Comparing the Detection of Iron-Based Pottery Pigment on a Carbon-Coated Sherd by SEM-EDS and by Micro-XRF-SEM

PubMed Central

Pendleton, Michael W.; Washburn, Dorothy K.; Ellis, E. Ann; Pendleton, Bonnie B.

2014-01-01

The same sherd was analyzed using a scanning electron microscope with energy dispersive spectroscopy (SEM-EDS) and a micro X-ray fluorescence tube attached to a scanning electron microscope (Micro-XRF-SEM) to compare the effectiveness of elemental detection of iron-based pigment. To enhance SEM-EDS mapping, the sherd was carbon coated. The carbon coating was not required to produce Micro-XRF-SEM maps but was applied to maintain an unbiased comparison between the systems. The Micro-XRF-SEM analysis was capable of lower limits of detection than that of the SEM-EDS system, and therefore the Micro-XRF-SEM system could produce elemental maps of elements not easily detected by SEM-EDS mapping systems. Because SEM-EDS and Micro-XRF-SEM have been used for imaging and chemical analysis of biological samples, this comparison of the detection systems should be useful to biologists, especially those involved in bone or tooth (hard tissue) analysis. PMID:24600333

Bi-orthogonal Symbol Mapping and Detection in Optical CDMA Communication System

NASA Astrophysics Data System (ADS)

Liu, Maw-Yang

2017-12-01

In this paper, the bi-orthogonal symbol mapping and detection scheme is investigated in time-spreading wavelength-hopping optical CDMA communication system. The carrier-hopping prime code is exploited as signature sequence, whose put-of-phase autocorrelation is zero. Based on the orthogonality of carrier-hopping prime code, the equal weight orthogonal signaling scheme can be constructed, and the proposed scheme using bi-orthogonal symbol mapping and detection can be developed. The transmitted binary data bits are mapped into corresponding bi-orthogonal symbols, where the orthogonal matrix code and its complement are utilized. In the receiver, the received bi-orthogonal data symbol is fed into the maximum likelihood decoder for detection. Under such symbol mapping and detection, the proposed scheme can greatly enlarge the Euclidean distance; hence, the system performance can be drastically improved.

Composite Interval Mapping Based on Lattice Design for Error Control May Increase Power of Quantitative Trait Locus Detection.

PubMed

He, Jianbo; Li, Jijie; Huang, Zhongwen; Zhao, Tuanjie; Xing, Guangnan; Gai, Junyi; Guan, Rongzhan

2015-01-01

Experimental error control is very important in quantitative trait locus (QTL) mapping. Although numerous statistical methods have been developed for QTL mapping, a QTL detection model based on an appropriate experimental design that emphasizes error control has not been developed. Lattice design is very suitable for experiments with large sample sizes, which is usually required for accurate mapping of quantitative traits. However, the lack of a QTL mapping method based on lattice design dictates that the arithmetic mean or adjusted mean of each line of observations in the lattice design had to be used as a response variable, resulting in low QTL detection power. As an improvement, we developed a QTL mapping method termed composite interval mapping based on lattice design (CIMLD). In the lattice design, experimental errors are decomposed into random errors and block-within-replication errors. Four levels of block-within-replication errors were simulated to show the power of QTL detection under different error controls. The simulation results showed that the arithmetic mean method, which is equivalent to a method under random complete block design (RCBD), was very sensitive to the size of the block variance and with the increase of block variance, the power of QTL detection decreased from 51.3% to 9.4%. In contrast to the RCBD method, the power of CIMLD and the adjusted mean method did not change for different block variances. The CIMLD method showed 1.2- to 7.6-fold higher power of QTL detection than the arithmetic or adjusted mean methods. Our proposed method was applied to real soybean (Glycine max) data as an example and 10 QTLs for biomass were identified that explained 65.87% of the phenotypic variation, while only three and two QTLs were identified by arithmetic and adjusted mean methods, respectively.

Incorporating Aptamers in the Multiple Analyte Profiling Assays (xMAP): Detection of C-Reactive Protein.

PubMed

Bernard, Elyse D; Nguyen, Kathy C; DeRosa, Maria C; Tayabali, Azam F; Aranda-Rodriguez, Rocio

2017-01-01

Aptamers are short oligonucleotide sequences used in detection systems because of their high affinity binding to a variety of macromolecules. With the introduction of aptamers over 25 years ago came the exploration of their use in many different applications as a substitute for antibodies. Aptamers have several advantages; they are easy to synthesize, can bind to analytes for which it is difficult to obtain antibodies, and in some cases bind better than antibodies. As such, aptamer applications have significantly expanded as an adjunct to a variety of different immunoassay designs. The Multiple-Analyte Profiling (xMAP) technology developed by Luminex Corporation commonly uses antibodies for the detection of analytes in small sample volumes through the use of fluorescently coded microbeads. This technology permits the simultaneous detection of multiple analytes in each sample tested and hence could be applied in many research fields. Although little work has been performed adapting this technology for use with apatmers, optimizing aptamer-based xMAP assays would dramatically increase the versatility of analyte detection. We report herein on the development of an xMAP bead-based aptamer/antibody sandwich assay for a biomarker of inflammation (C-reactive protein or CRP). Protocols for the coupling of aptamers to xMAP beads, validation of coupling, and for an aptamer/antibody sandwich-type assay for CRP are detailed. The optimized conditions, protocols and findings described in this research could serve as a starting point for the development of new aptamer-based xMAP assays.

Cosmic string detection with tree-based machine learning

NASA Astrophysics Data System (ADS)

Vafaei Sadr, A.; Farhang, M.; Movahed, S. M. S.; Bassett, B.; Kunz, M.

2018-07-01

We explore the use of random forest and gradient boosting, two powerful tree-based machine learning algorithms, for the detection of cosmic strings in maps of the cosmic microwave background (CMB), through their unique Gott-Kaiser-Stebbins effect on the temperature anisotropies. The information in the maps is compressed into feature vectors before being passed to the learning units. The feature vectors contain various statistical measures of the processed CMB maps that boost cosmic string detectability. Our proposed classifiers, after training, give results similar to or better than claimed detectability levels from other methods for string tension, Gμ. They can make 3σ detection of strings with Gμ ≳ 2.1 × 10-10 for noise-free, 0.9'-resolution CMB observations. The minimum detectable tension increases to Gμ ≳ 3.0 × 10-8 for a more realistic, CMB S4-like (II) strategy, improving over previous results.

Cosmic String Detection with Tree-Based Machine Learning

NASA Astrophysics Data System (ADS)

Vafaei Sadr, A.; Farhang, M.; Movahed, S. M. S.; Bassett, B.; Kunz, M.

2018-05-01

We explore the use of random forest and gradient boosting, two powerful tree-based machine learning algorithms, for the detection of cosmic strings in maps of the cosmic microwave background (CMB), through their unique Gott-Kaiser-Stebbins effect on the temperature anisotropies. The information in the maps is compressed into feature vectors before being passed to the learning units. The feature vectors contain various statistical measures of the processed CMB maps that boost cosmic string detectability. Our proposed classifiers, after training, give results similar to or better than claimed detectability levels from other methods for string tension, Gμ. They can make 3σ detection of strings with Gμ ≳ 2.1 × 10-10 for noise-free, 0.9΄-resolution CMB observations. The minimum detectable tension increases to Gμ ≳ 3.0 × 10-8 for a more realistic, CMB S4-like (II) strategy, improving over previous results.

A Technology Analysis to Support Acquisition of UAVs for Gulf Coalition Forces Operations

DTIC Science & Technology

2017-06-01

their selection of the most suitable and cost-effective unmanned aerial vehicles to support detection operations. This study uses Map Aware Non ...being detected by Gulf Coalition Forces and improved time to detect them, support the use of UAVs in detection missions. Computer experimentations and...aerial vehicles to support detection operations. We use Map Aware Non - Uniform Automata, an agent-based simulation software platform, for the

Saliency detection using mutual consistency-guided spatial cues combination

NASA Astrophysics Data System (ADS)

Wang, Xin; Ning, Chen; Xu, Lizhong

2015-09-01

Saliency detection has received extensive interests due to its remarkable contribution to wide computer vision and pattern recognition applications. However, most existing computational models are designed for detecting saliency in visible images or videos. When applied to infrared images, they may suffer from limitations in saliency detection accuracy and robustness. In this paper, we propose a novel algorithm to detect visual saliency in infrared images by mutual consistency-guided spatial cues combination. First, based on the luminance contrast and contour characteristics of infrared images, two effective saliency maps, i.e., the luminance contrast saliency map and contour saliency map are constructed, respectively. Afterwards, an adaptive combination scheme guided by mutual consistency is exploited to integrate these two maps to generate the spatial saliency map. This idea is motivated by the observation that different maps are actually related to each other and the fusion scheme should present a logically consistent view of these maps. Finally, an enhancement technique is adopted to incorporate spatial saliency maps at various scales into a unified multi-scale framework to improve the reliability of the final saliency map. Comprehensive evaluations on real-life infrared images and comparisons with many state-of-the-art saliency models demonstrate the effectiveness and superiority of the proposed method for saliency detection in infrared images.

Automatic spatiotemporal matching of detected pleural thickenings

NASA Astrophysics Data System (ADS)

Chaisaowong, Kraisorn; Keller, Simon Kai; Kraus, Thomas

2014-01-01

Pleural thickenings can be found in asbestos exposed patient's lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).

Page layout analysis and classification for complex scanned documents

NASA Astrophysics Data System (ADS)

Erkilinc, M. Sezer; Jaber, Mustafa; Saber, Eli; Bauer, Peter; Depalov, Dejan

2011-09-01

A framework for region/zone classification in color and gray-scale scanned documents is proposed in this paper. The algorithm includes modules for extracting text, photo, and strong edge/line regions. Firstly, a text detection module which is based on wavelet analysis and Run Length Encoding (RLE) technique is employed. Local and global energy maps in high frequency bands of the wavelet domain are generated and used as initial text maps. Further analysis using RLE yields a final text map. The second module is developed to detect image/photo and pictorial regions in the input document. A block-based classifier using basis vector projections is employed to identify photo candidate regions. Then, a final photo map is obtained by applying probabilistic model based on Markov random field (MRF) based maximum a posteriori (MAP) optimization with iterated conditional mode (ICM). The final module detects lines and strong edges using Hough transform and edge-linkages analysis, respectively. The text, photo, and strong edge/line maps are combined to generate a page layout classification of the scanned target document. Experimental results and objective evaluation show that the proposed technique has a very effective performance on variety of simple and complex scanned document types obtained from MediaTeam Oulu document database. The proposed page layout classifier can be used in systems for efficient document storage, content based document retrieval, optical character recognition, mobile phone imagery, and augmented reality.

Inferring biomarkers for Mycobacterium avium subsp. paratuberculosis infection and disease progression in cattle using experimental data

NASA Astrophysics Data System (ADS)

Magombedze, Gesham; Shiri, Tinevimbo; Eda, Shigetoshi; Stabel, Judy R.

2017-03-01

Available diagnostic assays for Mycobacterium avium subsp. paratuberculosis (MAP) have poor sensitivities and cannot detect early stages of infection, therefore, there is need to find new diagnostic markers for early infection detection and disease stages. We analyzed longitudinal IFN-γ, ELISA-antibody and fecal shedding experimental sensitivity scores for MAP infection detection and disease progression. We used both statistical methods and dynamic mathematical models to (i) evaluate the empirical assays (ii) infer and explain biological mechanisms that affect the time evolution of the biomarkers, and (iii) predict disease stages of 57 animals that were naturally infected with MAP. This analysis confirms that the fecal test is the best marker for disease progression and illustrates that Th1/Th2 (IFN-γ/ELISA antibodies) assays are important for infection detection, but cannot reliably predict persistent infections. Our results show that the theoretical simulated macrophage-based assay is a potential good diagnostic marker for MAP persistent infections and predictor of disease specific stages. We therefore recommend specifically designed experiments to test the use of a based assay in the diagnosis of MAP infections.

Radar Based Navigation in Unknown Terrain

DTIC Science & Technology

2012-12-31

localization and mapping ( SLAM ) approach. The radar processing algorithms detect strong, persistent, and stationary reflectors embedded in the...Global System for Mobile Communications . . . . . . . . . 2 LIDAR Light Detection and Ranging . . . . . . . . . . . . . . . . 2 SAR Synthetic Aperture...22 SLAM Simultaneous Localization and Mapping . . . . . . . . . . 25 FDM Frequency Division Multiplexing

Landslide Inventory Mapping from Bitemporal 10 m SENTINEL-2 Images Using Change Detection Based Markov Random Field

NASA Astrophysics Data System (ADS)

Qin, Y.; Lu, P.; Li, Z.

2018-04-01

Landslide inventory mapping is essential for hazard assessment and mitigation. In most previous studies, landslide mapping was achieved by visual interpretation of aerial photos and remote sensing images. However, such method is labor-intensive and time-consuming, especially over large areas. Although a number of semi-automatic landslide mapping methods have been proposed over the past few years, limitations remain in terms of their applicability over different study areas and data, and there is large room for improvement in terms of the accuracy and automation degree. For these reasons, we developed a change detection-based Markov Random Field (CDMRF) method for landslide inventory mapping. The proposed method mainly includes two steps: 1) change detection-based multi-threshold for training samples generation and 2) MRF for landslide inventory mapping. Compared with the previous methods, the proposed method in this study has three advantages: 1) it combines multiple image difference techniques with multi-threshold method to generate reliable training samples; 2) it takes the spectral characteristics of landslides into account; and 3) it is highly automatic with little parameter tuning. The proposed method was applied for regional landslides mapping from 10 m Sentinel-2 images in Western China. Results corroborated the effectiveness and applicability of the proposed method especially the capability of rapid landslide mapping. Some directions for future research are offered. This study to our knowledge is the first attempt to map landslides from free and medium resolution satellite (i.e., Sentinel-2) images in China.

Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating

NASA Astrophysics Data System (ADS)

Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero

2017-06-01

During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are no shadows on intensity images produced from the data. These are significant advantages in developing automated classification and change detection procedures.

Spatial-Spectral Approaches to Edge Detection in Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Cox, Cary M.

This dissertation advances geoinformation science at the intersection of hyperspectral remote sensing and edge detection methods. A relatively new phenomenology among its remote sensing peers, hyperspectral imagery (HSI) comprises only about 7% of all remote sensing research - there are five times as many radar-focused peer reviewed journal articles than hyperspectral-focused peer reviewed journal articles. Similarly, edge detection studies comprise only about 8% of image processing research, most of which is dedicated to image processing techniques most closely associated with end results, such as image classification and feature extraction. Given the centrality of edge detection to mapping, that most important of geographic functions, improving the collective understanding of hyperspectral imagery edge detection methods constitutes a research objective aligned to the heart of geoinformation sciences. Consequently, this dissertation endeavors to narrow the HSI edge detection research gap by advancing three HSI edge detection methods designed to leverage HSI's unique chemical identification capabilities in pursuit of generating accurate, high-quality edge planes. The Di Zenzo-based gradient edge detection algorithm, an innovative version of the Resmini HySPADE edge detection algorithm and a level set-based edge detection algorithm are tested against 15 traditional and non-traditional HSI datasets spanning a range of HSI data configurations, spectral resolutions, spatial resolutions, bandpasses and applications. This study empirically measures algorithm performance against Dr. John Canny's six criteria for a good edge operator: false positives, false negatives, localization, single-point response, robustness to noise and unbroken edges. The end state is a suite of spatial-spectral edge detection algorithms that produce satisfactory edge results against a range of hyperspectral data types applicable to a diverse set of earth remote sensing applications. This work also explores the concept of an edge within hyperspectral space, the relative importance of spatial and spectral resolutions as they pertain to HSI edge detection and how effectively compressed HSI data improves edge detection results. The HSI edge detection experiments yielded valuable insights into the algorithms' strengths, weaknesses and optimal alignment to remote sensing applications. The gradient-based edge operator produced strong edge planes across a range of evaluation measures and applications, particularly with respect to false negatives, unbroken edges, urban mapping, vegetation mapping and oil spill mapping applications. False positives and uncompressed HSI data presented occasional challenges to the algorithm. The HySPADE edge operator produced satisfactory results with respect to localization, single-point response, oil spill mapping and trace chemical detection, and was challenged by false positives, declining spectral resolution and vegetation mapping applications. The level set edge detector produced high-quality edge planes for most tests and demonstrated strong performance with respect to false positives, single-point response, oil spill mapping and mineral mapping. False negatives were a regular challenge for the level set edge detection algorithm. Finally, HSI data optimized for spectral information compression and noise was shown to improve edge detection performance across all three algorithms, while the gradient-based algorithm and HySPADE demonstrated significant robustness to declining spectral and spatial resolutions.

Infrared and visible image fusion method based on saliency detection in sparse domain

NASA Astrophysics Data System (ADS)

Liu, C. H.; Qi, Y.; Ding, W. R.

2017-06-01

Infrared and visible image fusion is a key problem in the field of multi-sensor image fusion. To better preserve the significant information of the infrared and visible images in the final fused image, the saliency maps of the source images is introduced into the fusion procedure. Firstly, under the framework of the joint sparse representation (JSR) model, the global and local saliency maps of the source images are obtained based on sparse coefficients. Then, a saliency detection model is proposed, which combines the global and local saliency maps to generate an integrated saliency map. Finally, a weighted fusion algorithm based on the integrated saliency map is developed to achieve the fusion progress. The experimental results show that our method is superior to the state-of-the-art methods in terms of several universal quality evaluation indexes, as well as in the visual quality.

Based on time and spatial-resolved SERS mapping strategies for detection of pesticides.

PubMed

Ma, Bingbing; Li, Pan; Yang, Liangbao; Liu, Jinhuai

2015-08-15

For the sensitive and convenient detection of pesticides, several sensing methods and materials have been widely explored. However, it is still a challenge to obtain sensitive, simple detection techniques for pesticides. Here, the simple and sensitive Time-resolved SERS mapping (T-SERS) and Spatial-resolved SERS mapping (S-SERS) are presented for detection of pesticides by using Au@Ag NPs as SERS substrate. The Time-resolved SERS mapping (T-SERS) is based on state translation nanoparticles from the wet state to the dry state to realize SERS measurements. During the SERS measurement, adhesive force drives the particles closer together and then average interparticle gap becomes smaller. Following, air then begins to intersperse into the liquid network and the particles are held together by adhesive forces at the solid-liquid-air interface. In the late stage of water evaporation, all particles are uniformly distributed. Thus, so called hotspots matrix that can hold hotspots between every two adjacent particles in efficient space with minimal polydispersity of particle size are achieved, accompanying the red-shift of surface plasmon peak and appearance of an optimal SPR resonated sharply with excitation wavelength. Here, we found that the T-SERS method exhibits the detection limits of 1-2 orders of magnitude higher than that of S-SERS. On the other hand, the T-SERS is very simple method with high detection sensitivity, better reproducibility (RSD=10.8%) and is beneficial to construction of a calibration curve in comparison with that of Spatial-resolved SERS mapping (S-SERS). Most importantly, as a result of its remarkable sensitivity, T-SERS mapping strategies have been applied to detection of several pesticides and the detect limit can down to 1nM for paraoxon, 0.5nM for sumithion. In short, T-SERS mapping measurement promises to open a market for SERS practical detection with prominent advantages. Copyright © 2015. Published by Elsevier B.V.

Hotspot detection in pancreatic neuroendocrine tumors: density approximation by α-shape maps

NASA Astrophysics Data System (ADS)

Niazi, M. K. K.; Hartman, Douglas J.; Pantanowitz, Liron; Gurcan, Metin N.

2016-03-01

The grading of neuroendocrine tumors of the digestive system is dependent on accurate and reproducible assessment of the proliferation with the tumor, either by counting mitotic figures or counting Ki-67 positive nuclei. At the moment, most pathologists manually identify the hotspots, a practice which is tedious and irreproducible. To better help pathologists, we present an automatic method to detect all potential hotspots in neuroendocrine tumors of the digestive system. The method starts by segmenting Ki-67 positive nuclei by entropy based thresholding, followed by detection of centroids for all Ki-67 positive nuclei. Based on geodesic distance, approximated by the nuclei centroids, we compute two maps: an amoeba map and a weighted amoeba map. These maps are later combined to generate the heat map, the segmentation of which results in the hotspots. The method was trained on three and tested on nine whole slide images of neuroendocrine tumors. When evaluated by two expert pathologists, the method reached an accuracy of 92.6%. The current method does not discriminate between tumor, stromal and inflammatory nuclei. The results show that α-shape maps may represent how hotspots are perceived.

Adjusting the specificity of an engine map based on the sensitivity of an engine control parameter relative to a performance variable

DOEpatents

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2014-10-28

Methods and systems for engine control optimization are provided. A first and a second operating condition of a vehicle engine are detected. An initial value is identified for a first and a second engine control parameter corresponding to a combination of the detected operating conditions according to a first and a second engine map look-up table. The initial values for the engine control parameters are adjusted based on a detected engine performance variable to cause the engine performance variable to approach a target value. A first and a second sensitivity of the engine performance variable are determined in response to changes in the engine control parameters. The first engine map look-up table is adjusted when the first sensitivity is greater than a threshold, and the second engine map look-up table is adjusted when the second sensitivity is greater than a threshold.

ERS-2 SAR and IRS-1C LISS III data fusion: A PCA approach to improve remote sensing based geological interpretation

NASA Astrophysics Data System (ADS)

Pal, S. K.; Majumdar, T. J.; Bhattacharya, Amit K.

Fusion of optical and synthetic aperture radar data has been attempted in the present study for mapping of various lithologic units over a part of the Singhbhum Shear Zone (SSZ) and its surroundings. ERS-2 SAR data over the study area has been enhanced using Fast Fourier Transformation (FFT) based filtering approach, and also using Frost filtering technique. Both the enhanced SAR imagery have been then separately fused with histogram equalized IRS-1C LISS III image using Principal Component Analysis (PCA) technique. Later, Feature-oriented Principal Components Selection (FPCS) technique has been applied to generate False Color Composite (FCC) images, from which corresponding geological maps have been prepared. Finally, GIS techniques have been successfully used for change detection analysis in the lithological interpretation between the published geological map and the fusion based geological maps. In general, there is good agreement between these maps over a large portion of the study area. Based on the change detection studies, few areas could be identified which need attention for further detailed ground-based geological studies.

Mapping yeast origins of replication via single-stranded DNA detection.

PubMed

Feng, Wenyi; Raghuraman, M K; Brewer, Bonita J

2007-02-01

Studies in th Saccharomyces cerevisiae have provided a framework for understanding how eukaryotic cells replicate their chromosomal DNA to ensure faithful transmission of genetic information to their daughter cells. In particular, S. cerevisiae is the first eukaryote to have its origins of replication mapped on a genomic scale, by three independent groups using three different microarray-based approaches. Here we describe a new technique of origin mapping via detection of single-stranded DNA in yeast. This method not only identified the majority of previously discovered origins, but also detected new ones. We have also shown that this technique can identify origins in Schizosaccharomyces pombe, illustrating the utility of this method for origin mapping in other eukaryotes.

Accelerometer-based automatic voice onset detection in speech mapping with navigated repetitive transcranial magnetic stimulation.

PubMed

Vitikainen, Anne-Mari; Mäkelä, Elina; Lioumis, Pantelis; Jousmäki, Veikko; Mäkelä, Jyrki P

2015-09-30

The use of navigated repetitive transcranial magnetic stimulation (rTMS) in mapping of speech-related brain areas has recently shown to be useful in preoperative workflow of epilepsy and tumor patients. However, substantial inter- and intraobserver variability and non-optimal replicability of the rTMS results have been reported, and a need for additional development of the methodology is recognized. In TMS motor cortex mappings the evoked responses can be quantitatively monitored by electromyographic recordings; however, no such easily available setup exists for speech mappings. We present an accelerometer-based setup for detection of vocalization-related larynx vibrations combined with an automatic routine for voice onset detection for rTMS speech mapping applying naming. The results produced by the automatic routine were compared with the manually reviewed video-recordings. The new method was applied in the routine navigated rTMS speech mapping for 12 consecutive patients during preoperative workup for epilepsy or tumor surgery. The automatic routine correctly detected 96% of the voice onsets, resulting in 96% sensitivity and 71% specificity. Majority (63%) of the misdetections were related to visible throat movements, extra voices before the response, or delayed naming of the previous stimuli. The no-response errors were correctly detected in 88% of events. The proposed setup for automatic detection of voice onsets provides quantitative additional data for analysis of the rTMS-induced speech response modifications. The objectively defined speech response latencies increase the repeatability, reliability and stratification of the rTMS results. Copyright © 2015 Elsevier B.V. All rights reserved.

Rapid Landslide Mapping by Means of Post-Event Polarimetric SAR Imagery

NASA Astrophysics Data System (ADS)

Plank, Simon; Martinis, Sandro; Twele, Andre

2016-08-01

Rapid mapping of landslides, quickly providing information about the extent of the affected area and type and grade of damage, is crucial to enable fast crisis response. Reviewing the literature shows that most synthetic aperture radar (SAR) data-based landslide mapping procedures use change detection techniques. However, the required very high resolution (VHR) pre-event SAR imagery, acquired shortly before the landslide event, is commonly not available. Due to limitations in onboard disk space and downlink transmission rates modern VHR SAR missions do not systematically cover the entire world. We present a fast and robust procedure for mapping of landslides, based on change detection between freely available and systematically acquired pre-event optical and post-event polarimetric SAR data.

A Two-Layers Based Approach of an Enhanced-Map for Urban Positioning Support

PubMed Central

Piñana-Díaz, Carolina; Toledo-Moreo, Rafael; Toledo-Moreo, F. Javier; Skarmeta, Antonio

2012-01-01

This paper presents a two-layer based enhanced map that can support navigation in urban environments. One layer is dedicated to describe the drivable road with a special focus on the accurate description of its bounds. This feature can support positioning and advanced map-matching when compared with standard polyline-based maps. The other layer depicts building heights and locations, thus enabling the detection of non-line-of-sight signals coming from GPS satellites not in direct view. Both the concept and the methodology for creating these enhanced maps are shown in the paper. PMID:23202172

Map based localization to assist commercial fleet operations.

DOT National Transportation Integrated Search

2014-08-01

This report outlines key recent contributions to the state of the art in lane detection, lane departure warning, : and map-based sensor fusion algorithms. These key studies are used as a basis for a discussion about the : limitations of systems that ...

Cloud detection method for Chinese moderate high resolution satellite imagery (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo

2016-10-01

Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.

Change detection and classification in brain MR images using change vector analysis.

PubMed

Simões, Rita; Slump, Cornelis

2011-01-01

The automatic detection of longitudinal changes in brain images is valuable in the assessment of disease evolution and treatment efficacy. Most existing change detection methods that are currently used in clinical research to monitor patients suffering from neurodegenerative diseases--such as Alzheimer's--focus on large-scale brain deformations. However, such patients often have other brain impairments, such as infarcts, white matter lesions and hemorrhages, which are typically overlooked by the deformation-based methods. Other unsupervised change detection algorithms have been proposed to detect tissue intensity changes. The outcome of these methods is typically a binary change map, which identifies changed brain regions. However, understanding what types of changes these regions underwent is likely to provide equally important information about lesion evolution. In this paper, we present an unsupervised 3D change detection method based on Change Vector Analysis. We compute and automatically threshold the Generalized Likelihood Ratio map to obtain a binary change map. Subsequently, we perform histogram-based clustering to classify the change vectors. We obtain a Kappa Index of 0.82 using various types of simulated lesions. The classification error is 2%. Finally, we are able to detect and discriminate both small changes and ventricle expansions in datasets from Mild Cognitive Impairment patients.

Solution of the problem of superposing image and digital map for detection of new objects

NASA Astrophysics Data System (ADS)

Rizaev, I. S.; Miftakhutdinov, D. I.; Takhavova, E. G.

2018-01-01

The problem of superposing the map of the terrain with the image of the terrain is considered. The image of the terrain may be represented in different frequency bands. Further analysis of the results of collation the digital map with the image of the appropriate terrain is described. Also the approach to detection of differences between information represented on the digital map and information of the image of the appropriate area is offered. The algorithm for calculating the values of brightness of the converted image area on the original picture is offered. The calculation is based on using information about the navigation parameters and information according to arranged bench marks. For solving the posed problem the experiments were performed. The results of the experiments are shown in this paper. The presented algorithms are applicable to the ground complex of remote sensing data to assess differences between resulting images and accurate geopositional data. They are also suitable for detecting new objects in the image, based on the analysis of the matching the digital map and the image of corresponding locality.

