon surface, training the network to recognize abnormalities in the appearance of surface dangling bonds. Of the machine learning methods tested, a convolutional neural network yielded the greatest accuracy, achieving a positive identification of degraded tips in 97% of the test cases. By using multiple points of comparison and majority voting, the accuracy of the method is improved beyond 99%.

Evaporative concentration on a paper-based device to concentrate analytes in a biological fluid.

PubMed

Wong, Sharon Y; Cabodi, Mario; Rolland, Jason; Klapperich, Catherine M

2014-12-16

We report the first demonstration of using heat on a paper device to rapidly concentrate a clinically relevant analyte of interest from a biological fluid. Our technology relies on the application of localized heat to a paper strip to evaporate off hundreds of microliters of liquid to concentrate the target analyte. This method can be used to enrich for a target analyte that is present at low concentrations within a biological fluid to enhance the sensitivity of downstream detection methods. We demonstrate our method by concentrating the tuberculosis-specific glycolipid, lipoarabinomannan (LAM), a promising urinary biomarker for the detection and diagnosis of tuberculosis. We show that the heat does not compromise the subsequent immunodetectability of LAM, and in 20 min, the tuberculosis biomarker was concentrated by nearly 20-fold in simulated urine. Our method requires only 500 mW of power, and sample flow is self-driven via capillary action. As such, our technology can be readily integrated into portable, battery-powered, instrument-free diagnostic devices intended for use in low-resource settings.

GUIDE-Seq enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases

PubMed Central

Nguyen, Nhu T.; Liebers, Matthew; Topkar, Ved V.; Thapar, Vishal; Wyvekens, Nicolas; Khayter, Cyd; Iafrate, A. John; Le, Long P.; Aryee, Martin J.; Joung, J. Keith

2014-01-01

CRISPR RNA-guided nucleases (RGNs) are widely used genome-editing reagents, but methods to delineate their genome-wide off-target cleavage activities have been lacking. Here we describe an approach for global detection of DNA double-stranded breaks (DSBs) introduced by RGNs and potentially other nucleases. This method, called Genome-wide Unbiased Identification of DSBs Enabled by Sequencing (GUIDE-Seq), relies on capture of double-stranded oligodeoxynucleotides into breaks Application of GUIDE-Seq to thirteen RGNs in two human cell lines revealed wide variability in RGN off-target activities and unappreciated characteristics of off-target sequences. The majority of identified sites were not detected by existing computational methods or ChIP-Seq. GUIDE-Seq also identified RGN-independent genomic breakpoint ‘hotspots’. Finally, GUIDE-Seq revealed that truncated guide RNAs exhibit substantially reduced RGN-induced off-target DSBs. Our experiments define the most rigorous framework for genome-wide identification of RGN off-target effects to date and provide a method for evaluating the safety of these nucleases prior to clinical use. PMID:25513782

Loop-Mediated Isothermal Amplification-Lateral-Flow Dipstick (LAMP-LFD) to detect Toxoplasma gondii oocyst in ready-to-eat salad.

PubMed

Lalle, Marco; Possenti, Alessia; Dubey, Jitender P; Pozio, Edoardo

2018-04-01

The apicomplexan parasite Toxoplasma gondii is the causative agent of toxoplasmosis, a foodborne zoonosis with a global distribution and estimated to cause up to 20% of the total foodborne disease burden in Europe. Association between T. gondii infection and the consumption of unwashed raw fruits and vegetables contaminated with oocysts has been reported and the increasing habit to eat pre-washed ready-to-eat salads poses a new potential risk for consumers. It is therefore important to trace the occurrence of potential contamination with this parasite to guarantee the safety of ready-to-eat vegetables. Detection of T. gondii in vegetables by molecular techniques has been achieved but low sensitivity (PCR) or expensive equipments (qPCR) limit routine applicability. Here, we describe the development and validation of a sensitive and robust method relying on a LAMP assay, targeting the 529 bp locus, to detect T. gondii oocysts down to 25 oocysts/50 g in ready-to-eat baby lettuce. The LAMP has been also adapted for a faster visualization of the result by a lateral flow dipstick chromatographic detection method. Copyright © 2017 Elsevier Ltd. All rights reserved.

The seasonal occupancy and diel behaviour of Antarctic sperm whales revealed by acoustic monitoring.

PubMed

Miller, Brian S; Miller, Elanor J

2018-04-03

The seasonal occupancy and diel behaviour of sperm whales (Physeter macrocephalus) was investigated using data from long-term acoustic recorders deployed off east Antarctica. An automated method for investigating acoustic presence of sperm whales was developed, characterised, and applied to multi-year acoustic datasets at three locations. Instead of focusing on the acoustic properties of detected clicks, the method relied solely on the inter-click-interval (ICI) for determining presence within an hour-long recording. Parameters for our classifier were informed by knowledge of typical vocal behaviour of sperm whales. Sperm whales were detected predominantly from Dec-Feb, occasionally in Nov, Mar, Apr, and May, but never in the Austral winter or early spring months. Ice cover was found to have a statistically significant negative effect on sperm whale presence. In ice-free months sperm whales were detected more often during daylight hours and were seldom detected at night, and this effect was also statistically significant. Seasonal presence at the three east Antarctic recording sites were in accord with what has been inferred from 20th century whale catches off western Antarctica and from stomach contents of whales caught off South Africa.

PhenomeExpress: a refined network analysis of expression datasets by inclusion of known disease phenotypes.

PubMed

Soul, Jamie; Hardingham, Timothy E; Boot-Handford, Raymond P; Schwartz, Jean-Marc

2015-01-29

We describe a new method, PhenomeExpress, for the analysis of transcriptomic datasets to identify pathogenic disease mechanisms. Our analysis method includes input from both protein-protein interaction and phenotype similarity networks. This introduces valuable information from disease relevant phenotypes, which aids the identification of sub-networks that are significantly enriched in differentially expressed genes and are related to the disease relevant phenotypes. This contrasts with many active sub-network detection methods, which rely solely on protein-protein interaction networks derived from compounded data of many unrelated biological conditions and which are therefore not specific to the context of the experiment. PhenomeExpress thus exploits readily available animal model and human disease phenotype information. It combines this prior evidence of disease phenotypes with the experimentally derived disease data sets to provide a more targeted analysis. Two case studies, in subchondral bone in osteoarthritis and in Pax5 in acute lymphoblastic leukaemia, demonstrate that PhenomeExpress identifies core disease pathways in both mouse and human disease expression datasets derived from different technologies. We also validate the approach by comparison to state-of-the-art active sub-network detection methods, which reveals how it may enhance the detection of molecular phenotypes and provide a more detailed context to those previously identified as possible candidates.

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Detecting periods of eating during free-living by tracking wrist motion.

PubMed

Dong, Yujie; Scisco, Jenna; Wilson, Mike; Muth, Eric; Hoover, Adam

2014-07-01

This paper is motivated by the growing prevalence of obesity, a health problem affecting over 500 million people. Measurements of energy intake are commonly used for the study and treatment of obesity. However, the most widely used tools rely upon self-report and require a considerable manual effort, leading to underreporting of consumption, noncompliance, and discontinued use over the long term. The purpose of this paper is to describe a new method that uses a watch-like configuration of sensors to continuously track wrist motion throughout the day and automatically detect periods of eating. Our method uses the novel idea that meals tend to be preceded and succeeded by the periods of vigorous wrist motion. We describe an algorithm that segments and classifies such periods as eating or noneating activities. We also evaluate our method on a large dataset (43 subjects, 449 total h of data, containing 116 periods of eating) collected during free-living. Our results show an accuracy of 81% for detecting eating at 1-s resolution in comparison to manually marked event logs of periods eating. These results indicate that vigorous wrist motion is a useful indicator for identifying the boundaries of eating activities, and that our method should prove useful in the continued development of body-worn sensor tools for monitoring energy intake.

Methods to measure olfactory behavior in mice

PubMed Central

Zou, Junhui; Wang, Wenbin; Pan, Yung-Wei; Lu, Song; Xia, Zhengui

2015-01-01

Mice rely on the sense of olfaction to detect food sources, recognize social and mating partners, and avoid predators. Many behaviors of mice including learning and memory, social interaction, fear, and anxiety are closely associated with their function of olfaction, and behavior tasks designed to evaluate those brain functions may use odors as cues. Accurate assessment of olfaction is not only essential for the study of olfactory system but also critical for proper interpretation of various mouse behaviors especially learning and memory, emotionality and affect, and sociality. Here we describe a series of behavior experiments that offer multidimensional and quantitative assessments for mouse’s olfactory function, including olfactory habituation, discrimination, odor preference, odor detection sensitivity, and olfactory memory, to both social and nonsocial odors. PMID:25645244

A novel TaqMan® assay for Nosema ceranae quantification in honey bee, based on the protein coding gene Hsp70.

PubMed

Cilia, Giovanni; Cabbri, Riccardo; Maiorana, Giacomo; Cardaio, Ilaria; Dall'Olio, Raffaele; Nanetti, Antonio

2018-04-01

Nosema ceranae is now a widespread honey bee pathogen with high incidence in apiculture. Rapid and reliable detection and quantification methods are a matter of concern for research community, nowadays mainly relying on the use of biomolecular techniques such as PCR, RT-PCR or HRMA. The aim of this technical paper is to provide a new qPCR assay, based on the highly-conserved protein coding gene Hsp70, to detect and quantify the microsporidian Nosema ceranae affecting the western honey bee Apis mellifera. The validation steps to assess efficiency, sensitivity, specificity and robustness of the assay are described also. Copyright © 2018 Elsevier GmbH. All rights reserved.

Probabilistic detection of volcanic ash using a Bayesian approach

PubMed Central

Mackie, Shona; Watson, Matthew

2014-01-01

Airborne volcanic ash can pose a hazard to aviation, agriculture, and both human and animal health. It is therefore important that ash clouds are monitored both day and night, even when they travel far from their source. Infrared satellite data provide perhaps the only means of doing this, and since the hugely expensive ash crisis that followed the 2010 Eyjafjalljökull eruption, much research has been carried out into techniques for discriminating ash in such data and for deriving key properties. Such techniques are generally specific to data from particular sensors, and most approaches result in a binary classification of pixels into “ash” and “ash free” classes with no indication of the classification certainty for individual pixels. Furthermore, almost all operational methods rely on expert-set thresholds to determine what constitutes “ash” and can therefore be criticized for being subjective and dependent on expertise that may not remain with an institution. Very few existing methods exploit available contemporaneous atmospheric data to inform the detection, despite the sensitivity of most techniques to atmospheric parameters. The Bayesian method proposed here does exploit such data and gives a probabilistic, physically based classification. We provide an example of the method's implementation for a scene containing both land and sea observations, and a large area of desert dust (often misidentified as ash by other methods). The technique has already been successfully applied to other detection problems in remote sensing, and this work shows that it will be a useful and effective tool for ash detection. Key Points Presentation of a probabilistic volcanic ash detection scheme Method for calculation of probability density function for ash observations Demonstration of a remote sensing technique for monitoring volcanic ash hazards PMID:25844278

Probabilistic detection of volcanic ash using a Bayesian approach.

PubMed

Mackie, Shona; Watson, Matthew

2014-03-16

Airborne volcanic ash can pose a hazard to aviation, agriculture, and both human and animal health. It is therefore important that ash clouds are monitored both day and night, even when they travel far from their source. Infrared satellite data provide perhaps the only means of doing this, and since the hugely expensive ash crisis that followed the 2010 Eyjafjalljökull eruption, much research has been carried out into techniques for discriminating ash in such data and for deriving key properties. Such techniques are generally specific to data from particular sensors, and most approaches result in a binary classification of pixels into "ash" and "ash free" classes with no indication of the classification certainty for individual pixels. Furthermore, almost all operational methods rely on expert-set thresholds to determine what constitutes "ash" and can therefore be criticized for being subjective and dependent on expertise that may not remain with an institution. Very few existing methods exploit available contemporaneous atmospheric data to inform the detection, despite the sensitivity of most techniques to atmospheric parameters. The Bayesian method proposed here does exploit such data and gives a probabilistic, physically based classification. We provide an example of the method's implementation for a scene containing both land and sea observations, and a large area of desert dust (often misidentified as ash by other methods). The technique has already been successfully applied to other detection problems in remote sensing, and this work shows that it will be a useful and effective tool for ash detection. Presentation of a probabilistic volcanic ash detection schemeMethod for calculation of probability density function for ash observationsDemonstration of a remote sensing technique for monitoring volcanic ash hazards.

Literature Review of the Extraction and Analysis of Trace Contaminants in Food

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

Williams, Audrey Martin; Alcaraz, Armando

2010-06-15

There exists a serious concern that chemical warfare agents (CWA) may be used in a terrorist attack against military or civilian populations. While many precautions have been taken on the military front (e.g. protective clothing, gas masks), such precautions are not suited for the widespread application to civilian populations. Thus, defense of the civilian population, and applicable to the military population, has focused on prevention and early detection. Early detection relies on accurate and sensitive analytical methods to detect and identify CWA in a variety of matrices. Once a CWA is detected, the analytical needs take on a forensic applicationmore » – are there any chemical signatures present in the sample that could indicate its source? These signatures could include byproducts of the reaction, unreacted starting materials, degradation products, or impurities. Therefore, it is important that the analytical method used can accurately identify such signatures, as well as the CWA itself. Contained herein is a review of the open literature describing the detection of CWA in various matrices and the detection of trace toxic chemicals in food. Several relevant reviews have been published in the literature,1-5 including a review of analytical separation techniques for CWA by Hooijschuur et al.1 The current review is not meant to reiterate the published manuscripts; is focused mainly on extraction procedures, as well as the detection of VX and its hydrolysis products, as it is closely related to Russian VX, which is not prevalent in the literature. It is divided by the detection technique used, as such; extraction techniques are included with each detection method.« less

The correct estimate of the probability of false detection of the matched filter in weak-signal detection problems . II. Further results with application to a set of ALMA and ATCA data

NASA Astrophysics Data System (ADS)

Vio, R.; Vergès, C.; Andreani, P.

2017-08-01

The matched filter (MF) is one of the most popular and reliable techniques to the detect signals of known structure and amplitude smaller than the level of the contaminating noise. Under the assumption of stationary Gaussian noise, MF maximizes the probability of detection subject to a constant probability of false detection or false alarm (PFA). This property relies upon a priori knowledge of the position of the searched signals, which is usually not available. Recently, it has been shown that when applied in its standard form, MF may severely underestimate the PFA. As a consequence the statistical significance of features that belong to noise is overestimated and the resulting detections are actually spurious. For this reason, an alternative method of computing the PFA has been proposed that is based on the probability density function (PDF) of the peaks of an isotropic Gaussian random field. In this paper we further develop this method. In particular, we discuss the statistical meaning of the PFA and show that, although useful as a preliminary step in a detection procedure, it is not able to quantify the actual reliability of a specific detection. For this reason, a new quantity is introduced called the specific probability of false alarm (SPFA), which is able to carry out this computation. We show how this method works in targeted simulations and apply it to a few interferometric maps taken with the Atacama Large Millimeter/submillimeter Array (ALMA) and the Australia Telescope Compact Array (ATCA). We select a few potential new point sources and assign an accurate detection reliability to these sources.

Can camera traps monitor Komodo dragons a large ectothermic predator?

PubMed

Ariefiandy, Achmad; Purwandana, Deni; Seno, Aganto; Ciofi, Claudio; Jessop, Tim S

2013-01-01

Camera trapping has greatly enhanced population monitoring of often cryptic and low abundance apex carnivores. Effectiveness of passive infrared camera trapping, and ultimately population monitoring, relies on temperature mediated differences between the animal and its ambient environment to ensure good camera detection. In ectothermic predators such as large varanid lizards, this criterion is presumed less certain. Here we evaluated the effectiveness of camera trapping to potentially monitor the population status of the Komodo dragon (Varanus komodoensis), an apex predator, using site occupancy approaches. We compared site-specific estimates of site occupancy and detection derived using camera traps and cage traps at 181 trapping locations established across six sites on four islands within Komodo National Park, Eastern Indonesia. Detection and site occupancy at each site were estimated using eight competing models that considered site-specific variation in occupancy (ψ)and varied detection probabilities (p) according to detection method, site and survey number using a single season site occupancy modelling approach. The most parsimonious model [ψ (site), p (site survey); ω = 0.74] suggested that site occupancy estimates differed among sites. Detection probability varied as an interaction between site and survey number. Our results indicate that overall camera traps produced similar estimates of detection and site occupancy to cage traps, irrespective of being paired, or unpaired, with cage traps. Whilst one site showed some evidence detection was affected by trapping method detection was too low to produce an accurate occupancy estimate. Overall, as camera trapping is logistically more feasible it may provide, with further validation, an alternative method for evaluating long-term site occupancy patterns in Komodo dragons, and potentially other large reptiles, aiding conservation of this species.

Can Camera Traps Monitor Komodo Dragons a Large Ectothermic Predator?

PubMed Central

Ariefiandy, Achmad; Purwandana, Deni; Seno, Aganto; Ciofi, Claudio; Jessop, Tim S.

2013-01-01

Camera trapping has greatly enhanced population monitoring of often cryptic and low abundance apex carnivores. Effectiveness of passive infrared camera trapping, and ultimately population monitoring, relies on temperature mediated differences between the animal and its ambient environment to ensure good camera detection. In ectothermic predators such as large varanid lizards, this criterion is presumed less certain. Here we evaluated the effectiveness of camera trapping to potentially monitor the population status of the Komodo dragon (Varanus komodoensis), an apex predator, using site occupancy approaches. We compared site-specific estimates of site occupancy and detection derived using camera traps and cage traps at 181 trapping locations established across six sites on four islands within Komodo National Park, Eastern Indonesia. Detection and site occupancy at each site were estimated using eight competing models that considered site-specific variation in occupancy (ψ)and varied detection probabilities (p) according to detection method, site and survey number using a single season site occupancy modelling approach. The most parsimonious model [ψ (site), p (site*survey); ω = 0.74] suggested that site occupancy estimates differed among sites. Detection probability varied as an interaction between site and survey number. Our results indicate that overall camera traps produced similar estimates of detection and site occupancy to cage traps, irrespective of being paired, or unpaired, with cage traps. Whilst one site showed some evidence detection was affected by trapping method detection was too low to produce an accurate occupancy estimate. Overall, as camera trapping is logistically more feasible it may provide, with further validation, an alternative method for evaluating long-term site occupancy patterns in Komodo dragons, and potentially other large reptiles, aiding conservation of this species. PMID:23527027

Sleep spindle and K-complex detection using tunable Q-factor wavelet transform and morphological component analysis

PubMed Central

Lajnef, Tarek; Chaibi, Sahbi; Eichenlaub, Jean-Baptiste; Ruby, Perrine M.; Aguera, Pierre-Emmanuel; Samet, Mounir; Kachouri, Abdennaceur; Jerbi, Karim

2015-01-01

A novel framework for joint detection of sleep spindles and K-complex events, two hallmarks of sleep stage S2, is proposed. Sleep electroencephalography (EEG) signals are split into oscillatory (spindles) and transient (K-complex) components. This decomposition is conveniently achieved by applying morphological component analysis (MCA) to a sparse representation of EEG segments obtained by the recently introduced discrete tunable Q-factor wavelet transform (TQWT). Tuning the Q-factor provides a convenient and elegant tool to naturally decompose the signal into an oscillatory and a transient component. The actual detection step relies on thresholding (i) the transient component to reveal K-complexes and (ii) the time-frequency representation of the oscillatory component to identify sleep spindles. Optimal thresholds are derived from ROC-like curves (sensitivity vs. FDR) on training sets and the performance of the method is assessed on test data sets. We assessed the performance of our method using full-night sleep EEG data we collected from 14 participants. In comparison to visual scoring (Expert 1), the proposed method detected spindles with a sensitivity of 83.18% and false discovery rate (FDR) of 39%, while K-complexes were detected with a sensitivity of 81.57% and an FDR of 29.54%. Similar performances were obtained when using a second expert as benchmark. In addition, when the TQWT and MCA steps were excluded from the pipeline the detection sensitivities dropped down to 70% for spindles and to 76.97% for K-complexes, while the FDR rose up to 43.62 and 49.09%, respectively. Finally, we also evaluated the performance of the proposed method on a set of publicly available sleep EEG recordings. Overall, the results we obtained suggest that the TQWT-MCA method may be a valuable alternative to existing spindle and K-complex detection methods. Paths for improvements and further validations with large-scale standard open-access benchmarking data sets are discussed. PMID:26283943

Cell-free DNA fragment-size distribution analysis for non-invasive prenatal CNV prediction.

PubMed

Arbabi, Aryan; Rampášek, Ladislav; Brudno, Michael

2016-06-01

Non-invasive detection of aneuploidies in a fetal genome through analysis of cell-free DNA circulating in the maternal plasma is becoming a routine clinical test. Such tests, which rely on analyzing the read coverage or the allelic ratios at single-nucleotide polymorphism (SNP) loci, are not sensitive enough for smaller sub-chromosomal abnormalities due to sequencing biases and paucity of SNPs in a genome. We have developed an alternative framework for identifying sub-chromosomal copy number variations in a fetal genome. This framework relies on the size distribution of fragments in a sample, as fetal-origin fragments tend to be smaller than those of maternal origin. By analyzing the local distribution of the cell-free DNA fragment sizes in each region, our method allows for the identification of sub-megabase CNVs, even in the absence of SNP positions. To evaluate the accuracy of our method, we used a plasma sample with the fetal fraction of 13%, down-sampled it to samples with coverage of 10X-40X and simulated samples with CNVs based on it. Our method had a perfect accuracy (both specificity and sensitivity) for detecting 5 Mb CNVs, and after reducing the fetal fraction (to 11%, 9% and 7%), it could correctly identify 98.82-100% of the 5 Mb CNVs and had a true-negative rate of 95.29-99.76%. Our source code is available on GitHub at https://github.com/compbio-UofT/FSDA CONTACT: : brudno@cs.toronto.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Fluorometric determination of the activity of alkaline phosphatase based on the competitive binding of gold nanoparticles and pyrophosphate to CePO4:Tb nanorods.

PubMed

Xu, Ai-Zhen; Zhang, Li; Zeng, Hui-Hui; Liang, Ru-Ping; Qiu, Jian-Ding

2018-05-09

A fluorometric method is described for the determination of the activity of alkaline phosphatase (ALP). It relies on the competition between gold nanoparticles (AuNPs) and pyrophosphate (PPi) for the coordination sites on the surface of CePO 4 :Tb nanorods. The green fluorescence of the CePO 4 :Tb is reduced in the presence of AuNPs due to fluorescence resonance energy transfer (FRET), but can be restored on addition of PPi due to the stronger affinity of PPi to the CePO 4 :Tb. In the presence of ALP, PPi is hydrolyzed to form phosphate which has much weaker affinity for the CePO 4 :Tb. Hence, the AuNPs will reassemble on the CePO 4 :Tb, and fluorescence is reduced. Fluorescence drops linearly in the 0.2 to 100 U·L -1 activity range, and the detection limit is 60 mU·L -1 (at S/N = 3). The method does not require any modification of the surface of the CePO 4 :Tb and is highly sensitive and selective. The inhibition of ALP activity by Na 3 VO 4 was also studied. In our perception, the method may find application in the diagnosis of ALP-related diseases, in screening for inhibitors, and in studies on ALP-related functions in biological systems. Graphical abstract A assay for the detection of alkaline phosphatase is proposed based on the fluorescence resonance energy transfer between CePO 4 :Tb and AuNPs. It relies on the competitive binding of AuNPs and pyrophosphate (PPi) to CePO 4 :Tb and the hydrolysis of PPi by ALP.

Line Transect Surveys Underdetect Terrestrial Mammals: Implications for the Sustainability of Subsistence Hunting

PubMed Central

Levi, Taal; Oliveira, Luiz F. B.; Luzar, Jeffrey B.; Overman, Han; Read, Jane M.

2016-01-01

Conservation of Neotropical game species must take into account the livelihood and food security needs of local human populations. Hunting management decisions should therefore rely on abundance and distribution data that are as representative as possible of true population sizes and dynamics. We simultaneously applied a commonly used encounter-based method and an infrequently used sign-based method to estimate hunted vertebrate abundance in a 48,000-km2 indigenous landscape in southern Guyana. Diurnal direct encounter data collected during three years along 216, four-kilometer -long transects consistently under-detected many diurnal and nocturnal mammal species readily detected through sign. Of 32 species analyzed, 31 were detected by both methods; however, encounters did not detect one and under-detected another 12 of the most heavily hunted species relative to sign, while sign under-detected 12 never or rarely collected species relative to encounters. The six most important game animals in the region, all ungulates, were not encountered at 11–40% of village and control sites or on 29–72% of transects where they were detected by sign. Using the sign methodology, we find that tapirs, one of the terrestrial vertebrates considered most sensitive to overexploitation, are present at many sites where they were never visually detected during distance sampling. We find that this is true for many other species as well. These high rates of under-detection suggest that behavioral changes in hunted populations may affect apparent occurrence and abundance of these populations. Accumulation curves (detection of species on transects) were much steeper for sign for 12 of 16 hunted species than for encounters, but that pattern was reversed for 12 of 16 species unhunted in our area. We conclude that collection of sign data is an efficient and effective method of monitoring hunted vertebrate populations that complements encounter and camera-trapping methods in areas impacted by hunting. Sign surveys may be the most viable method for large-scale, management-oriented studies in remote areas, particularly those focused on community-based wildlife management. PMID:27074025

Deep Learning-Based Data Forgery Detection in Automatic Generation Control

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

Zhang, Fengli; Li, Qinghua

Automatic Generation Control (AGC) is a key control system in the power grid. It is used to calculate the Area Control Error (ACE) based on frequency and tie-line power flow between balancing areas, and then adjust power generation to maintain the power system frequency in an acceptable range. However, attackers might inject malicious frequency or tie-line power flow measurements to mislead AGC to do false generation correction which will harm the power grid operation. Such attacks are hard to be detected since they do not violate physical power system models. In this work, we propose algorithms based on Neural Networkmore » and Fourier Transform to detect data forgery attacks in AGC. Different from the few previous work that rely on accurate load prediction to detect data forgery, our solution only uses the ACE data already available in existing AGC systems. In particular, our solution learns the normal patterns of ACE time series and detects abnormal patterns caused by artificial attacks. Evaluations on the real ACE dataset show that our methods have high detection accuracy.« less

The application of visible wavelength reflectance hyperspectral imaging for the detection and identification of blood stains.

PubMed

Li, Bo; Beveridge, Peter; O'Hare, William T; Islam, Meez

2014-12-01

Current methods of detection and identification of blood stains rely largely on visual examination followed by presumptive tests such as Kastle-Meyer, Leuco-malachite green or luminol. Although these tests are useful, they can produce false positives and can also have a negative impact on subsequent DNA tests. A novel application of visible wavelength reflectance hyperspectral imaging has been used for the detection and positive identification of blood stains in a non contact and non destructive manner on a range of coloured substrates. The identification of blood staining was based on the unique visible absorption spectrum of haemoglobin between 400 and 500 nm. Images illustrating successful discrimination of blood stains from nine red substances are included. It has also been possible to distinguish between blood and approximately 40 other reddish stains. The technique was also successfully used to detect latent blood stains deposited on white filter paper at dilutions of up to 1 in 512 folds and on red tissue at dilutions of up to 1 in 32 folds. Finally, in a blind trial, the method successfully detected and identified a total of 9 blood stains on a red T-shirt. Copyright © 2014 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

Salient object detection based on multi-scale contrast.

PubMed

Wang, Hai; Dai, Lei; Cai, Yingfeng; Sun, Xiaoqiang; Chen, Long

2018-05-01

Due to the development of deep learning networks, a salient object detection based on deep learning networks, which are used to extract the features, has made a great breakthrough compared to the traditional methods. At present, the salient object detection mainly relies on very deep convolutional network, which is used to extract the features. In deep learning networks, an dramatic increase of network depth may cause more training errors instead. In this paper, we use the residual network to increase network depth and to mitigate the errors caused by depth increase simultaneously. Inspired by image simplification, we use color and texture features to obtain simplified image with multiple scales by means of region assimilation on the basis of super-pixels in order to reduce the complexity of images and to improve the accuracy of salient target detection. We refine the feature on pixel level by the multi-scale feature correction method to avoid the feature error when the image is simplified at the above-mentioned region level. The final full connection layer not only integrates features of multi-scale and multi-level but also works as classifier of salient targets. The experimental results show that proposed model achieves better results than other salient object detection models based on original deep learning networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sparsity based target detection for compressive spectral imagery

NASA Astrophysics Data System (ADS)

Boada, David Alberto; Arguello Fuentes, Henry

2016-09-01

Hyperspectral imagery provides significant information about the spectral characteristics of objects and materials present in a scene. It enables object and feature detection, classification, or identification based on the acquired spectral characteristics. However, it relies on sophisticated acquisition and data processing systems able to acquire, process, store, and transmit hundreds or thousands of image bands from a given area of interest which demands enormous computational resources in terms of storage, computationm, and I/O throughputs. Specialized optical architectures have been developed for the compressed acquisition of spectral images using a reduced set of coded measurements contrary to traditional architectures that need a complete set of measurements of the data cube for image acquisition, dealing with the storage and acquisition limitations. Despite this improvement, if any processing is desired, the image has to be reconstructed by an inverse algorithm in order to be processed, which is also an expensive task. In this paper, a sparsity-based algorithm for target detection in compressed spectral images is presented. Specifically, the target detection model adapts a sparsity-based target detector to work in a compressive domain, modifying the sparse representation basis in the compressive sensing problem by means of over-complete training dictionaries and a wavelet basis representation. Simulations show that the presented method can achieve even better detection results than the state of the art methods.

Creating an automated chiller fault detection and diagnostics tool using a data fault library.

PubMed

Bailey, Margaret B; Kreider, Jan F

2003-07-01

Reliable, automated detection and diagnosis of abnormal behavior within vapor compression refrigeration cycle (VCRC) equipment is extremely desirable for equipment owners and operators. The specific type of VCRC equipment studied in this paper is a 70-ton helical rotary, air-cooled chiller. The fault detection and diagnostic (FDD) tool developed as part of this research analyzes chiller operating data and detects faults through recognizing trends or patterns existing within the data. The FDD method incorporates a neural network (NN) classifier to infer the current state given a vector of observables. Therefore the FDD method relies upon the availability of normal and fault empirical data for training purposes and therefore a fault library of empirical data is assembled. This paper presents procedures for conducting sophisticated fault experiments on chillers that simulate air-cooled condenser, refrigerant, and oil related faults. The experimental processes described here are not well documented in literature and therefore will provide the interested reader with a useful guide. In addition, the authors provide evidence, based on both thermodynamics and empirical data analysis, that chiller performance is significantly degraded during fault operation. The chiller's performance degradation is successfully detected and classified by the NN FDD classifier as discussed in the paper's final section.

