WorldWideScience

Sample records for subpixel target detection

  1. Detection of Subpixel Submerged Mine-Like Targets in WorldView-2 Multispectral Imagery

    Science.gov (United States)

    2012-09-01

    exploit the capabilities of the technology already in use, such as the WorldView-2. This is a complicated issue, as any capability has to be able to...Applied Science and Analysis Inc. 91 Mayer, R., & Bucholtz, F. (2003). Object detection by using “ whitening / dewhitening” to transform target

  2. 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.

  3. Subpixel Mapping of Hyperspectral Image Based on Linear Subpixel Feature Detection and Object Optimization

    Science.gov (United States)

    Liu, Zhaoxin; Zhao, Liaoying; Li, Xiaorun; Chen, Shuhan

    2018-04-01

    Owing to the limitation of spatial resolution of the imaging sensor and the variability of ground surfaces, mixed pixels are widesperead in hyperspectral imagery. The traditional subpixel mapping algorithms treat all mixed pixels as boundary-mixed pixels while ignoring the existence of linear subpixels. To solve this question, this paper proposed a new subpixel mapping method based on linear subpixel feature detection and object optimization. Firstly, the fraction value of each class is obtained by spectral unmixing. Secondly, the linear subpixel features are pre-determined based on the hyperspectral characteristics and the linear subpixel feature; the remaining mixed pixels are detected based on maximum linearization index analysis. The classes of linear subpixels are determined by using template matching method. Finally, the whole subpixel mapping results are iteratively optimized by binary particle swarm optimization algorithm. The performance of the proposed subpixel mapping method is evaluated via experiments based on simulated and real hyperspectral data sets. The experimental results demonstrate that the proposed method can improve the accuracy of subpixel mapping.

  4. A robust sub-pixel edge detection method of infrared image based on tremor-based retinal receptive field model

    Science.gov (United States)

    Gao, Kun; Yang, Hu; Chen, Xiaomei; Ni, Guoqiang

    2008-03-01

    Because of complex thermal objects in an infrared image, the prevalent image edge detection operators are often suitable for a certain scene and extract too wide edges sometimes. From a biological point of view, the image edge detection operators work reliably when assuming a convolution-based receptive field architecture. A DoG (Difference-of- Gaussians) model filter based on ON-center retinal ganglion cell receptive field architecture with artificial eye tremors introduced is proposed for the image contour detection. Aiming at the blurred edges of an infrared image, the subsequent orthogonal polynomial interpolation and sub-pixel level edge detection in rough edge pixel neighborhood is adopted to locate the foregoing rough edges in sub-pixel level. Numerical simulations show that this method can locate the target edge accurately and robustly.

  5. Tracking Subpixel Targets with Critically Sampled Optical Sensors

    Science.gov (United States)

    2012-09-01

    LEFT BLANK xii LIST OF ACRONYMS AND ABBREVIATIONS PSF point spread function SNR signal-to-noise ratio SLAM simultaneous localization and tracking EO... LIDAR light detection and ranging FOV field of view RMS root mean squared PF particle filter TBD track before detect MCMC monte carlo markov chain

  6. Detection of Olea europaea subsp. cuspidata and Juniperus procera in the dry Afromontane forest of northern Ethiopia using subpixel analysis of Landsat imagery

    Science.gov (United States)

    Hishe, Hadgu; Giday, Kidane; Neka, Mulugeta; Soromessa, Teshome; Van Orshoven, Jos; Muys, Bart

    2015-01-01

    Comprehensive and less costly forest inventory approaches are required to monitor the spatiotemporal dynamics of key species in forest ecosystems. Subpixel analysis using the earth resources data analysis system imagine subpixel classification procedure was tested to extract Olea europaea subsp. cuspidata and Juniperus procera canopies from Landsat 7 enhanced thematic mapper plus imagery. Control points with various canopy area fractions of the target species were collected to develop signatures for each of the species. With these signatures, the imagine subpixel classification procedure was run for each species independently. The subpixel process enabled the detection of O. europaea subsp. cuspidata and J. procera trees in pure and mixed pixels. Total of 100 pixels each were field verified for both species. An overall accuracy of 85% was achieved for O. europaea subsp. cuspidata and 89% for J. procera. A high overall accuracy level of detecting species at a natural forest was achieved, which encourages using the algorithm for future species monitoring activities. We recommend that the algorithm has to be validated in similar environment to enrich the knowledge on its capability to ensure its wider usage.

  7. Measurement of 3-D Vibrational Motion by Dynamic Photogrammetry Using Least-Square Image Matching for Sub-Pixel Targeting to Improve Accuracy

    Science.gov (United States)

    Lee, Hyoseong; Rhee, Huinam; Oh, Jae Hong; Park, Jin Ho

    2016-01-01

    This paper deals with an improved methodology to measure three-dimensional dynamic displacements of a structure by digital close-range photogrammetry. A series of stereo images of a vibrating structure installed with targets are taken at specified intervals by using two daily-use cameras. A new methodology is proposed to accurately trace the spatial displacement of each target in three-dimensional space. This method combines the correlation and the least-square image matching so that the sub-pixel targeting can be obtained to increase the measurement accuracy. Collinearity and space resection theory are used to determine the interior and exterior orientation parameters. To verify the proposed method, experiments have been performed to measure displacements of a cantilevered beam excited by an electrodynamic shaker, which is vibrating in a complex configuration with mixed bending and torsional motions simultaneously with multiple frequencies. The results by the present method showed good agreement with the measurement by two laser displacement sensors. The proposed methodology only requires inexpensive daily-use cameras, and can remotely detect the dynamic displacement of a structure vibrating in a complex three-dimensional defection shape up to sub-pixel accuracy. It has abundant potential applications to various fields, e.g., remote vibration monitoring of an inaccessible or dangerous facility. PMID:26978366

  8. Field programmable gate array based hardware implementation of a gradient filter for edge detection in colour images with subpixel precision

    International Nuclear Information System (INIS)

    Schellhorn, M; Rosenberger, M; Correns, M; Blau, M; Goepfert, A; Rueckwardt, M; Linss, G

    2010-01-01

    Within the field of industrial image processing the use of colour cameras becomes ever more common. Increasingly the established black and white cameras are replaced by economical single-chip colour cameras with Bayer pattern. The use of the additional colour information is particularly important for recognition or inspection. Become interesting however also for the geometric metrology, if measuring tasks can be solved more robust or more exactly. However only few suitable algorithms are available, in order to detect edges with the necessary precision. All attempts require however additional computation expenditure. On the basis of a new filter for edge detection in colour images with subpixel precision, the implementation on a pre-processing hardware platform is presented. Hardware implemented filters offer the advantage that they can be used easily with existing measuring software, since after the filtering a single channel image is present, which unites the information of all colour channels. Advanced field programmable gate arrays represent an ideal platform for the parallel processing of multiple channels. The effective implementation presupposes however a high programming expenditure. On the example of the colour filter implementation, arising problems are analyzed and the chosen solution method is presented.

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

    Science.gov (United States)

    2012-09-01

    sweep, which is towed behind the helicopter and produces a magnetic signature in order to force magnetic influence mines to detonate. The MH-60S...Science and civilisation in China, Volume 5, Part 7. Cambridge University Press. Olsen, R. C. (2007). Remote sensing from air and space. Bellingham

  10. Transductive and matched-pair machine learning for difficult target detection problems

    Science.gov (United States)

    Theiler, James

    2014-06-01

    This paper will describe the application of two non-traditional kinds of machine learning (transductive machine learning and the more recently proposed matched-pair machine learning) to the target detection problem. The approach combines explicit domain knowledge to model the target signal with a more agnostic machine-learning approach to characterize the background. The concept is illustrated with simulated data from an elliptically-contoured background distribution, on which a subpixel target of known spectral signature but unknown spatial extent has been implanted.

  11. Chandra ACIS Sub-pixel Resolution

    Science.gov (United States)

    Kim, Dong-Woo; Anderson, C. S.; Mossman, A. E.; Allen, G. E.; Fabbiano, G.; Glotfelty, K. J.; Karovska, M.; Kashyap, V. L.; McDowell, J. C.

    2011-05-01

    We investigate how to achieve the best possible ACIS spatial resolution by binning in ACIS sub-pixel and applying an event repositioning algorithm after removing pixel-randomization from the pipeline data. We quantitatively assess the improvement in spatial resolution by (1) measuring point source sizes and (2) detecting faint point sources. The size of a bright (but no pile-up), on-axis point source can be reduced by about 20-30%. With the improve resolution, we detect 20% more faint sources when embedded on the extended, diffuse emission in a crowded field. We further discuss the false source rate of about 10% among the newly detected sources, using a few ultra-deep observations. We also find that the new algorithm does not introduce a grid structure by an aliasing effect for dithered observations and does not worsen the positional accuracy

  12. 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...

  13. Infrared Small Moving Target Detection via Saliency Histogram and Geometrical Invariability

    Directory of Open Access Journals (Sweden)

    Minjie Wan

    2017-06-01

    Full Text Available In order to detect both bright and dark small moving targets effectively in infrared (IR video sequences, a saliency histogram and geometrical invariability based method is presented in this paper. First, a saliency map that roughly highlights the salient regions of the original image is obtained by tuning its amplitude spectrum in the frequency domain. Then, a saliency histogram is constructed by means of averaging the accumulated saliency value of each gray level in the map, through which bins corresponding to bright target and dark target are assigned with large values in the histogram. Next, single-frame detection of candidate targets is accomplished by a binarized segmentation using an adaptive threshold, and their centroid coordinates with sub-pixel accuracy are calculated through a connected components labeling method as well as a gray-weighted criterion. Finally, considering the motion characteristics in consecutive frames, an inter-frame false alarm suppression method based on geometrical invariability is developed to improve the precision rate further. Quantitative analyses demonstrate the detecting precision of this proposed approach can be up to 97% and Receiver Operating Characteristic (ROC curves further verify our method outperforms other state-of-the-arts methods in both detection rate and false alarm rate.

  14. Magnetic biosensor system to detect biological targets

    KAUST Repository

    Li, Fuquan; Gooneratne, Chinthaka Pasan; Kosel, Jü rgen

    2012-01-01

    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

  15. Manifold structure preservative for hyperspectral target detection

    Science.gov (United States)

    Imani, Maryam

    2018-05-01

    A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.

  16. Covariance descriptor fusion for target detection

    Science.gov (United States)

    Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih

    2016-05-01

    Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.

  17. Target Detection Using an AOTF Hyperspectral Imager

    Science.gov (United States)

    Cheng, L-J.; Mahoney, J.; Reyes, F.; Suiter, H.

    1994-01-01

    This paper reports results of a recent field experiment using a prototype system to evaluate the acousto-optic tunable filter polarimetric hyperspectral imaging technology for target detection applications.

  18. Alteration mineral mapping in inaccessible regions using target detection algorithms to ASTER data

    International Nuclear Information System (INIS)

    Pour, A B; Hashim, M; Park, Y

    2017-01-01

    In this study, the applications of target detection algorithms such as Constrained Energy Minimization (CEM), Orthogonal Subspace Projection (OSP) and Adaptive Coherence Estimator (ACE) to shortwave infrared bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data was investigated to extract geological information for alteration mineral mapping in poorly exposed lithologies in inaccessible domains. The Oscar II coast area north-eastern Graham Land, Antarctic Peninsula (AP) was selected in this study to conduct a satellite-based remote sensing mapping technique. It is an inaccessible region due to the remoteness of many rock exposures and the necessity to travel over sever mountainous and glacier-cover terrains for geological field mapping and sample collection. Fractional abundance of alteration minerals such as muscovite, kaolinite, illite, montmorillonite, epidote, chlorite and biotite were identified in alteration zones using CEM, OSP and ACE algorithms in poorly mapped and unmapped zones at district scale for the Oscar II coast area. The results of this investigation demonstrated the applicability of ASTER shortwave infrared spectral data for lithological and alteration mineral mapping in poorly exposed lithologies and inaccessible regions, particularly using the image processing algorithms that are capable to detect sub-pixel targets in the remotely sensed images, where no prior information is available. (paper)

  19. Dim point target detection against bright background

    Science.gov (United States)

    Zhang, Yao; Zhang, Qiheng; Xu, Zhiyong; Xu, Junping

    2010-05-01

    For target detection within a large-field cluttered background from a long distance, several difficulties, involving low contrast between target and background, little occupancy, illumination ununiformity caused by vignetting of lens, and system noise, make it a challenging problem. The existing approaches to dim target detection can be roughly divided into two categories: detection before tracking (DBT) and tracking before detection (TBD). The DBT-based scheme has been widely used in practical applications due to its simplicity, but it often requires working in the situation with a higher signal-to-noise ratio (SNR). In contrast, the TBD-based methods can provide impressive detection results even in the cases of very low SNR; unfortunately, the large memory requirement and high computational load prevents these methods from real-time tasks. In this paper, we propose a new method for dim target detection. We address this problem by combining the advantages of the DBT-based scheme in computational efficiency and of the TBD-based in detection capability. Our method first predicts the local background, and then employs the energy accumulation and median filter to remove background clutter. The dim target is finally located by double window filtering together with an improved high order correlation which speeds up the convergence. The proposed method is implemented on a hardware platform and performs suitably in outside experiments.

  20. Automatic target detection using binary template matching

    Science.gov (United States)

    Jun, Dong-San; Sun, Sun-Gu; Park, HyunWook

    2005-03-01

    This paper presents a new automatic target detection (ATD) algorithm to detect targets such as battle tanks and armored personal carriers in ground-to-ground scenarios. Whereas most ATD algorithms were developed for forward-looking infrared (FLIR) images, we have developed an ATD algorithm for charge-coupled device (CCD) images, which have superior quality to FLIR images in daylight. The proposed algorithm uses fast binary template matching with an adaptive binarization, which is robust to various light conditions in CCD images and saves computation time. Experimental results show that the proposed method has good detection performance.

  1. 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.

  2. 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.

  3. Characterizing Subpixel Spatial Resolution of a Hybrid CMOS Detector

    Science.gov (United States)

    Bray, Evan; Burrows, Dave; Chattopadhyay, Tanmoy; Falcone, Abraham; Hull, Samuel; Kern, Matthew; McQuaide, Maria; Wages, Mitchell

    2018-01-01

    The detection of X-rays is a unique process relative to other wavelengths, and allows for some novel features that increase the scientific yield of a single observation. Unlike lower photon energies, X-rays liberate a large number of electrons from the silicon absorber array of the detector. This number is usually on the order of several hundred to a thousand for moderate-energy X-rays. These electrons tend to diffuse outward into what is referred to as the charge cloud. This cloud can then be picked up by several pixels, forming a specific pattern based on the exact incident location. By conducting the first ever “mesh experiment" on a hybrid CMOS detector (HCD), we have experimentally determined the charge cloud shape and used it to characterize responsivity of the detector with subpixel spatial resolution.

  4. Camouflage, detection and identification of moving targets.

    Science.gov (United States)

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

    2013-05-07

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

  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. Transforming landscape ecological evaluations using sub-pixel remote sensing classifications: A study of invasive saltcedar (Tamarix spp.)

    Science.gov (United States)

    Frazier, Amy E.

    Invasive species disrupt landscape patterns and compromise the functionality of ecosystem processes. Non-native saltcedar (Tamarix spp.) poses significant threats to native vegetation and groundwater resources in the southwestern U.S. and Mexico, and quantifying spatial and temporal distribution patterns is essential for monitoring its spread. Advanced remote sensing classification techniques such as sub-pixel classifications are able to detect and discriminate saltcedar from native vegetation with high accuracy, but these types of classifications are not compatible with landscape metrics, which are the primary tool available for statistically assessing distribution patterns, because they do not have discrete class boundaries. The objective of this research is to develop new methods that allow sub-pixel classifications to be analyzed using landscape metrics. The research will be carried out through three specific aims: (1) develop and test a method to transform continuous sub-pixel classifications into categorical representations that are compatible with widely used landscape metric tools, (2) establish a gradient-based concept of landscape using sub-pixel classifications and the technique developed in the first objective to explore the relationships between pattern and process, and (3) generate a new super-resolution mapping technique method to predict the spatial locations of fractional land covers within a pixel. Results show that the threshold gradient method is appropriate for discretizing sub-pixel data, and can be used to generate increased information about the landscape compared to traditional single-value metrics. Additionally, the super-resolution classification technique was also able to provide detailed sub-pixel mapping information, but additional work will be needed to develop rigorous validation and accuracy assessment techniques.

  7. 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.

  8. Space moving target detection using time domain feature

    Science.gov (United States)

    Wang, Min; Chen, Jin-yong; Gao, Feng; Zhao, Jin-yu

    2018-01-01

    The traditional space target detection methods mainly use the spatial characteristics of the star map to detect the targets, which can not make full use of the time domain information. This paper presents a new space moving target detection method based on time domain features. We firstly construct the time spectral data of star map, then analyze the time domain features of the main objects (target, stars and the background) in star maps, finally detect the moving targets using single pulse feature of the time domain signal. The real star map target detection experimental results show that the proposed method can effectively detect the trajectory of moving targets in the star map sequence, and the detection probability achieves 99% when the false alarm rate is about 8×10-5, which outperforms those of compared algorithms.

  9. 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.

  10. Pixel-Level Decorrelation and BiLinearly Interpolated Subpixel Sensitivity applied to WASP-29b

    Science.gov (United States)

    Challener, Ryan; Harrington, Joseph; Cubillos, Patricio; Blecic, Jasmina; Deming, Drake

    2017-10-01

    Measured exoplanet transit and eclipse depths can vary significantly depending on the methodology used, especially at the low S/N levels in Spitzer eclipses. BiLinearly Interpolated Subpixel Sensitivity (BLISS) models a physical, spatial effect, which is independent of any astrophysical effects. Pixel-Level Decorrelation (PLD) uses the relative variations in pixels near the target to correct for flux variations due to telescope motion. PLD is being widely applied to all Spitzer data without a thorough understanding of its behavior. It is a mathematical method derived from a Taylor expansion, and many of its parameters do not have a physical basis. PLD also relies heavily on binning the data to remove short time-scale variations, which can artifically smooth the data. We applied both methods to 4 eclipse observations of WASP-29b, a Saturn-sized planet, which was observed twice with the 3.6 µm and twice with the 4.5 µm channels of Spitzer's IRAC in 2010, 2011 and 2014 (programs 60003, 70084, and 10054, respectively). We compare the resulting eclipse depths and midpoints from each model, assess each method's ability to remove correlated noise, and discuss how to choose or combine the best data analysis methods. We also refined the orbit from eclipse timings, detecting a significant nonzero eccentricity, and we used our Bayesian Atmospheric Radiative Transfer (BART) code to retrieve the planet's atmosphere, which is consistent with a blackbody. Spitzer is operated by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. This work was supported by NASA Planetary Atmospheres grant NNX12AI69G and NASA Astrophysics Data Analysis Program grant NNX13AF38G.

  11. Camouflage target detection via hyperspectral imaging plus information divergence measurement

    Science.gov (United States)

    Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Ji, Yiqun; Shen, Weimin

    2016-01-01

    Target detection is one of most important applications in remote sensing. Nowadays accurate camouflage target distinction is often resorted to spectral imaging technique due to its high-resolution spectral/spatial information acquisition ability as well as plenty of data processing methods. In this paper, hyper-spectral imaging technique together with spectral information divergence measure method is used to solve camouflage target detection problem. A self-developed visual-band hyper-spectral imaging device is adopted to collect data cubes of certain experimental scene before spectral information divergences are worked out so as to discriminate target camouflage and anomaly. Full-band information divergences are measured to evaluate target detection effect visually and quantitatively. Information divergence measurement is proved to be a low-cost and effective tool for target detection task and can be further developed to other target detection applications beyond spectral imaging technique.

  12. Moving Target Detection and Active Tracking with a Multicamera Network

    Directory of Open Access Journals (Sweden)

    Long Zhao

    2014-01-01

    Full Text Available We propose a systematic framework for Intelligence Video Surveillance System (IVSS with a multicamera network. The proposed framework consists of low-cost static and PTZ cameras, target detection and tracking algorithms, and a low-cost PTZ camera feedback control algorithm based on target information. The target detection and tracking is realized by fixed cameras using a moving target detection and tracking algorithm; the PTZ camera is manoeuvred to actively track the target from the tracking results of the static camera. The experiments are carried out using practical surveillance system data, and the experimental results show that the systematic framework and algorithms presented in this paper are efficient.

  13. Hyperspectral Imagery Target Detection Using Improved Anomaly Detection and Signature Matching Methods

    National Research Council Canada - National Science Library

    Smetek, Timothy E

    2007-01-01

    This research extends the field of hyperspectral target detection by developing autonomous anomaly detection and signature matching methodologies that reduce false alarms relative to existing benchmark detectors...

  14. 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.

  15. Small Surface Target Detection with EO/IR Sensors

    NARCIS (Netherlands)

    Jong, A.N. de; Kemp, R.A.W.

    1998-01-01

    The detection of small surface targets at sea is an increasing requirement for warships. The present sensors on board do not provide the required detection probabilities for these low observable targets like small rubber boats, floating mines, periscopes, people etc. The reason for the low

  16. Quantum Illumination-Based Target Detection and Discrimination

    Science.gov (United States)

    2014-06-30

    photodiode with an estimated quantum efficiency of 85% and an ultralow-noise transimpedance amplifier . Compared with to our initial QI measurements...demonstrated high signal-to-noise ratio (SNR) quantum-illumination target detection in a lossy, noisy environment using an optical parametric amplifier ...Research Triangle Park, NC 27709-2211 quantum communication, target detection, entanglement, parametric downconversion, optical parametric amplifiers

  17. Dim target detection method based on salient graph fusion

    Science.gov (United States)

    Hu, Ruo-lan; Shen, Yi-yan; Jiang, Jun

    2018-02-01

    Dim target detection is one key problem in digital image processing field. With development of multi-spectrum imaging sensor, it becomes a trend to improve the performance of dim target detection by fusing the information from different spectral images. In this paper, one dim target detection method based on salient graph fusion was proposed. In the method, Gabor filter with multi-direction and contrast filter with multi-scale were combined to construct salient graph from digital image. And then, the maximum salience fusion strategy was designed to fuse the salient graph from different spectral images. Top-hat filter was used to detect dim target from the fusion salient graph. Experimental results show that proposal method improved the probability of target detection and reduced the probability of false alarm on clutter background images.

  18. Small target pre-detection with an attention mechanism

    Science.gov (United States)

    Wang, Yuehuan; Zhang, Tianxu; Wang, Guoyou

    2002-04-01

    We introduce the concept of predetection based on an attention mechanism to improve the efficiency of small-target detection by limiting the image region of detection. According to the characteristics of small-target detection, local contrast is taken as the only feature in predetection and a nonlinear sampling model is adopted to make the predetection adaptive to detect small targets with different area sizes. To simplify the predetection itself and decrease the false alarm probability, neighboring nodes in the sampling grid are used to generate a saliency map, and a short-term memory is adopted to accelerate the `pop-out' of targets. We discuss the fact that the proposed approach is simple enough in computational complexity. In addition, even in a cluttered background, attention can be led to targets in a satisfying few iterations, which ensures that the detection efficiency will not be decreased due to false alarms. Experimental results are presented to demonstrate the applicability of the approach.

  19. Comparison of BiLinearly Interpolated Subpixel Sensitivity Mapping and Pixel-Level Decorrelation

    Science.gov (United States)

    Challener, Ryan C.; Harrington, Joseph; Cubillos, Patricio; Foster, Andrew S.; Deming, Drake; WASP Consortium

    2016-10-01

    Exoplanet eclipse signals are weaker than the systematics present in the Spitzer Space Telescope's Infrared Array Camera (IRAC), and thus the correction method can significantly impact a measurement. BiLinearly Interpolated Subpixel Sensitivity (BLISS) mapping calculates the sensitivity of the detector on a subpixel grid and corrects the photometry for any sensitivity variations. Pixel-Level Decorrelation (PLD) removes the sensitivity variations by considering the relative intensities of the pixels around the source. We applied both methods to WASP-29b, a Saturn-sized planet with a mass of 0.24 ± 0.02 Jupiter masses and a radius of 0.84 ± 0.06 Jupiter radii, which we observed during eclipse twice with the 3.6 µm and once with the 4.5 µm channels of IRAC aboard Spitzer in 2010 and 2011 (programs 60003 and 70084, respectively). We compared the results of BLISS and PLD, and comment on each method's ability to remove time-correlated noise. WASP-29b exhibits a strong detection at 3.6 µm and no detection at 4.5 µm. Spitzer is operated by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. This work was supported by NASA Planetary Atmospheres grant NNX12AI69G and NASA Astrophysics Data Analysis Program grant NNX13AF38G.

  20. Detection of dim targets in multiple environments

    Science.gov (United States)

    Mirsky, Grace M.; Woods, Matthew; Grasso, Robert J.

    2013-10-01

    The proliferation of a wide variety of weapons including Anti-Aircraft Artillery (AAA), rockets, and small arms presents a substantial threat to both military and civilian aircraft. To address this ever-present threat, Northrop Grumman has assessed unguided threat phenomenology to understand the underlying physical principles for detection. These principles, based upon threat transit through the atmosphere, exploit a simple phenomenon universal to all objects moving through an atmosphere comprised of gaseous media to detect and track the threat in the presence of background and clutter. Threat detection has rapidly become a crucial component of aircraft survivability systems that provide situational awareness to the crew. It is particularly important to platforms which may spend a majority of their time at low altitudes and within the effective range of a large variety of weapons. Detection of these threats presents a unique challenge as this class of threat typically has a dim signature coupled with a short duration. Correct identification of each of the threat components (muzzle flash and projectile) is important to determine trajectory and intent while minimizing false alarms and maintaining a high detection probability in all environments.

  1. A robust Hough transform algorithm for determining the radiation centers of circular and rectangular fields with subpixel accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Du Weiliang; Yang, James [Department of Radiation Physics, University of Texas M D Anderson Cancer Center, 1515 Holcombe Blvd, Unit 94, Houston, TX 77030 (United States)], E-mail: wdu@mdanderson.org

    2009-02-07

    Uncertainty in localizing the radiation field center is among the major components that contribute to the overall positional error and thus must be minimized. In this study, we developed a Hough transform (HT)-based computer algorithm to localize the radiation center of a circular or rectangular field with subpixel accuracy. We found that the HT method detected the centers of the test circular fields with an absolute error of 0.037 {+-} 0.019 pixels. On a typical electronic portal imager with 0.5 mm image resolution, this mean detection error was translated to 0.02 mm, which was much finer than the image resolution. It is worth noting that the subpixel accuracy described here does not include experimental uncertainties such as linac mechanical instability or room laser inaccuracy. The HT method was more accurate and more robust to image noise and artifacts than the traditional center-of-mass method. Application of the HT method in Winston-Lutz tests was demonstrated to measure the ball-radiation center alignment with subpixel accuracy. Finally, the method was applied to quantitative evaluation of the radiation center wobble during collimator rotation.

  2. Target Detection Based on EBPSK Satellite Passive Radar

    Directory of Open Access Journals (Sweden)

    Lu Zeyuan

    2015-05-01

    Full Text Available Passive radar is a topic anti stealth technology with simple structure, and low cost. Radiation source model, signal transmission model, and target detection are the key points of passive radar technology research. The paper analyzes the characteristics of EBPSK signal modulation and target detection method aspect of spaceborne radiant source. By comparison with other satellite navigation and positioning system, the characteristics of EBPSK satellite passive radar system are analyzed. It is proved that the maximum detection range of EBPSK satellite signal can satisfy the needs of the proposed model. In the passive radar model, sparse representation is used to achieve high resolution DOA detection. The comparison with the real target track by simulation demonstrates that effective detection of airborne target using EBPSK satellite passive radar system based on sparse representation is efficient.

  3. Detection and identification of human targets in radar data

    Science.gov (United States)

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

    2007-04-01

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

  4. Photonics: From target recognition to lesion detection

    Science.gov (United States)

    Henry, E. Michael

    1994-01-01

    Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

  5. 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.

  6. Spatial scaling of net primary productivity using subpixel landcover information

    Science.gov (United States)

    Chen, X. F.; Chen, Jing M.; Ju, Wei M.; Ren, L. L.

    2008-10-01

    Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. These biases result from overlooking subpixel variability of land surface characteristics. Vegetation heterogeneity is an important factor introducing biases in regional ecological modeling, especially when the modeling is made on large grids. This study suggests a simple algorithm that uses subpixel information on the spatial variability of land cover type to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that NPP obtained from calculations made at coarse spatial resolutions are multiplied by simple functions that attempt to reproduce the effects of subpixel variability of land cover type on NPP. Its application to a carbon-hydrology coupled model(BEPS-TerrainLab model) estimates made at a 1-km resolution over a watershed (named Baohe River Basin) located in the southwestern part of Qinling Mountains, Shaanxi Province, China, improved estimates of average NPP as well as its spatial variability.

  7. 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.

  8. Infrared small target detection with kernel Fukunaga Koontz transform

    Science.gov (United States)

    Liu, Rui-ming; Liu, Er-qi; Yang, Jie; Zhang, Tian-hao; Wang, Fang-lin

    2007-09-01

    The Fukunaga-Koontz transform (FKT) has been proposed for many years. It can be used to solve two-pattern classification problems successfully. However, there are few researchers who have definitely extended FKT to kernel FKT (KFKT). In this paper, we first complete this task. Then a method based on KFKT is developed to detect infrared small targets. KFKT is a supervised learning algorithm. How to construct training sets is very important. For automatically detecting targets, the synthetic target images and real background images are used to train KFKT. Because KFKT can represent the higher order statistical properties of images, we expect better detection performance of KFKT than that of FKT. The well-devised experiments verify that KFKT outperforms FKT in detecting infrared small targets.

  9. 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.

  10. Texture orientation-based algorithm for detecting infrared maritime targets.

    Science.gov (United States)

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

    2015-05-20

    Infrared maritime target detection is a key technology for maritime target searching systems. However, in infrared maritime images (IMIs) taken under complicated sea conditions, background clutters, such as ocean waves, clouds or sea fog, usually have high intensity that can easily overwhelm the brightness of real targets, which is difficult for traditional target detection algorithms to deal with. To mitigate this problem, this paper proposes a novel target detection algorithm based on texture orientation. This algorithm first extracts suspected targets by analyzing the intersubband correlation between horizontal and vertical wavelet subbands of the original IMI on the first scale. Then the self-adaptive wavelet threshold denoising and local singularity analysis of the original IMI is combined to remove false alarms further. Experiments show that compared with traditional algorithms, this algorithm can suppress background clutter much better and realize better single-frame detection for infrared maritime targets. Besides, in order to guarantee accurate target extraction further, the pipeline-filtering algorithm is adopted to eliminate residual false alarms. The high practical value and applicability of this proposed strategy is backed strongly by experimental data acquired under different environmental conditions.

  11. Detection of range migrating targets in compound-Gaussian clutter

    NARCIS (Netherlands)

    Petrov, N.; le Chevalier, F.; Yarovyi, O.

    2018-01-01

    This paper deals with the problem of coherent radar detection of fast moving targets in a high range resolution mode. In particular, we are focusing on the spiky clutter modeled as a compound Gaussian process with rapidly varying power along range. Additionally, a fast moving target of interest has

  12. Ordinal Regression Based Subpixel Shift Estimation for Video Super-Resolution

    Directory of Open Access Journals (Sweden)

    Petrovic Nemanja

    2007-01-01

    Full Text Available We present a supervised learning-based approach for subpixel motion estimation which is then used to perform video super-resolution. The novelty of this work is the formulation of the problem of subpixel motion estimation in a ranking framework. The ranking formulation is a variant of classification and regression formulation, in which the ordering present in class labels namely, the shift between patches is explicitly taken into account. Finally, we demonstrate the applicability of our approach on superresolving synthetically generated images with global subpixel shifts and enhancing real video frames by accounting for both local integer and subpixel shifts.

  13. 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.

  14. 2D Sub-Pixel Disparity Measurement Using QPEC / Medicis

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Hochberg, Yonit; Kahn, Yonatan; Lisanti, Mariangela; Tully, Christopher G.; Zurek, Kathryn M.

    2017-09-01

    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.

  16. Neuromorphic Modeling of Moving Target Detection in Insects

    Science.gov (United States)

    2007-12-31

    Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39, 18 Grants FA9550-04-1-0283 and FA9550-04-1-0294 Neuromorphic Modeling of Moving Target Detection...natural for neuromorphic sensory processing. We developed visual motion detection circuitry, including photodetectors, early vision, and models for both...Lincoln Labs 3DM2 run, Tanner Research reserved and utilized space corresponding to two MOSIS ’tiny chips ’ (2mm square each), each with three interconnected

  17. Subpixel level mapping of remotely sensed image using colorimetry

    Directory of Open Access Journals (Sweden)

    M. Suresh

    2018-04-01

    Full Text Available The problem of extracting proportion of classes present within a pixel has been a challenge for researchers for which already numerous methodologies have been developed but still saturation is far ahead, since still the methods accounting these mixed classes are not perfect and they would never be perfect until one can talk about one to one correspondence for each pixel and ground data, which is practically impossible. In this paper a step towards generation of new method for finding out mixed class proportions in a pixel on the basis of the mixing property of colors as per colorimetry. The methodology involves locating the class color of a mixed pixel on chromaticity diagram and then using contextual information mainly the location of neighboring pixels on chromaticity diagram to estimate the proportion of classes in the mixed pixel.Also the resampling method would be more accurate when accounting for sharp and exact boundaries. With the usage of contextual information can generate the resampled image containing only the colors which really exist. The process is simply accounting the fraction and then the number of pixels by multiplying the fraction by total number of pixels into which one pixel is splitted to get number of pixels of each color based on contextual information. Keywords: Subpixel classification, Remote sensing imagery, Colorimetric color space, Sampling and subpixel mapping

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

    Directory of Open Access Journals (Sweden)

    Drzewiecki Wojciech

    2017-12-01

    Full Text Available 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.

  19. 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.

  20. Detection of target phonemes in spontaneous and read speech.

    Science.gov (United States)

    Mehta, G; Cutler, A

    1988-01-01

    Although spontaneous speech occurs more frequently in most listeners' experience than read speech, laboratory studies of human speech recognition typically use carefully controlled materials read from a script. The phonological and prosodic characteristics of spontaneous and read speech differ considerably, however, which suggests that laboratory results may not generalise to the recognition of spontaneous speech. In the present study listeners were presented with both spontaneous and read speech materials, and their response time to detect word-initial target phonemes was measured. Responses were, overall, equally fast in each speech mode. However, analysis of effects previously reported in phoneme detection studies revealed significant differences between speech modes. In read speech but not in spontaneous speech, later targets were detected more rapidly than targets preceded by short words. In contrast, in spontaneous speech but not in read speech, targets were detected more rapidly in accented than in unaccented words and in strong than in weak syllables. An explanation for this pattern is offered in terms of characteristic prosodic differences between spontaneous and read speech. The results support claims from previous work that listeners pay great attention to prosodic information in the process of recognising speech.

  1. Performance evaluation of sea surface simulation methods for target detection

    Science.gov (United States)

    Xia, Renjie; Wu, Xin; Yang, Chen; Han, Yiping; Zhang, Jianqi

    2017-11-01

    With the fast development of sea surface target detection by optoelectronic sensors, machine learning has been adopted to improve the detection performance. Many features can be learned from training images by machines automatically. However, field images of sea surface target are not sufficient as training data. 3D scene simulation is a promising method to address this problem. For ocean scene simulation, sea surface height field generation is the key point to achieve high fidelity. In this paper, two spectra-based height field generation methods are evaluated. Comparison between the linear superposition and linear filter method is made quantitatively with a statistical model. 3D ocean scene simulating results show the different features between the methods, which can give reference for synthesizing sea surface target images with different ocean conditions.

  2. Detectability counts when assessing populations for biodiversity targets.

    Directory of Open Access Journals (Sweden)

    Silviu O Petrovan

    Full Text Available Efficient, practical and accurate estimates of population parameters are a necessary basis for effective conservation action to meet biodiversity targets. The brown hare is representative of many European farmland species: historically widespread and abundant but having undergone rapid declines as a result of agricultural intensification. As a priority species in the UK Biodiversity Action Plan, it has national targets for population increase that are part of wider national environmental indicators. Previous research has indicated that brown hare declines have been greatest in pastural landscapes and that gains might be made by focussing conservation effort there. We therefore used hares in pastural landscapes to examine how basic changes in survey methodology can affect the precision of population density estimates and related these to national targets for biodiversity conservation in the UK. Line transects for hares carried out at night resulted in higher numbers of detections, had better-fitting detection functions and provided more robust density estimates with lower effort than those during the day, due primarily to the increased probability of detection of hares at night and the nature of hare responses to the observer. Hare spring densities varied widely within a single region, with a pooled mean of 20.6 hares km(-2, significantly higher than the reported national average of hares in pastures of 3.3 hares km(-2. The high number of encounters allowed us to resolve hare densities at site, season and year scales. We demonstrate how survey conduct can impact on data quantity and quality with implications for setting and monitoring biodiversity targets. Our case study of the brown hare provides evidence that for wildlife species with low detectability, large scale volunteer-based monitoring programmes, either species specific or generalist, might be more successfully and efficiently carried out by a small number of trained personnel able to

  3. Hierarchical effects on target detection and conflict monitoring

    Science.gov (United States)

    Cao, Bihua; Gao, Feng; Ren, Maofang; Li, Fuhong

    2016-01-01

    Previous neuroimaging studies have demonstrated a hierarchical functional structure of the frontal cortices of the human brain, but the temporal course and the electrophysiological signature of the hierarchical representation remains unaddressed. In the present study, twenty-one volunteers were asked to perform a nested cue-target task, while their scalp potentials were recorded. The results showed that: (1) in comparison with the lower-level hierarchical targets, the higher-level targets elicited a larger N2 component (220–350 ms) at the frontal sites, and a smaller P3 component (350–500 ms) across the frontal and parietal sites; (2) conflict-related negativity (non-target minus target) was greater for the lower-level hierarchy than the higher-level, reflecting a more intensive process of conflict monitoring at the final step of target detection. These results imply that decision making, context updating, and conflict monitoring differ among different hierarchical levels of abstraction. PMID:27561989

  4. A comparison of directed search target detection versus in-scene target detection in Worldview-2 datasets

    Science.gov (United States)

    Grossman, S.

    2015-05-01

    Since the events of September 11, 2001, the intelligence focus has moved from large order-of-battle targets to small targets of opportunity. Additionally, the business community has discovered the use of remotely sensed data to anticipate demand and derive data on their competition. This requires the finer spectral and spatial fidelity now available to recognize those targets. This work hypothesizes that directed searches using calibrated data perform at least as well as inscene manually intensive target detection searches. It uses calibrated Worldview-2 multispectral images with NEF generated signatures and standard detection algorithms to compare bespoke directed search capabilities against ENVI™ in-scene search capabilities. Multiple execution runs are performed at increasing thresholds to generate detection rates. These rates are plotted and statistically analyzed. While individual head-to-head comparison results vary, 88% of the directed searches performed at least as well as in-scene searches with 50% clearly outperforming in-scene methods. The results strongly support the premise that directed searches perform at least as well as comparable in-scene searches.

  5. Detection of target phonemes in spontaneous and read speech

    OpenAIRE

    Mehta, G.; Cutler, A.

    1988-01-01

    Although spontaneous speech occurs more frequently in most listeners’ experience than read speech, laboratory studies of human speech recognition typically use carefully controlled materials read from a script. The phonological and prosodic characteristics of spontaneous and read speech differ considerably, however, which suggests that laboratory results may not generalize to the recognition of spontaneous and read speech materials, and their response time to detect word-initial target phonem...

  6. Estimation of urban surface water at subpixel level from neighborhood pixels using multispectral remote sensing image (Conference Presentation)

    Science.gov (United States)

    Xie, Huan; Luo, Xin; Xu, Xiong; Wang, Chen; Pan, Haiyan; Tong, Xiaohua; Liu, Shijie

    2016-10-01

    Water body is a fundamental element in urban ecosystems and water mapping is critical for urban and landscape planning and management. As remote sensing has increasingly been used for water mapping in rural areas, this spatially explicit approach applied in urban area is also a challenging work due to the water bodies mainly distributed in a small size and the spectral confusion widely exists between water and complex features in the urban environment. Water index is the most common method for water extraction at pixel level, and spectral mixture analysis (SMA) has been widely employed in analyzing urban environment at subpixel level recently. In this paper, we introduce an automatic subpixel water mapping method in urban areas using multispectral remote sensing data. The objectives of this research consist of: (1) developing an automatic land-water mixed pixels extraction technique by water index; (2) deriving the most representative endmembers of water and land by utilizing neighboring water pixels and adaptive iterative optimal neighboring land pixel for respectively; (3) applying a linear unmixing model for subpixel water fraction estimation. Specifically, to automatically extract land-water pixels, the locally weighted scatter plot smoothing is firstly used to the original histogram curve of WI image . And then the Ostu threshold is derived as the start point to select land-water pixels based on histogram of the WI image with the land threshold and water threshold determination through the slopes of histogram curve . Based on the previous process at pixel level, the image is divided into three parts: water pixels, land pixels, and mixed land-water pixels. Then the spectral mixture analysis (SMA) is applied to land-water mixed pixels for water fraction estimation at subpixel level. With the assumption that the endmember signature of a target pixel should be more similar to adjacent pixels due to spatial dependence, the endmember of water and land are determined

  7. Combining orthogonal polarization for elongated target detection with GPR

    International Nuclear Information System (INIS)

    Lualdi, Maurizio; Lombardi, Federico

    2014-01-01

    For an accurate imaging of ground penetrating radar data the polarization characteristics of the propagating electromagnetic (EM) wavefield and wave amplitude variations with antenna pattern orientation must be taken into account. For objects that show some directionality feature and cylindrical shape any misalignment between transmitter and target can strongly modify the polarization state of the backscattered wavefield, thus conditioning the detection capability of the system. Hints on the depolarization can be used to design the optimal GPR antenna survey to avoid omissions and pitfalls during data processing. This research addresses the issue of elongated target detection through a multi azimuth (or multi polarization) approach based on the combination of mutually orthogonal GPR data. Results from the analysis of the formal scattering problem demonstrate how this strategy can reach a scalar formulation of the scattering matrix and achieve a rotational invariant quantity. The effectiveness of the algorithm is then evaluated with a detailed field example showing results closely proximal to those obtained under the optimal alignment condition: detection is significantly improved and the risk of target missing is reduced. (paper)

  8. Camouflaged target detection based on polarized spectral features

    Science.gov (United States)

    Tan, Jian; Zhang, Junping; Zou, Bin

    2016-05-01

    The polarized hyperspectral images (PHSI) include polarization, spectral, spatial and radiant features, which provide more information about objects and scenes than traditional intensity or spectrum ones. And polarization can suppress the background and highlight the object, leading to the high potential to improve camouflaged target detection. So polarized hyperspectral imaging technique has aroused extensive concern in the last few years. Nowadays, the detection methods are still not very mature, most of which are rooted in the detection of hyperspectral image. And before using these algorithms, Stokes vector is used to process the original four-dimensional polarized hyperspectral data firstly. However, when the data is large and complex, the amount of calculation and error will increase. In this paper, tensor is applied to reconstruct the original four-dimensional data into new three-dimensional data, then, the constraint energy minimization (CEM) is used to process the new data, which adds the polarization information to construct the polarized spectral filter operator and takes full advantages of spectral and polarized information. This way deals with the original data without extracting the Stokes vector, so as to reduce the computation and error greatly. The experimental results also show that the proposed method in this paper is more suitable for the target detection of the PHSI.