Generating Impact Maps from Automatically Detected Bomb Craters in Aerial Wartime Images Using Marked Point Processes

NASA Astrophysics Data System (ADS)

Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian

2018-04-01

The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

Mapping the Recent US Hurricanes Triggered Flood Events in Near Real Time

NASA Astrophysics Data System (ADS)

Shen, X.; Lazin, R.; Anagnostou, E. N.; Wanik, D. W.; Brakenridge, G. R.

2017-12-01

Synthetic Aperture Radar (SAR) observations is the only reliable remote sensing data source to map flood inundation during severe weather events. Unfortunately, since state-of-art data processing algorithms cannot meet the automation and quality standard of a near-real-time (NRT) system, quality controlled inundation mapping by SAR currently depends heavily on manual processing, which limits our capability to quickly issue flood inundation maps at global scale. Specifically, most SAR-based inundation mapping algorithms are not fully automated, while those that are automated exhibit severe over- and/or under-detection errors that limit their potential. These detection errors are primarily caused by the strong overlap among the SAR backscattering probability density functions (PDF) of different land cover types. In this study, we tested a newly developed NRT SAR-based inundation mapping system, named Radar Produced Inundation Diary (RAPID), using Sentinel-1 dual polarized SAR data over recent flood events caused by Hurricanes Harvey, Irma, and Maria (2017). The system consists of 1) self-optimized multi-threshold classification, 2) over-detection removal using land-cover information and change detection, 3) under-detection compensation, and 4) machine-learning based correction. Algorithm details are introduced in another poster, H53J-1603. Good agreements were obtained by comparing the result from RAPID with visual interpretation of SAR images and manual processing from Dartmouth Flood Observatory (DFO) (See Figure 1). Specifically, the over- and under-detections that is typically noted in automated methods is significantly reduced to negligible levels. This performance indicates that RAPID can address the automation and accuracy issues of current state-of-art algorithms and has the potential to apply operationally on a number of satellite SAR missions, such as SWOT, ALOS, Sentinel etc. RAPID data can support many applications such as rapid assessment of damage losses and disaster alleviation/rescue at global scale.

Map-invariant spectral analysis for the identification of DNA periodicities

PubMed Central

2012-01-01

Many signal processing based methods for finding hidden periodicities in DNA sequences have primarily focused on assigning numerical values to the symbolic DNA sequence and then applying spectral analysis tools such as the short-time discrete Fourier transform (ST-DFT) to locate these repeats. The key results pertaining to this approach are however obtained using a very specific symbolic to numerical map, namely the so-called Voss representation. An important research problem is to therefore quantify the sensitivity of these results to the choice of the symbolic to numerical map. In this article, a novel algebraic approach to the periodicity detection problem is presented and provides a natural framework for studying the role of the symbolic to numerical map in finding these repeats. More specifically, we derive a new matrix-based expression of the DNA spectrum that comprises most of the widely used mappings in the literature as special cases, shows that the DNA spectrum is in fact invariable under all these mappings, and generates a necessary and sufficient condition for the invariance of the DNA spectrum to the symbolic to numerical map. Furthermore, the new algebraic framework decomposes the periodicity detection problem into several fundamental building blocks that are totally independent of each other. Sophisticated digital filters and/or alternate fast data transforms such as the discrete cosine and sine transforms can therefore be always incorporated in the periodicity detection scheme regardless of the choice of the symbolic to numerical map. Although the newly proposed framework is matrix based, identification of these periodicities can be achieved at a low computational cost. PMID:23067324

A Wireless Sensor System for Real-Time Measurement of Pressure Profiles at Lower Limb Protheses to Ensure Proper Fitting

DTIC Science & Technology

2011-10-01

been developed. The next step is to develop a the base technology into a grid like mapping sensor, construct the excitation and detection circuits...the project involves advancing the base technology into a grid -like mapping se nsor, constructing the excitation and detection circuits, modifying and...further. In conclusion, the screen printing and etching process allows for precise repeat able production of sensing elements for grid fabrication

Recovery of chemical Estimates by Field Inhomogeneity Neighborhood Error Detection (REFINED): Fat/Water Separation at 7T

PubMed Central

Narayan, Sreenath; Kalhan, Satish C.; Wilson, David L.

2012-01-01

I.Abstract Purpose To reduce swaps in fat-water separation methods, a particular issue on 7T small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Materials and Methods Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Results Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Conclusion Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. PMID:23023815

Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): fat/water separation at 7 tesla.

PubMed

Narayan, Sreenath; Kalhan, Satish C; Wilson, David L

2013-05-01

To reduce swaps in fat-water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. Copyright © 2012 Wiley Periodicals, Inc.

Stereo-vision-based terrain mapping for off-road autonomous navigation

NASA Astrophysics Data System (ADS)

Rankin, Arturo L.; Huertas, Andres; Matthies, Larry H.

2009-05-01

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as nogo regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

Stereo Vision Based Terrain Mapping for Off-Road Autonomous Navigation

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.; Huertas, Andres; Matthies, Larry H.

2009-01-01

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as no-go regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

Comparison of soft-input-soft-output detection methods for dual-polarized quadrature duobinary system

NASA Astrophysics Data System (ADS)

Chang, Chun; Huang, Benxiong; Xu, Zhengguang; Li, Bin; Zhao, Nan

2018-02-01

Three soft-input-soft-output (SISO) detection methods for dual-polarized quadrature duobinary (DP-QDB), including maximum-logarithmic-maximum-a-posteriori-probability-algorithm (Max-log-MAP)-based detection, soft-output-Viterbi-algorithm (SOVA)-based detection, and a proposed SISO detection, which can all be combined with SISO decoding, are presented. The three detection methods are investigated at 128 Gb/s in five-channel wavelength-division-multiplexing uncoded and low-density-parity-check (LDPC) coded DP-QDB systems by simulations. Max-log-MAP-based detection needs the returning-to-initial-states (RTIS) process despite having the best performance. When the LDPC code with a code rate of 0.83 is used, the detecting-and-decoding scheme with the SISO detection does not need RTIS and has better bit error rate (BER) performance than the scheme with SOVA-based detection. The former can reduce the optical signal-to-noise ratio (OSNR) requirement (at BER=10-5) by 2.56 dB relative to the latter. The application of the SISO iterative detection in LDPC-coded DP-QDB systems makes a good trade-off between requirements on transmission efficiency, OSNR requirement, and transmission distance, compared with the other two SISO methods.

High-Performance Signal Detection for Adverse Drug Events using MapReduce Paradigm.

PubMed

Fan, Kai; Sun, Xingzhi; Tao, Ying; Xu, Linhao; Wang, Chen; Mao, Xianling; Peng, Bo; Pan, Yue

2010-11-13

Post-marketing pharmacovigilance is important for public health, as many Adverse Drug Events (ADEs) are unknown when those drugs were approved for marketing. However, due to the large number of reported drugs and drug combinations, detecting ADE signals by mining these reports is becoming a challenging task in terms of computational complexity. Recently, a parallel programming model, MapReduce has been introduced by Google to support large-scale data intensive applications. In this study, we proposed a MapReduce-based algorithm, for common ADE detection approach, Proportional Reporting Ratio (PRR), and tested it in mining spontaneous ADE reports from FDA. The purpose is to investigate the possibility of using MapReduce principle to speed up biomedical data mining tasks using this pharmacovigilance case as one specific example. The results demonstrated that MapReduce programming model could improve the performance of common signal detection algorithm for pharmacovigilance in a distributed computation environment at approximately liner speedup rates.

Mapping Quantitative Field Resistance Against Apple Scab in a 'Fiesta' x 'Discovery' Progeny.

PubMed

Liebhard, R; Koller, B; Patocchi, A; Kellerhals, M; Pfammatter, W; Jermini, M; Gessler, C

2003-04-01

ABSTRACT Breeding of resistant apple cultivars (Malus x domestica) as a disease management strategy relies on the knowledge and understanding of the underlying genetics. The availability of molecular markers and genetic linkage maps enables the detection and the analysis of major resistance genes as well as of quantitative trait loci (QTL) contributing to the resistance of a genotype. Such a genetic linkage map was constructed, based on a segregating population of the cross between apple cvs. Fiesta (syn. Red Pippin) and Discovery. The progeny was observed for 3 years at three different sites in Switzerland and field resistance against apple scab (Venturia inaequalis) was assessed. Only a weak correlation was detected between leaf scab and fruit scab. A QTL analysis was performed, based on the genetic linkage map consisting of 804 molecular markers and covering all 17 chromosomes of apple. With the maximum likelihood-based interval mapping method, eight genomic regions were identified, six conferring resistance against leaf scab and two conferring fruit scab resistance. Although cv. Discovery showed a much stronger resistance against scab in the field, most QTL identified were attributed to the more susceptible parent 'Fiesta'. This indicated a high degree of homozygosity at the scab resistance loci in 'Discovery', preventing their detection in the progeny due to the lack of segregation.

Object detection system based on multimodel saliency maps

NASA Astrophysics Data System (ADS)

Guo, Ya'nan; Luo, Chongfan; Ma, Yide

2017-03-01

Detection of visually salient image regions is extensively applied in computer vision and computer graphics, such as object detection, adaptive compression, and object recognition, but any single model always has its limitations to various images, so in our work, we establish a method based on multimodel saliency maps to detect the object, which intelligently absorbs the merits of various individual saliency detection models to achieve promising results. The method can be roughly divided into three steps: in the first step, we propose a decision-making system to evaluate saliency maps obtained by seven competitive methods and merely select the three most valuable saliency maps; in the second step, we introduce heterogeneous PCNN algorithm to obtain three prime foregrounds; and then a self-designed nonlinear fusion method is proposed to merge these saliency maps; at last, the adaptive improved and simplified PCNN model is used to detect the object. Our proposed method can constitute an object detection system for different occasions, which requires no training, is simple, and highly efficient. The proposed saliency fusion technique shows better performance over a broad range of images and enriches the applicability range by fusing different individual saliency models, this proposed system is worthy enough to be called a strong model. Moreover, the proposed adaptive improved SPCNN model is stemmed from the Eckhorn's neuron model, which is skilled in image segmentation because of its biological background, and in which all the parameters are adaptive to image information. We extensively appraise our algorithm on classical salient object detection database, and the experimental results demonstrate that the aggregation of saliency maps outperforms the best saliency model in all cases, yielding highest precision of 89.90%, better recall rates of 98.20%, greatest F-measure of 91.20%, and lowest mean absolute error value of 0.057, the value of proposed saliency evaluation EHA reaches to 215.287. We deem our method can be wielded to diverse applications in the future.

Determination of a Limited Scope Network's Lightning Detection Efficiency

NASA Technical Reports Server (NTRS)

Rompala, John T.; Blakeslee, R.

2008-01-01

This paper outlines a modeling technique to map lightning detection efficiency variations over a region surveyed by a sparse array of ground based detectors. A reliable flash peak current distribution (PCD) for the region serves as the technique's base. This distribution is recast as an event probability distribution function. The technique then uses the PCD together with information regarding: site signal detection thresholds, type of solution algorithm used, and range attenuation; to formulate the probability that a flash at a specified location will yield a solution. Applying this technique to the full region produces detection efficiency contour maps specific to the parameters employed. These contours facilitate a comparative analysis of each parameter's effect on the network's detection efficiency. In an alternate application, this modeling technique gives an estimate of the number, strength, and distribution of events going undetected. This approach leads to a variety of event density contour maps. This application is also illustrated. The technique's base PCD can be empirical or analytical. A process for formulating an empirical PCD specific to the region and network being studied is presented. A new method for producing an analytical representation of the empirical PCD is also introduced.

A unified approach for debugging is-a structure and mappings in networked taxonomies

PubMed Central

2013-01-01

Background With the increased use of ontologies and ontology mappings in semantically-enabled applications such as ontology-based search and data integration, the issue of detecting and repairing defects in ontologies and ontology mappings has become increasingly important. These defects can lead to wrong or incomplete results for the applications. Results We propose a unified framework for debugging the is-a structure of and mappings between taxonomies, the most used kind of ontologies. We present theory and algorithms as well as an implemented system RepOSE, that supports a domain expert in detecting and repairing missing and wrong is-a relations and mappings. We also discuss two experiments performed by domain experts: an experiment on the Anatomy ontologies from the Ontology Alignment Evaluation Initiative, and a debugging session for the Swedish National Food Agency. Conclusions Semantically-enabled applications need high quality ontologies and ontology mappings. One key aspect is the detection and removal of defects in the ontologies and ontology mappings. Our system RepOSE provides an environment that supports domain experts to deal with this issue. We have shown the usefulness of the approach in two experiments by detecting and repairing circa 200 and 30 defects, respectively. PMID:23548155

Detecting spatial regimes in ecosystems

USGS Publications Warehouse

Sundstrom, Shana M.; Eason, Tarsha; Nelson, R. John; Angeler, David G.; Barichievy, Chris; Garmestani, Ahjond S.; Graham, Nicholas A.J.; Granholm, Dean; Gunderson, Lance; Knutson, Melinda; Nash, Kirsty L.; Spanbauer, Trisha; Stow, Craig A.; Allen, Craig R.

2017-01-01

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.

A high-density genetic map and growth related QTL mapping in bighead carp (Hypophthalmichthys nobilis)

PubMed Central

Fu, Beide; Liu, Haiyang; Yu, Xiaomu; Tong, Jingou

2016-01-01

Growth related traits in fish are controlled by quantitative trait loci (QTL), but no QTL for growth have been detected in bighead carp (Hypophthalmichthys nobilis) due to the lack of high-density genetic map. In this study, an ultra-high density genetic map was constructed with 3,121 SNP markers by sequencing 117 individuals in a F1 family using 2b-RAD technology. The total length of the map was 2341.27 cM, with an average marker interval of 0.75 cM. A high level of genomic synteny between our map and zebrafish was detected. Based on this genetic map, one genome-wide significant and 37 suggestive QTL for five growth-related traits were identified in 6 linkage groups (i.e. LG3, LG11, LG15, LG18, LG19, LG22). The phenotypic variance explained (PVE) by these QTL varied from 15.4% to 38.2%. Marker within the significant QTL region was surrounded by CRP1 and CRP2, which played an important role in muscle cell division. These high-density map and QTL information provided a solid base for QTL fine mapping and comparative genomics in bighead carp. PMID:27345016

Detecting spatial regimes in ecosystems | Science Inventory ...

EPA Pesticide Factsheets

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory based method, on both terrestrial and aquatic animal data (US Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps, and multivariate analysis such as nMDS (non-metric Multidimensional Scaling) and cluster analysis. We successfully detect spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change. Use an information theory based method to identify ecological boundaries and compare our results to traditional early warning

Model-Based Building Detection from Low-Cost Optical Sensors Onboard Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Karantzalos, K.; Koutsourakis, P.; Kalisperakis, I.; Grammatikopoulos, L.

2015-08-01

The automated and cost-effective building detection in ultra high spatial resolution is of major importance for various engineering and smart city applications. To this end, in this paper, a model-based building detection technique has been developed able to extract and reconstruct buildings from UAV aerial imagery and low-cost imaging sensors. In particular, the developed approach through advanced structure from motion, bundle adjustment and dense image matching computes a DSM and a true orthomosaic from the numerous GoPro images which are characterised by important geometric distortions and fish-eye effect. An unsupervised multi-region, graphcut segmentation and a rule-based classification is responsible for delivering the initial multi-class classification map. The DTM is then calculated based on inpaininting and mathematical morphology process. A data fusion process between the detected building from the DSM/DTM and the classification map feeds a grammar-based building reconstruction and scene building are extracted and reconstructed. Preliminary experimental results appear quite promising with the quantitative evaluation indicating detection rates at object level of 88% regarding the correctness and above 75% regarding the detection completeness.

A Deep Convolutional Coupling Network for Change Detection Based on Heterogeneous Optical and Radar Images.

PubMed

Liu, Jia; Gong, Maoguo; Qin, Kai; Zhang, Puzhao

2018-03-01

We propose an unsupervised deep convolutional coupling network for change detection based on two heterogeneous images acquired by optical sensors and radars on different dates. Most existing change detection methods are based on homogeneous images. Due to the complementary properties of optical and radar sensors, there is an increasing interest in change detection based on heterogeneous images. The proposed network is symmetric with each side consisting of one convolutional layer and several coupling layers. The two input images connected with the two sides of the network, respectively, are transformed into a feature space where their feature representations become more consistent. In this feature space, the different map is calculated, which then leads to the ultimate detection map by applying a thresholding algorithm. The network parameters are learned by optimizing a coupling function. The learning process is unsupervised, which is different from most existing change detection methods based on heterogeneous images. Experimental results on both homogenous and heterogeneous images demonstrate the promising performance of the proposed network compared with several existing approaches.

Smartphone-Based Mobile Detection Platform for Molecular Diagnostics and Spatiotemporal Disease Mapping.

PubMed

Song, Jinzhao; Pandian, Vikram; Mauk, Michael G; Bau, Haim H; Cherry, Sara; Tisi, Laurence C; Liu, Changchun

2018-04-03

Rapid and quantitative molecular diagnostics in the field, at home, and at remote clinics is essential for evidence-based disease management, control, and prevention. Conventional molecular diagnostics requires extensive sample preparation, relatively sophisticated instruments, and trained personnel, restricting its use to centralized laboratories. To overcome these limitations, we designed a simple, inexpensive, hand-held, smartphone-based mobile detection platform, dubbed "smart-connected cup" (SCC), for rapid, connected, and quantitative molecular diagnostics. Our platform combines bioluminescent assay in real-time and loop-mediated isothermal amplification (BART-LAMP) technology with smartphone-based detection, eliminating the need for an excitation source and optical filters that are essential in fluorescent-based detection. The incubation heating for the isothermal amplification is provided, electricity-free, with an exothermic chemical reaction, and incubation temperature is regulated with a phase change material. A custom Android App was developed for bioluminescent signal monitoring and analysis, target quantification, data sharing, and spatiotemporal mapping of disease. SCC's utility is demonstrated by quantitative detection of Zika virus (ZIKV) in urine and saliva and HIV in blood within 45 min. We demonstrate SCC's connectivity for disease spatiotemporal mapping with a custom-designed website. Such a smart- and connected-diagnostic system does not require any lab facilities and is suitable for use at home, in the field, in the clinic, and particularly in resource-limited settings in the context of Internet of Medical Things (IoMT).

Comparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery

PubMed Central

Tsai, Yu Hsin; Stow, Douglas; Weeks, John

2013-01-01

The goal of this study was to map and quantify the number of newly constructed buildings in Accra, Ghana between 2002 and 2010 based on high spatial resolution satellite image data. Two semi-automated feature detection approaches for detecting and mapping newly constructed buildings based on QuickBird very high spatial resolution satellite imagery were analyzed: (1) post-classification comparison; and (2) bi-temporal layerstack classification. Feature Analyst software based on a spatial contextual classifier and ENVI Feature Extraction that uses a true object-based image analysis approach of image segmentation and segment classification were evaluated. Final map products representing new building objects were compared and assessed for accuracy using two object-based accuracy measures, completeness and correctness. The bi-temporal layerstack method generated more accurate results compared to the post-classification comparison method due to less confusion with background objects. The spectral/spatial contextual approach (Feature Analyst) outperformed the true object-based feature delineation approach (ENVI Feature Extraction) due to its ability to more reliably delineate individual buildings of various sizes. Semi-automated, object-based detection followed by manual editing appears to be a reliable and efficient approach for detecting and enumerating new building objects. A bivariate regression analysis was performed using neighborhood-level estimates of new building density regressed on a census-derived measure of socio-economic status, yielding an inverse relationship with R2 = 0.31 (n = 27; p = 0.00). The primary utility of the new building delineation results is to support spatial analyses of land cover and land use and demographic change. PMID:24415810

Multitask saliency detection model for synthetic aperture radar (SAR) image and its application in SAR and optical image fusion

NASA Astrophysics Data System (ADS)

Liu, Chunhui; Zhang, Duona; Zhao, Xintao

2018-03-01

Saliency detection in synthetic aperture radar (SAR) images is a difficult problem. This paper proposed a multitask saliency detection (MSD) model for the saliency detection task of SAR images. We extract four features of the SAR image, which include the intensity, orientation, uniqueness, and global contrast, as the input of the MSD model. The saliency map is generated by the multitask sparsity pursuit, which integrates the multiple features collaboratively. Detection of different scale features is also taken into consideration. Subjective and objective evaluation of the MSD model verifies its effectiveness. Based on the saliency maps obtained by the MSD model, we apply the saliency map of the SAR image to the SAR and color optical image fusion. The experimental results of real data show that the saliency map obtained by the MSD model helps to improve the fusion effect, and the salient areas in the SAR image can be highlighted in the fusion results.

Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks.

PubMed

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-11-24

Vehicle detection in aerial images is an important and challenging task. Traditionally, many target detection models based on sliding-window fashion were developed and achieved acceptable performance, but these models are time-consuming in the detection phase. Recently, with the great success of convolutional neural networks (CNNs) in computer vision, many state-of-the-art detectors have been designed based on deep CNNs. However, these CNN-based detectors are inefficient when applied in aerial image data due to the fact that the existing CNN-based models struggle with small-size object detection and precise localization. To improve the detection accuracy without decreasing speed, we propose a CNN-based detection model combining two independent convolutional neural networks, where the first network is applied to generate a set of vehicle-like regions from multi-feature maps of different hierarchies and scales. Because the multi-feature maps combine the advantage of the deep and shallow convolutional layer, the first network performs well on locating the small targets in aerial image data. Then, the generated candidate regions are fed into the second network for feature extraction and decision making. Comprehensive experiments are conducted on the Vehicle Detection in Aerial Imagery (VEDAI) dataset and Munich vehicle dataset. The proposed cascaded detection model yields high performance, not only in detection accuracy but also in detection speed.

Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks

PubMed Central

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-01-01

Vehicle detection in aerial images is an important and challenging task. Traditionally, many target detection models based on sliding-window fashion were developed and achieved acceptable performance, but these models are time-consuming in the detection phase. Recently, with the great success of convolutional neural networks (CNNs) in computer vision, many state-of-the-art detectors have been designed based on deep CNNs. However, these CNN-based detectors are inefficient when applied in aerial image data due to the fact that the existing CNN-based models struggle with small-size object detection and precise localization. To improve the detection accuracy without decreasing speed, we propose a CNN-based detection model combining two independent convolutional neural networks, where the first network is applied to generate a set of vehicle-like regions from multi-feature maps of different hierarchies and scales. Because the multi-feature maps combine the advantage of the deep and shallow convolutional layer, the first network performs well on locating the small targets in aerial image data. Then, the generated candidate regions are fed into the second network for feature extraction and decision making. Comprehensive experiments are conducted on the Vehicle Detection in Aerial Imagery (VEDAI) dataset and Munich vehicle dataset. The proposed cascaded detection model yields high performance, not only in detection accuracy but also in detection speed. PMID:29186756

Salient region detection by fusing bottom-up and top-down features extracted from a single image.

PubMed

Tian, Huawei; Fang, Yuming; Zhao, Yao; Lin, Weisi; Ni, Rongrong; Zhu, Zhenfeng

2014-10-01

Recently, some global contrast-based salient region detection models have been proposed based on only the low-level feature of color. It is necessary to consider both color and orientation features to overcome their limitations, and thus improve the performance of salient region detection for images with low-contrast in color and high-contrast in orientation. In addition, the existing fusion methods for different feature maps, like the simple averaging method and the selective method, are not effective sufficiently. To overcome these limitations of existing salient region detection models, we propose a novel salient region model based on the bottom-up and top-down mechanisms: the color contrast and orientation contrast are adopted to calculate the bottom-up feature maps, while the top-down cue of depth-from-focus from the same single image is used to guide the generation of final salient regions, since depth-from-focus reflects the photographer's preference and knowledge of the task. A more general and effective fusion method is designed to combine the bottom-up feature maps. According to the degree-of-scattering and eccentricities of feature maps, the proposed fusion method can assign adaptive weights to different feature maps to reflect the confidence level of each feature map. The depth-from-focus of the image as a significant top-down feature for visual attention in the image is used to guide the salient regions during the fusion process; with its aid, the proposed fusion method can filter out the background and highlight salient regions for the image. Experimental results show that the proposed model outperforms the state-of-the-art models on three public available data sets.

A biosensor assay for the detection of Mycobacterium avium subsp. paratuberculosis in fecal samples

PubMed Central

Kumanan, Vijayarani; Nugen, Sam R.; Baeumner, Antje J.

2009-01-01

A simple, membrane-strip-based lateral-flow (LF) biosensor assay and a high-throughput microtiter plate assay have been combined with a reverse transcriptase polymerase chain reaction (RT-PCR) for the detection of a small number (ten) of viable Mycobacterium (M.) avium subsp. paratuberculosis (MAP) cells in fecal samples. The assays are based on the identification of the RNA of the IS900 element of MAP. For the assay, RNA was extracted from fecal samples spiked with a known quantity of (101 to 106) MAP cells and amplified using RT-PCR and identified by the LF biosensor and the microtiter plate assay. While the LF biosensor assay requires only 30 min of assay time, the overall process took 10 h for the detection of 10 viable cells. The assays are based on an oligonucleotide sandwich hybridization assay format and use either a membrane flow through system with an immobilized DNA probe that hybridizes with the target sequence or a microtiter plate well. Signal amplification is provided when the target sequence hybridizes to a second DNA probe that has been coupled to liposomes encapsulating the dye, sulforhodamine B. The dye in the liposomes provides a signal that can be read visually, quantified with a hand-held reflectometer, or with a fluorescence reader. Specificity analysis of the assays revealed no cross reactivity with other mycobacteria, such as M. avium complex, M. ulcerans, M. marium, M. kansasii, M. abscessus, M. asiaticum, M. phlei, M. fortuitum, M. scrofulaceum, M. intracellulare, M. smegmatis, and M. bovis. The overall assay for the detection of live MAP organisms is comparatively less expensive and quick, especially in comparison to standard MAP detection using a culture method requiring 6-8 weeks of incubation time, and is significantly less expensive than real-time PCR. PMID:19255522

Infrared dim target detection based on visual attention

NASA Astrophysics Data System (ADS)

Wang, Xin; Lv, Guofang; Xu, Lizhong

2012-11-01

Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. Based on human visual attention mechanisms, an automatic detection algorithm for infrared dim target is presented. After analyzing the characteristics of infrared dim target images, the method firstly designs Difference of Gaussians (DoG) filters to compute the saliency map. Then the salient regions where the potential targets exist in are extracted by searching through the saliency map with a control mechanism of winner-take-all (WTA) competition and inhibition-of-return (IOR). At last, these regions are identified by the characteristics of the dim IR targets, so the true targets are detected, and the spurious objects are rejected. The experiments are performed for some real-life IR images, and the results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

Forest Fire Advanced System Technology (FFAST): A Conceptual Design for Detection and Mapping

Treesearch

J. David Nichols; John R. Warren

1987-01-01

The Forest Fire Advanced System Technology (FFAST) project is developing a data system to provide near-real-time forest fire information to fire management at the fire Incident Command Post (ICP). The completed conceptual design defined an integrated forest fire detection and mapping system that is based upon technology available in the 1990's. System component...

Fluorescence spectroscopy using indocyanine green for lymph node mapping

NASA Astrophysics Data System (ADS)

Haj-Hosseini, Neda; Behm, Pascal; Shabo, Ivan; Wârdell, Karin

2014-02-01

The principles of cancer treatment has for years been radical resection of the primary tumor. In the oncologic surgeries where the affected cancer site is close to the lymphatic system, it is as important to detect the draining lymph nodes for metastasis (lymph node mapping). As a replacement for conventional radioactive labeling, indocyanine green (ICG) has shown successful results in lymph node mapping; however, most of the ICG fluorescence detection techniques developed are based on camera imaging. In this work, fluorescence spectroscopy using a fiber-optical probe was evaluated on a tissue-like ICG phantom with ICG concentrations of 6-64 μM and on breast tissue from five patients. Fiber-optical based spectroscopy was able to detect ICG fluorescence at low intensities; therefore, it is expected to increase the detection threshold of the conventional imaging systems when used intraoperatively. The probe allows spectral characterization of the fluorescence and navigation in the tissue as opposed to camera imaging which is limited to the view on the surface of the tissue.

