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Sample records for sub-pixel target detection

  1. A BAND SELECTION METHOD FOR SUB-PIXEL TARGET DETECTION IN HYPERSPECTRAL IMAGES BASED ON LABORATORY AND FIELD REFLECTANCE SPECTRAL COMPARISON

    Directory of Open Access Journals (Sweden)

    S. Sharifi hashjin

    2016-06-01

    Full Text Available In recent years, developing target detection algorithms has received growing interest in hyperspectral images. In comparison to the classification field, few studies have been done on dimension reduction or band selection for target detection in hyperspectral images. This study presents a simple method to remove bad bands from the images in a supervised manner for sub-pixel target detection. The proposed method is based on comparing field and laboratory spectra of the target of interest for detecting bad bands. For evaluation, the target detection blind test dataset is used in this study. Experimental results show that the proposed method can improve efficiency of the two well-known target detection methods, ACE and CEM.

  2. Sentinel-2’s Potential for Sub-Pixel Landscape Feature Detection

    Directory of Open Access Journals (Sweden)

    Julien Radoux

    2016-06-01

    Full Text Available Land cover and land use maps derived from satellite remote sensing imagery are critical to support biodiversity and conservation, especially over large areas. With its 10 m to 20 m spatial resolution, Sentinel-2 is a promising sensor for the detection of a variety of landscape features of ecological relevance. However, many components of the ecological network are still smaller than the 10 m pixel, i.e., they are sub-pixel targets that stretch the sensor’s resolution to its limit. This paper proposes a framework to empirically estimate the minimum object size for an accurate detection of a set of structuring landscape foreground/background pairs. The developed method combines a spectral separability analysis and an empirical point spread function estimation for Sentinel-2. The same approach was also applied to Landsat-8 and SPOT-5 (Take 5, which can be considered as similar in terms of spectral definition and spatial resolution, respectively. Results show that Sentinel-2 performs consistently on both aspects. A large number of indices have been tested along with the individual spectral bands and target discrimination was possible in all but one case. Overall, results for Sentinel-2 highlight the critical importance of a good compromise between the spatial and spectral resolution. For instance, the Sentinel-2 roads detection limit was of 3 m and small water bodies are separable with a diameter larger than 11 m. In addition, the analysis of spectral mixtures draws attention to the uneven sensitivity of a variety of spectral indices. The proposed framework could be implemented to assess the fitness for purpose of future sensors within a large range of applications.

  3. Detection of sub-pixel fractures in X-ray dark-field tomography

    Energy Technology Data Exchange (ETDEWEB)

    Lauridsen, Torsten; Feidenhans' l, Robert [University of Copenhagen, Niels Bohr Institute, Copenhagen (Denmark); Willner, Marian; Pfeiffer, Franz [Technische Universitaet Muenchen, Department of Physics and Institute of Medical Engineering, Garching (Germany); Bech, Martin [Lund University, Medical Radiation Physics, Lund (Sweden)

    2015-11-15

    We present a new method for detecting fractures in solid materials below the resolution given by the detector pixel size by using grating-based X-ray interferometry. The technique is particularly useful for detecting sub-pixel cracks in large samples where the size of the sample is preventing high-resolution μCT studies of the entire sample. The X-ray grating interferometer produces three distinct modality signals: absorption, phase and dark field. The method utilizes the unique scattering features of the dark-field signal. We have used tomograms reconstructed from each of the three signals to detect cracks in a model sample consisting of stearin. (orig.)

  4. Comparison of three sub-pixel computation approaches

    Science.gov (United States)

    Zhao, An; Zheng, Lin; Jiang, Meixin

    2005-10-01

    Sub-pixel classification is a tough issue in remote sensing field. Although many kinds of software or its Module can be used to address this problem, their rationale, algorithms and methodologies are different, resulting in different use of different method for different purpose. This makes many users feel confused when they want to detect mixed feature content within a pixel and to use sub-pixel approach for practical application. It is necessary to make an in-depth comparison study for different sub-pixel methods in order for RS&GIS users to choose proper sub-pixel methods for their specific applications. After reviewing the basic theories and methods in dealing with sub-pixels, this paper made an introductory analysis to their principles, algorithms, parameters and computing process of three sub-pixel calculation methods, or Linear Unmixing in platform ILWIS3.0, Erdas8.5's Sub-pixel Classifier, eCognition3.0's Nearest Neighbor. A case study of three sub-pixel methods was then made of flood monitoring in Poyang Lake region of P.R.China with image data of band-1 and band-2 of NOAA AVHRR image. Finally, a theoretic, technological and practical comparison study was made of these three sub-pixel methods in aspects of the basic principles, the parameters to be set, the suitable application fields and their respective use limitation. Opinions and comments were presented in the end on the use of the sub-pixel calculation results of these three methods in a hope to provide some reference to future sub-pixel application study for the researchers in interest.

  5. Exploring the limits of identifying sub-pixel thermal features using ASTER TIR data

    Science.gov (United States)

    Vaughan, R.G.; Keszthelyi, L.P.; Davies, A.G.; Schneider, D.J.; Jaworowski, C.; Heasler, H.

    2010-01-01

    Understanding the characteristics of volcanic thermal emissions and how they change with time is important for forecasting and monitoring volcanic activity and potential hazards. Satellite instruments view volcanic thermal features across the globe at various temporal and spatial resolutions. Thermal features that may be a precursor to a major eruption, or indicative of important changes in an on-going eruption can be subtle, making them challenging to reliably identify with satellite instruments. The goal of this study was to explore the limits of the types and magnitudes of thermal anomalies that could be detected using satellite thermal infrared (TIR) data. Specifically, the characterization of sub-pixel thermal features with a wide range of temperatures is considered using ASTER multispectral TIR data. First, theoretical calculations were made to define a "thermal mixing detection threshold" for ASTER, which quantifies the limits of ASTER's ability to resolve sub-pixel thermal mixing over a range of hot target temperatures and % pixel areas. Then, ASTER TIR data were used to model sub-pixel thermal features at the Yellowstone National Park geothermal area (hot spring pools with temperatures from 40 to 90 ??C) and at Mount Erebus Volcano, Antarctica (an active lava lake with temperatures from 200 to 800 ??C). Finally, various sources of uncertainty in sub-pixel thermal calculations were quantified for these empirical measurements, including pixel resampling, atmospheric correction, and background temperature and emissivity assumptions.

  6. Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data

    Science.gov (United States)

    2012-09-01

    Santa Barbara, 2007 Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN REMOTE SENSING INTELLIGENCE...David Trask Second Reader Dan Boger Chair, Department of Information Sciences iv THIS PAGE INTENTIONALLY LEFT BLANK v ABSTRACT Due...days as a navy mine-sweeping team searched the river. No 6 mine was ever found and the threat was deemed a hoax , but the cost to maritime shipping

  7. Sub-pixel mineral mapping using EO-1 Hyperion hyperspectral data

    Science.gov (United States)

    Kumar, C.; Shetty, A.; Raval, S.; Champatiray, P. K.; Sharma, R.

    2014-11-01

    This study describes the utility of Earth Observation (EO)-1 Hyperion data for sub-pixel mineral investigation using Mixture Tuned Target Constrained Interference Minimized Filter (MTTCIMF) algorithm in hostile mountainous terrain of Rajsamand district of Rajasthan, which hosts economic mineralization such as lead, zinc, and copper etc. The study encompasses pre-processing, data reduction, Pixel Purity Index (PPI) and endmember extraction from reflectance image of surface minerals such as illite, montmorillonite, phlogopite, dolomite and chlorite. These endmembers were then assessed with USGS mineral spectral library and lab spectra of rock samples collected from field for spectral inspection. Subsequently, MTTCIMF algorithm was implemented on processed image to obtain mineral distribution map of each detected mineral. A virtual verification method has been adopted to evaluate the classified image, which uses directly image information to evaluate the result and confirm the overall accuracy and kappa coefficient of 68 % and 0.6 respectively. The sub-pixel level mineral information with reasonable accuracy could be a valuable guide to geological and exploration community for expensive ground and/or lab experiments to discover economic deposits. Thus, the study demonstrates the feasibility of Hyperion data for sub-pixel mineral mapping using MTTCIMF algorithm with cost and time effective approach.

  8. Sub-pixel mineral mapping using EO-1 Hyperion hyperspectral data

    OpenAIRE

    Kumar, C.; Shetty, A.; S Raval; Champatiray, P. K.; Sharma, R.

    2014-01-01

    This study describes the utility of Earth Observation (EO)-1 Hyperion data for sub-pixel mineral investigation using Mixture Tuned Target Constrained Interference Minimized Filter (MTTCIMF) algorithm in hostile mountainous terrain of Rajsamand district of Rajasthan, which hosts economic mineralization such as lead, zinc, and copper etc. The study encompasses pre-processing, data reduction, Pixel Purity Index (PPI) and endmember extraction from reflectance image of surface minerals su...

  9. Sub-pixel Area Calculation Methods for Estimating Irrigated Areas

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    Suraj Pandey

    2007-10-01

    Full Text Available The goal of this paper was to develop and demonstrate practical methods forcomputing sub-pixel areas (SPAs from coarse-resolution satellite sensor data. Themethods were tested and verified using: (a global irrigated area map (GIAM at 10-kmresolution based, primarily, on AVHRR data, and (b irrigated area map for India at 500-mbased, primarily, on MODIS data. The sub-pixel irrigated areas (SPIAs from coarse-resolution satellite sensor data were estimated by multiplying the full pixel irrigated areas(FPIAs with irrigated area fractions (IAFs. Three methods were presented for IAFcomputation: (a Google Earth Estimate (IAF-GEE; (b High resolution imagery (IAF-HRI; and (c Sub-pixel de-composition technique (IAF-SPDT. The IAF-GEE involvedthe use of “zoom-in-views” of sub-meter to 4-meter very high resolution imagery (VHRIfrom Google Earth and helped determine total area available for irrigation (TAAI or netirrigated areas that does not consider intensity or seasonality of irrigation. The IAF-HRI isa well known method that uses finer-resolution data to determine SPAs of the coarser-resolution imagery. The IAF-SPDT is a unique and innovative method wherein SPAs aredetermined based on the precise location of every pixel of a class in 2-dimensionalbrightness-greenness-wetness (BGW feature-space plot of red band versus near-infraredband spectral reflectivity. The SPIAs computed using IAF-SPDT for the GIAM was within2 % of the SPIA computed using well known IAF-HRI. Further the fractions from the 2 methods were significantly correlated. The IAF-HRI and IAF-SPDT help to determine annualized or gross irrigated areas (AIA that does consider intensity or seasonality (e.g., sum of areas from season 1, season 2, and continuous year-round crops. The national census based irrigated areas for the top 40 irrigated nations (which covers about 90% of global irrigation was significantly better related (and had lesser uncertainties and errors when

  10. 2D Sub-Pixel Disparity Measurement Using QPEC / Medicis

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    M. Cournet

    2016-06-01

    Full Text Available In the frame of its earth observation missions, CNES created a library called QPEC, and one of its launcher called Medicis. QPEC / Medicis is a sub-pixel two-dimensional stereo matching algorithm that works on an image pair. This tool is a block matching algorithm, which means that it is based on a local method. Moreover it does not regularize the results found. It proposes several matching costs, such as the Zero mean Normalised Cross-Correlation or statistical measures (the Mutual Information being one of them, and different match validation flags. QPEC / Medicis is able to compute a two-dimensional dense disparity map with a subpixel precision. Hence, it is more versatile than disparity estimation methods found in computer vision literature, which often assume an epipolar geometry. CNES uses Medicis, among other applications, during the in-orbit image quality commissioning of earth observation satellites. For instance the Pléiades-HR 1A & 1B and the Sentinel-2 geometric calibrations are based on this block matching algorithm. Over the years, it has become a common tool in ground segments for in-flight monitoring purposes. For these two kinds of applications, the two-dimensional search and the local sub-pixel measure without regularization can be essential. This tool is also used to generate automatic digital elevation models, for which it was not initially dedicated. This paper deals with the QPEC / Medicis algorithm. It also presents some of its CNES applications (in-orbit commissioning, in flight monitoring or digital elevation model generation. Medicis software is distributed outside the CNES as well. This paper finally describes some of these external applications using Medicis, such as ground displacement measurement, or intra-oral scanner in the dental domain.

  11. Sub-pixel measurement system for grid's width and period based on an improved partial area effect

    Science.gov (United States)

    Zhu, Feijia; Jin, Peng

    2017-12-01

    Based on the partial area effect of charge-coupled device (CCD), a sub-pixel line detecting algorithm is proposed to measure the width and the period of a metal grid. An optical pointing system is developed and applied to accurately measure the line-width and the period of a grid. The grid's moving image is captured by the developed system. From the obtained images, one can determine position of a line with sub-pixel resolution. By controlling the grid's movement and aiming at the grid, the absolute coordinates of a grating ruler are obtained. Simulated calculations and experiments are performed with recorded video images to validate the performance of the proposed algorithm. The results show that the precision of the proposed estimation algorithm can reach 0.025 pixels for a moving image.

  12. Sub-pixel analysis to enhance the accuracy of evapotranspiration determined using MODIS images

    National Research Council Canada - National Science Library

    Abdalhaleem A Hassaballa; Abdul-Nasir Matori; Khalid A Al-Gaadi; Elkamil H Tola; Rangaswamy Madugundu

    2017-01-01

    ...) were recorded at the time of satellite overpass. In order to enhance the accuracy of the generated ET maps, MODIS images were subjected to sub-pixel analysis by assigning weights for different land surface cover...

  13. Thorough statistical comparison of machine learning regression models and their ensembles for sub-pixel imperviousness and imperviousness change mapping

    Science.gov (United States)

    Drzewiecki, Wojciech

    2017-12-01

    We evaluated the performance of nine machine learning regression algorithms and their ensembles for sub-pixel estimation of impervious areas coverages from Landsat imagery. The accuracy of imperviousness mapping in individual time points was assessed based on RMSE, MAE and R2. These measures were also used for the assessment of imperviousness change intensity estimations. The applicability for detection of relevant changes in impervious areas coverages at sub-pixel level was evaluated using overall accuracy, F-measure and ROC Area Under Curve. The results proved that Cubist algorithm may be advised for Landsat-based mapping of imperviousness for single dates. Stochastic gradient boosting of regression trees (GBM) may be also considered for this purpose. However, Random Forest algorithm is endorsed for both imperviousness change detection and mapping of its intensity. In all applications the heterogeneous model ensembles performed at least as well as the best individual models or better. They may be recommended for improving the quality of sub-pixel imperviousness and imperviousness change mapping. The study revealed also limitations of the investigated methodology for detection of subtle changes of imperviousness inside the pixel. None of the tested approaches was able to reliably classify changed and non-changed pixels if the relevant change threshold was set as one or three percent. Also for fi ve percent change threshold most of algorithms did not ensure that the accuracy of change map is higher than the accuracy of random classifi er. For the threshold of relevant change set as ten percent all approaches performed satisfactory.

  14. Implementation and optimization of sub-pixel motion estimation on BWDSP platform

    Science.gov (United States)

    Jia, Shangzhu; Lang, Wenhui; Zeng, Feiyang; Liu, Yufu

    2017-08-01

    Sub-pixel Motion estimation algorithm is a key technology in video coding inter-frame prediction algorithm, which has important influence on video coding performance. In the latest video coding standard H.265/HEVC, interpolation filters based on DCT are used to Sub-pixel motion estimation, but it has very high computation complexity. In order to ensure the real-time performance of hardware coding, we combine the characteristics of BWDSP architecture, using code level optimization techniques to realize the sub-pixel motion estimation algorithm. Experimental results demonstrate that In the BWDSP simulation environment, the proposed method significantly decreases the running clock cycle and thus improves the performance of the encoder.

  15. Simulating urban land cover changes at sub-pixel level in a coastal city

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    Zhao, Xiaofeng; Deng, Lei; Feng, Huihui; Zhao, Yanchuang

    2014-10-01

    The simulation of urban expansion or land cover changes is a major theme in both geographic information science and landscape ecology. Yet till now, almost all of previous studies were based on grid computations at pixel level. With the prevalence of spectral mixture analysis in urban land cover research, the simulation of urban land cover at sub-pixel level is being put into agenda. This study provided a new approach of land cover simulation at sub-pixel level. Landsat TM/ETM+ images of Xiamen city, China on both the January of 2002 and 2007 were used to acquire land cover data through supervised classification. Then the two classified land cover data were utilized to extract the transformation rule between 2002 and 2007 using logistic regression. The transformation possibility of each land cover type in a certain pixel was taken as its percent in the same pixel after normalization. And cellular automata (CA) based grid computation was carried out to acquire simulated land cover on 2007. The simulated 2007 sub-pixel land cover was testified with a validated sub-pixel land cover achieved by spectral mixture analysis in our previous studies on the same date. And finally the sub-pixel land cover of 2017 was simulated for urban planning and management. The results showed that our method is useful in land cover simulation at sub-pixel level. Although the simulation accuracy is not quite satisfactory for all the land cover types, it provides an important idea and a good start in the CA-based urban land cover simulation.

  16. Radial lens distortion correction with sub-pixel accuracy for X-ray micro-tomography.

    Science.gov (United States)

    Vo, Nghia T; Atwood, Robert C; Drakopoulos, Michael

    2015-12-14

    Distortion correction or camera calibration for an imaging system which is highly configurable and requires frequent disassembly for maintenance or replacement of parts needs a speedy method for recalibration. Here we present direct techniques for calculating distortion parameters of a non-linear model based on the correct determination of the center of distortion. These techniques are fast, very easy to implement, and accurate at sub-pixel level. The implementation at the X-ray tomography system of the I12 beamline, Diamond Light Source, which strictly requires sub-pixel accuracy, shows excellent performance in the calibration image and in the reconstructed images.

  17. Sub-Pixel Magnetic Field and Plasma Dynamics Derived from Photospheric Spectral Data

    Science.gov (United States)

    Rasca, Anthony P.; Chen, James; Pevtsov, Alexei A.

    2017-08-01

    Current high-resolution observations of the photosphere show small dynamic features at the resolving limit during emerging flux events. However, line-of-sight (LOS) magnetogram pixels only contain the net uncanceled magnetic flux, which is expected to increase for fixed regions as resolution limits improve. Using a new method with spectrographic images, we quantify distortions in photospheric absorption (or emission) lines caused by sub-pixel magnetic field and plasma dynamics in the vicinity of active regions and emerging flux events. Absorption lines—quantified by their displacement, width, asymmetry, and peakedness—have previously been used with Stokes I images from SOLIS/VSM to relate line distortions with sub-pixel plasma dynamics driven by solar flares or small-scale flux ropes. The method is extended to include the full Stokes parameters and relate inferred sub-pixel dynamics with small-scale magnetic fields. Our analysis is performed on several sets of spectrographic images taken by SOLIS/VSM while observing eruptive and non-eruptive active regions. We discuss the results of this application and their relevance for understanding magnetic fields signatures and coupled plasma properties on sub-pixel scales.

  18. Estimation of sub-pixel water area on Tibet plateau using multiple endmembers spectral mixture spectral analysis from MODIS data

    Science.gov (United States)

    Cui, Qian; Shi, Jiancheng; Xu, Yuanliu

    2011-12-01

    Water is the basic needs for human society, and the determining factor of stability of ecosystem as well. There are lots of lakes on Tibet Plateau, which will lead to flood and mudslide when the water expands sharply. At present, water area is extracted from TM or SPOT data for their high spatial resolution; however, their temporal resolution is insufficient. MODIS data have high temporal resolution and broad coverage. So it is valuable resource for detecting the change of water area. Because of its low spatial resolution, mixed-pixels are common. In this paper, four spectral libraries are built using MOD09A1 product, based on that, water body is extracted in sub-pixels utilizing Multiple Endmembers Spectral Mixture Analysis (MESMA) using MODIS daily reflectance data MOD09GA. The unmixed result is comparing with contemporaneous TM data and it is proved that this method has high accuracy.

  19. Robust Matching of Wavelet Features for Sub-Pixel Registration of Landsat Data

    Science.gov (United States)

    LeMoigne, Jacqueline; Netanyahu, Nathan S.; Masek, Jeffrey G.; Mount, David M.; Goward, Samuel; Zukor, Dorothy (Technical Monitor)

    2001-01-01

    For many Earth and Space Science applications, automatic geo-registration at sub-pixel accuracy has become a necessity. In this work, we are focusing on building an operational system, which will provide a sub-pixel accuracy registration of Landsat-5 and Landsat-7 data. The input to our registration method consists of scenes that have been geometrically and radiometrically corrected. Such pre-processed scenes are then geo-registered relative to a database of Landsat chips. The method assumes a transformation composed of a rotation and a translation, and utilizes rotation- and translation-invariant wavelets to extract image features that are matched using statistically robust feature matching and a generalized Hausdorff distance metric. The registration process is described and results on four Landsat input scenes of the Washington, D.C. area are presented.

  20. Autonomous Sub-Pixel Satellite Track Endpoint Determination for Space Based Images

    Energy Technology Data Exchange (ETDEWEB)

    Simms, L M

    2011-03-07

    An algorithm for determining satellite track endpoints with sub-pixel resolution in spaced-based images is presented. The algorithm allows for significant curvature in the imaged track due to rotation of the spacecraft capturing the image. The motivation behind the subpixel endpoint determination is first presented, followed by a description of the methodology used. Results from running the algorithm on real ground-based and simulated spaced-based images are shown to highlight its effectiveness.

  1. Variability of myocardial perfusion dark rim Gibbs artifacts due to sub-pixel shifts

    Directory of Open Access Journals (Sweden)

    Kellman Peter

    2009-05-01

    Full Text Available Abstract Background Gibbs ringing has been shown as a possible source of dark rim artifacts in myocardial perfusion studies. This type of artifact is usually described as transient, lasting a few heart beats, and localised in random segments of the myocardial wall. Dark rim artifacts are known to be unpredictably variable. This article aims to illustrate that a sub-pixel shift, i.e. a small displacement of the pixels with respect to the endocardial border, can result in different Gibbs ringing and hence different artifacts. Therefore a hypothesis for one cause of dark rim artifact variability is given based on the sub-pixel position of the endocardial border. This article also demonstrates the consequences for Gibbs artifacts when two different methods of image interpolation are applied (post-FFT interpolation, and pre-FFT zero-filling. Results Sub-pixel shifting of in vivo perfusion studies was shown to change the appearance of Gibbs artifacts. This effect was visible in the original uninterpolated images, and in the post-FFT interpolated images. The same shifted data interpolated by pre-FFT zero-filling exhibited much less variability in the Gibbs artifact. The in vivo findings were confirmed by phantom imaging and numerical simulations. Conclusion Unless pre-FFT zero-filling interpolation is performed, Gibbs artifacts are very dependent on the position of the subendocardial wall within the pixel. By introducing sub-pixel shifts relative to the endocardial border, some of the variability of the dark rim artifacts in different myocardial segments, in different patients and from frame to frame during first-pass perfusion due to cardiac and respiratory motion can be explained. Image interpolation by zero-filling can be used to minimize this dependency.

  2. Improved Surface Reflectance from Remote Sensing Data with Sub-Pixel Topographic Information

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    Laure Roupioz

    2014-10-01

    Full Text Available Several methods currently exist to efficiently correct topographic effects on the radiance measured by satellites. Most of those methods use topographic information and satellite data at the same spatial resolution. In this study, the 30 m spatial resolution data of the Digital Elevation Model (DEM from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer are used to account for those topographic effects when retrieving land surface reflectance from satellite data at lower spatial resolution (e.g., 1 km. The methodology integrates the effects of sub-pixel topography on the estimation of the total irradiance received at the surface considering direct, diffuse and terrain irradiance. The corrected total irradiance is then used to compute the topographically corrected surface reflectance. The proposed method has been developed to be applied on various kilometric pixel size satellite data. In this study, it was tested and validated with synthetic Landsat data aggregated at 1 km. The results obtained after a sub-pixel topographic correction are compared with the ones obtained after a pixel level topographic correction and show that in rough terrain, the sub-pixel topography correction method provides better results even if it tends to slightly overestimate the retrieved land surface reflectance in some cases.

  3. Sub-Pixel Classification of MODIS EVI for Annual Mappings of Impervious Surface Areas

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    Narumasa Tsutsumida

    2016-02-01

    Full Text Available Regular monitoring of expanding impervious surfaces areas (ISAs in urban areas is highly desirable. MODIS data can meet this demand in terms of frequent observations but are lacking in spatial detail, leading to the mixed land cover problem when per-pixel classifications are applied. To overcome this issue, this research develops and applies a spatio-temporal sub-pixel model to estimate ISAs on an annual basis during 2001–2013 in the Jakarta Metropolitan Area, Indonesia. A Random Forest (RF regression inferred the ISA proportion from annual 23 values of MODIS MOD13Q1 EVI and reference data in which such proportion was visually allocated from very high-resolution images in Google Earth over time at randomly selected locations. Annual maps of ISA proportion were generated and showed an average increase of 30.65 km2/year over 13 years. For comparison, a series of RF per-pixel classifications were also developed from the same reference data using a Boolean class constructed from different thresholds of ISA proportion. Results from per-pixel models varied when such thresholds change, suggesting difficulty of estimation of actual ISAs. This research demonstrated the advantages of spatio-temporal sub-pixel analysis for annual ISAs mapping and addresses the problem associated with definitions of thresholds in per-pixel approaches.

  4. Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis

    Directory of Open Access Journals (Sweden)

    Carlos Augusto Zangrando Toneli

    2011-09-01

    Full Text Available Sub-pixel analysis is capable of generating continuous fields, which represent the spatial variability of certain thematic classes. The aim of this work was to develop numerical models to represent the variability of tree cover and bare surfaces within the study area. This research was conducted in the riparian buffer within a watershed of the São Francisco River in the North of Minas Gerais, Brazil. IKONOS and Landsat TM imagery were used with the GUIDE algorithm to construct the models. The results were two index images derived with regression trees for the entire study area, one representing tree cover and the other representing bare surface. The use of non-parametric and non-linear regression tree models presented satisfactory results to characterize wetland, deciduous and savanna patterns of forest formation.

  5. Evaluating Fourier Cross-Correlation Sub-Pixel Registration in Landsat Images

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    Jaime Almonacid-Caballer

    2017-10-01

    Full Text Available Multi-temporal analysis is one of the main applications of remote sensing, and Landsat imagery has been one of the main resources for many years. However, the moderate spatial resolution (30 m restricts their use for high precision applications. In this paper, we simulate Landsat scenes to evaluate, by means of an exhaustive number of tests, a subpixel registration process based on phase correlation and the upsampling of the Fourier transform. From a high resolution image (0.5 m, two sets of 121 synthetic images of fixed translations are created to simulate Landsat scenes (30 m. In this sense, the use of the point spread function (PSF of the Landsat TM (Thematic Mapper sensor in the downsampling process improves the results compared to those obtained by simple averaging. In the process of obtaining sub-pixel accuracy by upsampling the cross correlation matrix by a certain factor, the limit of improvement is achieved at 0.1 pixels. We show that image size affects the cross correlation results, but for images equal or larger than 100 × 100 pixels similar accuracies are expected. The large dataset used in the tests allows us to describe the intra-pixel distribution of the errors obtained in the registration process and how they follow a waveform instead of random/stochastic behavior. The amplitude of this waveform, representing the highest expected error, is estimated at 1.88 m. Finally, a validation test is performed over a set of sub-pixel shorelines obtained from actual Landsat-5 TM, Landsat-7 ETM+ (Enhanced Thematic Mapper Plus and Landsat-8 OLI (Operation Land Imager scenes. The evaluation of the shoreline accuracy with respect to permanent seawalls, before and after the registration, shows the importance of the registering process and serves as a non-synthetic validation test that reinforce previous results.

  6. Simulation of urban land surface temperature based on sub-pixel land cover in a coastal city

    Science.gov (United States)

    Zhao, Xiaofeng; Deng, Lei; Feng, Huihui; Zhao, Yanchuang

    2014-11-01

    The sub-pixel urban land cover has been proved to have obvious correlations with land surface temperature (LST). Yet these relationships have seldom been used to simulate LST. In this study we provided a new approach of urban LST simulation based on sub-pixel land cover modeling. Landsat TM/ETM+ images of Xiamen city, China on both the January of 2002 and 2007 were used to acquire land cover and then extract the transformation rule using logistic regression. The transformation possibility was taken as its percent in the same pixel after normalization. And cellular automata were used to acquire simulated sub-pixel land cover on 2007 and 2017. On the other hand, the correlations between retrieved LST and sub-pixel land cover achieved by spectral mixture analysis in 2002 were examined and a regression model was built. Then the regression model was used on simulated 2007 land cover to model the LST of 2007. Finally the LST of 2017 was simulated for urban planning and management. The results showed that our method is useful in LST simulation. Although the simulation accuracy is not quite satisfactory, it provides an important idea and a good start in the modeling of urban LST.

  7. Characterizing sub-pixel landsat ETM plus fire severity on experimental fires in the Kruger National Park, South Africa

    CSIR Research Space (South Africa)

    Landmann, T

    2003-07-01

    Full Text Available Burn severity was quantitatively mapped using a unique linear spectral mixture model to determine sub-pixel abundances of different ashes and combustion completeness measured on the corresponding fire-affected pixels in Landsat data. A new burn...

  8. Sub-pixel localisation of passive micro-coil fiducial markers in interventional MRI.

    Science.gov (United States)

    Rea, Marc; McRobbie, Donald; Elhawary, Haytham; Tse, Zion T H; Lamperth, Michael; Young, Ian

    2009-04-01

    Electromechanical devices enable increased accuracy in surgical procedures, and the recent development of MRI-compatible mechatronics permits the use of MRI for real-time image guidance. Integrated imaging of resonant micro-coil fiducials provides an accurate method of tracking devices in a scanner with increased flexibility compared to gradient tracking. Here we report on the ability of ten different image-processing algorithms to track micro-coil fiducials with sub-pixel accuracy. Five algorithms: maximum pixel, barycentric weighting, linear interpolation, quadratic fitting and Gaussian fitting were applied both directly to the pixel intensity matrix and to the cross-correlation matrix obtained by 2D convolution with a reference image. Using images of a 3 mm fiducial marker and a pixel size of 1.1 mm, intensity linear interpolation, which calculates the position of the fiducial centre by interpolating the pixel data to find the fiducial edges, was found to give the best performance for minimal computing power; a maximum error of 0.22 mm was observed in fiducial localisation for displacements up to 40 mm. The inherent standard deviation of fiducial localisation was 0.04 mm. This work enables greater accuracy to be achieved in passive fiducial tracking.

  9. Spectral Unmixing Applied to Desert Soils for the Detection of Sub-Pixel Disturbances

    Science.gov (United States)

    2012-09-01

    scattering and absorption (From Olsen, 2007). ....4 Figure 2. This figure from http://www.astro.cornell.edu/ academics /courses/astro201...spectral regions that are illustrated in Figure 2 (Elachi and Van Zyl, 2006). Figure 2. This figure from http://www.astro.cornell.edu/ academics ...gopher till values 0.0419, 0.026, 0.073, home hill clay values 0.092, 0.0087, 0.137, and hard picnic area clay values 0.0805, 0.154, 0.000 (flat

  10. The Bering Autonomous Target Detection

    DEFF Research Database (Denmark)

    Jørgensen, John Leif; Denver, Troelz; Betto, Maurizio

    2003-01-01

    An autonomous asteroid target detection and tracking method has been developed. The method features near omnidirectionality and focus on high speed operations and completeness of search of the near space rather than the traditional faint object search methods, employed presently at the larger...... telescopes. The method has proven robust in operation and is well suited for use onboard spacecraft. As development target for the method and the associated instrumentation the asteroid research mission Bering has been used. Onboard a spacecraft, the autonomous detection is centered around the fully...... autonomous star tracker the Advanced Stellar Compass (ASC). One feature of this instrument is that potential targets are registered directly in terms of date, right ascension, declination, and intensity, which greatly facilitates both tracking search and registering. Results from ground and inflight tests...

  11. DONUTS: A science frame autoguiding algorithm with sub-pixel precision, capable of guiding on defocused stars

    OpenAIRE

    McCormac, J.; Pollacco, D.; Skillen, I.; Faedi, F.; Todd, I.; Watson, C. A.

    2013-01-01

    We present the DONUTS autoguiding algorithm, designed to fix stellar positions at the sub-pixel level for high-cadence time-series photometry, which is also capable of autoguiding on defocused stars. DONUTS was designed to calculate guide corrections from a series of science images and re-centre telescope pointing between each exposure. The algorithm has the unique ability of calculating guide corrections from under-sampled to heavily defocused point spread functions. We present the case for ...

  12. Quantifying Sub-Pixel Surface Water Coverage in Urban Environments Using Low-Albedo Fraction from Landsat Imagery

    OpenAIRE

    Weiwei Sun; Bo Du; Shaolong Xiong

    2017-01-01

    The problem of mixed pixels negatively affects the delineation of accurate surface water in Landsat Imagery. Linear spectral unmixing has been demonstrated to be a powerful technique for extracting surface materials at a sub-pixel scale. Therefore, in this paper, we propose an innovative low albedo fraction (LAF) method based on the idea of unconstrained linear spectral unmixing. The LAF stands on the “High Albedo-Low Albedo-Vegetation” model of spectral unmixing analysis in urban environment...

  13. DONUTS: A Science Frame Autoguiding Algorithm with Sub-Pixel Precision, Capable of Guiding on Defocused Stars

    Science.gov (United States)

    McCormac, J.; Pollacco, D.; Skillen, I.; Faedi, F.; Todd, I.; Watson, C. A.

    2013-05-01

    We present the DONUTS autoguiding algorithm, designed to fix stellar positions at the sub-pixel level for high-cadence time-series photometry, and also capable of autoguiding on defocused stars. DONUTS was designed to calculate guide corrections from a series of science images and recentre telescope pointing between each exposure. The algorithm has the unique ability of calculating guide corrections from undersampled to heavily defocused point spread functions. We present the case for why such an algorithm is important for high precision photometry and give our results from off and on-sky testing. We discuss the limitations of DONUTS and the facilities where it soon will be deployed.

  14. Mapping the Spatial Distribution of Winter Crops at Sub-Pixel Level Using AVHRR NDVI Time Series and Neural Nets

    Directory of Open Access Journals (Sweden)

    Felix Rembold

    2013-03-01

    Full Text Available For large areas, it is difficult to assess the spatial distribution and inter-annual variation of crop acreages through field surveys. Such information, however, is of great value for governments, land managers, planning authorities, commodity traders and environmental scientists. Time series of coarse resolution imagery offer the advantage of global coverage at low costs, and are therefore suitable for large-scale crop type mapping. Due to their coarse spatial resolution, however, the problem of mixed pixels has to be addressed. Traditional hard classification approaches cannot be applied because of sub-pixel heterogeneity. We evaluate neural networks as a modeling tool for sub-pixel crop acreage estimation. The proposed methodology is based on the assumption that different cover type proportions within coarse pixels prompt changes in time profiles of remotely sensed vegetation indices like the Normalized Difference Vegetation Index (NDVI. Neural networks can learn the relation between temporal NDVI signatures and the sought crop acreage information. This learning step permits a non-linear unmixing of the temporal information provided by coarse resolution satellite sensors. For assessing the feasibility and accuracy of the approach, a study region in central Italy (Tuscany was selected. The task consisted of mapping the spatial distribution of winter crops abundances within 1 km AVHRR pixels between 1988 and 2001. Reference crop acreage information for network training and validation was derived from high resolution Thematic Mapper/Enhanced Thematic Mapper (TM/ETM+ images and official agricultural statistics. Encouraging results were obtained demonstrating the potential of the proposed approach. For example, the spatial distribution of winter crop acreage at sub-pixel level was mapped with a cross-validated coefficient of determination of 0.8 with respect to the reference information from high resolution imagery. For the eight years for which

  15. An autocorrelation-based method for improvement of sub-pixel displacement estimation in ultrasound strain imaging.

    Science.gov (United States)

    Kim, Seungsoo; Aglyamov, Salavat R; Park, Suhyun; O'Donnell, Matthew; Emelianov, Stanislav Y

    2011-04-01

    In ultrasound strain and elasticity imaging, an accurate and cost-effective sub-pixel displacement estimator is required because strain/elasticity imaging quality relies on the displacement SNR, which can often be higher if more computational resources are provided. In this paper, we introduce an autocorrelation-based method to cost-effectively improve subpixel displacement estimation quality. To quantitatively evaluate the performance of the autocorrelation method, simulated and tissue-mimicking phantom experiments were performed. The computational cost of the autocorrelation method is also discussed. The results of our study suggest the autocorrelation method can be used for a real-time elasticity imaging system. © 2011 IEEE

  16. Quantifying Sub-Pixel Surface Water Coverage in Urban Environments Using Low-Albedo Fraction from Landsat Imagery

    Directory of Open Access Journals (Sweden)

    Weiwei Sun

    2017-05-01

    Full Text Available The problem of mixed pixels negatively affects the delineation of accurate surface water in Landsat Imagery. Linear spectral unmixing has been demonstrated to be a powerful technique for extracting surface materials at a sub-pixel scale. Therefore, in this paper, we propose an innovative low albedo fraction (LAF method based on the idea of unconstrained linear spectral unmixing. The LAF stands on the “High Albedo-Low Albedo-Vegetation” model of spectral unmixing analysis in urban environments, and investigates the urban surface water extraction problem with the low albedo fraction map. Three experiments are carefully designed using Landsat TM/ETM+ images on the three metropolises of Wuhan, Shanghai, and Guangzhou in China, and per-pixel and sub-pixel accuracies are estimated. The results are compared against extraction accuracies from three popular water extraction methods including the normalized difference water index (NDWI, modified normalized difference water index (MNDWI, and automated water extraction index (AWEI. Experimental results show that LAF achieves a better accuracy when extracting urban surface water than both MNDWI and AWEI do, especially in boundary mixed pixels. Moreover, the LAF has the smallest threshold variations among the three methods, and the fraction threshold of 1 is a proper choice for LAF to obtain good extraction results. Therefore, the LAF is a promising approach for extracting urban surface water coverage.

  17. Color capable sub-pixel resolving optofluidic microscope and its application to blood cell imaging for malaria diagnosis.

    Directory of Open Access Journals (Sweden)

    Seung Ah Lee

    Full Text Available Miniaturization of imaging systems can significantly benefit clinical diagnosis in challenging environments, where access to physicians and good equipment can be limited. Sub-pixel resolving optofluidic microscope (SROFM offers high-resolution imaging in the form of an on-chip device, with the combination of microfluidics and inexpensive CMOS image sensors. In this work, we report on the implementation of color SROFM prototypes with a demonstrated optical resolution of 0.66 µm at their highest acuity. We applied the prototypes to perform color imaging of red blood cells (RBCs infected with Plasmodium falciparum, a particularly harmful type of malaria parasites and one of the major causes of death in the developing world.

  18. Target detection and tracking in infrared video

    Science.gov (United States)

    Deng, Zhihui; Zhu, Jihong

    2017-07-01

    In this paper, we propose a method for target detection and tracking in infrared video. The target is defined by its location and extent in a single frame. In the initialization process, we use an adaptive threshold to segment the target and then extract the fern feature and normalize it as a template. The detector uses the random forest and fern to detect the target in the infrared video. The random forest and fern is a random combination of 2bit Binary Pattern, which is robust to infrared targets with blurred and unknown contours. The tracker uses the gray-value weighted mean-Shift algorithm to track the infrared target which is always brighter than the background. And the tracker can track the deformed target efficiently and quickly. When the target disappears, the detector will redetect the target in the coming infrared image. Finally, we verify the algorithm on the real-time infrared target detection and tracking platform. The result shows that our algorithm performs better than TLD in terms of recall and runtime in infrared video.

  19. Automated Multi-Peak Tracking Kymography (AMTraK: A Tool to Quantify Sub-Cellular Dynamics with Sub-Pixel Accuracy.

    Directory of Open Access Journals (Sweden)

    Anushree R Chaphalkar

    Full Text Available Kymographs or space-time plots are widely used in cell biology to reduce the dimensions of a time-series in microscopy for both qualitative and quantitative insight into spatio-temporal dynamics. While multiple tools for image kymography have been described before, quantification remains largely manual. Here, we describe a novel software tool for automated multi-peak tracking kymography (AMTraK, which uses peak information and distance minimization to track and automatically quantify kymographs, integrated in a GUI. The program takes fluorescence time-series data as an input and tracks contours in the kymographs based on intensity and gradient peaks. By integrating a branch-point detection method, it can be used to identify merging and splitting events of tracks, important in separation and coalescence events. In tests with synthetic images, we demonstrate sub-pixel positional accuracy of the program. We test the program by quantifying sub-cellular dynamics in rod-shaped bacteria, microtubule (MT transport and vesicle dynamics. A time-series of E. coli cell division with labeled nucleoid DNA is used to identify the time-point and rate at which the nucleoid segregates. The mean velocity of microtubule (MT gliding motility due to a recombinant kinesin motor is estimated as 0.5 μm/s, in agreement with published values, and comparable to estimates using software for nanometer precision filament-tracking. We proceed to employ AMTraK to analyze previously published time-series microscopy data where kymographs had been manually quantified: clathrin polymerization kinetics during vesicle formation and anterograde and retrograde transport in axons. AMTraK analysis not only reproduces the reported parameters, it also provides an objective and automated method for reproducible analysis of kymographs from in vitro and in vivo fluorescence microscopy time-series of sub-cellular dynamics.

  20. Automated Multi-Peak Tracking Kymography (AMTraK): A Tool to Quantify Sub-Cellular Dynamics with Sub-Pixel Accuracy.

    Science.gov (United States)

    Chaphalkar, Anushree R; Jain, Kunalika; Gangan, Manasi S; Athale, Chaitanya A

    2016-01-01

    Kymographs or space-time plots are widely used in cell biology to reduce the dimensions of a time-series in microscopy for both qualitative and quantitative insight into spatio-temporal dynamics. While multiple tools for image kymography have been described before, quantification remains largely manual. Here, we describe a novel software tool for automated multi-peak tracking kymography (AMTraK), which uses peak information and distance minimization to track and automatically quantify kymographs, integrated in a GUI. The program takes fluorescence time-series data as an input and tracks contours in the kymographs based on intensity and gradient peaks. By integrating a branch-point detection method, it can be used to identify merging and splitting events of tracks, important in separation and coalescence events. In tests with synthetic images, we demonstrate sub-pixel positional accuracy of the program. We test the program by quantifying sub-cellular dynamics in rod-shaped bacteria, microtubule (MT) transport and vesicle dynamics. A time-series of E. coli cell division with labeled nucleoid DNA is used to identify the time-point and rate at which the nucleoid segregates. The mean velocity of microtubule (MT) gliding motility due to a recombinant kinesin motor is estimated as 0.5 μm/s, in agreement with published values, and comparable to estimates using software for nanometer precision filament-tracking. We proceed to employ AMTraK to analyze previously published time-series microscopy data where kymographs had been manually quantified: clathrin polymerization kinetics during vesicle formation and anterograde and retrograde transport in axons. AMTraK analysis not only reproduces the reported parameters, it also provides an objective and automated method for reproducible analysis of kymographs from in vitro and in vivo fluorescence microscopy time-series of sub-cellular dynamics.

  1. PSICIC: noise and asymmetry in bacterial division revealed by computational image analysis at sub-pixel resolution.

    Directory of Open Access Journals (Sweden)

    Jonathan M Guberman

    2008-11-01

    Full Text Available Live-cell imaging by light microscopy has demonstrated that all cells are spatially and temporally organized. Quantitative, computational image analysis is an important part of cellular imaging, providing both enriched information about individual cell properties and the ability to analyze large datasets. However, such studies are often limited by the small size and variable shape of objects of interest. Here, we address two outstanding problems in bacterial cell division by developing a generally applicable, standardized, and modular software suite termed Projected System of Internal Coordinates from Interpolated Contours (PSICIC that solves common problems in image quantitation. PSICIC implements interpolated-contour analysis for accurate and precise determination of cell borders and automatically generates internal coordinate systems that are superimposable regardless of cell geometry. We have used PSICIC to establish that the cell-fate determinant, SpoIIE, is asymmetrically localized during Bacillus subtilis sporulation, thereby demonstrating the ability of PSICIC to discern protein localization features at sub-pixel scales. We also used PSICIC to examine the accuracy of cell division in Esherichia coli and found a new role for the Min system in regulating division-site placement throughout the cell length, but only prior to the initiation of cell constriction. These results extend our understanding of the regulation of both asymmetry and accuracy in bacterial division while demonstrating the general applicability of PSICIC as a computational approach for quantitative, high-throughput analysis of cellular images.

  2. Small target detection using objectness and saliency

    Science.gov (United States)

    Zhang, Naiwen; Xiao, Yang; Fang, Zhiwen; Yang, Jian; Wang, Li; Li, Tao

    2017-10-01

    We are motived by the need for generic object detection algorithm which achieves high recall for small targets in complex scenes with acceptable computational efficiency. We propose a novel object detection algorithm, which has high localization quality with acceptable computational cost. Firstly, we obtain the objectness map as in BING[1] and use NMS to get the top N points. Then, k-means algorithm is used to cluster them into K classes according to their location. We set the center points of the K classes as seed points. For each seed point, an object potential region is extracted. Finally, a fast salient object detection algorithm[2] is applied to the object potential regions to highlight objectlike pixels, and a series of efficient post-processing operations are proposed to locate the targets. Our method runs at 5 FPS on 1000*1000 images, and significantly outperforms previous methods on small targets in cluttered background.

  3. Magnetic biosensor system to detect biological targets

    KAUST Repository

    Li, Fuquan

    2012-09-01

    Magneto-resistive sensors in combination with magnetic beads provide sensing platforms, which are small in size and highly sensitive. These platforms can be fully integrated with microchannels and electronics to enable devices capable of performing complex tasks. Commonly, a sandwich method is used that requires a specific coating of the sensor\\'s surface to immobilize magnetic beads and biological targets on top of the sensor. This paper concerns a micro device to detect biological targets using magnetic concentration, magnetic as well as mechanical trapping and magnetic sensing. Target detection is based on the size difference between bare magnetic beads and magnetic beads with targets attached. This method remedies the need for a coating layer and reduces the number of steps required to run an experiment. © 2012 IEEE.

  4. An Automated Approach for Sub-Pixel Registration of Landsat-8 Operational Land Imager (OLI and Sentinel-2 Multi Spectral Instrument (MSI Imagery

    Directory of Open Access Journals (Sweden)

    Lin Yan

    2016-06-01

    -points were extracted and had affine-transformation root-mean-square error fits of approximately 0.3 pixels at 10 m resolution and dense-matching prediction errors of similar magnitude. These results and visual assessment of the affine transformed data indicate that the methodology provides sub-pixel registration performance required for meaningful Landsat-8 OLI and Sentinel-2A MSI data comparison and combined data applications.

  5. Spectral Target Detection using Schroedinger Eigenmaps

    Science.gov (United States)

    Dorado-Munoz, Leidy P.

    Applications of optical remote sensing processes include environmental monitoring, military monitoring, meteorology, mapping, surveillance, etc. Many of these tasks include the detection of specific objects or materials, usually few or small, which are surrounded by other materials that clutter the scene and hide the relevant information. This target detection process has been boosted lately by the use of hyperspectral imagery (HSI) since its high spectral dimension provides more detailed spectral information that is desirable in data exploitation. Typical spectral target detectors rely on statistical or geometric models to characterize the spectral variability of the data. However, in many cases these parametric models do not fit well HSI data that impacts the detection performance. On the other hand, non-linear transformation methods, mainly based on manifold learning algorithms, have shown a potential use in HSI transformation, dimensionality reduction and classification. In target detection, non-linear transformation algorithms are used as preprocessing techniques that transform the data to a more suitable lower dimensional space, where the statistical or geometric detectors are applied. One of these non-linear manifold methods is the Schroedinger Eigenmaps (SE) algorithm that has been introduced as a technique for semi-supervised classification. The core tool of the SE algorithm is the Schroedinger operator that includes a potential term that encodes prior information about the materials present in a scene, and enables the embedding to be steered in some convenient directions in order to cluster similar pixels together. A completely novel target detection methodology based on SE algorithm is proposed for the first time in this thesis. The proposed methodology does not just include the transformation of the data to a lower dimensional space but also includes the definition of a detector that capitalizes on the theory behind SE. The fact that target pixels and

  6. Biological models for automatic target detection

    Science.gov (United States)

    Schachter, Bruce

    2008-04-01

    Humans are better at detecting targets in literal imagery than any known algorithm. Recent advances in modeling visual processes have resulted from f-MRI brain imaging with humans and the use of more invasive techniques with monkeys. There are four startling new discoveries. 1) The visual cortex does not simply process an incoming image. It constructs a physics based model of the image. 2) Coarse category classification and range-to-target are estimated quickly - possibly through the dorsal pathway of the visual cortex, combining rapid coarse processing of image data with expectations and goals. This data is then fed back to lower levels to resize the target and enhance the recognition process feeding forward through the ventral pathway. 3) Giant photosensitive retinal ganglion cells provide data for maintaining circadian rhythm (time-of-day) and modeling the physics of the light source. 4) Five filter types implemented by the neurons of the primary visual cortex have been determined. A computer model for automatic target detection has been developed based upon these recent discoveries. It uses an artificial neural network architecture with multiple feed-forward and feedback paths. Our implementation's efficiency derives from the observation that any 2-D filter kernel can be approximated by a sum of 2-D box functions. And, a 2-D box function easily decomposes into two 1-D box functions. Further efficiency is obtained by decomposing the largest neural filter into a high pass filter and a more sparsely sampled low pass filter.

  7. A computational imaging target specific detectivity metric

    Science.gov (United States)

    Preece, Bradley L.; Nehmetallah, George

    2017-05-01

    Due to the large quantity of low-cost, high-speed computational processing available today, computational imaging (CI) systems are expected to have a major role for next generation multifunctional cameras. The purpose of this work is to quantify the performance of theses CI systems in a standardized manner. Due to the diversity of CI system designs that are available today or proposed in the near future, significant challenges in modeling and calculating a standardized detection signal-to-noise ratio (SNR) to measure the performance of these systems. In this paper, we developed a path forward for a standardized detectivity metric for CI systems. The detectivity metric is designed to evaluate the performance of a CI system searching for a specific known target or signal of interest, and is defined as the optimal linear matched filter SNR, similar to the Hotelling SNR, calculated in computational space with special considerations for standardization. Therefore, the detectivity metric is designed to be flexible, in order to handle various types of CI systems and specific targets, while keeping the complexity and assumptions of the systems to a minimum.

  8. Lidar-based Evaluation of Sub-pixel Forest Structural Characteristics and Sun-sensor Geometries that Influence MODIS Leaf Area Index Product Accuracy and Retrieval Quality

    Science.gov (United States)

    Jensen, J.; Humes, K. S.

    2010-12-01

    Leaf Area Index (LAI) is an important structural component of vegetation because the foliar surface of plants largely controls the exchange of water, nutrients, and energy within terrestrial ecosystems. Because LAI is a key variable used to model water, energy, and biogeochemical cycles, Moderate Resolution Imaging Spectroradiometer (MODIS) LAI products are widely used in many studies to better understand and quantify exchanges between the terrestrial surface and the atmosphere. Within the last decade, significant resources and efforts have been invested toward MODIS LAI validation for a variety of biome types and a suite of published work has provided valuable feedback on the agreement between MODIS-derived LAI via radiative transfer (RT) inversion compared to multispectral-based empirical estimates of LAI. Our study provides an alternative assessment of the MODIS LAI product for a 58,000 ha evergreen needleleaf forest located in the western Rocky Mountain range in northern Idaho by using lidar data to model (R2=0.86, RMSE=0.76) and map fine-scale estimates of vegetation structure over a region for which multispectral LAI estimates were unacceptable. In an effort to provide feedback on algorithm performance, we evaluated the agreement between lidar-modeled and MODIS-retrieved LAI by specific MODIS LAI retrieval algorithm and product quality definitions. We also examined the sub-pixel vegetation structural conditions and satellite-sensor geometries that tend to influence MODIS LAI retrieval algorithm and product quality over our study area. Our results demonstrate a close agreement between lidar LAI and MODIS LAI retrieved using the main RT algorithm and consistently large MODIS LAI overestimates for pixels retrieved from a saturated set of RT solutions. Our evaluation also illuminated some conditions for which sub-pixel structural characteristics and sun-sensor geometries influenced retrieval quality and product agreement. These conditions include: 1) the

  9. An improved Fourier-based sub-pixel image registration algorithm for raw image sequence of LASIS

    Science.gov (United States)

    Ma, Xiaolong; Yang, Jianfeng; Qiao, Weidong; Xue, Bin

    2008-03-01

    Previous studies indicate that parallel computing for hyperspectral remote sensing synthetic image generation is quite feasible. However, due to the limitation of computing ability within single cluster, one can only generate three bands and a 1000*1000 pixels image in a reasonable time period even using a 40-50 node parallel computing cluster. In this paper, we discuss the capability of using Grid computing where the so-called eScience or cyberinfrastructure is utilized to integrate distributed computing resources to act as a single virtual computer with huge scientific computational abilities and storage spaces. The technique demonstrated in this paper demonstrates the feasibility of a Grid-Enabled Monte Carlo Hyperspectral Synthetic Image Remote Sensing Model (GRID-MCHSIM) for future coastal water quality remote sensing algorithm developments and detection of bottom features and targets in water.

  10. Video enhancement effectiveness for target detection

    Science.gov (United States)

    Simon, Michael; Fischer, Amber; Petrov, Plamen

    2011-05-01

    Unmanned aerial vehicles (UAVs) capture real-time video data of military targets while keeping the warfighter at a safe distance. This keeps soldiers out of harm's way while they perform intelligence, surveillance and reconnaissance (ISR) and close-air support troops in contact (CAS-TIC) situations. The military also wants to use UAV video to achieve force multiplication. One method of achieving effective force multiplication involves fielding numerous UAVs with cameras and having multiple videos processed simultaneously by a single operator. However, monitoring multiple video streams is difficult for operators when the videos are of low quality. To address this challenge, we researched several promising video enhancement algorithms that focus on improving video quality. In this paper, we discuss our video enhancement suite and provide examples of video enhancement capabilities, focusing on stabilization, dehazing, and denoising. We provide results that show the effects of our enhancement algorithms on target detection and tracking algorithms. These results indicate that there is potential to assist the operator in identifying and tracking relevant targets with aided target recognition even on difficult video, increasing the force multiplier effect of UAVs. This work also forms the basis for human factors research into the effects of enhancement algorithms on ISR missions.

  11. Assessment of Schrodinger Eigenmaps for target detection

    Science.gov (United States)

    Dorado Munoz, Leidy P.; Messinger, David W.; Czaja, Wojtek

    2014-06-01

    Non-linear dimensionality reduction methods have been widely applied to hyperspectral imagery due to its structure as the information can be represented in a lower dimension without losing information, and because the non-linear methods preserve the local geometry of the data while the dimension is reduced. One of these methods is Laplacian Eigenmaps (LE), which assumes that the data lies on a low dimensional manifold embedded in a high dimensional space. LE builds a nearest neighbor graph, computes its Laplacian and performs the eigendecomposition of the Laplacian. These eigenfunctions constitute a basis for the lower dimensional space in which the geometry of the manifold is preserved. In addition to the reduction problem, LE has been widely used in tasks such as segmentation, clustering, and classification. In this regard, a new Schrodinger Eigenmaps (SE) method was developed and presented as a semi-supervised classification scheme in order to improve the classification performance and take advantage of the labeled data. SE is an algorithm built upon LE, where the former Laplacian operator is replaced by the Schrodinger operator. The Schrodinger operator includes a potential term V, that, taking advantage of the additional information such as labeled data, allows clustering of similar points. In this paper, we explore the idea of using SE in target detection. In this way, we present a framework where the potential term V is defined as a barrier potential: a diagonal matrix encoding the spatial position of the target, and the detection performance is evaluated by using different targets and different hyperspectral scenes.

  12. DESIGN OF DYADIC-INTEGER-COEFFICIENTS BASED BI-ORTHOGONAL WAVELET FILTERS FOR IMAGE SUPER-RESOLUTION USING SUB-PIXEL IMAGE REGISTRATION

    Directory of Open Access Journals (Sweden)

    P.B. Chopade

    2014-05-01

    Full Text Available This paper presents image super-resolution scheme based on sub-pixel image registration by the design of a specific class of dyadic-integer-coefficient based wavelet filters derived from the construction of a half-band polynomial. First, the integer-coefficient based half-band polynomial is designed by the splitting approach. Next, this designed half-band polynomial is factorized and assigned specific number of vanishing moments and roots to obtain the dyadic-integer coefficients low-pass analysis and synthesis filters. The possibility of these dyadic-integer coefficients based wavelet filters is explored in the field of image super-resolution using sub-pixel image registration. The two-resolution frames are registered at a specific shift from one another to restore the resolution lost by CCD array of camera. The discrete wavelet transform (DWT obtained from the designed coefficients is applied on these two low-resolution images to obtain the high resolution image. The developed approach is validated by comparing the quality metrics with existing filter banks.

  13. Target detection by way of Kalman filtering

    Science.gov (United States)

    Sipe, Gary A.

    1993-03-01

    A simple, time domain method is used to analyze moderate to high PRF radar signals. The quantities of interest are the signal's PRF, SNR, and time of arrival. The time of arrival problem is important because it can be used, with multiple sensors, to determine the position of the emitting target. An algorithm is described which will produce these values using Kalman filtering. Individual pulses in a pulsed type radar are measured against a threshold using a two sample detection scheme to provide some glitch rejection. Results of individual time domain measurements of the signal parameter are smoothed with a Kalman filter. Integrating the pulse train envelope during the radar dwell time provides the energy centroid for a scan cycle. This centroid, time differenced with multiple sensors, provides observables for an Extended Kalman Filter for emitter localization. The work here simulates all data. Tests of the algorithms developed were conducted on real, classified data in addition to the work presented here.

  14. Detection of IR target by fusing multispectral IR data

    Science.gov (United States)

    Li, Liya; Qi, Meng; Gao, Xuhui

    2011-08-01

    Detection of the small target in clutter, usually regarded as singular points in the infrared image, is an important issue in infrared searching and tracking (IRST) system. Because of the far range of the target to the sensor, the stealth technology, the effects of inherent sensor noise and the phenomena of nature, the target is more difficult to be detected. Multispectral sensor system has been proved it could greatly improve detection of the small, hard-to-find targets by multispectral processing techniques (such as sensor or image fusion). Aiming at the problem of multispectral IR Target Detection, a kind method of the multispectral IR target detection is proposed, based on the existed detection systems. In this method, the image registration is done firstly to make the different sensors have a same scene. Then, a fusion rule, named as adaptive weighted voting theory, is developed to combine the target detection results from the different spectral sensors. The adaptive weighted voting theory can give the different weights, based on the different spectral IR characteristics, and these weights decide the detected target is identified as real target or background. The experimental results show that the proposed method can reduce the detection uncertainty and improve the detection performance. Compared with the single spectral detection results and the others fusion detection methods, it can decrease the lost alarm rate and the false alarm rate effectively. The proposed method has been employed in our IR surveillance system, and it is easy to be used in the various circumstances.

  15. A Framework Based on 2-D Taylor Expansion for Quantifying the Impacts of Sub-Pixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bi-Spectral Method

    Science.gov (United States)

    Zhang, Z.; Werner, F.; Cho, H. -M.; Wind, G.; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, Kerry

    2016-01-01

    The bi-spectral method retrieves cloud optical thickness and cloud droplet effective radius simultaneously from a pair of cloud reflectance observations, one in a visible or near-infrared (VISNIR) band and the other in a shortwave infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved and re. In the literature, the retrievals of and re are often assumed to be independent and considered separately when investigating the impact of sub-pixel cloud reflectance variations on the bi-spectral method. As a result, the impact on is contributed only by the sub-pixel variation of VISNIR band reflectance and the impact on re only by the sub-pixel variation of SWIR band reflectance. In our new framework, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VISNIR and SWIR cloud reflectances and their covariance on the and re retrievals. This framework takes into account the fact that the retrievals are determined by both VISNIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VISNIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval. We test our framework using synthetic cloud fields from a large-eddy simulation and real observations from Moderate Resolution Imaging Spectroradiometer. The predicted results based on our framework agree very well with the numerical simulations. Our framework can be used

  16. An Overview of Radar Waveform Optimization for Target Detection

    Directory of Open Access Journals (Sweden)

    Wang Lulu

    2016-10-01

    Full Text Available An optimal waveform design method that fully employs the knowledge of the target and the environment can further improve target detection performance, thus is of vital importance to research. In this paper, methods of radar waveform optimization for target detection are reviewed and summarized and provide the basis for the research.

  17. Mechanisms for Visual Detection of Small Targets in Insects

    Science.gov (United States)

    2009-12-01

    AOARD-09-4058 / FA2386-09-1-4058 Mechanisms for Visual Detection of Small Targets in Insects Final Performance Report December 1, 2009...SUBTITLE Mechanisms for Visual Detection of Small Targets in Insects 5a. CONTRACT NUMBER FA23860914058 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...grantee investigated insect visual detection of small targets against a cluttered, moving background. The work focused on deducing neural mechanisms

  18. Detection technique of targets for missile defense system

    Science.gov (United States)

    Guo, Hua-ling; Deng, Jia-hao; Cai, Ke-rong

    2009-11-01

    Ballistic missile defense system (BMDS) is a weapon system for intercepting enemy ballistic missiles. It includes ballistic-missile warning system, target discrimination system, anti-ballistic-missile guidance systems, and command-control communication system. Infrared imaging detection and laser imaging detection are widely used in BMDS for surveillance, target detection, target tracking, and target discrimination. Based on a comprehensive review of the application of target-detection techniques in the missile defense system, including infrared focal plane arrays (IRFPA), ground-based radar detection technology, 3-dimensional imaging laser radar with a photon counting avalanche photodiode (APD) arrays and microchip laser, this paper focuses on the infrared and laser imaging detection techniques in missile defense system, as well as the trends for their future development.

  19. A Framework for Quantifying the Impacts of Sub-Pixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bi-Spectral Method.

    Science.gov (United States)

    Zhang, Z; Werner, F.; Cho, H. -M.; Wind, Galina; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, Kerry

    2017-01-01

    The so-called bi-spectral method retrieves cloud optical thickness (t) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near infrared (VIS/NIR) band and the other in a shortwave-infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved t and re. In this study, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the t and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the t and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval.

  20. A framework for quantifying the impacts of sub-pixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bi-spectral method

    Science.gov (United States)

    Zhang, Z.; Werner, F.; Cho, H.-M.; Wind, G.; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, Kerry

    2017-02-01

    The so-called bi-spectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near infrared (VIS/NIR) band and the other in a shortwave-infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and re. In this study, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the τ and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval.

  1. Adjusted Spectral Matched Filter for Target Detection in Hyperspectral Imagery

    Directory of Open Access Journals (Sweden)

    Lianru Gao

    2015-05-01

    Full Text Available Supervised target detection and anomaly detection are widely used in various applications, depending upon the availability of target spectral signature. Basically, they are based on a similar linear process, which makes them highly correlated. In this paper, we propose a novel adjusted spectral matched filter (ASMF for hyperspectral target detection, which aims to effectively improve target detection performance with anomaly detection output. Specifically, a typical case is presented by using the Reed-Xiaoli (RX anomaly detector to adjust the output of supervised constrained energy minimization (CEM detector. The adjustment is appropriately controlled by a weighting parameter in different detection scenarios. Experiments were implemented by using both synthetic and real hyperspectral datasets. Compared to the traditional single detection method (e.g., CEM, the experimental results demonstrate that the proposed ASMF can effectively improve its performance by utilizing the result from an anomaly detector (e.g., RX, particularly in situations with a complex background or strong anomalies.

  2. Point target detection using super-resolution reconstruction

    NARCIS (Netherlands)

    Lange, D.J.J. de; Dijk, J.; Eekeren, A.W.M. van; Schutte, K.

    2007-01-01

    Surveillance applications are primarily concerned with detection of targets. In electro-optical surveillance systems, missiles or other weapons coming towards you are observed as moving points. Typically, such moving targets need to be detected in a very short time. One of the problems is that the

  3. Mechanism for Visual Detection of Small Targets in Insects

    Science.gov (United States)

    2013-06-14

    1 Final Report for AOARD Grant FA2386-10-1-4114 AOARD 104114 “Mechanisms for Visual Detection of Small Targets in Insects ” 14 June...Final 3. DATES COVERED 15-06-2010 to 15-12-2012 4. TITLE AND SUBTITLE Mechanism for visual detection of small targets in insects 5a. CONTRACT...unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Specialized Small Target Motion Detector Neurons (STMDs) in the optic lobes of the insect brain

  4. Multi-target Radar Detection within a Sparsity Framework

    OpenAIRE

    Yap, Han Lun; Pribić, Radmila

    2013-01-01

    Traditional radar detection schemes are typically studied for single target scenarios and they can be non-optimal when there are multiple targets in the scene. In this paper, we develop a framework to discuss multi-target detection schemes with sparse reconstruction techniques that is based on the Neyman-Pearson criterion. We will describe an initial result in this framework concerning false alarm probability with LASSO as the sparse reconstruction technique. Then, several simulations validat...

  5. Enhanced Algorithms for EO/IR Electronic Stabilization, Clutter Suppression, and Track-Before-Detect for Multiple Low Observable Targets

    Science.gov (United States)

    Tartakovsky, A.; Brown, A.; Brown, J.

    The paper describes the development and evaluation of a suite of advanced algorithms which provide significantly-improved capabilities for finding, fixing, and tracking multiple ballistic and flying low observable objects in highly stressing cluttered environments. The algorithms have been developed for use in satellite-based staring and scanning optical surveillance suites for applications including theatre and intercontinental ballistic missile early warning, trajectory prediction, and multi-sensor track handoff for midcourse discrimination and intercept. The functions performed by the algorithms include electronic sensor motion compensation providing sub-pixel stabilization (to 1/100 of a pixel), as well as advanced temporal-spatial clutter estimation and suppression to below sensor noise levels, followed by statistical background modeling and Bayesian multiple-target track-before-detect filtering. The multiple-target tracking is performed in physical world coordinates to allow for multi-sensor fusion, trajectory prediction, and intercept. Output of detected object cues and data visualization are also provided. The algorithms are designed to handle a wide variety of real-world challenges. Imaged scenes may be highly complex and infinitely varied -- the scene background may contain significant celestial, earth limb, or terrestrial clutter. For example, when viewing combined earth limb and terrestrial scenes, a combination of stationary and non-stationary clutter may be present, including cloud formations, varying atmospheric transmittance and reflectance of sunlight and other celestial light sources, aurora, glint off sea surfaces, and varied natural and man-made terrain features. The targets of interest may also appear to be dim, relative to the scene background, rendering much of the existing deployed software useless for optical target detection and tracking. Additionally, it may be necessary to detect and track a large number of objects in the threat cloud

  6. An Improved GLRT Method for Target Detection in SAR Imagery

    Directory of Open Access Journals (Sweden)

    Ju Yingyun

    2015-01-01

    Full Text Available Automatic ground vehicle detection based on SAR imagery is one of the important military applications of SAR. A region-based generalized likelihood ratio test (GLRT method is proposed in this paper, and this method combines the GLRT detection theory and image segmentation technology. First, the SAR imagery is roughly segmented as land clutter region and potential target region through the split and merge procedure often used for processing the original images. Then, based on the segmentation results, the reasonable statistical models for the data in the two regions are built respectively. Finally, with the knowledge of statistical characteristics of clutter and target, GLRT detection method is applied to the each pixel in the potential target region to obtain more accurate detection results. Experimental results based on real SAR data show that the proposed method can effectively detect the ground vehicle targets from the land clutter with excellent accuracy and speed.