  9. 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

  10. A Targeted Swallow Screen for the Detection of Postoperative Dysphagia.

    Science.gov (United States)

    Gee, Erica; Lancaster, Elizabeth; Meltzer, Jospeh; Mendelsohn, Abie H; Benharash, Peyman

    2015-10-01

    Postoperative dysphagia leads to aspiration pneumonia, prolonged hospital stay, and is associated with increased mortality. A simple and sensitive screening test to identify patients requiring objective dysphagia evaluation is presently lacking. In this study, we evaluated the efficacy of a novel targeted swallow screen evaluation. This was a prospective trial involving all adult patients who underwent elective cardiac surgery with cardiopulmonary bypass at our institution over an 8-week period. Within 24 hours of extubation and before the initiation of oral intake, all postsurgical patients were evaluated using the targeted swallow screen. A fiberoptic endoscopic evaluation of swallowing was requested for failed screenings. During the study, 50 postcardiac surgery patients were screened. Fifteen (30%) failed the targeted swallow screen, and ten of the fifteen (66%) failed the subsequent fiberoptic endoscopic evaluation of swallowing exam and were confirmed to have dysphagia. The screening test had 100 per cent sensitivity for detecting dysphagia in our patient population, and a specificity of 87.5 per cent. The overall incidence of dysphagia was 20 per cent. We have shown that a targeted swallow evaluation can efficiently screen patients during the postcardiac surgery period. Furthermore, we have shown that the true incidence of dysphagia after cardiac surgery is significantly higher than previously recognized in literature.

  11. Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter

    Science.gov (United States)

    Bal, A.; Alam, M. S.; Aslan, M. S.

    2006-05-01

    Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.

  12. 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...... 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...

  13. Estimation bias from using nonlinear Fourier plane correlators for sub-pixel image shift measurement and implications for the binary joint transform correlator

    Science.gov (United States)

    Grycewicz, Thomas J.; Florio, Christopher J.; Franz, Geoffrey A.; Robinson, Ross E.

    2007-09-01

    When using Fourier plane digital algorithms or an optical correlator to measure the correlation between digital images, interpolation by center-of-mass or quadratic estimation techniques can be used to estimate image displacement to the sub-pixel level. However, this can lead to a bias in the correlation measurement. This bias shifts the sub-pixel output measurement to be closer to the nearest pixel center than the actual location. The paper investigates the bias in the outputs of both digital and optical correlators, and proposes methods to minimize this effect. We use digital studies and optical implementations of the joint transform correlator to demonstrate optical registration with accuracies better than 0.1 pixels. We use both simulations of image shift and movies of a moving target as inputs. We demonstrate bias error for both center-of-mass and quadratic interpolation, and discuss the reasons that this bias is present. Finally, we suggest measures to reduce or eliminate the bias effects. We show that when sub-pixel bias is present, it can be eliminated by modifying the interpolation method. By removing the bias error, we improve registration accuracy by thirty percent.

  14. [Study on spectral detection of green plant target].

    Science.gov (United States)

    Deng, Wei; Zhao, Chun-jiang; He, Xiong-kui; Chen, Li-ping; Zhang, Lu-da; Wu, Guang-wei; Mueller, J; Zhai, Chang-yuan

    2010-08-01

    Weeds grow scatteredly in fields, where many insentient objects exist, for example, withered grasses, dry twig and barriers. In order to improve the precision level of spraying, it is important to study green plant detecting technology. The present paper discussed detecting method of green plant by using spectral recognizing technology, because of the real-time feature of spectral recognition. By analyzing the reflectivity difference between each of the two sides of the "red edge" of the spectrum from plants and surrounding environment, green plant discriminat index (GPDI) is defined as the value which equals the reflectivity ratio at the wavelength of 850 nm divided by the reflectivity ratio at the wavelength of 650 nm. The original spectral data of green plants and the background were measured by using the handhold FieldSpec 3 Spectroradiometer manufactured by ASD Inc. in USA. The spectral data were processed to get the reflectivity of each measured objects and to work out the GPDI thereof as well. The classification model of green plant and its background was built up using decision tree method in order to obtain the threshold of GPDI to distinguish green plants and the background. The threshold of GPDI was chosen as 5.54. The detected object was recognized as green plant when it is GPDI>GPDITH, and vice versa. Through another test, the accuracy rate was verified which was 100% by using the threshold. The authors designed and developed the green plant detector based on single chip microcomputer (SCM) "AT89S51" and photodiode "OPT101" to realize detecting green plants from the background. After passing through two optical filters, the center wavelengths of which are 650 and 850 nm respectively, the reflected light from measured targets was detected by two photodiodes and converted into electrical signals. These analog signals were then converted to digital signals via an analog-to-digital converter (ADS7813) after being amplified by a signal amplifier (OP400

  15. A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

    Science.gov (United States)

    Shuxin, Li; Zhilong, Zhang; Biao, Li

    2018-01-01

    Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

  16. 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).

  17. Subpixelic measurement of large 1D displacements: principle, processing algorithms, performances and software.

    Science.gov (United States)

    Guelpa, Valérian; Laurent, Guillaume J; Sandoz, Patrick; Zea, July Galeano; Clévy, Cédric

    2014-03-12

    This paper presents a visual measurement method able to sense 1D rigid body displacements with very high resolutions, large ranges and high processing rates. Sub-pixelic resolution is obtained thanks to a structured pattern placed on the target. The pattern is made of twin periodic grids with slightly different periods. The periodic frames are suited for Fourier-like phase calculations-leading to high resolution-while the period difference allows the removal of phase ambiguity and thus a high range-to-resolution ratio. The paper presents the measurement principle as well as the processing algorithms (source files are provided as supplementary materials). The theoretical and experimental performances are also discussed. The processing time is around 3 µs for a line of 780 pixels, which means that the measurement rate is mostly limited by the image acquisition frame rate. A 3-σ repeatability of 5 nm is experimentally demonstrated which has to be compared with the 168 µm measurement range.

  18. Subpixel edge localization with reduced uncertainty by violating the Nyquist criterion

    Science.gov (United States)

    Heidingsfelder, Philipp; Gao, Jun; Wang, Kun; Ott, Peter

    2014-12-01

    In this contribution, the extent to which the Nyquist criterion can be violated in optical imaging systems with a digital sensor, e.g., a digital microscope, is investigated. In detail, we analyze the subpixel uncertainty of the detected position of a step edge, the edge of a stripe with a varying width, and that of a periodic rectangular pattern for varying pixel pitches of the sensor, thus also in aliased conditions. The analysis includes the investigation of different algorithms of edge localization based on direct fitting or based on the derivative of the edge profile, such as the common centroid method. In addition to the systematic error of these algorithms, the influence of the photon noise (PN) is included in the investigation. A simplified closed form solution for the uncertainty of the edge position caused by the PN is derived. The presented results show that, in the vast majority of cases, the pixel pitch can exceed the Nyquist sampling distance by about 50% without an increase of the uncertainty of edge localization. This allows one to increase the field-of-view without increasing the resolution of the sensor and to decrease the size of the setup by reducing the magnification. Experimental results confirm the simulation results.

  19. Error diffusion applied to the manipulation of liquid-crystal display subpixels

    Science.gov (United States)

    Dallas, William J.; Fan, Jiahua; Roehrig, Hans; Krupinski, Elizabeth A.

    2004-05-01

    Flat-panel displays based on liquid crystal technology are becoming widely used in the medical imaging arena. Despite the impressive capabilities of presently-existing panels, some medical images push their boundaries. We are working with mammograms that contain up to 4800 x 6400 14-bit pixels. Stated differently, these images contain 30 mega-pixels each. In the standard environment, for film viewing, the mammograms are hung four-up, i.e. four images are located side by side. Because many of the LCD panels used for monochrome display of medical images are based on color models, the pixels of the panels are divided into sub-pixels. These sub-pixels vary in their numbers and in the degrees of independence. Manufacturers have used both spatial and temporal modulation of these sub-pixels to improve the quality of images presented by the monitors. In this presentation we show how the sub-pixel structure of some present and future displays can be used to attain higher spatial resolution than the full-pixel resolution specification would suggest while also providing increased contrast resolution. The error diffusion methods we discuss provide a natural way of controlling sub-pixels and implementing trade-offs. In smooth regions of the image contrast resolution can maximized. In rapidly-varying regions of the image spatial resolution can be favored.

  20. Magneto-mechanical trapping systems for biological target detection

    International Nuclear Information System (INIS)

    Li, Fuquan; Kodzius, Rimantas; Gooneratne, Chinthaka P.; Foulds, Ian G.; Kosel, Jürgen

    2014-01-01

    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. (author)

  1. 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.

  2. Visual performance on detection tasks with double-targets of the same and different difficulty.

    Science.gov (United States)

    Chan, Alan H S; Courtney, Alan J; Ma, C W

    2002-10-20

    This paper reports a study of measurement of horizontal visual sensitivity limits for 16 subjects in single-target and double-targets detection tasks. Two phases of tests were conducted in the double-targets task; targets of the same difficulty were tested in phase one while targets of different difficulty were tested in phase two. The range of sensitivity for the double-targets test was found to be smaller than that for single-target in both the same and different target difficulty cases. The presence of another target was found to affect performance to a marked degree. Interference effect of the difficult target on detection of the easy one was greater than that of the easy one on the detection of the difficult one. Performance decrement was noted when correct percentage detection was plotted against eccentricity of target in both the single-target and double-targets tests. Nevertheless, the non-significant correlation found between the performance for the two tasks demonstrated that it was impossible to predict quantitatively ability for detection of double targets from the data for single targets. This indicated probable problems in generalizing data for single target visual lobes to those for multiple targets. Also lobe area values obtained from measurements using a single-target task cannot be applied in a mathematical model for situations with multiple occurrences of targets.

  3. Sub-pixel analysis to support graphic security after scanning at low resolution

    Science.gov (United States)

    Haas, Bertrand; Cordery, Robert; Gou, Hongmei; Decker, Steve

    2006-02-01

    Whether in the domain of audio, video or finance, our world tends to become increasingly digital. However, for diverse reasons, the transition from analog to digital is often much extended in time, and proceeds by long steps (and sometimes never completes). One such step is the conversion of information on analog media to digital information. We focus in this paper on the conversion (scanning) of printed documents to digital images. Analog media have the advantage over digital channels that they can harbor much imperceptible information that can be used for fraud detection and forensic purposes. But this secondary information usually fails to be retrieved during the conversion step. This is particularly relevant since the Check-21 act (Check Clearing for the 21st Century act) became effective in 2004 and allows images of checks to be handled by banks as usual paper checks. We use here this situation of check scanning as our primary benchmark for graphic security features after scanning. We will first present a quick review of the most common graphic security features currently found on checks, with their specific purpose, qualities and disadvantages, and we demonstrate their poor survivability after scanning in the average scanning conditions expected from the Check-21 Act. We will then present a novel method of measurement of distances between and rotations of line elements in a scanned image: Based on an appropriate print model, we refine direct measurements to an accuracy beyond the size of a scanning pixel, so we can then determine expected distances, periodicity, sharpness and print quality of known characters, symbols and other graphic elements in a document image. Finally we will apply our method to fraud detection of documents after gray-scale scanning at 300dpi resolution. We show in particular that alterations on legitimate checks or copies of checks can be successfully detected by measuring with sub-pixel accuracy the irregularities inherently introduced

  4. 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.

  5. 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

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

    Science.gov (United States)

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

    2016-01-01

    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 database generated

  7. 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.

  8. Detection algorithm of infrared small target based on improved SUSAN operator

    Science.gov (United States)

    Liu, Xingmiao; Wang, Shicheng; Zhao, Jing

    2010-10-01

    The methods of detecting small moving targets in infrared image sequences that contain moving nuisance objects and background noise is analyzed in this paper. A novel infrared small target detection algorithm based on improved SUSAN operator is put forward. The algorithm selects double templates for the infrared small target detection: one size is greater than the small target point size and another size is equal to the small target point size. First, the algorithm uses the big template to calculate the USAN of each pixel in the image and detect the small target, the edge of the image and isolated noise pixels; Then the algorithm uses the another template to calculate the USAN of pixels detected in the first step and improves the principles of SUSAN algorithm based on the characteristics of the small target so that the algorithm can only detect small targets and don't sensitive to the edge pixels of the image and isolated noise pixels. So the interference of the edge of the image and isolate noise points are removed and the candidate target points can be identified; At last, the target is detected by utilizing the continuity and consistency of target movement. The experimental results indicate that the improved SUSAN detection algorithm can quickly and effectively detect the infrared small targets.

  9. A Study of Adaptive Detection of Range-Distributed Targets

    National Research Council Canada - National Science Library

    Gerlach, Karl R

    2000-01-01

    ... to be characterized as complex zero-mean correlated Gaussian random variables. The target's or targets' complex amplitudes are assumed to be distributed across the entire input data block (sensor x range...

  10. Digital Speckle Photography of Subpixel Displacements of Speckle Structures Based on Analysis of Their Spatial Spectra

    Science.gov (United States)

    Maksimova, L. A.; Ryabukho, P. V.; Mysina, N. Yu.; Lyakin, D. V.; Ryabukho, V. P.

    2018-04-01

    We have investigated the capabilities of the method of digital speckle interferometry for determining subpixel displacements of a speckle structure formed by a displaceable or deformable object with a scattering surface. An analysis of spatial spectra of speckle structures makes it possible to perform measurements with a subpixel accuracy and to extend the lower boundary of the range of measurements of displacements of speckle structures to the range of subpixel values. The method is realized on the basis of digital recording of the images of undisplaced and displaced speckle structures, their spatial frequency analysis using numerically specified constant phase shifts, and correlation analysis of spatial spectra of speckle structures. Transformation into the frequency range makes it possible to obtain quantities to be measured with a subpixel accuracy from the shift of the interference-pattern minimum in the diffraction halo by introducing an additional phase shift into the complex spatial spectrum of the speckle structure or from the slope of the linear plot of the function of accumulated phase difference in the field of the complex spatial spectrum of the displaced speckle structure. The capabilities of the method have been investigated in natural experiment.

  11. Robust Small Target Co-Detection from Airborne Infrared Image Sequences.

    Science.gov (United States)

    Gao, Jingli; Wen, Chenglin; Liu, Meiqin

    2017-09-29

    In this paper, a novel infrared target co-detection model combining the self-correlation features of backgrounds and the commonality features of targets in the spatio-temporal domain is proposed to detect small targets in a sequence of infrared images with complex backgrounds. Firstly, a dense target extraction model based on nonlinear weights is proposed, which can better suppress background of images and enhance small targets than weights of singular values. Secondly, a sparse target extraction model based on entry-wise weighted robust principal component analysis is proposed. The entry-wise weight adaptively incorporates structural prior in terms of local weighted entropy, thus, it can extract real targets accurately and suppress background clutters efficiently. Finally, the commonality of targets in the spatio-temporal domain are used to construct target refinement model for false alarms suppression and target confirmation. Since real targets could appear in both of the dense and sparse reconstruction maps of a single frame, and form trajectories after tracklet association of consecutive frames, the location correlation of the dense and sparse reconstruction maps for a single frame and tracklet association of the location correlation maps for successive frames have strong ability to discriminate between small targets and background clutters. Experimental results demonstrate that the proposed small target co-detection method can not only suppress background clutters effectively, but also detect targets accurately even if with target-like interference.

  12. A new method of small target detection based on neural network

    Science.gov (United States)

    Hu, Jing; Hu, Yongli; Lu, Xinxin

    2018-02-01

    The detection and tracking of moving dim target in infrared image have been an research hotspot for many years. The target in each frame of images only occupies several pixels without any shape and structure information. Moreover, infrared small target is often submerged in complicated background with low signal-to-clutter ratio, making the detection very difficult. Different backgrounds exhibit different statistical properties, making it becomes extremely complex to detect the target. If the threshold segmentation is not reasonable, there may be more noise points in the final detection, which is unfavorable for the detection of the trajectory of the target. Single-frame target detection may not be able to obtain the desired target and cause high false alarm rate. We believe the combination of suspicious target detection spatially in each frame and temporal association for target tracking will increase reliability of tracking dim target. The detection of dim target is mainly divided into two parts, In the first part, we adopt bilateral filtering method in background suppression, after the threshold segmentation, the suspicious target in each frame are extracted, then we use LSTM(long short term memory) neural network to predict coordinates of target of the next frame. It is a brand-new method base on the movement characteristic of the target in sequence images which could respond to the changes in the relationship between past and future values of the values. Simulation results demonstrate proposed algorithm can effectively predict the trajectory of the moving small target and work efficiently and robustly with low false alarm.

  13. An infrared small target detection method based on multiscale local homogeneity measure

    Science.gov (United States)

    Nie, Jinyan; Qu, Shaocheng; Wei, Yantao; Zhang, Liming; Deng, Lizhen

    2018-05-01

    Infrared (IR) small target detection plays an important role in the field of image detection area owing to its intrinsic characteristics. This paper presents a multiscale local homogeneity measure (MLHM) for infrared small target detection, which can enhance the performance of IR small target detection system. Firstly, intra-patch homogeneity of the target itself and the inter-patch heterogeneity between target and the local background regions are integrated to enhance the significant of small target. Secondly, a multiscale measure based on local regions is proposed to obtain the most appropriate response. Finally, an adaptive threshold method is applied to small target segmentation. Experimental results on three different scenarios indicate that the MLHM has good performance under the interference of strong noise.

  14. A Study of Adaptive Detection of Range-Distributed Targets

    National Research Council Canada - National Science Library

    Gerlach, Karl R

    2000-01-01

    .... The unknown parameters associated with the hypothesis test are the complex amplitudes in range of the desired target and the unknown covariance matrix of the additive interference, which is assumed...

  15. Electromagnetic Induction Spectroscopy for the Detection of Subsurface Targets

    Science.gov (United States)

    2012-12-01

    is proportional to the product of the transmitted and received magnetic fields and the magnetic polarizability tensor of the target being measured by...the EMI sensor (Appendix A). The magnetic polarizability tensor of several canonical targets can be calculated analytically, and these formulas show...prescreener. A simple voting mechanism is employed to discourage temporary mislabeling of land- mines by taking advantage of the sequential measurements. As

  16. The Automatic Measurement of Targets

    DEFF Research Database (Denmark)

    Höhle, Joachim

    1997-01-01

    The automatic measurement of targets is demonstrated by means of a theoretical example and by an interactive measuring program for real imagery from a réseau camera. The used strategy is a combination of two methods: the maximum correlation coefficient and the correlation in the subpixel range...... interactive software is also part of a computer-assisted learning program on digital photogrammetry....

  17. Knowledge-Base Application to Ground Moving Target Detection

    National Research Council Canada - National Science Library

    Adve, R

    2001-01-01

    This report summarizes a multi-year in-house effort to apply knowledge-base control techniques and advanced Space-Time Adaptive Processing algorithms to improve detection performance and false alarm...

  18. Penalty dynamic programming algorithm for dim targets detection in sensor systems.

    Science.gov (United States)

    Huang, Dayu; Xue, Anke; Guo, Yunfei

    2012-01-01

    In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.

  19. Supervised target detection in hyperspectral images using one-class Fukunaga-Koontz Transform

    Science.gov (United States)

    Binol, Hamidullah; Bal, Abdullah

    2016-05-01

    A novel hyperspectral target detection technique based on Fukunaga-Koontz transform (FKT) is presented. FKT offers significant properties for feature selection and ordering. However, it can only be used to solve multi-pattern classification problems. Target detection may be considered as a two-class classification problem, i.e., target versus background clutter. Nevertheless, background clutter typically contains different types of materials. That's why; target detection techniques are different than classification methods by way of modeling clutter. To avoid the modeling of the background clutter, we have improved one-class FKT (OC-FKT) for target detection. The statistical properties of target training samples are used to define tunnel-like boundary of the target class. Non-target samples are then created synthetically as to be outside of the boundary. Thus, only limited target samples become adequate for training of FKT. The hyperspectral image experiments confirm that the proposed OC-FKT technique provides an effective means for target detection.

  20. Detection and characterization of ship targets using CryoSat-2 altimeter waveforms

    OpenAIRE

    G?mez-Enri, Jesus; Scozzari, Andrea; Soldovieri, Francesco; Coca, Josep; Vignudelli, Stefano

    2016-01-01

    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 conven...

  1. Delayed Detection of Tonal Targets in Background Noise in Dyslexia

    Science.gov (United States)

    Chait, Maria; Eden, Guinevere; Poeppel, David; Simon, Jonathan Z.; Hill, Deborah F.; Flowers, D. Lynn

    2007-01-01

    Individuals with developmental dyslexia are often impaired in their ability to process certain linguistic and even basic non-linguistic auditory signals. Recent investigations report conflicting findings regarding impaired low-level binaural detection mechanisms associated with dyslexia. Binaural impairment has been hypothesized to stem from a…

  2. 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

  3. An assessment of independent component analysis for detection of military targets from hyperspectral images

    Science.gov (United States)

    Tiwari, K. C.; Arora, M. K.; Singh, D.

    2011-10-01

    Hyperspectral data acquired over hundreds of narrow contiguous wavelength bands are extremely suitable for target detection due to their high spectral resolution. Though spectral response of every material is expected to be unique, but in practice, it exhibits variations, which is known as spectral variability. Most target detection algorithms depend on spectral modelling using a priori available target spectra In practice, target spectra is, however, seldom available a priori. Independent component analysis (ICA) is a new evolving technique that aims at finding out components which are statistically independent or as independent as possible. The technique therefore has the potential of being used for target detection applications. A assessment of target detection from hyperspectral images using ICA and other algorithms based on spectral modelling may be of immense interest, since ICA does not require a priori target information. The aim of this paper is, thus, to assess the potential of ICA based algorithm vis a vis other prevailing algorithms for military target detection. Four spectral matching algorithms namely Orthogonal Subspace Projection (OSP), Constrained Energy Minimisation (CEM), Spectral Angle Mapper (SAM) and Spectral Correlation Mapper (SCM), and four anomaly detection algorithms namely OSP anomaly detector (OSPAD), Reed-Xiaoli anomaly detector (RXD), Uniform Target Detector (UTD) and a combination of Reed-Xiaoli anomaly detector and Uniform Target Detector (RXD-UTD) were considered. The experiments were conducted using a set of synthetic and AVIRIS hyperspectral images containing aircrafts as military targets. A comparison of true positive and false positive rates of target detections obtained from ICA and other algorithms plotted on a receiver operating curves (ROC) space indicates the superior performance of the ICA over other algorithms.

  4. A stepwise regression tree for nonlinear approximation: applications to estimating subpixel land cover

    Science.gov (United States)

    Huang, C.; Townshend, J.R.G.

    2003-01-01

    A stepwise regression tree (SRT) algorithm was developed for approximating complex nonlinear relationships. Based on the regression tree of Breiman et al . (BRT) and a stepwise linear regression (SLR) method, this algorithm represents an improvement over SLR in that it can approximate nonlinear relationships and over BRT in that it gives more realistic predictions. The applicability of this method to estimating subpixel forest was demonstrated using three test data sets, on all of which it gave more accurate predictions than SLR and BRT. SRT also generated more compact trees and performed better than or at least as well as BRT at all 10 equal forest proportion interval ranging from 0 to 100%. This method is appealing to estimating subpixel land cover over large areas.

  5. Sensitivity of the normalized difference vegetation index to subpixel canopy cover, soil albedo, and pixel scale

    Science.gov (United States)

    Jasinski, Michael F.

    1990-01-01

    An analytical framework is provided for examining the physically based behavior of the normalized difference vegetation index (NDVI) in terms of the variability in bulk subpixel landscape components and with respect to variations in pixel scales, within the context of the stochastic-geometric canopy reflectance model. Analysis focuses on regional scale variability in horizontal plant density and soil background reflectance distribution. Modeling is generalized to different plant geometries and solar angles through the use of the nondimensional solar-geometric similarity parameter. Results demonstrate that, for Poisson-distributed plants and for one deterministic distribution, NDVI increases with increasing subpixel fractional canopy amount, decreasing soil background reflectance, and increasing shadows, at least within the limitations of the geometric reflectance model. The NDVI of a pecan orchard and a juniper landscape is presented and discussed.

  6. 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

  7. Feasibility Study on Passive-radar Detection of Space Targets Using Spaceborne Illuminators of Opportunity

    Directory of Open Access Journals (Sweden)

    Jiang Tie-zhen

    2015-01-01

    Full Text Available Space target surveillance generally uses active radars. To take full advantage of passive radars, the idea of using spaceborne illuminators of opportunity for space target detection is presented in this paper. Analysis of the detectable time and direct wave suppression shows that passive radar using spaceborne illuminators of opportunity can effectively detect a Low-Earth-Orbit (LEO target. Meanwhile, Ku and L band bi-static radar cross section of passive radars that use spaceborne illuminators of opportunity are presented by simulation, providing the basis of choosing space target forward scatter. Finally the key parameters, mainly system gain, accumulation time and radiation source selection are studied. Results show that system size using satellite TV signals as illuminators of opportunity is relatively small. These encouraging results should stimulate the development of passive radar detection of space targets using spaceborne illuminators of opportunity.

  8. Design of interpolation functions for subpixel-accuracy stereo-vision systems.

    Science.gov (United States)

    Haller, Istvan; Nedevschi, Sergiu

    2012-02-01

    Traditionally, subpixel interpolation in stereo-vision systems was designed for the block-matching algorithm. During the evaluation of different interpolation strategies, a strong correlation was observed between the type of the stereo algorithm and the subpixel accuracy of the different solutions. Subpixel interpolation should be adapted to each stereo algorithm to achieve maximum accuracy. In consequence, it is more important to propose methodologies for interpolation function generation than specific function shapes. We propose two such methodologies based on data generated by the stereo algorithms. The first proposal uses a histogram to model the environment and applies histogram equalization to an existing solution adapting it to the data. The second proposal employs synthetic images of a known environment and applies function fitting to the resulted data. The resulting function matches the algorithm and the data as best as possible. An extensive evaluation set is used to validate the findings. Both real and synthetic test cases were employed in different scenarios. The test results are consistent and show significant improvements compared with traditional solutions. © 2011 IEEE

  9. Improving sub-pixel imperviousness change prediction by ensembling heterogeneous non-linear regression models

    Science.gov (United States)

    Drzewiecki, Wojciech

    2016-12-01

    In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels) was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques. The results proved that in case of sub-pixel evaluation the most accurate prediction of change may not necessarily be based on the most accurate individual assessments. When single methods are considered, based on obtained results Cubist algorithm may be advised for Landsat based mapping of imperviousness for single dates. However, Random Forest may be endorsed when the most reliable evaluation of imperviousness change is the primary goal. It gave lower accuracies for individual assessments, but better prediction of change due to more correlated errors of individual predictions. Heterogeneous model ensembles performed for individual time points assessments at least as well as the best individual models. In case of imperviousness change assessment the ensembles always outperformed single model approaches. It means that it is possible to improve the accuracy of sub-pixel imperviousness change assessment using ensembles of heterogeneous non-linear regression models.

  10. Contrast, size, and orientation-invariant target detection in infrared imagery

    Science.gov (United States)

    Zhou, Yi-Tong; Crawshaw, Richard D.

    1991-08-01

    Automatic target detection in IR imagery is a very difficult task due to variations in target brightness, shape, size, and orientation. In this paper, the authors present a contrast, size, and orientation invariant algorithm based on Gabor functions for detecting targets from a single IR image frame. The algorithms consists of three steps. First, it locates potential targets by using low-resolution Gabor functions which resist noise and background clutter effects, then, it removes false targets and eliminates redundant target points based on a similarity measure. These two steps mimic human vision processing but are different from Zeevi's Foveating Vision System. Finally, it uses both low- and high-resolution Gabor functions to verify target existence. This algorithm has been successfully tested on several IR images that contain multiple examples of military vehicles with different size and brightness in various background scenes and orientations.

  11. A Review of Ground Target Detection and Classification Techniques in Forward Scattering Radars

    Directory of Open Access Journals (Sweden)

    M. E. A. Kanona

    2018-06-01

    Full Text Available This paper presents a review of target detection and classification in forward scattering radar (FSR which is a special state of bistatic radars, designed to detect and track moving targets in the narrow region along the transmitter-receiver base line. FSR has advantages and incredible features over other types of radar configurations. All previous studies proved that FSR can be used as an alternative system for ground target detection and classification. The radar and FSR fundamentals were addressed and classification algorithms and techniques were debated. On the other hand, the current and future applications and the limitations of FSR were discussed.

  12. Low velocity target detection based on time-frequency image for high frequency ground wave radar

    Institute of Scientific and Technical Information of China (English)

    YAN Songhua; WU Shicai; WEN Biyang

    2007-01-01

    The Doppler spectral broadening resulted from non-stationary movement of target and radio-frequency interference will decrease the veracity of target detection by high frequency ground wave(HEGW)radar.By displaying the change of signal energy on two dimensional time-frequency images based on time-frequency analysis,a new mathematical morphology method to distinguish target from nonlinear time-frequency curves is presented.The analyzed results from the measured data verify that with this new method the target can be detected correctly from wide Doppler spectrum.

  13. MLC quality assurance using EPID: A fitting technique with subpixel precision

    International Nuclear Information System (INIS)

    Mamalui-Hunter, Maria; Li, Harold; Low, Daniel A.

    2008-01-01

    Amorphous silicon based electronic portal imaging devices (EPIDs) have been shown to be a good alternative to radiographic film for routine quality assurance (QA) of multileaf collimator (MLC) positioning accuracy. In this work, we present a method of acquiring an EPID image of a traditional strip-test image using analytical fits of the interleaf and leaf abutment image signatures. After exposure, the EPID image pixel values are divided by an open field image to remove EPID response and radiation field variations. Profiles acquired in the direction orthogonal to the leaf motion exhibit small peaks caused by interleaf leakage. Gaussian profiles are fitted to the interleaf leakage peaks, the results of which are, using multiobjective optimization, used to calculate the image rotational angle with respect to the collimator axis of rotation. The relative angle is used to rotate the image to align the MLC leaf travel to the image pixel axes. The leaf abutments also present peaks that are fitted by heuristic functions, in this case modified Lorentzian functions. The parameters of the Lorentzian functions are used to parameterize the leaf gap width and positions. By imaging a set of MLC fields with varying gaps forming symmetric and asymmetric abutments, calibration curves with regard to relative peak height (RPH) versus nominal gap width are obtained. Based on this calibration data, the individual leaf positions are calculated to compare with the nominal programmed positions. The results demonstrate that the collimator rotation angle can be determined as accurate as 0.01 deg. . A change in MLC gap width of 0.2 mm leads to a change in RPH of about 10%. For asymmetrically produced gaps, a 0.2 mm MLC leaf gap width change causes 0.2 pixel peak position change. Subpixel resolution is obtained by using a parameterized fit of the relatively large abutment peaks. By contrast, for symmetrical gap changes, the peak position remains unchanged with a standard deviation of 0

  14. 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.

  15. 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.

  16. Moving Target Detection With Compact Laser Doppler Radar

    Science.gov (United States)

    Sepp, G.; Breining, A.; Eisfeld, W.; Knopp, R.; Lill, E.; Wagner, D.

    1989-12-01

    This paper describes an experimental integrated optronic system for detection and tracking of moving objects. The system is based on a CO2 waveguide laser Doppler ra-dar with homodyne receiver and galvanometer mirror beam scanner. A "hot spot" seeker consisting of a thermal imager with image processor transmits the coordinates of IR-emitting, i.e. potentially powered, objects to the laser radar scanner. The scanner addresses these "hot" locations operating in a large field-of-view (FOV) random ac-cess mode. Hot spots exhibiting a Doppler shifted laser signal are indicated in the thermal image by velocity-to-colour encoded markers. After switching to a small FOV scanning mode, the laser Doppler radar is used to track fast moving objects. Labora-tory and field experiments with moving objects including rotating discs, automobiles and missiles are described.

  17. 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.

  18. 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.

  19. Remote sensing image ship target detection method based on visual attention model

    Science.gov (United States)

    Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

    2017-11-01

    The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

  20. Performance of target detection algorithm in compressive sensing miniature ultraspectral imaging compressed sensing system

    Science.gov (United States)

    Gedalin, Daniel; Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Rotman, Stanley R.; Stern, Adrian

    2017-04-01

    Compressive sensing theory was proposed to deal with the high quantity of measurements demanded by traditional hyperspectral systems. Recently, a compressive spectral imaging technique dubbed compressive sensing miniature ultraspectral imaging (CS-MUSI) was presented. This system uses a voltage controlled liquid crystal device to create multiplexed hyperspectral cubes. We evaluate the utility of the data captured using the CS-MUSI system for the task of target detection. Specifically, we compare the performance of the matched filter target detection algorithm in traditional hyperspectral systems and in CS-MUSI multiplexed hyperspectral cubes. We found that the target detection algorithm performs similarly in both cases, despite the fact that the CS-MUSI data is up to an order of magnitude less than that in conventional hyperspectral cubes. Moreover, the target detection is approximately an order of magnitude faster in CS-MUSI data.

  1. 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...

  2. 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...

  3. Signal Detection, Target Tracking and Differential Geometry Applications to Statistical Inference

    National Research Council Canada - National Science Library

    Rao, C

    1997-01-01

    Signal detection and target tracking. A novel method known as polynomial rooting approach is proposed to obtain estimates of frequencies, amplitudes and noise variance of two-dimensional exponential signals...

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

    KAUST Repository

    Jardak, Seifallah; Kiuru, Tero; Metso, Mikko; Pursula, Pekka; Hakli, Janne; Hirvonen, Mervi; Ahmed, Sajid; Alouini, Mohamed-Slim

    2016-01-01

    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

  5. 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...

  6. Targeted screening strategies to detect Trypanosoma cruzi infection in children.

    Directory of Open Access Journals (Sweden)

    Michael Z Levy

    2007-12-01

    Full Text Available 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.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.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.

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

    OpenAIRE

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

    2016-01-01

    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 th...

  8. 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.

  9. Detection of Target ssDNA Using a Microfabricated Hall Magnetometer with Correlated Optical Readout

    Directory of Open Access Journals (Sweden)

    Steven M. Hira

    2012-01-01

    Full Text Available Sensing biological agents at the genomic level, while enhancing the response time for biodetection over commonly used, optics-based techniques such as nucleic acid microarrays or enzyme-linked immunosorbent assays (ELISAs, is an important criterion for new biosensors. Here, we describe the successful detection of a 35-base, single-strand nucleic acid target by Hall-based magnetic transduction as a mimic for pathogenic DNA target detection. The detection platform has low background, large signal amplification following target binding and can discriminate a single, 350 nm superparamagnetic bead labeled with DNA. Detection of the target sequence was demonstrated at 364 pM (<2 target DNA strands per bead target DNA in the presence of 36 μM nontarget (noncomplementary DNA (<10 ppm target DNA using optical microscopy detection on a GaAs Hall mimic. The use of Hall magnetometers as magnetic transduction biosensors holds promise for multiplexing applications that can greatly improve point-of-care (POC diagnostics and subsequent medical care.

  10. Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction

    Science.gov (United States)

    Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

    2007-11-01

    Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

  11. Improved target detection and bearing estimation utilizing fast orthogonal search for real-time spectral analysis

    International Nuclear Information System (INIS)

    Osman, Abdalla; El-Sheimy, Naser; Nourledin, Aboelamgd; Theriault, Jim; Campbell, Scott

    2009-01-01

    The problem of target detection and tracking in the ocean environment has attracted considerable attention due to its importance in military and civilian applications. Sonobuoys are one of the capable passive sonar systems used in underwater target detection. Target detection and bearing estimation are mainly obtained through spectral analysis of received signals. The frequency resolution introduced by current techniques is limited which affects the accuracy of target detection and bearing estimation at a relatively low signal-to-noise ratio (SNR). This research investigates the development of a bearing estimation method using fast orthogonal search (FOS) for enhanced spectral estimation. FOS is employed in this research in order to improve both target detection and bearing estimation in the case of low SNR inputs. The proposed methods were tested using simulated data developed for two different scenarios under different underwater environmental conditions. The results show that the proposed method is capable of enhancing the accuracy for target detection as well as bearing estimation especially in cases of a very low SNR

  12. Results from the search-lidar demonstrator project for detection of small Sea-Surface targets

    NARCIS (Netherlands)

    Heuvel, J.C. van den; Putten, F.J.M. van; Cohen, L.H.; Kemp, R.A.W.; Franssen, G.C.

    2009-01-01

    Coastal surveillance and naval operations in the littoral both have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and a low velocity that makes them hard to detect by radar. Typical threats include jet skis, FIAC's, and speedboats. Previous lidar

  13. Search-Lidar Demonstrator for Detection of Small Sea-Surface Targets

    NARCIS (Netherlands)

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

    2008-01-01

    Coastal surveillance and naval operations in the littoral both have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and a low velocity that makes them hard to detect by radar. Typical threats include jet skis, FIAC’s, and speedboats. Lidar

  14. 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.

  15. Defending a single object against an attacker trying to detect a subset of false targets

    International Nuclear Information System (INIS)

    Peng, R.; Zhai, Q.Q.; Levitin, G.

    2016-01-01

    Deployment of false targets can be a very important and effective measure for enhancing the survivability of an object subjected to intentional attacks. Existing papers have assumed that false targets are either perfect or can be detected with a constant probability. In practice, the attacker may allocate part of its budget into intelligence actions trying to detect a subset of false targets. Analogously, the defender can allocate part of its budget into disinformation actions to prevent the false targets from being detected. In this paper, the detection probability of each false target is assumed to be a function of the intelligence and disinformation efforts allocated on the false target. The optimal resource distribution between target identification/disinformation and attack/protection efforts is studied as solutions of a non-cooperative two period min–max game between the two competitors for the case of constrained defense and attack resources. - Highlights: • A defense-attack problem is studied as a two-period min–max game. • Both intelligence contest over false targets and impact contest are considered. • Optimal defense and attack strategies are investigated with different parameters.

  16. 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...

  17. Moving target detection based on temporal-spatial information fusion for infrared image sequences

    Science.gov (United States)

    Toing, Wu-qin; Xiong, Jin-yu; Zeng, An-jun; Wu, Xiao-ping; Xu, Hao-peng

    2009-07-01

    Moving target detection and localization is one of the most fundamental tasks in visual surveillance. In this paper, through analyzing the advantages and disadvantages of the traditional approaches about moving target detection, a novel approach based on temporal-spatial information fusion is proposed for moving target detection. The proposed method combines the spatial feature in single frame and the temporal properties within multiple frames of an image sequence of moving target. First, the method uses the spatial image segmentation for target separation from background and uses the local temporal variance for extracting targets and wiping off the trail artifact. Second, the logical "and" operator is used to fuse the temporal and spatial information. In the end, to the fusion image sequence, the morphological filtering and blob analysis are used to acquire exact moving target. The algorithm not only requires minimal computation and memory but also quickly adapts to the change of background and environment. Comparing with other methods, such as the KDE, the Mixture of K Gaussians, etc., the simulation results show the proposed method has better validity and higher adaptive for moving target detection, especially in infrared image sequences with complex illumination change, noise change, and so on.

  18. 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.

  19. Measuring coseismic displacements with point-like targets offset tracking

    KAUST Repository

    Hu, Xie; Wang, Teng; Liao, Mingsheng

    2014-01-01

    Offset tracking is an important complement to measure large ground displacements in both azimuth and range dimensions where synthetic aperture radar (SAR) interferometry is unfeasible. Subpixel offsets can be obtained by searching for the cross-correlation peak calculated from the match patches uniformly distributed on two SAR images. However, it has its limitations, including redundant computation and incorrect estimations on decorrelated patches. In this letter, we propose a simple strategy that performs offset tracking on detected point-like targets (PT). We first detect image patches within bright PT by using a sinc-like template from a single SAR image and then perform offset tracking on them to obtain the pixel shifts. Compared with the standard method, the application on the 2010 M 7.2 El Mayor-Cucapah earthquake shows that the proposed PT offset tracking can significantly increase the cross-correlation and thus result in both efficiency and reliability improvements. © 2013 IEEE.

  20. Diagnostic imaging strategy for MDCT- or MRI-detected breast lesions: use of targeted sonography

    International Nuclear Information System (INIS)

    Nakano, Satoko; Ohtsuka, Masahiko; Mibu, Akemi; Karikomi, Masato; Sakata, Hitomi; Yamamoto, Masahiro

    2012-01-01

    Leading-edge technology such as magnetic resonance imaging (MRI) or computed tomography (CT) often reveals mammographically and ultrasonographically occult lesions. MRI is a well-documented, effective tool to evaluate these lesions; however, the detection rate of targeted sonography varies for MRI detected lesions, and its significance is not well established in diagnostic strategy of MRI detected lesions. We assessed the utility of targeted sonography for multidetector-row CT (MDCT)- or MRI-detected lesions in practice. We retrospectively reviewed 695 patients with newly diagnosed breast cancer who were candidates for breast conserving surgery and underwent MDCT or MRI in our hospital between January 2004 and March 2011. Targeted sonography was performed in all MDCT- or MRI-detected lesions followed by imaging-guided biopsy. Patient background, histopathology features and the sizes of the lesions were compared among benign, malignant and follow-up groups. Of the 695 patients, 61 lesions in 56 patients were detected by MDCT or MRI. The MDCT- or MRI-detected lesions were identified by targeted sonography in 58 out of 61 lesions (95.1%). Patients with pathological diagnoses were significantly older and more likely to be postmenopausal than the follow-up patients. Pathological diagnosis proved to be benign in 20 cases and malignant in 25. The remaining 16 lesions have been followed up. Lesion size and shape were not significantly different among the benign, malignant and follow-up groups. Approximately 95% of MDCT- or MRI-detected lesions were identified by targeted sonography, and nearly half of these lesions were pathologically proven malignancies in this study. Targeted sonography is a useful modality for MDCT- or MRI-detected breast lesions

  1. Abnormal Ventral and Dorsal Attention Network Activity During Single and Dual Target Detection in Schizophrenia

    Directory of Open Access Journals (Sweden)

    Amy M. Jimenez

    2016-03-01

    Full Text Available Early visual perception and attention are impaired in schizophrenia, and these deficits can be observed on target detection tasks. These tasks activate distinct ventral and dorsal brain networks which support stimulus-driven and goal-directed attention, respectively. We used single and dual target rapid serial visual presentation (RSVP tasks during fMRI with an ROI approach to examine regions within these networks associated with target detection and the attentional blink (AB in 21 schizophrenia outpatients and 25 healthy controls. In both tasks, letters were targets and numbers were distractors. For the dual target task, the second target (T2 was presented at 3 different lags after the first target (T1 (lag1=100ms, lag3=300ms, lag7=700ms. For both single and dual target tasks, patients identified fewer targets than controls. For the dual target task, both groups showed the expected AB effect with poorer performance at lag 3 than at lags 1 or 7, and there was no group by lag interaction. During the single target task, patients showed abnormally increased deactivation of the temporo-parietal junction (TPJ, a key region of the ventral network. When attention demands were increased during the dual target task, patients showed overactivation of the posterior intraparietal cortex, a key dorsal network region, along with failure to deactivate TPJ. Results suggest inefficient and faulty suppression of salience-oriented processing regions, resulting in increased sensitivity to stimuli in general, and difficulty distinguishing targets from non-targets.

  2. 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.

  3. 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.