The non-contact detection and identification of blood stained fingerprints using visible wavelength reflectance hyperspectral imaging: Part 1.

PubMed

Cadd, Samuel; Li, Bo; Beveridge, Peter; O'Hare, William T; Campbell, Andrew; Islam, Meez

2016-05-01

Blood is one of the most commonly encountered types of biological evidence found at scenes of violent crime and one of the most commonly observed fingerprint contaminants. Current visualisation methods rely on presumptive tests or chemical enhancement methods. Although these can successfully visualise ridge detail, they are destructive, do not confirm the presence of blood and can have a negative impact on DNA sampling. A novel application of visible wavelength reflectance hyperspectral imaging (HSI) has been used for the detection and positive identification of blood stained fingerprints in a non-contact and non-destructive manner on white ceramic tiles. The identification of blood was based on the unique visible absorption spectrum of haemoglobin between 400 and 500 nm. HSI has been used to successfully visualise ridge detail in blood stained fingerprints to the ninth depletion. Ridge detail was still detectable with diluted blood to 20-fold dilutions. Latent blood stains were detectable to 15,000-fold dilutions. Ridge detail was detectable for fingerprints up to 6 months old. HSI was also able to conclusively distinguish blood stained fingerprints from fingerprints in six paints and eleven other red/brown media with zero false positives. Copyright © 2016 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

The detectability of cracks using sonic IR

NASA Astrophysics Data System (ADS)

Morbidini, Marco; Cawley, Peter

2009-05-01

This paper proposes a methodology to study the detectability of fatigue cracks in metals using sonic IR (also known as thermosonics). The method relies on the validation of simple finite-element thermal models of the cracks and specimens in which the thermal loads have been defined by means of a priori measurement of the additional damping introduced in the specimens by each crack. This estimate of crack damping is used in conjunction with a local measurement of the vibration strain during ultrasonic excitation to retrieve the power released at the crack; these functions are then input to the thermal model of the specimens to find the resulting temperature rises (sonic IR signals). The method was validated on mild steel beams with two-dimensional cracks obtained in the low-cycle fatigue regime as well as nickel-based superalloy beams with three-dimensional "thumbnail" cracks generated in the high-cycle fatigue regime. The equivalent 40kHz strain necessary to obtain a desired temperature rise was calculated for cracks in the nickel superalloy set, and the detectability of cracks as a function of length in the range of 1-5mm was discussed.

Simulation-driven machine learning: Bearing fault classification

NASA Astrophysics Data System (ADS)

Sobie, Cameron; Freitas, Carina; Nicolai, Mike

2018-01-01

Increasing the accuracy of mechanical fault detection has the potential to improve system safety and economic performance by minimizing scheduled maintenance and the probability of unexpected system failure. Advances in computational performance have enabled the application of machine learning algorithms across numerous applications including condition monitoring and failure detection. Past applications of machine learning to physical failure have relied explicitly on historical data, which limits the feasibility of this approach to in-service components with extended service histories. Furthermore, recorded failure data is often only valid for the specific circumstances and components for which it was collected. This work directly addresses these challenges for roller bearings with race faults by generating training data using information gained from high resolution simulations of roller bearing dynamics, which is used to train machine learning algorithms that are then validated against four experimental datasets. Several different machine learning methodologies are compared starting from well-established statistical feature-based methods to convolutional neural networks, and a novel application of dynamic time warping (DTW) to bearing fault classification is proposed as a robust, parameter free method for race fault detection.

Detection and localisation of protein-protein interactions in Saccharomyces cerevisiae using a split-GFP method.

PubMed

Barnard, Emma; McFerran, Neil V; Trudgett, Alan; Nelson, John; Timson, David J

2008-05-01

An alternative method for monitoring protein-protein interactions in Saccharomyces cerevisiae has been developed. It relies on the ability of two fragments of enhanced green fluorescent protein (EGFP) to reassemble and fluoresce when fused to interacting proteins. Since this fluorescence can be detected in living cells, simultaneous detection and localisation of interacting pairs is possible. DNA sequences encoding N- and C-terminal EGFP fragments flanked by sequences from the genes of interest were transformed into S. cerevisiae JPY5 cells and homologous recombination into the genome verified by PCR. The system was evaluated by testing known interacting proteins: labelling of the phosphofructokinase subunits, Pfk1p and Pfk2p, with N- and C-terminal EGFP fragments, respectively, resulted in green fluorescence in the cytoplasm. The system works in other cellular compartments: labelling of Idh1p and Idh2p (mitochondrial matrix), Sdh3p and Sdh4p (mitochondrial membrane) and Pap2p and Mtr4p (nucleus) all resulted in fluorescence in the appropriate cellular compartment.

Measurement of O-GlcNAcylated endothelial nitric oxide synthase by using 2',5'-ADP-Sepharose pull-down assay.

PubMed

Long, Yang; Yan, Jianghong; Luo, Suxin; Liu, Zhenguo; Xia, Yong

2017-11-15

Endothelial nitric oxide synthase (eNOS) plays central roles in cardiovascular regulation and disease. eNOS function is critically affected by O-linked N-acetylglucosamine (O-GlcNAc) modification. The present method for measuring O-GlcNAcylated eNOS relies on immunoprecipitation. Such method exhibits low detection efficiency and is also costly. We here report a simplified assay by employing the high binding affinity of eNOS with the 2',5'-ADP-Sepharose resins. Together with the O-GlcNAc antibody, this assay readily allows the detection of O-GlcNAcylated eNOS in both cultured endothelial cells and rat vascular tissues. By using this assay, we demonstrate that eNOS O-GlcNAcylation is markedly elevated in the vessels of diabetic rats. Thus, a 2',5'-ADP-Sepharose-based pull-down assay is developed to measure O-GlcNAcylated eNOS. This assay is simple and efficient in detecting O-GlcNAcylated eNOS in cultured cells and animal tissues under both normal and disease conditions. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessment of in vitro killing assays for detecting praziquantel-induced death in Posthodiplostomum minimum metacercariae.

PubMed

Bader, Chris; Jesudoss Chelladurai, Jeba; Starling, David E; Jones, Douglas E; Brewer, Matthew T

2017-10-01

Control of parasitic infections may be achieved by eliminating developmental stages present within intermediate hosts, thereby disrupting the parasite life cycle. For several trematodes relevant to human and veterinary medicine, this involves targeting the metacercarial stage found in fish intermediate hosts. Treatment of fish with praziquantel is one potential approach for targeting the metacercaria stage. To date, studies investigating praziquantel-induced metacercarial death in fish rely on counting parasites and visually assessing morphology or movement. In this study, we investigate quantitative methods for detecting praziquantel-induced death using a Posthodiplostomum minimum model. Our results revealed that propidium iodide staining accurately identified praziquantel-induced death and the level of staining was proportional to the concentration of praziquantel. In contrast, detection of ATP, resazurin metabolism, and trypan blue staining were poor indicators of metacercarial death. The propidium iodide method offers an advantage over simple visualization of parasite movement and could be used to determine EC 50 values relevant for comparison of praziquantel sensitivity or resistance. Copyright © 2017 Elsevier Inc. All rights reserved.

Intraoperative detection of 18F-FDG-avid tissue sites using the increased probe counting efficiency of the K-alpha probe design and variance-based statistical analysis with the three-sigma criteria

PubMed Central

2013-01-01

Background Intraoperative detection of 18F-FDG-avid tissue sites during 18F-FDG-directed surgery can be very challenging when utilizing gamma detection probes that rely on a fixed target-to-background (T/B) ratio (ratiometric threshold) for determination of probe positivity. The purpose of our study was to evaluate the counting efficiency and the success rate of in situ intraoperative detection of 18F-FDG-avid tissue sites (using the three-sigma statistical threshold criteria method and the ratiometric threshold criteria method) for three different gamma detection probe systems. Methods Of 58 patients undergoing 18F-FDG-directed surgery for known or suspected malignancy using gamma detection probes, we identified nine 18F-FDG-avid tissue sites (from amongst seven patients) that were seen on same-day preoperative diagnostic PET/CT imaging, and for which each 18F-FDG-avid tissue site underwent attempted in situ intraoperative detection concurrently using three gamma detection probe systems (K-alpha probe, and two commercially-available PET-probe systems), and then were subsequently surgical excised. Results The mean relative probe counting efficiency ratio was 6.9 (± 4.4, range 2.2–15.4) for the K-alpha probe, as compared to 1.5 (± 0.3, range 1.0–2.1) and 1.0 (± 0, range 1.0–1.0), respectively, for two commercially-available PET-probe systems (P < 0.001). Successful in situ intraoperative detection of 18F-FDG-avid tissue sites was more frequently accomplished with each of the three gamma detection probes tested by using the three-sigma statistical threshold criteria method than by using the ratiometric threshold criteria method, specifically with the three-sigma statistical threshold criteria method being significantly better than the ratiometric threshold criteria method for determining probe positivity for the K-alpha probe (P = 0.05). Conclusions Our results suggest that the improved probe counting efficiency of the K-alpha probe design used in conjunction with the three-sigma statistical threshold criteria method can allow for improved detection of 18F-FDG-avid tissue sites when a low in situ T/B ratio is encountered. PMID:23496877

Comparison of different detection methods for persistent multiple hypothesis tracking in wide area motion imagery

NASA Astrophysics Data System (ADS)

Hartung, Christine; Spraul, Raphael; Schuchert, Tobias

2017-10-01

Wide area motion imagery (WAMI) acquired by an airborne multicamera sensor enables continuous monitoring of large urban areas. Each image can cover regions of several square kilometers and contain thousands of vehicles. Reliable vehicle tracking in this imagery is an important prerequisite for surveillance tasks, but remains challenging due to low frame rate and small object size. Most WAMI tracking approaches rely on moving object detections generated by frame differencing or background subtraction. These detection methods fail when objects slow down or stop. Recent approaches for persistent tracking compensate for missing motion detections by combining a detection-based tracker with a second tracker based on appearance or local context. In order to avoid the additional complexity introduced by combining two trackers, we employ an alternative single tracker framework that is based on multiple hypothesis tracking and recovers missing motion detections with a classifierbased detector. We integrate an appearance-based similarity measure, merge handling, vehicle-collision tests, and clutter handling to adapt the approach to the specific context of WAMI tracking. We apply the tracking framework on a region of interest of the publicly available WPAFB 2009 dataset for quantitative evaluation; a comparison to other persistent WAMI trackers demonstrates state of the art performance of the proposed approach. Furthermore, we analyze in detail the impact of different object detection methods and detector settings on the quality of the output tracking results. For this purpose, we choose four different motion-based detection methods that vary in detection performance and computation time to generate the input detections. As detector parameters can be adjusted to achieve different precision and recall performance, we combine each detection method with different detector settings that yield (1) high precision and low recall, (2) high recall and low precision, and (3) best f-score. Comparing the tracking performance achieved with all generated sets of input detections allows us to quantify the sensitivity of the tracker to different types of detector errors and to derive recommendations for detector and parameter choice.

Automated object-based classification of topography from SRTM data

PubMed Central

Drăguţ, Lucian; Eisank, Clemens

2012-01-01

We introduce an object-based method to automatically classify topography from SRTM data. The new method relies on the concept of decomposing land-surface complexity into more homogeneous domains. An elevation layer is automatically segmented and classified at three scale levels that represent domains of complexity by using self-adaptive, data-driven techniques. For each domain, scales in the data are detected with the help of local variance and segmentation is performed at these appropriate scales. Objects resulting from segmentation are partitioned into sub-domains based on thresholds given by the mean values of elevation and standard deviation of elevation respectively. Results resemble reasonably patterns of existing global and regional classifications, displaying a level of detail close to manually drawn maps. Statistical evaluation indicates that most of classes satisfy the regionalization requirements of maximizing internal homogeneity while minimizing external homogeneity. Most objects have boundaries matching natural discontinuities at regional level. The method is simple and fully automated. The input data consist of only one layer, which does not need any pre-processing. Both segmentation and classification rely on only two parameters: elevation and standard deviation of elevation. The methodology is implemented as a customized process for the eCognition® software, available as online download. The results are embedded in a web application with functionalities of visualization and download. PMID:22485060

Automated object-based classification of topography from SRTM data

NASA Astrophysics Data System (ADS)

Drăguţ, Lucian; Eisank, Clemens

2012-03-01

We introduce an object-based method to automatically classify topography from SRTM data. The new method relies on the concept of decomposing land-surface complexity into more homogeneous domains. An elevation layer is automatically segmented and classified at three scale levels that represent domains of complexity by using self-adaptive, data-driven techniques. For each domain, scales in the data are detected with the help of local variance and segmentation is performed at these appropriate scales. Objects resulting from segmentation are partitioned into sub-domains based on thresholds given by the mean values of elevation and standard deviation of elevation respectively. Results resemble reasonably patterns of existing global and regional classifications, displaying a level of detail close to manually drawn maps. Statistical evaluation indicates that most of classes satisfy the regionalization requirements of maximizing internal homogeneity while minimizing external homogeneity. Most objects have boundaries matching natural discontinuities at regional level. The method is simple and fully automated. The input data consist of only one layer, which does not need any pre-processing. Both segmentation and classification rely on only two parameters: elevation and standard deviation of elevation. The methodology is implemented as a customized process for the eCognition® software, available as online download. The results are embedded in a web application with functionalities of visualization and download.

HyDEn: A Hybrid Steganocryptographic Approach for Data Encryption Using Randomized Error-Correcting DNA Codes

PubMed Central

Regoui, Chaouki; Durand, Guillaume; Belliveau, Luc; Léger, Serge

2013-01-01

This paper presents a novel hybrid DNA encryption (HyDEn) approach that uses randomized assignments of unique error-correcting DNA Hamming code words for single characters in the extended ASCII set. HyDEn relies on custom-built quaternary codes and a private key used in the randomized assignment of code words and the cyclic permutations applied on the encoded message. Along with its ability to detect and correct errors, HyDEn equals or outperforms existing cryptographic methods and represents a promising in silico DNA steganographic approach. PMID:23984392

Current Understanding of the Pathophysiology of Myocardial Fibrosis and Its Quantitative Assessment in Heart Failure

PubMed Central

Liu, Tong; Song, Deli; Dong, Jianzeng; Zhu, Pinghui; Liu, Jie; Liu, Wei; Ma, Xiaohai; Zhao, Lei; Ling, Shukuan

2017-01-01

Myocardial fibrosis is an important part of cardiac remodeling that leads to heart failure and death. Myocardial fibrosis results from increased myofibroblast activity and excessive extracellular matrix deposition. Various cells and molecules are involved in this process, providing targets for potential drug therapies. Currently, the main detection methods of myocardial fibrosis rely on serum markers, cardiac magnetic resonance imaging, and endomyocardial biopsy. This review summarizes our current knowledge regarding the pathophysiology, quantitative assessment, and novel therapeutic strategies of myocardial fibrosis. PMID:28484397

Trinity: Transcriptome Assembly for Genetic and Functional Analysis of Cancer | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The cancer transcriptome is shaped by genetic changes, variation in gene transcription, mRNA processing, editing and stability, and the cancer microbiome. Deciphering this variation and understanding its implications on tumorigenesis requires sophisticated computational analyses. Most RNA-Seq analyses rely on methods that first map short reads to a reference genome, and then compare them to annotated transcripts or assemble them. However, this strategy can be limited when the cancer genome is substantially different than the reference or for detecting sequences from the cancer microbiome.

A Probabilistic Approach to Network Event Formation from Pre-Processed Waveform Data

NASA Astrophysics Data System (ADS)

Kohl, B. C.; Given, J.

2017-12-01

The current state of the art for seismic event detection still largely depends on signal detection at individual sensor stations, including picking accurate arrivals times and correctly identifying phases, and relying on fusion algorithms to associate individual signal detections to form event hypotheses. But increasing computational capability has enabled progress toward the objective of fully utilizing body-wave recordings in an integrated manner to detect events without the necessity of previously recorded ground truth events. In 2011-2012 Leidos (then SAIC) operated a seismic network to monitor activity associated with geothermal field operations in western Nevada. We developed a new association approach for detecting and quantifying events by probabilistically combining pre-processed waveform data to deal with noisy data and clutter at local distance ranges. The ProbDet algorithm maps continuous waveform data into continuous conditional probability traces using a source model (e.g. Brune earthquake or Mueller-Murphy explosion) to map frequency content and an attenuation model to map amplitudes. Event detection and classification is accomplished by combining the conditional probabilities from the entire network using a Bayesian formulation. This approach was successful in producing a high-Pd, low-Pfa automated bulletin for a local network and preliminary tests with regional and teleseismic data show that it has promise for global seismic and nuclear monitoring applications. The approach highlights several features that we believe are essential to achieving low-threshold automated event detection: Minimizes the utilization of individual seismic phase detections - in traditional techniques, errors in signal detection, timing, feature measurement and initial phase ID compound and propagate into errors in event formation, Has a formalized framework that utilizes information from non-detecting stations, Has a formalized framework that utilizes source information, in particular the spectral characteristics of events of interest, Is entirely model-based, i.e. does not rely on a priori's - particularly important for nuclear monitoring, Does not rely on individualized signal detection thresholds - it's the network solution that matters.

Comparison of Threshold Detection Methods for the Generalized Pareto Distribution (GPD): Application to the NOAA-NCDC Daily Rainfall Dataset

NASA Astrophysics Data System (ADS)

Deidda, Roberto; Mamalakis, Antonis; Langousis, Andreas

2015-04-01

One of the most crucial issues in statistical hydrology is the estimation of extreme rainfall from data. To that extent, based on asymptotic arguments from Extreme Excess (EE) theory, several studies have focused on developing new, or improving existing methods to fit a Generalized Pareto Distribution (GPD) model to rainfall excesses above a properly selected threshold u. The latter is generally determined using various approaches that can be grouped into three basic classes: a) non-parametric methods that locate the changing point between extreme and non-extreme regions of the data, b) graphical methods where one studies the dependence of the GPD parameters (or related metrics) to the threshold level u, and c) Goodness of Fit (GoF) metrics that, for a certain level of significance, locate the lowest threshold u that a GPD model is applicable. In this work, we review representative methods for GPD threshold detection, discuss fundamental differences in their theoretical bases, and apply them to daily rainfall records from the NOAA-NCDC open-access database (http://www.ncdc.noaa.gov/oa/climate/ghcn-daily/). We find that non-parametric methods that locate the changing point between extreme and non-extreme regions of the data are generally not reliable, while graphical methods and GoF metrics that rely on limiting arguments for the upper distribution tail lead to unrealistically high thresholds u. The latter is expected, since one checks the validity of the limiting arguments rather than the applicability of a GPD distribution model. Better performance is demonstrated by graphical methods and GoF metrics that rely on GPD properties. Finally, we discuss the effects of data quantization (common in hydrologic applications) on the estimated thresholds. Acknowledgments: The research project is implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund (ESF) and the Greek State.

Water Mapping Using Multispectral Airborne LIDAR Data

NASA Astrophysics Data System (ADS)

Yan, W. Y.; Shaker, A.; LaRocque, P. E.

2018-04-01

This study investigates the use of the world's first multispectral airborne LiDAR sensor, Optech Titan, manufactured by Teledyne Optech to serve the purpose of automatic land-water classification with a particular focus on near shore region and river environment. Although there exist recent studies utilizing airborne LiDAR data for shoreline detection and water surface mapping, the majority of them only perform experimental testing on clipped data subset or rely on data fusion with aerial/satellite image. In addition, most of the existing approaches require manual intervention or existing tidal/datum data for sample collection of training data. To tackle the drawbacks of previous approaches, we propose and develop an automatic data processing workflow for land-water classification using multispectral airborne LiDAR data. Depending on the nature of the study scene, two methods are proposed for automatic training data selection. The first method utilizes the elevation/intensity histogram fitted with Gaussian mixture model (GMM) to preliminarily split the land and water bodies. The second method mainly relies on the use of a newly developed scan line elevation intensity ratio (SLIER) to estimate the water surface data points. Regardless of the training methods being used, feature spaces can be constructed using the multispectral LiDAR intensity, elevation and other features derived from these parameters. The comprehensive workflow was tested with two datasets collected for different near shore region and river environment, where the overall accuracy yielded better than 96 %.

Evidence of VX nerve agent use from contaminated white mustard plants

PubMed Central

Gravett, Matthew R.; Hopkins, Farrha B.; Self, Adam J.; Webb, Andrew J.; Timperley, Christopher M.; Baker, Matthew J.

2014-01-01

The Chemical Weapons Convention prohibits the development, production, acquisition, stockpiling, retention, transfer or use of chemical weapons by Member States. Verification of compliance and investigations into allegations of use require accurate detection of chemical warfare agents (CWAs) and their degradation products. Detection of CWAs such as organophosphorus nerve agents in the environment relies mainly upon the analysis of soil. We now present a method for the detection of the nerve agent VX and its hydrolysis products by gas chromatography and liquid chromatography mass spectrometry of ethanol extracts of contaminated white mustard plants (Sinapis alba) which retained the compounds of interest for up to 45 days. VX is hydrolysed by the plants to ethyl methylphosphonic acid and then to methylphosphonic acid. The utility of white mustard as a nerve agent detector and remediator of nerve agent-polluted sites is discussed. The work described will help deter the employment of VX in conflict. PMID:25104906

Integrating a DNA Strand Displacement Reaction with a Whispering Gallery Mode Sensor for Label-Free Mercury (II) Ion Detection.

PubMed

Wu, Fengchi; Wu, Yuqiang; Niu, Zhongwei; Vollmer, Frank

2016-07-29

Mercury is an extremely toxic chemical pollutant of our environment. It has attracted the world's attention due to its high mobility and the ease with which it accumulates in organisms. Sensitive devices and methods specific for detecting mercury ions are, hence, in great need. Here, we have integrated a DNA strand displacement reaction with a whispering gallery mode (WGM) sensor for demonstrating the detection of Hg(2+) ions. Our approach relies on the displacement of a DNA hairpin structure, which forms after the binding of mercury ions to an aptamer DNA sequence. The strand displacement reaction of the DNA aptamer provides highly specific and quantitative means for determining the mercury ion concentration on a label-free WGM sensor platform. Our approach also shows the possibility for manipulating the kinetics of a strand displacement reaction with specific ionic species.

Integrating a DNA Strand Displacement Reaction with a Whispering Gallery Mode Sensor for Label-Free Mercury (II) Ion Detection

PubMed Central

Wu, Fengchi; Wu, Yuqiang; Niu, Zhongwei; Vollmer, Frank

2016-01-01

Mercury is an extremely toxic chemical pollutant of our environment. It has attracted the world’s attention due to its high mobility and the ease with which it accumulates in organisms. Sensitive devices and methods specific for detecting mercury ions are, hence, in great need. Here, we have integrated a DNA strand displacement reaction with a whispering gallery mode (WGM) sensor for demonstrating the detection of Hg2+ ions. Our approach relies on the displacement of a DNA hairpin structure, which forms after the binding of mercury ions to an aptamer DNA sequence. The strand displacement reaction of the DNA aptamer provides highly specific and quantitative means for determining the mercury ion concentration on a label-free WGM sensor platform. Our approach also shows the possibility for manipulating the kinetics of a strand displacement reaction with specific ionic species. PMID:27483277

Hyperspectral imaging applied to medical diagnoses and food safety

NASA Astrophysics Data System (ADS)

Carrasco, Oscar; Gomez, Richard B.; Chainani, Arun; Roper, William E.

2003-08-01

This paper analyzes the feasibility and performance of HSI systems for medical diagnosis as well as for food safety. Illness prevention and early disease detection are key elements for maintaining good health. Health care practitioners worldwide rely on innovative electronic devices to accurately identify disease. Hyperspectral imaging (HSI) is an emerging technique that may provide a less invasive procedure than conventional diagnostic imaging. By analyzing reflected and fluorescent light applied to the human body, a HSI system serves as a diagnostic tool as well as a method for evaluating the effectiveness of applied therapies. The safe supply and production of food is also of paramount importance to public health illness prevention. Although this paper will focus on imaging and spectroscopy in food inspection procedures -- the detection of contaminated food sources -- to ensure food quality, HSI also shows promise in detecting pesticide levels in food production (agriculture.)

Development and Evaluation of a Blocking Enzyme-Linked Immunosorbent Assay and Virus Neutralization Assay To Detect Antibodies to Viral Hemorrhagic Septicemia Virus

PubMed Central

Wilson, Anna; Goldberg, Tony; Marcquenski, Susan; Olson, Wendy; Goetz, Frederick; Hershberger, Paul; Hart, Lucas

2014-01-01

Viral hemorrhagic septicemia virus (VHSV) is a target of surveillance by many state and federal agencies in the United States. Currently, the detection of VHSV relies on virus isolation, which is lethal to fish and indicates only the current infection status. A serological method is required to ascertain prior exposure. Here, we report two serologic tests for VHSV that are nonlethal, rapid, and species independent, a virus neutralization (VN) assay and a blocking enzyme-linked immunosorbent assay (ELISA). The results show that the VN assay had a specificity of 100% and sensitivity of 42.9%; the anti-nucleocapsid-blocking ELISA detected nonneutralizing VHSV antibodies at a specificity of 88.2% and a sensitivity of 96.4%. The VN assay and ELISA are valuable tools for assessing exposure to VHSV. PMID:24429071

Faster Detection of Poliomyelitis Outbreaks to Support Polio Eradication

PubMed Central

Chenoweth, Paul; Okayasu, Hiro; Donnelly, Christl A.; Aylward, R. Bruce; Grassly, Nicholas C.

2016-01-01

As the global eradication of poliomyelitis approaches the final stages, prompt detection of new outbreaks is critical to enable a fast and effective outbreak response. Surveillance relies on reporting of acute flaccid paralysis (AFP) cases and laboratory confirmation through isolation of poliovirus from stool. However, delayed sample collection and testing can delay outbreak detection. We investigated whether weekly testing for clusters of AFP by location and time, using the Kulldorff scan statistic, could provide an early warning for outbreaks in 20 countries. A mixed-effects regression model was used to predict background rates of nonpolio AFP at the district level. In Tajikistan and Congo, testing for AFP clusters would have resulted in an outbreak warning 39 and 11 days, respectively, before official confirmation of large outbreaks. This method has relatively high specificity and could be integrated into the current polio information system to support rapid outbreak response activities. PMID:26890053

Faster Detection of Poliomyelitis Outbreaks to Support Polio Eradication.

PubMed

Blake, Isobel M; Chenoweth, Paul; Okayasu, Hiro; Donnelly, Christl A; Aylward, R Bruce; Grassly, Nicholas C

2016-03-01

As the global eradication of poliomyelitis approaches the final stages, prompt detection of new outbreaks is critical to enable a fast and effective outbreak response. Surveillance relies on reporting of acute flaccid paralysis (AFP) cases and laboratory confirmation through isolation of poliovirus from stool. However, delayed sample collection and testing can delay outbreak detection. We investigated whether weekly testing for clusters of AFP by location and time, using the Kulldorff scan statistic, could provide an early warning for outbreaks in 20 countries. A mixed-effects regression model was used to predict background rates of nonpolio AFP at the district level. In Tajikistan and Congo, testing for AFP clusters would have resulted in an outbreak warning 39 and 11 days, respectively, before official confirmation of large outbreaks. This method has relatively high specificity and could be integrated into the current polio information system to support rapid outbreak response activities.

Detecting Position Using ARKit

ERIC Educational Resources Information Center

Dilek, Ufuk; Erol, Mustafa

2018-01-01

Developed by using ARKit, a novel app which can be used to detect position in physics experiments was introduced. The ARKit relies on a new technique. The result of the experiment presented in this study was satisfactory, suggesting that the new technique can be employed in position detection experiments/demonstrations that are conducted using…

Pyrosequencing®-Based Identification of Low-Frequency Mutations Enriched Through Enhanced-ice-COLD-PCR.

PubMed

How-Kit, Alexandre; Tost, Jörg

2015-01-01

A number of molecular diagnostic assays have been developed in the last years for mutation detection. Although these methods have become increasingly sensitive, most of them are incompatible with a sequencing-based readout and require prior knowledge of the mutation present in the sample. Consequently, coamplification at low denaturation (COLD)-PCR-based methods have been developed and combine a high analytical sensitivity due to mutation enrichment in the sample with the identification of known or unknown mutations by downstream sequencing experiments. Among these methods, the recently developed Enhanced-ice-COLD-PCR appeared as the most powerful method as it outperformed the other COLD-PCR-based methods in terms of the mutation enrichment and due to the simplicity of the experimental setup of the assay. Indeed, E-ice-COLD-PCR is very versatile as it can be used on all types of PCR platforms and is applicable to different types of samples including fresh frozen, FFPE, and plasma samples. The technique relies on the incorporation of an LNA containing blocker probe in the PCR reaction followed by selective heteroduplex denaturation enabling amplification of the mutant allele while amplification of the wild-type allele is prevented. Combined with Pyrosequencing(®), which is a very quantitative high-resolution sequencing technology, E-ice-COLD-PCR can detect and identify mutations with a limit of detection down to 0.01 %.

Vineyard management in virtual reality: autonomous control of a transformable drone

NASA Astrophysics Data System (ADS)

Griffiths, H.; Shen, H.; Li, N.; Rojas, S.; Perkins, N.; Liu, M.

2017-05-01

Grape vines are susceptible to many diseases. Routine scouting is critically important to keep vineyards in healthy condition. Currently, scouting relies on experienced farm workers to inspect acres of land while arduously filling out reports to document crop health conditions. This process is both labor and time consuming. Using drones to assist farm workers in scouting has great potential to improve the efficiency of vineyard management. Due to the complexity in grape farm disease detection, the drones are normally used to detect suspicious areas to help farm workers to prioritize scouting activities. Operations still rely heavily on humans for further inspection to be certain about the health conditions of the vines. This paper introduces an autonomous transition flight control method for a transformable drone, which is suitable for the future virtual presence of humans in further inspecting suspicious areas. The transformable drone adopts a tilt-rotor mechanism to automatically switch between hover and horizontal flight modes, following commands from virtual reality devices held in the ground control station. The conceptual design and transformation dynamics of the drone will be first discussed, followed by a model predictive control system developed to automatically control the transition flight. Simulation is also provided to show the effectiveness of the proposed control system.

Innovations in bonding to zirconia based ceramics: Part III. Phosphate monomer resin cements.