  7. Passive Sonar Target Detection Using Statistical Classifier and Adaptive Threshold

    Directory of Open Access Journals (Sweden)

    Hamed Komari Alaie

    2018-01-01

    Full Text Available This paper presents the results of an experimental investigation about target detecting with passive sonar in Persian Gulf. Detecting propagated sounds in the water is one of the basic challenges of the researchers in sonar field. This challenge will be complex in shallow water (like Persian Gulf and noise less vessels. Generally, in passive sonar, the targets are detected by sonar equation (with constant threshold that increases the detection error in shallow water. The purpose of this study is proposed a new method for detecting targets in passive sonars using adaptive threshold. In this method, target signal (sound is processed in time and frequency domain. For classifying, Bayesian classification is used and posterior distribution is estimated by Maximum Likelihood Estimation algorithm. Finally, target was detected by combining the detection points in both domains using Least Mean Square (LMS adaptive filter. Results of this paper has showed that the proposed method has improved true detection rate by about 24% when compared other the best detection method.

  8. The simulation study on optical target laser active detection performance

    Science.gov (United States)

    Li, Ying-chun; Hou, Zhao-fei; Fan, Youchen

    2014-12-01

    According to the working principle of laser active detection system, the paper establishes the optical target laser active detection simulation system, carry out the simulation study on the detection process and detection performance of the system. For instance, the performance model such as the laser emitting, the laser propagation in the atmosphere, the reflection of optical target, the receiver detection system, the signal processing and recognition. We focus on the analysis and modeling the relationship between the laser emitting angle and defocus amount and "cat eye" effect echo laser in the reflection of optical target. Further, in the paper some performance index such as operating range, SNR and the probability of the system have been simulated. The parameters including laser emitting parameters, the reflection of the optical target and the laser propagation in the atmosphere which make a great influence on the performance of the optical target laser active detection system. Finally, using the object-oriented software design methods, the laser active detection system with the opening type, complete function and operating platform, realizes the process simulation that the detection system detect and recognize the optical target, complete the performance simulation of each subsystem, and generate the data report and the graph. It can make the laser active detection system performance models more intuitive because of the visible simulation process. The simulation data obtained from the system provide a reference to adjust the structure of the system parameters. And it provides theoretical and technical support for the top level design of the optical target laser active detection system and performance index optimization.

  9. Detection of Moving Targets Using Soliton Resonance Effect

    Science.gov (United States)

    Kulikov, Igor K.; Zak, Michail

    2013-01-01

    The objective of this research was to develop a fundamentally new method for detecting hidden moving targets within noisy and cluttered data-streams using a novel "soliton resonance" effect in nonlinear dynamical systems. The technique uses an inhomogeneous Korteweg de Vries (KdV) equation containing moving-target information. Solution of the KdV equation will describe a soliton propagating with the same kinematic characteristics as the target. The approach uses the time-dependent data stream obtained with a sensor in form of the "forcing function," which is incorporated in an inhomogeneous KdV equation. When a hidden moving target (which in many ways resembles a soliton) encounters the natural "probe" soliton solution of the KdV equation, a strong resonance phenomenon results that makes the location and motion of the target apparent. Soliton resonance method will amplify the moving target signal, suppressing the noise. The method will be a very effective tool for locating and identifying diverse, highly dynamic targets with ill-defined characteristics in a noisy environment. The soliton resonance method for the detection of moving targets was developed in one and two dimensions. Computer simulations proved that the method could be used for detection of singe point-like targets moving with constant velocities and accelerations in 1D and along straight lines or curved trajectories in 2D. The method also allows estimation of the kinematic characteristics of moving targets, and reconstruction of target trajectories in 2D. The method could be very effective for target detection in the presence of clutter and for the case of target obscurations.

  10. Heterogeneous CPU-GPU moving targets detection for UAV video

    Science.gov (United States)

    Li, Maowen; Tang, Linbo; Han, Yuqi; Yu, Chunlei; Zhang, Chao; Fu, Huiquan

    2017-07-01

    Moving targets detection is gaining popularity in civilian and military applications. On some monitoring platform of motion detection, some low-resolution stationary cameras are replaced by moving HD camera based on UAVs. The pixels of moving targets in the HD Video taken by UAV are always in a minority, and the background of the frame is usually moving because of the motion of UAVs. The high computational cost of the algorithm prevents running it at higher resolutions the pixels of frame. Hence, to solve the problem of moving targets detection based UAVs video, we propose a heterogeneous CPU-GPU moving target detection algorithm for UAV video. More specifically, we use background registration to eliminate the impact of the moving background and frame difference to detect small moving targets. In order to achieve the effect of real-time processing, we design the solution of heterogeneous CPU-GPU framework for our method. The experimental results show that our method can detect the main moving targets from the HD video taken by UAV, and the average process time is 52.16ms per frame which is fast enough to solve the problem.

  11. Fast infrared maritime target detection: Binarization via histogram curve transformation

    Science.gov (United States)

    Wang, Bin; Dong, Lili; Zhao, Ming; Xu, Wenhai

    2017-06-01

    To improve the accuracy and efficiency of infrared maritime target detection under different environmental conditions and for different kinds of targets, we proposed a novel self-adaptive binarization algorithm which is based on the histogram curve transformation. The main contribution was a rapid and robust method for detecting infrared maritime targets that have positive local contrasts. This method has low computational complexity and high detection accuracy under a variety of conditions and enhances the accuracy and speed of single-frame detection for infrared maritime distressed targets. The proposed histogram rightwards cyclic shift binarization (HRCSB) first transforms the histogram curve (HC) according to a self-adaptive gray level transformation equation. Then, the background subtraction based on Gaussian filtering can be used to generate an enhanced image. Finally, the final HC can be extracted from this enhanced image. After a cyclic shift of the final HC, the average gray level of the shifted HC can reveal an effective threshold for detecting targets from the enhanced image. Experimental results show that, compared with four existing algorithms, the proposed HRCSB can successfully detect targets under a variety of conditions while keeping a low false alarm rate and a low computational complexity. Thus, the proposed HRCSB algorithm has potential for excellent applicability.

  12. Hyperspectral target detection using regularized high-order matched filter

    Science.gov (United States)

    Shi, Zhenwei; Yang, Shuo; Jiang, Zhiguo

    2011-05-01

    Automatic target detection is an important application in the hyperspectral image processing field. Most statistics-based detection algorithms use second-order statistics to construct detectors. However, for target detection in a real hyperspectral image, targets of interest usually occupy a few pixels with small population. In this case, high-order statistics could characterize targets more effectively than second-order statistics. Also, the inherent variation of spectra of targets is an obstacle to successful target detection. In this paper, we propose a regularized high-order matched filter (RHF) which uses high-order statistics to build an objective function and uses a regularized term to make the algorithm robust to target spectral variation. A gradient descent method is used to solve this optimization problem, and we obtain the convergence properties of the RHF. According to the experimental hyperspectral data, the results have shown that the proposed algorithm performed better than those classical second-order statistics-based algorithms and some kernel-based methods.

  13. Moving target detection method based on improved Gaussian mixture model

    Science.gov (United States)

    Ma, J. Y.; Jie, F. R.; Hu, Y. J.

    2017-07-01

    Gaussian Mixture Model is often employed to build background model in background difference methods for moving target detection. This paper puts forward an adaptive moving target detection algorithm based on improved Gaussian Mixture Model. According to the graylevel convergence for each pixel, adaptively choose the number of Gaussian distribution to learn and update background model. Morphological reconstruction method is adopted to eliminate the shadow.. Experiment proved that the proposed method not only has good robustness and detection effect, but also has good adaptability. Even for the special cases when the grayscale changes greatly and so on, the proposed method can also make outstanding performance.

  14. Infrared small target detection technology based on OpenCV

    Science.gov (United States)

    Liu, Lei; Huang, Zhijian

    2013-09-01

    Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

  15. An Automated Directed Spectral Search Methodology for Small Target Detection

    Science.gov (United States)

    Grossman, Stanley I.

    Much of the current efforts in remote sensing tackle macro-level problems such as determining the extent of wheat in a field, the general health of vegetation or the extent of mineral deposits in an area. However, for many of the remaining remote sensing challenges being studied currently, such as border protection, drug smuggling, treaty verification, and the war on terror, most targets are very small in nature - a vehicle or even a person. While in typical macro-level problems the objective vegetation is in the scene, for small target detection problems it is not usually known if the desired small target even exists in the scene, never mind finding it in abundance. The ability to find specific small targets, such as vehicles, typifies this problem. Complicating the analyst's life, the growing number of available sensors is generating mountains of imagery outstripping the analysts' ability to visually peruse them. This work presents the important factors influencing spectral exploitation using multispectral data and suggests a different approach to small target detection. The methodology of directed search is presented, including the use of scene-modeled spectral libraries, various search algorithms, and traditional statistical and ROC curve analysis. The work suggests a new metric to calibrate analysis labeled the analytic sweet spot as well as an estimation method for identifying the sweet spot threshold for an image. It also suggests a new visualization aid for highlighting the target in its entirety called nearest neighbor inflation (NNI). It brings these all together to propose that these additions to the target detection arena allow for the construction of a fully automated target detection scheme. This dissertation next details experiments to support the hypothesis that the optimum detection threshold is the analytic sweet spot and that the estimation method adequately predicts it. Experimental results and analysis are presented for the proposed directed

  16. Directional detection of dark matter with two-dimensional targets

    Directory of Open Access Journals (Sweden)

    Yonit Hochberg

    2017-09-01

    Full Text Available We propose two-dimensional materials as targets for direct detection of dark matter. Using graphene as an example, we focus on the case where dark matter scattering deposits sufficient energy on a valence-band electron to eject it from the target. We show that the sensitivity of graphene to dark matter of MeV to GeV mass can be comparable, for similar exposure and background levels, to that of semiconductor targets such as silicon and germanium. Moreover, a two-dimensional target is an excellent directional detector, as the ejected electron retains information about the angular dependence of the incident dark matter particle. This proposal can be implemented by the PTOLEMY experiment, presenting for the first time an opportunity for directional detection of sub-GeV dark matter.

  17. Optimal Joint Target Detection and Parameter Estimation By MIMO Radar

    CERN Document Server

    Tajer, Ali; Wang, Xiaodong; Moustakides, George V

    2009-01-01

    We consider multiple-input multiple-output (MIMO) radar systems with widely-spaced antennas. Such antenna configuration facilitates capturing the inherent diversity gain due to independent signal dispersion by the target scatterers. We consider a new MIMO radar framework for detecting a target that lies in an unknown location. This is in contrast with conventional MIMO radars which break the space into small cells and aim at detecting the presence of a target in a specified cell. We treat this problem through offering a novel composite hypothesis testing framework for target detection when (i) one or more parameters of the target are unknown and we are interested in estimating them, and (ii) only a finite number of observations are available. The test offered optimizes a metric which accounts for both detection and estimation accuracies. In this paper as the parameter of interest we focus on the vector of time-delays that the waveforms undergo from being emitted by the transmit antennas until being observed b...

  18. Real Time Intelligent Target Detection and Analysis with Machine Vision

    Science.gov (United States)

    Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

    2000-01-01

    We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

  19. Antivibration pipeline-filtering algorithm for maritime small target detection

    Science.gov (United States)

    Wang, Bin; Xu, Wenhai; Zhao, Ming; Wu, Houde

    2014-11-01

    When searching for small targets at sea based on an infrared imaging system, irregular and random vibration of the airborne imaging platform causes intense interference for the pipeline-filtering, which is an algorithm that performs well in detecting small targets but is particularly sensitive to interframe vibrations of sequence images. This paper puts forward a pipeline-filtering algorithm that has a good performance on self-adaptive antivibration. In the block matching method that combines the normalized cross-correlations coefficient with the normalized mutual information, the interframe vibration of sequence images is acquired in real time and used to correct coordinates of the single-frame detection results, and then the corrected detection results are used to complete the pipeline-filtering. In addition, under severe sea conditions, small targets at sea may disappear transiently, leading to missing detection. This algorithm is also able to resolve this problem. Experimental results show that the algorithm can overcome the problem of interframe vibration of sequence images, thus realizing accurate detection of small maritime targets.

  20. Computational optimisation of targeted DNA sequencing for cancer detection

    Science.gov (United States)

    Martinez, Pierre; McGranahan, Nicholas; Birkbak, Nicolai Juul; Gerlinger, Marco; Swanton, Charles

    2013-12-01

    Despite recent progress thanks to next-generation sequencing technologies, personalised cancer medicine is still hampered by intra-tumour heterogeneity and drug resistance. As most patients with advanced metastatic disease face poor survival, there is need to improve early diagnosis. Analysing circulating tumour DNA (ctDNA) might represent a non-invasive method to detect mutations in patients, facilitating early detection. In this article, we define reduced gene panels from publicly available datasets as a first step to assess and optimise the potential of targeted ctDNA scans for early tumour detection. Dividing 4,467 samples into one discovery and two independent validation cohorts, we show that up to 76% of 10 cancer types harbour at least one mutation in a panel of only 25 genes, with high sensitivity across most tumour types. Our analyses demonstrate that targeting ``hotspot'' regions would introduce biases towards in-frame mutations and would compromise the reproducibility of tumour detection.

  1. Radon Spectrum and Its Application for Small Moving Target Detection

    Science.gov (United States)

    2015-04-01

    UNCLASSIFIED UNCLASSIFIED Radon Spectrum and Its Application for Small Moving Target Detection Yunhan Dong National Security...coherent processing, the concept of a Radon spectrum that is a kind of normalised Radon transform is proposed and used for radar non-coherent detection...One advantage of using the Radon transform for non-coherent processing is that integration in all directions is considered, and hence range migration

  2. Insect detection of small targets moving in visual clutter.

    Directory of Open Access Journals (Sweden)

    Karin Nordström

    2006-03-01

    Full Text Available Detection of targets that move within visual clutter is a common task for animals searching for prey or conspecifics, a task made even more difficult when a moving pursuer needs to analyze targets against the motion of background texture (clutter. Despite the limited optical acuity of the compound eye of insects, this challenging task seems to have been solved by their tiny visual system. Here we describe neurons found in the male hoverfly, Eristalis tenax, that respond selectively to small moving targets. Although many of these target neurons are inhibited by the motion of a background pattern, others respond to target motion within the receptive field under a surprisingly large range of background motion stimuli. Some neurons respond whether or not there is a speed differential between target and background. Analysis of responses to very small targets (smaller than the size of the visual field of single photoreceptors or those targets with reduced contrast shows that these neurons have extraordinarily high contrast sensitivity. Our data suggest that rejection of background motion may result from extreme selectivity for small targets contrasting against local patches of the background, combined with this high sensitivity, such that background patterns rarely contain features that satisfactorily drive the neuron.

  3. Effects of age and eccentricity on visual target detection

    Directory of Open Access Journals (Sweden)

    Nicole eGruber

    2014-01-01

    Full Text Available The aim of this study was to examine the effects of aging and target eccentricity on a visual search task comprising 30 images of everyday life projected into a hemisphere, realizing a ± 90° visual field. The task performed binocularly allowed participants to freely move their eyes to scan images for an appearing target or distractor stimulus (presented at 10°; 30°, and 50° eccentricity. The distractor stimulus required no response, while the target stimulus required acknowledgment by pressing the response button. 117 healthy subjects (mean age=49.63 years, SD=17.40 years, age range 20-78 years were studied. The results show that target detection performance decreases with age as well as with increasing eccentricity, especially for older subjects. Reaction time also increases with age and eccentricity, but in contrast to target detection, there is no interaction between age and eccentricity. Eye movement analysis showed that younger subjects exhibited a passive search strategy while older subjects exhibited an active search strategy probably as a compensation for their reduced peripheral detection performance.

  4. Image enhancement and moving target detection in IR image sequences

    NARCIS (Netherlands)

    Beck, W.

    1993-01-01

    Results are presented of noise reduction by motion compensated temporal filtering in a noisy IR image sequence and of moving target detection in an air-to-ground IR image sequence. In the case of motion compensated temporal filtering our approach consists of estimating the optical flow between

  5. Clutter suppression for moving targets detection with wideband radar

    NARCIS (Netherlands)

    Le Chevalier, F.; Krasnov, O.A.; Deudon, F.; Bidon, S.

    2011-01-01

    Wideband (high range resolution) radars have been proposed [7] as high performance systems for detection of small targets in adverse environments, due to their small resolution cells and non-ambiguity in range and velocity (velocity ambiguity removed by the measurement of the range migration of the

  6. Practical biophysics: Sensors for rapid detection of biological targets utilizing target-induced oligonucleotide annealing.

    Science.gov (United States)

    Heyduk, Tomasz

    2010-10-01

    Detection and quantitation of biomolecules is one of the most commonly performed measurements in biomedical research and clinical diagnostics. There is high demand for convenient, rapid and sensitive biomolecule detection methodologies. In this review we discuss a family of sensors that have been developed in our laboratory that share a common simple biophysical mechanism of action and that are capable of rapid detection of a diverse range of biological targets. The sensors generate fluorescence signal in the presence of the target molecule through target-induced association of short fluorochrome-labeled complementary oligonucleotides that are attached to target recognition elements of the sensors (antibodies, aptamers, etc.) via nanometer scale flexible linkers. This sensor design can be used for detecting proteins, antibodies, nucleic acids and whole cells. The assays using these sensors require only adding a sample to the sensor mix followed by simple fluorescence intensity readout. The simplicity, the speed of detection and the potential for miniaturization are the main assets of these sensors. 2010 Elsevier B.V. All rights reserved.

  7. Target amplification for broad spectrum microbial diagnostics and detection.

    Science.gov (United States)

    Leski, Tomasz A; Malanoski, Anthony P; Stenger, David A; Lin, Baochuan

    2010-02-01

    Microarrays are massively parallel detection platforms that were first used extensively for gene expression studies, but have also been successfully applied to microbial detection in a number of diverse fields requiring broad-range microbial identification. This technology has enabled researchers to gain an insight into the microbial diversity of environmental samples, facilitated discovery of a number of new pathogens and enabled studies of multipathogen infections. In contrast to gene expression studies, the concentrations of targets in analyzed samples for microbial detection are usually much lower, and require the use of nucleic acid amplification techniques. The rapid advancement of manufacturing technologies has increased the content of the microarrays; thus, the required amplification is a challenging problem. The constant parallel improvements in both microarray and sample amplification techniques in the near future may lead to a radical progression in medical diagnostics and systems for efficient detection of microorganisms in the environment.

  8. Measuring target detection performance in paradigms with high event rates.

    Science.gov (United States)

    Bendixen, Alexandra; Andersen, Søren K

    2013-05-01

    Combining behavioral and neurophysiological measurements inevitably implies mutual constraints, such as when the neurophysiological measurement requires fast-paced stimulus presentation and hence the attribution of a behavioral response to a particular preceding stimulus becomes ambiguous. We develop and test a method for validly assessing behavioral detection performance in spite of this ambiguity. We examine four approaches taken in the literature to treat such situations. We analytically derive a new variant of computing the classical parameters of signal detection theory, hit and false alarm rates, adapted to fast-paced paradigms. Each of the previous approaches shows specific shortcomings (susceptibility towards response window choice, biased estimates of behavioral detection performance). Superior performance of our new approach is demonstrated for both simulated and empirical behavioral data. Further evidence is provided by reliable correspondence between behavioral performance and the N2b component as an electrophysiological indicator of target detection. The appropriateness of our approach is substantiated by both theoretical and empirical arguments. We demonstrate an easy-to-implement solution for measuring target detection performance independent of the rate of event presentation. Thus overcoming the measurement bias of previous approaches, our method will help to clarify the behavioral relevance of different measures of cortical activation. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  9. Superpixel sparse representation for target detection in hyperspectral imagery

    Science.gov (United States)

    Dong, Chunhua; Naghedolfeizi, Masoud; Aberra, Dawit; Qiu, Hao; Zeng, Xiangyan

    2017-05-01

    Sparse Representation (SR) is an effective classification method. Given a set of data vectors, SR aims at finding the sparsest representation of each data vector among the linear combinations of the bases in a given dictionary. In order to further improve the classification performance, the joint SR that incorporates interpixel correlation information of neighborhoods has been proposed for image pixel classification. However, SR and joint SR demand significant amount of computational time and memory, especially when classifying a large number of pixels. To address this issue, we propose a superpixel sparse representation (SSR) algorithm for target detection in hyperspectral imagery. We firstly cluster hyperspectral pixels into nearly uniform hyperspectral superpixels using our proposed patch-based SLIC approach based on their spectral and spatial information. The sparse representations of these superpixels are then obtained by simultaneously decomposing superpixels over a given dictionary consisting of both target and background pixels. The class of a hyperspectral pixel is determined by a competition between its projections on target and background subdictionaries. One key advantage of the proposed superpixel representation algorithm with respect to pixelwise and joint sparse representation algorithms is that it reduces computational cost while still maintaining competitive classification performance. We demonstrate the effectiveness of the proposed SSR algorithm through experiments on target detection in the in-door and out-door scene data under daylight illumination as well as the remote sensing data. Experimental results show that SSR generally outperforms state of the art algorithms both quantitatively and qualitatively.

  10. Macrophage-targeted photodynamic detection of vulnerable atherosclerotic plaque

    Science.gov (United States)

    Hamblin, Michael R.; Tawakol, Ahmed; Castano, Ana P.; Gad, Faten; Zahra, Touqir; Ahmadi, Atosa; Stern, Jeremy; Ortel, Bernhard; Chirico, Stephanie; Shirazi, Azadeh; Syed, Sakeena; Muller, James E.

    2003-06-01

    Rupture of a vulnerable atherosclerotic plaque (VP) leading to coronary thrombosis is the chief cause of sudden cardiac death. VPs are angiographically insignificant lesions, which are excessively inflamed and characterized by dense macrophage infiltration, large necrotic lipid cores, thin fibrous caps, and paucity of smooth muscle cells. We have recently shown that chlorin(e6) conjugated with maleylated albumin can target macrophages with high selectivity via the scavenger receptor. We report the potential of this macrophage-targeted fluorescent probe to localize in VPs in a rabbit model of atherosclerosis, and allow detection and/or diagnosis by fluorescence spectroscopy or imaging. Atherosclerotic lesions were induced in New Zealand White rabbit aortas by balloon injury followed by administration of a high-fat diet. 24-hours after IV injection of the conjugate into atherosclerotic or normal rabbits, the animals were sacrificed, and aortas were removed, dissected and examined for fluorescence localization in plaques by fiber-based spectrofluorimetry and confocal microscopy. Dye uptake within the aortas was also quantified by fluorescence extraction of samples from aorta segments. Biodistribution of the dye was studied in many organs of the rabbits. Surface spectrofluorimetry after conjugate injection was able to distinguish between plaque and adjacent aorta, between atherosclerotic and normal aorta, and balloon-injured and normal iliac arteries with high significance. Discrete areas of high fluorescence (up to 20 times control were detected in the balloon-injured segments, presumably corresponding to macrophage-rich plaques. Confocal microscopy showed red ce6 fluorescence localized in plaques that showed abundant foam cells and macrophages by histology. Extraction data on aortic tissue corroborated the selectivity of the conjugate for plaques. These data support the strategy of employing macrophage-targeted fluorescent dyes to detect VP by intravascular

  11. A moving target detecting and tracking system based on DSP

    Science.gov (United States)

    Cai, Daonan; Zhao, Yuejin; Liu, Ming; Dong, Liquan; Liu, Xiaohua

    2018-01-01

    In order to solve the target fast tracking problem in embedded system, a moving target detecting and tracking algorithm based on a combination of three-frame difference and template matching is proposed. The system utilizes DSP to design a set of image processing equipment and DSP uses TI company's DM6437.Three-frame difference can detect a initial position of the target, then Mean Normalized Product Correlation(NNPROD) template matching algorithm was utilized in a partial area to achieve a precise position and reduce the amount of calculation. The algorithm utilized four templates and image compression to fit pose and scale changes when moving. To meet the real-time requirement, an improved algorithm of NNPROD was proposed under certain lighting conditions, what ' s more the C language code was optimized and TI company's highly optimized VLIB vision library was reasonably utilized. After several tests, the results showed that NNPROD can fit the changing of environmental light well, but more time was needed. The improved method can still work well with the changes of pose and scale when the light changes less intensely , and the processing speed of the improved method increased from the previous 11F / s to 23F / s.

  12. Target detection and recognition techniques of line imaging ladar sensor

    Science.gov (United States)

    Sun, Zhi-hui; Deng, Jia-hao; Yan, Xiao-wei

    2009-07-01

    A line imaging ladar sensor using linear diode laser array and linear avalanche photodiode (APD) array is developed for precise terminal guidance and intelligent proximity fuzing applications. The detection principle of line imaging ladar is discussed in detail, and design method of the line imaging ladar sensor system is given. Taking military tank target as example, simulated tank height and intensity images are obtained by the line imaging ladar simulation system. The subsystems of line imaging ladar sensor including transmitter and receiver are designed. Multi-pulse coherent algorithm and correlation detection method are adopted to improve the SNR of echo and to estimate time-of-flight, respectively. Experiment results show that the power SNR can be improved by N (number of coherent average) times and the maximum range error is 0.25 m. A few of joint transform correlation (JTC) techniques are discussed to improve noncooperative target recognition capability in height image with complex background. Simulation results show that binary JTC, non-zero-order modified fringe-adjusted JTC and non-zero-order amplitude-modulated JTC can improve the target recognition performance effectively.

  13. Detection and track of a stochastic target using multiple measurements

    Energy Technology Data Exchange (ETDEWEB)

    Cunningham, C.T.

    1995-11-01

    The authors are interested in search and tracking problems. In a search, the target might be located among a number of hiding places. Multiple measurements from various locations might be used to determine the likelihood that a particular hiding place is occupied. An obvious example would be a search for a weak radiation source in a building. Search teams might make many measurements with radiation detectors and analyze this data to determine likely areas for further searching. In this paper the authors present a statistical interpretation of the implications of measurements made on a stochastic system, one which makes random state transitions with known average rates. Knowledge of the system is represented as a statistical ensemble of instances which accord with measurements and prior information. The evolution of ratios of populations in this ensemble due to measurements and stochastic transitions may be calculated efficiently. Applied to target detection and tracking, this approach allows a rigorous definition of probability of detection and probability of false alarm and reveals a computationally useful functional relationship between the two. An example of a linear array of simple counters is considered in detail. For it, accurate analytic approximations are developed for detection and tracking statistics as functions of system parameters. A single measure of effectiveness for individual sensors is found which is a major determinant of system performance and which would be useful for initial sensor design.

  14. Waveguide invariant broadband target detection and reverberation estimation.

    Science.gov (United States)

    Goldhahn, Ryan; Hickman, Granger; Krolik, Jeffrey

    2008-11-01

    Reverberation often limits the performance of active sonar systems. In particular, backscatter off of a rough ocean floor can obscure target returns and/or large bottom scatterers can be easily confused with water column targets of interest. Conventional active sonar detection involves constant false alarm rate (CFAR) normalization of the reverberation return which does not account for the frequency-selective fading caused by multipath propagation. This paper presents an alternative to conventional reverberation estimation motivated by striations observed in time-frequency analysis of active sonar data. A mathematical model for these reverberation striations is derived using waveguide invariant theory. This model is then used to motivate waveguide invariant reverberation estimation which involves averaging the time-frequency spectrum along these striations. An evaluation of this reverberation estimate using real Mediterranean data is given and its use in a generalized likelihood ratio test based CFAR detector is demonstrated. CFAR detection using waveguide invariant reverberation estimates is shown to outperform conventional cell-averaged and frequency-invariant CFAR detection methods in shallow water environments producing strong reverberation returns which exhibit the described striations.

  15. High Resolution Software Defined Radar System for Target Detection

    Directory of Open Access Journals (Sweden)

    S. Costanzo

    2013-01-01

    Full Text Available The Universal Software Radio Peripheral USRP NI2920, a software defined transceiver so far mainly used in Software Defined Radio applications, is adopted in this work to design a high resolution L-Band Software Defined Radar system. The enhanced available bandwidth, due to the Gigabit Ethernet interface, is exploited to obtain a higher slant-range resolution with respect to the existing Software Defined Radar implementations. A specific LabVIEW application, performing radar operations, is discussed, and successful validations are presented to demonstrate the accurate target detection capability of the proposed software radar architecture. In particular, outdoor and indoor test are performed by adopting a metal plate as reference structure located at different distances from the designed radar system, and results obtained from the measured echo are successfully processed to accurately reveal the correct target position, with the predicted slant-range resolution equal to 6 m.

  16. Wide field-of-view target detection and simultaneous narrow field of view target analysis

    Science.gov (United States)

    Nichols, Richard W.; Miller, Geoffrey M.

    2009-05-01

    Protecting national borders, military and industrial complexes, national Infrastructure and high-value targets is critical to national security. Traditional solutions use a combination of ground surveillance radar, motion detection systems and video surveillance systems. Our development objective was to provide wide area 360-degree surveillance and ground-moving target detection using a passive optical system. In order to meet this objective, the development of an optical system capable of wide-area surveillance with intelligent cueing, high-resolution tracking and target identification is required. The predominant approach to optical surveillance has traditionally been gimbaled narrow field-of-view systems. These systems miss the majority of events occurring around them because of their inability to focus on anything other than a single event or object at any one time. Details of the system requirements definition, design trade studies and selected design configurations are discussed. The experimental results obtained during the current development phase have provided consistently high quality images and enhanced situational awareness. A summary of field validation methods and results is provided.

  17. Small maritime target detection through false color fusion

    Science.gov (United States)

    Toet, Alexander; Wu, Tirui

    2008-04-01

    We present an algorithm that produces a fused false color representation of a combined multiband IR and visual imaging system for maritime applications. Multispectral IR imaging techniques are increasingly deployed in maritime operations, to detect floating mines or to find small dinghies and swimmers during search and rescue operations. However, maritime backgrounds usually contain a large amount of clutter that severely hampers the detection of small targets. Our new algorithm deploys the correlation between the target signatures in two different IR frequency bands (3-5 and 8-12 μm) to construct a fused IR image with a reduced amount of clutter. The fused IR image is then combined with a visual image in a false color RGB representation for display to a human operator. The algorithm works as follows. First, both individual IR bands are filtered with a morphological opening top-hat transform to extract small details. Second, a common image is extracted from the two filtered IR bands, and assigned to the red channel of an RGB image. Regions of interest that appear in both IR bands remain in this common image, while most uncorrelated noise details are filtered out. Third, the visual band is assigned to the green channel and, after multiplication with a constant (typically 1.6) also to the blue channel. Fourth, the brightness and colors of this intermediate false color image are renormalized by adjusting its first order statistics to those of a representative reference scene. The result of these four steps is a fused color image, with naturalistic colors (bluish sky and grayish water), in which small targets are clearly visible.

  18. Kepler Planet Detection Metrics: Per-Target Detection Contours for Data Release 25

    Science.gov (United States)

    Burke, Christopher J.; Catanzarite, Joseph

    2017-01-01

    A necessary input to planet occurrence calculations is an accurate model for the pipeline completeness (Burke et al., 2015). This document describes the use of the Kepler planet occurrence rate products in order to calculate a per-target detection contour for the measured Data Release 25 (DR25) pipeline performance. A per-target detection contour measures for a given combination of orbital period, Porb, and planet radius, Rp, what fraction of transit signals are recoverable by the Kepler pipeline (Twicken et al., 2016; Jenkins et al., 2017). The steps for calculating a detection contour follow the procedure outlined in Burke et al. (2015), but have been updated to provide improved accuracy enabled by the substantially larger database of transit injection and recovery tests that were performed on the final version (i.e., SOC 9.3) of the Kepler pipeline (Christiansen, 2017; Burke Catanzarite, 2017a). In the following sections, we describe the main inputs to the per-target detection contour and provide a worked example of the python software released with this document (Kepler Planet Occurrence Rate Tools KeplerPORTs)1 that illustrates the generation of a detection contour in practice. As background material for this document and its nomenclature, we recommend the reader be familiar with the previous method of calculating a detection contour (Section 2 of Burke et al.,2015), input parameters relevant for describing the data quantity and quality of Kepler targets (Burke Catanzarite, 2017b), and the extensive new transit injection and recovery tests of the Kepler pipeline (Christiansen et al., 2016; Burke Catanzarite, 2017a; Christiansen, 2017).

  19. Point-of-care detection of extracellular vesicles: Sensitivity optimization and multiple-target detection.

    Science.gov (United States)

    Oliveira-Rodríguez, Myriam; Serrano-Pertierra, Esther; García, Agustín Costa; López-Martín, Soraya; Yañez-Mo, María; Cernuda-Morollón, Eva; Blanco-López, M C

    2017-01-15

    Extracellular vesicles (EVs) are membrane-bound nanovesicles delivered by different cellular lineages under physiological and pathological conditions. Although these vesicles have shown relevance as biomarkers for a number of diseases, their isolation and detection still has several technical drawbacks, mainly related with problems of sensitivity and time-consumed. Here, we reported a rapid and multiple-targeted lateral flow immunoassay (LFIA) system for the detection of EVs isolated from human plasma. A range of different labels (colloidal gold, carbon black and magnetic nanoparticles) was compared as detection probe in LFIA, being gold nanoparticles that showed better results. Using this platform, we demonstrated that improvements may be carried out by incorporating additional capture lines with different antibodies. The device exhibited a limit of detection (LOD) of 3.4×10 6 EVs/µL when anti-CD81 and anti-CD9 were selected as capture antibodies in a multiple-targeted format, and anti-CD63 labeled with gold nanoparticles was used as detection probe. This LFIA, coupled to EVs isolation kits, could become a rapid and useful tool for the point-of-care detection of EVs, with a total analysis time of two hours. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Targeted and non-targeted detection of lemon juice adulteration by LC-MS and chemometrics.

    Science.gov (United States)

    Wang, Zhengfang; Jablonski, Joseph E

    2016-01-01

    Economically motivated adulteration (EMA) of lemon juice was detected by LC-MS and principal component analysis (PCA). Twenty-two batches of freshly squeezed lemon juice were adulterated by adding an aqueous solution containing 5% citric acid and 6% sucrose to pure lemon juice to obtain 30%, 60% and 100% lemon juice samples. Their total titratable acidities, °Brix and pH values were measured, and then all the lemon juice samples were subject to LC-MS analysis. Concentrations of hesperidin and eriocitrin, major phenolic components of lemon juice, were quantified. The PCA score plots for LC-MS datasets were used to preview the classification of pure and adulterated lemon juice samples. Results showed a large inherent variability in the chemical properties among 22 batches of 100% lemon juice samples. Measurement or quantitation of one or several chemical properties (targeted detection) was not effective in detecting lemon juice adulteration. However, by using the LC-MS datasets, including both chromatographic and mass spectrometric information, 100% lemon juice samples were successfully differentiated from adulterated samples containing 30% lemon juice in the PCA score plot. LC-MS coupled with chemometric analysis can be a complement to existing methods for detecting juice adulteration.

  1. Detection of Perfectly-Conducting Targets with Airborne Electromagnetic Systems

    Science.gov (United States)

    Smiarowski, Adam

    A significant problem with exploring for electrically conductive mineral deposits with airborne electromagnetic (AEM) methods is that many of the most valuable sulphide deposits are too conductive to be detected with conventional systems. High-grade sulphide deposits with bulk electrical conductivities on the order of 100,000 S/m can appear as "perfect conductors" to most EM systems because the decay of secondary fields (the "time constant" of the deposit) generated in the target by the system transmitter takes much longer than the short measuring time of EM systems. Their EM response is essentially undetectable with off-time measurements. One solution is to make measurements during the transmitter on-time when the secondary field of the target produced by magnetic flux exclusion is large. The difficulty is that the secondary field must be measured in the presence of a primary field which is orders of magnitude larger. The goal of this thesis is to advance the methodology of making AEM measurements during transmitter on-time by analysing experimental data from three different AEM systems. The first system analysed is a very large separation, two helicopter system where geometry is measured using GPS sensors. In order to calculate the primary field at the receiver with sufficient accuracy, the very large (nominally 400 m) separation requires geometry to be known to better than 1 m. Using the measured geometry to estimate and remove the primary field, I show that a very conductive target can be detected at depths of 200m using the total secondary field. I then used fluxgate magnetometers to correct for receiver rotation which allowed the component of the secondary field to be determined. The second system I examined was a large separation fixed-wing AEM system. Using a towed receiver bird with a smaller (≈ 135m) separation, the geometry must be known much more accurately. In the absence of direct measurement of this geometry, I used a least-squares prediction

  2. Deterministic Aided STAP for Target Detection in Heterogeneous Situations

    Directory of Open Access Journals (Sweden)

    J.-F. Degurse

    2013-01-01

    Full Text Available Classical space-time adaptive processing (STAP detectors are strongly limited when facing highly heterogeneous environments. Indeed, in this case, representative target free data are no longer available. Single dataset algorithms, such as the MLED algorithm, have proved their efficiency in overcoming this problem by only working on primary data. These methods are based on the APES algorithm which removes the useful signal from the covariance matrix. However, a small part of the clutter signal is also removed from the covariance matrix in this operation. Consequently, a degradation of clutter rejection performance is observed. We propose two algorithms that use deterministic aided STAP to overcome this issue of the single dataset APES method. The results on realistic simulated data and real data show that these methods outperform traditional single dataset methods in detection and in clutter rejection.

  3. Transcranial direct current stimulation accelerates allocentric target detection.

    Science.gov (United States)

    Medina, Jared; Beauvais, Jacques; Datta, Abhishek; Bikson, Marom; Coslett, H Branch; Hamilton, Roy H

    2013-05-01

    Previous research on hemispatial neglect has provided evidence for dissociable mechanisms for egocentric and allocentric processing. Although a few studies have examined whether tDCS to posterior parietal cortex can be beneficial for attentional processing in neurologically intact individuals, none have examined the potential effect of tDCS on allocentric and/or egocentric processing. Our objective was to examine whether transcranial direct current stimulation (tDCS), a noninvasive brain stimulation technique that can increase (anodal) or decrease (cathodal) cortical activity, can affect visuospatial processing in an allocentric and/or egocentric frame of reference. We tested healthy individuals on a target detection task in which the target--a circle with a gap--was either to the right or left of the viewer (egocentric), or contained a gap on the right or left side of the circle (allocentric). Individuals performed the task before, during, and after tDCS to the posterior parietal cortex in one of three stimulation conditions--right anodal/left cathodal, right cathodal/left anodal, and sham. We found an allocentric hemispatial effect both during and after tDCS, such that right anodal/left cathodal tDCS resulted in faster reaction times for detecting stimuli with left-sided gaps compared to right-sided gaps. Our study suggests that right anodal/left cathodal tDCS has a facilitatory effect on allocentric visuospatial processing, and might be useful as a therapeutic technique for individuals suffering from allocentric neglect. Copyright © 2013 Elsevier Inc. All rights reserved.

  4. [Research on Anti-Camouflaged Target System Based on Spectral Detection and Image Recognition].

    Science.gov (United States)

    Wang, Bo; Gao, Yu-bin; Lu, Xu-tao

    2015-05-01

    To be able to quickly and efficiently identify Enemy camouflaged maneuvering targets in the wild environment, target recognition system was designed based on spectral detection technology and video target recognition method. System was composed of the visible light image acquisition module and static interferometer module. The system used image recognition technology to obtain two dimensional video images of measurement region, and through spectrum detection technology to identify targets. Ultimately, measured target was rebuilt on the corresponding position in the image, so the visual target recognition was realized. After the theoretical derivation, identifiable target function formula of the system was obtained, and based on the functional relationship to complete the quantitative experiments for target recognition. In the experiments, maneuvering target in the battlefield environment was simulated by a car. At different distances, the background was respectively selected to detect a flat wasteland, bushes and abandoned buildings. Obvious target, coated camouflage target and covered disguises target was respectively spectrum detection. Experimental results show that spectrum detection technology can overcome the shortcomings of unrecognized the camouflaged target by traditional image target recognition method. Testing background had some influence on spectrum detection results, and the continuity of the background was conducive to target recognition. Covered disguises target was the hardest to identify in various camouflage mode. As the distance between the target and the system increases, signal to noise ratio of the system was reduced. In summary, the system can achieve effective recognition of camouflaged targets to meet the design requirements.

  5. Magneto-mechanical trapping systems for biological target detection

    KAUST Repository

    Li, Fuquan

    2014-03-29

    We demonstrate a magnetic microsystem capable of detecting nucleic acids via the size difference between bare magnetic beads and bead compounds. The bead compounds are formed through linking nonmagnetic beads and magnetic beads by the target nucleic acids. The system comprises a tunnel magneto-resistive (TMR) sensor, a trapping well, and a bead-concentrator. The TMR sensor detects the stray field of magnetic beads inside the trapping well, while the sensor output depends on the number of beads. The size of the bead compounds is larger than that of bare magnetic beads, and fewer magnetic beads are required to fill the trapping well. The bead-concentrator, in turn, is capable of filling the trap in a controlled fashion and so to shorten the assay time. The bead-concentrator includes conducting loops surrounding the trapping well and a conducting line underneath. The central conducting line serves to attract magnetic beads in the trapping well and provides a magnetic field to magnetize them so to make them detectable by the TMR sensor. This system excels by its simplicity in that the DNA is incubated with magnetic and nonmagnetic beads, and the solution is then applied to the chip and analyzed in a single step. In current experiments, a signal-to-noise ratio of 40.3 dB was obtained for a solution containing 20.8 nM of DNA. The sensitivity and applicability of this method can be controlled by the size or concentration of the nonmagnetic bead, or by the dimension of the trapping well.

  6. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    Directory of Open Access Journals (Sweden)

    Sungho Kim

    2016-07-01

    Full Text Available Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR images or infrared (IR images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter and an asymmetric morphological closing filter (AMCF, post-filter into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic

  7. Target detection using the background model from the topological anomaly detection algorithm

    Science.gov (United States)

    Dorado Munoz, Leidy P.; Messinger, David W.; Ziemann, Amanda K.

    2013-05-01

    The Topological Anomaly Detection (TAD) algorithm has been used as an anomaly detector in hyperspectral and multispectral images. TAD is an algorithm based on graph theory that constructs a topological model of the background in a scene, and computes an anomalousness ranking for all of the pixels in the image with respect to the background in order to identify pixels with uncommon or strange spectral signatures. The pixels that are modeled as background are clustered into groups or connected components, which could be representative of spectral signatures of materials present in the background. Therefore, the idea of using the background components given by TAD in target detection is explored in this paper. In this way, these connected components are characterized in three different approaches, where the mean signature and endmembers for each component are calculated and used as background basis vectors in Orthogonal Subspace Projection (OSP) and Adaptive Subspace Detector (ASD). Likewise, the covariance matrix of those connected components is estimated and used in detectors: Constrained Energy Minimization (CEM) and Adaptive Coherence Estimator (ACE). The performance of these approaches and the different detectors is compared with a global approach, where the background characterization is derived directly from the image. Experiments and results using self-test data set provided as part of the RIT blind test target detection project are shown.

  8. EEG indices of reward motivation and target detectability in a rapid visual detection task.

    Science.gov (United States)

    Hughes, Gethin; Mathan, Santosh; Yeung, Nick

    2013-01-01

    A large corpus of data has demonstrated the sensitivity of behavioral and neural measures to variation in the availability of reward. The present study aimed to extend this work by exploring reward motivation in an RSVP task using complex satellite imagery. We found that reward motivation significantly influenced neural activity both in the preparatory period and in response to target images. Pre-stimulus alpha activity and, to a lesser degree, P3 and CNV amplitude were found to be significantly predictive of reward condition on single trials. Target-locked P3 amplitude was modulated both by reward condition and by variation in target detectability inherent to our task. We further quantified this exogenous influence, showing that P3 differences reflected single-trial variation in P3 amplitude for different targets. These findings provide theoretical insight into the neural indices of reward in an RSVP task, and have important applications in the field of satellite imagery analysis. Copyright © 2012 Elsevier Inc. All rights reserved.

  9. Infrared small target detection method based on decomposition of polarization information

    Science.gov (United States)

    Zhang, Yan; Shi, Zhi-Guang; Qiu, Tiao-Wen

    2017-05-01

    A method of feature extraction and small target detection, based on infrared polarization, which uses the technical superiority of infrared polarization imaging in artificial target detection to solve the clutter interference problem in infrared target detection, is proposed. First, using the differences in the polarization characteristics of the artificial target and the natural background, the infrared polarization information models for the target and background are established. The compositions of intensity information, polarization information, and target polarization information are extracted, and enhancement measures are analyzed. Then, the variable polarization theories are combined to extract the target polarization characteristics and suppress the background clutter. Finally, the infrared small target is detected, and comparisons with existing methods demonstrate the effectiveness and reliability of the proposed method.

  10. Automated Threshold Selection for Template-Based Sonar Target Detection

    Science.gov (United States)

    2017-08-01

    Matched Filter Each matched filter mask contains three distinct regions: highlight, dead zone , and shadow/post- target. A different set of matched...and shadow zones . Both model both the targets and the backgrounds. Several methods have also used the fusion of multiple frequency bands to improve

  11. Recoil detection with a polarized sup 3 He target

    CERN Document Server

    Higinbotham, D W; Bauer, T; Boersma, D J; Van der Brand, J F J; Bulten, H J; Van Buuren, L D; Ent, R; Ferro-Luzzi, M; Geurts, D; Harvey, M; Heimberg, P; Norum, B E; Passchier, I; Poolman, H R; Six, E; Steenbakkers, M F M; Szczerba, D; Vries, H D

    2000-01-01

    The ultra-thin gas targets used in storage ring internal target experiments allow low energy, heavy nuclei to emerge from the target region. A detector capable of analyzing these nuclei provides unique access to many nuclear reactions. We report here the first use of such a detector in conjunction with a polarized sup 3 He internal target and a polarized electron beam. The results of using the detector as a luminosity monitor and as a polarimeter to measure the product of beam and target polarizations are presented. The ability to study coherent pion production via the reactions sup 3 H=vector (e-vector, e' sup 3 He)pi sup 0 and sup 3 H-vector(e-vector, e' sup 3 H)pi sup + is shown along with the ability of the detector to unambiguously separate the two- and three-body breakup channels of the reaction sup 3 H-vectore(e-vector, e'p).

  12. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    National Research Council Canada - National Science Library

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-01-01

    .... This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate...

  13. Theoretical foundations of NRL spectral target detection algorithms.

    Science.gov (United States)

    Schaum, Alan

    2015-11-01

    The principal spectral detection algorithms developed at the Naval Research Laboratory (NRL) over the past 20 years for use in operational systems are described. These include anomaly detectors, signature-based methods, and techniques for anomalous change detection. Newer derivations are provided that have motivated more recent work. Mathematical methods facilitating the use of forward models for the prediction of spectral signature statistics are described and a detection algorithm is derived for ocean surveillance that is based on principles of clairvoyant fusion.

  14. Two Algorithms for the Detection and Tracking of Moving Vehicle Targets in Aerial Infrared Image Sequences

    Directory of Open Access Journals (Sweden)

    Yutian Cao

    2015-12-01

    Full Text Available In this paper, by analyzing the characteristics of infrared moving targets, a Symmetric Frame Differencing Target Detection algorithm based on local clustering segmentation is proposed. In consideration of the high real-time performance and accuracy of traditional symmetric differencing, this novel algorithm uses local grayscale clustering to accomplish target detection after carrying out symmetric frame differencing to locate the regions of change. In addition, the mean shift tracking algorithm is also improved to solve the problem of missed targets caused by error convergence. As a result, a kernel-based mean shift target tracking algorithm based on detection updates is also proposed. This tracking algorithm makes use of the interaction between detection and tracking to correct the tracking errors in real time and to realize robust target tracking in complex scenes. In addition, the validity, robustness and stability of the proposed algorithms are all verified by experiments on mid-infrared aerial sequences with vehicles as targets.

  15. A chest-shape target automatic detection method based on Deformable Part Models

    Science.gov (United States)

    Zhang, Mo; Jin, Weiqi; Li, Li

    2016-10-01

    Automatic weapon platform is one of the important research directions at domestic and overseas, it needs to accomplish fast searching for the object to be shot under complex background. Therefore, fast detection for given target is the foundation of further task. Considering that chest-shape target is common target of shoot practice, this paper treats chestshape target as the target and studies target automatic detection method based on Deformable Part Models. The algorithm computes Histograms of Oriented Gradient(HOG) features of the target and trains a model using Latent variable Support Vector Machine(SVM); In this model, target image is divided into several parts then we can obtain foot filter and part filters; Finally, the algorithm detects the target at the HOG features pyramid with method of sliding window. The running time of extracting HOG pyramid with lookup table can be shorten by 36%. The result indicates that this algorithm can detect the chest-shape target in natural environments indoors or outdoors. The true positive rate of detection reaches 76% with many hard samples, and the false positive rate approaches 0. Running on a PC (Intel(R)Core(TM) i5-4200H CPU) with C++ language, the detection time of images with the resolution of 640 × 480 is 2.093s. According to TI company run library about image pyramid and convolution for DM642 and other hardware, our detection algorithm is expected to be implemented on hardware platform, and it has application prospect in actual system.

  16. Approach for moving small target detection in infrared image sequence based on reinforcement learning

    Science.gov (United States)

    Wang, Chuanyun; Qin, Shiyin

    2016-09-01

    Addressing the problems of moving small target detection in infrared image sequence caused by background clutter and target size variation with time, an approach for moving small target detection is proposed under a pipeline framework with an optimization strategy based on reinforcement learning. The pipeline framework is composed by pipeline establishment, target-background images separation, and target confirmation, in which the pipeline is established by designating several successive images with temporal sliding window, target-background images separation is dealt with low-rank and sparse matrix decomposition via robust principal component analysis, and target confirmation is achieved by employing a voting mechanism over more than one separated target images of the same input image. For unremitting optimization of target-background images separation, the weighting parameter of low-rank and sparse matrix decomposition is dynamically regulated by the way of reinforcement learning in consecutive detection, in which the complexity evaluation from sequential infrared images and results assessment of moving small target detection are integrated. The experiment results over four infrared small target image sequences with different cloudy sky backgrounds demonstrate the effectiveness and advantages of the proposed approach in both background clutter suppression and small target detection.

  17. Physics-based Detection of Subpixel Targets in Hyperspectral Imagery

    Science.gov (United States)

    2007-01-01

    IEEE Proceedings of the1999 Aerospace Conference, vol. 4, pp 177-181, March 1999. [4] E. A. Ashton and A. Schaum , “Algorithms for the detection...34Anomaly Detection from Hyperspectral Imagery," IEEE Signal Processing Magazine, vol. 19, no. 1, pp. 58-69, January 2002. [104] A.D. Stocker and P. Schaum

  18. A comparison of classification techniques for glacier change detection using multispectral images

    Directory of Open Access Journals (Sweden)

    Rahul Nijhawan

    2016-09-01

    Full Text Available Main aim of this paper is to compare the classification accuracies of glacier change detection by following classifiers: sub-pixel classification algorithm, indices based supervised classification and object based algorithm using Landsat imageries. It was observed that shadow effect was not removed in sub-pixel based classification which was removed by the indices method. Further the accuracy was improved by object based classification. Objective of the paper is to analyse different classification algorithms and interpret which one gives the best results in mountainous regions. The study showed that object based method was best in mountainous regions as optimum results were obtained in the shadowed covered regions.

  19. Targeting Premalignant Lesions - Implications for Early Breast Cancer Detection and Intervention

    Science.gov (United States)

    2017-04-01

    AWARD NUMBER: W81XWH-14-1-0032 TITLE: Targeting Premalignant Lesions - Implications for Early Breast Cancer Detection and Intervention PRINCIPAL...Mar 2017 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Targeting Premalignant Lesions - Implications for Early Breast Cancer Detection and...12. DISTRIBUTION / AVAILABILITY STATEMENT Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Breast cancer

  20. UAV to UAV Target Detection and Pose Estimation

    Science.gov (United States)

    2012-06-01

    open computer vision) for real-time implementation and faster computation since OpenCV has precompiled libraries that may work better for real image...affordable CCD cameras and open coding libraries . We accomplish this by reviewing past literature about UAV detection and pose estimation and exploring...capabilities suitable for the purpose of UAV to UAV detection and pose estima- tion using affordable CCD cameras and open coding libraries . We

  1. Continuum fusion solutions for replacement target models in electro-optic detection.

    Science.gov (United States)

    Schaum, Alan

    2014-05-01

    The additive target model is used routinely in the statistical detection of opaque targets, despite its phenomenological inaccuracy. The more appropriate replacement target model is seldom used, because the standard method for producing a detection algorithm from it proves to be intractable, unless narrow restrictions are imposed. Now, the recently developed continuum fusion (CF) methodology allows an expanded solution set to the general replacement target problem. It also provides a mechanism for producing approximate solutions for the standard approach. We illustrate the principles of CF by using them to generate both types of answers for the correct detection model.

  2. Maneuvering Target Detection Based on JRC System in Gaussian and Non-Gaussian Clutter

    Directory of Open Access Journals (Sweden)

    Yu Yao

    2015-01-01

    Full Text Available Aimed at the problem of detecting maneuvering targets in the Gaussian and sea clutter environments and based on the established motion state model, this paper proposed a new scheme that uses a joint radar-communication (JRC system with Kalman filter to accurately detect the target with the generalized likelihood ratio test (GLRT theory and a constant false alarm rate (CFAR based threshold. Also, the theoretical threshold and probability function of GLRT target detection based on CFAR were given. Moreover, target detection probability of the new JRC system in Weibull and K distribution clutter is deduced. In addition to theoretical considerations, simulations and measurement results of the new JRC systems demonstrate excellent detection performance for maneuvering targets in the Weibull and K distribution channel.

  3. Hitting the Target: How T Cells Detect and Eliminate Tumors.

    Science.gov (United States)

    Zamora, Anthony E; Crawford, Jeremy Chase; Thomas, Paul G

    2018-01-15

    The successes of antitumor immuno-based therapies and the application of next-generation sequencing to mutation profiling have produced insights into the specific targets of antitumor T cells. Mutated proteins have tremendous potential as targets for interventions using autologous T cells or engineered cell therapies and may serve as important correlates of efficacy for immunoregulatory interventions including immune checkpoint blockade. As mutated self, tumors present an exceptional case for host immunity, which has primarily evolved in response to foreign pathogens. Tumor Ags' resemblance to self may limit immune recognition, but key features appear to be the same between antipathogen and antitumor responses. Determining which targets will make efficacious Ags and which responses might be elicited therapeutically are key questions for the field. Here we discuss current knowledge on antitumor specificity, the mutations that provide immunogenic targets, and how cross-reactivity and immunodominance may contribute to variation in immune responses among tumor types. Copyright © 2018 by The American Association of Immunologists, Inc.

  4. Multiple Detection Probabilistic Data Association Filter for Multistatic Target Tracking

    Science.gov (United States)

    2011-07-01

    to identify target originated measurement from a clutter [2], [4], [6], [12], [13]. Non-Bayesian, one-to-one matching, hard decision oriented data...volume () (see section III-B). ∙ Poisson model (parametric MD-PDA): (()) = − () ( ())() ()! (40) where is spacial

  5. Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images

    Directory of Open Access Journals (Sweden)

    Anton G. Pavlov

    2008-02-01

    Full Text Available We present in this paper a sequential Monte Carlo methodology for joint detection and tracking of a multiaspect target in image sequences. Unlike the traditional contact/association approach found in the literature, the proposed methodology enables integrated, multiframe target detection and tracking incorporating the statistical models for target aspect, target motion, and background clutter. Two implementations of the proposed algorithm are discussed using, respectively, a resample-move (RS particle filter and an auxiliary particle filter (APF. Our simulation results suggest that the APF configuration outperforms slightly the RS filter in scenarios of stealthy targets.

  6. Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images

    Directory of Open Access Journals (Sweden)

    Bruno MarceloGS

    2008-01-01

    Full Text Available We present in this paper a sequential Monte Carlo methodology for joint detection and tracking of a multiaspect target in image sequences. Unlike the traditional contact/association approach found in the literature, the proposed methodology enables integrated, multiframe target detection and tracking incorporating the statistical models for target aspect, target motion, and background clutter. Two implementations of the proposed algorithm are discussed using, respectively, a resample-move (RS particle filter and an auxiliary particle filter (APF. Our simulation results suggest that the APF configuration outperforms slightly the RS filter in scenarios of stealthy targets.

  7. Detection of Metallic and Electronic Radar Targets by Acoustic Modulation of Electromagnetic Waves

    Science.gov (United States)

    2017-07-01

    electronic targets within the near field of an ultra-wideband radar antenna operating in the ultra-high frequency band. 15. SUBJECT TERMS radar ...ARL-TR-8076● JULY 2017 US Army Research Laboratory Detection of Metallic and Electronic Radar Targets by Acoustic Modulation of...US Army Research Laboratory Detection of Metallic and Electronic Radar Targets by Acoustic Modulation of Electromagnetic Waves by Gregory

  8. Optimal intermittence in search strategies under speed-selective target detection.

    Science.gov (United States)

    Campos, Daniel; Méndez, Vicenç; Bartumeus, Frederic

    2012-01-13

    Random search theory has been previously explored for both continuous and intermittent scanning modes with full target detection capacity. Here we present a new class of random search problems in which a single searcher performs flights of random velocities, the detection probability when it passes over a target location being conditioned to the searcher speed. As a result, target detection involves an N-passage process for which the mean search time is here analytically obtained through a renewal approximation. We apply the idea of speed-selective detection to random animal foraging since a fast movement is known to significantly degrade perception abilities in many animals. We show that speed-selective detection naturally introduces an optimal level of behavioral intermittence in order to solve the compromise between fast relocations and target detection capability.

  9. The research on infrared small-target detection technology under complex background

    Science.gov (United States)

    Liu, Lei; Wang, Xin; Chen, Jilu; Huang, Zhijian

    2011-06-01

    In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detecting are described. Then, according to actual needs and the comparison results of those algorithms, some of them are optimized in combination with the image pre-processing. On the foundation of above works, a moving target detecting and tracking software base on the OpenCV is developed by the software developing platform MFC. Three kinds of detecting algorithms are integrated in this software. These three detecting algorithms are Frame Difference method, Background Estimation method and Mixture Gaussian Modeling method. In order to explain the software clearly, the framework and the function are described in this paper. At last, the implementing processes and results are analyzed, and those algorithms for detecting targets are evaluated from the two aspects of subjective and objective. This paper is very significant in the application of the infrared target detecting technology.

  10. Co-seismic displacements from differencing and sub-pixel correlation of multi-temporal LiDAR and cadastral surveys: application to the Greendale Fault, Canterbury, New Zealand

    Science.gov (United States)

    Duffy, B. G.; Van Dissen, R.; Quigley, M.; Litchfield, N. J.; McInnes, C.; Leprince, S.; Barrell, D.; Stahl, T. A.; Bilderback, E. L.

    2011-12-01

    Surface rupture on the dextral strike-slip Greendale fault during the 2010 Mw 7.1 Darfield (Canterbury), earthquake in New Zealand terminated in a releasing bend at the western end of the fault. Our first-ever co-seismic application of multi-temporal aerial LiDAR, coupled with cadastral surveying, real time kinematic GPS scarp profiling and offset mapping provides unprecedented documentation of surface displacements at the western end of the Greendale fault, particularly at the transition into the releasing bend. Cadastral trilateration data from the northern end of the releasing bend area demonstrate that the hanging wall (NE) side of the fault moved 1.5 m to the southeast while the footwall (SW) side of the fault moved 0.6 m to the southwest. This resulted in an oblique transtensional net slip of 2.5 m. At the southern end of the releasing bend, the north-side-down transtensional structure transitions into a north-side down transpressional structure. High-resolution absolute vertical motions associated with this transition, as well as relationships of drainage morphology to fault geometry, are captured by differencing of pre- and post-fault LiDAR. Vertical differencing reveals the distribution of vertical offsets, with some scarps defined that have vertical displacement gradients of only 1:1000. The geomorphology of these subtle vertical displacements reveals that the transition into the releasing bend is accommodated by a restraining stepover. Sub-pixel correlation of the pre-and post-earthquake LiDAR rasters using COSI-Corr (http://www.tectonics.caltech.edu/slip_history/spot_coseis/index.html) additionally reveal E-W shortening of approximately 0.8 m across a discontinuity that represents one side of the restraining stepover. This is consistent with the cadastral survey results. Our results demonstrate the utility of multi-temporal LiDAR for documenting both the vertical and horizontal components of co-seismic deformation.

  11. Effects of Cue Reliability on Target Detection and Visual Scanning

    Science.gov (United States)

    2010-12-01

    system is high, it is believed that the potential for a missed target and loss of life might dissuade Soldiers from totally ignoring the system, but...had normal hearing , as determined by an audiogram. The voluntary, fully informed consent of the persons used in this research was obtained as...pressure level (SPL) through the participant’s headphones was 73-dB SPL as measured through an artificial ear. A sample view of the three simulator

  12. Constant false alarm rate algorithm for the dim-small target detection based on the distribution characteristics of target coordinates

    Science.gov (United States)

    Fei, Xiao-Liang; Ren, Kan; Qian, Wei-xian; Wang, Peng-cheng

    2015-10-01

    CFAR (Constant False Alarm Rate) is a key technology in Infrared dim-small target detection system. Because the traditional constant false alarm rate detection algorithm gets the probability density distribution which is based on the pixel information of each area in the whole image and calculates the target segmentation threshold of each area by formula of Constant false alarm rate, the problems including the difficulty of probability distribution statistics and large amount of algorithm calculation and long delay time are existing. In order to solve the above problems effectively, a formula of Constant false alarm rate based on target coordinates distribution is presented. Firstly, this paper proposes a new formula of Constant false alarm rate by improving the traditional formula of Constant false alarm rate based on the single grayscale distribution which objective statistical distribution features are introduced. So the control of false alarm according to the target distribution information is implemented more accurately and the problem of high false alarm that is caused of the complex background in local area as the cloud reflection and the ground clutter interference is solved. At the same time, in order to reduce the amount of algorithm calculation and improve the real-time characteristics of algorithm, this paper divides the constant false-alarm statistical area through two-dimensional probability density distribution of target number adaptively which is different from the general identifying methods of constant false-alarm statistical area. Finally, the target segmentation threshold of next frame is calculated by iteration based on the function of target distribution probability density in image sequence which can achieve the purpose of controlling the false alarm until the false alarm is down to the upper limit. The experiment results show that the proposed method can significantly improve the operation time and meet the real-time requirements on

  13. Computational optimisation of targeted DNA sequencing for cancer detection

    DEFF Research Database (Denmark)

    Martinez, Pierre; McGranahan, Nicholas; Birkbak, Nicolai Juul

    2013-01-01

    Despite recent progress thanks to next-generation sequencing technologies, personalised cancer medicine is still hampered by intra-tumour heterogeneity and drug resistance. As most patients with advanced metastatic disease face poor survival, there is need to improve early diagnosis. Analysing...... introduce biases towards in-frame mutations and would compromise the reproducibility of tumour detection....

  14. Detecting proxima b's atmosphere with JWST targeting CO

    NARCIS (Netherlands)

    Snellen, I. A G; Désert, J. M.; Waters, L. B.F.M.; Robinson, T; Meadows, V.; van Dishoeck, E.F.; Brandl, B.R.; Henning, T.; Bouwman, J.; Lahuis, F.; Min, M.; Lovis, C.; Dominik, C.; Van Eylen, V.; Sing, D.; Anglada-Escudé, G.; Birkby, J. L.; Brogi, M.

    2017-01-01

    Exoplanet Proxima b will be an important laboratory for the search for extraterrestrial life for the decades ahead. Here, we discuss the prospects of detecting carbon dioxide at 15 μm using a spectral filtering technique with the Medium Resolution Spectrograph (MRS) mode of the Mid-Infrared

  15. Comparison of Machine Learning Techniques for Target Detection

    NARCIS (Netherlands)

    Vink, J.P.; Haan, G. de

    2013-01-01

    This paper focuses on machine learning techniques for real-time detection. Although many supervised learning techniques have been described in the literature, no technique always performs best. Several comparative studies are available, but have not always been performedcarefully, leading to invalid

  16. Tunnel and Subsurface Void Detection and Range to Target Measurement

    Energy Technology Data Exchange (ETDEWEB)

    Phillip B. West

    2009-06-01

    Engineers and technicians at the Idaho National Laboratory invented, designed, built and tested a device capable of detecting and measuring the distance to, an underground void, or tunnel. Preliminary tests demonstrated positive detection of, and range to, a void thru as much as 30 meters of top-soil earth. Device uses acoustic driving point impedance principles pioneered by the Laboratory for well-bore physical properties logging. Data receipts recorded by the device indicates constructive-destructive interference patterns characteristic of acoustic wave reflection from a downward step-change in impedance mismatch. Prototype tests demonstrated that interference patterns in receipt waves could depict the patterns indicative of specific distances. A tool with this capability can quickly (in seconds) indicate the presence and depth/distance of a void or tunnel. Using such a device, border security and military personnel can identify threats of intrusion or weapons caches in most all soil conditions including moist and rocky.

  17. Collision Target Detection Using a Single Antenna for Automotive RADAR

    OpenAIRE

    Abakar Issakha, Souleymane; Vincent, Francois; Ferro-Famil, Laurent; Bodereau, Frantz

    2017-01-01

    International audience; The goal of most modern automotive safety driver assistance functions is to avoid possible collisions. Pedestrian protection, predictive emergency braking or turn and crossing assist functions are usually based on two steps. First, the radar provides detailed information on the environment, and then a detection procedure is driven. Because of the complicated environment near the vehicle, this second step is a difficult task to achieve in order to give reliable informat...

  18. Target Detection Routine (TADER). User’s Guide.

    Science.gov (United States)

    1987-09-01

    o System range capability subset (one record - omitted for standoff SLAR and penetrating system) o System inherent detection probability subset ( IELT ...records, i.e., one per element type) * System capability modifier subset/A=1, E=1 ( IELT records) o System capability modifier subset/A=1, E=2 ( IELT ...records) s System capability modifier subset/A=2, E=1 ( IELT records) o System capability modifier subset/A=2, E=2 ( IELT records) Unit Data Set (one set

  19. Track-Before-Detect Algorithm for Weak Extended Target Based on Particle Filter under Clutter Environment

    Directory of Open Access Journals (Sweden)

    Wu Sunyong

    2017-06-01

    Full Text Available The Track-Before-Detect (TBD algorithm based on the particle filter is proposed for weak extended target detection and tracking in low signal to clutter noise radio. The rod-shaped object is analyzed by dividing the cell on range and azimuth under the Weibull clutter. On the basis of a point target, the likelihood function and particle weights can be obtained by the target spread function. In the TBD algorithm, the binary target variable and the target shape parameters is added to the state vector and the scattering points in the sample collection is given based on the particle filter, which can detect and estimate the target state and the shape parameters under the clutter environment. Simulation results show that the stability of the algorithm is very good.

  20. Investigation of ground target detection methods in fully polarimetric wide angle synthetic aperture radar images

    Science.gov (United States)

    Laggan, Wayne B.