  4. Segmentation of arterial vessel wall motion to sub-pixel resolution using M-mode ultrasound.

    Science.gov (United States)

    Fancourt, Craig; Azer, Karim; Ramcharan, Sharmilee L; Bunzel, Michelle; Cambell, Barry R; Sachs, Jeffrey R; Walker, Matthew

    2008-01-01

    We describe a method for segmenting arterial vessel wall motion to sub-pixel resolution, using the returns from M-mode ultrasound. The technique involves measuring the spatial offset between all pairs of scans from their cross-correlation, converting the spatial offsets to relative wall motion through a global optimization, and finally translating from relative to absolute wall motion by interpolation over the M-mode image. The resulting detailed wall distension waveform has the potential to enhance existing vascular biomarkers, such as strain and compliance, as well as enable new ones.

  5. Demonstration of biased membrane static figure mapping by optical beam subpixel centroid shift

    Energy Technology Data Exchange (ETDEWEB)

    Pinto, Fabrizio, E-mail: fpinto@jazanu.edu.sa [Laboratory for Quantum Vacuum Applications, Department of Physics, Faculty of Science, Jazan University, P.O. Box 114, Gizan 45142 (Saudi Arabia)

    2016-06-10

    The measurement of Casimir forces by means of condenser microphones has been shown to be quite promising since its early introduction almost half-a-century ago. However, unlike the remarkable progress achieved in characterizing the vibrating membrane in the dynamical case, the accurate determination of the membrane static figure under electrostatic bias remains a challenge. In this paper, we discuss our first data obtained by measuring the centroid shift of an optical beam with subpixel accuracy by charge coupled device (CCD) and by an extensive analysis of noise sources present in the experimental setup.

  6. Improving sub-pixel imperviousness change prediction by ensembling heterogeneous non-linear regression models

    Directory of Open Access Journals (Sweden)

    Drzewiecki Wojciech

    2016-12-01

    Full Text Available In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques.

  7. Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems

    Directory of Open Access Journals (Sweden)

    Yunfei Guo

    2012-04-01

    Full Text Available In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD called penalty DP-TBD (PDP-TBD is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.

  8. 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

  9. Drone Detection with Chirp‐Pulse Radar Based on Target Fluctuation Models

    Directory of Open Access Journals (Sweden)

    Byung‐Kwan Kim

    2018-04-01

    Full Text Available This paper presents a pulse radar system to detect drones based on a target fluctuation model, specifically the Swerling target model. Because drones are small atypical objects and are mainly composed of non‐conducting materials, their radar cross‐section value is low and fluctuating. Therefore, determining the target fluctuation model and applying a proper integration method are important. The proposed system is herein experimentally verified and the results are discussed. A prototype design of the pulse radar system is based on radar equations. It adopts three different pulse modes and a coherent pulse integration to ensure a high signal‐to‐noise ratio. Outdoor measurements are performed with a prototype radar system to detect Doppler frequencies from both the drone frame and blades. The results indicate that the drone frame and blades are detected within an instrumental maximum range. Additionally, the results show that the drone's frame and blades are close to the Swerling 3 and 4 target models, respectively. By the analysis of the Swerling target models, proper integration methods for detecting drones are verified and can thus contribute to increasing in detectability.

  10. 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.

  11. Design and implement of infrared small target real-time detection system based on pipeline technology

    Science.gov (United States)

    Sun, Lihui; Wang, Yongzhong; He, Yongqiang

    2007-01-01

    The detection for motive small target in infrared image sequence has become a hot topic nowadays. Background suppress algorithm based on minim gradient median filter and temporal recursion target detection algorithm are introduced. On the basis of contents previously mentioned, a four stages pipeline structure infrared small target detection process system, which aims at characters of algorithm complexity, large amounts of data to process, high frame frequency and exigent real-time character in this kind of application, is designed and implemented. The logical structure of the system was introduced and the function and signals flows are programmed. The system is composed of two FPGA chips and two DSP chips of TI. According to the function of each part, the system is divided into image preprocess stage, target detection stage, track relation stage and image output stage. The experiment of running algorithms on the system presented in this paper proved that the system could meet acquisition and process of 50Hz 240x320 digital image and the system could real time detect small target with a signal-noise ratio more than 3 reliably. The system achieves the characters of large amount of memory, high real-time processing, excellent extension and favorable interactive interface.

  12. 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.

  13. A strategy to objectively evaluate the necessity of correcting detected target deviations in image guided radiotherapy

    International Nuclear Information System (INIS)

    Yue, Ning J.; Kim, Sung; Jabbour, Salma; Narra, Venkat; Haffty, Bruce G.

    2007-01-01

    Image guided radiotherapy technologies are being increasingly utilized in the treatment of various cancers. These technologies have enhanced the ability to detect temporal and spatial deviations of the target volume relative to planned radiation beams. Correcting these detected deviations may, in principle, improve the accuracy of dose delivery to the target. However, in many situations, a clinical decision has to be made as to whether it is necessary to correct some of the deviations since the relevant dosimetric impact may or may not be significant, and the corresponding corrective action may be either impractical or time consuming. Ideally this decision should be based on objective and reproducible criteria rather than subjective judgment. In this study, a strategy is proposed for the objective evaluation of the necessity of deviation correction during the treatment verification process. At the treatment stage, without any alteration from the planned beams, the treatment beams should provide the desired dose coverage to the geometric volume identical to the planning target volume (PTV). Given this fact, the planned dose distribution and PTV geometry were used to compute the dose coverage and PTV enclosure of the clinical target volume (CTV) that was detected from imaging during the treatment setup verification. The spatial differences between the detected CTV and the planning CTV are essentially the target deviations. The extent of the PTV enclosure of the detected CTV as well as its dose coverage were used as criteria to evaluate the necessity of correcting any of the target deviations. This strategy, in principle, should be applicable to any type of target deviations, including both target deformable and positional changes and should be independent of how the deviations are detected. The proposed strategy was used on two clinical prostate cancer cases. In both cases, gold markers were implanted inside the prostate for the purpose of treatment setup

  14. Study on moving target detection to passive radar based on FM broadcast transmitter

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Target detection by a noncooperative illuminator is a topic of general interest in the electronic warfare field.First of all,direct-path interference(DPI)suppression which is the technique of bottleneck of moving target detection by a noncooperative frequency modulation(FM) broadcast transmitter is analyzed in this article;Secondly,a space-time-frequency domain synthetic solution to this problem is introduced:Adaptive nulling array processing is considered in the space domain,DPI cancellation based on adaptive fractional delay interpolation(AFDI)technique is used in planned time domain,and long-time coherent integration is utilized in the frequency domain;Finally,an experimental system is planned by considering FM broadcast transmitter as a noncooperative illuminator,Simulation results by real collected data show that the proposed method has a better performance of moving target detection.

  15. Low-Altitude and Slow-Speed Small Target Detection Based on Spectrum Zoom Processing

    Directory of Open Access Journals (Sweden)

    Xuwang Zhang

    2018-01-01

    Full Text Available This paper proposes a spectrum zoom processing based target detection algorithm for detecting the weak echo of low-altitude and slow-speed small (LSS targets in heavy ground clutter environments, which can be used to retrofit the existing radar systems. With the existing range-Doppler frequency images, the proposed method firstly concatenates the data from the same Doppler frequency slot of different images and then applies the spectrum zoom processing. After performing the clutter suppression, the target detection can be finally implemented. Through the theoretical analysis and real data verification, it is shown that the proposed algorithm can obtain a preferable spectrum zoom result and improve the signal-to-clutter ratio (SCR with a very low computational load.

  16. Two-dimensional hidden semantic information model for target saliency detection and eyetracking identification

    Science.gov (United States)

    Wan, Weibing; Yuan, Lingfeng; Zhao, Qunfei; Fang, Tao

    2018-01-01

    Saliency detection has been applied to the target acquisition case. This paper proposes a two-dimensional hidden Markov model (2D-HMM) that exploits the hidden semantic information of an image to detect its salient regions. A spatial pyramid histogram of oriented gradient descriptors is used to extract features. After encoding the image by a learned dictionary, the 2D-Viterbi algorithm is applied to infer the saliency map. This model can predict fixation of the targets and further creates robust and effective depictions of the targets' change in posture and viewpoint. To validate the model with a human visual search mechanism, two eyetrack experiments are employed to train our model directly from eye movement data. The results show that our model achieves better performance than visual attention. Moreover, it indicates the plausibility of utilizing visual track data to identify targets.

  17. 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.

  18. Location detection and tracking of moving targets by a 2D IR-UWB radar system.

    Science.gov (United States)

    Nguyen, Van-Han; Pyun, Jae-Young

    2015-03-19

    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.

  19. 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.

  20. Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain

    Science.gov (United States)

    Zhou, Anran; Xie, Weixin; Pei, Jihong

    2018-06-01

    Accurate detection of maritime targets in infrared imagery under various sea clutter conditions is always a challenging task. The fractional Fourier transform (FRFT) is the extension of the Fourier transform in the fractional order, and has richer spatial-frequency information. By combining it with the high order statistic filtering, a new ship detection method is proposed. First, the proper range of angle parameter is determined to make it easier for the ship components and background to be separated. Second, a new high order statistic curve (HOSC) at each fractional frequency point is designed. It is proved that maximal peak interval in HOSC reflects the target information, while the points outside the interval reflect the background. And the value of HOSC relative to the ship is much bigger than that to the sea clutter. Then, search the curve's maximal target peak interval and extract the interval by bandpass filtering in fractional Fourier domain. The value outside the peak interval of HOSC decreases rapidly to 0, so the background is effectively suppressed. Finally, the detection result is obtained by the double threshold segmenting and the target region selection method. The results show the proposed method is excellent for maritime targets detection with high clutters.

  1. Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

    Science.gov (United States)

    Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

    2018-03-01

    In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

  2. 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

  3. Directional support value of Gaussian transformation for infrared small target detection.

    Science.gov (United States)

    Yang, Changcai; Ma, Jiayi; Qi, Shengxiang; Tian, Jinwen; Zheng, Sheng; Tian, Xin

    2015-03-20

    Robust small target detection is one of the key techniques in IR search and tracking systems for self-defense or attacks. In this paper we present a robust solution for small target detection in a single IR image. The key ideas of the proposed method are to use the directional support value of Gaussian transform (DSVoGT) to enhance the targets, and use the multiscale representation provided by DSVoGT to reduce the false alarm rate. The original image is decomposed into sub-bands in different orientations by convolving the image with the directional support value filters, which are deduced from the weighted mapped least-squares-support vector machines (LS-SVMs). Based on the sub-band images, a support value of Gaussian matrix is constructed, and the trace of this matrix is then defined as the target measure. The corresponding multiscale correlations of the target measures are computed for enhancing target signal while suppressing the background clutter. We demonstrate the advantages of the proposed method on real IR images and compare the results against those obtained from standard detection approaches, including the top-hat filter, max-mean filter, max-median filter, min-local-Laplacian of Gaussian (LoG) filter, as well as LS-SVM. The experimental results on various cluttered background images show that the proposed method outperforms other detectors.

  4. 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.

  5. 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.

  6. 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.

  7. Usefulness of thin slice target CT scan in detecting mediastinal and hilar lymphadenopathy

    International Nuclear Information System (INIS)

    Yoshida, Shoji; Maeda, Tomoho; Nishioka, Masatoshi

    1986-01-01

    Comparative study of target scan with the different slice thickness and scan modes was performed to evaluate the mediastinal and hilar lymphadenopathy. 20 cases in controls and 35 cases in lymphadenopathy were examined. To delineate mediastinal and hilar lymphadenopathy, the scan mode of standard target was most useful in contrast and sharpness. Thin slice thickness with 5 mm was necessary in detecting small lymphnode or contour and internal structure of enlarged lymphnode. Valuable estimation of 5 mm contiguous target scan was obtained in the subaortic node (no. 5), tracheobronchial node (no. 4), precarinal and subcarinal node (no. 7) and right hilar node (no. 12). (author)

  8. NMR parallel Q-meter with double-balanced-mixer detection for polarized target experiments

    International Nuclear Information System (INIS)

    Boissevain, J.; Tippens, W.B.

    1983-01-01

    A constant-voltage, parallel-tuned nuclear magnetic resonance (NMR) circuit, patterned after a Liverpool design, has been developed for polarized target experiments. Measuring the admittance of the resonance circuit allows advantageous use of double-balanced mixer detection. The resonant circuit is tolerant of stray capacitance between the NMR coil and the target cavity, thus easing target-cell-design constraints. The reference leg of the circuit includes a voltage-controlled attenuator and phase shifter for ease of tuning. The NMR output features a flat background and has good linearity and stability

  9. 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.

  10. Quantifying Human Performance of a Dynamic Military Target Detection Task: An Application of the Theory of Signal Detection.

    Science.gov (United States)

    1995-06-01

    applied to analyze numerous experimental tasks (Macmillan and Creelman , 1991). One of these tasks, target detection, is the subject research. In...between each associated pair of false alarm rate and hit rate z-scores is d’ for the bias level associated with the pairing (Macmillan and Creelman , 1991...unequal variance in normal distributions (Macmillan and Creelman , 1991). 61 1966). It is described in detail for the interested reader by Green and

  11. Detection of atherosclerotic lesions and intimal macrophages using CD36-targeted nanovesicles.

    Science.gov (United States)

    Nie, Shufang; Zhang, Jia; Martinez-Zaguilan, Raul; Sennoune, Souad; Hossen, Md Nazir; Lichtenstein, Alice H; Cao, Jun; Meyerrose, Gary E; Paone, Ralph; Soontrapa, Suthipong; Fan, Zhaoyang; Wang, Shu

    2015-12-28

    Current approaches to the diagnosis and therapy of atherosclerosis cannot target 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 inflammatory responses. The presence of these cells is positively associated with lesion progression, severity and destabilization. Hence, they are an important diagnostic and therapeutic target. The objective of this study was to noninvasively assess the distribution and accumulation of intimal macrophages using CD36-targeted nanovesicles. Soy phosphatidylcholine was used to synthesize liposome-like nanovesicles. 1-(Palmitoyl)-2-(5-keto-6-octene-dioyl) phosphatidylcholine was incorporated on their surface to target the CD36 receptor. All in vitro data demonstrate that these targeted nanovesicles had a high binding affinity for the oxLDL binding site of the CD36 receptor and participated in CD36-mediated recognition and uptake of nanovesicles by macrophages. Intravenous administration into LDL receptor null mice of targeted compared to non-targeted nanovesicles resulted in higher uptake in aortic lesions. The nanovesicles co-localized with macrophages and their CD36 receptors in aortic lesions. This molecular target approach may facilitate the in vivo noninvasive imaging of atherosclerotic lesions in terms of intimal macrophage accumulation and distribution and disclose lesion features related to inflammation and possibly vulnerability thereby facilitate early lesion detection and targeted delivery of therapeutic compounds to intimal macrophages. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. Improved training for target detection using Fukunaga-Koontz transform and distance classifier correlation filter

    Science.gov (United States)

    Elbakary, M. I.; Alam, M. S.; Aslan, M. S.

    2008-03-01

    In a FLIR image sequence, a target may disappear permanently or may reappear after some frames and crucial information such as direction, position and size related to the target are lost. If the target reappears at a later frame, it may not be tracked again because the 3D orientation, size and location of the target might be changed. To obtain information about the target before disappearing and to detect the target after reappearing, distance classifier correlation filter (DCCF) is trained manualy by selecting a number of chips randomly. This paper introduces a novel idea to eliminates the manual intervention in training phase of DCCF. Instead of selecting the training chips manually and selecting the number of the training chips randomly, we adopted the K-means algorithm to cluster the training frames and based on the number of clusters we select the training chips such that a training chip for each cluster. To detect and track the target after reappearing in the field-ofview ,TBF and DCCF are employed. The contduced experiemnts using real FLIR sequences show results similar to the traditional agorithm but eleminating the manual intervention is the advantage of the proposed algorithm.

  13. 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.

  14. Added value of second biopsy target in screen-detected widespread suspicious breast calcifications.

    Science.gov (United States)

    Falkner, Nathalie M; Hince, Dana; Porter, Gareth; Dessauvagie, Ben; Jeganathan, Sanjay; Bulsara, Max; Lo, Glen

    2018-06-01

    There is controversy on the optimal work-up of screen-detected widespread breast calcifications: whether to biopsy a single target or multiple targets. This study evaluates agreement between multiple biopsy targets within the same screen-detected widespread (≥25 mm) breast calcification to determine if the second biopsy adds value. Retrospective observational study of women screened in a statewide general population risk breast cancer mammographic screening program from 2009 to 2016. Screening episodes recalled for widespread calcifications where further views indicated biopsy, and two or more separate target areas were sampled within the same lesion were included. Percentage agreement and Cohen's Kappa were calculated. A total of 293317 women were screened during 761124 separate episodes with recalls for widespread calcifications in 2355 episodes. In 171 women, a second target was biopsied within the same lesion. In 149 (86%) cases, the second target biopsy result agreed with the first biopsy (κ = 0.6768). Agreement increased with increasing mammography score (85%, 86% and 92% for score 3, 4 and 5 lesions). Same day multiple biopsied lesions were three times more likely to yield concordant results compared to post-hoc second target biopsy cases. While a single target biopsy is sufficient to discriminate a benign vs. malignant diagnosis in most cases, in 14% there is added value in performing a second target biopsy. Biopsies performed prospectively are more likely to yield concordant results compared to post-hoc second target biopsy cases, suggesting a single prospective biopsy may be sufficient when results are radiological-pathological concordant; discordance still requires repeat sampling. © 2018 The Royal Australian and New Zealand College of Radiologists.

  15. Sparse representation for infrared Dim target detection via a discriminative over-complete dictionary learned online.

    Science.gov (United States)

    Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju

    2014-05-27

    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.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Antonio Plaza

    2010-01-01

    Full Text Available 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.

  18. 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.

  19. Tensor Fukunaga-Koontz transform for small target detection in infrared images

    Science.gov (United States)

    Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli

    2016-09-01

    Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.

  20. Fluorescence turn-on detection of target sequence DNA based on silicon nanodot-mediated quenching.

    Science.gov (United States)

    Zhang, Yanan; Ning, Xinping; Mao, Guobin; Ji, Xinghu; He, Zhike

    2018-05-01

    We have developed a new enzyme-free method for target sequence DNA detection based on the dynamic quenching of fluorescent silicon nanodots (SiNDs) toward Cy5-tagged DNA probe. Fascinatingly, the water-soluble SiNDs can quench the fluorescence of cyanine (Cy5) in Cy5-tagged DNA probe in homogeneous solution, and the fluorescence of Cy5-tagged DNA probe can be restored in the presence of target sequence DNA (the synthetic target miRNA-27a). Based on this phenomenon, a SiND-featured fluorescent sensor has been constructed for "turn-on" detection of the synthetic target miRNA-27a for the first time. This newly developed approach possesses the merits of low cost, simple design, and convenient operation since no enzymatic reaction, toxic reagents, or separation procedures are involved. The established method achieves a detection limit of 0.16 nM, and the relative standard deviation of this method is 9% (1 nM, n = 5). The linear range is 0.5-20 nM, and the recoveries in spiked human fluids are in the range of 90-122%. This protocol provides a new tactic in the development of the nonenzymic miRNA biosensors and opens a promising avenue for early diagnosis of miRNA-associated disease. Graphical abstract The SiND-based fluorescent sensor for detection of S-miR-27a.

  1. Targets Mask U-Net for Wind Turbines Detection in Remote Sensing Images

    Science.gov (United States)

    Han, M.; Wang, H.; Wang, G.; Liu, Y.

    2018-04-01

    To detect wind turbines precisely and quickly in very high resolution remote sensing images (VHRRSI) we propose target mask U-Net. This convolution neural network (CNN), which is carefully designed to be a wide-field detector, models the pixel class assignment to wind turbines and their context information. The shadow, which is the context information of the target in this study, has been regarded as part of a wind turbine instance. We have trained the target mask U-Net on training dataset, which is composed of down sampled image blocks and instance mask blocks. Some post-processes have been integrated to eliminate wrong spots and produce bounding boxes of wind turbine instances. The evaluation metrics prove the reliability and effectiveness of our method for the average F1-score of our detection method is up to 0.97. The comparison of detection accuracy and time consuming with the weakly supervised targets detection method based on CNN illustrates the superiority of our method.

  2. 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

  3. A speeded-up saliency region-based contrast detection method for small targets

    Science.gov (United States)

    Li, Zhengjie; Zhang, Haiying; Bai, Jiaojiao; Zhou, Zhongjun; Zheng, Huihuang

    2018-04-01

    To cope with the rapid development of the real applications for infrared small targets, the researchers have tried their best to pursue more robust detection methods. At present, the contrast measure-based method has become a promising research branch. Following the framework, in this paper, a speeded-up contrast measure scheme is proposed based on the saliency detection and density clustering. First, the saliency region is segmented by saliency detection method, and then, the Multi-scale contrast calculation is carried out on it instead of traversing the whole image. Second, the target with a certain "integrity" property in spatial is exploited to distinguish the target from the isolated noises by density clustering. Finally, the targets are detected by a self-adaptation threshold. Compared with time-consuming MPCM (Multiscale Patch Contrast Map), the time cost of the speeded-up version is within a few seconds. Additional, due to the use of "clustering segmentation", the false alarm caused by heavy noises can be restrained to a lower level. The experiments show that our method has a satisfied FASR (False alarm suppression ratio) and real-time performance compared with the state-of-art algorithms no matter in cloudy sky or sea-sky background.

  4. Aerial surveillance based on hierarchical object classification for ground target detection

    Science.gov (United States)

    Vázquez-Cervantes, Alberto; García-Huerta, Juan-Manuel; Hernández-Díaz, Teresa; Soto-Cajiga, J. A.; Jiménez-Hernández, Hugo

    2015-03-01

    Unmanned aerial vehicles have turned important in surveillance application due to the flexibility and ability to inspect and displace in different regions of interest. The instrumentation and autonomy of these vehicles have been increased; i.e. the camera sensor is now integrated. Mounted cameras allow flexibility to monitor several regions of interest, displacing and changing the camera view. A well common task performed by this kind of vehicles correspond to object localization and tracking. This work presents a hierarchical novel algorithm to detect and locate objects. The algorithm is based on a detection-by-example approach; this is, the target evidence is provided at the beginning of the vehicle's route. Afterwards, the vehicle inspects the scenario, detecting all similar objects through UTM-GPS coordinate references. Detection process consists on a sampling information process of the target object. Sampling process encode in a hierarchical tree with different sampling's densities. Coding space correspond to a huge binary space dimension. Properties such as independence and associative operators are defined in this space to construct a relation between the target object and a set of selected features. Different densities of sampling are used to discriminate from general to particular features that correspond to the target. The hierarchy is used as a way to adapt the complexity of the algorithm due to optimized battery duty cycle of the aerial device. Finally, this approach is tested in several outdoors scenarios, proving that the hierarchical algorithm works efficiently under several conditions.

  5. 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,

  6. Detection of Moving Targets Based on Doppler Spectrum Analysis Technique for Passive Coherent Radar

    Directory of Open Access Journals (Sweden)

    Zhao Yao-dong

    2013-06-01

    Full Text Available A novel method of moving targets detection taking Doppler spectrum analysis technique for Passive Coherent Radar (PCR is provided. After dividing the receiving signals into segments as pulse series, it utilizes the technique of pulse compress and Doppler processing to detect and locate the targets. Based on the algorithm for Pulse-Doppler (PD radar, the equipollence between continuous and pulsed wave in match filtering is proved and details of this method are introduced. To compare it with the traditional method of Cross-Ambiguity Function (CAF calculation, the relationship and mathematical modes of them are analyzed, with some suggestions on parameters choosing. With little influence to the gain of targets, the method can greatly promote the processing efficiency. The validity of the proposed method is demonstrated by offline processing real collected data sets and simulation results.

  7. Infrared images target detection based on background modeling in the discrete cosine domain

    Science.gov (United States)

    Ye, Han; Pei, Jihong

    2018-02-01

    Background modeling is the critical technology to detect the moving target for video surveillance. Most background modeling techniques are aimed at land monitoring and operated in the spatial domain. A background establishment becomes difficult when the scene is a complex fluctuating sea surface. In this paper, the background stability and separability between target are analyzed deeply in the discrete cosine transform (DCT) domain, on this basis, we propose a background modeling method. The proposed method models each frequency point as a single Gaussian model to represent background, and the target is extracted by suppressing the background coefficients. Experimental results show that our approach can establish an accurate background model for seawater, and the detection results outperform other background modeling methods in the spatial domain.

  8. 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.

  9. 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 (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.

  10. 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.

  11. 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.

  12. 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...

  13. A new frozen-spin target for 4π particle detection

    International Nuclear Information System (INIS)

    Bradtke, Ch.; Dutz, H.; Peschel, H.; Goertz, S.; Harmsen, J.; Hasegawa, S.; Horikawa, N.; Iwata, T.; Kageya, T.; Matsuda, T.; Meier, A.; Meyer, W.; Radtke, E.; Reicherz, G.; Rohlof, Ch.; Thomas, A.; Wakai, A.

    1999-01-01

    A new frozen-spin target has been developed, that allows the detection of emitted particles in an angular acceptance of almost 4π in the laboratory frame. The central part of this new target represents a 3 He/ 4 He dilution refrigerator that is installed horizontally along the beam axis. The refrigerator includes an internal superconducting holding coil to maintain the nucleon polarization in the frozen-spin mode longitudinally to the beam. The design of the dilution refrigerator and the use of an internal holding coil enabled for the first time the measurement of a spin-dependent total cross section in combination with a polarized solid state target. This new frozen-spin target was used successfully to measure the helicity asymmetry of the total photoabsorption cross-section at the Mainz accelerator facility MAMI. This experiment has been performed in order to verify for the first time the GDH sum rule

  14. A new frozen-spin target for 4 pi particle detection

    CERN Document Server

    Bradtke, C; Peschel, H; Görtz, S; Harmsen, J; Hasegawa, S; Horikawa, N; Iwata, T; Kageya, T; Matsuda, T; Meier, A; Meyer, Werner T; Radtke, E; Reicherz, G; Rohlof, C; Thomas, A; Wakai, A

    1999-01-01

    A new frozen-spin target has been developed, that allows the detection of emitted particles in an angular acceptance of almost 4 pi in the laboratory frame. The central part of this new target represents a sup 3 He/ sup 4 He dilution refrigerator that is installed horizontally along the beam axis. The refrigerator includes an internal superconducting holding coil to maintain the nucleon polarization in the frozen-spin mode longitudinally to the beam. The design of the dilution refrigerator and the use of an internal holding coil enabled for the first time the measurement of a spin-dependent total cross section in combination with a polarized solid state target. This new frozen-spin target was used successfully to measure the helicity asymmetry of the total photoabsorption cross-section at the Mainz accelerator facility MAMI. This experiment has been performed in order to verify for the first time the GDH sum rule.

  15. 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 (R 2 ) 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.

  16. 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.

  17. A Novel Detection Method for Underwater Moving Targets by Measuring Their ELF Emissions with Inductive Sensors

    Directory of Open Access Journals (Sweden)

    Jinhong Wang

    2017-07-01

    Full Text Available In this article, we propose a novel detection method for underwater moving targets by detecting their extremely low frequency (ELF emissions with inductive sensors. The ELF field source of the targets is modeled by a horizontal electric dipole at distances more than several times of the targets’ length. The formulas for the fields produced in air are derived with a three-layer model (air, seawater and seafloor and are evaluated with a complementary numerical integration technique. A proof of concept measurement is presented. The ELF emissions from a surface ship were detected by inductive electronic and magnetic sensors as the ship was leaving a harbor. ELF signals are of substantial strength and have typical characteristic of harmonic line spectrum, and the fundamental frequency has a direct relationship with the ship’s speed. Due to the high sensitivity and low noise level of our sensors, it is capable of resolving weak ELF signals at long distance. In our experiment, a detection distance of 1300 m from the surface ship above the sea surface was realized, which shows that this method would be an appealing complement to the usual acoustic detection and magnetic anomaly detection capability.

  18. Robust Detection of Moving Human Target in Foliage-Penetration Environment Based on Hough Transform

    Directory of Open Access Journals (Sweden)

    P. Lei

    2014-04-01

    Full Text Available Attention has been focused on the robust moving human target detection in foliage-penetration environment, which presents a formidable task in a radar system because foliage is a rich scattering environment with complex multipath propagation and time-varying clutter. Generally, multiple-bounce returns and clutter are additionally superposed to direct-scatter echoes. They obscure true target echo and lead to poor visual quality time-range image, making target detection particular difficult. Consequently, an innovative approach is proposed to suppress clutter and mitigate multipath effects. In particular, a clutter suppression technique based on range alignment is firstly applied to suppress the time-varying clutter and the instable antenna coupling. Then entropy weighted coherent integration (EWCI algorithm is adopted to mitigate the multipath effects. In consequence, the proposed method effectively reduces the clutter and ghosting artifacts considerably. Based on the high visual quality image, the target trajectory is detected robustly and the radial velocity is estimated accurately with the Hough transform (HT. Real data used in the experimental results are provided to verify the proposed method.

  19. 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.

  20. 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.

  1. 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.

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

    Science.gov (United States)

    2012-09-01

    to use this information to produce a trafficability product providing the consumer with information that is helpful in navigating through areas of...1989; Sieh and Bursik, 1986). The ring around the dome of the volcano is the result of a strombolian type of eruption (Sieh and Bursik, 1986; Sharp...6ENCHES. LANDSLIDES CUESTAS HILLSIDES AND E$-CAAPME:NT$ IN A ORY SlJEIHtJMJO Ct.IMAftC lOf.IE CAH0NA-8E0AY-HACifRM.AN M0091’a,lely d9flp .lOd \\let

  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. Ship detection for high resolution optical imagery with adaptive target filter

    Science.gov (United States)

    Ju, Hongbin

    2015-10-01

    Ship detection is important due to both its civil and military use. In this paper, we propose a novel ship detection method, Adaptive Target Filter (ATF), for high resolution optical imagery. The proposed framework can be grouped into two stages, where in the first stage, a test image is densely divided into different detection windows and each window is transformed to a feature vector in its feature space. The Histograms of Oriented Gradients (HOG) is accumulated as a basic feature descriptor. In the second stage, the proposed ATF highlights all the ship regions and suppresses the undesired backgrounds adaptively. Each detection window is assigned a score, which represents the degree of the window belonging to a certain ship category. The ATF can be adaptively obtained by the weighted Logistic Regression (WLR) according to the distribution of backgrounds and targets of the input image. The main innovation of our method is that we only need to collect positive training samples to build the filter, while the negative training samples are adaptively generated by the input image. This is different to other classification method such as Support Vector Machine (SVM) and Logistic Regression (LR), which need to collect both positive and negative training samples. The experimental result on 1-m high resolution optical images shows the proposed method achieves a desired ship detection performance with higher quality and robustness than other methods, e.g., SVM and LR.

  5. 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...

  6. 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.

  7. 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.

  8. 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.

  9. 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. PMID:26222882

  10. 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...

  11. Automatic detection of the unknown number point targets in FMICW radar signals

    Czech Academy of Sciences Publication Activity Database

    Rejfek, L.; Mošna, Zbyšek; Beran, L.; Fišer, O.; Dobrovolný, M.

    2017-01-01

    Roč. 4, č. 11 (2017), s. 116-120 ISSN 2313-626X R&D Projects: GA ČR(CZ) GA15-24688S Institutional support: RVO:68378289 Keywords : FMICW radar * 2D FFT * signal filtration * taraget detection * target parameter estimation Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences http://science-gate.com/IJAAS/Articles/2017-4-11/18%202017-4-11-pp.116-120.pdf

  12. Analytical Approach to Target Detection and Localization at High-Frequency Bands Using Multipath Propagation

    Science.gov (United States)

    2016-04-25

    ElectroMagnetic, Multipath propagation, Reflection-diffraction, SAR signal processing 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18...protection, and traffic surveillance, etc. With these above reasons, we are motivated to introduce a new approach to the target detection and...coherent integrating the backscattering signal , we propose a 3D propagation model that is useful not only in explaining the mechanisms of wave

  13. Ultramild protein-mediated click chemistry creates efficient oligonucleotide probes for targeting and detecting nucleic acids

    DEFF Research Database (Denmark)

    Nåbo, Lina J.; Madsen, Charlotte S.; Jensen, Knud J.

    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...... targeting and detection properties. We focus in particular on the pH sensitivity of these new probes and their high target specificity. For the first time, human copper(I)-binding chaperon Cox17 was applied to effectively catalyze click labeling of oligonucleotides. This was performed under ultramild...... 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...

  14. Switchable DNA interfaces for the highly sensitive detection of label-free DNA targets.

    Science.gov (United States)

    Rant, Ulrich; Arinaga, Kenji; Scherer, Simon; Pringsheim, Erika; Fujita, Shozo; Yokoyama, Naoki; Tornow, Marc; Abstreiter, Gerhard

    2007-10-30

    We report a method to detect label-free oligonucleotide targets. The conformation of surface-tethered probe nucleic acids is modulated by alternating electric fields, which cause the molecules to extend away from or fold onto the biased surface. Binding (hybridization) of targets to the single-stranded probes results in a pronounced enhancement of the layer-height modulation amplitude, monitored optically in real time. The method features an exceptional detection limit of <3 x 10(8) bound targets per cm(2) sensor area. Single base-pair mismatches in the sequences of DNA complements may readily be identified; moreover, binding kinetics and binding affinities can be determined with high accuracy. When driving the DNA to oscillate at frequencies in the kHz regime, distinct switching kinetics are revealed for single- and double-stranded DNA. Molecular dynamics are used to identify the binding state of molecules according to their characteristic kinetic fingerprints by using a chip-compatible detection format.

  15. Detection of ferromagnetic target based on mobile magnetic gradient tensor system

    Energy Technology Data Exchange (ETDEWEB)

    Gang, Y.I.N., E-mail: gang.gang88@163.com; Yingtang, Zhang; Zhining, Li; Hongbo, Fan; Guoquan, Ren

    2016-03-15

    Attitude change of mobile magnetic gradient tensor system critically affects the precision of gradient measurements, thereby increasing ambiguity in target detection. This paper presents a rotational invariant-based method for locating and identifying ferromagnetic targets. Firstly, unit magnetic moment vector was derived based on the geometrical invariant, such that the intermediate eigenvector of the magnetic gradient tensor is perpendicular to the magnetic moment vector and the source–sensor displacement vector. Secondly, unit source–sensor displacement vector was derived based on the characteristic that the angle between magnetic moment vector and source–sensor displacement is a rotational invariant. By introducing a displacement vector between two measurement points, the magnetic moment vector and the source–sensor displacement vector were theoretically derived. To resolve the problem of measurement noises existing in the realistic detection applications, linear equations were formulated using invariants corresponding to several distinct measurement points and least square solution of magnetic moment vector and source–sensor displacement vector were obtained. Results of simulation and principal verification experiment showed the correctness of the analytical method, along with the practicability of the least square method. - Highlights: • Ferromagnetic target detection method is proposed based on rotational invariants • Intermediate eigenvector is perpendicular to magnetic moment and displacement vector • Angle between magnetic moment and displacement vector is a rotational invariant • Magnetic moment and displacement vector are derived based on invariants of two points.

  16. Targeted Ultrasound for MR-Detected Lesions in Breast Cancer Patients

    International Nuclear Information System (INIS)

    Shin, Jung Hee; Han, Boo Kyung; Choe, Yeon Hyeon; Ko, Kyung Ran; Choi, Nami

    2007-01-01

    To investigate the usefulness of targeted ultrasound (US) in the identification of additional suspicious lesions found by magnetic resonance (MR) imaging in breast cancer patients and the changes in treatment based on the identification of the lesions by the use of targeted US. One-hundred forty nine patients who underwent breast MR imaging for a preoperative evaluation of breast cancer between January 2002 and July 2004 were included in the study. We searched all cases for any additional lesions that were found initially by MR imaging and investigated the performance of targeted US in identifying the lesions. We also investigated their pathological outcomes and changes in treatment as a result of lesion identification. Of the 149 patients with breast cancer, additional suspicious lesions were detected with MR imaging in 62 patients (42%). Of the 69 additional lesions found in those 62 patients, 26 (38%) were confirmed as cancers by histology. Thirty-eight lesions in 31 patients were examined with targeted US and were histologically revealed as cancers in 18 (47%), high risk lesions in two (5%), benign lesions in 15 (39%), and unidentified lesions in three (8%). The cancer rate was statistically higher in lesions with a US correlate than in lesions without a US correlate (p = 0.028). Of 31 patients, the surgical plan was altered in 27 (87%). The use of targeted US justified a change in treatment for 22 patients (81%) and misled five patients (19%) into having an unnecessary surgical excision. Targeted US can play a useful role in the evaluation of additional suspicious lesions detected by MR imaging in breast cancer patients, but is limited in lesions without a US correlate

  17. 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.

  18. Dependency of human target detection performance on clutter and quality of supporting image analysis algorithms in a video surveillance task

    Science.gov (United States)

    Huber, Samuel; Dunau, Patrick; Wellig, Peter; Stein, Karin

    2017-10-01

    Background: In target detection, the success rates depend strongly on human observer performances. Two prior studies tested the contributions of target detection algorithms and prior training sessions. The aim of this Swiss-German cooperation study was to evaluate the dependency of human observer performance on the quality of supporting image analysis algorithms. Methods: The participants were presented 15 different video sequences. Their task was to detect all targets in the shortest possible time. Each video sequence showed a heavily cluttered simulated public area from a different viewing angle. In each video sequence, the number of avatars in the area was altered to 100, 150 and 200 subjects. The number of targets appearing was kept at 10%. The number of marked targets varied from 0, 5, 10, 20 up to 40 marked subjects while keeping the positive predictive value of the detection algorithm at 20%. During the task, workload level was assessed by applying an acoustic secondary task. Detection rates and detection times for the targets were analyzed using inferential statistics. Results: The study found Target Detection Time to increase and Target Detection Rates to decrease with increasing numbers of avatars. The same is true for the Secondary Task Reaction Time while there was no effect on Secondary Task Hit Rate. Furthermore, we found a trend for a u-shaped correlation between the numbers of markings and RTST indicating increased workload. Conclusion: The trial results may indicate useful criteria for the design of training and support of observers in observational tasks.

  19. panelcn.MOPS: Copy-number detection in targeted NGS panel data for clinical diagnostics.

    Science.gov (United States)

    Povysil, Gundula; Tzika, Antigoni; Vogt, Julia; Haunschmid, Verena; Messiaen, Ludwine; Zschocke, Johannes; Klambauer, Günter; Hochreiter, Sepp; Wimmer, Katharina

    2017-07-01

    Targeted next-generation-sequencing (NGS) panels have largely replaced Sanger sequencing in clinical diagnostics. They allow for the detection of copy-number variations (CNVs) in addition to single-nucleotide variants and small insertions/deletions. However, existing computational CNV detection methods have shortcomings regarding accuracy, quality control (QC), incidental findings, and user-friendliness. We developed panelcn.MOPS, a novel pipeline for detecting CNVs in targeted NGS panel data. Using data from 180 samples, we compared panelcn.MOPS with five state-of-the-art methods. With panelcn.MOPS leading the field, most methods achieved comparably high accuracy. panelcn.MOPS reliably detected CNVs ranging in size from part of a region of interest (ROI), to whole genes, which may comprise all ROIs investigated in a given sample. The latter is enabled by analyzing reads from all ROIs of the panel, but presenting results exclusively for user-selected genes, thus avoiding incidental findings. Additionally, panelcn.MOPS offers QC criteria not only for samples, but also for individual ROIs within a sample, which increases the confidence in called CNVs. panelcn.MOPS is freely available both as R package and standalone software with graphical user interface that is easy to use for clinical geneticists without any programming experience. panelcn.MOPS combines high sensitivity and specificity with user-friendliness rendering it highly suitable for routine clinical diagnostics. © 2017 The Authors. Human Mutation published by Wiley Periodicals, Inc.

  20. Rapid Target Detection in High Resolution Remote Sensing Images Using Yolo Model

    Science.gov (United States)

    Wu, Z.; Chen, X.; Gao, Y.; Li, Y.

    2018-04-01

    Object detection in high resolution remote sensing images is a fundamental and challenging problem in the field of remote sensing imagery analysis for civil and military application due to the complex neighboring environments, which can cause the recognition algorithms to mistake irrelevant ground objects for target objects. Deep Convolution Neural Network(DCNN) is the hotspot in object detection for its powerful ability of feature extraction and has achieved state-of-the-art results in Computer Vision. Common pipeline of object detection based on DCNN consists of region proposal, CNN feature extraction, region classification and post processing. YOLO model frames object detection as a regression problem, using a single CNN predicts bounding boxes and class probabilities in an end-to-end way and make the predict faster. In this paper, a YOLO based model is used for object detection in high resolution sensing images. The experiments on NWPU VHR-10 dataset and our airport/airplane dataset gain from GoogleEarth show that, compare with the common pipeline, the proposed model speeds up the detection process and have good accuracy.

  1. 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.

  2. Detection of attack-targeted scans from the Apache HTTP Server access logs

    Directory of Open Access Journals (Sweden)

    Merve Baş Seyyar

    2018-01-01

    Full Text Available A web application could be visited for different purposes. It is possible for a web site to be visited by a regular user as a normal (natural visit, to be viewed by crawlers, bots, spiders, etc. for indexing purposes, lastly to be exploratory scanned by malicious users prior to an attack. An attack targeted web scan can be viewed as a phase of a potential attack and can lead to more attack detection as compared to traditional detection methods. In this work, we propose a method to detect attack-oriented scans and to distinguish them from other types of visits. In this context, we use access log files of Apache (or ISS web servers and try to determine attack situations through examination of the past data. In addition to web scan detections, we insert a rule set to detect SQL Injection and XSS attacks. Our approach has been applied on sample data sets and results have been analyzed in terms of performance measures to compare our method and other commonly used detection techniques. Furthermore, various tests have been made on log samples from real systems. Lastly, several suggestions about further development have been also discussed.

  3. A comparison of machine learning techniques for detection of drug target articles.

    Science.gov (United States)

    Danger, Roxana; Segura-Bedmar, Isabel; Martínez, Paloma; Rosso, Paolo

    2010-12-01

    Important progress in treating diseases has been possible thanks to the identification of drug targets. Drug targets are the molecular structures whose abnormal activity, associated to a disease, can be modified by drugs, improving the health of patients. Pharmaceutical industry needs to give priority to their identification and validation in order to reduce the long and costly drug development times. In the last two decades, our knowledge about drugs, their mechanisms of action and drug targets has rapidly increased. Nevertheless, most of this knowledge is hidden in millions of medical articles and textbooks. Extracting knowledge from this large amount of unstructured information is a laborious job, even for human experts. Drug target articles identification, a crucial first step toward the automatic extraction of information from texts, constitutes the aim of this paper. A comparison of several machine learning techniques has been performed in order to obtain a satisfactory classifier for detecting drug target articles using semantic information from biomedical resources such as the Unified Medical Language System. The best result has been achieved by a Fuzzy Lattice Reasoning classifier, which reaches 98% of ROC area measure. Copyright © 2010 Elsevier Inc. All rights reserved.

  4. Modern Approaches to the Computation of the Probability of Target Detection in Cluttered Environments

    Science.gov (United States)

    Meitzler, Thomas J.

    The field of computer vision interacts with fields such as psychology, vision research, machine vision, psychophysics, mathematics, physics, and computer science. The focus of this thesis is new algorithms and methods for the computation of the probability of detection (Pd) of a target in a cluttered scene. The scene can be either a natural visual scene such as one sees with the naked eye (visual), or, a scene displayed on a monitor with the help of infrared sensors. The relative clutter and the temperature difference between the target and background (DeltaT) are defined and then used to calculate a relative signal -to-clutter ratio (SCR) from which the Pd is calculated for a target in a cluttered scene. It is shown how this definition can include many previous definitions of clutter and (DeltaT). Next, fuzzy and neural -fuzzy techniques are used to calculate the Pd and it is shown how these methods can give results that have a good correlation with experiment. The experimental design for actually measuring the Pd of a target by observers is described. Finally, wavelets are applied to the calculation of clutter and it is shown how this new definition of clutter based on wavelets can be used to compute the Pd of a target.