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

PubMed

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

2018-01-10

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

Exploring representations of protein structure for automated remote homology detection and mapping of protein structure space

PubMed Central

2014-01-01

Background Due to rapid sequencing of genomes, there are now millions of deposited protein sequences with no known function. Fast sequence-based comparisons allow detecting close homologs for a protein of interest to transfer functional information from the homologs to the given protein. Sequence-based comparison cannot detect remote homologs, in which evolution has adjusted the sequence while largely preserving structure. Structure-based comparisons can detect remote homologs but most methods for doing so are too expensive to apply at a large scale over structural databases of proteins. Recently, fragment-based structural representations have been proposed that allow fast detection of remote homologs with reasonable accuracy. These representations have also been used to obtain linearly-reducible maps of protein structure space. It has been shown, as additionally supported from analysis in this paper that such maps preserve functional co-localization of the protein structure space. Methods Inspired by a recent application of the Latent Dirichlet Allocation (LDA) model for conducting structural comparisons of proteins, we propose higher-order LDA-obtained topic-based representations of protein structures to provide an alternative route for remote homology detection and organization of the protein structure space in few dimensions. Various techniques based on natural language processing are proposed and employed to aid the analysis of topics in the protein structure domain. Results We show that a topic-based representation is just as effective as a fragment-based one at automated detection of remote homologs and organization of protein structure space. We conduct a detailed analysis of the information content in the topic-based representation, showing that topics have semantic meaning. The fragment-based and topic-based representations are also shown to allow prediction of superfamily membership. Conclusions This work opens exciting venues in designing novel representations to extract information about protein structures, as well as organizing and mining protein structure space with mature text mining tools. PMID:25080993

Arctic lead detection using a waveform mixture algorithm from CryoSat-2 data

NASA Astrophysics Data System (ADS)

Lee, Sanggyun; Kim, Hyun-cheol; Im, Jungho

2018-05-01

We propose a waveform mixture algorithm to detect leads from CryoSat-2 data, which is novel and different from the existing threshold-based lead detection methods. The waveform mixture algorithm adopts the concept of spectral mixture analysis, which is widely used in the field of hyperspectral image analysis. This lead detection method was evaluated with high-resolution (250 m) MODIS images and showed comparable and promising performance in detecting leads when compared to the previous methods. The robustness of the proposed approach also lies in the fact that it does not require the rescaling of parameters (i.e., stack standard deviation, stack skewness, stack kurtosis, pulse peakiness, and backscatter σ0), as it directly uses L1B waveform data, unlike the existing threshold-based methods. Monthly lead fraction maps were produced by the waveform mixture algorithm, which shows interannual variability of recent sea ice cover during 2011-2016, excluding the summer season (i.e., June to September). We also compared the lead fraction maps to other lead fraction maps generated from previously published data sets, resulting in similar spatiotemporal patterns.

How to Display Hazards and other Scientific Data Using Google Maps

NASA Astrophysics Data System (ADS)

Venezky, D. Y.; Fee, J. M.

2007-12-01

The U.S. Geological Survey's (USGS) Volcano Hazard Program (VHP) is launching a map-based interface to display hazards information using the Google® Map API (Application Program Interface). Map-based interfaces provide a synoptic view of data, making patterns easier to detect and allowing users to quickly ascertain where hazards are in relation to major population and infrastructure centers. Several map-based interfaces are now simple to run on a web server, providing ideal platforms for sharing information with colleagues, emergency managers, and the public. There are three main steps to making data accessible on a map-based interface; formatting the input data, plotting the data on the map, and customizing the user interface. The presentation, "Creating Geospatial RSS and ATOM feeds for Map-based Interfaces" (Fee and Venezky, this session), reviews key features for map input data. Join us for this presentation on how to plot data in a geographic context and then format the display with images, custom markers, and links to external data. Examples will show how the VHP Volcano Status Map was created and how to plot a field trip with driving directions.

Magnetic Separation Methods for the Detection of Mycobacterium avium subsp. paratuberculosis in Various Types of Matrices: A Review

PubMed Central

Dziedzinska, Radka

2017-01-01

The main reasons to improve the detection of Mycobacterium avium subsp. paratuberculosis (MAP) are animal health and monitoring of MAP entering the food chain via meat, milk, and/or dairy products. Different approaches can be used for the detection of MAP, but the use of magnetic separation especially in conjunction with PCR as an end-point detection method has risen in past years. However, the extraction of DNA which is a crucial step prior to PCR detection can be complicated due to the presence of inhibitory substances. Magnetic separation methods involving either antibodies or peptides represent a powerful tool for selective separation of target bacteria from other nontarget microorganisms and inhibitory sample components. These methods enable the concentration of pathogens present in the initial matrix into smaller volume and facilitate the isolation of sufficient quantities of pure DNA. The purpose of this review was to summarize the methods based on the magnetic separation approach that are currently available for the detection of MAP in a broad range of matrices. PMID:28642876

Regional Principal Color Based Saliency Detection

PubMed Central

Lou, Jing; Ren, Mingwu; Wang, Huan

2014-01-01

Saliency detection is widely used in many visual applications like image segmentation, object recognition and classification. In this paper, we will introduce a new method to detect salient objects in natural images. The approach is based on a regional principal color contrast modal, which incorporates low-level and medium-level visual cues. The method allows a simple computation of color features and two categories of spatial relationships to a saliency map, achieving higher F-measure rates. At the same time, we present an interpolation approach to evaluate resulting curves, and analyze parameters selection. Our method enables the effective computation of arbitrary resolution images. Experimental results on a saliency database show that our approach produces high quality saliency maps and performs favorably against ten saliency detection algorithms. PMID:25379960

Detecting spatial regimes in ecosystems

EPA Science Inventory

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological ...

Small-size pedestrian detection in large scene based on fast R-CNN

NASA Astrophysics Data System (ADS)

Wang, Shengke; Yang, Na; Duan, Lianghua; Liu, Lu; Dong, Junyu

2018-04-01

Pedestrian detection is a canonical sub-problem of object detection with high demand during recent years. Although recent deep learning object detectors such as Fast/Faster R-CNN have shown excellent performance for general object detection, they have limited success for small size pedestrian detection in large-view scene. We study that the insufficient resolution of feature maps lead to the unsatisfactory accuracy when handling small instances. In this paper, we investigate issues involving Fast R-CNN for pedestrian detection. Driven by the observations, we propose a very simple but effective baseline for pedestrian detection based on Fast R-CNN, employing the DPM detector to generate proposals for accuracy, and training a fast R-CNN style network to jointly optimize small size pedestrian detection with skip connection concatenating feature from different layers to solving coarseness of feature maps. And the accuracy is improved in our research for small size pedestrian detection in the real large scene.

Potential of Pest and Host Phenological Data in the Attribution of Regional Forest Disturbance Detection Maps According to Causal Agent

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William; Norman Steve; Christie, William

2014-01-01

Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced since 2010 for the conterminous U.S., as part of the on-line ForWarn national forest threat early warning system. The latter has been used by the forest health community to identify and track many regional forest disturbances caused by multiple biotic and abiotic damage agents. Attribution of causal agents for detected disturbances has been a goal since project initiation in 2006. Combined with detailed cover type maps, geospatial pest phenology data offer a potential means for narrowing the candidate causal agents responsible for a given biotic disturbance. U.S. Aerial Detection Surveys (ADS) employ such phenology data. Historic ADS products provide general locational data on recent insect-induced forest type specific disturbances that may help in determining candidate causal agents for MODIS-based disturbance maps, especially when combined with other historic geospatial disturbance data (e.g., wildfire burn scars and drought maps). Historic ADS disturbance detection polygons can show severe and extensive regional forest disturbances, though they also can show polygons with sparsely scattered or infrequent disturbances. Examples will be discussed that use various historic disturbance data to help determine potential causes of MODIS-detected regional forest disturbance anomalies.

Detecting and Quantifying Topography in Neural Maps

PubMed Central

Yarrow, Stuart; Razak, Khaleel A.; Seitz, Aaron R.; Seriès, Peggy

2014-01-01

Topographic maps are an often-encountered feature in the brains of many species, yet there are no standard, objective procedures for quantifying topography. Topographic maps are typically identified and described subjectively, but in cases where the scale of the map is close to the resolution limit of the measurement technique, identifying the presence of a topographic map can be a challenging subjective task. In such cases, an objective topography detection test would be advantageous. To address these issues, we assessed seven measures (Pearson distance correlation, Spearman distance correlation, Zrehen's measure, topographic product, topological correlation, path length and wiring length) by quantifying topography in three classes of cortical map model: linear, orientation-like, and clusters. We found that all but one of these measures were effective at detecting statistically significant topography even in weakly-ordered maps, based on simulated noisy measurements of neuronal selectivity and sparse sampling of the maps. We demonstrate the practical applicability of these measures by using them to examine the arrangement of spatial cue selectivity in pallid bat A1. This analysis shows that significantly topographic arrangements of interaural intensity difference and azimuth selectivity exist at the scale of individual binaural clusters. PMID:24505279

High-resolution carbon mapping on the million-hectare Island of Hawaii

Treesearch

Gregory P. Asner; R. Flint Hughes; Joseph Mascaro; Amanda L. Uowolo; David E. Knapp; James Jacobson; Ty Kennedy-Bowdoin; John K . Clark

2011-01-01

Current markets and international agreements for reducing emissions from deforestation and forest degradation (REDD) rely on carbon (C) monitoring techniques. Combining field measurements, airborne light detection and ranging (LiDAR)-based observations, and satellite-based imagery, we developed a 30-meter-resolution map of aboveground C density spanning 40 vegetation...

What is missing? An operational inundation mapping framework by SAR data

NASA Astrophysics Data System (ADS)

Shen, X.; Anagnostou, E. N.; Zeng, Z.; Kettner, A.; Hong, Y.

2017-12-01

Compared to optical sensors, synthetic aperture radar (SAR) works all-day all-weather. In addition, its spatial resolution does not decrease with the height of the platform and is thus applicable to a range of important studies. However, existing studies did not address the operational demands of real-time inundation mapping. The direct proof is that no water body product exists for any SAR-based satellites. Then what is missing between science and products? Automation and quality. What makes it so difficult to develop an operational inundation mapping technique based on SAR data? Spectrum-wise, unlike optical water indices such as MNDWI, AWEI etc., where a relative constant threshold may apply across acquisition of images, regions and sensors, the threshold to separate water from non-water pixels in each SAR images has to be individually chosen. The optimization of the threshold is the first obstacle to the automation of the SAR data algorithm. Morphologically, the quality and reliability of the results have been compromised by over-detection caused by smooth surface and shadowing area, the noise-like speckle and under-detection caused by strong-scatter disturbance. In this study, we propose a three-step framework that addresses all aforementioned issues of operational inundation mapping by SAR data. The framework consists of 1) optimization of Wishart distribution parameters of single/dual/fully-polarized SAR data, 2) morphological removal of over-detection, and 3) machine-learning based removal of under-detection. The framework utilizes not only the SAR data, but also the synergy of digital elevation model (DEM), and optical sensor-based products of fine resolution, including the water probability map, land cover classification map (optional), and river width. The framework has been validated throughout multiple areas in different parts of the world using different satellite SAR data and globally available ancillary data products. Therefore, it has the potential to contribute as an operational inundation mapping algorithm to any SAR missions, such as SWOT, ALOS, Sentinel, etc. Selected results using ALOS/PALSAR-1 L-band dual polarized data around the Connecticut River is provided in the attached Figure.

A stereo-vision hazard-detection algorithm to increase planetary lander autonomy

NASA Astrophysics Data System (ADS)

Woicke, Svenja; Mooij, Erwin

2016-05-01

For future landings on any celestial body, increasing the lander autonomy as well as decreasing risk are primary objectives. Both risk reduction and an increase in autonomy can be achieved by including hazard detection and avoidance in the guidance, navigation, and control loop. One of the main challenges in hazard detection and avoidance is the reconstruction of accurate elevation models, as well as slope and roughness maps. Multiple methods for acquiring the inputs for hazard maps are available. The main distinction can be made between active and passive methods. Passive methods (cameras) have budgetary advantages compared to active sensors (radar, light detection and ranging). However, it is necessary to proof that these methods deliver sufficiently good maps. Therefore, this paper discusses hazard detection using stereo vision. To facilitate a successful landing not more than 1% wrong detections (hazards that are not identified) are allowed. Based on a sensitivity analysis it was found that using a stereo set-up at a baseline of ≤ 2 m is feasible at altitudes of ≤ 200 m defining false positives of less than 1%. It was thus shown that stereo-based hazard detection is an effective means to decrease the landing risk and increase the lander autonomy. In conclusion, the proposed algorithm is a promising candidate for future landers.

Evaluation of PMS-PCR technology for detection of Mycobacterium avium subsp. paratuberculosis directly from bovine fecal specimens.

PubMed

Salgado, M; Steuer, P; Troncoso, E; Collins, M T

2013-12-27

Mycobacterium avium subsp. paratuberculosis (MAP) causes paratuberculosis, or Johne's disease, in animals. Diagnosis of MAP infection is challenging because of the pathogen's fastidious in vitro growth requirements and low-level intermittent shedding in feces during the preclinical phase of the infection. Detection of these "low-shedders" is important for effective control of paratuberculosis as these animals serve as sources of infection for susceptible calves. Magnetic separation technology, used in combination with culture or molecular methods for the isolation and detection of pathogenic bacteria, enhances the analytical sensitivity and specificity of detection methods. The aim of the present study was to evaluate peptide-mediated magnetic separation (PMS) capture technology coupled with IS900 PCR using the Roche real-time PCR system (PMS-PCR), in comparison with fecal culture using BACTEC-MGIT 960 system, for detection of MAP in bovine fecal samples. Among the 351 fecal samples 74.9% (263/351) were PMS-PCR positive while only 12.3% (43/351) were MGIT culture-positive (p=0.0001). All 43 MGIT culture-positive samples were also positive by PMS-PCR. Mean PMS-PCR crossing-point (Cp) values for the 13 fecal samples with the highest number of MAP, based on time to detection, (26.3) were significantly lower than for the 17 fecal samples with <100 MAP per 2g feces (30.06) (p<0.05). PMS-PCR technology provided results in a shorter time and yielded a higher number of positive results than MGIT culture. Earlier and faster detection of animals shedding MAP by PMS-PCR should significantly strengthen control efforts for MAP-infected cattle herds by helping to limit infection transmission at earlier stages of the infection. Copyright © 2013 Elsevier B.V. All rights reserved.

Road Signs Detection and Recognition Utilizing Images and 3d Point Cloud Acquired by Mobile Mapping System

NASA Astrophysics Data System (ADS)

Li, Y. H.; Shinohara, T.; Satoh, T.; Tachibana, K.

2016-06-01

High-definition and highly accurate road maps are necessary for the realization of automated driving, and road signs are among the most important element in the road map. Therefore, a technique is necessary which can acquire information about all kinds of road signs automatically and efficiently. Due to the continuous technical advancement of Mobile Mapping System (MMS), it has become possible to acquire large number of images and 3d point cloud efficiently with highly precise position information. In this paper, we present an automatic road sign detection and recognition approach utilizing both images and 3D point cloud acquired by MMS. The proposed approach consists of three stages: 1) detection of road signs from images based on their color and shape features using object based image analysis method, 2) filtering out of over detected candidates utilizing size and position information estimated from 3D point cloud, region of candidates and camera information, and 3) road sign recognition using template matching method after shape normalization. The effectiveness of proposed approach was evaluated by testing dataset, acquired from more than 180 km of different types of roads in Japan. The results show a very high success in detection and recognition of road signs, even under the challenging conditions such as discoloration, deformation and in spite of partial occlusions.

Anomaly Detection for Beam Loss Maps in the Large Hadron Collider

NASA Astrophysics Data System (ADS)

Valentino, Gianluca; Bruce, Roderik; Redaelli, Stefano; Rossi, Roberto; Theodoropoulos, Panagiotis; Jaster-Merz, Sonja

2017-07-01

In the LHC, beam loss maps are used to validate collimator settings for cleaning and machine protection. This is done by monitoring the loss distribution in the ring during infrequent controlled loss map campaigns, as well as in standard operation. Due to the complexity of the system, consisting of more than 50 collimators per beam, it is difficult to identify small changes in the collimation hierarchy, which may be due to setting errors or beam orbit drifts with such methods. A technique based on Principal Component Analysis and Local Outlier Factor is presented to detect anomalies in the loss maps and therefore provide an automatic check of the collimation hierarchy.

Application of SEASAT-1 Synthetic Aperture Radar (SAR) data to enhance and detect geological lineaments and to assist LANDSAT landcover classification mapping. [Appalachian Region, West Virginia

NASA Technical Reports Server (NTRS)

Sekhon, R.

1981-01-01

Digital SEASAT-1 synthetic aperture radar (SAR) data were used to enhance linear features to extract geologically significant lineaments in the Appalachian region. Comparison of Lineaments thus mapped with an existing lineament map based on LANDSAT MSS images shows that appropriately processed SEASAT-1 SAR data can significantly improve the detection of lineaments. Merge MSS and SAR data sets were more useful fo lineament detection and landcover classification than LANDSAT or SEASAT data alone. About 20 percent of the lineaments plotted from the SEASAT SAR image did not appear on the LANDSAT image. About 6 percent of minor lineaments or parts of lineaments present in the LANDSAT map were missing from the SEASAT map. Improvement in the landcover classification (acreage and spatial estimation accuracy) was attained by using MSS-SAR merged data. The aerial estimation of residential/built-up and forest categories was improved. Accuracy in estimating the agricultural and water categories was slightly reduced.

Diagnostic Ability of Wide-field Retinal Nerve Fiber Layer Maps Using Swept-Source Optical Coherence Tomography for Detection of Preperimetric and Early Perimetric Glaucoma.

PubMed

Lee, Won June; Na, Kyeong Ik; Kim, Young Kook; Jeoung, Jin Wook; Park, Ki Ho

2017-06-01

To evaluate the diagnostic ability of wide-field retinal nerve fiber layer (RNFL) maps with swept-source optical coherence tomography (SS-OCT) for detection of preperimetric (PPG) and early perimetric glaucoma (EG). One hundred eighty-four eyes, including 67 healthy eyes, 43 eyes with PPG, and 74 eyes with EG, were analyzed. Patients underwent a comprehensive ocular examination including red-free RNFL photography, visual field testing and wide-field SS-OCT scanning (DRI-OCT-1 Atlantis; Topcon, Tokyo, Japan). SS-OCT provides a wide-field RNFL thickness map and a SuperPixel map, which are composed of the RNFL deviation map of the peripapillary area and the deviation map of the composition of the ganglion cell layer with the inner plexiform layer and RNFL (GC-IPL+RNFL) in the macular area. The ability to discriminate PPG and EG from healthy eyes was assessed using sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) for all parameters and criteria provided by the wide-field SS-OCT scan. The wide-field RNFL thickness map using SS-OCT showed the highest sensitivity of PPG-diagnostic and EG-diagnostic performance compared with the other SS-OCT criteria based on the internal normative base (93.0 and 97.3%, respectively). Among the SS-OCT continuous parameters, the RFNL thickness of the 7 clock-hour, inferior and inferotemporal macular ganglion cell analyses showed the largest AUC of PPG-diagnostic and EG-diagnostic performance (AUC=0.809 to 0.865). The wide-field RNFL thickness map using SS-OCT performed well in distinguishing eyes with PPG and EG from healthy eyes. In the clinical setting, wide-field RNFL maps of SS-OCT can be useful tools for detection of early-stage glaucoma.

The energy ratio mapping algorithm: a tool to improve the energy-based detection of odontocete echolocation clicks.

PubMed

Klinck, Holger; Mellinger, David K

2011-04-01

The energy ratio mapping algorithm (ERMA) was developed to improve the performance of energy-based detection of odontocete echolocation clicks, especially for application in environments with limited computational power and energy such as acoustic gliders. ERMA systematically evaluates many frequency bands for energy ratio-based detection of echolocation clicks produced by a target species in the presence of the species mix in a given geographic area. To evaluate the performance of ERMA, a Teager-Kaiser energy operator was applied to the series of energy ratios as derived by ERMA. A noise-adaptive threshold was then applied to the Teager-Kaiser function to identify clicks in data sets. The method was tested for detecting clicks of Blainville's beaked whales while rejecting echolocation clicks of Risso's dolphins and pilot whales. Results showed that the ERMA-based detector correctly identified 81.6% of the beaked whale clicks in an extended evaluation data set. Average false-positive detection rate was 6.3% (3.4% for Risso's dolphins and 2.9% for pilot whales).

Automated Plantation Mapping in Indonesia Using Remote Sensing Data

NASA Astrophysics Data System (ADS)

Karpatne, A.; Jia, X.; Khandelwal, A.; Kumar, V.

2017-12-01

Plantation mapping is critical for understanding and addressing deforestation, a key driver of climate change and ecosystem degradation. Unfortunately, most plantation maps are limited to small areas for specific years because they rely on visual inspection of imagery. In this work, we propose a data-driven approach which automatically generates yearly plantation maps for large regions using MODIS multi-spectral data. While traditional machine learning algorithms face manifold challenges in this task, e.g. imperfect training labels, spatio-temporal data heterogeneity, noisy and high-dimensional data, lack of evaluation data, etc., we introduce a novel deep learning-based framework that combines existing imperfect plantation products as training labels and models the spatio-temporal relationships of land covers. We also explores the post-processing steps based on Hidden Markov Model that further improve the detection accuracy. Then we conduct extensive evaluation of the generated plantation maps. Specifically, by randomly sampling and comparing with high-resolution Digital Globe imagery, we demonstrate that the generated plantation maps achieve both high precision and high recall. When compared with existing plantation mapping products, our detection can avoid both false positives and false negatives. Finally, we utilize the generated plantation maps in analyzing the relationship between forest fires and growth of plantations, which assists in better understanding the cause of deforestation in Indonesia.

Convolutional neural network features based change detection in satellite images

NASA Astrophysics Data System (ADS)

Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

2016-07-01

With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

Web Based Rapid Mapping of Disaster Areas using Satellite Images, Web Processing Service, Web Mapping Service, Frequency Based Change Detection Algorithm and J-iView

NASA Astrophysics Data System (ADS)

Bandibas, J. C.; Takarada, S.

2013-12-01

Timely identification of areas affected by natural disasters is very important for a successful rescue and effective emergency relief efforts. This research focuses on the development of a cost effective and efficient system of identifying areas affected by natural disasters, and the efficient distribution of the information. The developed system is composed of 3 modules which are the Web Processing Service (WPS), Web Map Service (WMS) and the user interface provided by J-iView (fig. 1). WPS is an online system that provides computation, storage and data access services. In this study, the WPS module provides online access of the software implementing the developed frequency based change detection algorithm for the identification of areas affected by natural disasters. It also sends requests to WMS servers to get the remotely sensed data to be used in the computation. WMS is a standard protocol that provides a simple HTTP interface for requesting geo-registered map images from one or more geospatial databases. In this research, the WMS component provides remote access of the satellite images which are used as inputs for land cover change detection. The user interface in this system is provided by J-iView, which is an online mapping system developed at the Geological Survey of Japan (GSJ). The 3 modules are seamlessly integrated into a single package using J-iView, which could rapidly generate a map of disaster areas that is instantaneously viewable online. The developed system was tested using ASTER images covering the areas damaged by the March 11, 2011 tsunami in northeastern Japan. The developed system efficiently generated a map showing areas devastated by the tsunami. Based on the initial results of the study, the developed system proved to be a useful tool for emergency workers to quickly identify areas affected by natural disasters.

Oil Spill Map for Indian Sea Region based on Bhuvan- Geographic Information System using Satellite Images

NASA Astrophysics Data System (ADS)

Vijaya kumar, L. J.; Kishore, J. K.; Kesava Rao, P.; Annadurai, M.; Dutt, C. B. S.; Hanumantha Rao, K.; Sasamal, S. K.; Arulraj, M.; Prasad, A. V. V.; Kumari, E. V. S. Sita; Satyanarayana, S. N.; Shenoy, H. P.

2014-11-01

Oil spills in the ocean are a serious marine disaster that needs regular monitoring for environmental risk assessment and mitigation. Recent use of Polarimetric SAR imagery in near real time oil spill detection systems is associated with attempts towards automatic and unambiguous oil spill detection based on decomposition methods. Such systems integrate remote sensing technology, geo information, communication system, hardware and software systems to provide key information for analysis and decision making. Geographic information systems (GIS) like BHUVAN can significantly contribute to oil spill management based on Synthetic Aperture Radar (SAR) images. India has long coast line from Gujarat to Bengal and hundreds of ports. The increase in shipping also increases the risk of oil spills in our maritime zone. The availability of RISAT-1 SAR images enhances the scope to monitor oil spills and develop GIS on Bhuvan which can be accessed by all the users, such as ships, coast guard, environmentalists etc., The GIS enables realization of oil spill maps based on integration of the geographical, remote sensing, oil & gas production/infrastructure data and slick signatures detected by SAR. SAR and GIS technologies can significantly improve the realization of oil spill footprint distribution maps. Preliminary assessment shows that the Bhuvan promises to be an ideal solution to understand spatial, temporal occurrence of oil spills in the marine atlas of India. The oil spill maps on Bhuvan based GIS facility will help the ONGC and Coast Guard organization.

Cadastral Map Assembling Using Generalized Hough Transformation

NASA Astrophysics Data System (ADS)

Liu, Fei; Ohyama, Wataru; Wakabayashi, Tetsushi; Kimura, Fumitaka

There are numerous cadastral maps generated by the past land surveying. The raster digitization of these paper maps is in progress. For effective and efficient use of these maps, we have to assemble the set of maps to make them superimposable on other geographic information in a GIS. The problem can be seen as a complex jigsaw puzzle where the pieces are the cadastral sections extracted from the map. We present an automatic solution to this geographic jigsaw puzzle, based on the generalized Hough transformation that detects the longest common boundary between every piece and its neighbors. The experiments have been conducted using the map of Mie Prefecture, Japan and the French cadastral map. The results of the experiments with the French cadastral maps showed that the proposed method, which consists of a flood filling procedure of internal area and detection and normalization of the north arrow direction, is suitable for assembling the cadastral map. The final goal of the process is to integrate every piece of the puzzle into a national geographic reference frame and database.

A comparative study evaluating the efficacy of IS_MAP04 with IS900 and IS_MAP02 as a new diagnostic target for the detection of Mycobacterium avium subspecies paratuberculosis from bovine faeces.

PubMed

de Kruijf, Marcel; Govender, Rodney; Yearsley, Dermot; Coffey, Aidan; O'Mahony, Jim

2017-05-01

The aim of this study was to investigate the efficacy of IS_MAP04 as a potential new diagnostic quantitative PCR (qPCR) target for the detection of Mycobacterium avium subspecies paratuberculosis from bovine faeces. IS_MAP04 primers were designed and tested negative against non-MAP strains. The detection limit of IS_MAP04 qPCR was evaluated on different MAP K-10 DNA concentrations and on faecal samples spiked with different MAP K-10 cell dilutions. A collection of 106 faecal samples was analysed and the efficacy of IS_MAP04 was statistically compared with IS900 and IS_MAP02. The detection limits observed for IS_MAP04 and IS900 on MAP DNA was 34 fg and 3.4 fg respectively. The detection limit of MAP from inoculated faecal samples was 10 2 CFU/g for both IS_MAP04 and IS900 targets and a detection limit of 10 2 CFU/g was also achieved with a TaqMan qPCR targeting IS_MAP04. The efficacy of IS_MAP04 to detect positive MAP faecal samples was 83.0% compared to 85.8% and 83.9% for IS900 and IS_MAP02 respectively. Strong kappa agreements were observed between IS_MAP04 and IS900 (κ=0.892) and between IS_MAP04 and IS_MAP02 (κ=0.897). As a new molecular target, IS_MAP04 showed that the detection limit was comparable to IS900 to detect MAP from inoculated faecal material. The MAP detection efficacy of IS_MAP04 from naturally infected faecal samples proved to be relatively comparable to IS_MAP02, but yielded efficacy results slightly less than IS900. Moreover, IS_MAP04 could be of significant value when used in duplex or multiplex qPCR assays. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparative Genomics Analyses Reveal Extensive Chromosome Colinearity and Novel Quantitative Trait Loci in Eucalyptus.