    1995-03-01

    Target detection is a high priority of the Air Force for the purpose of reconnaissance and bombardment. This research investigates and develops methods to distinguish ground targets from clutter (i.e. foliage, landscape etc.) in Wide Angle Synthetic Aperture Radar (WASAR) images. WASAR uses multiple aspect angle SAR images of the same target scene. The WASAR data was generated from a pre-release software package (XPATCH-ES) provided by the sponsor (WL-AARA). A statistical analysis and feature extraction is performed on the XPATCH-ES data. Polarimetric and wide angle covariance matrices are estimated and analyzed. From an analysis of the wide angle covariance matrix it is shown that natural clutter has in general a uniform radar return for changing aspect angles, whereas the radar return for a target varies. Based on this analysis, two new wide angle algorithms, the WASAR Whitening Filter and the Adaptive WASAR Whitening Filter (AWWF) are developed. The target detection performance of polarimetric and multi aspect angle image combining algorithms are quantified using Receiver Operating Characteristic curves and target to clutter ratios. It is shown that wide angle processing provides superior target detection performance over polarimetric processing. Combinations of wide angle and polarimetric algorithms were used to achieve a 13.7 dB processing gain in target to clutter ratio when compared to unprocessed images of the target scene. This represents a significant improvement in target detection capabilities.

  1. Detection of Space-debris Using Space-Based Integrated Detection and Image Processing System

    Science.gov (United States)

    Azzazy, M.; Justice, J.

    2014-09-01

    Detection and cataloguing of space-debris is paramount to satellite operations. Space debris vary in size from very small objects 10-4 m2 to large objects approximately > 1 m2. The detection of small debris using earth-based telescopes and detection systems present a great challenge; long integration time, and large blur due to atmospheric turbulence. Space-based detection systems are usually expensive and have limited image processing capabilities to detect and track space debris. In this paper we describe the development of a relatively inexpensive space-based integrated sensor/processor that allows the detection of objects as small as 10-4 m2 at 50 km range (equivalent to star magnitude 10). The sensor noise floor is equivalent to star magnitude 12. The sensor field of regard is 60°x120°. The elevation field of regard is covered by two 25 mega-pixel focal plane arrays, each with 4 cm aperture covering 30 degrees field of view. A gimbal is then used to scan the sensor in the azimuthal direction. The sensor frame rate to cover the full field of regard is 10 frames/sec. The FPA outputs are processed onboard to register the images, remove background stars, identify the debris, and determine their coordinate and sidereal motion relative to the camera frame of reference. Image registration: rotation and translation to sub-pixel level was achieved using Radon transformation and fast Fourier transform techniques. The image registration algorithm was optimized to run on an FPGA. Star background is then removed from the registered images and the location and sidereal motion of the debris are then determined. The image processing system uses stars with magnitudes between 5 and 7 along with a look-up table map of the sky to convert the debris coordinate system to an inertial coordinate system which is then transmitted to the ground. A high fidelity simulation model has been developed and used to guide and test the image processing algorithms. The high fidelity simulation

  2. Characterizing sensitivity of longwave infrared hyperspectral target detection with respect to signature mismatch and dimensionality reduction

    Science.gov (United States)

    Meola, Joseph

    2017-05-01

    Hyperspectral target detection typically relies upon libraries of material reflectance and emissivity signatures. Application to real-world, airborne data requires estimation of atmospheric properties in order to convert reflectance/emissivity signatures to the sensor data domain. In the longwave infrared, an additional nuisance parameter of surface temperature exists that further complicates the signature conversion process. A significant amount of work has been done in atmospheric compensation and temperature-emissivity-separation techniques. This work examines the sensitivity of target detection performance for various materials with respect to target signature mismatch introduced from atmospheric compensation error or target temperature mismatch. Additionally, the impact of dimensionality reduction via principal components analysis is assessed.

  3. Dim small targets detection based on self-adaptive caliber temporal-spatial filtering

    Science.gov (United States)

    Fan, Xiangsuo; Xu, Zhiyong; Zhang, Jianlin; Huang, Yongmei; Peng, Zhenming

    2017-09-01

    To boost the detect ability of dim small targets, this paper began by using improved anisotropy for background prediction (IABP), followed by target enhancement by improved high-order cumulates (HQS). Finally, on the basis of image pre-processing, to address the problem of missed and wrong detection caused by fixed caliber of traditional pipeline filtering, this paper used targets' multi-frame movement correlation in the time-space domain, combined with the scale-space theory, to propose a temporal-spatial filtering algorithm which allows the caliber to make self-adaptive changes according to the changes of the targets' scale, effectively solving the detection-related issues brought by unchanged caliber and decreased/increased size of the targets. Experiments showed that the improved anisotropic background predication could be loyal to the true background of the original image to the maximum extent, presenting a superior overall performance to other background prediction methods; the improved HQS significantly increased the signal-noise ratio of images; when the signal-noise ratio was lower than 2.6 dB, this detection algorithm could effectively eliminate noise and detect targets. For the algorithm, the lowest signal-to-noise ratio of the detectable target is 0.37.

  4. Improved OAM-Based Radar Targets Detection Using Uniform Concentric Circular Arrays

    Directory of Open Access Journals (Sweden)

    Mingtuan Lin

    2016-01-01

    Full Text Available Without any relative moves or beam scanning, the novel Orbital-Angular-Momentum- (OAM- based radar targets detection technique using uniform concentric circular arrays (UCCAs shows the azimuthal estimation ability, which provides new perspective for radar system design. However, the main estimation method, that is, Fast Fourier Transform (FFT, under this scheme suffers from low resolution. As a solution, this paper rebuilds the OAM-based radar targets detection model and introduces the multiple signal classification (MUSIC algorithm to improve the resolution for detecting targets within the main lobes. The spatial smoothing technique is proposed to tackle the coherent problem brought by the proposed model. Analytical study and simulation demonstrate the superresolution estimation capacity the MUSIC algorithm can achieve for detecting targets within the main lobes. The performance of the MUSIC algorithm to detect targets not illuminated by the main lobes is further evaluated. Despite the fact that MUSIC algorithm loses the resolution advantage under this case, its estimation is more robust than that of the FFT method. Overall, the proposed MUSIC algorithm for the OAM-based radar system demonstrates the superresolution ability for detecting targets within the main lobes and good robustness for targets out of the main lobes.

  5. Nicking endonuclease and target recycles signal amplification assisted quantum dots for fluorescence detection of DNA

    Energy Technology Data Exchange (ETDEWEB)

    Niu Shuyan; Li Quanyi; Qu Lijing; Wang Wei [Key Lab of Eco-chemical Engineering, Ministry of Education, College of Chemistry and Molecular Engineering, Qingdao University of Science and Technology, Qingdao 266042 (China)

    2010-11-08

    An ultrasensitive fluorescence detection method for DNA based on nicking endonuclease (NEase) and target recycles assisted with CdTe quantum dots (QDs) is reported. In the detection system, when the target DNA is present, it hybridizes with a linker strand to from a duplex, in which the NEase recognizes specific nucleotide sequences and cleaves the linker strand. After nicking, the fragments of the linker strand spontaneously dissociate from the target DNA and another linker strand hybridizes to the target to trigger another strand-scission cycle. On the other hand, when the target was absent, no duplex is formed and no fragment of linker strand is produced. Then CdTe QDs and magnetic beads (MBs), which were all modified with DNA sequences complementary to that of the linker strands are added to the solution to detect the presence of a target DNA. The signal was generated through the difference in Foerster resonance energy transfer (FRET) between the MB and CdTe QDs. This method indicates that one target DNA leads to cleavage of hundreds of linker DNA, increasing detection sensitivity by nearly three orders of magnitude. This method should be applicable whenever there is a requirement to detect a specific DNA sequence and can also be used for multicomponent detection.

  6. Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

    Science.gov (United States)

    Zou, Zhengxia; Shi, Zhenwei

    2018-03-01

    We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

  7. DNA Sequence Signatures for Rapid Detection of Six Target Bacterial Pathogens Using PCR Assays

    Directory of Open Access Journals (Sweden)

    Kenjiro Nagamine

    2015-01-01

    Full Text Available Using Streptococcus pyogenes as a model, we previously established a stepwise computational workflow to effectively identify species-specific DNA signatures that could be used as PCR primer sets to detect target bacteria with high specificity and sensitivity. In this study, we extended the workflow for the rapid development of PCR assays targeting Enterococcus faecalis, Enterococcus faecium, Clostridium perfringens, Clostridium difficile, Clostridium tetani , and Staphylococcus aureus , which are of safety concern for human tissue intended for transplantation. Twenty-one primer sets that had sensitivity of detecting 5–50 fg DNA from target bacteria with high specificity were selected. These selected primer sets can be used in a PCR array for detecting target bacteria with high sensitivity and specificity. The workflow could be widely applicable for the rapid development of PCR-based assays for a wide range of target bacteria, including those of biothreat agents.

  8. Polarization Calculation and Underwater Target Detection Inspired by Biological Visual Imaging

    Directory of Open Access Journals (Sweden)

    Jie Shen

    2014-04-01

    Full Text Available In challenging underwater environments, the polarization parameter maps calculated by the Stokes model are characterized by the high noise and error, harassing the underwater target detection tasks. In order to solve this problem, this paper proposes a novel bionic polarization calculation and underwater target detection method by modeling the visual system of mantis shrimps. This system includes many operators including a polarization-opposition calculation, a factor optimization and a visual neural network model. A calibration learning method is proposed to search the optimal value of the factors in the linear subtraction model. Finally, a six-channel visual neural network model is proposed to detect the underwater targets. Experimental results proved that the maps produced by the polarization-opposition parameter is more accurate and have lower noise than that produced by the Stokes parameter, achieving better performance in underwater target detection tasks.

  9. Limitations and Strengths of the Fourier Transform Method to Detect Accelerating Targets

    National Research Council Canada - National Science Library

    Thayaparan, Thayananthan

    2000-01-01

    .... In using a Pulse Doppler Radar to detect a non-accelerating target in additive white Gaussian noise and to estimate its radial velocity, the Fourier method provides an output signal-to-noise ratio (SNR...

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

    National Research Council Canada - National Science Library

    Tikuisis, Peter; Keefe, Allan A

    2007-01-01

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

  11. Research and Analysis Laser Target Optics Characteristics and Signal Recognition Processing in Detection Screen System

    National Research Council Canada - National Science Library

    Hanshan Li; Yanran Li

    2014-01-01

      In order to improve the measurement accuracy of the laser measurement distance system, this paper studies the laser target optics characteristics based on the laser detection principle in the laser...

  12. FPGA-Based Real-Time Moving Target Detection System for Unmanned Aerial Vehicle Application

    National Research Council Canada - National Science Library

    Tang, Jia Wei; Shaikh-Husin, Nasir; Sheikh, Usman Ullah; Marsono, M. N

    2016-01-01

      Moving target detection is the most common task for Unmanned Aerial Vehicle (UAV) to find and track object of interest from a bird's eye view in mobile aerial surveillance for civilian applications such as search and rescue operation...

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

    National Research Council Canada - National Science Library

    Tikuisis, Peter

    2006-01-01

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

  14. Targeted Screening Strategies to Detect Trypanosoma cruzi Infection in Children

    Science.gov (United States)

    Levy, Michael Z.; Kawai, Vivian; Bowman, Natalie M.; Waller, Lance A.; Cabrera, Lilia; Pinedo-Cancino, Viviana V.; Seitz, Amy E.; Steurer, Frank J.; Cornejo del Carpio, Juan G.; Cordova-Benzaquen, Eleazar; Maguire, James H.; Gilman, Robert H.; Bern, Caryn

    2007-01-01

    Background Millions of people are infected with Trypanosoma cruzi, the causative agent of Chagas disease in Latin America. Anti-trypanosomal drug therapy can cure infected individuals, but treatment efficacy is highest early in infection. Vector control campaigns disrupt transmission of T. cruzi, but without timely diagnosis, children infected prior to vector control often miss the window of opportunity for effective chemotherapy. Methods and Findings We performed a serological survey in children 2–18 years old living in a peri-urban community of Arequipa, Peru, and linked the results to entomologic, spatial and census data gathered during a vector control campaign. 23 of 433 (5.3% [95% CI 3.4–7.9]) children were confirmed seropositive for T. cruzi infection by two methods. Spatial analysis revealed that households with infected children were very tightly clustered within looser clusters of households with parasite-infected vectors. Bayesian hierarchical mixed models, which controlled for clustering of infection, showed that a child's risk of being seropositive increased by 20% per year of age and 4% per vector captured within the child's house. Receiver operator characteristic (ROC) plots of best-fit models suggest that more than 83% of infected children could be identified while testing only 22% of eligible children. Conclusions We found evidence of spatially-focal vector-borne T. cruzi transmission in peri-urban Arequipa. Ongoing vector control campaigns, in addition to preventing further parasite transmission, facilitate the collection of data essential to identifying children at high risk of T. cruzi infection. Targeted screening strategies could make integration of diagnosis and treatment of children into Chagas disease control programs feasible in lower-resource settings. PMID:18160979

  15. Max-mean and max-median filters for detection of small targets

    Science.gov (United States)

    Deshpande, Suyog D.; Er, Meng H.; Venkateswarlu, Ronda; Chan, Philip

    1999-10-01

    This paper deals with the problem of detection and tracking of low observable small-targets from a sequence of IR images against structural background and non-stationary clutter. There are many algorithms reported in the open literature for detection and tracking of targets of significant size in the image plane with good results. However, the difficulties of detecting small-targets arise from the fact that they are not easily discernable from clutter. The focus of research in this area is to reduce the false alarm rate to an acceptable level. Triple Temporal Filter reported by Jerry Silverman et. al., is one of the promising algorithms in this are. In this paper, we investigate the usefulness of Max-Mean and Max-Median filters in preserving the edges of clouds and structural backgrounds, which helps in detecting small-targets. Subsequently, anti-mean and anti-median operations result in good performance of detecting targets against moving clutter. The raw image is first filtered by max-mean/max-median filter. Then the filtered output is subtracted from the original image to enhance the potential targets. A thresholding step is incorporated in order to limit the number of potential target pixels. The threshold is obtained by using the statistics of the image. Finally, the thresholded images are accumulated so that the moving target forms a continuous trajectory and can be detected by using the post-processing algorithm. It is assumed that most of the targets occupy a couple of pixels. Head-on moving and maneuvering targets are not considered. These filters have ben tested successfully with the available database and the result are presented.

  16. Detection and Imaging of Moving Targets with LiMIT SAR Data

    Science.gov (United States)

    2017-03-03

    sandeep.mishra@baesystems.com Abstract Detecting moving targets in SAR imagery has recently gained a lot of interest as a way to replace optical...movers by applying a set of possible motion corrections to the image, and use a novel matched filter to detect the movers in this space. We can then image...called SAR-GMTI) has recently gained a lot of interest as a way to image and classify moving targets, and to mitigate GMTI performance gaps. Synthetic

  17. Multirapid Serial Visual Presentation Framework for EEG-Based Target Detection

    Directory of Open Access Journals (Sweden)

    Zhimin Lin

    2017-01-01

    Full Text Available Target image detection based on a rapid serial visual presentation (RSVP paradigm is a typical brain-computer interface system with various applications, such as image retrieval. In an RSVP paradigm, a P300 component is detected to determine target images. This strategy requires high-precision single-trial P300 detection methods. However, the performance of single-trial detection methods is relatively lower than that of multitrial P300 detection methods. Image retrieval based on multitrial P300 is a new research direction. In this paper, we propose a triple-RSVP paradigm with three images being presented simultaneously and a target image appearing three times. Thus, multitrial P300 classification methods can be used to improve detection accuracy. In this study, these mechanisms were extended and validated, and the characteristics of the multi-RSVP framework were further explored. Two different P300 detection algorithms were also utilized in multi-RSVP to demonstrate that the scheme is universally applicable. Results revealed that the detection accuracy of the multi-RSVP paradigm was higher than that of the standard RSVP paradigm. The results validate the effectiveness of the proposed method, and this method can provide a whole new idea in the field of EEG-based target detection.

  18. Dim point target enhancement and detection based on improved NL-means in complex background

    Science.gov (United States)

    Lv, Ping-Yue; Lin, Chang-Qing

    2017-07-01

    In order to achieve a single-frame enhancement and detection of dim point targets efficiently, a new method based on morphological top-hat transformation and modified non-local means (NL-means, NLM) for target enhancement is presented. After enhancing dim point targets, an estimating algorithm called local reverse entropy is applied to get candidate targets, and obtains detecting results in the end. In this model, white top-hat and black top-hat are combined to obtain pre-processed image, then the targets are enhanced for the second time through modified NL-means algorithm. The background in the residual image of enhanced image and original image is mostly suppressed, then it is regarded as the input of local reverse entropy estimation method (LREM). Detecting results can be obtained by setting proper thresholds. The 4 × 4 weak lattice targets with different brightness are superimposed on different infrared image backgrounds. The experimental results show that, when the SCR is low (SCR≈1), the detection algorithm model proposed in this paper has higher SCR gain than other target-enhancing algorithms such as TDLMS, max-median, max-mean, non-local means, etc. and the detection performance is the best.

  19. Detection of Small Sea-Surface Targets with a Search Lidar

    NARCIS (Netherlands)

    Heuvel, J.C. van den; Bekman, H.H.P.T.; Putten, F.J.M.; Cohen, L.A.

    2007-01-01

    Naval operations in the littoral have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and low velocity, which makes them hard to detect by radar in the presence of sea clutter. Typical threats include periscopes, jet skies, FIAC’s, and speedboats.

  20. Novel Spatiotemporal Filter for Dim Point Targets Detection in Infrared Image Sequences

    Directory of Open Access Journals (Sweden)

    Zhaohui Li

    2015-01-01

    Full Text Available Dim point target detection is of great importance in both civil and military fields. In this paper a novel spatiotemporal filter is proposed to incorporate both the spatial and temporal features of moving dim point targets. Since targets are expected to be detected as far as possible, in this situation, they have no texture features in spatial dimensions, appearing like isolated points. Based on the attributes, potential targets are extracted by searching the local maximum point in a sliding window. And the potential targets are then correlated based on target moving patterns. After combining local maximum points and target moving patterns, structure background in infrared scene is removed. Next, the temporal profiles of infrared sense are reviewed and examined. By a new max-median filter performing on temporal profiles, the intensity of target pulse signal is extracted. Finally, each temporal profile is divided into several pieces to estimate the variance of the temporal profiles, which leads to a new detection metric. The proposed approach is tested via several infrared image sequences. The results show that our proposed method can significantly reduce the complex background in aerial infrared image sequence and have a good detection performance.

  1. Risk maps for targeting exotic plant pest detection programs in the United States

    Science.gov (United States)

    R.D. Magarey; D.M. Borchert; J.S. Engle; M Garcia-Colunga; Frank H. Koch; et al

    2011-01-01

    In the United States, pest risk maps are used by the Cooperative Agricultural Pest Survey for spatial and temporal targeting of exotic plant pest detection programs. Methods are described to create standardized host distribution, climate and pathway risk maps for the top nationally ranked exotic pest targets. Two examples are provided to illustrate the risk mapping...

  2. Moving target detection through omni-orientational vision fixed on AGV

    Science.gov (United States)

    Yang, Shu-Ying; Cao, Zuo-Liang; He, Pei-Lian

    2006-10-01

    Extremely wide view of the omni-vision performs highly advanced for the vehicle navigation and target detection. However moving targets detection through omni-vision fixed on AGV (Automatic Guided Vehicle) involves more complex environments, where both the targets and the vehicle are in the moving condition. The moving targets will be detected in a moving background. After analyzing the character on omniorientational vision and image, we propose to use the estimation in optical flow fields, Gabor filter over optical flow fields for detecting moving objects. Because polar angle θ and polar radius R of polar coordinates are being changed as the targets moving, we improved optical flow approach which can be calculated based on the polar coordinates at the omniorientational center. We constructed Gabor filter which has 24 orientations every 15°, and filter optical flow fields at 24 orientations. By the contrast of the Gabor filter images at the same orientation and the same AGV position between the situation which there aren't any moving targets in the environment and the situation which there are some moving targets in the same environment, the moving targets' optical flow fields could be recognized. Experiment results show that the proposed approach is feasible and effective.

  3. Scan statistics with local vote for target detection in distributed system

    Science.gov (United States)

    Luo, Junhai; Wu, Qi

    2017-12-01

    Target detection has occupied a pivotal position in distributed system. Scan statistics, as one of the most efficient detection methods, has been applied to a variety of anomaly detection problems and significantly improves the probability of detection. However, scan statistics cannot achieve the expected performance when the noise intensity is strong, or the signal emitted by the target is weak. The local vote algorithm can also achieve higher target detection rate. After the local vote, the counting rule is always adopted for decision fusion. The counting rule does not use the information about the contiguity of sensors but takes all sensors' data into consideration, which makes the result undesirable. In this paper, we propose a scan statistics with local vote (SSLV) method. This method combines scan statistics with local vote decision. Before scan statistics, each sensor executes local vote decision according to the data of its neighbors and its own. By combining the advantages of both, our method can obtain higher detection rate in low signal-to-noise ratio environment than the scan statistics. After the local vote decision, the distribution of sensors which have detected the target becomes more intensive. To make full use of local vote decision, we introduce a variable-step-parameter for the SSLV. It significantly shortens the scan period especially when the target is absent. Analysis and simulations are presented to demonstrate the performance of our method.

  4. Antenna allocation in MIMO radar with widely separated antennas for multi-target detection.

    Science.gov (United States)

    Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

    2014-10-27

    In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes.

  5. Detection and localization of multiple short range targets using FMCW radar signal

    KAUST Repository

    Jardak, Seifallah

    2016-07-26

    In this paper, a 24 GHz frequency-modulated continuous wave radar is used to detect and localize both stationary and moving targets. Depending on the application, the implemented software offers different modes of operation. For example, it can simply output raw data samples for advanced offline processing or directly carry out a two dimensional fast Fourier transform to estimate the location and velocity of multiple targets. To suppress clutter and detect only moving targets, two methods based on the background reduction and the slow time processing techniques are implemented. A trade-off between the two methods is presented based on their performance and the required processing time. © 2016 IEEE.

  6. Sea-Based Infrared Scene Interpretation by Background Type Classification and Coastal Region Detection for Small Target Detection.

    Science.gov (United States)

    Kim, Sungho

    2015-09-23

    Sea-based infrared search and track (IRST) is important for homeland security by detecting missiles and asymmetric boats. This paper proposes a novel scheme to interpret various infrared scenes by classifying the infrared background types and detecting the coastal regions in omni-directional images. The background type or region-selective small infrared target detector should be deployed to maximize the detection rate and to minimize the number of false alarms. A spatial filter-based small target detector is suitable for identifying stationary incoming targets in remote sea areas with sky only. Many false detections can occur if there is an image sector containing a coastal region, due to ground clutter and the difficulty in finding true targets using the same spatial filter-based detector. A temporal filter-based detector was used to handle these problems. Therefore, the scene type and coastal region information is critical to the success of IRST in real-world applications. In this paper, the infrared scene type was determined using the relationships between the sensor line-of-sight (LOS) and a horizontal line in an image. The proposed coastal region detector can be activated if the background type of the probing sector is determined to be a coastal region. Coastal regions can be detected by fusing the region map and curve map. The experimental results on real infrared images highlight the feasibility of the proposed sea-based scene interpretation. In addition, the effects of the proposed scheme were analyzed further by applying region-adaptive small target detection.

  7. Automatic detection and tracking of multiple interacting targets from a moving platform

    Science.gov (United States)

    Mao, Hongwei; Yang, Chenhui; Abousleman, Glen P.; Si, Jennie

    2014-01-01

    In real-world scenarios, a target tracking system could be severely compromised by interactions, i.e., influences from the proximity and/or behavior of other targets or background objects. Closely spaced targets are difficult to distinguish, and targets may be partially or totally invisible for uncontrolled durations when occluded by other objects. These situations are very likely to degrade the performance or cause the tracker to fail because the system may use invalid target observations to update the tracks. To address these issues, we propose an integrated multitarget tracking system. A background-subtraction-based method is used to automatically detect moving objects in video frames captured by a moving camera. The data association method evaluates the overlap rates between newly detected objects (observations) and already-tracked targets and makes decisions pertaining to whether a target is interacting with other targets and whether it has a valid observation. According to the association results, distinct strategies are employed to update and manage the tracks of interacting versus well-isolated targets. This system has been tested with real-world airborne videos from the DARPA Video Verification of Identity program database and demonstrated excellent track continuity in the presence of occlusions and multiple target interactions, very low false alarm rate, and real-time operation on an ordinary general-purpose computer.

  8. Multiresolution Signal Processing Techniques for Ground Moving Target Detection Using Airborne Radar

    Directory of Open Access Journals (Sweden)

    Bergin Jameson S

    2006-01-01

    Full Text Available Synthetic aperture radar (SAR exploits very high spatial resolution via temporal integration and ownship motion to reduce the background clutter power in a given resolution cell to allow detection of nonmoving targets. Ground moving target indicator (GMTI radar, on the other hand, employs much lower-resolution processing but exploits relative differences in the space-time response between moving targets and clutter for detection. Therefore, SAR and GMTI represent two different temporal processing resolution scales which have typically been optimized and demonstrated independently to work well for detecting either stationary (in the case of SAR or exo-clutter (in the case of GMTI targets. Based on this multiresolution interpretation of airborne radar data processing, there appears to be an opportunity to develop detection techniques that attempt to optimize the signal processing resolution scale (e.g., length of temporal integration to match the dynamics of a target of interest. This paper investigates signal processing techniques that exploit long CPIs to improve the detection performance of very slow-moving targets.

  9. A fast-saliency method for real-time infrared small target detection

    Science.gov (United States)

    Qi, Shengxiang; Xu, Guojing; Mou, Zhiying; Huang, Dayu; Zheng, Xueli

    2016-07-01

    Infrared small target detection plays an important role in applications including military reconnaissance, early warning and terminal guidance. In this paper, we present a fast method, called fast-saliency, with very low computational complexity, for real-time small target detection in single image frame under various complex backgrounds. Different from traditional algorithms, the proposed method is inspired by a recent research on visual saliency detection indicating that small salient signals could be well detected by a gradient enhancement operation combined with Gaussian smoothing, which is able to delineate regions of small targets in infrared images. Concisely, there are only four simple steps contained in fast-saliency. In order, they are gradient operation, square computation, Gaussian smoothing and automatic thresholding, representing the four procedures as highpass filtering, target enhancement, noise suppression and target segmentation, respectively. Especially, for the most crucial step, gradient operation, we innovatively propose a 5 × 5 facet kernel operator that holds the key for separating the small targets from backgrounds. To verify the effectiveness of our proposed method, a set of real infrared images covering typical backgrounds with sea, sky and ground clutters are tested in experiments. The results demonstrate that it outperforms the state-of-the-art methods not only in detection accuracy, but also in computation efficiency.

  10. Infrared Dim and Small Targets Detection Method Based on Local Energy Center of Sequential Image

    Directory of Open Access Journals (Sweden)

    Xiangsuo Fan

    2017-01-01

    Full Text Available In order to detect infrared (IR dim and small targets in a strong clutter background, a method based on local energy center of sequential image is proposed. This paper began by using improved anisotropy for background prediction (IABP, followed by target enhancement by improved high-order cumulates (HOC. Finally, on the basis of image preprocessing, the paper constructs a sequential image energy center detection algorithm that integrates the neighborhood, continuity, area, and energy and other motion characteristics of the target. Experiments showed that the improved anisotropic background predication could be loyal to the true background of the original image to the maximum extent, presenting a superior overall performance to other background prediction methods; the improved HOC significantly increased the signal-noise ratio of images; when the signal-noise ratio (SNR is lower than 2.5 dB, the proposed method could effectively eliminate noise and detect targets.

  11. Small target detection based on difference accumulation and Gaussian curvature under complex conditions

    Science.gov (United States)

    Zhang, He; Niu, Yanxiong; Zhang, Hao

    2017-12-01

    Small target detection is a significant subject in infrared search and track and other photoelectric imaging systems. The small target is imaged under complex conditions, which contains clouds, horizon and bright part. In this paper, a novel small target detection method is proposed based on difference accumulation, clustering and Gaussian curvature. Difference accumulation varies from regions. Therefore, after obtaining difference accumulations, clustering is applied to determine whether the pixel belongs to the heterogeneous region, and eliminate heterogeneous region. Then Gaussian curvature is used to separate target from the homogeneous region. Experiments are conducted for verification, along with comparisons to several other methods. The experimental results demonstrate that our method has an advantage of 1-2 orders of magnitude on SCRG and BSF than others. Given that the false alarm rate is 1, the detection probability can be approximately 0.9 by using proposed method.

  12. Detection of target DNA using fluorescent cationic polymer and peptide nucleic acid probes on solid support

    Directory of Open Access Journals (Sweden)

    Leclerc Mario

    2005-04-01

    Full Text Available Abstract Background Nucleic acids detection using microarrays requires labelling of target nucleic acids with fluorophores or other reporter molecules prior to hybridization. Results Using surface-bound peptide nucleic acids (PNA probes and soluble fluorescent cationic polythiophenes, we show a simple and sensitive electrostatic approach to detect and identify unlabelled target nucleic acid on microarray. Conclusion This simple methodology opens exciting possibilities for applied genetic analysis for the diagnosis of infections, identification of genetic mutations, and forensic inquiries. This electrostatic strategy could also be used with other nucleic acid detection methods such as electrochemistry, silver staining, metallization, quantum dots, or electrochemical dyes.

  13. Detection of target DNA using fluorescent cationic polymer and peptide nucleic acid probes on solid support

    Science.gov (United States)

    Raymond, Frédéric R; Ho, Hoang-Anh; Peytavi, Régis; Bissonnette, Luc; Boissinot, Maurice; Picard, François J; Leclerc, Mario; Bergeron, Michel G

    2005-01-01

    Background Nucleic acids detection using microarrays requires labelling of target nucleic acids with fluorophores or other reporter molecules prior to hybridization. Results Using surface-bound peptide nucleic acids (PNA) probes and soluble fluorescent cationic polythiophenes, we show a simple and sensitive electrostatic approach to detect and identify unlabelled target nucleic acid on microarray. Conclusion This simple methodology opens exciting possibilities for applied genetic analysis for the diagnosis of infections, identification of genetic mutations, and forensic inquiries. This electrostatic strategy could also be used with other nucleic acid detection methods such as electrochemistry, silver staining, metallization, quantum dots, or electrochemical dyes. PMID:15850478

  14. Scale invariant SURF detector and automatic clustering segmentation for infrared small targets detection

    Science.gov (United States)

    Zhang, Haiying; Bai, Jiaojiao; Li, Zhengjie; Liu, Yan; Liu, Kunhong

    2017-06-01

    The detection and discrimination of infrared small dim targets is a challenge in automatic target recognition (ATR), because there is no salient information of size, shape and texture. Many researchers focus on mining more discriminative information of targets in temporal-spatial. However, such information may not be available with the change of imaging environments, and the targets size and intensity keep changing in different imaging distance. So in this paper, we propose a novel research scheme using density-based clustering and backtracking strategy. In this scheme, the speeded up robust feature (SURF) detector is applied to capture candidate targets in single frame at first. And then, these points are mapped into one frame, so that target traces form a local aggregation pattern. In order to isolate the targets from noises, a newly proposed density-based clustering algorithm, fast search and find of density peak (FSFDP for short), is employed to cluster targets by the spatial intensive distribution. Two important factors of the algorithm, percent and γ , are exploited fully to determine the clustering scale automatically, so as to extract the trace with highest clutter suppression ratio. And at the final step, a backtracking algorithm is designed to detect and discriminate target trace as well as to eliminate clutter. The consistence and continuity of the short-time target trajectory in temporal-spatial is incorporated into the bounding function to speed up the pruning. Compared with several state-of-arts methods, our algorithm is more effective for the dim targets with lower signal-to clutter ratio (SCR). Furthermore, it avoids constructing the candidate target trajectory searching space, so its time complexity is limited to a polynomial level. The extensive experimental results show that it has superior performance in probability of detection (Pd) and false alarm suppressing rate aiming at variety of complex backgrounds.

  15. Multi-Target Detection from Full-Waveform Airborne Laser Scanner Using Phd Filter

    Science.gov (United States)

    Fuse, T.; Hiramatsu, D.; Nakanishi, W.

    2016-06-01

    We propose a new technique to detect multiple targets from full-waveform airborne laser scanner. We introduce probability hypothesis density (PHD) filter, a type of Bayesian filtering, by which we can estimate the number of targets and their positions simultaneously. PHD filter overcomes some limitations of conventional Gaussian decomposition method; PHD filter doesn't require a priori knowledge on the number of targets, assumption of parametric form of the intensity distribution. In addition, it can take a similarity between successive irradiations into account by modelling relative positions of the same targets spatially. Firstly we explain PHD filter and particle filter implementation to it. Secondly we formulate the multi-target detection problem on PHD filter by modelling components and parameters within it. At last we conducted the experiment on real data of forest and vegetation, and confirmed its ability and accuracy.

  16. MULTI-TARGET DETECTION FROM FULL-WAVEFORM AIRBORNE LASER SCANNER USING PHD FILTER

    Directory of Open Access Journals (Sweden)

    T. Fuse

    2016-06-01

    Full Text Available We propose a new technique to detect multiple targets from full-waveform airborne laser scanner. We introduce probability hypothesis density (PHD filter, a type of Bayesian filtering, by which we can estimate the number of targets and their positions simultaneously. PHD filter overcomes some limitations of conventional Gaussian decomposition method; PHD filter doesn’t require a priori knowledge on the number of targets, assumption of parametric form of the intensity distribution. In addition, it can take a similarity between successive irradiations into account by modelling relative positions of the same targets spatially. Firstly we explain PHD filter and particle filter implementation to it. Secondly we formulate the multi-target detection problem on PHD filter by modelling components and parameters within it. At last we conducted the experiment on real data of forest and vegetation, and confirmed its ability and accuracy.

  17. MutScan: fast detection and visualization of target mutations by scanning FASTQ data.

    Science.gov (United States)

    Chen, Shifu; Huang, Tanxiao; Wen, Tiexiang; Li, Hong; Xu, Mingyan; Gu, Jia

    2018-01-22

    Some types of clinical genetic tests, such as cancer testing using circulating tumor DNA (ctDNA), require sensitive detection of known target mutations. However, conventional next-generation sequencing (NGS) data analysis pipelines typically involve different steps of filtering, which may cause miss-detection of key mutations with low frequencies. Variant validation is also indicated for key mutations detected by bioinformatics pipelines. Typically, this process can be executed using alignment visualization tools such as IGV or GenomeBrowse. However, these tools are too heavy and therefore unsuitable for validating mutations in ultra-deep sequencing data. We developed MutScan to address problems of sensitive detection and efficient validation for target mutations. MutScan involves highly optimized string-searching algorithms, which can scan input FASTQ files to grab all reads that support target mutations. The collected supporting reads for each target mutation will be piled up and visualized using web technologies such as HTML and JavaScript. Algorithms such as rolling hash and bloom filter are applied to accelerate scanning and make MutScan applicable to detect or visualize target mutations in a very fast way. MutScan is a tool for the detection and visualization of target mutations by only scanning FASTQ raw data directly. Compared to conventional pipelines, this offers a very high performance, executing about 20 times faster, and offering maximal sensitivity since it can grab mutations with even one single supporting read. MutScan visualizes detected mutations by generating interactive pile-ups using web technologies. These can serve to validate target mutations, thus avoiding false positives. Furthermore, MutScan can visualize all mutation records in a VCF file to HTML pages for cloud-friendly VCF validation. MutScan is an open source tool available at GitHub: https://github.com/OpenGene/MutScan.

  18. Golay Complementary Waveforms in Reed–Müller Sequences for Radar Detection of Nonzero Doppler Targets

    Science.gov (United States)

    Wang, Xuezhi; Huang, Xiaotao; Suvorova, Sofia; Moran, Bill

    2018-01-01

    Golay complementary waveforms can, in theory, yield radar returns of high range resolution with essentially zero sidelobes. In practice, when deployed conventionally, while high signal-to-noise ratios can be achieved for static target detection, significant range sidelobes are generated by target returns of nonzero Doppler causing unreliable detection. We consider signal processing techniques using Golay complementary waveforms to improve radar detection performance in scenarios involving multiple nonzero Doppler targets. A signal processing procedure based on an existing, so called, Binomial Design algorithm that alters the transmission order of Golay complementary waveforms and weights the returns is proposed in an attempt to achieve an enhanced illumination performance. The procedure applies one of three proposed waveform transmission ordering algorithms, followed by a pointwise nonlinear processor combining the outputs of the Binomial Design algorithm and one of the ordering algorithms. The computational complexity of the Binomial Design algorithm and the three ordering algorithms are compared, and a statistical analysis of the performance of the pointwise nonlinear processing is given. Estimation of the areas in the Delay–Doppler map occupied by significant range sidelobes for given targets are also discussed. Numerical simulations for the comparison of the performances of the Binomial Design algorithm and the three ordering algorithms are presented for both fixed and randomized target locations. The simulation results demonstrate that the proposed signal processing procedure has a better detection performance in terms of lower sidelobes and higher Doppler resolution in the presence of multiple nonzero Doppler targets compared to existing methods. PMID:29324708

  19. High-Resolution Remotely Sensed Small Target Detection by Imitating Fly Visual Perception Mechanism

    Directory of Open Access Journals (Sweden)

    Fengchen Huang

    2012-01-01

    Full Text Available The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.

  20. High-resolution remotely sensed small target detection by imitating fly visual perception mechanism.

    Science.gov (United States)

    Huang, Fengchen; Xu, Lizhong; Li, Min; Tang, Min

    2012-01-01

    The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.

  1. Real-time automatic small infrared target detection using local spectral filtering in the frequency

    Science.gov (United States)

    Chen, Hao; Zhang, Hong; Li, Jiafeng; Yuan, Ding; Sun, Mingui

    2014-11-01

    Accurate and fast detection of small infrared target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. Based on human visual attention mechanism, an automatic detection algorithm for small infrared target is presented. In this paper, instead of searching for infrared targets, we model regular patches that do not attract much attention by our visual system. This is inspired by the property that the regular patches in spatial domain turn out to correspond to the spikes in the amplitude spectrum. Unlike recent approaches using global spectral filtering, we define the concept of local maxima suppression using local spectral filtering to smooth the spikes in the amplitude spectrum, thereby producing the pop-out of the infrared targets. In the proposed method, we firstly compute the amplitude spectrum of an input infrared image. Second, we find the local maxima of the amplitude spectrum using cubic facet model. Third, we suppress the local maxima using the convolution of the local spectrum with a low-pass Gaussian kernel of an appropriate scale. At last, the detection result in spatial domain is obtained by reconstructing the 2D signal using the original phase and the log amplitude spectrum by suppressing local maxima. The experiments are performed for some real-life IR images, and the results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be further used for real-time detection and tracking.

  2. Multispectral radiation detection of small changes in target emissivity. [ice measurements on space shuttle external tank

    Science.gov (United States)

    Gagliano, J. A.; Newton, J. M.; Schuchardt, J. M.

    1982-01-01

    An investigation into the multispectral radiation detection of small changes in target emissivity has been performed by Georgia Tech. A series of ice detection measurements on the shuttle external tank (ET) were performed using an advanced instrumentation radiometer operating at 35/95 GHz. Actual shuttle ET ice detection measurements were run at NASA's National Space Technology Laboratory (NSTL) during cryogenic fueling operations prior to orbiter engine firing tests. Investigations revealed that ET icing caused an increase in surface brightness temperature and the test results further demonstrated the usefulness of millimeter wave radiometry for the detection of ice on the ET.

  3. Distributed Detection of Randomly Located Targets in Mobility-Assisted Sensor Networks with Node Mobility Management

    Directory of Open Access Journals (Sweden)

    Jayaweera SudharmanK

    2010-01-01

    Full Text Available Performance gain achieved by adding mobile nodes to a stationary sensor network for target detection depends on factors such as the number of mobile nodes deployed, mobility patterns, speed and energy constraints of mobile nodes, and the nature of the target locations (deterministic or random. In this paper, we address the problem of distributed detection of a randomly located target by a hybrid sensor network. Specifically, we develop two decision-fusion architectures for detection where in the first one, impact of node mobility is taken into account for decisions updating at the fusion center, while in the second model the impact of node mobility is taken at the node level decision updating. The cost of deploying mobile nodes is analyzed in terms of the minimum fraction of mobile nodes required to achieve the desired performance level within a desired delay constraint. Moreover, we consider managing node mobility under given constraints.

  4. Visual real-time detection, recognition and tracking of ground and airborne targets

    Science.gov (United States)

    Kovács, Levente; Benedek, Csaba

    2011-03-01

    This paper presents methods and algorithms for real-time visual target detection, recognition and tracking, both in the case of ground-based objects (surveyed from a moving airborne imaging sensor) and flying targets (observed from a ground-based or vehicle mounted sensor). The methods are highly parallelized and partially implemented on GPU, with the goal of real-time speeds even in the case of multiple target observations. Real-time applicability is in focus. The methods use single camera observations, providing a passive and expendable alternative for expensive and/or active sensors. Use cases involve perimeter defense and surveillance situations, where passive detection and observation is a priority (e.g. aerial surveillance of a compound, detection of reconnaissance drones, etc.).

  5. Effects of Alzheimer’s Disease on visual target detection: a “peripheral bias”

    Directory of Open Access Journals (Sweden)

    Vanessa Vallejo

    2016-08-01

    Full Text Available Visual exploration is an omnipresent activity in everyday life, and might represent an important determinant of visual attention deficits in patients with Alzheimer’s Disease (AD. The present study aimed at investigating visual search performance in AD patients, in particular target detection in the far periphery, in daily living scenes. Eighteen AD patients and twenty healthy controls participated in the study. They were asked to freely explore a hemispherical screen, covering ± 90°, and to respond to targets presented at 10°, 30°, and 50° eccentricity, while their eye movements were recorded. Compared to healthy controls, AD patients recognized less targets appearing in the center. No difference was found in target detection in the periphery. This pattern was confirmed by the fixation distribution analysis. These results show a neglect for the central part of the visual field for AD patients and provide new insights by mean of a search task involving a larger field of view.

  6. Effects of Alzheimer's Disease on Visual Target Detection: A "Peripheral Bias".

    Science.gov (United States)

    Vallejo, Vanessa; Cazzoli, Dario; Rampa, Luca; Zito, Giuseppe A; Feuerstein, Flurin; Gruber, Nicole; Müri, René M; Mosimann, Urs P; Nef, Tobias

    2016-01-01

    Visual exploration is an omnipresent activity in everyday life, and might represent an important determinant of visual attention deficits in patients with Alzheimer's Disease (AD). The present study aimed at investigating visual search performance in AD patients, in particular target detection in the far periphery, in daily living scenes. Eighteen AD patients and 20 healthy controls participated in the study. They were asked to freely explore a hemispherical screen, covering ±90°, and to respond to targets presented at 10°, 30°, and 50° eccentricity, while their eye movements were recorded. Compared to healthy controls, AD patients recognized less targets appearing in the center. No difference was found in target detection in the periphery. This pattern was confirmed by the fixation distribution analysis. These results show a neglect for the central part of the visual field for AD patients and provide new insights by mean of a search task involving a larger field of view.

  7. Effects of Alzheimer’s Disease on Visual Target Detection: A “Peripheral Bias”

    Science.gov (United States)

    Vallejo, Vanessa; Cazzoli, Dario; Rampa, Luca; Zito, Giuseppe A.; Feuerstein, Flurin; Gruber, Nicole; Müri, René M.; Mosimann, Urs P.; Nef, Tobias

    2016-01-01

    Visual exploration is an omnipresent activity in everyday life, and might represent an important determinant of visual attention deficits in patients with Alzheimer’s Disease (AD). The present study aimed at investigating visual search performance in AD patients, in particular target detection in the far periphery, in daily living scenes. Eighteen AD patients and 20 healthy controls participated in the study. They were asked to freely explore a hemispherical screen, covering ±90°, and to respond to targets presented at 10°, 30°, and 50° eccentricity, while their eye movements were recorded. Compared to healthy controls, AD patients recognized less targets appearing in the center. No difference was found in target detection in the periphery. This pattern was confirmed by the fixation distribution analysis. These results show a neglect for the central part of the visual field for AD patients and provide new insights by mean of a search task involving a larger field of view. PMID:27582704

  8. Implementation Of Vision-Based Landing Target Detection For VTOL UAV Using Raspberry Pi

    Directory of Open Access Journals (Sweden)

    Ei Ei Nyein

    2017-04-01

    Full Text Available This paper presents development and implementation of a real-time vision-based landing system for VTOL UAV. We use vision for precise target detection and recognition. A UAV is equipped with the onboard raspberry pi camera to take images and raspberry pi platform to operate the image processing techniques. Today image processing is used for various applications in this paper it is used for landing target extraction. And vision system is also used for take-off and landing function in VTOL UAV. Our landing target design is used as the helipad H shape. Firstly the image is captured to detect the target by the onboard camera. Next the capture image is operated in the onboard processor. Finally the alert sound signal is sent to the remote control RC for landing VTOL UAV. The information obtained from vision system is used to navigate a safe landing. The experimental results from real tests are presented.

  9. Location Detection and Tracking of Moving Targets by a 2D IR-UWB Radar System

    Directory of Open Access Journals (Sweden)

    Van-Han Nguyen

    2015-03-01

    Full Text Available In indoor environments, the Global Positioning System (GPS and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB technology has become a possible solution for object detection, localization and tracking in indoor environments, because of its high range resolution, compact size and low cost. This paper presents improved target detection and tracking techniques for moving objects with impulse-radio UWB (IR-UWB radar in a short-range indoor area. This is achieved through signal-processing steps, such as clutter reduction, target detection, target localization and tracking. In this paper, we introduce a new combination consisting of our proposed signal-processing procedures. In the clutter-reduction step, a filtering method that uses a Kalman filter (KF is proposed. Then, in the target detection step, a modification of the conventional CLEAN algorithm which is used to estimate the impulse response from observation region is applied for the advanced elimination of false alarms. Then, the output is fed into the target localization and tracking step, in which the target location and trajectory are determined and tracked by using unscented KF in two-dimensional coordinates. In each step, the proposed methods are compared to conventional methods to demonstrate the differences in performance. The experiments are carried out using actual IR-UWB radar under different scenarios. The results verify that the proposed methods can improve the probability and efficiency of target detection and tracking.

  10. Location Detection and Tracking of Moving Targets by a 2D IR-UWB Radar System

    Science.gov (United States)

    Nguyen, Van-Han; Pyun, Jae-Young

    2015-01-01

    In indoor environments, the Global Positioning System (GPS) and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB) technology has become a possible solution for object detection, localization and tracking in indoor environments, because of its high range resolution, compact size and low cost. This paper presents improved target detection and tracking techniques for moving objects with impulse-radio UWB (IR-UWB) radar in a short-range indoor area. This is achieved through signal-processing steps, such as clutter reduction, target detection, target localization and tracking. In this paper, we introduce a new combination consisting of our proposed signal-processing procedures. In the clutter-reduction step, a filtering method that uses a Kalman filter (KF) is proposed. Then, in the target detection step, a modification of the conventional CLEAN algorithm which is used to estimate the impulse response from observation region is applied for the advanced elimination of false alarms. Then, the output is fed into the target localization and tracking step, in which the target location and trajectory are determined and tracked by using unscented KF in two-dimensional coordinates. In each step, the proposed methods are compared to conventional methods to demonstrate the differences in performance. The experiments are carried out using actual IR-UWB radar under different scenarios. The results verify that the proposed methods can improve the probability and efficiency of target detection and tracking. PMID:25808773

  11. An Underwater Target Detection System for Electro-Optical Imagery Data

    Science.gov (United States)

    2010-06-01

    The detection method involves identifying frames of interest (FOI) containing the potential targets. Once the FOI have been identified, regions of...complicated one. Previous work on EO data has been focused on Streak Tube Imaging Lidar ( STIL ) system [1]–[4], and laser line scan (LLS) [5]–[7...based systems. STIL sensor produces high- resolution 3-D images of underwater objects by scanning (line by line), on the target field [1]. The collected

  12. Targeting Premalignant Lesions: Implications for Early Breast Cancer Detection and Intervention

    Science.gov (United States)

    2016-04-01

    1 AWARD NUMBER: W81XWH-14-1-0032 TITLE: Targeting Premalignant Lesions : Implications for Early Breast Cancer Detection and Intervention...2015 – 31 Mar 2016 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-14-1-0032 Targeting Premalignant Lesions : Implications for Early Breast...carcinoma. In this study, we aimed to identify peptides that specifically recognize premalignant lesions in the mammary tissue. To achieve this goal, we

  13. High Speed Dim Air Target Detection Using Airborne Radar under Clutter and Jamming Effects

    OpenAIRE

    A. E. Almslmany; Q. S. Cao; Wang, C.Y.

    2015-01-01

    The challenging potential problems associated with using airborne radar in detection of high Speed Maneuvering Dim Target (HSMDT) are the highly noise, jamming and clutter effects. The problem is not only how to remove clutter and jamming as well as the range migration and Doppler ambiguity estimation problems due to high relative speed between the targets and airborne radar. Some of the recently published works ignored the range migration problems, while the others ignored the Doppler ambigu...

  14. Target Word-Specific Experiment by Detecting Event-Related Potential for ALS Patients

    Science.gov (United States)

    Kanou, Naoyuki; Sakuma, Kenji; Nakashima, Kenji

    For communication of ALS patients, the authors put emphasis on ERP. This paper described that ALS patient could get high rate of correct judgment on the target word-specific experiment by detecting ERP. For practical use, it is very important that ALS patients can communicate with surrounding person smoothly. The authors discussed how to shorten the time to specify the target word, and discussed the prevention of misjudgment.

  15. Multiple Moving Targets Detection and Parameters Estimation in Strong Reverberation Environments

    Directory of Open Access Journals (Sweden)

    Ge Yu

    2016-01-01

    Full Text Available This paper considers the problem of multiple moving targets detection and parameters estimation (direction of arrival and range in strong reverberation environments. As reverberation has a strong correlation with target echo, the performance of target detection and parameters estimation is significantly degraded in practical underwater environments. In this paper, we utilize two uniform circular arrays to receive plane wave of the linear frequency modulation signal reflected from far-field targets. On the basis of received signal, we build a variance matrix of multiple beams by using modal decomposition, conventional beamforming, and fractional Fourier transform (FrFT. We then propose a novel detection method and an estimation method of parameters based on the constructed image. A significant feature of the proposed methods is that our design does not involve any a priori knowledge about targets number and parameters of marine environments. Finally, we demonstrate via numerical simulation examples that the detection probability and the accuracy of estimated parameters of the proposed method are higher than the existing methods in both low signal-to-reverberation ratio and signal-to-noise ratio environment.

  16. Detection of barycenter of planar target based on laser reflective tomography

    Science.gov (United States)

    Lin, Fang; Wang, Jin-cheng; Lei, Wu-hu; Hu, Yi-hua

    2017-11-01

    Reflective tomography imaging Lidar system has been proved a useful approach in remote high-resolution imaging. For space target such as debris, barycenter detection could help monitor their motion status and track. We proposed a barycenter location method based on laser reflection tomography, which could precisely determine the range information and location of barycenter of planar target, whether it is coincident with rotation center or not. Experiments on actual Lidar system was conducted and the results came out that calculated barycenter is about 5 cm away from the real barycenter in detection range of 50 m, which could initially confirm the efficiency of this method.

  17. Vision models for target detection and recognition in memory of Arthur Menendez

    CERN Document Server

    Peli, Eli

    1995-01-01

    This book is an international collection of contributions from academia, industry and the armed forces. It addresses current and emerging Spatial Vision Models and their application to the understanding, prediction and evaluation of the tasks of target detection and recognition. The discussion in many of the chapters is framed in terms of military targets and military vision aids. However, the techniques analyses and problems are by no means limited to this area of application. The detection and recognition of an armored vehicle from a reconnaissance image are performed by the same visual syst

  18. Target Detection in SAR Images Based on a Level Set Approach

    Energy Technology Data Exchange (ETDEWEB)

    Marques, Regis C.P.; Medeiros, Fatima N.S.; Ushizima, Daniela M.

    2008-09-01

    This paper introduces a new framework for point target detection in synthetic aperture radar (SAR) images. We focus on the task of locating reflective small regions using alevel set based algorithm. Unlike most of the approaches in image segmentation, we address an algorithm which incorporates speckle statistics instead of empirical parameters and also discards speckle filtering. The curve evolves according to speckle statistics, initially propagating with a maximum upward velocity in homogeneous areas. Our approach is validated by a series of tests on synthetic and real SAR images and compared with three other segmentation algorithms, demonstrating that it configures a novel and efficient method for target detection purpose.

  19. Optimizing a custom tiling microarray for low input detection and identification of unamplified virus targets.

    Science.gov (United States)

    Yu, Christine; Wales, Samantha Q; Mammel, Mark K; Hida, Kaoru; Kulka, Michael

    2016-08-01

    Viruses are major pathogens causing foodborne illnesses and are often present at low levels in foods, thus requiring sensitive techniques for their detection in contaminated foods. The lack of efficient culture methods for many foodborne viruses and the potential for multi-species viral contamination have driven investigation toward non-amplification based methods for virus detection and identification. A custom DNA microarray (FDA_EVIR) was assessed for its sensitivity in the detection and identification of low-input virus targets, human hepatitis A virus, norovirus, and coxsackievirus, individually and in combination. Modifications to sample processing were made to accommodate low input levels of unamplified virus targets, which included addition of carrier cDNA, RNase treatment, and optimization of DNase I-mediated target fragmentation. Amplification-free detection and identification of foodborne viruses were achieved in the range of 250-500 copies of virus RNA. Alternative data analysis methods were employed to distinguish the genotypes of the viruses particularly at lower levels of target input and the single probe-based analysis approach made it possible to identify a minority species in a multi-virus complex. The oligonucleotide array is shown to be a promising platform to detect foodborne viruses at low levels close to what are anticipated in food or environmental samples. Published by Elsevier B.V.

  20. Detection and Characterization of Ship Targets Using CryoSat-2 Altimeter Waveforms

    Directory of Open Access Journals (Sweden)

    Jesús Gómez-Enri

    2016-02-01

    Full Text Available This article describes an investigation of the new possibilities offered by SAR altimetry compared with conventional altimetry in the detection and characterization of non-ocean targets. We explore the capabilities of the first SAR altimeter installed on the European Space Agency satellite CryoSat-2 for the detection and characterization of ships. We propose a methodology for the detection of anomalous targets in the radar signals, based on the advantages of SAR/Doppler processing over conventional altimetry. A simple metric is proposed for the automatic detection and separation of ship targets; additional geometric considerations are introduced, to assess the compatibility between the structures detected and the actual location and characteristics of the ships observed. A test-case is presented with multiple targets that are confirmed as large vessels cruising in the proximity of a CryoSat-2 track crossing the Alboran Sea (Western Mediterranean. The presence and position of these ships at the time of satellite passage have been corroborated by the data retrieved from the Automatic Information System database. A principal motive for this research is the future altimetry missions that will provide global SAR coverage (e.g., Sentinel-3. This methodology may complement the existing tracking systems, with particular reference to the capability of compiling global statistics based on freely available data.

  1. Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar.

    Science.gov (United States)

    Raja Abdullah, Raja Syamsul Azmir; Abdul Aziz, Noor Hafizah; Abdul Rashid, Nur Emileen; Ahmad Salah, Asem; Hashim, Fazirulhisyam

    2016-09-29

    The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system's capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.

  2. Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar

    Directory of Open Access Journals (Sweden)

    Raja Syamsul Azmir Raja Abdullah

    2016-09-01

    Full Text Available The passive bistatic radar (PBR system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR. The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system’s capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.

  3. Visual accommodation and target detection in the vicinity of a window post.

    Science.gov (United States)

    Chong, J; Triggs, T J

    1989-02-01

    The visual environment of a driver in a car or a pilot in an airplane has intervening objects from the vehicle such as A-pillar posts between the windscreen and the doors in the car or cockpit pillars in the airplane. The presence of such objects can bias the observer's visual accommodation response because of the Mandelbaum effect (e.g., Owens, 1979). When subjects were allowed to focus toward a distance by looking through a large aperture in an intervening post, the detection (monocular) of a briefly presented distant target was found to be significantly better than when no aperture was present. When the size of the aperture was decreased from 2.3 to 1.15 deg diameter, target detection performance was significantly decreased and remained constant as further reduction of foveal cues was made. Although the detection results were generally in agreement with the visual accommodation results, detection accuracy changed significantly only with marked changes in accommodation. In addition to an accommodation bias, interference to target detection was also observed for those targets occurring at a laterally proximal position to the intervening object.

  4. In situ targeted MRI detection of Helicobacter pylori with stable magnetic graphitic nanocapsules

    Science.gov (United States)

    Li, Yunjie; Hu, Xiaoxiao; Ding, Ding; Zou, Yuxiu; Xu, Yiting; Wang, Xuewei; Zhang, Yin; Chen, Long; Chen, Zhuo; Tan, Weihong

    2017-06-01

    Helicobacter pylori infection is implicated in the aetiology of many diseases. Despite numerous studies, a painless, fast and direct method for the in situ detection of H. pylori remains a challenge, mainly due to the strong acidic/enzymatic environment of the gastric mucosa. Herein, we report the use of stable magnetic graphitic nanocapsules (MGNs), for in situ targeted magnetic resonance imaging (MRI) detection of H. pylori. Several layers of graphene as the shell effectively protect the magnetic core from corrosion while retaining the superior contrast effect for MRI in the gastric environment. Boronic-polyethylene glycol molecules were synthesized and modified on the MGN surface for targeted MRI detection. In a mouse model of H. pylori-induced infection, H. pylori was specifically detected through both T2-weighted MR imaging and Raman gastric mucosa imaging using functionalized MGNs. These results indicated that enhancement of MRI using MGNs may be a promising diagnostic and bioimaging platform for very harsh conditions.

  5. Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications

    Science.gov (United States)

    Zhu, Zhe

    2017-08-01

    The free and open access to all archived Landsat images in 2008 has completely changed the way of using Landsat data. Many novel change detection algorithms based on Landsat time series have been developed We present a comprehensive review of four important aspects of change detection studies based on Landsat time series, including frequencies, preprocessing, algorithms, and applications. We observed the trend that the more recent the study, the higher the frequency of Landsat time series used. We reviewed a series of image preprocessing steps, including atmospheric correction, cloud and cloud shadow detection, and composite/fusion/metrics techniques. We divided all change detection algorithms into six categories, including thresholding, differencing, segmentation, trajectory classification, statistical boundary, and regression. Within each category, six major characteristics of different algorithms, such as frequency, change index, univariate/multivariate, online/offline, abrupt/gradual change, and sub-pixel/pixel/spatial were analyzed. Moreover, some of the widely-used change detection algorithms were also discussed. Finally, we reviewed different change detection applications by dividing these applications into two categories, change target and change agent detection.

  6. Detection of genetically modified organisms (GMOs) using isothermal amplification of target DNA sequences.

    Science.gov (United States)

    Lee, David; La Mura, Maurizio; Allnutt, Theo R; Powell, Wayne

    2009-02-02

    The most common method of GMO detection is based upon the amplification of GMO-specific DNA amplicons using the polymerase chain reaction (PCR). Here we have applied the loop-mediated isothermal amplification (LAMP) method to amplify GMO-related DNA sequences, 'internal' commonly-used motifs for controlling transgene expression and event-specific (plant-transgene) junctions. We have tested the specificity and sensitivity of the technique for use in GMO studies. Results show that detection of 0.01% GMO in equivalent background DNA was possible and dilutions of template suggest that detection from single copies of the template may be possible using LAMP. This work shows that GMO detection can be carried out using LAMP for routine screening as well as for specific events detection. Moreover, the sensitivity and ability to amplify targets, even with a high background of DNA, here demonstrated, highlights the advantages of this isothermal amplification when applied for GMO detection.

  7. Sparse Representation for Infrared Dim Target Detection via a Discriminative Over-Complete Dictionary Learned Online

    Directory of Open Access Journals (Sweden)

    Zheng-Zhou Li

    2014-05-01

    Full Text Available It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn’t be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

  8. Detecting ship targets in spaceborne infrared image based on modeling radiation anomalies

    Science.gov (United States)

    Wang, Haibo; Zou, Zhengxia; Shi, Zhenwei; Li, Bo

    2017-09-01

    Using infrared imaging sensors to detect ship target in the ocean environment has many advantages compared to other sensor modalities, such as better thermal sensitivity and all-weather detection capability. We propose a new ship detection method by modeling radiation anomalies for spaceborne infrared image. The proposed method can be decomposed into two stages, where in the first stage, a test infrared image is densely divided into a set of image patches and the radiation anomaly of each patch is estimated by a Gaussian Mixture Model (GMM), and thereby target candidates are obtained from anomaly image patches. In the second stage, target candidates are further checked by a more discriminative criterion to obtain the final detection result. The main innovation of the proposed method is inspired by the biological mechanism that human eyes are sensitive to the unusual and anomalous patches among complex background. The experimental result on short wavelength infrared band (1.560 - 2.300 μm) and long wavelength infrared band (10.30 - 12.50 μm) of Landsat-8 satellite shows the proposed method achieves a desired ship detection accuracy with higher recall than other classical ship detection methods.

  9. Detecting single-target changes in multiple object tracking: The case of peripheral vision.

    Science.gov (United States)

    Vater, Christian; Kredel, Ralf; Hossner, Ernst-Joachim

    2016-05-01

    In the present study, we investigated whether peripheral vision can be used to monitor multiple moving objects and to detect single-target changes. For this purpose, in Experiment 1, a modified multiple object tracking (MOT) setup with a large projection screen and a constant-position centroid phase had to be checked first. Classical findings regarding the use of a virtual centroid to track multiple objects and the dependency of tracking accuracy on target speed could be successfully replicated. Thereafter, the main experimental variations regarding the manipulation of to-be-detected target changes could be introduced in Experiment 2. In addition to a button press used for the detection task, gaze behavior was assessed using an integrated eyetracking system. The analysis of saccadic reaction times in relation to the motor response showed that peripheral vision is naturally used to detect motion and form changes in MOT, because saccades to the target often occurred after target-change offset. Furthermore, for changes of comparable task difficulties, motion changes are detected better by peripheral vision than are form changes. These findings indicate that the capabilities of the visual system (e.g., visual acuity) affect change detection rates and that covert-attention processes may be affected by vision-related aspects such as spatial uncertainty. Moreover, we argue that a centroid-MOT strategy might reduce saccade-related costs and that eyetracking seems to be generally valuable to test the predictions derived from theories of MOT. Finally, we propose implications for testing covert attention in applied settings.

  10. Infrared dim and small target detecting and tracking method inspired by Human Visual System

    Science.gov (United States)

    Dong, Xiabin; Huang, Xinsheng; Zheng, Yongbin; Shen, Lurong; Bai, Shengjian

    2014-01-01

    Detecting and tracking dim and small target in infrared images and videos is one of the most important techniques in many computer vision applications, such as video surveillance and infrared imaging precise guidance. Recently, more and more algorithms based on Human Visual System (HVS) have been proposed to detect and track the infrared dim and small target. In general, HVS concerns at least three mechanisms including contrast mechanism, visual attention and eye movement. However, most of the existing algorithms simulate only a single one of the HVS mechanisms, resulting in many drawbacks of these algorithms. A novel method which combines the three mechanisms of HVS is proposed in this paper. First, a group of Difference of Gaussians (DOG) filters which simulate the contrast mechanism are used to filter the input image. Second, a visual attention, which is simulated by a Gaussian window, is added at a point near the target in order to further enhance the dim small target. This point is named as the attention point. Eventually, the Proportional-Integral-Derivative (PID) algorithm is first introduced to predict the attention point of the next frame of an image which simulates the eye movement of human being. Experimental results of infrared images with different types of backgrounds demonstrate the high efficiency and accuracy of the proposed method to detect and track the dim and small targets.

  11. Clusters versus GPUs for Parallel Target and Anomaly Detection in Hyperspectral Images

    Directory of Open Access Journals (Sweden)

    Paz Abel

    2010-01-01

    Full Text Available Abstract Remotely sensed hyperspectral sensors provide image data containing rich information in both the spatial and the spectral domain, and this information can be used to address detection tasks in many applications. In many surveillance applications, the size of the objects (targets searched for constitutes a very small fraction of the total search area and the spectral signatures associated to the targets are generally different from those of the background, hence the targets can be seen as anomalies. In hyperspectral imaging, many algorithms have been proposed for automatic target and anomaly detection. Given the dimensionality of hyperspectral scenes, these techniques can be time-consuming and difficult to apply in applications requiring real-time performance. In this paper, we develop several new parallel implementations of automatic target and anomaly detection algorithms. The proposed parallel algorithms are quantitatively evaluated using hyperspectral data collected by the NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS system over theWorld Trade Center (WTC in New York, five days after the terrorist attacks that collapsed the two main towers in theWTC complex.

  12. Mid-infrared imaging system based on polarizers for detecting marine targets covered in sun glint.

    Science.gov (United States)

    Zhao, Huijie; Ji, Zheng; Zhang, Ying; Sun, Xiaofeng; Song, Pengfei; Li, Yansong

    2016-07-25

    When a marine target is detected by a mid-infrared detector on a sunny day, the target's information could be lost if it is located in sun glint. Therefore, we developed a new mid-infrared imaging system capable of effectively detecting marine targets in regions of strong sun glint, which is presented in this report. Firstly, the theory of the analysis methods employed in different detection scenarios is briefly described to establish whether one or two polarizers should be utilized to suppress further the p-polarized component of sun glint. Secondly, for the case in which a second polarizer is employed, the formula for the optimum angle between the two polarizers is given. Then, the results of our field experiment are presented, demonstrating that the developed system can significantly reduce sun glint and can enhance the contrast of target images. A commonly used image processing algorithm proved capable of identifying a target in sun glint, confirming the effectiveness of our proposed mid-infrared polarization imaging system.

  13. Detection of small targets in a marine environment using laser radar

    NARCIS (Netherlands)

    Kunz, G.J.; Bekman, H.H.P.T.; Benoist, K.W.; Cohen, L.H.; Heuvel, J.C. van den; Putten, F.J.M.

    2005-01-01

    Small maritime targets, e.g., periscope tubes, jet skies, swimmers and small boats, are potential threats for naval ships under many conditions, but are difficult to detect with current radar systems due to their limited radar cross section and the presence of sea clutter. On the other hand,

  14. Low-energy cross section measurements through detection of secondary gamma emission and thick target

    Energy Technology Data Exchange (ETDEWEB)

    Barron P, L.; Chavez L, E.; Huerta H, A.; Ortiz, M.E. [Instituto de Fisica UNAM, A.P. 20-364, 04510 Mexico, D.F. (Mexico); Murillo O, G.; Aguilera, E.F.; Martinez Q, E.; Moreno B, E.; Policroniades R, R.; Varela G, A. [Instituto Nacional de Investigaciones Nucleares, Departamento del Acelerador, A.P. 18-1027, 11801, Mexico, D.F. (Mexico)

    2004-12-01

    In this work, the detection of secondary gamma rays in a tightly shielded Germanium detector, together with a high intensity heavy ion beam on a thick target is used to measure the fusion cross section for the {sup 12} C + {sup 12} C system at very low energies. (Author) 14 refs., 1 tab., 8 figs.

  15. Algorithm for Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar Gradiometer

    Science.gov (United States)

    2016-06-01

    TECHNICAL REPORT Algorithm for Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar...Distribution Statement A This document has been cleared for public release This report was prepared under contract to...constitute or imply its endorsement, recommendation, or favoring by the Department of Defense. REPORT DOCUMENTATION PAGE Standard Form 298 (Rev. 8

  16. Target detection and driving behaviour measurements in a driving simulator at mesopic light levels

    NARCIS (Netherlands)

    Alferdinck, J.W.A.M.