  5. Theoretical study and experimental detection of cavitation phenomena in Liquid Lithium Target Facility for IFMIF

    International Nuclear Information System (INIS)

    Orco, G. Dell; Horiike, H.; Ida, M.; Nakamura, H.

    2006-01-01

    In the IFMIF (International Fusion Materials Irradiation Facility) testing facility, the required high energy neutrons emission will be produced by reaction of two D + beams with a free surface liquid Lithium jet target flowing along concave back-wall at 20 m/s. The Lithium height in the experimental loop and its relevant static pressure, the high flow velocities and the presence of several devices for the flow control and the pressure reduction increase the risk of cavitation onset in the target system. Special attention has to be taken in the primary pump, in the flow straightener, in the nozzle and their interconnections where the local pressure decreases and/or velocity increases or flow separations could promote the emission of cavitation vapour bubbles. The successive bubble re-implosions, in the higher pressure liquid bulk, could activate material erosion and transportation of activated particulates. These bubbles, if emitted close to the free jet flow, could also procure hydraulic instability and disturbance of the neutron field in the D + beams-Lithium target zone. Therefore, the cavitation risk must be properly foreseen along the whole IFMIF Lithium target circuit and its occurrence at different operating condition should be also monitored by special instrumentation. ENEA, in close cooperation with JAEA, has demonstrated the capability to detect the onset of the cavitation noises in liquid Lithium, by using the ENEA patented accelerometric gauge called CASBA-2000, during hydraulic test campaigns carried-out at Osaka University Lithium facility on a straight mock-up of the IFMIF back plate target. Comparison with the Thoma' cavitation similitude criteria have also determined the critical threshold limit for the estimation of the onset. Theoretical study on the conditions of cavitations generation in the IFMIF Lithium Target Circuit were also launched between ENEA and JAEA aiming at analysing the risk of the cavitation occurrence in the Lithium flow by

  6. Improved initial guess with semi-subpixel level accuracy in digital image correlation by feature-based method

    Science.gov (United States)

    Zhang, Yunlu; Yan, Lei; Liou, Frank

    2018-05-01

    The quality initial guess of deformation parameters in digital image correlation (DIC) has a serious impact on convergence, robustness, and efficiency of the following subpixel level searching stage. In this work, an improved feature-based initial guess (FB-IG) scheme is presented to provide initial guess for points of interest (POIs) inside a large region. Oriented FAST and Rotated BRIEF (ORB) features are semi-uniformly extracted from the region of interest (ROI) and matched to provide initial deformation information. False matched pairs are eliminated by the novel feature guided Gaussian mixture model (FG-GMM) point set registration algorithm, and nonuniform deformation parameters of the versatile reproducing kernel Hilbert space (RKHS) function are calculated simultaneously. Validations on simulated images and real-world mini tensile test verify that this scheme can robustly and accurately compute initial guesses with semi-subpixel level accuracy in cases with small or large translation, deformation, or rotation.

  7. 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).

  8. Adaptive Energy-Efficient Target Detection Based on Mobile Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Tengyue Zou

    2017-05-01

    Full Text Available Target detection is a widely used application for area surveillance, elder care, and fire alarms; its purpose is to find a particular object or event in a region of interest. Usually, fixed observing stations or static sensor nodes are arranged uniformly in the field. However, each part of the field has a different probability of being intruded upon; if an object suddenly enters an area with few guardian devices, a loss of detection will occur, and the stations in the safe areas will waste their energy for a long time without any discovery. Thus, mobile wireless sensor networks may benefit from adaptation and pertinence in detection. Sensor nodes equipped with wheels are able to move towards the risk area via an adaptive learning procedure based on Bayesian networks. Furthermore, a clustering algorithm based on k-means++ and an energy control mechanism is used to reduce the energy consumption of nodes. The extended Kalman filter and a voting data fusion method are employed to raise the localization accuracy of the target. The simulation and experimental results indicate that this new system with adaptive energy-efficient methods is able to achieve better performance than the traditional ones.

  9. 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.

  10. Adaptive Energy-Efficient Target Detection Based on Mobile Wireless Sensor Networks.

    Science.gov (United States)

    Zou, Tengyue; Li, Zhenjia; Li, Shuyuan; Lin, Shouying

    2017-05-04

    Target detection is a widely used application for area surveillance, elder care, and fire alarms; its purpose is to find a particular object or event in a region of interest. Usually, fixed observing stations or static sensor nodes are arranged uniformly in the field. However, each part of the field has a different probability of being intruded upon; if an object suddenly enters an area with few guardian devices, a loss of detection will occur, and the stations in the safe areas will waste their energy for a long time without any discovery. Thus, mobile wireless sensor networks may benefit from adaptation and pertinence in detection. Sensor nodes equipped with wheels are able to move towards the risk area via an adaptive learning procedure based on Bayesian networks. Furthermore, a clustering algorithm based on k -means++ and an energy control mechanism is used to reduce the energy consumption of nodes. The extended Kalman filter and a voting data fusion method are employed to raise the localization accuracy of the target. The simulation and experimental results indicate that this new system with adaptive energy-efficient methods is able to achieve better performance than the traditional ones.

  11. Application of adjusted subpixel method (ASM) in HRCT measurements of the bronchi in bronchial asthma patients and healthy individuals.

    Science.gov (United States)

    Mincewicz, Grzegorz; Rumiński, Jacek; Krzykowski, Grzegorz

    2012-02-01

    Recently, we described a model system which included corrections of high-resolution computed tomography (HRCT) bronchial measurements based on the adjusted subpixel method (ASM). To verify the clinical application of ASM by comparing bronchial measurements obtained by means of the traditional eye-driven method, subpixel method alone and ASM in a group comprised of bronchial asthma patients and healthy individuals. The study included 30 bronchial asthma patients and the control group comprised of 20 volunteers with no symptoms of asthma. The lowest internal and external diameters of the bronchial cross-sections (ID and ED) and their derivative parameters were determined in HRCT scans using: (1) traditional eye-driven method, (2) subpixel technique, and (3) ASM. In the case of the eye-driven method, lower ID values along with lower bronchial lumen area and its percentage ratio to total bronchial area were basic parameters that differed between asthma patients and healthy controls. In the case of the subpixel method and ASM, both groups were not significantly different in terms of ID. Significant differences were observed in values of ED and total bronchial area with both parameters being significantly higher in asthma patients. Compared to ASM, the eye-driven method overstated the values of ID and ED by about 30% and 10% respectively, while understating bronchial wall thickness by about 18%. Results obtained in this study suggest that the traditional eye-driven method of HRCT-based measurement of bronchial tree components probably overstates the degree of bronchial patency in asthma patients. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  12. Application of adjusted subpixel method (ASM) in HRCT measurements of the bronchi in bronchial asthma patients and healthy individuals

    International Nuclear Information System (INIS)

    Mincewicz, Grzegorz; Rumiński, Jacek; Krzykowski, Grzegorz

    2012-01-01

    Background: Recently, we described a model system which included corrections of high-resolution computed tomography (HRCT) bronchial measurements based on the adjusted subpixel method (ASM). Objective: To verify the clinical application of ASM by comparing bronchial measurements obtained by means of the traditional eye-driven method, subpixel method alone and ASM in a group comprised of bronchial asthma patients and healthy individuals. Methods: The study included 30 bronchial asthma patients and the control group comprised of 20 volunteers with no symptoms of asthma. The lowest internal and external diameters of the bronchial cross-sections (ID and ED) and their derivative parameters were determined in HRCT scans using: (1) traditional eye-driven method, (2) subpixel technique, and (3) ASM. Results: In the case of the eye-driven method, lower ID values along with lower bronchial lumen area and its percentage ratio to total bronchial area were basic parameters that differed between asthma patients and healthy controls. In the case of the subpixel method and ASM, both groups were not significantly different in terms of ID. Significant differences were observed in values of ED and total bronchial area with both parameters being significantly higher in asthma patients. Compared to ASM, the eye-driven method overstated the values of ID and ED by about 30% and 10% respectively, while understating bronchial wall thickness by about 18%. Conclusions: Results obtained in this study suggest that the traditional eye-driven method of HRCT-based measurement of bronchial tree components probably overstates the degree of bronchial patency in asthma patients.

  13. Subpixel Snow Cover Mapping from MODIS Data by Nonparametric Regression Splines

    Science.gov (United States)

    Akyurek, Z.; Kuter, S.; Weber, G. W.

    2016-12-01

    Spatial extent of snow cover is often considered as one of the key parameters in climatological, hydrological and ecological modeling due to its energy storage, high reflectance in the visible and NIR regions of the electromagnetic spectrum, significant heat capacity and insulating properties. A significant challenge in snow mapping by remote sensing (RS) is the trade-off between the temporal and spatial resolution of satellite imageries. In order to tackle this issue, machine learning-based subpixel snow mapping methods, like Artificial Neural Networks (ANNs), from low or moderate resolution images have been proposed. Multivariate Adaptive Regression Splines (MARS) is a nonparametric regression tool that can build flexible models for high dimensional and complex nonlinear data. Although MARS is not often employed in RS, it has various successful implementations such as estimation of vertical total electron content in ionosphere, atmospheric correction and classification of satellite images. This study is the first attempt in RS to evaluate the applicability of MARS for subpixel snow cover mapping from MODIS data. Total 16 MODIS-Landsat ETM+ image pairs taken over European Alps between March 2000 and April 2003 were used in the study. MODIS top-of-atmospheric reflectance, NDSI, NDVI and land cover classes were used as predictor variables. Cloud-covered, cloud shadow, water and bad-quality pixels were excluded from further analysis by a spatial mask. MARS models were trained and validated by using reference fractional snow cover (FSC) maps generated from higher spatial resolution Landsat ETM+ binary snow cover maps. A multilayer feed-forward ANN with one hidden layer trained with backpropagation was also developed. The mutual comparison of obtained MARS and ANN models was accomplished on independent test areas. The MARS model performed better than the ANN model with an average RMSE of 0.1288 over the independent test areas; whereas the average RMSE of the ANN model

  14. Hotspots ampersand other hidden targets: Probability of detection, number, frequency and area

    International Nuclear Information System (INIS)

    Vita, C.L.

    1994-01-01

    Concepts and equations are presented for making probability-based estimates of the detection probability, and the number, frequency, and area of hidden targets, including hotspots, at a given site. Targets include hotspots, which are areas of extreme or particular contamination, and any object or feature that is hidden from direct visual observation--including buried objects and geologic or hydrologic details or anomalies. Being Bayesian, results are fundamentally consistent with observational methods. Results are tools for planning or interpreting exploration programs used in site investigation or characterization, remedial design, construction, or compliance monitoring, including site closure. Used skillfully and creatively, these tools can help streamline and expedite environmental restoration, reducing time and cost, making site exploration cost-effective, and providing acceptable risk at minimum cost. 14 refs., 4 figs

  15. An improved computing method for the image edge detection

    Institute of Scientific and Technical Information of China (English)

    Gang Wang; Liang Xiao; Anzhi He

    2007-01-01

    The framework of detecting the image edge based on the sub-pixel multi-fractal measure (SPMM) is presented. The measure is defined, which gives the sub-pixel local distribution of the image gradient. The more precise singularity exponent of every pixel can be obtained by performing the SPMM analysis on the image. Using the singularity exponents and the multi-fractal spectrum of the image, the image can be segmented into a series of sets with different singularity exponents, thus the image edge can be detected automatically and easily. The simulation results show that the SPMM has higher quality factor in the image edge detection.

  16. 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.

  17. 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. 

  18. Target vessel detection by epicardial ultrasound in off-pump coronary bypass surgery.

    Science.gov (United States)

    Hayakawa, Masato; Asai, Tohru; Kinoshita, Takeshi; Suzuki, Tomoaki; Shiraishi, Shoichiro

    2013-01-01

    The detection of embedded coronary arteries is difficult especially in off-pump coronary bypass surgery. From June 2010, we introduced high-frequency epicardial ultrasound (ECUS) to assess and evaluate embedded arteries during off-pump coronary bypass surgery. Between June 2010 and June 2011, a total of 89 consecutive patients underwent isolated coronary bypass surgery at our institution. The patients consisted of 72 men and 17 women with a mean age of 67.9 years. We routinely use the VeriQC system (MediStim, Oslo, Norway) to detect the target vessels in the operation. The patients were assigned to one of two groups, depending on whether ECUS was used in the operation (n = 10, ECUS group) or not (n = 79, non-ECUS group). We analyzed the impact of introducing the ECUS in terms of operative outcome. All patients underwent revascularization using the off-pump technique without emergent conversion to cardiopulmonary bypass during surgery. The total number of distal anastomoses was 299, and 12 target vessels could not be identified either visually or on palpation. Thus, the frequency of the embedded coronary arteries was 4.01% (12/299 cases). The preoperative profiles of the two groups were not significantly different. Operation time was significantly longer in the ECUS group (P = 0.02). There were no significant differences in postoperative outcome between the two groups. In the present study, in which the target coronary arteries could not be detected either visually or on palpation in 12 (4.01%) of 299 cases, the use of high-frequency ECUS allowed all patients to undergo off-pump coronary bypass surgery without conversion to cardiopulmonary bypass during the operation. High-frequency ECUS is therefore useful in off-pump coronary bypass surgery.

  19. Detection of Accelerating Targets in Clutter Using a De-Chirping Technique

    Science.gov (United States)

    2014-06-01

    Cubic Phase Functions By definition the Wigner -Ville distribution, W , of a signal x(n) can be written generally as W (n, ω) = ∑ m x(n+m/2)x∗(n−m/2)e−jωm...which is known as the Radon- Wigner transform (RWT), as discussed by Wood [3] and Lohmann [16]. Similarly, the Ambiguity Function , AF, for the signal...the integrated cubic phase functions , at least in the case of single target detection with the linear fre- quency modulated (LFM) waveform. This is

  20. Detection method of elastic scattering in the Coulomb interference region: scintillation target

    International Nuclear Information System (INIS)

    Azaiez, Hamza.

    1981-01-01

    Measurement of polarization in (p-p) elastic scattering in the Coulomb interference region is considered as a valid method for calibrating high energy polarized proton beams. Possibility of using a scintillation target to detect low energy recoil protons in this /t/ region has been studied by using a 4 GeV/c π - beam from CERN PS. The results obtained with a steack of thin plastic scintillators, each 1 mm thick, showed the feasibility of detecting recoil protons in a /t/ range as low a 5.10 -3 (GeV/c) 2 . This method thus confirmed experimentally can be used also to measure, using a polarized beam, polarization in Coulomb interference region [fr

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2018-05-01

    Abstract. 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-TIMSCID- 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

  2. Infrared maritime target detection using a probabilistic single Gaussian model of sea clutter in Fourier domain

    Science.gov (United States)

    Zhou, Anran; Xie, Weixin; Pei, Jihong; Chen, Yapei

    2018-02-01

    For ship targets detection in cluttered infrared image sequences, a robust detection method, based on the probabilistic single Gaussian model of sea background in Fourier domain, is put forward. The amplitude spectrum sequences at each frequency point of the pure seawater images in Fourier domain, being more stable than the gray value sequences of each background pixel in the spatial domain, are regarded as a Gaussian model. Next, a probability weighted matrix is built based on the stability of the pure seawater's total energy spectrum in the row direction, to make the Gaussian model more accurate. Then, the foreground frequency points are separated from the background frequency points by the model. Finally, the false-alarm points are removed utilizing ships' shape features. The performance of the proposed method is tested by visual and quantitative comparisons with others.

  3. Harmonic pulsed excitation and motion detection of a vibrating reflective target.

    Science.gov (United States)

    Urban, Matthew W; Greenleaf, James F

    2008-01-01

    Elasticity imaging is an emerging medical imaging modality. Methods involving acoustic radiation force excitation and pulse-echo ultrasound motion detection have been investigated to assess the mechanical response of tissue. In this work new methods for dynamic radiation force excitation and motion detection are presented. The theory and model for harmonic motion detection of a vibrating reflective target are presented. The model incorporates processing of radio frequency data acquired using pulse-echo ultrasound to measure harmonic motion with amplitudes ranging from 100 to 10,000 nm. A numerical study was performed to assess the effects of different parameters on the accuracy and precision of displacement amplitude and phase estimation and showed how estimation errors could be minimized. Harmonic pulsed excitation is introduced as a multifrequency radiation force excitation method that utilizes ultrasound tonebursts repeated at a rate f(r). The radiation force, consisting of frequency components at multiples of f(r), is generated using 3.0 MHz ultrasound, and motion detection is performed simultaneously with 9.0 MHz pulse-echo ultrasound. A parameterized experimental analysis showed that displacement can be measured with small errors for motion with amplitudes as low as 100 nm. The parameterized numerical and experimental analyses provide insight into how to optimize acquisition parameters to minimize measurement errors.

  4. 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

  5. A Robust Subpixel Motion Estimation Algorithm Using HOS in the Parametric Domain

    Directory of Open Access Journals (Sweden)

    Ibn-Elhaj E

    2009-01-01

    Full Text Available Motion estimation techniques are widely used in todays video processing systems. The most frequently used techniques are the optical flow method and phase correlation method. The vast majority of these algorithms consider noise-free data. Thus, in the case of the image sequences are severely corrupted by additive Gaussian (perhaps non-Gaussian noises of unknown covariance, the classical techniques will fail to work because they will also estimate the noise spatial correlation. In this paper, we have studied this topic from a viewpoint different from the above to explore the fundamental limits in image motion estimation. Our scheme is based on subpixel motion estimation algorithm using bispectrum in the parametric domain. The motion vector of a moving object is estimated by solving linear equations involving third-order hologram and the matrix containing Dirac delta function. Simulation results are presented and compared to the optical flow and phase correlation algorithms; this approach provides more reliable displacement estimates particularly for complex noisy image sequences. In our simulation, we used the database freely available on the web.

  6. A Robust Subpixel Motion Estimation Algorithm Using HOS in the Parametric Domain

    Directory of Open Access Journals (Sweden)

    E. M. Ismaili Aalaoui

    2009-02-01

    Full Text Available Motion estimation techniques are widely used in todays video processing systems. The most frequently used techniques are the optical flow method and phase correlation method. The vast majority of these algorithms consider noise-free data. Thus, in the case of the image sequences are severely corrupted by additive Gaussian (perhaps non-Gaussian noises of unknown covariance, the classical techniques will fail to work because they will also estimate the noise spatial correlation. In this paper, we have studied this topic from a viewpoint different from the above to explore the fundamental limits in image motion estimation. Our scheme is based on subpixel motion estimation algorithm using bispectrum in the parametric domain. The motion vector of a moving object is estimated by solving linear equations involving third-order hologram and the matrix containing Dirac delta function. Simulation results are presented and compared to the optical flow and phase correlation algorithms; this approach provides more reliable displacement estimates particularly for complex noisy image sequences. In our simulation, we used the database freely available on the web.

  7. Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

    Science.gov (United States)

    Ganguly, S.; Kumar, U.; Nemani, R. R.; Kalia, S.; Michaelis, A.

    2017-12-01

    In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS - national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91% was achieved, which is a 6% improvement in unmixing based classification relative to per-pixel based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

  8. 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.

  9. 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.

  10. Workflow for the Targeted and Untargeted Detection of Small Metabolites in Fish Skin Mucus

    Directory of Open Access Journals (Sweden)

    Lada Ivanova

    2018-06-01

    Full Text Available The skin mucus of fish is in permanent contact with the aquatic environment. Data from the analysis of the chemical composition of skin mucus could potentially be used for monitoring the health status of the fish. Knowledge about mucus composition or change in composition over time could also contribute to understanding the aetiology of certain diseases. The objective of the present study was the development of a workflow for non-invasive sampling of skin mucus from farmed salmon (Salmo salar for the targeted and untargeted detection of small metabolites. Skin mucus was either scraped off, wiped off using medical wipes, or the mucus’ water phase was absorbed using the same type of medical wipes that was used for the wiping method. Following a simple filtration step, the obtained mucus samples were subjected to hydrophilic interaction chromatography coupled to high-resolution mass spectrometry. Post-acquisition processing included the targeted analysis of 86 small metabolites, of which up to 60 were detected in absorbed mucus. Untargeted analysis of the mucus samples from equally treated salmon revealed that the total variation of the metabolome was lowest in absorbed mucus and highest in the scraped mucus. Thus, future studies including small-molecule metabolomics of skin mucus in fish would benefit from a sampling regime employing absorption of the water phase in order to minimize the bias related to the sampling step. Furthermore, the absorption method is also a less invasive approach allowing for repetitive sampling within short time intervals.

  11. REVISED STELLAR PROPERTIES OF KEPLER TARGETS FOR THE QUARTER 1-16 TRANSIT DETECTION RUN

    Energy Technology Data Exchange (ETDEWEB)

    Huber, Daniel [NASA Ames Research Center, Moffett Field, CA 94035 (United States); Aguirre, Victor Silva [Stellar Astrophysics Centre, Department of Physics and Astronomy, Aarhus University, Ny Munkegade 120, DK-8000 Aarhus C (Denmark); Matthews, Jaymie M. [Department of Physics and Astronomy, University of British Columbia, Vancouver (Canada); Pinsonneault, Marc H. [Department of Astronomy, Ohio State University, OH 43210 (United States); Gaidos, Eric [Department of Geology and Geophysics, University of Hawaii at Manoa, Honolulu, HI 96822 (United States); García, Rafael A. [Laboratoire AIM, CEA/DSM-CNRS, Université Paris 7 Diderot, IRFU/SAp, Centre de Saclay, F-91191 Gif-sur-Yvette (France); Hekker, Saskia [Max-Planck-Institut für Sonnensystemforschung, Justus-von-Liebig-Weg 3, D-37077 Göttingen (Germany); Mathur, Savita [Space Science Institute, 4750 Walnut Street, Suite 205, Boulder, CO 80301 (United States); Mosser, Benoit [LESIA, CNRS, Université Pierre et Marie Curie, Université Denis, Diderot, Observatoire de Paris, F-92195 Meudon cedex (France); Torres, Guillermo [Harvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138 (United States); Bastien, Fabienne A. [Department of Physics and Astronomy, Vanderbilt University, 1807 Station B, Nashville, TN 37235 (United States); Basu, Sarbani [Department of Astronomy, Yale University, New Haven, CT 06511 (United States); Bedding, Timothy R. [Sydney Institute for Astronomy (SIfA), School of Physics, University of Sydney, NSW 2006 (Australia); Chaplin, William J. [School of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT (United Kingdom); Demory, Brice-Olivier [Department of Physics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 (United States); Fleming, Scott W., E-mail: daniel.huber@nasa.gov [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); and others

    2014-03-01

    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 gravity, and metallicity) derived from different observational techniques (photometry, spectroscopy, asteroseismology, and exoplanet transits), which were then homogeneously fitted to a grid of Dartmouth stellar isochrones. We use broadband photometry and asteroseismology to characterize 11,532 Kepler targets which were previously unclassified in the Kepler Input Catalog (KIC). We report the detection of oscillations in 2762 of these targets, classifying them as giant stars and increasing the number of known oscillating giant stars observed by Kepler by ∼20% to a total of ∼15,500 stars. Typical uncertainties in derived radii and masses are ∼40% and ∼20%, respectively, for stars with photometric constraints only, and 5%-15% and ∼10% for stars based on spectroscopy and/or asteroseismology, although these uncertainties vary strongly with spectral type and luminosity class. A comparison with the Q1-Q12 catalog shows a systematic decrease in radii of M dwarfs, while radii for K dwarfs decrease or increase depending on the Q1-Q12 provenance (KIC or Yonsei-Yale isochrones). Radii of F-G dwarfs are on average unchanged, with the exception of newly identified giants. The Q1-Q16 star properties catalog is a first step toward an improved characterization of all Kepler targets to support planet-occurrence studies.

  12. 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

  13. Time reversal optical tomography and decomposition methods for detection and localization of targets in highly scattering turbid media

    Science.gov (United States)

    Wu, Binlin

    New near-infrared (NIR) diffuse optical tomography (DOT) approaches were developed to detect, locate, and image small targets embedded in highly scattering turbid media. The first approach, referred to as time reversal optical tomography (TROT), is based on time reversal (TR) imaging and multiple signal classification (MUSIC). The second approach uses decomposition methods of non-negative matrix factorization (NMF) and principal component analysis (PCA) commonly used in blind source separation (BSS) problems, and compare the outcomes with that of optical imaging using independent component analysis (OPTICA). The goal is to develop a safe, affordable, noninvasive imaging modality for detection and characterization of breast tumors in early growth stages when those are more amenable to treatment. The efficacy of the approaches was tested using simulated data, and experiments involving model media and absorptive, scattering, and fluorescent targets, as well as, "realistic human breast model" composed of ex vivo breast tissues with embedded tumors. The experimental arrangements realized continuous wave (CW) multi-source probing of samples and multi-detector acquisition of diffusely transmitted signal in rectangular slab geometry. A data matrix was generated using the perturbation in the transmitted light intensity distribution due to the presence of absorptive or scattering targets. For fluorescent targets the data matrix was generated using the diffusely transmitted fluorescence signal distribution from the targets. The data matrix was analyzed using different approaches to detect and characterize the targets. The salient features of the approaches include ability to: (a) detect small targets; (b) provide three-dimensional location of the targets with high accuracy (~within a millimeter or 2); and (c) assess optical strength of the targets. The approaches are less computation intensive and consequently are faster than other inverse image reconstruction methods that

  14. 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.

  15. Wildlife detection dog training: A case study on achieving generalization between target odor variations while retaining specificity

    NARCIS (Netherlands)

    Oldenburg, Cor; Schoon, Adee; Heitkönig, I.M.A.

    2016-01-01

    Wildlife detection dogs are required to correctly discriminate target wildlife species odor from nontarget
    species odors (specificity), while enabling some degree of target odor variation (generality). Because
    there is no standardized training protocol, and little knowledge on training

  16. 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.

  17. 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.

  18. Permafrost-An alternative target material for ultra-high energy neutrino detection?

    International Nuclear Information System (INIS)

    Nahnhauer, R.; Rostovtsev, A.A.; Tosi, D.

    2008-01-01

    The interest in the detection of cosmic neutrinos with energies above 10 17 eV has increased considerably in recent years. Possible target materials for in-matter arrays of ∼100 km 3 size under discussion are water, ice and rock salt. Here we propose to investigate permafrost as an additional alternative, covering ∼20% of Earth land surface and reaching down to more than 1000 m depth at certain locations. If sufficiently large attenuation lengths for radio and acoustic signals can be demonstrated by in-situ measurements, the construction of a large hybrid array within this material may be possible in the Northern Hemisphere. Properties and problems of a possible location in Siberia are discussed below. Some acoustic data are compared with laboratory measurements using 'artificial' permafrost

  19. Detecting and Georegistering Moving Ground Targets in Airborne QuickSAR via Keystoning and Multiple-Phase Center Interferometry

    Directory of Open Access Journals (Sweden)

    R. P. Perry

    2008-03-01

    Full Text Available SAR images experience significant range walk and, without some form of motion compensation, can be quite blurred. The MITRE-developed Keystone formatting simultaneously and automatically compensates for range walk due to the radial velocity component of each moving target, independent of the number of targets or the value of each target's radial velocity with respect to the ground. Target radial motion also causes moving targets in synthetic aperture radar images to appear at locations offset from their true instantaneous locations on the ground. In a multichannel radar, the interferometric phase values associated with all nonmoving points on the ground appear as a continuum of phase differences while the moving targets appear as interferometric phase discontinuities. By multiple threshold comparisons and grouping of pixels within the intensity and the phase images, we show that it is possible to reliably detect and accurately georegister moving targets within short-duration SAR (QuickSAR images.

  20. SUPERPIXEL BASED FACTOR ANALYSIS AND TARGET TRANSFORMATION METHOD FOR MARTIAN MINERALS DETECTION

    Directory of Open Access Journals (Sweden)

    X. Wu

    2018-04-01

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

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    Fabio Baselice

    2016-04-01

    Full Text Available 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.

  3. Correction of sub-pixel topographical effects on land surface albedo retrieved from geostationary satellite (FengYun-2D) observations

    International Nuclear Information System (INIS)

    Roupioz, L; Nerry, F; Jia, L; Menenti, M

    2014-01-01

    The Qinghai-Tibetan Plateau is characterised by a very strong relief which affects albedo retrieval from satellite data. The objective of this study is to highlight the effects of sub-pixel topography and to account for those effects when retrieving land surface albedo from geostationary satellite FengYun-2D (FY-2D) data with 1.25km spatial resolution using the high spatial resolution (30 m) data of the Digital Elevation Model (DEM) from ASTER. The methodology integrates the effects of sub-pixel topography on the estimation of the total irradiance received at the surface, allowing the computation of the topographically corrected surface reflectance. Furthermore, surface albedo is estimated by applying the parametric BRDF (Bidirectional Reflectance Distribution Function) model called RPV (Rahman-Pinty-Verstraete) to the terrain corrected surface reflectance. The results, evaluated against ground measurements collected over several experimental sites on the Qinghai-Tibetan Plateau, document the advantage of integrating the sub-pixel topography effects in the land surface reflectance at 1km resolution to estimate the land surface albedo. The results obtained after using sub-pixel topographic correction are compared with the ones obtained after using pixel level topographic correction. The preliminary results imply that, in highly rugged terrain, the sub-pixel topography correction method gives more accurate results. The pixel level correction tends to overestimate surface albedo

  4. Landform classification using a sub-pixel spatial attraction model to increase spatial resolution of digital elevation model (DEM

    Directory of Open Access Journals (Sweden)

    Marzieh Mokarrama

    2018-04-01

    Full Text Available The purpose of the present study is preparing a landform classification by using digital elevation model (DEM which has a high spatial resolution. To reach the mentioned aim, a sub-pixel spatial attraction model was used as a novel method for preparing DEM with a high spatial resolution in the north of Darab, Fars province, Iran. The sub-pixel attraction models convert the pixel into sub-pixels based on the neighboring pixels fraction values, which can only be attracted by a central pixel. Based on this approach, a mere maximum of eight neighboring pixels can be selected for calculating of the attraction value. In the mentioned model, other pixels are supposed to be far from the central pixel to receive any attraction. In the present study by using a sub-pixel attraction model, the spatial resolution of a DEM was increased. The design of the algorithm is accomplished by using a DEM with a spatial resolution of 30 m (the Advanced Space borne Thermal Emission and Reflection Radiometer; (ASTER and a 90 m (the Shuttle Radar Topography Mission; (SRTM. In the attraction model, scale factors of (S = 2, S = 3, and S = 4 with two neighboring methods of touching (T = 1 and quadrant (T = 2 are applied to the DEMs by using MATLAB software. The algorithm is evaluated by taking the best advantages of 487 sample points, which are measured by surveyors. The spatial attraction model with scale factor of (S = 2 gives better results compared to those scale factors which are greater than 2. Besides, the touching neighborhood method is turned to be more accurate than the quadrant method. In fact, dividing each pixel into more than two sub-pixels decreases the accuracy of the resulted DEM. On the other hand, in these cases DEM, is itself in charge of increasing the value of root-mean-square error (RMSE and shows that attraction models could not be used for S which is greater than 2. Thus considering results, the proposed model is highly capable of

  5. A Tumor-Targeted Nanodelivery System to Improve Early MRI Detection of Cancer

    Directory of Open Access Journals (Sweden)

    Kathleen F. Pirollo

    2006-01-01

    Full Text Available The development of improvements in magnetic resonance imaging (MRI that would enhance sensitivity, leading to earlier detection of cancer and visualization of metastatic disease, is an area of intense exploration. We have devised a tumor-targeting, liposomal nanodelivery platform for use in gene medicine. This systemically administered nanocomplex has been shown to specifically and efficiently deliver both genes and oligonucleotides to primary and metastatic tumor cells, resulting in significant tumor growth inhibition and even tumor regression. Here we examine the effect on MRI of incorporating conventional MRI contrast agent Magnevist® into our anti-transferrin receptor single-chain antibody (TfRscFv liposomal complex. Both in vitro and in an in vivo orthotopic mouse model of pancreatic cancer, we show increased resolution and image intensity with the complexed Magnevist®. Using advanced microscopy techniques (scanning electron microscopy and scanning probe microscopy, we also established that the Magnevist® is in fact encapsulated by the liposome in the complex and that the complex still retains its nanodimensional size. These results demonstrate that this TfRscFv-liposome-Magnevist® nanocomplex has the potential to become a useful tool in early cancer detection.

  6. Improved Deep Belief Networks (IDBN Dynamic Model-Based Detection and Mitigation for Targeted Attacks on Heavy-Duty Robots

    Directory of Open Access Journals (Sweden)

    Lianpeng Li

    2018-04-01

    Full Text Available In recent years, the robots, especially heavy-duty robots, have become the hardest-hit areas for targeted attacks. These attacks come from both the cyber-domain and the physical-domain. In order to improve the security of heavy-duty robots, this paper proposes a detection and mitigation mechanism which based on improved deep belief networks (IDBN and dynamic model. The detection mechanism consists of two parts: (1 IDBN security checks, which can detect targeted attacks from the cyber-domain; (2 Dynamic model and security detection, used to detect the targeted attacks which can possibly lead to a physical-domain damage. The mitigation mechanism was established on the base of the detection mechanism and could mitigate transient and discontinuous attacks. Moreover, a test platform was established to carry out the performance evaluation test for the proposed mechanism. The results show that, the detection accuracy for the attack of the cyber-domain of IDBN reaches 96.2%, and the detection accuracy for the attack of physical-domain control commands reaches 94%. The performance evaluation test has verified the reliability and high efficiency of the proposed detection and mitigation mechanism for heavy-duty robots.

  7. 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

  8. Integrated detection, estimation, and guidance in pursuit of a maneuvering target

    Science.gov (United States)

    Dionne, Dany

    The thesis focuses on efficient solutions of non-cooperative pursuit-evasion games with imperfect information on the state of the system. This problem is important in the context of interception of future maneuverable ballistic missiles. However, the theoretical developments are expected to find application to a broad class of hybrid control and estimation problems in industry. The validity of the results is nevertheless confirmed using a benchmark problem in the area of terminal guidance. A specific interception scenario between an incoming target with no information and a single interceptor missile with noisy measurements is analyzed in the form of a linear hybrid system subject to additive abrupt changes. The general research is aimed to achieve improved homing accuracy by integrating ideas from detection theory, state estimation theory and guidance. The results achieved can be summarized as follows. (i) Two novel maneuver detectors are developed to diagnose abrupt changes in a class of hybrid systems (detection and isolation of evasive maneuvers): a new implementation of the GLR detector and the novel adaptive- H0 GLR detector. (ii) Two novel state estimators for target tracking are derived using the novel maneuver detectors. The state estimators employ parameterized family of functions to described possible evasive maneuvers. (iii) A novel adaptive Bayesian multiple model predictor of the ballistic miss is developed which employs semi-Markov models and ideas from detection theory. (iv) A novel integrated estimation and guidance scheme that significantly improves the homing accuracy is also presented. The integrated scheme employs banks of estimators and guidance laws, a maneuver detector, and an on-line governor; the scheme is adaptive with respect to the uncertainty affecting the probability density function of the filtered state. (v) A novel discretization technique for the family of continuous-time, game theoretic, bang-bang guidance laws is introduced. The

  9. Twin target self-amplification-based DNA machine for highly sensitive detection of cancer-related gene.

    Science.gov (United States)

    Xu, Huo; Jiang, Yifan; Liu, Dengyou; Liu, Kai; Zhang, Yafeng; Yu, Suhong; Shen, Zhifa; Wu, Zai-Sheng

    2018-06-29

    The sensitive detection of cancer-related genes is of great significance for early diagnosis and treatment of human cancers, and previous isothermal amplification sensing systems were often based on the reuse of target DNA, the amplification of enzymatic products and the accumulation of reporting probes. However, no reporting probes are able to be transformed into target species and in turn initiate the signal of other probes. Herein we reported a simple, isothermal and highly sensitive homogeneous assay system for tumor suppressor p53 gene detection based on a new autonomous DNA machine, where the signaling probe, molecular beacon (MB), was able to execute the function similar to target DNA besides providing the common signal. In the presence of target p53 gene, the operation of DNA machine can be initiated, and cyclical nucleic acid strand-displacement polymerization (CNDP) and nicking/polymerization cyclical amplification (NPCA) occur, during which the MB was opened by target species and cleaved by restriction endonuclease. In turn, the cleaved fragments could activate the next signaling process as target DNA did. According to the functional similarity, the cleaved fragment was called twin target, and the corresponding fashion to amplify the signal was named twin target self-amplification. Utilizing this newly-proposed DNA machine, the target DNA could be detected down to 0.1 pM with a wide dynamic range (6 orders of magnitude) and single-base mismatched targets were discriminated, indicating a very high assay sensitivity and good specificity. In addition, the DNA machine was not only used to screen the p53 gene in complex biological matrix but also was capable of practically detecting genomic DNA p53 extracted from A549 cell line. This indicates that the proposed DNA machine holds the potential application in biomedical research and early clinical diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.

  10. Claudin-4-targeted optical imaging detects pancreatic cancer and its precursor lesions.

    Science.gov (United States)

    Neesse, Albrecht; Hahnenkamp, Anke; Griesmann, Heidi; Buchholz, Malte; Hahn, Stefan A; Maghnouj, Abdelouahid; Fendrich, Volker; Ring, Janine; Sipos, Bence; Tuveson, David A; Bremer, Christoph; Gress, Thomas M; Michl, Patrick

    2013-07-01

    Novel imaging methods based on specific molecular targets to detect both established neoplasms and their precursor lesions are highly desirable in cancer medicine. Previously, we identified claudin-4, an integral constituent of tight junctions, as highly expressed in various gastrointestinal tumours including pancreatic cancer. Here, we investigate the potential of targeting claudin-4 with a naturally occurring ligand to visualise pancreatic cancer and its precursor lesions in vitro and in vivo by near-infrared imaging approaches. A non-toxic C-terminal fragment of the claudin-4 ligand Clostridium perfringens enterotoxin (C-CPE) was labelled with a cyanine dye (Cy5.5). Binding of the optical tracer was analysed on claudin-4 positive and negative cells in vitro, and tumour xenografts in vivo. In addition, two genetically engineered mouse models for pancreatic intraepithelial neoplasia (PanIN) and pancreatic cancer were used for in vivo validation. Optical imaging studies were conducted using 2D planar fluorescence reflectance imaging (FRI) technology and 3D fluorescence-mediated tomography (FMT). In vitro, the peptide-dye conjugate showed high binding affinity to claudin-4 positive CAPAN1 cells, while claudin-4 negative HT1080 cells revealed little or no fluorescence. In vivo, claudin-4 positive tumour xenografts, endogenous pancreatic tumours, hepatic metastases, as well as preinvasive PanIN lesions, were visualised by FRI and FMT up to 48 h after injection showing a significantly higher average of fluorochrome concentration as compared with claudin-4 negative xenografts and normal pancreatic tissue. C-CPE-Cy5.5 combined with novel optical imaging methods enables non-invasive visualisation of claudin-4 positive murine pancreatic tumours and their precursor lesions, representing a promising modality for early diagnostic imaging.

  11. Efficacy of Exome-Targeted Capture Sequencing to Detect Mutations in Known Cerebellar Ataxia Genes.

    Science.gov (United States)

    Coutelier, Marie; Hammer, Monia B; Stevanin, Giovanni; Monin, Marie-Lorraine; Davoine, Claire-Sophie; Mochel, Fanny; Labauge, Pierre; Ewenczyk, Claire; Ding, Jinhui; Gibbs, J Raphael; Hannequin, Didier; Melki, Judith; Toutain, Annick; Laugel, Vincent; Forlani, Sylvie; Charles, Perrine; Broussolle, Emmanuel; Thobois, Stéphane; Afenjar, Alexandra; Anheim, Mathieu; Calvas, Patrick; Castelnovo, Giovanni; de Broucker, Thomas; Vidailhet, Marie; Moulignier, Antoine; Ghnassia, Robert T; Tallaksen, Chantal; Mignot, Cyril; Goizet, Cyril; Le Ber, Isabelle; Ollagnon-Roman, Elisabeth; Pouget, Jean; Brice, Alexis; Singleton, Andrew; Durr, Alexandra

    2018-05-01

    Molecular diagnosis is difficult to achieve in disease groups with a highly heterogeneous genetic background, such as cerebellar ataxia (CA). In many patients, candidate gene sequencing or focused resequencing arrays do not allow investigators to reach a genetic conclusion. To assess the efficacy of exome-targeted capture sequencing to detect mutations in genes broadly linked to CA in a large cohort of undiagnosed patients and to investigate their prevalence. Three hundred nineteen index patients with CA and without a history of dominant transmission were included in the this cohort study by the Spastic Paraplegia and Ataxia Network. Centralized storage was in the DNA and cell bank of the Brain and Spine Institute, Salpetriere Hospital, Paris, France. Patients were classified into 6 clinical groups, with the largest being those with spastic ataxia (ie, CA with pyramidal signs [n = 100]). Sequencing was performed from January 1, 2014, through December 31, 2016. Detected variants were classified as very probably or definitely causative, possibly causative, or of unknown significance based on genetic evidence and genotype-phenotype considerations. Identification of variants in genes broadly linked to CA, classified in pathogenicity groups. The 319 included patients had equal sex distribution (160 female [50.2%] and 159 male patients [49.8%]; mean [SD] age at onset, 27.9 [18.6] years). The age at onset was younger than 25 years for 131 of 298 patients (44.0%) with complete clinical information. Consanguinity was present in 101 of 298 (33.9%). Very probable or definite diagnoses were achieved for 72 patients (22.6%), with an additional 19 (6.0%) harboring possibly pathogenic variants. The most frequently mutated genes were SPG7 (n = 14), SACS (n = 8), SETX (n = 7), SYNE1 (n = 6), and CACNA1A (n = 6). The highest diagnostic rate was obtained for patients with an autosomal recessive CA with oculomotor apraxia-like phenotype (6 of 17 [35.3%]) or

  12. Targeted Screening With Combined Age- and Morphology-Based Criteria Enriches Detection of Lynch Syndrome in Endometrial Cancer.

    Science.gov (United States)

    Lin, Douglas I; Hecht, Jonathan L

    2016-06-01

    Endometrial cancer is associated with Lynch syndrome in 2% to 6% of cases. Adequate screening may prevent of a second cancer and incident cancers in family members via risk-reducing strategies. The goal of the study was to evaluate the detection rate of Lynch syndrome via a targeted screening approach. In 2009, we incorporated targeted Lynch syndrome screening via immunohistochemistry for MLH1, PMS2, MSH2, and MSH6, followed by MLH1 promoter hypermethylation, in select cases of endometrial carcinoma. Criteria for patient selection included (1) all patients Lynch syndrome. Therefore, targeted screening with combined age and morphology based criteria enriches detection of Lynch syndrome in endometrial cancer. However, the detection rate is lower than the rates from published series that offer universal screening. © The Author(s) 2016.

  13. 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.