PubMed

Li, Fagen; Zhou, Changpin; Weng, Qijie; Li, Mei; Yu, Xiaoli; Guo, Yong; Wang, Yu; Zhang, Xiaohong; Gan, Siming

2015-01-01

Dense genetic maps, along with quantitative trait loci (QTLs) detected on such maps, are powerful tools for genomics and molecular breeding studies. In the important woody genus Eucalyptus, the recent release of E. grandis genome sequence allows for sequence-based genomic comparison and searching for positional candidate genes within QTL regions. Here, dense genetic maps were constructed for E. urophylla and E. tereticornis using genomic simple sequence repeats (SSR), expressed sequence tag (EST) derived SSR, EST-derived cleaved amplified polymorphic sequence (EST-CAPS), and diversity arrays technology (DArT) markers. The E. urophylla and E. tereticornis maps comprised 700 and 585 markers across 11 linkage groups, totaling at 1,208.2 and 1,241.4 cM in length, respectively. Extensive synteny and colinearity were observed as compared to three earlier DArT-based eucalypt maps (two maps with E. grandis × E. urophylla and one map of E. globulus) and with the E. grandis genome sequence. Fifty-three QTLs for growth (10-56 months of age) and wood density (56 months) were identified in 22 discrete regions on both maps, in which only one colocalizaiton was found between growth and wood density. Novel QTLs were revealed as compared with those previously detected on DArT-based maps for similar ages in Eucalyptus. Eleven to 585 positional candidate genes were obained for a 56-month-old QTL through aligning QTL confidence interval with the E. grandis genome. These results will assist in comparative genomics studies, targeted gene characterization, and marker-assisted selection in Eucalyptus and the related taxa.

Comparative Genomics Analyses Reveal Extensive Chromosome Colinearity and Novel Quantitative Trait Loci in Eucalyptus

PubMed Central

Weng, Qijie; Li, Mei; Yu, Xiaoli; Guo, Yong; Wang, Yu; Zhang, Xiaohong; Gan, Siming

2015-01-01

Dense genetic maps, along with quantitative trait loci (QTLs) detected on such maps, are powerful tools for genomics and molecular breeding studies. In the important woody genus Eucalyptus, the recent release of E. grandis genome sequence allows for sequence-based genomic comparison and searching for positional candidate genes within QTL regions. Here, dense genetic maps were constructed for E. urophylla and E. tereticornis using genomic simple sequence repeats (SSR), expressed sequence tag (EST) derived SSR, EST-derived cleaved amplified polymorphic sequence (EST-CAPS), and diversity arrays technology (DArT) markers. The E. urophylla and E. tereticornis maps comprised 700 and 585 markers across 11 linkage groups, totaling at 1,208.2 and 1,241.4 cM in length, respectively. Extensive synteny and colinearity were observed as compared to three earlier DArT-based eucalypt maps (two maps with E. grandis × E. urophylla and one map of E. globulus) and with the E. grandis genome sequence. Fifty-three QTLs for growth (10–56 months of age) and wood density (56 months) were identified in 22 discrete regions on both maps, in which only one colocalizaiton was found between growth and wood density. Novel QTLs were revealed as compared with those previously detected on DArT-based maps for similar ages in Eucalyptus. Eleven to 585 positional candidate genes were obained for a 56-month-old QTL through aligning QTL confidence interval with the E. grandis genome. These results will assist in comparative genomics studies, targeted gene characterization, and marker-assisted selection in Eucalyptus and the related taxa. PMID:26695430

Detection of Thermal Erosion Gullies from High-Resolution Images Using Deep Learning

NASA Astrophysics Data System (ADS)

Huang, L.; Liu, L.; Jiang, L.; Zhang, T.; Sun, Y.

2017-12-01

Thermal erosion gullies, one type of thermokarst landforms, develop due to thawing of ice-rich permafrost. Mapping the location and extent of thermal erosion gullies can help understand the spatial distribution of thermokarst landforms and their temporal evolution. Remote sensing images provide an effective way for mapping thermokarst landforms, especially thermokarst lakes. However, thermal erosion gullies are challenging to map from remote sensing images due to their small sizes and significant variations in geometric/radiometric properties. It is feasible to manually identify these features, as a few previous studies have carried out. However manual methods are labor-intensive, therefore, cannot be used for a large study area. In this work, we conduct automatic mapping of thermal erosion gullies from high-resolution images by using Deep Learning. Our study area is located in Eboling Mountain (Qinghai, China). Within a 6 km2 peatland area underlain by ice-rich permafrost, at least 20 thermal erosional gullies are well developed. The image used is a 15-cm-resolution Digital Orthophoto Map (DOM) generated in July 2016. First, we extracted 14 gully patches and ten non-gully patches as training data. And we performed image augmentation. Next, we fine-tuned the pre-trained model of DeepLab, a deep-learning algorithm for semantic image segmentation based on Deep Convolutional Neural Networks. Then, we performed inference on the whole DOM and obtained intermediate results in forms of polygons for all identified gullies. At last, we removed misidentified polygons based on a few pre-set criteria on the size and shape of each polygon. Our final results include 42 polygons. Validated against field measurements using GPS, most of the gullies are detected correctly. There are 20 false detections due to the small number and low quality of training images. We also found three new gullies that missed in the field observations. This study shows that (1) despite a challenging mapping task, DeepLab can detect small, irregular-shaped thermal erosion gullies with high accuracy. (2) Automatic detection is critical for mapping thermal erosion gully since manual mapping or field work may miss some targets even in a relatively small region. (3) The quantity and quality of training data are crucial for detection accuracy.

Ladar imaging detection of salient map based on PWVD and Rényi entropy

NASA Astrophysics Data System (ADS)

Xu, Yuannan; Zhao, Yuan; Deng, Rong; Dong, Yanbing

2013-10-01

Spatial-frequency information of a given image can be extracted by associating the grey-level spatial data with one of the well-known spatial/spatial-frequency distributions. The Wigner-Ville distribution (WVD) has a good characteristic that the images can be represented in spatial/spatial-frequency domains. For intensity and range images of ladar, through the pseudo Wigner-Ville distribution (PWVD) using one or two dimension window, the statistical property of Rényi entropy is studied. We also analyzed the change of Rényi entropy's statistical property in the ladar intensity and range images when the man-made objects appear. From this foundation, a novel method for generating saliency map based on PWVD and Rényi entropy is proposed. After that, target detection is completed when the saliency map is segmented using a simple and convenient threshold method. For the ladar intensity and range images, experimental results show the proposed method can effectively detect the military vehicles from complex earth background with low false alarm.

Identification of sero-reactive antigens for the early diagnosis of Johne’s disease in cattle

PubMed Central

Randall, Arlo; Grohn, Yrjo T.; Katani, Robab; Schilling, Megan; Radzio-Basu, Jessica

2017-01-01

Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of Johne’s disease (JD), a chronic intestinal inflammatory disease of cattle and other ruminants. JD has a high herd prevalence and causes serious animal health problems and significant economic loss in domesticated ruminants throughout the world. Since serological detection of MAP infected animals during the early stages of infection remains challenging due to the low sensitivity of extant assays, we screened 180 well-characterized serum samples using a whole proteome microarray from Mycobacterium tuberculosis (MTB), a close relative of MAP. Based on extensive testing of serum and milk samples, fecal culture and qPCR for direct detection of MAP, the samples were previously assigned to one of 4 groups: negative low exposure (n = 30, NL); negative high exposure (n = 30, NH); fecal positive, ELISA negative (n = 60, F+E-); and fecal positive, ELISA positive (n = 60, F+E+). Of the 740 reactive proteins, several antigens were serologically recognized early but not late in infection, suggesting a complex and dynamic evolution of the MAP humoral immune response during disease progression. Ordinal logistic regression models identified a subset of 47 candidate proteins with significantly different normalized intensity values (p<0.05), including 12 in the NH and 23 in F+E- groups, suggesting potential utility for the early detection of MAP infected animals. Next, the diagnostic utility of four MAP orthologs (MAP1569, MAP2942c, MAP2609, and MAP1272c) was assessed and reveal moderate to high diagnostic sensitivities (range 48.3% to 76.7%) and specificity (range 96.7% to 100%), with a combined 88.3% sensitivity and 96.7% specificity. Taken together, the results of our analyses have identified several candidate MAP proteins of potential utility for the early detection of MAP infection, as well individual MAP proteins that may serve as the foundation for the next generation of well-defined serological diagnosis of JD in cattle. PMID:28863177

MO-FG-CAMPUS-TeP1-03: Pre-Treatment Surface Imaging Based Collision Detection

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

Wiant, D; Maurer, J; Liu, H

2016-06-15

Purpose: Modern radiotherapy increasingly employs large immobilization devices, gantry attachments, and couch rotations for treatments. All of which raise the risk of collisions between the patient and the gantry / couch. Collision detection is often achieved by manually checking each couch position in the treatment room and sometimes results in extraneous imaging if collisions are detected after image based setup has begun. In the interest of improving efficiency and avoiding extra imaging, we explore the use of a surface imaging based collision detection model. Methods: Surfaces acquired from AlignRT (VisionRT, London, UK) were transferred in wavefront format to a custommore » Matlab (Mathworks, Natick, MA) software package (CCHECK). Computed tomography (CT) scans acquired at the same time were sent to CCHECK in DICOM format. In CCHECK, binary maps of the surfaces were created and overlaid on the CT images based on the fixed relationship of the AlignRT and CT coordinate systems. Isocenters were added through a graphical user interface (GUI). CCHECK then compares the inputted surfaces to a model of the linear accelerator (linac) to check for collisions at defined gantry and couch positions. Note, CCHECK may be used with or without a CT. Results: The nominal surface image field of view is 650 mm × 900 mm, with variance based on patient position and size. The accuracy of collision detections is primarily based on the linac model and the surface mapping process. The current linac model and mapping process yield detection accuracies on the order of 5 mm, assuming no change in patient posture between surface acquisition and treatment. Conclusions: CCHECK provides a non-ionizing method to check for collisions without the patient in the treatment room. Collision detection accuracy may be improved with more robust linac modeling. Additional gantry attachments (e.g. conical collimators) can be easily added to the model.« less

Temporal similarity perfusion mapping: A standardized and model-free method for detecting perfusion deficits in stroke

PubMed Central

Song, Sunbin; Luby, Marie; Edwardson, Matthew A.; Brown, Tyler; Shah, Shreyansh; Cox, Robert W.; Saad, Ziad S.; Reynolds, Richard C.; Glen, Daniel R.; Cohen, Leonardo G.; Latour, Lawrence L.

2017-01-01

Introduction Interpretation of the extent of perfusion deficits in stroke MRI is highly dependent on the method used for analyzing the perfusion-weighted signal intensity time-series after gadolinium injection. In this study, we introduce a new model-free standardized method of temporal similarity perfusion (TSP) mapping for perfusion deficit detection and test its ability and reliability in acute ischemia. Materials and methods Forty patients with an ischemic stroke or transient ischemic attack were included. Two blinded readers compared real-time generated interactive maps and automatically generated TSP maps to traditional TTP/MTT maps for presence of perfusion deficits. Lesion volumes were compared for volumetric inter-rater reliability, spatial concordance between perfusion deficits and healthy tissue and contrast-to-noise ratio (CNR). Results Perfusion deficits were correctly detected in all patients with acute ischemia. Inter-rater reliability was higher for TSP when compared to TTP/MTT maps and there was a high similarity between the lesion volumes depicted on TSP and TTP/MTT (r(18) = 0.73). The Pearson's correlation between lesions calculated on TSP and traditional maps was high (r(18) = 0.73, p<0.0003), however the effective CNR was greater for TSP compared to TTP (352.3 vs 283.5, t(19) = 2.6, p<0.03.) and MTT (228.3, t(19) = 2.8, p<0.03). Discussion TSP maps provide a reliable and robust model-free method for accurate perfusion deficit detection and improve lesion delineation compared to traditional methods. This simple method is also computationally faster and more easily automated than model-based methods. This method can potentially improve the speed and accuracy in perfusion deficit detection for acute stroke treatment and clinical trial inclusion decision-making. PMID:28973000

Auditory Evidence Grids

DTIC Science & Technology

2006-01-01

information of the robot (Figure 1) acquired via laser-based localization techniques. The results are maps of the global soundscape . The algorithmic...environments than noise maps. Furthermore, provided the acoustic localization algorithm can detect the sources, the soundscape can be mapped with many...gathering information about the auditory soundscape in which it is working. In addition to robustness in the presence of noise, it has also been

A numerical study of defect detection in a plaster dome ceiling using structural acoustics.

PubMed

Bucaro, J A; Romano, A J; Valdivia, N; Houston, B H; Dey, S

2009-07-01

A numerical study is carried out to evaluate the effectiveness of using measured surface displacements resulting from acoustic speaker excitation to detect and localize flaws in a domed, plaster ceiling. The response of the structure to an incident acoustic pressure is obtained at four frequencies between 100 and 400 Hz using a parallel h-p structural acoustic finite element-based code. Three ceiling conditions are modeled: the pristine ceiling considered rigidly attached to the domed-shape support, partial detachment of a segment of the plaster layer from the support, and an interior pocket of plaster deconsolidation modeled as a heavy fluid. Spatial maps of the normal displacement resulting from speaker excitation are interpreted with the help of predictions based on static analysis. It is found that acoustic speaker excitation can provide displacement levels readily detected by commercially available laser Doppler vibrometer systems. Further, it is concluded that for 1 in. thick plaster layers, detachment sizes as small as 4 cm are detectable by direct observation of the measured displacement maps. Finally, spatial structure differences are observed in the displacement maps beneath the two defect types, which may provide a wavenumber-based feature useful for distinguishing plaster detachment from other defects such as deconsolidation.

A complete solution of cartographic displacement based on elastic beams model and Delaunay triangulation

NASA Astrophysics Data System (ADS)

Liu, Y.; Guo, Q.; Sun, Y.

2014-04-01

In map production and generalization, it is inevitable to arise some spatial conflicts, but the detection and resolution of these spatial conflicts still requires manual operation. It is become a bottleneck hindering the development of automated cartographic generalization. Displacement is the most useful contextual operator that is often used for resolving the conflicts arising between two or more map objects. Automated generalization researches have reported many approaches of displacement including sequential approaches and optimization approaches. As an excellent optimization approach on the basis of energy minimization principles, elastic beams model has been used in resolving displacement problem of roads and buildings for several times. However, to realize a complete displacement solution, techniques of conflict detection and spatial context analysis should be also take into consideration. So we proposed a complete solution of displacement based on the combined use of elastic beams model and constrained Delaunay triangulation (CDT) in this paper. The solution designed as a cyclic and iterative process containing two phases: detection phase and displacement phase. In detection phase, CDT of map is use to detect proximity conflicts, identify spatial relationships and structures, and construct auxiliary structure, so as to support the displacement phase on the basis of elastic beams. In addition, for the improvements of displacement algorithm, a method for adaptive parameters setting and a new iterative strategy are put forward. Finally, we implemented our solution on a testing map generalization platform, and successfully tested it against 2 hand-generated test datasets of roads and buildings respectively.

Regional snow-avalanche detection using object-based image analysis of near-infrared aerial imagery

NASA Astrophysics Data System (ADS)

Korzeniowska, Karolina; Bühler, Yves; Marty, Mauro; Korup, Oliver

2017-10-01

Snow avalanches are destructive mass movements in mountain regions that continue to claim lives and cause infrastructural damage and traffic detours. Given that avalanches often occur in remote and poorly accessible steep terrain, their detection and mapping is extensive and time consuming. Nonetheless, systematic avalanche detection over large areas could help to generate more complete and up-to-date inventories (cadastres) necessary for validating avalanche forecasting and hazard mapping. In this study, we focused on automatically detecting avalanches and classifying them into release zones, tracks, and run-out zones based on 0.25 m near-infrared (NIR) ADS80-SH92 aerial imagery using an object-based image analysis (OBIA) approach. Our algorithm takes into account the brightness, the normalised difference vegetation index (NDVI), the normalised difference water index (NDWI), and its standard deviation (SDNDWI) to distinguish avalanches from other land-surface elements. Using normalised parameters allows applying this method across large areas. We trained the method by analysing the properties of snow avalanches at three 4 km-2 areas near Davos, Switzerland. We compared the results with manually mapped avalanche polygons and obtained a user's accuracy of > 0.9 and a Cohen's kappa of 0.79-0.85. Testing the method for a larger area of 226.3 km-2, we estimated producer's and user's accuracies of 0.61 and 0.78, respectively, with a Cohen's kappa of 0.67. Detected avalanches that overlapped with reference data by > 80 % occurred randomly throughout the testing area, showing that our method avoids overfitting. Our method has potential for large-scale avalanche mapping, although further investigations into other regions are desirable to verify the robustness of our selected thresholds and the transferability of the method.

Pearl millet [Pennisetum glaucum (L.) R. Br.] consensus linkage map constructed using four RIL mapping populations and newly developed EST-SSRs.

PubMed

Rajaram, Vengaldas; Nepolean, Thirunavukkarasu; Senthilvel, Senapathy; Varshney, Rajeev K; Vadez, Vincent; Srivastava, Rakesh K; Shah, Trushar M; Supriya, Ambawat; Kumar, Sushil; Ramana Kumari, Basava; Bhanuprakash, Amindala; Narasu, Mangamoori Lakshmi; Riera-Lizarazu, Oscar; Hash, Charles Thomas

2013-03-09

Pearl millet [Pennisetum glaucum (L.) R. Br.] is a widely cultivated drought- and high-temperature tolerant C4 cereal grown under dryland, rainfed and irrigated conditions in drought-prone regions of the tropics and sub-tropics of Africa, South Asia and the Americas. It is considered an orphan crop with relatively few genomic and genetic resources. This study was undertaken to increase the EST-based microsatellite marker and genetic resources for this crop to facilitate marker-assisted breeding. Newly developed EST-SSR markers (99), along with previously mapped EST-SSR (17), genomic SSR (53) and STS (2) markers, were used to construct linkage maps of four F7 recombinant inbred populations (RIP) based on crosses ICMB 841-P3 × 863B-P2 (RIP A), H 77/833-2 × PRLT 2/89-33 (RIP B), 81B-P6 × ICMP 451-P8 (RIP C) and PT 732B-P2 × P1449-2-P1 (RIP D). Mapped loci numbers were greatest for RIP A (104), followed by RIP B (78), RIP C (64) and RIP D (59). Total map lengths (Haldane) were 615 cM, 690 cM, 428 cM and 276 cM, respectively. A total of 176 loci detected by 171 primer pairs were mapped among the four crosses. A consensus map of 174 loci (899 cM) detected by 169 primer pairs was constructed using MergeMap to integrate the individual linkage maps. Locus order in the consensus map was well conserved for nearly all linkage groups. Eighty-nine EST-SSR marker loci from this consensus map had significant BLAST hits (top hits with e-value ≤ 1E-10) on the genome sequences of rice, foxtail millet, sorghum, maize and Brachypodium with 35, 88, 58, 48 and 38 loci, respectively. The consensus map developed in the present study contains the largest set of mapped SSRs reported to date for pearl millet, and represents a major consolidation of existing pearl millet genetic mapping information. This study increased numbers of mapped pearl millet SSR markers by >50%, filling important gaps in previously published SSR-based linkage maps for this species and will greatly facilitate SSR-based QTL mapping and applied marker-assisted selection programs.

Intensity and Compactness Enabled Saliency Estimation for Leakage Detection in Diabetic and Malarial Retinopathy.

PubMed

Zhao, Yitian; Zheng, Yalin; Liu, Yonghuai; Yang, Jian; Zhao, Yifan; Chen, Duanduan; Wang, Yongtian

2017-01-01

Leakage in retinal angiography currently is a key feature for confirming the activities of lesions in the management of a wide range of retinal diseases, such as diabetic maculopathy and paediatric malarial retinopathy. This paper proposes a new saliency-based method for the detection of leakage in fluorescein angiography. A superpixel approach is firstly employed to divide the image into meaningful patches (or superpixels) at different levels. Two saliency cues, intensity and compactness, are then proposed for the estimation of the saliency map of each individual superpixel at each level. The saliency maps at different levels over the same cues are fused using an averaging operator. The two saliency maps over different cues are fused using a pixel-wise multiplication operator. Leaking regions are finally detected by thresholding the saliency map followed by a graph-cut segmentation. The proposed method has been validated using the only two publicly available datasets: one for malarial retinopathy and the other for diabetic retinopathy. The experimental results show that it outperforms one of the latest competitors and performs as well as a human expert for leakage detection and outperforms several state-of-the-art methods for saliency detection.

Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining.

PubMed

Tang, Tianyu; Zhou, Shilin; Deng, Zhipeng; Zou, Huanxin; Lei, Lin

2017-02-10

Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well. In this study, an improved detection method based on Faster R-CNN is proposed in order to accomplish the two challenges mentioned above. Firstly, to improve the recall, we employ a hyper region proposal network (HRPN) to extract vehicle-like targets with a combination of hierarchical feature maps. Then, we replace the classifier after RPN by a cascade of boosted classifiers to verify the candidate regions, aiming at reducing false detection by negative example mining. We evaluate our method on the Munich vehicle dataset and the collected vehicle dataset, with improvements in accuracy and robustness compared to existing methods.

Development of cleaved amplified polymorphic sequence markers and a CAPS-based genetic linkage map in watermelon (Citrullus lanatus [Thunb.] Matsum. and Nakai) constructed using whole-genome re-sequencing data

PubMed Central

Liu, Shi; Gao, Peng; Zhu, Qianglong; Luan, Feishi; Davis, Angela R.; Wang, Xiaolu

2016-01-01

Cleaved amplified polymorphic sequence (CAPS) markers are useful tools for detecting single nucleotide polymorphisms (SNPs). This study detected and converted SNP sites into CAPS markers based on high-throughput re-sequencing data in watermelon, for linkage map construction and quantitative trait locus (QTL) analysis. Two inbred lines, Cream of Saskatchewan (COS) and LSW-177 had been re-sequenced and analyzed by Perl self-compiled script for CAPS marker development. 88.7% and 78.5% of the assembled sequences of the two parental materials could map to the reference watermelon genome, respectively. Comparative assembled genome data analysis provided 225,693 and 19,268 SNPs and indels between the two materials. 532 pairs of CAPS markers were designed with 16 restriction enzymes, among which 271 pairs of primers gave distinct bands of the expected length and polymorphic bands, via PCR and enzyme digestion, with a polymorphic rate of 50.94%. Using the new CAPS markers, an initial CAPS-based genetic linkage map was constructed with the F2 population, spanning 1836.51 cM with 11 linkage groups and 301 markers. 12 QTLs were detected related to fruit flesh color, length, width, shape index, and brix content. These newly CAPS markers will be a valuable resource for breeding programs and genetic studies of watermelon. PMID:27162496

Exploiting Surroundedness for Saliency Detection: A Boolean Map Approach.

PubMed

Zhang, Jianming; Sclaroff, Stan

2016-05-01

We demonstrate the usefulness of surroundedness for eye fixation prediction by proposing a Boolean Map based Saliency model (BMS). In our formulation, an image is characterized by a set of binary images, which are generated by randomly thresholding the image's feature maps in a whitened feature space. Based on a Gestalt principle of figure-ground segregation, BMS computes a saliency map by discovering surrounded regions via topological analysis of Boolean maps. Furthermore, we draw a connection between BMS and the Minimum Barrier Distance to provide insight into why and how BMS can properly captures the surroundedness cue via Boolean maps. The strength of BMS is verified by its simplicity, efficiency and superior performance compared with 10 state-of-the-art methods on seven eye tracking benchmark datasets.

Mapped DNA probes from Ioblolly pine can be used for restriction fragment length polymorphism mapping in other conifers

Treesearch

M.R. Ahuja; M.E. Devey; A.T. Groover; K.D. Jermstad; D.B Neale

1994-01-01

A high-density genetic map based on restriction fragment length polymorphisms (RFLPs) is being constructed for loblolly pine (Pinus taeda L.). Consequently, a large number of DNA probes from loblolly pine are potentially available for use in other species. We have used some of these DNA probes to detect RFLPs in 12 conifers and an angiosperm....

Rapid geodesic mapping of brain functional connectivity: implementation of a dedicated co-processor in a field-programmable gate array (FPGA) and application to resting state functional MRI.

PubMed

Minati, Ludovico; Cercignani, Mara; Chan, Dennis

2013-10-01

Graph theory-based analyses of brain network topology can be used to model the spatiotemporal correlations in neural activity detected through fMRI, and such approaches have wide-ranging potential, from detection of alterations in preclinical Alzheimer's disease through to command identification in brain-machine interfaces. However, due to prohibitive computational costs, graph-based analyses to date have principally focused on measuring connection density rather than mapping the topological architecture in full by exhaustive shortest-path determination. This paper outlines a solution to this problem through parallel implementation of Dijkstra's algorithm in programmable logic. The processor design is optimized for large, sparse graphs and provided in full as synthesizable VHDL code. An acceleration factor between 15 and 18 is obtained on a representative resting-state fMRI dataset, and maps of Euclidean path length reveal the anticipated heterogeneous cortical involvement in long-range integrative processing. These results enable high-resolution geodesic connectivity mapping for resting-state fMRI in patient populations and real-time geodesic mapping to support identification of imagined actions for fMRI-based brain-machine interfaces. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Development of a biomimetic enzyme-linked immunosorbent assay based on molecularly imprinted polymers on paper for the detection of carbaryl.

PubMed

Zhang, Can; Cui, Hanyu; Han, Yufeng; Yu, Fangfang; Shi, Xiaoman

2018-02-01

A biomimetic enzyme-linked immunosorbent assay (BELISA) which was based on molecularly imprinted polymers on paper (MIPs-paper) with specific recognition was developed. As a detector, the surface of paper was modified with γ-MAPS by hydrolytic action and anchored the MIP layer on γ-MAPS modified-paper by copolymerization to construct the artificial antibody Through a series of experimentation and verification, we successful got the MIPs-paper and established BELISA for the detection of carbaryl. The development of MIPs-paper based on BELISA was applied to detect carbaryl in real samples and validated by an enzyme-linked immunosorbent assay (ELISA) based on anti-carbaryl biological antibody. The results of these two methods (BELISA and ELISA) were well correlated (R 2 =0.944). The established method of MIPs-paper BELISA exhibits the advantages of low cost, higher stability and being re-generable, which can be applied as a convenient tool for the fast and efficient detection of carbaryl. Copyright © 2017. Published by Elsevier Ltd.

An Investigation of Automatic Change Detection for Topographic Map Updating

NASA Astrophysics Data System (ADS)

Duncan, P.; Smit, J.

2012-08-01

Changes to the landscape are constantly occurring and it is essential for geospatial and mapping organisations that these changes are regularly detected and captured, so that map databases can be updated to reflect the current status of the landscape. The Chief Directorate of National Geospatial Information (CD: NGI), South Africa's national mapping agency, currently relies on manual methods of detecting changes and capturing these changes. These manual methods are time consuming and labour intensive, and rely on the skills and interpretation of the operator. It is therefore necessary to move towards more automated methods in the production process at CD: NGI. The aim of this research is to do an investigation into a methodology for automatic or semi-automatic change detection for the purpose of updating topographic databases. The method investigated for detecting changes is through image classification as well as spatial analysis and is focussed on urban landscapes. The major data input into this study is high resolution aerial imagery and existing topographic vector data. Initial results indicate the traditional pixel-based image classification approaches are unsatisfactory for large scale land-use mapping and that object-orientated approaches hold more promise. Even in the instance of object-oriented image classification generalization of techniques on a broad-scale has provided inconsistent results. A solution may lie with a hybrid approach of pixel and object-oriented techniques.

Artificial-epitope mapping for CK-MB assay.

PubMed

Tai, Dar-Fu; Ho, Yi-Fang; Wu, Cheng-Hsin; Lin, Tzu-Chieh; Lu, Kuo-Hao; Lin, Kun-Shian

2011-06-07

A quantitative method using artificial antibody to detect creatine kinases was developed. Linear epitope sequences were selected based on an artificial-epitope mapping strategy. Nine different MIPs corresponding to the selected peptides were then fabricated on QCM chips. The subtle conformational changes were also recognized by these chips.