    2006-01-01

    During night-time driving hazardous objects often appear at mesopic light levels, which are typically measured using light meters with a spectral sensitivity that is only valid for photopic light levels. In order to develop suitable mesopic models a target detection experiment was performed in a

  17. Targeted superparamagnetic iron oxide nanoparticles for early detection of cancer: Possibilities and challenges.

    Science.gov (United States)

    Bakhtiary, Zahra; Saei, Amir Ata; Hajipour, Mohammad J; Raoufi, Mohammad; Vermesh, Ophir; Mahmoudi, Morteza

    2016-02-01

    Nanomedicine, the integration of nanotechnological tools in medicine demonstrated promising potential to revolutionize the diagnosis and treatment of various human health conditions. Nanoparticles (NPs) have shown much promise in diagnostics of cancer, especially since they can accommodate targeting molecules on their surface, which search for specific tumor cell receptors upon injection into the blood stream. This concentrates the NPs in the desired tumor location. Furthermore, such receptor-specific targeting may be exploited for detection of potential metastases in an early stage. Some NPs, such as superparamagnetic iron oxide NPs (SPIONs), are also compatible with magnetic resonance imaging (MRI), which makes their clinical translation and application rather easy and accessible for tumor imaging purposes. Furthermore, multifunctional and/or theranostic NPs can be used for simultaneous imaging of cancer and drug delivery. In this review article, we will specifically focus on the application of SPIONs in early detection and imaging of major cancer types. Super-paramagnetic iron oxide nanoparticles (SPIONs) have been reported by many to be useful as an MRI contrast agent in the detection of tumors. To further enhance the tumor imaging, SPIONs can be coupled with tumor targeting motifs. In this article, the authors performed a comprehensive review on the current status of using targeted SPIONS in tumor detection and also the potential hurdles to overcome. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Improving target detection in visual search through the augmenting multi-sensory cues

    NARCIS (Netherlands)

    Hancock, P.A.; Mercado, J.E.; Merlo, J.; Erp, J.B.F. van

    2013-01-01

    The present experiment tested 60 individuals on a multiple screen, visual target detection task. Using a within-participant design, individuals received no-cue augmentation, an augmenting tactile cue alone, an augmenting auditory cue alone or both of the latter augmentations in combination. Results

  19. A seemingly most effective target for early detection and intervention of prostate tumor invasion

    Directory of Open Access Journals (Sweden)

    Yan-gao Man

    2010-01-01

    Full Text Available This commentary proposes that budding tumor cell projections from focally disrupted tumor capsules represent a most effective target for early detection and intervention of prostate tumor invasion. The rationale, supporting data, and clinical applications of the hypothesis are discussed.

  20. Effects of clonidine and scopolamine on multiple target detection in rapid serial visual presentation

    NARCIS (Netherlands)

    Brown, S.B.R.E.; Slagter, H.A.; van Noorden, M.S.; Giltay, E.J.; van der Wee, N.J.A.; Nieuwenhuis, S.

    2016-01-01

    Rationale: The specific role of neuromodulator systems in regulating rapid fluctuations of attention is still poorly understood. Objectives: In this study, we examined the effects of clonidine and scopolamine on multiple target detection in a rapid serial visual presentation task to assess the role

  1. Visual attention distracter insertion for improved EEG rapid serial visual presentation (RSVP) target stimuli detection

    Science.gov (United States)

    Khosla, Deepak; Huber, David J.; Martin, Kevin

    2017-05-01

    This paper† describes a technique in which we improve upon the prior performance of the Rapid Serial Visual Presentation (RSVP) EEG paradigm for image classification though the insertion of visual attention distracters and overall sequence reordering based upon the expected ratio of rare to common "events" in the environment and operational context. Inserting distracter images maintains the ratio of common events to rare events at an ideal level, maximizing the rare event detection via P300 EEG response to the RSVP stimuli. The method has two steps: first, we compute the optimal number of distracters needed for an RSVP stimuli based on the desired sequence length and expected number of targets and insert the distracters into the RSVP sequence, and then we reorder the RSVP sequence to maximize P300 detection. We show that by reducing the ratio of target events to nontarget events using this method, we can allow RSVP sequences with more targets without sacrificing area under the ROC curve (azimuth).

  2. A monocular vision system based on cooperative targets detection for aircraft pose measurement

    Science.gov (United States)

    Wang, Zhenyu; Wang, Yanyun; Cheng, Wei; Chen, Tao; Zhou, Hui

    2017-08-01

    In this paper, a monocular vision measurement system based on cooperative targets detection is proposed, which can capture the three-dimensional information of objects by recognizing the checkerboard target and calculating of the feature points. The aircraft pose measurement is an important problem for aircraft’s monitoring and control. Monocular vision system has a good performance in the range of meter. This paper proposes an algorithm based on coplanar rectangular feature to determine the unique solution of distance and angle. A continuous frame detection method is presented to solve the problem of corners’ transition caused by symmetry of the targets. Besides, a displacement table test system based on three-dimensional precision and measurement system human-computer interaction software has been built. Experiment result shows that it has a precision of 2mm in the range of 300mm to 1000mm, which can meet the requirement of the position measurement in the aircraft cabin.

  3. Indoor detection of passive targets recast as an inverse scattering problem

    Science.gov (United States)

    Gottardi, G.; Moriyama, T.

    2017-10-01

    The wireless local area networks represent an alternative to custom sensors and dedicated surveillance systems for target indoor detection. The availability of the channel state information has opened the exploitation of the spatial and frequency diversity given by the orthogonal frequency division multiplexing. Such a fine-grained information can be used to solve the detection problem as an inverse scattering problem. The goal of the detection is to reconstruct the properties of the investigation domain, namely to estimate if the domain is empty or occupied by targets, starting from the measurement of the electromagnetic perturbation of the wireless channel. An innovative inversion strategy exploiting both the frequency and the spatial diversity of the channel state information is proposed. The target-dependent features are identified combining the Kruskal-Wallis test and the principal component analysis. The experimental validation points out the detection performance of the proposed method when applied to an existing wireless link of a WiFi architecture deployed in a real indoor scenario. False detection rates lower than 2 [%] have been obtained.

  4. FPGA-Based Real-Time Moving Target Detection System for Unmanned Aerial Vehicle Application

    Directory of Open Access Journals (Sweden)

    Jia Wei Tang

    2016-01-01

    Full Text Available Moving target detection is the most common task for Unmanned Aerial Vehicle (UAV to find and track object of interest from a bird’s eye view in mobile aerial surveillance for civilian applications such as search and rescue operation. The complex detection algorithm can be implemented in a real-time embedded system using Field Programmable Gate Array (FPGA. This paper presents the development of real-time moving target detection System-on-Chip (SoC using FPGA for deployment on a UAV. The detection algorithm utilizes area-based image registration technique which includes motion estimation and object segmentation processes. The moving target detection system has been prototyped on a low-cost Terasic DE2-115 board mounted with TRDB-D5M camera. The system consists of Nios II processor and stream-oriented dedicated hardware accelerators running at 100 MHz clock rate, achieving 30-frame per second processing speed for 640 × 480 pixels’ resolution greyscale videos.

  5. Specific and selective target detection of supra-genome 21 Mers Salmonella via silicon nanowires biosensor

    Science.gov (United States)

    Mustafa, Mohammad Razif Bin; Dhahi, Th S.; Ehfaed, Nuri. A. K. H.; Adam, Tijjani; Hashim, U.; Azizah, N.; Mohammed, Mohammed; Noriman, N. Z.

    2017-09-01

    The nano structure based on silicon can be surface modified to be used as label-free biosensors that allow real-time measurements. The silicon nanowire surface was functionalized using 3-aminopropyltrimethoxysilane (APTES), which functions as a facilitator to immobilize biomolecules on the silicon nanowire surface. The process is simple, economical; this will pave the way for point-of-care applications. However, the surface modification and subsequent detection mechanism still not clear. Thus, study proposed step by step process of silicon nano surface modification and its possible in specific and selective target detection of Supra-genome 21 Mers Salmonella. The device captured the molecule with precisely; the approach took the advantages of strong binding chemistry created between APTES and biomolecule. The results indicated how modifications of the nanowires provide sensing capability with strong surface chemistries that can lead to specific and selective target detection.

  6. Maximizing the probability an aerial anti-submarine torpedo detects its target

    Science.gov (United States)

    Wang, Zhi-Jie

    2009-06-01

    As a result of the high speed of anti-submarine patrol aircraft as well as their wide range, high efficiency and other characteristics, aerial torpedoes released by anti-submarine patrol aircraft have become the key anti submarine tool. In order to improve operational efficiency, a deep study was made of the target detection probabilities for aerial torpedoes released by anti-submarine patrol aircraft. The operational modes of aerial torpedoes were analyzed and mathematical-simulation models were then established. The detection probabilities of three attacking modes were then calculated. Measures were developed for improving low probabilities of detection when attacking a probable target position. This study provides an important frame of reference for the operation of aerial torpedo released by anti-submarine patrol aircraft.

  7. EURISOL-DS Multi-MW Target: Cavitations detection by the a Laser Doppler Vibrometer

    CERN Document Server

    Cyril Kharoua, Yacine Kadi, Jacques Lettry, Laure Blumenfeld, Karel Samec (CERN)Knud Thomsen, Sergej Dementevjs, Rade Milenkovich (PSI)Anatoli Zik, Erik Platacis (IPUL)

    This technical note summarises the innovative measurement devices used within Task #2 of the European Isotope Separation On-Line Radioactive Ion Beam Facility Design Study (EURISOL-DS) to detect the occurrence of cavitation in liquid metal flowing inside the CGS target mock-up.During the METEX hydraulic experiment carried out at IPUL (Institute of Physics of the University of Latvia), a Laser Doppler Vibrometer was used to characterize the wall vibrations of the beam window at different flow regimes. A series of tests proved the high sensitivity of the LDV to detect the occurrence of cavitation in the liquid metal flowing inside the target. In this context, a dedicated test procedure was developed to establish the validity of using LDV for detecting the onset of cavitation.

  8. Gastric cancer target detection using near-infrared hyperspectral imaging with chemometrics

    Science.gov (United States)

    Yi, Weisong; Zhang, Jian; Jiang, Houmin; Zhang, Niya

    2014-09-01

    Gastric cancer is one of the leading causes of cancer death in the world due to its high morbidity and mortality. Hyperspectral imaging (HSI) is an emerging, non-destructive, cutting edge analytical technology that combines conventional imaging and spectroscopy in one single system. The manuscript has investigated the application of near-infrared hyperspectral imaging (900-1700 nm) (NIR-HSI) for gastric cancer detection with algorithms. Major spectral differences were observed in three regions (950-1050, 1150-1250, and 1400-1500 nm). By inspecting cancerous mean spectrum three major absorption bands were observed around 975, 1215 and 1450 nm. Furthermore, the cancer target detection results are consistent and conformed with histopathological examination results. These results suggest that NIR-HSI is a simple, feasible and sensitive optical diagnostic technology for gastric cancer target detection with chemometrics.

  9. Fluorophore-quencher based activatable targeted optical probes for detecting in vivo cancer metastases.

    Science.gov (United States)

    Ogawa, Mikako; Kosaka, Nobuyuki; Longmire, Michelle R; Urano, Yasuteru; Choyke, Peter L; Kobayashi, Hisataka

    2009-01-01

    In vivo molecularly targeted fluorescence imaging of tumors has been proposed as a strategy for improving cancer detection and management. Activatable fluorophores, which increased their fluorescence by 10-fold after binding tumor cells, result in much higher target to background ratios than conventional fluorophores. We developed an in vivo targeted activatable optical imaging probe based on a fluorophore-quencher pair, bound to a targeting moiety. With this system, fluorescence is quenched by the fluorophore-quencher interaction outside cancer cells, but is activated within the target cells by dissociation of the fluorophore-quencher pair. We selected the TAMRA (fluorophore)-QSY7 (quencher) pair and conjugated it to either avidin (targeting the D-galactose receptor) or trastuzumab (a monoclonal antibody against the human epithelial growth factor receptor type2 (HER2/neu)) and evaluated their performance in mouse models of cancer. Two probes, TAMRA-QSY7 conjugated avidin (Av-TM-Q7) and trastuzumab (Traz-TM-Q7) were synthesized. Both demonstrated better than similar self-quenching probes. In vitro fluorescence microscopic studies of SHIN3 and NIH/3T3/HER2+ cells demonstrated that Av-TM-Q7 and Traz-TM-Q7 produced high intracellular fluorescent signal. In vivo imaging with Av-TM-Q7 and Traz-TM-Q7 in mice enabled the detection of small tumors. This molecular imaging probe, based on a fluorophore-quencher pair conjugated to a targeting ligand, successfully detected tumors in vivo due to its high activation ratio and low background signal. Thus, these activatable probes, based on the fluorophore-quencher system, hold promise clinically for "see and treat" strategies of cancer management.

  10. One Novel Multiple-Target Plasmid Reference Molecule Targeting Eight Genetically Modified Canola Events for Genetically Modified Canola Detection.

    Science.gov (United States)

    Li, Zhuqing; Li, Xiang; Wang, Canhua; Song, Guiwen; Pi, Liqun; Zheng, Lan; Zhang, Dabing; Yang, Litao

    2017-09-27

    Multiple-target plasmid DNA reference materials have been generated and utilized as good substitutes of matrix-based reference materials in the analysis of genetically modified organisms (GMOs). Herein, we report the construction of one multiple-target plasmid reference molecule, pCAN, which harbors eight GM canola event-specific sequences (RF1, RF2, MS1, MS8, Topas 19/2, Oxy235, RT73, and T45) and a partial sequence of the canola endogenous reference gene PEP. The applicability of this plasmid reference material in qualitative and quantitative PCR assays of the eight GM canola events was evaluated, including the analysis of specificity, limit of detection (LOD), limit of quantification (LOQ), and performance of pCAN in the analysis of various canola samples, etc. The LODs are 15 copies for RF2, MS1, and RT73 assays using pCAN as the calibrator and 10 genome copies for the other events. The LOQ in each event-specific real-time PCR assay is 20 copies. In quantitative real-time PCR analysis, the PCR efficiencies of all event-specific and PEP assays are between 91% and 97%, and the squared regression coefficients (R2) are all higher than 0.99. The quantification bias values varied from 0.47% to 20.68% with relative standard deviation (RSD) from 1.06% to 24.61% in the quantification of simulated samples. Furthermore, 10 practical canola samples sampled from imported shipments in the port of Shanghai, China, were analyzed employing pCAN as the calibrator, and the results were comparable with those assays using commercial certified materials as the calibrator. Concluding from these results, we believe that this newly developed pCAN plasmid is one good candidate for being a plasmid DNA reference material in the detection and quantification of the eight GM canola events in routine analysis.

  11. Antagonism pattern detection between microRNA and target expression in Ewing's sarcoma.

    Directory of Open Access Journals (Sweden)

    Loredana Martignetti

    Full Text Available MicroRNAs (miRNAs have emerged as fundamental regulators that silence gene expression at the post-transcriptional and translational levels. The identification of their targets is a major challenge to elucidate the regulated biological processes. The overall effect of miRNA is reflected on target mRNA expression, suggesting the design of new investigative methods based on high-throughput experimental data such as miRNA and transcriptome profiles. We propose a novel statistical measure of non-linear dependence between miRNA and mRNA expression, in order to infer miRNA-target interactions. This approach, which we name antagonism pattern detection, is based on the statistical recognition of a triangular-shaped pattern in miRNA-target expression profiles. This pattern is observed in miRNA-target expression measurements since their simultaneously elevated expression is statistically under-represented in the case of miRNA silencing effect. The proposed method enables miRNA target prediction to strongly rely on cellular context and physiological conditions reflected by expression data. The procedure has been assessed on synthetic datasets and tested on a set of real positive controls. Then it has been applied to analyze expression data from Ewing's sarcoma patients. The antagonism relationship is evaluated as a good indicator of real miRNA-target biological interaction. The predicted targets are consistently enriched for miRNA binding site motifs in their 3'UTR. Moreover, we reveal sets of predicted targets for each miRNA sharing important biological function. The procedure allows us to infer crucial miRNA regulators and their potential targets in Ewing's sarcoma disease. It can be considered as a valid statistical approach to discover new insights in the miRNA regulatory mechanisms.

  12. Hybrid detection of target sequence DNA based on phosphorescence resonance energy transfer.

    Science.gov (United States)

    Miao, Yanming; Lv, Jinzhi; Yan, Guiqin

    2017-08-15

    The severe background fluorescence and scattering light of real biological samples or environmental samples largely reduce the sensitivity and accuracy of fluorescence resonance energy transfer sensors based on fluorescent quantum dots (QDs). To solve this problem, we designed a novel target sequence DNA biosensor based on phosphorescent resonance energy transfer (PRET). This sensor relied on Mn-doped ZnS (Mn-ZnS) room-temperature phosphorescence (RTP) QDs/poly-(diallyldimethylammonium chloride) (PDADMAC) nanocomposite (QDs+) as the energy donor and the single-strand DNA-ROX as the energy receptor. Thereby, an RTP biosensor was built and used to quantitatively detect target sequence DNA. This biosensor had a detection limit of 0.16nM and a linear range of 0.5-20nM for target sequence DNA. The dependence on RTP of QDs effectively avoided the interference from background fluorescence and scattering light in biological samples. Moreover, this sensor did not need sample pretreatment. Thus, this sensor compared with FRET is more feasible for quantitative detection of target sequence DNA in biological samples. Interestingly, the QDs+ nanocomposite prolonged the phosphorescence lifetime of Mn-ZnS QDs by 2.6 times to 4.94ms, which was 5-6 magnitude-order larger than that of fluorescent QDs. Thus, this sensor largely improves the optical properties of QDs and permits chemical reactions at a long enough time scale. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Target Detection over the Diurnal Cycle Using a Multispectral Infrared Sensor.

    Science.gov (United States)

    Zhao, Huijie; Ji, Zheng; Li, Na; Gu, Jianrong; Li, Yansong

    2016-12-29

    When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene is indistinguishable due to the temperature variation. In this paper, the benefits of using a multispectral-based infrared sensor over the diurnal cycle have been shown. Firstly, a brief theoretical analysis on how the thermal crossover influences a conventional thermal sensor, within the conditions where the thermal crossover would happen and why the mid-infrared (3~5 μm) multispectral technology is effective, is presented. Furthermore, the effectiveness of this technology is also described and we describe how the prototype design and multispectral technology is employed to help solve the thermal crossover detection problem. Thirdly, several targets are set up outside and imaged in the field experiment over a 24-h period. The experimental results show that the multispectral infrared imaging system can enhance the contrast of the detected images and effectively solve the failure of the conventional infrared sensor during the diurnal cycle, which is of great significance for infrared surveillance applications.

  14. A New Strategy to Reduce Influenza Escape: Detecting Therapeutic Targets Constituted of Invariance Groups

    Directory of Open Access Journals (Sweden)

    Julie Lao

    2017-03-01

    Full Text Available The pathogenicity of the different flu species is a real public health problem worldwide. To combat this scourge, we established a method to detect drug targets, reducing the possibility of escape. Besides being able to attach a drug candidate, these targets should have the main characteristic of being part of an essential viral function. The invariance groups that are sets of residues bearing an essential function can be detected genetically. They consist of invariant and synthetic lethal residues (interdependent residues not varying or slightly varying when together. We analyzed an alignment of more than 10,000 hemagglutinin sequences of influenza to detect six invariance groups, close in space, and on the protein surface. In parallel we identified five potential pockets on the surface of hemagglutinin. By combining these results, three potential binding sites were determined that are composed of invariance groups located respectively in the vestigial esterase domain, in the bottom of the stem and in the fusion area. The latter target is constituted of residues involved in the spring-loaded mechanism, an essential step in the fusion process. We propose a model describing how this potential target could block the reorganization of the hemagglutinin HA2 secondary structure and prevent viral entry into the host cell.

  15. Hyperspectral Target Detection via Adaptive Joint Sparse Representation and Multi-Task Learning with Locality Information

    Directory of Open Access Journals (Sweden)

    Yuxiang Zhang

    2017-05-01

    Full Text Available Target detection from hyperspectral images is an important problem but encounters a critical challenge of simultaneously reducing spectral redundancy and preserving the discriminative information. Recently, the joint sparse representation and multi-task learning (JSR-MTL approach was proposed to address the challenge. However, it does not fully explore the prior class label information of the training samples and the difference between the target dictionary and background dictionary when constructing the model. Besides, there may exist estimation bias for the unknown coefficient matrix with the use of minimization which is usually inconsistent in variable selection. To address these problems, this paper proposes an adaptive joint sparse representation and multi-task learning detector with locality information (JSRMTL-ALI. The proposed method has the following capabilities: (1 it takes full advantage of the prior class label information to construct an adaptive joint sparse representation and multi-task learning model; (2 it explores the great difference between the target dictionary and background dictionary with different regularization strategies in order to better encode the task relatedness; (3 it applies locality information by imposing an iterative weight on the coefficient matrix in order to reduce the estimation bias. Extensive experiments were carried out on three hyperspectral images, and it was found that JSRMTL-ALI generally shows a better detection performance than the other target detection methods.

  16. Distinguishing cytosine methylation using electrochemical, label-free detection of DNA hybridization and ds-targets.

    Science.gov (United States)

    Zhu, Bicheng; Booth, Marsilea A; Shepherd, Phillip; Sheppard, Allan; Travas-Sejdic, Jadranka

    2015-02-15

    In this communication we report on two important effects related to the detection of DNAs. Firstly, we investigate the sensor response to target DNA when the target is in a double stranded (ds) form and compare the response to single stranded (ss) target DNA. The importance in evaluating such an effect lies in the fact that most biological DNA targets are found in ds form. Secondly, we use synthetic ds targets to investigate the effect of DNA methylation on the sensor response. DNA methylation is known to affect functional properties of DNA and is related to a number of diseases, including various cancers. In these studies, we utilize our previously developed sensor platform, which is based on the use of a glassy carbon electrode-confined conducting polymer that is covalently modified with DNA probe sequences. The signal detection methodology we use is measuring a change in the reaction kinetics of ferro-ferricyanide redox couple at the electrode upon hybridization by means of electrical impedance spectroscopy (EIS). Additionally, EIS is utilized to study the kinetics of the hybridization of the conducting polymer-bound probe with methylated vs. non-methylated ds-DNA. Preliminary results are proving valuable as a guide to the future design of sensors for gene methylation. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Engineered Peptides for Applications in Cancer-Targeted Drug Delivery and Tumor Detection.

    Science.gov (United States)

    Soudy, R; Byeon, N; Raghuwanshi, Y; Ahmed, S; Lavasanifar, A; Kaur, K

    2017-01-01

    Cancer-targeting peptides as ligands for targeted delivery of anticancer drugs or drug carriers have the potential to significantly enhance the selectivity and the therapeutic benefit of current chemotherapeutic agents. Identification of tumor-specific biomarkers like integrins, aminopeptidase N, and epidermal growth factor receptor as well as the popularity of phage display techniques along with synthetic combinatorial methods used for peptide design and structure optimization have fueled the advancement and application of peptide ligands for targeted drug delivery and tumor detection in cancer treatment, detection and guided therapy. Although considerable preclinical data have shown remarkable success in the use of tumor targeting peptides, peptides generally suffer from poor pharmacokinetics, enzymatic instability, and weak receptor affinity, and they need further structural modification before successful translation to clinics is possible. The current review gives an overview of the different engineering strategies that have been developed for peptide structure optimization to confer selectivity and stability. We also provide an update on the methods used for peptide ligand identification, and peptide- receptor interactions. Additionally, some applications for the use of peptides in targeted delivery of chemotherapeutics and diagnostics over the past 5 years are summarized. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  18. NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs.

    Science.gov (United States)

    Morisset, Dany; Dobnik, David; Hamels, Sandrine; Zel, Jana; Gruden, Kristina

    2008-10-01

    We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1-25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification.

  19. Target detection in diagnostic ultrasound: Evaluation of a method based on the CLEAN algorithm.

    Science.gov (United States)

    Masoom, Hassan; Adve, Raviraj S; Cobbold, Richard S C

    2013-02-01

    A technique is proposed for the detection of abnormalities (targets) in ultrasound images using little or no a priori information and requiring little operator intervention. The scheme is a combination of the CLEAN algorithm, originally proposed for radio astronomy, and constant false alarm rate (CFAR) processing, as developed for use in radar systems. The CLEAN algorithm identifies areas in the ultrasound image that stand out above a threshold in relation to the background; CFAR techniques allow for an adaptive, semi-automated, selection of the threshold. Neither appears to have been previously used for target detection in ultrasound images and never together in any context. As a first step towards assessing the potential of this method we used a widely used method of simulating B-mode images (Field II). We assumed the use of a 256 element linear array operating at 3.0MHz into a water-like medium containing a density of point scatterers sufficient to simulate a background of fully developed speckle. Spherical targets with diameters ranging from 0.25 to 6.0mm and contrasts ranging from 0 to 12dB relative to the background were used as test objects. Using a contrast-detail analysis, the probability of detection curves indicate these targets can be consistently detected within a speckle background. Our results indicate that the method has considerable promise for the semi-automated detection of abnormalities with diameters greater than a few millimeters, depending on the contrast. Copyright © 2012 Elsevier B.V. All rights reserved.

  20. Target detection in sun glint using the improved MWIR polarization technique

    Science.gov (United States)

    Zheng, Ji; Zhao, Huijie; Li, Yansong; Cheng, Chi; Sun, Xiaofeng; Song, Pengfei; Wang, Shitao

    2017-08-01

    The sun glint problem is a major issue to be addressed for MWIR marine targets detection. The traditional technique based on the single horizontal linear polarizer was a common method to reduce the sun glint by eliminating its s-polarized component, nevertheless, the residual p-polarized component could be still too strong to saturate the detector in some cases. To solve this problem, the improved polarization technique based on two rotatable polarizers is presented. The field experiment results show that the improved polarization technique can significantly reduce sun glint and enhance the contrast of target images, confirming the effectiveness of the technology.

  1. Covariance-based band selection and its application to near-real-time hyperspectral target detection

    Science.gov (United States)

    Kim, Jun-Hyung; Kim, Jieun; Yang, Yukyung; Kim, Sohyun; Kim, Hyun Sook

    2017-05-01

    The matched filter (MF) and adaptive coherence estimator (ACE) show great effectiveness in hyperspectral target detection applications. Practical applications in which on-board processing is generally required demand real-time or near-real-time implementation of these detectors. However, a vast amount of hyperspectral data may make real-time or near-real-time implementation of the detection algorithms almost impossible. Band selection can be one of the solutions to this problem by reducing the number of spectral bands. We propose a new band selection method that prioritizes spectral bands based on their influence on the detection performance of the MF and ACE and discards the least influential bands. We validate the performance of our method using real hyperspectral images. We also demonstrate our technique on near-real-time detection tasks and show it to be a feasible approach to the tasks.

  2. A Versatile Multiple Target Detection System Based on DNA Nano-assembled Linear FRET Arrays.

    Science.gov (United States)

    Li, Yansheng; Du, Hongwu; Wang, Wenqian; Zhang, Peixun; Xu, Liping; Wen, Yongqiang; Zhang, Xueji

    2016-05-27

    DNA molecules have been utilized both as powerful synthetic building blocks to create nanoscale architectures and as inconstant programmable templates for assembly of biosensors. In this paper, a versatile, scalable and multiplex detection system is reported based on an extending fluorescent resonance energy transfer (FRET) cascades on a linear DNA assemblies. Seven combinations of three kinds of targets are successfully detected through the changes of fluorescence spectra because of the three-steps FRET or non-FRET continuity mechanisms. This nano-assembled FRET-based nanowire is extremely significant for the development of rapid, simple and sensitive detection system. The method used here could be extended to a general platform for multiplex detection through more-step FRET process.

  3. Joint sparsity based heterogeneous data-level fusion for target detection and estimation

    Science.gov (United States)

    Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe

    2017-05-01

    Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.

  4. Combining in vitro protein detection and in vivo antibody detection identifies potential vaccine targets against Staphylococcus aureus during osteomyelitis.

    Science.gov (United States)

    den Reijer, P Martijn; Sandker, Marjan; Snijders, Susan V; Tavakol, Mehri; Hendrickx, Antoni P A; van Wamel, Willem J B

    2017-02-01

    Currently, little is known about the in vivo human immune response against Staphylococcus aureus during a biofilm-associated infection, such as osteomyelitis, and how this relates to protein production in biofilms in vitro. Therefore, we characterized IgG responses in 10 patients with chronic osteomyelitis against 50 proteins of S. aureus, analyzed the presence of these proteins in biofilms of the infecting isolates on polystyrene (PS) and human bone in vitro, and explored the relation between in vivo and in vitro data. IgG levels against 15 different proteins were significantly increased in patients compared to healthy controls. Using a novel competitive Luminex-based assay, eight of these proteins [alpha toxin, Staphylococcus aureus formyl peptide receptor-like 1 inhibitor (FlipR), glucosaminidase, iron-responsive surface determinants A and H, the putative ABC transporter SACOL0688, staphylococcal complement inhibitor (SCIN), and serine-aspartate repeat-containing protein E (SdrE)] were also detected in a majority of the infecting isolates during biofilm formation in vitro. However, 4 other proteins were detected in only a minority of isolates in vitro while, vice versa, 7 proteins were detected in multiple isolates in vitro but not associated with significantly increased IgG levels in patients. Detection of proteins was largely confirmed using a transcriptomic approach. Our data provide further insights into potential therapeutic targets, such as for vaccination, to reduce S. aureus virulence and biofilm formation. At the same time, our data suggest that either in vitro or immunological in vivo data alone should be interpreted cautiously and that combined studies are necessary to identify potential targets.

  5. A novel algorithm based on wavelet transform for ship target detection in optical remote sensing images

    Science.gov (United States)

    Huang, Bo; Xu, Tingfa; Chen, Sining; Huang, Tingting

    2017-07-01

    The rapid development of the satellite observation technology provides a very rich source of data for sea reconnaissance and ships surveillance. In the face of such a vast sea remote sensing data, it is urgent need to realize the automatic ship detection in optical remote sensing images, but the optical remote sensing images are easily affected by meteorological conditions, such as clouds, waves, which results in larger false alarm; and the weak contrast between optical remote sensing image target and background is easy to cause missing alarm. In this paper, a novel algorithm based on wavelet transform for ship target detection in optical remote sensing images is proposed, which can effectively remove these noise and interference. The segmentation of sea and land background is first applied to the image preprocessing to achieve more accurate detection results, and then discrete wavelet transform is used to deal with the part of sea background. The results show that almost all of the offshore ships can be detected, and through the comparison of the results of four different wavelet basis functions, the accuracy of ship detection is further improved.

  6. A novel electrochemical method to detect cell surface carbohydrates and target cells.

    Science.gov (United States)

    Shao, Zhenyu; Li, Yun; Yang, Qianlu; Wang, Jing; Li, Genxi

    2010-12-01

    Glycosylation of cell surfaces is a critical factor in many biological processes; however, the lack of effective analytical tools for the detection of cell surface carbohydrates has been the bottleneck for probing into the processes. In this paper, a novel electrochemical method is presented for the analysis of cell surface carbohydrates, which can be also used to detect the target cells. Firstly, 5-hydroxy-3-hexanedithiol-1,4-naphthoquinone (JUG(thio)), the electrochemical reporter, and anti-selectin aptamer are successively modified onto the surface of a gold electrode. Different concentrations of intestinal human colon adenocarcinoma (LS180) cells are employed as the target cells for this study. Consequently, the specific carbohydrates on the surfaces of LS180 cells and anti-selectin aptamers will compete for combination with selectin in the system. As a result, the oxidation signal of JUG(thio) is changed and the detection of the cell surface carbohydrates can be achieved easily and sensitively. Furthermore, the proposed method can be used to specifically detect LS180 cells in a wide concentration range, from 10(3) to 10(7) cells/mL, with a good linear relationship and low detection limit, which might be promising for the diagnosis of cancer and some other diseases in the future.

  7. Fast and sensitive detection of indels induced by precise gene targeting

    DEFF Research Database (Denmark)

    Yang, Zhang; Steentoft, Catharina; Hauge, Camilla

    2015-01-01

    The nuclease-based gene editing tools are rapidly transforming capabilities for altering the genome of cells and organisms with great precision and in high throughput studies. A major limitation in application of precise gene editing lies in lack of sensitive and fast methods to detect...... and characterize the induced DNA changes. Precise gene editing induces double-stranded DNA breaks that are repaired by error-prone non-homologous end joining leading to introduction of insertions and deletions (indels) at the target site. These indels are often small and difficult and laborious to detect...

  8. TRUSTWORTHY OPTIMIZED CLUSTERING BASED TARGET DETECTION AND TRACKING FOR WIRELESS SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    C. Jehan

    2016-06-01

    Full Text Available In this paper, an efficient approach is proposed to address the problem of target tracking in wireless sensor network (WSN. The problem being tackled here uses adaptive dynamic clustering scheme for tracking the target. It is a specific problem in object tracking. The proposed adaptive dynamic clustering target tracking scheme uses three steps for target tracking. The first step deals with the identification of clusters and cluster heads using OGSAFCM. Here, kernel fuzzy c-means (KFCM and gravitational search algorithm (GSA are combined to create clusters. At first, oppositional gravitational search algorithm (OGSA is used to optimize the initial clustering center and then the KFCM algorithm is availed to guide the classification and the cluster formation process. In the OGSA, the concept of the opposition based population initialization in the basic GSA to improve the convergence profile. The identified clusters are changed dynamically. The second step deals with the data transmission to the cluster heads. The third step deals with the transmission of aggregated data to the base station as well as the detection of target. From the experimental results, the proposed scheme efficiently and efficiently identifies the target. As a result the tracking error is minimized.

  9. Real-Time Target Detection Architecture Based on Reduced Complexity Hyperspectral Processing

    Directory of Open Access Journals (Sweden)

    We-Duke Cho

    2008-06-01

    Full Text Available This paper presents a real-time target detection architecture for hyperspectral image processing. The architecture is based on a reduced complexity algorithm for high-throughput applications.We propose an efficient pipelined processing element architecture and a scalable multiple-processing element architecture by exploiting data partitioning. We present a processing unit modeling based on the data reduction algorithm in hyperspectral image processing and propose computing structure, that is, to optimize memory usage and eliminates memory bottleneck. We investigate the interconnection topology for the multipleprocessing element architecture to improve the speed. The proposed architecture is designed and implemented in FPGA to illustrate the relationship between hardware complexity and execution throughput of hyperspectral image processing for target detection.

  10. Detection-Discrimination Method for Multiple Repeater False Targets Based on Radar Polarization Echoes

    Directory of Open Access Journals (Sweden)

    Z. W. ZONG

    2014-04-01

    Full Text Available Multiple repeat false targets (RFTs, created by the digital radio frequency memory (DRFM system of jammer, are widely used in practical to effectively exhaust the limited tracking and discrimination resource of defence radar. In this paper, common characteristic of radar polarization echoes of multiple RFTs is used for target recognition. Based on the echoes from two receiving polarization channels, the instantaneous polarization radio (IPR is defined and its variance is derived by employing Taylor series expansion. A detection-discrimination method is designed based on probability grids. By using the data from microwave anechoic chamber, the detection threshold of the method is confirmed. Theoretical analysis and simulations indicate that the method is valid and feasible. Furthermore, the estimation performance of IPRs of RFTs due to the influence of signal noise ratio (SNR is also covered.

  11. Target detection in hyperspectral images using projection pursuit with interference rejection

    Science.gov (United States)

    Ifarraguerri, Agustin I.; Ren, Hsuan; Chang, Chein-I.

    1998-12-01

    We present a method for the automatic, unsupervised detection of spectrally distinct targets from the background using hyperspectral imaging. The approach is based on the concepts of projection pursuit (PP) and unsupervised orthogonal subspace projection (UOSP). It has the advantage of not requiring any prior knowledge of the scene or the objects' spectral signatures. All information is obtained from the data. First, PP is used to both reduce the data dimensionality and locate potential targets. Then, UOSP suppresses the signatures from undesired objects or interferers that cause false detections when a spectral filter is applied. The result is a set of gray scale images where objects belonging to the same spectral class are enhanced while the background and other undesired objects are suppressed. This method is demonstrated using data from the Hyperspectral Digital Imagery Collection Experiment (HYDICE).

  12. Shilling Attacks Detection in Recommender Systems Based on Target Item Analysis.

    Science.gov (United States)

    Zhou, Wei; Wen, Junhao; Koh, Yun Sing; Xiong, Qingyu; Gao, Min; Dobbie, Gillian; Alam, Shafiq

    2015-01-01

    Recommender systems are highly vulnerable to shilling attacks, both by individuals and groups. Attackers who introduce biased ratings in order to affect recommendations, have been shown to negatively affect collaborative filtering (CF) algorithms. Previous research focuses only on the differences between genuine profiles and attack profiles, ignoring the group characteristics in attack profiles. In this paper, we study the use of statistical metrics to detect rating patterns of attackers and group characteristics in attack profiles. Another question is that most existing detecting methods are model specific. Two metrics, Rating Deviation from Mean Agreement (RDMA) and Degree of Similarity with Top Neighbors (DegSim), are used for analyzing rating patterns between malicious profiles and genuine profiles in attack models. Building upon this, we also propose and evaluate a detection structure called RD-TIA for detecting shilling attacks in recommender systems using a statistical approach. In order to detect more complicated attack models, we propose a novel metric called DegSim' based on DegSim. The experimental results show that our detection model based on target item analysis is an effective approach for detecting shilling attacks.

  13. Radon-Fractional Fourier Transform and Its Application to Radar Maneuvering Target Detection (Preprint)

    Science.gov (United States)

    2014-10-09

    Radon -Fractional Fourier Transform and Its Application to Radar Maneuvering Target Detection Xiaolong Chen*, Fuqing Cai, Yu Cong, Jian Guan...unit (ARU) and Doppler frequency migration (DFM) effects. In this paper, a novel transform called the Radon -fractional Fourier transform (RFRFT) is...are carried out and the performances of different methods including MTD, FRFT, and the Radon -Fourier transform (RFT) are compared, which demonstrate

  14. Targeted delivery of gold nanoparticle contrast agents for reporting gene detection by magnetic resonance imaging.

    Science.gov (United States)

    Vistain, Luke F; Rotz, Matthew W; Rathore, Richa; Preslar, Adam T; Meade, Thomas J

    2016-01-04

    Detection of protein expression by MRI requires a high payload of Gd(III) per protein binding event. Presented here is a targeted AuDNA nanoparticle capable of delivering several hundred Gd(III) chelates to the HaloTag reporter protein. Incubating this particle with HaloTag-expressing cells produced a 9.4 contrast-to-noise ratio compared to non-expressing cells.

  15. Moving target detection in flash mode against stroboscopic mode by active range-gated laser imaging

    Science.gov (United States)

    Zhang, Xuanyu; Wang, Xinwei; Sun, Liang; Fan, Songtao; Lei, Pingshun; Zhou, Yan; Liu, Yuliang

    2018-01-01

    Moving target detection is important for the application of target tracking and remote surveillance in active range-gated laser imaging. This technique has two operation modes based on the difference of the number of pulses per frame: stroboscopic mode with the accumulation of multiple laser pulses per frame and flash mode with a single shot of laser pulse per frame. In this paper, we have established a range-gated laser imaging system. In the system, two types of lasers with different frequency were chosen for the two modes. Electric fan and horizontal sliding track were selected as the moving targets to compare the moving blurring between two modes. Consequently, the system working in flash mode shows more excellent performance in motion blurring against stroboscopic mode. Furthermore, based on experiments and theoretical analysis, we presented the higher signal-to-noise ratio of image acquired by stroboscopic mode than flash mode in indoor and underwater environment.

  16. Application of time-reversal-based processing techniques to enhance detection of GPR targets

    CERN Document Server

    Santos, Vinicius R N

    2016-01-01

    In this paper we analyze the performance of time-reversal (TR) techniques in conjunction with various Ground Penetrating Radar (GPR) pre-processing methods aimed at improving detection of subsurface targets. TR techniques were first developed for ultrasound applications and, by exploiting the invariance of the wave equation under time reversal, can yield features such as superresolution and statistical stability. The TR method was examined here using both synthetic and actual GPR field data under four different pre-processing strategies on the raw data, namely: mean background removal, eigenvalue background removal, a sliding-window space-frequency technique, and a noise-robust spatial differentiator along the scan direction. Depending on the acquisition mode, it was possible to determine with good precision the position and depth of the studied targets as well as, in some cases, to differentiate the targets from nearby clutter such as localized geological anomalies. The proposed methodology has the potential...

  17. Survey and Rapid detection of Bordetella pertussis in clinical samples targeting the BP485 in China

    Directory of Open Access Journals (Sweden)

    Wei eLiu

    2015-03-01

    Full Text Available Bordetella pertussis is an important human respiratory pathogen. Here, we describe a loop-mediated isothermal amplification (LAMP method for the rapid detection of B. pertussis in clinical samples based on a visual test. The LAMP assay detected the BP485 target sequence within 60 min with a detection limit of 1.3 pg/µl, a 10-fold increase in sensitivity compared with conventional PCR. All 31 non-pertussis respiratory pathogens tested were negative for LAMP detection, indicating the high specificity of the primers for B. pertussis. To evaluate the application of the LAMP assay to clinical diagnosis, of 105 sputum and nasopharyngeal samples collected from the patients with suspected respiratory infections in China, a total of 12 Bordetella pertussis isolates were identified from 33 positive samples detected by LAMP-based surveillance targeting BP485. Strikingly, a 4.5 months old baby and her mother were found to be infected with B. pertussis at the same time. All isolates belonged to different B. pertussis multilocus sequence typing (MLST groups with different alleles of the virulence-related genes including 4 alleles of ptxA, 6 of prn, 4 of tcfA, 2 of fim2 and 3 of fim3. The diversity of B. pertussis carrying toxin genes in clinical strains indicates a rapid and continuing evolution of B. pertussis. This combined with its high prevalence will make it difficult to control. In conclusion, we have developed a visual detection LAMP assay, which could be a useful tool for rapid B. pertussis detection, especially in situations where resources are poor and in point-of-care tests.

  18. Targeted prostate biopsy: value of multiparametric magnetic resonance imaging in detection of localized cancer

    Science.gov (United States)

    Le, Jesse D; Huang, Jiaoti; Marks, Leonard S

    2014-01-01

    Prostate cancer is the second most common cancer in men, with 1.1 million new cases worldwide reported by the World Health Organization in one recent year. Transrectal ultrasound (TRUS)-guided biopsy has been used for the diagnosis of prostate cancer for over 2 decades, but the technique is usually blind to cancer location. Moreover, the false negative rate of TRUS biopsy has been reported to be as high as 47%. Multiparametric magnetic resonance imaging (mp-MRI) includes T1- and T2-weighted imaging as well as dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI). mp-MRI is a major advance in the imaging of prostate cancer, enabling targeted biopsy of suspicious lesions. Evolving targeted biopsy techniques—including direct in-bore biopsy, cognitive fusion and software-based MRI-ultrasound (MRI-US) fusion—have led to a several-fold improvement in cancer detection compared to the earlier method. Importantly, the detection of clinically significant cancers has been greatly facilitated by targeting, compared to systematic biopsy alone. Targeted biopsy via MRI-US fusion may dramatically alter the way prostate cancer is diagnosed and managed. PMID:24589455

  19. A Canopy Density Model for Planar Orchard Target Detection Based on Ultrasonic Sensors.

    Science.gov (United States)

    Li, Hanzhe; Zhai, Changyuan; Weckler, Paul; Wang, Ning; Yang, Shuo; Zhang, Bo

    2016-12-24

    Orchard target-oriented variable rate spraying is an effective method to reduce pesticide drift and excessive residues. To accomplish this task, the orchard targets' characteristic information is needed to control liquid flow rate and airflow rate. One of the most important characteristics is the canopy density. In order to establish the canopy density model for a planar orchard target which is indispensable for canopy density calculation, a target density detection testing system was developed based on an ultrasonic sensor. A time-domain energy analysis method was employed to analyze the ultrasonic signal. Orthogonal regression central composite experiments were designed and conducted using man-made canopies of known density with three or four layers of leaves. Two model equations were obtained, of which the model for the canopies with four layers was found to be the most reliable. A verification test was conducted with different layers at the same density values and detecting distances. The test results showed that the relative errors of model density values and actual values of five, four, three and two layers of leaves were acceptable, while the maximum relative errors were 17.68%, 25.64%, 21.33% and 29.92%, respectively. It also suggested the model equation with four layers had a good applicability with different layers which increased with adjacent layers.

  20. Study of time-reversal-based signal processing applied to polarimetric GPR detection of elongated targets

    Science.gov (United States)

    Santos, Vinicius Rafael N.; Teixeira, Fernando L.

    2017-04-01

    Ground penetrating radar (GPR) is a useful sensing modality for mapping and identification of underground infrastructure networks, such as metal and concrete pipes (gas, water or sewer), phone conduits or cables, and other buried objects. Due to the polarization-dependent response of typical targets, it is of interest to investigate the optimum antenna arrangement and/or combination of arrangements that maximize the detection and classification capabilities of polarimetric GPR imaging systems. Here, we provide a preliminary study of time-reversal-based techniques applied to target detection by GPR utilizing different relative orientations of linear-polarized antenna elements (with respect to each other, as well as to the targets). We modeled three different pipe materials (metallic, plastic and concrete) and GPR systems operating at center frequencies of 100 MHz and 200 MHz. Full-wave numerical simulations are adopted to account for mutual coupling between targets. This type of assessment study may contribute to the improvement of GPR data interpretation of infrastructure networks in urban area surveys and in other engineering studies.

  1. Analysis of the Chirplet Transform-Based Algorithm for Radar Detection of Accelerated Targets

    Science.gov (United States)

    Galushko, V. G.; Vavriv, D. M.

    2017-06-01

    Purpose: Efficiency analysis of an optimal algorithm of chirp signal processing based on the chirplet transform as applied to detection of radar targets in uniformly accelerated motion. Design/methodology/approach: Standard methods of the optimal filtration theory are used to investigate the ambiguity function of chirp signals. Findings: An analytical expression has been derived for the ambiguity function of chirp signals that is analyzed with respect to detection of radar targets moving at a constant acceleration. Sidelobe level and characteristic width of the ambiguity function with respect to the coordinates frequency and rate of its change have been estimated. The gain in the signal-to-noise ratio has been assessed that is provided by the algorithm under consideration as compared with application of the standard Fourier transform to detection of chirp signals against a “white” noise background. It is shown that already with a comparatively small (number of processing channels (elementary filters with respect to the frequency change rate) the gain in the signal-tonoise ratio exceeds 10 dB. A block diagram of implementation of the algorithm under consideration is suggested on the basis of a multichannel weighted Fourier transform. Recommendations as for selection of the detection algorithm parameters have been developed. Conclusions: The obtained results testify to efficiency of application of the algorithm under consideration to detection of radar targets moving at a constant acceleration. Nevertheless, it seems expedient to perform computer simulations of its operability with account for the noise impact along with trial measurements in real conditions.

  2. Adding temporally localized noise can enhance the contribution of target knowledge on contrast detection.

    Science.gov (United States)

    Silvestre, Daphné; Cavanagh, Patrick; Arleo, Angelo; Allard, Rémy

    2017-02-01

    External noise paradigms are widely used to characterize sensitivity by comparing the effect of a variable on contrast threshold when it is limited by internal versus external noise. A basic assumption of external noise paradigms is that the processing properties are the same in low and high noise. However, recent studies (e.g., Allard & Cavanagh, 2011; Allard & Faubert, 2014b) suggest that this assumption could be violated when using spatiotemporally localized noise (i.e., appearing simultaneously and at the same location as the target) but not when using spatiotemporally extended noise (i.e., continuously displayed, full-screen, dynamic noise). These previous findings may have been specific to the crowding and 0D noise paradigms that were used, so the purpose of the current study is to test if this violation of noise-invariant processing also occurs in a standard contrast detection task in white noise. The rationale of the current study is that local external noise triggers the use of recognition rather than detection and that a recognition process should be more affected by uncertainty about the shape of the target than one involving detection. To investigate the contribution of target knowledge on contrast detection, the effect of orientation uncertainty was evaluated for a contrast detection task in the absence of noise and in the presence of spatiotemporally localized or extended noise. A larger orientation uncertainty effect was observed with temporally localized noise than with temporally extended noise or with no external noise, indicating a change in the nature of the processing for temporally localized noise. We conclude that the use of temporally localized noise in external noise paradigms risks triggering a shift in process, invalidating the noise-invariant processing required for the paradigm. If, instead, temporally extended external noise is used to match the properties of internal noise, no such processing change occurs.

  3. Detection of genetically modified organisms (GMOs using isothermal amplification of target DNA sequences

    Directory of Open Access Journals (Sweden)

    La Mura Maurizio

    2009-02-01

    Full Text Available Abstract Background The most common method of GMO detection is based upon the amplification of GMO-specific DNA amplicons using the polymerase chain reaction (PCR. Here we have applied the loop-mediated isothermal amplification (LAMP method to amplify GMO-related DNA sequences, 'internal' commonly-used motifs for controlling transgene expression and event-specific (plant-transgene junctions. Results We have tested the specificity and sensitivity of the technique for use in GMO studies. Results show that detection of 0.01% GMO in equivalent background DNA was possible and dilutions of template suggest that detection from single copies of the template may be possible using LAMP. Conclusion This work shows that GMO detection can be carried out using LAMP for routine screening as well as for specific events detection. Moreover, the sensitivity and ability to amplify targets, even with a high background of DNA, here demonstrated, highlights the advantages of this isothermal amplification when applied for GMO detection.

  4. CNVkit: Genome-Wide Copy Number Detection and Visualization from Targeted DNA Sequencing.

    Directory of Open Access Journals (Sweden)

    Eric Talevich

    2016-04-01

    Full Text Available Germline copy number variants (CNVs and somatic copy number alterations (SCNAs are of significant importance in syndromic conditions and cancer. Massively parallel sequencing is increasingly used to infer copy number information from variations in the read depth in sequencing data. However, this approach has limitations in the case of targeted re-sequencing, which leaves gaps in coverage between the regions chosen for enrichment and introduces biases related to the efficiency of target capture and library preparation. We present a method for copy number detection, implemented in the software package CNVkit, that uses both the targeted reads and the nonspecifically captured off-target reads to infer copy number evenly across the genome. This combination achieves both exon-level resolution in targeted regions and sufficient resolution in the larger intronic and intergenic regions to identify copy number changes. In particular, we successfully inferred copy number at equivalent to 100-kilobase resolution genome-wide from a platform targeting as few as 293 genes. After normalizing read counts to a pooled reference, we evaluated and corrected for three sources of bias that explain most of the extraneous variability in the sequencing read depth: GC content, target footprint size and spacing, and repetitive sequences. We compared the performance of CNVkit to copy number changes identified by array comparative genomic hybridization. We packaged the components of CNVkit so that it is straightforward to use and provides visualizations, detailed reporting of significant features, and export options for integration into existing analysis pipelines. CNVkit is freely available from https://github.com/etal/cnvkit.

  5. Baseline processing pipeline for fast automatic target detection and recognition in airborne 3D ladar imagery

    Science.gov (United States)

    Roy, Simon; Maheux, Jean

    2011-06-01

    It has been proven that 3D ladar imagery has a strong potential for automatic target detection (ATD) and automatic target recognition (ATR); ladars enhance target information, which may then be exploited to yield higher recognition rates and lower false alarms. Although numerous techniques have been proposed for both 3D ATD and 3D ATR, no single approach has proven capable of systematically outperforming all other techniques for every possible scenario. In this context, this paper describes a set of fast 3D ATD/ATR algorithms designed to process cooperative targets in airborne 3D ladar imagery. This algorithmic chain consists of four modules: detection, segmentation, classification and recognition. In each module, fast algorithms were implemented, some of which stem from open literature while others were designed in-house. The purpose of this algorithmic chain is to provide a baseline approach for efficient processing of simple scenarios. The ultimate goal of this work is to characterize and compare algorithms with respect to increasingly complex scenarios, in hopes of progressing towards an adaptive processing pipeline for context-driven 3D ATD/ATR. In this paper, the four modules of the baseline processing pipeline are first described. Preliminary test results obtained with real airborne ladar imagery are then presented, in which fast and accurate 3D ATD/ATR is performed with a library of 20 scanned vehicles. Finally, a demonstration is presented to illustrate how this baseline approach may be expanded to tackle more complex scenarios, such as non-cooperative targets concealed under vegetation.

  6. A Canopy Density Model for Planar Orchard Target Detection Based on Ultrasonic Sensors

    Directory of Open Access Journals (Sweden)

    Hanzhe Li

    2016-12-01

    Full Text Available Orchard target-oriented variable rate spraying is an effective method to reduce pesticide drift and excessive residues. To accomplish this task, the orchard targets’ characteristic information is needed to control liquid flow rate and airflow rate. One of the most important characteristics is the canopy density. In order to establish the canopy density model for a planar orchard target which is indispensable for canopy density calculation, a target density detection testing system was developed based on an ultrasonic sensor. A time-domain energy analysis method was employed to analyze the ultrasonic signal. Orthogonal regression central composite experiments were designed and conducted using man-made canopies of known density with three or four layers of leaves. Two model equations were obtained, of which the model for the canopies with four layers was found to be the most reliable. A verification test was conducted with different layers at the same density values and detecting distances. The test results showed that the relative errors of model density values and actual values of five, four, three and two layers of leaves were acceptable, while the maximum relative errors were 17.68%, 25.64%, 21.33% and 29.92%, respectively. It also suggested the model equation with four layers had a good applicability with different layers which increased with adjacent layers.

  7. Multi-Chromatic Analysis of SAR Images for Coherent Target Detection

    Directory of Open Access Journals (Sweden)

    Fabio Bovenga

    2014-09-01

    Full Text Available This work investigates the possibility of performing target analysis through the Multi-Chromatic Analysis (MCA, a technique that basically explores the information content of sub-band images obtained by processing portions of the range spectrum of a synthetic aperture radar (SAR image. According to the behavior of the SAR signal at the different sub-bands, MCA allows target classification. Two strategies have been experimented by processing TerraSAR-X images acquired over the Venice Lagoon, Italy: one exploiting the phase of interferometric sub-band pairs, the other using the spectral coherence derived by computing the coherence between sub-band images of a single SAR acquisition. The first approach introduces the concept of frequency-persistent scatterers (FPS, which is complementary to that of the time-persistent scatterers (PS. FPS and PS populations have been derived and analyzed to evaluate the respective characteristics and the physical nature of the targets. Spectral coherence analysis has been applied to vessel detection, according to the property that, in presence of a random distribution of surface scatterers, as for open sea surfaces, spectral coherence is expected to be proportional to sub-band intersection, while in presence of manmade structures it is preserved anyhow. First results show that spectral coherence is well preserved even for very small vessels, and can be used as a complementary information channel to constrain vessel detection in addition to classical Constant False Alarm Rate techniques based on the sole intensity channel.

  8. Rapid amplification/detection of nucleic acid targets utilizing a HDA/thin film biosensor.

    Science.gov (United States)

    Jenison, Robert; Jaeckel, Heidi; Klonoski, Joshua; Latorra, David; Wiens, Jacinta

    2014-08-07

    Thin film biosensors exploit a flat, optically coated silicon-based surface whereupon formation of nucleic acid hybrids are enzymatically transduced in a molecular thin film that can be detected by the unaided human eye under white light. While the limit of sensitivity for detection of nucleic acid targets is at sub-attomole levels (60 000 copies) many clinical specimens containing bacterial pathogens have much lower levels of analyte present. Herein, we describe a platform, termed HDA/thin film biosensor, which performs helicase-dependant nucleic acid amplification on a thin film biosensor surface to improve the limit of sensitivity to 10 copies of the mecA gene present in methicillin-resistant strains of Staphylococcus. As double-stranded DNA is unwound by helicase it was either bound by solution-phase DNA primers to be copied by DNA polymerase or hybridized to surface immobilized probe on the thin film biosensor surface to be detected. Herein, we show that amplification reactions on the thin film biosensor are equivalent to in standard thin wall tubes, with detection at the limit of sensitivity of the assay occurring after 30 minutes of incubation time. Further we validate the approach by detecting the presence of the mecA gene in methicillin-resistant Staphylococcus aureus (MRSA) from positive blood culture aliquots with high specificity (signal/noise ratio of 105).

  9. Improved detection specificity for plasma proteins by targeting cysteine-containing peptides with photo-SRM.

    Science.gov (United States)

    Enjalbert, Quentin; Girod, Marion; Simon, Romain; Jeudy, Jérémy; Chirot, Fabien; Salvador, Arnaud; Antoine, Rodolphe; Dugourd, Philippe; Lemoine, Jérôme

    2013-03-01

    Targeted mass spectrometry using selected reaction monitoring (SRM) has emerged as an alternative to immunoassays for protein quantification owing to faster development time and higher multiplexing capability. However, the SRM strategy is faced with the high complexity of peptide mixtures after trypsin digestion of whole plasma or the cellular proteome that most of the time causes contamination, irremediably, by interfering compounds in the transition channels monitored. This problem becomes increasingly acute when the targeted protein is present at a low concentration. In this work, the merit of laser-induced photo-dissociation in the visible region at 473 nm implemented in an hybrid quadrupole linear ion-trap mass spectrometer (photo-SRM) was evaluated for detection specificity of cysteine-containing peptides in a group of plasma proteins after tagging with a dabcyl chromophore. Compared with conventional SRM, photo-SRM chromatograms have improved detection specificity for most of peptides monitored. Comparison of the signals obtained for the best proteotypic peptides in SRM mode and those recorded by photo-SRM of cysteine-containing peptides for the same proteins reveals either increased (up to 10-fold) or similar signal to photo-SRM detection. Finally, photo-SRM has extended response linearity across a calibration plot obtained by diluting human plasma in rat plasma, down to the lowest concentrations. Hence, photo-SRM may advantageously complement conventional SRM in assay of proteins in complex biological matrices.

  10. Novel Signal-Enhancing Approaches for Optical Detection of Nucleic Acids—Going beyond Target Amplification

    Directory of Open Access Journals (Sweden)

    Laura Miotke

    2015-09-01

    Full Text Available Detection of low-abundance nucleic acids is a challenging task, which over the last two decades has been solved using enzymatic target amplification. Enzymatic synthesis enhances the signal so that diverse, scientifically and clinically relevant molecules can be identified and studied, including cancer DNA, viral nucleic acids, and regulatory RNAs. However, using enzymes increases the detection time and cost, not to mention the high risk of mistakes with amplification and data alignment. These limitations have stimulated a growing interest in enzyme-free methods within researchers and industry. In this review we discuss recent advances in signal-enhancing approaches aimed at nucleic acid diagnostics that do not require target amplification. Regardless of enzyme usage, signal enhancement is crucial for the reliable detection of nucleic acids at low concentrations. We pay special attention to novel nanomaterials, fluorescence microscopy, and technical advances in detectors for optical assessment. We summarize sensitivity parameters of the currently available assays and devices which makes this review relevant to the broad spectrum of researchers working in fields from biophysics, to engineering, to synthetic biology and bioorganic chemistry.

  11. Detection of Target Biomolecules by Magnetic Reporting Using Rod-Like Nanosensors

    Science.gov (United States)

    Guertin, R. P.; Goldberg, E.; Harrah, T. P.; Sonkusale, S.; Park, K.; Sun, S.; Oh, J. I.; Naughton, M.

    2008-03-01

    We describe the ongoing development of a device to assay a variety of cellular, viral and molecular targets by measuring the increase of the Brownian relaxation time, τ, in solution of magnetically-tagged nanoscale detectors. The shift shows as a frequency reduction of the peak of the complex magnetic susceptibility, χ(φ)''. Measurements of χ(φ)'' with 12 nm monodisperse nanoparticles of CoFe2O4 coated with polyethelyne glycol reveal spectra with the narrowest lines yet reported. Thin avidin coating of these particles reveals small shifts in χ(φ)''. Bacteriophage T4 tail fibers, engineered to specific lengths (30-150 nm), were employed as the platform for magnetic nanoparticle attachment and at the other end for an inserted target peptide epitope. Attachment of the nanoparticles to bacteriophage T4 tail fibers was successful, though no detectable shifts in χ(φ)'' were detected due to weak attachment. The advantages associated with non-spherical geometry detectors will be discussed, as will preliminary measurements with rare earth oxide magnetic nanoparticles. Progress on miniaturization and low power requirements of the electronic detection system will be reported. Supported by NERCE/BEID (NIAID).

  12. High Speed Dim Air Target Detection Using Airborne Radar under Clutter and Jamming Effects

    Directory of Open Access Journals (Sweden)

    A. E. Almslmany

    2015-06-01

    Full Text Available The challenging potential problems associated with using airborne radar in detection of high Speed Maneuvering Dim Target (HSMDT are the highly noise, jamming and clutter effects. The problem is not only how to remove clutter and jamming as well as the range migration and Doppler ambiguity estimation problems due to high relative speed between the targets and airborne radar. Some of the recently published works ignored the range migration problems, while the others ignored the Doppler ambiguity estimation. In this paper a new hybrid technique using Optimum Space Time Adaptive Processing (OSTAP, Second Order Keystone Transform (SOKT, and the Improved Fractional Radon Transform (IFrRT was proposed. The OSTAP was applied as anti-jamming and clutter rejection method, the SOKT corrects the range curvature and part of the range walk, then the IFrRT estimates the target’ radial acceleration and corrects the residual range walk. The simulation demonstrates the validity and effectiveness of the proposed technique, and its advantages over the previous researches by comparing its probability of detection with the traditional methods. The new approach increases the probability of detection, and also overcomes the limitation of Doppler frequency ambiguity.

  13. Detection of Balamuthia mandrillaris DNA by real-time PCR targeting the RNase P gene

    Directory of Open Access Journals (Sweden)

    Lewin Astrid

    2008-12-01

    Full Text Available Abstract Background The free-living amoeba Balamuthia mandrillaris may cause fatal encephalitis both in immunocompromised and in – apparently – immunocompetent humans and other mammalian species. Rapid, specific, sensitive, and reliable detection requiring little pathogen-specific expertise is an absolute prerequisite for a successful therapy and a welcome tool for both experimental and epidemiological research. Results A real-time polymerase chain reaction assay using TaqMan® probes (real-time PCR was established specifically targeting the RNase P gene of B. mandrillaris amoebae. The assay detected at least 2 (down to 0.5 genomes of B. mandrillaris grown in axenic culture. It did not react with DNA from closely related Acanthamoeba (3 species, nor with DNA from Toxoplasma gondii, Leishmania major, Pneumocystis murina, Mycobacterium bovis (BCG, human brain, various mouse organs, or from human and murine cell lines. The assay efficiently detected B. mandrillaris DNA in spiked cell cultures, spiked murine organ homogenates, B. mandrillaris-infected mice, and CNS tissue-DNA preparations from 2 patients with proven cerebral balamuthiasis. This novel primer set was successfully combined with a published set that targets the B. mandrillaris 18S rRNA gene in a duplex real-time PCR assay to ensure maximum specificity and as a precaution against false negative results. Conclusion A real-time PCR assay for B. mandrillaris amoebae is presented, that is highly specific, sensitive, and reliable and thus suited both for diagnosis and for research.

  14. Staphylococcus aureus methicillin resistance detected by HPLC-MS/MS targeted metabolic profiling.

    Science.gov (United States)

    Schelli, Katie; Rutowski, Joshua; Roubidoux, Julia; Zhu, Jiangjiang

    2017-03-15

    Recently, novel bioanalytical methods, such as NMR and mass spectrometry based metabolomics approaches, have started to show promise in providing rapid, sensitive and reproducible detection of Staphylococcus aureus antibiotic resistance. Here we performed a proof-of-concept study focused on the application of HPLC-MS/MS based targeted metabolic profiling for detecting and monitoring the bacterial metabolic profile changes in response to sub-lethal levels of methicillin exposure. One hundred seventy-seven targeted metabolites from over 20 metabolic pathways were specifically screened and one hundred and thirty metabolites from in vitro bacterial tests were confidently detected from both methicillin susceptible and methicillin resistant Staphylococcus aureus (MSSA and MRSA, respectively). The metabolic profiles can be used to distinguish the isogenic pairs of MSSA strains from MRSA strains, without or with sub-lethal levels of methicillin exposure. In addition, better separation between MSSA and MRSA strains can be achieved in the latter case using principal component analysis (PCA). Metabolite data from isogenic pairs of MSSA and MRSA strains were further compared without and with sub-lethal levels of methicillin exposure, with metabolic pathway analyses additionally performed. Both analyses suggested that the metabolic activities of MSSA strains were more susceptible to the perturbation of the sub-lethal levels of methicillin exposure compared to the MRSA strains. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. A Joint-optimized Real-time Target Detection Algorithm for Passive Radar

    Directory of Open Access Journals (Sweden)

    Zhao Yong-ke

    2015-01-01

    Full Text Available Passive radar exploits an external illuminator signal to detect targets. It has the advantages of silence, anti-interference, and counter-stealth ability. In most cases, direct and multipath clutters should be suppressed first. Then coherent detection can be made by performing a cross-ambiguity function of the remaining target echoes and the reference signal. However, under a wide-band signal, a long-integration time, or multi-beam circumstances, a large number of computations and amount of memory is required for normal processing. This paper expresses the mathematical relationships of clutter suppression algorithms based on the Minimum Mean Square Error (MMSE principle and coherent detection algorithms based on the cross-ambiguity function. Herein, a joint-optimize and processing method is presented. This method reduces the number of computations and amount of memory required, is easy to implement on GPU devices such as CUDA, and will be useful for engineering applications. Its high-efficiency and real-time properties are validated in the experimental results.

  16. Target-responsive DNA hydrogel mediated "stop-flow" microfluidic paper-based analytic device for rapid, portable and visual detection of multiple targets.

    Science.gov (United States)

    Wei, Xiaofeng; Tian, Tian; Jia, Shasha; Zhu, Zhi; Ma, Yanli; Sun, Jianjun; Lin, Zhenyu; Yang, Chaoyong James

    2015-04-21

    A versatile point-of-care assay platform was developed for simultaneous detection of multiple targets based on a microfluidic paper-based analytic device (μPAD) using a target-responsive hydrogel to mediate fluidic flow and signal readout. An aptamer-cross-linked hydrogel was used as a target-responsive flow regulator in the μPAD. In the absence of a target, the hydrogel is formed in the flow channel, stopping the flow in the μPAD and preventing the colored indicator from traveling to the final observation spot, thus yielding a "signal off" readout. In contrast, in the presence of a target, no hydrogel is formed because of the preferential interaction of target and aptamer. This allows free fluidic flow in the μPAD, carrying the indicator to the observation spot and producing a "signal on" readout. The device is inexpensive to fabricate, easy to use, and disposable after detection. Testing results can be obtained within 6 min by the naked eye via a simple loading operation without the need for any auxiliary equipment. Multiple targets, including cocaine, adenosine, and Pb(2+), can be detected simultaneously, even in complex biological matrices such as urine. The reported method offers simple, low cost, rapid, user-friendly, point-of-care testing, which will be useful in many applications.