  14. A false-alarm aware methodology to develop robust and efficient multi-scale infrared small target detection algorithm

    Science.gov (United States)

    Moradi, Saed; Moallem, Payman; Sabahi, Mohamad Farzan

    2018-03-01

    False alarm rate and detection rate are still two contradictory metrics for infrared small target detection in an infrared search and track system (IRST), despite the development of new detection algorithms. In certain circumstances, not detecting true targets is more tolerable than detecting false items as true targets. Hence, considering background clutter and detector noise as the sources of the false alarm in an IRST system, in this paper, a false alarm aware methodology is presented to reduce false alarm rate while the detection rate remains undegraded. To this end, advantages and disadvantages of each detection algorithm are investigated and the sources of the false alarms are determined. Two target detection algorithms having independent false alarm sources are chosen in a way that the disadvantages of the one algorithm can be compensated by the advantages of the other one. In this work, multi-scale average absolute gray difference (AAGD) and Laplacian of point spread function (LoPSF) are utilized as the cornerstones of the desired algorithm of the proposed methodology. After presenting a conceptual model for the desired algorithm, it is implemented through the most straightforward mechanism. The desired algorithm effectively suppresses background clutter and eliminates detector noise. Also, since the input images are processed through just four different scales, the desired algorithm has good capability for real-time implementation. Simulation results in term of signal to clutter ratio and background suppression factor on real and simulated images prove the effectiveness and the performance of the proposed methodology. Since the desired algorithm was developed based on independent false alarm sources, our proposed methodology is expandable to any pair of detection algorithms which have different false alarm sources.

  15. Evaluation of the Use of Sub-Pixel Offset Tracking Techniques to Monitor Landslides in Densely Vegetated Steeply Sloped Areas

    Directory of Open Access Journals (Sweden)

    Luyi Sun

    2016-08-01

    Full Text Available Sub-Pixel Offset Tracking (sPOT is applied to derive high-resolution centimetre-level landslide rates in the Three Gorges Region of China using TerraSAR-X Hi-resolution Spotlight (TSX HS space-borne SAR images. These results contrast sharply with previous use of conventional differential Interferometric Synthetic Aperture Radar (DInSAR techniques in areas with steep slopes, dense vegetation and large variability in water vapour which indicated around 12% phase coherent coverage. By contrast, sPOT is capable of measuring two dimensional deformation of large gradient over steeply sloped areas covered in dense vegetation. Previous applications of sPOT in this region relies on corner reflectors (CRs, (high coherence features to obtain reliable measurements. However, CRs are expensive and difficult to install, especially in remote areas; and other potential high coherence features comparable with CRs are very few and outside the landslide boundary. The resultant sub-pixel level deformation field can be statistically analysed to yield multi-modal maps of deformation regions. This approach is shown to have a significant impact when compared with previous offset tracking measurements of landslide deformation, as it is demonstrated that sPOT can be applied even in densely vegetated terrain without relying on high-contrast surface features or requiring any de-noising process.

  16. 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.

  17. 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.

  18. Detection of low-energy antinuclei in space using an active-target particle detector

    Energy Technology Data Exchange (ETDEWEB)

    Poeschl, Thomas; Greenwald, Daniel; Konorov, Igor; Paul, Stephan [Physics Department E18, Technische Universitaet Muenchen (Germany); Losekamm, Martin [Physics Department E18, Technische Universitaet Muenchen (Germany); Institute of Astronautics, Technische Universitaet Muenchen (Germany)

    2015-07-01

    Measuring antimatter in space excellently probes various astrophysical processes. The abundances and energy spectra of antiparticles reveal a lot about the creation and propagation of cosmic-ray particles in the universe. Abnormalities in their spectra can reveal exotic sources or inaccuracies in our understanding of the involved processes. The measurement of antiprotons and the search for antideuterons and antihelium are optimal at low kinetic energies since background from high-energy cosmic-ray collisions is low. For this reason, we are developing an active-target particle detector capable of detecting ions and anti-ions in the energy range of 30-100 MeV per nucleon. The detector consists of 900 scintillating fibers coupled to silicon photomultipliers and is designed to operate on nanosatellites. The primary application of the detector will be the Antiproton Flux in Space (AFIS) mission, whose goal is the measurement of geomagnetically trapped antiprotons inside Earth's inner radiation belt. In this talk, we explain our particle identification technique and present results from first in-beam measurements with a prototype.

  19. Research on the development of space target detecting system and three-dimensional reconstruction technology

    Science.gov (United States)

    Li, Dong; Wei, Zhen; Song, Dawei; Sun, Wenfeng; Fan, Xiaoyan

    2016-11-01

    With the development of space technology, the number of spacecrafts and debris are increasing year by year. The demand for detecting and identification of spacecraft is growing strongly, which provides support to the cataloguing, crash warning and protection of aerospace vehicles. The majority of existing approaches for three-dimensional reconstruction is scattering centres correlation, which is based on the radar high resolution range profile (HRRP). This paper proposes a novel method to reconstruct the threedimensional scattering centre structure of target from a sequence of radar ISAR images, which mainly consists of three steps. First is the azimuth scaling of consecutive ISAR images based on fractional Fourier transform (FrFT). The later is the extraction of scattering centres and matching between adjacent ISAR images using grid method. Finally, according to the coordinate matrix of scattering centres, the three-dimensional scattering centre structure is reconstructed using improved factorization method. The three-dimensional structure is featured with stable and intuitive characteristic, which provides a new way to improve the identification probability and reduce the complexity of the model matching library. A satellite model is reconstructed using the proposed method from four consecutive ISAR images. The simulation results prove that the method has gotten a satisfied consistency and accuracy.

  20. Target-Specific Assay for Rapid and Quantitative Detection of Mycobacterium chimaera DNA.

    Science.gov (United States)

    Zozaya-Valdés, Enrique; Porter, Jessica L; Coventry, John; Fyfe, Janet A M; Carter, Glen P; Gonçalves da Silva, Anders; Schultz, Mark B; Seemann, Torsten; Johnson, Paul D R; Stewardson, Andrew J; Bastian, Ivan; Roberts, Sally A; Howden, Benjamin P; Williamson, Deborah A; Stinear, Timothy P

    2017-06-01

    Mycobacterium chimaera is an opportunistic environmental mycobacterium belonging to the Mycobacterium avium - M. intracellulare complex. Although most commonly associated with pulmonary disease, there has been growing awareness of invasive M. chimaera infections following cardiac surgery. Investigations suggest worldwide spread of a specific M. chimaera clone, associated with contaminated hospital heater-cooler units used during the surgery. Given the global dissemination of this clone, its potential to cause invasive disease, and the laboriousness of current culture-based diagnostic methods, there is a pressing need to develop rapid and accurate diagnostic assays specific for M. chimaera Here, we assessed 354 mycobacterial genome sequences and confirmed that M. chimaera is a phylogenetically coherent group. In silico comparisons indicated six DNA regions present only in M. chimaera We targeted one of these regions and developed a TaqMan quantitative PCR (qPCR) assay for M. chimaera with a detection limit of 100 CFU/ml in whole blood spiked with bacteria. In vitro screening against DNA extracted from 40 other mycobacterial species and 22 bacterial species from 21 diverse genera confirmed the in silico -predicted specificity for M. chimaera Screening 33 water samples from heater-cooler units with this assay highlighted the increased sensitivity of PCR compared to culture, with 15 of 23 culture-negative samples positive by M. chimaera qPCR. We have thus developed a robust molecular assay that can be readily and rapidly deployed to screen clinical and environmental specimens for M. chimaera . Copyright © 2017 American Society for Microbiology.

  1. Developing and evaluating a target-background similarity metric for camouflage detection.

    Directory of Open Access Journals (Sweden)

    Chiuhsiang Joe Lin

    Full Text Available BACKGROUND: Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. METHODOLOGY: In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. SIGNIFICANCE: The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results.

  2. Developing and evaluating a target-background similarity metric for camouflage detection.

    Science.gov (United States)

    Lin, Chiuhsiang Joe; Chang, Chi-Chan; Liu, Bor-Shong

    2014-01-01

    Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI) correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results.

  3. 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.

  4. 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.

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

    Science.gov (United States)

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

    2016-10-27

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

  6. High affinity γPNA sandwich hybridization assay for rapid detection of short nucleic acid targets with single mismatch discrimination.

    Science.gov (United States)

    Goldman, Johnathan M; Zhang, Li Ang; Manna, Arunava; Armitage, Bruce A; Ly, Danith H; Schneider, James W

    2013-07-08

    Hybridization analysis of short DNA and RNA targets presents many challenges for detection. The commonly employed sandwich hybridization approach cannot be implemented for these short targets due to insufficient probe-target binding strengths for unmodified DNA probes. Here, we present a method capable of rapid and stable sandwich hybridization detection for 22 nucleotide DNA and RNA targets. Stable hybridization is achieved using an n-alkylated, polyethylene glycol γ-carbon modified peptide nucleic acid (γPNA) amphiphile. The γPNA's exceptionally high affinity enables stable hybridization of a second DNA-based probe to the remaining bases of the short target. Upon hybridization of both probes, an electrophoretic mobility shift is measured via interaction of the n-alkane modification on the γPNA with capillary electrophoresis running buffer containing nonionic surfactant micelles. We find that sandwich hybridization of both probes is stable under multiple binding configurations and demonstrate single base mismatch discrimination. The binding strength of both probes is also stabilized via coaxial stacking on adjacent hybridization to targets. We conclude with a discussion on the implementation of the proposed sandwich hybridization assay as a high-throughput microRNA detection method.

  7. Characterization of image heterogeneity using 2D Minkowski functionals increases the sensitivity of detection of a targeted MRI contrast agent.

    Science.gov (United States)

    Canuto, Holly C; McLachlan, Charles; Kettunen, Mikko I; Velic, Marko; Krishnan, Anant S; Neves, Andre' A; de Backer, Maaike; Hu, D-E; Hobson, Michael P; Brindle, Kevin M

    2009-05-01

    A targeted Gd(3+)-based contrast agent has been developed that detects tumor cell death by binding to the phosphatidylserine (PS) exposed on the plasma membrane of dying cells. Although this agent has been used to detect tumor cell death in vivo, the differences in signal intensity between treated and untreated tumors was relatively small. As cell death is often spatially heterogeneous within tumors, we investigated whether an image analysis technique that parameterizes heterogeneity could be used to increase the sensitivity of detection of this targeted contrast agent. Two-dimensional (2D) Minkowski functionals (MFs) provided an automated and reliable method for parameterization of image heterogeneity, which does not require prior assumptions about the number of regions or features in the image, and were shown to increase the sensitivity of detection of the contrast agent as compared to simple signal intensity analysis. (c) 2009 Wiley-Liss, Inc.

  8. 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

  9. Universal, colorimetric microRNA detection strategy based on target-catalyzed toehold-mediated strand displacement reaction

    Science.gov (United States)

    Park, Yeonkyung; Lee, Chang Yeol; Kang, Shinyoung; Kim, Hansol; Park, Ki Soo; Park, Hyun Gyu

    2018-02-01

    In this work, we developed a novel, label-free, and enzyme-free strategy for the colorimetric detection of microRNA (miRNA), which relies on a target-catalyzed toehold-mediated strand displacement (TMSD) reaction. The system employs a detection probe that specifically binds to the target miRNA and sequentially releases a catalyst strand (CS) intended to trigger the subsequent TMSD reaction. Thus, the presence of target miRNA releases the CS that mediates the formation of an active G-quadruplex DNAzyme which is initially caged and inactivated by a blocker strand. In addition, a fuel strand that is supplemented for the recycling of the CS promotes another TMSD reaction, consequently generating a large number of active G-quadruplex DNAzymes. As a result, a distinct colorimetric signal is produced by the ABTS oxidation promoted by the peroxidase mimicking activity of the released G-quadruplex DNAzymes. Based on this novel strategy, we successfully detected miR-141, a promising biomarker for human prostate cancer, with high selectivity. The diagnostic capability of this system was also demonstrated by reliably determining target miR-141 in human serum, showing its great potential towards real clinical applications. Importantly, the proposed approach is composed of separate target recognition and signal transduction modules. Thus, it could be extended to analyze different target miRNAs by simply redesigning the detection probe while keeping the same signal transduction module as a universal signal amplification unit, which was successfully demonstrated by analyzing another target miRNA, let-7d.

  10. HaloPlex Targeted Resequencing for Mutation Detection in Clinical Formalin-Fixed, Paraffin-Embedded Tumor Samples.

    Science.gov (United States)

    Moens, Lotte N J; Falk-Sörqvist, Elin; Ljungström, Viktor; Mattsson, Johanna; Sundström, Magnus; La Fleur, Linnéa; Mathot, Lucy; Micke, Patrick; Nilsson, Mats; Botling, Johan

    2015-11-01

    In recent years, the advent of massively parallel next-generation sequencing technologies has enabled substantial advances in the study of human diseases. Combined with targeted DNA enrichment methods, high sequence coverage can be obtained for different genes simultaneously at a reduced cost per sample, creating unique opportunities for clinical cancer diagnostics. However, the formalin-fixed, paraffin-embedded (FFPE) process of tissue samples, routinely used in pathology departments, results in DNA fragmentation and nucleotide modifications that introduce a number of technical challenges for downstream biomolecular analyses. We evaluated the HaloPlex target enrichment system for somatic mutation detection in 80 tissue fractions derived from 20 clinical cancer cases with paired tumor and normal tissue available in both FFPE and fresh-frozen format. Several modifications to the standard method were introduced, including a reduced target fragment length and two strand capturing. We found that FFPE material can be used for HaloPlex-based target enrichment and next-generation sequencing, even when starting from small amounts of DNA. By specifically capturing both strands for each target fragment, we were able to reduce the number of false-positive errors caused by FFPE-induced artifacts and lower the detection limit for somatic mutations. We believe that the HaloPlex method presented here will be broadly applicable as a tool for somatic mutation detection in clinical cancer settings. Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  11. Impact of tDCS on Performance and Learning of Target Detection: Interaction with Stimulus Characteristics and Experimental Design

    Science.gov (United States)

    Coffman, B. A.; Trumbo, M. C.; Flores, R. A.; Garcia, C. M.; van der Merwe, A. J.; Wassermann, E. M.; Weisend, M. P.; Clark, V. P.

    2012-01-01

    We have previously found that transcranial direct current stimulation (tDCS) over right inferior frontal cortex (RIFC) enhances performance during learning of a difficult visual target detection task (Clark et al., 2012). In order to examine the cognitive mechanisms of tDCS that lead to enhanced performance, here we analyzed its differential…

  12. Fast Detection of Compressively Sensed IR Targets Using Stochastically Trained Least Squares and Compressed Quadratic Correlation Filters

    KAUST Repository

    Millikan, Brian; Dutta, Aritra; Sun, Qiyu; Foroosh, Hassan

    2017-01-01

    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.

  13. 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.

  14. Non-target activity detection by post-radioembolization yttrium-90 PET/CT: Image assessment technique and case examples

    Directory of Open Access Journals (Sweden)

    Yung Hsiang eKao

    2014-02-01

    Full Text Available High-resolution yttrium-90 (90Y imaging of post-radioembolization microsphere biodistribution may be achieved by conventional positron emission tomography with integrated computed tomography (PET/CT scanners that have time-of-flight capability. However, reconstructed 90Y PET/CT images have high background noise, making non-target activity detection technically challenging. This educational article describes our image assessment technique for non-target activity detection by 90Y PET/CT which qualitatively overcomes the problem of background noise. We present selected case examples of non-target activity in untargeted liver, stomach, gallbladder, chest wall and kidney, supported by angiography and 90Y bremsstrahlung single photon emission computed tomography with integrated computed tomography (SPECT/CT or technetium-99m macroaggregated albumin SPECT/CT.

  15. Cell Density Affects the Detection of Chk1 Target Engagement by the Selective Inhibitor V158411.

    Science.gov (United States)

    Geneste, Clara C; Massey, Andrew J

    2018-02-01

    Understanding drug target engagement and the relationship to downstream pharmacology is critical for drug discovery. Here we have evaluated target engagement of Chk1 by the small-molecule inhibitor V158411 using two different target engagement methods (autophosphorylation and cellular thermal shift assay [CETSA]). Target engagement measured by these methods was subsequently related to Chk1 inhibitor-dependent pharmacology. Inhibition of autophosphorylation was a robust method for measuring V158411 Chk1 target engagement. In comparison, while target engagement determined using CETSA appeared robust, the V158411 CETSA target engagement EC 50 values were 43- and 19-fold greater than the autophosphorylation IC 50 values. This difference was attributed to the higher cell density in the CETSA assay configuration. pChk1 (S296) IC 50 values determined using the CETSA assay conditions were 54- and 33-fold greater than those determined under standard conditions and were equivalent to the CETSA EC 50 values. Cellular conditions, especially cell density, influenced the target engagement of V158411 for Chk1. The effects of high cell density on apparent compound target engagement potency should be evaluated when using target engagement assays that necessitate high cell densities (such as the CETSA conditions used in this study). In such cases, the subsequent relation of these data to downstream pharmacological changes should therefore be interpreted with care.

  16. 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.

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

    Science.gov (United States)

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

    2015-09-01

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

  18. 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.

  19. 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...

  20. Detecting Targeted Malicious Email through Supervised Classification of Persistent Threat and Recipient Oriented Features

    Science.gov (United States)

    Amin, Rohan Mahesh

    2010-01-01

    Targeted email attacks to enable computer network exploitation have become more prevalent, more insidious, and more widely documented in recent years. Beyond nuisance spam or phishing designed to trick users into revealing personal information, targeted malicious email (TME) facilitates computer network exploitation and the gathering of sensitive…

  1. Breaking camouflage and detecting targets require optic flow and image structure information.

    Science.gov (United States)

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

    2017-08-01

    Use of motion to break camouflage extends back to the Cambrian [In the Blink of an Eye: How Vision Sparked the Big Bang of Evolution (New York Basic Books, 2003)]. We investigated the ability to break camouflage and continue to see camouflaged targets after motion stops. This is crucial for the survival of hunting predators. With camouflage, visual targets and distracters cannot be distinguished using only static image structure (i.e., appearance). Motion generates another source of optical information, optic flow, which breaks camouflage and specifies target locations. Optic flow calibrates image structure with respect to spatial relations among targets and distracters, and calibrated image structure makes previously camouflaged targets perceptible in a temporally stable fashion after motion stops. We investigated this proposal using laboratory experiments and compared how many camouflaged targets were identified either with optic flow information alone or with combined optic flow and image structure information. Our results show that the combination of motion-generated optic flow and target-projected image structure information yielded efficient and stable perception of camouflaged targets.

  2. Target detection and localization in shallow water: an experimental demonstration of the acoustic barrier problem at the laboratory scale.

    Science.gov (United States)

    Marandet, Christian; Roux, Philippe; Nicolas, Barbara; Mars, Jérôme

    2011-01-01

    This study demonstrates experimentally at the laboratory scale the detection and localization of a wavelength-sized target in a shallow ultrasonic waveguide between two source-receiver arrays at 3 MHz. In the framework of the acoustic barrier problem, at the 1/1000 scale, the waveguide represents a 1.1-km-long, 52-m-deep ocean acoustic channel in the kilohertz frequency range. The two coplanar arrays record in the time-domain the transfer matrix of the waveguide between each pair of source-receiver transducers. Invoking the reciprocity principle, a time-domain double-beamforming algorithm is simultaneously performed on the source and receiver arrays. This array processing projects the multireverberated acoustic echoes into an equivalent set of eigenrays, which are defined by their launch and arrival angles. Comparison is made between the intensity of each eigenray without and with a target for detection in the waveguide. Localization is performed through tomography inversion of the acoustic impedance of the target, using all of the eigenrays extracted from double beamforming. The use of the diffraction-based sensitivity kernel for each eigenray provides both the localization and the signature of the target. Experimental results are shown in the presence of surface waves, and methodological issues are discussed for detection and localization.

  3. Sub-Pixel Accuracy Crack Width Determination on Concrete Beams in Load Tests by Triangle Mesh Geometry Analysis

    Science.gov (United States)

    Liebold, F.; Maas, H.-G.

    2018-05-01

    This paper deals with the determination of crack widths of concrete beams during load tests from monocular image sequences. The procedure starts in a reference image of the probe with suitable surface texture under zero load, where a large number of points is defined by an interest operator. Then a triangulated irregular network is established to connect the points. Image sequences are recorded during load tests with the load increasing continuously or stepwise, or at intermittently changing load. The vertices of the triangles are tracked through the consecutive images of the sequence with sub-pixel accuracy by least squares matching. All triangles are then analyzed for changes by principal strain calculation. For each triangle showing significant strain, a crack width is computed by a thorough geometric analysis of the relative movement of the vertices.

  4. A Novel Sub-pixel Measurement Algorithm Based on Mixed the Fractal and Digital Speckle Correlation in Frequency Domain

    Directory of Open Access Journals (Sweden)

    Zhangfang Hu

    2014-10-01

    Full Text Available The digital speckle correlation is a non-contact in-plane displacement measurement method based on machine vision. Motivated by the facts that the low accuracy and large amount of calculation produced by the traditional digital speckle correlation method in spatial domain, we introduce a sub-pixel displacement measurement algorithm which employs a fast interpolation method based on fractal theory and digital speckle correlation in frequency domain. This algorithm can overcome either the blocking effect or the blurring caused by the traditional interpolation methods, and the frequency domain processing also avoids the repeated searching in the correlation recognition of the spatial domain, thus the operation quantity is largely reduced and the information extracting speed is improved. The comparative experiment is given to verify that the proposed algorithm in this paper is effective.

  5. X-ray phase contrast imaging of objects with subpixel-size inhomogeneities: a geometrical optics model.

    Science.gov (United States)

    Gasilov, Sergei V; Coan, Paola

    2012-09-01

    Several x-ray phase contrast extraction algorithms use a set of images acquired along the rocking curve of a perfect flat analyzer crystal to study the internal structure of objects. By measuring the angular shift of the rocking curve peak, one can determine the local deflections of the x-ray beam propagated through a sample. Additionally, some objects determine a broadening of the crystal rocking curve, which can be explained in terms of multiple refraction of x rays by many subpixel-size inhomogeneities contained in the sample. This fact may allow us to differentiate between materials and features characterized by different refraction properties. In the present work we derive an expression for the beam broadening in the form of a linear integral of the quantity related to statistical properties of the dielectric susceptibility distribution function of the object.

  6. 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.

  7. Right hemisphere dominance during spatial selective attention and target detection occurs outside the dorsal fronto-parietal network

    Science.gov (United States)

    Shulman, Gordon L.; Pope, Daniel L. W.; Astafiev, Serguei V.; McAvoy, Mark P.; Snyder, Abraham Z.; Corbetta, Maurizio

    2010-01-01

    Spatial selective attention is widely considered to be right hemisphere dominant. Previous functional magnetic resonance imaging (fMRI) studies, however, have reported bilateral blood-oxygenation-level-dependent (BOLD) responses in dorsal fronto-parietal regions during anticipatory shifts of attention to a location (Kastner et al., 1999; Corbetta et al., 2000; Hopfinger et al., 2000). Right-lateralized activity has mainly been reported in ventral fronto-parietal regions for shifts of attention to an unattended target stimulus (Arrington et al., 2000; Corbetta et al., 2000). However, clear conclusions cannot be drawn from these studies because hemispheric asymmetries were not assessed using direct voxel-wise comparisons of activity in left and right hemispheres. Here, we used this technique to measure hemispheric asymmetries during shifts of spatial attention evoked by a peripheral cue stimulus and during target detection at the cued location. Stimulus-driven shifts of spatial attention in both visual fields evoked right-hemisphere dominant activity in temporo-parietal junction (TPJ). Target detection at the attended location produced a more widespread right hemisphere dominance in frontal, parietal, and temporal cortex, including the TPJ region asymmetrically activated during shifts of spatial attention. However, hemispheric asymmetries were not observed during either shifts of attention or target detection in the dorsal fronto-parietal regions (anterior precuneus, medial intraparietal sulcus, frontal eye fields) that showed the most robust activations for shifts of attention. Therefore, right hemisphere dominance during stimulus-driven shifts of spatial attention and target detection reflects asymmetries in cortical regions that are largely distinct from the dorsal fronto-parietal network involved in the control of selective attention. PMID:20219998

  8. 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.

  9. Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China

    Directory of Open Access Journals (Sweden)

    Haoming Xia

    2017-01-01

    Full Text Available Wetland inundation is crucial to the survival and prosperity of fauna and flora communities in wetland ecosystems. Even small changes in surface inundation may result in a substantial impact on the wetland ecosystem characteristics and function. This study presented a novel method for wetland inundation mapping at a subpixel scale in a typical wetland region on the Zoige Plateau, northeast Tibetan Plateau, China, by combining use of an unmanned aerial vehicle (UAV and Landsat-8 Operational Land Imager (OLI data. A reference subpixel inundation percentage (SIP map at a Landsat-8 OLI 30 m pixel scale was first generated using high resolution UAV data (0.16 m. The reference SIP map and Landsat-8 OLI imagery were then used to develop SIP estimation models using three different retrieval methods (Linear spectral unmixing (LSU, Artificial neural networks (ANN, and Regression tree (RT. Based on observations from 2014, the estimation results indicated that the estimation model developed with RT method could provide the best fitting results for the mapping wetland SIP (R2 = 0.933, RMSE = 8.73% compared to the other two methods. The proposed model with RT method was validated with observations from 2013, and the estimated SIP was highly correlated with the reference SIP, with an R2 of 0.986 and an RMSE of 9.84%. This study highlighted the value of high resolution UAV data and globally and freely available Landsat data in combination with the developed approach for monitoring finely gradual inundation change patterns in wetland ecosystems.

  10. Subpixel Snow-covered Area Including Differentiated Grain Size from AVIRIS Data Over the Sierra Nevada Mountain Range

    Science.gov (United States)

    Hill, R.; Calvin, W. M.; Harpold, A. A.

    2016-12-01

    Mountain snow storage is the dominant source of water for humans and ecosystems in western North America. Consequently, the spatial distribution of snow-covered area is fundamental to both hydrological, ecological, and climate models. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were collected along the entire Sierra Nevada mountain range extending from north of Lake Tahoe to south of Mt. Whitney during the 2015 and 2016 snow-covered season. The AVIRIS dataset used in this experiment consists of 224 contiguous spectral channels with wavelengths ranging 400-2500 nanometers at a 15-meter spatial pixel size. Data from the Sierras were acquired on four days: 2/24/15 during a very low snow year, 3/24/16 near maximum snow accumulation, and 5/12/16 and 5/18/16 during snow ablation and snow loss. Previous retrieval of subpixel snow-covered area in alpine regions used multiple snow endmembers due to the sensitivity of snow spectral reflectance to grain size. We will present a model that analyzes multiple endmembers of varying snow grain size, vegetation, rock, and soil in segmented regions along the Sierra Nevada to determine snow-cover spatial extent, snow sub-pixel fraction and approximate grain size or melt state. The root mean squared error will provide a spectrum-wide assessment of the mixture model's goodness-of-fit. Analysis will compare snow-covered area and snow-cover depletion in the 2016 year, and annual variation from the 2015 year. Field data were also acquired on three days concurrent with the 2016 flights in the Sagehen Experimental Forest and will support ground validation of the airborne data set.

  11. Exploring Subpixel Learning Algorithms for Estimating Global Land Cover Fractions from Satellite Data Using High Performance Computing

    Directory of Open Access Journals (Sweden)

    Uttam Kumar

    2017-10-01

    Full Text Available Land cover (LC refers to the physical and biological cover present over the Earth’s surface in terms of the natural environment such as vegetation, water, bare soil, etc. Most LC features occur at finer spatial scales compared to the resolution of primary remote sensing satellites. Therefore, observed data are a mixture of spectral signatures of two or more LC features resulting in mixed pixels. One solution to the mixed pixel problem is the use of subpixel learning algorithms to disintegrate the pixel spectrum into its constituent spectra. Despite the popularity and existing research conducted on the topic, the most appropriate approach is still under debate. As an attempt to address this question, we compared the performance of several subpixel learning algorithms based on least squares, sparse regression, signal–subspace and geometrical methods. Analysis of the results obtained through computer-simulated and Landsat data indicated that fully constrained least squares (FCLS outperformed the other techniques. Further, FCLS was used to unmix global Web-Enabled Landsat Data to obtain abundances of substrate (S, vegetation (V and dark object (D classes. Due to the sheer nature of data and computational needs, we leveraged the NASA Earth Exchange (NEX high-performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into four classes, namely forest, farmland, water and urban areas (in conjunction with nighttime lights data over California, USA using a random forest classifier. Validation of these LC maps with the National Land Cover Database 2011 products and North American Forest Dynamics static forest map shows a 6% improvement in unmixing-based classification relative to per-pixel classification. As such, abundance maps continue to offer a useful alternative to high-spatial-resolution classified maps for forest inventory analysis, multi

  12. A multidimensional strategy to detect polypharmacological targets in the absence of structural and sequence homology.

    Science.gov (United States)

    Durrant, Jacob D; Amaro, Rommie E; Xie, Lei; Urbaniak, Michael D; Ferguson, Michael A J; Haapalainen, Antti; Chen, Zhijun; Di Guilmi, Anne Marie; Wunder, Frank; Bourne, Philip E; McCammon, J Andrew

    2010-01-22

    Conventional drug design embraces the "one gene, one drug, one disease" philosophy. Polypharmacology, which focuses on multi-target drugs, has emerged as a new paradigm in drug discovery. The rational design of drugs that act via polypharmacological mechanisms can produce compounds that exhibit increased therapeutic potency and against which resistance is less likely to develop. Additionally, identifying multiple protein targets is also critical for side-effect prediction. One third of potential therapeutic compounds fail in clinical trials or are later removed from the market due to unacceptable side effects often caused by off-target binding. In the current work, we introduce a multidimensional strategy for the identification of secondary targets of known small-molecule inhibitors in the absence of global structural and sequence homology with the primary target protein. To demonstrate the utility of the strategy, we identify several targets of 4,5-dihydroxy-3-(1-naphthyldiazenyl)-2,7-naphthalenedisulfonic acid, a known micromolar inhibitor of Trypanosoma brucei RNA editing ligase 1. As it is capable of identifying potential secondary targets, the strategy described here may play a useful role in future efforts to reduce drug side effects and/or to increase polypharmacology.

  13. Targeted detection of murine colonic dysplasia in vivo with flexible multispectral scanning fiber endoscopy

    Science.gov (United States)

    Joshi, Bishnu P.; Miller, Sharon J.; Lee, Cameron; Gustad, Adam; Seibel, Eric J.; Wang, Thomas D.

    2012-02-01

    We demonstrate a multi-spectral scanning fiber endoscope (SFE) that collects fluorescence images in vivo from three target peptides that bind specifically to murine colonic adenomas. This ultrathin endoscope was demonstrated in a genetically engineered mouse model of spontaneous colorectal adenomas based on somatic Apc (adenomatous polyposis coli) gene inactivation. The SFE delivers excitation at 440, 532, 635 nm with human patients by simultaneously visualizing multiple over expressed molecular targets unique to dysplasia.

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

    Science.gov (United States)

    2007-03-01

    diverses conditions environnementales difficiles, dont l’exposition à la chaleur et au froid, le bruit, l’exercice épuisant et la privation de sommeil...urban scenario used for marksmanship testing. The arrow indicates a walking target and the centrepiece depicting a poster of a soldier was a permanent... poster of a soldier was a permanent display that was used to hide targets. The heating and cooling protocols caused significant separations in core

  15. 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.

  16. Design of mitochondria-targeted colorimetric and ratiometric fluorescent probes for rapid detection of SO2 derivatives in living cells

    Science.gov (United States)

    Yang, Yutao; Zhou, Tingting; Bai, Bozan; Yin, Caixia; Xu, Wenzhi; Li, Wei

    2018-05-01

    Two mitochondria-targeted colorimetric and ratiometric fluorescent probes for SO2 derivatives were constructed based on the SO2 derivatives-triggered Michael addition reaction. The probes exhibit high specificity toward HSO3-/SO32- by interrupting their conjugation system resulting in a large ratiometric blue shift of 46-121 nm in their emission spectrum. The two well-resolved emission bands can ensure accurate detection of HSO3-. The detection limits were calculated to be 1.09 and 1.35 μM. Importantly, probe 1 and probe 2 were successfully used to fluorescence ratiometric imaging of endogenous HSO3- in BT-474 cells.

  17. 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…

  18. 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.

  19. 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.

  20. Target-induced structure switching of hairpin aptamers for label-free and sensitive fluorescent detection of ATP via exonuclease-catalyzed target recycling amplification.

    Science.gov (United States)

    Xu, Yunying; Xu, Jin; Xiang, Yun; Yuan, Ruo; Chai, Yaqin

    2014-01-15

    In this work, we described the development of a new label-free, simple and sensitive fluorescent ATP sensing platform based on exonuclease III (Exo III)-catalyzed target recycling (ECTR) amplification and SYBR Green I indicator. The hairpin aptamer probes underwent conformational structure switching and re-configuration in the presence of ATP, which led to catalytic cleavage of the re-configured aptamers by Exo III to release ATP and to initiate the ECTR process. Such ECTR process resulted in the digestion of a significant number of the hairpin aptamer probes, leading to much less intercalation of SYBR Green I to the hairpin stems and drastic suppression of the fluorescence emission for sensitive ATP detection down to the low nanomolar level. Due to the highly specific affinity bindings between aptamers and ATP, the developed method exhibited excellent selectivity toward ATP against other analogous molecules. Besides, our ATP sensing approach used un-modified aptamer probes and could be performed in a "mix-and-detect" fashion in homogenous solutions. All these distinct advantages of the developed method thus made it hold great potential for the development of simple and robust sensing strategies for the detection of other small molecules. © 2013 Elsevier B.V. All rights reserved.

  1. Using a Regression Method for Estimating Performance in a Rapid Serial Visual Presentation Target-Detection Task

    Science.gov (United States)

    2017-12-01

    Fig. 2 Simulation method; the process for one iteration of the simulation . It was repeated 250 times per combination of HR and FAR. Analysis was...distribution is unlimited. 8 Fig. 2 Simulation method; the process for one iteration of the simulation . It was repeated 250 times per combination of HR...stimuli. Simulations show that this regression method results in an unbiased and accurate estimate of target detection performance. The regression

  2. Detection of occult, undisplaced hip fractures with a dual-energy CT algorithm targeted to detection of bone marrow edema.

    Science.gov (United States)

    Reddy, T; McLaughlin, P D; Mallinson, P I; Reagan, A C; Munk, P L; Nicolaou, S; Ouellette, H A

    2015-02-01

    The purpose of this study is to describe our initial clinical experience with dual-energy computed tomography (DECT) virtual non-calcium (VNC) images for the detection of bone marrow (BM) edema in patients with suspected hip fracture following trauma. Twenty-five patients presented to the emergency department at a level 1 trauma center between January 1, 2011 and January 1, 2013 with clinical suspicion of hip fracture and normal radiographs were included. All CT scans were performed on a dual-source, dual-energy CT system. VNC images were generated using prototype software and were compared to regular bone reconstructions by two musculoskeletal radiologists in consensus. Radiological and/or clinical diagnosis of fracture at 30-day follow-up was used as the reference standard. Twenty-one patients were found to have DECT-VNC signs of bone marrow edema. Eighteen of these 21 patients were true positive and three were false positive. A concordant fracture was clearly seen on bone reconstruction images in 15 of the 18 true positive cases. In three cases, DECT-VNC was positive for bone marrow edema where bone reconstruction CT images were negative. Four patients demonstrated no DECT-VNC signs of bone marrow edema: two cases were true negative, two cases were false negative. When compared with the gold standard of hip fracture determined at retrospective follow-up, the sensitivity of DECT-VNC images of the hip was 90 %, specificity was 40 %, positive predictive value was 86 %, and negative predictive value was 50 %. Our initial experience would suggest that DECT-VNC is highly sensitive but poorly specific in the diagnosis of hip fractures in patients with normal radiographs. The value of DECT-VNC primarily lies in its ability to help detect fractures which may be subtle or undetectable on bone reconstruction CT images.

  3. [Using exon combined target region capture sequencing chip to detect the disease-causing genes of retinitis pigmentosa].

    Science.gov (United States)

    Rong, Weining; Chen, Xuejuan; Li, Huiping; Liu, Yani; Sheng, Xunlun

    2014-06-01

    To detect the disease-causing genes of 10 retinitis pigmentosa pedigrees by using exon combined target region capture sequencing chip. Pedigree investigation study. From October 2010 to December 2013, 10 RP pedigrees were recruited for this study in Ningxia Eye Hospital. All the patients and family members received complete ophthalmic examinations. DNA was abstracted from patients, family members and controls. Using exon combined target region capture sequencing chip to screen the candidate disease-causing mutations. Polymerase chain reaction (PCR) and direct sequencing were used to confirm the disease-causing mutations. Seventy patients and 23 normal family members were recruited from 10 pedigrees. Among 10 RP pedigrees, 1 was autosomal dominant pedigrees and 9 were autosomal recessive pedigrees. 7 mutations related to 5 genes of 5 pedigrees were detected. A frameshift mutation on BBS7 gene was detected in No.2 pedigree, the patients of this pedigree combined with central obesity, polydactyly and mental handicap. No.2 pedigree was diagnosed as Bardet-Biedl syndrome finally. A missense mutation was detected in No.7 and No.10 pedigrees respectively. Because the patients suffered deafness meanwhile, the final diagnosis was Usher syndrome. A missense mutation on C3 gene related to age-related macular degeneration was also detected in No. 7 pedigrees. A nonsense mutation and a missense mutation on CRB1 gene were detected in No. 1 pedigree and a splicesite mutation on PROM1 gene was detected in No. 5 pedigree. Retinitis pigmentosa is a kind of genetic eye disease with diversity clinical phenotypes. Rapid and effective genetic diagnosis technology combined with clinical characteristics analysis is helpful to improve the level of clinical diagnosis of RP.

  4. High Precision Edge Detection Algorithm for Mechanical Parts

    Directory of Open Access Journals (Sweden)

    Duan Zhenyun

    2018-04-01

    Full Text Available High precision and high efficiency measurement is becoming an imperative requirement for a lot of mechanical parts. So in this study, a subpixel-level edge detection algorithm based on the Gaussian integral model is proposed. For this purpose, the step edge normal section line Gaussian integral model of the backlight image is constructed, combined with the point spread function and the single step model. Then gray value of discrete points on the normal section line of pixel edge is calculated by surface interpolation, and the coordinate as well as gray information affected by noise is fitted in accordance with the Gaussian integral model. Therefore, a precise location of a subpixel edge was determined by searching the mean point. Finally, a gear tooth was measured by M&M3525 gear measurement center to verify the proposed algorithm. The theoretical analysis and experimental results show that the local edge fluctuation is reduced effectively by the proposed method in comparison with the existing subpixel edge detection algorithms. The subpixel edge location accuracy and computation speed are improved. And the maximum error of gear tooth profile total deviation is 1.9 μm compared with measurement result with gear measurement center. It indicates that the method has high reliability to meet the requirement of high precision measurement.

  5. High Precision Edge Detection Algorithm for Mechanical Parts

    Science.gov (United States)

    Duan, Zhenyun; Wang, Ning; Fu, Jingshun; Zhao, Wenhui; Duan, Boqiang; Zhao, Jungui

    2018-04-01

    High precision and high efficiency measurement is becoming an imperative requirement for a lot of mechanical parts. So in this study, a subpixel-level edge detection algorithm based on the Gaussian integral model is proposed. For this purpose, the step edge normal section line Gaussian integral model of the backlight image is constructed, combined with the point spread function and the single step model. Then gray value of discrete points on the normal section line of pixel edge is calculated by surface interpolation, and the coordinate as well as gray information affected by noise is fitted in accordance with the Gaussian integral model. Therefore, a precise location of a subpixel edge was determined by searching the mean point. Finally, a gear tooth was measured by M&M3525 gear measurement center to verify the proposed algorithm. The theoretical analysis and experimental results show that the local edge fluctuation is reduced effectively by the proposed method in comparison with the existing subpixel edge detection algorithms. The subpixel edge location accuracy and computation speed are improved. And the maximum error of gear tooth profile total deviation is 1.9 μm compared with measurement result with gear measurement center. It indicates that the method has high reliability to meet the requirement of high precision measurement.

  6. Pancreatic cancer cell detection by targeted lipid microbubbles and multiphoton imaging

    Science.gov (United States)

    Cromey, Benjamin; McDaniel, Ashley; Matsunaga, Terry; Vagner, Josef; Kieu, Khanh Quoc; Banerjee, Bhaskar

    2018-04-01

    Surgical resection of pancreatic cancer represents the only chance of cure and long-term survival in this common disease. Unfortunately, determination of a cancer-free margin at surgery is based on one or two tiny frozen section biopsies, which is far from ideal. Not surprisingly, cancer is usually left behind and is responsible for metastatic disease. We demonstrate a method of receptor-targeted imaging using peptide ligands, lipid microbubbles, and multiphoton microscopy that could lead to a fast and accurate way of examining the entire cut surface during surgery. Using a plectin-targeted microbubble, we performed a blinded in-vitro study to demonstrate avid binding of targeted microbubbles to pancreatic cancer cells but not noncancerous cell lines. Further work should lead to a much-needed point-of-care diagnostic test for determining clean margins in oncologic surgery.

  7. 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

    2017-01-01

    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. PMID:28273838

  8. An Investigation into the Passive Detection of Point Targets Using FM Broadcasts or White Noise

    National Research Council Canada - National Science Library

    Lindstrom, Chadwick

    1998-01-01

    Over the past three years, researchers at the University of Washington have been developing a multistatic radar system that uses commercial FM radio broadcasts to detect plasma waves in the ionosphere...

  9. 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.

  10. Performance comparison of multi-detector detection statistics in targeted compact binary coalescence GW search

    OpenAIRE

    Haris, K; Pai, Archana

    2016-01-01

    Global network of advanced Interferometric gravitational wave (GW) detectors are expected to be on-line soon. Coherent observation of GW from a distant compact binary coalescence (CBC) with a network of interferometers located in different continents give crucial information about the source such as source location and polarization information. In this paper we compare different multi-detector network detection statistics for CBC search. In maximum likelihood ratio (MLR) based detection appro...

  11. 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.

  12. Generic detection of poleroviruses using an RT-PCR assay targeting the RdRp coding sequence.

    Science.gov (United States)

    Lotos, Leonidas; Efthimiou, Konstantinos; Maliogka, Varvara I; Katis, Nikolaos I

    2014-03-01

    In this study a two-step RT-PCR assay was developed for the generic detection of poleroviruses. The RdRp coding region was selected as the primers' target, since it differs significantly from that of other members in the family Luteoviridae and its sequence can be more informative than other regions in the viral genome. Species specific RT-PCR assays targeting the same region were also developed for the detection of the six most widespread poleroviral species (Beet mild yellowing virus, Beet western yellows virus, Cucurbit aphid-borne virus, Carrot red leaf virus, Potato leafroll virus and Turnip yellows virus) in Greece and the collection of isolates. These isolates along with other characterized ones were used for the evaluation of the generic PCR's detection range. The developed assay efficiently amplified a 593bp RdRp fragment from 46 isolates of 10 different Polerovirus species. Phylogenetic analysis using the generic PCR's amplicon sequence showed that although it cannot accurately infer evolutionary relationships within the genus it can differentiate poleroviruses at the species level. Overall, the described generic assay could be applied for the reliable detection of Polerovirus infections and, in combination with the specific PCRs, for the identification of new and uncharacterized species in the genus. Copyright © 2013 Elsevier B.V. All rights reserved.