Where Boron? Mars Rover Detects It

NASA Image and Video Library

2016-12-13

This map shows the route driven by NASA's Curiosity Mars rover (blue line) and locations where the rover's Chemistry and Camera (ChemCam) instrument detected the element boron (dots, colored by abundance of boron according to the key at right). The main map shows the traverse from landing day (Sol 0) in August 2012 to the rover's location in September 2016, with boron detections through September 2015. The inset at upper left shows a magnified version of the most recent portion of that traverse, with boron detections during that portion. Overlapping dots represent cases when boron was detected in multiple ChemCam observation points in the same target and non-overlapping dots represent cases where two different targets in the same location have boron. Most of the mission's detections of boron have been made in the most recent seven months (about 200 sols) of the rover's uphill traverse. The base image for the map is from the High Resolution Imaging Science Experiment (HiRISE) camera on NASA's Mars Reconnaissance Orbiter. North is up. The scale bar at lower right represents one kilometer (0.62 mile). http://photojournal.jpl.nasa.gov/catalog/PIA21150

Single strand conformation polymorphism based SNP and Indel markers for genetic mapping and synteny analysis of common bean (Phaseolus vulgaris L.)

PubMed Central

2009-01-01

Background Expressed sequence tags (ESTs) are an important source of gene-based markers such as those based on insertion-deletions (Indels) or single-nucleotide polymorphisms (SNPs). Several gel based methods have been reported for the detection of sequence variants, however they have not been widely exploited in common bean, an important legume crop of the developing world. The objectives of this project were to develop and map EST based markers using analysis of single strand conformation polymorphisms (SSCPs), to create a transcript map for common bean and to compare synteny of the common bean map with sequenced chromosomes of other legumes. Results A set of 418 EST based amplicons were evaluated for parental polymorphisms using the SSCP technique and 26% of these presented a clear conformational or size polymorphism between Andean and Mesoamerican genotypes. The amplicon based markers were then used for genetic mapping with segregation analysis performed in the DOR364 × G19833 recombinant inbred line (RIL) population. A total of 118 new marker loci were placed into an integrated molecular map for common bean consisting of 288 markers. Of these, 218 were used for synteny analysis and 186 presented homology with segments of the soybean genome with an e-value lower than 7 × 10-12. The synteny analysis with soybean showed a mosaic pattern of syntenic blocks with most segments of any one common bean linkage group associated with two soybean chromosomes. The analysis with Medicago truncatula and Lotus japonicus presented fewer syntenic regions consistent with the more distant phylogenetic relationship between the galegoid and phaseoloid legumes. Conclusion The SSCP technique is a useful and inexpensive alternative to other SNP or Indel detection techniques for saturating the common bean genetic map with functional markers that may be useful in marker assisted selection. In addition, the genetic markers based on ESTs allowed the construction of a transcript map and given their high conservation between species allowed synteny comparisons to be made to sequenced genomes. This synteny analysis may support positional cloning of target genes in common bean through the use of genomic information from these other legumes. PMID:20030833

Method and apparatus for in-situ detection and isolation of aircraft engine faults

NASA Technical Reports Server (NTRS)

Bonanni, Pierino Gianni (Inventor); Brunell, Brent Jerome (Inventor)

2007-01-01

A method for performing a fault estimation based on residuals of detected signals includes determining an operating regime based on a plurality of parameters, extracting predetermined noise standard deviations of the residuals corresponding to the operating regime and scaling the residuals, calculating a magnitude of a measurement vector of the scaled residuals and comparing the magnitude to a decision threshold value, extracting an average, or mean direction and a fault level mapping for each of a plurality of fault types, based on the operating regime, calculating a projection of the measurement vector onto the average direction of each of the plurality of fault types, determining a fault type based on which projection is maximum, and mapping the projection to a continuous-valued fault level using a lookup table.

Potential mapping with charged-particle beams

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Impact of SZ cluster residuals in CMB maps and CMB-LSS cross-correlations

NASA Astrophysics Data System (ADS)

Chen, T.; Remazeilles, M.; Dickinson, C.

2018-06-01

Residual foreground contamination in cosmic microwave background (CMB) maps, such as the residual contamination from thermal Sunyaev-Zeldovich (SZ) effect in the direction of galaxy clusters, can bias the cross-correlation measurements between CMB and large-scale structure optical surveys. It is thus essential to quantify those residuals and, if possible, to null out SZ cluster residuals in CMB maps. We quantify for the first time the amount of SZ cluster contamination in the released Planck 2015 CMB maps through (i) the stacking of CMB maps in the direction of the clusters, and (ii) the computation of cross-correlation power spectra between CMB maps and the SDSS-IV large-scale structure data. Our cross-power spectrum analysis yields a 30σ detection at the cluster scale (ℓ = 1500-2500) and a 39σ detection on larger scales (ℓ = 500-1500) due to clustering of SZ clusters, giving an overall 54σ detection of SZ cluster residuals in the Planck CMB maps. The Planck 2015 NILC CMB map is shown to have 44 ± 4% of thermal SZ foreground emission left in it. Using the 'Constrained ILC' component separation technique, we construct an alternative Planck CMB map, the 2D-ILC map, which is shown to have negligible SZ contamination, at the cost of being slightly more contaminated by Galactic foregrounds and noise. We also discuss the impact of the SZ residuals in CMB maps on the measurement of the ISW effect, which is shown to be negligible based on our analysis.

Efficient, Validated Method for Detection of Mycobacterial Growth in Liquid Culture Media by Use of Bead Beating, Magnetic-Particle-Based Nucleic Acid Isolation, and Quantitative PCR

PubMed Central

Waldron, Anna M.; Begg, Douglas J.; de Silva, Kumudika; Purdie, Auriol C.; Whittington, Richard J.

2015-01-01

Pathogenic mycobacteria are difficult to culture, requiring specialized media and a long incubation time, and have complex and exceedingly robust cell walls. Mycobacterium avium subsp. paratuberculosis (MAP), the causative agent of Johne's disease, a chronic wasting disease of ruminants, is a typical example. Culture of MAP from the feces and intestinal tissues is a commonly used test for confirmation of infection. Liquid medium offers greater sensitivity than solid medium for detection of MAP; however, support for the BD Bactec 460 system commonly used for this purpose has been discontinued. We previously developed a new liquid culture medium, M7H9C, to replace it, with confirmation of growth reliant on PCR. Here, we report an efficient DNA isolation and quantitative PCR methodology for the specific detection and confirmation of MAP growth in liquid culture media containing egg yolk. The analytical sensitivity was at least 104-fold higher than a commonly used method involving ethanol precipitation of DNA and conventional PCR; this may be partly due to the addition of a bead-beating step to manually disrupt the cell wall of the mycobacteria. The limit of detection, determined using pure cultures of two different MAP strains, was 100 to 1,000 MAP organisms/ml. The diagnostic accuracy was confirmed using a panel of cattle fecal (n = 54) and sheep fecal and tissue (n = 90) culture samples. This technique is directly relevant for diagnostic laboratories that perform MAP cultures but may also be applicable to the detection of other species, including M. avium and M. tuberculosis. PMID:25609725

Efficient, validated method for detection of mycobacterial growth in liquid culture media by use of bead beating, magnetic-particle-based nucleic acid isolation, and quantitative PCR.

PubMed

Plain, Karren M; Waldron, Anna M; Begg, Douglas J; de Silva, Kumudika; Purdie, Auriol C; Whittington, Richard J

2015-04-01

Pathogenic mycobacteria are difficult to culture, requiring specialized media and a long incubation time, and have complex and exceedingly robust cell walls. Mycobacterium avium subsp. paratuberculosis (MAP), the causative agent of Johne's disease, a chronic wasting disease of ruminants, is a typical example. Culture of MAP from the feces and intestinal tissues is a commonly used test for confirmation of infection. Liquid medium offers greater sensitivity than solid medium for detection of MAP; however, support for the BD Bactec 460 system commonly used for this purpose has been discontinued. We previously developed a new liquid culture medium, M7H9C, to replace it, with confirmation of growth reliant on PCR. Here, we report an efficient DNA isolation and quantitative PCR methodology for the specific detection and confirmation of MAP growth in liquid culture media containing egg yolk. The analytical sensitivity was at least 10(4)-fold higher than a commonly used method involving ethanol precipitation of DNA and conventional PCR; this may be partly due to the addition of a bead-beating step to manually disrupt the cell wall of the mycobacteria. The limit of detection, determined using pure cultures of two different MAP strains, was 100 to 1,000 MAP organisms/ml. The diagnostic accuracy was confirmed using a panel of cattle fecal (n=54) and sheep fecal and tissue (n=90) culture samples. This technique is directly relevant for diagnostic laboratories that perform MAP cultures but may also be applicable to the detection of other species, including M. avium and M. tuberculosis. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Advancing research and applications with lightning detection and mapping systems

NASA Astrophysics Data System (ADS)

MacGorman, Donald R.; Goodman, Steven J.

2011-11-01

Southern Thunder 2011 Workshop; Norman, Oklahoma, 11-14 July 2011 The Southern Thunder 2011 (ST11) Workshop was the fourth in a series intended to accelerate research and operational applications made possible by the expanding availability of ground-based and satellite systems that detect and map all types of lightning (in-cloud and cloud-to-ground). This community workshop, first held in 2004, brings together lightning data providers, algorithm developers, and operational users in government, academia, and industry.

Brain Injury Lesion Imaging Using Preconditioned Quantitative Susceptibility Mapping without Skull Stripping.

PubMed

Soman, S; Liu, Z; Kim, G; Nemec, U; Holdsworth, S J; Main, K; Lee, B; Kolakowsky-Hayner, S; Selim, M; Furst, A J; Massaband, P; Yesavage, J; Adamson, M M; Spincemallie, P; Moseley, M; Wang, Y

2018-04-01

Identifying cerebral microhemorrhage burden can aid in the diagnosis and management of traumatic brain injury, stroke, hypertension, and cerebral amyloid angiopathy. MR imaging susceptibility-based methods are more sensitive than CT for detecting cerebral microhemorrhage, but methods other than quantitative susceptibility mapping provide results that vary with field strength and TE, require additional phase maps to distinguish blood from calcification, and depict cerebral microhemorrhages as bloom artifacts. Quantitative susceptibility mapping provides universal quantification of tissue magnetic property without these constraints but traditionally requires a mask generated by skull-stripping, which can pose challenges at tissue interphases. We evaluated the preconditioned quantitative susceptibility mapping MR imaging method, which does not require skull-stripping, for improved depiction of brain parenchyma and pathology. Fifty-six subjects underwent brain MR imaging with a 3D multiecho gradient recalled echo acquisition. Mask-based quantitative susceptibility mapping images were created using a commonly used mask-based quantitative susceptibility mapping method, and preconditioned quantitative susceptibility images were made using precondition-based total field inversion. All images were reviewed by a neuroradiologist and a radiology resident. Ten subjects (18%), all with traumatic brain injury, demonstrated blood products on 3D gradient recalled echo imaging. All lesions were visible on preconditioned quantitative susceptibility mapping, while 6 were not visible on mask-based quantitative susceptibility mapping. Thirty-one subjects (55%) demonstrated brain parenchyma and/or lesions that were visible on preconditioned quantitative susceptibility mapping but not on mask-based quantitative susceptibility mapping. Six subjects (11%) demonstrated pons artifacts on preconditioned quantitative susceptibility mapping and mask-based quantitative susceptibility mapping; they were worse on preconditioned quantitative susceptibility mapping. Preconditioned quantitative susceptibility mapping MR imaging can bring the benefits of quantitative susceptibility mapping imaging to clinical practice without the limitations of mask-based quantitative susceptibility mapping, especially for evaluating cerebral microhemorrhage-associated pathologies, such as traumatic brain injury. © 2018 by American Journal of Neuroradiology.

Factors affecting basket catheter detection of real and phantom rotors in the atria: A computational study.

PubMed

Martinez-Mateu, Laura; Romero, Lucia; Ferrer-Albero, Ana; Sebastian, Rafael; Rodríguez Matas, José F; Jalife, José; Berenfeld, Omer; Saiz, Javier

2018-03-01

Anatomically based procedures to ablate atrial fibrillation (AF) are often successful in terminating paroxysmal AF. However, the ability to terminate persistent AF remains disappointing. New mechanistic approaches use multiple-electrode basket catheter mapping to localize and target AF drivers in the form of rotors but significant concerns remain about their accuracy. We aimed to evaluate how electrode-endocardium distance, far-field sources and inter-electrode distance affect the accuracy of localizing rotors. Sustained rotor activation of the atria was simulated numerically and mapped using a virtual basket catheter with varying electrode densities placed at different positions within the atrial cavity. Unipolar electrograms were calculated on the entire endocardial surface and at each of the electrodes. Rotors were tracked on the interpolated basket phase maps and compared with the respective atrial voltage and endocardial phase maps, which served as references. Rotor detection by the basket maps varied between 35-94% of the simulation time, depending on the basket's position and the electrode-to-endocardial wall distance. However, two different types of phantom rotors appeared also on the basket maps. The first type was due to the far-field sources and the second type was due to interpolation between the electrodes; increasing electrode density decreased the incidence of the second but not the first type of phantom rotors. In the simulations study, basket catheter-based phase mapping detected rotors even when the basket was not in full contact with the endocardial wall, but always generated a number of phantom rotors in the presence of only a single real rotor, which would be the desired ablation target. Phantom rotors may mislead and contribute to failure in AF ablation procedures.

Factors affecting basket catheter detection of real and phantom rotors in the atria: A computational study

PubMed Central

Romero, Lucia; Rodríguez Matas, José F.; Berenfeld, Omer; Saiz, Javier

2018-01-01

Anatomically based procedures to ablate atrial fibrillation (AF) are often successful in terminating paroxysmal AF. However, the ability to terminate persistent AF remains disappointing. New mechanistic approaches use multiple-electrode basket catheter mapping to localize and target AF drivers in the form of rotors but significant concerns remain about their accuracy. We aimed to evaluate how electrode-endocardium distance, far-field sources and inter-electrode distance affect the accuracy of localizing rotors. Sustained rotor activation of the atria was simulated numerically and mapped using a virtual basket catheter with varying electrode densities placed at different positions within the atrial cavity. Unipolar electrograms were calculated on the entire endocardial surface and at each of the electrodes. Rotors were tracked on the interpolated basket phase maps and compared with the respective atrial voltage and endocardial phase maps, which served as references. Rotor detection by the basket maps varied between 35–94% of the simulation time, depending on the basket’s position and the electrode-to-endocardial wall distance. However, two different types of phantom rotors appeared also on the basket maps. The first type was due to the far-field sources and the second type was due to interpolation between the electrodes; increasing electrode density decreased the incidence of the second but not the first type of phantom rotors. In the simulations study, basket catheter-based phase mapping detected rotors even when the basket was not in full contact with the endocardial wall, but always generated a number of phantom rotors in the presence of only a single real rotor, which would be the desired ablation target. Phantom rotors may mislead and contribute to failure in AF ablation procedures. PMID:29505583

A Combined Approach to Cartographic Displacement for Buildings Based on Skeleton and Improved Elastic Beam Algorithm

PubMed Central

Liu, Yuangang; Guo, Qingsheng; Sun, Yageng; Ma, Xiaoya

2014-01-01

Scale reduction from source to target maps inevitably leads to conflicts of map symbols in cartography and geographic information systems (GIS). Displacement is one of the most important map generalization operators and it can be used to resolve the problems that arise from conflict among two or more map objects. In this paper, we propose a combined approach based on constraint Delaunay triangulation (CDT) skeleton and improved elastic beam algorithm for automated building displacement. In this approach, map data sets are first partitioned. Then the displacement operation is conducted in each partition as a cyclic and iterative process of conflict detection and resolution. In the iteration, the skeleton of the gap spaces is extracted using CDT. It then serves as an enhanced data model to detect conflicts and construct the proximity graph. Then, the proximity graph is adjusted using local grouping information. Under the action of forces derived from the detected conflicts, the proximity graph is deformed using the improved elastic beam algorithm. In this way, buildings are displaced to find an optimal compromise between related cartographic constraints. To validate this approach, two topographic map data sets (i.e., urban and suburban areas) were tested. The results were reasonable with respect to each constraint when the density of the map was not extremely high. In summary, the improvements include (1) an automated parameter-setting method for elastic beams, (2) explicit enforcement regarding the positional accuracy constraint, added by introducing drag forces, (3) preservation of local building groups through displacement over an adjusted proximity graph, and (4) an iterative strategy that is more likely to resolve the proximity conflicts than the one used in the existing elastic beam algorithm. PMID:25470727

A deviation based assessment methodology for multiple machine health patterns classification and fault detection

NASA Astrophysics Data System (ADS)

Jia, Xiaodong; Jin, Chao; Buzza, Matt; Di, Yuan; Siegel, David; Lee, Jay

2018-01-01

Successful applications of Diffusion Map (DM) in machine failure detection and diagnosis have been reported in several recent studies. DM provides an efficient way to visualize the high-dimensional, complex and nonlinear machine data, and thus suggests more knowledge about the machine under monitoring. In this paper, a DM based methodology named as DM-EVD is proposed for machine degradation assessment, abnormality detection and diagnosis in an online fashion. Several limitations and challenges of using DM for machine health monitoring have been analyzed and addressed. Based on the proposed DM-EVD, a deviation based methodology is then proposed to include more dimension reduction methods. In this work, the incorporation of Laplacian Eigen-map and Principal Component Analysis (PCA) are explored, and the latter algorithm is named as PCA-Dev and is validated in the case study. To show the successful application of the proposed methodology, case studies from diverse fields are presented and investigated in this work. Improved results are reported by benchmarking with other machine learning algorithms.

Multiresolution saliency map based object segmentation

NASA Astrophysics Data System (ADS)

Yang, Jian; Wang, Xin; Dai, ZhenYou

2015-11-01

Salient objects' detection and segmentation are gaining increasing research interest in recent years. A saliency map can be obtained from different models presented in previous studies. Based on this saliency map, the most salient region (MSR) in an image can be extracted. This MSR, generally a rectangle, can be used as the initial parameters for object segmentation algorithms. However, to our knowledge, all of those saliency maps are represented in a unitary resolution although some models have even introduced multiscale principles in the calculation process. Furthermore, some segmentation methods, such as the well-known GrabCut algorithm, need more iteration time or additional interactions to get more precise results without predefined pixel types. A concept of a multiresolution saliency map is introduced. This saliency map is provided in a multiresolution format, which naturally follows the principle of the human visual mechanism. Moreover, the points in this map can be utilized to initialize parameters for GrabCut segmentation by labeling the feature pixels automatically. Both the computing speed and segmentation precision are evaluated. The results imply that this multiresolution saliency map-based object segmentation method is simple and efficient.

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

PubMed Central

Kim, Sungho

2015-01-01

Sea-based infrared search and track (IRST) is important for homeland security by detecting missiles and asymmetric boats. This paper proposes a novel scheme to interpret various infrared scenes by classifying the infrared background types and detecting the coastal regions in omni-directional images. The background type or region-selective small infrared target detector should be deployed to maximize the detection rate and to minimize the number of false alarms. A spatial filter-based small target detector is suitable for identifying stationary incoming targets in remote sea areas with sky only. Many false detections can occur if there is an image sector containing a coastal region, due to ground clutter and the difficulty in finding true targets using the same spatial filter-based detector. A temporal filter-based detector was used to handle these problems. Therefore, the scene type and coastal region information is critical to the success of IRST in real-world applications. In this paper, the infrared scene type was determined using the relationships between the sensor line-of-sight (LOS) and a horizontal line in an image. The proposed coastal region detector can be activated if the background type of the probing sector is determined to be a coastal region. Coastal regions can be detected by fusing the region map and curve map. The experimental results on real infrared images highlight the feasibility of the proposed sea-based scene interpretation. In addition, the effects of the proposed scheme were analyzed further by applying region-adaptive small target detection. PMID:26404308

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed Central

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

2011-01-01

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

Focal Cortical Dysplasia (FCD) lesion analysis with complex diffusion approach.

PubMed

Rajan, Jeny; Kannan, K; Kesavadas, C; Thomas, Bejoy

2009-10-01

Identification of Focal Cortical Dysplasia (FCD) can be difficult due to the subtle MRI changes. Though sequences like FLAIR (fluid attenuated inversion recovery) can detect a large majority of these lesions, there are smaller lesions without signal changes that can easily go unnoticed by the naked eye. The aim of this study is to improve the visibility of focal cortical dysplasia lesions in the T1 weighted brain MRI images. In the proposed method, we used a complex diffusion based approach for calculating the FCD affected areas. Based on the diffused image and thickness map, a complex map is created. From this complex map; FCD areas can be easily identified. MRI brains of 48 subjects selected by neuroradiologists were given to computer scientists who developed the complex map for identifying the cortical dysplasia. The scientists were blinded to the MRI interpretation result of the neuroradiologist. The FCD could be identified in all the patients in whom surgery was done, however three patients had false positive lesions. More lesions were identified in patients in whom surgery was not performed and lesions were seen in few of the controls. These were considered as false positive. This computer aided detection technique using complex diffusion approach can help detect focal cortical dysplasia in patients with epilepsy.

Using gradient-based ray and candidate shadow maps for environmental illumination distribution estimation

NASA Astrophysics Data System (ADS)

Eem, Changkyoung; Kim, Iksu; Hong, Hyunki

2015-07-01

A method to estimate the environmental illumination distribution of a scene with gradient-based ray and candidate shadow maps is presented. In the shadow segmentation stage, we apply a Canny edge detector to the shadowed image by using a three-dimensional (3-D) augmented reality (AR) marker of a known size and shape. Then the hierarchical tree of the connected edge components representing the topological relation is constructed, and the connected components are merged, taking their hierarchical structures into consideration. A gradient-based ray that is perpendicular to the gradient of the edge pixel in the shadow image can be used to extract the shadow regions. In the light source detection stage, shadow regions with both a 3-D AR marker and the light sources are partitioned into candidate shadow maps. A simple logic operation between each candidate shadow map and the segmented shadow is used to efficiently compute the area ratio between them. The proposed method successively extracts the main light sources according to their relative contributions on the segmented shadows. The proposed method can reduce unwanted effects due to the sampling positions in the shadow region and the threshold values in the shadow edge detection.

A combined approach based on MAF analysis and AHP method to fault detection mapping: A case study from a gas field, southwest of Iran

NASA Astrophysics Data System (ADS)

Shakiba, Sima; Asghari, Omid; Khah, Nasser Keshavarz Faraj

2018-01-01

A combined geostatitical methodology based on Min/Max Auto-correlation Factor (MAF) analysis and Analytical Hierarchy Process (AHP) is presented to generate a suitable Fault Detection Map (FDM) through seismic attributes. Five seismic attributes derived from a 2D time slice obtained from data related to a gas field located in southwest of Iran are used including instantaneous amplitude, similarity, energy, frequency, and Fault Enhancement Filter (FEF). The MAF analysis is implemented to reduce dimension of input variables, and then AHP method is applied on three obtained de-correlated MAF factors as evidential layer. Three Decision Makers (DMs) are used to construct PCMs for determining weights of selected evidential layer. Finally, weights obtained by AHP were multiplied in normalized valued of each alternative (MAF layers) and the concluded weighted layers were integrated in order to prepare final FDM. Results proved that applying algorithm proposed in this study generate a map more acceptable than the each individual attribute and sharpen the non-surface discontinuities as well as enhancing continuity of detected faults.

Impact of Aerosol Dust on xMAP Multiplex Detection of Different Class Pathogens

PubMed Central

Kleymenov, Denis A.; Gushchin, Vladimir A.; Gintsburg, Alexander L.; Tkachuk, Artem P.

2017-01-01

Environmental or city-scale bioaerosol surveillance can provide additional value for biodefense and public health. Efficient bioaerosol monitoring should rely on multiplex systems capable of detecting a wide range of biologically hazardous components potentially present in air (bacteria, viruses, toxins and allergens). xMAP technology from LuminexTM allows multiplex bead-based detection of antigens or nucleic acids, but its use for simultaneous detection of different classes of pathogens (bacteria, virus, toxin) is questionable. Another problem is the detection of pathogens in complex matrices, e.g., in the presence of dust. In the this research, we developed the model xMAP multiplex test-system aiRDeTeX 1.0, which enables detection of influenza A virus, Adenovirus type 6 Salmonella typhimurium, and cholera toxin B subunit representing RNA virus, DNA virus, gram-negative bacteria and toxin respectively as model organisms of biologically hazardous components potentially present in or spreadable through the air. We have extensively studied the effect of matrix solution (PBS, distilled water), environmental dust and ultrasound treatment for monoplex and multiplex detection efficiency of individual targets. All targets were efficiently detectable in PBS and in the presence of dust. Ultrasound does not improve the detection except for bacterial LPS. PMID:29238328

Fully Convolutional Network-Based Multifocus Image Fusion.

PubMed

Guo, Xiaopeng; Nie, Rencan; Cao, Jinde; Zhou, Dongming; Qian, Wenhua

2018-07-01

As the optical lenses for cameras always have limited depth of field, the captured images with the same scene are not all in focus. Multifocus image fusion is an efficient technology that can synthesize an all-in-focus image using several partially focused images. Previous methods have accomplished the fusion task in spatial or transform domains. However, fusion rules are always a problem in most methods. In this letter, from the aspect of focus region detection, we propose a novel multifocus image fusion method based on a fully convolutional network (FCN) learned from synthesized multifocus images. The primary novelty of this method is that the pixel-wise focus regions are detected through a learning FCN, and the entire image, not just the image patches, are exploited to train the FCN. First, we synthesize 4500 pairs of multifocus images by repeatedly using a gaussian filter for each image from PASCAL VOC 2012, to train the FCN. After that, a pair of source images is fed into the trained FCN, and two score maps indicating the focus property are generated. Next, an inversed score map is averaged with another score map to produce an aggregative score map, which take full advantage of focus probabilities in two score maps. We implement the fully connected conditional random field (CRF) on the aggregative score map to accomplish and refine a binary decision map for the fusion task. Finally, we exploit the weighted strategy based on the refined decision map to produce the fused image. To demonstrate the performance of the proposed method, we compare its fused results with several start-of-the-art methods not only on a gray data set but also on a color data set. Experimental results show that the proposed method can achieve superior fusion performance in both human visual quality and objective assessment.

Grade Expectations: Mapping Stakeholder Views of Online Plagiarism Detection

ERIC Educational Resources Information Center

Ashe, Diana; Manning, Michelle

2007-01-01

Based upon a pilot study of the leading online plagiarism detection service, this article examines the views of faculty and students as the main stakeholders in the controversy over online plagiarism detection. Rather than give advice outside of a specific institutional context, this study offers an understanding of the reasoning that informs the…

Independent component analysis (ICA) and self-organizing map (SOM) approach to multidetection system for network intruders

NASA Astrophysics Data System (ADS)

Abdi, Abdi M.; Szu, Harold H.

2003-04-01

With the growing rate of interconnection among computer systems, network security is becoming a real challenge. Intrusion Detection System (IDS) is designed to protect the availability, confidentiality and integrity of critical network information systems. Today"s approach to network intrusion detection involves the use of rule-based expert systems to identify an indication of known attack or anomalies. However, these techniques are less successful in identifying today"s attacks. Hackers are perpetually inventing new and previously unanticipated techniques to compromise information infrastructure. This paper proposes a dynamic way of detecting network intruders on time serious data. The proposed approach consists of a two-step process. Firstly, obtaining an efficient multi-user detection method, employing the recently introduced complexity minimization approach as a generalization of a standard ICA. Secondly, we identified unsupervised learning neural network architecture based on Kohonen"s Self-Organizing Map for potential functional clustering. These two steps working together adaptively will provide a pseudo-real time novelty detection attribute to supplement the current intrusion detection statistical methodology.