  17. Research on the algorithm of infrared target detection based on the frame difference and background subtraction method

    Science.gov (United States)

    Liu, Yun; Zhao, Yuejin; Liu, Ming; Dong, Liquan; Hui, Mei; Liu, Xiaohua; Wu, Yijian

    2015-09-01

    As an important branch of infrared imaging technology, infrared target tracking and detection has a very important scientific value and a wide range of applications in both military and civilian areas. For the infrared image which is characterized by low SNR and serious disturbance of background noise, an innovative and effective target detection algorithm is proposed in this paper, according to the correlation of moving target frame-to-frame and the irrelevance of noise in sequential images based on OpenCV. Firstly, since the temporal differencing and background subtraction are very complementary, we use a combined detection method of frame difference and background subtraction which is based on adaptive background updating. Results indicate that it is simple and can extract the foreground moving target from the video sequence stably. For the background updating mechanism continuously updating each pixel, we can detect the infrared moving target more accurately. It paves the way for eventually realizing real-time infrared target detection and tracking, when transplanting the algorithms on OpenCV to the DSP platform. Afterwards, we use the optimal thresholding arithmetic to segment image. It transforms the gray images to black-white images in order to provide a better condition for the image sequences detection. Finally, according to the relevance of moving objects between different frames and mathematical morphology processing, we can eliminate noise, decrease the area, and smooth region boundaries. Experimental results proves that our algorithm precisely achieve the purpose of rapid detection of small infrared target.

  18. Planar optical waveguide based sandwich assay sensors and processes for the detection of biological targets including early detection of cancers

    Science.gov (United States)

    Martinez, Jennifer S [Santa Fe, NM; Swanson, Basil I [Los Alamos, NM; Shively, John E [Arcadia, CA; Li, Lin [Monrovia, CA

    2009-06-02

    An assay element is described including recognition ligands adapted for binding to carcinoembryonic antigen (CEA) bound to a film on a single mode planar optical waveguide, the film from the group of a membrane, a polymerized bilayer membrane, and a self-assembled monolayer containing polyethylene glycol or polypropylene glycol groups therein and an assay process for detecting the presence of CEA is described including injecting a possible CEA-containing sample into a sensor cell including the assay element, maintaining the sample within the sensor cell for time sufficient for binding to occur between CEA present within the sample and the recognition ligands, injecting a solution including a reporter ligand into the sensor cell; and, interrogating the sample within the sensor cell with excitation light from the waveguide, the excitation light provided by an evanescent field of the single mode penetrating into the biological target-containing sample to a distance of less than about 200 nanometers from the waveguide thereby exciting any bound reporter ligand within a distance of less than about 200 nanometers from the waveguide and resulting in a detectable signal.

  19. Targeted histology sampling from atypical small acinar proliferation area detected by repeat transrectal prostate biopsy

    Directory of Open Access Journals (Sweden)

    A. V. Karman

    2017-01-01

    Full Text Available Оbjective: to define the approach to the management of patients with the detected ASAP area.Materials and methods. In the time period from 2012 through 2015, 494 patients with previously negative biopsy and remaining suspicion of prostate cancer (PCa were examined. The patients underwent repeat 24-core multifocal prostate biopsy with taking additional tissue samples from suspicious areas detected by multiparametric magnetic resonance imaging and transrectal ultrasound. An isolated ASAP area was found in 127 (25. 7 % of the 494 examined men. All of them were offered to perform repeat target transrectal biopsy of this area. Targeted transrectal ultrasound guided biopsy of the ASAP area was performed in 56 (44.1 % of the 127 patients, 53 of them being included in the final analysis.Results. PCa was diagnosed in 14 (26.4 % of the 53 patients, their mean age being 64.4 ± 6.9 years. The average level of prostate-specific antigen (PSA in PCa patients was 6.8 ± 3.0 ng/ml, in those with benign lesions – 9.3 ± 6.5 ng/ml; the percentage ratio of free/total PSA with PCa was 16.2 ± 7,8 %, with benign lesions – 23.3 ± 7.7 %; PSA density in PCa patients was 0.14 ± 0.07 ng/ml/cm3, in those with benign lesions – 0.15 ± 0.12 ng/ml/cm3. Therefore, with ASAP area being detected in repeat prostate biopsy samples, it is advisable that targeted extended biopsy of this area be performed. 

  20. GPU implementation of target and anomaly detection algorithms for remotely sensed hyperspectral image analysis

    Science.gov (United States)

    Paz, Abel; Plaza, Antonio

    2010-08-01

    Automatic target and anomaly detection are considered very important tasks for hyperspectral data exploitation. These techniques are now routinely applied in many application domains, including defence and intelligence, public safety, precision agriculture, geology, or forestry. Many of these applications require timely responses for swift decisions which depend upon high computing performance of algorithm analysis. However, with the recent explosion in the amount and dimensionality of hyperspectral imagery, this problem calls for the incorporation of parallel computing techniques. In the past, clusters of computers have offered an attractive solution for fast anomaly and target detection in hyperspectral data sets already transmitted to Earth. However, these systems are expensive and difficult to adapt to on-board data processing scenarios, in which low-weight and low-power integrated components are essential to reduce mission payload and obtain analysis results in (near) real-time, i.e., at the same time as the data is collected by the sensor. An exciting new development in the field of commodity computing is the emergence of commodity graphics processing units (GPUs), which can now bridge the gap towards on-board processing of remotely sensed hyperspectral data. In this paper, we describe several new GPU-based implementations of target and anomaly detection algorithms for hyperspectral data exploitation. The parallel algorithms are implemented on latest-generation Tesla C1060 GPU architectures, and quantitatively evaluated using hyperspectral data collected by NASA's AVIRIS system over the World Trade Center (WTC) in New York, five days after the terrorist attacks that collapsed the two main towers in the WTC complex.

  1. Relating approach-to-target and detection tasks in animal psychoacoustics.

    Science.gov (United States)

    Sollini, Joseph; Alves-Pinto, Ana; Sumner, Christian J

    2016-08-01

    Psychophysical experiments seek to measure the limits of perception. While straightforward in humans, in animals they are time consuming. Choosing an appropriate task and interpreting measurements can be challenging. We investigated the localization of high-frequency auditory signals in noise using an "approach-to-target" task in ferrets, how task performance should be interpreted in terms of perception, and how the measurements relate to other types of tasks. To establish their general ability to localize, animals were first trained to discriminate broadband noise from 12 locations. Subsequently we tested their ability to discriminate between band-limited targets at 2 or 3 more widely spaced locations, in a continuous background noise. The ability to discriminate between 3 possible locations (-90°, 0°, 90°) of a 10-kHz pure tone decreased gradually over a wide range (>30 dB) of signal-to-noise ratios (SNRs). Location discrimination ability was better for wide band noise targets (0.5 and 2 octave). These results were consistent with localization ability limiting performance for pure tones. Discrimination of pure tones at 2 locations (-90/left, 90/right) was robust at positive SNRs, yielding psychometric functions which fell steeply at negative SNRs. Thresholds for discrimination were similar to previous tone-in-noise thresholds measured in ferrets using a yes/no task. Thus, using an approach-to-target task, sound "localization" in noise can reflect detectability or the ability to localize, depending on the stimulus configuration. Signal-detection-theory-based models were able to account for the results when discriminating between pure tones from 2- and 3-source locations. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  2. Shape-Based Online Multitarget Tracking and Detection for Targets Causing Multiple Measurements: Variational Bayesian Clustering and Lossless Data Association.

    Science.gov (United States)

    De Laet, Tinne; Bruyninckx, Herman; De Schutter, Joris

    2011-12-01

    This paper proposes a novel online two-level multitarget tracking and detection (MTTD) algorithm. The algorithm focuses on multitarget detection and tracking for the case of multiple measurements per target and for an unknown and varying number of targets. Information is continuously exchanged in both directions between the two levels. Using the high level target position and shape information, the low level clusters the measurements. Furthermore, the low level features automatic relevance detection (ARD), as it automatically determines the optimal number of clusters from the measurements taking into account the expected target shapes. The high level's data association allows for a varying number of targets. A joint probabilistic data association algorithm looks for associations between clusters of measurements and targets. These associations are used to update the target trackers and the target shapes with the individual measurements. No information is lost in the two-level approach since the measurement information is not summarized into features. The target trackers are based on an underlying motion model, while the high level is supplemented with a filter estimating the number of targets. The algorithm is verified using both simulations and experiments using two sensor modalities, video and laser scanner, for detection and tracking of people and ants.

  3. Detection, quantification, and microlocalisation of targets of pesticides using microchannel plate autoradiographic imagers.

    Science.gov (United States)

    Tarhoni, Mabruka H; Vigneswara, Vasanthy; Smith, Marie; Anderson, Susan; Wigmore, Peter; Lees, John E; Ray, David E; Carter, Wayne G

    2011-10-11

    Organophosphorus (OP) compounds are a diverse chemical group that includes nerve agents and pesticides. They share a common chemical signature that facilitates their binding and adduction of acetylcholinesterase (AChE) within nerve synapses to induce cholinergic toxicity. However, this group diversity results in non-uniform binding and inactivation of other secondary protein targets, some of which may be adducted and protein activity influenced, even when only a relatively minor portion of tissue AChE is inhibited. The determination of individual OP protein binding targets has been hampered by the sensitivity of methods of detection and quantification of protein-pesticide adducts. We have overcome this limitation by the employment of a microchannel plate (MCP) autoradiographic detector to monitor a radiolabelled OP tracer compound. We preincubated rat thymus tissue in vitro with the OP pesticides, azamethiphos-oxon, chlorfenvinphos-oxon, chlorpyrifos-oxon, diazinon-oxon, and malaoxon, and then subsequently radiolabelled the free OP binding sites remaining with 3H-diisopropylfluorophosphate (3H-DFP). Proteins adducted by OP pesticides were detected as a reduction in 3H-DFP radiolabelling after protein separation by one dimensional polyacrylamide gel electrophoresis and quantitative digital autoradiography using the MCP imager. Thymus tissue proteins of molecular weights -28 kDa, 59 kDa, 66 kDa, and 82 kDa displayed responsiveness to adduction by this panel of pesticides. The 59 kDa protein target (previously putatively identified as carboxylesterase I) was only significantly adducted by chlorfenvinphos-oxon (p MCP autoradiography. Some of these 3H-DFP proteins spots were responsive to adduction by preincubation with chlorfenvinphos-oxon. In addition, we exploited the useful spatial resolution of the MCP imager (-70 mm) to determine pesticide micolocalisation in vivo, after animal dosing and autoradiography of brain tissue sections. Collectively, MCP autoradiographic

  4. Target detect system in 3D using vision apply on plant reproduction by tissue culture

    Science.gov (United States)

    Vazquez Rueda, Martin G.; Hahn, Federico

    2001-03-01

    This paper presents the preliminary results for a system in tree dimension that use a system vision to manipulate plants in a tissue culture process. The system is able to estimate the position of the plant in the work area, first calculate the position and send information to the mechanical system, and recalculate the position again, and if it is necessary, repositioning the mechanical system, using an neural system to improve the location of the plant. The system use only the system vision to sense the position and control loop using a neural system to detect the target and positioning the mechanical system, the results are compared with an open loop system.

  5. Detection of pathogenic biofilms with bacterial amyloid targeting fluorescent probe, CDy11

    DEFF Research Database (Denmark)

    Kim, Jun-Young; Sahu, Srikanta; Yau, Yin-Hoe

    2016-01-01

    Bacterial biofilms are responsible for a wide range of persistent infections. In the clinic, diagnosis of biofilm-associated infections relies heavily on culturing methods, which fail to detect nonculturable bacteria. Identification of novel fluorescent probes for biofilm imaging will greatly...... facilitate diagnosis of pathogenic bacterial infection. Herein, we report a novel fluorescent probe, CDy11 (compound of designation yellow 11), which targets amyloid in the Pseudomonas aeruginosa biofilm matrix through a diversity oriented fluorescent library approach (DOFLA). CDy11 was further demonstrated...... for in vivo imaging of P. aeruginosa in implant and corneal infection mice models....

  6. Antenna Polarization Optimization for Target Detection in Non-Gaussian Clutter

    Directory of Open Access Journals (Sweden)

    Xu Cheng

    2015-01-01

    Full Text Available Adaptive polarization design of radar antenna has recently become the focus of attention in radar polarization community. A polarimetric detector against non-Gaussian clutter with transmitter polarization optimization has been proposed in this paper. First, the radar data model including the realistic dependence of the clutter on the transmitted polarization is introduced. Then the polarimetric detector with transmitter polarization optimization is developed. By employing the simulation, we demonstrate that the polarization waveform optimization can bring the significant performance gain on target detection as compared to the conventional full-polarization approach. Besides, jointly optimizing transmitter and receiver polarization to form a scalar measurement is confirmed not to achieve a better detection performance than vector measurement with only transmitter polarization optimization.

  7. Advances in Target Detection and Tracking in Forward-Looking InfraRed (FLIR Imagery

    Directory of Open Access Journals (Sweden)

    Andrea Sanna

    2014-10-01

    Full Text Available Here we give context to the Special Issue on “Detection and Tracking of Targets in Forward-Looking InfraRed (FLIR Imagery” in Sensors. We start with an introduction to the role of infrared images in today’s vision-based applications, by outlining the specific challenges that characterize detection and tracking in FLIR images. We then illustrate why selected papers have been chosen to represent the domain of interest, by summarizing their main contributions to the state-of-the-art. Lastly, we sum up the main evidence found, and we underline some of the aspects that are worthy of further investigation in future research activities.

  8. Improved collaborative representation model with multitask learning using spatial support for target detection in hyperspectral imagery

    Science.gov (United States)

    Zhao, Chunhui; Li, Wei; Arturo Sanchez-Azofeifa, G.; Qi, Bin; Cui, Bing

    2016-01-01

    We propose an improved collaborative representation model with multitask learning using spatial support (ICRTD-MTL) for target detection (TD) in hyperspectral imagery. The proposed model consists of the following aspects. First, multiple features are extracted from the hyperspectral image to represent pixels from different perspectives. Next, we apply these features into the unified CRTD-MTL to acquire a collaborative vector for each feature. To adjust the contribution of each feature, a weight coefficient is included in the optimization problem. Once the collaborative vector is obtained, the class of the test sample can be determined by the characteristics of the collaborative vector on reconstruction. Finally, the spatial correlation and spectral similarity of adjacent neighboring pixels are incorporated into each feature to improve the detection accuracy. The experimental results suggest that the proposed algorithm obtains an excellent performance.

  9. Detection, Quantification, and Microlocalisation of Targets of Pesticides Using Microchannel Plate Autoradiographic Imagers

    Directory of Open Access Journals (Sweden)

    Mabruka H. Tarhoni

    2011-10-01

    Full Text Available Organophosphorus (OP compounds are a diverse chemical group that includes nerve agents and pesticides. They share a common chemical signature that facilitates their binding and adduction of acetylcholinesterase (AChE within nerve synapses to induce cholinergic toxicity. However, this group diversity results in non-uniform binding and inactivation of other secondary protein targets, some of which may be adducted and protein activity influenced, even when only a relatively minor portion of tissue AChE is inhibited. The determination of individual OP protein binding targets has been hampered by the sensitivity of methods of detection and quantification of protein-pesticide adducts. We have overcome this limitation by the employment of a microchannel plate (MCP autoradiographic detector to monitor a radiolabelled OP tracer compound. We preincubated rat thymus tissue in vitro with the OP pesticides, azamethiphos-oxon, chlorfenvinphos-oxon, chlorpyrifos-oxon, diazinon-oxon, and malaoxon, and then subsequently radiolabelled the free OP binding sites remaining with 3H-diisopropylfluorophosphate (3H-DFP. Proteins adducted by OP pesticides were detected as a reduction in 3H-DFP radiolabelling after protein separation by one dimensional polyacrylamide gel electrophoresis and quantitative digital autoradiography using the MCP imager. Thymus tissue proteins of molecular weights ~28 kDa, 59 kDa, 66 kDa, and 82 kDa displayed responsiveness to adduction by this panel of pesticides. The 59 kDa protein target (previously putatively identified as carboxylesterase I was only significantly adducted by chlorfenvinphos-oxon (p < 0.001, chlorpyrifos-oxon (p < 0.0001, and diazinon-oxon (p < 0.01, the 66 kDa protein target (previously identified as serum albumin similarly only adducted by the same three pesticides (p < 0.0001, (p < 0.001, and (p < 0.01, and the 82 kDa protein target (previously identified as acyl peptide hydrolase only adducted by chlorpyrifos-oxon (p

  10. Simultaneous detection of intracellular target and off-target binding of small molecule cancer drugs at nanomolar concentrations.

    NARCIS (Netherlands)

    Glauner, H.B.; Ruttekolk, I.R.R.; Hansen, K.; Steemers, B.; Chung, Y.D.; Becker, F.; Hannus, S.; Brock, R.E.

    2010-01-01

    BACKGROUND AND PURPOSE: In vitro assays that determine activities of drug candidates with isolated targets have only limited predictive value for activities in cellular assays. Poor membrane permeability and off-target binding are major reasons for such discrepancies. However, it still difficult to

  11. Rapid and sensitive detection of early esophageal squamous cell carcinoma with fluorescence probe targeting dipeptidylpeptidase IV

    Science.gov (United States)

    Onoyama, Haruna; Kamiya, Mako; Kuriki, Yugo; Komatsu, Toru; Abe, Hiroyuki; Tsuji, Yosuke; Yagi, Koichi; Yamagata, Yukinori; Aikou, Susumu; Nishida, Masato; Mori, Kazuhiko; Yamashita, Hiroharu; Fujishiro, Mitsuhiro; Nomura, Sachiyo; Shimizu, Nobuyuki; Fukayama, Masashi; Koike, Kazuhiko; Urano, Yasuteru; Seto, Yasuyuki

    2016-01-01

    Early detection of esophageal squamous cell carcinoma (ESCC) is an important prognosticator, but is difficult to achieve by conventional endoscopy. Conventional lugol chromoendoscopy and equipment-based image-enhanced endoscopy, such as narrow-band imaging (NBI), have various practical limitations. Since fluorescence-based visualization is considered a promising approach, we aimed to develop an activatable fluorescence probe to visualize ESCCs. First, based on the fact that various aminopeptidase activities are elevated in cancer, we screened freshly resected specimens from patients with a series of aminopeptidase-activatable fluorescence probes. The results indicated that dipeptidylpeptidase IV (DPP-IV) is specifically activated in ESCCs, and would be a suitable molecular target for detection of esophageal cancer. Therefore, we designed, synthesized and characterized a series of DPP-IV-activatable fluorescence probes. When the selected probe was topically sprayed onto endoscopic submucosal dissection (ESD) or surgical specimens, tumors were visualized within 5 min, and when the probe was sprayed on biopsy samples, the sensitivity, specificity and accuracy reached 96.9%, 85.7% and 90.5%. We believe that DPP-IV-targeted activatable fluorescence probes are practically translatable as convenient tools for clinical application to enable rapid and accurate diagnosis of early esophageal cancer during endoscopic or surgical procedures. PMID:27245876

  12. Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

    Science.gov (United States)

    Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.; Baker, Erin S.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco

    2017-09-01

    In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10-200 nM range, while simultaneously achieving discovery measurements of not initially targeted peptides as markers from the same proteins and, eventually, other proteins. [Figure not available: see fulltext.

  13. Non-targeted detection of milk powder adulteration using Raman spectroscopy and chemometrics: melamine case study.

    Science.gov (United States)

    Karunathilaka, Sanjeewa R; Farris, Samantha; Mossoba, Magdi M; Moore, Jeffrey C; Yakes, Betsy Jean

    2017-02-01

    Raman spectroscopy in combination with chemometrics was explored as a rapid, non-targeted screening method for the detection of milk powder (MP) adulteration using melamine as an example contaminant. Raman spectroscopy and an unsupervised pattern-recognition method, principal component analysis (PCA), allowed for the differentiation of authentic MPs from adulterated ones at concentrations > 1.0% for dry-blended (DB) samples and > 0.30% for wet-blended (WB) ones. Soft independent modelling of class analogy (SIMCA), a supervised pattern-recognition method, was also used to classify test samples as adulterated or authentic. Combined statistics at a 97% confidence level from the SIMCA models correctly classified adulteration of MP with melamine at concentrations ≥ 0.5% for DB samples and ≥ 0.30% for WB ones, while no false-positives from authentic MPs were found when the spectra in the 600-700 cm(-)(1) range were pre-processed using standard normal variate (SNV) followed by a gap-segment derivatisation. The combined technique of Raman spectroscopy and chemometrics proved to be a useful tool for the rapid and cost-efficient non-targeted detection of adulteration in MP at per cent spiking levels.

  14. A Plant Immune Receptor Detects Pathogen Effectors that Target WRKY Transcription Factors.

    Science.gov (United States)

    Sarris, Panagiotis F; Duxbury, Zane; Huh, Sung Un; Ma, Yan; Segonzac, Cécile; Sklenar, Jan; Derbyshire, Paul; Cevik, Volkan; Rallapalli, Ghanasyam; Saucet, Simon B; Wirthmueller, Lennart; Menke, Frank L H; Sohn, Kee Hoon; Jones, Jonathan D G

    2015-05-21

    Defense against pathogens in multicellular eukaryotes depends on intracellular immune receptors, yet surveillance by these receptors is poorly understood. Several plant nucleotide-binding, leucine-rich repeat (NB-LRR) immune receptors carry fusions with other protein domains. The Arabidopsis RRS1-R NB-LRR protein carries a C-terminal WRKY DNA binding domain and forms a receptor complex with RPS4, another NB-LRR protein. This complex detects the bacterial effectors AvrRps4 or PopP2 and then activates defense. Both bacterial proteins interact with the RRS1 WRKY domain, and PopP2 acetylates lysines to block DNA binding. PopP2 and AvrRps4 interact with other WRKY domain-containing proteins, suggesting these effectors interfere with WRKY transcription factor-dependent defense, and RPS4/RRS1 has integrated a "decoy" domain that enables detection of effectors that target WRKY proteins. We propose that NB-LRR receptor pairs, one member of which carries an additional protein domain, enable perception of pathogen effectors whose function is to target that domain. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Target detection: Magnetic resonance imaging-ultrasound fusion–guided prostate biopsy

    Science.gov (United States)

    Sonn, Geoffrey A.; Margolis, Daniel J.; Marks, Leonard S.

    2014-01-01

    Recent advances in multiparametric magnetic resonance imaging (MRI) have enabled image-guided detection of prostate cancer. Fusion of MRI with real-time ultrasound (US) allows the information from MRI to be used to direct biopsy needles under US guidance in an office-based procedure. Fusion can be performed either cognitively or electronically, using a fusion device. Fusion devices allow superimposition (coregistration) of stored MRI images on real-time US images; areas of suspicion found on MRI can then serve as targets during US-guided biopsy. Currently available fusion devices use a variety of technologies to perform coregistration: robotic tracking via a mechanical arm with built-in encoders (Artemis/Eigen, BioJet/Geoscan); electromagnetic tracking (UroNav/Philips-Invivo, Hi-RVS/Hitachi); or tracking with a 3D US probe (Urostation/Koelis). Targeted fusion biopsy has been shown to identify more clinically significant cancers and fewer insignificant cancers than conventional biopsy. Fusion biopsy appears to be a major advancement over conventional biopsy because it allows (1) direct targeting of suspicious areas not seen on US and (2) follow-up biopsy of specific cancerous sites in men undergoing active surveillance. PMID:24239473

  16. Smartphone-based portable wireless optical system for the detection of target analytes.

    Science.gov (United States)

    Gautam, Shreedhar; Batule, Bhagwan S; Kim, Hyo Yong; Park, Ki Soo; Park, Hyun Gyu

    2017-02-01

    Rapid and accurate on-site wireless measurement of hazardous molecules or biomarkers is one of the biggest challenges in nanobiotechnology. A novel smartphone-based Portable and Wireless Optical System (PAWS) for rapid, quantitative, and on-site analysis of target analytes is described. As a proof-of-concept, we employed gold nanoparticles (GNP) and an enzyme, horse radish peroxidase (HRP), to generate colorimetric signals in response to two model target molecules, melamine and hydrogen peroxide, respectively. The colorimetric signal produced by the presence of the target molecules is converted to an electrical signal by the inbuilt electronic circuit of the device. The converted electrical signal is then measured wirelessly via multimeter in the smartphone which processes the data and displays the results, including the concentration of analytes and its significance. This handheld device has great potential as a programmable and miniaturized platform to achieve rapid and on-site detection of various analytes in a point-of-care testing (POCT) manner. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Insonation frequency selection may assist detection and therapeutic delivery of targeted ultrasound contrast agents.

    Science.gov (United States)

    Payne, Edward; Ooi, Andrew; Manasseh, Richard

    2011-02-01

    Ultrasound-targeted drug delivery relies on the unique nature of ultrasound contrast agents--they are microbubbles that respond strongly to ultrasound. Intravenously injected microbubbles are smaller than a blood cell. By increasing the ultrasound power, the bubbles can be ruptured at the targeted endothelial wall, locally releasing any molecules in the bubble shell. Furthermore, ultrasound-activated microbubbles are known to cause sonoporation--the process by which ultrasound drives molecules through cellular membranes. However, techniques are required to selectively detect and rupture only those microbubbles on target walls. Experiments are presented on the behaviour of microbubbles on walls. For accuracy, imaging measurements are made on model microbubbles larger than contrast agents. Bubble size was varied and the resonant frequency peak determined. Microbubbles on walls have a shifted frequency in good agreement with theory: a 20-25% downshift from the frequency when far from walls. Effects other than the presence of the wall account for less than 5% of the shift. Theory predicts the frequency downshift should be sustained for actual contrast-agent sized bubbles. The effect of real, compliant cell walls requires investigation. An appropriate downshift in the applied ultrasound frequency could selectively tune gene or drug delivery. To make this feasible, it may be necessary to manufacture monodispersed microbubbles.

  18. Sensitive targeted multiple protein quantification based on elemental detection of Quantum Dots

    Energy Technology Data Exchange (ETDEWEB)

    Montoro Bustos, Antonio R.; Garcia-Cortes, Marta [Department of Physical and Analytical Chemistry, University of Oviedo, Julián Clavería 8, Oviedo 33006 (Spain); González-Iglesias, Hector [Fundación de Investigación Oftalmológica, Instituto Oftalmológico Fernandez-Vega, Avenida Doctores Fernández-Vega, 34, Oviedo 33012 (Spain); Ruiz Encinar, Jorge, E-mail: ruizjorge@uniovi.es [Department of Physical and Analytical Chemistry, University of Oviedo, Julián Clavería 8, Oviedo 33006 (Spain); Costa-Fernández, José M. [Department of Physical and Analytical Chemistry, University of Oviedo, Julián Clavería 8, Oviedo 33006 (Spain); Coca-Prados, Miguel [Fundación de Investigación Oftalmológica, Instituto Oftalmológico Fernandez-Vega, Avenida Doctores Fernández-Vega, 34, Oviedo 33012 (Spain); Department of Ophthalmology and Visual Science, Yale University School of Medicine, New Haven, CT 06510 (United States); Sanz-Medel, Alfredo, E-mail: asm@uniovi.es [Department of Physical and Analytical Chemistry, University of Oviedo, Julián Clavería 8, Oviedo 33006 (Spain)

    2015-06-16

    Highlights: • Novel generic platform for multiparametric quantification of proteins. • QDs labeling and ICP-MS detection allow significant analytical signal amplification. • ICP-MS mass balances information provided an internal validation of the immunoassay. • Multiparametric determination of 5 proteins in human serum samples. • ICP-MS reduced matrix effects as compared to other conventional detection techniques. - Abstract: A generic strategy based on the use of CdSe/ZnS Quantum Dots (QDs) as elemental labels for protein quantification, using immunoassays with elemental mass spectrometry (ICP-MS), detection is presented. In this strategy, streptavidin modified QDs (QDs-SA) are bioconjugated to a biotinylated secondary antibody (b-Ab{sub 2}). After a multi-technique characterization of the synthesized generic platform (QDs-SA-b-Ab{sub 2}) it was applied to the sequential quantification of five proteins (transferrin, complement C3, apolipoprotein A1, transthyretin and apolipoprotein A4) at different concentration levels in human serum samples. It is shown how this generic strategy does only require the appropriate unlabeled primary antibody for each protein to be detected. Therefore, it introduces a way out to the need for the cumbersome and specific bioconjugation of the QDs to the corresponding specific recognition antibody for every target analyte (protein). Results obtained were validated with those obtained using UV–vis spectrophotometry and commercial ELISA Kits. As expected, ICP-MS offered one order of magnitude lower DL (0.23 fmol absolute for transferrin) than the classical spectrophotometric detection (3.2 fmol absolute). ICP-MS precision and detection limits, however turned out to be compromised by procedural blanks. The full analytical performance of the ICP-MS-based immunoassay proposed was assessed for detection of transferrin (Tf), present at the low ng mL{sup −1} range in a complex “model” synthetic matrix, where the total protein

  19. Spectrum Compensation for Time Reversal Method on Ultrasonic Target Detection Using Pulse Compression.

    Science.gov (United States)

    Chimura, Dai; Toh, Ryo; Motooka, Seiichi

    2017-09-04

    This paper discusses a method of time reversal (TR) for target detection using a signal with a higher signal-to-noise ratio (SNR) and higher resolution. To acquire a signal with a higher SNR and broader spectrum, we have proposed a sensitivity-compensated (SC) signal. In this study, we propose three types of sensitivity-compensated-for-time-reversal (SC-for-TR) signals. A sensitivity-compensated-amplitude-modulated-for-time-reversal signal and a sensitivity-compensated-frequency-modulated-for-time-reversal signal are calculated using squared spectrum compensation. Moreover, to enhance the transmitting energy of a time reversed wave for higher SNR, we propose a sensitivity-compensated-amplitude-and-frequency-modulated-for -time-reversal (SCAFM-for-TR) signal. The SCAFM-for-TR signal is calculated by amplitude modulation and frequency modulation for deriving a time reversed wave with a constant envelope waveform and compensated spectrum. In this study, the efficiency of the SC-for-TR signals is investigated on target ranging in water using pulse compression. Accordingly, the SC-for-TR signals derive a pulse compressed signal with higher resolution. In addition, the precision of target ranging using the SCAFM-for-TR signal is greater than that using the other SC-for-TR signals at an arrangement when a target was fixed at a position where a signal with a lower SNR is received. These results show that the measurements using the SC-for-TR signals improve time resolution and the measurements using the SCAFM-for-TR signal improve the SNR.

  20. A Fast Algorithm of Generalized Radon-Fourier Transform for Weak Maneuvering Target Detection

    Directory of Open Access Journals (Sweden)

    Weijie Xia

    2016-01-01

    Full Text Available The generalized Radon-Fourier transform (GRFT has been proposed to detect radar weak maneuvering targets by realizing coherent integration via jointly searching in motion parameter space. Two main drawbacks of GRFT are the heavy computational burden and the blind speed side lobes (BSSL which will cause serious false alarms. The BSSL learning-based particle swarm optimization (BPSO has been proposed before to reduce the computational burden of GRFT and solve the BSSL problem simultaneously. However, the BPSO suffers from an apparent loss in detection performance compared with GRFT. In this paper, a fast implementation algorithm of GRFT using the BSSL learning-based modified wind-driven optimization (BMWDO is proposed. In the BMWDO, the BSSL learning procedure is also used to deal with the BSSL phenomenon. Besides, the MWDO adjusts the coefficients in WDO with Levy distribution and uniform distribution, and it outperforms PSO in a noisy environment. Compared with BPSO, the proposed method can achieve better detection performance with a similar computational cost. Several numerical experiments are also provided to demonstrate the effectiveness of the proposed method.

  1. Agroterrorism targeting livestock: a review with a focus on early detection systems.

    Science.gov (United States)

    Elbers, Armin; Knutsson, Rickard

    2013-09-01

    Agroterrorism targeting livestock can be described as the intentional introduction of an animal disease agent against livestock with the purpose of causing economic damage, disrupting socioeconomic stability of a country, and creating panic and distress. This type of terrorism can be alluring to terrorists because animal disease agents are easily available. This review addresses the vulnerabilities of the livestock industry to agroterrorism. However, we also show that early detection systems have recently been developed for agroterrorism and deliberate spread of animal pathogens in livestock, including an agroterrorism intelligence cycle, syndromic surveillance programs, and computer-based clinical decision support systems that can be used for early detection of notifiable animal diseases. The development of DIVA-vaccines in the past 10 to 15 years has created, in principle, an excellent response instrument to counter intentional animal disease outbreaks. These developments have made our animal agriculture less vulnerable to agroterrorism. But we cannot relax; there are still many challenges, in particular with respect to integration of first line of defense, law enforcement, and early detection systems for animal diseases.

  2. Performance comparison of multidetector detection statistics in targeted compact binary coalescence gravitational wave searches

    Science.gov (United States)

    Haris, K.; Pai, Archana

    2017-11-01

    A global network of advanced interferometric gravitational wave detectors is expected to be on-line soon. Coherent observation of gravitational waves from a distant compact binary coalescence with a network of interferometers located in different continents gives crucial information about the source, such as its location and polarization. In this paper we compare different multidetector network detection statistics for compact binary coalescence searches. In maximum likelihood ratio based detection approaches, the likelihood ratio is optimized to obtain the best model parameters, and the best likelihood ratio value is used as a statistic to make decisions regarding the presence of signals. However, an alternative Bayesian approach involves the marginalization of the likelihood ratio over the parameters and obtains the average likelihood ratio test. We obtain an analytical expression for the Bayesian statistic using the two effective synthetic data streams for targeted searches of nonspinning compact binary systems with an uninformative prior on the parameters. Simulations are carried out to test the validity of the approximation and compare the detection performance with the maximum likelihood ratio and the "hybrid" statistic. We observe that the hybrid statistic gives comparable or better performance with respect to the Bayesian statistic.

  3. Simultaneous detection of multiple DNA targets by integrating dual-color graphene quantum dot nanoprobes and carbon nanotubes.

    Science.gov (United States)

    Qian, Zhaosheng; Shan, Xiaoyue; Chai, Lujing; Chen, Jianrong; Feng, Hui

    2014-12-01

    Simultaneous detection of multiple DNA targets was achieved based on a biocompatible graphene quantum dots (GQDs) and carbon nanotubes (CNTs) platform through spontaneous assembly between dual-color GQD-based probes and CNTs and subsequently self-recognition between DNA probes and targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. The effects of incidentally learned temporal and spatial predictability on response times and visual fixations during target detection and discrimination.

    Directory of Open Access Journals (Sweden)

    Melissa R Beck

    Full Text Available Responses are quicker to predictable stimuli than if the time and place of appearance is uncertain. Studies that manipulate target predictability often involve overt cues to speed up response times. However, less is known about whether individuals will exhibit faster response times when target predictability is embedded within the inter-trial relationships. The current research examined the combined effects of spatial and temporal target predictability on reaction time (RT and allocation of overt attention in a sustained attention task. Participants responded as quickly as possible to stimuli while their RT and eye movements were measured. Target temporal and spatial predictability were manipulated by altering the number of: 1 different time intervals between a response and the next target; and 2 possible spatial locations of the target. The effects of target predictability on target detection (Experiment 1 and target discrimination (Experiment 2 were tested. For both experiments, shorter RTs as target predictability increased across both space and time were found. In addition, the influences of spatial and temporal target predictability on RT and the overt allocation of attention were task dependent; suggesting that effective orienting of attention relies on both spatial and temporal predictability. These results indicate that stimulus predictability can be increased without overt cues and detected purely through inter-trial relationships over the course of repeated stimulus presentations.

  5. Detecting Threat-Related Intentional Actions of Others: Effects of Image Quality, Response Mode, and Target Cuing on Vigilance

    Science.gov (United States)

    Parasuraman, Raja; de Visser, Ewart; Clarke, Ellen; McGarry, W. Ryan; Hussey, Elizabeth; Shaw, Tyler; Thompson, James C.

    2009-01-01

    Three experiments examined the vigilance performance of participants watching videos depicting intentional actions of an individual's hand reaching for and grasping an object--involving transporting or using either a gun or a hairdryer--in order to detect infrequent threat-related actions. Participants indicated detection of target actions either…

  6. Site-targeted acoustic contrast agent detects molecular expression of tissue factor after balloon angioplasty

    Science.gov (United States)

    Hall, Christopher S.; Abendschein, Dana R.; Scherrer, David E.; Scott, Michael J.; Marsh, Jon N.; Wickline, Samuel A.; Lanza, Gregory M.

    2000-04-01

    expression of tissue factor could prove to be a prognostically important predictor of subsequent restenosis. Moreover, with the incorporation of specific drug treatments into the nanoparticulate contrast agent, ultrasonic molecular imaging may yield reliable detection and quantification of nascent pathologies and facilitate targeted drug therapy.

  7. Multi-Frequency Target Detection Techniques for DVB-T Based Passive Radar Sensors

    Directory of Open Access Journals (Sweden)

    Tatiana Martelli

    2016-09-01

    Full Text Available This paper investigates the possibility to improve target detection capability in a DVB-T- based passive radar sensor by jointly exploiting multiple digital television channels broadcast by the same transmitter of opportunity. Based on the remarkable results obtained by such a multi-frequency approach using other signals of opportunity (i.e., FM radio broadcast transmissions, we propose appropriate modifications to the previously devised signal processing techniques for them to be effective in the newly considered scenarios. The resulting processing schemes are extensively applied against experimental DVB-T-based passive radar data pertaining to different surveillance applications. The obtained results clearly show the effectiveness of the proposed multi-frequency approaches and demonstrate their suitability for application in the considered scenarios.

  8. Fully resolved immersed electrohydrodynamics for target-detection, particle motion, and self propulsion

    Science.gov (United States)

    Bhalla, Amneet P. S.; Griffith, Boyce E.; Patankar, Neelesh A.

    2012-11-01

    Motion of particles, rigid or deforming, through conductive fluid media under the presence of electric fields require the solution of coupled electrodynamics and hydrodynamics equations. In this work we present a numerical method for modeling such coupled equations in an adaptive mesh refinement and immersed body framework. The methodology permits us to locally resolve high electric field gradients and boundary layers near the fluid-structure interfaces at a moderate computational expense. Using such a framework a broad range of problems such as ``electrolocation'' (a technique used by knifefish to detect its target due to the distortion of self generated electric field by a prey in its vicinity), dielectrophoretic motion of particles in microfluidic channels, development of artificial ``electrosense'' for underwater vehicles, among others, can be addressed. NSF support is gratefully acknowledged.

  9. An Overview on the Marine Neurotoxin, Saxitoxin: Genetics, Molecular Targets, Methods of Detection and Ecological Functions

    Directory of Open Access Journals (Sweden)

    Gary S. Sayler

    2013-03-01

    Full Text Available Marine neurotoxins are natural products produced by phytoplankton and select species of invertebrates and fish. These compounds interact with voltage-gated sodium, potassium and calcium channels and modulate the flux of these ions into various cell types. This review provides a summary of marine neurotoxins, including their structures, molecular targets and pharmacologies. Saxitoxin and its derivatives, collectively referred to as paralytic shellfish toxins (PSTs, are unique among neurotoxins in that they are found in both marine and freshwater environments by organisms inhabiting two kingdoms of life. Prokaryotic cyanobacteria are responsible for PST production in freshwater systems, while eukaryotic dinoflagellates are the main producers in marine waters. Bioaccumulation by filter-feeding bivalves and fish and subsequent transfer through the food web results in the potentially fatal human illnesses, paralytic shellfish poisoning and saxitoxin pufferfish poisoning. These illnesses are a result of saxitoxin’s ability to bind to the voltage-gated sodium channel, blocking the passage of nerve impulses and leading to death via respiratory paralysis. Recent advances in saxitoxin research are discussed, including the molecular biology of toxin synthesis, new protein targets, association with metal-binding motifs and methods of detection. The eco-evolutionary role(s PSTs may serve for phytoplankton species that produce them are also discussed.

  10. An overview on the marine neurotoxin, saxitoxin: genetics, molecular targets, methods of detection and ecological functions.

    Science.gov (United States)

    Cusick, Kathleen D; Sayler, Gary S

    2013-03-27

    Marine neurotoxins are natural products produced by phytoplankton and select species of invertebrates and fish. These compounds interact with voltage-gated sodium, potassium and calcium channels and modulate the flux of these ions into various cell types. This review provides a summary of marine neurotoxins, including their structures, molecular targets and pharmacologies. Saxitoxin and its derivatives, collectively referred to as paralytic shellfish toxins (PSTs), are unique among neurotoxins in that they are found in both marine and freshwater environments by organisms inhabiting two kingdoms of life. Prokaryotic cyanobacteria are responsible for PST production in freshwater systems, while eukaryotic dinoflagellates are the main producers in marine waters. Bioaccumulation by filter-feeding bivalves and fish and subsequent transfer through the food web results in the potentially fatal human illnesses, paralytic shellfish poisoning and saxitoxin pufferfish poisoning. These illnesses are a result of saxitoxin's ability to bind to the voltage-gated sodium channel, blocking the passage of nerve impulses and leading to death via respiratory paralysis. Recent advances in saxitoxin research are discussed, including the molecular biology of toxin synthesis, new protein targets, association with metal-binding motifs and methods of detection. The eco-evolutionary role(s) PSTs may serve for phytoplankton species that produce them are also discussed.

  11. Horizontal electromagnetic field sensor for detection and classification of metal targets

    Science.gov (United States)

    Nelson, Carl V.; Huynh, Toan B.; Writer, Timothy; Lacko, Peter R.

    2001-10-01

    This paper describes a prototype electromagnetic induction (EMI) sensor system designed specifically to measure the horizontal component of a metal target's eddy current time decay signature. Instead of creating a vertical magnetic field from a horizontal loop transmitter configuration used by most EMI metal detectors, the prototype transmitter geometry has been designed especially for creating a horizontal magneti field (HMF). One of the potential advantages of the HMF sensor is the relatively uniform magnetic field that is created over a large volume. A second potential advantage is that, compared to a conventional loop antenna, the magnetic field intensity falls off slowly with distance from the plane of the sensor. These two advantages potentially make the HMF sensor well suited for detection and classification of metal targets buried deeply in the ground (e.b., unexploded ordnance, UXO) or from a vehicle-mounted mine detector sensor. Preliminary modeling of the antenna and laboratory data from a time-domain version of the HMF sensor are presented.

  12. A New Methodology for 3D Target Detection in Automotive Radar Applications.

    Science.gov (United States)

    Baselice, Fabio; Ferraioli, Giampaolo; Lukin, Sergyi; Matuozzo, Gianfranco; Pascazio, Vito; Schirinzi, Gilda

    2016-04-29

    Today there is a growing interest in automotive sensor monitoring systems. One of the main challenges is to make them an effective and valuable aid in dangerous situations, improving transportation safety. The main limitation of visual aid systems is that they do not produce accurate results in critical visibility conditions, such as in presence of rain, fog or smoke. Radar systems can greatly help in overcoming such limitations. In particular, imaging radar is gaining interest in the framework of Driver Assistance Systems (DAS). In this manuscript, a new methodology able to reconstruct the 3D imaged scene and to detect the presence of multiple targets within each line of sight is proposed. The technique is based on the use of Compressive Sensing (CS) theory and produces the estimation of multiple targets for each line of sight, their range distance and their reflectivities. Moreover, a fast approach for 2D focus based on the FFT algorithm is proposed. After the description of the proposed methodology, different simulated case studies are reported in order to evaluate the performances of the proposed approach.

  13. Comparison of targeted proteomics approaches for detecting and quantifying proteins derived from human cancer tissues.

    Science.gov (United States)

    Faktor, Jakub; Sucha, Rita; Paralova, Vendula; Liu, Yansheng; Bouchal, Pavel

    2017-03-01

    Targeted mass spectrometry-based proteomics approaches enable the simultaneous and reproducible quantification of multiple protein analytes across numerous conditions in biology and clinical studies. These approaches involve e.g. selected reaction monitoring (SRM) typically conducted on a triple quadrupole mass spectrometer, its high-resolution variant named pseudo-SRM (p-SRM), carried out in a quadrupole coupled with an TOF analyzer (qTOF), and "sequential window acquisition of all theoretical spectra" (SWATH). Here we compared these methods in terms of signal-to-noise ratio (S/N), coefficient of variance (CV), fold change (FC), limit of detection and quantitation (LOD, LOQ). We have shown the highest S/N for p-SRM mode, followed by SRM and SWATH, demonstrating a trade-off between sensitivity and level of multiplexing for SRM, p-SRM, and SWATH. SRM was more sensitive than p-SRM based on determining their LOD and LOQ. Although SWATH has the worst S/N, it enables peptide multiplexing with post-acquisition definition of the targets, leading to better proteome coverage. FC between breast tumors of different clinical-pathological characteristics were highly correlated (R2 >0.97) across three methods and consistent with the previous study on 96 tumor tissues. Our technical note presented here, therefore, confirmed that outputs of all the three methods were biologically relevant and highly applicable to cancer research. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Better target detection in the presence of collinear flankers under high working memory load

    Directory of Open Access Journals (Sweden)

    Jan W. De Fockert

    2014-10-01

    Full Text Available There are multiple ways in which working memory can influence selective attention. Aside from the content-specific effects of working memory on selective attention, whereby attention is more likely to be directed towards information that matches the contents of working memory, the mere level of load on working memory has also been shown to have an effect on selective attention. Specifically, high load on working memory is associated with increased processing of irrelevant information. In most demonstrations of the effect to-date, this has led to impaired target performance, leaving open the possibility that the effect partly reflects an increase in general task difficulty under high load. Here we show that working memory load can result in a performance gain when processing of distracting information aids target performance. The facilitation in the detection of a low-contrast Gabor stimulus in the presence of collinear flanking Gabors was greater when load on a concurrent working memory task was high, compared to low. This finding suggests that working memory can interact with selective attention at an early stage in visual processing.

  15. Photodynamic quenched cathepsin activity based probes for cancer detection and macrophage targeted therapy.

    Science.gov (United States)

    Ben-Nun, Yael; Merquiol, Emmanuelle; Brandis, Alexander; Turk, Boris; Scherz, Avigdor; Blum, Galia

    2015-01-01

    Elevated cathepsins levels and activities are found in several types of human cancer, making them valuable biomarkers for detection and targeting therapeutics. We designed small molecule quenched activity-based probes (qABPs) that fluoresce upon activity-dependent covalent modification, yielding cell killing by Photodynamic Therapy (PDT). These novel molecules are highly selective theranostic probes that enable both detection and treatment of cancer with minimal side effects. Our qABPs carry a photosensitizer (PS), which is activated by light, resulting in oxidative stress and subsequent cell ablation, and a quencher that when removed by active cathepsins allow the PS to fluoresce and demonstrate PD properties. Our most powerful and stable PS-qABP, YBN14, consists of a selective cathepsin recognition sequence, a QC-1 quencher and a new bacteriochlorin derivative as a PS. YBN14 allowed rapid and selective non-invasive in vivo imaging of subcutaneous tumors and induced specific tumor macrophage apoptosis by light treatment, resulting in a substantial tumor shrinkage in an aggressive breast cancer mouse model. These results demonstrate for the first time that the PS-qABPs technology offers a functional theranostic tool, which can be applied to numerous tumor types and other inflammation-associated diseases.

  16. Driver Gene Mutations in Stools of Colorectal Carcinoma Patients Detected by Targeted Next-Generation Sequencing.

    Science.gov (United States)

    Armengol, Gemma; Sarhadi, Virinder K; Ghanbari, Reza; Doghaei-Moghaddam, Masoud; Ansari, Reza; Sotoudeh, Masoud; Puolakkainen, Pauli; Kokkola, Arto; Malekzadeh, Reza; Knuutila, Sakari

    2016-07-01

    Detection of driver gene mutations in stool DNA represents a promising noninvasive approach for screening colorectal cancer (CRC). Amplicon-based next-generation sequencing (NGS) is a good option to study mutations in many cancer genes simultaneously and from a low amount of DNA. Our aim was to assess the feasibility of identifying mutations in 22 cancer driver genes with Ion Torrent technology in stool DNA from a series of 65 CRC patients. The assay was successful in 80% of stool DNA samples. NGS results showed 83 mutations in cancer driver genes, 29 hotspot and 54 novel mutations. One to five genes were mutated in 75% of cases. TP53, KRAS, FBXW7, and SMAD4 were the top mutated genes, consistent with previous studies. Of samples with mutations, 54% presented concomitant mutations in different genes. Phosphatidylinositol 3-kinase/mitogen-activated protein kinase pathway genes were mutated in 70% of samples, with 58% having alterations in KRAS, NRAS, or BRAF. Because mutations in these genes can compromise the efficacy of epidermal growth factor receptor blockade in CRC patients, identifying mutations that confer resistance to some targeted treatments may be useful to guide therapeutic decisions. In conclusion, the data presented herein show that NGS procedures on stool DNA represent a promising tool to detect genetic mutations that could be used in the future for diagnosis, monitoring, or treating CRC. Copyright © 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  17. Detection of short repeated genomic sequences on metaphase chromosomes using padlock probes and target primed rolling circle DNA synthesis

    Directory of Open Access Journals (Sweden)

    Stougaard Magnus

    2007-11-01

    Full Text Available Abstract Background In situ detection of short sequence elements in genomic DNA requires short probes with high molecular resolution and powerful specific signal amplification. Padlock probes can differentiate single base variations. Ligated padlock probes can be amplified in situ by rolling circle DNA synthesis and detected by fluorescence microscopy, thus enhancing PRINS type reactions, where localized DNA synthesis reports on the position of hybridization targets, to potentially reveal the binding of single oligonucleotide-size probe molecules. Such a system has been presented for the detection of mitochondrial DNA in fixed cells, whereas attempts to apply rolling circle detection to metaphase chromosomes have previously failed, according to the literature. Methods Synchronized cultured cells were fixed with methanol/acetic acid to prepare chromosome spreads in teflon-coated diagnostic well-slides. Apart from the slide format and the chromosome spreading everything was done essentially according to standard protocols. Hybridization targets were detected in situ with padlock probes, which were ligated and amplified using target primed rolling circle DNA synthesis, and detected by fluorescence labeling. Results An optimized protocol for the spreading of condensed metaphase chromosomes in teflon-coated diagnostic well-slides was developed. Applying this protocol we generated specimens for target primed rolling circle DNA synthesis of padlock probes recognizing a 40 nucleotide sequence in the male specific repetitive satellite I sequence (DYZ1 on the Y-chromosome and a 32 nucleotide sequence in the repetitive kringle IV domain in the apolipoprotein(a gene positioned on the long arm of chromosome 6. These targets were detected with good efficiency, but the efficiency on other target sites was unsatisfactory. Conclusion Our aim was to test the applicability of the method used on mitochondrial DNA to the analysis of nuclear genomes, in particular as

  18. Real-time implementation of a multispectral mine target detection algorithm

    Science.gov (United States)

    Samson, Joseph W.; Witter, Lester J.; Kenton, Arthur C.; Holloway, John H., Jr.

    2003-09-01

    Spatial-spectral anomaly detection (the "RX Algorithm") has been exploited on the USMC's Coastal Battlefield Reconnaissance and Analysis (COBRA) Advanced Technology Demonstration (ATD) and several associated technology base studies, and has been found to be a useful method for the automated detection of surface-emplaced antitank land mines in airborne multispectral imagery. RX is a complex image processing algorithm that involves the direct spatial convolution of a target/background mask template over each multispectral image, coupled with a spatially variant background spectral covariance matrix estimation and inversion. The RX throughput on the ATD was about 38X real time using a single Sun UltraSparc system. A goal to demonstrate RX in real-time was begun in FY01. We now report the development and demonstration of a Field Programmable Gate Array (FPGA) solution that achieves a real-time implementation of the RX algorithm at video rates using COBRA ATD data. The approach uses an Annapolis Microsystems Firebird PMC card containing a Xilinx XCV2000E FPGA with over 2,500,000 logic gates and 18MBytes of memory. A prototype system was configured using a Tek Microsystems VME board with dual-PowerPC G4 processors and two PMC slots. The RX algorithm was translated from its C programming implementation into the VHDL language and synthesized into gates that were loaded into the FPGA. The VHDL/synthesizer approach allows key RX parameters to be quickly changed and a new implementation automatically generated. Reprogramming the FPGA is done rapidly and in-circuit. Implementation of the RX algorithm in a single FPGA is a major first step toward achieving real-time land mine detection.

  19. Comparison of PCR assays targeting the multi-copy targets B1 gene and 529 bp repetitive element for detection of Toxoplasma gondii in swine muscle.

    Science.gov (United States)

    Veronesi, Fabrizia; Santoro, Azzurra; Milardi, Giovanni Luigi; Diaferia, Manuela; Branciari, Raffaella; Miraglia, Dino; Cioffi, Attilia; Gabrielli, Simona; Ranucci, David

    2017-05-01

    The comparison of the sensitivities of two molecular assays designed to target the multi-copy sequences of the Toxoplasma gondii genomic B1 region and 529 bp-RE respectively, in detecting T. gondii in swine muscle was assessed. Diaphragm pillars were obtained from 498 slaughtered pigs managed in intensive farms in Central Italy. Genomic DNA was extracted from the tissues and T. gondii-B1 and 529 bp-RE sequences were amplified by specific PCR protocols. Toxoplasma gondii DNA was detected in 165 samples (33.13%). There was a good correlation (κ = 0.77) between the results obtained targeting the two different genetic markers, however the 529 bp RE-PCR assay overall detected a significantly higher (P < 0.05) number of T. gondii-positive samples (150 samples) than the B1-PCR protocol (134). Our results show that: i) standardized B1 and 529 bp-RE PCRs applied to muscle tissues can detect a high rate of T. gondii-infection; ii) a multi-target PCR approach is recommended for the accurate diagnosis of infection in swine and can also be used in food testing. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. SCREDENT: Scalable Real-time Anomalies Detection and Notification of Targeted Malware in Mobile Devices

    National Research Council Canada - National Science Library

    McNeil, Paul; Shetty, Sachin; Guntu, Divya; Barve, Gauree

    2016-01-01

    ... mobile attacks targeting the Android mobile operating system. In recent times, adversaries leverage situational awareness, user and device context to create targeted malware for mobile devices. Sever...

  1. A flexible and fully integrated system for amplification, detection and genotyping of genomic DNA targets based on microfluidic oligonucleotide arrays.

    Science.gov (United States)

    Summerer, Daniel; Hevroni, Dona; Jain, Amit; Oldenburger, Olga; Parker, Jefferson; Caruso, Anthony; Stähler, Cord F; Stähler, Peer F; Beier, Markus

    2010-05-31

    A strategy allowing for amplification, detection and genotyping of different genomic DNA targets in a single reaction container is described. The method makes use of primer-directed solution-phase amplification with integrated labeling in a closed, microfluidic oligonucleotide array. Selective array probes allow for subsequent detection and genotyping of generated amplicons by hybridization. The array contains up to 15,624 programmable features that can be designed, de novo synthesized and tested within 24 hours using an automated benchtop microarray synthesizer. This enables rapid prototyping and adaptation of the system to newly emerging targets such as pathogenic bacterial or viral subtypes. The system was evaluated by amplifying and detecting different loci of viral (HPV), bacterial (Bacillus sp.) and eukaryotic (human) genomes. Multiplex PCR and semi-quantitative detection with excellent detection limits of automation grade of the system reduces contamination risk and workload and should enhance safety and reproducibility. 2010 Elsevier B.V. All rights reserved.

  2. An Automatic Target Detection Algorithm for Swath Sonar Backscatter Imagery, Using Image Texture and Independent Component Analysis

    Directory of Open Access Journals (Sweden)

    Elias Fakiris

    2016-04-01

    Full Text Available In the present paper, a methodological scheme, bringing together common Acoustic Seabed Classification (ASC systems and a powerful data decomposition approach, called Independent Component Analysis (ICA, is demonstrated regarding its suitability for detecting small targets in Side Scan Sonar imagery. Traditional ASC systems extract numerous texture descriptors, leading to a large feature vector, the dimensionality of which is reduced by means of data decomposition techniques, usually Principal Component Analysis (PCA, prior to classification. However, in the target detection issue, data decomposition should point towards finding components that represent sub-ordinary image information (i.e., small targets rather than a dominant one. ICA has long been proved to be suitable for separating targets from a background, and this study represents a novel exhibition of its applicability to Side Scan Sonar (SSS images. The present study attempts to build a fully automated target detection approach that combines image based feature extraction, ICA, and unsupervised classification. The suitability of the proposed approach has been demonstrated using an SSS data-set containing more than 70 manmade targets, most of them metallic, validated through a marine magnetic survey or ground truthing inspection. The method exhibited very good performance as it was able to detect more than 77% of the targets and it produced less than seven false alarms per km2. Moreover, it was compared to cases where, in the exact same methodological scheme, no decomposition technique is used, or PCA is employed instead of ICA, achieving the highest detection rate, but, more importantly, producing more than six times less false alarms, thus proving that ICA successfully manages to maximize target to background separation.

  3. Disruptive camouflage tricks the human eye: a study of detection times of two near-similar targets in natural backgrounds

    Science.gov (United States)

    Selj, Gorm K.

    2015-10-01

    Our understanding of camouflage, in military as well as in evolutionary perspectives, has been developing over the last 100 years. In that period of time several underlying principles have emerged. It has turned out in the recent decade that background pattern matching alone may not be sufficient to conceal targets because of the ubiquitous and revealing information contained by the edges of a target. In this paper we have studied one concealment strategy, the so-called disruptive coloration, further as it predicts that high contrast patches placed at the target's outline will impede detection, by creating false target edges when exposed to the observer. Such disruptive coloration is contra-intuitive as it may impede detection in spite of the fact that the patches themselves may be poorly concealed. In military environments the "disruptive approach" within camouflage has been textbook material for decades. Still, very little has been reported, supporting this idea, especially when it comes to the concealment of human targets in natural sceneries. We report here experimental evidence from a field study, containing detection data from 12 unique natural scenes (5 testing the disruptive effect, 7 as reference tests), with both human targets and human observers, showing that disruptively colored camouflage patches along a human's outline (its head) may increase detection time significantly as when compared to a similar (human) target concealed only with background matching. Hence, our results support the idea that disruptive coloration may impede detection and similarly that the best concealment is achieved when disruptive coloration is added to a target that matches the background (reasonably) well. This study raises important question to the current understanding of human vision and concealment as well as to any approach to describe the human visual system mathematically.

  4. Development of an atmospheric infrared radiation model with high clouds for target detection

    Science.gov (United States)

    Bellisario, Christophe; Malherbe, Claire; Schweitzer, Caroline; Stein, Karin

    2016-10-01

    In the field of target detection, the simulation of the camera FOV (field of view) background is a significant issue. The presence of heterogeneous clouds might have a strong impact on a target detection algorithm. In order to address this issue, we present here the construction of the CERAMIC package (Cloudy Environment for RAdiance and MIcrophysics Computation) that combines cloud microphysical computation and 3D radiance computation to produce a 3D atmospheric infrared radiance in attendance of clouds. The input of CERAMIC starts with an observer with a spatial position and a defined FOV (by the mean of a zenithal angle and an azimuthal angle). We introduce a 3D cloud generator provided by the French LaMP for statistical and simplified physics. The cloud generator is implemented with atmospheric profiles including heterogeneity factor for 3D fluctuations. CERAMIC also includes a cloud database from the French CNRM for a physical approach. We present here some statistics developed about the spatial and time evolution of the clouds. Molecular optical properties are provided by the model MATISSE (Modélisation Avancée de la Terre pour l'Imagerie et la Simulation des Scènes et de leur Environnement). The 3D radiance is computed with the model LUCI (for LUminance de CIrrus). It takes into account 3D microphysics with a resolution of 5 cm-1 over a SWIR bandwidth. In order to have a fast computation time, most of the radiance contributors are calculated with analytical expressions. The multiple scattering phenomena are more difficult to model. Here a discrete ordinate method with correlated-K precision to compute the average radiance is used. We add a 3D fluctuations model (based on a behavioral model) taking into account microphysics variations. In fine, the following parameters are calculated: transmission, thermal radiance, single scattering radiance, radiance observed through the cloud and multiple scattering radiance. Spatial images are produced, with a

  5. Effect of unlabeled helper probes on detection of an RNA target by bead-based sandwich hybridization

    DEFF Research Database (Denmark)

    Barken, K.B.; Cabig-Ciminska, M.; Holmgren, A.

    2004-01-01

    Unlabeled helper oligonucleotides assisting a bead-based sandwich hybridization assay were tested for the optimal placement of the capture and detection probes. The target used was a full-length in vitro synthesized mRNA molecule. Helper probes complementary to regions adjacent to the binding site...... of the 5' end attached capture probe were found much more effective than helper probes targeting positions adjacent to the detection probe binding site. The difference is believed to be caused by a disruption of the RNA secondary structure in the area where the capture probe binds, thereby reducing...... structural interference from the bead. The use of additional helpers showed an additive effect. Using helpers, at both sides of the capture and detection probes showed a 15- to 40-fold increase in hybridization efficiency depending on the target, thereby increasing the sensitivity of the hybridization assays...

  6. Integration of bio-inspired, control-based visual and olfactory data for the detection of an elusive target

    Science.gov (United States)

    Duong, Tuan A.; Duong, Nghi; Le, Duong

    2017-01-01

    In this paper, we present an integration technique using a bio-inspired, control-based visual and olfactory receptor system to search for elusive targets in practical environments where the targets cannot be seen obviously by either sensory data. Bio-inspired Visual System is based on a modeling of extended visual pathway which consists of saccadic eye movements and visual pathway (vertebrate retina, lateral geniculate nucleus and visual cortex) to enable powerful target detections of noisy, partial, incomplete visual data. Olfactory receptor algorithm, namely spatial invariant independent component analysis, that was developed based on data of old factory receptor-electronic nose (enose) of Caltech, is adopted to enable the odorant target detection in an unknown environment. The integration of two systems is a vital approach and sets up a cornerstone for effective and low-cost of miniaturized UAVs or fly robots for future DOD and NASA missions, as well as for security systems in Internet of Things environments.

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

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2016-10-01

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

  8. HPV DNA target hybridization concentrations studies using interdigitated electrodes (IDE) for early detection of cervical cancer

    Science.gov (United States)

    Noriani, C.; Hashim, U.; Azizah, N.; Nadzirah, Sh.; Arshad, M. K. Md; Ruslinda, A. R.; Gopinath, Subash C. B.

    2017-03-01

    Human Papillomaviruses (HPV) is the major cause of cervical cancer. HPV 16 and HPV 18 are the two types of HPV are the most HPV-associated cancers and responsible as a high-risk HPV. Cervical cancer took about 70 percent of all cases due to HPV infections. Cervical cancer mostly growth on a woman's cervix and its was developed slowly as cancer. TiO2 particles give better performance and low cost of the biosensor. The used of 3-aminopropyl triethoxysilane (APTES) will be more efficient for DNA nanochip. APTES used as absorption reaction to immobilize organic biomolecules on the inorganic surface. Furthermore, APTES provide better functionalization of the adsorption mechanism on IDE. The surface functionalized for immobilizing the DNA, which is the combination of the DNA probe and the HPV target produces high sensitivity and speed detection of the IDE. The Current-Voltage (IV) characteristic proved the sensitivity of the DNA nanochip increase as the concentration varied from 0% concentration to 24% of APTES concentration.

  9. Detecting Target Objects by Natural Language Instructions Using an RGB-D Camera

    Directory of Open Access Journals (Sweden)

    Jiatong Bao

    2016-12-01

    Full Text Available Controlling robots by natural language (NL is increasingly attracting attention for its versatility, convenience and no need of extensive training for users. Grounding is a crucial challenge of this problem to enable robots to understand NL instructions from humans. This paper mainly explores the object grounding problem and concretely studies how to detect target objects by the NL instructions using an RGB-D camera in robotic manipulation applications. In particular, a simple yet robust vision algorithm is applied to segment objects of interest. With the metric information of all segmented objects, the object attributes and relations between objects are further extracted. The NL instructions that incorporate multiple cues for object specifications are parsed into domain-specific annotations. The annotations from NL and extracted information from the RGB-D camera are matched in a computational state estimation framework to search all possible object grounding states. The final grounding is accomplished by selecting the states which have the maximum probabilities. An RGB-D scene dataset associated with different groups of NL instructions based on different cognition levels of the robot are collected. Quantitative evaluations on the dataset illustrate the advantages of the proposed method. The experiments of NL controlled object manipulation and NL-based task programming using a mobile manipulator show its effectiveness and practicability in robotic applications.

  10. Masking of Time-Frequency Patterns in Applications of Passive Underwater Target Detection

    Directory of Open Access Journals (Sweden)

    Sildam Jüri

    2010-01-01

    Full Text Available Spectrogram analysis of acoustical sounds for underwater target classification is utilized when loud nonstationary interference sources overlap with a signal of interest in time but can be separated in time-frequency ( domain. We propose a signal masking method which in a plane combines local statistical and morphological features of the signal of interest. A dissimilarity measure of adjacent cells is used for local estimation of entropy , followed by estimation of entropy difference, where is calculated along the time axis at a mean frequency and is calculated along the frequency axis at a mean time of the window, respectively. Due to a limited number of points used in estimation, the number of possible values, which define a primary mask, is also limited. secondary mask is defined using morphological operators applied to, for example, and . We demonstrate how primary and secondary masks can be used for signal detection and discrimination, respectively. We also show that the proposed approach can be generalized within the framework of Genetic Programming.

  11. Human synthetic lethal inference as potential anti-cancer target gene detection

    Directory of Open Access Journals (Sweden)

    Solé Ricard V

    2009-12-01

    Full Text Available Abstract Background Two genes are called synthetic lethal (SL if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism's fitness. The detection of SL gene pairs constitutes a promising alternative for anti-cancer therapy. As cancer cells exhibit a large number of mutations, the identification of these mutated genes' SL partners may provide specific anti-cancer drug candidates, with minor perturbations to the healthy cells. Since existent SL data is mainly restricted to yeast screenings, the road towards human SL candidates is limited to inference methods. Results In the present work, we use phylogenetic analysis and database manipulation (BioGRID for interactions, Ensembl and NCBI for homology, Gene Ontology for GO attributes in order to reconstruct the phylogenetically-inferred SL gene network for human. In addition, available data on cancer mutated genes (COSMIC and Cancer Gene Census databases as well as on existent approved drugs (DrugBank database supports our selection of cancer-therapy candidates. Conclusions Our work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research. Novel SL screening analysis and the use of highly curated databases would contribute to improve the results of this methodology.

  12. Masking of Time-Frequency Patterns in Applications of Passive Underwater Target Detection

    Directory of Open Access Journals (Sweden)

    Jüri Sildam

    2010-01-01

    Full Text Available Spectrogram analysis of acoustical sounds for underwater target classification is utilized when loud nonstationary interference sources overlap with a signal of interest in time but can be separated in time-frequency (TF domain. We propose a signal masking method which in a TF plane combines local statistical and morphological features of the signal of interest. A dissimilarity measure D of adjacent TF cells is used for local estimation of entropy H, followed by estimation of ΔH=Htc−Hfc entropy difference, where Hfc is calculated along the time axis at a mean frequency fc and Htc is calculated along the frequency axis at a mean time tc of the TF window, respectively. Due to a limited number of points used in ΔH estimation, the number of possible ΔH values, which define a primary mask, is also limited. A secondary mask is defined using morphological operators applied to, for example, H and ΔH. We demonstrate how primary and secondary masks can be used for signal detection and discrimination, respectively. We also show that the proposed approach can be generalized within the framework of Genetic Programming.