  13. Time-Resolved Spectroscopy and Near Infrared Imaging for Prostate Cancer Detection: Receptor-targeted and Native Biomarker

    Science.gov (United States)

    Pu, Yang

    Optical spectroscopy and imaging using near-infrared (NIR) light provides powerful tools for non-invasive detection of cancer in tissue. Optical techniques are capable of quantitative reconstructions maps of tissue absorption and scattering properties, thus can map in vivo the differences in the content of certain marker chromophores and/or fluorophores in normal and cancerous tissues (for example: water, tryptophan, collagen and NADH contents). Potential clinical applications of optical spectroscopy and imaging include functional tumor detection and photothermal therapeutics. Optical spectroscopy and imaging apply contrasts from intrinsic tissue chromophores such as water, collagen and NADH, and extrinsic optical contrast agents such as Indocyanine Green (ICG) to distinguish disease tissue from the normal one. Fluorescence spectroscopy and imaging also gives high sensitivity and specificity for biomedical diagnosis. Recent developments on specific-targeting fluorophores such as small receptor-targeted dye-peptide conjugate contrast agent offer high contrast between normal and cancerous tissues hence provide promising future for early tumour detection. This thesis focus on a study to distinguish the cancerous prostate tissue from the normal prostate tissues with enhancement of specific receptor-targeted prostate cancer contrast agents using optical spectroscopy and imaging techniques. The scattering and absorption coefficients, and anisotropy factor of cancerous and normal prostate tissues were investigated first as the basis for the biomedical diagnostic and optical imaging. Understanding the receptors over-expressed prostate cancer cells and molecular target mechanism of ligand, two small ICG-derivative dye-peptides, namely Cypate-Bombesin Peptide Analogue Conjugate (Cybesin) and Cypate-Octreotate Peptide Conjugate (Cytate), were applied to study their clinical potential for human prostate cancer detection. In this work, the steady-state and time

  14. Identification of target cells by immunohistochemical detection of covalently rearranged estradiol in rehydrated paraffin sections.

    Science.gov (United States)

    Jungblut, P W; Sierralta, W D

    1998-04-01

    Estradiol is released from the binding niche of the receptor and covalently arrested in the molecular vicinity by the Mannich reaction during target fixation in acetic acid/formaldehyde. The exposed steroid is freely accessible for appropriate antibodies. It can be visualized in sections by the second antibody/enzyme technique in high resolution and without enhancements.

  15. Quencher-free molecular beacon tethering 7-hydroxycoumarin detects targets through protonation/deprotonation.

    Science.gov (United States)

    Kashida, Hiromu; Yamaguchi, Kyohei; Hara, Yuichi; Asanuma, Hiroyuki

    2012-07-15

    In this study, we synthesized a simple but efficient quencher-free molecular beacon tethering 7-hydroxycoumarin on D-threoninol based on its pK(a) change. The pK(a) of 7-hydroxycoumarin in a single strand was determined as 8.8, whereas that intercalated in the duplex was over 10. This large pK(a) shift (more than 1.2) upon hybridization could be attributed to the anionic and hydrophobic microenvironment inside the DNA duplex. Because 7-hydroxycoumarin quenches its fluorescence upon protonation, the emission intensity of the duplex at pH 8.5 was 1/15 that of the single strand. We applied this quenching mechanism to the preparation of a quencher-free molecular beacon by introducing the dye into the middle of the stem part. In the absence of the target, the stem region formed a duplex and fluorescence was quenched. However, when the target was added, the molecular beacon opened and the dye was deprotonated. As a result, the emission intensity of the molecular beacon with the target was 10 times higher than that without the target. Accordingly, a quencher-free molecular beacon utilizing the pK(a) change was successfully developed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. 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

  17. Multi-target detection and positioning in crowds using multiple camera surveillance

    Science.gov (United States)

    Huang, Jiahu; Zhu, Qiuyu; Xing, Yufeng

    2018-04-01

    In this study, we propose a pixel correspondence algorithm for positioning in crowds based on constraints on the distance between lines of sight, grayscale differences, and height in a world coordinates system. First, a Gaussian mixture model is used to obtain the background and foreground from multi-camera videos. Second, the hair and skin regions are extracted as regions of interest. Finally, the correspondences between each pixel in the region of interest are found under multiple constraints and the targets are positioned by pixel clustering. The algorithm can provide appropriate redundancy information for each target, which decreases the risk of losing targets due to a large viewing angle and wide baseline. To address the correspondence problem for multiple pixels, we construct a pixel-based correspondence model based on a similar permutation matrix, which converts the correspondence problem into a linear programming problem where a similar permutation matrix is found by minimizing an objective function. The correct pixel correspondences can be obtained by determining the optimal solution of this linear programming problem and the three-dimensional position of the targets can also be obtained by pixel clustering. Finally, we verified the algorithm with multiple cameras in experiments, which showed that the algorithm has high accuracy and robustness.

  18. Early Detection of Prostate Cancer with New Nanoparticle-Based Ultrasound Contrast Agents Targeted to PSMA

    Science.gov (United States)

    2017-08-01

    protein therapy making use of a filamentous nanotechnology. The targeted delivery of doxorubicin and tumor necrosis factor-related apoptosis...3/31/2012 Vascular modulation with or without chemotherapy for enhancement of RF ablation; Role: Co- Investigator 2010 SIR Foundation Grant (PI...Characterization of Slow Precipitating Implants for Vascular Occlusion. IEEE International Ultrasonics Symposium 2017 Annual meeting. In preparation

  19. Analytical purification of a 60-kDa target protein of artemisinin detected in Trypanosoma brucei brucei

    Directory of Open Access Journals (Sweden)

    Benetode Konziase

    2015-12-01

    Full Text Available Here we describe the isolation and purity determination of Trypanosoma brucei (T. b. brucei candidate target proteins of artemisinin. The candidate target proteins were detected and purified from their biological source (T. b. brucei lysate using the diazirine-free biotinylated probe 5 for an affinity binding to a streptavidin-tagged resin and, subsequently, the labeled target proteins were purified by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE. We herein showed the electrophoresis gel and the immunoblotting film containing the 60-kDa trypanosomal candidate target protein of artemisinin as a single band, which was visualized on-gel by the reverse-staining method and on a Western blotting film by enhanced chemiluminescence. The data provided in this article are related to the original research article “Biotinylated probes of artemisinin with labeling affinity toward Trypanosoma brucei brucei target proteins”, by Konziase (Anal. Biochem., vol. 482, 2015, pp. 25–31. http://dx.doi.org/10.1016/j.ab.2015.04.020.

  20. Tumor Specific Detection of an Optically Targeted Antibody Combined with a Quencher-conjugated Neutravidin “Quencher-Chaser”: A Dual “Quench and Chase” Strategy to Improve Target to Non-target Ratios for Molecular Imaging of Cancer

    Science.gov (United States)

    Ogawa, Mikako; Kosaka, Nobuyuki; Choyke, Peter L; Kobayashi, Hisataka

    2009-01-01

    In vivo molecular cancer imaging with monoclonal antibodies has great potential not only for cancer detection but also for cancer characterization. However, the prolonged retention of intravenously injected antibody in the blood causes low target tumor-to-background ratio (TBR). Avidin has been used as a “chase” to clear the unbound, circulating biotinylated antibody and decrease the background signal. Here, we utilize a combined approach of a Fluorescence Resonance Energy Transfer (FRET) quenched antibody with an “avidin chase” to increase TBR. Trastuzumab, a humanized monoclonal antibody against human epidermal growth factor receptor type 2 (HER2), was biotinylated and conjugated with the near-infrared (NIR) fluorophore Alexa680 to synthesize Tra-Alexa680-biotin. Next, the FRET quencher, QSY-21, was conjugated to avidin, neutravidin (nAv) or streptavidin (sAv), thus creating Av-QSY21, nAv-QSY21 or sAv-QSY21 as “chasers”. The fluorescence was quenched in vitro by binding Tra-Alexa680-biotin to Av-QSY21, nAv-QSY21 or sAv-QSY21. To evaluate if the injection of quencher-conjugated avidin-derivatives can improve target TBR by using a dual “quench and chase” strategy, both target (3T3/HER2+) and non-target (Balb3T3/ZsGreen) tumor bearing mice were employed. The “FRET quench” effect induced by all the QSY21 avidin-based conjugates reduced but did not totally eliminate background signal from the blood pool. The addition of nAv-QSY21 administration increased target TBR mainly due to the “chase” effect where unbound conjugated antibody was preferentially cleared to the liver. The relatively slow clearance of unbound nAv-QSY21 leads to further reductions in background signal by leaking out of the vascular space and binding to unbound antibodies in the extravascular space of tumors resulting in decreased non-target tumor-to-background ratios but increased target TBR due to the “FRET quench” effect because target-bound antibodies were internalized

  1. 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.

  2. 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

  3. Dynamical scene analysis with a moving camera: mobile targets detection system

    International Nuclear Information System (INIS)

    Hennebert, Christine

    1996-01-01

    This thesis work deals with the detection of moving objects in monocular image sequences acquired with a mobile camera. We propose a method able to detect small moving objects in visible or infrared images of real outdoor scenes. In order to detect objects of very low apparent motion, we consider an analysis on a large temporal interval. We have chosen to compensate for the dominant motion due to the camera displacement for several consecutive images in order to form a sub-sequence of images for which the camera seems virtually static. We have also developed a new approach allowing to extract the different layers of a real scene in order to deal with cases where the 2D motion due to the camera displacement cannot be globally compensated for. To this end, we use a hierarchical model with two levels: the local merging step and the global merging one. Then, an appropriate temporal filtering is applied to registered image sub-sequence to enhance signals corresponding to moving objects. The detection issue is stated as a labeling problem within a statistical regularization based on Markov Random Fields. Our method has been validated on numerous real image sequences depicting complex outdoor scenes. Finally, the feasibility of an integrated circuit for mobile object detection has been proved. This circuit could lead to an ASIC creation. (author) [fr

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

    Science.gov (United States)

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

    2018-03-21

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

  5. Critical heat flux acoustic detection: Methods and application to ITER divertor vertical target monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Courtois, X., E-mail: xavier.courtois@cea.fr [CEA, IRFM, F-13108 Saint-Paul-Lez-Durance (France); Escourbiac, F. [ITER Organization, Route de Vinon sur Verdon, F-13115 Saint-Paul-Lez-Durance (France); Richou, M.; Cantone, V. [CEA, IRFM, F-13108 Saint-Paul-Lez-Durance (France); Constans, S. [AREVA-NP, Le Creusot (France)

    2013-10-15

    Actively cooled plasma facing components (PFCs) have to exhaust high heat fluxes from plasma radiation and plasma–wall interaction. Critical heat flux (CHF) event may occur in the cooling channel due to unexpected heat loading or operational conditions, and has to be detected as soon as possible. Therefore it is essential to develop means of monitoring based on precursory signals providing an early detection of this destructive phenomenon, in order to be able to stop operation before irremediable damages appear. Capabilities of CHF early detection based on acoustic techniques on PFC mock-ups cooled by pressurised water were already demonstrated. This paper addresses the problem of the detection in case of flow rate reduction and of flow dilution resulting from multiple plasma facing units (PFU) which are hydraulically connected in parallel, which is the case of ITER divertor. An experimental study is launched on a dedicated mock-up submitted to heat loads up to the CHF. It shows that the measurement of the acoustic waves, generated by the cooling phenomena, allows the CHF detection in conditions similar to that of the ITER divertor, with a reasonable number of sensors. The paper describes the mock-ups and the tests sequences, and comments the results.

  6. CD33 monoclonal antibody conjugated Au cluster nano-bioprobe for targeted flow-cytometric detection of acute myeloid leukaemia

    Science.gov (United States)

    Retnakumari, Archana; Jayasimhan, Jasusri; Chandran, Parwathy; Menon, Deepthy; Nair, Shantikumar; Mony, Ullas; Koyakutty, Manzoor

    2011-07-01

    Protein stabilized gold nanoclusters (Au-NCs) are biocompatible, near-infrared (NIR) emitting nanosystems having a wide range of biomedical applications. Here, we report the development of a Au-NC based targeted fluorescent nano-bioprobe for the flow-cytometric detection of acute myeloid leukaemia (AML) cells. Au-NCs with ~ 25-28 atoms showing bright red-NIR fluorescence (600-750 nm) and average size of ~ 0.8 nm were prepared by bovine serum albumin assisted reduction-cum-stabilization in aqueous phase. The protein protected clusters were conjugated with monoclonal antibody against CD33 myeloid antigen, which is overexpressed in ~ 99.2% of the primitive population of AML cells, as confirmed by immunophenotyping using flow cytometry. Au-NC-CD33 conjugates having average size of ~ 12 nm retained bright fluorescence over an extended duration of ~ a year, as the albumin protein protects Au-NCs against degradation. Nanotoxicity studies revealed excellent biocompatibility of Au-NC conjugates, as they showed no adverse effect on the cell viability and inflammatory response. Target specificity of the conjugates for detecting CD33 expressing AML cells (KG1a) in flow cytometry showed specific staining of ~ 95.4% of leukaemia cells within 1-2 h compared to a non-specific uptake of ~ 8.2% in human peripheral blood cells (PBMCs) which are CD33low. The confocal imaging also demonstrated the targeted uptake of CD33 conjugated Au-NCs by leukaemia cells, thus confirming the flow cytometry results. This study demonstrates that novel nano-bioprobes can be developed using protein protected fluorescent nanoclusters of Au for the molecular receptor targeted flow cytometry based detection and imaging of cancer cells.

  7. CD33 monoclonal antibody conjugated Au cluster nano-bioprobe for targeted flow-cytometric detection of acute myeloid leukaemia

    International Nuclear Information System (INIS)

    Retnakumari, Archana; Jayasimhan, Jasusri; Chandran, Parwathy; Menon, Deepthy; Nair, Shantikumar; Mony, Ullas; Koyakutty, Manzoor

    2011-01-01

    Protein stabilized gold nanoclusters (Au-NCs) are biocompatible, near-infrared (NIR) emitting nanosystems having a wide range of biomedical applications. Here, we report the development of a Au-NC based targeted fluorescent nano-bioprobe for the flow-cytometric detection of acute myeloid leukaemia (AML) cells. Au-NCs with ∼ 25-28 atoms showing bright red-NIR fluorescence (600-750 nm) and average size of ∼ 0.8 nm were prepared by bovine serum albumin assisted reduction-cum-stabilization in aqueous phase. The protein protected clusters were conjugated with monoclonal antibody against CD33 myeloid antigen, which is overexpressed in ∼ 99.2% of the primitive population of AML cells, as confirmed by immunophenotyping using flow cytometry. Au-NC-CD33 conjugates having average size of ∼ 12 nm retained bright fluorescence over an extended duration of ∼ a year, as the albumin protein protects Au-NCs against degradation. Nanotoxicity studies revealed excellent biocompatibility of Au-NC conjugates, as they showed no adverse effect on the cell viability and inflammatory response. Target specificity of the conjugates for detecting CD33 expressing AML cells (KG1a) in flow cytometry showed specific staining of ∼ 95.4% of leukaemia cells within 1-2 h compared to a non-specific uptake of ∼ 8.2% in human peripheral blood cells (PBMCs) which are CD33 low . The confocal imaging also demonstrated the targeted uptake of CD33 conjugated Au-NCs by leukaemia cells, thus confirming the flow cytometry results. This study demonstrates that novel nano-bioprobes can be developed using protein protected fluorescent nanoclusters of Au for the molecular receptor targeted flow cytometry based detection and imaging of cancer cells.

  8. CD33 monoclonal antibody conjugated Au cluster nano-bioprobe for targeted flow-cytometric detection of acute myeloid leukaemia

    Energy Technology Data Exchange (ETDEWEB)

    Retnakumari, Archana; Jayasimhan, Jasusri; Chandran, Parwathy; Menon, Deepthy; Nair, Shantikumar; Mony, Ullas; Koyakutty, Manzoor, E-mail: manzoork@aims.amrita.edu, E-mail: ullasmony@aims.amrita.edu [Amrita Centre for Nanoscience and Molecular Medicine, Amrita Institute of Medical Science, Cochin 682 041 (India)

    2011-07-15

    Protein stabilized gold nanoclusters (Au-NCs) are biocompatible, near-infrared (NIR) emitting nanosystems having a wide range of biomedical applications. Here, we report the development of a Au-NC based targeted fluorescent nano-bioprobe for the flow-cytometric detection of acute myeloid leukaemia (AML) cells. Au-NCs with {approx} 25-28 atoms showing bright red-NIR fluorescence (600-750 nm) and average size of {approx} 0.8 nm were prepared by bovine serum albumin assisted reduction-cum-stabilization in aqueous phase. The protein protected clusters were conjugated with monoclonal antibody against CD33 myeloid antigen, which is overexpressed in {approx} 99.2% of the primitive population of AML cells, as confirmed by immunophenotyping using flow cytometry. Au-NC-CD33 conjugates having average size of {approx} 12 nm retained bright fluorescence over an extended duration of {approx} a year, as the albumin protein protects Au-NCs against degradation. Nanotoxicity studies revealed excellent biocompatibility of Au-NC conjugates, as they showed no adverse effect on the cell viability and inflammatory response. Target specificity of the conjugates for detecting CD33 expressing AML cells (KG1a) in flow cytometry showed specific staining of {approx} 95.4% of leukaemia cells within 1-2 h compared to a non-specific uptake of {approx} 8.2% in human peripheral blood cells (PBMCs) which are CD33{sup low}. The confocal imaging also demonstrated the targeted uptake of CD33 conjugated Au-NCs by leukaemia cells, thus confirming the flow cytometry results. This study demonstrates that novel nano-bioprobes can be developed using protein protected fluorescent nanoclusters of Au for the molecular receptor targeted flow cytometry based detection and imaging of cancer cells.

  9. Sensor and methods of detecting target materials and situations in closed systems

    Energy Technology Data Exchange (ETDEWEB)

    Mee, David K.; Ripley, Edward B.; Nienstedt, Zachary C.; Nienstedt, Alex W.; Howell, Jr., Layton N.

    2018-03-13

    Disclosed is a passive, in-situ pressure sensor. The sensor includes a sensing element having a ferromagnetic metal and a tension inducing mechanism coupled to the ferromagnetic metal. The tension inducing mechanism is operable to change a tensile stress upon the ferromagnetic metal based on a change in pressure in the sensing element. Changes in pressure are detected based on changes in the magnetic switching characteristics of the ferromagnetic metal when subjected to an alternating magnetic field caused by the change in the tensile stress. The sensing element is embeddable in a closed system for detecting pressure changes without the need for any penetrations of the system for power or data acquisition by detecting changes in the magnetic switching characteristics of the ferromagnetic metal caused by the tensile stress.

  10. Development and Testing of a Multiple Frequency Continuous Wave Radar for Target Detection and Classification

    Science.gov (United States)

    2007-03-01

    1 2’ VIH " 1 ’ 󈧏) (34) where is the modified Bessel function of zero order. Here is the conditional variance and is the conditional probability...10, the probability of detection is the area under the signal-plus-noise curve above the detection threshold co M vF (V 2+ A2)]10 ( vAPd= fnp~ju,( vIH ...Spectrogram O /STFT < 12 +J F Q’I " ’ " ""-’"’" -STFT TFRgram 2I1+ IST 21 U- •’j -/STFT,, I HP STFT ISTFTI Figure 19. 3FCW radar processing prior to

  11. Detectability Measurement of GPR for Buried Target in Self-Designed Test Field

    International Nuclear Information System (INIS)

    Son, Soo Jung; Shin, Byoung Chul

    2000-01-01

    In this paper, we were investigated the detectability on various specimen in self-designed test field using the GPR system with three antenna elements. The GPR system was constantly radiated 730MHz frequency. To examine the detectability on various condition, the test were experimented using different materials, size and buried depth. As an adjusted wave-propagation velocity, the location of hyperbolic curve pattern were displayed B-scan CRT. And the pattern was exactly positioned when it was compared to the real buried-depth. Therefore, we can confirm similarity between the wave-propagation velocity and previous results

  12. Improving specificity of Bordetella pertussis detection using a four target real-time PCR.

    Directory of Open Access Journals (Sweden)

    Helena Martini

    Full Text Available 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.

  13. Improving specificity of Bordetella pertussis detection using a four target real-time PCR

    Science.gov (United States)

    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. PMID:28403204

  14. Detection of Traffic Initiated by Mobile Malware Targeting Android Devices in 3GPP Networks

    OpenAIRE

    Kühnel, Marián

    2017-01-01

    Android devices have become the most popular of mobile devices; omnipresent in both business and private use. They are virtually always on and offer functionalities exceeding those of desktop computers. These properties, as well as sensitive information stored on Android devices, render them an attractive target for mobile malware authors. As the volume of mobile malware increases, analysis is becoming challenging and, sometimes, infeasible. Additionally, current network-based intrusion detec...

  15. Detection of Fast Moving and Accelerating Targets Compensating Range and Doppler Migration

    Science.gov (United States)

    2014-06-01

    TR–2978 UNCLASSIFIED the chirp bandwidth is changed from pulse to pulse to realise the range migration com- pensation. Also, Dai et. al. [11] proposed...injected at different closing velocities and acceleration values . Figure 1(a) shows the range-Doppler map of a non-accelarating target moving at 100 knots...increase the noise floor. Hence, consideration must be given to establish a criteria for the combination processing to achieve a net SNR improvement for a

  16. Fluorometric detection of adenine in target DNA by exciplex formation with fluorescent 8-arylethynylated deoxyguanosine.

    Science.gov (United States)

    Saito, Yoshio; Kugenuma, Kenji; Tanaka, Makiko; Suzuki, Azusa; Saito, Isao

    2012-06-01

    We demonstrated an intriguing method to discriminate adenine by incident appearance of an intense new emission via exciplex formation in hybridization of target DNA with newly designed fluorescent 8-arylethynylated deoxyguanosine derivatives. We described the synthesis of such highly electron donating fluorescent guanosine derivatives and their incorporation into DNA oligomers which may be used for the structural study and the fluorometric analysis of nucleic acids. Copyright © 2012 Elsevier Ltd. All rights reserved.

  17. Noninvasive Prenatal Detection of Trisomy 21 by Targeted Semiconductor Sequencing: A Technical Feasibility Study.

    Science.gov (United States)

    Xi, Yanwei; Arbabi, Aryan; McNaughton, Amy J M; Hamilton, Alison; Hull, Danna; Perras, Helene; Chiu, Tillie; Morrison, Shawna; Goldsmith, Claire; Creede, Emilie; Anger, Gregory J; Honeywell, Christina; Cloutier, Mireille; Macchio, Natasha; Kiss, Courtney; Liu, Xudong; Crocker, Susan; Davies, Gregory A; Brudno, Michael; Armour, Christine M

    2017-01-01

    To develop an alternate noninvasive prenatal testing method for the assessment of trisomy 21 (T21) using a targeted semiconductor sequencing approach. A customized AmpliSeq panel was designed with 1,067 primer pairs targeting specific regions on chromosomes 21, 18, 13, and others. A total of 235 samples, including 30 affected with T21, were sequenced with an Ion Torrent Proton sequencer, and a method was developed for assessing the probability of fetal aneuploidy via derivation of a risk score. Application of the derived risk score yields a bimodal distribution, with the affected samples clustering near 1.0 and the unaffected near 0. For a risk score cutoff of 0.345, above which all would be considered at "high risk," all 30 T21-positive pregnancies were correctly predicted to be affected, and 199 of the 205 non-T21 samples were correctly predicted. The average hands-on time spent on library preparation and sequencing was 19 h in total, and the average number of reads of sequence obtained was 3.75 million per sample. With the described targeted sequencing approach on the semiconductor platform using a custom-designed library and a probabilistic statistical approach, we have demonstrated the feasibility of an alternate method of assessment for fetal T21. © 2017 S. Karger AG, Basel.

  18. 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.

  19. Nanotechnology-Based Detection and Targeted Therapy in Cancer: Nano-Bio Paradigms and Applications

    Energy Technology Data Exchange (ETDEWEB)

    Mousa, Shaker A., E-mail: shaker.mosua@acphs.edu [The Pharmaceutical Research Institute at Albany College of Pharmacy and Health Sciences, 1 Discovery Drive, Rensselaer, NY 12144 (United States); College of Medicine, King Saud University, Riyadh (Saudi Arabia); Bharali, Dhruba J. [The Pharmaceutical Research Institute at Albany College of Pharmacy and Health Sciences, 1 Discovery Drive, Rensselaer, NY 12144 (United States)

    2011-07-15

    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.

  20. 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.

  1. Extracellular polysaccharides as target compounds for the immunological detection of Aspergillus and Penicillium in food

    NARCIS (Netherlands)

    Kamphuis, H.J.

    1992-01-01

    This thesis is devoted to the immunological detection of Aspergillus and Penicillium in food products. More specifically, the immunogenicity, antigenicity, production and structure of the water-soluble extracellular polysaccharides (EPS) of these

  2. Nanotechnology-Based Detection and Targeted Therapy in Cancer: Nano-Bio Paradigms and Applications

    International Nuclear Information System (INIS)

    Mousa, Shaker A.; Bharali, Dhruba J.

    2011-01-01

    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

  3. 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 ≲ c BSA ≲ 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 ≲ c BSA ≲ 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.

  4. 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.

  5. Selective Detection of Target Volatile Organic Compounds in Contaminated Humid Air Using a Sensor Array with Principal Component Analysis

    Science.gov (United States)

    Itoh, Toshio; Akamatsu, Takafumi; Tsuruta, Akihiro; Shin, Woosuck

    2017-01-01

    We investigated selective detection of the target volatile organic compounds (VOCs) nonanal, n-decane, and acetoin for lung cancer-related VOCs, and acetone and methyl i-butyl ketone for diabetes-related VOCs, in humid air with simulated VOC contamination (total concentration: 300 μg/m3). We used six “grain boundary-response type” sensors, including four commercially available sensors (TGS 2600, 2610, 2610, and 2620) and two Pt, Pd, and Au-loaded SnO2 sensors (Pt, Pd, Au/SnO2), and two “bulk-response type” sensors, including Zr-doped CeO2 (CeZr10), i.e., eight sensors in total. We then analyzed their sensor signals using principal component analysis (PCA). Although the six “grain boundary-response type” sensors were found to be insufficient for selective detection of the target gases in humid air, the addition of two “bulk-response type” sensors improved the selectivity, even with simulated VOC contamination. To further improve the discrimination, we selected appropriate sensors from the eight sensors based on the PCA results. The selectivity to each target gas was maintained and was not affected by contamination. PMID:28753948

  6. 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.

  7. Non-targeted detection of chemical contamination in carbonated soft drinks using NMR spectroscopy, variable selection and chemometrics

    International Nuclear Information System (INIS)

    Charlton, Adrian J.; Robb, Paul; Donarski, James A.; Godward, John

    2008-01-01

    An efficient method for detecting malicious and accidental contamination of foods has been developed using a combined 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 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

  8. 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.

  9. Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data.

    Directory of Open Access Journals (Sweden)

    Anne Bruun Krøigård

    Full Text Available 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 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 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 and Virmid for the detection of single nucleotide mutations and small deletions and insertions. We report a large variation in the number of calls from the nine somatic variant callers on the same sequencing data and highly variable agreement. Sequencing depth had markedly diverse impact on individual callers, as for some callers, increased sequencing depth highly improved sensitivity. For SNV calling, we report EBCall, Mutect, Virmid and Strelka to be the most reliable somatic variant callers for both exome sequencing and targeted deep sequencing. For indel calling, EBCall is superior due to high sensitivity and robustness to changes in sequencing depths.

  10. Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data.

    Science.gov (United States)

    Krøigård, Anne Bruun; Thomassen, Mads; Lænkholm, Anne-Vibeke; Kruse, Torben A; Larsen, Martin Jakob

    2016-01-01

    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 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 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 and Virmid for the detection of single nucleotide mutations and small deletions and insertions. We report a large variation in the number of calls from the nine somatic variant callers on the same sequencing data and highly variable agreement. Sequencing depth had markedly diverse impact on individual callers, as for some callers, increased sequencing depth highly improved sensitivity. For SNV calling, we report EBCall, Mutect, Virmid and Strelka to be the most reliable somatic variant callers for both exome sequencing and targeted deep sequencing. For indel calling, EBCall is superior due to high sensitivity and robustness to changes in sequencing depths.

  11. Expression profiling on high-density DNA grids to detect novel targets in dendritic cells

    International Nuclear Information System (INIS)

    Weissmann, M.

    2000-10-01

    Gene expression analyzes on a large scale using DNA microarrays is a novel approach to study transcription of thousands of genes in parallel. By comparing gene expression profiles of different cell-types and of cells in different activation, novel regulatory networks will be identified that are unique to a cell-type and hence, important in its biological function. Among the differentially expressed genes many novel drug targets will be found. The Genetic department of the Novartis Research Institute was following this approach to identify novel genes, which are critical in the antigen presenting function of DCs and could become promising drug targets. Drugs that modulate effector functions of DCs towards induction of energy or tolerance in T-cells could be useful in the treatment of chronic inflammatory or autoimmune diseases. By using specific robotics equipment high-density cDNA grids on nylon membranes have been produced for hybridizations with various radioactive labeled DNA probes. By our format, based on 384 well plates and limited by the resolution power of our current image analysis software, 27.648 cDNA clones, bacterial colonies or pure DNA, were spotted on one filter. For RNA profiling, we generated filters containing a collection of genes expressed in peripheral blood DCs or monocytes and characterized by oligonucleotide fingerprinting (ONF) as being differentially expressed. The gene collection contained many unknown genes. Sequence analysis of to date 18.000 cDNA clones led to an estimate of 5.000 non-redundant genes being represented in the collection. 10 % of them are either completely unknown or homologous to rare ESTs (expressed sequence tags) in the public EST database. These clones occurred predominantly in small fingerprint clusters and were therefore assumed to be rarely expressed in DCs or monocytes. Some of those genes may become novel drug targets if their expression is DC specific or induced by external stimuli driving DCs into

  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

    2016-11-30

    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 >10 7  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. Subpixel mapping and test beam studies with a HV2FEI4v2 CMOS-Sensor-Hybrid Module for the ATLAS inner detector upgrade

    Science.gov (United States)

    Bisanz, T.; Große-Knetter, J.; Quadt, A.; Rieger, J.; Weingarten, J.

    2017-08-01

    The upgrade to the High Luminosity Large Hadron Collider will increase the instantaneous luminosity by more than a factor of 5, thus creating significant challenges to the tracking systems of all experiments. Recent advancement of active pixel detectors designed in CMOS processes provide attractive alternatives to the well-established hybrid design using passive sensors since they allow for smaller pixel sizes and cost effective production. This article presents studies of a high-voltage CMOS active pixel sensor designed for the ATLAS tracker upgrade. The sensor is glued to the read-out chip of the Insertable B-Layer, forming a capacitively coupled pixel detector. The pixel pitch of the device under test is 33× 125 μm2, while the pixels of the read-out chip have a pitch of 50× 250 μm2. Three pixels of the CMOS device are connected to one read-out pixel, the information of which of these subpixels is hit is encoded in the amplitude of the output signal (subpixel encoding). Test beam measurements are presented that demonstrate the usability of this subpixel encoding scheme.

  14. Subpixel edge estimation with lens aberrations compensation based on the iterative image approximation for high-precision thermal expansion measurements of solids

    Science.gov (United States)

    Inochkin, F. M.; Kruglov, S. K.; Bronshtein, I. G.; Kompan, T. A.; Kondratjev, S. V.; Korenev, A. S.; Pukhov, N. F.

    2017-06-01

    A new method for precise subpixel edge estimation is presented. The principle of the method is the iterative image approximation in 2D with subpixel accuracy until the appropriate simulated is found, matching the simulated and acquired images. A numerical image model is presented consisting of three parts: an edge model, object and background brightness distribution model, lens aberrations model including diffraction. The optimal values of model parameters are determined by means of conjugate-gradient numerical optimization of a merit function corresponding to the L2 distance between acquired and simulated images. Computationally-effective procedure for the merit function calculation along with sufficient gradient approximation is described. Subpixel-accuracy image simulation is performed in a Fourier domain with theoretically unlimited precision of edge points location. The method is capable of compensating lens aberrations and obtaining the edge information with increased resolution. Experimental method verification with digital micromirror device applied to physically simulate an object with known edge geometry is shown. Experimental results for various high-temperature materials within the temperature range of 1000°C..2400°C are presented.

  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. Increasing Early Detection of Prostate Cancer in African American Men through a Culturally Targeted Print Intervention

    Science.gov (United States)

    2008-06-01

    and brittle bones . 8 INFORM YOUR DOCTOR Certain activities, conditions, and substances can also affect PSA levels, including: • medicines (such as...Growth rates for this type of cancer can vary. Studies have shown that prostate tumors grow at different rates in different people . While some...This is one reason why early detection may be important. • When the cancer spreads beyond the prostate, it becomes more difficult to manage and the

  17. Targeted next generation sequencing for the detection of ciprofloxacin resistance markers using molecular inversion probes

    Science.gov (United States)

    2016-07-06

    ecological studies have shown development of antibiotic resistance in bacterial pathogens caused by increased antibiotic usage in animals , food, and...et al. Danish Integrated Antimicrobial Resistance Monitoring and Research Program. Emerging Infectious Diseases 13, 1633-1639, doi:10.3201...F. J. Molecular detection of antimicrobial resistance . Clin. Microbiol. Rev. 14, 836-871, table of contents, doi:10.1128/CMR.14.4.836-871.2001

  18. System for Automatic Detection and Analysis of Targets in FMICW Radar Signal

    Czech Academy of Sciences Publication Activity Database

    Rejfek, Luboš; Mošna, Zbyšek; Urbář, Jaroslav; Koucká Knížová, Petra

    2016-01-01

    Roč. 67, č. 1 (2016), s. 36-41 ISSN 1335-3632 R&D Projects: GA ČR(CZ) GAP209/12/2440; GA ČR(CZ) GA15-24688S Institutional support: RVO:68378289 Keywords : power spectral density (PSD) * FMICW radar * Doppler measurement * thresholding * false alert detection Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.483, year: 2016 http://iris.elf.stuba.sk/JEEEC/data/pdf/1_116-05.pdf

  19. An N-targeting real-time PCR strategy for the accurate detection of spring viremia of carp virus.

    Science.gov (United States)

    Shao, Ling; Xiao, Yu; He, Zhengkan; Gao, Longying

    2016-03-01

    Spring viremia of carp virus (SVCV) is a highly pathogenic agent of several economically important Cyprinidae fish species. Currently, there are no effective vaccines or drugs for this virus, and prevention of the disease mostly relies on prompt diagnosis. Previously, nested RT-PCR and RT-qPCR detection methods based on the glycoprotein gene G have been developed. However, the high genetic diversity of the G gene seriously limits the reliability of those methods. Compared with the G gene, phylogenetic analyses indicate that the nucleoprotein gene N is more conserved. Furthermore, studies in other members of the Rhabdoviridae family reveals that their gene transcription level follows the order N>P>M>G>L, indicating that an N gene based RT-PCR should have higher sensitivity. Therefore, two pairs of primers and two corresponding probes targeting the conserved regions of the N gene were designed. RT-qPCR assays demonstrated all primers and probes could detect phylogenetically distant isolates specifically and efficiently. Moreover, in artificially infected fish, the detected copy numbers of the N gene were much higher than those of the G gene in all tissues, and both the N and G gene copy numbers were highest in the kidney and spleen. Testing in 1100 farm-raised fish also showed that the N-targeting strategy was more reliable than the G-targeting methods. The method developed in this study provides a reliable tool for the rapid diagnosis of SVCV. Copyright © 2015 Elsevier B.V. All rights reserved.

  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. Molecular targets in urothelial cancer: detection, treatment, and animal models of bladder cancer

    Science.gov (United States)

    Smolensky, Dmitriy; Rathore, Kusum; Cekanova, Maria

    2016-01-01

    Bladder cancer remains one of the most expensive cancers to treat in the United States due to the length of required treatment and degree of recurrence. In order to treat bladder cancer more effectively, targeted therapies are being investigated. In order to use targeted therapy in a patient, it is important to provide a genetic background of the patient. Recent advances in genome sequencing, as well as transcriptome analysis, have identified major pathway components altered in bladder cancer. The purpose of this review is to provide a broad background on bladder cancer, including its causes, diagnosis, stages, treatments, animal models, as well as signaling pathways in bladder cancer. The major focus is given to the PI3K/AKT pathway, p53/pRb signaling pathways, and the histone modification machinery. Because several promising immunological therapies are also emerging in the treatment of bladder cancer, focus is also given on general activation of the immune system for the treatment of bladder cancer. PMID:27784990

  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. Practical target location and accuracy indicator in digital close range photogrammetry using consumer grade cameras

    Science.gov (United States)

    Moriya, Gentaro; Chikatsu, Hirofumi

    2011-07-01

    Recently, pixel numbers and functions of consumer grade digital camera are amazingly increasing by modern semiconductor and digital technology, and there are many low-priced consumer grade digital cameras which have more than 10 mega pixels on the market in Japan. In these circumstances, digital photogrammetry using consumer grade cameras is enormously expected in various application fields. There is a large body of literature on calibration of consumer grade digital cameras and circular target location. Target location with subpixel accuracy had been investigated as a star tracker issue, and many target location algorithms have been carried out. It is widely accepted that the least squares models with ellipse fitting is the most accurate algorithm. However, there are still problems for efficient digital close range photogrammetry. These problems are reconfirmation of the target location algorithms with subpixel accuracy for consumer grade digital cameras, relationship between number of edge points along target boundary and accuracy, and an indicator for estimating the accuracy of normal digital close range photogrammetry using consumer grade cameras. With this motive, an empirical testing of several algorithms for target location with subpixel accuracy and an indicator for estimating the accuracy are investigated in this paper using real data which were acquired indoors using 7 consumer grade digital cameras which have 7.2 mega pixels to 14.7 mega pixels.

  4. G-quadruplex aptamer targeting Protein A and its capability to detect Staphylococcus aureus demonstrated by ELONA

    OpenAIRE

    Stoltenburg, Regina; Kraf?ikov?, Petra; V?glask?, 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 P...

  5. 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.

  6. Development and application of deep convolutional neural network in target detection

    Science.gov (United States)

    Jiang, Xiaowei; Wang, Chunping; Fu, Qiang

    2018-04-01

    With the development of big data and algorithms, deep convolution neural networks with more hidden layers have more powerful feature learning and feature expression ability than traditional machine learning methods, making artificial intelligence surpass human level in many fields. This paper first reviews the development and application of deep convolutional neural networks in the field of object detection in recent years, then briefly summarizes and ponders some existing problems in the current research, and the future development of deep convolutional neural network is prospected.

  7. 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 <10 genome equivalents (GE) in the reaction mixture. Application of the amplification reactions on genomic DNA from a variety of pathogenic and non-pathogenic 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

  8. Targeting Cathepsin E in Pancreatic Cancer by a Small Molecule Allows In Vivo Detection

    Directory of Open Access Journals (Sweden)

    Edmund J. Keliher

    2013-07-01

    Full Text Available When resectable, invasive pancreatic ductal adenocarcinoma (PDAC is most commonly treated with surgery and radiochemotherapy. Given the intricate local anatomy and locoregional mode of dissemination, achieving clean surgical margins can be a significant challenge. On the basis of observations that cathepsin E (CTSE is overexpressed in PDAC and that an United States Food and Drug Administration (FDA-approved protease inhibitor has high affinity for CTSE, we have developed a CTSE optical imaging agent [ritonavir tetramethyl-BODIPY (RIT-TMB] for potential intraoperative use.We show nanomolar affinity [half maximal inhibitory concentration (IC50 of 39.9 ± 1.2 nM] against CTSE of the RIT-TMB in biochemical assays and intracellular accumulation and target-to-background ratios that allow specific delineation of individual cancer cells. This approach should be useful for more refined surgical staging, planning, and resection with curative intent.

  9. Automatic optimal filament segmentation with sub-pixel accuracy using generalized linear models and B-spline level-sets.

    Science.gov (United States)

    Xiao, Xun; Geyer, Veikko F; Bowne-Anderson, Hugo; Howard, Jonathon; Sbalzarini, Ivo F

    2016-08-01

    Biological filaments, such as actin filaments, microtubules, and cilia, are often imaged using different light-microscopy techniques. Reconstructing the filament curve from the acquired images constitutes the filament segmentation problem. Since filaments have lower dimensionality than the image itself, there is an inherent trade-off between tracing the filament with sub-pixel accuracy and avoiding noise artifacts. Here, we present a globally optimal filament segmentation method based on B-spline vector level-sets and a generalized linear model for the pixel intensity statistics. We show that the resulting optimization problem is convex and can hence be solved with global optimality. We introduce a simple and efficient algorithm to compute such optimal filament segmentations, and provide an open-source implementation as an ImageJ/Fiji plugin. We further derive an information-theoretic lower bound on the filament segmentation error, quantifying how well an algorithm could possibly do given the information in the image. We show that our algorithm asymptotically reaches this bound in the spline coefficients. We validate our method in comprehensive benchmarks, compare with other methods, and show applications from fluorescence, phase-contrast, and dark-field microscopy. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  10. A novel, simple and rapid nondenaturing FISH (ND-FISH) technique for the detection of plant telomeres. Potential used and possible target structures detected.

    Science.gov (United States)

    Cuadrado, Angeles; Golczyk, Hieronim; Jouve, Nicolás

    2009-01-01

    We report a new technique-nondenaturing FISH (ND-FISH)-for the rapid detection of plant telomeres without the need for prior denaturation of the chromosomes. In its development, two modified, synthetic oligonucleotides, 21 nt in length, fluorescently labelled at their 5' and 3' ends and complementary to either the cytidine-rich (C(3)TA(3)) or guanosine-rich (T(3)AG(3)) telomeric DNA strands, were used as probes. The high binding affinity of these probes and the short hybridization time required allows the visualization of plant telomeres in less than an hour. In tests, both probes gave strong signals visualized as double spots at both chromosome ends; this was true of both the mitotic and meiotic chromosomes of barley, wheat, rye, maize, Brachypodium distachyon and Rhoeo spathacea. They were also able to detect telomere motifs at certain intercalary sites in the chromosomes of R. spathacea. To investigate the nature of the target structures detected, the chromosomes were treated with RNase A and single strand-specific nuclease S1 before ND-FISH experiments. Signal formation was resistant to standard enzymatic treatment, but sensitive when much higher enzyme concentrations were used. The results are discussed in relation to current knowledge of telomere structure.

  11. 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.

  12. Small-target leak detection for a closed vessel via infrared image sequences

    Science.gov (United States)

    Zhao, Ling; Yang, Hongjiu

    2017-03-01

    This paper focus on a leak diagnosis and localization method based on infrared image sequences. Some problems on high probability of false warning and negative affect for marginal information are solved by leak detection. An experimental model is established for leak diagnosis and localization on infrared image sequences. The differential background prediction is presented to eliminate the negative affect of marginal information on test vessel based on a kernel regression method. A pipeline filter based on layering voting is designed to reduce probability of leak point false warning. A synthesize leak diagnosis and localization algorithm is proposed based on infrared image sequences. The effectiveness and potential are shown for developed techniques through experimental results.

  13. 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.

  14. 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

  15. The selective processing of emotional visual stimuli while detecting auditory targets: an ERP analysis.

    Science.gov (United States)

    Schupp, Harald T; Stockburger, Jessica; Bublatzky, Florian; Junghöfer, Markus; Weike, Almut I; Hamm, Alfons O

    2008-09-16

    Event-related potential studies revealed an early posterior negativity (EPN) for emotional compared to neutral pictures. Exploring the emotion-attention relationship, a previous study observed that a primary visual discrimination task interfered with the emotional modulation of the EPN component. To specify the locus of interference, the present study assessed the fate of selective visual emotion processing while attention is directed towards the auditory modality. While simply viewing a rapid and continuous stream of pleasant, neutral, and unpleasant pictures in one experimental condition, processing demands of a concurrent auditory target discrimination task were systematically varied in three further experimental conditions. Participants successfully performed the auditory task as revealed by behavioral performance and selected event-related potential components. Replicating previous results, emotional pictures were associated with a larger posterior negativity compared to neutral pictures. Of main interest, increasing demands of the auditory task did not modulate the selective processing of emotional visual stimuli. With regard to the locus of interference, selective emotion processing as indexed by the EPN does not seem to reflect shared processing resources of visual and auditory modality.