Sea Ice Detection Based on Differential Delay-Doppler Maps from UK TechDemoSat-1

PubMed Central

Zhu, Yongchao; Yu, Kegen; Zou, Jingui; Wickert, Jens

2017-01-01

Global Navigation Satellite System (GNSS) signals can be exploited to remotely sense atmosphere and land and ocean surface to retrieve a range of geophysical parameters. This paper proposes two new methods, termed as power-summation of differential Delay-Doppler Maps (PS-D) and pixel-number of differential Delay-Doppler Maps (PN-D), to distinguish between sea ice and sea water using differential Delay-Doppler Maps (dDDMs). PS-D and PN-D make use of power-summation and pixel-number of dDDMs, respectively, to measure the degree of difference between two DDMs so as to determine the transition state (water-water, water-ice, ice-ice and ice-water) and hence ice and water are detected. Moreover, an adaptive incoherent averaging of DDMs is employed to improve the computational efficiency. A large number of DDMs recorded by UK TechDemoSat-1 (TDS-1) over the Arctic region are used to test the proposed sea ice detection methods. Through evaluating against ground-truth measurements from the Ocean Sea Ice SAF, the proposed PS-D and PN-D methods achieve a probability of detection of 99.72% and 99.69% respectively, while the probability of false detection is 0.28% and 0.31% respectively. PMID:28704948

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

PubMed

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

2016-09-01

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

Automatic detection of artifacts in converted S3D video

NASA Astrophysics Data System (ADS)

Bokov, Alexander; Vatolin, Dmitriy; Zachesov, Anton; Belous, Alexander; Erofeev, Mikhail

2014-03-01

In this paper we present algorithms for automatically detecting issues specific to converted S3D content. When a depth-image-based rendering approach produces a stereoscopic image, the quality of the result depends on both the depth maps and the warping algorithms. The most common problem with converted S3D video is edge-sharpness mismatch. This artifact may appear owing to depth-map blurriness at semitransparent edges: after warping, the object boundary becomes sharper in one view and blurrier in the other, yielding binocular rivalry. To detect this problem we estimate the disparity map, extract boundaries with noticeable differences, and analyze edge-sharpness correspondence between views. We pay additional attention to cases involving a complex background and large occlusions. Another problem is detection of scenes that lack depth volume: we present algorithms for detecting at scenes and scenes with at foreground objects. To identify these problems we analyze the features of the RGB image as well as uniform areas in the depth map. Testing of our algorithms involved examining 10 Blu-ray 3D releases with converted S3D content, including Clash of the Titans, The Avengers, and The Chronicles of Narnia: The Voyage of the Dawn Treader. The algorithms we present enable improved automatic quality assessment during the production stage.

Non-supervised method for early forest fire detection and rapid mapping

NASA Astrophysics Data System (ADS)

Artés, Tomás; Boca, Roberto; Liberta, Giorgio; San-Miguel, Jesús

2017-09-01

Natural hazards are a challenge for the society. Scientific community efforts have been severely increased assessing tasks about prevention and damage mitigation. The most important points to minimize natural hazard damages are monitoring and prevention. This work focuses particularly on forest fires. This phenomenon depends on small-scale factors and fire behavior is strongly related to the local weather. Forest fire spread forecast is a complex task because of the scale of the phenomena, the input data uncertainty and time constraints in forest fire monitoring. Forest fire simulators have been improved, including some calibration techniques avoiding data uncertainty and taking into account complex factors as the atmosphere. Such techniques increase dramatically the computational cost in a context where the available time to provide a forecast is a hard constraint. Furthermore, an early mapping of the fire becomes crucial to assess it. In this work, a non-supervised method for forest fire early detection and mapping is proposed. As main sources, the method uses daily thermal anomalies from MODIS and VIIRS combined with land cover map to identify and monitor forest fires with very few resources. This method relies on a clustering technique (DBSCAN algorithm) and on filtering thermal anomalies to detect the forest fires. In addition, a concave hull (alpha shape algorithm) is applied to obtain rapid mapping of the fire area (very coarse accuracy mapping). Therefore, the method leads to a potential use for high-resolution forest fire rapid mapping based on satellite imagery using the extent of each early fire detection. It shows the way to an automatic rapid mapping of the fire at high resolution processing as few data as possible.

Specifications for updating USGS land use and land cover maps

USGS Publications Warehouse

Milazzo, Valerie A.

1983-01-01

To meet the increasing demands for up-to-date land use and land cover information, a primary goal of the U.S. Geological Survey's (USGS) national land use and land cover mapping program is to provide for periodic updating of maps and data in a timely and uniform manner. The technical specifications for updating existing USGS land use and land cover maps that are presented here cover both the interpretive aspects of detecting and identifying land use and land cover changes and the cartographic aspects of mapping and presenting the change data in conventional map format. They provide the map compiler with the procedures and techniques necessary to then use these change data to update existing land use and land cover maps in a manner that is both standardized and repeatable. Included are specifications for the acquisition of remotely sensed source materials, selection of compilation map bases, handling of data base corrections, editing and quality control operations, generation of map update products for USGS open file, and the reproduction and distribution of open file materials. These specifications are planned to become part of the National Mapping Division's Technical Instructions.

Terrain mapping and control of unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kang, Yeonsik

In this thesis, methods for terrain mapping and control of unmanned aerial vehicles (UAVs) are proposed. First, robust obstacle detection and tracking algorithm are introduced to eliminate the clutter noise uncorrelated with the real obstacle. This is an important problem since most types of sensor measurements are vulnerable to noise. In order to eliminate such noise, a Kalman filter-based interacting multiple model (IMM) algorithm is employed to effectively detect obstacles and estimate their positions precisely. Using the outcome of the IMM-based obstacle detection algorithm, a new method of building a probabilistic occupancy grid map is proposed based on Bayes rule in probability theory. Since the proposed map update law uses the outputs of the IMM-based obstacle detection algorithm, simultaneous tracking of moving targets and mapping of stationary obstacles are possible. This can be helpful especially in a noisy outdoor environment where different types of obstacles exist. Another feature of the algorithm is its capability to eliminate clutter noise as well as measurement noise. The proposed algorithm is simulated in Matlab using realistic sensor models. The results show close agreement with the layout of real obstacles. An efficient method called "quadtree" is used to process massive geographical information in a convenient manner. The algorithm is evaluated in a realistic simulation environment called RIPTIDE, which the NASA Ames Research Center developed to access the performance of complicated software for UAVs. Supposing that a UAV is equipped with abovementioned obstacle detection and mapping algorithm, the control problem of a small fixed-wing UAV is studied. A Nonlinear Model Predictive Control (NMPC is designed as a high level controller for the fixed-wing UAV using a kinematic model of the UAV. The kinematic model is employed because of the assumption that there exist low level controls on the UAV. The UAV dynamics are nonlinear with input constraints which is the main challenge explored in this thesis. The control objective of the NMPC is determined to track a desired line, and the analysis of the designed NMPC's stability is followed to find the conditions that can assure stability. Then, the control objective is extended to track adjoined multiple line segments with obstacle avoidance capability. In simulation, the performance of the NMPC is superb with fast convergence and small overshoot. The computation time is not a burden for a fixed-wing UAV controller with a Pentium level on-board computer that provides a reasonable control update rate.

An improved image non-blind image deblurring method based on FoEs

NASA Astrophysics Data System (ADS)

Zhu, Qidan; Sun, Lei

2013-03-01

Traditional non-blind image deblurring algorithms always use maximum a posterior(MAP). MAP estimates involving natural image priors can reduce the ripples effectively in contrast to maximum likelihood(ML). However, they have been found lacking in terms of restoration performance. Based on this issue, we utilize MAP with KL penalty to replace traditional MAP. We develop an image reconstruction algorithm that minimizes the KL divergence between the reference distribution and the prior distribution. The approximate KL penalty can restrain over-smooth caused by MAP. We use three groups of images and Harris corner detection to prove our method. The experimental results show that our algorithm of non-blind image restoration can effectively reduce the ringing effect and exhibit the state-of-the-art deblurring results.

Histological validation of near-infrared reflectance multispectral imaging technique for caries detection and quantification

NASA Astrophysics Data System (ADS)

Salsone, Silvia; Taylor, Andrew; Gomez, Juliana; Pretty, Iain; Ellwood, Roger; Dickinson, Mark; Lombardo, Giuseppe; Zakian, Christian

2012-07-01

Near infrared (NIR) multispectral imaging is a novel noninvasive technique that maps and quantifies dental caries. The technique has the ability to reduce the confounding effect of stain present on teeth. The aim of this study was to develop and validate a quantitative NIR multispectral imaging system for caries detection and assessment against a histological reference standard. The proposed technique is based on spectral imaging at specific wavelengths in the range from 1000 to 1700 nm. A total of 112 extracted teeth (molars and premolars) were used and images of occlusal surfaces at different wavelengths were acquired. Three spectral reflectance images were combined to generate a quantitative lesion map of the tooth. The maximum value of the map at the corresponding histological section was used as the NIR caries score. The NIR caries score significantly correlated with the histological reference standard (Spearman's Coefficient=0.774, p<0.01). Caries detection sensitivities and specificities of 72% and 91% for sound areas, 36% and 79% for lesions on the enamel, and 82% and 69% for lesions in dentin were found. These results suggest that NIR spectral imaging is a novel and promising method for the detection, quantification, and mapping of dental caries.

Histological validation of near-infrared reflectance multispectral imaging technique for caries detection and quantification.

PubMed

Salsone, Silvia; Taylor, Andrew; Gomez, Juliana; Pretty, Iain; Ellwood, Roger; Dickinson, Mark; Lombardo, Giuseppe; Zakian, Christian

2012-07-01

Near infrared (NIR) multispectral imaging is a novel noninvasive technique that maps and quantifies dental caries. The technique has the ability to reduce the confounding effect of stain present on teeth. The aim of this study was to develop and validate a quantitative NIR multispectral imaging system for caries detection and assessment against a histological reference standard. The proposed technique is based on spectral imaging at specific wavelengths in the range from 1000 to 1700 nm. A total of 112 extracted teeth (molars and premolars) were used and images of occlusal surfaces at different wavelengths were acquired. Three spectral reflectance images were combined to generate a quantitative lesion map of the tooth. The maximum value of the map at the corresponding histological section was used as the NIR caries score. The NIR caries score significantly correlated with the histological reference standard (Spearman's Coefficient=0.774, p<0.01). Caries detection sensitivities and specificities of 72% and 91% for sound areas, 36% and 79% for lesions on the enamel, and 82% and 69% for lesions in dentin were found. These results suggest that NIR spectral imaging is a novel and promising method for the detection, quantification, and mapping of dental caries.

All over the map: An interobserver agreement study of tumor location based on the PI-RADSv2 sector map.

PubMed

Greer, Matthew D; Shih, Joanna H; Barrett, Tristan; Bednarova, Sandra; Kabakus, Ismail; Law, Yan Mee; Shebel, Haytham; Merino, Maria J; Wood, Bradford J; Pinto, Peter A; Choyke, Peter L; Turkbey, Baris

2018-01-17

Prostate imaging reporting and data system version 2 (PI-RADSv2) recommends a sector map for reporting findings of prostate cancer mulitparametric MRI (mpMRI). Anecdotally, radiologists may demonstrate inconsistent reproducibility with this map. To evaluate interobserver agreement in defining prostate tumor location on mpMRI using the PI-RADSv2 sector map. Retrospective. Thirty consecutive patients who underwent mpMRI between October, 2013 and March, 2015 and who subsequently underwent prostatectomy with whole-mount processing. 3T mpMRI with T 2 W, diffusion-weighted imaging (DWI) (apparent diffusion coefficient [ADC] and b-2000), dynamic contrast-enhanced (DCE). Six radiologists (two high, two intermediate, and two low experience) from six institutions participated. Readers were blinded to lesion location and detected up to four lesions as per PI-RADSv2 guidelines. Readers marked the long-axis of lesions, saved screen-shots of each lesion, and then marked the lesion location on the PI-RADSv2 sector map. Whole-mount prostatectomy specimens registered to the MRI served as ground truth. Index lesions were defined as the highest grade lesion or largest lesion if grades were equivalent. Agreement was calculated for the exact, overlap, and proportion of agreement. Readers detected an average of 1.9 lesions per patient (range 1.6-2.3). 96.3% (335/348) of all lesions for all readers were scored PI-RADS ≥3. Readers defined a median of 2 (range 1-18) sectors per lesion. Agreement for detecting index lesions by screen shots was 83.7% (76.1%-89.9%) vs. 71.0% (63.1-78.3%) overlap agreement on the PI-RADS sector map (P < 0.001). Exact agreement for defining sectors of detected index lesions was only 21.2% (95% confidence interval [CI]: 14.4-27.7%) and rose to 49.0% (42.4-55.3%) when overlap was considered. Agreement on defining the same level of disease (ie, apex, mid, base) was 61.4% (95% CI 50.2-71.8%). Readers are highly likely to detect the same index lesion on mpMRI, but exhibit poor reproducibility when attempting to define tumor location on the PI-RADSv2 sector map. The poor agreement of the PI-RADSv2 sector map raises concerns its utility in clinical practice. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

A High-Density Genetic Map with Array-Based Markers Facilitates Structural and Quantitative Trait Locus Analyses of the Common Wheat Genome

PubMed Central

Iehisa, Julio Cesar Masaru; Ohno, Ryoko; Kimura, Tatsuro; Enoki, Hiroyuki; Nishimura, Satoru; Okamoto, Yuki; Nasuda, Shuhei; Takumi, Shigeo

2014-01-01

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map. PMID:24972598

A high-density genetic map with array-based markers facilitates structural and quantitative trait locus analyses of the common wheat genome.

PubMed

Iehisa, Julio Cesar Masaru; Ohno, Ryoko; Kimura, Tatsuro; Enoki, Hiroyuki; Nishimura, Satoru; Okamoto, Yuki; Nasuda, Shuhei; Takumi, Shigeo

2014-10-01

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Vehicle Detection for RCTA/ANS (Autonomous Navigation System)

NASA Technical Reports Server (NTRS)

Brennan, Shane; Bajracharya, Max; Matthies, Larry H.; Howard, Andrew B.

2012-01-01

Using a stereo camera pair, imagery is acquired and processed through the JPLV stereo processing pipeline. From this stereo data, large 3D blobs are found. These blobs are then described and classified by their shape to determine which are vehicles and which are not. Prior vehicle detection algorithms are either targeted to specific domains, such as following lead cars, or are intensity- based methods that involve learning typical vehicle appearances from a large corpus of training data. In order to detect vehicles, the JPL Vehicle Detection (JVD) algorithm goes through the following steps: 1. Take as input a left disparity image and left rectified image from JPLV stereo. 2. Project the disparity data onto a two-dimensional Cartesian map. 3. Perform some post-processing of the map built in the previous step in order to clean it up. 4. Take the processed map and find peaks. For each peak, grow it out into a map blob. These map blobs represent large, roughly vehicle-sized objects in the scene. 5. Take these map blobs and reject those that do not meet certain criteria. Build descriptors for the ones that remain. Pass these descriptors onto a classifier, which determines if the blob is a vehicle or not. The probability of detection is the probability that if a vehicle is present in the image, is visible, and un-occluded, then it will be detected by the JVD algorithm. In order to estimate this probability, eight sequences were ground-truthed from the RCTA (Robotics Collaborative Technology Alliances) program, totaling over 4,000 frames with 15 unique vehicles. Since these vehicles were observed at varying ranges, one is able to find the probability of detection as a function of range. At the time of this reporting, the JVD algorithm was tuned to perform best at cars seen from the front, rear, or either side, and perform poorly on vehicles seen from oblique angles.

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

PubMed

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.

Active edge maps for medical image registration

NASA Astrophysics Data System (ADS)

Kerwin, William; Yuan, Chun

2001-07-01

Applying edge detection prior to performing image registration yields several advantages over raw intensity- based registration. Advantages include the ability to register multicontrast or multimodality images, immunity to intensity variations, and the potential for computationally efficient algorithms. In this work, a common framework for edge-based image registration is formulated as an adaptation of snakes used in boundary detection. Called active edge maps, the new formulation finds a one-to-one transformation T(x) that maps points in a source image to corresponding locations in a target image using an energy minimization approach. The energy consists of an image component that is small when edge features are well matched in the two images, and an internal term that restricts T(x) to allowable configurations. The active edge map formulation is illustrated here with a specific example developed for affine registration of carotid artery magnetic resonance images. In this example, edges are identified using a magnitude of gradient operator, image energy is determined using a Gaussian weighted distance function, and the internal energy includes separate, adjustable components that control volume preservation and rigidity.

Real-time change and damage detection of landslides and other earth movements threatening public infrastructure.

DOT National Transportation Integrated Search

2012-03-01

construction and maintenance. Repeat surveys using terrestrial laser scanning (TLS, ground-based LiDAR) enable rapid 3D data acquisition to map, see, analyze, and understand the processes generating such problems. Previously, change detection and ana...

Where and When: Optimal Scheduling of the Electromagnetic Follow-up of Gravitational-wave Events Based on Counterpart Light-curve Models

NASA Astrophysics Data System (ADS)

Salafia, Om Sharan; Colpi, Monica; Branchesi, Marica; Chassande-Mottin, Eric; Ghirlanda, Giancarlo; Ghisellini, Gabriele; Vergani, Susanna D.

2017-09-01

The electromagnetic (EM) follow-up of a gravitational-wave (GW) event requires scanning a wide sky region, defined by the so-called “skymap,” to detect and identify a transient counterpart. We propose a novel method that exploits the information encoded in the GW signal to construct a “detectability map,” which represents the time-dependent (“when”) probability of detecting the transient at each position of the skymap (“where”). Focusing on the case of a neutron star binary inspiral, we model the associated short gamma-ray burst afterglow and macronova emission using the probability distributions of binary parameters (sky position, distance, orbit inclination, mass ratio) extracted from the GW signal as inputs. The resulting family of possible light curves is the basis for constructing the detectability map. As a practical example, we apply the method to a simulated GW signal produced by a neutron star merger at 75 Mpc whose localization uncertainty is very large (˜1500 deg2). We construct observing strategies for optical, infrared, and radio facilities based on the detectability maps, taking VST, VISTA, and MeerKAT as prototypes. Assuming limiting fluxes of r˜ 24.5, J˜ 22.4 (AB magnitudes), and 500 μ {Jy} (1.4 {GHz}) for ˜1000 s of exposure each, the afterglow and macronova emissions are successfully detected with a minimum observing time of 7, 15, and 5 hr respectively.

Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles

PubMed Central

Mou, Xiaozheng; Wang, Han

2018-01-01

This paper proposes a wide-baseline stereo-based static obstacle mapping approach for unmanned surface vehicles (USVs). The proposed approach eliminates the complicated calibration work and the bulky rig in our previous binocular stereo system, and raises the ranging ability from 500 to 1000 m with a even larger baseline obtained from the motion of USVs. Integrating a monocular camera with GPS and compass information in this proposed system, the world locations of the detected static obstacles are reconstructed while the USV is traveling, and an obstacle map is then built. To achieve more accurate and robust performance, multiple pairs of frames are leveraged to synthesize the final reconstruction results in a weighting model. Experimental results based on our own dataset demonstrate the high efficiency of our system. To the best of our knowledge, we are the first to address the task of wide-baseline stereo-based obstacle mapping in a maritime environment. PMID:29617293

Optical sensors for application in intelligent food-packaging technology

NASA Astrophysics Data System (ADS)

McEvoy, Aisling K.; Von Bueltzingsloewen, Christoph; McDonagh, Colette M.; MacCraith, Brian D.; Klimant, Ingo; Wolfbeis, Otto S.

2003-03-01

Modified Atmosphere Packaged (MAP) food employs a protective gas mixture, which normally contains selected amounts of carbon dioxide (CO2) and oxygen (O2), in order to extend the shelf life of food. Conventional MAP analysis of package integrity involves destructive sampling of packages followed by carbon dioxide and oxygen detection. For quality control reasons, as well as to enhance food safety, the concept of optical on-pack sensors for monitoring the gas composition of the MAP package at different stages of the distribution process is very attractive. The objective of this work was to develop printable formulations of oxygen and carbon dioxide sensors for use in food packaging. Oxygen sensing is achieved by detecting the degree of quenching of a fluorescent ruthenium complex entrapped in a sol-gel matrix. In particular, a measurement technique based on the quenching of the fluorescence decay time, phase fluorometric detection, is employed. A scheme for detecting CO2 has been developed which is compatible with the oxygen detection scheme. It is fluorescence-based and uses the pH-sensitive 8-hydroxypyrene-1,3,6-trisulfonic acid (HPTS) indicator dye encapsulated in an organically modified silica (ORMOSIL) glass matrix. Dual Luminophore Referencing (DLR) has been employed as an internal referencing scheme, which provides many of the advantages of lifetime-based fluorometric methods. Oxygen cross-sensitivity was minimised by encapsulating the reference luminophore in dense sol-gel microspheres. The sensor performance compared well with standard methods for both oxygen and carbon dioxide detection. The results of preliminary on-pack print trials are presented and a preliminary design of an integrated dual gas optical read-out device is discussed.

Expanded Processing Techniques for EMI Systems

DTIC Science & Technology

2012-07-01

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

The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

NASA Technical Reports Server (NTRS)

Hogan, Christine A.

1996-01-01

A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation composition was noted in the change detection image.

An Improved Otsu Threshold Segmentation Method for Underwater Simultaneous Localization and Mapping-Based Navigation

PubMed Central

Yuan, Xin; Martínez, José-Fernán; Eckert, Martina; López-Santidrián, Lourdes

2016-01-01

The main focus of this paper is on extracting features with SOund Navigation And Ranging (SONAR) sensing for further underwater landmark-based Simultaneous Localization and Mapping (SLAM). According to the characteristics of sonar images, in this paper, an improved Otsu threshold segmentation method (TSM) has been developed for feature detection. In combination with a contour detection algorithm, the foreground objects, although presenting different feature shapes, are separated much faster and more precisely than by other segmentation methods. Tests have been made with side-scan sonar (SSS) and forward-looking sonar (FLS) images in comparison with other four TSMs, namely the traditional Otsu method, the local TSM, the iterative TSM and the maximum entropy TSM. For all the sonar images presented in this work, the computational time of the improved Otsu TSM is much lower than that of the maximum entropy TSM, which achieves the highest segmentation precision among the four above mentioned TSMs. As a result of the segmentations, the centroids of the main extracted regions have been computed to represent point landmarks which can be used for navigation, e.g., with the help of an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-SLAM approach is a recursive and iterative estimation-update process, which besides a prediction and an update stage (as in classical Extended Kalman Filter (EKF)), includes an augmentation stage. During navigation, the robot localizes the centroids of different segments of features in sonar images, which are detected by our improved Otsu TSM, as point landmarks. Using them with the AEKF achieves more accurate and robust estimations of the robot pose and the landmark positions, than with those detected by the maximum entropy TSM. Together with the landmarks identified by the proposed segmentation algorithm, the AEKF-SLAM has achieved reliable detection of cycles in the map and consistent map update on loop closure, which is shown in simulated experiments. PMID:27455279

An Improved Otsu Threshold Segmentation Method for Underwater Simultaneous Localization and Mapping-Based Navigation.

PubMed

Yuan, Xin; Martínez, José-Fernán; Eckert, Martina; López-Santidrián, Lourdes

2016-07-22

The main focus of this paper is on extracting features with SOund Navigation And Ranging (SONAR) sensing for further underwater landmark-based Simultaneous Localization and Mapping (SLAM). According to the characteristics of sonar images, in this paper, an improved Otsu threshold segmentation method (TSM) has been developed for feature detection. In combination with a contour detection algorithm, the foreground objects, although presenting different feature shapes, are separated much faster and more precisely than by other segmentation methods. Tests have been made with side-scan sonar (SSS) and forward-looking sonar (FLS) images in comparison with other four TSMs, namely the traditional Otsu method, the local TSM, the iterative TSM and the maximum entropy TSM. For all the sonar images presented in this work, the computational time of the improved Otsu TSM is much lower than that of the maximum entropy TSM, which achieves the highest segmentation precision among the four above mentioned TSMs. As a result of the segmentations, the centroids of the main extracted regions have been computed to represent point landmarks which can be used for navigation, e.g., with the help of an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-SLAM approach is a recursive and iterative estimation-update process, which besides a prediction and an update stage (as in classical Extended Kalman Filter (EKF)), includes an augmentation stage. During navigation, the robot localizes the centroids of different segments of features in sonar images, which are detected by our improved Otsu TSM, as point landmarks. Using them with the AEKF achieves more accurate and robust estimations of the robot pose and the landmark positions, than with those detected by the maximum entropy TSM. Together with the landmarks identified by the proposed segmentation algorithm, the AEKF-SLAM has achieved reliable detection of cycles in the map and consistent map update on loop closure, which is shown in simulated experiments.

Urban land-cover change detection through sub-pixel imperviousness mapping using remotely sensed data

USGS Publications Warehouse

Yang, Limin; Xian, George Z.; Klaver, Jacqueline M.; Deal, Brian

2003-01-01

We developed a Sub-pixel Imperviousness Change Detection (SICD) approach to detect urban land-cover changes using Landsat and high-resolution imagery. The sub-pixel percent imperviousness was mapped for two dates (09 March 1993 and 11 March 2001) over western Georgia using a regression tree algorithm. The accuracy of the predicted imperviousness was reasonable based on a comparison using independent reference data. The average absolute error between predicted and reference data was 16.4 percent for 1993 and 15.3 percent for 2001. The correlation coefficient (r) was 0.73 for 1993 and 0.78 for 2001, respectively. Areas with a significant increase (greater than 20 percent) in impervious surface from 1993 to 2001 were mostly related to known land-cover/land-use changes that occurred in this area, suggesting that the spatial change of an impervious surface is a useful indicator for identifying spatial extent, intensity, and, potentially, type of urban land-cover/land-use changes. Compared to other pixel-based change-detection methods (band differencing, rationing, change vector, post-classification), information on changes in sub-pixel percent imperviousness allow users to quantify and interpret urban land-cover/land-use changes based on their own definition. Such information is considered complementary to products generated using other change-detection methods. In addition, the procedure for mapping imperviousness is objective and repeatable, hence, can be used for monitoring urban land-cover/land-use change over a large geographic area. Potential applications and limitations of the products developed through this study in urban environmental studies are also discussed.

Systematic evaluation of deep learning based detection frameworks for aerial imagery

NASA Astrophysics Data System (ADS)

Sommer, Lars; Steinmann, Lucas; Schumann, Arne; Beyerer, Jürgen

2018-04-01

Object detection in aerial imagery is crucial for many applications in the civil and military domain. In recent years, deep learning based object detection frameworks significantly outperformed conventional approaches based on hand-crafted features on several datasets. However, these detection frameworks are generally designed and optimized for common benchmark datasets, which considerably differ from aerial imagery especially in object sizes. As already demonstrated for Faster R-CNN, several adaptations are necessary to account for these differences. In this work, we adapt several state-of-the-art detection frameworks including Faster R-CNN, R-FCN, and Single Shot MultiBox Detector (SSD) to aerial imagery. We discuss adaptations that mainly improve the detection accuracy of all frameworks in detail. As the output of deeper convolutional layers comprise more semantic information, these layers are generally used in detection frameworks as feature map to locate and classify objects. However, the resolution of these feature maps is insufficient for handling small object instances, which results in an inaccurate localization or incorrect classification of small objects. Furthermore, state-of-the-art detection frameworks perform bounding box regression to predict the exact object location. Therefore, so called anchor or default boxes are used as reference. We demonstrate how an appropriate choice of anchor box sizes can considerably improve detection performance. Furthermore, we evaluate the impact of the performed adaptations on two publicly available datasets to account for various ground sampling distances or differing backgrounds. The presented adaptations can be used as guideline for further datasets or detection frameworks.

Probing cellular heterogeneity in cytokine-secreting immune cells using droplet-based microfluidics.

PubMed

Chokkalingam, Venkatachalam; Tel, Jurjen; Wimmers, Florian; Liu, Xin; Semenov, Sergey; Thiele, Julian; Figdor, Carl G; Huck, Wilhelm T S

2013-12-21

Here, we present a platform to detect cytokine (IL-2, IFN-γ, TNF-α) secretion of single, activated T-cells in droplets over time. We use a novel droplet-based microfluidic approach to encapsulate cells in monodisperse agarose droplets together with functionalized cytokine-capture beads for subsequent binding and detection of secreted cytokines from single cells. This method allows high-throughput detection of cellular heterogeneity and maps subsets within cell populations with specific functions.

Lane detection based on color probability model and fuzzy clustering

NASA Astrophysics Data System (ADS)

Yu, Yang; Jo, Kang-Hyun

2018-04-01

In the vehicle driver assistance systems, the accuracy and speed of lane line detection are the most important. This paper is based on color probability model and Fuzzy Local Information C-Means (FLICM) clustering algorithm. The Hough transform and the constraints of structural road are used to detect the lane line accurately. The global map of the lane line is drawn by the lane curve fitting equation. The experimental results show that the algorithm has good robustness.

Establishment a real-time reverse transcription PCR based on host biomarkers for the detection of the subclinical cases of Mycobacterium avium subsp. paratuberculosis.