PubMed

Mirmohammadi, Hesam; Aboushelib, Moustafa N M; Salameh, Ziad; Feilzer, Albert J; Kleverlaan, Cornelis J

2010-08-01

To compare the bond strength values and the ranking order of three phosphate monomer containing resin cements using microtensile (microTBS) and microshear (microSBS) bond strength tests. Zirconia discs (Procera Zirconia) were bonded to resin composite discs (Filtek Z250) using three different cements (Panavia F 2.0, RelyX UniCem, and Multilink). Two bond strength tests were used to determine zirconia resin bond strength; microtensile bond strength test (microTBS) and microshear bond strength test (microSBS). Ten specimens were tested for each group (n=10). Two-way analysis of variance (ANOVA) was used to analyze the data (alpha=0.05). There were statistical significant differences in bond strength values and in the ranking order obtained using the two test methods. microTBS reported significant differences in bond strength values, whereas microSBS failed to detect such effect. Both Multilink and Panavia demonstrated basically cohesive failure in the resin cement while RelyX UniCem demonstrated interfacial failure. Based on the findings of this study, the data obtained using either microTBS or microSBS could not be directly compared. microTBS was more sensitive to material differences compared to microSBS which failed to detect such differences. Copyright 2010 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Microfluidic devices for sample preparation and rapid detection of foodborne pathogens.

PubMed

Kant, Krishna; Shahbazi, Mohammad-Ali; Dave, Vivek Priy; Ngo, Tien Anh; Chidambara, Vinayaka Aaydha; Than, Linh Quyen; Bang, Dang Duong; Wolff, Anders

2018-03-10

Rapid detection of foodborne pathogens at an early stage is imperative for preventing the outbreak of foodborne diseases, known as serious threats to human health. Conventional bacterial culturing methods for foodborne pathogen detection are time consuming, laborious, and with poor pathogen diagnosis competences. This has prompted researchers to call the current status of detection approaches into question and leverage new technologies for superior pathogen sensing outcomes. Novel strategies mainly rely on incorporating all the steps from sample preparation to detection in miniaturized devices for online monitoring of pathogens with high accuracy and sensitivity in a time-saving and cost effective manner. Lab on chip is a blooming area in diagnosis, which exploits different mechanical and biological techniques to detect very low concentrations of pathogens in food samples. This is achieved through streamlining the sample handling and concentrating procedures, which will subsequently reduce human errors and enhance the accuracy of the sensing methods. Integration of sample preparation techniques into these devices can effectively minimize the impact of complex food matrix on pathogen diagnosis and improve the limit of detections. Integration of pathogen capturing bio-receptors on microfluidic devices is a crucial step, which can facilitate recognition abilities in harsh chemical and physical conditions, offering a great commercial benefit to the food-manufacturing sector. This article reviews recent advances in current state-of-the-art of sample preparation and concentration from food matrices with focus on bacterial capturing methods and sensing technologies, along with their advantages and limitations when integrated into microfluidic devices for online rapid detection of pathogens in foods and food production line. Copyright © 2018. Published by Elsevier Inc.

Change detection of medical images using dictionary learning techniques and principal component analysis.

PubMed

Nika, Varvara; Babyn, Paul; Zhu, Hongmei

2014-07-01

Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of magnetic resonance imaging (MRI) scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are being used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. We present an improved version of the EigenBlockCD algorithm, named the EigenBlockCD-2. The EigenBlockCD-2 algorithm performs an initial global registration and identifies the changes between serial MR images of the brain. Blocks of pixels from a baseline scan are used to train local dictionaries to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between [Formula: see text] and [Formula: see text] norms as two possible similarity measures in the improved EigenBlockCD-2 algorithm. We show the advantages of the [Formula: see text] norm over the [Formula: see text] norm both theoretically and numerically. We also demonstrate the performance of the new EigenBlockCD-2 algorithm for detecting changes of MR images and compare our results with those provided in the recent literature. Experimental results with both simulated and real MRI scans show that our improved EigenBlockCD-2 algorithm outperforms the previous methods. It detects clinical changes while ignoring the changes due to the patient's position and other acquisition artifacts.

Enhancing the sensitivity of Dengue virus serotype detection by RT-PCR among infected children in India.

PubMed

Ahamed, Syed Fazil; Vivek, Rosario; Kotabagi, Shalini; Nayak, Kaustuv; Chandele, Anmol; Kaja, Murali-Krishna; Shet, Anita

2017-06-01

Dengue surveillance relies on reverse transcription-polymerase chain reaction (RT-PCR), for confirmation of dengue virus (DENV) serotypes. We compared efficacies of published and modified primer sets targeting envelope (Env) and capsid-premembrane (C-prM) genes for detection of circulating DENV serotypes in southern India. Acute samples from children with clinically-diagnosed dengue were used for RT-PCR testing. All samples were also subjected to dengue serology (NS1 antigen and anti-dengue-IgM/IgG rapid immunochromatographic assay). Nested RT-PCR was performed on viral RNA using three methods targeting 654bp C-prM, 511bp C-prM and 641bp Env regions, respectively. RT-PCR-positive samples were validated by population sequencing. Among 171 children with suspected dengue, 121 were dengue serology-positive and 50 were dengue serology-negative. Among 121 serology-positives, RT-PCR detected 91 (75.2%) by CprM654, 72 (59.5%) by CprM511, and 74 (61.1%) by Env641. Among 50 serology-negatives, 10 (20.0%) were detected by CprM654, 12 (24.0%) by CprM511, and 11 (22.0%) by Env641. Overall detection rate using three methods sequentially was 82.6% (100/121) among serology-positive and 40.0% (20/50) among serology-negative samples; 6.6% (8/120) had co-infection with multiple DENV serotypes. We conclude that detection of acute dengue was enhanced by a modified RT-PCR method targeting the 654bp C-prM region, and further improved by using all three methods sequentially. Copyright © 2017 Elsevier B.V. All rights reserved.

A Method for the Minimization of Competition Bias in Signal Detection from Spontaneous Reporting Databases.

PubMed

Arnaud, Mickael; Salvo, Francesco; Ahmed, Ismaïl; Robinson, Philip; Moore, Nicholas; Bégaud, Bernard; Tubert-Bitter, Pascale; Pariente, Antoine

2016-03-01

The two methods for minimizing competition bias in signal of disproportionate reporting (SDR) detection--masking factor (MF) and masking ratio (MR)--have focused on the strength of disproportionality for identifying competitors and have been tested using competitors at the drug level. The aim of this study was to develop a method that relies on identifying competitors by considering the proportion of reports of adverse events (AEs) that mention the drug class at an adequate level of drug grouping to increase sensitivity (Se) for SDR unmasking, and its comparison with MF and MR. Reports in the French spontaneous reporting database between 2000 and 2005 were selected. Five AEs were considered: myocardial infarction, pancreatitis, aplastic anemia, convulsions, and gastrointestinal bleeding; related reports were retrieved using standardized Medical Dictionary for Regulatory Activities (MedDRA(®)) queries. Potential competitors of AEs were identified using the developed method, i.e. Competition Index (ComIn), as well as MF and MR. All three methods were tested according to Anatomical Therapeutic Chemical (ATC) classification levels 2-5. For each AE, SDR detection was performed, first in the complete database, and second after removing reports mentioning competitors; SDRs only detected after the removal were unmasked. All unmasked SDRs were validated using the Summary of Product Characteristics, and constituted the reference dataset used for computing the performance for SDR unmasking (area under the curve [AUC], Se). Performance of the ComIn was highest when considering competitors at ATC level 3 (AUC: 62 %; Se: 52 %); similar results were obtained with MF and MR. The ComIn could greatly minimize the competition bias in SDR detection. Further study using a larger dataset is needed.

Detection of Ballast Damage by In-Situ Vibration Measurement of Sleepers

NASA Astrophysics Data System (ADS)

Lam, H. F.; Wong, M. T.; Keefe, R. M.

2010-05-01

Ballasted track is one of the most important elements of railway transportation systems worldwide. Owing to its importance in railway safety, many monitoring and evaluation methods have been developed. Current railway track monitoring systems are comprehensive, fast and efficient in testing railway track level and alignment, rail gauge, rail corrugation, etc. However, the monitoring of ballast condition still relies very much on visual inspection and core tests. Although extensive research has been carried out in the development of non-destructive methods for ballast condition evaluation, a commonly accepted and cost-effective method is still in demand. In Hong Kong practice, if abnormal train vibration is reported by the train operator or passengers, permanent way inspectors will locate the problem area by track geometry measurement. It must be pointed out that visual inspection can only identify ballast damage on the track surface, the track geometry deficiencies and rail twists can be detected using a track gauge. Ballast damage under the sleeper loading area and the ballast shoulder, which are the main factors affecting track stability and ride quality, are extremely difficult if not impossible to be detected by visual inspection. Core test is a destructive test, which is expensive, time consuming and may be disruptive to traffic. A fast real-time ballast damage detection method that can be implemented by permanent way inspectors with simple equipment can certainly provide valuable information for engineers in assessing the safety and riding quality of ballasted track systems. The main objective of this paper is to study the feasibility in using the vibration characteristics of sleepers in quantifying the ballast condition under the sleepers, and so as to explore the possibility in developing a handy method for the detection of ballast damage based on the measured vibration of sleepers.

Wavelet-based statistical classification of skin images acquired with reflectance confocal microscopy

PubMed Central

Halimi, Abdelghafour; Batatia, Hadj; Le Digabel, Jimmy; Josse, Gwendal; Tourneret, Jean Yves

2017-01-01

Detecting skin lentigo in reflectance confocal microscopy images is an important and challenging problem. This imaging modality has not yet been widely investigated for this problem and there are a few automatic processing techniques. They are mostly based on machine learning approaches and rely on numerous classical image features that lead to high computational costs given the very large resolution of these images. This paper presents a detection method with very low computational complexity that is able to identify the skin depth at which the lentigo can be detected. The proposed method performs multiresolution decomposition of the image obtained at each skin depth. The distribution of image pixels at a given depth can be approximated accurately by a generalized Gaussian distribution whose parameters depend on the decomposition scale, resulting in a very-low-dimension parameter space. SVM classifiers are then investigated to classify the scale parameter of this distribution allowing real-time detection of lentigo. The method is applied to 45 healthy and lentigo patients from a clinical study, where sensitivity of 81.4% and specificity of 83.3% are achieved. Our results show that lentigo is identifiable at depths between 50μm and 60μm, corresponding to the average location of the the dermoepidermal junction. This result is in agreement with the clinical practices that characterize the lentigo by assessing the disorganization of the dermoepidermal junction. PMID:29296480

A magnetic nanobead-based bioassay provides sensitive detection of single- and biplex bacterial DNA using a portable AC susceptometer.

PubMed

Strömberg, Mattias; Zardán Gómez de la Torre, Teresa; Nilsson, Mats; Svedlindh, Peter; Strømme, Maria

2014-01-01

Bioassays relying on magnetic read-out using probe-tagged magnetic nanobeads are potential platforms for low-cost biodiagnostic devices for pathogen detection. For optimal assay performance it is crucial to apply an easy, efficient and robust bead-probe conjugation protocol. In this paper, sensitive (1.5 pM) singleplex detection of bacterial DNA sequences is demonstrated in a portable AC susceptometer by a magnetic nanobead-based bioassay principle; the volume-amplified magnetic nanobead detection assay (VAM-NDA). Two bead sizes, 100 and 250 nm, are investigated along with a highly efficient, rapid, robust, and stable conjugation chemistry relying on the avidin-biotin interaction for bead-probe attachment. Avidin-biotin conjugation gives easy control of the number of detection probes per bead; thus allowing for systematic investigation of the impact of varying the detection probe surface coverage upon bead immobilization in rolling circle amplified DNA-coils. The existence of an optimal surface coverage is discussed. Biplex VAM-NDA detection is for the first time demonstrated in the susceptometer: Semi-quantitative results are obtained and it is concluded that the concentration of DNA-coils in the incubation volume is of crucial importance for target quantification. The present findings bring the development of commercial biodiagnostic devices relying on the VAM-NDA further towards implementation in point-of-care and outpatient settings. © 2013 The Authors. Biotechnology Journal published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the Creative Commons Attribution-License, which permits use and distribution in any medium, provided the original work is properly cited.

Passive versus active hazard detection and avoidance systems

NASA Astrophysics Data System (ADS)

Neveu, D.; Mercier, G.; Hamel, J.-F.; Simard Bilodeau, V.; Woicke, S.; Alger, M.; Beaudette, D.

2015-06-01

Upcoming planetary exploration missions will require advanced guidance, navigation and control technologies to reach landing sites with high precision and safety. Various technologies are currently in development to meet that goal. Some technologies rely on passive sensors and benefit from the low mass and power of such solutions while others rely on active sensors and benefit from an improved robustness and accuracy. This paper presents two different hazard detection and avoidance (HDA) system design approaches. The first architecture relies only on a camera as the passive HDA sensor while the second relies, in addition, on a Lidar as the active HDA sensor. Both options use in common an innovative hazard map fusion algorithm aiming at identifying the safest landing locations. This paper presents the simulation tools and reports the closed-loop software simulation results obtained using each design option. The paper also reports the Monte Carlo simulation campaign that was used to assess the robustness of each design option. The performance of each design option is compared against each other in terms of performance criteria such as percentage of success, mean distance to nearest hazard, etc. The applicability of each design option to planetary exploration missions is also discussed.

Measurement of the velocity of neutral fragments by the "correlated ion and neutral time of flight" method combined with "velocity-map imaging"

NASA Astrophysics Data System (ADS)

Berthias, F.; Feketeová, L.; Della Negra, R.; Dupasquier, T.; Fillol, R.; Abdoul-Carime, H.; Farizon, B.; Farizon, M.; Märk, T. D.

2017-08-01

In the challenging field of imaging molecular dynamics, a novel method has been developed and implemented that allows the measurement of the velocity of neutral fragments produced in collision induced dissociation experiments on an event-by-event basis. This has been made possible by combining a correlated ion and neutral time of flight method with a velocity map imaging technique. This new method relies on a multiparametric correlated detection of the neutral and charged fragments from collision induced dissociation on one single detector. Its implementation on the DIAM device (Device for irradiation of biomolecular clusters) (Dispositif d'Irradiation d'Agrégats bioMoléculaires) allowed us to measure the velocity distribution of water molecules evaporated from collision induced dissociation of mass- and energy-selected protonated water clusters.

Introducing the Filtered Park's and Filtered Extended Park's Vector Approach to detect broken rotor bars in induction motors independently from the rotor slots number

NASA Astrophysics Data System (ADS)

Gyftakis, Konstantinos N.; Marques Cardoso, Antonio J.; Antonino-Daviu, Jose A.

2017-09-01

The Park's Vector Approach (PVA), together with its variations, has been one of the most widespread diagnostic methods for electrical machines and drives. Regarding the broken rotor bars fault diagnosis in induction motors, the common practice is to rely on the width increase of the Park's Vector (PV) ring and then apply some more sophisticated signal processing methods. It is shown in this paper that this method can be unreliable and is strongly dependent on the magnetic poles and rotor slot numbers. To overcome this constraint, the novel Filtered Park's/Extended Park's Vector Approach (FPVA/FEPVA) is introduced. The investigation is carried out with FEM simulations and experimental testing. The results prove to satisfyingly coincide, whereas the proposed advanced FPVA method is desirably reliable.

Automating Cell Detection and Classification in Human Brain Fluorescent Microscopy Images Using Dictionary Learning and Sparse Coding

PubMed Central

Alegro, Maryana; Theofilas, Panagiotis; Nguy, Austin; Castruita, Patricia A.; Seeley, William; Heinsen, Helmut; Ushizima, Daniela M.

2017-01-01

Background Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. New method Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. Results Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. Comparison with existing methods We compared our results to four open-access IF-based cell-counting tools available in the literature. Our method showed improved accuracy for all data samples. Conclusion The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks. PMID:28267565

Estimation of the sensitivity of various environmental sampling methods for detection of Salmonella in duck flocks.

PubMed

Arnold, Mark E; Mueller-Doblies, Doris; Gosling, Rebecca J; Martelli, Francesca; Davies, Robert H

2015-01-01

Reports of Salmonella in ducks in the UK currently rely upon voluntary submissions from the industry, and as there is no harmonized statutory monitoring and control programme, it is difficult to compare data from different years in order to evaluate any trends in Salmonella prevalence in relation to sampling methodology. Therefore, the aim of this project was to assess the sensitivity of a selection of environmental sampling methods, including the sampling of faeces, dust and water troughs or bowls for the detection of Salmonella in duck flocks, and a range of sampling methods were applied to 67 duck flocks. Bayesian methods in the absence of a gold standard were used to provide estimates of the sensitivity of each of the sampling methods relative to the within-flock prevalence. There was a large influence of the within-flock prevalence on the sensitivity of all sample types, with sensitivity reducing as the within-flock prevalence reduced. Boot swabs (individual and pool of four), swabs of faecally contaminated areas and whole house hand-held fabric swabs showed the overall highest sensitivity for low-prevalence flocks and are recommended for use to detect Salmonella in duck flocks. The sample type with the highest proportion positive was a pool of four hair nets used as boot swabs, but this was not the most sensitive sample for low-prevalence flocks. All the environmental sampling types (faeces swabs, litter pinches, drag swabs, water trough samples and dust) had higher sensitivity than individual faeces sampling. None of the methods consistently identified all the positive flocks, and at least 10 samples would be required for even the most sensitive method (pool of four boot swabs) to detect a 5% prevalence. The sampling of dust had a low sensitivity and is not recommended for ducks.

Light-Actuated Micromechanical Relays for Zero-Power Infrared Detection

DTIC Science & Technology

2017-03-01

Light-Actuated Micromechanical Relays for Zero-Power Infrared Detection Zhenyun Qian, Sungho Kang, Vageeswar Rajaram, Cristian Cassella, Nicol E...near-zero power infrared (IR) detection . Differently from any existing switching element, the proposed LMR relies on a plasmonically-enhanced...chip enabling the monolithic fabrication of multiple LMRs connected together to form a logic topology suitable for the detection of specific

Classification of Aerial Photogrammetric 3d Point Clouds

NASA Astrophysics Data System (ADS)

Becker, C.; Häni, N.; Rosinskaya, E.; d'Angelo, E.; Strecha, C.

2017-05-01

We present a powerful method to extract per-point semantic class labels from aerial photogrammetry data. Labelling this kind of data is important for tasks such as environmental modelling, object classification and scene understanding. Unlike previous point cloud classification methods that rely exclusively on geometric features, we show that incorporating color information yields a significant increase in accuracy in detecting semantic classes. We test our classification method on three real-world photogrammetry datasets that were generated with Pix4Dmapper Pro, and with varying point densities. We show that off-the-shelf machine learning techniques coupled with our new features allow us to train highly accurate classifiers that generalize well to unseen data, processing point clouds containing 10 million points in less than 3 minutes on a desktop computer.

Transfer of non-Gaussian quantum states of mechanical oscillator to light

NASA Astrophysics Data System (ADS)

Filip, Radim; Rakhubovsky, Andrey A.

2015-11-01

Non-Gaussian quantum states are key resources for quantum optics with continuous-variable oscillators. The non-Gaussian states can be deterministically prepared by a continuous evolution of the mechanical oscillator isolated in a nonlinear potential. We propose feasible and deterministic transfer of non-Gaussian quantum states of mechanical oscillators to a traveling light beam, using purely all-optical methods. The method relies on only basic feasible and high-quality elements of quantum optics: squeezed states of light, linear optics, homodyne detection, and electro-optical feedforward control of light. By this method, a wide range of novel non-Gaussian states of light can be produced in the future from the mechanical states of levitating particles in optical tweezers, including states necessary for the implementation of an important cubic phase gate.

GI-SVM: A sensitive method for predicting genomic islands based on unannotated sequence of a single genome.

PubMed

Lu, Bingxin; Leong, Hon Wai

2016-02-01

Genomic islands (GIs) are clusters of functionally related genes acquired by lateral genetic transfer (LGT), and they are present in many bacterial genomes. GIs are extremely important for bacterial research, because they not only promote genome evolution but also contain genes that enhance adaption and enable antibiotic resistance. Many methods have been proposed to predict GI. But most of them rely on either annotations or comparisons with other closely related genomes. Hence these methods cannot be easily applied to new genomes. As the number of newly sequenced bacterial genomes rapidly increases, there is a need for methods to detect GI based solely on sequences of a single genome. In this paper, we propose a novel method, GI-SVM, to predict GIs given only the unannotated genome sequence. GI-SVM is based on one-class support vector machine (SVM), utilizing composition bias in terms of k-mer content. From our evaluations on three real genomes, GI-SVM can achieve higher recall compared with current methods, without much loss of precision. Besides, GI-SVM allows flexible parameter tuning to get optimal results for each genome. In short, GI-SVM provides a more sensitive method for researchers interested in a first-pass detection of GI in newly sequenced genomes.

Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding.

PubMed

Alegro, Maryana; Theofilas, Panagiotis; Nguy, Austin; Castruita, Patricia A; Seeley, William; Heinsen, Helmut; Ushizima, Daniela M; Grinberg, Lea T

2017-04-15

Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. We compared our results to four open-access IF-based cell-counting tools available in the literature. Our method showed improved accuracy for all data samples. The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks. Copyright © 2017 Elsevier B.V. All rights reserved.

Mouse V1 population correlates of visual detection rely on heterogeneity within neuronal response patterns

PubMed Central

Montijn, Jorrit S; Goltstein, Pieter M; Pennartz, Cyriel MA

2015-01-01

Previous studies have demonstrated the importance of the primary sensory cortex for the detection, discrimination, and awareness of visual stimuli, but it is unknown how neuronal populations in this area process detected and undetected stimuli differently. Critical differences may reside in the mean strength of responses to visual stimuli, as reflected in bulk signals detectable in functional magnetic resonance imaging, electro-encephalogram, or magnetoencephalography studies, or may be more subtly composed of differentiated activity of individual sensory neurons. Quantifying single-cell Ca2+ responses to visual stimuli recorded with in vivo two-photon imaging, we found that visual detection correlates more strongly with population response heterogeneity rather than overall response strength. Moreover, neuronal populations showed consistencies in activation patterns across temporally spaced trials in association with hit responses, but not during nondetections. Contrary to models relying on temporally stable networks or bulk signaling, these results suggest that detection depends on transient differentiation in neuronal activity within cortical populations. DOI: http://dx.doi.org/10.7554/eLife.10163.001 PMID:26646184

Application of graph-based semi-supervised learning for development of cyber COP and network intrusion detection

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Colonna-Romano, John; Eslami, Mohammed

2017-05-01

The United States increasingly relies on cyber-physical systems to conduct military and commercial operations. Attacks on these systems have increased dramatically around the globe. The attackers constantly change their methods, making state-of-the-art commercial and military intrusion detection systems ineffective. In this paper, we present a model to identify functional behavior of network devices from netflow traces. Our model includes two innovations. First, we define novel features for a host IP using detection of application graph patterns in IP's host graph constructed from 5-min aggregated packet flows. Second, we present the first application, to the best of our knowledge, of Graph Semi-Supervised Learning (GSSL) to the space of IP behavior classification. Using a cyber-attack dataset collected from NetFlow packet traces, we show that GSSL trained with only 20% of the data achieves higher attack detection rates than Support Vector Machines (SVM) and Naïve Bayes (NB) classifiers trained with 80% of data points. We also show how to improve detection quality by filtering out web browsing data, and conclude with discussion of future research directions.

Classification with an edge: Improving semantic image segmentation with boundary detection

NASA Astrophysics Data System (ADS)

Marmanis, D.; Schindler, K.; Wegner, J. D.; Galliani, S.; Datcu, M.; Stilla, U.

2018-01-01

We present an end-to-end trainable deep convolutional neural network (DCNN) for semantic segmentation with built-in awareness of semantically meaningful boundaries. Semantic segmentation is a fundamental remote sensing task, and most state-of-the-art methods rely on DCNNs as their workhorse. A major reason for their success is that deep networks learn to accumulate contextual information over very large receptive fields. However, this success comes at a cost, since the associated loss of effective spatial resolution washes out high-frequency details and leads to blurry object boundaries. Here, we propose to counter this effect by combining semantic segmentation with semantically informed edge detection, thus making class boundaries explicit in the model. First, we construct a comparatively simple, memory-efficient model by adding boundary detection to the SEGNET encoder-decoder architecture. Second, we also include boundary detection in FCN-type models and set up a high-end classifier ensemble. We show that boundary detection significantly improves semantic segmentation with CNNs in an end-to-end training scheme. Our best model achieves >90% overall accuracy on the ISPRS Vaihingen benchmark.

Decision support methods for the detection of adverse events in post-marketing data.

PubMed

Hauben, M; Bate, A

2009-04-01

Spontaneous reporting is a crucial component of post-marketing drug safety surveillance despite its significant limitations. The size and complexity of some spontaneous reporting system databases represent a challenge for drug safety professionals who traditionally have relied heavily on the scientific and clinical acumen of the prepared mind. Computer algorithms that calculate statistical measures of reporting frequency for huge numbers of drug-event combinations are increasingly used to support pharamcovigilance analysts screening large spontaneous reporting system databases. After an overview of pharmacovigilance and spontaneous reporting systems, we discuss the theory and application of contemporary computer algorithms in regular use, those under development, and the practical considerations involved in the implementation of computer algorithms within a comprehensive and holistic drug safety signal detection program.

Witnessing entanglement without entanglement witness operators.

PubMed

Pezzè, Luca; Li, Yan; Li, Weidong; Smerzi, Augusto

2016-10-11

Quantum mechanics predicts the existence of correlations between composite systems that, although puzzling to our physical intuition, enable technologies not accessible in a classical world. Notwithstanding, there is still no efficient general method to theoretically quantify and experimentally detect entanglement of many qubits. Here we propose to detect entanglement by measuring the statistical response of a quantum system to an arbitrary nonlocal parametric evolution. We witness entanglement without relying on the tomographic reconstruction of the quantum state, or the realization of witness operators. The protocol requires two collective settings for any number of parties and is robust against noise and decoherence occurring after the implementation of the parametric transformation. To illustrate its user friendliness we demonstrate multipartite entanglement in different experiments with ions and photons by analyzing published data on fidelity visibilities and variances of collective observables.

To cut or not to cut? Assessing the modular structure of brain networks.

PubMed

Chang, Yu-Teng; Pantazis, Dimitrios; Leahy, Richard M

2014-05-01

A wealth of methods has been developed to identify natural divisions of brain networks into groups or modules, with one of the most prominent being modularity. Compared with the popularity of methods to detect community structure, only a few methods exist to statistically control for spurious modules, relying almost exclusively on resampling techniques. It is well known that even random networks can exhibit high modularity because of incidental concentration of edges, even though they have no underlying organizational structure. Consequently, interpretation of community structure is confounded by the lack of principled and computationally tractable approaches to statistically control for spurious modules. In this paper we show that the modularity of random networks follows a transformed version of the Tracy-Widom distribution, providing for the first time a link between module detection and random matrix theory. We compute parametric formulas for the distribution of modularity for random networks as a function of network size and edge variance, and show that we can efficiently control for false positives in brain and other real-world networks. Copyright © 2014 Elsevier Inc. All rights reserved.

Multilevel depth and image fusion for human activity detection.

PubMed

Ni, Bingbing; Pei, Yong; Moulin, Pierre; Yan, Shuicheng

2013-10-01

Recognizing complex human activities usually requires the detection and modeling of individual visual features and the interactions between them. Current methods only rely on the visual features extracted from 2-D images, and therefore often lead to unreliable salient visual feature detection and inaccurate modeling of the interaction context between individual features. In this paper, we show that these problems can be addressed by combining data from a conventional camera and a depth sensor (e.g., Microsoft Kinect). We propose a novel complex activity recognition and localization framework that effectively fuses information from both grayscale and depth image channels at multiple levels of the video processing pipeline. In the individual visual feature detection level, depth-based filters are applied to the detected human/object rectangles to remove false detections. In the next level of interaction modeling, 3-D spatial and temporal contexts among human subjects or objects are extracted by integrating information from both grayscale and depth images. Depth information is also utilized to distinguish different types of indoor scenes. Finally, a latent structural model is developed to integrate the information from multiple levels of video processing for an activity detection. Extensive experiments on two activity recognition benchmarks (one with depth information) and a challenging grayscale + depth human activity database that contains complex interactions between human-human, human-object, and human-surroundings demonstrate the effectiveness of the proposed multilevel grayscale + depth fusion scheme. Higher recognition and localization accuracies are obtained relative to the previous methods.

Solid state tritium detector for biomedical applications

NASA Astrophysics Data System (ADS)

Gordon, J. S.; Farrell, R.; Daley, K.; Oakes, C. E.

1994-08-01

Radioactive labeling of proteins is a very important technique used in biomedical research to identify, isolate, and investigate the expression and properties of proteins in biological systems. In such procedures, the preferred radiolabel is often tritium. Presently, binding assays involving tritium are carried out using inconvenient and expensive techniques which rely on the use of scintillation fluid counting systems. This traditional method involves both time-consuming laboratory protocols and the generation of substantial quantities of radioactive and chemical waste. We have developed a novel technology to measure the tritium content of biological specimens that does not rely on scintillation fluids. The tritiated samples can be positioned directly under a large area, monolithic array of specially prepared avalanche photodiodes (APDs) which record the tritium activity distribution at each point within the field of view of the array. The 1 mm(sup 2) sensing elements exhibit an intrinsic tritium beta detection efficiency of 27% with high gain uniformity and very low cross talk.

Utilizing a Key Aptamer Structure-Switching Mechanism for the Ultrahigh Frequency Detection of Cocaine.

PubMed

Neves, Miguel A D; Blaszykowski, Christophe; Thompson, Michael

2016-03-15

Aptasensing of small molecules remains a challenge as detection often requires the use of labels or signal amplification methodologies, resulting in both difficult-to-prepare sensor platforms and multistep, complex assays. Furthermore, many aptasensors rely on the binding mechanism or structural changes associated with target capture by the aptameric probe, resulting in a detection scheme customized to each aptamer. It is in this context that we report herein a sensitive cocaine aptasensor that offers both real-time and label-free measurement capabilities. Detection relies on the electromagnetic piezoelectric acoustic sensor (EMPAS) platform. The sensing interface consists of a S-(11-trichlorosilyl-undecanyl)benzenethiosulfonate (BTS) adlayer-coated quartz disc onto which a structure-switching cocaine aptamer (MN6) is immobilized, completing the preparation of the MN6 cocaine aptasensor (M6CA). The EMPAS system has recently been employed as the foundation of a cocaine aptasensor based on a structurally rigid cocaine aptamer variant (MN4), an aptasensor referred to by analogy as M4CA. M6CA represents a significant increase in terms of analytical performance, compared to not only M4CA but also other cocaine aptamer-based sensors that do not rely on signal amplification, producing an apparent K(d) of 27 ± 6 μM and a 0.3 μM detection limit. Remarkably, the latter is in the range of that achieved by cocaine aptasensors relying on signal amplification. Furthermore, M6CA proved to be capable not only of regaining its cocaine-binding ability via simple buffer flow over the sensing interface (i.e., without the necessity to implement an additional regeneration step, such as in the case of M4CA), but also of detecting cocaine in a multicomponent matrix possessing potentially assay-interfering species. Finally, through observation of the distinct shape of its response profiles to cocaine injection, demonstration was made that the EMPAS system in practice offers the possibility to distinguish between the binding mechanisms of structure-switching (MN6) vs rigid (MN4) aptameric probes, an ability that could allow the EMPAS to provide a more universal aptasensing platform than what is ordinarily observed in the literature.