  16. Globular domain of adiponectin: promising target molecule for detection of atherosclerotic lesions

    Science.gov (United States)

    Almer, Gunter; Saba-Lepek, Matthias; Haj-Yahya, Samih; Rohde, Eva; Strunk, Dirk; Fröhlich, Eleonore; Prassl, Ruth; Mangge, Harald

    2011-01-01

    Background: Adiponectin, an adipocyte-specific plasma protein, has been shown to accumulate in injured endothelial cells during development of atherosclerotic lesions. In this study, we investigated the potential of different adiponectin subfractions with special emphasis on globular adiponectin (gAd) to recognize and visualize atherosclerotic lesions. Methods: Recombinant mouse gAd and subfractions of full-length adiponectin (ie, trimeric, hexameric, and oligomeric forms) were fluorescence-labeled. Aortas of wild-type and apoprotein E-deficient mice fed a high cholesterol diet were dissected and incubated with the labeled biomarkers. Imaging was performed using confocal laser scanning microscopy. Results: Confocal laser scanning microscopic images showed that gAd binds more strongly to atherosclerotic plaques than full-length adiponectin subfractions. Further, we showed that gAd accumulates preferentially in endothelial cells and the fibrous cap area of plaques. Here we demonstrate for the first time that gAd recognizes atherosclerotic plaques on aortic sections of apoprotein E-deficient mice. Conclusion: These results suggest that gAd, in addition to its physiological properties, is also suitable as a target molecule for prospective diagnostic strategies in imaging atherosclerotic lesions. PMID:22022204

  17. A mitochondria-targeted mass spectrometry probe to detect glyoxals: implications for diabetes☆

    Science.gov (United States)

    Pun, Pamela Boon Li; Logan, Angela; Darley-Usmar, Victor; Chacko, Balu; Johnson, Michelle S.; Huang, Guang W.; Rogatti, Sebastian; Prime, Tracy A.; Methner, Carmen; Krieg, Thomas; Fearnley, Ian M.; Larsen, Lesley; Larsen, David S.; Menger, Katja E.; Collins, Yvonne; James, Andrew M.; Kumar, G.D. Kishore; Hartley, Richard C.; Smith, Robin A.J.; Murphy, Michael P.

    2014-01-01

    The glycation of protein and nucleic acids that occurs as a consequence of hyperglycemia disrupts cell function and contributes to many pathologies, including those associated with diabetes and aging. Intracellular glycation occurs after the generation of the reactive 1,2-dicarbonyls methylglyoxal and glyoxal, and disruption of mitochondrial function is associated with hyperglycemia. However, the contribution of these reactive dicarbonyls to mitochondrial damage in pathology is unclear owing to uncertainties about their levels within mitochondria in cells and in vivo. To address this we have developed a mitochondria-targeted reagent (MitoG) designed to assess the levels of mitochondrial dicarbonyls within cells. MitoG comprises a lipophilic triphenylphosphonium cationic function, which directs the molecules to mitochondria within cells, and an o-phenylenediamine moiety that reacts with dicarbonyls to give distinctive and stable products. The extent of accumulation of these diagnostic heterocyclic products can be readily and sensitively quantified by liquid chromatography–tandem mass spectrometry, enabling changes to be determined. Using the MitoG-based analysis we assessed the formation of methylglyoxal and glyoxal in response to hyperglycemia in cells in culture and in the Akita mouse model of diabetes in vivo. These findings indicated that the levels of methylglyoxal and glyoxal within mitochondria increase during hyperglycemia both in cells and in vivo, suggesting that they can contribute to the pathological mitochondrial dysfunction that occurs in diabetes and aging. PMID:24316194

  18. A mitochondria-targeted mass spectrometry probe to detect glyoxals: implications for diabetes.

    Science.gov (United States)

    Pun, Pamela Boon Li; Logan, Angela; Darley-Usmar, Victor; Chacko, Balu; Johnson, Michelle S; Huang, Guang W; Rogatti, Sebastian; Prime, Tracy A; Methner, Carmen; Krieg, Thomas; Fearnley, Ian M; Larsen, Lesley; Larsen, David S; Menger, Katja E; Collins, Yvonne; James, Andrew M; Kumar, G D Kishore; Hartley, Richard C; Smith, Robin A J; Murphy, Michael P

    2014-02-01

    The glycation of protein and nucleic acids that occurs as a consequence of hyperglycemia disrupts cell function and contributes to many pathologies, including those associated with diabetes and aging. Intracellular glycation occurs after the generation of the reactive 1,2-dicarbonyls methylglyoxal and glyoxal, and disruption of mitochondrial function is associated with hyperglycemia. However, the contribution of these reactive dicarbonyls to mitochondrial damage in pathology is unclear owing to uncertainties about their levels within mitochondria in cells and in vivo. To address this we have developed a mitochondria-targeted reagent (MitoG) designed to assess the levels of mitochondrial dicarbonyls within cells. MitoG comprises a lipophilic triphenylphosphonium cationic function, which directs the molecules to mitochondria within cells, and an o-phenylenediamine moiety that reacts with dicarbonyls to give distinctive and stable products. The extent of accumulation of these diagnostic heterocyclic products can be readily and sensitively quantified by liquid chromatography-tandem mass spectrometry, enabling changes to be determined. Using the MitoG-based analysis we assessed the formation of methylglyoxal and glyoxal in response to hyperglycemia in cells in culture and in the Akita mouse model of diabetes in vivo. These findings indicated that the levels of methylglyoxal and glyoxal within mitochondria increase during hyperglycemia both in cells and in vivo, suggesting that they can contribute to the pathological mitochondrial dysfunction that occurs in diabetes and aging. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

  19. In vivo detection of c-MET expression in a rat hepatocarcinogenesis model using molecularly targeted magnetic resonance imaging.

    Science.gov (United States)

    Towner, Rheal A; Smith, Nataliya; Tesiram, Yasvir A; Abbott, Andrew; Saunders, Debbie; Blindauer, Rebecca; Herlea, Oana; Silasi-Mansat, Robert; Lupu, Florea

    2007-01-01

    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 T(2) 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.

  20. In Vivo Detection of c-MET Expression in a Rat Hepatocarcinogenesis Model Using Molecularly Targeted Magnetic Resonance Imaging

    Directory of Open Access Journals (Sweden)

    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.

  1. Marine target detection in quad-pol synthetic aperture radar imagery based on the relative phase of cross-polarized channels

    Science.gov (United States)

    Wang, Yunhua; Li, Huimin; Zhang, Yanmin; Guo, Lixin

    2015-01-01

    A focus on marine target detection in noise corrupted fully polarimetric synthetic aperture radar (SAR) is presented. The property of the relative phase between two cross-polarized channels reveals that the relative phases evaluated within sea surface area or noise corrupted area are widely spread phase angle region [-π,π] due to decorrelation effect; however, the relative phases are concentrated to zero and ±π for real target and its first-order azimuth ambiguities (FOAAs), respectively. Exploiting this physical behavior, the reciprocal of the mean square value of the relative phase (RMSRP) is defined as a new parameter for target detection, and the experiments based on fully polarimetric Radarsat-2 SAR images show that the strong noise and the FOAAs can be effectively suppressed in RMSRP image. Meanwhile, validity of the new parameter for target detection is also verified by two typical Radarsat-2 SAR images, in which targets' ambiguities and strong noise are present.

  2. 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.

  3. Application of Data Mining and Knowledge Discovery Techniques to Enhance Binary Target Detection and Decision-Making for Compromised Visual Images

    National Research Council Canada - National Science Library

    Repperger, D. W; Phillips, C. A; Schrider, C. D; Smith, E. A

    2004-01-01

    In an effort to improve decision-making on the identity of unknown objects appearing in visual images when the surrounding environment may be noisy and cluttered, a highly sensitive target detection...

  4. 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.

  5. 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.

  6. Identification of type IV collagen exposure as a molecular imaging target for early detection of thoracic aortic dissection

    Science.gov (United States)

    Xu, Ke; Xu, Chen; Zhang, Yanzhenzi; Qi, Feiran; Yu, Bingran; Li, Ping; Jia, Lixin; Li, Yulin; Xu, Fu-jian; Du, Jie

    2018-01-01

    Thoracic aortic dissection (TAD) is an aggressive and life-threatening vascular disease and there is no effective means of early diagnosis of dissection. Type IV collagen (Col-IV) is a major component of the sub-endothelial basement membrane, which is initially exposed followed by endothelial injury as early-stage event of TAD. So, we want to build a noninvasive diagnostic method to detect early dissection by identifying the exposed Col-IV via MRI. Methods: Col-IV-targeted magnetic resonance/ fluorescence dual probe (Col-IV-DOTA-Gd-rhodamine B; CDR) was synthesized by amide reaction and coordination reaction. Flow cytometry analysis was used to evaluate the cell viability of SMC treated with CDR and fluorescence assays were used to assess the Col-IV targeting ability of CDR in vitro. We then examined the sensitivity and specificity of CDR at different stages of TAD via MRI and bioluminescence imaging in vivo. Results: The localization of Col-IV (under the intima) was observed by histology images. CDR bound specifically to Col-IV-expressing vascular smooth muscle cells and BAPN-induced dissected aorta. The CDR signal was co-detected by magnetic resonance imaging (MRI) and bioluminescence imaging as early as 2 weeks after BAPN administration (pre-dissection stage). The ability to detect rupture of dissected aorta was indicated by a strong normalized signal enhancement (NSE) in vivo. Moreover, NSE was negatively correlated with the time of dissection rupture after BAPN administration (r2 = 0.8482). Conclusion: As confirmed by in vivo studies, the CDR can identify the exposed Col-IV in degenerated aorta to monitor the progress of aortic dissection from the early stage to the rupture via MRI. Thus, CDR-enhanced MRI proposes a potential method for dissection screening, and for monitoring disease progression and therapeutic response. PMID:29290819

  7. 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.

  8. 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.

  9. Long-range depth profiling of camouflaged targets using single-photon detection

    Science.gov (United States)

    Tobin, Rachael; Halimi, Abderrahim; McCarthy, Aongus; Ren, Ximing; McEwan, Kenneth J.; McLaughlin, Stephen; Buller, Gerald S.

    2018-03-01

    We investigate the reconstruction of depth and intensity profiles from data acquired using a custom-designed time-of-flight scanning transceiver based on the time-correlated single-photon counting technique. The system had an operational wavelength of 1550 nm and used a Peltier-cooled InGaAs/InP single-photon avalanche diode detector. Measurements were made of human figures, in plain view and obscured by camouflage netting, from a stand-off distance of 230 m in daylight using only submilliwatt average optical powers. These measurements were analyzed using a pixelwise cross correlation approach and compared to analysis using a bespoke algorithm designed for the restoration of multilayered three-dimensional light detection and ranging images. This algorithm is based on the optimization of a convex cost function composed of a data fidelity term and regularization terms, and the results obtained show that it achieves significant improvements in image quality for multidepth scenarios and for reduced acquisition times.

  10. Mutation Detection in Patients with Retinal Dystrophies Using Targeted Next Generation Sequencing.

    Directory of Open Access Journals (Sweden)

    Nicole Weisschuh

    Full Text Available Retinal dystrophies (RD constitute a group of blinding diseases that are characterized by clinical variability and pronounced genetic heterogeneity. The different nonsyndromic and syndromic forms of RD can be attributed to mutations in more than 200 genes. Consequently, next generation sequencing (NGS technologies are among the most promising approaches to identify mutations in RD. We screened a large cohort of patients comprising 89 independent cases and families with various subforms of RD applying different NGS platforms. While mutation screening in 50 cases was performed using a RD gene capture panel, 47 cases were analyzed using whole exome sequencing. One family was analyzed using whole genome sequencing. A detection rate of 61% was achieved including mutations in 34 known and two novel RD genes. A total of 69 distinct mutations were identified, including 39 novel mutations. Notably, genetic findings in several families were not consistent with the initial clinical diagnosis. Clinical reassessment resulted in refinement of the clinical diagnosis in some of these families and confirmed the broad clinical spectrum associated with mutations in RD genes.

  11. 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.

  12. Visually directed vs. software-based targeted biopsy compared to transperineal template mapping biopsy in the detection of clinically significant prostate cancer.

    Science.gov (United States)

    Valerio, Massimo; McCartan, Neil; Freeman, Alex; Punwani, Shonit; Emberton, Mark; Ahmed, Hashim U

    2015-10-01

    Targeted biopsy based on cognitive or software magnetic resonance imaging (MRI) to transrectal ultrasound registration seems to increase the detection rate of clinically significant prostate cancer as compared with standard biopsy. However, these strategies have not been directly compared against an accurate test yet. The aim of this study was to obtain pilot data on the diagnostic ability of visually directed targeted biopsy vs. software-based targeted biopsy, considering transperineal template mapping (TPM) biopsy as the reference test. Prospective paired cohort study included 50 consecutive men undergoing TPM with one or more visible targets detected on preoperative multiparametric MRI. Targets were contoured on the Biojet software. Patients initially underwent software-based targeted biopsies, then visually directed targeted biopsies, and finally systematic TPM. The detection rate of clinically significant disease (Gleason score ≥3+4 and/or maximum cancer core length ≥4mm) of one strategy against another was compared by 3×3 contingency tables. Secondary analyses were performed using a less stringent threshold of significance (Gleason score ≥4+3 and/or maximum cancer core length ≥6mm). Median age was 68 (interquartile range: 63-73); median prostate-specific antigen level was 7.9ng/mL (6.4-10.2). A total of 79 targets were detected with a mean of 1.6 targets per patient. Of these, 27 (34%), 28 (35%), and 24 (31%) were scored 3, 4, and 5, respectively. At a patient level, the detection rate was 32 (64%), 34 (68%), and 38 (76%) for visually directed targeted, software-based biopsy, and TPM, respectively. Combining the 2 targeted strategies would have led to detection rate of 39 (78%). At a patient level and at a target level, software-based targeted biopsy found more clinically significant diseases than did visually directed targeted biopsy, although this was not statistically significant (22% vs. 14%, P = 0.48; 51.9% vs. 44.3%, P = 0.24). Secondary

  13. Potential actionable targets in appendiceal cancer detected by immunohistochemistry, fluorescent in situ hybridization, and mutational analysis

    Science.gov (United States)

    Millis, Sherri Z.; Kimbrough, Jeffery; Doll, Nancy; Von Hoff, Daniel; Ramanathan, Ramesh K.

    2017-01-01

    Background Appendiceal cancers are rare and consist of carcinoid, mucocele, pseudomyxoma peritonei (PMP), goblet cell carcinoma, lymphoma, and adenocarcinoma histologies. Current treatment involves surgical resection or debulking, but no standard exists for adjuvant chemotherapy or treatment for metastatic disease. Methods Samples were identified from approximately 60,000 global tumors analyzed at a referral molecular profiling CLIA-certified laboratory. A total of 588 samples with appendix primary tumor sites were identified (male/female ratio of 2:3; mean age =55). Sixty-two percent of samples were adenocarcinomas (used for analysis); the rest consisted of 9% goblet cell, 15% mucinous; 6% pseudomyxoma, and less than 5% carcinoids and 2% neuroendocrine. Tests included sequencing [Sanger, next generation sequencing (NGS)], protein expression/immunohistochemistry (IHC), and gene amplification [fluorescent in situ hybridization (FISH) or CISH]. Results Profiling across all appendiceal cancer histological subtypes for IHC revealed: 97% BRCP, 81% MRP1, 81% COX-2, 71% MGMT, 56% TOPO1, 5% PTEN, 52% EGFR, 40% ERCC1, 38% SPARC, 35% PDGFR, 35% TOPO2A, 25% RRM1, 21% TS, 16% cKIT, and 12% for TLE3. NGS revealed mutations in the following genes: 50.4% KRAS, 21.9% P53, 17.6% GNAS, 16.5% SMAD4, 10% APC, 7.5% ATM, 5.5% PIK3CA, 5.0% FBXW7, and 1.8% BRAF. Conclusions Appendiceal cancers show considerable heterogeneity with high levels of drug resistance proteins (BCRP and MRP1), which highlight the difficulty in treating these tumors and suggest an individualized approach to treatment. The incidence of low TS (79%) could be used as a backbone of therapy (using inhibitors such as 5FU/capecitabine or newer agents). Therapeutic options includeTOPO1 inhibitors (irinotecan/topotecan), EGFR inhibitors (erlotinib, cetuximab), PDGFR antagonists (regorafenib, axitinib), MGMT (temozolomide). Clinical trials targeting pathways involving KRAS, p53, GNAS, SMAD4, APC, ATM, PIK3CA, FBXW7, and

  14. Implementation of a Targeted Screening Program to Detect Airflow Obstruction Suggestive of Chronic Obstructive Pulmonary Disease within a Presurgical Screening Clinic

    Directory of Open Access Journals (Sweden)

    Chantal Robitaille

    2015-01-01

    Full Text Available BACKGROUND: Targeted spirometry screening for chronic obstructive pulmonary disease (COPD has been studied in primary care and community settings. Limitations regarding availability and quality of testing remain. A targeted spirometry screening program was implemented within a presurgical screening (PSS clinic to detect undiagnosed airways disease and identify patients with COPD/asthma in need of treatment optimization.

  15. Optomagnetic Detection of MicroRNA Based on Duplex-Specific Nuclease-Assisted Target Recycling and Multilayer Core-Satellite Magnetic Superstructures

    DEFF Research Database (Denmark)

    Tian, Bo; Ma, Jing; Qiu, Zhen

    2017-01-01

    -efficiency, and potential for bioresponsive multiplexing. Herein, we demonstrate a sensitive and rapid miRNA detection method based on optomagnetic read-out, duplex-specific nuclease (DSN)-assisted target recycling, and the use of multilayer core-satellite magnetic superstructures. Triggered by the presence of target mi...

  16. Evaluation of dual target-specific real-time PCR for the detection of Kingella kingae in a Danish paediatric population

    DEFF Research Database (Denmark)

    de Knegt, Victoria Elizabeth; Kristiansen, Gitte Qvist; Schønning, Kristian

    2017-01-01

    BACKGROUND: We aimed to evaluate the relevance of dual target real-time polymerase chain (PCR) assays targeting the rtxA and cpn60 genes of the paediatric pathogen Kingella kingae. We also studied for the first time the clinical and epidemiological features of K. kingae infections in a Danish pop......-value: peak in autumn. CONCLUSION: Dual target-specific real-time PCR markedly improved the detection of K. kingae in clinical specimens when compared to culture methods....

  17. Targeting safety improvements through identification of incident origination and detection in a near-miss incident learning system

    International Nuclear Information System (INIS)

    Novak, Avrey; Nyflot, Matthew J.; Ermoian, Ralph P.; Jordan, Loucille E.; Sponseller, Patricia A.; Kane, Gabrielle M.; Ford, Eric C.; Zeng, Jing

    2016-01-01

    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.

  18. 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.

  19. Feature-space assessment of electrical impedance tomography coregistered with computed tomography in detecting multiple contrast targets

    International Nuclear Information System (INIS)

    Krishnan, Kalpagam; Liu, Jeff; Kohli, Kirpal

    2014-01-01

    Purpose: 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. Methods: 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. Results: In detecting distilled and normal saline water in bolus medium, EIT as a stand

  20. Simultaneous detection of five different DNA targets by real-time Taqman PCR using the Roche LightCycler480: Application in viral molecular diagnostics

    NARCIS (Netherlands)

    Molenkamp, Richard; van der Ham, Alwin; Schinkel, Janke; Beld, Marcel

    2007-01-01

    One of the most interesting aspects of real-time PCR based on the detection of fluorophoric labeled oligonucleotides is the possibility of being able to detect conveniently multiple targets in the same PCR reaction. Recently, Roche Diagnostics launched a real-time PCR platform, the LightCycler480

  1. Polymerase chain reaction assay targeting cytochrome b gene for the detection of dog meat adulteration in meatball formulation.

    Science.gov (United States)

    Rahman, Md Mahfujur; Ali, Md Eaqub; Hamid, Sharifah Bee Abd; Mustafa, Shuhaimi; Hashim, Uda; Hanapi, Ummi Kalthum

    2014-08-01

    A polymerase chain reaction (PCR) assay for the assessment of dog meat adulteration in meatballs was developed. The assay selectively amplified a 100-bp region of canine mitochondrial cytochrome b gene from pure, raw, processed and mixed backgrounds. The specificity of the assay was tested against 11 animals and 3 plants species, commonly available for meatball formulation. The stability of the assay was proven under extensively autoclaving conditions that breakdown target DNA. A blind test from ready to eat chicken and beef meatballs showed that the assay can repeatedly detect 0.2% canine meat tissues under complex matrices using 0.04 ng of dog DNA extracted from differentially treated meatballs. The simplicity, stability and sensitivity of the assay suggested that it could be used in halal food industry for the authentication of canine derivatives in processed foods. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Detection of siRNA Mediated Target mRNA Cleavage Activities in Human Cells by a Novel Stem-Loop Array RT-PCR Analysis

    Science.gov (United States)

    2016-09-07

    sequences of the target mRNA, and a double stranded stem at the 5′ end that forms a stem -loop to function as a forceps to stabilize the secondary...E-mjournal homepage: www.elsevier.com/locate/bbrepDetection of siRNA-mediated target mRNA cleavage activities in human cells by a novel stem -loop...challenges for the accurate and efficient detection and verification of cleavage sites on target mRNAs. Here we used a sensitive stem -loop array reverse

  3. Detecting Vascular-Targeting Effects of the Hypoxic Cytotoxin Tirapazamine in Tumor Xenografts Using Magnetic Resonance Imaging

    International Nuclear Information System (INIS)

    Bains, Lauren J.; Baker, Jennifer; Kyle, Alastair H.; Minchinton, Andrew I.; Reinsberg, Stefan A.

    2009-01-01

    Purpose: To determine whether vascular-targeting effects can be detected in vivo using magnetic resonance imaging (MRI). Methods and Materials: MR images of HCT-116 xenograft-bearing mice were acquired at 7 Tesla before and 24 hours after intraperitoneal injections of tirapazamine. Quantitative dynamic contrast-enhanced MRI analyses were performed to evaluate changes in tumor perfusion using two biomarkers: the volume transfer constant (K trans ) and the initial area under the concentration-time curve (IAUC). We used novel implanted fiducial markers to obtain cryosections that corresponded to MR image planes from excised tumors; quantitative immunohistochemical mapping of tumor vasculature, perfusion, and necrosis enabled correlative analysis between these and MR images. Results: Conventional histological analysis showed lower vascular perfusion or greater amounts of necrosis in the central regions of five of eight tirapazamine-treated tumors, with three treated tumors showing no vascular dysfunction response. MRI data reflected this result, and a striking decrease in both K trans and IAUC values was seen with the responsive tumors. Retrospective evaluation of pretreatment MRI parameters revealed that those tumors that did not respond to the vascular-targeting effects of tirapazamine had significantly higher pretreatment K trans and IAUC values. Conclusions: MRI-derived parameter maps showed good agreement with histological tumor mapping. MRI was found to be an effective tool for noninvasively monitoring and predicting tirapazamine-mediated central vascular dysfunction.

  4. Power allocation for target detection in radar networks based on low probability of intercept: A cooperative game theoretical strategy

    Science.gov (United States)

    Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

    2017-08-01

    Distributed radar network systems have been shown to have many unique features. Due to their advantage of signal and spatial diversities, radar networks are attractive for target detection. In practice, the netted radars in radar networks are supposed to maximize their transmit power to achieve better detection performance, which may be in contradiction with low probability of intercept (LPI). Therefore, this paper investigates the problem of adaptive power allocation for radar networks in a cooperative game-theoretic framework such that the LPI performance can be improved. Taking into consideration both the transmit power constraints and the minimum signal to interference plus noise ratio (SINR) requirement of each radar, a cooperative Nash bargaining power allocation game based on LPI is formulated, whose objective is to minimize the total transmit power by optimizing the power allocation in radar networks. First, a novel SINR-based network utility function is defined and utilized as a metric to evaluate power allocation. Then, with the well-designed network utility function, the existence and uniqueness of the Nash bargaining solution are proved analytically. Finally, an iterative Nash bargaining algorithm is developed that converges quickly to a Pareto optimal equilibrium for the cooperative game. Numerical simulations and theoretic analysis are provided to evaluate the effectiveness of the proposed algorithm.

  5. 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

    2016-09-21

    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.

  6. MALDI based identification of soybean protein markers--possible analytical targets for allergen detection in processed foods.

    Science.gov (United States)

    Cucu, Tatiana; De Meulenaer, Bruno; Devreese, Bart

    2012-02-01

    Soybean (Glycine max) is extensively used all over the world due to its nutritional qualities. However, soybean is included in the "big eight" list of food allergens. According to the EU directive 2007/68/EC, food products containing soybeans have to be labeled in order to protect the allergic consumers. Nevertheless, soybeans can still inadvertently be present in food products. The development of analytical methods for the detection of traces of allergens is important for the protection of allergic consumers. Mass spectrometry of marker proteolytical fragments of protein allergens is growingly recognized as a detection method in food control. However, quantification of soybean at the peptide level is hindered due to limited information regarding specific stable markers derived after proteolytic digestion. The aim of this study was to use MALDI-TOF/MS and MS/MS as a fast screening tool for the identification of stable soybean derived tryptic markers which were still identifiable even if the proteins were subjected to various changes at the molecular level through a number of reactions typically occurring during food processing (denaturation, the Maillard reaction and oxidation). The peptides (401)Val-Arg(410) from the G1 glycinin (Gly m 6) and the (518)Gln-Arg(528) from the α' chain of the β-conglycinin (Gly m 5) proved to be the most stable. These peptides hold potential to be used as targets for the development of new analytical methods for the detection of soybean protein traces in processed foods. Copyright © 2011 Elsevier Inc. All rights reserved.

  7. 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

    2010-03-01

    Full Text Available 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.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.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.

  8. 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 high mapping accuracy of 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

  9. 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.

  10. Digital breast tomosynthesis (DBT) to characterize MRI-detected additional lesions unidentified at targeted ultrasound in newly diagnosed breast cancer patients

    International Nuclear Information System (INIS)

    Mariscotti, Giovanna; Durando, Manuela; Regini, Elisa; Fornari, Alberto; Fonio, Paolo; Gandini, Giovanni; Houssami, Nehmat; Campanino, Pier Paolo; Bussone, Riccardo; Castellano, Isabella; Sapino, Anna

    2015-01-01

    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.)

  11. 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.)

  12. 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

  13. The effect of mood state on visual search times for detecting a target in noise: An application of smartphone technology.

    Science.gov (United States)

    Maekawa, Toru; Anderson, Stephen J; de Brecht, Matthew; Yamagishi, Noriko

    2018-01-01

    The study of visual perception has largely been completed without regard to the influence that an individual's emotional status may have on their performance in visual tasks. However, there is a growing body of evidence to suggest that mood may affect not only creative abilities and interpersonal skills but also the capacity to perform low-level cognitive tasks. Here, we sought to determine whether rudimentary visual search processes are similarly affected by emotion. Specifically, we examined whether an individual's perceived happiness level affects their ability to detect a target in noise. To do so, we employed pop-out and serial visual search paradigms, implemented using a novel smartphone application that allowed search times and self-rated levels of happiness to be recorded throughout each twenty-four-hour period for two weeks. This experience sampling protocol circumvented the need to alter mood artificially with laboratory-based induction methods. Using our smartphone application, we were able to replicate the classic visual search findings, whereby pop-out search times remained largely unaffected by the number of distractors whereas serial search times increased with increasing number of distractors. While pop-out search times were unaffected by happiness level, serial search times with the maximum numbers of distractors (n = 30) were significantly faster for high happiness levels than low happiness levels (p = 0.02). Our results demonstrate the utility of smartphone applications in assessing ecologically valid measures of human visual performance. We discuss the significance of our findings for the assessment of basic visual functions using search time measures, and for our ability to search effectively for targets in real world settings.

  14. 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

  15. A Framework Based on 2-D Taylor Expansion for Quantifying the Impacts of Subpixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bispectral 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, K.

    2016-01-01

    The bispectral 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 subpixel variations of cloud reflectances can lead to a significant bias in the retrieved t and re. In the literature, the retrievals of t and re are often assumed to be independent and considered separately when investigating the impact of subpixel cloud reflectance variations on the bispectral method. As a result, the impact on t is contributed only by the subpixel variation of VIS/NIR band reflectance and the impact on re only by the subpixel 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 subpixel 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 subpixel cloud reflectance variations impact the t and re retrievals based on the bispectral method. In particular, our framework provides a mathematical explanation of how the subpixel 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. 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

  16. The Effects of Sleep on Emotional Target Detection Performance: A Novel iPad-Based Pediatric Game

    Directory of Open Access Journals (Sweden)

    Annalisa Colonna

    2018-03-01

    .063. Performance improvement after restricted sleep was inversely correlated with sleep opportunity time (p = 0.03, total sleep time (p = 0.01 and total non-REM time (p = 0.005.Conclusion: This tool, designed to be simple to use and appealing to children, revealed a preserving effect of typical and disrupted sleep periods on performance during an emotionally themed target detection task compared with an equivalent wakefulness period.

  17. Robust diagnosis of Ewing sarcoma by immunohistochemical detection of super-enhancer-driven EWSR1-ETS targets

    Science.gov (United States)

    Marchetto, Aruna; Gerke, Julia S.; Rubio, Rebeca Alba; Kiran, Merve M.; Musa, Julian; Knott, Maximilian M. L.; Ohmura, Shunya; Li, Jing; Akpolat, Nusret; Akatli, Ayse N.; Özen, Özlem; Dirksen, Uta; Hartmann, Wolfgang; de Alava, Enrique; Baumhoer, Daniel; Sannino, Giuseppina; Kirchner, Thomas; Grünewald, Thomas G. P.

    2018-01-01

    Ewing sarcoma is an undifferentiated small-round-cell sarcoma. Although molecular detection of pathognomonic EWSR1-ETS fusions such as EWSR1-FLI1 enables definitive diagnosis, substantial confusion can arise if molecular diagnostics are unavailable. Diagnosis based on the conventional immunohistochemical marker CD99 is unreliable due to its abundant expression in morphological mimics. To identify novel diagnostic immunohistochemical markers for Ewing sarcoma, we performed comparative expression analyses in 768 tumors representing 21 entities including Ewing-like sarcomas, which confirmed that CIC-DUX4-, BCOR-CCNB3-, EWSR1-NFATc2-, and EWSR1-ETS-translocated sarcomas are distinct entities, and revealed that ATP1A1, BCL11B, and GLG1 constitute specific markers for Ewing sarcoma. Their high expression was validated by immunohistochemistry and proved to depend on EWSR1-FLI1-binding to highly active proximal super-enhancers. Automated cut-off-finding and combination-testing in a tissue-microarray comprising 174 samples demonstrated that detection of high BCL11B and/or GLG1 expression is sufficient to reach 96% specificity for Ewing sarcoma. While 88% of tested Ewing-like sarcomas displayed strong CD99-immunoreactivity, none displayed combined strong BCL11B- and GLG1-immunoreactivity. Collectively, we show that ATP1A1, BCL11B, and GLG1 are EWSR1-FLI1 targets, of which BCL11B and GLG1 offer a fast, simple, and cost-efficient way to diagnose Ewing sarcoma by immunohistochemistry. These markers may significantly reduce the number of misdiagnosed patients, and thus improve patient care. PMID:29416716

  18. 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.

  19. 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.

  20. Detecting drug-target binding in cells using fluorescence-activated cell sorting coupled with mass spectrometry analysis

    Science.gov (United States)

    Wilson, Kris; Webster, Scott P.; Iredale, John P.; Zheng, Xiaozhong; Homer, Natalie Z.; Pham, Nhan T.; Auer, Manfred; Mole, Damian J.

    2018-01-01

    The assessment of drug-target engagement for determining the efficacy of a compound inside cells remains challenging, particularly for difficult target proteins. Existing techniques are more suited to soluble protein targets. Difficult target proteins include those with challenging in vitro solubility, stability or purification properties that preclude target isolation. Here, we report a novel technique that measures intracellular compound-target complex formation, as well as cellular permeability, specificity and cytotoxicity-the toxicity-affinity-permeability-selectivity (TAPS) technique. The TAPS assay is exemplified here using human kynurenine 3-monooxygenase (KMO), a challenging intracellular membrane protein target of significant current interest. TAPS confirmed target binding of known KMO inhibitors inside cells. We conclude that the TAPS assay can be used to facilitate intracellular hit validation on most, if not all intracellular drug targets.

  1. 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.

  2. The Persistence of Experience: Prior Attentional and Emotional State Affects Network Functioning in a Target Detection Task.

    Science.gov (United States)

    Stern, Emily R; Muratore, Alexandra F; Taylor, Stephan F; Abelson, James L; Hof, Patrick R; Goodman, Wayne K

    2015-09-01

    Efficient, adaptive behavior relies on the ability to flexibly move between internally focused (IF) and externally focused (EF) attentional states. Despite evidence that IF cognitive processes such as event imagination comprise a significant amount of awake cognition, the consequences of internal absorption on the subsequent recruitment of brain networks during EF tasks are unknown. The present functional magnetic resonance imaging (fMRI) study employed a novel attentional state switching task. Subjects imagined positive and negative events (IF task) or performed a working memory task (EF task) before switching to a target detection (TD) task also requiring attention to external information, allowing for the investigation of neural functioning during external attention based on prior attentional state. There was a robust increase of activity in frontal, parietal, and temporal regions during TD when subjects were previously performing the EF compared with IF task, an effect that was most pronounced following negative IF. Additionally, dorsolateral prefrontal cortex was less negatively coupled with ventromedial prefrontal and posterior cingulate cortices during TD following IF compared with EF. These findings reveal the striking consequences for brain activity following immersion in an IF attentional state, which have strong implications for psychiatric disorders characterized by excessive internal focus. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  3. Sustained posterior contralateral activity indicates re-entrant target processing in visual change detection: An EEG study

    Directory of Open Access Journals (Sweden)

    Daniel eSchneider

    2014-05-01

    Full Text Available The present study investigated the neural mechanisms that contribute to the detection of visual feature changes between stimulus displays by means of event-related lateralizations of the electroencephalogram (EEG. Participants were instructed to respond to a luminance change in either of two lateralized stimuli that could randomly occur alone or together with an irrelevant orientation change of the same or contralateral stimulus. Task performance based on response times and accuracy was decreased compared to the remaining stimulus conditions when relevant and irrelevant feature changes were presented contralateral to each other (lateral distractor condition. The sensory response to the feature changes was reflected in a posterior contralateral positivity at around 100ms after change presentation and a posterior contralateral negativity in the N1 time window (N1pc. N2pc reflected a subsequent attentional bias in favor of the relevant luminance change. The continuation of the sustained posterior contralateral negativity (SPCN following N2pc covaried with response times within feature change conditions and revealed a posterior topography comparable to the earlier components associated with sensory and attentional mechanisms. Therefore, this component might reflect the re-processing of information based on sustained short-term memory representations in the visual system until a stable target percept is created that can serve as the perceptual basis for response selection and the initiation of goal-directed behavior.

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

    Science.gov (United States)

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

    2010-01-01

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

  5. The AFIS experiment: Detecting low energetic antiprotons in a low earth orbit, using an active target detector

    Energy Technology Data Exchange (ETDEWEB)

    Poeschl, Thomas; Gaisbauer, Dominic; Greenwald, Daniel; Hahn, Alexander; Hauptmann, Philipp; Konorov, Igor; Meng, Lingxin; Paul, Stephan [Physics Department E18, Technische Universitaet Muenchen (Germany); Losekamm, Martin [Physics Department E18, Technische Universitaet Muenchen (Germany); Institute of Astronautics, Technische Universitaet Muenchen (Germany); Renker, Dieter [Physics Department E17, Technische Universitaet Muenchen (Germany)

    2014-07-01

    Since the first observation of geomagnetically trapped antiprotons by the PAMELA experiment and the new results on the positron excess by the AMS-02 experiment, the creation and transport of antimatter in the Earth's upper atmosphere attracts more and more attention both at theoretical and experimental side. For this reason the AFIS experiment was initiated to measure the flux of low energetic antiprotons in the South Atlantic Anomaly (SAA). We developed an active target detector made from scintillating fibers connected to silicon photomultipliers which allows to detect antiprotons in the energy interval of about 30 MeV-100 MeV. The stopping curve of incoming antiprotons (Bragg peak) and the signal of outgoing pions created from the annihilation, are used for particle identification as well as triggering. We plan to implement this detector on a 3 unit cubesat satellite in the framework the 'Move2Warp' mission, which is carried out as a student project by the Technische Universitaet Muenchen.

  6. Detection of Aspergillus fumigatus pulmonary fungal infections in mice with 99mTc-labeled MORF oligomers targeting ribosomal RNA

    International Nuclear Information System (INIS)

    Wang Yuzhen; Chen Ling; Liu Xinrong; Cheng Dengfeng; Liu Guozheng; Liu Yuxia; Dou Shuping; Hnatowich, Donald J.; Rusckowski, Mary

    2013-01-01

    Purpose: Invasive aspergillosis is a major cause of infectious morbidity and mortality in immunocompromised patients. The fungus Aspergillus fumigatus (A. fumigatus) is the primary causative agent of invasive aspergillosis. However, A. fumigatus infections remain difficult to diagnose particularly in the early stages due to the lack of a rapid, sensitive and specific diagnostic approach. In this study, we investigated 99m Tc labeled MORF oligomers targeting fungal ribosomal RNA (rRNA) for the imaging detection of fungal infections. Procedures: Three phosphorodiamidate morpholino (MORF) oligomer (a DNA analogue) probes were designed: AGEN, complementary to a sequence of the fungal 28S ribosomal RNA (rRNA) of Aspergillus, as a genus-specific probe; AFUM, complementary to the 28S rRNA sequence of A. fumigatus, as a fungus species-specific probe; and cMORF, irrelevant to all fungal species, as a control probe. The probes were conjugated with Alexa Fluor 633 carboxylic acid succinimidyl ester (AF633) for fluorescence imaging or with NHS-mercaptoacetyl triglycine (NHS-MAG3) for nuclear imaging with 99m Tc and then evaluated in vitro and in vivo. Results: The specific binding of AGEN and AFUM to fungal total RNA was confirmed by dot blot hybridization while specific binding of AGEN and AFUM in fixed and live A. fumigatus was demonstrated by both fluorescent in situ hybridization (FISH) analysis and accumulation in live cells. SPECT imaging of BALB/c mice with pulmonary A. fumigatus infections and administered 99m Tc labeled AGEN and AFUM showed immediate and obvious accumulation in the infected lungs, while no significant accumulation of the control 99m Tc-cMORF in the infected lung was observed. Compared to non-infected mice, with sacrifice at 1 h, the accumulation of 99m Tc-AGEN and 99m Tc-AFUM in the lungs of mice infected with A. fumigatus was 2 and 2.7 fold higher respectively. Conclusions: In vivo targeting fungal ribosomal RNA with 99m Tc labeled MORF probes AGEN

  7. Methane Flux Estimation from Point Sources using GOSAT Target Observation: Detection Limit and Improvements with Next Generation Instruments

    Science.gov (United States)

    Kuze, A.; Suto, H.; Kataoka, F.; Shiomi, K.; Kondo, Y.; Crisp, D.; Butz, A.

    2017-12-01

    Atmospheric methane (CH4) has an important role in global radiative forcing of climate but its emission estimates have larger uncertainties than carbon dioxide (CO2). The area of anthropogenic emission sources is usually much smaller than 100 km2. The Thermal And Near infrared Sensor for carbon Observation Fourier-Transform Spectrometer (TANSO-FTS) onboard the Greenhouse gases Observing SATellite (GOSAT) has measured CO2 and CH4 column density using sun light reflected from the earth's surface. It has an agile pointing system and its footprint can cover 87-km2 with a single detector. By specifying pointing angles and observation time for every orbit, TANSO-FTS can target various CH4 point sources together with reference points every 3 day over years. We selected a reference point that represents CH4 background density before or after targeting a point source. By combining satellite-measured enhancement of the CH4 column density and surface measured wind data or estimates from the Weather Research and Forecasting (WRF) model, we estimated CH4emission amounts. Here, we picked up two sites in the US West Coast, where clear sky frequency is high and a series of data are available. The natural gas leak at Aliso Canyon showed a large enhancement and its decrease with time since the initial blowout. We present time series of flux estimation assuming the source is single point without influx. The observation of the cattle feedlot in Chino, California has weather station within the TANSO-FTS footprint. The wind speed is monitored continuously and the wind direction is stable at the time of GOSAT overpass. The large TANSO-FTS footprint and strong wind decreases enhancement below noise level. Weak wind shows enhancements in CH4, but the velocity data have large uncertainties. We show the detection limit of single samples and how to reduce uncertainty using time series of satellite data. We will propose that the next generation instruments for accurate anthropogenic CO2 and CH

  8. SU-E-I-10: Investigation On Detectability of a Small Target for Different Slice Direction of a Volumetric Cone Beam CT Image

    International Nuclear Information System (INIS)

    Lee, C; Han, M; Baek, J

    2015-01-01

    Purpose: To investigate the detectability of a small target for different slice direction of a volumetric cone beam CT image and its impact on dose reduction. Methods: Analytic projection data of a sphere object (1 mm diameter, 0.2/cm attenuation coefficient) were generated and reconstructed by FDK algorithm. In this work, we compared the detectability of the small target from four different backprojection Methods: hanning weighted ramp filter with linear interpolation (RECON 1), hanning weighted ramp filter with Fourier interpolation (RECON2), ramp filter with linear interpolation (RECON 3), and ramp filter with Fourier interpolation (RECON4), respectively. For noise simulation, 200 photons per measurement were used, and the noise only data were reconstructed using FDK algorithm. For each reconstructed volume, axial and coronal slice were extracted and detection-SNR was calculated using channelized Hotelling observer (CHO) with dense difference-of-Gaussian (D-DOG) channels. Results: Detection-SNR of coronal images varies for different backprojection methods, while axial images have a similar detection-SNR. Detection-SNR 2 ratios of coronal and axial images in RECON1 and RECON2 are 1.33 and 1.15, implying that the coronal image has a better detectability than axial image. In other words, using coronal slices for the small target detection can reduce the patient dose about 33% and 15% compared to using axial slices in RECON 1 and RECON 2. Conclusion: In this work, we investigated slice direction dependent detectability of a volumetric cone beam CT image. RECON 1 and RECON 2 produced the highest detection-SNR, with better detectability in coronal slices. These results indicate that it is more beneficial to use coronal slice to improve detectability of a small target in a volumetric cone beam CT image. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (NIPA-2014-H0201

  9. SU-E-I-10: Investigation On Detectability of a Small Target for Different Slice Direction of a Volumetric Cone Beam CT Image

    Energy Technology Data Exchange (ETDEWEB)

    Lee, C; Han, M; Baek, J [Yonsei University, Incheon (Korea, Republic of)

    2015-06-15

    Purpose: To investigate the detectability of a small target for different slice direction of a volumetric cone beam CT image and its impact on dose reduction. Methods: Analytic projection data of a sphere object (1 mm diameter, 0.2/cm attenuation coefficient) were generated and reconstructed by FDK algorithm. In this work, we compared the detectability of the small target from four different backprojection Methods: hanning weighted ramp filter with linear interpolation (RECON 1), hanning weighted ramp filter with Fourier interpolation (RECON2), ramp filter with linear interpolation (RECON 3), and ramp filter with Fourier interpolation (RECON4), respectively. For noise simulation, 200 photons per measurement were used, and the noise only data were reconstructed using FDK algorithm. For each reconstructed volume, axial and coronal slice were extracted and detection-SNR was calculated using channelized Hotelling observer (CHO) with dense difference-of-Gaussian (D-DOG) channels. Results: Detection-SNR of coronal images varies for different backprojection methods, while axial images have a similar detection-SNR. Detection-SNR{sup 2} ratios of coronal and axial images in RECON1 and RECON2 are 1.33 and 1.15, implying that the coronal image has a better detectability than axial image. In other words, using coronal slices for the small target detection can reduce the patient dose about 33% and 15% compared to using axial slices in RECON 1 and RECON 2. Conclusion: In this work, we investigated slice direction dependent detectability of a volumetric cone beam CT image. RECON 1 and RECON 2 produced the highest detection-SNR, with better detectability in coronal slices. These results indicate that it is more beneficial to use coronal slice to improve detectability of a small target in a volumetric cone beam CT image. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (NIPA-2014-H0201

  10. Disulfide-induced self-assembled targets : A novel strategy for the label free colorimetric detection of DNAs/RNAs via unmodified gold nanoparticles

    NARCIS (Netherlands)

    Shokri, Ehsan; Hosseini, Morteza; Davari, Mehdi D.; Ganjali, Mohammad R.; Peppelenbosch, Maikel P.; Rezaee, Farhad

    2017-01-01

    A modified non-cross-linking gold-nanoparticles (Au-NPs) aggregation strategy has been developed for the label free colorimetric detection of DNAs/RNAs based on self-assembling target species in the presence of thiolated probes. Two complementary thiol-modified probes, each of which specifically

  11. Disulfide-induced self-assembled targets: A novel strategy for the label free colorimetric detection of DNAs/RNAs via unmodified gold nanoparticles

    NARCIS (Netherlands)

    Shokri, E. (Ehsan); M. Hosseini (Morteza); Davari, M.D. (Mehdi D.); Ganjali, M.R. (Mohammad R.); M.P. Peppelenbosch (Maikel); F. Rezaee (Farhad)

    2017-01-01

    textabstractA modified non-cross-linking gold-nanoparticles (Au-NPs) aggregation strategy has been developed for the label free colorimetric detection of DNAs/RNAs based on self-assembling target species in the presence of thiolated probes. Two complementary thiol- modified probes, each of which

  12. Immunoglobulin kappa deleting element rearrangements in precursor-B acute lymphoblastic leukemia are stable targets for detection of minimal residual disease by real-time quantitative PCR

    NARCIS (Netherlands)

    van der Velden, V. H. J.; Willemse, M. J.; van der Schoot, C. E.; Hählen, K.; van Wering, E. R.; van Dongen, J. J. M.