PubMed

Park, Hyun-Eui; Park, Hong-Tae; Jung, Young Hoon; Yoo, Han Sang

2017-01-01

Bovine paratuberculosis (PTB) is a chronic enteric inflammatory disease of ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP) that causes large economic losses in the dairy industry. Spread of PTB is mainly provoked by a long subclinical stage during which MAP is shed into the environment with feces; accordingly, detection of subclinical animals is very important to its control. However, current diagnostic methods are not suitable for detection of subclinical animals. Therefore, the current study was conducted to develop a diagnostic method for analysis of the expression of genes of prognostic potential biomarker candidates in the whole blood of cattle naturally infected with MAP. Real-time PCR with nine potential biomarker candidates was developed for the diagnosis of MAP subclinical infection. Animals were divided into four groups based on fecal MAP PCR and serum ELISA. Eight genes (Timp1, Hp, Serpine1, Tfrc, Mmp9, Defb1, Defb10, and S100a8) were up-regulated in MAP-infected cattle (p <0.05). Moreover, ROC analysis revealed that eight genes (Timp1, Hp, Serpine1, Tfrc, Mmp9, Defb1, Defb10, and S100a8) showed fair diagnostic performance (AUC≥0.8). Four biomarkers (Timp1, S100a8, Defb1, and Defb10) showed the highest diagnostic accuracy in the PCR positive and ELISA negative group (PN group) and three biomarkers (Tfrc, Hp, and Serpine1) showed the highest diagnostic accuracy in the PCR negative and ELISA positive group (NP group). Moreover, three biomarkers (S100a8, Hp, and Defb10) were considered the most reliable for the PCR positive and ELISA positive group (PP group). Taken together, our data suggest that real-time PCR based on eight biomarkers (Timp1, Hp, Serpine1, Tfrc, Mmp9, Defb1, Defb10, and S100a8) might be useful for diagnosis of JD, including subclinical stage cases.

Establishment a real-time reverse transcription PCR based on host biomarkers for the detection of the subclinical cases of Mycobacterium avium subsp. paratuberculosis

PubMed Central

Park, Hyun-Eui; Park, Hong-Tae; Jung, Young Hoon

2017-01-01

Bovine paratuberculosis (PTB) is a chronic enteric inflammatory disease of ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP) that causes large economic losses in the dairy industry. Spread of PTB is mainly provoked by a long subclinical stage during which MAP is shed into the environment with feces; accordingly, detection of subclinical animals is very important to its control. However, current diagnostic methods are not suitable for detection of subclinical animals. Therefore, the current study was conducted to develop a diagnostic method for analysis of the expression of genes of prognostic potential biomarker candidates in the whole blood of cattle naturally infected with MAP. Real-time PCR with nine potential biomarker candidates was developed for the diagnosis of MAP subclinical infection. Animals were divided into four groups based on fecal MAP PCR and serum ELISA. Eight genes (Timp1, Hp, Serpine1, Tfrc, Mmp9, Defb1, Defb10, and S100a8) were up-regulated in MAP-infected cattle (p <0.05). Moreover, ROC analysis revealed that eight genes (Timp1, Hp, Serpine1, Tfrc, Mmp9, Defb1, Defb10, and S100a8) showed fair diagnostic performance (AUC≥0.8). Four biomarkers (Timp1, S100a8, Defb1, and Defb10) showed the highest diagnostic accuracy in the PCR positive and ELISA negative group (PN group) and three biomarkers (Tfrc, Hp, and Serpine1) showed the highest diagnostic accuracy in the PCR negative and ELISA positive group (NP group). Moreover, three biomarkers (S100a8, Hp, and Defb10) were considered the most reliable for the PCR positive and ELISA positive group (PP group). Taken together, our data suggest that real-time PCR based on eight biomarkers (Timp1, Hp, Serpine1, Tfrc, Mmp9, Defb1, Defb10, and S100a8) might be useful for diagnosis of JD, including subclinical stage cases. PMID:28542507

CsSNP: A Web-Based Tool for the Detecting of Comparative Segments SNPs.

PubMed

Wang, Yi; Wang, Shuangshuang; Zhou, Dongjie; Yang, Shuai; Xu, Yongchao; Yang, Chao; Yang, Long

2016-07-01

SNP (single nucleotide polymorphism) is a popular tool for the study of genetic diversity, evolution, and other areas. Therefore, it is necessary to develop a convenient, utility, robust, rapid, and open source detecting-SNP tool for all researchers. Since the detection of SNPs needs special software and series steps including alignment, detection, analysis and present, the study of SNPs is limited for nonprofessional users. CsSNP (Comparative segments SNP, http://biodb.sdau.edu.cn/cssnp/ ) is a freely available web tool based on the Blat, Blast, and Perl programs to detect comparative segments SNPs and to show the detail information of SNPs. The results are filtered and presented in the statistics figure and a Gbrowse map. This platform contains the reference genomic sequences and coding sequences of 60 plant species, and also provides new opportunities for the users to detect SNPs easily. CsSNP is provided a convenient tool for nonprofessional users to find comparative segments SNPs in their own sequences, and give the users the information and the analysis of SNPs, and display these data in a dynamic map. It provides a new method to detect SNPs and may accelerate related studies.

Identification of new antigen candidates for the early diagnosis of Mycobacterium avium subsp. paratuberculosis infection in goats.

PubMed

Souriau, Armel; Freret, Sandrine; Foret, Benjamin; Willemsen, Peter T J; Bakker, Douwe; Guilloteau, Laurence A

2017-12-01

Currently Mycobacterium avium subsp. paratuberculosis (MAP) infection is diagnosed through indirect tests based on the immune response induced by the infection. The antigens commonly used in IFN-γ release assays (IGRA) are purified protein derivative tuberculins (PPD). However, PPDs, lack both specificity (Sp) and sensitivity (Se) in the early phase of infection. This study investigated the potential of 16 MAP recombinant proteins and five lipids to elicit the release of IFN-γ in goats from herds with or without a history of paratuberculosis. Ten recombinant proteins were selected as potential candidates for the detection of MAP infection in young goats. They were found to detect 25 to 75% of infected shedder (IS) and infected non-shedder (INS) kids younger than 10months of age. In comparison, PPD was shown to detect only 10% of INS and no IS kids. For seven antigens, Se (21-33%) and Sp (≥90%) of IGRA were shown to be comparable with PPD at 20months old. Only three antigens were suitable candidates to detect IS adult goats, although Se was lower than that obtained with PPD. In paratuberculosis-free herds, IGRA results were negative in 97% of indoor goats and 86% of outdoor goats using the 10 antigens. However, 22 to 44% of one-year-old outdoor goats were positive suggesting that they may be infected. In conclusion, this study showed that ten MAP recombinant proteins are potential candidates for early detection of MAP infected goats. Combining these antigens could form a possible set of MAP antigens to optimize the Se of caprine IGRA. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of New Candidate Gene and EST-Based Molecular Markers for Gossypium Species

PubMed Central

Buyyarapu, Ramesh; Kantety, Ramesh V.; Yu, John Z.; Saha, Sukumar; Sharma, Govind C.

2011-01-01

New source of molecular markers accelerate the efforts in improving cotton fiber traits and aid in developing high-density integrated genetic maps. We developed new markers based on candidate genes and G. arboreum EST sequences that were used for polymorphism detection followed by genetic and physical mapping. Nineteen gene-based markers were surveyed for polymorphism detection in 26 Gossypium species. Cluster analysis generated a phylogenetic tree with four major sub-clusters for 23 species while three species branched out individually. CAP method enhanced the rate of polymorphism of candidate gene-based markers between G. hirsutum and G. barbadense. Two hundred A-genome based SSR markers were designed after datamining of G. arboreum EST sequences (Mississippi Gossypium arboreum   EST-SSR: MGAES). Over 70% of MGAES markers successfully produced amplicons while 65 of them demonstrated polymorphism between the parents of G. hirsutum and G. barbadense RIL population and formed 14 linkage groups. Chromosomal localization of both candidate gene-based and MGAES markers was assisted by euploid and hypoaneuploid CS-B analysis. Gene-based and MGAES markers were highly informative as they were designed from candidate genes and fiber transcriptome with a potential to be integrated into the existing cotton genetic and physical maps. PMID:22315588

Methodology for fast detection of false sharing in threaded scientific codes

DOEpatents

Chung, I-Hsin; Cong, Guojing; Murata, Hiroki; Negishi, Yasushi; Wen, Hui-Fang

2014-11-25

A profiling tool identifies a code region with a false sharing potential. A static analysis tool classifies variables and arrays in the identified code region. A mapping detection library correlates memory access instructions in the identified code region with variables and arrays in the identified code region while a processor is running the identified code region. The mapping detection library identifies one or more instructions at risk, in the identified code region, which are subject to an analysis by a false sharing detection library. A false sharing detection library performs a run-time analysis of the one or more instructions at risk while the processor is re-running the identified code region. The false sharing detection library determines, based on the performed run-time analysis, whether two different portions of the cache memory line are accessed by the generated binary code.

Structure-guided statistical textural distinctiveness for salient region detection in natural images.

PubMed

Scharfenberger, Christian; Wong, Alexander; Clausi, David A

2015-01-01

We propose a simple yet effective structure-guided statistical textural distinctiveness approach to salient region detection. Our method uses a multilayer approach to analyze the structural and textural characteristics of natural images as important features for salient region detection from a scale point of view. To represent the structural characteristics, we abstract the image using structured image elements and extract rotational-invariant neighborhood-based textural representations to characterize each element by an individual texture pattern. We then learn a set of representative texture atoms for sparse texture modeling and construct a statistical textural distinctiveness matrix to determine the distinctiveness between all representative texture atom pairs in each layer. Finally, we determine saliency maps for each layer based on the occurrence probability of the texture atoms and their respective statistical textural distinctiveness and fuse them to compute a final saliency map. Experimental results using four public data sets and a variety of performance evaluation metrics show that our approach provides promising results when compared with existing salient region detection approaches.

Fine-scale mapping of vector habitats using very high resolution satellite imagery: a liver fluke case-study.

PubMed

De Roeck, Els; Van Coillie, Frieke; De Wulf, Robert; Soenen, Karen; Charlier, Johannes; Vercruysse, Jozef; Hantson, Wouter; Ducheyne, Els; Hendrickx, Guy

2014-12-01

The visualization of vector occurrence in space and time is an important aspect of studying vector-borne diseases. Detailed maps of possible vector habitats provide valuable information for the prediction of infection risk zones but are currently lacking for most parts of the world. Nonetheless, monitoring vector habitats from the finest scales up to farm level is of key importance to refine currently existing broad-scale infection risk models. Using Fasciola hepatica, a parasite liver fluke, as a case in point, this study illustrates the potential of very high resolution (VHR) optical satellite imagery to efficiently and semi-automatically detect detailed vector habitats. A WorldView2 satellite image capable of <5m resolution was acquired in the spring of 2013 for the area around Bruges, Belgium, a region where dairy farms suffer from liver fluke infections transmitted by freshwater snails. The vector thrives in small water bodies (SWBs), such as ponds, ditches and other humid areas consisting of open water, aquatic vegetation and/or inundated grass. These water bodies can be as small as a few m2 and are most often not present on existing land cover maps because of their small size. We present a classification procedure based on object-based image analysis (OBIA) that proved valuable to detect SWBs at a fine scale in an operational and semi-automated way. The classification results were compared to field and other reference data such as existing broad-scale maps and expert knowledge. Overall, the SWB detection accuracy reached up to 87%. The resulting fine-scale SWB map can be used as input for spatial distribution modelling of the liver fluke snail vector to enable development of improved infection risk mapping and management advice adapted to specific, local farm situations.

Multirisk analysis along the Road 7, Mendoza Province, Argentina

NASA Astrophysics Data System (ADS)

Wick, Emmanuel; Baumann, Valérie; Michoud, Clément; Derron, Marc-Henri; Jaboyedoff, Michel; Rune Lauknes, Tom; Marengo, Hugo; Rosas, Mario

2010-05-01

The National Road 7 crosses Argentina from East to West, linking Buenos Aires to the Chile border. This road is an extremely important corridor crossing the Andes Cordillera, but it is exposed to numerous natural hazards, such as rockfalls, debris flows and snow avalanches. The study area is located in the Mendoza Province, between Potrerillos and Las Cuevas in the Chilean border. This study has for main goals to achieve a regional mapping of geohazards susceptibility along the Road 7 corridor using modern remote sensing and numerical modelling techniques completed by field investigations. The main topics are: - Detection and monitoring of deep-seated gravitational slope deformations by time-series satellite radar interferometry (InSAR) methods. The area of interest is mountainous with almost no vegetation permitting an optimized InSAR processing. Our results are based on applying the small-baseline subset (SBAS) method to a time-series of Envisat ASAR images. - Rockfalls susceptibility mapping is realized using statistical analysis of the slope angle distribution, including external knowledge on the geology and land cover, to detect the potential source areas (quantitative DEM analysis). The run-outs are assessed with numerical methods based on the shallow angle method with Conefall. A second propagation is performed using the alpha-beta methodology (3D numerical modelling) with RAS and is compared to the first one. - Debris flow susceptibility mapping is realized using DF-IGAR to detect starting and spreading areas. Slope, flow accumulations, contributive surfaces, plan curvature, geological and land use dataset are used. The spreading is simulated by a multiple flow algorithm (rules the path that the debris flow will follow) coupled to a run-out distance calculation (energy-based). - Snow avalanches susceptibility mapping is realized using DF-IGAR to map sources areas and propagations. To detect the sources areas, slope, altitude, land-use and minimum surfaces are needed. DF-IGAR simulates the spreading by means of the "Perla" methodology. Furthermore, RAS performs the spreading based on the "alpha-beta" method. All these methods are based on Aster and SRTM DEM (grid 30 m) and observations of both optical and radar satellite imagery (Aster, Quickbird, Worldview, Ikonos, Envisat ASAR) and aerial photographs. Several field campaigns are performed to calibrate the regional models with adapted parameters. Susceptibility maps of the entire area for rockfalls, debris flows and snow avalanches at a scale of 1:100'000 are created. Those maps and the field investigations are cross-checked to identify and prioritize hotspots. It appears that numerous road sectors are subject to highly active phenomena. Some mitigation works already exist but they are often under-dimensioned, inadequate or neglected. Recommendations for priority and realistic mitigation measures along the endangered road sectors identified are proposed.

A new surveillance and response tool: risk map of infected Oncomelania hupensis detected by Loop-mediated isothermal amplification (LAMP) from pooled samples.

PubMed

Tong, Qun-Bo; Chen, Rui; Zhang, Yi; Yang, Guo-Jing; Kumagai, Takashi; Furushima-Shimogawara, Rieko; Lou, Di; Yang, Kun; Wen, Li-Yong; Lu, Shao-Hong; Ohta, Nobuo; Zhou, Xiao-Nong

2015-01-01

Although schistosomiasis remains a serious health problem worldwide, significant achievements in schistosomiasis control has been made in the People's Republic of China. The disease has been eliminated in five out of 12 endemic provinces, and the prevalence in remaining endemic areas is very low and is heading toward elimination. A rapid and sensitive method for monitoring the distribution of infected Oncomelania hupensis is urgently required. We applied a loop-mediated isothermal amplification (LAMP) assay targeting 28S rDNA for the rapid and effective detection of Schistosoma japonicum DNA in infected and prepatent infected O. hupensis snails. The detection limit of the LAMP method was 100 fg of S. japonicum genomic DNA. To promote the application of the approach in the field, the LAMP assay was used to detect infection in pooled samples of field-collected snails. In the pooled sample detection, snails were collected from 28 endemic areas, and 50 snails from each area were pooled based on the maximum pool size estimation, crushed together and DNA was extracted from each pooled sample as template for the LAMP assay. Based on the formula for detection from pooled samples, the proportion of positive pooled samples and the positive proportion of O. hupensis detected by LAMP of Xima village reached 66.67% and 1.33%, while those of Heini, Hongjia, Yangjiang and Huangshan villages were 33.33% and 0.67%, and those of Tuanzhou and Suliao villages were 16.67% and 0.33%, respectively. The remaining 21 monitoring field sites gave negative results. A risk map for the transmission of schistosomiasis was constructed using ArcMap, based on the positive proportion of O. hupensis infected with S. japonicum, as detected by the LAMP assay, which will form a guide for surveillance and response strategies in high risk areas. Copyright © 2014 Elsevier B.V. All rights reserved.

Usefulness of the Poincaré maps in detection of T-wave alternans in precordial leads of standard ECG--a comparison with the spectral method.

PubMed

Ruta, J; Strumiłło, P

2001-01-01

T-wave alternans (TWA) at microvolt level is considered as an important non-invasive risk factor for sudden death. Several methods are used to measure such repolarization variations, but each of them has some limitations. The purpose of our study is to assess the usefulness of Poincaré maps, a method based on nonlinear dynamics theory, in detection of repolarization abnormalities. In 30 postinfarction patients presence of TWA in precordial ECG leads was assessed by the spectral method (SM) and by the Poincaré maps (PM). Quantitative measures of both methods: alternans voltage (AV) and alternans distance (AD) were compared using linear regression. Significant correlation between both measures (r = 0.92, p < 0.01) was found. The value of AD > or = 10 microV was accepted as significant for the presence of T-wave alternans. Poincaré mapping seems to be a useful and simple method for detection of TWA. The alternans distance equal or greater than 10 microV can be considered as a level determinative for the presence of TWA.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1983-01-01

Multispectral scanning, infrared imagery, thematic mapping, and spectroradiometry from LANDSAT, GOES, and ground based instruments are being used to determine conifer distribution, maximum and minimum temperatures, topography, and crop diseases in Michigan's lower Peninsula. Image interpretation and automatic digital processing information from LANDSAT data are employed to classify and map the coniferous forests. Radiant temperature data from GOES were compared to temperature readings from the climatological station network. Digital data from LANDSAT is being used to develop techniques for detecting, monitoring, and modeling land surface change. Improved reflectance signatures through spectroradiometry aided in the detection of viral diseases in blueberry fields and vineyards. Soil survey maps from aerial reconnaissance are included as well as information on education, conferences, and awards.

Semantic Image Based Geolocation Given a Map (Author’s Initial Manuscript)

DTIC Science & Technology

2016-09-01

novel technique for detection and identification of building facades from geo-tagged reference view using the map and geometry of the building facades. We...2D map of the environment, and geometry of building facades. We evaluate our approach for building identification and geo-localization on a new...location recognition and building identification is done by matching the query view to a reference set, followed by estimation of 3D building facades

Provisional maps of thermal areas in Yellowstone National Park, based on satellite thermal infrared imaging and field observations

USGS Publications Warehouse

Vaughan, R. Greg; Heasler, Henry; Jaworowski, Cheryl; Lowenstern, Jacob B.; Keszthelyi, Laszlo P.

2014-01-01

Maps that define the current distribution of geothermally heated ground are useful toward setting a baseline for thermal activity to better detect and understand future anomalous hydrothermal and (or) volcanic activity. Monitoring changes in the dynamic thermal areas also supports decisions regarding the development of Yellowstone National Park infrastructure, preservation and protection of park resources, and ensuring visitor safety. Because of the challenges associated with field-based monitoring of a large, complex geothermal system that is spread out over a large and remote area, satellite-based thermal infrared images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to map the location and spatial extent of active thermal areas, to generate thermal anomaly maps, and to quantify the radiative component of the total geothermal heat flux. ASTER thermal infrared data acquired during winter nights were used to minimize the contribution of solar heating of the surface. The ASTER thermal infrared mapping results were compared to maps of thermal areas based on field investigations and high-resolution aerial photos. Field validation of the ASTER thermal mapping is an ongoing task. The purpose of this report is to make available ASTER-based maps of Yellowstone’s thermal areas. We include an appendix containing the names and characteristics of Yellowstone’s thermal areas, georeferenced TIFF files containing ASTER thermal imagery, and several spatial data sets in Esri shapefile format.

'Nano-immuno test' for the detection of live Mycobacterium avium subspecies paratuberculosis bacilli in the milk samples using magnetic nano-particles and chromogen.

PubMed

Singh, Manju; Singh, Shoor Vir; Gupta, Saurabh; Chaubey, Kundan Kumar; Stephan, Bjorn John; Sohal, Jagdip Singh; Dutta, Manali

2018-04-26

Early rapid detection of Mycobacterium avium subspecies paratuberculosis (MAP) bacilli in milk samples is the major challenge since traditional culture method is time consuming and laboratory dependent. We report a simple, sensitive and specific nano-technology based 'Nano-immuno test' capable of detecting viable MAP bacilli in the milk samples within 10 h. Viable MAP bacilli were captured by MAP specific antibody-conjugated magnetic nano-particles using resazurin dye as chromogen. Test was optimized using true culture positive (10-bovine and 12-goats) and true culture negative (16-bovine and 25-goats) raw milk samples. Domestic livestock species in India are endemically infected with MAP. After successful optimization, sensitivity and specificity of the 'nano-immuno test' in goats with respect to milk culture was 91.7% and 96.0%, respectively. Whereas, it was 90.0% (sensitivity) and 92.6% (specificity) with respect to IS900 PCR. In bovine milk samples, sensitivity and specificity of 'nano-immuno test' with respect to milk culture was 90.0% and 93.7%, respectively. However, with respect to IS900 PCR, the sensitivity and specificity was 88.9% and 94.1%, respectively. Test was validated with field raw milk samples (goats-258 and bovine-138) collected from domestic livestock species to detect live/viable MAP bacilli. Of 138 bovine raw milk samples screened by six diagnostic tests, 81 (58.7%) milk samples were positive for MAP infection in one or more than one diagnostic tests. Of 81 (58.7%) positive bovine raw milk samples, only 24 (17.4%) samples were detected positive for the presence of viable MAP bacilli. Of 258 goats raw milk samples screened by six diagnostic tests, 141 (54.6%) were positive for MAP infection in one or more than one test. Of 141 (54.6%) positive raw milk samples from goats, only 48 (34.0%) were detected positive for live MAP bacilli. Simplicity and efficiency of this novel 'nano-immuno test' makes it suitable for wide-scale screening of milk samples in the field. Standardization, validation and re-usability of functionalized nano-particles and the test was successfully achieved in field samples. Test was highly specific, simple to perform and easy to read by naked eyes and does not require laboratory support in the performance of test. Test has potential to be used as screening test to estimate bio-load of MAP in milk samples at National level.

Deconvolution single shot multibox detector for supermarket commodity detection and classification

NASA Astrophysics Data System (ADS)

Li, Dejian; Li, Jian; Nie, Binling; Sun, Shouqian

2017-07-01

This paper proposes an image detection model to detect and classify supermarkets shelves' commodity. Based on the principle of the features directly affects the accuracy of the final classification, feature maps are performed to combine high level features with bottom level features. Then set some fixed anchors on those feature maps, finally the label and the position of commodity is generated by doing a box regression and classification. In this work, we proposed a model named Deconvolutiuon Single Shot MultiBox Detector, we evaluated the model using 300 images photographed from real supermarket shelves. Followed the same protocol in other recent methods, the results showed that our model outperformed other baseline methods.

Infrared small target detection based on multiscale center-surround contrast measure

NASA Astrophysics Data System (ADS)

Fu, Hao; Long, Yunli; Zhu, Ran; An, Wei

2018-04-01

Infrared(IR) small target detection plays a critical role in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some difficulties remained to the clutter environment. According to the principle of human discrimination of small targets from a natural scene that there is a signature of discontinuity between the object and its neighboring regions, we develop an efficient method for infrared small target detection called multiscale centersurround contrast measure (MCSCM). First, to determine the maximum neighboring window size, an entropy-based window selection technique is used. Then, we construct a novel multiscale center-surround contrast measure to calculate the saliency map. Compared with the original image, the MCSCM map has less background clutters and noise residual. Subsequently, a simple threshold is used to segment the target. Experimental results show our method achieves better performance.

Urban forest topographical mapping using UAV LIDAR

NASA Astrophysics Data System (ADS)

Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi

2017-12-01

Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

A Probabilistic Model of Illegal Drug Trafficking Operations in the Eastern Pacific and Caribbean Sea

DTIC Science & Technology

2013-09-01

partner agencies and nations, detects, tracks, and interdicts illegal drug-trafficking in this region. In this thesis, we develop a probability model based...trafficking in this region. In this thesis, we develop a probability model based on intelligence inputs to generate a spatial temporal heat map specifying the...complement and vet such complicated simulation by developing more analytically tractable models. We develop probability models to generate a heat map

Uav-Based Detection of Unknown Radioactive Biomass Deposits in Chernobyl's Exclusion Zone

NASA Astrophysics Data System (ADS)

Briechle, S.; Sizov, A.; Tretyak, O.; Antropov, V.; Molitor, N.; Krzystek, P.

2018-05-01

Shortly after the explosion of the Chernobyl nuclear power plant (ChNPP) in 1986, radioactive fall-out and contaminated trees (socalled Red Forest) were buried in the Chernobyl Exclusion Zone (ChEZ). These days, exact locations of the buried contaminated material are needed. Moreover, 3D vegetation maps are necessary to simulate the impact of tornados and forest fire. After 30 years, some of the so-called trenches and clamps are visible. However, some of them are overgrown and have slightly settled in the centimeter and decimeter range. This paper presents a pipeline that comprises 3D vegetation mapping and machine learning methods to precisely map trenches and clamps from remote sensing data. The dataset for our experiments consists of UAV-based LiDAR data, multi-spectral data, and aerial gamma-spectrometry data. Depending on the study areas overall accuracies ranging from 95.6 % to 99.0 % were reached for the classification of radioactive deposits. Our first results demonstrate an accurate and reliable UAV-based detection of unknown radioactive biomass deposits in the ChEZ.

An Auscultaiting Diagnosis Support System for Assessing Hemodialysis Shunt Stenosis by Using Self-organizing Map

NASA Astrophysics Data System (ADS)

Suzuki, Yutaka; Fukasawa, Mizuya; Sakata, Osamu; Kato, Hatsuhiro; Hattori, Asobu; Kato, Takaya

Vascular access for hemodialysis is a lifeline for over 280,000 chronic renal failure patients in Japan. Early detection of stenosis may facilitate long-term use of hemodialysis shunts. Stethoscope auscultation of vascular murmurs has some utility in the assessment of access patency; however, the sensitivity of this diagnostic approach is skill dependent. This study proposes a novel diagnosis support system to detect stenosis by using vascular murmurs. The system is based on a self-organizing map (SOM) and short-time maximum entropy method (STMEM) for data analysis. SOM is an artificial neural network, which is trained using unsupervised learning to produce a feature map that is useful for visualizing the analogous relationship between input data. The author recorded vascular murmurs before and after percutaneous transluminal angioplasty (PTA). The SOM-based classification was consistent with to the classification based on MEM spectral and spectrogram characteristics. The ratio of pre-PTA murmurs in the stenosis category was much higher than the post-PTA murmurs. The results suggest that the proposed method may be an effective tool in the determination of shunt stenosis.

Comparison between genetic algorithm and self organizing map to detect botnet network traffic

NASA Astrophysics Data System (ADS)

Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

2017-11-01

In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

AlphaSpace: Fragment-Centric Topographical Mapping To Target Protein–Protein Interaction Interfaces

PubMed Central

2016-01-01

Inhibition of protein–protein interactions (PPIs) is emerging as a promising therapeutic strategy despite the difficulty in targeting such interfaces with drug-like small molecules. PPIs generally feature large and flat binding surfaces as compared to typical drug targets. These features pose a challenge for structural characterization of the surface using geometry-based pocket-detection methods. An attractive mapping strategy—that builds on the principles of fragment-based drug discovery (FBDD)—is to detect the fragment-centric modularity at the protein surface and then characterize the large PPI interface as a set of localized, fragment-targetable interaction regions. Here, we introduce AlphaSpace, a computational analysis tool designed for fragment-centric topographical mapping (FCTM) of PPI interfaces. Our approach uses the alpha sphere construct, a geometric feature of a protein’s Voronoi diagram, to map out concave interaction space at the protein surface. We introduce two new features—alpha-atom and alpha-space—and the concept of the alpha-atom/alpha-space pair to rank pockets for fragment-targetability and to facilitate the evaluation of pocket/fragment complementarity. The resulting high-resolution interfacial map of targetable pocket space can be used to guide the rational design and optimization of small molecule or biomimetic PPI inhibitors. PMID:26225450

Using Land Surface Phenology as the Basis for a National Early Warning System for Forest Disturbances

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Spruce, J.; Norman, S. P.; Hoffman, F. M.