Applied Genomics: Data Mining Reveals Species-Specific Malaria Diagnostic Targets More Sensitive than 18S rRNA▿†‡

PubMed Central

Demas, Allison; Oberstaller, Jenna; DeBarry, Jeremy; Lucchi, Naomi W.; Srinivasamoorthy, Ganesh; Sumari, Deborah; Kabanywanyi, Abdunoor M.; Villegas, Leopoldo; Escalante, Ananias A.; Kachur, S. Patrick; Barnwell, John W.; Peterson, David S.; Udhayakumar, Venkatachalam; Kissinger, Jessica C.

2011-01-01

Accurate and rapid diagnosis of malaria infections is crucial for implementing species-appropriate treatment and saving lives. Molecular diagnostic tools are the most accurate and sensitive method of detecting Plasmodium, differentiating between Plasmodium species, and detecting subclinical infections. Despite available whole-genome sequence data for Plasmodium falciparum and P. vivax, the majority of PCR-based methods still rely on the 18S rRNA gene targets. Historically, this gene has served as the best target for diagnostic assays. However, it is limited in its ability to detect mixed infections in multiplex assay platforms without the use of nested PCR. New diagnostic targets are needed. Ideal targets will be species specific, highly sensitive, and amenable to both single-step and multiplex PCRs. We have mined the genomes of P. falciparum and P. vivax to identify species-specific, repetitive sequences that serve as new PCR targets for the detection of malaria. We show that these targets (Pvr47 and Pfr364) exist in 14 to 41 copies and are more sensitive than 18S rRNA when utilized in a single-step PCR. Parasites are routinely detected at levels of 1 to 10 parasites/μl. The reaction can be multiplexed to detect both species in a single reaction. We have examined 7 P. falciparum strains and 91 P. falciparum clinical isolates from Tanzania and 10 P. vivax strains and 96 P. vivax clinical isolates from Venezuela, and we have verified a sensitivity and specificity of ∼100% for both targets compared with a nested 18S rRNA approach. We show that bioinformatics approaches can be successfully applied to identify novel diagnostic targets and improve molecular methods for pathogen detection. These novel targets provide a powerful alternative molecular diagnostic method for the detection of P. falciparum and P. vivax in conventional or multiplex PCR platforms. PMID:21525225

Determining dark matter properties with a XENONnT/LZ signal and LHC Run 3 monojet searches

NASA Astrophysics Data System (ADS)

Baum, Sebastian; Catena, Riccardo; Conrad, Jan; Freese, Katherine; Krauss, Martin B.

2018-04-01

We develop a method to forecast the outcome of the LHC Run 3 based on the hypothetical detection of O (100 ) signal events at XENONnT. Our method relies on a systematic classification of renormalizable single-mediator models for dark matter-quark interactions and is valid for dark matter candidates of spin less than or equal to one. Applying our method to simulated data, we find that at the end of the LHC Run 3 only two mutually exclusive scenarios would be compatible with the detection of O (100 ) signal events at XENONnT. In the first scenario, the energy distribution of the signal events is featureless, as for canonical spin-independent interactions. In this case, if a monojet signal is detected at the LHC, dark matter must have spin 1 /2 and interact with nucleons through a unique velocity-dependent operator. If a monojet signal is not detected, dark matter interacts with nucleons through canonical spin-independent interactions. In a second scenario, the spectral distribution of the signal events exhibits a bump at nonzero recoil energies. In this second case, a monojet signal can be detected at the LHC Run 3; dark matter must have spin 1 /2 and interact with nucleons through a unique momentum-dependent operator. We therefore conclude that the observation of O (100 ) signal events at XENONnT combined with the detection, or the lack of detection, of a monojet signal at the LHC Run 3 would significantly narrow the range of possible dark matter-nucleon interactions. As we argued above, it can also provide key information on the dark matter particle spin.

Enhancement in sample collection for the detection of MDMA using a novel planar SPME (PSPME) device coupled to ion mobility spectrometry (IMS).

PubMed

Gura, Sigalit; Guerra-Diaz, Patricia; Lai, Hanh; Almirall, José R

2009-07-01

Trace detection of illicit drugs challenges the scientific community to develop improved sensitivity and selectivity in sampling and detection techniques. Ion mobility spectrometry (IMS) is one of the prominent trace detectors for illicit drugs and explosives, mostly due to its portability, high sensitivity and fast analysis. Current sampling methods for IMS rely on wiping suspected surfaces or withdrawing air through filters to collect particulates. These methods depend greatly on the particulates being bound onto surfaces or having sufficient vapour pressure to be airborne. Many of these compounds are not readily available in the headspace due to their low vapour pressure. This research presents a novel SPME device for enhanced air sampling and shows the use of optimized IMS by genetic algorithms to target volatile markers and/or odour signatures of illicit substances. The sampling method was based on unique static samplers, planar substrates coated with sol-gel polydimethyl siloxane (PDMS) nanoparticles, also known as planar solid-phase microextraction (PSPME). Due to its surface chemistry, high surface area and capacity, PSPME provides significant increases in sensitivity over conventional fibre SPME. The results show a 50-400 times increase in the detection capacity for piperonal, the odour signature of 3,4-methylenedioxymethamphetamine (MDMA). The PSPME-IMS technique was able to detect 600 ng of piperonal in a 30 s extraction from a quart-sized can containing 5 MDMA tablets, while detection using fibre SPME-IMS was not attainable. In a blind study of six cases suspected to contain varying amounts of MDMA in the tablets, PSPME-IMS successfully detected five positive cases and also produced no false positives or false negatives. One positive case had minimal amounts of MDMA resulting in a false negative response for fibre SPME-IMS.

Agreement for HPV genotyping detection between self-collected specimens on a FTA cartridge and clinician-collected specimens

PubMed Central

Guan, YaoYao; Gravitt, Patti E.; Howard, Roslyn; Eby, Yolanda J.; Wang, Shaoming; Li, Belinda; Feng, Changyan; Qiao, You-Lin; Castle, Philip E.

2016-01-01

The current method of transporting self-collected cervicovaginal specimen for HPV DNA testing relies on liquid based medium, which is challenging and expensive to transport. A novel, dry storage and transportation device, Whatman indicating FTA™ Elute Cartridge, avoids some of the pitfalls of liquid-based medium. This method has been shown to be comparable to liquid-based collection medium, but relative performance of self-collected (SC) and clinician-collected (CC) samples onto FTA cards has not been reported. The objective of this study is to compare the analytic performance of self- and clinician-collected samples onto FTA cartridges for the detection of carcinogenic HPV using Linear Array. There was a 91% agreement, 69% positive agreement, and kappa of 0.75 between the clinician-collected and self-collected specimens for detection of any carcinogenic HPV genotype. When the HPV results were categorized hierarchically according to cervical cancer risk, there was no difference in the distribution of the HPV results for the clinician- and self-collected specimens (p = 0.7). This study concludes that FTA elute cartridge is a promising method of specimen transport for cervical cancer screening programs considering using self-collected specimen and HPV testing. Larger studies with clinical endpoints are now needed to assess the clinical performance. PMID:23370404

What do results from coordinate-based meta-analyses tell us?

PubMed

Albajes-Eizagirre, Anton; Radua, Joaquim

2018-08-01

Coordinate-based meta-analyses (CBMA) methods, such as Activation Likelihood Estimation (ALE) and Seed-based d Mapping (SDM), have become an invaluable tool for summarizing the findings of voxel-based neuroimaging studies. However, the progressive sophistication of these methods may have concealed two particularities of their statistical tests. Common univariate voxelwise tests (such as the t/z-tests used in SPM and FSL) detect voxels that activate, or voxels that show differences between groups. Conversely, the tests conducted in CBMA test for "spatial convergence" of findings, i.e., they detect regions where studies report "more peaks than in most regions", regions that activate "more than most regions do", or regions that show "larger differences between groups than most regions do". The first particularity is that these tests rely on two spatial assumptions (voxels are independent and have the same probability to have a "false" peak), whose violation may make their results either conservative or liberal, though fortunately current versions of ALE, SDM and some other methods consider these assumptions. The second particularity is that the use of these tests involves an important paradox: the statistical power to detect a given effect is higher if there are no other effects in the brain, whereas lower in presence of multiple effects. Copyright © 2018 Elsevier Inc. All rights reserved.

A Microbiological Revolution Meets an Ancient Disease: Improving the Management of Tuberculosis with Genomics

PubMed Central

Wlodarska, Marta; Johnston, James C.; Gardy, Jennifer L.

2015-01-01

SUMMARY Tuberculosis (TB) is an ancient disease with an enormous global impact. Despite declining global incidence, the diagnosis, phenotyping, and epidemiological investigation of TB require significant clinical microbiology laboratory resources. Current methods for the detection and characterization of Mycobacterium tuberculosis consist of a series of laboratory tests varying in speed and performance, each of which yields incremental information about the disease. Since the sequencing of the first M. tuberculosis genome in 1998, genomic tools have aided in the diagnosis, treatment, and control of TB. Here we summarize genomics-based methods that are positioned to be introduced in the modern clinical TB laboratory, and we highlight how recent advances in genomics will improve the detection of antibiotic resistance-conferring mutations and the understanding of M. tuberculosis transmission dynamics and epidemiology. We imagine the future TB clinic as one that relies heavily on genomic interrogation of the M. tuberculosis isolate, allowing for more rapid diagnosis of TB and real-time monitoring of outbreak emergence. PMID:25810419

Convolutional networks for vehicle track segmentation

NASA Astrophysics Data System (ADS)

Quach, Tu-Thach

2017-10-01

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple and fast models to label track pixels. These models, however, are unable to capture natural track features, such as continuity and parallelism. More powerful but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3×3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate in low power and have limited training data. As a result, we aim for small and efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our six-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.

Detection of Hand-to-Mouth Gestures Using a RF Operated Proximity Sensor for Monitoring Cigarette Smoking.

PubMed

Lopez-Meyer, Paulo; Patil, Yogendra; Tiffany, Tiffany; Sazonov, Edward

2013-01-01

Common methods for monitoring of cigarette smoking, such as portable puff-topography instruments or self-report questionnaires, tend to be biased due to conscious or unconscious underreporting. Additionally, these methods may change the natural smoking behavior of individuals. Our long term objective is the development of a wearable non-invasive monitoring system (Personal Automatic Cigarette Tracker - PACT) to reliably monitor cigarette smoking behavior under free living conditions. PACT monitors smoking by observing characteristic breathing patterns of smoke inhalations that follow a cigarette-to-mouth hand gesture. As envisioned, PACT does not rely on self-report or require any conscious effort from the user. A major element of the PACT is a proximity sensor that detects typical cigarette-to-mouth gesture during cigarette smoking. This study describes the design and validation of a prototype RF proximity sensor that captures hand-to-mouth gestures with a high sensitivity (0.90), and a methodology that can reject up to 68% of artifacts gestures originating from activities other than cigarette smoking.

Congo red staining on 1 micron de-plasticized sections for detection of lesions in Alzheimer's disease and related disorders.

PubMed

Snow, A D; Mar, H; Nochlin, D; Wight, T N

1989-01-01

Neuritic plaques (NPs), neurofibrillary tangles (NFTs) and congophilic angiopathy (CA), the three characteristic lesions in Alzheimer's disease, are easily detected in paraffin sections using light microscopy and specific staining methods including Congo red and Thioflavin S. Identification of these lesions in plastic thick sections (1 micron) is more tedious and relies essentially on morphological criteria. This causes investigators to subsequently analyze large numbers of thin sections under the electron microscope. Since many researchers use electron microscopy for various aspects of Alzheimer's disease and related research, it would be advantageous to have a rapid method enabling the investigator to quickly and reliably identify in thick sections the characteristic NPs, NFTs and/or CA, which can then be used for further analysis at the ultrastructural level. In this context, the present study describes a dependable technique for identifying NPs, NFTs and/or CA in Alzheimer's disease and related disorders and involves Congo red staining on one micron sections after plastic removal.

Straightforward fabrication of black nano silica dusting powder for latent fingerprint imaging

NASA Astrophysics Data System (ADS)

Komalasari, Isna; Krismastuti, Fransiska Sri Herwahyu; Elishian, Christine; Handayani, Eka Mardika; Nugraha, Willy Cahya; Ketrin, Rosi

2017-11-01

Imaging of latent fingerprint pattern (aka fingermark) is one of the most important and accurate detection methods in forensic investigation because of the characteristic of individual fingerprint. This detection technique relies on the mechanical adherence of fingerprint powder to the moisture and oily component of the skin left on the surface. The particle size of fingerprint powder is one of the critical parameter to obtain excellent fingerprint image. This study develops a simple, cheap and straightforward method to fabricate Nano size black dusting fingerprint powder based on Nano silica and applies the powder to visualize latent fingerprint. The nanostructured silica was prepared from tetraethoxysilane (TEOS) and then modified with Nano carbon, methylene blue and sodium acetate to color the powder. Finally, as a proof-of-principle, the ability of this black Nano silica dusting powder to image latent fingerprint is successfully demonstrated and the results show that this fingerprint powder provides clearer fingerprint pattern compared to the commercial one highlighting the potential application of the nanostructured silica in forensic science.

Overview of craft brewing specificities and potentially associated microbiota.

PubMed

Rodhouse, Lindsey; Carbonero, Franck

2017-09-14

The brewing process differs slightly in craft breweries as compared to industrial breweries, as there are fewer control points. This affects the microbiota of the final product. Beer contains several antimicrobial properties that protect it from pathogens, such as low pH, low oxygen and high carbon dioxide content, and the addition of hops. However, these hurdles have limited power controlling spoilage organisms. Contamination by these organisms can originate in the raw materials, persist in the environment, and be introduced by using flavoring ingredients later in the process. Spoilage is a prominent issue in brewing, and can cause quality degradation resulting in consumer rejection and product waste. For example, lactic acid bacteria are predominately associated with producing a ropy texture and haze, along with producing diacetyl which gives the beer butter flavor notes. Other microorganisms may not affect flavor or aroma, but can retard fermentation by consuming nutrients needed by fermentation yeast. Quality control in craft breweries today relies on culturing methods to detect specific spoilage organisms. Using media can be beneficial for detecting the most common beer spoilers, such as Lactobacillus and Pediococci. However, these methods are time consuming with long incubation periods. Molecular methods such as community profiling or high throughput sequencing are better used for identifying entire populations of beer. These methods allow for detection, differentiation, and identification of taxa.

Fusion of digital breast tomosynthesis images via wavelet synthesis for improved lesion conspicuity

NASA Astrophysics Data System (ADS)

Hariharan, Harishwaran; Pomponiu, Victor; Zheng, Bin; Whiting, Bruce; Gur, David

2014-03-01

Full-field digital mammography (FFDM) is the most common screening procedure for detecting early breast cancer. However, due to complications such as overlapping breast tissue in projection images, the efficacy of FFDM reading is reduced. Recent studies have shown that digital breast tomosynthesis (DBT), in combination with FFDM, increases detection sensitivity considerably while decreasing false-positive, recall rates. There is a huge interest in creating diagnostically accurate 2-D interpretations from the DBT slices. Most of the 2-D syntheses rely on visualizing the maximum intensities (brightness) from each slice through different methods. We propose a wavelet based fusion method, where we focus on preserving holistic information from larger structures such as masses while adding high frequency information that is relevant and helpful for diagnosis. This method enables the spatial generation of a 2D image from a series of DBT images, each of which contains both smooth and coarse structures distributed in the wavelet domain. We believe that the wavelet-synthesized images, generated from their DBT image datasets, provide radiologists with improved lesion and micro-calcification conspicuity as compared with FFDM images. The potential impact of this fusion method is (1) Conception of a device-independent, data-driven modality that increases the conspicuity of lesions, thereby facilitating early detection and potentially reducing recall rates; (2) Reduction of the accompanying radiation dose to the patient.

A 5-mC Dot Blot Assay Quantifying the DNA Methylation Level of Chondrocyte Dedifferentiation In Vitro.

PubMed

Jia, Zhaofeng; Liang, Yujie; Ma, Bin; Xu, Xiao; Xiong, Jianyi; Duan, Li; Wang, Daping

2017-05-17

The dedifferentiation of hyaline chondrocytes into fibroblastic chondrocytes often accompanies monolayer expansion of chondrocytes in vitro. The global DNA methylation level of chondrocytes is considered to be a suitable biomarker for the loss of the chondrocyte phenotype. However, results based on different experimental methods can be inconsistent. Therefore, it is important to establish a precise, simple, and rapid method to quantify global DNA methylation levels during chondrocyte dedifferentiation. Current genome-wide methylation analysis techniques largely rely on bisulfite genomic sequencing. Due to DNA degradation during bisulfite conversion, these methods typically require a large sample volume. Other methods used to quantify global DNA methylation levels include high-performance liquid chromatography (HPLC). However, HPLC requires complete digestion of genomic DNA. Additionally, the prohibitively high cost of HPLC instruments limits HPLC's wider application. In this study, genomic DNA (gDNA) was extracted from human chondrocytes cultured with varying number of passages. The gDNA methylation level was detected using a methylation-specific dot blot assay. In this dot blot approach, a gDNA mixture containing the methylated DNA to be detected was spotted directly onto an N + membrane as a dot inside a previously drawn circular template pattern. Compared with other gel electrophoresis-based blotting approaches and other complex blotting procedures, the dot blot method saves significant time. In addition, dot blots can detect overall DNA methylation level using a commercially available 5-mC antibody. We found that the DNA methylation level differed between the monolayer subcultures, and therefore could play a key role in chondrocyte dedifferentiation. The 5-mC dot blot is a reliable, simple, and rapid method to detect the general DNA methylation level to evaluate chondrocyte phenotype.

Segmentation of blurred objects using wavelet transform: application to x-ray images

NASA Astrophysics Data System (ADS)

Barat, Cecile S.; Ducottet, Christophe; Bilgot, Anne; Desbat, Laurent

2004-02-01

First, we present a wavelet-based algorithm for edge detection and characterization, which is an adaptation of Mallat and Hwang"s method. This algorithm relies on a modelization of contours as smoothed singularities of three particular types (transitions, peaks and lines). On the one hand, it allows to detect and locate edges at an adapted scale. On the other hand, it is able to identify the type of each detected edge point and to measure its amplitude and smoothing size. The latter parameters represent respectively the contrast and the smoothness level of the edge point. Second, we explain that this method has been integrated in a 3D bone surface reconstruction algorithm designed for computer-assisted and minimal invasive orthopaedic surgery. In order to decrease the dose to the patient and to obtain rapidly a 3D image, we propose to identify a bone shape from few X-ray projections by using statistical shape models registered to segmented X-ray projections. We apply this approach to pedicle screw insertion (scoliosis, fractures...) where ten to forty percent of the screws are known to be misplaced. In this context, the proposed edge detection algorithm allows to overcome the major problem of vertebrae segmentation in the X-ray images.

Finite element model updating and damage detection for bridges using vibration measurement.

DOT National Transportation Integrated Search

2013-12-01

In this report, the results of a study on developing a damage detection methodology based on Statistical Pattern Recognition are : presented. This methodology uses a new damage sensitive feature developed in this study that relies entirely on modal :...

48 CFR 252.244-7001 - Contractor purchasing system administration.

Code of Federal Regulations, 2014 CFR

2014-10-01

....246-7007, Contractor Counterfeit Electronic Part Detection and Avoidance System, if applicable; (20... Defense to rely upon information produced by the system that is needed for management purposes. (b... Counterfeit Electronic Part Detection and Avoidance System; (2) Provide for an organizational and...

Application of image recognition-based automatic hyphae detection in fungal keratitis.

PubMed

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.

Towards high-throughput molecular detection of Plasmodium: new approaches and molecular markers

PubMed Central

Steenkeste, Nicolas; Incardona, Sandra; Chy, Sophy; Duval, Linda; Ekala, Marie-Thérèse; Lim, Pharath; Hewitt, Sean; Sochantha, Tho; Socheat, Doung; Rogier, Christophe; Mercereau-Puijalon, Odile; Fandeur, Thierry; Ariey, Frédéric

2009-01-01

Background Several strategies are currently deployed in many countries in the tropics to strengthen malaria control toward malaria elimination. To measure the impact of any intervention, there is a need to detect malaria properly. Mostly, decisions still rely on microscopy diagnosis. But sensitive diagnosis tools enabling to deal with a large number of samples are needed. The molecular detection approach offers a much higher sensitivity, and the flexibility to be automated and upgraded. Methods Two new molecular methods were developed: dot18S, a Plasmodium-specific nested PCR based on the 18S rRNA gene followed by dot-blot detection of species by using species-specific probes and CYTB, a Plasmodium-specific nested PCR based on cytochrome b gene followed by species detection using SNP analysis. The results were compared to those obtained with microscopic examination and the "standard" 18S rRNA gene based nested PCR using species specific primers. 337 samples were diagnosed. Results Compared to the microscopy the three molecular methods were more sensitive, greatly increasing the estimated prevalence of Plasmodium infection, including P. malariae and P. ovale. A high rate of mixed infections was uncovered with about one third of the villagers infected with more than one malaria parasite species. Dot18S and CYTB sensitivity outranged the "standard" nested PCR method, CYTB being the most sensitive. As a consequence, compared to the "standard" nested PCR method for the detection of Plasmodium spp., the sensitivity of dot18S and CYTB was respectively 95.3% and 97.3%. Consistent detection of Plasmodium spp. by the three molecular methods was obtained for 83% of tested isolates. Contradictory results were mostly related to detection of Plasmodium malariae and Plasmodium ovale in mixed infections, due to an "all-or-none" detection effect at low-level parasitaemia. Conclusion A large reservoir of asymptomatic infections was uncovered using the molecular methods. Dot18S and CYTB, the new methods reported herein are highly sensitive, allow parasite DNA extraction as well as genus- and species-specific diagnosis of several hundreds of samples, and are amenable to high-throughput scaling up for larger sample sizes. Such methods provide novel information on malaria prevalence and epidemiology and are suited for active malaria detection. The usefulness of such sensitive malaria diagnosis tools, especially in low endemic areas where eradication plans are now on-going, is discussed in this paper. PMID:19402894

Measuring the speed of light with baryon acoustic oscillations.

PubMed

Salzano, Vincenzo; Dąbrowski, Mariusz P; Lazkoz, Ruth

2015-03-13

In this Letter, we describe a new method to use baryon acoustic oscillations (BAO) to derive a constraint on the possible variation of the speed of light. The method relies on the fact that there is a simple relation between the angular diameter distance (D(A)) maximum and the Hubble function (H) evaluated at the same maximum-condition redshift, which includes speed of light c. We note the close analogy of the BAO probe with a laboratory experiment: here we have D(A) which plays the role of a standard (cosmological) ruler, and H^{-1}, with the dimension of time, as a (cosmological) clock. We evaluate if current or future missions such as Euclid can be sensitive enough to detect any variation of c.

Food and forensic molecular identification: update and challenges.

PubMed

Teletchea, Fabrice; Maudet, Celia; Hänni, Catherine

2005-07-01

The need for accurate and reliable methods for animal species identification has steadily increased during past decades, particularly with the recent food scares and the overall crisis of biodiversity primarily resulting from the huge ongoing illegal traffic of endangered species. A relatively new biotechnological field, known as species molecular identification, based on the amplification and analysis of DNA, offers promising solutions. Indeed, despite the fact that retrieval and analysis of DNA in processed products is a real challenge, numerous technically consistent methods are now available and allow the detection of animal species in almost any organic substrate. However, this field is currently facing a turning point and should rely more on knowledge primarily from three fundamental fields--paleogenetics, molecular evolution and systematics.

Application of MALDI-TOF mass spectrometry in clinical diagnostic microbiology.

PubMed

De Carolis, Elena; Vella, Antonietta; Vaccaro, Luisa; Torelli, Riccardo; Spanu, Teresa; Fiori, Barbara; Posteraro, Brunella; Sanguinetti, Maurizio

2014-09-12

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently emerged as a powerful technique for identification of microorganisms, changing the workflow of well-established laboratories so that its impact on microbiological diagnostics has been unparalleled. In comparison with conventional identification methods that rely on biochemical tests and require long incubation procedures, MALDI-TOF MS has the advantage of identifying bacteria and fungi directly from colonies grown on culture plates in a few minutes and with simple procedures. Numerous studies on different systems available demonstrate the reliability and accuracy of the method, and new frontiers have been explored besides microbial species level identification, such as direct identification of pathogens from positive blood cultures, subtyping, and drug susceptibility detection.

Engineering nanomaterials-based biosensors for food safety detection.

PubMed

Lv, Man; Liu, Yang; Geng, Jinhui; Kou, Xiaohong; Xin, Zhihong; Yang, Dayong

2018-05-30

Food safety always remains a grand global challenge to human health, especially in developing countries. To solve food safety pertained problems, numerous strategies have been developed to detect biological and chemical contaminants in food. Among these approaches, nanomaterials-based biosensors provide opportunity to realize rapid, sensitive, efficient and portable detection, overcoming the restrictions and limitations of traditional methods such as complicated sample pretreatment, long detection time, and relying on expensive instruments and well-trained personnel. In this review article, we provide a cross-disciplinary perspective to review the progress of nanomaterials-based biosensors for the detection of food contaminants. The review article is organized by the category of food contaminants including pathogens/toxins, heavy metals, pesticides, veterinary drugs and illegal additives. In each category of food contaminant, the biosensing strategies are summarized including optical, colorimetric, fluorescent, electrochemical, and immune- biosensors; the relevant analytes, nanomaterials and biosensors are analyzed comprehensively. Future perspectives and challenges are also discussed briefly. We envision that our review could bridge the gap between the fields of food science and nanotechnology, providing implications for the scientists or engineers in both areas to collaborate and promote the development of nanomaterials-based biosensors for food safety detection. Copyright © 2018 Elsevier B.V. All rights reserved.

Molecular Viability Testing of UV-Inactivated Bacteria.

PubMed

Weigel, Kris M; Nguyen, Felicia K; Kearney, Moira R; Meschke, John S; Cangelosi, Gerard A

2017-05-15

PCR is effective in detecting bacterial DNA in samples, but it is unable to differentiate viable bacteria from inactivated cells or free DNA fragments. New PCR-based analytical strategies have been developed to address this limitation. Molecular viability testing (MVT) correlates bacterial viability with the ability to rapidly synthesize species-specific rRNA precursors (pre-rRNA) in response to brief nutritional stimulation. Previous studies demonstrated that MVT can assess bacterial inactivation by chlorine, serum, and low-temperature pasteurization. Here, we demonstrate that MVT can detect inactivation of Escherichia coli , Aeromonas hydrophila , and Enterococcus faecalis cells by UV irradiation. Some UV-inactivated E. coli cells transiently retained the ability to synthesize pre-rRNA postirradiation (generating false-positive MVT results), but this activity ceased within 1 h following UV exposure. Viable but transiently undetectable (by culture) E. coli cells were consistently detected by MVT. An alternative viability testing method, viability PCR (vPCR), correlates viability with cell envelope integrity. This method did not distinguish viable bacteria from UV-inactivated bacteria under some conditions, indicating that the inactivated cells retained intact cell envelopes. MVT holds promise as a means to rapidly assess microbial inactivation by UV treatment. IMPORTANCE UV irradiation is increasingly being used to disinfect water, food, and other materials for human use. Confirming the effectiveness of UV disinfection remains a challenging task. In particular, microbiological methods that rely on rapid detection of microbial DNA can yield misleading results, due to the detection of remnant DNA associated with dead microbial cells. This report describes a novel method that rapidly distinguishes living microbial cells from dead microbial cells after UV disinfection. Copyright © 2017 American Society for Microbiology.

Genome-wide detection of conservative site-specific recombination in bacteria

PubMed Central

Mathias Garrett, Elizabeth; Camilli, Andrew

2018-01-01

The ability of clonal bacterial populations to generate genomic and phenotypic heterogeneity is thought to be of great importance for many commensal and pathogenic bacteria. One common mechanism contributing to diversity formation relies on the inversion of small genomic DNA segments in a process commonly referred to as conservative site-specific recombination. This phenomenon is known to occur in several bacterial lineages, however it remains notoriously difficult to identify due to the lack of conserved features. Here, we report an easy-to-implement method based on high-throughput paired-end sequencing for genome-wide detection of conservative site-specific recombination on a single-nucleotide level. We demonstrate the effectiveness of the method by successfully detecting several novel inversion sites in an epidemic isolate of the enteric pathogen Clostridium difficile. Using an experimental approach, we validate the inversion potential of all detected sites in C. difficile and quantify their prevalence during exponential and stationary growth in vitro. In addition, we demonstrate that the master recombinase RecV is responsible for the inversion of some but not all invertible sites. Using a fluorescent gene-reporter system, we show that at least one gene from a two-component system located next to an invertible site is expressed in an on-off mode reminiscent of phase variation. We further demonstrate the applicability of our method by mining 209 publicly available sequencing datasets and show that conservative site-specific recombination is common in the bacterial realm but appears to be absent in some lineages. Finally, we show that the gene content associated with the inversion sites is diverse and goes beyond traditionally described surface components. Overall, our method provides a robust platform for detection of conservative site-specific recombination in bacteria and opens a new avenue for global exploration of this important phenomenon. PMID:29621238

Convenient, inexpensive quantification of elemental sulfur by simultaneous in situ reduction and colorimetric detection.

PubMed

Kwasniewski, Misha T; Allison, Rachel B; Wilcox, Wayne F; Sacks, Gavin L

2011-10-03

Rapid, inexpensive, and convenient methods for quantifying elemental sulfur (S(0)) with low or sub-μgg(-1) limits of detection would be useful for a range of applications where S(0) can act as a precursor for noxious off-aromas, e.g., S(0) in pesticide residues on winegrapes or as a contaminant in drywall. However, existing quantification methods rely on toxic reagents, expensive and cumbersome equipment, or demonstrate poor selectivity. We have developed and optimized an inexpensive, rapid method (∼15 min per sample) for quantifying S(0) in complex matrices. Following dispersion of the sample in PEG-400 and buffering, S(0) is quantitatively reduced to H(2)S in situ by dithiothreitol and simultaneously quantified by commercially available colorimetric H(2)S detection tubes. By employing multiple tubes, the method demonstrated linearity from 0.03 to 100 μg S(0) g(-1) for a 5 g sample (R(2)=0.994, mean CV=6.4%), and the methodological detection limit was 0.01 μg S(0) g(-1). Interferences from sulfite or sulfate were not observed. Mean recovery of an S(0) containing sulfur fungicide in grape macerate was 84.7% with a mean CV of 10.4%. Mean recovery of S(0) in a colloidal sulfur preparation from a drywall matrix was 106.6% with a mean CV of 6.9%. Comparable methodological detection limits, sensitivity, and recoveries were achieved in grape juice, grape macerate and with 1g drywall samples, indicating that the methodology should be robust across a range of complex matrices. Copyright © 2011 Elsevier B.V. All rights reserved.