  13. Impairment of novelty detection in mice targeted for the Chl1 gene.

    Science.gov (United States)

    Pratte, Michel; Jamon, Marc

    2009-06-22

    A deficit in cell adhesion molecules including the human Chl1 (close homologue of the L1 cell adhesion molecule) gene may cause impairment of cognitive processes. Aberrant connectivity in the CA3 region of the hippocampus has been reported in mice lacking the CHL1 protein after Chl1 gene targeting. Previous studies have observed a deficit in the processing of novel information by CHL1-deficient mice. We investigated deficits in spatial discrimination and object discrimination in three groups of mice--Chl1(+/+), Chl1(+/-) and Chl1(-/-)--performing spatial and object novelty tasks. The results indicated that wild-type mice easily recognized objects that were either "displaced" or "substituted". Chl1(-/-) mice showed severe impairment of the capacity to react to both spatial and non-spatial novelty. Chl1(+/-) mice were severely restricted in their ability to detect spatial changes, but succeeded in novel object discrimination. A dose-dependent sensitivity of the organization of the CA3 layer to the CHL1 protein may explain this result. However, the observations suggest that a dysfunction of parts of the brain other than the hippocampus may be involved in the impairment.

  14. M stars as targets for terrestrial exoplanet searches and biosignature detection.

    Science.gov (United States)

    Scalo, John; Kaltenegger, Lisa; Segura, Antígona; Segura, Ant Gona; Fridlund, Malcolm; Ribas, Ignasi; Kulikov, Yu N; Grenfell, John L; Rauer, Heike; Odert, Petra; Leitzinger, Martin; Selsis, F; Khodachenko, Maxim L; Eiroa, Carlos; Kasting, Jim; Lammer, Helmut

    2007-02-01

    The changing view of planets orbiting low mass stars, M stars, as potentially hospitable worlds for life and its remote detection was motivated by several factors, including the demonstration of viable atmospheres and oceans on tidally locked planets, normal incidence of dust disks, including debris disks, detection of planets with masses in the 5-20 M() range, and predictions of unusually strong spectral biosignatures. We present a critical discussion of M star properties that are relevant for the long- and short-term thermal, dynamical, geological, and environmental stability of conventional liquid water habitable zone (HZ) M star planets, and the advantages and disadvantages of M stars as targets in searches for terrestrial HZ planets using various detection techniques. Biological viability seems supported by unmatched very long-term stability conferred by tidal locking, small HZ size, an apparent short-fall of gas giant planet perturbers, immunity to large astrosphere compressions, and several other factors, assuming incidence and evolutionary rate of life benefit from lack of variability. Tectonic regulation of climate and dynamo generation of a protective magnetic field, especially for a planet in synchronous rotation, are important unresolved questions that must await improved geodynamic models, though they both probably impose constraints on the planet mass. M star HZ terrestrial planets must survive a number of early trials in order to enjoy their many Gyr of stability. Their formation may be jeopardized by an insufficient initial disk supply of solids, resulting in the formation of objects too small and/or dry for habitability. The small empirical gas giant fraction for M stars reduces the risk of formation suppression or orbit disruption from either migrating or nonmigrating giant planets, but effects of perturbations from lower mass planets in these systems are uncertain. During the first approximately 1 Gyr, atmospheric retention is at peril because of

  15. M Stars as Targets for Terrestrial Exoplanet Searches And Biosignature Detection

    Science.gov (United States)

    Scalo, John; Kaltenegger, Lisa; Segura, Ant Gona; Fridlund, Malcolm; Ribas, Ignasi; Kulikov, Yu. N.; Grenfell, John L.; Rauer, Hieke; Odert, Petra; Leitzinger, Martin; Selsis, F.; Khodachenko, Maxim L.; Eiroa, Carlos; Kasting, Jim; Lammer, Helmut

    2007-02-01

    The changing view of planets orbiting low mass stars, M stars, as potentially hospitable worlds for life and its remote detection was motivated by several factors, including the demonstration of viable atmospheres and oceans on tidally locked planets, normal incidence of dust disks, including debris disks, detection of planets with masses in the 5-20 M⊕ range, and predictions of unusually strong spectral biosignatures. We present a critical discussion of M star properties that are relevant for the long- and short-term thermal, dynamical, geological, and environmental stability of conventional liquid water habitable zone (HZ) M star planets, and the advantages and disadvantages of M stars as targets in searches for terrestrial HZ planets using various detection techniques. Biological viability seems supported by unmatched very long-term stability conferred by tidal locking, small HZ size, an apparent short-fall of gas giant planet perturbers, immunity to large astrosphere compressions, and several other factors, assuming incidence and evolutionary rate of life benefit from lack of variability. Tectonic regulation of climate and dynamo generation of a protective magnetic field, especially for a planet in synchronous rotation, are important unresolved questions that must await improved geodynamic models, though they both probably impose constraints on the planet mass. M star HZ terrestrial planets must survive a number of early trials in order to enjoy their many Gyr of stability. Their formation may be jeopardized by an insufficient initial disk supply of solids, resulting in the formation of objects too small and/or dry for habitability. The small empirical gas giant fraction for M stars reduces the risk of formation suppression or orbit disruption from either migrating or nonmigrating giant planets, but effects of perturbations from lower mass planets in these systems are uncertain. During the first ~1 Gyr, atmospheric retention is at peril because of intense and

  16. Quakefinder: A scalable data mining system for detecting earthquakes from space

    Energy Technology Data Exchange (ETDEWEB)

    Stolorz, P.; Dean, C. [California Inst. of Technology, Pasadena, CA (United States)

    1996-12-31

    We present an application of novel massively parallel datamining techniques to highly precise inference of important physical processes from remote sensing imagery. Specifically, we have developed and applied a system, Quakefinder, that automatically detects and measures tectonic activity in the earth`s crust by examination of satellite data. We have used Quakefinder to automatically map the direction and magnitude of ground displacements due to the 1992 Landers earthquake in Southern California, over a spatial region of several hundred square kilometers, at a resolution of 10 meters, to a (sub-pixel) precision of 1 meter. This is the first calculation that has ever been able to extract area-mapped information about 2D tectonic processes at this level of detail. We outline the architecture of the Quakefinder system, based upon a combination of techniques drawn from the fields of statistical inference, massively parallel computing and global optimization. We confirm the overall correctness of the procedure by comparison of our results with known locations of targeted faults obtained by careful and time-consuming field measurements. The system also performs knowledge discovery by indicating novel unexplained tectonic activity away from the primary faults that has never before been observed. We conclude by discussing the future potential of this data mining system in the broad context of studying subtle spatio-temporal processes within massive image streams.

  17. Targeted Metabolomics Approach To Detect the Misuse of Steroidal Aromatase Inhibitors in Equine Sports by Biomarker Profiling.

    Science.gov (United States)

    Chan, George Ho Man; Ho, Emmie Ngai Man; Leung, David Kwan Kon; Wong, Kin Sing; Wan, Terence See Ming

    2016-01-05

    The use of anabolic androgenic steroids (AAS) is prohibited in both human and equine sports. The conventional approach in doping control testing for AAS (as well as other prohibited substances) is accomplished by the direct detection of target AAS or their characteristic metabolites in biological samples using hyphenated techniques such as gas chromatography or liquid chromatography coupled with mass spectrometry. Such an approach, however, falls short when dealing with unknown designer steroids where reference materials and their pharmacokinetics are not available. In addition, AASs with fast elimination times render the direct detection approach ineffective as the detection window is short. A targeted metabolomics approach is a plausible alternative to the conventional direct detection approach for controlling the misuse of AAS in sports. Because the administration of AAS of the same class may trigger similar physiological responses or effects in the body, it may be possible to detect such administrations by monitoring changes in the endogenous steroidal expression profile. This study attempts to evaluate the viability of using the targeted metabolomics approach to detect the administration of steroidal aromatase inhibitors, namely androst-4-ene-3,6,17-trione (6-OXO) and androsta-1,4,6-triene-3,17-dione (ATD), in horses. Total (free and conjugated) urinary concentrations of 31 endogenous steroids were determined by gas chromatography-tandem mass spectrometry for a group of 2 resting and 2 in-training thoroughbred geldings treated with either 6-OXO or ATD. Similar data were also obtained from a control (untreated) group of in-training thoroughbred geldings (n = 28). Statistical processing and chemometric procedures using principle component analysis and orthogonal projection to latent structures-discriminant analysis (OPLS-DA) have highlighted 7 potential biomarkers that could be used to differentiate urine samples obtained from the control and the treated groups

  18. Passive Coherent Detection and Target Location with Multiple Non-Cooperative Transmitters

    Science.gov (United States)

    2015-06-01

    16 1. Bistatic Radar Trigonometry ............................................................16 2. Least-Squares... Trigonometry The AOA of the target echo signal R and target-to-receiver range RR are required to define the target’s location with respect to the

  19. A programmable Y-shaped junction scaffold-mediated modular and cascade amplification strategy for the one-step, isothermal and ultrasensitive detection of target DNA.

    Science.gov (United States)

    Liu, Shufeng; Gong, Hongwei; Sun, Xinya; Liu, Tao; Wang, Li

    2015-12-28

    The programmable DNA polymerization across the two branches of the assembled Y-shaped junction was ingeniously manipulated for modular target recycling and cascade lambda exonuclease cleavage, which afforded the one-pot, isothermal and ultrasensitive detection of target DNA. A low detection limit of 28.2 fM of target DNA with an excellent selectivity could be obtained.

  20. Genetic polymorphisms regulating dopamine signaling in the frontal cortex interact to affect target detection under high working memory load.

    Science.gov (United States)

    Smith, Christopher T; Swift-Scanlan, Theresa; Boettiger, Charlotte A

    2014-02-01

    Frontal-dependent task performance is typically modulated by dopamine (DA) according to an inverted-U pattern, whereby intermediate levels of DA signaling optimizes performance. Numerous studies implicate trait differences in DA signaling based on differences in the catechol-O-methyltransferase (COMT) gene in executive function task performance. However, little work has investigated genetic variations in DA signaling downstream from COMT. One candidate is the DA- and cAMP-regulated phosphoprotein of molecular weight 32 kDa (DARPP-32), which mediates signaling through the D1-type DA receptor, the dominant DA receptor in the frontal cortex. Using an n-back task, we used signal detection theory to measure performance in a healthy adult population (n = 97) genotyped for single nucleotide polymorphisms in the COMT (rs4680) and DARPP-32 (rs907094) genes. Correct target detection (hits) and false alarms were used to calculate d' measures for each working memory load (0-, 2-, and 3-back). At the highest load (3-back) only, we observed a significant COMT × DARPP-32 interaction, such that the DARPP-32 T/T genotype enhanced target detection in COMT(ValVal) individuals, but impaired target detection in COMT(Met) carriers. These findings suggest that enhanced dopaminergic signaling via the DARPP-32 T allele aids target detection in individuals with presumed low frontal DA (COMT(ValVal)) but impairs target detection in those with putatively higher frontal DA levels (COMT(Met) carriers). Moreover, these data support an inverted-U model with intermediate levels of DA signaling optimizing performance on tasks requiring maintenance of mental representations in working memory.

  1. Time-reversal optical tomography: detecting and locating extended targets in a turbid medium

    Science.gov (United States)

    Wu, Binlin; Cai, W.; Xu, M.; Gayen, S. K.

    2012-03-01

    Time Reversal Optical Tomography (TROT) is developed to locate extended target(s) in a highly scattering turbid medium, and estimate their optical strength and size. The approach uses Diffusion Approximation of Radiative Transfer Equation for light propagation along with Time Reversal (TR) Multiple Signal Classification (MUSIC) scheme for signal and noise subspaces for assessment of target location. A MUSIC pseudo spectrum is calculated using the eigenvectors of the TR matrix T, whose poles provide target locations. Based on the pseudo spectrum contours, retrieval of target size is modeled as an optimization problem, using a "local contour" method. The eigenvalues of T are related to optical strengths of targets. The efficacy of TROT to obtain location, size, and optical strength of one absorptive target, one scattering target, and two absorptive targets, all for different noise levels was tested using simulated data. Target locations were always accurately determined. Error in optical strength estimates was small even at 20% noise level. Target size and shape were more sensitive to noise. Results from simulated data demonstrate high potential for application of TROT in practical biomedical imaging applications.

  2. Detection of prion protein in urine-derived injectable fertility products by a targeted proteomic approach.

    Directory of Open Access Journals (Sweden)

    Alain Van Dorsselaer

    Full Text Available BACKGROUND: Iatrogenic transmission of human prion disease can occur through medical or surgical procedures, including injection of hormones such as gonadotropins extracted from cadaver pituitaries. Annually, more than 300,000 women in the United States and Canada are prescribed urine-derived gonadotropins for infertility. Although menopausal urine donors are screened for symptomatic neurological disease, incubation of Creutzfeldt-Jakob disease (CJD is impossible to exclude by non-invasive testing. Risk of carrier status of variant CJD (vCJD, a disease associated with decades-long peripheral incubation, is estimated to be on the order of 100 per million population in the United Kingdom. Studies showing infectious prions in the urine of experimental animals with and without renal disease suggest that prions could be present in asymptomatic urine donors. Several human fertility products are derived from donated urine; recently prion protein has been detected in preparations of human menopausal gonadotropin (hMG. METHODOLOGY/PRINCIPAL FINDINGS: Using a classical proteomic approach, 33 and 34 non-gonadotropin proteins were identified in urinary human chorionic gonadotropin (u-hCG and highly-purified urinary human menopausal gonadotropin (hMG-HP products, respectively. Prion protein was identified as a major contaminant in u-hCG preparations for the first time. An advanced prion protein targeted proteomic approach was subsequently used to conduct a survey of gonadotropin products; this approach detected human prion protein peptides in urine-derived injectable fertility products containing hCG, hMG and hMG-HP, but not in recombinant products. CONCLUSIONS/SIGNIFICANCE: The presence of protease-sensitive prion protein in urinary-derived injectable fertility products containing hCG, hMG, and hMG-HP suggests that prions may co-purify in these products. Intramuscular injection is a relatively efficient route of transmission of human prion disease, and

  3. Meteoroid Impact Detection for Exploration of Asteroids (MIDEA): Meteoroid Impact Rates on Potential Asteroid Targets

    Science.gov (United States)

    Lee, N.; Close, S.

    2016-12-01

    Meteoroid impacts on asteroid surfaces produce a plasma that can be sampled by a nearby spacecraft. This plasma provides a mechanism for exploring the surface composition of asteroids using a constellation of free-flying, ultralight sensors. The requirements for detection of the expanding impact plasma is that the meteoroid is large and fast enough to produce sufficient charge, and that the asteroid surface is electrically biased so that the electrons are captured and positive ions are ejected. For a sensor positioned at a distance of 100-500 m, nanogram-sized meteoroids impacting at speeds greater than 20 km/s onto a sunlit surface can produce a detectable signal. We used NASA's Meteoroid Engineering Model (MEM) and the Grün interplanetary flux model to estimate the impact rate of meteoroids on a selection of asteroid candidates. These include near-Earth asteroids (NEAs) as well as several bodies in the main belt. Orbital trajectories were obtained using JPL's Horizons interface, and the sunward-facing meteoroid flux was computed using MEM for µg-sized meteoroids at speeds of 20 km/s or greater. The Grün model was used to scale the flux to ng-sized meteoroids. The figure below shows the maximum and minimum impact rate for each of the target bodies, ordered by their orbital semi-major axis. The NEAs have maximum rates of 0.18 to 0.30 m-2 day-1, corresponding to an impact on each square meter every 3.3 to 5.4 days. The main-belt bodies are impacted far less frequently. However, 1999 JD8, which has a high eccentricity of 0.47, has a maximum impact rate about ten times greater than Elst-Pizarro, despite having a similar semi-major axis. Because of the gossamer nature of the ultralight sensors envisioned for this exploration concept, mission duration is limited by degradation of the electronics. The impacts predicted for NEAs and for some high-eccentricity asteroids in the main belt are frequent enough to allow an asteroid to be well characterized in under a month.

  4. Phenylboronic Acid Templated Gold Nanoclusters for Mucin Detection Using a Smartphone-Based Device and Targeted Cancer Cell Theranostics.

    Science.gov (United States)

    Dutta, Deepanjalee; Sailapu, Sunil Kumar; Chattopadhyay, Arun; Ghosh, Siddhartha Sankar

    2018-01-18

    A phenylboronic acid templated gold nanocluster probe was developed to detect biomarker mucin by a noninvasive fluorescence-based method using a point-of-care smartphone-based fluorescence detection device. The gold nanocluster probe is able to detect mucin specifically. The same probe was applied for in vitro targeted bioimaging of HeLa and Hep G2 cancer cells, and it demonstrated specific therapeutic effects toward cancer cells as well as multicellular tumor spheroids imparting theranostic properties. The module is found to be more effective toward HeLa cells, and a pathway of cell death was established using flow-cytometry-based assays.

  5. Detection of stimulus displacements across saccades is capacity-limited and biased in favor of the saccade target

    Directory of Open Access Journals (Sweden)

    David E. Irwin

    2015-11-01

    Full Text Available Retinal image displacements caused by saccadic eye movements are generally unnoticed. Recent theories have proposed that perceptual stability across saccades depends on a local evaluation process centered on the saccade target object rather than on remapping and evaluating the positions of all objects in a display. In 3 experiments we examined whether objects other than the saccade target also influence perceptual stability by measuring displacement detection thresholds across saccades for saccade targets and a variable number of non-saccade objects. We found that the positions of multiple objects are maintained across saccades, but with variable precision, with the saccade target object having priority in the perception of displacement, most likely because it is the focus of attention before the saccade and resides near the fovea after the saccade. The perception of displacement of objects that are not the saccade target is affected by acuity limitations, attentional limitations, and limitations on memory capacity. Unlike previous studies that have found that a postsaccadic blank improves the detection of displacement direction across saccades, we found that postsaccadic blanking hurt the detection of displacement per se by increasing false alarms. Overall, our results are consistent with the hypothesis that visual working memory underlies the perception of stability across saccades.

  6. Development of Real Time PCR Using Novel Genomic Target for Detection of Multiple Salmonella Serovars from Milk and Chickens

    Science.gov (United States)

    Background: A highly sensitive and specific novel genomic and plasmid target-based PCR platform was developed to detect multiple Salmonella serovars (S. Heidelberg, S. Dublin, S. Hadar, S. Kentucky and S. Enteritidis). Through extensive genome mining of protein databases of these serovars and compar...

  7. Fast Detection of Compressively Sensed IR Targets Using Stochastically Trained Least Squares and Compressed Quadratic Correlation Filters

    KAUST Repository

    Millikan, Brian

    2017-05-02

    Target detection of potential threats at night can be deployed on a costly infrared focal plane array with high resolution. Due to the compressibility of infrared image patches, the high resolution requirement could be reduced with target detection capability preserved. For this reason, a compressive midwave infrared imager (MWIR) with a low-resolution focal plane array has been developed. As the most probable coefficient indices of the support set of the infrared image patches could be learned from the training data, we develop stochastically trained least squares (STLS) for MWIR image reconstruction. Quadratic correlation filters (QCF) have been shown to be effective for target detection and there are several methods for designing a filter. Using the same measurement matrix as in STLS, we construct a compressed quadratic correlation filter (CQCF) employing filter designs for compressed infrared target detection. We apply CQCF to the U.S. Army Night Vision and Electronic Sensors Directorate dataset. Numerical simulations show that the recognition performance of our algorithm matches that of the standard full reconstruction methods, but at a fraction of the execution time.

  8. Target Detection Method for Water Mapping Using Landsat 8 OLI/TIRS Imagery

    Directory of Open Access Journals (Sweden)

    Luyan Ji

    2015-02-01

    Full Text Available Extracting surface water distribution with satellite imagery has been an important subject in remote sensing. Spectral indices of water only use information from a limited number of bands, thus they may have poor performance from pixels contaminated by ice/snow, clouds, etc. The detection algorithms using information from all spectral bands, such as constrained energy minimization (CEM, could avoid this problem to some extent. However, these are mostly designed for hyperspectral imagery, and may fail when applied to multispectral data. It has been proved that adding linearly irrelevant data to original data could improve the performance of CEM. In this study, two kinds of linearly irrelevant data are added for water extraction: the spectral indices and the spectral similarity metric data. CEM is designed for targets with low-probability distribution in an image, but water bodies do not always satisfy this condition. We thereby impose a sensible coefficient for each pixel to form the weighted autocorrelation matrix. In this study, the weight is based on the orthogonal subspace projection, so this new method is named Orthogonal subspace projection Weighted CEM (OWCEM. The newly launched Landsat 8 images over two lakes, the Hala Lake in China with ice/snow distributed in the north, and the Huron Lake in North America, a lake with a very large surface area, are selected to test the accuracy and robustness of our algorithm. The Kappa coefficient and the receiver operating characteristic (ROC curve are calculated as an accuracy evaluation standard. For both lakes, our method can greatly suppress the background (including ice/snow and clouds and extract the complete water surface with a high accuracy (Kappa coefficient > 0.96.

  9. Performance Evaluation of Target Detection with a Near-Space Vehicle-Borne Radar in Blackout Condition.

    Science.gov (United States)

    Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Deng, Bin; Qin, Yuliang

    2016-01-06

    Radar is a very important sensor in surveillance applications. Near-space vehicle-borne radar (NSVBR) is a novel installation of a radar system, which offers many benefits, like being highly suited to the remote sensing of extremely large areas, having a rapidly deployable capability and having low vulnerability to electronic countermeasures. Unfortunately, a target detection challenge arises because of complicated scenarios, such as nuclear blackout, rain attenuation, etc. In these cases, extra care is needed to evaluate the detection performance in blackout situations, since this a classical problem along with the application of an NSVBR. However, the existing evaluation measures are the probability of detection and the receiver operating curve (ROC), which cannot offer detailed information in such a complicated application. This work focuses on such requirements. We first investigate the effect of blackout on an electromagnetic wave. Performance evaluation indexes are then built: three evaluation indexes on the detection capability and two evaluation indexes on the robustness of the detection process. Simulation results show that the proposed measure will offer information on the detailed performance of detection. These measures are therefore very useful in detecting the target of interest in a remote sensing system and are helpful for both the NSVBR designers and users.

  10. Sub-pixel spatial resolution wavefront phase imaging

    Science.gov (United States)

    Stahl, H. Philip (Inventor); Mooney, James T. (Inventor)

    2012-01-01

    A phase imaging method for an optical wavefront acquires a plurality of phase images of the optical wavefront using a phase imager. Each phase image is unique and is shifted with respect to another of the phase images by a known/controlled amount that is less than the size of the phase imager's pixels. The phase images are then combined to generate a single high-spatial resolution phase image of the optical wavefront.

  11. RGD-targeted paramagnetic liposomes for early detection of tumor: In vitro and in vivo studies

    Energy Technology Data Exchange (ETDEWEB)

    Li Wei; Su Bo; Meng Shuyan; Ju Lixia; Yan Linghua; Ding Yongmei; Song Yin; Zhou Wei; Li Heyan; Tang Liang; Zhao Yinmin [Research Institute of Oncology, Tongji University Medical School, 507 Zhenmin Road, Shanghai 200433 (China); Zhou Caicun, E-mail: caicunzhou@yahoo.com.cn [Research Institute of Oncology, Tongji University Medical School, 507 Zhenmin Road, Shanghai 200433 (China)

    2011-11-15

    Magnetic resonance molecular imaging has emerged as a potential approach for tumor diagnosis in the last few decades. This approach consists of the delivery of MR contrast agents to the tumor by specific targeted carriers. For this purpose, a lipopeptide was constructed by using a cyclic RGD peptide headgroup coupled to palmitic acid anchors via a KGG tripeptide spacer. Targeted paramagnetic liposomes were then prepared by the incorporation of RGD-coupled-lipopeptides into lipid bilayers for specific bounding to tumor. In vitro, study demonstrated that RGD-targeted liposomes exhibited a better binding affinity to targeted cells than non-targeted liposomes. MR imaging of mice bearing A549 tumors with the RGD-targeted paramagnetic liposomes also resulted in a greater signal enhancement of tumor compared to non-targeted liposomes and pure contrast agents groups. In addition, biodistribution study also showed specific tumor targeting of RGD-targeted paramagnetic liposomes in vivo. Therefore, RGD-targeted paramagnetic liposomes prepared in the present study may be a more promising method for early tumor diagnosis.

  12. Monte Carlo simulations as a tool to optimize target detection by AUV/ROV laser line scanners

    Science.gov (United States)

    Montes-Hugo, Martin A.; Carder, Kendall

    2005-05-01

    The widespread use of laser line scanners (LLS) aboard autonomous underwater vehicles (AUV) and remotely operated vehicles (ROV) in the last decade has opened a unique window to a series of homeland security applications. Numerical experiments were performed to calculate the target signal and the effect of background medium (bottom, water) signals on target identification of fan-type LLS (Real-time Ocean Bottom Optical Topographer, ROBOT). Several 2-D Monte Carlo simulations were run with various bottom albedos, optical properties of the water, laser wavelengths, target distances, and source-detector angles. A forward 1-D Monte Carlo model was validated using Hydrolight based on upwelling and downwelling irradiance values computed at different depths. Signal/noise values (S/N) at the ROBOT detector were obtained by dividing the target peak by the path-radiance peak for each line-spread function. Since bottom-target reflectance was assumed Lambertian, target contribution was symmetrical with respect to the center of the target. Conversely, background contributions evidenced a bulge on the path radiance side of the target center, which was more apparent at higher turbidities. As expected, S/N values were higher when ROBOT was closer to the target. For daylight simulations, system noise includes both LLS path radiance and environmental path and target radiances because they reduce the laser-line contrast. The Hybrid marine optical model (HyMOM) provided the environmental radiance field. Optimum target detection based on laser wavelength and source-detector angle will depend on chosen ambient light conditions and AUV-ROVs altitude settings.

  13. Imporved method for stereo vision-based human detection for a mobile robot following a target person

    Directory of Open Access Journals (Sweden)

    Ali, Badar

    2015-05-01

    Full Text Available Interaction between humans and robots is a fundamental need for assistive and service robots. Their ability to detect and track people is a basic requirement for interaction with human beings. This article presents a new approach to human detection and targeted person tracking by a mobile robot. Our work is based on earlier methods that used stereo vision-based tracking linked directly with Hu moment-based detection. The earlier technique was based on the assumption that only one person is present in the environment – the target person – and it was not able to handle more than this one person. In our novel method, we solved this problem by using the Haar-based human detection method, and included a target person selection step before initialising tracking. Furthermore, rather than linking the Kalman filter directly with human detection, we implemented the tracking method before the Kalman filter-based estimation. We used the Pioneer 3AT robot, equipped with stereo camera and sonars, as the test platform.

  14. In situ detection of denitrifying bacteria by mRNA-targeted nucleic acid probes and catalyzed reporter deposition

    DEFF Research Database (Denmark)

    Kofoed, Michael Vedel; Stief, Peter; Poulsen, Morten

    reduction of nitrate to dinitrogen gas, is essential for the removal of fixed nitrogen from natural and engineered ecosystems. However, community structure and activity dynamics of denitrifying bacteria in most systems are poorly understood, partially due to difficulties in identifying and quantifying...... (active) denitrifiers. The goal of this study was therefore to develop a protocol for the in situ detection of denitrifying bacterial cells by targeting the mRNA of denitrification genes, hereby linking denitrification activity directly to the single-cell level. Target genes were narG (encoding nitrate...... reductase) and nosZ (encoding nitrous oxide reductase), to detect nitrate-reducing and completely denitrifying bacteria, respectively. Enzyme-labelled oligonucleotide probes and digoxygenin-labelled polynucleotide probes were evaluated for in situ hybridization in combination with immunochemical detection...

  15. Development of a qualitative real-time PCR method to detect 19 targets for identification of genetically modified organisms.

    Science.gov (United States)

    Peng, Cheng; Wang, Pengfei; Xu, Xiaoli; Wang, Xiaofu; Wei, Wei; Chen, Xiaoyun; Xu, Junfeng

    2016-01-01

    As the amount of commercially available genetically modified organisms (GMOs) grows recent years, the diversity of target sequences for molecular detection techniques are eagerly needed. Considered as the gold standard for GMO analysis, the real-time PCR technology was optimized to produce a high-throughput GMO screening method. With this method we can detect 19 transgenic targets. The specificity of the assays was demonstrated to be 100 % by the specific amplification of DNA derived from reference material from 20 genetically modified crops and 4 non modified crops. Furthermore, most assays showed a very sensitive detection, reaching the limit of ten copies. The 19 assays are the most frequently used genetic elements present in GM crops and theoretically enable the screening of the known GMO described in Chinese markets. Easy to use, fast and cost efficient, this method approach fits the purpose of GMO testing laboratories.

  16. Method for detecting binding efficiencies of synthetic oligonucleotides: Targeting bacteria and insects

    Science.gov (United States)

    Expanding applications of gene-based targeting biotechnology in functional genomics and the treatment of plants, animals, and microbes has synergized the need for new methods to measure binding efficiencies of these products to their genetic targets. The adaptation and innovative use of Cell–Penetra...

  17. Electrochemical detection of protein by using magnetic graphene-based target enrichment and copper nanoparticles-assisted signal amplification.

    Science.gov (United States)

    Zhao, Jing; Lv, Yun; Kang, Mingyang; Wang, Keming; Xiang, Yang

    2015-11-21

    In this paper, we propose a new method for protein detection by making use of magnetic graphene for enrichment and separation of the targets and duplex DNA-templated copper nanoparticles for amplification of electrochemical signals. Because the binding of the target protein (e.g. folate receptor) and small molecule (e.g. folate) can protect complementary DNA (cDNA) from exonuclease III-catalyzed degradation, duplex DNA from the hybridization of probe DNA and cDNA can act as the template for the formation of copper nanoparticles (CuNPs). Afterward, CuNPs-coated DNA can be enriched on the surface of magnetic graphene through the 3'-overhanging end of probe DNA, and then separated from the reaction mixture with the aid of magnet. As a result, copper ions released from acid-dissolution of CuNPs can catalyze the oxidation of o-phenylenediamine (OPD) by dissolved oxygen, resulting in an amplified electrochemical response. Our method can sensitively detect target protein over a wide linear range and with a low detection limit of 7.8 pg mL(-1), which can easily distinguish the targets even in complex serum samples. Therefore, this method may be promising for the clinical diagnosis of protein biomarkers by changing the recognition elements in the future.

  18. Early detection of malaria foci for targeted interventions in endemic southern Zambia

    Directory of Open Access Journals (Sweden)

    Chime Nnenna

    2011-09-01

    Full Text Available Abstract Background Zambia has achieved significant reductions in the burden of malaria through a strategy of "scaling-up" effective interventions. Progress toward ultimate malaria elimination will require sustained prevention coverage and further interruption of transmission through active strategies to identify and treat asymptomatic malaria reservoirs. A surveillance system in Zambia's Southern Province has begun to implement such an approach. An early detection system could be an additional tool to identify foci of elevated incidence for targeted intervention. Methods Based on surveillance data collected weekly from 13 rural health centres (RHCs divided into three transmission zones, early warning thresholds were created following a technique successfully implemented in Thailand. Alert levels were graphed for all 52 weeks of a year using the mean and 95% confidence interval upper limit of a Poisson distribution of the weekly diagnosed malaria cases for every available week of historic data (beginning in Aug, 2008 at each of the sites within a zone. Annually adjusted population estimates for the RHC catchment areas served as person-time of weekly exposure. The zonal threshold levels were validated against the incidence data from each of the 13 respective RHCs. Results Graphed threshold levels for the three zones generally conformed to observed seasonal incidence patterns. Comparing thresholds with historic weekly incidence values, the overall percentage of aberrant weeks ranged from 1.7% in Mbabala to 36.1% in Kamwanu. For most RHCs, the percentage of weeks above threshold was greater during the high transmission season and during the 2009 year compared to 2010. 39% of weeks breaching alert levels were part of a series of three or more consecutive aberrant weeks. Conclusions The inconsistent sensitivity of the zonal threshold levels impugns the reliability of the alert system. With more years of surveillance data available, individual

  19. Remote ballistic emplacement of an electro-optical and acoustic target detection and localization system

    Science.gov (United States)

    West, Aaron; Mellini, Mark

    2015-05-01

    Near real time situational awareness in uncontrolled non line of sight (NLOS) and beyond line of sight (BLOS) environments is critical in the asymmetric battlefield of future conflicts. The ability to detect and accurately locate hostile forces in difficult terrain or urban environments can dramatically increase the survivability and effectiveness of dismounted soldiers, especially when they are limited to the resources available only to the small unit. The Sensor Mortar Network (SMortarNet) is a 60mm Intelligence, Surveillance, and Reconnaissance (ISR) mortar designed to give the Squad near real time situational awareness in uncontrolled NLOS environments. SMortarNet is designed to track targets both acoustically and electro optically and can fuse tracks between, the acoustic, EO, and magnetic modalities on board. The system is linked to other mortar nodes and the user via a masterless frequency hopping spread spectrum ad-hoc mesh radio network. This paper will discuss SMortarNet in the context of a squad level dismounted soldier, its technical capabilities, and its benefit to the small unit Warfighter. The challenges with ballistic remote emplacement of sensitive components and the on board signal processing capabilities of the system will also be covered. The paper will also address how the sensor network can be integrated with existing soldier infrastructure, such as the NettWarrior platform, for rapid transition to soldier systems. Networks of low power sensors can have many forms, but the more practical networks for warfighters are ad hoc radio-based systems that can be rapidly deployed and can leverage a range of assets available at a given time. The low power long life networks typically have limited bandwidth and may have unreliable communication depending on the network health, which makes autonomous sensors a critical component of the network. SMortarNet reduces data to key information features at the sensor itself. The smart sensing approach enables

  20. Discriminating between camouflaged targets by their time of detection by a human-based observer assessment method

    Science.gov (United States)

    Selj, G. K.; Søderblom, M.

    2015-10-01

    Detection of a camouflaged object in natural sceneries requires the target to be distinguishable from its local background. The development of any new camouflage pattern therefore has to rely on a well-founded test methodology - which has to be correlated with the final purpose of the pattern - as well as an evaluation procedure, containing the optimal criteria for i) discriminating between the targets and then eventually ii) for a final rank of the targets. In this study we present results from a recent camouflage assessment trial where human observers were used in a search by photo methodology to assess generic test camouflage patterns. We conducted a study to investigate possible improvements in camouflage patterns for battle dress uniforms. The aim was to do a comparative study of potential, and generic patterns intended for use in arid areas (sparsely vegetated, semi desert). We developed a test methodology that was intended to be simple, reliable and realistic with respect to the operational benefit of camouflage. Therefore we chose to conduct a human based observer trial founded on imagery of realistic targets in natural backgrounds. Inspired by a recent and similar trial in the UK, we developed new and purpose-based software to be able to conduct the observer trial. Our preferred assessment methodology - the observer trial - was based on target recordings in 12 different, but operational relevant scenes, collected in a dry and sparsely vegetated area (Rhodes). The scenes were chosen with the intention to span as broadly as possible. The targets were human-shaped mannequins and were situated identically in each of the scenes to allow for a relative comparison of camouflage effectiveness in each scene. Test of significance, among the targets' performance, was carried out by non-parametric tests as the corresponding time of detection distributions in overall were found to be difficult to parameterize. From the trial, containing 12 different scenes from

  1. Fusion of forward-looking infrared camera and down-looking ground penetrating radar for buried target detection

    Science.gov (United States)

    Yuksel, Seniha E.; Akar, Gozde Bozdagi; Ozturk, Serhat

    2015-05-01

    In this paper, we propose a system to detect buried disk-shaped landmines from ground penetrating radar (GPR) and forward-looking long wave infrared (FL-LWIR) data. The data is collected from a test area of 500m2, which was prepared at the IPA Defence, Ankara, Turkey. This test area was divided into four lanes, each of size 25m length by 4m width and 1m depth. Each lane was first carefully cleaned of stones and clutter and then filled with different soil types, namely fine-medium sand, course sand, sandy silt loam and loam mix. In all lanes, various clutter objects and landmines were buried at different depths and at 1meter intervals. In the proposed approach, IR data is used as a pre-screener. Then possible target regions are further analyzed using the GPR data. IR data processing is done in three steps such as preprocessing, target detection, and postprocessing. In the pre-processing stage, bilateral noise reduction filtering is performed. The target detection stage finds circular targets by a radial transformation algorithm. The proposed approach is compared with the RX algorithm used widely for anomaly detection. The suspicious regions are further analyzed using Histogram of Oriented Gradient (HOG) features that are extracted from GPR images and classified by SVM. The same approach can also be applied in a parallel way where the results are combined using decision level fusion. The results of the proposed approach are given on different scenarios including different weather temperature and depth of buried targets.

  2. Somatic copy number alterations detected by ultra-deep targeted sequencing predict prognosis in oral cavity squamous cell carcinoma.

    Science.gov (United States)

    Peng, Chien-Hua; Liao, Chun-Ta; Ng, Ka-Pou; Tai, An-Shun; Peng, Shih-Chi; Yeh, Jen-Pao; Chen, Shu-Jen; Tsao, Kuo-Chien; Yen, Tzu-Chen; Hsieh, Wen-Ping

    2015-08-14

    Ultra-deep targeted sequencing (UDT-Seq) has advanced our knowledge on the incidence and functional significance of somatic mutations. However, the utility of UDT-Seq in detecting copy number alterations (CNAs) remains unclear. With the goal of improving molecular prognostication and identifying new therapeutic targets, we designed this study to assess whether UDT-Seq may be useful for detecting CNA in oral cavity squamous cell carcinoma (OSCC). We sequenced a panel of clinically actionable cancer mutations in 310 formalin-fixed paraffin-embedded OSCC specimens. A linear model was developed to overcome uneven coverage across target regions and multiple samples. The 5-year rates of secondary primary tumors, local recurrence, neck recurrence, distant metastases, and survival served as the outcome measures. We confirmed the prognostic significance of the CNA signatures in an independent sample of 105 primary OSCC specimens. The CNA burden across 10 targeted genes was found to predict prognosis in two independent cohorts. FGFR1 and PIK3CAamplifications were associated with prognosis independent of clinical risk factors. Genes exhibiting CNA were clustered in the proteoglycan metabolism, the FOXO signaling, and the PI3K-AKT signaling pathways, for which targeted drugs are already available or currently under development. UDT-Seq is clinically useful to identify CNA, which significantly improve the prognostic information provided by traditional clinicopathological risk factors in OSCC patients.

  3. A Review on Hot-IP Finding Methods and Its Application in Early DDoS Target Detection

    Directory of Open Access Journals (Sweden)

    Xuan Dau Hoang

    2016-10-01

    Full Text Available On the high-speed connections of the Internet or computer networks, the IP (Internet Protocol packet traffic passing through the network is extremely high, and that makes it difficult for network monitoring and attack detection applications. This paper reviews methods to find the high-occurrence-frequency elements in the data stream and applies the most efficient methods to find Hot-IPs that are high-frequency IP addresses of IP packets passing through the network. Fast finding of Hot-IPs in the IP packet stream can be effectively used in early detection of DDoS (Distributed Denial of Service attack targets and spreading sources of network worms. Research results show that the Count-Min method gives the best overall performance for Hot-IP detection thanks to its low computational complexity, low space requirement and fast processing speed. We also propose an early detection model of DDoS attack targets based on Hot-IP finding, which can be deployed on the target network routers.

  4. Sensitive detection of soy (Glycine max) by real-time polymerase chain reaction targeting the mitochondrial atpA gene.

    Science.gov (United States)

    Bauer, Tobias; Kirschbaum, Katja; Panter, Silvia; Kenk, Marion; Bergemann, Jörg

    2011-01-01

    Detection of trace amounts of allergens is essential for correct labeling of food products by the food industry. PCR-based detection methods currently used for this purpose are targeting sequences of DNA present in the cell nucleus. In addition to nuclear DNA, a substantial amount of mitochondrial DNA (mtDNA) copies are present in the cytoplasm of eukaryotic cells. The nuclear DNA usually consists of a set of DNA molecules present in two copies per cell, whereas mitochondrial DNA is present in a few hundred copies per cell. Thus, an increase in sensitivity can be expected when mtDNA is used as the target. In this study, we present a reporter probe-based real-time PCR method amplifying the mitochondrial gene of the alpha chain of adenosine triphosphate synthetase from soy. Increase in sensitivity was examined by determining the minimal amount of soy DNA detectable by mtDNA and nuclear DNA (nDNA) amplification. Additionally, the LOD of soy in a food matrix was determined for mtDNA amplification and compared to the LOD determined by nDNA amplification. As food matrix, a model spice spiked with soy flour was used. Sensitivity of PCR-based soy detection can be increased by using mtDNA as the target.

  5. Novel targets for detection of cancer and their modulation by chemopreventive natural compounds.

    Science.gov (United States)

    Ahmad, Aamir; Sakr, Wael A; Rahman, K M Wahidur

    2012-01-01

    Cancer affects the lives of millions of people. Several signaling pathways have been proposed as therapeutic targets for cancer therapy, and many more continue to be validated. With the identification and validation of therapeutic targets comes the question of designing novel strategies to effectively counter such targets. Natural compounds from dietary sources form the basis of many ancient medicinal systems. They are pleiotropic i.e. they act on multiple targets, and, therefore, are often the first agents to be tested against a novel therapeutic target. This review article summarizes the knowledge so far on some actively pursued targets - Notch, CXCR4, Wnt and sonic hedgehog (shh) pathways, the process of epithelial-mesenchymal transition (EMT) as well as molecular markers such as uPA-uPAR, survivin, FoxM1, and the microRNAs. We have performed an extensive survey of literature to list modulation of these targets by natural agents such as curcumin, indole-3-carbinol (I3C), 3,3'-diindolylmethane (DIM), resveratrol, epigallocatechin-3-gallate (EGCG), genistein etc. We believe that this review will stimulate further research for elucidating and appreciating the value of these wonderful gifts from nature.

  6. An iterative and targeted sampling design informed by habitat suitability models for detecting focal plant species over extensive areas.

    Science.gov (United States)

    Wang, Ophelia; Zachmann, Luke J; Sesnie, Steven E; Olsson, Aaryn D; Dickson, Brett G

    2014-01-01

    Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods

  7. An iterative and targeted sampling design informed by habitat suitability models for detecting focal plant species over extensive areas.

    Directory of Open Access Journals (Sweden)

    Ophelia Wang

    Full Text Available Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1 detecting non-native invasive plants across previously unsampled gradients, and 2 characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The

  8. A least trimmed square method for clutter removal in infrared small target detection

    Science.gov (United States)

    Bai, Kun; Wang, Yuehuan

    2013-10-01

    In this paper, a new procedure based on least trimmed square for clutter background estimation is proposed. Least trimmed square method identifies multiple outliers in the image, such as noise and target region. Then the clutter background is estimated without these outliers. The performance of this method is compared with the algorithms based on least mean square method, the results show that our method gets higher signal clutter ratio (SCR) gain in target region than other methods which use LMS filter.

  9. Survey and visual detection of Zaire ebolavirus in clinical samples targeting the nucleoprotein gene in Sierra Leone

    Directory of Open Access Journals (Sweden)

    Jing Yuan

    2015-12-01

    Full Text Available Ebola virus (EBOV can lead to severe hemorrhagic fever with a high risk of death in humans and other primates. To guide treatment and prevent spread of the viral infection, a rapid and sensitive detection method is required for clinical samples. Here, we described and evaluated a reverse transcription loop-mediated isothermal amplification (RT-LAMP method to detect Zaire ebolavirus using the nucleoprotein gene (NP as a target sequence. Two different techniques were used, a calcein/Mn2+ complex chromogenic method and real-time turbidity monitoring. The RT-LAMP assay detected the NP target sequence with a limit of 4.56 copies/μL within 45 min under 61°C, a similar even or increase in sensitivity than that of real-time reverse transcription-polymerase chain reaction (RT-PCR. Additionally, all pseudoviral particles or non- Zaire EBOV genomes were negative for LAMP detection, indicating that the assay was highly specific for EBOV. To appraise the availability of the RT-LAMP method for use in clinical diagnosis of EBOV, of 417 blood or swab samples collected from patients with clinically suspected infections in Sierra Leone, 307 were identified for RT-LAMP-based surveillance of EBOV. Therefore, the highly specific and sensitive RT-LAMP method allows the rapid detection of EBOV, and is a suitable tool for clinical screening, diagnosis, and primary quarantine purposes.

  10. Early Detection Rapid Response Program Targets New Noxious Weed Species in Washington State

    Science.gov (United States)

    Andreas, Jennifer E.; Halpern, Alison D.; DesCamp, Wendy C.; Miller, Timothy W.

    2015-01-01

    Early detection, rapid response is a critical component of invasive plant management. It can be challenging, however, to detect new invaders before they become established if landowners cannot identify species of concern. In order to increase awareness, eye-catching postcards were developed in Washington State as part of a noxious weed educational…

  11. Locating sensors for detecting source-to-target patterns of special nuclear material smuggling: a spatial information theoretic approach.

    Science.gov (United States)

    Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

    2010-01-01

    In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.

  12. Locating Sensors for Detecting Source-to-Target Patterns of Special Nuclear Material Smuggling: A Spatial Information Theoretic Approach

    Directory of Open Access Journals (Sweden)

    Xuesong Zhou

    2010-08-01

    Full Text Available In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.

  13. Detection and quantification of angiogenesis in experimental valve disease with integrin-targeted nanoparticles and 19-fluorine MRI/MRS

    Directory of Open Access Journals (Sweden)

    Zhang Huiying

    2008-09-01

    Full Text Available Abstract Background Angiogenesis is a critical early feature of atherosclerotic plaque development and may also feature prominently in the pathogenesis of aortic valve stenosis. It has been shown that MRI can detect and quantify specific molecules of interest expressed in cardiovascular disease and cancer by measuring the unique fluorine signature of appropriately targeted perfluorocarbon (PFC nanoparticles. In this study, we demonstrated specific binding of ανβ3 integrin targeted nanoparticles to neovasculature in a rabbit model of aortic valve disease. We also showed that fluorine MRI could be used to detect and quantify the development of neovasculature in the excised aortic valve leaflets. Methods New Zealand White rabbits consumed a cholesterol diet for ~180 days and developed aortic valve thickening, inflammation, and angiogenesis mimicking early human aortic valve disease. Rabbits (n = 7 were treated with ανβ3 integrin targeted PFC nanoparticles or control untargeted PFC nanoparticles (n = 6. Competitive inhibition in vivo of nanoparticle binding (n = 4 was tested by pretreatment with targeted nonfluorinated nanoparticles followed 2 hours later by targeted PFC nanoparticles. 2 hours after treatment, aortic valves were excised and 19F MRS was performed at 11.7T. Integrated 19F spectral peaks were compared using a one-way ANOVA and Hsu's MCB (multiple comparisons with the best post hoc t test. In 3 additional rabbits treated with ανβ3 integrin targeted PFC nanoparticles, 19F spectroscopy was performed on a 3.0T clinical scanner. The presence of angiogenesis was confirmed by immunohistochemistry. Results Valves of rabbits treated with targeted PFC nanoparticles had 220% more fluorine signal than valves of rabbits treated with untargeted PFC nanoparticles (p νβ3 integrin staining revealed the presence of neovasculature within the valve leaflets. Conclusion Integrin-targeted PFC nanoparticles specifically detect early angiogenesis

  14. Fluorescence self-quenching assay for the detection of target collagen sequences using a short probe peptide.

    Science.gov (United States)

    Nian, Linge; Hu, Yue; Fu, Caihong; Song, Chen; Wang, Jie; Xiao, Jianxi

    2018-01-01

    The development of novel assays to detect collagen fragments is of utmost importance for diagnostic, prognostic and therapeutic decisions in various collagen-related diseases, and one essential question is to discover probe peptides that can specifically recognize target collagen sequences. Herein we have developed the fluorescence self-quenching assay as a convenient tool to screen the capability of a series of fluorescent probe peptides of variable lengths to bind with target collagen peptides. We have revealed that the targeting ability of probe peptides is length-dependent, and have discovered a relatively short probe peptide FAM-G(POG)8 capable to identify the target peptide. We have further demonstrated that fluorescence self-quenching assay together with this short probe peptide can be applied to specifically detect the desired collagen fragment in complex biological media. Fluorescence self-quenching assay provides a powerful new tool to discover effective peptides for the recognition of collagen biomarkers, and it may have great potential to identify probe peptides for various protein biomarkers involved in pathological conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Facile Synthesis of Biocompatible Fluorescent Nanoparticles for Cellular Imaging and Targeted Detection of Cancer Cells.

    Science.gov (United States)

    Tang, Fu; Wang, Chun; Wang, Xiaoyu; Li, Lidong

    2015-11-18

    In this work, we report the facile synthesis of functional core-shell structured nanoparticles with fluorescence enhancement, which show specific targeting of cancer cells. Biopolymer poly-l-lysine was used to coat the silver core with various shell thicknesses. Then, the nanoparticles were functionalized with folic acid as a targeting agent for folic acid receptor. The metal-enhanced fluorescence effect was observed when the fluorophore (5-(and-6)-carboxyfluorescein-succinimidyl ester) was conjugated to the modified nanoparticle surface. Cellular imaging assay of the nanoparticles in folic acid receptor-positive cancer cells showed their excellent biocompatibility and selectivity. The as-prepared functional nanoparticles demonstrate the efficiency of the metal-enhanced fluorescence effect and provide an alternative approach for the cellular imaging and targeting of cancer cells.

  16. Combination of atomic force microscopy and mass spectrometry for the detection of target protein in the serum samples of children with autism spectrum disorders

    Science.gov (United States)

    Kaysheva, A. L.; Pleshakova, T. O.; Kopylov, A. T.; Shumov, I. D.; Iourov, I. Y.; Vorsanova, S. G.; Yurov, Y. B.; Ziborov, V. S.; Archakov, A. I.; Ivanov, Y. D.

    2017-10-01

    Possibility of detection of target proteins associated with development of autistic disorders in children with use of combined atomic force microscopy and mass spectrometry (AFM/MS) method is demonstrated. The proposed method is based on the combination of affine enrichment of proteins from biological samples and visualization of these proteins by AFM and MS analysis with quantitative detection of target proteins.

  17. Design of an Acoustic Target Intrusion Detection System Based on Small-Aperture Microphone Array

    Directory of Open Access Journals (Sweden)

    Xingshui Zu

    2017-03-01

    Full Text Available Automated surveillance of remote locations in a wireless sensor network is dominated by the detection algorithm because actual intrusions in such locations are a rare event. Therefore, a detection method with low power consumption is crucial for persistent surveillance to ensure longevity of the sensor networks. A simple and effective two-stage algorithm composed of energy detector (ED and delay detector (DD with all its operations in time-domain using small-aperture microphone array (SAMA is proposed. The algorithm analyzes the quite different velocities between wind noise and sound waves to improve the detection capability of ED in the surveillance area. Experiments in four different fields with three types of vehicles show that the algorithm is robust to wind noise and the probability of detection and false alarm are 96.67% and 2.857%, respectively.

  18. Design of an Acoustic Target Intrusion Detection System Based on Small-Aperture Microphone Array.

    Science.gov (United States)

    Zu, Xingshui; Guo, Feng; Huang, Jingchang; Zhao, Qin; Liu, Huawei; Li, Baoqing; Yuan, Xiaobing

    2017-03-04

    Automated surveillance of remote locations in a wireless sensor network is dominated by the detection algorithm because actual intrusions in such locations are a rare event. Therefore, a detection method with low power consumption is crucial for persistent surveillance to ensure longevity of the sensor networks. A simple and effective two-stage algorithm composed of energy detector (ED) and delay detector (DD) with all its operations in time-domain using small-aperture microphone array (SAMA) is proposed. The algorithm analyzes the quite different velocities between wind noise and sound waves to improve the detection capability of ED in the surveillance area. Experiments in four different fields with three types of vehicles show that the algorithm is robust to wind noise and the probability of detection and false alarm are 96.67% and 2.857%, respectively.

  19. A novel SERRS sandwich-hybridization assay to detect specific DNA target.

    Directory of Open Access Journals (Sweden)

    Cécile Feuillie

    Full Text Available In this study, we have applied Surface Enhanced Resonance Raman Scattering (SERRS technology to the specific detection of DNA. We present an innovative SERRS sandwich-hybridization assay that allows specific DNA detection without any enzymatic amplification, such as is the case with Polymerase Chain Reaction (PCR. In some substrates, such as ancient or processed remains, enzymatic amplification fails due to DNA alteration (degradation, chemical modification or to the presence of inhibitors. Consequently, the development of a non-enzymatic method, allowing specific DNA detection, could avoid long, expensive and inconclusive amplification trials. Here, we report the proof of concept of a SERRS sandwich-hybridization assay that leads to the detection of a specific chamois DNA. This SERRS assay reveals its potential as a non-enzymatic alternative technology to DNA amplification methods (particularly the PCR method with several applications for species detection. As the amount and type of damage highly depend on the preservation conditions, the present SERRS assay would enlarge the range of samples suitable for DNA analysis and ultimately would provide exciting new opportunities for the investigation of ancient DNA in the fields of evolutionary biology and molecular ecology, and of altered DNA in food frauds detection and forensics.

  20. Direct Detection and Differentiation of Pathogenic Leptospira Species Using a Multi-Gene Targeted Real Time PCR Approach

    Science.gov (United States)

    Ferreira, Ana Sofia; Costa, Pedro; Rocha, Teresa; Amaro, Ana; Vieira, Maria Luísa; Ahmed, Ahmed; Thompson, Gertrude; Hartskeerl, Rudy A.; Inácio, João

    2014-01-01

    Leptospirosis is a growing public and veterinary health concern caused by pathogenic species of Leptospira. Rapid and reliable laboratory tests for the direct detection of leptospiral infections in animals are in high demand not only to improve diagnosis but also for understanding the epidemiology of the disease. In this work we describe a novel and simple TaqMan-based multi-gene targeted real-time PCR approach able to detect and differentiate Leptospira interrogans, L. kirschneri, L. borgpeteresenii and L. noguchii, which constitute the veterinary most relevant pathogenic species of Leptospira. The method uses sets of species-specific probes, and respective flanking primers, designed from ompL1 and secY gene sequences. To monitor the presence of inhibitors, a duplex amplification assay targeting both the mammal β-actin and the leptospiral lipL32 genes was implemented. The analytical sensitivity of all primer and probe sets was estimated to be Leptospira strains and other non-related bacteria revealed a 100% analytical specificity. Additionally, pathogenic leptospires were successfully detected in five out of 29 tissue samples from animals (Mus spp., Rattus spp., Dolichotis patagonum and Sus domesticus). Two samples were infected with L. borgpetersenii, two with L. interrogans and one with L. kirschneri. The possibility to detect and identify these pathogenic agents to the species level in domestic and wildlife animals reinforces the diagnostic information and will enhance our understanding of the epidemiology of leptopirosis. PMID:25398140

  1. Targeting Deregulated Epigenetic Control in Cancer: Cancer Epigenomics as a Platform for Risk Assessment, Early Detection, Targeted Therapy and Potential for Relapse

    Science.gov (United States)

    Zaidi, Sayyed K.; van Wijnen, Andre J.; Lian, Jane B.; Stein, Janet L.; Stein, Gary S.

    2013-01-01

    Summary Cancer is a multifaceted disease that involves acquisition of genetic mutations, deletions, and amplifications as well as deregulation of epigenetic mechanisms that fine-tune gene regulation. Key epigenetic mechanisms that include histone modifications, DNA methylation, and non-coding RNA-mediated gene silencing are often deregulated in a variety of cancers. Subnuclear localization of key proteins in the interphase nucleus and bookmarking of genes by lineage commitment factors in mitosis – a new dimension to epigenetic control of fundamental biological processes – is also modified in cancer. In this review, we discuss the various aspects of epigenetic control that are operative in a variety of cancers and their potential for risk assessment, early detection, targeted therapy and personalized medicine. PMID:23589100

  2. Location and detection of explosive-contaminated human fingerprints on distant targets using standoff laser-induced breakdown spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Lucena, P.; Gaona, I.; Moros, J.; Laserna, J.J., E-mail: laserna@uma.es

    2013-07-01

    Detection of explosive-contaminated human fingerprints constitutes an analytical challenge of high significance in security issues and in forensic sciences. The use of a laser-induced breakdown spectroscopy (LIBS) sensor working at 31 m distance to the target, fitted with 2D scanning capabilities and designed for capturing spectral information from laser-induced plasmas of fingerprints is presented. Distribution chemical maps based on Na and CN emissions are used to locate and detect chloratite, DNT, TNT, RDX and PETN residues that have been deposited on the surface of aluminum and glass substrates. An effectiveness of 100% on fingerprints detection, regardless the substrate scanned, is reached. Environmental factors that affect the prevalence of the fingerprint LIBS response are discussed. - Highlights: • Explosive remnants left behind by fingerprints have been detected from afar. • Operating in scanning mode, LIBS boasts high ability to locate traces over a surface. • Effectiveness in trace detection plainly depends on the scanning spatial resolution. • The detection capability of LIBS shrinks as the fingerprints deteriorate over time.

  3. Agroterrorism targeting livestock: a review with a focus on early detection systems

    NARCIS (Netherlands)

    Elbers, A.R.W.; Knutsson, R.

    2013-01-01

    Agroterrorism targeting livestock can be described as the intentional introduction of an animal disease agent against livestock with the purpose of causing economic damage, disrupting socioeconomic stability of a country, and creating panic and distress. This type of terrorism can be alluring to

  4. Detection of atherosclerotic lesions and intimal macrophages using CD36-targeted nanovesicles

    Science.gov (United States)

    Current approaches to the diagnosis and therapy of atherosclerosis cannot target to lesion-determinant cells in the artery wall. Intimal macrophage infiltration promotes atherosclerotic lesion development by facilitating the accumulation of oxidized low-density lipoproteins (oxLDL) and increasing in...

  5. Change detection in urban and rural driving scenes: Effects of target type and safety relevance on change blindness.

    Science.gov (United States)

    Beanland, Vanessa; Filtness, Ashleigh J; Jeans, Rhiannon

    2017-03-01

    The ability to detect changes is crucial for safe driving. Previous research has demonstrated that drivers often experience change blindness, which refers to failed or delayed change detection. The current study explored how susceptibility to change blindness varies as a function of the driving environment, type of object changed, and safety relevance of the change. Twenty-six fully-licenced drivers completed a driving-related change detection task. Changes occurred to seven target objects (road signs, cars, motorcycles, traffic lights, pedestrians, animals, or roadside trees) across two environments (urban or rural). The contextual safety relevance of the change was systematically manipulated within each object category, ranging from high safety relevance (i.e., requiring a response by the driver) to low safety relevance (i.e., requiring no response). When viewing rural scenes, compared with urban scenes, participants were significantly faster and more accurate at detecting changes, and were less susceptible to "looked-but-failed-to-see" errors. Interestingly, safety relevance of the change differentially affected performance in urban and rural environments. In urban scenes, participants were more efficient at detecting changes with higher safety relevance, whereas in rural scenes the effect of safety relevance has marginal to no effect on change detection. Finally, even after accounting for safety relevance, change blindness varied significantly between target types. Overall the results suggest that drivers are less susceptible to change blindness for objects that are likely to change or move (e.g., traffic lights vs. road signs), and for moving objects that pose greater danger (e.g., wild animals vs. pedestrians). Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Hyperspectral target detection analysis of a cluttered scene from a virtual airborne sensor platform using MuSES

    Science.gov (United States)

    Packard, Corey D.; Viola, Timothy S.; Klein, Mark D.

    2017-10-01

    The ability to predict spectral electro-optical (EO) signatures for various targets against realistic, cluttered backgrounds is paramount for rigorous signature evaluation. Knowledge of background and target signatures, including plumes, is essential for a variety of scientific and defense-related applications including contrast analysis, camouflage development, automatic target recognition (ATR) algorithm development and scene material classification. The capability to simulate any desired mission scenario with forecast or historical weather is a tremendous asset for defense agencies, serving as a complement to (or substitute for) target and background signature measurement campaigns. In this paper, a systematic process for the physical temperature and visible-through-infrared radiance prediction of several diverse targets in a cluttered natural environment scene is presented. The ability of a virtual airborne sensor platform to detect and differentiate targets from a cluttered background, from a variety of sensor perspectives and across numerous wavelengths in differing atmospheric conditions, is considered. The process described utilizes the thermal and radiance simulation software MuSES and provides a repeatable, accurate approach for analyzing wavelength-dependent background and target (including plume) signatures in multiple band-integrated wavebands (multispectral) or hyperspectrally. The engineering workflow required to combine 3D geometric descriptions, thermal material properties, natural weather boundary conditions, all modes of heat transfer and spectral surface properties is summarized. This procedure includes geometric scene creation, material and optical property attribution, and transient physical temperature prediction. Radiance renderings, based on ray-tracing and the Sandford-Robertson BRDF model, are coupled with MODTRAN for the inclusion of atmospheric effects. This virtual hyperspectral/multispectral radiance prediction methodology has been

  7. The preclinical natural history of serous ovarian cancer: defining the target for early detection.

    Directory of Open Access Journals (Sweden)

    Patrick O Brown

    2009-07-01

    Full Text Available Ovarian cancer kills approximately 15,000 women in the United States every year, and more than 140,000 women worldwide. Most deaths from ovarian cancer are caused by tumors of the serous histological type, which are rarely diagnosed before the cancer has spread. Rational design of a potentially life-saving early detection and intervention strategy requires understanding the lesions we must detect in order to prevent lethal progression. Little is known about the natural history of lethal serous ovarian cancers before they become clinically apparent. We can learn about this occult period by studying the unsuspected serous cancers that are discovered in a small fraction of apparently healthy women who undergo prophylactic bilateral salpingo-oophorectomy (PBSO.We developed models for the growth, progression, and detection of occult serous cancers on the basis of a comprehensive analysis of published data on serous cancers discovered by PBSO in BRCA1 mutation carriers. Our analysis yielded several critical insights into the early natural history of serous ovarian cancer. First, these cancers spend on average more than 4 y as in situ, stage I, or stage II cancers and approximately 1 y as stage III or IV cancers before they become clinically apparent. Second, for most of the occult period, serous cancers are less than 1 cm in diameter, and not visible on gross examination of the ovaries and Fallopian tubes. Third, the median diameter of a serous ovarian cancer when it progresses to an advanced stage (stage III or IV is about 3 cm. Fourth, to achieve 50% sensitivity in detecting tumors before they advance to stage III, an annual screen would need to detect tumors of 1.3 cm in diameter; 80% detection sensitivity would require detecting tumors less than 0.4 cm in diameter. Fifth, to achieve a 50% reduction in serous ovarian cancer mortality with an annual screen, a test would need to detect tumors of 0.5 cm in diameter.Our analysis has formalized

  8. New target tissue for food-borne virus detection in oysters.

    Science.gov (United States)

    Wang, D; Wu, Q; Yao, L; Wei, M; Kou, X; Zhang, J

    2008-11-01

    To evaluate the different tissues of naturally contaminated oyster for food-borne virus detection. The different tissues of 136 field oyster samples were analysed for norovirus (NV), hepatitis A virus (HAV) and rotavirus (RV) by reverse transcription (RT)-PCR and were confirmed by sequencing. These viruses were detected in 20 samples (14.71%), showing positivity for NV (1.47%), HAV (5.15%) and RV (8.82%). Furthermore, among different tissues, the highest positive rate of the food-borne viruses was found in the gills (14.71%), followed by the stomach (13.97%) and the digestive diverticula (13.24%). The food-borne viruses were detected in the gills, stomach, digestive diverticula and the cilia of the mantle. In addition, the results showed that the gills are one of the appropriate tissues for viral detection in oysters by nucleic acid assay. This is the first paper to report on the presence of food-borne viruses in the gills and the cilia of the mantle of naturally contaminated oysters. The research team hopes that the results of the study will be of help in sampling the appropriate tissues for the detection of food-borne viruses in commercial oysters.

  9. Detection of new in-path targets by drivers using Stop & Go Adaptive Cruise Control.

    Science.gov (United States)

    Stanton, Neville A; Dunoyer, Alain; Leatherland, Adam

    2011-05-01

    This paper reports on the design and evaluation of in-car displays used to support Stop & Go Adaptive Cruise Control. Stop & Go Adaptive Cruise Control is an extension of Adaptive Cruise Control, as it is able to bring the vehicle to a complete stop. Previous versions of Adaptive Cruise Control have only operated above 26 kph. The greatest concern for these technologies is the appropriateness of the driver's response in any given scenario. Three different driver interfaces were proposed to support the detection of modal, spatial and temporal changes of the system: an iconic display, a flashing iconic display, and a representation of the radar. The results show that drivers correctly identified more changes detected by the system with the radar display than with the other displays, but higher levels of workload accompanied this increased detection. Copyright © 2010 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  10. Cross-priming amplification targeting the coagulase gene for rapid detection of coagulase-positive Staphylococci.

    Science.gov (United States)

    Qiao, B; Cui, J-Y; Sun, L; Yang, S; Zhao, Y-L

    2015-07-01

    To develop and evaluate cross-priming amplification (CPA) combined with immuno-blotting for the detection of coagulase-positive Staphylococci including Staphylococcus aureus. Twenty-four sets of cross and detection primers were designed according to four sequences of coagulase gene in Staph. aureus. The most specific primer pair was screened out for the next amplification and interaction. The specificity was evaluated in a total of 53 species of Staph. aureus and non-Staph. aureus. Two red lines indicating positive were always observed on the BioHelix Express strip for 12 subspecies of Staph. aureus. In contrast, only one signal line showing negative results was detected in all of non-Staph. aureus samples. The limit of detection (LOD) of CPA was 3·6 ± 2·7 fg for the genomic DNA, which is about 100 and 10 times sensitive than those of PCR and loop-mediated isothermal amplification respectively. For the pure culture of Staph. aureus and milk powders, the LODs of CPA were about 1·34 CFU per reaction and 5·2 ± 3·7 CFU per 100 g of milk powder respectively. The CPA method was also successfully applied to evaluate the contamination of Staph. aureus in 318 samples of daily food. CPA is a very sensitive and rapid method to detect Staph. aureus by simple laboratory instrument. It is the first report on the application of the CPA with immuno-blotting for detection of coagulase-positive Staphylococci including Staph. aureus. © 2015 The Society for Applied Microbiology.

  11. Improving specificity of Bordetella pertussis detection using a four target real-time PCR.

    Science.gov (United States)

    Martini, Helena; Detemmerman, Liselot; Soetens, Oriane; Yusuf, Erlangga; Piérard, Denis

    2017-01-01

    The incidence of whooping cough, a contagious respiratory disease caused by Bordetella pertussis, is on the rise despite existing vaccination programmes. Similar, though usually milder, respiratory symptoms may be caused by other members of the Bordetella genus: B. parapertussis, B. holmesii, and B. bronchiseptica. Pertussis diagnosis is mostly done using PCR, but the use of multiple targets is necessary in order to differentiate the different Bordetella spp. with sufficient sensitivity and specificity. In this study we evaluate a multiplex PCR assay for the differentiation of B. pertussis from other Bordetella spp., using the targets IS481, IS1001, IS1002, and recA. Moreover, we retrospectively explore the epidemiology of Bordetella spp. infections in Belgium, using the aforementioned assay over a three-year period, from 2013 until 2015.

  12. A New SAR Image Segmentation Algorithm for the Detection of Target and Shadow Regions.

    Science.gov (United States)

    Huang, Shiqi; Huang, Wenzhun; Zhang, Ting

    2016-12-07

    The most distinctive characteristic of synthetic aperture radar (SAR) is that it can acquire data under all weather conditions and at all times. However, its coherent imaging mechanism introduces a great deal of speckle noise into SAR images, which makes the segmentation of target and shadow regions in SAR images very difficult. This paper proposes a new SAR image segmentation method based on wavelet decomposition and a constant false alarm rate (WD-CFAR). The WD-CFAR algorithm not only is insensitive to the speckle noise in SAR images but also can segment target and shadow regions simultaneously, and it is also able to effectively segment SAR images with a low signal-to-clutter ratio (SCR). Experiments were performed to assess the performance of the new algorithm on various SAR images. The experimental results show that the proposed method is effective and feasible and possesses good characteristics for general application.