    2002-01-01

    Immunoglobulin gene rearrangements are used as PCR targets for detection of minimal residual disease (MRD) in acute lymphoblastic leukemia (ALL). We Investigated the occurrence of monoclonal immunoglobulin kappa-deleting element (IGK-Kde) rearrangements by Southern blotting and PCR/heteroduplex

  13. Direct detection of RNA in vitro and in situ by target-primed RCA: The impact of E. coli RNase III on the detection efficiency of RNA sequences distanced far from the 3'-end.

    Science.gov (United States)

    Merkiene, Egle; Gaidamaviciute, Edita; Riauba, Laurynas; Janulaitis, Arvydas; Lagunavicius, Arunas

    2010-08-01

    We improved the target RNA-primed RCA technique for direct detection and analysis of RNA in vitro and in situ. Previously we showed that the 3' --> 5' single-stranded RNA exonucleolytic activity of Phi29 DNA polymerase converts the target RNA into a primer and uses it for RCA initiation. However, in some cases, the single-stranded RNA exoribonucleolytic activity of the polymerase is hindered by strong double-stranded structures at the 3'-end of target RNAs. We demonstrate that in such hampered cases, the double-stranded RNA-specific Escherichia coli RNase III efficiently assists Phi29 DNA polymerase in converting the target RNA into a primer. These observations extend the target RNA-primed RCA possibilities to test RNA sequences distanced far from the 3'-end and customize this technique for the inner RNA sequence analysis.

  14. 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.

  15. Disulfide-induced self-assembled targets: A novel strategy for the label free colorimetric detection of DNAs/RNAs via unmodified gold nanoparticles

    Science.gov (United States)

    Shokri, Ehsan; Hosseini, Morteza; Davari, Mehdi D.; Ganjali, Mohammad R.; Peppelenbosch, Maikel P.; Rezaee, Farhad

    2017-04-01

    A modified non-cross-linking gold-nanoparticles (Au-NPs) aggregation strategy has been developed for the label free colorimetric detection of DNAs/RNAs based on self-assembling target species in the presence of thiolated probes. Two complementary thiol- modified probes, each of which specifically binds at one half of the target introduced SH groups at both ends of dsDNA. Continuous disulfide bond formation at 3‧ and 5‧ terminals of targets leads to the self-assembly of dsDNAs into the sulfur- rich and flexible products with different lengths. These products have a high affinity for the surface of Au-NPs and efficiently protect the surface from salt induced aggregation. To evaluate the assay efficacy, a small part of the citrus tristeza virus (CTV) genome was targeted, leading to a detection limit of about 5 × 10-9 mol.L-1 over a linear ranged from 20 × 10-9 to 10 × 10-7 mol.L-1. This approach also exhibits good reproducibility and recovery levels in the presence of plant total RNA or human plasma total circulating RNA extracts. Self-assembled targets can be then sensitively distinguished from non-assembled or mismatched targets after gel electrophoresis. The disulfide reaction method and integrating self-assembled DNAs/RNAs targets with bare AuNPs as a sensitive indicator provide us a powerful and simple visual detection tool for a wide range of applications.

  16. Colorimetric detection of genetically modified organisms based on exonuclease III-assisted target recycling and hemin/G-quadruplex DNAzyme amplification.

    Science.gov (United States)

    Zhang, Decai; Wang, Weijia; Dong, Qian; Huang, Yunxiu; Wen, Dongmei; Mu, Yuejing; Yuan, Yong

    2017-12-21

    An isothermal colorimetric method is described for amplified detection of the CaMV 35S promoter sequence in genetically modified organism (GMO). It is based on (a) target DNA-triggered unlabeled molecular beacon (UMB) termini binding, and (b) exonuclease III (Exo III)-assisted target recycling, and (c) hemin/G-quadruplex (DNAzyme) based signal amplification. The specific binding of target to the G-quadruplex sequence-locked UMB triggers the digestion of Exo III. This, in turn, releases an active G-quadruplex segment and target DNA for successive hybridization and cleavage. The Exo III impellent recycling of targets produces numerous G-quadruplex sequences. These further associate with hemin to form DNAzymes and hence will catalyze H 2 O 2 -mediated oxidation of the chromogenic enzyme substrate ABTS 2- causing the formation of a green colored product. This finding enables a sensitive colorimetric determination of GMO DNA (at an analytical wavelength of 420 nm) at concentrations as low as 0.23 nM. By taking advantage of isothermal incubation, this method does not require sophisticated equipment or complicated syntheses. Analyses can be performed within 90 min. The method also discriminates single base mismatches. In our perception, it has a wide scope in that it may be applied to the detection of many other GMOs. Graphical abstract An isothermal and sensitive colorimetric method is described for amplified detection of CaMV 35S promoter sequence in genetically modified organism (GMO). It is based on target DNA-triggered molecular beacon (UMB) termini-binding and exonuclease III assisted target recycling, and on hemin/G-quadruplex (DNAzyme) signal amplification.

  17. The passive and active periods for the intermittent use of an active sensor to detect an evasive target

    OpenAIRE

    Bache, Niels

    2013-01-01

    Your task is to detect a submarine with your active sonar. The submarine can hear your active sonar before you can detect him. If the submarine is fast enough he can evade you before you can detect him. How do you then detect him? If you are using your active sonar continuously you will not detect him. Likewise, if you are not using your sonar at all. In between those two extremes there is an optimum. We will find that optimum. Or said more precisely and general: In the same two dimensional r...

  18. A Subpixel Classification of Multispectral Satellite Imagery for Interpetation of Tundra-Taiga Ecotone Vegetation (Case Study on Tuliok River Valley, Khibiny, Russia)

    Science.gov (United States)

    Mikheeva, A. I.; Tutubalina, O. V.; Zimin, M. V.; Golubeva, E. I.

    2017-12-01

    The tundra-taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra-taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra-taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their abundance on the basis of quantitative criteria, which provides a more accurate characteristic of ecotone vegetation when compared to the per-pixel approach of automatic imagery interpretation.

  19. Target recycling amplification for label-free and sensitive colorimetric detection of adenosine triphosphate based on un-modified aptamers and DNAzymes.

    Science.gov (United States)

    Gong, Xue; Li, Jinfu; Zhou, Wenjiao; Xiang, Yun; Yuan, Ruo; Chai, Yaqin

    2014-05-30

    Based on target recycling amplification, the development of a new label-free, simple and sensitive colorimetric detection method for ATP by using un-modified aptamers and DNAzymes is described. The association of the model target molecules (ATP) with the corresponding aptamers of the dsDNA probes leads to the release of the G-quadruplex sequences. The ATP-bound aptamers can be further degraded by Exonuclease III to release ATP, which can again bind the aptamers of the dsDNA probes to initiate the target recycling amplification process. Due to this target recycling amplification, the amount of the released G-quadruplex sequences is significantly enhanced. Subsequently, these G-quadruplex sequences bind hemin to form numerous peroxidase mimicking DNAzymes, which cause substantially intensified color change of the probe solution for highly sensitive colorimetric detection of ATP down to the sub-nanomolar (0.33nM) level. Our method is highly selective toward ATP against other control molecules and can be performed in one single homogeneous solution, which makes our sensing approach hold great potential for sensitive colorimetric detection of other small molecules and proteins. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. Next Generation Snow Cover Mapping: Can Future Hyperspectral Satellite Spectrometer Systems Improve Subpixel Snow-covered Area and Grain Size in the Sierra Nevada?

    Science.gov (United States)

    Hill, R.; Calvin, W. M.; Harpold, A.

    2017-12-01

    Mountain snow storage is the dominant source of water for humans and ecosystems in western North America. Consequently, the spatial distribution of snow-covered area is fundamental to both hydrological, ecological, and climate models. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were collected along the entire Sierra Nevada mountain range extending from north of Lake Tahoe to south of Mt. Whitney during the 2015 and 2016 snow-covered season. The AVIRIS dataset used in this experiment consists of 224 contiguous spectral channels with wavelengths ranging 400-2500 nanometers at a 15-meter spatial pixel size. Data from the Sierras were acquired on four days: 2/24/15 during a very low snow year, 3/24/16 near maximum snow accumulation, and 5/12/16 and 5/18/16 during snow ablation and snow loss. Building on previous retrieval of subpixel snow-covered area algorithms that take into account varying grain size we present a model that analyzes multiple endmembers of varying snow grain size, vegetation, rock, and soil in segmented regions along the Sierra Nevada to determine snow-cover spatial extent, snow sub-pixel fraction, and approximate grain size. In addition, varying simulated models of the data will compare and contrast the retrieval of current snow products such as MODIS Snow-Covered Area and Grain Size (MODSCAG) and the Airborne Space Observatory (ASO). Specifically, does lower spatial resolution (MODIS), broader resolution bandwidth (MODIS), and limited spectral resolution (ASO) affect snow-cover area and grain size approximations? The implications of our findings will help refine snow mapping products for planned hyperspectral satellite spectrometer systems such as EnMAP (slated to launch in 2019), HISUI (planned for inclusion on the International Space Station in 2018), and HyspIRI (currently under consideration).

  1. Planar optical waveguide based sandwich assay sensors and processes for the detection of biological targets including protein markers, pathogens and cellular debris

    Science.gov (United States)

    Martinez, Jennifer S [Santa Fe, NM; Swanson, Basil I [Los Alamos, NM; Grace, Karen M [Los Alamos, NM; Grace, Wynne K [Los Alamos, NM; Shreve, Andrew P [Santa Fe, NM

    2009-06-02

    An assay element is described including recognition ligands 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 a biological target is described including injecting a biological target-containing sample into a sensor cell including the assay element, with the recognition ligands adapted for binding to selected biological targets, maintaining the sample within the sensor cell for time sufficient for binding to occur between selected biological targets 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 the fluorescent-label in any bound reporter ligand within a distance of less than about 200 nanometers from the waveguide and resulting in a detectable signal.

  2. Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging and Fusion Guided Targeted Biopsy Evaluated by Transperineal Template Saturation Prostate Biopsy for the Detection and Characterization of Prostate Cancer.

    Science.gov (United States)

    Mortezavi, Ashkan; Märzendorfer, Olivia; Donati, Olivio F; Rizzi, Gianluca; Rupp, Niels J; Wettstein, Marian S; Gross, Oliver; Sulser, Tullio; Hermanns, Thomas; Eberli, Daniel

    2018-02-21

    We evaluated the diagnostic accuracy of multiparametric magnetic resonance imaging and multiparametric magnetic resonance imaging/transrectal ultrasound fusion guided targeted biopsy against that of transperineal template saturation prostate biopsy to detect prostate cancer. We retrospectively analyzed the records of 415 men who consecutively presented for prostate biopsy between November 2014 and September 2016 at our tertiary care center. Multiparametric magnetic resonance imaging was performed using a 3 Tesla device without an endorectal coil, followed by transperineal template saturation prostate biopsy with the BiopSee® fusion system. Additional fusion guided targeted biopsy was done in men with a suspicious lesion on multiparametric magnetic resonance imaging, defined as Likert score 3 to 5. Any Gleason pattern 4 was defined as clinically significant prostate cancer. The detection rates of multiparametric magnetic resonance imaging and fusion guided targeted biopsy were compared with the detection rate of transperineal template saturation prostate biopsy using the McNemar test. We obtained a median of 40 (range 30 to 55) and 3 (range 2 to 4) transperineal template saturation prostate biopsy and fusion guided targeted biopsy cores, respectively. Of the 124 patients (29.9%) without a suspicious lesion on multiparametric magnetic resonance imaging 32 (25.8%) were found to have clinically significant prostate cancer on transperineal template saturation prostate biopsy. Of the 291 patients (70.1%) with a Likert score of 3 to 5 clinically significant prostate cancer was detected in 129 (44.3%) by multiparametric magnetic resonance imaging fusion guided targeted biopsy, in 176 (60.5%) by transperineal template saturation prostate biopsy and in 187 (64.3%) by the combined approach. Overall 58 cases (19.9%) of clinically significant prostate cancer would have been missed if fusion guided targeted biopsy had been performed exclusively. The sensitivity of

  3. Differential detection of type II methanotrophic bacteria in acidic peatlands using newly developed 16S rRNA-targeted fluorescent oligonucleotide probes.

    Science.gov (United States)

    Dedysh, Svetlana N; Dunfield, Peter F; Derakshani, Manigee; Stubner, Stephan; Heyer, Jürgen; Liesack, Werner

    2003-04-01

    Abstract Based on an extensive 16S rRNA sequence database for type II methanotrophic bacteria, a set of 16S rRNA-targeted oligonucleotide probes was developed for differential detection of specific phylogenetic groups of these bacteria by fluorescence in situ hybridisation (FISH). This set of oligonucleotides included a genus-specific probe for Methylocystis (Mcyst-1432) and three species-specific probes for Methylosinus sporium (Msins-647), Methylosinus trichosporium (Msint-1268) and the recently described acidophilic methanotroph Methylocapsa acidiphila (Mcaps-1032). These novel probes were applied to further characterise the type II methanotroph community that was detected in an acidic Sphagnum peat from West Siberia in a previous study (Dedysh et al. (2001) Appl. Environ. Microbiol. 67, 4850-4857). The largest detectable population of indigenous methanotrophs simultaneously hybridised with a group-specific probe targeting all currently known Methylosinus/Methylocystis spp. (M-450), with a genus-specific probe for Methylocystis spp. (Mcyst-1432), and with an additional probe (Mcyst-1261) that had been designed to target a defined phylogenetic subgroup of Methylocystis spp. The same subgroup of Methylocystis was also detected in acidic peat sampled from Sphagnum-dominated wetland in northern Germany. The population size of this peat-inhabiting Methylocystis subgroup was 2.0+/-0.1x10(6) cells g(-1) (wet weight) of peat from Siberia and 5.5+/-0.5x10(6) cells g(-1) of peat from northern Germany. This represented 60 and 95%, respectively, of the total number of methanotroph cells detected by FISH in these two wetland sites. Other major methanotroph populations were M. acidiphila and Methylocella palustris. Type I methanotrophs accounted for not more than 1% of total methanotroph cells. Neither M. trichosporium nor M. sporium were detected in acidic Sphagnum peat.

  4. Silver nanoclusters-assisted ion-exchange reaction with CdTe quantum dots for photoelectrochemical detection of adenosine by target-triggering multiple-cycle amplification strategy.

    Science.gov (United States)

    Zhao, Yang; Tan, Lu; Gao, Xiaoshan; Jie, Guifen; Huang, Tingyu

    2018-07-01

    Herein, we successfully devised a novel photoelectrochemical (PEC) platform for ultrasensitive detection of adenosine by target-triggering cascade multiple cycle amplification based on the silver nanoparticles-assisted ion-exchange reaction with CdTe quantum dots (QDs). In the presence of target adenosine, DNA s1 is released from the aptamer and then hybridizes with hairpin DNA (HP1), which could initiate the cycling cleavage process under the reaction of nicking endonuclease. Then the product (DNA b) of cycle I could act as the "DNA trigger" of cycle II to further generate a large number of DNA s1, which again go back to cycle I, thus a cascade multiple DNA cycle amplification was carried out to produce abundant DNA c. These DNA c fragments with the cytosine (C)-rich loop were captured by magnetic beads, and numerous silver nanoclusters (Ag NCs) were synthesized by AgNO 3 and sodium borohydride. The dissolved AgNCs released numerous silver ions which could induce ion exchange reaction with the CdTe QDs, thus resulting in greatly amplified change of photocurrent for target detection. The detection linear range for adenosine was 1.0 fM ~10 nM with the detection limit of 0.5 fM. The present PEC strategy combining cascade multiple DNA cycle amplification and AgNCs-induced ion-exchange reaction with QDs provides new insight into rapid, and ultrasensitive PEC detection of different biomolecules, which showed great potential for detecting trace amounts in bioanalysis and clinical biomedicine. Copyright © 2018 Elsevier B.V. All rights reserved.

  5. Effect of H-wave polarization on laser radar detection of partially convex targets in random media.

    Science.gov (United States)

    El-Ocla, Hosam

    2010-07-01

    A study on the performance of laser radar cross section (LRCS) of conducting targets with large sizes is investigated numerically in free space and random media. The LRCS is calculated using a boundary value method with beam wave incidence and H-wave polarization. Considered are those elements that contribute to the LRCS problem including random medium strength, target configuration, and beam width. The effect of the creeping waves, stimulated by H-polarization, on the LRCS behavior is manifested. Targets taking large sizes of up to five wavelengths are sufficiently larger than the beam width and are sufficient for considering fairly complex targets. Scatterers are assumed to have analytical partially convex contours with inflection points.

  6. Ultrasensitive electrochemical biosensor for detection of DNA from Bacillus subtilis by coupling target-induced strand displacement and nicking endonuclease signal amplification.

    Science.gov (United States)

    Hu, Yuhua; Xu, Xueqin; Liu, Qionghua; Wang, Ling; Lin, Zhenyu; Chen, Guonan

    2014-09-02

    A simple, ultrasensitive, and specific electrochemical biosensor was designed to determine the given DNA sequence of Bacillus subtilis by coupling target-induced strand displacement and nicking endonuclease signal amplification. The target DNA (TD, the DNA sequence from the hypervarient region of 16S rDNA of Bacillus subtilis) could be detected by the differential pulse voltammetry (DPV) in a range from 0.1 fM to 20 fM with the detection limit down to 0.08 fM at the 3s(blank) level. This electrochemical biosensor exhibits high distinction ability to single-base mismatch, double-bases mismatch, and noncomplementary DNA sequence, which may be expected to detect single-base mismatch and single nucleotide polymorphisms (SNPs). Moreover, the applicability of the designed biosensor for detecting the given DNA sequence from Bacillus subtilis was investigated. The result obtained by electrochemical method is approximately consistent with that by a real-time quantitative polymerase chain reaction detecting system (QPCR) with SYBR Green.

  7. Joint Direction-of-Departure and Direction-of-Arrival Estimation in a UWB MIMO Radar Detecting Targets with Fluctuating Radar Cross Sections

    Directory of Open Access Journals (Sweden)

    Idnin Pasya

    2014-01-01

    Full Text Available This paper presents a joint direction-of-departure (DOD and direction-of-arrival (DOA estimation in a multiple-input multiple-output (MIMO radar utilizing ultra wideband (UWB signals in detecting targets with fluctuating radar cross sections (RCS. The UWB MIMO radar utilized a combination of two-way MUSIC and majority decision based on angle histograms of estimated DODs and DOAs at each frequency of the UWB signal. The proposed angle estimation scheme was demonstrated to be effective in detecting targets with fluctuating RCS, compared to conventional spectra averaging method used in subband angle estimations. It was found that a wider bandwidth resulted in improved estimation performance. Numerical simulations along with experimental evaluations in a radio anechoic chamber are presented.

  8. New pediatric vision screener employing polarization-modulated, retinal-birefringence-scanning-based strabismus detection and bull's eye focus detection with an improved target system: opto-mechanical design and operation

    Science.gov (United States)

    Irsch, Kristina; Gramatikov, Boris I.; Wu, Yi-Kai; Guyton, David L.

    2014-06-01

    Amblyopia ("lazy eye") is a major public health problem, caused by misalignment of the eyes (strabismus) or defocus. If detected early in childhood, there is an excellent response to therapy, yet most children are detected too late to be treated effectively. Commercially available vision screening devices that test for amblyopia's primary causes can detect strabismus only indirectly and inaccurately via assessment of the positions of external light reflections from the cornea, but they cannot detect the anatomical feature of the eyes where fixation actually occurs (the fovea). Our laboratory has been developing technology to detect true foveal fixation, by exploiting the birefringence of the uniquely arranged Henle fibers delineating the fovea using retinal birefringence scanning (RBS), and we recently described a polarization-modulated approach to RBS that enables entirely direct and reliable detection of true foveal fixation, with greatly enhanced signal-to-noise ratio and essentially independent of corneal birefringence (a confounding variable with all polarization-sensitive ophthalmic technology). Here, we describe the design and operation of a new pediatric vision screener that employs polarization-modulated, RBS-based strabismus detection and bull's eye focus detection with an improved target system, and demonstrate the feasibility of this new approach.

  9. New pediatric vision screener employing polarization-modulated, retinal-birefringence-scanning-based strabismus detection and bull's eye focus detection with an improved target system: opto-mechanical design and operation.

    Science.gov (United States)

    Irsch, Kristina; Gramatikov, Boris I; Wu, Yi-Kai; Guyton, David L

    2014-06-01

    Amblyopia ("lazy eye") is a major public health problem, caused by misalignment of the eyes (strabismus) or defocus. If detected early in childhood, there is an excellent response to therapy, yet most children are detected too late to be treated effectively. Commercially available vision screening devices that test for amblyopia's primary causes can detect strabismus only indirectly and inaccurately via assessment of the positions of external light reflections from the cornea, but they cannot detect the anatomical feature of the eyes where fixation actually occurs (the fovea). Our laboratory has been developing technology to detect true foveal fixation, by exploiting the birefringence of the uniquely arranged Henle fibers delineating the fovea using retinal birefringence scanning (RBS), and we recently described a polarization-modulated approach to RBS that enables entirely direct and reliable detection of true foveal fixation, with greatly enhanced signal-to-noise ratio and essentially independent of corneal birefringence (a confounding variable with all polarization-sensitive ophthalmic technology). Here, we describe the design and operation of a new pediatric vision screener that employs polarization-modulated, RBS-based strabismus detection and bull's eye focus detection with an improved target system, and demonstrate the feasibility of this new approach.

  10. A method of detection to the grinding wheel layer thickness based on computer vision

    Science.gov (United States)

    Ji, Yuchen; Fu, Luhua; Yang, Dujuan; Wang, Lei; Liu, Changjie; Wang, Zhong

    2018-01-01

    This paper proposed a method of detection to the grinding wheel layer thickness based on computer vision. A camera is used to capture images of grinding wheel layer on the whole circle. Forward lighting and back lighting are used to enables a clear image to be acquired. Image processing is then executed on the images captured, which consists of image preprocessing, binarization and subpixel subdivision. The aim of binarization is to help the location of a chord and the corresponding ring width. After subpixel subdivision, the thickness of the grinding layer can be calculated finally. Compared with methods usually used to detect grinding wheel wear, method in this paper can directly and quickly get the information of thickness. Also, the eccentric error and the error of pixel equivalent are discussed in this paper.

  11. MRI screening-detected breast lesions in high-risk young women: the value of targeted second-look ultrasound and imaging-guided biopsy.

    Science.gov (United States)

    Peter, P; Dhillon, R; Bose, S; Bourke, A

    2016-10-01

    To analyse the value of targeted second-look ultrasound and imaging-guided biopsy in high-risk young women eligible for screening magnetic resonance imaging (MRI) in a tertiary referral centre in Perth, Western Australia. A retrospective analysis of eligible high-risk young women who underwent screening breast MRI and targeted second-look ultrasound between June 2012 and June 2014 was performed with review of data. Over a 2-year period, 139 women underwent high-risk screening MRI. Of these, 30 women (with a total of 45 lesions) were recalled for targeted second-look ultrasound. Thirty-four MRI-detected lesions were identified on targeted ultrasound with 19 of them proceeding to ultrasound-guided biopsy, while the remaining 15 lesions were considered benign on ultrasound, were not biopsied, and were stable on follow-up imaging 12 months later. One lesion proceeded to an MRI-guided biopsy to confirm a benign result. Of the 11 lesions not seen on ultrasound, nine underwent MRI biopsy, one proceeded directly to hook wire localisation and excision, and one did not return for biopsy and was lost to follow-up. The overall biopsy rate was 14.4%. The cancer detection rate was 1.4%. The results of this study indicate that targeted second-look ultrasound and ultrasound-guided biopsy is a cost-effective and time-efficient approach for MRI-detected lesions in young women at high risk of developing breast cancer. MRI-guided biopsy should be considered for ultrasonographically occult suspicious lesions as there is a low, but definite, risk of cancer. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

  12. Development of a Targeted Next-Generation Sequencing Assay to Detect Diagnostically Relevant Mutations of JAK2, CALR, and MPL in Myeloproliferative Neoplasms.

    Science.gov (United States)

    Frawley, Thomas; O'Brien, Cathal P; Conneally, Eibhlin; Vandenberghe, Elisabeth; Percy, Melanie; Langabeer, Stephen E; Haslam, Karl

    2018-02-01

    The classical Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs), consisting of polycythemia vera, essential thrombocythemia, and primary myelofibrosis, are a heterogeneous group of neoplasms that harbor driver mutations in the JAK2, CALR, and MPL genes. The detection of mutations in these genes has been incorporated into the recent World Health Organization (WHO) diagnostic criteria for MPN. Given a pressing clinical need to screen for mutations in these genes in a routine diagnostic setting, a targeted next-generation sequencing (NGS) assay for the detection of MPN-associated mutations located in JAK2 exon 14, JAK2 exon 12, CALR exon 9, and MPL exon 10 was developed to provide a single platform alternative to reflexive, stepwise diagnostic algorithms. Polymerase chain reaction (PCR) primers were designed to target mutation hotspots in JAK2 exon 14, JAK2 exon 12, MPL exon 10, and CALR exon 9. Multiplexed PCR conditions were optimized by using qualitative PCR followed by NGS. Diagnostic genomic DNA from 35 MPN patients, known to harbor driver mutations in one of the target genes, was used to validate the assay. One hundred percent concordance was observed between the previously-identified mutations and those detected by NGS, with no false positives, nor any known mutations missed (specificity = 100%, CI = 0.96, sensitivity = 100%, CI = 0.89). Improved resolution of mutation sequences was also revealed by NGS analysis. Detection of diagnostically relevant driver mutations of MPN is enhanced by employing a targeted multiplex NGS approach. This assay presents a robust solution to classical MPN mutation screening, providing an alternative to time-consuming sequential analyses.

  13. Performances and stability of a 2.4 ton Gd organic liquid scintillator target for ν-bar e detection

    International Nuclear Information System (INIS)

    Barabanov, I R; Bezrukov, L B; Danilov, N A; Krilov, Yu S; Yanovich, E A; Malguin, A S; Cattadori, C M; Vacri, A di; Ioannucci, L; Bruno, G; Aglietta, M; Bonardi, A; Fulgione, W; Porta, A; Kemp, E; Selvi, M

    2010-01-01

    In this paper we report the performance and the chemical and physical properties of a 2 x 1.2 ton organic liquid scintillator target doped with Gd up to ∼ 0.1%, and the results of a 3 year long stability survey of the target. In particular we have measured and monitored the optical and fluorescent properties of the Gd-doped liquid scintillator (LS), the amount of both Gd and primary fluor in solution, and the performance of the two Gd doped targets as neutron detectors, namely neutron capture efficiency and average capture time. The experimental survey is ongoing, the targets being continuously monitored. From the spectrophotometric measurements performed on samples periodically extracted along the three years, we can exclude, at 99% C.L. level, a degradation of the light transmittance of the Gd-doped liquid scintillator larger than 1% y -1 ; from the in-tank measurements no significant decrease of the neutron capture efficiency and neutron capture time is observed. This is the largest stable Gd-doped organic liquid scintillator target ever produced and continuously operated for a long period.

  14. 16S rRNA-targeted probes for specific detection of Thermoanaerobacterium spp., Thermoanaerobacterium thermosaccharolyticum, and Caldicellulosiruptor spp. by fluorescent in situ hybridization in biohydrogen producing systems

    Energy Technology Data Exchange (ETDEWEB)

    O-Thong, Sompong [Department of Environmental Engineering, Technical University of Denmark, Bygningstorvet Bg 115, DK-2800, Kgs Lyngby (Denmark); Department of Biology, Faculty of Science, Thaksin University, Patthalung 93110 (Thailand); Prasertsan, Poonsuk [Department of Industrial Biotechnology, Faculty of Agro-Industry, Prince of Songkla University, Hat-Yai, Songkhla 90112 (Thailand); Karakashev, Dimitar; Angelidaki, Irini [Department of Environmental Engineering, Technical University of Denmark, Bygningstorvet Bg 115, DK-2800, Kgs Lyngby (Denmark)

    2008-11-15

    16S rRNA gene targeted oligonucleotide probes for specific detection of genera Thermoanaerobacterium (Tbm1282), Caldicellulosiruptor (Ccs432), and specie Thermoanaerobacterium thermosaccharolyticum (Tbmthsacc184) were designed and used to monitor the spatial distribution of hydrogen producing bacteria in sludge and granules from anaerobic reactors. The designed probes were checked for their specificity and then validated using fluorescence in situ hybridization with target microorganisms and non-target microorganisms. Thermoanaerobacterium spp., T. thermosaccharolyticum and Caldicellulosiruptor spp. were detected with the probes designed with coverage of 75%, 100% and 93%, respectively. Thermophilic (60 C) hydrogen producing reactors, one fed with sucrose and another, fed with palm oil mill effluent comprised of following major groups of hydrogen producers: Thermoanaerobacterium spp. (49% and 36%), T. thermosaccharolyticum (16% and 10%), phylum Firmicutes (low G+C) gram positive bacteria (15% and 27%). Extreme-thermophilic (70 C) hydrogen producing reactors, one fed with xylose and another, fed with lignocellulosic hydrolysate comprised of following major groups of hydrogen producers: Caldicellulosiruptor spp. (40.5% and 20.5%), phylum Firmicutes (low G+C) gram positive bacteria (17% and 20%), Archaea (7% and 8.5%), and Thermoanaerobacterium spp. (0% and 5%). Results obtained, showed good applicability of the probes Tbm1282, Tbmthsacc184 and Ccs432 for specific detection and quantification of thermophilic and extreme-thermophilic hydrogen producers in complex environments. (author)

  15. Cascaded strand displacement for non-enzymatic target recycling amplification and label-free electronic detection of microRNA from tumor cells

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Kai; Dou, Baoting; Yang, Jianmei; Yuan, Ruo; Xiang, Yun, E-mail: yunatswu@swu.edu.cn

    2016-04-15

    The monitoring of microRNA (miRNA) expression levels is of great importance in cancer diagnosis. In the present work, based on two cascaded toehold-mediated strand displacement reactions (TSDRs), we have developed a label- and enzyme-free target recycling signal amplification approach for sensitive electronic detection of miRNA-21 from human breast cancer cells. The junction probes containing the locked G-quadruplex forming sequences are self-assembled on the senor surface. The presence of the target miRNA-21 initiates the first TSDR and results in the disassembly of the junction probes and the release of the active G-quadruplex forming sequences. Subsequently, the DNA fuel strand triggers the second TSDR and leads to cyclic reuse of the target miRNA-21. The cascaded TSDRs thus generate many active G-quadruplex forming sequences on the sensor surface, which associate with hemin to produce significantly amplified current response for sensitive detection of miRNA-21 at 1.15 fM. The sensor is also selective and can be employed to monitor miRNA-21 from human breast cancer cells. - Highlights: • Amplified and sensitive detection of microRNA from tumor cells is achieved. • Signal amplification is realized by two cascaded strand displacement reactions. • The developed sensor is selective and label-free without involving any enzymes.

  16. Automatic detection of multiple UXO-like targets using magnetic anomaly inversion and self-adaptive fuzzy c-means clustering

    Science.gov (United States)

    Yin, Gang; Zhang, Yingtang; Fan, Hongbo; Ren, Guoquan; Li, Zhining

    2017-12-01

    We have developed a method for automatically detecting UXO-like targets based on magnetic anomaly inversion and self-adaptive fuzzy c-means clustering. Magnetic anomaly inversion methods are used to estimate the initial locations of multiple UXO-like sources. Although these initial locations have some errors with respect to the real positions, they form dense clouds around the actual positions of the magnetic sources. Then we use the self-adaptive fuzzy c-means clustering algorithm to cluster these initial locations. The estimated number of cluster centroids represents the number of targets and the cluster centroids are regarded as the locations of magnetic targets. Effectiveness of the method has been demonstrated using synthetic datasets. Computational results show that the proposed method can be applied to the case of several UXO-like targets that are randomly scattered within in a confined, shallow subsurface, volume. A field test was carried out to test the validity of the proposed method and the experimental results show that the prearranged magnets can be detected unambiguously and located precisely.

  17. Improved Detection of Lassa Virus by Reverse Transcription-PCR Targeting the 5′ Region of S RNA▿

    OpenAIRE

    Ölschläger, Stephan; Lelke, Michaela; Emmerich, Petra; Panning, Marcus; Drosten, Christian; Hass, Meike; Asogun, Danny; Ehichioya, Deborah; Omilabu, Sunday; Günther, Stephan

    2010-01-01

    The method of choice for the detection of Lassa virus is reverse transcription (RT)-PCR. However, the high degree of genetic variability of the virus poses a problem with the design of RT-PCR assays that will reliably detect all strains. Recently, we encountered difficulties in detecting some strains from Liberia and Nigeria in a commonly used glycoprotein precursor (GPC) gene-specific RT-PCR assay (A. H. Demby, J. Chamberlain, D. W. Brown, and C. S. Clegg, J. Clin. Microbiol. 32:2898-2903, 1...

  18. Development of behavioral parameters and ERPs in a novel-target visual detection paradigm in children, adolescents and young adults.

    Science.gov (United States)

    Rojas-Benjumea, María Ángeles; Sauqué-Poggio, Ana María; Barriga-Paulino, Catarina I; Rodríguez-Martínez, Elena I; Gómez, Carlos M

    2015-07-04

    The present study analyzes the development of ERPs related to the process of selecting targets based on their novelty. One hundred and sixty-seven subjects from 6 to 26 years old were recorded with 30 electrodes during a visual target novelty paradigm. Behavioral results showed good performance in children that improved with age: a decrease in RTs and errors and an increase in the d' sensitivity parameter with age were obtained. In addition, the C response bias parameter evolved from a conservative to a neutral bias with age. Fronto-polar Selection Positivity (FSP) was statistically significant in all the age groups when standards and targets were compared. There was a statistically significant difference in the posterior Selection Negativity (SN) between the target and standard conditions in all age groups. The P3a component obtained was statistically significant in the emergent adult (18-21 years) and young adult (22-26 years) groups. The modulation of the P3b component by novel targets was statistically significant in all the age groups, but it decreased in amplitude with age. Peak latencies of the FSP and P3b components decreased with age. The results reveal differences in the ERP indexes for the cognitive evaluation of the stimuli presented, depending on the age of the subjects. The ability of the target condition to induce the modulation of the studied components would depend on the posterior-anterior gradient of cortex maturation and on the gradient of maturation of the low to higher order association areas.

  19. Robustness and precision of an automatic marker detection algorithm for online prostate daily targeting using a standard V-EPID.

    Science.gov (United States)

    Aubin, S; Beaulieu, L; Pouliot, S; Pouliot, J; Roy, R; Girouard, L M; Martel-Brisson, N; Vigneault, E; Laverdière, J

    2003-07-01

    An algorithm for the daily localization of the prostate using implanted markers and a standard video-based electronic portal imaging device (V-EPID) has been tested. Prior to planning, three gold markers were implanted in the prostate of seven patients. The clinical images were acquired with a BeamViewPlus 2.1 V-EPID for each field during the normal course radiotherapy treatment and are used off-line to determine the ability of the automatic marker detection algorithm to adequately and consistently detect the markers. Clinical images were obtained with various dose levels from ranging 2.5 to 75 MU. The algorithm is based on marker attenuation characterization in the portal image and spatial distribution. A total of 1182 clinical images were taken. The results show an average efficiency of 93% for the markers detected individually and 85% for the group of markers. This algorithm accomplishes the detection and validation in 0.20-0.40 s. When the center of mass of the group of implanted markers is used, then all displacements can be corrected to within 1.0 mm in 84% of the cases and within 1.5 mm in 97% of cases. The standard video-based EPID tested provides excellent marker detection capability even with low dose levels. The V-EPID can be used successfully with radiopaque markers and the automatic detection algorithm to track and correct the daily setup deviations due to organ motions.

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

    Science.gov (United States)

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

    2013-08-01

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

  1. Feasibility of detecting B → h/sup plus/h/sup minus/ in a fixed-target experiment

    International Nuclear Information System (INIS)

    Peng, J.C.; Mishra, C.S.; Moss, J.M.; McGaughey, P.; Kapustinsky, J.

    1988-01-01

    We discuss a proposal to measure two-body, two-prong decays of neutral B mesons and Λ/sub b/ in an 800 GeV fixed-target experiment. We expect to obtain a large sample (/approximately/10 3 events) of these decays if the branching ratios are /approximately/5 /times/ 10/sup /minus/5/. 23 refs., 2 figs., 3 tabs

  2. 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

    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...

  3. Comparative evaluation of PCR amplification of RLEP, 16S rRNA, rpoT and Sod A gene targets for detection of M. leprae DNA from clinical and environmental samples

    Directory of Open Access Journals (Sweden)

    Ravindra P Turankar

    2015-01-01

    Conclusion: Amongst all the gene targets used in this study, PCR positivity using RLEP gene target was the highest in all the clinical and environmental samples. Further, the RLEP gene target was able to detect 53% of blood samples as positive in BI-negative leprosy cases indicating its future standardization and use for diagnostic purposes.

  4. A highly sensitive label-free electrochemical aptasensor for interferon-gamma detection based on graphene controlled assembly and nuclease cleavage-assisted target recycling amplification.

    Science.gov (United States)

    Yan, Genping; Wang, Yonghong; He, Xiaoxiao; Wang, Kemin; Liu, Jinquan; Du, Yudan

    2013-06-15

    We report here a highly sensitive and label-free electrochemical aptasensing technology for detection of interferon-gamma (IFN-γ) based on graphene controlled assembly and enzyme cleavage-assisted target recycling amplification strategy. In this work, in the absence of IFN-γ, the graphene could not be assembled onto the 16-mercaptohexadecanoic acid (MHA) modified gold electrode because the IFN-γ binding aptamer was strongly adsorbed on the graphene due to the strong π-π interaction. Thus the electronic transmission was blocked (eT OFF). However, the presence of target IFN-γ and DNase I led to desorption of aptamer from the graphene surface and further cleavage of the aptamer, thereby releasing the IFN-γ. The released IFN-γ could then re-attack other aptamers on the graphene, resulting in the successive release of the aptamers from the graphene. At the same time, the "naked" graphene could be assembled onto the MHA modified gold electrode with hydrophobic interaction and π-conjunction, mediating the electron transfer between the electrode and the electroactive indicator. Then, measurable electrochemical signals were generated (eT ON), which was related to the concentration of the IFN-γ. By taking advantages of graphene and enzyme cleavage-assisted target recycling amplification, the developed label-free electrochemical aptasensing technology showed a linear response to concentration of IFN-γ range from 0.1 to 0.7 pM. The detection limit of IFN-γ was determined to be 0.065 pM. Moreover, this aptasensor shows good selectivity toward the target in the presence of other relevant proteins. Our strategy thus opens new opportunities for label-free and amplified detection of other kinds of proteins. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Loop-Mediated Isothermal Amplification Assay Targeting the MOMP Gene for Rapid Detection of Chlamydia psittaci Abortus Strain

    Directory of Open Access Journals (Sweden)

    Guo-Zhen Lin, Fu-Ying Zheng, Ji-Zhang Zhou, Guang-Hua Wang, Xiao-An Cao, Xiao-Wei Gong and Chang-Qing Qiu*

    2012-05-01

    Full Text Available For rapid detection of the Chlamydia psittaci abortus strain, a loop-mediated isothermal amplification (LAMP assay was developed and evaluated in this study. The primers for the LAMP assay were designed on the basis of the main outer membrane protein (MOMP gene sequence of C. psittaci. Analysis showed that the assay could detect the abortus strain of C. psittaci with adequate specificity. The sensitivity of the test was the same as that of the nested-conventional PCR and higher than that of chick embryo isolation. Testing of 153 samples indicated that the LAMP assay could detect the genome of the C. psittaci abortus strain effectively in clinical samples. This assay is a useful tool for rapid diagnosis of C. psittaci infection in sheep, swine and cattle.

  6. Affinity-Mediated Homogeneous Electrochemical Aptasensor on a Graphene Platform for Ultrasensitive Biomolecule Detection via Exonuclease-Assisted Target-Analog Recycling Amplification.

    Science.gov (United States)

    Ge, Lei; Wang, Wenxiao; Sun, Ximei; Hou, Ting; Li, Feng

    2016-02-16

    As is well-known, graphene shows a remarkable difference in affinity toward nonstructured single-stranded (ss) DNA and double-stranded (ds) DNA. This property makes it popular to prepare DNA-based optical sensors. In this work, taking this unique property of graphene in combination with the sensitive electrochemical transducer, we report a novel affinity-mediated homog