A rapid method to identify Salmonella enterica serovar Gallinarum biovar Pullorum using a specific target gene ipaJ.

PubMed

Xu, Lijuan; Liu, Zijian; Li, Yang; Yin, Chao; Hu, Yachen; Xie, Xiaolei; Li, Qiuchun; Jiao, Xinan

2018-06-01

Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum) is the pathogen of pullorum disease, which leads to severe economic losses in many developing countries. Traditional methods to identify S. enterica have relied on biochemical reactions and serotyping, which are time-consuming with accurate identification if properly carried out. In this study, we developed a rapid polymerase chain reaction (PCR) method targeting the specific gene ipaJ to detect S. Pullorum. Among the 650 S. Pullorum strains isolated from 1962 to 2016 all over China, 644 strains were identified to harbour ipaJ gene in the plasmid pSPI12, accounting for a detection rate of 99.08%. Six strains were ipaJ negative because pSPI12 was not found in these strains according to whole genome sequencing results. There was no cross-reaction with other Salmonella serotypes, including Salmonella enterica serovar Gallinarum biovar Gallinarum (S. Gallinarum), which show a close genetic relationship with S. Pullorum. This shows that the PCR method could distinguish S. Gallinarum from S. Pullorum in one-step PCR without complicated biochemical identification. The limit of detection of this PCR method was as low as 90 fg/μl or 10 2 CFU, which shows a high sensitivity. Moreover, this method was applied to identify Salmonella isolated from the chicken farm and the results were consistent with what we obtained from biochemical reactions and serotyping. Together, all the results demonstrated that this one-step PCR method is simple and feasible to efficiently identify S. Pullorum.

Formalized Conflicts Detection Based on the Analysis of Multiple Emails: An Approach Combining Statistics and Ontologies

NASA Astrophysics Data System (ADS)

Zakaria, Chahnez; Curé, Olivier; Salzano, Gabriella; Smaïli, Kamel

In Computer Supported Cooperative Work (CSCW), it is crucial for project leaders to detect conflicting situations as early as possible. Generally, this task is performed manually by studying a set of documents exchanged between team members. In this paper, we propose a full-fledged automatic solution that identifies documents, subjects and actors involved in relational conflicts. Our approach detects conflicts in emails, probably the most popular type of documents in CSCW, but the methods used can handle other text-based documents. These methods rely on the combination of statistical and ontological operations. The proposed solution is decomposed in several steps: (i) we enrich a simple negative emotion ontology with terms occuring in the corpus of emails, (ii) we categorize each conflicting email according to the concepts of this ontology and (iii) we identify emails, subjects and team members involved in conflicting emails using possibilistic description logic and a set of proposed measures. Each of these steps are evaluated and validated on concrete examples. Moreover, this approach's framework is generic and can be easily adapted to domains other than conflicts, e.g. security issues, and extended with operations making use of our proposed set of measures.

A computational platform for MALDI-TOF mass spectrometry data: application to serum and plasma samples.

PubMed

Mantini, Dante; Petrucci, Francesca; Pieragostino, Damiana; Del Boccio, Piero; Sacchetta, Paolo; Candiano, Giovanni; Ghiggeri, Gian Marco; Lugaresi, Alessandra; Federici, Giorgio; Di Ilio, Carmine; Urbani, Andrea

2010-01-03

Mass spectrometry (MS) is becoming the gold standard for biomarker discovery. Several MS-based bioinformatics methods have been proposed for this application, but the divergence of the findings by different research groups on the same MS data suggests that the definition of a reliable method has not been achieved yet. In this work, we propose an integrated software platform, MASCAP, intended for comparative biomarker detection from MALDI-TOF MS data. MASCAP integrates denoising and feature extraction algorithms, which have already shown to provide consistent peaks across mass spectra; furthermore, it relies on statistical analysis and graphical tools to compare the results between groups. The effectiveness in mass spectrum processing is demonstrated using MALDI-TOF data, as well as SELDI-TOF data. The usefulness in detecting potential protein biomarkers is shown comparing MALDI-TOF mass spectra collected from serum and plasma samples belonging to the same clinical population. The analysis approach implemented in MASCAP may simplify biomarker detection, by assisting the recognition of proteomic expression signatures of the disease. A MATLAB implementation of the software and the data used for its validation are available at http://www.unich.it/proteomica/bioinf. (c) 2009 Elsevier B.V. All rights reserved.

Reagent-free and portable detection of Bacillus anthracis spores using a microfluidic incubator and smartphone microscope.

PubMed

Hutchison, Janine R; Erikson, Rebecca L; Sheen, Allison M; Ozanich, Richard M; Kelly, Ryan T

2015-09-21

Bacillus anthracis is the causative agent of anthrax and can be contracted by humans and herbivorous mammals by inhalation, ingestion, or cutaneous exposure to bacterial spores. Due to its stability and disease potential, B. anthracis is a recognized biothreat agent and robust detection and viability methods are needed to identify spores from unknown samples. Here we report the use of smartphone-based microscopy (SPM) in combination with a simple microfluidic incubation device (MID) to detect 50 to 5000 B. anthracis Sterne spores in 3 to 5 hours. This technique relies on optical monitoring of the conversion of the ∼1 μm spores to the filamentous vegetative cells that range from tens to hundreds of micrometers in length. This distinguishing filament formation is unique to B. anthracis as compared to other members of the Bacillus cereus group. A unique feature of this approach is that the sample integrity is maintained, and the vegetative biomass can be removed from the chip for secondary molecular analysis such as PCR. Compared with existing chip-based and rapid viability PCR methods, this new approach reduces assay time by almost half, and is highly sensitive, specific, and cost effective.

PRNP variants in goats reduce sensitivity of detection of PrPSc by immunoassay

USDA-ARS?s Scientific Manuscript database

Immunoassays are extensively utilized in disease diagnostics with monoclonal antibodies serving as critical tools within the assay. Detection of scrapie in sheep and goats relies heavily on immunoassays including immunohistochemistry, western blotting, and ELISA. In the United States, regulatory tes...

Emergent FDA biodefense issues for microarray technology: process analytical technology.

PubMed

Weinberg, Sandy

2004-11-01

A successful biodefense strategy relies upon any combination of four approaches. A nation can protect its troops and citizenry first by advanced mass vaccination, second, by responsive ring vaccination, and third, by post-exposure therapeutic treatment (including vaccine therapies). Finally, protection can be achieved by rapid detection followed by exposure limitation (suites and air filters) or immediate treatment (e.g., antibiotics, rapid vaccines and iodine pills). All of these strategies rely upon or are enhanced by microarray technologies. Microarrays can be used to screen, engineer and test vaccines. They are also used to construct early detection tools. While effective biodefense utilizes a variety of tactical tools, microarray technology is a valuable arrow in that quiver.

Logic design for dynamic and interactive recovery.

NASA Technical Reports Server (NTRS)

Carter, W. C.; Jessep, D. C.; Wadia, A. B.; Schneider, P. R.; Bouricius, W. G.

1971-01-01

Recovery in a fault-tolerant computer means the continuation of system operation with data integrity after an error occurs. This paper delineates two parallel concepts embodied in the hardware and software functions required for recovery; detection, diagnosis, and reconfiguration for hardware, data integrity, checkpointing, and restart for the software. The hardware relies on the recovery variable set, checking circuits, and diagnostics, and the software relies on the recovery information set, audit, and reconstruct routines, to characterize the system state and assist in recovery when required. Of particular utility is a handware unit, the recovery control unit, which serves as an interface between error detection and software recovery programs in the supervisor and provides dynamic interactive recovery.

First step toward translation of thermophotonic lock-in imaging to dentistry as an early caries detection technology

NASA Astrophysics Data System (ADS)

Ojaghi, Ashkan; Parkhimchyk, Artur; Tabatabaei, Nima

2016-09-01

Early detection of the most prevalent oral disease worldwide, i.e., dental caries, still remains as one of the major challenges in dentistry. The current dental standard of care relies on caries detection methods, such as visual inspection and x-ray radiography, which lack the sufficient specificity and sensitivity to detect caries at early stages of formation when they can be healed. We report on the feasibility of early caries detection in a clinically and commercially viable thermophotonic imaging system. The system incorporates intensity-modulated laser light along with a low-cost long-wavelength infrared (LWIR; 8 to 14 μm) camera, providing diagnostic contrast based on the enhanced light absorption of early caries. The LWIR camera is highly suitable for integration into clinical platforms because of its low weight and cost. In addition, through theoretical modeling, we show that LWIR detection enhances the diagnostic contrast due to the minimal LWIR transmittance of enamel and suppression of the masking effect of the direct thermal Planck emission. Diagnostic performance of the system and its detection threshold are experimentally evaluated by monitoring the inception and progression of artificially induced occlusal and smooth surface caries. The results are suggestive of the suitability of the developed LWIR system for detecting early dental caries.

A microfluidic approach for hemoglobin detection in whole blood

NASA Astrophysics Data System (ADS)

Taparia, Nikita; Platten, Kimsey C.; Anderson, Kristin B.; Sniadecki, Nathan J.

2017-10-01

Diagnosis of anemia relies on the detection of hemoglobin levels in a blood sample. Conventional blood analyzers are not readily available in most low-resource regions where anemia is prevalent, so detection methods that are low-cost and point-of-care are needed. Here, we present a microfluidic approach to measure hemoglobin concentration in a sample of whole blood. Unlike conventional approaches, our microfluidic approach does not require hemolysis. We detect the level of hemoglobin in a blood sample optically by illuminating the blood in a microfluidic channel at a peak wavelength of 540 nm and measuring its absorbance using a CMOS sensor coupled with a lens to magnify the image onto the detector. We compare measurements in microchannels with channel heights of 50 and 115 μm and found the channel with the 50 μm height provided a better range of detection. Since we use whole blood and not lysed blood, we fit our data to an absorption model that includes optical scattering in order to obtain a calibration curve for our system. Based on this calibration curve and data collected, we can measure hemoglobin concentration within 1 g/dL for severe cases of anemia. In addition, we measured optical density for blood flowing at a shear rate of 500 s-1 and observed it did not affect the nonlinear model. With this method, we provide an approach that uses microfluidic detection of hemoglobin levels that can be integrated with other microfluidic approaches for blood analysis.

The Critical Power Model as a Potential Tool for Anti-doping

PubMed Central

Puchowicz, Michael J.; Mizelman, Eliran; Yogev, Assaf; Koehle, Michael S.; Townsend, Nathan E.; Clarke, David C.

2018-01-01

Existing doping detection strategies rely on direct and indirect biochemical measurement methods focused on detecting banned substances, their metabolites, or biomarkers related to their use. However, the goal of doping is to improve performance, and yet evidence from performance data is not considered by these strategies. The emergence of portable sensors for measuring exercise intensities and of player tracking technologies may enable the widespread collection of performance data. How these data should be used for doping detection is an open question. Herein, we review the basis by which performance models could be used for doping detection, followed by critically reviewing the potential of the critical power (CP) model as a prototypical performance model that could be used in this regard. Performance models are mathematical representations of performance data specific to the athlete. Some models feature parameters with physiological interpretations, changes to which may provide clues regarding the specific doping method. The CP model is a simple model of the power-duration curve and features two physiologically interpretable parameters, CP and W′. We argue that the CP model could be useful for doping detection mainly based on the predictable sensitivities of its parameters to ergogenic aids and other performance-enhancing interventions. However, our argument is counterbalanced by the existence of important limitations and unresolved questions that need to be addressed before the model is used for doping detection. We conclude by providing a simple worked example showing how it could be used and propose recommendations for its implementation. PMID:29928234

An improved algorithm for small and cool fire detection using MODIS data: A preliminary study in the southeastern United States

Treesearch

Wanting Wang; John J. Qu; Xianjun Hao; Yongqiang Liu; William T. Sommers

2006-01-01

Traditional fire detection algorithms mainly rely on hot spot detection using thermal infrared (TIR) channels with fixed or contextual thresholds. Three solar reflectance channels (0.65 μm, 0.86 μm, and 2.1 μm) were recently adopted into the MODIS version 4 contextual algorithm to improve the active fire detection. In the southeastern United...

Detection and measurement of fetal anatomies from ultrasound images using a constrained probabilistic boosting tree.

PubMed

Carneiro, Gustavo; Georgescu, Bogdan; Good, Sara; Comaniciu, Dorin

2008-09-01

We propose a novel method for the automatic detection and measurement of fetal anatomical structures in ultrasound images. This problem offers a myriad of challenges, including: difficulty of modeling the appearance variations of the visual object of interest, robustness to speckle noise and signal dropout, and large search space of the detection procedure. Previous solutions typically rely on the explicit encoding of prior knowledge and formulation of the problem as a perceptual grouping task solved through clustering or variational approaches. These methods are constrained by the validity of the underlying assumptions and usually are not enough to capture the complex appearances of fetal anatomies. We propose a novel system for fast automatic detection and measurement of fetal anatomies that directly exploits a large database of expert annotated fetal anatomical structures in ultrasound images. Our method learns automatically to distinguish between the appearance of the object of interest and background by training a constrained probabilistic boosting tree classifier. This system is able to produce the automatic segmentation of several fetal anatomies using the same basic detection algorithm. We show results on fully automatic measurement of biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), femur length (FL), humerus length (HL), and crown rump length (CRL). Notice that our approach is the first in the literature to deal with the HL and CRL measurements. Extensive experiments (with clinical validation) show that our system is, on average, close to the accuracy of experts in terms of segmentation and obstetric measurements. Finally, this system runs under half second on a standard dual-core PC computer.

An N-targeting real-time PCR strategy for the accurate detection of spring viremia of carp virus.

PubMed

Shao, Ling; Xiao, Yu; He, Zhengkan; Gao, Longying

2016-03-01

Spring viremia of carp virus (SVCV) is a highly pathogenic agent of several economically important Cyprinidae fish species. Currently, there are no effective vaccines or drugs for this virus, and prevention of the disease mostly relies on prompt diagnosis. Previously, nested RT-PCR and RT-qPCR detection methods based on the glycoprotein gene G have been developed. However, the high genetic diversity of the G gene seriously limits the reliability of those methods. Compared with the G gene, phylogenetic analyses indicate that the nucleoprotein gene N is more conserved. Furthermore, studies in other members of the Rhabdoviridae family reveals that their gene transcription level follows the order N>P>M>G>L, indicating that an N gene based RT-PCR should have higher sensitivity. Therefore, two pairs of primers and two corresponding probes targeting the conserved regions of the N gene were designed. RT-qPCR assays demonstrated all primers and probes could detect phylogenetically distant isolates specifically and efficiently. Moreover, in artificially infected fish, the detected copy numbers of the N gene were much higher than those of the G gene in all tissues, and both the N and G gene copy numbers were highest in the kidney and spleen. Testing in 1100 farm-raised fish also showed that the N-targeting strategy was more reliable than the G-targeting methods. The method developed in this study provides a reliable tool for the rapid diagnosis of SVCV. Copyright © 2015 Elsevier B.V. All rights reserved.

Improving vector-borne pathogen surveillance: A laboratory-based study exploring the potential to detect dengue virus and malaria parasites in mosquito saliva.

PubMed

Melanson, Vanessa R; Jochim, Ryan; Yarnell, Michael; Ferlez, Karen Bingham; Shashikumar, Soumya; Richardson, Jason H

2017-01-01

Vector-borne pathogen surveillance programmes typically rely on the collection of large numbers of potential vectors followed by screening protocols focused on detecting pathogens in the arthropods. These processes are laborious, time consuming, expensive, and require screening of large numbers of samples. To streamline the surveillance process, increase sample throughput, and improve cost-effectiveness, a method to detect dengue virus and malaria parasites (Plasmodium falciparum) by leveraging the sugar-feeding behaviour of mosquitoes and their habit of expectorating infectious agents in their saliva during feeding was investigated in this study. Dengue virus 2 (DENV-2) infected female Aedes aegypti mosquitoes and P. falciparum infected female Anopheles stephensi mosquitoes were allowed to feed on honey coated Flinders Technical Associates -FTA® cards dyed with blue food colouring. The feeding resulted in deposition of saliva containing either DENV-2 particles or P. falciparum sporozoites onto the FTA card. Nucleic acid was extracted from each card and the appropriate real-time PCR (qPCR) assay was run to detect the pathogen of interest. As little as one plaque forming unit (PFU) of DENV-2 and as few as 60 P. falciparum parasites deposited on FTA cards from infected mosquitoes were detected via qPCR. Hence, their use to collect mosquito saliva for pathogen detection is a relevant technique for vector surveillance. This study provides laboratory confirmation that FTA cards can be used to capture and stabilize expectorated DENV-2 particles and P. falciparum sporozoites from infectious, sugar-feeding mosquitoes in very low numbers. Thus, the FTA card-based mosquito saliva capture method offers promise to overcome current limitations and revolutionize traditional mosquito-based pathogen surveillance programmes. Field testing and further method development are required to optimize this strategy.

The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants.

PubMed

Block, Annette; Debode, Frédéric; Grohmann, Lutz; Hulin, Julie; Taverniers, Isabel; Kluga, Linda; Barbau-Piednoir, Elodie; Broeders, Sylvia; Huber, Ingrid; Van den Bulcke, Marc; Heinze, Petra; Berben, Gilbert; Busch, Ulrich; Roosens, Nancy; Janssen, Eric; Žel, Jana; Gruden, Kristina; Morisset, Dany

2013-08-22

Since their first commercialization, the diversity of taxa and the genetic composition of transgene sequences in genetically modified plants (GMOs) are constantly increasing. To date, the detection of GMOs and derived products is commonly performed by PCR-based methods targeting specific DNA sequences introduced into the host genome. Information available regarding the GMOs' molecular characterization is dispersed and not appropriately organized. For this reason, GMO testing is very challenging and requires more complex screening strategies and decision making schemes, demanding in return the use of efficient bioinformatics tools relying on reliable information. The GMOseek matrix was built as a comprehensive, online open-access tabulated database which provides a reliable, comprehensive and user-friendly overview of 328 GMO events and 247 different genetic elements (status: 18/07/2013). The GMOseek matrix is aiming to facilitate GMO detection from plant origin at different phases of the analysis. It assists in selecting the targets for a screening analysis, interpreting the screening results, checking the occurrence of a screening element in a group of selected GMOs, identifying gaps in the available pool of GMO detection methods, and designing a decision tree. The GMOseek matrix is an independent database with effective functionalities in a format facilitating transferability to other platforms. Data were collected from all available sources and experimentally tested where detection methods and certified reference materials (CRMs) were available. The GMOseek matrix is currently a unique and very valuable tool with reliable information on GMOs from plant origin and their present genetic elements that enables further development of appropriate strategies for GMO detection. It is flexible enough to be further updated with new information and integrated in different applications and platforms.

Change Detection Based on Persistent Scatterer Interferometry - a New Method of Monitoring Building Changes

NASA Astrophysics Data System (ADS)

Yang, C. H.; Kenduiywo, B. K.; Soergel, U.

2016-06-01

Persistent Scatterer Interferometry (PSI) is a technique to detect a network of extracted persistent scatterer (PS) points which feature temporal phase stability and strong radar signal throughout time-series of SAR images. The small surface deformations on such PS points are estimated. PSI particularly works well in monitoring human settlements because regular substructures of man-made objects give rise to large number of PS points. If such structures and/or substructures substantially alter or even vanish due to big change like construction, their PS points are discarded without additional explorations during standard PSI procedure. Such rejected points are called big change (BC) points. On the other hand, incoherent change detection (ICD) relies on local comparison of multi-temporal images (e.g. image difference, image ratio) to highlight scene modifications of larger size rather than detail level. However, image noise inevitably degrades ICD accuracy. We propose a change detection approach based on PSI to synergize benefits of PSI and ICD. PS points are extracted by PSI procedure. A local change index is introduced to quantify probability of a big change for each point. We propose an automatic thresholding method adopting change index to extract BC points along with a clue of the period they emerge. In the end, PS ad BC points are integrated into a change detection image. Our method is tested at a site located around north of Berlin main station where steady, demolished, and erected building substructures are successfully detected. The results are consistent with ground truth derived from time-series of aerial images provided by Google Earth. In addition, we apply our technique for traffic infrastructure, business district, and sports playground monitoring.

The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants

PubMed Central

2013-01-01

Background Since their first commercialization, the diversity of taxa and the genetic composition of transgene sequences in genetically modified plants (GMOs) are constantly increasing. To date, the detection of GMOs and derived products is commonly performed by PCR-based methods targeting specific DNA sequences introduced into the host genome. Information available regarding the GMOs’ molecular characterization is dispersed and not appropriately organized. For this reason, GMO testing is very challenging and requires more complex screening strategies and decision making schemes, demanding in return the use of efficient bioinformatics tools relying on reliable information. Description The GMOseek matrix was built as a comprehensive, online open-access tabulated database which provides a reliable, comprehensive and user-friendly overview of 328 GMO events and 247 different genetic elements (status: 18/07/2013). The GMOseek matrix is aiming to facilitate GMO detection from plant origin at different phases of the analysis. It assists in selecting the targets for a screening analysis, interpreting the screening results, checking the occurrence of a screening element in a group of selected GMOs, identifying gaps in the available pool of GMO detection methods, and designing a decision tree. The GMOseek matrix is an independent database with effective functionalities in a format facilitating transferability to other platforms. Data were collected from all available sources and experimentally tested where detection methods and certified reference materials (CRMs) were available. Conclusions The GMOseek matrix is currently a unique and very valuable tool with reliable information on GMOs from plant origin and their present genetic elements that enables further development of appropriate strategies for GMO detection. It is flexible enough to be further updated with new information and integrated in different applications and platforms. PMID:23965170

Ultrananocrystalline Diamond Membranes for Detection of High-Mass Proteins

NASA Astrophysics Data System (ADS)

Kim, H.; Park, J.; Aksamija, Z.; Arbulu, M.; Blick, R. H.

2016-12-01

Mechanical resonators realized on the nanoscale by now offer applications in mass sensing of biomolecules with extraordinary sensitivity. The general idea is that perfect mechanical mass sensors should be of extremely small size to achieve zepto- or yoctogram sensitivity in weighing single molecules similar to a classical scale. However, the small effective size and long response time for weighing biomolecules with a cantilever restricts their usefulness as a high-throughput method. Commercial mass spectrometry (MS), on the other hand, such as electrospray ionization and matrix-assisted laser desorption and ionization (MALDI) time of flight (TOF) and their charge-amplifying detectors are the gold standards to which nanomechanical resonators have to live up to. These two methods rely on the ionization and acceleration of biomolecules and the following ion detection after a mass selection step, such as TOF. The principle we describe here for ion detection is based on the conversion of kinetic energy of the biomolecules into thermal excitation of chemical vapor deposition diamond nanomembranes via phonons followed by phonon-mediated detection via field emission of thermally emitted electrons. We fabricate ultrathin diamond membranes with large lateral dimensions for MALDI TOF MS of high-mass proteins. These diamond membranes are realized by straightforward etching methods based on semiconductor processing. With a minimal thickness of 100 nm and cross sections of up to 400 ×400 μ m2 , the membranes offer extreme aspect ratios. Ion detection is demonstrated in MALDI TOF analysis over a broad range from insulin to albumin. The resulting data in detection show much enhanced resolution as compared to existing detectors, which can offer better sensitivity and overall performance in resolving protein masses.

ARCOCT: Automatic detection of lumen border in intravascular OCT images.

PubMed

Cheimariotis, Grigorios-Aris; Chatzizisis, Yiannis S; Koutkias, Vassilis G; Toutouzas, Konstantinos; Giannopoulos, Andreas; Riga, Maria; Chouvarda, Ioanna; Antoniadis, Antonios P; Doulaverakis, Charalambos; Tsamboulatidis, Ioannis; Kompatsiaris, Ioannis; Giannoglou, George D; Maglaveras, Nicos

2017-11-01

Intravascular optical coherence tomography (OCT) is an invaluable tool for the detection of pathological features on the arterial wall and the investigation of post-stenting complications. Computational lumen border detection in OCT images is highly advantageous, since it may support rapid morphometric analysis. However, automatic detection is very challenging, since OCT images typically include various artifacts that impact image clarity, including features such as side branches and intraluminal blood presence. This paper presents ARCOCT, a segmentation method for fully-automatic detection of lumen border in OCT images. ARCOCT relies on multiple, consecutive processing steps, accounting for image preparation, contour extraction and refinement. In particular, for contour extraction ARCOCT employs the transformation of OCT images based on physical characteristics such as reflectivity and absorption of the tissue and, for contour refinement, local regression using weighted linear least squares and a 2nd degree polynomial model is employed to achieve artifact and small-branch correction as well as smoothness of the artery mesh. Our major focus was to achieve accurate contour delineation in the various types of OCT images, i.e., even in challenging cases with branches and artifacts. ARCOCT has been assessed in a dataset of 1812 images (308 from stented and 1504 from native segments) obtained from 20 patients. ARCOCT was compared against ground-truth manual segmentation performed by experts on the basis of various geometric features (e.g. area, perimeter, radius, diameter, centroid, etc.) and closed contour matching indicators (the Dice index, the Hausdorff distance and the undirected average distance), using standard statistical analysis methods. The proposed method was proven very efficient and close to the ground-truth, exhibiting non statistically-significant differences for most of the examined metrics. ARCOCT allows accurate and fully-automated lumen border detection in OCT images. Copyright © 2017 Elsevier B.V. All rights reserved.

The invisible AGN catalogue: a mid-infrared-radio selection method for optically faint active galactic nuclei

NASA Astrophysics Data System (ADS)

Truebenbach, Alexandra E.; Darling, Jeremy

2017-06-01

A large fraction of active galactic nuclei (AGN) are 'invisible' in extant optical surveys due to either distance or dust-obscuration. The existence of this large population of dust-obscured, infrared (IR)-bright AGN is predicted by models of galaxy-supermassive black hole coevolution and is required to explain the observed X-ray and IR backgrounds. Recently, IR colour cuts with Wide-field Infrared Survey Explorer have identified a portion of this missing population. However, as the host galaxy brightness relative to that of the AGN increases, it becomes increasingly difficult to differentiate between IR emission originating from the AGN and from its host galaxy. As a solution, we have developed a new method to select obscured AGN using their 20-cm continuum emission to identify the objects as AGN. We created the resulting invisible AGN catalogue by selecting objects that are detected in AllWISE (mid-IR) and FIRST (20 cm), but are not detected in SDSS (optical) or 2MASS (near-IR), producing a final catalogue of 46 258 objects. 30 per cent of the objects are selected by existing selection methods, while the remaining 70 per cent represent a potential previously unidentified population of candidate AGN that are missed by mid-IR colour cuts. Additionally, by relying on a radio continuum detection, this technique is efficient at detecting radio-loud AGN at z ≥ 0.29, regardless of their level of dust obscuration or their host galaxy's relative brightness.

Design and Development of Nanostructured Surfaces for Enhanced Optical Sensing

NASA Astrophysics Data System (ADS)

Santiago Cordoba, Miguel A.

At smaller size regimes, materials' physicochemical properties change with respect to bulk analogs. In the case of metal nanoparticles like gold or silver, specific wavelengths of light can induce a coherent oscillation of their conduction electrons, generating an optical field confined to the nanoparticle surface. This phenomenon is termed surface plasmon, and has been used as an enhancing mechanism in optical sensing, allowing the detection of foreign materials at small concentrations. The goal of this dissertation is to develop nanostructured materials relying on surface plasmons that can be combined with different optical sensing platforms in order to enhance current detection limits. Initially, we focus on the development of surfactant free, stimuli responsive nanoparticle thin films, which undergo an active release when exposed to a stimulus such as a change in pH. These nanoparticle thin films provide faster analyte particle transport and direct electronic coupling with the analyte molecule, all without attenuating the evanescent wave from the optical transducer to the particle. These stimuli responsive nanostructured substrates are tested within a surface enhanced Raman platform for the detection of biomolecular probes at sub-nanomolar concentrations and microL sample sizes. Furthermore, the developed nanosubstrates can be patterned, providing a versatile nanoparticle thin film for multiplexing analysis, offering a substantial advantage over conventional surface based nanoparticle detection methods. Our results encouraged further optimization of light-matter interactions in optical detection platforms. It is for that reason that this dissertation evolves towards confined optical systems. Particularly, whispering gallery microcavities confine electromagnetic waves - at high volumes - at the boundary of a dielectric resonator. In this dissertation, we examined the sensitivity of whispering gallery modes combining optical microcavities with plasmonic nanoparticles in analogy to a "nanoantenna". First, our hybrid methodology is tested by analyzing the resonant wavelength displacement of a whispering gallery mode cavity upon perturbation with a gold nanoparticle layer containing a model protein. Next, we developed a real-time optical sensing platform relying on whispering gallery microcavities and surface plasmons, and then tested it for the detection of a model protein at fM concentration (less than 1000 protein molecules). Finally, this plasmonic-photonic coupling process involving whispering gallery modes is studied via a self-referenced methodology relying on the mode splitting of a whispering gallery resonance. Specifically, we studied the mode splitting evolution of a resonant whispering gallery microcavity as a function of gold nanoparticle adherence with varying diameters. Mode splitting increases as the localized surface plasmon wavelength of the nanoparticle approaches the spectral line of the whispering gallery mode. Plasmonic-photonic coupling observed in this study provides a novel alternative to achieve single particle detection using mode splitting, as well as understanding optimization of particle size for plasmonic-photonic coupling. The study described herein opens a new way to optimize current optical sensing technology, enabling not only the detection of an analyte, but also the execution of fundamental studies of analyte interactions at ultralow concentrations.

Detecting position using ARKit

NASA Astrophysics Data System (ADS)

Dilek, Ufuk; Erol, Mustafa

2018-03-01

Developed by using ARKit, a novel app which can be used to detect position in physics experiments was introduced. The ARKit relies on a new technique. The result of the experiment presented in this study was satisfactory, suggesting that the new technique can be employed in position detection experiments/demonstrations that are conducted using mobile technology. This technique has several promising advantages over video analysis.