  13. A New SAR Image Segmentation Algorithm for the Detection of Target and Shadow Regions

    Science.gov (United States)

    Huang, Shiqi; Huang, Wenzhun; Zhang, Ting

    2016-01-01

    The most distinctive characteristic of synthetic aperture radar (SAR) is that it can acquire data under all weather conditions and at all times. However, its coherent imaging mechanism introduces a great deal of speckle noise into SAR images, which makes the segmentation of target and shadow regions in SAR images very difficult. This paper proposes a new SAR image segmentation method based on wavelet decomposition and a constant false alarm rate (WD-CFAR). The WD-CFAR algorithm not only is insensitive to the speckle noise in SAR images but also can segment target and shadow regions simultaneously, and it is also able to effectively segment SAR images with a low signal-to-clutter ratio (SCR). Experiments were performed to assess the performance of the new algorithm on various SAR images. The experimental results show that the proposed method is effective and feasible and possesses good characteristics for general application. PMID:27924935

  14. Immunohistochemical detection of a potential molecular therapeutic target for canine hemangiosarcoma.

    Science.gov (United States)

    Adachi, Mami; Hoshino, Yuki; Izumi, Yusuke; Takagi, Satoshi

    2016-05-03

    Canine hemangiosarcoma (HSA) is a progressive malignant neoplasm of dogs for which there is currently no effective treatment. A recent study suggested that receptor tyrosine kinases (RTKs), the PI3K/Akt/m-TOR and MAPK pathways are all activated in canine and human HSA. The aim of the present study was to investigate the overexpression of these proteins by immunohistochemistry in canine splenic HSA to identify potential molecular therapeutic targets. A total of 10 splenic HSAs and two normal splenic samples surgically resected from dogs were sectioned and stained with hematoxylin and eosin for histological diagnosis or analyzed using immunohistochemistry. The expression of RTKs, c-kit, VEGFR-2 and PDGFR-2, as well as PI3K/Akt/m-TOR and MEK was higher in canine splenic HSAs compared to normal spleens. These proteins may therefore be potential therapeutic targets in canine splenic HSA.

  15. Targeted next generation sequencing for the detection of ciprofloxacin resistance markers using molecular inversion probes

    Science.gov (United States)

    2016-07-06

    both classify the organism along with known resistance markers however the expertise and computing infrastructure required for analyzing data is still...caveat to targeted sequencing approaches; however, most new outbreaks such as Ebola virus or new resistant hospital acquired infections like...Mechanism of quinolone action and resistance. Biochemistry 53, 1565-1574, doi :10.1021/bi5000564 (2014). 4 Loveless, B. M. et al. Identification of

  16. NanoCluster Beacon - A New Molecular Probe for Homogeneous Detection of Nucleic Acid Targets

    Science.gov (United States)

    2011-02-01

    upon target DNA binding, termed a NanoCluster Beacon ( NCB ). We discovered that interactions between silver nanoclusters and a proximal, guanine- rich...into a palette of colors (green, yellow/orange, and red) by employing different proximal sequences, potentially enabling the use of NCBs in...common 5’-C3NNNNNC4 motif, where N is either a thymine (T) or an adenine (A) base. We optimized the design of NCBs by testing the effect of different

  17. Early Detection of Ovarian Cancer by Tumor Epithelium-Targeted Molecular Ultrasound

    Science.gov (United States)

    2014-10-01

    abortion and pre-eclampsia. Here, we sought to examine the presence of ILC2s in uterine tissue and investigate the effects of ST2 deficiency on suc...CD9. These results suggest a novel role of IL-16 and may be useful in designing antitumor immune therapeutics targeting IL-16 for OVCA prevention...in endometrial lymphocytes, endometrium and trophoblast during healthy and abortive porcine pregnancy M Bidarimath1, AK Edwards1, JM Wessels2, K

  18. Early Detection of Ovarian Cancer by Contrast-Enhanced Ultrasound-Targeted Imaging

    Science.gov (United States)

    2013-09-01

    predictions were confirmed by gross examination of hens at necropsy . Ovarian tumors, their stages, and types were confirmed by routine histologic... rabbit anti- chicken DR-6 antibodies. Sera (n = 22; age range 2.5 to 3.0 years) from hens with ovarian cancer were compared with normal hens...of targeted imaging were compared and confirmed by gross examination of hens at necropsy and from routine histology. As observed on sonography

  19. Multiplex target enrichment using DNA indexing for ultra-high throughput SNP detection.

    LENUS (Irish Health Repository)

    Kenny, Elaine M

    2011-02-01

    Screening large numbers of target regions in multiple DNA samples for sequence variation is an important application of next-generation sequencing but an efficient method to enrich the samples in parallel has yet to be reported. We describe an advanced method that combines DNA samples using indexes or barcodes prior to target enrichment to facilitate this type of experiment. Sequencing libraries for multiple individual DNA samples, each incorporating a unique 6-bp index, are combined in equal quantities, enriched using a single in-solution target enrichment assay and sequenced in a single reaction. Sequence reads are parsed based on the index, allowing sequence analysis of individual samples. We show that the use of indexed samples does not impact on the efficiency of the enrichment reaction. For three- and nine-indexed HapMap DNA samples, the method was found to be highly accurate for SNP identification. Even with sequence coverage as low as 8x, 99% of sequence SNP calls were concordant with known genotypes. Within a single experiment, this method can sequence the exonic regions of hundreds of genes in tens of samples for sequence and structural variation using as little as 1 μg of input DNA per sample.

  20. Continuous Transmission Frequency Modulation Detection under Variable Sonar-Target Speed Conditions

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2013-03-01

    Full Text Available As a ranging sensor, a continuous transmission frequency modulation (CTFM sonar with its ability for range finding and range profile formation works effectively under stationary conditions. When a relative velocity exists between the target and the sonar, the echo signal is Doppler-shifted. This situation causes the output of the sensor to deviate from the actual target range, thus limiting its applications to stationary conditions only. This work presents an approach for correcting such a deviation. By analyzing the Doppler effect during the propagation process, the sensor output can be corrected by a Doppler factor. To obtain this factor, a conventional CTFM system is slightly modified by adding a single tone signal with a frequency that locates out-of-sweep range of the transmitted signal. The Doppler factor can be extracted from the echo. Both verification experiments and performance tests are carried out. Results indicate the validity of the proposed approach. Moreover, ranging precision under different processing setups is discussed. For adjacent multiple targets, the discrimination ability is influenced by displacement and velocity. A discrimination boundary is provided through an analysis.

  1. Optimization of Prostate Biopsy: the Role of Magnetic Resonance Imaging Targeted Biopsy in Detection, Localization and Risk Assessment

    Science.gov (United States)

    Bjurlin, Marc A.; Meng, Xiaosong; Le Nobin, Julien; Wysock, James S.; Lepor, Herbert; Rosenkrantz, Andrew B.; Taneja, Samir S.

    2014-01-01

    Purpose Optimization of prostate biopsy requires addressing the shortcomings of standard systematic transrectal ultrasound guided biopsy, including false-negative rates, incorrect risk stratification, detection of clinically insignificant disease and the need for repeat biopsy. Magnetic resonance imaging is an evolving noninvasive imaging modality that increases the accurate localization of prostate cancer at the time of biopsy, and thereby enhances clinical risk assessment and improves the ability to appropriately counsel patients regarding therapy. In this review we 1) summarize the various sequences that comprise a prostate multiparametric magnetic resonance imaging examination along with its performance characteristics in cancer detection, localization and reporting standards; 2) evaluate potential applications of magnetic resonance imaging targeting in prostate biopsy among men with no previous biopsy, a negative previous biopsy and those with low stage cancer; and 3) describe the techniques of magnetic resonance imaging targeted biopsy and comparative study outcomes. Materials and Methods A bibliographic search covering the period up to October 2013 was conducted using MEDLINE®/PubMed®. Articles were reviewed and categorized based on which of the 3 objectives of this review was addressed. Data were extracted, analyzed and summarized. Results Multiparametric magnetic resonance imaging consists of anatomical T2-weighted imaging coupled with at least 2 functional imaging techniques. It has demonstrated improved prostate cancer detection sensitivity up to 80% in the peripheral zone and 81% in the transition zone. A prostate cancer magnetic resonance imaging suspicion score has been developed, and is depicted using the Likert or PI-RADS (Prostate Imaging Reporting and Data System) scale for better standardization of magnetic resonance imaging interpretation and reporting. Among men with no previous biopsy, magnetic resonance imaging increases the frequency of

  2. Study on the Detection of Moving Target in the Mining Method Based on Hybrid Algorithm for Sports Video Analysis

    Directory of Open Access Journals (Sweden)

    Huang Tian

    2014-10-01

    Full Text Available Moving object detection and tracking is the computer vision and image processing is a hot research direction, based on the analysis of the moving target detection and tracking algorithm in common use, focus on the sports video target tracking non rigid body. In sports video, non rigid athletes often have physical deformation in the process of movement, and may be associated with the occurrence of moving target under cover. Media data is surging to fast search and query causes more difficulties in data. However, the majority of users want to be able to quickly from the multimedia data to extract the interested content and implicit knowledge (concepts, rules, rules, models and correlation, retrieval and query quickly to take advantage of them, but also can provide the decision support problem solving hierarchy. Based on the motion in sport video object as the object of study, conducts the system research from the theoretical level and technical framework and so on, from the layer by layer mining between low level motion features to high-level semantic motion video, not only provides support for users to find information quickly, but also can provide decision support for the user to solve the problem.

  3. Detection of dim point targets in cluttered maritime backgrounds through multisensor image fusion

    NARCIS (Netherlands)

    Toet, A.

    2002-01-01

    Multispectral IR imaging techniques are frequently deployed in maritime operations, for instance to detect floating mines or to find small dinghies and swimmers during search and rescue operations. However, maritime backgrounds usually contain a large amount of clutter that severely hampers the

  4. Revised Stellar Properties of Kepler Targets for the Quarter 1-16 Transit Detection Run

    NARCIS (Netherlands)

    Huber, D.; Silva Aguirre, V.; Matthews, J.M.; Pinsonneault, M.H.; Gaidos, E.; García, R.A.; Hekker, S.; Mathur, S.; Mosser, B.; Torres, G.; Bastien, F.A.; Basu, S.; Bedding, T.R.; Chaplin, W.J.; Demory, B.O.; Fleming, S.W.; Guo, Z.; Mann, A.W.; Rowe, J.F.; Serenelli, A.M.; Smith, M.A.; Stello, D.

    2014-01-01

    We present revised properties for 196,468 stars observed by the NASA Kepler mission and used in the analysis of Quarter 1-16 (Q1-Q16) data to detect and characterize transiting planets. The catalog is based on a compilation of literature values for atmospheric properties (temperature, surface

  5. Nanotechnology-Based Detection and Targeted Therapy in Cancer: Nano-Bio Paradigms and Applications

    Directory of Open Access Journals (Sweden)

    Dhruba J. Bharali

    2011-07-01

    Full Text Available The application of nanotechnology to biomedicine, particularly in cancer diagnosis and treatment, promises to have a profound impact on healthcare. The exploitation of the unique properties of nano-sized particles for cancer therapeutics is most popularly known as nanomedicine. The goals of this review are to discuss the current state of nanomedicine in the field of cancer detection and the subsequent application of nanotechnology to treatment. Current cancer detection methods rely on the patient contacting their provider when they feel ill, or relying on non-specific screening methods, which unfortunately often result in cancers being detected only after it is too late for effective treatment. Cancer treatment paradigms mainly rely on whole body treatment with chemotherapy agents, exposing the patient to medications that non-specifically kill rapidly dividing cells, leading to debilitating side effects. In addition, the use of toxic organic solvents/excipients can hamper the further effectiveness of the anticancer drug. Nanomedicine has the potential to increase the specificity of treatment of cancer cells while leaving healthy cells intact through the use of novel nanoparticles. This review discusses the use of nanoparticles such as quantum dots, nanoshells, nanocrystals, nanocells, and dendrimers for the detection and treatment of cancer. Future directions and perspectives of this cutting-edge technology are also discussed.

  6. Targeted and Untargeted Detection of Skim Milk Powder Adulteration by Near-Infrared Spectroscopy

    NARCIS (Netherlands)

    Capuano, Edoardo; Boerrigter-Eenling, Rita; Koot, Alex; Ruth, van S.M.

    2015-01-01

    In the present study, near-infrared spectroscopy (NIRS) was explored as a fast and reliable screening method for the detection of adulteration of skim milk powder (SMP). Sixty genuine SMP were adulterated with acid whey (1–25 % w/w), starch (2 and 5 %) and maltodextrin (2 and 5 %) for a total of

  7. High-Throughput, Protein-Targeted Biomolecular Detection Using Frequency-Domain Faraday Rotation Spectroscopy.

    Science.gov (United States)

    Murdock, Richard J; Putnam, Shawn A; Das, Soumen; Gupta, Ankur; Chase, Elyse D Z; Seal, Sudipta

    2017-03-01

    A clinically relevant magneto-optical technique (fd-FRS, frequency-domain Faraday rotation spectroscopy) for characterizing proteins using antibody-functionalized magnetic nanoparticles (MNPs) is demonstrated. This technique distinguishes between the Faraday rotation of the solvent, iron oxide core, and functionalization layers of polyethylene glycol polymers (spacer) and model antibody-antigen complexes (anti-BSA/BSA, bovine serum albumin). A detection sensitivity of ≈10 pg mL(-1) and broad detection range of 10 pg mL(-1) ≲ cBSA ≲ 100 µg mL(-1) are observed. Combining this technique with predictive analyte binding models quantifies (within an order of magnitude) the number of active binding sites on functionalized MNPs. Comparative enzyme-linked immunosorbent assay (ELISA) studies are conducted, reproducing the manufacturer advertised BSA ELISA detection limits from 1 ng mL(-1) ≲ cBSA ≲ 500 ng mL(-1) . In addition to the increased sensitivity, broader detection range, and similar specificity, fd-FRS can be conducted in less than ≈30 min, compared to ≈4 h with ELISA. Thus, fd-FRS is shown to be a sensitive optical technique with potential to become an efficient diagnostic in the chemical and biomolecular sciences. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Research and Development of Non-Spectroscopic MEMS-Based Sensor Arrays for Targeted Gas Detection

    Energy Technology Data Exchange (ETDEWEB)

    Loui, A; McCall, S K

    2011-10-24

    The ability to monitor the integrity of gas volumes is of interest to the stockpile surveillance community. Specifically, the leak detection of noble gases, at relevant concentration ranges and distinguished from other chemical species that may be simultaneously present, is particularly challenging. Aside from the laboratory-based method of gas chromatography-mass spectrometry (GC-MS), where samples may be collected by solid-phase microextraction (SPME) or cryofocusing, the other major approaches for gas-phase detection employ lasers typically operating in the mid-infrared wavelength region. While mass spectrometry can readily detect noble gases - the helium leak detector is an obvious example - laser-based methods such as infrared (IR) or Raman spectroscopy are completely insensitive to them as their monatomic nature precludes a non-zero dipole moment or changes in polarizability upon excitation. Therefore, noble gases can only be detected by one of two methods: (1) atomic emission spectroscopies which require the generation of plasmas through laser-induced breakdown, electrical arcing, or similar means; (2) non-spectroscopic methods which measure one or more physical properties (e.g., mass, thermal conductivity, density). In this report, we present our progress during Fiscal Year 2011 (FY11) in the research and development of a non-spectroscopic method for noble gas detection. During Fiscal Year 2010 (FY10), we demonstrated via proof-of-concept experiments that the combination of thermal conductivity detection (TCD) and coating-free damped resonance detection (CFDRD) using micro-electromechanical systems (MEMS) could provide selective sensing of these inert species. Since the MEMS-based TCD technology was directly adapted from a brassboard prototype commissioned by a previous chemical sensing project, FY11 efforts focused on advancing the state of the newer CFDRD method. This work, guided by observations previously reported in the open literature, has not only

  9. Non-targeted detection of chemical contamination in carbonated soft drinks using NMR spectroscopy, variable selection and chemometrics

    Energy Technology Data Exchange (ETDEWEB)

    Charlton, Adrian J. [Department for Environment, Food and Rural Affairs, Central Science Laboratory, Sand Hutton, York YO41 1LZ (United Kingdom)], E-mail: adrian.charlton@csl.gov.uk; Robb, Paul; Donarski, James A.; Godward, John [Department for Environment, Food and Rural Affairs, Central Science Laboratory, Sand Hutton, York YO41 1LZ (United Kingdom)

    2008-06-23

    An efficient method for detecting malicious and accidental contamination of foods has been developed using a combined {sup 1}H nuclear magnetic resonance (NMR) and chemometrics approach. The method has been demonstrated using a commercially available carbonated soft drink, as being capable of identifying atypical products and to identify contaminant resonances. Soft-independent modelling of class analogy (SIMCA) was used to compare {sup 1}H NMR profiles of genuine products (obtained from the manufacturer) against retail products spiked in the laboratory with impurities. The benefits of using feature selection for extracting contaminant NMR frequencies were also assessed. Using example impurities (paraquat, p-cresol and glyphosate) NMR spectra were analysed using multivariate methods resulting in detection limits of approximately 0.075, 0.2, and 0.06 mM for p-cresol, paraquat and glyphosate, respectively. These detection limits are shown to be approximately 100-fold lower than the minimum lethal dose for paraquat. The methodology presented here is used to assess the composition of complex matrices for the presence of contaminating molecules without a priori knowledge of the nature of potential contaminants. The ability to detect if a sample does not fit into the expected profile without recourse to multiple targeted analyses is a valuable tool for incident detection and forensic applications.

  10. Kepler Planet Detection Metrics: Per-Target Flux-Level Transit Injection Tests of TPS for Data Release 25

    Science.gov (United States)

    Burke, Christopher J.; Catanzarite, Joseph

    2017-01-01

    the recovered signals can be further classified as planet candidates or false positives in the exact same manner as detections from the nominal (i.e., observed) pipeline run (Twicken et al., 2016, Thompson et al., in preparation). To date, the PLTI test has been the standard means of measuring pipeline completeness averaged over large samples of targets (Christiansen et al., 2015, 2016; Christiansen, 2017). However, since the PLTI test uses only one injection per target, it does not elucidate individual-target variations in pipeline completeness due to differences in stellar properties or astrophysical variability. Thus, we developed the FLTI test to provide a numerically efficient way to fully map individual targets and explore the performance of the pipeline in greater detail. The FLTI tests thereby allow a thorough validation of the pipeline completeness models (such as window function (Burke and Catanzarite, 2017a), detection efficiency (Burke Catanzarite, 2017b), etc.) across the spectrum of Kepler targets (i.e., various astrophysical phenomena and differences in instrumental noise). Tests during development of the FLTI capability revealed that there are significant target-to-target variations in the detection efficiency.

  11. Detection of Mismatch Repair Deficiency and Microsatellite Instability in Colorectal Adenocarcinoma by Targeted Next-Generation Sequencing.

    Science.gov (United States)

    Nowak, Jonathan A; Yurgelun, Matthew B; Bruce, Jacqueline L; Rojas-Rudilla, Vanesa; Hall, Dimity L; Shivdasani, Priyanka; Garcia, Elizabeth P; Agoston, Agoston T; Srivastava, Amitabh; Ogino, Shuji; Kuo, Frank C; Lindeman, Neal I; Dong, Fei

    2017-01-01

    Mismatch repair protein deficiency (MMR-D) and high microsatellite instability (MSI-H) are features of Lynch syndrome-associated colorectal carcinomas and have implications in clinical management. We evaluate the ability of a targeted next-generation sequencing panel to detect MMR-D and MSI-H based on mutational phenotype. Using a criterion of >40 total mutations per megabase or >5 single-base insertion or deletion mutations in repeats per megabase, sequencing achieves 92% sensitivity and 100% specificity for MMR-D by immunohistochemistry in a training cohort of 149 colorectal carcinomas and 91% sensitivity and 98% specificity for MMR-D in a validation cohort of 94 additional colorectal carcinomas. False-negative samples are attributable to tumor heterogeneity, and next-generation sequencing results are concordant with analysis of microsatellite loci by PCR. In a subset of 95 carcinomas with microsatellite analysis, sequencing achieves 100% sensitivity and 99% specificity for MSI-H in the combined training and validation set. False-positive results for MMR-D and MSI-H are attributable to ultramutated cancers with POLE mutations, which are confirmed by direct sequencing of the POLE gene and are detected by mutational signature analysis. These findings provide a framework for a targeted tumor sequencing panel to accurately detect MMR-D and MSI-H in colorectal carcinomas. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  12. Porous Silicon-Based Biosensors: Towards Real-Time Optical Detection of Target Bacteria in the Food Industry

    Science.gov (United States)

    Massad-Ivanir, Naama; Shtenberg, Giorgi; Raz, Nitzan; Gazenbeek, Christel; Budding, Dries; Bos, Martine P.; Segal, Ester

    2016-11-01

    Rapid detection of target bacteria is crucial to provide a safe food supply and to prevent foodborne diseases. Herein, we present an optical biosensor for identification and quantification of Escherichia coli (E. coli, used as a model indicator bacteria species) in complex food industry process water. The biosensor is based on a nanostructured, oxidized porous silicon (PSi) thin film which is functionalized with specific antibodies against E. coli. The biosensors were exposed to water samples collected directly from process lines of fresh-cut produce and their reflectivity spectra were collected in real time. Process water were characterized by complex natural micro-flora (microbial load of >107 cell/mL), in addition to soil particles and plant cell debris. We show that process water spiked with culture-grown E. coli, induces robust and predictable changes in the thin-film optical interference spectrum of the biosensor. The latter is ascribed to highly specific capture of the target cells onto the biosensor surface, as confirmed by real-time polymerase chain reaction (PCR). The biosensors were capable of selectively identifying and quantifying the target cells, while the target cell concentration is orders of magnitude lower than that of other bacterial species, without any pre-enrichment or prior processing steps.

  13. Peroxisomal Targeting as a Sensitive Tool to Detect Protein-Small RNA Interactions through in Vivo Piggybacking

    Directory of Open Access Journals (Sweden)

    Marco Incarbone

    2018-02-01

    Full Text Available Peroxisomes are organelles that play key roles in eukaryotic metabolism. Their protein complement is entirely imported from the cytoplasm thanks to a unique pathway that is able to translocate folded proteins and protein complexes across the peroxisomal membrane. The import of molecules bound to a protein targeted to peroxisomes is an active process known as ‘piggybacking’ and we have recently shown that P15, a virus-encoded protein possessing a peroxisomal targeting sequence, is able to piggyback siRNAs into peroxisomes. Here, we extend this observation by analyzing the small RNA repertoire found in peroxisomes of P15-expressing plants. A direct comparison with the P15-associated small RNA retrieved during immunoprecipitation (IP experiments, revealed that in vivo piggybacking coupled to peroxisome isolation could be a more sensitive means to determine the various small RNA species bound by a given protein. This increased sensitivity of peroxisome isolation as opposed to IP experiments was also striking when we analyzed the small RNA population bound by the Tomato bushy stunt virus-encoded P19, one of the best characterized viral suppressors of RNA silencing (VSR, artificially targeted to peroxisomes. These results support that peroxisomal targeting should be considered as a novel/alternative experimental approach to assess in vivo interactions that allows detection of labile binding events. The advantages and limitations of this approach are discussed.

  14. Detection and analysis of tau-neutrino interactions in DONUT emulsion target

    CERN Document Server

    Kodama, K; Tzanakos, G S; Baller, B; Lundberg, B; Rameika, R; Song, J S; Yoon, C S; Chung, S H; Aoki, S; Hara, T; Erickson, C; Heller, K; Schwienhorst, R; Sielaff, J; Trammell, J; Hoshino, K; Jiko, H; Kawada, J; Kawai, T; Komatsu, M; Matsuoka, H; Miyanishi, M; Nakamura, M; Nakano, T; Narita, K; Niwa, K; Nonaka, N; Okada, K; Sato, O; Toshito, T; Paolone, V; Kafka, T

    2002-01-01

    The DONUT experiment used an emulsion/counter-hybrid-detector, which succeeded in detecting tau-neutrino charged-current interactions. A new method of emulsion analysis, NETSCAN, was used to locate neutrino events and detect tau decays. It is based on a fully automated emulsion readout system (Ultra Track Selector) developed at Nagoya University. The achieved plate-to-plate alignment accuracy of approx 0.2 mu m over an area of 2.6 mmx2.6 mm permitted an efficient and systematic tau decay search using emulsion data. Moreover, this accuracy allowed measurement of particle momenta by multiple Coulomb scattering, and contributed to the efficient background rejection for the nu subtau candidates. This paper describes details of our emulsion analysis methods.

  15. A Targeted Attack For Enhancing Resiliency of Intelligent Intrusion Detection Modules in Energy Cyber Physical Systems

    Energy Technology Data Exchange (ETDEWEB)

    Youssef, Tarek [Florida Intl Univ., Miami, FL (United States); El Hariri, Mohammad [Florida Intl Univ., Miami, FL (United States); Habib, Hani [Florida Intl Univ., Miami, FL (United States); Mohammed, Osama [Florida Intl Univ., Miami, FL (United States); Harmon, E [Florida Intl Univ., Miami, FL (United States)

    2017-02-28

    Abstract— Secure high-speed communication is required to ensure proper operation of complex power grid systems and prevent malicious tampering activities. In this paper, artificial neural networks with temporal dependency are introduced for false data identification and mitigation for broadcasted IEC 61850 SMV messages. The fast responses of such intelligent modules in intrusion detection make them suitable for time- critical applications, such as protection. However, care must be taken in selecting the appropriate intelligence model and decision criteria. As such, this paper presents a customizable malware script to sniff and manipulate SMV messages and demonstrates the ability of the malware to trigger false positives in the neural network’s response. The malware developed is intended to be as a vaccine to harden the intrusion detection system against data manipulation attacks by enhancing the neural network’s ability to learn and adapt to these attacks.

  16. Quantitative Detection of Clostridium perfringens in Broiler Chickens by Real-Time PCR Targeting the Alpha-Toxin Gene

    DEFF Research Database (Denmark)

    Abildgaard, Lone; Engberg, Ricarda M.; Schramm, Andreas

    2006-01-01

    QUANTITATIVE DETECTION OF CLOSTRIDIUM PERFRINGENS IN BROILER CHICKENS BY REAL-TIME PCR TARGETING THE ALPHA-TOXIN GENE L. Abildgaard 1, R.M. Engberg 1, A. Schramm 2, O. Højberg 1 1 Danish Institute of Agricultural Sciences, Department of Animal Health, Welfare and Nutrition, Tjele, Denmark; 2...... University of Aarhus, Institute of Biological Sciences, Department of Microbiology, Aarhus, Denmark Necrotic enteritis is a severe gastrointestinal disease in broiler chickens caused by C. perfringens producing α-toxin (phospholipase C). The incidence of necrotic enteritis in broilers has been reduced...... by antibiotics (ionophores) presently used to prevent parasitic coccidiosis. From 2012 the European Union has banned these anticoccidials as feed additives, wherefore alternatives are needed to suppress C. perfringens and/or α-toxin production. A real-time PCR primer-probe set targeting the α-toxin gene...

  17. Experimental Study of High-Range-Resolution Medical Acoustic Imaging for Multiple Target Detection by Frequency Domain Interferometry

    Science.gov (United States)

    Kimura, Tomoki; Taki, Hirofumi; Sakamoto, Takuya; Sato, Toru

    2009-07-01

    We employed frequency domain interferometry (FDI) for use as a medical acoustic imager to detect multiple targets with high range resolution. The phase of each frequency component of an echo varies with the frequency, and target intervals can be estimated from the phase variance. This processing technique is generally used in radar imaging. When the interference within a range gate is coherent, the cross correlation between the desired signal and the coherent interference signal is nonzero. The Capon method works under the guiding principle that output power minimization cancels the desired signal with a coherent interference signal. Therefore, we utilize frequency averaging to suppress the correlation of the coherent interference. The results of computational simulations using a pseudoecho signal show that the Capon method with adaptive frequency averaging (AFA) provides a higher range resolution than a conventional method. These techniques were experimentally investigated and we confirmed the effectiveness of the proposed method of processing by FDI.

  18. Analytical Approach to Target Detection and Localization at High-Frequency Bands Using Multipath Propagation

    Science.gov (United States)

    2016-04-25

    coherent integrating the backscattering signal, we propose a 3D propagation model that is useful not only in explaining the mechanisms of wave ...and Propagation and North American Radio Science Meeting, APS/URSI 2015 Conf. venue: Vancouver, BC, Canada Title: A 3D Model To Characterize...reflections and diffractions. However, this model still validates for indoor propagation . From this field, we can then detect and predict precisely the

  19. Direct detection of diarrheagenic Aeromonas from faeces by polymerase chain reaction (PCR) targeting aerolysin toxin gene.

    Science.gov (United States)

    Kannan, S; Suresh Kanna, P; Karkuzhali, K; Chattopadhyay, U K; Pal, D

    2001-01-01

    Detection of diarrheagenic Aeromonas specific aerolysin toxin (Aer) gene by PCR based assay and isolation, identification of diarrhea causing Aeromonas from faeces by culture methods were carried out in the Division of Active Surveillance, National Institute of Cholera and Enteric Diseases (NICED), Kolkata, India for a period of 12 months. Out of 602 faecal samples collected from patients with acute diarrhea admitted in Infectious Diseases (ID) Hospital, Kolkata, 68 (11.29%) samples were found to be possessing Aer gene by PCR technique. The conventional culture methods using selective media yielded only 64 (10.6%) Aeromonas strains from the same faecal samples. The different Aeromonas species possessing Aer gene identified by PCR based technique include A. hydrophila (55.8%), A. caviae (17.6%), A. veronii (10.2%), A. schubertii (4.4%), A. jandaei (2.9%) and A. trota (8.8%). The isolation and identification of Aeromonas by routine culture did not detect enterotoxigenic A. trota present in four diarrheal faecal samples. The failure of the growth of enterotoxigenic A. trota on selective media may be attributed to the ampicillin susceptibility of those strains. The quality control studies revealed that PCR method for the direct detection of Aer gene from the faeces has the sensitivity of 100% and specificity of 98%.

  20. SPIDERS: selection of spectroscopic targets using AGN candidates detected in all-sky X-ray surveys

    Science.gov (United States)

    Dwelly, T.; Salvato, M.; Merloni, A.; Brusa, M.; Buchner, J.; Anderson, S. F.; Boller, Th.; Brandt, W. N.; Budavári, T.; Clerc, N.; Coffey, D.; Del Moro, A.; Georgakakis, A.; Green, P. J.; Jin, C.; Menzel, M.-L.; Myers, A. D.; Nandra, K.; Nichol, R. C.; Ridl, J.; Schwope, A. D.; Simm, T.

    2017-07-01

    SPIDERS (SPectroscopic IDentification of eROSITA Sources) is a Sloan Digital Sky Survey IV (SDSS-IV) survey running in parallel to the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) cosmology project. SPIDERS will obtain optical spectroscopy for large numbers of X-ray-selected active galactic nuclei (AGN) and galaxy cluster members detected in wide-area eROSITA, XMM-Newton and ROSAT surveys. We describe the methods used to choose spectroscopic targets for two sub-programmes of SPIDERS X-ray selected AGN candidates detected in the ROSAT All Sky and the XMM-Newton Slew surveys. We have exploited a Bayesian cross-matching algorithm, guided by priors based on mid-IR colour-magnitude information from the Wide-field Infrared Survey Explorer survey, to select the most probable optical counterpart to each X-ray detection. We empirically demonstrate the high fidelity of our counterpart selection method using a reference sample of bright well-localized X-ray sources collated from XMM-Newton, Chandra and Swift-XRT serendipitous catalogues, and also by examining blank-sky locations. We describe the down-selection steps which resulted in the final set of SPIDERS-AGN targets put forward for spectroscopy within the eBOSS/TDSS/SPIDERS survey, and present catalogues of these targets. We also present catalogues of ˜12 000 ROSAT and ˜1500 XMM-Newton Slew survey sources that have existing optical spectroscopy from SDSS-DR12, including the results of our visual inspections. On completion of the SPIDERS programme, we expect to have collected homogeneous spectroscopic redshift information over a footprint of ˜7500 deg2 for >85 per cent of the ROSAT and XMM-Newton Slew survey sources having optical counterparts in the magnitude range 17 < r < 22.5, producing a large and highly complete sample of bright X-ray-selected AGN suitable for statistical studies of AGN evolution and clustering.

  1. Cost-Effectiveness of Magnetic Resonance Imaging and Targeted Fusion Biopsy for Early Detection of Prostate Cancer.

    Science.gov (United States)

    Barnett, Christine L; Davenport, Matthew S; Montgomery, Jeffrey S; Wei, John T; Montie, James E; Denton, Brian T

    2018-02-01

    To determine how best to use MRI and targeted MR/ultrasound fusion biopsy for early detection of prostate cancer in men with elevated PSA and whether it can be cost-effective. A Markov model of prostate cancer onset and progression was developed to estimate health and economic consequences of prostate cancer screening with MRI. Men were screened with prostate-specific antigen (PSA) from ages 55 to 69. Men with elevated PSA (>4 ng/mL) received an MRI, followed by targeted fusion or combined (standard + targeted fusion) biopsy on positive MRI, and standard or no biopsy on negative MRI. Prostate imaging reporting and data system (PI-RADS) score on MRI determined biopsy decisions. Deaths averted, quality-adjusted life years (QALYs), cost, and incremental cost-effectiveness ratio (ICER) were estimated for each strategy. With a negative MRI, standard biopsy was more expensive and had lower QALYs than performing no biopsy. The optimal screening strategy (ICER: $23,483/QALY) recommended combined biopsy for men with PI-RADS score ≥3 and no biopsy for men with PI-RADS score <3, and reduced the number of screening biopsies by 15%. Threshold analysis suggests MRI continues to be cost-effective when sensitivity and specificity of MRI and combined biopsy are simultaneously reduced by 19.0. Our analysis suggests MRI followed by targeted MR/ultrasound fusion biopsy can be a cost-effective approach for early detection of prostate cancer. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  2. Antibody targeting of phosphatidylserine for the detection and immunotherapy of cancer

    Directory of Open Access Journals (Sweden)

    Belzile O

    2018-01-01

    Full Text Available Olivier Belzile,1 Xianming Huang,2,3 Jian Gong,2,3 Jay Carlson,2,3 Alan J Schroit,1 Rolf A Brekken,1 Bruce D Freimark2,3 1Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TX, 2Department of Preclinical Research, 3Department of Antibody Discovery, Peregrine Pharmaceuticals, Inc., Tustin, CA, USA Abstract: Phosphatidylserine (PS is a negatively charged phospholipid in all eukaryotic cells that is actively sequestered to the inner leaflet of the cell membrane. Exposure of PS on apoptotic cells is a normal physiological process that triggers their rapid removal by phagocytic engulfment under noninflammatory conditions via receptors primarily expressed on immune cells. PS is aberrantly exposed in the tumor microenvironment and contributes to the overall immunosuppressive signals that antagonize the development of local and systemic antitumor immune responses. PS-mediated immunosuppression in the tumor microenvironment is further exacerbated by chemotherapy and radiation treatments that result in increased levels of PS on dying cells and necrotic tissue. Antibodies targeting PS localize to tumors and block PS-mediated immunosuppression. Targeting exposed PS in the tumor microenvironment may be a novel approach to enhance immune responses to cancer. Keywords: immunosuppression, tumor microenvironment, immunotherapy, imaging, phosphatidylserine, bavituximab

  3. Critical evaluation of magnetic resonance imaging targeted, transrectal ultrasound guided transperineal fusion biopsy for detection of prostate cancer.

    Science.gov (United States)

    Kuru, Timur H; Roethke, Matthias C; Seidenader, Jonas; Simpfendörfer, Tobias; Boxler, Silvan; Alammar, Khalid; Rieker, Philip; Popeneciu, Valentin I; Roth, Wilfried; Pahernik, Sascha; Schlemmer, Heinz-Peter; Hohenfellner, Markus; Hadaschik, Boris A

    2013-10-01

    Diagnosis and precise risk stratification of prostate cancer is essential for individualized treatment decisions. Magnetic resonance imaging/transrectal ultrasound fusion has shown encouraging results for detecting clinically significant prostate cancer. We critically evaluated magnetic resonance imaging targeted, transrectal ultrasound guided transperineal fusion biopsy in routine clinical practice. Included in this prospective study were 347 consecutive patients with findings suspicious for prostate cancer. Median age was 65 years (range 42 to 84) and mean prostate specific antigen was 9.85 ng/ml (range 0.5 to 104). Of the men 49% previously underwent transrectal ultrasound guided biopsies, which were negative, and 51% underwent primary biopsy. In all patients 3 Tesla multiparametric magnetic resonance imaging was done. Systematic stereotactic prostate biopsies plus magnetic resonance imaging targeted, transrectal ultrasound guided biopsies were performed in those with abnormalities on magnetic resonance imaging. Imaging data and biopsy results were analyzed. A self-designed questionnaire was sent to all men on further clinical history and biopsy adverse effects. Of 347 patients biopsy samples of 200 (58%) showed prostate cancer and 73.5% of biopsy proven prostate cancer were clinically relevant according to National Comprehensive Cancer Network (NCCN) criteria. On multiparametric magnetic resonance imaging 104 men had findings highly suspicious for prostate cancer. The tumor detection rate was 82.6% (86 of 104 men) with a Gleason score of 7 or greater in 72%. Overall targeted cores detected significantly more cancer than systematic biopsies (30% vs 8.2%). Of 94 patients without cancer suspicious lesions on magnetic resonance imaging 11 (11.7%) were diagnosed with intermediate risk disease. Regarding adverse effects, 152 of 300 patients (50.6%) reported mild hematuria, 26% had temporary erectile dysfunction and 2.6% needed short-term catheterization after biopsy

  4. A rapid assay for detection of Rose rosette virus using reverse transcription-recombinase polymerase amplification using multiple gene targets.

    Science.gov (United States)

    Babu, Binoy; Washburn, Brian K; Miller, Steven H; Poduch, Kristina; Sarigul, Tulin; Knox, Gary W; Ochoa-Corona, Francisco M; Paret, Mathews L

    2017-02-01

    Rose rosette disease caused by Rose rosette virus (RRV; genus Emaravirus) is the most economically relevant disease of Knock Out® series roses in the U.S. As there are no effective chemical control options for the disease, the most critical disease management strategies include the use of virus free clean plants for propagation and early detection and destruction of infected plants. The current diagnostic techniques for RRV including end-point reverse transcription-polymerase chain reaction (RT-PCR) and real-time PCR (RT-qPCR) are highly sensitive, but limited to diagnostic labs with the equipment and expertise; and is time consuming. To address this limitation, an isothermal reverse transcription-recombinase polymerase amplification (RT-RPA) assay based on multiple gene targets for specific detection of RRV was developed. The assay is highly specific and did not cross react with other viruses belonging to the inclusive and exclusive genus. Dilution assays using the in vitro transcripts showed that the primer sets designed (RPA-267, RPA-131, and RPA-321) are highly sensitive, consistently detecting RRV with a detection limit of 1fg/μL. Testing of the infected plants using the primer sets indicated that the virus could be detected from leaves, stems and petals of roses. The primer pair RPA-267 produced 100% positive detection of the virus from infected leaf tissues, while primer set RPA-131 produced 100% detection from stems and petals. The primer set RPA-321 produced 83%, 87.5% and 75% positive detection from leaves, petals and stem tissues, respectively. In addition, the assay has been efficiently used in the detection of RRV infecting Knock Out® roses, collected from different states in the U.S. The assay can be completed in 20min as compared to the end-point RT-PCR assay (3-4h) and RT-qPCR (1.5h). The RT-RPA assay is reliable, rapid, highly sensitive, and can be easily used in diagnostic laboratories for detection of RRV with no need for any special equipment

  5. Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data

    DEFF Research Database (Denmark)

    Krøigård, Anne Bruun; Thomassen, Mads; Lænkholm, Anne-Vibeke

    2016-01-01

    and matched normal tissue in order to detect somatic mutations. The advent of many new somatic variant callers creates a need for comparison and validation of the tools, as no de facto standard for detection of somatic mutations exists and only limited comparisons have been reported. We have performed......Next generation sequencing is extensively applied to catalogue somatic mutations in cancer, in research settings and increasingly in clinical settings for molecular diagnostics, guiding therapy decisions. Somatic variant callers perform paired comparisons of sequencing data from cancer tissue...... a comprehensive evaluation using exome sequencing and targeted deep sequencing data of paired tumor-normal samples from five breast cancer patients to evaluate the performance of nine publicly available somatic variant callers: EBCall, Mutect, Seurat, Shimmer, Indelocator, Somatic Sniper, Strelka, VarScan 2...

  6. Novel Method of Unambiguous Moving Target Detection in Pulse-Doppler Radar with Random Pulse Repetition Interval

    Directory of Open Access Journals (Sweden)

    Liu Zhen

    2012-03-01

    Full Text Available Blind zones and ambiguities in range and velocity measurement are two important issues in traditional pulse-Doppler radar. By generating random deviations with respect to a mean Pulse Repetition Interval (PRI, this paper proposes a novel algorithm of Moving Target Detection (MTD based on the Compressed Sensing (CS theory, in which the random deviations of the PRIare converted to the Restricted Isometry Property (RIP of the observing matrix. The ambiguities of range and velocity are eliminated by designing the signal parameters. The simulation results demonstrate that this scheme has high performance of detection, and there is no ambiguity and blind zones as well. It can also shorten the coherent processing interval compared to traditional staggered PRI mode because only one pulse train is needed instead of several trains.

  7. Quantitative Detection of Methanotrophs in Soil by Novel pmoA-Targeted Real-Time PCR Assays

    Science.gov (United States)

    Kolb, Steffen; Knief, Claudia; Stubner, Stephan; Conrad, Ralf

    2003-01-01

    Methane oxidation in soils is mostly accomplished by methanotrophic bacteria. Little is known about the abundance of methanotrophs in soils, since quantification by cultivation and microscopic techniques is cumbersome. Comparison of 16S ribosomal DNA and pmoA (α subunit of the particulate methane monooxygenase) phylogenetic trees showed good correlation and revealed five distinct groups of methanotrophs within the α and γ subclasses of Proteobacteria: the Methylococcus group, the Methylobacter/Methylosarcina group, the Methylosinus group, the Methylocapsa group, and the forest clones group (a cluster of pmoA sequences retrieved from forest soils). We developed quantitative real-time PCR assays with SybrGreen for each of these five groups and for all methanotrophic bacteria by targeting the pmoA gene. Detection limits were between 101 and 102 target molecules per reaction for all assays. Real-time PCR analysis of soil samples spiked with cells of Methylococcus capsulatus, Methylomicrobium album, and Methylosinus trichosporium recovered almost all the added bacteria. Only the Methylosinus-specific assay recovered only 20% of added cells, possibly due to a lower lysis efficiency of type II methanotrophs. Analysis of the methanotrophic community structure in a flooded rice field soil showed (5.0 ± 1.4) × 106 pmoA molecules g−1 for all methanotrophs. The Methylosinus group was predominant (2.7 × 106 ± 1.1 × 106 target molecules g−1). In addition, bacteria of the Methylobacter/Methylosarcina group were abundant (2.0 × 106 ± 0.9 × 106 target molecules g of soil−1). On the other hand, pmoA affiliated with the forest clones and the Methylocapsa group was below the detection limit of 1.9 × 104 target molecules g of soil−1. Our results showed that pmoA-targeted real-time PCR allowed fast and sensitive quantification of the five major groups of methanotrophs in soil. This approach will thus be useful for quantitative analysis of the community structure of

  8. Ultramild protein-mediated click chemistry creates efficient oligonucleotide probes for targeting and detecting nucleic acids

    DEFF Research Database (Denmark)

    Nåbo, Lina J.; Madsen, Charlotte Stahl; Jensen, Knud Jørgen

    2015-01-01

    Functionalized synthetic oligonucleotides are finding growing applications in research, clinical studies, and therapy. However, it is not easy to prepare them in a biocompatible and highly efficient manner. We report a new strategy to synthesize oligonucleotides with promising nucleic acid...... conditions with fluorophore, peptide, and carbohydrate azide derivatives. In thermal denaturation studies, the modified probes showed specific binding to complementary DNA and RNA targets. Finally, we demonstrated the pH sensitivity of the new rhodamine-based fluorescent probes in vitro and rationalize our...... results by electronic structure calculations. Functionalized oligonucleotides were prepared in good yields by protein-mediated CuAAC click reactions for the first time with a human copper-binding chaperon. The carbohydrate, peptide, and fluorescent derivatives display high binding affinity and selectivity...

  9. RVD: a command-line program for ultrasensitive rare single nucleotide variant detection using targeted next-generation DNA resequencing.

    Science.gov (United States)

    Cushing, Anna; Flaherty, Patrick; Hopmans, Erik; Bell, John M; Ji, Hanlee P

    2013-05-23

    Rare single nucleotide variants play an important role in genetic diversity and heterogeneity of specific human disease. For example, an individual clinical sample can harbor rare mutations at minor frequencies. Genetic diversity within an individual clinical sample is oftentimes reflected in rare mutations. Therefore, detecting rare variants prior to treatment may prove to be a useful predictor for therapeutic response. Current rare variant detection algorithms using next generation DNA sequencing are limited by inherent sequencing error rate and platform availability. Here we describe an optimized implementation of a rare variant detection algorithm called RVD for use in targeted gene resequencing. RVD is available both as a command-line program and for use in MATLAB and estimates context-specific error using a beta-binomial model to call variants with minor allele frequency (MAF) as low as 0.1%. We show that RVD accepts standard BAM formatted sequence files. We tested RVD analysis on multiple Illumina sequencing platforms, among the most widely used DNA sequencing platforms. RVD meets a growing need for highly sensitive and specific tools for variant detection. To demonstrate the usefulness of RVD, we carried out a thorough analysis of the software's performance on synthetic and clinical virus samples sequenced on both an Illumina GAIIx and a MiSeq. We expect RVD can improve understanding the genetics and treatment of common viral diseases including influenza. RVD is available at the following URL:http://dna-discovery.stanford.edu/software/rvd/.

  10. Microscale sample deposition onto hydrophobic target plates for trace level detection of neuropeptides in brain tissue by MALDI-MS.

    Science.gov (United States)

    Wei, Hui; Dean, Stacey L; Parkin, Mark C; Nolkrantz, Kerstin; O'Callaghan, James P; Kennedy, Robert T

    2005-10-01

    A sample preparation method that combines a modified target plate with a nanoscale reversed-phase column (nanocolumn) was developed for detection of neuropeptides by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). A gold-coated MALDI plate was modified with an octadecanethiol (ODT) self-assembled monolayer to create a hydrophobic surface that could concentrate peptide samples into a approximately 200-500-microm diameter spot. The spot sizes generated were comparable to those obtained for a substrate patterned with 200-microm hydrophilic spots on a hydrophobic substrate. The sample spots on the ODT-coated plate were 100-fold smaller than those formed on an unmodified gold plate with a 1-microl sample and generated 10 to 50 times higher mass sensitivity for peptide standards by MALDI-TOF MS. When the sample was deposited on an ODT-modified plate from a nanocolumn, the detection limit for peptides was as low as 20 pM for 5-microl samples corresponding to 80 amol deposited. This technique was used to analyze extracts of microwave-fixed tissue from rat brain striatum. Ninety-eight putative peptides were detected including several that had masses matching neuropeptides expected in this brain region such as substance P, rimorphin, and neurotensin. Twenty-three peptides had masses that matched peaks detected by capillary liquid chromatography with electrospray ionization MS. Copyright (c) 2005 John Wiley & Sons, Ltd.

  11. Detection of Salmonella spp. survival and virulence in poultry feed by targeting the hilA gene.

    Science.gov (United States)

    Park, S H; Jarquin, R; Hanning, I; Almeida, G; Ricke, S C

    2011-08-01

    The objectives of this work were to evaluate immunomagnetic beads and a reverse transcriptase (RT)-PCR method for the detection of Salmonella inoculated into feed. In addition, a reverse transcriptase (RT)-PCR method was evaluated for quantifying virulence gene hilA expression of Salmonella ssp. in poultry feed matrices and utilized to determine the influence of poultry feed environmental factors on Salmonella hilA expression. An immunomagnetic separation technique was evaluated for increased recovery of Salmonella from feed. Salmonella cultures were inoculated into feed samples and exposed to heat treatments of 70°C and sampled periodically. From these samples, RNA was collected and hilA gene expression was measured relative to the housekeeping 16S rRNA gene. The immunomagnetic bead protocol increased recovery by 1 log. The up-regulation of hilA was demonstrated after 5 and 10 min of inoculated feed samples being exposed to heat treatment. From this work, the data indicate that the ability to detect live Salmonella cells in feed samples may be increased by targeting the hilA gene. Foodborne salmonellosis originating from poultry is a major problem, and feed is a leading source of contamination in poultry, but detection in feed is complicated by low concentrations. The assays and experiments in this study examine possible improvements to recovery and detection of Salmonella in feed. © 2011 The Authors. Journal of Applied Microbiology © 2011 The Society for Applied Microbiology.

  12. Sentinel lymph node biopsy revisited: ultrasound-guided photoacoustic detection of micrometastases using molecularly targeted plasmonic nanosensors

    Science.gov (United States)

    Luke, Geoffrey P.; Myers, Jeffrey N.; Emelianov, Stanislav Y.; Sokolov, Konstantin V.

    2014-01-01

    Metastases rather than primary tumors are responsible for killing most cancer patients. Cancer cells often invade regional lymph nodes (LN) before colonizing other parts of the body. However, due to the low sensitivity and specificity of current imaging methods to detect localized nodal spread, an invasive surgical procedure - sentinel lymph node biopsy - is generally employed to identify metastatic cancer cells. Here we introduce a new approach for more sensitive in vivo detection of lymph node micrometastases, based on the use of ultrasound-guided spectroscopic photoacoustic (sPA) imaging of molecularly-activated plasmonic nanosensors (MAPS). Using a metastatic murine model of oral squamous cell carcinoma, we showed that MAPS targeted to the EGFR shifted their optical absorption spectrum to the red-near-infrared region after specific interactions with nodal metastatic cells, enabling their non-invasive detection by sPA. Notably, LN metastases as small as 50 μm were detected at centimeter-depth range with high sensitivity and specificity. Large sPA signals appeared in metastatic LN within 30 minutes of MAPS injection, in support of the clinical utility of this method. Our findings offer a rapid and effective tool to non-invasively identify micrometastases as an alternate to sentinal node biopsy analysis. PMID:25106426

  13. Cost-effective and label-free holographic biosensor for detection of herpes simplex virus (Conference Presentation)

    Science.gov (United States)

    Ray, Aniruddha; Ho, Ha; Daloglu, Mustafa; Torres, Avee; McLeod, Euan; Ozcan, Aydogan

    2017-03-01

    Herpes is one of the most widespread sexually transmitted viral diseases. Timely detection of Herpes Simplex Virus (HSV) can help prevent the rampant spreading of the virus. Current detection techniques such as viral culture, immuno-assays or Polymerase-Chain-Reaction, are time extensive and require expert handling. Here we present a field-portable, easy-to-use, and cost-effective biosensor for the detection of HSV based on holographic imaging. The virus is first captured from a target solution onto specifically developed substrates, prepared by coating glass coverslips with HSV-specific antibodies, and imaged using a lensfree holographic microscope. Several light-emitting-diodes (LEDs), coupled to multi-mode optical-fibers, are used to illuminate the sample containing the viruses. A micro-controller is used to activate the LEDs one at a time and in-line holograms are recorded using a CMOS imager placed immediately above the substrate. These sub-pixel shifted holograms are used to generate a super-resolved hologram, which is reconstructed to obtain the phase and amplitude images of the viruses. The signal of the viruses is enhanced using self-assembled PEG-based nanolenses, formed around the viral particles. Based on the phase information of the reconstructed images we can estimate the size of the viral particles, with an accuracy of +/- 11 nm, as well as quantify the viral load. The limit-of-detection of this system is estimated to be <500 viral copies per 100 μL sample volume that is imaged over 30 mm^2 field-of-view. This holographic microscopy based biosensor is label-free, cost-effective and field-portable, providing results in 2 hours, including sample preparation and imaging time.

  14. The study of concentration effects of target hybridization on cervical cancer detection using interdigitated electrodes (IDE)

    Science.gov (United States)

    Noriani, C.; Hashim, U.; Azizah, N.

    2016-07-01

    Human Papilloma Virus (HPV) is a virus from the Papilloma virus family that affects human skin and the moist membranes that line the body, such as the throat, mouth, feet, fingers, nails, anus and cervix [1]. There are over 100 types, of which 40 can affect the genital area. Most known HPV types cause no symptoms to humans. Some, however, can cause verrucae (warts), while a small number can increase the risk of developing several cancers, such as that of the cervix, penis, vagina, anus and oropharynx (oral part of the pharynx - throat cancer). HPV strand 16 and 18 are well known for causing the advanced of Cervical Cancer (CC). Currently, integrated electrodes (IDEs) are implemented in various sensing devices including surface acoustic wave (SAW) sensors, chemical sensors as well as current MEMS biosensors. IDEs have been optimized for a variety of sensing applications including biosensors sensors, acoustic sensors, and chemical sensors. However, optimization for cancer cell detection has yet to be reported. The output signal strength of IDEs is controlled through careful design of the active area, width, and spacing of the electrode fingers the efficiency of DNA nanochip depends mainly on the sequence of the capture probes and the way they are attached to the support [2]. This strategy presented a simple, rapid and sensitive platform for HPV detection and would become a powerful tool for pathogenic microorganisms screening in clinical diagnosis. The coupling procedure must be quick, covalent, and reproducible.

  15. SERPINA1 Full-Gene Sequencing Identifies Rare Mutations Not Detected in Targeted Mutation Analysis.

    Science.gov (United States)

    Graham, Rondell P; Dina, Michelle A; Howe, Sarah C; Butz, Malinda L; Willkomm, Kurt S; Murray, David L; Snyder, Melissa R; Rumilla, Kandelaria M; Halling, Kevin C; Highsmith, W Edward

    2015-11-01

    Genetic α-1 antitrypsin (AAT) deficiency is characterized by low serum AAT levels and the identification of causal mutations or an abnormal protein. It needs to be distinguished from deficiency because of nongenetic causes, and diagnostic delay may contribute to worse patient outcome. Current routine clinical testing assesses for only the most common mutations. We wanted to determine the proportion of unexplained cases of AAT deficiency that harbor causal mutations not identified through current standard allele-specific genotyping and isoelectric focusing (IEF). All prospective cases from December 1, 2013, to October 1, 2014, with a low serum AAT level not explained by allele-specific genotyping and IEF were assessed through full-gene sequencing with a direct sequencing method for pathogenic mutations. We reviewed the results using American Council of Medical Genetics criteria. Of 3523 cases, 42 (1.2%) met study inclusion criteria. Pathogenic or likely pathogenic mutations not identified through clinical testing were detected through full-gene sequencing in 16 (38%) of the 42 cases. Rare mutations not detected with current allele-specific testing and IEF underlie a substantial proportion of genetic AAT deficiency. Full-gene sequencing, therefore, has the ability to improve accuracy in the diagnosis of AAT deficiency. Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  16. Detection of Aichi virus with antibody targeting of conserved viral protein 1 epitope.

    Science.gov (United States)

    Chen, Yao-Shen; Chen, Bao-Chen; Lin, You-Sheng; Chang, Jenn-Tzong; Huang, Tsi-Shu; Chen, Jih-Jung; Chang, Tsung-Hsien

    2013-10-01

    Aichi virus (AiV) is an emerging single-stranded, positive-sense, non-enveloped RNA virus in the Picornaviridae that causes acute gastroenteritis in humans. The first case of AiV infection in Taiwan was diagnosed in a human neonate with enterovirus-associated symptoms; the virus was successfully isolated and propagated. To establish a method to detect AiV, we analyzed the antigen epitope and generated a polyclonal antibody against AiV viral protein 1 (VP1). This peptide-purified anti-AiV VP1 antibody showed high specificity against AiV VP1 without cross-reaction to nine other tested strains of Picornaviruses. The anti-AiV VP1 antibody was used in immunofluorescence analysis, immunoblotting, and enzyme-linked immunosorbent assay to elucidate the cell tropism and replication kinetics of AiV. Use of the anti-AiV VP1 antibody also revealed AiV infection restriction with interferon type I and polyI/C antiviral treatment. The AiV infection and detection system may provide an in vitro platform for AiV virology study.

  17. Molecular detection of meat animal species targeting MT 12S rRNA gene.

    Science.gov (United States)

    Mahajan, M V; Gadekar, Y P; Dighe, V D; Kokane, R D; Bannalikar, A S

    2011-05-01

    The efficacy of PCR-RFLP analysis of mt 12S rRNA gene in identification of animal species from meat samples of known and unknown origin and adulterated meat samples was evaluated. In PCR, all the samples generated an amplicon of 456 bp. Restriction enzyme digestion of the PCR product with AluI, HhaI, BspTI and ApoI revealed characteristic RFLP patterns. Of the samples of unknown origin few were identified as cattle, few as buffalo and some were admixtures of two, suggesting adulteration. The RFLP pattern of one did not match any of species included in the study, which on sequencing was confirmed as camel meat. Application of this technique on adulterated meat samples could detect both animal species in proportion of 50:50 and 75:25 (except in case of goat+cattle). The technique however could not detect any of the two species when proportion of mixture was 90:10 (except in case of cattle+buffalo). Copyright © 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.

  18. Detection and tracking of human targets in indoor and urban environments using through-the-wall radar sensors

    Science.gov (United States)

    Radzicki, Vincent R.; Boutte, David; Taylor, Paul; Lee, Hua

    2017-05-01

    Radar based detection of human targets behind walls or in dense urban environments is an important technical challenge with many practical applications in security, defense, and disaster recovery. Radar reflections from a human can be orders of magnitude weaker than those from objects encountered in urban settings such as walls, cars, or possibly rubble after a disaster. Furthermore, these objects can act as secondary reflectors and produce multipath returns from a person. To mitigate these issues, processing of radar return data needs to be optimized for recognizing human motion features such as walking, running, or breathing. This paper presents a theoretical analysis on the modulation effects human motion has on the radar waveform and how high levels of multipath can distort these motion effects. From this analysis, an algorithm is designed and optimized for tracking human motion in heavily clutter environments. The tracking results will be used as the fundamental detection/classification tool to discriminate human targets from others by identifying human motion traits such as predictable walking patterns and periodicity in breathing rates. The theoretical formulations will be tested against simulation and measured data collected using a low power, portable see-through-the-wall radar system that could be practically deployed in real-world scenarios. Lastly, the performance of the algorithm is evaluated in a series of experiments where both a single person and multiple people are moving in an indoor, cluttered environment.

  19. Public education and targeted outreach to underserved women through the National Breast and Cervical Cancer Early Detection Program.

    Science.gov (United States)

    Levano, Whitney; Miller, Jacqueline W; Leonard, Banning; Bellick, Linda; Crane, Barbara E; Kennedy, Stephenie K; Haslage, Natalie M; Hammond, Whitney; Tharpe, Felicia S

    2014-08-15

    The National Breast and Cervical Cancer Early Detection Program (NBCCEDP) was established to provide low-income, uninsured, and underinsured women access to cancer screening and diagnostic services with the goal of increasing the early detection and prevention of breast and cervical cancer. Although this is a valuable resource for women who might not have the means to get screened otherwise, providing services at no cost, by itself, does not guarantee uptake of screening services. Public education and targeted outreach facilitate the critical link between public service programs and the communities they serve. The purpose of public education and outreach in the NBCCEDP is to increase the number of women who use breast and cervical cancer screening services by raising awareness, providing education, addressing barriers, and motivating women to complete screening exams and follow-up. Effective strategies focus on helping to remove structural, physical, interpersonal, financial, and cultural barriers; educate women about the importance of screening and inform women about the services available to them. This article provides an overview of the importance of public education and targeted outreach activities for cancer screening through community-based programs including examples from NBCCEDP grantees that highlight successes, challenges, and solutions, encountered when conducting these types of interventions. © 2014 American Cancer Society.

  20. A Novel Method for Proximity Detection of Moving Targets Using a Large-Scale Planar Capacitive Sensor System

    Directory of Open Access Journals (Sweden)

    Yong Ye

    2016-05-01

    Full Text Available A novel method for proximity detection of moving targets (with high dielectric constants using a large-scale (the size of each sensor is 31 cm × 19 cm planar capacitive sensor system (PCSS is proposed. The capacitive variation with distance is derived, and a pair of electrodes in a planar capacitive sensor unit (PCSU with a spiral shape is found to have better performance on sensitivity distribution homogeneity and dynamic range than three other shapes (comb shape, rectangular shape, and circular shape. A driving excitation circuit with a Clapp oscillator is proposed, and a capacitance measuring circuit with sensitivity of 0.21 V p − p / pF is designed. The results of static experiments and dynamic experiments demonstrate that the voltage curves of static experiments are similar to those of dynamic experiments; therefore, the static data can be used to simulate the dynamic curves. The dynamic range of proximity detection for three projectiles is up to 60 cm, and the results of the following static experiments show that the PCSU with four neighboring units has the highest sensitivity (the sensitivities of other units are at least 4% lower; when the attack angle decreases, the intensity of sensor signal increases. This proposed method leads to the design of a feasible moving target detector with simple structure and low cost, which can be applied in the interception system.

  1. Label-free functional nucleic acid sensors for detecting target agents

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Yi; Xiang, Yu

    2015-01-13

    A general methodology to design label-free fluorescent functional nucleic acid sensors using a vacant site approach and an abasic site approach is described. In one example, a method for designing label-free fluorescent functional nucleic acid sensors (e.g., those that include a DNAzyme, aptamer or aptazyme) that have a tunable dynamic range through the introduction of an abasic site (e.g., dSpacer) or a vacant site into the functional nucleic acids. Also provided is a general method for designing label-free fluorescent aptamer sensors based on the regulation of malachite green (MG) fluorescence. A general method for designing label-free fluorescent catalytic and molecular beacons (CAMBs) is also provided. The methods demonstrated here can be used to design many other label-free fluorescent sensors to detect a wide range of analytes. Sensors and methods of using the disclosed sensors are also provided.

  2. Identification of novel candidate target genes in amplicons of Glioblastoma multiforme tumors detected by expression and CGH microarray profiling.

    Science.gov (United States)

    Ruano, Yolanda; Mollejo, Manuela; Ribalta, Teresa; Fiaño, Concepción; Camacho, Francisca I; Gómez, Elena; de Lope, Angel Rodríguez; Hernández-Moneo, Jose-Luis; Martínez, Pedro; Meléndez, Bárbara

    2006-09-26

    Conventional cytogenetic and comparative genomic hybridization (CGH) studies in brain malignancies have shown that glioblastoma multiforme (GBM) is characterized by complex structural and numerical alterations. However, the limited resolution of these techniques has precluded the precise identification of detailed specific gene copy number alterations. We performed a genome-wide survey of gene copy number changes in 20 primary GBMs by CGH on cDNA microarrays. A novel amplicon at 4p15, and previously uncharacterized amplicons at 13q32-34 and 1q32 were detected and are analyzed here. These amplicons contained amplified genes not previously reported. Other amplified regions containing well-known oncogenes in GBMs were also detected at 7p12 (EGFR), 7q21 (CDK6), 4q12 (PDGFRA), and 12q13-15 (MDM2 and CDK4). In order to identify the putative target genes of the amplifications, and to determine the changes in gene expression levels associated with copy number change events, we carried out parallel gene expression profiling analyses using the same cDNA microarrays. We detected overexpression of the novel amplified genes SLA/LP and STIM2 (4p15), and TNFSF13B and COL4A2 (13q32-34). Some of the candidate target genes of amplification (EGFR, CDK6, MDM2, CDK4, and TNFSF13B) were tested in an independent set of 111 primary GBMs by using FISH and immunohistological assays. The novel candidate 13q-amplification target TNFSF13B was amplified in 8% of the tumors, and showed protein expression in 20% of the GBMs. This high-resolution analysis allowed us to propose novel candidate target genes such as STIM2 at 4p15, and TNFSF13B or COL4A2 at 13q32-34 that could potentially contribute to the pathogenesis of these tumors and which would require futher investigations. We showed that overexpression of the amplified genes could be attributable to gene dosage and speculate that deregulation of those genes could be important in the development and progression of GBM. Our findings highlight

  3. Identification of novel candidate target genes in amplicons of Glioblastoma multiforme tumors detected by expression and CGH microarray profiling

    Directory of Open Access Journals (Sweden)

    Hernández-Moneo Jose-Luis

    2006-09-01

    Full Text Available Abstract Background Conventional cytogenetic and comparative genomic hybridization (CGH studies in brain malignancies have shown that glioblastoma multiforme (GBM is characterized by complex structural and numerical alterations. However, the limited resolution of these techniques has precluded the precise identification of detailed specific gene copy number alterations. Results We performed a genome-wide survey of gene copy number changes in 20 primary GBMs by CGH on cDNA microarrays. A novel amplicon at 4p15, and previously uncharacterized amplicons at 13q32-34 and 1q32 were detected and are analyzed here. These amplicons contained amplified genes not previously reported. Other amplified regions containg well-known oncogenes in GBMs were also detected at 7p12 (EGFR, 7q21 (CDK6, 4q12 (PDGFRA, and 12q13-15 (MDM2 and CDK4. In order to identify the putative target genes of the amplifications, and to determine the changes in gene expression levels associated with copy number change events, we carried out parallel gene expression profiling analyses using the same cDNA microarrays. We detected overexpression of the novel amplified genes SLA/LP and STIM2 (4p15, and TNFSF13B and COL4A2 (13q32-34. Some of the candidate target genes of amplification (EGFR, CDK6, MDM2, CDK4, and TNFSF13B were tested in an independent set of 111 primary GBMs by using FISH and immunohistological assays. The novel candidate 13q-amplification target TNFSF13B was amplified in 8% of the tumors, and showed protein expression in 20% of the GBMs. Conclusion This high-resolution analysis allowed us to propose novel candidate target genes such as STIM2 at 4p15, and TNFSF13B or COL4A2 at 13q32-34 that could potentially contribute to the pathogenesis of these tumors and which would require futher investigations. We showed that overexpression of the amplified genes could be attributable to gene dosage and speculate that deregulation of those genes could be important in the development

  4. Detection of miR-33 Expression and the Verification of Its Target Genes in the Fatty Liver of Geese

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    Yun Zheng

    2015-06-01

    Full Text Available Background: miRNAs are single-stranded, small RNA molecules with a length of 18–25 nucleotides. They bind to the 3′ untranslated regions of mRNA transcripts to reduce the translation of these transcripts or to cause their degradation. The roles of these molecules differ in biological processes, such as cell differentiation, proliferation, apoptosis and tumor genesis. miRNA-33 is encoded by the gene introns of proteins that bind sterol-regulatory elements. This molecule cooperates with these proteins to control cholesterol homeostasis, fatty acid levels and the genes that are related to the expression of fat metabolism. The examination of miR-33 expression and its target genes can promote the in-depth study of the miRNA regulation mechanism in the formation process of goose fatty liver and can lay a foundation for research into human fatty liver. Methodology/principal findings: (1 Through real-time fluorescent quantitative polymerase chain reaction (TaqMan MicroRNA Assay, we detected the expression of miR-33 during the feeding of Landes geese. The expression level of miR-33 increases significantly in the liver after 19 days in comparison with the control group; (2 By using the bioinformatics software programs TargetScan, miRDB and miRCosm to predict the target genes of miR-33 according to laboratory prophase transcriptome results and references, we screen nine target genes: adenosine triphosphate binding cassette transporters A1, adenosine triphosphate binding cassette transporters G1, Neimann Pick C, carnitine O-octanoyltransferase (CROT, cyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase, beta subunit (HADHB, AMP-activated protein kinase, alpha subunit 1 (AMPKα1, insulin receptor substrate 2, glutamic pyruvate transaminase and adipose differentiation-related protein. The dual luciferase reporter gene system in the CHO cell line verifies that CROT, HADHB and NPC1 are the target genes of miR-33 in geese. The inhibition rate of

  5. In Vivo Detection of c-MET Expression in a Rat Hepatocarcinogenesis Model Using Molecularly Targeted Magnetic Resonance Imaging

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    Rheal A. Towner

    2007-01-01

    Full Text Available The multifunctional growth factor scatter factor/hepatocyte growth factor and its tyrosine kinase receptor, c-MET, have been implicated in the genesis and malignant progression of numerous human malignancies, including hepatocellular carcinomas. The incidence of hepatocellular carcinomas in the United States has increased noticeably over the past two decades and is listed as the fifth major cancer in men worldwide. In this study, we used a choline-deficient l-amino acid (CDAA-defined rat hepatocarcinogenesis model to visualize increased in vivo expression of the c-MET antigen in neoplastic lesion formation with the use of a super paramagnetic iron oxide (SPIO–anti-c-MET molecularly targeted magnetic resonance imaging (MRI contrast agent. SPIO–anti-c-MET was used for the first time to detect overexpression of c-MET in neoplastic nodules and tumors within the livers of CDAA-treated rats, as determined by a decrease in MRI signal intensity and a decrease in regional T2 values. Specificity for the binding of the molecularly targeted anti-c-MET contrast agent was determined using rat hepatoma (H4-II-E-C3 cell cultures and immunofluorescence microscopic imaging of the targeting agents within neoplastic liver tissue 1 to 2 hours following intravenous administration of SPIO–anti-c-MET and MRI investigation. This method has the ability to visualize in vivo the overexpression of c-MET at early developmental stages of tumor formation.