Witnessing entanglement without entanglement witness operators

PubMed Central

Pezzè, Luca; Li, Yan; Li, Weidong; Smerzi, Augusto

2016-01-01

Quantum mechanics predicts the existence of correlations between composite systems that, although puzzling to our physical intuition, enable technologies not accessible in a classical world. Notwithstanding, there is still no efficient general method to theoretically quantify and experimentally detect entanglement of many qubits. Here we propose to detect entanglement by measuring the statistical response of a quantum system to an arbitrary nonlocal parametric evolution. We witness entanglement without relying on the tomographic reconstruction of the quantum state, or the realization of witness operators. The protocol requires two collective settings for any number of parties and is robust against noise and decoherence occurring after the implementation of the parametric transformation. To illustrate its user friendliness we demonstrate multipartite entanglement in different experiments with ions and photons by analyzing published data on fidelity visibilities and variances of collective observables. PMID:27681625

Non-supervised method for early forest fire detection and rapid mapping

NASA Astrophysics Data System (ADS)

Artés, Tomás; Boca, Roberto; Liberta, Giorgio; San-Miguel, Jesús

2017-09-01

Natural hazards are a challenge for the society. Scientific community efforts have been severely increased assessing tasks about prevention and damage mitigation. The most important points to minimize natural hazard damages are monitoring and prevention. This work focuses particularly on forest fires. This phenomenon depends on small-scale factors and fire behavior is strongly related to the local weather. Forest fire spread forecast is a complex task because of the scale of the phenomena, the input data uncertainty and time constraints in forest fire monitoring. Forest fire simulators have been improved, including some calibration techniques avoiding data uncertainty and taking into account complex factors as the atmosphere. Such techniques increase dramatically the computational cost in a context where the available time to provide a forecast is a hard constraint. Furthermore, an early mapping of the fire becomes crucial to assess it. In this work, a non-supervised method for forest fire early detection and mapping is proposed. As main sources, the method uses daily thermal anomalies from MODIS and VIIRS combined with land cover map to identify and monitor forest fires with very few resources. This method relies on a clustering technique (DBSCAN algorithm) and on filtering thermal anomalies to detect the forest fires. In addition, a concave hull (alpha shape algorithm) is applied to obtain rapid mapping of the fire area (very coarse accuracy mapping). Therefore, the method leads to a potential use for high-resolution forest fire rapid mapping based on satellite imagery using the extent of each early fire detection. It shows the way to an automatic rapid mapping of the fire at high resolution processing as few data as possible.

Planetary quarantine

NASA Technical Reports Server (NTRS)

1971-01-01

Methods for presterilization cleaning or decontamination of spacecraft hardware to reduce microbial load, without harming materials or spacecraft components, are investigated. Three methods were considered: (1) chemicals in liquid form, relying on physical removal as well as bacterial or bacteriostatic action; (2) chemicals used in the gaseous phase, relying on bacterial activity; and (3) mechanical cleaning relying on physical removal of organisms. These methods were evaluated in terms of their effectiveness in microbial burden reduction and compatibility with spacecraft hardware. Results show chemical methods were effective against spore microorganisms but were harmful to spacecraft materials. Mechanical methods were also effective with the degree depending upon the type of instrument employed. Mechanical methods caused problems in handling the equipment, due to vacuum pressure damaging the very thin layered materials used for shielding, and the bristles used in the process caused streaks or abrasions on some spacecraft components.

Tools for detecting insect semiochemicals: a review.

PubMed

Brezolin, Alexandra Nava; Martinazzo, Janine; Muenchen, Daniela Kunkel; de Cezaro, Alana Marie; Rigo, Aline Andressa; Steffens, Clarice; Steffens, Juliana; Blassioli-Moraes, Maria Carolina; Borges, Miguel

2018-07-01

Semiochemicals are chemical compounds that are released by many species as a means of intra- and interspecific communication. Insects have extremely advanced olfactory systems; indeed, they rely on smell when performing many of their main behaviors, such as oviposition, breeding, prey location, and defense. This characteristic of insects implies that semiochemicals could be used for various applications, including in agriculture, where they could be employed along with other tools to control pest insects. The aim of this review is to present the main techniques used and the state of the art in the detection of semiochemicals, focusing on pheromones. In addition to the traditional methods of identifying semiochemicals, such as gas chromatography coupled to a high-resolution detection mode (e.g., flame ionization (FID), electron capture (ECD), photoionization (PID), or mass spectrometry (MS)), other tools are addressed in this review, including sensors and biosensors. While these new technologies may be used under laboratory conditions to improve or complement technologies that are already being used, they are mainly intended for use as new agricultural tools for detecting and controlling pest insects in the field.

Detection of tropospheric OH and HO2 by laser-induced fluorescence at low pressure using the 308nm excitation of OH

NASA Technical Reports Server (NTRS)

Hofzumahaus, Andreas; Holland, Frank

1994-01-01

Laser-induced fluorescence (LIF) spectroscopy is a highly sensitive method for the direct in situ measurement of hydroxyl concentrations in the atmosphere. Its sensitivity and selectivity relies on the intense discrete UV-absorption lines of OH which are strongest around 282nm and 308nm. We have developed a LIF-instrument based on the low-pressure experiment (FAGE). However, we use 308nm instead of 282nm as excitation wavelength for OH, a concept that is also pursued by other groups. One advantage of the longer excitation wavelength is the higher detection sensitivity due to the about 6 times larger effective OH-fluorescence cross-section. Moreover, the O3/H2O-interference (OH self-generation by the laser) is about a factor of 200 smaller at 308nm than at 282nm. This keeps the interference level well below the projected detection limit of 10(exp 5) OH/cm(exp 3). Atmospheric HO2-radicals are detected by chemical conversion of HO2 into OH with NO.

A Plasmonic Mass Spectrometry Approach for Detection of Small Nutrients and Toxins

NASA Astrophysics Data System (ADS)

Wu, Shu; Qian, Linxi; Huang, Lin; Sun, Xuming; Su, Haiyang; Gurav, Deepanjali D.; Jiang, Mawei; Cai, Wei; Qian, Kun

2018-07-01

Nutriology relies on advanced analytical tools to study the molecular compositions of food and provide key information on sample quality/safety. Small nutrients detection is challenging due to the high diversity and broad dynamic range of molecules in food samples, and a further issue is to track low abundance toxins. Herein, we developed a novel plasmonic matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) approach to detect small nutrients and toxins in complex biological emulsion samples. Silver nanoshells (SiO2@Ag) with optimized structures were used as matrices and achieved direct analysis of 6 nL of human breast milk without any enrichment or separation. We performed identification and quantitation of small nutrients and toxins with limit-of-detection down to 0.4 pmol (for melamine) and reaction time shortened to minutes, which is superior to the conventional biochemical method currently in use. The developed approach contributes to the near-future application of MALDI MS in a broad field and personalized design of plasmonic materials for real-case bio-analysis.[Figure not available: see fulltext.

Development and use of a real-time polymerase chain reaction assay for the detection of Ophidiomyces ophiodiicola in snakes.

PubMed

Allender, Matthew C; Bunick, David; Dzhaman, Elena; Burrus, Lucienne; Maddox, Carol

2015-03-01

Fungal pathogens threatening the conservation of wildlife are becoming increasingly common. Since 2008, free-ranging snakes across North America have been experiencing a marked increase in the prevalence of snake fungal disease associated with Ophidiomyces ophiodiicola. Diagnosis has historically relied on histology, microbiology, and conventional polymerase chain reaction (PCR). More sensitive methods are needed to adequately characterize the epidemiology. The current study describes the development of a real-time PCR (qPCR) assay for detecting a segment of the internal transcribed spacer 1 region between the 18S and 5.8S ribosomal RNA gene. The assay was able to detect as few as 1.05 × 10(1) gene copies per reaction. An additional 4 positive cases were detected when comparing a conventional PCR (n = 3) and the qPCR (n = 7) when used on swab samples from 47 eastern massasauga rattlesnakes. The newly developed assay is a sensitive and specific tool for surveillance and monitoring in the conservation of free-ranging snakes. © 2015 The Author(s).

A Comparative Analysis of Coprologic Diagnostic Methods for Detection of Toxoplama gondii in Cats

PubMed Central

Salant, Harold; Spira, Dan T.; Hamburger, Joseph

2010-01-01

The relative role of transmission of Toxoplasma gondii infection from cats to humans appears to have recently increased in certain areas. Large-scale screening of oocyst shedding in cats cannot rely on microscopy because oocyst identification lacks sensitivity and specificity, or on bioassays, which require test animals and weeks before examination. We compared a sensitive and species-specific coprologic–polymerase chain reaction (copro-PCR) for detection of T. gondii infected cats with microscopy and a bioassay. In experimentally infected cats followed over time, microscopy was positive occasionally, and positive copro-PCR and bioassay results were obtained continuously from days 2 to 24 post-infection. The copro-PCR is at least as sensitive and specific as the bioassay and is capable of detecting infective oocysts during cat infection. Therefore, this procedure can be used as the new gold standard for determining potential cat infectivity. Its technologic advantages over the bioassay make it superior for large-scale screening of cats. PMID:20439968

The MUSE-Wide survey: detection of a clustering signal from Lyman α emitters in the range 3 < z < 6

NASA Astrophysics Data System (ADS)

Diener, C.; Wisotzki, L.; Schmidt, K. B.; Herenz, E. C.; Urrutia, T.; Garel, T.; Kerutt, J.; Saust, R. L.; Bacon, R.; Cantalupo, S.; Contini, T.; Guiderdoni, B.; Marino, R. A.; Richard, J.; Schaye, J.; Soucail, G.; Weilbacher, P. M.

2017-11-01

We present a clustering analysis of a sample of 238 Ly α emitters at redshift 3 ≲ z ≲ 6 from the MUSE-Wide survey. This survey mosaics extragalactic legacy fields with 1h MUSE pointings to detect statistically relevant samples of emission line galaxies. We analysed the first year observations from MUSE-Wide making use of the clustering signal in the line-of-sight direction. This method relies on comparing pair-counts at close redshifts for a fixed transverse distance and thus exploits the full potential of the redshift range covered by our sample. A clear clustering signal with a correlation length of r0=2.9^{+1.0}_{-1.1} Mpc (comoving) is detected. Whilst this result is based on only about a quarter of the full survey size, it already shows the immense potential of MUSE for efficiently observing and studying the clustering of Ly α emitters.

Probabilistic Model for Untargeted Peak Detection in LC-MS Using Bayesian Statistics.

PubMed

Woldegebriel, Michael; Vivó-Truyols, Gabriel

2015-07-21

We introduce a novel Bayesian probabilistic peak detection algorithm for liquid chromatography-mass spectroscopy (LC-MS). The final probabilistic result allows the user to make a final decision about which points in a chromatogram are affected by a chromatographic peak and which ones are only affected by noise. The use of probabilities contrasts with the traditional method in which a binary answer is given, relying on a threshold. By contrast, with the Bayesian peak detection presented here, the values of probability can be further propagated into other preprocessing steps, which will increase (or decrease) the importance of chromatographic regions into the final results. The present work is based on the use of the statistical overlap theory of component overlap from Davis and Giddings (Davis, J. M.; Giddings, J. Anal. Chem. 1983, 55, 418-424) as prior probability in the Bayesian formulation. The algorithm was tested on LC-MS Orbitrap data and was able to successfully distinguish chemical noise from actual peaks without any data preprocessing.

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

NASA Astrophysics Data System (ADS)

Sheynkman, Gloria M.; Shortreed, Michael R.; Cesnik, Anthony J.; Smith, Lloyd M.

2016-06-01

Mass spectrometry-based proteomics has emerged as the leading method for detection, quantification, and characterization of proteins. Nearly all proteomic workflows rely on proteomic databases to identify peptides and proteins, but these databases typically contain a generic set of proteins that lack variations unique to a given sample, precluding their detection. Fortunately, proteogenomics enables the detection of such proteomic variations and can be defined, broadly, as the use of nucleotide sequences to generate candidate protein sequences for mass spectrometry database searching. Proteogenomics is experiencing heightened significance due to two developments: (a) advances in DNA sequencing technologies that have made complete sequencing of human genomes and transcriptomes routine, and (b) the unveiling of the tremendous complexity of the human proteome as expressed at the levels of genes, cells, tissues, individuals, and populations. We review here the field of human proteogenomics, with an emphasis on its history, current implementations, the types of proteomic variations it reveals, and several important applications.

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

PubMed Central

Sheynkman, Gloria M.; Shortreed, Michael R.; Cesnik, Anthony J.; Smith, Lloyd M.

2016-01-01

Mass spectrometry–based proteomics has emerged as the leading method for detection, quantification, and characterization of proteins. Nearly all proteomic workflows rely on proteomic databases to identify peptides and proteins, but these databases typically contain a generic set of proteins that lack variations unique to a given sample, precluding their detection. Fortunately, proteogenomics enables the detection of such proteomic variations and can be defined, broadly, as the use of nucleotide sequences to generate candidate protein sequences for mass spectrometry database searching. Proteogenomics is experiencing heightened significance due to two developments: (a) advances in DNA sequencing technologies that have made complete sequencing of human genomes and transcriptomes routine, and (b) the unveiling of the tremendous complexity of the human proteome as expressed at the levels of genes, cells, tissues, individuals, and populations. We review here the field of human proteogenomics, with an emphasis on its history, current implementations, the types of proteomic variations it reveals, and several important applications. PMID:27049631

Representativeness of Tuberculosis Genotyping Surveillance in the United States, 2009-2010.

PubMed

Shak, Emma B; France, Anne Marie; Cowan, Lauren; Starks, Angela M; Grant, Juliana

2015-01-01

Genotyping of Mycobacterium tuberculosis isolates contributes to tuberculosis (TB) control through detection of possible outbreaks. However, 20% of U.S. cases do not have an isolate for testing, and 10% of cases with isolates do not have a genotype reported. TB outbreaks in populations with incomplete genotyping data might be missed by genotyping-based outbreak detection. Therefore, we assessed the representativeness of TB genotyping data by comparing characteristics of cases reported during January 1, 2009-December 31, 2010, that had a genotype result with those cases that did not. Of 22,476 cases, 14,922 (66%) had a genotype result. Cases without genotype results were more likely to be patients <19 years of age, with unknown HIV status, of female sex, U.S.-born, and with no recent history of homelessness or substance abuse. Although cases with a genotype result are largely representative of all reported U.S. TB cases, outbreak detection methods that rely solely on genotyping data may underestimate TB transmission among certain groups.

Representativeness of Tuberculosis Genotyping Surveillance in the United States, 2009–2010

PubMed Central

Shak, Emma B.; Cowan, Lauren; Starks, Angela M.; Grant, Juliana

2015-01-01

Genotyping of Mycobacterium tuberculosis isolates contributes to tuberculosis (TB) control through detection of possible outbreaks. However, 20% of U.S. cases do not have an isolate for testing, and 10% of cases with isolates do not have a genotype reported. TB outbreaks in populations with incomplete genotyping data might be missed by genotyping-based outbreak detection. Therefore, we assessed the representativeness of TB genotyping data by comparing characteristics of cases reported during January 1, 2009–December 31, 2010, that had a genotype result with those cases that did not. Of 22,476 cases, 14,922 (66%) had a genotype result. Cases without genotype results were more likely to be patients <19 years of age, with unknown HIV status, of female sex, U.S.-born, and with no recent history of homelessness or substance abuse. Although cases with a genotype result are largely representative of all reported U.S. TB cases, outbreak detection methods that rely solely on genotyping data may underestimate TB transmission among certain groups. PMID:26556930

Lower Limits on Aperture Size for an ExoEarth Detecting Coronagraphic Mission

NASA Technical Reports Server (NTRS)

Stark, Christopher C.; Roberge, Aki; Mandell, Avi; Clampin, Mark; Domagal-Goldman, Shawn D.; McElwain, Michael W.; Stapelfeldt, Karl R.

2015-01-01

The yield of Earth-like planets will likely be a primary science metric for future space-based missions that will drive telescope aperture size. Maximizing the exoEarth candidate yield is therefore critical to minimizing the required aperture. Here we describe a method for exoEarth candidate yield maximization that simultaneously optimizes, for the first time, the targets chosen for observation, the number of visits to each target, the delay time between visits, and the exposure time of every observation. This code calculates both the detection time and multiwavelength spectral characterization time required for planets. We also refine the astrophysical assumptions used as inputs to these calculations, relying on published estimates of planetary occurrence rates as well as theoretical and observational constraints on terrestrial planet sizes and classical habitable zones. Given these astrophysical assumptions, optimistic telescope and instrument assumptions, and our new completeness code that produces the highest yields to date, we suggest lower limits on the aperture size required to detect and characterize a statistically motivated sample of exoEarths.

Detecting Horizontal Gene Transfer between Closely Related Taxa

PubMed Central

Adato, Orit; Ninyo, Noga; Gophna, Uri; Snir, Sagi

2015-01-01

Horizontal gene transfer (HGT), the transfer of genetic material between organisms, is crucial for genetic innovation and the evolution of genome architecture. Existing HGT detection algorithms rely on a strong phylogenetic signal distinguishing the transferred sequence from ancestral (vertically derived) genes in its recipient genome. Detecting HGT between closely related species or strains is challenging, as the phylogenetic signal is usually weak and the nucleotide composition is normally nearly identical. Nevertheless, there is a great importance in detecting HGT between congeneric species or strains, especially in clinical microbiology, where understanding the emergence of new virulent and drug-resistant strains is crucial, and often time-sensitive. We developed a novel, self-contained technique named Near HGT, based on the synteny index, to measure the divergence of a gene from its native genomic environment and used it to identify candidate HGT events between closely related strains. The method confirms candidate transferred genes based on the constant relative mutability (CRM). Using CRM, the algorithm assigns a confidence score based on “unusual” sequence divergence. A gene exhibiting exceptional deviations according to both synteny and mutability criteria, is considered a validated HGT product. We first employed the technique to a set of three E. coli strains and detected several highly probable horizontally acquired genes. We then compared the method to existing HGT detection tools using a larger strain data set. When combined with additional approaches our new algorithm provides richer picture and brings us closer to the goal of detecting all newly acquired genes in a particular strain. PMID:26439115

New trends in bioanalytical tools for the detection of genetically modified organisms: an update.

PubMed

Michelini, Elisa; Simoni, Patrizia; Cevenini, Luca; Mezzanotte, Laura; Roda, Aldo

2008-10-01

Despite the controversies surrounding genetically modified organisms (GMOs), the production of GM crops is increasing, especially in developing countries. Thanks to new technologies involving genetic engineering and unprecedented access to genomic resources, the next decade will certainly see exponential growth in GMO production. Indeed, EU regulations based on the precautionary principle require any food containing more than 0.9% GM content to be labeled as such. The implementation of these regulations necessitates sampling protocols, the availability of certified reference materials and analytical methodologies that allow the accurate determination of the content of GMOs. In order to qualify for the validation process, a method should fulfil some criteria, defined as "acceptance criteria" by the European Network of GMO Laboratories (ENGL). Several methods have recently been developed for GMO detection and quantitation, mostly based on polymerase chain reaction (PCR) technology. PCR (including its different formats, e.g., double competitive PCR and real-time PCR) remains the technique of choice, thanks to its ability to detect even small amounts of transgenes in raw materials and processed foods. Other approaches relying on DNA detection are based on quartz crystal microbalance piezoelectric biosensors, dry reagent dipstick-type sensors and surface plasmon resonance sensors. The application of visible/near-infrared (vis/NIR) spectroscopy or mass spectrometry combined with chemometrics techniques has also been envisaged as a powerful GMO detection tool. Furthermore, in order to cope with the multiplicity of GMOs released onto the market, the new challenge is the development of routine detection systems for the simultaneous detection of numerous GMOs, including unknown GMOs.

Label-free direct surface-enhanced Raman scattering (SERS) of nucleic acids (Conference Presentation)

NASA Astrophysics Data System (ADS)

Guerrini, Luca; Morla-Folch, Judit; Gisbert-Quilis, Patricia; Xie, Hainan; Alvarez-Puebla, Ramon

2016-03-01

Recently, plasmonic-based biosensing has experienced an unprecedented level of attention, with a particular focus on the nucleic acid detection, offering efficient solutions to engineer simple, fast, highly sensitive sensing platforms while overcoming important limitations of PCR and microarray techniques. In the broad field of plasmonics, surface-enhanced Raman scattering (SERS) spectroscopy has arisen as a powerful analytical tool for detection and structural characterization of biomolecules. Today applications of SERS to nucleic acid analysis largely rely on indirect strategies, which have been demonstrated very effective for pure sensing purposes but completely dismiss the exquisite structural information provided by the direct acquisition of the biomolecular vibrational fingerprint. Contrarily, direct label-free SERS of nucleic acid shows an outstanding potential in terms of chemical-specific information which, however, remained largely unexpressed mainly because of the inherent poor spectral reproducibility and/or limited sensitivity. To address these limitations, we developed a fast and affordable high-throughput screening direct SERS method for gaining detailed genomic information on nucleic acids (DNA and RNA) and for the characterization and quantitative recognition of DNA interactions with exogenous agents. The simple strategy relies on the electrostatic adhesion of DNA/RNA onto positively-charged silver colloids that promotes the nanoparticle aggregation into stable clusters yielding intense and reproducible SERS spectra at picogram level (i.e. the analysis can be performed without the necessity of amplification steps thus providing realistic direct information of the nucleic acid in its native state). We anticipate this method to gain a vast impact and set of applications in different fields, including medical diagnostics, genomic screening, drug discovery, forensic science and even molecular electronics.

An Accurate Projector Calibration Method Based on Polynomial Distortion Representation

PubMed Central

Liu, Miao; Sun, Changku; Huang, Shujun; Zhang, Zonghua

2015-01-01

In structure light measurement systems or 3D printing systems, the errors caused by optical distortion of a digital projector always affect the precision performance and cannot be ignored. Existing methods to calibrate the projection distortion rely on calibration plate and photogrammetry, so the calibration performance is largely affected by the quality of the plate and the imaging system. This paper proposes a new projector calibration approach that makes use of photodiodes to directly detect the light emitted from a digital projector. By analyzing the output sequence of the photoelectric module, the pixel coordinates can be accurately obtained by the curve fitting method. A polynomial distortion representation is employed to reduce the residuals of the traditional distortion representation model. Experimental results and performance evaluation show that the proposed calibration method is able to avoid most of the disadvantages in traditional methods and achieves a higher accuracy. This proposed method is also practically applicable to evaluate the geometric optical performance of other optical projection system. PMID:26492247

Biosensors for Whole-Cell Bacterial Detection

PubMed Central

Rushworth, Jo V.; Hirst, Natalie A.; Millner, Paul A.

2014-01-01

SUMMARY Bacterial pathogens are important targets for detection and identification in medicine, food safety, public health, and security. Bacterial infection is a common cause of morbidity and mortality worldwide. In spite of the availability of antibiotics, these infections are often misdiagnosed or there is an unacceptable delay in diagnosis. Current methods of bacterial detection rely upon laboratory-based techniques such as cell culture, microscopic analysis, and biochemical assays. These procedures are time-consuming and costly and require specialist equipment and trained users. Portable stand-alone biosensors can facilitate rapid detection and diagnosis at the point of care. Biosensors will be particularly useful where a clear diagnosis informs treatment, in critical illness (e.g., meningitis) or to prevent further disease spread (e.g., in case of food-borne pathogens or sexually transmitted diseases). Detection of bacteria is also becoming increasingly important in antibioterrorism measures (e.g., anthrax detection). In this review, we discuss recent progress in the use of biosensors for the detection of whole bacterial cells for sensitive and earlier identification of bacteria without the need for sample processing. There is a particular focus on electrochemical biosensors, especially impedance-based systems, as these present key advantages in terms of ease of miniaturization, lack of reagents, sensitivity, and low cost. PMID:24982325

Immunogold Nanoparticles for Rapid Plasmonic Detection of C. sakazakii.

PubMed

Aly, Mohamed A; Domig, Konrad J; Kneifel, Wolfgang; Reimhult, Erik

2018-06-25

Cronobacter sakazakii is a foodborne pathogen that can cause a rare, septicemia, life-threatening meningitis, and necrotizing enterocolitis in infants. In general, standard methods for pathogen detection rely on culture, plating, colony counting and polymerase chain reaction DNA-sequencing for identification, which are time, equipment and skill demanding. Recently, nanoparticle- and surface-based immunoassays have increasingly been explored for pathogen detection. We investigate the functionalization of gold nanoparticles optimized for irreversible and specific binding to C. sakazakii and their use for spectroscopic detection of the pathogen. We demonstrate how 40-nm gold nanoparticles grafted with a poly(ethylene glycol) brush and functionalized with polyclonal antibodies raised against C. sakazakii can be used to specifically target C. sakazakii . The strong extinction peak of the Au nanoparticle plasmon polariton resonance in the optical range is used as a label for detection of the pathogens. Individual binding of the nanoparticles to the C. sakazakii surface is also verified by transmission electron microscopy. We show that a high degree of surface functionalization with anti- C. sakazakii optimizes the detection and leads to a detection limit as low as 10 CFU/mL within 2 h using a simple cuvette-based UV-Vis spectrometric readout that has great potential for further optimization.

Yeast-based biosensors: design and applications.

PubMed

Adeniran, Adebola; Sherer, Michael; Tyo, Keith E J

2015-02-01

Yeast-based biosensing (YBB) is an exciting research area, as many studies have demonstrated the use of yeasts to accurately detect specific molecules. Biosensors incorporating various yeasts have been reported to detect an incredibly large range of molecules including but not limited to odorants, metals, intracellular metabolites, carcinogens, lactate, alcohols, and sugars. We review the detection strategies available for different types of analytes, as well as the wide range of output methods that have been incorporated with yeast biosensors. We group biosensors into two categories: those that are dependent upon transcription of a gene to report the detection of a desired molecule and those that are independent of this reporting mechanism. Transcription-dependent biosensors frequently depend on heterologous expression of sensing elements from non-yeast organisms, a strategy that has greatly expanded the range of molecules available for detection by YBBs. Transcription-independent biosensors circumvent the problem of sensing difficult-to-detect analytes by instead relying on yeast metabolism to generate easily detected molecules when the analyte is present. The use of yeast as the sensing element in biosensors has proven to be successful and continues to hold great promise for a variety of applications. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Direct questioning is more effective than patient-initiated report for the detection of sexually transmitted infections in a primary care HIV clinic in Western Kenya.

PubMed

Woo, Victoria Gah Hay; Cohen, Craig R; Bukusi, Elizabeth A; Huchko, Megan J

2013-02-01

In resource-limited settings, detection of sexually transmitted infections (STIs) often relies on self-reported symptoms to initiate management. We found self-report demonstrated poor sensitivity for STI detection. Adding clinician-initiated questions about symptoms improved detection rates. Vaginal examination further increased sensitivity. Including clinician-initiated screening in resource-limited settings would improve management of treatable STIs.

Using composite sinusoidal patterns in structured-illumination reflectance imaging (SIRI) for enhanced detection of defects in food

USDA-ARS?s Scientific Manuscript database

Structured-illumination reflectance imaging (SIRI) provides a new means for enhanced detection of defects in horticultural products. Implementing the technique relies on retrieving amplitude images by illuminating the object with sinusoidal patterns of single spatial frequencies, which, however, are...

Captures of boll weevils (Coleoptera: Curculionidae) in relation to trap distance from cotton fields

USDA-ARS?s Scientific Manuscript database

Once populations of the boll weevil (Anthonomus grandis grandis Boheman) are suppressed, eradication programs rely on pheromone trap-based monitoring for timely detection of weevil populations in cotton (Gossypium spp.). Delayed detection may increase the costs of remedial treatments, and permit rep...

A spectrophotometric method for detecting substellar companions to late-type M stars

NASA Astrophysics Data System (ADS)

Oetiker, Brian Glen

The most common stars in the Galaxy are the main-sequence M stars, yet current techniques are not optimized for detecting companions around the lowest mass stars; those with spectral designations ranging from M6 to M10. Described in this study is a search for companions around such stars using two methods: a unique implementation of the transit method, and a newly designed differential spectrophotometric method. The TEP project focusses on the detection of transits of terrestrial sized and larger companions in the eclipsing binary system CM Draconis. The newly designed spectrophotometric technique combines the strengths of the spectroscopic and photometric methods, while minimizing their inherent weaknesses. This unique method relies on the placement of three narrow band optical filters on and around the Titanium Oxide (TiO) bandhead near 8420 Å, a feature commonly seen in the atmospheres of late M stars. One filter is placed on the slope of the bandhead feature, while the remaining two are located on the adjacent continuum portions of the star's spectrum. The companion-induced motion of the star results in a doppler shifting of the bandhead feature, which in turn causes a change in flux passing through the filter located on the slope of the TiO bandhead. The spectrophotometric method is optimized for detecting compact systems containing brown dwarfs and giant planets. Because of its low dispersion-high photon efficiency design, this method is well suited for surveying large numbers of faint M stars. A small scale survey has been implemented, producing a candidate brown dwarf class companion of the star WX UMa. Applying the spectrophotometric method to a larger scale survey for brown dwarf and giant planet companions, coupled with a photometric transit study addresses two key astronomical issues. By detecting or placing limits on compact late type M star systems, a discrimination among competing theories of planetary formation may be gained. Furthermore, searching for a broad range of companion masses, may result in a better understanding of the substellar mass function.

Oligonucleotide Based Magnetic Bead Capture of Onchocerca volvulus DNA for PCR Pool Screening of Vector Black Flies

PubMed Central

Gopal, Hemavathi; Hassan, Hassan K.; Rodríguez-Pérez, Mario A.; Toé, Laurent D.; Lustigman, Sara; Unnasch, Thomas R.

2012-01-01

Background Entomological surveys of Simulium vectors are an important component in the criteria used to determine if Onchocerca volvulus transmission has been interrupted and if focal elimination of the parasite has been achieved. However, because infection in the vector population is quite rare in areas where control has succeeded, large numbers of flies need to be examined to certify transmission interruption. Currently, this is accomplished through PCR pool screening of large numbers of flies. The efficiency of this process is limited by the size of the pools that may be screened, which is in turn determined by the constraints imposed by the biochemistry of the assay. The current method of DNA purification from pools of vector black flies relies upon silica adsorption. This method can be applied to screen pools containing a maximum of 50 individuals (from the Latin American vectors) or 100 individuals (from the African vectors). Methodology/Principal Findings We have evaluated an alternative method of DNA purification for pool screening of black flies which relies upon oligonucleotide capture of Onchocerca volvulus genomic DNA from homogenates prepared from pools of Latin American and African vectors. The oligonucleotide capture assay was shown to reliably detect one O. volvulus infective larva in pools containing 200 African or Latin American flies, representing a two-four fold improvement over the conventional assay. The capture assay requires an equivalent amount of technical time to conduct as the conventional assay, resulting in a two-four fold reduction in labor costs per insect assayed and reduces reagent costs to $3.81 per pool of 200 flies, or less than $0.02 per insect assayed. Conclusions/Significance The oligonucleotide capture assay represents a substantial improvement in the procedure used to detect parasite prevalence in the vector population, a major metric employed in the process of certifying the elimination of onchocerciasis. PMID:22724041

Oil-encapsulated nanodroplet array for bio-molecular detection.