  6. Rapid and ultrasensitive detection of microRNA by target-assisted isothermal exponential amplification coupled with poly (thymine)-templated fluorescent copper nanoparticles

    Science.gov (United States)

    Park, Kwan Woo; Batule, Bhagwan S.; Kang, Kyoung Suk; Park, Ki Soo; Park, Hyun Gyu

    2016-10-01

    We devised a novel method for rapid and ultrasensitive detection of target microRNA (miRNA) by employing target-assisted isothermal exponential amplification (TAIEA) combined with poly (thymine)-templated fluorescent copper nanoparticles (CuNPs) as signaling probes. The target miRNA hybridizes to the unimolecular template DNA and works as a primer for the extension reaction to form double-stranded product, which consequently generates two nicking endonuclease recognition sites. By simultaneous nicking and displacement reactions, exponential amplification generates many poly (thymine) strands as final products, which are employed for the synthesis of fluorescent CuNPs. Based on the fluorescent signal from CuNPs, target miRNA is detected as low as 0.27 fM around 1 h of total analysis time. The diagnostic capability of this system has been successfully demonstrated by reliably detecting target miRNA from different cell lysates, showing its great potential towards real clinical applications.

  7. Analytical specificity and sensitivity of the novel dual-target GeneProof Neisseria gonorrhoeae PCR kit for detection of N. gonorrhoeae.

    Science.gov (United States)

    Golparian, Daniel; Hellmark, Bengt; Unemo, Magnus

    2015-11-01

    Detection of Neisseria gonorrhoeae relies increasingly on nucleic acid amplification tests (NAATs). The specificity of many gonococcal NAATs has been suboptimal and supplementary testing remains recommended in Europe and several additional countries. The novel dual-target GeneProof Neisseria gonorrhoeae PCR kit, targeting porA pseudogene and 16S rRNA gene, showed a high specificity and sensitivity when isolates of non-gonococcal Neisseria and related species (n = 144), and gonococci (n = 104) were tested. However, rare gonococcal porA mutants were only detected in the 16S rRNA gene target and two non-gonococcal isolates showed a low-level cross-reactivity in the 16S rRNA gene target. The detection limit for both targets was 1.5 copies per reaction. © 2015 APMIS. Published by John Wiley & Sons Ltd.

  8. Ultrasensitive detection of target analyte-induced aggregation of gold nanoparticles using laser-induced nanoparticle Rayleigh scattering.

    Science.gov (United States)

    Lin, Jia-Hui; Tseng, Wei-Lung

    2015-01-01

    Detection of salt- and analyte-induced aggregation of gold nanoparticles (AuNPs) mostly relies on costly and bulky analytical instruments. To response this drawback, a portable, miniaturized, sensitive, and cost-effective detection technique is urgently required for rapid field detection and monitoring of target analyte via the use of AuNP-based sensor. This study combined a miniaturized spectrometer with a 532-nm laser to develop a laser-induced Rayleigh scattering technique, allowing the sensitive and selective detection of Rayleigh scattering from the aggregated AuNPs. Three AuNP-based sensing systems, including salt-, thiol- and metal ion-induced aggregation of the AuNPs, were performed to examine the sensitivity of laser-induced Rayleigh scattering technique. Salt-, thiol-, and metal ion-promoted NP aggregation were exemplified by the use of aptamer-adsorbed, fluorosurfactant-stabilized, and gallic acid-capped AuNPs for probing K(+), S-adenosylhomocysteine hydrolase-induced hydrolysis of S-adenosylhomocysteine, and Pb(2+), in sequence. Compared to the reported methods for monitoring the aggregated AuNPs, the proposed system provided distinct advantages of sensitivity. Laser-induced Rayleigh scattering technique was improved to be convenient, cheap, and portable by replacing a diode laser and a miniaturized spectrometer with a laser pointer and a smart-phone. Using this smart-phone-based detection platform, we can determine whether or not the Pb(2+) concentration exceed the maximum allowable level of Pb(2+) in drinking water. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Non-invasive Detection of Breast Cancer Lymph Node Metastasis using Carbonic Anhydrases IX and XII Targeted Imaging Probes

    Science.gov (United States)

    Tafreshi, Narges K.; Bui, Marilyn M.; Bishop, Kellsey; Lloyd, Mark C.; Enkemann, Steven A.; Lopez, Alexis S.; Abrahams, Dominique; Carter, Bradford W.; Vagner, Josef; Grobmyer, Stephen R.; Gillies, Robert J.; Morse, David L.

    2014-01-01

    Purpose To develop targeted molecular imaging probes for the non-invasive detection of breast cancer lymph node metastasis. Methods Six cell surface or secreted markers were identified by expression profiling and from the literature as being highly expressed in breast cancer lymph node metastases. Two of these markers were cell surface carbonic anhydrase isozymes (CAIX and/or CAXII) and were validated for protein expression by immunohistochemistry (IHC) of patient tissue samples on a breast cancer tissue microarray containing 47 normal breast tissue samples, 42 ductal carcinoma in situ, 43 invasive ductal carcinomas without metastasis, 46 invasive ductal carcinomas with metastasis and 49 lymph node macrometastases of breast carcinoma. Targeted probes were developed by conjugation of CAIX and CAXII specific monoclonal antibodies (mAbs) to a near-infrared fluorescent dye. Results Together, these two markers were expressed in 100% of the lymph node metastases surveyed. Selectivity of the imaging probes were confirmed by intravenous injection into nude mice bearing mammary fat pad tumors of marker expressing cells, and non-expressing cells or by pre-injection of unlabeled antibody. Imaging of LN metastases showed that peritumorally-injected probes detected nodes harboring metastatic tumor cells. As few as 1,000 cells were detected, as determined by implanting, under ultrasound guidance, a range in number of CAIX and CAXII expressing cells into the axillary LNs. Conclusion These imaging probes have potential for non-invasive staging of breast cancer in the clinic and elimination of unneeded surgery, which is costly and associated with morbidities. PMID:22016510

  10. Detecting very low allele fraction variants using targeted DNA sequencing and a novel molecular barcode-aware variant caller.

    Science.gov (United States)

    Xu, Chang; Nezami Ranjbar, Mohammad R; Wu, Zhong; DiCarlo, John; Wang, Yexun

    2017-01-03

    Detection of DNA mutations at very low allele fractions with high accuracy will significantly improve the effectiveness of precision medicine for cancer patients. To achieve this goal through next generation sequencing, researchers need a detection method that 1) captures rare mutation-containing DNA fragments efficiently in the mix of abundant wild-type DNA; 2) sequences the DNA library extensively to deep coverage; and 3) distinguishes low level true variants from amplification and sequencing errors with high accuracy. Targeted enrichment using PCR primers provides researchers with a convenient way to achieve deep sequencing for a small, yet most relevant region using benchtop sequencers. Molecular barcoding (or indexing) provides a unique solution for reducing sequencing artifacts analytically. Although different molecular barcoding schemes have been reported in recent literature, most variant calling has been done on limited targets, using simple custom scripts. The analytical performance of barcode-aware variant calling can be significantly improved by incorporating advanced statistical models. We present here a highly efficient, simple and scalable enrichment protocol that integrates molecular barcodes in multiplex PCR amplification. In addition, we developed smCounter, an open source, generic, barcode-aware variant caller based on a Bayesian probabilistic model. smCounter was optimized and benchmarked on two independent read sets with SNVs and indels at 5 and 1% allele fractions. Variants were called with very good sensitivity and specificity within coding regions. We demonstrated that we can accurately detect somatic mutations with allele fractions as low as 1% in coding regions using our enrichment protocol and variant caller.

  11. Testing of Haar-Like Feature in Region of Interest Detection for Automated Target Recognition (ATR) System

    Science.gov (United States)

    Zhang, Yuhan; Lu, Dr. Thomas

    2010-01-01

    The objectives of this project were to develop a ROI (Region of Interest) detector using Haar-like feature similar to the face detection in Intel's OpenCV library, implement it in Matlab code, and test the performance of the new ROI detector against the existing ROI detector that uses Optimal Trade-off Maximum Average Correlation Height filter (OTMACH). The ROI detector included 3 parts: 1, Automated Haar-like feature selection in finding a small set of the most relevant Haar-like features for detecting ROIs that contained a target. 2, Having the small set of Haar-like features from the last step, a neural network needed to be trained to recognize ROIs with targets by taking the Haar-like features as inputs. 3, using the trained neural network from the last step, a filtering method needed to be developed to process the neural network responses into a small set of regions of interests. This needed to be coded in Matlab. All the 3 parts needed to be coded in Matlab. The parameters in the detector needed to be trained by machine learning and tested with specific datasets. Since OpenCV library and Haar-like feature were not available in Matlab, the Haar-like feature calculation needed to be implemented in Matlab. The codes for Adaptive Boosting and max/min filters in Matlab could to be found from the Internet but needed to be integrated to serve the purpose of this project. The performance of the new detector was tested by comparing the accuracy and the speed of the new detector against the existing OTMACH detector. The speed was referred as the average speed to find the regions of interests in an image. The accuracy was measured by the number of false positives (false alarms) at the same detection rate between the two detectors.

  12. Targetting the hemozoin synthesis pathway for antimalarial drug and detected by TEM (Transmission electron microscope)

    Science.gov (United States)

    Abbas, Jamilah; Artanti, Nina; Sundowo, Andini; Dewijanti, Indah Dwiatmi; Hanafi, Muhammad; Lisa, Syafrudin, Din

    2017-11-01

    Malaria is a major public health problem mainly due to the development of resistance by the most lethal causative parasite species, the alarming spread of drug resistance and limited number of effective drug available now. Therefore it is important to discover new antimalarial drug. Malaria is caused by a singlecelled parasite from the genus Plasmodium. Plasmodium falciparum parasite infect red blood cells, ingesting and degradation hemoglobin in the acidic food vacuola trough a sequential metabolic process involving multiple proteases. During these process, hemoglobin is utilized as the predominant source of nutrition. Proteolysis of hemoglobin yields amino acid for protein synthesis as well as toxic heme. Massive degradation of hemoglobin generates large amount of toxic heme. Malaria parasite has evolved a distinct mechanism for detoxification of heme through conversion into insoluble crystalline pigment, known as hemozoin (β hematoin). Hemozoin synthesis is an indispensable process for the parasite and is the target for action of several known antimalarial drug. TEM (Transmission Electron Microscope) technology for hemozoin formation in vitro assay was done in this research. Calophyllum aerophyllum Lauterb as medicinal plants was used as a source of antimalarial drug. Acetone extracts of C. lowii showed growth inhibition against parasite P. falciparum with IC50 = 5.2 µg/mL. Whereas from hexane, acetone and methanol fraction of C. aerophyllum showed growth inhibition with IC50 = 0.054, 0.055 and 0.0054 µg/mL respectively. New drug from Calophyllum might have potential compounds that have unique structures and mechanism of action which required to develop new drug for treatment of sensitive and drug resistant strain of malaria.

  13. 360-Degree Visual Detection and Target Tracking on an Autonomous Surface Vehicle

    Science.gov (United States)

    Wolf, Michael T; Assad, Christopher; Kuwata, Yoshiaki; Howard, Andrew; Aghazarian, Hrand; Zhu, David; Lu, Thomas; Trebi-Ollennu, Ashitey; Huntsberger, Terry

    2010-01-01

    This paper describes perception and planning systems of an autonomous sea surface vehicle (ASV) whose goal is to detect and track other vessels at medium to long ranges and execute responses to determine whether the vessel is adversarial. The Jet Propulsion Laboratory (JPL) has developed a tightly integrated system called CARACaS (Control Architecture for Robotic Agent Command and Sensing) that blends the sensing, planning, and behavior autonomy necessary for such missions. Two patrol scenarios are addressed here: one in which the ASV patrols a large harbor region and checks for vessels near a fixed asset on each pass and one in which the ASV circles a fixed asset and intercepts approaching vessels. This paper focuses on the ASV's central perception and situation awareness system, dubbed Surface Autonomous Visual Analysis and Tracking (SAVAnT), which receives images from an omnidirectional camera head, identifies objects of interest in these images, and probabilistically tracks the objects' presence over time, even as they may exist outside of the vehicle's sensor range. The integrated CARACaS/SAVAnT system has been implemented on U.S. Navy experimental ASVs and tested in on-water field demonstrations.

  14. Application of Hybrid Along-Track Interferometry/Displaced Phase Center Antenna Method for Moving Human Target Detection in Forest Environments

    Science.gov (United States)

    2016-10-01

    Research Laboratory Application of Hybrid Along-Track Interferometry/Displaced Phase Center Antenna Method for Moving Human Target Detection...2 Fig. 2 GMTI-SAR images (hh-polarized) from hybrid ATI/DPCA method for scene in Fig. 1: a) with trees, moving human with variable...imaging and GMTI simultaneously, a hybrid ATI/DPCA method is exploited for moving human target detection in this work. The technique assumes the

  15. Towards real-time detection of tumor margins using photothermal imaging of immune-targeted gold nanoparticles.

    Science.gov (United States)

    Jakobsohn, Kobi; Motiei, Menachem; Sinvani, Moshe; Popovtzer, Rachela

    2012-01-01

    One of the critical problems in cancer management is local recurrence of disease. Between 20% and 30% of patients who undergo tumor resection surgery require reoperation due to incomplete excision. Currently, there are no validated methods for intraoperative tumor margin detection. In the present work, we demonstrate the potential use of gold nanoparticles (GNPs) as a novel contrast agent for photothermal molecular imaging of cancer. Phantoms containing different concentrations of GNPs were irradiated with continuous-wave laser and measured with a thermal imaging camera which detected the temperature field of the irradiated phantoms. The results clearly demonstrate the ability to distinguish between cancerous cells specifically targeted with GNPs and normal cells. This technique, which allows highly sensitive discrimination between adjacent low GNP concentrations, will allow tumor margin detection while the temperature increases by only a few degrees Celsius (for GNPs in relevant biological concentrations). We expect this real-time intraoperative imaging technique to assist surgeons in determining clear tumor margins and to maximize the extent of tumor resection while sparing normal background tissue.

  16. Detection and quantification of probiotic strain Lactobacillus gasseri K7 in faecal samples by targeting bacteriocin genes.

    Science.gov (United States)

    Treven, Primož; Turkova, Kristyna; Trmčić, Aljoša; Obermajer, Tanja; Rogelj, Irena; Matijašić, Bojana Bogovič

    2013-11-01

    Lactobacillus gasseri K7 is a probiotic strain that produces bacteriocins gassericin K7 A and K7 B. In order to develop a real-time quantitative PCR assay for the detection of L. gasseri K7, 18 reference strains of the Lactobacillus acidophilus group and 45 faecal samples of adults who have never consumed strain K7 were tested with PCR using 14 pairs of primers specific for gassericin K7 A and K7 B gene determinants. Incomplete gassericin K7 A or K7 B gene clusters were found to be dispersed in different lactobacilli strains as well as in faecal microbiota. One pair of primers was found to be specific for the total gene cluster of gassericin K7A and one for gassericin K7B. The real-time PCR analysis of faecal samples spiked with K7 strain revealed that primers specific for the gene cluster of the gassericin K7 A were more suitable for quantitative determination than those for gassericin K7 B, due to the lower detection level. Targeting of the gassericin K7 A or K7 B gene cluster with specific primers could be used for detection and quantification of L. gasseri K7 in human faecal samples without prior cultivation. The results of this study also present new insights into the prevalence of bacteriocin-encoding genes in gastrointestinal tract.

  17. Enhanced Biosensor Platforms for Detecting the Atherosclerotic Biomarker VCAM1 Based on Bioconjugation with Uniformly Oriented VCAM1-Targeting Nanobodies

    Directory of Open Access Journals (Sweden)

    Duy Tien Ta

    2016-07-01

    Full Text Available Surface bioconjugation of biomolecules has gained enormous attention for developing advanced biomaterials including biosensors. While conventional immobilization (by physisorption or covalent couplings using the functional groups of the endogenous amino acids usually results in surfaces with low activity, reproducibility and reusability, the application of methods that allow for a covalent and uniformly oriented coupling can circumvent these limitations. In this study, the nanobody targeting Vascular Cell Adhesion Molecule-1 (NbVCAM1, an atherosclerotic biomarker, is engineered with a C-terminal alkyne function via Expressed Protein Ligation (EPL. Conjugation of this nanobody to azidified silicon wafers and Biacore™ C1 sensor chips is achieved via Copper(I-catalyzed azide-alkyne cycloaddition (CuAAC “click” chemistry to detect VCAM1 binding via ellipsometry and surface plasmon resonance (SPR, respectively. The resulting surfaces, covered with uniformly oriented nanobodies, clearly show an increased antigen binding affinity, sensitivity, detection limit, quantitation limit and reusability as compared to surfaces prepared by random conjugation. These findings demonstrate the added value of a combined EPL and CuAAC approach as it results in strong control over the surface orientation of the nanobodies and an improved detecting power of their targets—a must for the development of advanced miniaturized, multi-biomarker biosensor platforms.

  18. Immune-enrichment of insulin in bio-fluids on gold-nanoparticle decorated target plate and in situ detection by MALDI MS.

    Science.gov (United States)

    Liang, Kai; Wu, Hongmei; Li, Yan

    2017-01-01

    Detection of low-abundance biomarkers using mass spectrometry (MS) is often hampered by non-target molecules in biological fluids. In addition, current procedures for sample preparation increase sample consumption and limit analysis throughput. Here, a simple strategy is proposed to construct an antibody-modified target plate for high-sensitivity MS detection of target markers such as insulin, in biological fluids. The target plate was first modified with gold nanoparticle, and then functionalized with corresponding antibody through chemical conjugation. Clinical specimens were incubated onto these antibody-functionalized target plates, and then subjected to matrix assisted laser desorption ionization mass spectrometry analysis. Insulin in samples was enriched specifically on this functional plate. The detection just required low-volume samples (lower than 5 µL) and simplified handling process (within 40 min). This method exhibited high sensitivity (limit of detection in standard samples, 0.8 nM) and good linear correlation of MS intensity with insulin concentration (R 2  = 0.994). More importantly, insulin present in real biological fluids such as human serum and cell lysate could be detected directly by using this functional target plate without additional sample preparations. Our method is easy to manipulate, cost-effective, and with a potential to be applied in the field of clinical biomarker detection.

  19. Targeting safety improvements through identification of incident origination and detection in a near-miss incident learning system

    Energy Technology Data Exchange (ETDEWEB)

    Novak, Avrey; Nyflot, Matthew J.; Ermoian, Ralph P.; Jordan, Loucille E.; Sponseller, Patricia A.; Kane, Gabrielle M.; Ford, Eric C.; Zeng, Jing, E-mail: jzeng13@uw.edu [Department of Radiation Oncology, University of Washington Medical Center, 1959 NE Pacific Street, Campus Box 356043, Seattle, Washington 98195 (United States)

    2016-05-15

    during the documentation of patient positioning and localization of the patient. Incidents were most frequently detected during treatment delivery (30%), and incidents identified at this point also had higher severity scores than other workflow areas (NMRI = 1.6). Incidents identified during on-treatment quality management were also more severe (NMRI = 1.7), and the specific process steps of reviewing portal and CBCT images tended to catch highest-severity incidents. On average, safety barriers caught 46% of all incidents, most frequently at physics chart review, therapist’s chart check, and the review of portal images; however, most of the incidents that pass through a particular safety barrier are not designed to be capable of being captured at that barrier. Conclusions: Incident learning systems can be used to assess the most common points of error origination and detection in radiation oncology. This can help tailor safety improvement efforts and target the highest impact portions of the workflow. The most severe near-miss events tend to originate during simulation, with the most severe near-miss events detected at the time of patient treatment. Safety barriers can be improved to allow earlier detection of near-miss events.

  20. Feature-space assessment of electrical impedance tomography coregistered with computed tomography in detecting multiple contrast targets.

    Science.gov (United States)

    Krishnan, Kalpagam; Liu, Jeff; Kohli, Kirpal

    2014-06-01

    Fusion of electrical impedance tomography (EIT) with computed tomography (CT) can be useful as a clinical tool for providing additional physiological information about tissues, but requires suitable fusion algorithms and validation procedures. This work explores the feasibility of fusing EIT and CT images using an algorithm for coregistration. The imaging performance is validated through feature space assessment on phantom contrast targets. EIT data were acquired by scanning a phantom using a circuit, configured for injecting current through 16 electrodes, placed around the phantom. A conductivity image of the phantom was obtained from the data using electrical impedance and diffuse optical tomography reconstruction software (EIDORS). A CT image of the phantom was also acquired. The EIT and CT images were fused using a region of interest (ROI) coregistration fusion algorithm. Phantom imaging experiments were carried out on objects of different contrasts, sizes, and positions. The conductive medium of the phantoms was made of a tissue-mimicking bolus material that is routinely used in clinical radiation therapy settings. To validate the imaging performance in detecting different contrasts, the ROI of the phantom was filled with distilled water and normal saline. Spatially separated cylindrical objects of different sizes were used for validating the imaging performance in multiple target detection. Analyses of the CT, EIT and the EIT/CT phantom images were carried out based on the variations of contrast, correlation, energy, and homogeneity, using a gray level co-occurrence matrix (GLCM). A reference image of the phantom was simulated using EIDORS, and the performances of the CT and EIT imaging systems were evaluated and compared against the performance of the EIT/CT system using various feature metrics, detectability, and structural similarity index measures. In detecting distilled and normal saline water in bolus medium, EIT as a stand-alone imaging system showed

  1. Multiplex T-RFLP allows for increased target number and specificity: detection of Salmonella enterica and six species of Listeria in a single test.

    Directory of Open Access Journals (Sweden)

    Geoffrey N Elliott

    Full Text Available A multiplex T-RFLP test was developed to detect and identify Salmonella enterica and all six species of Listeria inoculated into milk at minimal levels. Extensive in silico analysis was used to design a fifteen-primer, six-amplimer methodology and in vitro application showed target organism DNA, when amplified individually, yielded the predicted terminal restriction fragments (TRFs following digestion. Non-target organisms were either not-amplified or yielded TRFs which did not interfere with target identification. Multiple target DNA analysis gave over 86% detection of total TRFs predicted, and this was improved to over 90% detection of total TRFs predicted when only two target DNA extracts were combined analysed. Co-inoculation of milk with five strains each of the target species of S. enterica and L. monocytogenes, along with five strains of the non-target species E. coli was followed by enrichment in SEL medium for M-TRFLP analysis. This allowed for detection of both target species in all samples, with detection of one S. enterica and two Listeria TRFs in all cases, and detection of a second S. enterica TRF in 91% of cases. This was from an initial inoculum of <5 cfu per 25 ml milk with a background of competing E. coli present, and gave a result from sampling of under 20 hours. The ability to increase target species number without loss of sensitivity means that extensive screening can be performed at reduced cost due to a reduction in the number of tests required.

  2. Detection of amyloid plaques targeted by bifunctional USPIO in Alzheimer's disease transgenic mice using magnetic resonance microimaging.

    Directory of Open Access Journals (Sweden)

    Youssef Zaim Wadghiri

    Full Text Available Amyloid plaques are a key pathological hallmark of Alzheimer's disease (AD. The detection of amyloid plaques in the brain is important for the diagnosis of AD, as well as for following potential amyloid targeting therapeutic interventions. Our group has developed several contrast agents to detect amyloid plaques in vivo using magnetic resonance microimaging (µMRI in AD transgenic mice, where we used mannitol to enhance blood brain barrier (BBB permeability. In the present study, we used bifunctional ultrasmall superparamagnetic iron oxide (USPIO nanoparticles, chemically coupled with Aβ1-42 peptide to image amyloid plaque deposition in the mouse brain. We coupled the nanoparticles to polyethylene glycol (PEG in order to improve BBB permeability. These USPIO-PEG-Aβ1-42 nanoparticles were injected intravenously in AD model transgenic mice followed by initial in vivo and subsequent ex vivo μMRI. A 3D gradient multi-echo sequence was used for imaging with a 100 µm isotropic resolution. The amyloid plaques detected by T2*-weighted μMRI were confirmed with matched histological sections. The region of interest-based quantitative measurement of T2* values obtained from the in vivo μMRI showed contrast injected AD Tg mice had significantly reduced T2* values compared to wild-type mice. In addition, the ex vivo scans were examined with voxel-based analysis (VBA using statistical parametric mapping (SPM for comparison of USPIO-PEG-Aβ1-42 injected AD transgenic and USPIO alone injected AD transgenic mice. The regional differences seen by VBA in the USPIO-PEG-Aβ1-42 injected AD transgenic correlated with the amyloid plaque distribution histologically. Our results indicate that USPIO-PEG-Aβ1-42 can be used for amyloid plaque detection in vivo by intravenous injection without the need to co-inject an agent which increases permeability of the BBB. This technique could aid the development of novel amyloid targeting drugs by allowing therapeutic effects

  3. Fusion gene transcripts and Ig/TCR gene rearrangements are complementary but infrequent targets for PCR-based detection of minimal residual disease in acute myeloid leukemia

    NARCIS (Netherlands)

    Boeckx, N.; M.J. Willemse; T. Szczepanski (Tomasz); V.H.J. van der Velden (Vincent); A.W. Langerak (Anton); P. Vandekerckhove (Philippe); J.J.M. van Dongen (Jacques)

    2002-01-01

    textabstractPCR-based monitoring of minimal residual disease (MRD) in acute leukemias can be achieved via detection of fusion gene transcripts of chromosome aberrations or detection of immunoglobulin (lg) and T cell receptor (TCR) gene rearrangements. We wished to assess whether both PCR targets are

  4. Performance portability study of an automatic target detection and classification algorithm for hyperspectral image analysis using OpenCL

    Science.gov (United States)

    Bernabe, Sergio; Igual, Francisco D.; Botella, Guillermo; Garcia, Carlos; Prieto-Matias, Manuel; Plaza, Antonio

    2015-10-01

    Recent advances in heterogeneous high performance computing (HPC) have opened new avenues for demanding remote sensing applications. Perhaps one of the most popular algorithm in target detection and identification is the automatic target detection and classification algorithm (ATDCA) widely used in the hyperspectral image analysis community. Previous research has already investigated the mapping of ATDCA on graphics processing units (GPUs) and field programmable gate arrays (FPGAs), showing impressive speedup factors that allow its exploitation in time-critical scenarios. Based on these studies, our work explores the performance portability of a tuned OpenCL implementation across a range of processing devices including multicore processors, GPUs and other accelerators. This approach differs from previous papers, which focused on achieving the optimal performance on each platform. Here, we are more interested in the following issues: (1) evaluating if a single code written in OpenCL allows us to achieve acceptable performance across all of them, and (2) assessing the gap between our portable OpenCL code and those hand-tuned versions previously investigated. Our study includes the analysis of different tuning techniques that expose data parallelism as well as enable an efficient exploitation of the complex memory hierarchies found in these new heterogeneous devices. Experiments have been conducted using hyperspectral data sets collected by NASA's Airborne Visible Infra- red Imaging Spectrometer (AVIRIS) and the Hyperspectral Digital Imagery Collection Experiment (HYDICE) sensors. To the best of our knowledge, this kind of analysis has not been previously conducted in the hyperspectral imaging processing literature, and in our opinion it is very important in order to really calibrate the possibility of using heterogeneous platforms for efficient hyperspectral imaging processing in real remote sensing missions.

  5. Lack of interaction between concurrent caffeine and mobile phone exposure on visual target detection: an ERP study.

    Science.gov (United States)

    Trunk, Attila; Stefanics, Gábor; Zentai, Norbert; Bacskay, Ivett; Felinger, Attila; Thuróczy, György; Hernádi, István

    2014-09-01

    Caffeine affects information processing by acting predominantly on cortical activation, arousal and attention. Millions consume caffeine and simultaneously use their mobile phone (MP) during everyday activities. However, it is not known whether and how MP-emitted electromagnetic fields (EMFs) can modulate known psychoactive effects of caffeine. Here we investigated behavioral and neural correlates of caffeine and simultaneous MP exposure in a third generation (3G) Universal Mobile Telecommunication System (UMTS) signal modulation scheme. We recorded electroencephalography (EEG) and event related potentials (ERP) in an oddball paradigm to frequent standard (p=0.8) and rare target (p=0.2) stimuli in a placebo controlled, double blind, within-subject protocol in four experimental sessions: 1) no caffeine and no MP, 2) caffeine only, 3) MP only, and 4) caffeine and MP. The subjects' task was to discriminate between standard and target stimuli and respond to the latter by pressing a button while reaction time (RT) and EEG were recorded. To provide a complete analysis of any possible caffeine and/or MP treatment effects that may have occurred, we analyzed the P300 ERP wave using four different ERP measures: 1) peak latency, 2) peak amplitude, 3) 50% fractional area latency (FAL) and 4) area under the curve (AUC). Caffeine significantly shortened RT and decreased AUC of the P300 component compared to the control or the UMTS MP alone conditions. However, no effects were observed on RT or P300 in the UMTS MP exposure sessions, neither alone nor in combination with caffeine. Overall, the present results did not demonstrate any interactive or synergistic effects of caffeine and UMTS MP like EMF exposure on basic neural or cognitive measures. However, we found that caffeine consistently enhanced behavioral and ERP measures of visual target detection, showing that present results were obtained using a pharmacologically validated, consistent and replicable methodology. Copyright

  6. Highly sensitive detection of 25-HydroxyvitaminD3by using a target-induced displacement of aptamer.

    Science.gov (United States)

    Lee, Bang Hyun; Nguyen, Van Thuan; Gu, Man Bock

    2017-02-15

    For the prevention of 25-HydroxyvitaminD 3 deficiency, in this study, aptamers which can bind to 25-HydroxyvitaminD 3 with high specificity and affinity, were successfully developed by using immobilization-free, graphene oxide-based systemic evolution of ligands by exponential enrichment (GO-SELEX) method. The 9 sequences including VDBA14 aptamer were obtained out of 16 aptamer candidates, based on the specificity and affinity of the aptamers confirmed by both the gold nanoparticles (AuNPs)-based colorimetric assay and the isothermal titration calorimetry (ITC) method. Among them, the aptamer, VDBA14, developed in this study was found to show a great affinity to 25-HydroxyvitaminD 3 , with 11nM of its Kd value. Moreover, the circular dichroism (CD) analysis data indicated the target-induced displacement of the aptamer VDBA14clearly. In addition, this target-induced change of the aptamer was also confirmed again by conducting two different experimental formats, the use of streptavidin-coated 96-well plates and the use of magnetic beads. The results clearly indicated that the structure of VDBA14 aptamer was changed upon the binding of the target, 25-HydroxyvitaminD 3 , and so the indicator sequences (partially complementary to the aptamer sequence) tagged with an enzyme as a signaling molecule could be de-hybridized from the aptamer. Finally, the limit of detection for vitamin D based on AuNPs-based colorimetric assay using VDBA14 aptamer was found to be 1µM. All these results were taken together, the aptamer which was developed could play an exquisite role in the fields of early medical diagnosis of vitamin D deficiency with accurate, rapid and simple analytical method. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Sensitivity-enhanced solid-state NMR detection of expansin's target in plant cell walls

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Tuo [Iowa State Univ., Ames, IA (United States); Park, Yong Bum [Pennsylvania State Univ., State College, PA (United States); Caporini, Marc A. [Bruker Biospin Corporation, Billerica, MA (United States); Rosay, Melanie [Bruker Biospin Corporation, Billerica, MA (United States); Zhong, Linghao [Pennsylvania State Univ., State College, PA (United States); Cosgrove, Daniel J. [Pennsylvania State Univ., State College, PA (United States); Hong, Mei [Iowa State Univ., Ames, IA (United States)

    2013-08-29

    Structure determination of protein binding to noncrystalline macromolecular assemblies such as plant cell walls (CWs) poses a significant structural biology challenge. CWs are loosened during growth by expansin proteins, which weaken the noncovalent network formed by cellulose, hemicellulose, and pectins, but the CW target of expansins has remained elusive because of the minute amount of the protein required for activity and the complex nature of the CW. Using solid-state NMR spectroscopy, combined with sensitivity-enhancing dynamic nuclear polarization (DNP) and differential isotopic labeling of expansin and polysaccharides, we have now determined the functional binding target of expansin in the Arabidopsis thaliana CW. By transferring the electron polarization of a biradical dopant to the nuclei, DNP allowed selective detection of 13C spin diffusion from trace concentrations of 13C, 15N-labeled expansin in the CW to nearby polysaccharides. From the spin diffusion data of wild-type and mutant expansins, we conclude that to loosen the CW, expansin binds highly specific cellulose domains enriched in xyloglucan, whereas more abundant binding to pectins is unrelated to activity. Molecular dynamics simulations indicate short 13C-13C distances of 4–6 Å between a hydrophobic surface of the cellulose microfibril and an aromatic motif on the expansin surface, consistent with the observed NMR signals. DNP-enhanced 2D 13C correlation spectra further reveal that the expansin-bound cellulose has altered conformation and is enriched in xyloglucan, thus providing unique insight into the mechanism of CW loosening. DNP-enhanced NMR provides a powerful, generalizable approach for investigating protein binding to complex macromolecular targets.

  8. Targeted Biopsy to Detect Gleason Score Upgrading during Active Surveillance for Men with Low versus Intermediate Risk Prostate Cancer.

    Science.gov (United States)

    Nassiri, Nima; Margolis, Daniel J; Natarajan, Shyam; Sharma, Devi S; Huang, Jiaoti; Dorey, Frederick J; Marks, Leonard S

    2017-03-01

    We sought to determine the rate of upgrading to Gleason score 4 + 3 or greater using targeted biopsy for diagnosis and monitoring in men undergoing active surveillance of prostate cancer. Study subjects comprised all 259 men, including 196 with Gleason score 3 + 3 and 63 with Gleason score 3 + 4, who were diagnosed by magnetic resonance imaging/ultrasound fusion guided biopsy from 2009 to 2015 and underwent subsequent fusion biopsy for as long as 4 years of active surveillance. The primary end point was the discovery of Gleason score 4 + 3 or greater prostate cancer. Followup biopsies included targeting of positive sites, which were tracked in an Artemis™ device. Kaplan-Meier curves were generated to determine upgrading rates, stratified by initial Gleason score and prostate specific antigen density. Based on a Cox proportional hazard model, men with Gleason score 3 + 4 were 4.65 times more likely to have upgrading than men with an initial Gleason score of 3 + 3 at 3 years (p started with Gleason score 3 + 3 (p prostate specific antigen density 0.15 ng/ml/cm3 or greater and a grade 5 lesion on magnetic resonance imaging. The incidence rate ratio of upgrading (Gleason score 3 + 4 vs 3 + 3) was 4.25 per year of patient followup (p prostate cancer, targeting of tracked tumor foci by magnetic resonance imaging/ultrasound fusion biopsy allows for heightened detection of Gleason score 4 + 3 or greater cancers. Baseline variables directly related to important upgrading that warrant increased vigilance include Gleason score 3 + 4, prostate specific antigen density 0.15 ng/ml/cm3 or greater and grade 5 lesions on magnetic resonance imaging. Copyright © 2017 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  9. Detecting target changes in multiple object tracking with peripheral vision: More pronounced eccentricity effects for changes in form than in motion.

    Science.gov (United States)

    Vater, Christian; Kredel, Ralf; Hossner, Ernst-Joachim

    2017-05-01

    In the current study, dual-task performance is examined with multiple-object tracking as a primary task and target-change detection as a secondary task. The to-be-detected target changes in conditions of either change type (form vs. motion; Experiment 1) or change salience (stop vs. slowdown; Experiment 2), with changes occurring at either near (5°-10°) or far (15°-20°) eccentricities (Experiments 1 and 2). The aim of the study was to test whether changes can be detected solely with peripheral vision. By controlling for saccades and computing gaze distances, we could show that participants used peripheral vision to monitor the targets and, additionally, to perceive changes at both near and far eccentricities. Noticeably, gaze behavior was not affected by the actual target change. Detection rates as well as response times generally varied as a function of change condition and eccentricity, with faster detections for motion changes and near changes. However, in contrast to the effects found for motion changes, sharp declines in detection rates and increased response times were observed for form changes as a function of the eccentricities. This result can be ascribed to properties of the visual system, namely to the limited spatial acuity in the periphery and the comparably receptive motion sensitivity of peripheral vision. These findings show that peripheral vision is functional for simultaneous target monitoring and target-change detection as saccadic information suppression can be avoided and covert attention can be optimally distributed to all targets. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  10. G-quadruplex aptamer targeting Protein A and its capability to detect Staphylococcus aureus demonstrated by ELONA

    Science.gov (United States)

    Stoltenburg, Regina; Krafčiková, Petra; Víglaský, Viktor; Strehlitz, Beate

    2016-01-01

    Aptamers for whole cell detection are selected mostly by the Cell-SELEX procedure. Alternatively, the use of specific cell surface epitopes as target during aptamer selections allows the development of aptamers with ability to bind whole cells. In this study, we integrated a formerly selected Protein A-binding aptamer PA#2/8 in an assay format called ELONA (Enzyme-Linked OligoNucleotide Assay) and evaluated the ability of the aptamer to recognise and bind to Staphylococcus aureus presenting Protein A on the cell surface. The full-length aptamer and one of its truncated variants could be demonstrated to specifically bind to Protein A-expressing intact cells of S. aureus, and thus have the potential to expand the portfolio of aptamers that can act as an analytical agent for the specific recognition and rapid detection of the bacterial pathogen. The functionality of the aptamer was found to be based on a very complex, but also highly variable structure. Two structural key elements were identified. The aptamer sequence contains several G-clusters allowing folding into a G-quadruplex structure with the potential of dimeric and multimeric assembly. An inverted repeat able to form an imperfect stem-loop at the 5′-end also contributes essentially to the aptameric function. PMID:27650576

  11. Transrectal real-time tissue elastography targeted biopsy coupled with peak strain index improves the detection of clinically important prostate cancer.

    Science.gov (United States)

    Ma, Qi; Yang, Dong-Rong; Xue, Bo-Xin; Wang, Cheng; Chen, Han-Bin; Dong, Yun; Wang, Cai-Shan; Shan, Yu-Xi

    2017-07-01

    The focus of the present study was to evaluate transrectal real-time tissue elastography (RTE)-targeted two-core biopsy coupled with peak strain index for the detection of prostate cancer (PCa) and to compare this method with 10-core systematic biopsy. A total of 141 patients were enrolled for evaluation. The diagnostic value of peak strain index was assessed using a receiver operating characteristic curve. The cancer detection rates of the two approaches and corresponding positive cores and Gleason score were compared. The cancer detection rate per core in the RTE-targeted biopsy (44%) was higher compared with that in systematic biopsy (30%). The peak strain index value of PCa was higher compared with that of the benign lesion. PCa was detected with the highest sensitivity (87.5%) and specificity (85.5%) using the threshold value of a peak strain index of ≥5.97 with an area under the curve value of 0.95. When the Gleason score was ≥7, RTE-targeted biopsy coupled with peak strain index detected 95.6% of PCa cases, but 84.4% were detected using systematic biopsy. Peak strain index as a quantitative parameter may improve the differentiation of PCa from benign lesions in the prostate peripheral zone. Transrectal RTE-targeted biopsy coupled with peak strain index may enhance the detection of clinically significant PCa, particularly when combined with systematic biopsy.

  12. Testing the discrimination and detection limits of WorldView-2 imagery on a challenging invasive plant target

    Science.gov (United States)

    Robinson, T. P.; Wardell-Johnson, G. W.; Pracilio, G.; Brown, C.; Corner, R.; van Klinken, R. D.

    2016-02-01

    Invasive plants pose significant threats to biodiversity and ecosystem function globally, leading to costly monitoring and management effort. While remote sensing promises cost-effective, robust and repeatable monitoring tools to support intervention, it has been largely restricted to airborne platforms that have higher spatial and spectral resolutions, but which lack the coverage and versatility of satellite-based platforms. This study tests the ability of the WorldView-2 (WV2) eight-band satellite sensor for detecting the invasive shrub mesquite (Prosopis spp.) in the north-west Pilbara region of Australia. Detectability was challenged by the target taxa being largely defoliated by a leaf-tying biological control agent (Gelechiidae: Evippe sp. #1) and the presence of other shrubs and trees. Variable importance in the projection (VIP) scores identified bands offering greatest capacity for discrimination were those covering the near-infrared, red, and red-edge wavelengths. Wavelengths between 400 nm and 630 nm (coastal blue, blue, green, yellow) were not useful for species level discrimination in this case. Classification accuracy was tested on three band sets (simulated standard multispectral, all bands, and bands with VIP scores ≥1). Overall accuracies were comparable amongst all band-sets (Kappa = 0.71-0.77). However, mesquite omission rates were unacceptably high (21.3%) when using all eight bands relative to the simulated standard multispectral band-set (9.5%) and the band-set informed by VIP scores (11.9%). An incremental cover evaluation on the latter identified most omissions to be for objects 16 m2 allows application for mapping mesquite shrubs and coalesced stands, the former not previously possible, even with 3 m resolution hyperspectral imagery. WV2 imagery offers excellent portability potential for detecting other species where spectral/spatial resolution or coverage has been an impediment. New generation satellite sensors are removing barriers

  13. Targeted deposition of antibodies on a multiplex CMOS microarray and optimization of a sensitive immunoassay using electrochemical detection.

    Directory of Open Access Journals (Sweden)

    John Cooper

    Full Text Available BACKGROUND: The CombiMatrix ElectraSense microarray is a highly multiplex, complementary metal oxide semiconductor with 12,544 electrodes that are individually addressable. This platform is commercially available as a custom DNA microarray; and, in this configuration, it has also been used to tether antibodies (Abs specifically on electrodes using complementary DNA sequences conjugated to the Abs. METHODOLOGY/PRINCIPAL FINDINGS: An empirical method is described for developing and optimizing immunoassays on the CombiMatrix ElectraSense microarray based upon targeted deposition of polypyrrole (Ppy and capture Ab. This process was automated using instrumentation that can selectively apply a potential or current to individual electrodes and also measure current generated at the electrodes by an enzyme-enhanced electrochemical (ECD reaction. By designating groups of electrodes on the array for different Ppy deposition conditions, we determined that the sensitivity and specificity of a sandwich immunoassay for staphylococcal enterotoxin B (SEB is influenced by the application of different voltages or currents and the application time. The sandwich immunoassay used a capture Ab adsorbed to the Ppy and a reporter Ab labeled for fluorescence detection or ECD, and results from these methods of detection were different. CONCLUSIONS/SIGNIFICANCE: Using Ppy deposition conditions for optimum results, the lower limit of detection for SEB using the ECD assay was between 0.003 and 0.01 pg/ml, which represents an order of magnitude improvement over a conventional enzyme-linked immunosorbant assay. In the absence of understanding the variables and complexities that affect assay performance, this highly multiplexed electrode array provided a rapid, high throughput, and empirical approach for developing a sensitive immunoassay.

  14. Application of real time polymerase chain reaction targeting kex 1 gene & its comparison with the conventional methods for rapid detection of Pneumocystis jirovecii in clinical specimens

    Directory of Open Access Journals (Sweden)

    Mani Revathy

    2014-01-01

    Full Text Available Background & objectives: As there are no standard laboratory techniques for the rapid detection of Pneumocystis jirovecii in India, this study was undertaken to evaluate and establish an optimal and rapid technique for the detection of P. jirovecii by comparing three different techniques - staining technique, application of a real time polymerase chain reaction (RT-PCR targeting kex 1 gene and application of nested PCR targeting mitochondrial large subunit (mtLSU gene for rapid detection of P. jirovecii in HIV positive patients. Methods: One hundred and fifty sputum specimens from HIV positive (n = 75 and HIV negative (n = 75 patients were subjected to three different techniques -KOH/Calcoflour and Grocott methanamine silver staining (GMS, RT-PCR targeting kex1 gene, PCR targeting mtLSU region followed by DNA sequencing and BLAST analysis. Results: Among the 75 HIV positive patients, P. jirovecii was detected in 19 (25.33% patients by the staining techniques, and in 23 (30.65% patients each by PCR targeting mtLSU region and by RT- PCR targeting kex1 gene of P. jirovecii. PCR based DNA sequencing targeting mtLSU region revealed 97-100 per cent sequence homology with P. jirovecii sequences in GenBank. Interpretation & conclusions: Of the three techniques for detection of P. jirovecii evaluated in this study, false negativity was found to be more in staining technique and it also required high technical expertise to interpret the result. Both nested PCR and RT-PCR were reliable and equally sensitive, in rapid detection of P. jirovecii, but RT-PCR technique also generated the copy numbers for knowing the severity of infection.

  15. A new restriction endonuclease-based method for highly-specific detection of DNA targets from methicillin-resistant Staphylococcus aureus.

    Science.gov (United States)

    Smith, Maria W; Ghindilis, Andrei L; Seoudi, Ihab A; Smith, Kenneth; Billharz, Rosalind; Simon, Holly M

    2014-01-01

    PCR multiplexing has proven to be challenging, and thus has provided limited means for pathogen genotyping. We developed a new approach for analysis of PCR amplicons based on restriction endonuclease digestion. The first stage of the restriction enzyme assay is hybridization of a target DNA to immobilized complementary oligonucleotide probes that carry a molecular marker, horseradish peroxidase (HRP). At the second stage, a target-specific restriction enzyme is added, cleaving the target-probe duplex at the corresponding restriction site and releasing the HRP marker into solution, where it is quantified colorimetrically. The assay was tested for detection of the methicillin-resistant Staphylococcus aureus (MRSA) pathogen, using the mecA gene as a target. Calibration curves indicated that the limit of detection for both target oligonucleotide and PCR amplicon was approximately 1 nM. Sequences of target oligonucleotides were altered to demonstrate that (i) any mutation of the restriction site reduced the signal to zero; (ii) double and triple point mutations of sequences flanking the restriction site reduced restriction to 50-80% of the positive control; and (iii) a minimum of a 16-bp target-probe dsDNA hybrid was required for significant cleavage. Further experiments showed that the assay could detect the mecA amplicon from an unpurified PCR mixture with detection limits similar to those with standard fluorescence-based qPCR. Furthermore, addition of a large excess of heterologous genomic DNA did not affect amplicon detection. Specificity of the assay is very high because it involves two biorecognition steps. The proposed assay is low-cost and can be completed in less than 1 hour. Thus, we have demonstrated an efficient new approach for pathogen detection and amplicon genotyping in conjunction with various end-point and qPCR applications. The restriction enzyme assay may also be used for parallel analysis of multiple different amplicons from the same unpurified

  16. A new restriction endonuclease-based method for highly-specific detection of DNA targets from methicillin-resistant Staphylococcus aureus.

    Directory of Open Access Journals (Sweden)

    Maria W Smith

    Full Text Available PCR multiplexing has proven to be challenging, and thus has provided limited means for pathogen genotyping. We developed a new approach for analysis of PCR amplicons based on restriction endonuclease digestion. The first stage of the restriction enzyme assay is hybridization of a target DNA to immobilized complementary oligonucleotide probes that carry a molecular marker, horseradish peroxidase (HRP. At the second stage, a target-specific restriction enzyme is added, cleaving the target-probe duplex at the corresponding restriction site and releasing the HRP marker into solution, where it is quantified colorimetrically. The assay was tested for detection of the methicillin-resistant Staphylococcus aureus (MRSA pathogen, using the mecA gene as a target. Calibration curves indicated that the limit of detection for both target oligonucleotide and PCR amplicon was approximately 1 nM. Sequences of target oligonucleotides were altered to demonstrate that (i any mutation of the restriction site reduced the signal to zero; (ii double and triple point mutations of sequences flanking the restriction site reduced restriction to 50-80% of the positive control; and (iii a minimum of a 16-bp target-probe dsDNA hybrid was required for significant cleavage. Further experiments showed that the assay could detect the mecA amplicon from an unpurified PCR mixture with detection limits similar to those with standard fluorescence-based qPCR. Furthermore, addition of a large excess of heterologous genomic DNA did not affect amplicon detection. Specificity of the assay is very high because it involves two biorecognition steps. The proposed assay is low-cost and can be completed in less than 1 hour. Thus, we have demonstrated an efficient new approach for pathogen detection and amplicon genotyping in conjunction with various end-point and qPCR applications. The restriction enzyme assay may also be used for parallel analysis of multiple different amplicons from the same

  17. Digital breast tomosynthesis (DBT) to characterize MRI-detected additional lesions unidentified at targeted ultrasound in newly diagnosed breast cancer patients

    Energy Technology Data Exchange (ETDEWEB)

    Mariscotti, Giovanna; Durando, Manuela; Regini, Elisa; Fornari, Alberto; Fonio, Paolo; Gandini, Giovanni [Breast Imaging Service, Radiology - University of Turin, Department of Diagnostic Imaging and Radiotherapy, A.O.U. Citta della Salute e della Scienza, Torino (Italy); Houssami, Nehmat [University of Sydney, Screening and Test Evaluation Program, School of Public Health, Sydney Medical School, Sydney, NSW (Australia); Campanino, Pier Paolo [Ospedale Koelliker, Breast Imaging Service, Torino (Italy); Bussone, Riccardo [A.O.U. Citta della Salute e della Scienza of Turin, SSCVD Breast Surgery. Department of Surgery, Torino (Italy); Castellano, Isabella; Sapino, Anna [University of Turin, Department of Biomedical Sciences and Human Oncology, A.O.U. Citta della Salute e della Scienza, Torino (Italy)

    2015-09-15

    Preoperative breast magnetic resonance (MR) often generates additional suspicious findings needing further investigations. Targeted breast ultrasound (US) is the standard tool to characterize MR additional lesions. The purpose of this study is to evaluate the potential role of digital breast tomosynthesis (DBT) to characterize MR detected additional findings, unidentified at targeted breast US. This prospective study included women who a) had biopsy-proven, newly diagnosed breast cancers detected at conventional 2D mammography and/or US, referred to breast MR for tumour staging; and b) had DBT if additional MR findings were not detected at targeted ('second look') US. In 520 patients, MR identified 164 (in 114 women, 22 %) additional enhancing lesions. Targeted US identified 114/164 (69.5 %) of these, whereas 50/164 (30.5 %) remained unidentified. DBT identified 32/50 of these cases, increasing the overall characterization of MR detected additional findings to 89.0 % (146/164). Using DBT the identified lesions were significantly more likely to be malignant than benign MR-detected additional lesions (p = 0.04). DBT improves the characterization of additional MR findings not identified at targeted breast US in preoperative breast cancer staging. (orig.)

  18. Non-target time trend screening: a data reduction strategy for detecting emerging contaminants in biological samples.

    Science.gov (United States)

    Plassmann, Merle M; Tengstrand, Erik; Åberg, K Magnus; Benskin, Jonathan P

    2016-06-01

    Non-targeted mass spectrometry-based approaches for detecting novel xenobiotics in biological samples are hampered by the occurrence of naturally fluctuating endogenous substances, which are difficult to distinguish from environmental contaminants. Here, we investigate a data reduction strategy for datasets derived from a biological time series. The objective is to flag reoccurring peaks in the time series based on increasing peak intensities, thereby reducing peak lists to only those which may be associated with emerging bioaccumulative contaminants. As a result, compounds with increasing concentrations are flagged while compounds displaying random, decreasing, or steady-state time trends are removed. As an initial proof of concept, we created artificial time trends by fortifying human whole blood samples with isotopically labelled standards. Different scenarios were investigated: eight model compounds had a continuously increasing trend in the last two to nine time points, and four model compounds had a trend that reached steady state after an initial increase. Each time series was investigated at three fortification levels and one unfortified series. Following extraction, analysis by ultra performance liquid chromatography high-resolution mass spectrometry, and data processing, a total of 21,700 aligned peaks were obtained. Peaks displaying an increasing trend were filtered from randomly fluctuating peaks using time trend ratios and Spearman's rank correlation coefficients. The first approach was successful in flagging model compounds spiked at only two to three time points, while the latter approach resulted in all model compounds ranking in the top 11 % of the peak lists. Compared to initial peak lists, a combination of both approaches reduced the size of datasets by 80-85 %. Overall, non-target time trend screening represents a promising data reduction strategy for identifying emerging bioaccumulative contaminants in biological samples. Graphical abstract

  19. Targeted next-generation sequencing detects novel gene-phenotype associations and expands the mutational spectrum in cardiomyopathies.

    Directory of Open Access Journals (Sweden)

    Cinzia Forleo

    Full Text Available Cardiomyopathies are a heterogeneous group of primary diseases of the myocardium, including hypertrophic cardiomyopathy (HCM, dilated cardiomyopathy (DCM, and arrhythmogenic right ventricular cardiomyopathy (ARVC, with higher morbidity and mortality. These diseases are genetically diverse and associated with rare mutations in a large number of genes, many of which overlap among the phenotypes. To better investigate the genetic overlap between these three phenotypes and to identify new genotype-phenotype correlations, we designed a custom gene panel consisting of 115 genes known to be associated with cardiomyopathic phenotypes and channelopathies. A cohort of 38 unrelated patients, 16 affected by DCM, 14 by HCM and 8 by ARVC, was recruited for the study on the basis of more severe phenotypes and family history of cardiomyopathy and/or sudden death. We detected a total of 142 rare variants in 40 genes, and all patients were found to be carriers of at least one rare variant. Twenty-eight of the 142 rare variants were also predicted as potentially pathogenic variants and found in 26 patients. In 23 out of 38 patients, we found at least one novel potential gene-phenotype association. In particular, we detected three variants in OBSCN gene in ARVC patients, four variants in ANK2 gene and two variants in DLG1, TRPM4, and AKAP9 genes in DCM patients, two variants in PSEN2 gene and four variants in AKAP9 gene in HCM patients. Overall, our results confirmed that cardiomyopathic patients could carry multiple rare gene variants; in addition, our investigation of the genetic overlap among cardiomyopathies revealed new gene-phenotype associations. Furthermore, as our study confirms, data obtained using targeted next-generation sequencing could provide a remarkable contribution to the molecular diagnosis of cardiomyopathies, early identification of patients at risk for arrhythmia development, and better clinical management of cardiomyopathic patients.

  20. Targeted next-generation sequencing detects novel gene-phenotype associations and expands the mutational spectrum in cardiomyopathies.

    Science.gov (United States)

    Forleo, Cinzia; D'Erchia, Anna Maria; Sorrentino, Sandro; Manzari, Caterina; Chiara, Matteo; Iacoviello, Massimo; Guaricci, Andrea Igoren; De Santis, Delia; Musci, Rita Leonarda; La Spada, Antonino; Marangelli, Vito; Pesole, Graziano; Favale, Stefano

    2017-01-01

    Cardiomyopathies are a heterogeneous group of primary diseases of the myocardium, including hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), and arrhythmogenic right ventricular cardiomyopathy (ARVC), with higher morbidity and mortality. These diseases are genetically diverse and associated with rare mutations in a large number of genes, many of which overlap among the phenotypes. To better investigate the genetic overlap between these three phenotypes and to identify new genotype-phenotype correlations, we designed a custom gene panel consisting of 115 genes known to be associated with cardiomyopathic phenotypes and channelopathies. A cohort of 38 unrelated patients, 16 affected by DCM, 14 by HCM and 8 by ARVC, was recruited for the study on the basis of more severe phenotypes and family history of cardiomyopathy and/or sudden death. We detected a total of 142 rare variants in 40 genes, and all patients were found to be carriers of at least one rare variant. Twenty-eight of the 142 rare variants were also predicted as potentially pathogenic variants and found in 26 patients. In 23 out of 38 patients, we found at least one novel potential gene-phenotype association. In particular, we detected three variants in OBSCN gene in ARVC patients, four variants in ANK2 gene and two variants in DLG1, TRPM4, and AKAP9 genes in DCM patients, two variants in PSEN2 gene and four variants in AKAP9 gene in HCM patients. Overall, our results confirmed that cardiomyopathic patients could carry multiple rare gene variants; in addition, our investigation of the genetic overlap among cardiomyopathies revealed new gene-phenotype associations. Furthermore, as our study confirms, data obtained using targeted next-generation sequencing could provide a remarkable contribution to the molecular diagnosis of cardiomyopathies, early identification of patients at risk for arrhythmia development, and better clinical management of cardiomyopathic patients.

  1. Target-specific NMR detection of protein–ligand interactions with antibody-relayed {sup 15}N-group selective STD

    Energy Technology Data Exchange (ETDEWEB)

    Hetényi, Anasztázia [University of Szeged, Department of Medical Chemistry (Hungary); Hegedűs, Zsófia [University of Szeged, SZTE-MTA Lendület Foldamer Research Group, Institute of Pharmaceutical Analysis Department (Hungary); Fajka-Boja, Roberta; Monostori, Éva [Biological Research Center of the Hungarian Academy of Sciences, Lymphocyte Signal Transduction Laboratory, Institute of Genetics (Hungary); Kövér, Katalin E. [University of Debrecen, Department of Inorganic and Analytical Chemistry (Hungary); Martinek, Tamás A., E-mail: martinek@pharm.u-szeged.hu [University of Szeged, SZTE-MTA Lendület Foldamer Research Group, Institute of Pharmaceutical Analysis Department (Hungary)

    2016-12-15

    Fragment-based drug design has been successfully applied to challenging targets where the detection of the weak protein–ligand interactions is a key element. {sup 1}H saturation transfer difference (STD) NMR spectroscopy is a powerful technique for this work but it requires pure homogeneous proteins as targets. Monoclonal antibody (mAb)-relayed {sup 15}N-GS STD spectroscopy has been developed to resolve the problem of protein mixtures and impure proteins. A {sup 15}N-labelled target-specific mAb is selectively irradiated and the saturation is relayed through the target to the ligand. Tests on the anti-Gal-1 mAb/Gal-1/lactose system showed that the approach is experimentally feasible in a reasonable time frame. This method allows detection and identification of binding molecules directly from a protein mixture in a multicomponent system.

  2. Combination of mass spectrometry-based targeted lipidomics and supervised machine learning algorithms in detecting adulterated admixtures of white rice.

    Science.gov (United States)

    Lim, Dong Kyu; Long, Nguyen Phuoc; Mo, Changyeun; Dong, Ziyuan; Cui, Lingmei; Kim, Giyoung; Kwon, Sung Won

    2017-10-01

    The mixing of extraneous ingredients with original products is a common adulteration practice in food and herbal medicines. In particular, authenticity of white rice and its corresponding blended products has become a key issue in food industry. Accordingly, our current study aimed to develop and evaluate a novel discrimination method by combining targeted lipidomics with powerful supervised learning methods, and eventually introduce a platform to verify the authenticity of white rice. A total of 30 cultivars were collected, and 330 representative samples of white rice from Korea and China as well as seven mixing ratios were examined. Random forests (RF), support vector machines (SVM) with a radial basis function kernel, C5.0, model averaged neural network, and k-nearest neighbor classifiers were used for the classification. We achieved desired results, and the classifiers effectively differentiated white rice from Korea to blended samples with high prediction accuracy for the contamination ratio as low as five percent. In addition, RF and SVM classifiers were generally superior to and more robust than the other techniques. Our approach demonstrated that the relative differences in lysoGPLs can be successfully utilized to detect the adulterated mixing of white rice originating from different countries. In conclusion, the present study introduces a novel and high-throughput platform that can be applied to authenticate adulterated admixtures from original white rice samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Sequence-motif Detection of NAD(P)-binding Proteins: Discovery of a Unique Antibacterial Drug Target

    Science.gov (United States)

    Hua, Yun Hao; Wu, Chih Yuan; Sargsyan, Karen; Lim, Carmay

    2014-09-01

    Many enzymes use nicotinamide adenine dinucleotide or nicotinamide adenine dinucleotide phosphate (NAD(P)) as essential coenzymes. These enzymes often do not share significant sequence identity and cannot be easily detected by sequence homology. Previously, we determined all distinct locally conserved pyrophosphate-binding structures (3d motifs) from NAD(P)-bound protein structures, from which 1d sequence motifs were derived. Here, we aim to establish the precision of these 3d and 1d motifs to annotate NAD(P)-binding proteins. We show that the pyrophosphate-binding 3d motifs are characteristic of NAD(P)-binding proteins, as they are rarely found in nonNAD(P)-binding proteins. Furthermore, several 1d motifs could distinguish between proteins that bind only NAD and those that bind only NADP. They could also distinguish between NAD(P)-binding proteins from nonNAD(P)-binding ones. Interestingly, one of the pyrophosphate-binding 3d and corresponding 1d motifs was found only in enoyl-acyl carrier protein reductases, which are enzymes essential for bacterial fatty acid biosynthesis. This unique 3d motif serves as an attractive novel drug target, as it is conserved across many bacterial species and is not found in human proteins.

  4. The design of a cryogenic dark matter detector based on the detection of the recoil direction of target nuclei

    Energy Technology Data Exchange (ETDEWEB)

    Gaitskell, R.J. [Oxford Univ. (United Kingdom). Dept. of Physics; Angrave, L.C. [Oxford Univ. (United Kingdom). Dept. of Physics; Booth, N.E. [Oxford Univ. (United Kingdom). Dept. of Physics; Esposito, E. [Oxford Univ. (United Kingdom). Dept. of Physics; Giles, T.J. [Oxford Univ. (United Kingdom). Dept. of Physics; Hoess, C. [Oxford Univ. (United Kingdom). Dept. of Physics; Houwman, E.P. [Oxford Univ. (United Kingdom). Dept. of Physics; Salmon, G.L. [Oxford Univ. (United Kingdom). Dept. of Physics; Van den Putte, M. [Oxford Univ. (United Kingdom). Dept. of Physics; Waenninger, S. [Oxford Univ. (United Kingdom). Dept. of Physics

    1996-02-11

    We discuss the design of a cryogenic detector for a WIMP dark matter search based on single crystal absorbers and using Series Arrays of Superconducting Tunnel Junctions (SASTJs). The distribution of recoil vectors of target nuclei from WIMP interactions are affected by the motion of the laboratory through the dark matter halo. The angular distribution of recoil directions is skewed due to the motion of the solar system around the galaxy and is modulated by the diurnal and annual rotation of the earth. We discuss the kinematics of the recoil events and how a directional signal might be identified in our cryogenic detectors using the fast response of SASTJs to the ballistic phonons arising in the absorber from WIMP interactions. We consider how the anisotropy of a dark matter recoil distribution can be used to place statistical limits on its component relative to the isotropic background signal. We also consider how the dark matter limit is altered if only the axis of the nuclear recoil, rather than the full recoil direction is available. We also briefly consider the effect of phonon focusing within single crystal absorbers. Focusing will modulate strongly the signal detected by the SASTJs, on the crystal surface, as the position of the interaction within the crystal varies. A comparison is made between the behaviour of phonons in strongly focusing crystals, such as Nb, Si and LiF, and their near isotropic propagation in BaF{sub 2}. (orig.).

  5. AmoA-Targeted Polymerase Chain Reaction Primers for the Specific Detection and Quantification of Comammox Nitrospira in the Environment

    Directory of Open Access Journals (Sweden)

    Petra Pjevac

    2017-08-01

    Full Text Available Nitrification, the oxidation of ammonia via nitrite to nitrate, has always been considered to be catalyzed by the concerted activity of ammonia- and nitrite-oxidizing microorganisms. Only recently, complete ammonia oxidizers (“comammox”, which oxidize ammonia to nitrate on their own, were identified in the bacterial genus Nitrospira, previously assumed to contain only canonical nitrite oxidizers. Nitrospira are widespread in nature, but for assessments of the distribution and functional importance of comammox Nitrospira in ecosystems, cultivation-independent tools to distinguish comammox from strictly nitrite-oxidizing Nitrospira are required. Here we developed new PCR primer sets that specifically target the amoA genes coding for subunit A of the distinct ammonia monooxygenase of comammox Nitrospira. While existing primers capture only a fraction of the known comammox amoA diversity, the new primer sets cover as much as 95% of the comammox amoA clade A and 92% of the clade B sequences in a reference database containing 326 comammox amoA genes with sequence information at the primer binding sites. Application of the primers to 13 samples from engineered systems (a groundwater well, drinking water treatment and wastewater treatment plants and other habitats (rice paddy and forest soils, rice rhizosphere, brackish lake sediment and freshwater biofilm detected comammox Nitrospira in all samples and revealed a considerable diversity of comammox in most habitats. Excellent primer specificity for comammox amoA was achieved by avoiding the use of highly degenerate primer preparations and by using equimolar mixtures of oligonucleotides that match existing comammox amoA genes. Quantitative PCR with these equimolar primer mixtures was highly sensitive and specific, and enabled the efficient quantification of clade A and clade B comammox amoA gene copy numbers in environmental samples. The measured relative abundances of comammox Nitrospira, compared

  6. AmoA-Targeted Polymerase Chain Reaction Primers for the Specific Detection and Quantification of Comammox Nitrospira in the Environment.

    Science.gov (United States)

    Pjevac, Petra; Schauberger, Clemens; Poghosyan, Lianna; Herbold, Craig W; van Kessel, Maartje A H J; Daebeler, Anne; Steinberger, Michaela; Jetten, Mike S M; Lücker, Sebastian; Wagner, Michael; Daims, Holger

    2017-01-01

    Nitrification, the oxidation of ammonia via nitrite to nitrate, has always been considered to be catalyzed by the concerted activity of ammonia- and nitrite-oxidizing microorganisms. Only recently, complete ammonia oxidizers ("comammox"), which oxidize ammonia to nitrate on their own, were identified in the bacterial genus Nitrospira, previously assumed to contain only canonical nitrite oxidizers. Nitrospira are widespread in nature, but for assessments of the distribution and functional importance of comammox Nitro