PubMed

Qiao, Wen; Zhang, Tiantian; Yen, Tony; Ku, Ti-Hsuan; Song, Junlan; Lian, Ian; Lo, Yu-Hwa

2014-09-01

Detection of low abundance biomolecules is challenging for biosensors that rely on surface chemical reactions. For surface reaction based biosensors, it require to take hours or even days for biomolecules of diffusivities in the order of 10(-10-11) m2/s to reach the surface of the sensors by Brownian motion. In addition, often times the repelling Coulomb interactions between the molecules and the probes further defer the binding process, leading to undesirably long detection time for applications such as point-of-care in vitro diagnosis. In this work, we designed an oil encapsulated nanodroplet array microchip utilizing evaporation for pre-concentration of the targets to greatly shorten the reaction time and enhance the detection sensitivity. The evaporation process of the droplets is facilitated by the superhydrophilic surface and resulting nanodroplets are encapsulated by oil drops to form stable reaction chamber. Using this method, desirable droplet volumes, concentrations of target molecules, and reaction conditions (salt concentrations, reaction temperature, etc.) in favour of fast and sensitive detection are obtained. A linear response over 2 orders of magnitude in target concentration was achieved at 10 fM for protein targets and 100 fM for miRNA mimic oligonucleotides.

Magneto-actuated immunoassay for the detection of Mycobacterium fortuitum in hemodialysis water.

PubMed

Brugnera, Michelle Fernanda; Bundalian, Reynaldo; Laube, Tamara; Julián, Esther; Luquin, Marina; Zanoni, Maria Valnice Boldrin; Pividori, Maria Isabel

2016-06-01

This paper addresses a sensitive method for the detection of mycobacteria in hemodialysis water samples based on a magneto-actuated immunoassay with optical readout. In this approach, micro (2.8μm) sized magnetic particles were modified with an antibody against the lipoarabinomannan (LAM) located in the mycobacterial cell wall. The system relies on the immunocapturing of the mycobacteria with the tailored antiLAM magnetic particles to pre-concentrate the bacteria from the hemodialysis samples throughout an immunological reaction. The performance of the immunomagnetic separation on the magnetic carrier was evaluated using confocal microscopy to study the binding pattern, as well as a magneto-actuated immunoassay with optical readout for the rapid detection of the bacteria in spiked hemodialysis samples. In this approach, the antiLAM polyclonal antibody was labeled with fluorescein isothiocyanate. The optical readout was achieved by the incubation with a secondary anti-fluorescein antibody labeled with peroxidase as optical reporter. The magneto-actuated immunoassay was able to detect mycobacteria contamination in hemodialysis water at a limit of detection of 13CFUmL(-1) in a total assay time of 3h without any previous culturing pre-enrichment step. Copyright © 2016 Elsevier B.V. All rights reserved.

A global parallel model based design of experiments method to minimize model output uncertainty.

PubMed

Bazil, Jason N; Buzzard, Gregory T; Rundell, Ann E

2012-03-01

Model-based experiment design specifies the data to be collected that will most effectively characterize the biological system under study. Existing model-based design of experiment algorithms have primarily relied on Fisher Information Matrix-based methods to choose the best experiment in a sequential manner. However, these are largely local methods that require an initial estimate of the parameter values, which are often highly uncertain, particularly when data is limited. In this paper, we provide an approach to specify an informative sequence of multiple design points (parallel design) that will constrain the dynamical uncertainty of the biological system responses to within experimentally detectable limits as specified by the estimated experimental noise. The method is based upon computationally efficient sparse grids and requires only a bounded uncertain parameter space; it does not rely upon initial parameter estimates. The design sequence emerges through the use of scenario trees with experimental design points chosen to minimize the uncertainty in the predicted dynamics of the measurable responses of the system. The algorithm was illustrated herein using a T cell activation model for three problems that ranged in dimension from 2D to 19D. The results demonstrate that it is possible to extract useful information from a mathematical model where traditional model-based design of experiments approaches most certainly fail. The experiments designed via this method fully constrain the model output dynamics to within experimentally resolvable limits. The method is effective for highly uncertain biological systems characterized by deterministic mathematical models with limited data sets. Also, it is highly modular and can be modified to include a variety of methodologies such as input design and model discrimination.

Agreement for HPV genotyping detection between self-collected specimens on a FTA cartridge and clinician-collected specimens.

PubMed

Guan, Yaoyao; Gravitt, Patti E; Howard, Roslyn; Eby, Yolanda J; Wang, Shaoming; Li, Belinda; Feng, Changyan; Qiao, You-Lin; Castle, Philip E

2013-04-01

The current method of transporting self-collected cervicovaginal specimen for HPV DNA testing relies on liquid based medium, which is challenging and expensive to transport. A novel, dry storage and transportation device, Whatman indicating FTA™ Elute Cartridge, avoids some of the pitfalls of liquid-based medium. This method has been shown to be comparable to liquid-based collection medium, but relative performance of self-collected (SC) and clinician-collected (CC) samples onto FTA cards has not been reported. The objective of this study is to compare the analytic performance of self- and clinician-collected samples onto FTA cartridges for the detection of carcinogenic HPV using Linear Array. There was a 91% agreement, 69% positive agreement, and kappa of 0.75 between the clinician-collected and self-collected specimens for detection of any carcinogenic HPV genotype. When the HPV results were categorized hierarchically according to cervical cancer risk, there was no difference in the distribution of the HPV results for the clinician- and self-collected specimens (p=0.7). This study concludes that FTA elute cartridge is a promising method of specimen transport for cervical cancer screening programs considering using self-collected specimen and HPV testing. Larger studies with clinical endpoints are now needed to assess the clinical performance. Copyright © 2012 Elsevier B.V. All rights reserved.

Con-Text: Text Detection for Fine-grained Object Classification.

PubMed

Karaoglu, Sezer; Tao, Ran; van Gemert, Jan C; Gevers, Theo

2017-05-24

This work focuses on fine-grained object classification using recognized scene text in natural images. While the state-of-the-art relies on visual cues only, this paper is the first work which proposes to combine textual and visual cues. Another novelty is the textual cue extraction. Unlike the state-of-the-art text detection methods, we focus more on the background instead of text regions. Once text regions are detected, they are further processed by two methods to perform text recognition i.e. ABBYY commercial OCR engine and a state-of-the-art character recognition algorithm. Then, to perform textual cue encoding, bi- and trigrams are formed between the recognized characters by considering the proposed spatial pairwise constraints. Finally, extracted visual and textual cues are combined for fine-grained classification. The proposed method is validated on four publicly available datasets: ICDAR03, ICDAR13, Con-Text and Flickr-logo. We improve the state-of-the-art end-to-end character recognition by a large margin of 15% on ICDAR03. We show that textual cues are useful in addition to visual cues for fine-grained classification. We show that textual cues are also useful for logo retrieval. Adding textual cues outperforms visual- and textual-only in fine-grained classification (70.7% to 60.3%) and logo retrieval (57.4% to 54.8%).

Monitoring Butterfly Abundance: Beyond Pollard Walks

PubMed Central

Pellet, Jérôme; Bried, Jason T.; Parietti, David; Gander, Antoine; Heer, Patrick O.; Cherix, Daniel; Arlettaz, Raphaël

2012-01-01

Most butterfly monitoring protocols rely on counts along transects (Pollard walks) to generate species abundance indices and track population trends. It is still too often ignored that a population count results from two processes: the biological process (true abundance) and the statistical process (our ability to properly quantify abundance). Because individual detectability tends to vary in space (e.g., among sites) and time (e.g., among years), it remains unclear whether index counts truly reflect population sizes and trends. This study compares capture-mark-recapture (absolute abundance) and count-index (relative abundance) monitoring methods in three species (Maculinea nausithous and Iolana iolas: Lycaenidae; Minois dryas: Satyridae) in contrasted habitat types. We demonstrate that intraspecific variability in individual detectability under standard monitoring conditions is probably the rule rather than the exception, which questions the reliability of count-based indices to estimate and compare specific population abundance. Our results suggest that the accuracy of count-based methods depends heavily on the ecology and behavior of the target species, as well as on the type of habitat in which surveys take place. Monitoring programs designed to assess the abundance and trends in butterfly populations should incorporate a measure of detectability. We discuss the relative advantages and inconveniences of current monitoring methods and analytical approaches with respect to the characteristics of the species under scrutiny and resources availability. PMID:22859980

Zero velocity interval detection based on a continuous hidden Markov model in micro inertial pedestrian navigation

NASA Astrophysics Data System (ADS)

Sun, Wei; Ding, Wei; Yan, Huifang; Duan, Shunli

2018-06-01

Shoe-mounted pedestrian navigation systems based on micro inertial sensors rely on zero velocity updates to correct their positioning errors in time, which effectively makes determining the zero velocity interval play a key role during normal walking. However, as walking gaits are complicated, and vary from person to person, it is difficult to detect walking gaits with a fixed threshold method. This paper proposes a pedestrian gait classification method based on a hidden Markov model. Pedestrian gait data are collected with a micro inertial measurement unit installed at the instep. On the basis of analyzing the characteristics of the pedestrian walk, a single direction angular rate gyro output is used to classify gait features. The angular rate data are modeled into a univariate Gaussian mixture model with three components, and a four-state left–right continuous hidden Markov model (CHMM) is designed to classify the normal walking gait. The model parameters are trained and optimized using the Baum–Welch algorithm and then the sliding window Viterbi algorithm is used to decode the gait. Walking data are collected through eight subjects walking along the same route at three different speeds; the leave-one-subject-out cross validation method is conducted to test the model. Experimental results show that the proposed algorithm can accurately detect different walking gaits of zero velocity interval. The location experiment shows that the precision of CHMM-based pedestrian navigation improved by 40% when compared to the angular rate threshold method.

Development of micropump-actuated negative pressure pinched injection for parallel electrophoresis on array microfluidic chip.

PubMed

Li, Bowei; Jiang, Lei; Xie, Hua; Gao, Yan; Qin, Jianhua; Lin, Bingcheng

2009-09-01

A micropump-actuated negative pressure pinched injection method is developed for parallel electrophoresis on a multi-channel LIF detection system. The system has a home-made device that could individually control 16-port solenoid valves and a high-voltage power supply. The laser beam is excitated and distributes to the array separation channels for detection. The hybrid Glass-PDMS microfluidic chip comprises two common reservoirs, four separation channels coupled to their respective pneumatic micropumps and two reference channels. Due to use of pressure as a driving force, the proposed method has no sample bias effect for separation. There is only one high-voltage supply needed for separation without relying on the number of channels, which is significant for high-throughput analysis, and the time for sample loading is shortened to 1 s. In addition, the integrated micropumps can provide the versatile interface for coupling with other function units to satisfy the complicated demands. The performance is verified by separation of DNA marker and Hepatitis B virus DNA samples. And this method is also expected to show the potential throughput for the DNA analysis in the field of disease diagnosis.

Culturing of respiratory viruses in well-differentiated pseudostratified human airway epithelium as a tool to detect unknown viruses

PubMed Central

Jazaeri Farsani, Seyed Mohammad; Deijs, Martin; Dijkman, Ronald; Molenkamp, Richard; Jeeninga, Rienk E; Ieven, Margareta; Goossens, Herman; van der Hoek, Lia

2015-01-01

Background Currently, virus discovery is mainly based on molecular techniques. Here, we propose a method that relies on virus culturing combined with state-of-the-art sequencing techniques. The most natural ex vivo culture system was used to enable replication of respiratory viruses. Method Three respiratory clinical samples were tested on well-differentiated pseudostratified tracheobronchial human airway epithelial (HAE) cultures grown at an air–liquid interface, which resemble the airway epithelium. Cells were stained with convalescent serum of the patients to identify infected cells and apical washes were analyzed by VIDISCA-454, a next-generation sequencing virus discovery technique. Results Infected cells were observed for all three samples. Sequencing subsequently indicated that the cells were infected by either human coronavirus OC43, influenzavirus B, or influenzavirus A. The sequence reads covered a large part of the genome (52%, 82%, and 57%, respectively). Conclusion We present here a new method for virus discovery that requires a virus culture on primary cells and an antibody detection. The virus in the harvest can be used to characterize the viral genome sequence and cell tropism, but also provides progeny virus to initiate experiments to fulfill the Koch's postulates. PMID:25482367

Plume radiation

NASA Astrophysics Data System (ADS)

Dirscherl, R.

1993-06-01

The electromagnetic radiation originating from the exhaust plume of tactical missile motors is of outstanding importance for military system designers. Both missile- and countermeasure engineer rely on the knowledge of plume radiation properties, be it for guidance/interference control or for passive detection of adversary missiles. To allow access to plume radiation properties, they are characterized with respect to the radiation producing mechanisms like afterburning, its chemical constituents, and reactions as well as particle radiation. A classification of plume spectral emissivity regions is given due to the constraints imposed by available sensor technology and atmospheric propagation windows. Additionally assessment methods are presented that allow a common and general grouping of rocket motor properties into various categories. These methods describe state of the art experimental evaluation techniques as well as calculation codes that are most commonly used by developers of NATO countries. Dominant aspects influencing plume radiation are discussed and a standardized test technique is proposed for the assessment of plume radiation properties that include prediction procedures. These recommendations on terminology and assessment methods should be common to all employers of plume radiation. Special emphasis is put on the omnipresent need for self-protection by the passive detection of plume radiation in the ultraviolet (UV) and infrared (IR) spectral band.

Plant tissue-based chemiluminescence biosensor for ethanol.

PubMed

Huang, Yuming; Wu, Fangqiong

2006-07-01

A plant tissue-based chemiluminescence biosensor for ethanol based on using mushroom (Agaricus bisporus) tissue as the recognition element is proposed in this paper. The principle for ethanol sensing relies on the luminol-potassium hexacyanoferrate(III)-hydrogen peroxide transducer reaction, in which hydrogen peroxide is produced from the ethanol enzymatic catalytic oxidation by oxygen under the catalysis of alcohol oxidase in the tissue column. Under optimum conditions, the method allowed the measurement of ethanol in the range of 0.001 - 2 mmol/l with a detection limit (3 sigma) of 0.2 micromol/l. The relative standard deviation (RSD) was 4.14% (n = 11) for 0.05 mmol/l ethanol. The proposed method has been applied to the determination of ethanol in biological fluids and beverages with satisfactory results.

Automated pathologies detection in retina digital images based on complex continuous wavelet transform phase angles.

PubMed

Lahmiri, Salim; Gargour, Christian S; Gabrea, Marcel

2014-10-01

An automated diagnosis system that uses complex continuous wavelet transform (CWT) to process retina digital images and support vector machines (SVMs) for classification purposes is presented. In particular, each retina image is transformed into two one-dimensional signals by concatenating image rows and columns separately. The mathematical norm of phase angles found in each one-dimensional signal at each level of CWT decomposition are relied on to characterise the texture of normal images against abnormal images affected by exudates, drusen and microaneurysms. The leave-one-out cross-validation method was adopted to conduct experiments and the results from the SVM show that the proposed approach gives better results than those obtained by other methods based on the correct classification rate, sensitivity and specificity.

"Dip-and-read" paper-based analytical devices using distance-based detection with color screening.

PubMed

Yamada, Kentaro; Citterio, Daniel; Henry, Charles S

2018-05-15

An improved paper-based analytical device (PAD) using color screening to enhance device performance is described. Current detection methods for PADs relying on the distance-based signalling motif can be slow due to the assay time being limited by capillary flow rates that wick fluid through the detection zone. For traditional distance-based detection motifs, analysis can take up to 45 min for a channel length of 5 cm. By using a color screening method, quantification with a distance-based PAD can be achieved in minutes through a "dip-and-read" approach. A colorimetric indicator line deposited onto a paper substrate using inkjet-printing undergoes a concentration-dependent colorimetric response for a given analyte. This color intensity-based response has been converted to a distance-based signal by overlaying a color filter with a continuous color intensity gradient matching the color of the developed indicator line. As a proof-of-concept, Ni quantification in welding fume was performed as a model assay. The results of multiple independent user testing gave mean absolute percentage error and average relative standard deviations of 10.5% and 11.2% respectively, which were an improvement over analysis based on simple visual color comparison with a read guide (12.2%, 14.9%). In addition to the analytical performance comparison, an interference study and a shelf life investigation were performed to further demonstrate practical utility. The developed system demonstrates an alternative detection approach for distance-based PADs enabling fast (∼10 min), quantitative, and straightforward assays.

WordCluster: detecting clusters of DNA words and genomic elements

PubMed Central

2011-01-01

Background Many k-mers (or DNA words) and genomic elements are known to be spatially clustered in the genome. Well established examples are the genes, TFBSs, CpG dinucleotides, microRNA genes and ultra-conserved non-coding regions. Currently, no algorithm exists to find these clusters in a statistically comprehensible way. The detection of clustering often relies on densities and sliding-window approaches or arbitrarily chosen distance thresholds. Results We introduce here an algorithm to detect clusters of DNA words (k-mers), or any other genomic element, based on the distance between consecutive copies and an assigned statistical significance. We implemented the method into a web server connected to a MySQL backend, which also determines the co-localization with gene annotations. We demonstrate the usefulness of this approach by detecting the clusters of CAG/CTG (cytosine contexts that can be methylated in undifferentiated cells), showing that the degree of methylation vary drastically between inside and outside of the clusters. As another example, we used WordCluster to search for statistically significant clusters of olfactory receptor (OR) genes in the human genome. Conclusions WordCluster seems to predict biological meaningful clusters of DNA words (k-mers) and genomic entities. The implementation of the method into a web server is available at http://bioinfo2.ugr.es/wordCluster/wordCluster.php including additional features like the detection of co-localization with gene regions or the annotation enrichment tool for functional analysis of overlapped genes. PMID:21261981

Quasi-dynamic mode of nanomembranes for time-of-flight mass spectrometry of proteins.

PubMed

Park, Jonghoo; Kim, Hyunseok; Blick, Robert H

2012-04-21

Mechanical resonators realized on the nano-scale by now offer applications in mass-sensing of biomolecules with extraordinary sensitivity. The general idea is that perfect mechanical biosensors should be of extremely small size to achieve zeptogram sensitivity in weighing single molecules similar to a balance. However, the small scale and long response time of weighing biomolecules with a cantilever restrict their usefulness as a high-throughput method. Commercial mass spectrometry (MS) such as electro-spray ionization (ESI)-MS and matrix-assisted laser desorption/ionization (MALDI)-time of flight (TOF)-MS are the gold standards to which nanomechanical resonators have to live up to. These two methods rely on the ionization and acceleration of biomolecules and the following ion detection after a mass selection step, such as time-of-flight (TOF). Hence, the spectrum is typically represented in m/z, i.e. the mass to ionization charge ratio. Here, we describe the feasibility and mass range of detection of a new mechanical approach for ion detection in time-of-flight mass spectrometry, the principle of which is that the impinging ion packets excite mechanical oscillations in a silicon nitride nanomembrane. These mechanical oscillations are henceforth detected via field emission of electrons from the nanomembrane. Ion detection is demonstrated in MALDI-TOF analysis over a broad range with angiotensin, bovine serum albumin (BSA), and an equimolar protein mixture of insulin, BSA, and immunoglobulin G (IgG). We find an unprecedented mass range of operation of the nanomembrane detector.

A Compact Magnetic Field-Based Obstacle Detection and Avoidance System for Miniature Spherical Robots.

PubMed

Wu, Fang; Vibhute, Akash; Soh, Gim Song; Wood, Kristin L; Foong, Shaohui

2017-05-28

Due to their efficient locomotion and natural tolerance to hazardous environments, spherical robots have wide applications in security surveillance, exploration of unknown territory and emergency response. Numerous studies have been conducted on the driving mechanism, motion planning and trajectory tracking methods of spherical robots, yet very limited studies have been conducted regarding the obstacle avoidance capability of spherical robots. Most of the existing spherical robots rely on the "hit and run" technique, which has been argued to be a reasonable strategy because spherical robots have an inherent ability to recover from collisions. Without protruding components, they will not become stuck and can simply roll back after running into bstacles. However, for small scale spherical robots that contain sensitive surveillance sensors and cannot afford to utilize heavy protective shells, the absence of obstacle avoidance solutions would leave the robot at the mercy of potentially dangerous obstacles. In this paper, a compact magnetic field-based obstacle detection and avoidance system has been developed for miniature spherical robots. It utilizes a passive magnetic field so that the system is both compact and power efficient. The proposed system can detect not only the presence, but also the approaching direction of a ferromagnetic obstacle, therefore, an intelligent avoidance behavior can be generated by adapting the trajectory tracking method with the detection information. Design optimization is conducted to enhance the obstacle detection performance and detailed avoidance strategies are devised. Experimental results are also presented for validation purposes.

Improved detection of soma location and morphology in fluorescence microscopy images of neurons.

PubMed

Kayasandik, Cihan Bilge; Labate, Demetrio

2016-12-01

Automated detection and segmentation of somas in fluorescent images of neurons is a major goal in quantitative studies of neuronal networks, including applications of high-content-screenings where it is required to quantify multiple morphological properties of neurons. Despite recent advances in image processing targeted to neurobiological applications, existing algorithms of soma detection are often unreliable, especially when processing fluorescence image stacks of neuronal cultures. In this paper, we introduce an innovative algorithm for the detection and extraction of somas in fluorescent images of networks of cultured neurons where somas and other structures exist in the same fluorescent channel. Our method relies on a new geometrical descriptor called Directional Ratio and a collection of multiscale orientable filters to quantify the level of local isotropy in an image. To optimize the application of this approach, we introduce a new construction of multiscale anisotropic filters that is implemented by separable convolution. Extensive numerical experiments using 2D and 3D confocal images show that our automated algorithm reliably detects somas, accurately segments them, and separates contiguous ones. We include a detailed comparison with state-of-the-art existing methods to demonstrate that our algorithm is extremely competitive in terms of accuracy, reliability and computational efficiency. Our algorithm will facilitate the development of automated platforms for high content neuron image processing. A Matlab code is released open-source and freely available to the scientific community. Copyright © 2016 Elsevier B.V. All rights reserved.

An isothermal based recombinase polymerase amplification assay for rapid, sensitive and robust indexing of citrus yellow mosaic virus.

PubMed

Kumar, P V; Sharma, S K; Rishi, N; Ghosh, D K; Baranwal, V K

Management of viral diseases relies on definite and sensitive detection methods. Citrus yellow mosaic virus (CYMV), a double stranded DNA virus of the genus Badnavirus, causes yellow mosaic disease in citrus plants. CYMV is transmitted through budwood and requires a robust and simplified indexing protocol for budwood certification programme. The present study reports development and standardization of an isothermal based recombinase polymerase amplification (RPA) assay for a sensitive, rapid, easy, and cost-effective method for detection and diagnosis of CYMV. Two different oligonucleotide primer sets were designed from ORF III (coding for polyprotein) and ORF II (coding for virion associated protein) regions of CYMV to perform amplification assays. Comparative evaluation of RPA, PCR and immuno-capture recombinase polymerase amplification (IC-RPA) based assays were done using purified DNA and plant crude sap. CYMV infection was efficiently detected from the crude sap in RPA and IC-RPA assays. The primer set used in RPA was specific and did not show any cross-amplification with banana streak MY virus (BSMYV), another Badnavirus species. The results from the present study indicated that RPA assay can be used easily in routine indexing of citrus planting material. To the best of our knowledge, this is the first report on development of a rapid and simplified isothermal detection assay for CYMV and can be utilized as an effective technique in quarantine and budwood certification process.

X-ray phase-contrast tomography for high-spatial-resolution zebrafish muscle imaging

NASA Astrophysics Data System (ADS)

Vågberg, William; Larsson, Daniel H.; Li, Mei; Arner, Anders; Hertz, Hans M.

2015-11-01

Imaging of muscular structure with cellular or subcellular detail in whole-body animal models is of key importance for understanding muscular disease and assessing interventions. Classical histological methods for high-resolution imaging methods require excision, fixation and staining. Here we show that the three-dimensional muscular structure of unstained whole zebrafish can be imaged with sub-5 μm detail with X-ray phase-contrast tomography. Our method relies on a laboratory propagation-based phase-contrast system tailored for detection of low-contrast 4-6 μm subcellular myofibrils. The method is demonstrated on 20 days post fertilization zebrafish larvae and comparative histology confirms that we resolve individual myofibrils in the whole-body animal. X-ray imaging of healthy zebrafish show the expected structured muscle pattern while specimen with a dystrophin deficiency (sapje) displays an unstructured pattern, typical of Duchenne muscular dystrophy. The method opens up for whole-body imaging with sub-cellular detail also of other types of soft tissue and in different animal models.

Identifying disease polymorphisms from case-control genetic association data.

PubMed

Park, L

2010-12-01

In case-control association studies, it is typical to observe several associated polymorphisms in a gene region. Often the most significantly associated polymorphism is considered to be the disease polymorphism; however, it is not clear whether it is the disease polymorphism or there is more than one disease polymorphism in the gene region. Currently, there is no method that can handle these problems based on the linkage disequilibrium (LD) relationship between polymorphisms. To distinguish real disease polymorphisms from markers in LD, a method that can detect disease polymorphisms in a gene region has been developed. Relying on the LD between polymorphisms in controls, the proposed method utilizes model-based likelihood ratio tests to find disease polymorphisms. This method shows reliable Type I and Type II error rates when sample sizes are large enough, and works better with re-sequenced data. Applying this method to fine mapping using re-sequencing or dense genotyping data would provide important information regarding the genetic architecture of complex traits.

Using Cardiac Biomarkers in Veterinary Practice.

PubMed

Oyama, Mark A

2015-09-01

Blood-based assays for various cardiac biomarkers can assist in the diagnosis of heart disease in dogs and cats. The two most common markers are cardiac troponin-I and N-terminal pro-B-type natriuretic peptide. Biomarker assays can assist in differentiating cardiac from noncardiac causes of respiratory signs and detection of preclinical cardiomyopathy. Increasingly, studies indicate that cardiac biomarker testing can help assess the risk of morbidity and mortality in animals with heart disease. Usage of cardiac biomarker testing in clinical practice relies on proper patient selection, correct interpretation of test results, and incorporation of biomarker testing into existing diagnostic methods. Copyright © 2015 Elsevier Inc. All rights reserved.

Using cardiac biomarkers in veterinary practice.

PubMed

Oyama, Mark A

2013-11-01

Blood-based assays for various cardiac biomarkers can assist in the diagnosis of heart disease in dogs and cats. The two most common markers are cardiac troponin-I and N-terminal pro-B-type natriuretic peptide. Biomarker assays can assist in differentiating cardiac from noncardiac causes of respiratory signs and detection of preclinical cardiomyopathy. Increasingly, studies indicate that cardiac biomarker testing can help assess the risk of morbidity and mortality in animals with heart disease. Usage of cardiac biomarker testing in clinical practice relies on proper patient selection, correct interpretation of test results, and incorporation of biomarker testing into existing diagnostic methods. Copyright © 2013 Elsevier Inc. All rights reserved.

Detection of "noisy" chaos in a time series

NASA Technical Reports Server (NTRS)

Chon, K. H.; Kanters, J. K.; Cohen, R. J.; Holstein-Rathlou, N. H.

1997-01-01

Time series from biological system often displays fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". The output from most biological systems is probably the result of both the internal dynamics of the systems, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

Automatic diet monitoring: a review of computer vision and wearable sensor-based methods.

PubMed

Hassannejad, Hamid; Matrella, Guido; Ciampolini, Paolo; De Munari, Ilaria; Mordonini, Monica; Cagnoni, Stefano

2017-09-01

Food intake and eating habits have a significant impact on people's health. Widespread diseases, such as diabetes and obesity, are directly related to eating habits. Therefore, monitoring diet can be a substantial base for developing methods and services to promote healthy lifestyle and improve personal and national health economy. Studies have demonstrated that manual reporting of food intake is inaccurate and often impractical. Thus, several methods have been proposed to automate the process. This article reviews the most relevant and recent researches on automatic diet monitoring, discussing their strengths and weaknesses. In particular, the article reviews two approaches to this problem, accounting for most of the work in the area. The first approach is based on image analysis and aims at extracting information about food content automatically from food images. The second one relies on wearable sensors and has the detection of eating behaviours as its main goal.

Ground settlement monitoring from temporarily persistent scatterers between two SAR acquisitions

USGS Publications Warehouse

Lei, Z.; Xiaoli, D.; Guangcai, F.; Zhong, L.

2009-01-01

We present an improved differential interferometric synthetic aperture radar (DInSAR) analysis method that measures motions of scatterers whose phases are stable between two SAR acquisitions. Such scatterers are referred to as temporarily persistent scatterers (TPS) for simplicity. Unlike the persistent scatterer InSAR (PS-InSAR) method that relies on a time-series of interferograms, the new algorithm needs only one interferogram. TPS are identified based on pixel offsets between two SAR images, and are specially coregistered based on their estimated offsets instead of a global polynomial for the whole image. Phase unwrapping is carried out based on an algorithm for sparse data points. The method is successfully applied to measure the settlement in the Hong Kong Airport area. The buildings surrounded by vegetation were successfully selected as TPS and the tiny deformation signal over the area was detected. ??2009 IEEE.

Magnetically-refreshable receptor platform structures for reusable nano-biosensor chips

NASA Astrophysics Data System (ADS)

Yoo, Haneul; Lee, Dong Jun; Cho, Dong-guk; Park, Juhun; Nam, Ki Wan; Tak Cho, Young; Park, Jae Yeol; Chen, Xing; Hong, Seunghun

2016-01-01

We developed a magnetically-refreshable receptor platform structure which can be integrated with quite versatile nano-biosensor structures to build reusable nano-biosensor chips. This structure allows one to easily remove used receptor molecules from a biosensor surface and reuse the biosensor for repeated sensing operations. Using this structure, we demonstrated reusable immunofluorescence biosensors. Significantly, since our method allows one to place receptor molecules very close to a nano-biosensor surface, it can be utilized to build reusable carbon nanotube transistor-based biosensors which require receptor molecules within a Debye length from the sensor surface. Furthermore, we also show that a single sensor chip can be utilized to detect two different target molecules simply by replacing receptor molecules using our method. Since this method does not rely on any chemical reaction to refresh sensor chips, it can be utilized for versatile biosensor structures and virtually-general receptor molecular species.

Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors.

PubMed

Haghverdi, Laleh; Lun, Aaron T L; Morgan, Michael D; Marioni, John C

2018-06-01

Large-scale single-cell RNA sequencing (scRNA-seq) data sets that are produced in different laboratories and at different times contain batch effects that may compromise the integration and interpretation of the data. Existing scRNA-seq analysis methods incorrectly assume that the composition of cell populations is either known or identical across batches. We present a strategy for batch correction based on the detection of mutual nearest neighbors (MNNs) in the high-dimensional expression space. Our approach does not rely on predefined or equal population compositions across batches; instead, it requires only that a subset of the population be shared between batches. We demonstrate the superiority of our approach compared with existing methods by using both simulated and real scRNA-seq data sets. Using multiple droplet-based scRNA-seq data sets, we demonstrate that our MNN batch-effect-correction method can be scaled to large numbers of cells.

A biosensor for cadmium based on bioconvective patterns

NASA Technical Reports Server (NTRS)

Noever, David A.; Matsos, Helen C.

1990-01-01

An 'in vitro' method for monitoring cadmium, one of the most lethal bivalent heavy metals, can detect biologically active levels. The effects of cadmium tend to concentrate in protozoa far above natural levels and therein begin transferring through freshwater food chains to animals and humans. In a small sample volume (approximately 5 ml) the method uses the toxic response to the protozoa, Tetrahymena pyriformis, to cadmium. The assay relies on macroscopic bioconvective patterns to measure the toxic response, giving a sensitivity better than 1 micro-g/1 and a toxicity threshold to 7 micro-g/1 for Cd(2+). Cadmium hinders pattern formation in a dose-dependent manner. Arrested organism growth arises from slowed division and mutation to non-dividing classes. Unlike previous efforts, this method can be performed in a shallow flow device and does not require electronic or chemical analyses to monitor toxicity.

Wireless Strain Measurement with a Micromachined Magnetoelastic Resonator Using Ringdown Frequency Locking

PubMed Central

Green, Scott R.; Gianchandani, Yogesh B.

2017-01-01

Resonant magnetoelastic devices are widely used as anti-theft tags and are also being investigated for a range of sensing applications. The vast majority of magnetoelastic devices are operated at resonance, and rely upon an external interface to wirelessly detect the resonant frequency, and other characteristics. For micromachined devices, this detection method must accommodate diminished signal strength and elevated resonant frequencies. Feedthrough of the interrogating stimulus to the detector also presents a significant challenge. This paper describes a method of interrogating wireless magnetoelastic strain sensors using a new frequency-lock approach. Following a brief excitation pulse, the sensor ring-down is analyzed and a feedback loop is used to match the excitation frequency and the resonant frequency. Data acquisition hardware is used in conjunction with custom software to implement the frequency-lock loop. Advantages of the method include temporal isolation of interrogating stimulus from the sensor response and near real-time tracking of resonant frequencies. The method was investigated using a family of wireless strain sensors with resonant frequencies ranging from 120 to 240 kHz. Strain levels extending to 3.5 mstrain and sensitivities up to 14300 ppm/mstrain were measured with response times faster than 0.5 s. The standard deviation of the locked frequency did not exceed 0.1%. PMID:28713873

Screening tests for assessing the anaerobic biodegradation of pollutant chemicals in subsurface environments

USGS Publications Warehouse

Suflita, Joseph M.; Concannon, Frank

1995-01-01

Screening methods were developed to assess the susceptibility of ground water contaminants to anaerobic biodegradation. One method was an extrapolation of a procedure previously used to measure biodegradation activity in dilute sewage sludge. Aquifer solids and ground water with no additional nutritive media were incubated anaerobically in 160-ml serum bottles containing 250 mg·l−1 carbon of the substrate of interest. This method relied on the detection of gas pressure or methane production in substrateamended microcosms relative to background controls. Other screening procedures involved the consumption of stoichiometrically required amounts of sulfate or nitrate from the same type of incubations. Close agreement was obtained between the measured and calculated amounts of substrate bioconversion based on the measured biogas pressure in methanogenic microcosms. Storage of the microcosms for up to 6 months did not adversely influence the onset or rate of benzoic acid mineralization. The lower detection limits of the methanogenic assay were found to be a function of the size of the microcosm headspace, the mean oxidation state of the substrate carbon, and the method used to correct for background temperature fluctuations. Using these simple screening procedures, biodegradation information of regulatory interest could be generated, including, (i) the length of the adaptation period, (ii) the rate of substrate decay and (iii) the completeness of the bioconversion.

Following the footprints of polymorphic inversions on SNP data: from detection to association tests

PubMed Central

Cáceres, Alejandro; González, Juan R.

2015-01-01

Inversion polymorphisms have important phenotypic and evolutionary consequences in humans. Two different methodologies have been used to infer inversions from SNP dense data, enabling the use of large cohorts for their study. One approach relies on the differences in linkage disequilibrium across breakpoints; the other one captures the internal haplotype groups that tag the inversion status of chromosomes. In this article, we assessed the convergence of the two methods in the detection of 20 human inversions that have been reported in the literature. The methods converged in four inversions including inv-8p23, for which we studied its association with low-BMI in American children. Using a novel haplotype tagging method with control on inversion ancestry, we computed the frequency of inv-8p23 in two American cohorts and observed inversion haplotype admixture. Accounting for haplotype ancestry, we found that the European inverted allele in children carries a recessive risk of underweight, validated in an independent Spanish cohort (combined: OR= 2.00, P = 0.001). While the footprints of inversions on SNP data are complex, we show that systematic analyses, such as convergence of different methods and controlling for ancestry, can reveal the contribution of inversions to the ancestral composition of populations and to the heritability of human disease. PMID:25672393

A Dual-Process Account of Auditory Change Detection

ERIC Educational Resources Information Center

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

2010-01-01

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…

Design optimisation of a TOF-based collimated camera prototype for online hadrontherapy monitoring

NASA Astrophysics Data System (ADS)

Pinto, M.; Dauvergne, D.; Freud, N.; Krimmer, J.; Letang, J. M.; Ray, C.; Roellinghoff, F.; Testa, E.

2014-12-01

Hadrontherapy is an innovative radiation therapy modality for which one of the main key advantages is the target conformality allowed by the physical properties of ion species. However, in order to maximise the exploitation of its potentialities, online monitoring is required in order to assert the treatment quality, namely monitoring devices relying on the detection of secondary radiations. Herein is presented a method based on Monte Carlo simulations to optimise a multi-slit collimated camera employing time-of-flight selection of prompt-gamma rays to be used in a clinical scenario. In addition, an analytical tool is developed based on the Monte Carlo data to predict the expected precision for a given geometrical configuration. Such a method follows the clinical workflow requirements to simultaneously have a solution that is relatively accurate and fast. Two different camera designs are proposed, considering different endpoints based on the trade-off between camera detection efficiency and spatial resolution to be used in a proton therapy treatment with active dose delivery and assuming a homogeneous target.

Convolutional networks for vehicle track segmentation

DOE PAGES

Quach, Tu-Thach

2017-08-19

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate inmore » low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.« less

Profiling defect depth in composite materials using thermal imaging NDE

NASA Astrophysics Data System (ADS)

Obeidat, Omar; Yu, Qiuye; Han, Xiaoyan

2018-04-01

Sonic Infrared (IR) NDE, is a relatively new NDE technology; it has been demonstrated as a reliable and sensitive method to detect defects. SIR uses ultrasonic excitation with IR imaging to detect defects and flaws in the structures being inspected. An IR camera captures infrared radiation from the target for a period of time covering the ultrasound pulse. This period of time may be much longer than the pulse depending on the defect depth and the thermal properties of the materials. With the increasing deployment of composites in modern aerospace and automobile structures, fast, wide-area and reliable NDE methods are necessary. Impact damage is one of the major concerns in modern composites. Damage can occur at a certain depth without any visual indication on the surface. Defect depth information can influence maintenance decisions. Depth profiling relies on the time delays in the captured image sequence. We'll present our work on the defect depth profiling by using the temporal information of IR images. An analytical model is introduced to describe heat diffusion from subsurface defects in composite materials. Depth profiling using peak time is introduced as well.

Immunosignature: Serum Antibody Profiling for Cancer Diagnostics.

PubMed

Chapoval, Andrei I; Legutki, J Bart; Stafford, Philip; Trebukhov, Andrey V; Johnston, Stephen A; Shoikhet, Yakov N; Lazarev, Alexander F

2015-01-01

Biomarkers for preclinical diagnosis of cancer are valuable tools for detection of malignant tumors at early stages in groups at risk and screening healthy people, as well as monitoring disease recurrence after treatment of cancer. However the complexity of the body's response to the pathological processes makes it virtually impossible to evaluate this response to the development of the disease using a single biomarker that is present in the serum at low concentrations. An alternative approach to standard biomarker analysis is called immunosignature. Instead of going after biomarkers themselves this approach rely on the analysis of the humoral immune response to molecular changes associated with the development of pathological processes. It is known that antibodies are produced in response to proteins expressed during cancer development. Accordingly, the changes in antibody repertoire associated with tumor growth can serve as biomarkers of cancer. Immunosignature is a highly sensitive method for antibody repertoire analysis utilizing high density peptide microarrays. In the present review we discuss modern methods for antibody detection, as well as describe the principles and applications of immunosignature in research and clinical practice.

Convolutional networks for vehicle track segmentation

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

Quach, Tu-Thach

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate inmore » low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.« less

Specific recognition of hydatid cyst antigens by serum IgG, IgE, and IgA using western blot.

PubMed

Sbihi, Y; Janssen, D; Osuna, A

1997-01-01

Diagnosis of hydatid disease in humans relies on the detection of specific antibodies against antigens of the metacestode from Echinococcus granulosus. The specificity and sensitivity of current immunological techniques based on specific serum IgG rely on the way antigens are purified. We used Western immunoblotting to detect specific IgG, IgE, and IgA antibodies in serum from patients with hydatid disease using either crude antigen preparations (total hydatid fluid), purified fractions enriched in Antigens 5 and B, and glycoproteins from hydatid fluid. Depending on whether crude HF or purified antigen fractions were used, IgG and IgE recognized specifically low-to-medium MW bands between 12 and 42 kDa. IgA recognized specifically 110 kDa band in crude hydatid fluid and in the glycoprotein fraction of hydatid fluid, and a 42 kDa band in all antigen samples used. Besides the advantage of detecting specific IgA in crude hydatid fluid, these results offer the possibility of simplifying future immunological tests if specific secretory IgA can be similarly detected.

Terahertz pulsed imaging study of dental caries

NASA Astrophysics Data System (ADS)

Karagoz, Burcu; Altan, Hakan; Kamburoglu, Kıvanç

2015-07-01

Current diagnostic techniques in dentistry rely predominantly on X-rays to monitor dental caries. Terahertz Pulsed Imaging (TPI) has great potential for medical applications since it is a nondestructive imaging method. It does not cause any ionization hazard on biological samples due to low energy of THz radiation. Even though it is strongly absorbed by water which exhibits very unique chemical and physical properties that contribute to strong interaction with THz radiation, teeth can still be investigated in three dimensions. Recent investigations suggest that this method can be used in the early identification of dental diseases and imperfections in the tooth structure without the hazards of using techniques which rely on x-rays. We constructed a continuous wave (CW) and time-domain reflection mode raster scan THz imaging system that enables us to investigate various teeth samples in two or three dimensions. The samples comprised of either slices of individual tooth samples or rows of teeth embedded in wax, and the imaging was done by scanning the sample across the focus of the THz beam. 2D images were generated by acquiring the intensity of the THz radiation at each pixel, while 3D images were generated by collecting the amplitude of the reflected signal at each pixel. After analyzing the measurements in both the spatial and frequency domains, the results suggest that the THz pulse is sensitive to variations in the structure of the samples that suggest that this method can be useful in detecting the presence of caries.

Development of narrow-band fluorescence index for the detection of aflatoxin contaminated corn

NASA Astrophysics Data System (ADS)

Yao, Haibo; Hruska, Zuzana; Kincaid, Russell; Ononye, Ambrose; Brown, Robert L.; Bhatnagar, Deepak; Cleveland, Thomas E.

2011-06-01

Aflatoxin is produced by the fungus Aspergillus flavus when the fungus invades developing corn kernels. Because of its potent toxicity, the levels of aflatoxin are regulated by the Food and Drug Administration (FDA) in the US, allowing 20 ppb (parts per billion) limits in food, and feed intended for interstate commerce. Currently, aflatoxin detection and quantification methods are based on analytical tests. These tests require the destruction of samples, can be costly and time consuming, and often rely on less than desirable sampling techniques. Thus, the ability to detect aflatoxin in a rapid, non-invasive way is crucial to the corn industry in particular. This paper described how narrow-band fluorescence indices were developed for aflatoxin contamination detection based on single corn kernel samples. The indices were based on two bands extracted from full wavelength fluorescence hyperspectral imagery. The two band results were later applied to two large sample experiments with 25 g and 1 kg of corn per sample. The detection accuracies were 85% and 95% when 100 ppb threshold was used. Since the data acquisition period is significantly lower for several image bands than for full wavelength hyperspectral data, this study would be helpful in the development of real-time detection instrumentation for the corn industry.

Single-Color Digital PCR Provides High-Performance Detection of Cancer Mutations from Circulating DNA.

PubMed

Wood-Bouwens, Christina; Lau, Billy T; Handy, Christine M; Lee, HoJoon; Ji, Hanlee P

2017-09-01

We describe a single-color digital PCR assay that detects and quantifies cancer mutations directly from circulating DNA collected from the plasma of cancer patients. This approach relies on a double-stranded DNA intercalator dye and paired allele-specific DNA primer sets to determine an absolute count of both the mutation and wild-type-bearing DNA molecules present in the sample. The cell-free DNA assay uses an input of 1 ng of nonamplified DNA, approximately 300 genome equivalents, and has a molecular limit of detection of three mutation DNA genome-equivalent molecules per assay reaction. When using more genome equivalents as input, we demonstrated a sensitivity of 0.10% for detecting the BRAF V600E and KRAS G12D mutations. We developed several mutation assays specific to the cancer driver mutations of patients' tumors and detected these same mutations directly from the nonamplified, circulating cell-free DNA. This rapid and high-performance digital PCR assay can be configured to detect specific cancer mutations unique to an individual cancer, making it a potentially valuable method for patient-specific longitudinal monitoring. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

A label-free aptamer-fluorophore assembly for rapid and specific detection of cocaine in biofluids.

PubMed

Roncancio, Daniel; Yu, Haixiang; Xu, Xiaowen; Wu, Shuo; Liu, Ran; Debord, Joshua; Lou, Xinhui; Xiao, Yi

2014-11-18

We report a rapid and specific aptamer-based method for one-step cocaine detection with minimal reagent requirements. The feasibility of aptamer-based detection has been demonstrated with sensors that operate via target-induced conformational change mechanisms, but these have generally exhibited limited target sensitivity. We have discovered that the cocaine-binding aptamer MNS-4.1 can also bind the fluorescent molecule 2-amino-5,6,7-trimethyl-1,8-naphthyridine (ATMND) and thereby quench its fluorescence. We subsequently introduced sequence changes into MNS-4.1 to engineer a new cocaine-binding aptamer (38-GC) that exhibits higher affinity to both ligands, with reduced background signal and increased signal gain. Using this aptamer, we have developed a new sensor platform that relies on the cocaine-mediated displacement of ATMND from 38-GC as a result of competitive binding. We demonstrate that our sensor can detect cocaine within seconds at concentrations as low as 200 nM, which is 50-fold lower than existing assays based on target-induced conformational change. More importantly, our assay achieves successful cocaine detection in body fluids, with a limit of detection of 10.4, 18.4, and 36 μM in undiluted saliva, urine, and serum samples, respectively.

Optimal joint detection and estimation that maximizes ROC-type curves

PubMed Central

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K.

2017-01-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation. PMID:27093544

Optimal Joint Detection and Estimation That Maximizes ROC-Type Curves.

PubMed

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K

2016-09-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation.

Building change detection via a combination of CNNs using only RGB aerial imageries

NASA Astrophysics Data System (ADS)

Nemoto, Keisuke; Hamaguchi, Ryuhei; Sato, Masakazu; Fujita, Aito; Imaizumi, Tomoyuki; Hikosaka, Shuhei

2017-10-01

Building change information extracted from remote sensing imageries is important for various applications such as urban management and marketing planning. The goal of this work is to develop a methodology for automatically capturing building changes from remote sensing imageries. Recent studies have addressed this goal by exploiting 3-D information as a proxy for building height. In contrast, because in practice it is expensive or impossible to prepare 3-D information, we do not rely on 3-D data but focus on using only RGB aerial imageries. Instead, we employ deep convolutional neural networks (CNNs) to extract effective features, and improve change detection accuracy in RGB remote sensing imageries. We consider two aspects of building change detection, building detection and subsequent change detection. Our proposed methodology was tested on several areas, which has some differences such as dominant building characteristics and varying brightness values. On all over the tested areas, the proposed method provides good results for changed objects, with recall values over 75 % with a strict overlap requirement of over 50% in intersection-over-union (IoU). When the IoU threshold was relaxed to over 10%, resulting recall values were over 81%. We conclude that use of CNNs enables accurate detection of building changes without employing 3-D information.

Differential detection of pathogenic Yersinia spp. by fluorescence in situ hybridization.

PubMed

Rohde, Alexander; Hammerl, Jens Andre; Appel, Bernd; Dieckmann, Ralf; Al Dahouk, Sascha

2017-04-01

Yersinia enterocolitica, Y. pseudotuberculosis and Y. pestis are pathogens of major medical importance, which are responsible for a considerable number of infections every year. The detection of these species still relies on cultural methods, which are slow, labour intensive and often hampered by the presence of high amounts of accompanying flora. In this study, fluorescence in situ hybridization (FISH) was used to develop a fast, sensitive and reliable alternative to detect viable bacteria in food. For this purpose, highly specific probes targeting the 16S and 23S ribosomal RNA were employed to differentially detect each of the three species. In order to enable the differentiation of single nucleotide polymorphisms (SNPs), suitable competitor oligonucleotides and locked nucleic acids (LNAs) were used. Starved cells still showed a strong signal and a direct viable count (DVC) approach combined with FISH optimized live/dead discrimination. Sensitivity of the FISH test was high and even a single cell per gram of spiked minced pork meat could be detected within a day, demonstrating the applicability to identify foodborne hazards at an early stage. In conclusion, the established FISH tests proved to be promising tools to compensate existing drawbacks of the conventional cultural detection of these important zoonotic agents. Copyright © 2016 Elsevier Ltd. All rights reserved.

Damage detection in sandwich composite materials using laser vibrometry in conjunction with nonlinear system identification

NASA Astrophysics Data System (ADS)

Underwood, Sara; Koester, David; Adams, Douglas E.

2009-03-01

Fiberglass sandwich panels are tested to study a vibration-based method for locating damage in composite materials. This method does not rely on a direct comparison of the natural frequencies, mode shapes, or residues in the forced vibration response data. Specifically, a nonlinear system identification based method for damage detection is sought that reduces the sensitivity of damage detection results to changes in vibration measurements due to variations in boundary conditions, environmental conditions, and material properties of the panel. Damage mechanisms considered include a disbond between the core and face sheet and a crack within the core. A panel is excited by a skewed piezoelectric actuator over a broad frequency range while a three-dimensional scanning laser vibrometer measures the surface velocity of the panel along three orthogonal axes. The forced frequency response data measured using the scanning laser vibrometer at multiple excitation amplitudes is processed to identify areas of the panel that exhibit significant nonlinear response characteristics. It is demonstrated that these localized nonlinearities in the panel coincide with the damaged areas of the composite material. Because changes in the measured frequency response functions due to nonlinear distortions associated with the damage can be identified without comparing the vibration data to a reference (baseline) signature of the undamaged material, this vibration technique for damage detection in composite materials exhibits less sensitivity to variations in the underlying linear characteristics than traditional methods. It is also demonstrated that the damage at a given location can be classified as either due to a disbond or core crack because these two types of damage produce difference signatures when comparing the multi-amplitude frequency response functions.

Detecting inertial effects with airborne matter-wave interferometry

PubMed Central

Geiger, R.; Ménoret, V.; Stern, G.; Zahzam, N.; Cheinet, P.; Battelier, B.; Villing, A.; Moron, F.; Lours, M.; Bidel, Y.; Bresson, A.; Landragin, A.; Bouyer, P.

2011-01-01

Inertial sensors relying on atom interferometry offer a breakthrough advance in a variety of applications, such as inertial navigation, gravimetry or ground- and space-based tests of fundamental physics. These instruments require a quiet environment to reach their performance and using them outside the laboratory remains a challenge. Here we report the first operation of an airborne matter-wave accelerometer set up aboard a 0g plane and operating during the standard gravity (1g) and microgravity (0g) phases of the flight. At 1g, the sensor can detect inertial effects more than 300 times weaker than the typical acceleration fluctuations of the aircraft. We describe the improvement of the interferometer sensitivity in 0g, which reaches 2 x 10-4 ms-2 / √Hz with our current setup. We finally discuss the extension of our method to airborne and spaceborne tests of the Universality of free fall with matter waves. PMID:21934658

Development of a Photothermal Absorbance Detector for Use with Microfluidic Devices

PubMed Central

Dennis, Patty J.; Ferguson Welch, Erin R.; Alarie, Jean Pierre; Ramsey, J. Michael; Jorgenson, James W.

2010-01-01

The development of a photothermal absorbance detector for use with microfluidic devices is described. Unlike thermooptical techniques that rely on measuring refractive index changes, the solution viscosity is probed by continuously monitoring solution conductivity. Platinum electrodes microfabricated on a quartz substrate and bonded to a substrate containing the microchannels enable contact conductivity measurements. The effects of excitation frequency and voltage, electrode spacing, laser power, and laser modulation (chopping) frequency were evaluated experimentally. In the current configuration a limit of detection of 5 nM for DABSYL-tagged glucosamine was obtained using long injections (to give flat-topped peaks). This corresponds to an absorbance of 4.4 × 10−7 AU. Separation and detection of DABSYL-tagged glycine, proline, and tryptophan is also shown to demonstrate the feasibility of the method. In addition, simulations were used to investigate the applicability of the technique to small volume platforms. PMID:20411923

Using soft-hard fusion for misinformation detection and pattern of life analysis in OSINT

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Shabarekh, Charlotte

2017-05-01

Today's battlefields are shifting to "denied areas", where the use of U.S. Military air and ground assets is limited. To succeed, the U.S. intelligence analysts increasingly rely on available open-source intelligence (OSINT) which is fraught with inconsistencies, biased reporting and fake news. Analysts need automated tools for retrieval of information from OSINT sources, and these solutions must identify and resolve conflicting and deceptive information. In this paper, we present a misinformation detection model (MDM) which converts text to attributed knowledge graphs and runs graph-based analytics to identify misinformation. At the core of our solution is identification of knowledge conflicts in the fused multi-source knowledge graph, and semi-supervised learning to compute locally consistent reliability and credibility scores for the documents and sources, respectively. We present validation of proposed method using an open source dataset constructed from the online investigations of MH17 downing in Eastern Ukraine.

Compressed Sensing in On-Grid MIMO Radar.

PubMed

Minner, Michael F

2015-01-01

The accurate detection of targets is a significant problem in multiple-input multiple-output (MIMO) radar. Recent advances of Compressive Sensing offer a means of efficiently accomplishing this task. The sparsity constraints needed to apply the techniques of Compressive Sensing to problems in radar systems have led to discretizations of the target scene in various domains, such as azimuth, time delay, and Doppler. Building upon recent work, we investigate the feasibility of on-grid Compressive Sensing-based MIMO radar via a threefold azimuth-delay-Doppler discretization for target detection and parameter estimation. We utilize a colocated random sensor array and transmit distinct linear chirps to a small scene with few, slowly moving targets. Relying upon standard far-field and narrowband assumptions, we analyze the efficacy of various recovery algorithms in determining the parameters of the scene through numerical simulations, with particular focus on the ℓ 1-squared Nonnegative Regularization method.

Biosensors of bacterial cells.

PubMed

Burlage, Robert S; Tillmann, Joshua

2017-07-01

Biosensors are devices which utilize both an electrical component (transducer) and a biological component to study an environment. They are typically used to examine biological structures, organisms and processes. The field of biosensors has now become so large and varied that the technology can often seem impenetrable. Yet the principles which underlie the technology are uncomplicated, even if the details of the mechanisms are elusive. In this review we confine our analysis to relatively current advancements in biosensors for the detection of whole bacterial cells. This includes biosensors which rely on an added labeled component and biosensors which do not have a labeled component and instead detect the binding event or bound structure on the transducer. Methods to concentrate the bacteria prior to biosensor analysis are also described. The variety of biosensor types and their actual and potential uses are described. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluation of saffron (Crocus sativus L.) adulteration with plant adulterants by (1)H NMR metabolite fingerprinting.

PubMed

Petrakis, Eleftherios A; Cagliani, Laura R; Polissiou, Moschos G; Consonni, Roberto

2015-04-15

In the present work, a preliminary study for the detection of adulterated saffron and the identification of the adulterant used by means of (1)H NMR and chemometrics is reported. Authentic Greek saffron and four typical plant-derived materials utilised as bulking agents in saffron, i.e., Crocus sativus stamens, safflower, turmeric, and gardenia were investigated. A two-step approach, relied on the application of both OPLS-DA and O2PLS-DA models to the (1)H NMR data, was adopted to perform authentication and prediction of authentic and adulterated saffron. Taking into account the deficiency of established methodologies to detect saffron adulteration with plant adulterants, the method developed resulted reliable in assessing the type of adulteration and could be viable for dealing with extensive saffron frauds at a minimum level of 20% (w/w). Copyright © 2014 Elsevier Ltd. All rights reserved.

A technique for estimating the absolute gain of a photomultiplier tube

NASA Astrophysics Data System (ADS)

Takahashi, M.; Inome, Y.; Yoshii, S.; Bamba, A.; Gunji, S.; Hadasch, D.; Hayashida, M.; Katagiri, H.; Konno, Y.; Kubo, H.; Kushida, J.; Nakajima, D.; Nakamori, T.; Nagayoshi, T.; Nishijima, K.; Nozaki, S.; Mazin, D.; Mashuda, S.; Mirzoyan, R.; Ohoka, H.; Orito, R.; Saito, T.; Sakurai, S.; Takeda, J.; Teshima, M.; Terada, Y.; Tokanai, F.; Yamamoto, T.; Yoshida, T.

2018-06-01

Detection of low-intensity light relies on the conversion of photons to photoelectrons, which are then multiplied and detected as an electrical signal. To measure the actual intensity of the light, one must know the factor by which the photoelectrons have been multiplied. To obtain this amplification factor, we have developed a procedure for estimating precisely the signal caused by a single photoelectron. The method utilizes the fact that the photoelectrons conform to a Poisson distribution. The average signal produced by a single photoelectron can then be estimated from the number of noise events, without requiring analysis of the distribution of the signal produced by a single photoelectron. The signal produced by one or more photoelectrons can be estimated experimentally without any assumptions. This technique, and an example of the analysis of a signal from a photomultiplier tube, are described in this study.

PCR Testing of a Ventilated Caging System to Detect Murine Fur Mites

PubMed Central

Jensen, Eric S; Allen, Kenneth P; Henderson, Kenneth S; Szabo, Aniko; Thulin, Joseph D

2013-01-01

Rodents housed in microisolation caging are commonly monitored for infectious agents by the use of soiled bedding sentinels. This strategy relies on the successful transmission of rodent pathogens from the index rodents via soiled bedding to sentinel cages and the subsequent infection or colonization of sentinel rodents. When the prevalence of a pathogen is low or the target agent is not readily transmitted by soiled bedding, alternative testing methodologies should be used. Given the continued prevalence of institutions self-reporting murine fur mites and with the advent of a new sensitive and specific PCR assay for mites, we sought to determine whether the exhaust system of an individual ventilated caging (IVC) system could be used for monitoring the rack's rodent population for mites rather than relying on the responses of sentinels. We deployed single cages of mice (Mus musculus) that were known to be infested with either Radfordia affinis or Myobia musculi on a 70-cage rack, sampled the horizontal exhaust manifolds weekly, and used the new PCR assay to test these samples for mite DNA. We detected the presence of fur mites at a 94.1% probability of detection within 4 wk of placement. Therefore, we recommend swabbing and testing the shelf exhaust manifolds of IVC racks rather than relying on soiled-bedding sentinels as an indicator of the mite status of the rodents on that rack. PMID:23562030

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

Lubeigt, E.; Laboratoire de Mecanique et d'Acoustique, CNRS UPR 7051, 13402 Marseille Cedex 20; Mensah, S.

The fourth generation of nuclear reactor can use liquid sodium as the core coolant. When the reactor is operating, sodium temperatures can reach up to 600 deg. C. During maintenance periods, when the reactor is shut down, the coolant temperature is reduced to 200 deg. C. Because molten sodium is optically opaque, ultrasonic imaging techniques are developed for maintenance activities. Under-sodium imaging aims at i) checking the health of immersed structures. It should also allow ii) to assess component degradation or damage as cracks and shape defects as well as iii) the detection of lost objects. The under-sodium imaging systemmore » has to sustain high temperature (up to 300 deg. C) and hostility of the sodium environment. Furthermore, specific constraints such as transducers characteristics or the limited sensor mobility in the reactor vessel have to be considered. This work focuses on developing a methodology for detecting damages such as crack defects with ultrasound devices. Surface-breaking cracks or deep cracks are sought in the weld area, as welds are more subject to defects. Traditional methods enabled us to detect emerging cracks of submillimeter size with sodium-compatible high-temperature transducer. The presented approach relies on making use of prior knowledge about the environment through the implementation of differential imaging and time-reversal techniques. Indeed, this approach allows to detect a change by comparison with a reference measurement and by focusing back to any change in the environment. It is a means of analysis and understanding of the physical phenomena making it possible to design more effective inspection strategies. Difference between the measured signals reveals the acoustic field scattered by a perturbation (a crack for instance), which may occur between periodical measurements. The imaging method relies on the adequate combination of two computed ultrasonic fields, one forward and one adjoint. The adjoint field, which carries the information about the defects, is analogous to a time-reversal operation. One of the interests of the presented method is that the time-reversal operation is not done experimentally but numerically. Numerical simulations have been carried out to validate the practical relevance of this approach. The preliminary numerical results show a nice agreement between the guessed and the actual positions of the defect. After water-tests, in sodium-tests must be done in order to validate the water/sodium transposition. For this purpose, an under-sodium device is under development, which can move the transducers with four degrees of freedom in a 1.5 m{sup 3} sodium pot. (authors)« less