2011-12-01

The National Early Warning System (EWS) provides an 8-day coast-to-coast snapshot of potentially disturbed forests across the U.S.. A prototype system has produced national maps of potential forest disturbances every eight days since January 2010, identifying locations that may require further investigation. Through phenology, the system shows both early and delayed vegetation development and detects all types of unexpected forest disturbances, including insects, disease, wildfires, frost and ice damage, tornadoes, hurricanes, blowdowns, harvest, urbanization, landslides, drought, flood, and climate change. The USDA Forest Service Eastern Forest Environmental Threat Assessment Center is collaborating with NASA Stennis Space Center and the Western Wildland Environmental Threat Assessment Center to develop the tool. The EWS uses differences in phenological responses between an expectation based on historical data and a current view to strategically identify potential forest disturbances and direct attention to locations where forest behavior seems unusual. Disturbance maps are available via the Forest Change Assessment Viewer (FCAV) (http://ews.forestthreats.org/gis), which allows resource managers and other users to see the most current national disturbance maps as soon as they are available. Phenology-based detections show not only vegetation disturbances in the classical sense, but all departures from normal seasonal vegetation behavior. In 2010, the EWS detected a repeated late-frost event at high elevations in North Carolina, USA, that resulted in delayed seasonal development, contrasting with an early spring development at lower elevations, all within close geographic proximity. Throughout 2011, there was a high degree of correspondence between the National Climatic Data Center's North American Drought Monitor maps and EWS maps of phenological drought disturbance in forests. Urban forests showed earlier and more severe phenological drought disturbance than surrounding non-urban forests. An EWS news page (http://www.geobabbble.org/~hnw/EWSNews) highlights disturbances the system has detected during the 2011 season. Unsupervised statistical multivariate clustering of smoothed phenology data every 8 days over an 11-year period produces a detailed map of national vegetation types, including major disturbances. Examining the constancy of these phenological classifications at a particular location from year to year produces a national map showing the persistence of vegetation, regardless of vegetation type. Using spectral unmixing methods, national maps of evergreen decline can be produced which are a composite of insect, disease, and anthropogenic factors causing chronic decline in these forests, including hemlock wooly adelgid, mountain pine beetle, wildfire, tree harvest, and urbanization. Because phenology shows vegetation responses, all disturbance and recovery events detected by the EWS are viewed through the lens of the vegetation.

Geographic applications of ERTS-1 imagery to landscape change. [Mississippi River and Great Smoky Mountains of Tennessee and North Carolina

NASA Technical Reports Server (NTRS)

Rehder, J. B. (Principal Investigator)

1973-01-01

The author has identified the following significant results. ERTS-1 has proven to be an effective earth-orbiting monitor of landscape change. Its regional coverage for large areal monitoring has been effective for the detection and mapping of agricultural plowing regions, for general forest cover mapping, for flood mapping, for strip mine mapping, and for short-lived precipitation mapping patterns. Paramount to the entire study has been the temporal coverage provided by ERTS. Without the cyclic coverage on an 18 day basis, temporal coverage would have been inadequate for the detection and mapping of strip mining landscape change, the analysis of agricultural landscape change based on plowing patterns, the analysis of urban-suburban growth changes, and the mapping of the Mississippi River floods. Cost benefits from ERTS are unquestionably superior to aircraft systems in regard to large regional coverage and cyclic temporal parameters. For the analysis of landscape change in large regions such as statewide areas or even areas of 10,000 square miles, ERTS is of cost benefit consideration. Not only does the cost of imagery favor ERTS but the reduction of man-hours using ERTS has been in the magnitude of 1:10.

Real-time detection of transients in OGLE-IV with application of machine learning

NASA Astrophysics Data System (ADS)

Klencki, Jakub; Wyrzykowski, Łukasz

2016-06-01

The current bottleneck of transient detection in most surveys is the problem of rejecting numerous artifacts from detected candidates. We present a triple-stage hierarchical machine learning system for automated artifact filtering in difference imaging, based on self-organizing maps. The classifier, when tested on the OGLE-IV Transient Detection System, accepts 97% of real transients while removing up to 97.5% of artifacts.

Building phenotype networks to improve QTL detection: a comparative analysis of fatty acid and fat traits in pigs.

PubMed

Yang, B; Navarro, N; Noguera, J L; Muñoz, M; Guo, T F; Yang, K X; Ma, J W; Folch, J M; Huang, L S; Pérez-Enciso, M

2011-10-01

Models in QTL mapping can be improved by considering all potential variables, i.e. we can use remaining traits other than the trait under study as potential predictors. QTL mapping is often conducted by correcting for a few fixed effects or covariates (e.g. sex, age), although many traits with potential causal relationships between them are recorded. In this work, we evaluate by simulation several procedures to identify optimum models in QTL scans: forward selection, undirected dependency graph and QTL-directed dependency graph (QDG). The latter, QDG, performed better in terms of power and false discovery rate and was applied to fatty acid (FA) composition and fat deposition traits in two pig F2 crosses from China and Spain. Compared with the typical QTL mapping, QDG approach revealed several new QTL. To the contrary, several FA QTL on chromosome 4 (e.g. Palmitic, C16:0; Stearic, C18:0) detected by typical mapping vanished after adjusting for phenotypic covariates in QDG mapping. This suggests that the QTL detected in typical mapping could be indirect. When a QTL is supported by both approaches, there is an increased confidence that the QTL have a primary effect on the corresponding trait. An example is a QTL for C16:1 on chromosome 8. In conclusion, mapping QTL based on causal phenotypic networks can increase power and help to make more biologically sound hypothesis on the genetic architecture of complex traits. © 2011 Blackwell Verlag GmbH.

Video Altimeter and Obstruction Detector for an Aircraft

NASA Technical Reports Server (NTRS)

Delgado, Frank J.; Abernathy, Michael F.; White, Janis; Dolson, William R.

2013-01-01

Video-based altimetric and obstruction detection systems for aircraft have been partially developed. The hardware of a system of this type includes a downward-looking video camera, a video digitizer, a Global Positioning System receiver or other means of measuring the aircraft velocity relative to the ground, a gyroscope based or other attitude-determination subsystem, and a computer running altimetric and/or obstruction-detection software. From the digitized video data, the altimetric software computes the pixel velocity in an appropriate part of the video image and the corresponding angular relative motion of the ground within the field of view of the camera. Then by use of trigonometric relationships among the aircraft velocity, the attitude of the camera, the angular relative motion, and the altitude, the software computes the altitude. The obstruction-detection software performs somewhat similar calculations as part of a larger task in which it uses the pixel velocity data from the entire video image to compute a depth map, which can be correlated with a terrain map, showing locations of potential obstructions. The depth map can be used as real-time hazard display and/or to update an obstruction database.

1H-detected MAS solid-state NMR experiments enable the simultaneous mapping of rigid and dynamic domains of membrane proteins

NASA Astrophysics Data System (ADS)

Gopinath, T.; Nelson, Sarah E. D.; Veglia, Gianluigi

2017-12-01

Magic angle spinning (MAS) solid-state NMR (ssNMR) spectroscopy is emerging as a unique method for the atomic resolution structure determination of native membrane proteins in lipid bilayers. Although 13C-detected ssNMR experiments continue to play a major role, recent technological developments have made it possible to carry out 1H-detected experiments, boosting both sensitivity and resolution. Here, we describe a new set of 1H-detected hybrid pulse sequences that combine through-bond and through-space correlation elements into single experiments, enabling the simultaneous detection of rigid and dynamic domains of membrane proteins. As proof-of-principle, we applied these new pulse sequences to the membrane protein phospholamban (PLN) reconstituted in lipid bilayers under moderate MAS conditions. The cross-polarization (CP) based elements enabled the detection of the relatively immobile residues of PLN in the transmembrane domain using through-space correlations; whereas the most dynamic region, which is in equilibrium between folded and unfolded states, was mapped by through-bond INEPT-based elements. These new 1H-detected experiments will enable one to detect not only the most populated (ground) states of biomacromolecules, but also sparsely populated high-energy (excited) states for a complete characterization of protein free energy landscapes.

Surface plasmon holographic microscopy for near-field refractive index detection and thin film mapping

NASA Astrophysics Data System (ADS)

Zhao, Jianlin; Zhang, Jiwei; Dai, Siqing; Di, Jianglei; Xi, Teli

2018-02-01

Surface plasmon microscopy (SPM) is widely applied for label-free detection of changes of refractive index and concentration, as well as mapping thin films in near field. Traditionally, the SPM systems are based on the detection of light intensity or phase changes. Here, we present two kinds of surface plasmon holographic microscopy (SPHM) systems for amplitude- and phase-contrast imaging simultaneously. Through recording off-axis holograms and numerical reconstruction, the complex amplitude distributions of surface plasmon resonance (SPR) images can be obtained. According to the Fresnel's formula, in a prism/ gold/ dielectric structure, the reflection phase shift is uniquely decided by refractive index of the dielectric. By measuring the phase shift difference of the reflected light exploiting prism-coupling SPHM system based on common-path interference configuration, monitoring tiny refractive index variation and imaging biological tissue are performed. Furthermore, to characterize the thin film thickness in near field, we employ a four-layer SPR model in which the third film layer is within the evanescent field. The complex reflection coefficient, including the reflectivity and reflection phase shift, is uniquely decided by the film thickness. By measuring the complex amplitude distributions of the SPR images exploiting objective-coupling SPHM system based on common-path interference configuration, the thickness distributions of thin films are mapped with sub-nanometer resolution theoretically. Owing to its high temporal stability, the recommended SPHMs show great potentials for monitoring tiny refractive index variations, imaging biological tissues and mapping thin films in near field with dynamic, nondestructive and full-field measurement capabilities in chemistry, biomedicine field, etc.

Phenology-based Spartina alterniflora mapping in coastal wetland of the Yangtze Estuary using time series of GaoFen satellite no. 1 wide field of view imagery

NASA Astrophysics Data System (ADS)

Ai, Jinquan; Gao, Wei; Gao, Zhiqiang; Shi, Runhe; Zhang, Chao

2017-04-01

Spartina alterniflora is an aggressive invasive plant species that replaces native species, changes the structure and function of the ecosystem across coastal wetlands in China, and is thus a major conservation concern. Mapping the spread of its invasion is a necessary first step for the implementation of effective ecological management strategies. The performance of a phenology-based approach for S. alterniflora mapping is explored in the coastal wetland of the Yangtze Estuary using a time series of GaoFen satellite no. 1 wide field of view camera (GF-1 WFV) imagery. First, a time series of the normalized difference vegetation index (NDVI) was constructed to evaluate the phenology of S. alterniflora. Two phenological stages (the senescence stage from November to mid-December and the green-up stage from late April to May) were determined as important for S. alterniflora detection in the study area based on NDVI temporal profiles, spectral reflectance curves of S. alterniflora and its coexistent species, and field surveys. Three phenology feature sets representing three major phenology-based detection strategies were then compared to map S. alterniflora: (1) the single-date imagery acquired within the optimal phenological window, (2) the multitemporal imagery, including four images from the two important phenological windows, and (3) the monthly NDVI time series imagery. Support vector machines and maximum likelihood classifiers were applied on each phenology feature set at different training sample sizes. For all phenology feature sets, the overall results were produced consistently with high mapping accuracies under sufficient training samples sizes, although significantly improved classification accuracies (10%) were obtained when the monthly NDVI time series imagery was employed. The optimal single-date imagery had the lowest accuracies of all detection strategies. The multitemporal analysis demonstrated little reduction in the overall accuracy compared with the use of monthly NDVI time series imagery. These results show the importance of considering the phenological stage for image selection for mapping S. alterniflora using GF-1 WFV imagery. Furthermore, in light of the better tradeoff between the number of images and classification accuracy when using multitemporal GF-1 WFV imagery, we suggest using multitemporal imagery acquired at appropriate phenological windows for S. alterniflora mapping at regional scales.

a New Object-Based Framework to Detect Shodows in High-Resolution Satellite Imagery Over Urban Areas

NASA Astrophysics Data System (ADS)

Tatar, N.; Saadatseresht, M.; Arefi, H.; Hadavand, A.

2015-12-01

In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.

Surface materials map of Afghanistan: iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Kokaly, Raymond F.; Hoefen, Todd M.; Dudek, Kathleen B.; Livo, Keith E.

2012-01-01

This map shows the distribution of selected iron-bearing minerals and other materials derived from analysis of HyMap imaging spectrometer data of Afghanistan. Using a NASA (National Aeronautics and Space Administration) WB-57 aircraft flown at an altitude of ~15,240 meters or ~50,000 feet, 218 flight lines of data were collected over Afghanistan between August 22 and October 2, 2007. The HyMap data were converted to apparent surface reflectance, then further empirically adjusted using ground-based reflectance measurements. The reflectance spectrum of each pixel of HyMap data was compared to the spectral features of reference entries in a spectral library of minerals, vegetation, water, ice, and snow. This map shows the spatial distribution of iron-bearing minerals and other materials having diagnostic absorptions at visible and near-infrared wavelengths. These absorptions result from electronic processes in the minerals. Several criteria, including (1) the reliability of detection and discrimination of minerals using the HyMap spectrometer data, (2) the relative abundance of minerals, and (3) the importance of particular minerals to studies of Afghanistan's natural resources, guided the selection of entries in the reference spectral library and, therefore, guided the selection of mineral classes shown on this map. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated. Minerals having similar spectral features were less easily discriminated, especially where the minerals were not particularly abundant and (or) where vegetation cover reduced the absorption strength of mineral features. Complications in reflectance calibration also affected the detection and identification of minerals.

Surface materials map of Afghanistan: carbonates, phyllosilicates, sulfates, altered minerals, and other materials

USGS Publications Warehouse

Kokaly, Raymond F.; King, Trude V.V.; Hoefen, Todd M.; Dudek, Kathleen B.; Livo, Keith E.

2012-01-01

This map shows the distribution of selected carbonates, phyllosilicates, sulfates, altered minerals, and other materials derived from analysis of HyMap imaging spectrometer data of Afghanistan. Using a NASA (National Aeronautics and Space Administration) WB-57 aircraft flown at an altitude of ~15,240 meters or ~50,000 feet, 218 flight lines of data were collected over Afghanistan between August 22 and October 2, 2007. The HyMap data were converted to apparent surface reflectance, then further empirically adjusted using ground-based reflectance measurements. The reflectance spectrum of each pixel of HyMap data was compared to the spectral features of reference entries in a spectral library of minerals, vegetation, water, ice, and snow. This map shows the spatial distribution of minerals that have diagnostic absorption features in the shortwave infrared wavelengths. These absorption features result primarily from characteristic chemical bonds and mineralogical vibrations. Several criteria, including (1) the reliability of detection and discrimination of minerals using the HyMap spectrometer data, (2) the relative abundance of minerals, and (3) the importance of particular minerals to studies of Afghanistan's natural resources, guided the selection of entries in the reference spectral library and, therefore, guided the selection of mineral classes shown on this map. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated. Minerals having similar spectral features were less easily discriminated, especially where the minerals were not particularly abundant and (or) where vegetation cover reduced the absorption strength of mineral features. Complications in reflectance calibration also affected the detection and identification of minerals.

Automatic Pedestrian Crossing Detection and Impairment Analysis Based on Mobile Mapping System

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, Y.; Li, Q.

2017-09-01

Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians' lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

Probabilistic model for quick detection of dissimilar binary images

NASA Astrophysics Data System (ADS)

Mustafa, Adnan A. Y.

2015-09-01

We present a quick method to detect dissimilar binary images. The method is based on a "probabilistic matching model" for image matching. The matching model is used to predict the probability of occurrence of distinct-dissimilar image pairs (completely different images) when matching one image to another. Based on this model, distinct-dissimilar images can be detected by matching only a few points between two images with high confidence, namely 11 points for a 99.9% successful detection rate. For image pairs that are dissimilar but not distinct-dissimilar, more points need to be mapped. The number of points required to attain a certain successful detection rate or confidence depends on the amount of similarity between the compared images. As this similarity increases, more points are required. For example, images that differ by 1% can be detected by mapping fewer than 70 points on average. More importantly, the model is image size invariant; so, images of any sizes will produce high confidence levels with a limited number of matched points. As a result, this method does not suffer from the image size handicap that impedes current methods. We report on extensive tests conducted on real images of different sizes.

An incremental anomaly detection model for virtual machines.

PubMed

Zhang, Hancui; Chen, Shuyu; Liu, Jun; Zhou, Zhen; Wu, Tianshu

2017-01-01

Self-Organizing Map (SOM) algorithm as an unsupervised learning method has been applied in anomaly detection due to its capabilities of self-organizing and automatic anomaly prediction. However, because of the algorithm is initialized in random, it takes a long time to train a detection model. Besides, the Cloud platforms with large scale virtual machines are prone to performance anomalies due to their high dynamic and resource sharing characters, which makes the algorithm present a low accuracy and a low scalability. To address these problems, an Improved Incremental Self-Organizing Map (IISOM) model is proposed for anomaly detection of virtual machines. In this model, a heuristic-based initialization algorithm and a Weighted Euclidean Distance (WED) algorithm are introduced into SOM to speed up the training process and improve model quality. Meanwhile, a neighborhood-based searching algorithm is presented to accelerate the detection time by taking into account the large scale and high dynamic features of virtual machines on cloud platform. To demonstrate the effectiveness, experiments on a common benchmark KDD Cup dataset and a real dataset have been performed. Results suggest that IISOM has advantages in accuracy and convergence velocity of anomaly detection for virtual machines on cloud platform.

An incremental anomaly detection model for virtual machines

PubMed Central

Zhang, Hancui; Chen, Shuyu; Liu, Jun; Zhou, Zhen; Wu, Tianshu

2017-01-01

Self-Organizing Map (SOM) algorithm as an unsupervised learning method has been applied in anomaly detection due to its capabilities of self-organizing and automatic anomaly prediction. However, because of the algorithm is initialized in random, it takes a long time to train a detection model. Besides, the Cloud platforms with large scale virtual machines are prone to performance anomalies due to their high dynamic and resource sharing characters, which makes the algorithm present a low accuracy and a low scalability. To address these problems, an Improved Incremental Self-Organizing Map (IISOM) model is proposed for anomaly detection of virtual machines. In this model, a heuristic-based initialization algorithm and a Weighted Euclidean Distance (WED) algorithm are introduced into SOM to speed up the training process and improve model quality. Meanwhile, a neighborhood-based searching algorithm is presented to accelerate the detection time by taking into account the large scale and high dynamic features of virtual machines on cloud platform. To demonstrate the effectiveness, experiments on a common benchmark KDD Cup dataset and a real dataset have been performed. Results suggest that IISOM has advantages in accuracy and convergence velocity of anomaly detection for virtual machines on cloud platform. PMID:29117245

(Semi-)Automated landform mapping of the alpine valley Gradental (Austria) based on LiDAR data

NASA Astrophysics Data System (ADS)

Strasser, T.; Eisank, C.

2012-04-01

Alpine valleys are typically characterised as complex, hierarchical structured systems with rapid landform changes. Detection of landform changes can be supported by automated geomorphological mapping. Especially, the analysis over short time scales require a method for standardised, unbiased geomorphological map reproduction, which is delivered by automated mapping techniques. In general, digital geomorphological mapping is a challenging task, since knowledge about landforms with respect to their natural boundaries as well as their hierarchical and scaling relationships, has to be integrated in an objective way. A combination of very-high spatial resolution data (VHSR) such as LiDAR and new methods like object based image analysis (OBIA) allow for a more standardised production of geomorphological maps. In OBIA the processing units are spatially configured objects that are created by multi-scale segmentation. Therefore, not only spectral information can be used for assigning the objects to geomorphological classes, but also spatial and topological properties can be exploited. In this study we focus on the detection of landforms, especially bedrock sediment deposits (alluvion, debris cone, talus, moraine, rockglacier), as well as glaciers. The study site Gradental [N 46°58'29.1"/ E 12°48'53.8"] is located in the Schobergruppe (Austria, Carinthia) and is characterised by heterogenic geology conditions and high process activity. The area is difficult to access and dominated by steep slopes, thus hindering a fast and detailed geomorphological field mapping. Landforms are identified using aerial and terrestrial LiDAR data (1 m spatial resolution). These DEMs are analysed by an object based hierarchical approach, which is structured in three main steps. The first step is to define occurring landforms by basic land surface parameters (LSPs), topology and hierarchy relations. Based on those definitions a semantic model is created. Secondly, a multi-scale segmentation is performed on a three-band LSP that integrates slope, aspect and plan curvature, which expresses the driving forces of geomorphological processes. In the third step, the generated multi-level object structures are classified in order to produce the geomorphological map. The classification rules are derived from the semantic model. Due to landform type-specific scale dependencies of LSPs, the values of LSPs used in the classification are calculated in a multi-scale manner by constantly enlarging the size of the moving window. In addition, object form properties (density, compactness, rectangular fit) are utilised as additional information for landform characterisation. Validation of classification is performed by intersecting a visually interpreted reference map with the classification output map and calculating accuracy matrices. Validation shows an overall accuracy of 78.25 % and a Kappa of 0.65. The natural borders of landforms can be easily detected by the use of slope, aspect and plan curvature. This study illustrates the potential of OBIA for a more standardised and automated mapping of surface units (landforms, landcover). Therefore, the presented methodology features a prospective automated geomorphological mapping approach for alpine regions.

High-resolution Antibody Array Analysis of Childhood Acute Leukemia Cells*

PubMed Central

Kanderova, Veronika; Kuzilkova, Daniela; Stuchly, Jan; Vaskova, Martina; Brdicka, Tomas; Fiser, Karel; Hrusak, Ondrej; Lund-Johansen, Fridtjof

2016-01-01

Acute leukemia is a disease pathologically manifested at both genomic and proteomic levels. Molecular genetic technologies are currently widely used in clinical research. In contrast, sensitive and high-throughput proteomic techniques for performing protein analyses in patient samples are still lacking. Here, we used a technology based on size exclusion chromatography followed by immunoprecipitation of target proteins with an antibody bead array (Size Exclusion Chromatography-Microsphere-based Affinity Proteomics, SEC-MAP) to detect hundreds of proteins from a single sample. In addition, we developed semi-automatic bioinformatics tools to adapt this technology for high-content proteomic screening of pediatric acute leukemia patients. To confirm the utility of SEC-MAP in leukemia immunophenotyping, we tested 31 leukemia diagnostic markers in parallel by SEC-MAP and flow cytometry. We identified 28 antibodies suitable for both techniques. Eighteen of them provided excellent quantitative correlation between SEC-MAP and flow cytometry (p < 0.05). Next, SEC-MAP was applied to examine 57 diagnostic samples from patients with acute leukemia. In this assay, we used 632 different antibodies and detected 501 targets. Of those, 47 targets were differentially expressed between at least two of the three acute leukemia subgroups. The CD markers correlated with immunophenotypic categories as expected. From non-CD markers, we found DBN1, PAX5, or PTK2 overexpressed in B-cell precursor acute lymphoblastic leukemias, LAT, SH2D1A, or STAT5A overexpressed in T-cell acute lymphoblastic leukemias, and HCK, GLUD1, or SYK overexpressed in acute myeloid leukemias. In addition, OPAL1 overexpression corresponded to ETV6-RUNX1 chromosomal translocation. In summary, we demonstrated that SEC-MAP technology is a powerful tool for detecting hundreds of proteins in clinical samples obtained from pediatric acute leukemia patients. It provides information about protein size and reveals differences in protein expression between particular leukemia subgroups. Forty-seven of SEC-MAP identified targets were validated by other conventional method in this study. PMID:26785729

Mapping accuracy via spectrally and structurally based filtering techniques: comparisons through visual observations

NASA Astrophysics Data System (ADS)

Chockalingam, Letchumanan

2005-01-01

The data of Gunung Ledang region of Malaysia acquired through LANDSAT are considered to map certain hydrogeolocial features. To map these significant features, image-processing tools such as contrast enhancement, edge detection techniques are employed. The advantages of these techniques over the other methods are evaluated from the point of their validity in properly isolating features of hydrogeolocial interest are discussed. As these techniques take the advantage of spectral aspects of the images, these techniques have several limitations to meet the objectives. To discuss these limitations, a morphological transformation, which generally considers the structural aspects rather than spectral aspects from the image, are applied to provide comparisons between the results derived from spectral based and the structural based filtering techniques.

Improving the extraction of crisis information in the context of flood, fire, and landslide rapid mapping using SAR and optical remote sensing data

NASA Astrophysics Data System (ADS)

Martinis, Sandro; Clandillon, Stephen; Twele, André; Huber, Claire; Plank, Simon; Maxant, Jérôme; Cao, Wenxi; Caspard, Mathilde; May, Stéphane

2016-04-01

Optical and radar satellite remote sensing have proven to provide essential crisis information in case of natural disasters, humanitarian relief activities and civil security issues in a growing number of cases through mechanisms such as the Copernicus Emergency Management Service (EMS) of the European Commission or the International Charter 'Space and Major Disasters'. The aforementioned programs and initiatives make use of satellite-based rapid mapping services aimed at delivering reliable and accurate crisis information after natural hazards. Although these services are increasingly operational, they need to be continuously updated and improved through research and development (R&D) activities. The principal objective of ASAPTERRA (Advancing SAR and Optical Methods for Rapid Mapping), the ESA-funded R&D project being described here, is to improve, automate and, hence, speed-up geo-information extraction procedures in the context of natural hazards response. This is performed through the development, implementation, testing and validation of novel image processing methods using optical and Synthetic Aperture Radar (SAR) data. The methods are mainly developed based on data of the German radar satellites TerraSAR-X and TanDEM-X, the French satellite missions Pléiades-1A/1B as well as the ESA missions Sentinel-1/2 with the aim to better characterize the potential and limitations of these sensors and their synergy. The resulting algorithms and techniques are evaluated in real case applications during rapid mapping activities. The project is focussed on three types of natural hazards: floods, landslides and fires. Within this presentation an overview of the main methodological developments in each topic is given and demonstrated in selected test areas. The following developments are presented in the context of flood mapping: a fully automated Sentinel-1 based processing chain for detecting open flood surfaces, a method for the improved detection of flooded vegetation in Sentinel-1data using Entropy/Alpha decomposition, unsupervised Wishart Classification, and object-based post-classification as well as semi-automatic approaches for extracting inundated areas and flood traces in rural and urban areas from VHR and HR optical imagery using machine learning techniques. Methodological developments related to fires are the implementation of fast and robust methods for mapping burnt scars using change detection procedures using SAR (Sentinel-1, TerraSAR-X) and HR optical (e.g. SPOT, Sentinel-2) data as well as the extraction of 3D surface and volume change information from Pléiades stereo-pairs. In the context of landslides, fast and transferable change detection procedures based on SAR (TerraSAR-X) and optical (SPOT) data as well methods for extracting the extent of landslides only based on polarimetric VHR SAR (TerraSAR-X) data are presented.

Medical Image Fusion Based on Feature Extraction and Sparse Representation

PubMed Central

Wei, Gao; Zongxi, Song

2017-01-01

As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information. SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. The decision map is added to the normal sparse representation based method to improve the speed of the algorithm. Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images. The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods. PMID:28321246

Mapping of a major QTL for salt tolerance of mature field-grown maize plants based on SNP markers.

PubMed

Luo, Meijie; Zhao, Yanxin; Zhang, Ruyang; Xing, Jinfeng; Duan, Minxiao; Li, Jingna; Wang, Naishun; Wang, Wenguang; Zhang, Shasha; Chen, Zhihui; Zhang, Huasheng; Shi, Zi; Song, Wei; Zhao, Jiuran

2017-08-15

Salt stress significantly restricts plant growth and production. Maize is an important food and economic crop but is also a salt sensitive crop. Identification of the genetic architecture controlling salt tolerance facilitates breeders to select salt tolerant lines. However, the critical quantitative trait loci (QTLs) responsible for the salt tolerance of field-grown maize plants are still unknown. To map the main genetic factors contributing to salt tolerance in mature maize, a double haploid population (240 individuals) and 1317 single nucleotide polymorphism (SNP) markers were employed to produce a genetic linkage map covering 1462.05 cM. Plant height of mature maize cultivated in the saline field (SPH) and plant height-based salt tolerance index (ratio of plant height between saline and control fields, PHI) were used to evaluate salt tolerance of mature maize plants. A major QTL for SPH was detected on Chromosome 1 with the LOD score of 22.4, which explained 31.2% of the phenotypic variation. In addition, the major QTL conditioning PHI was also mapped at the same position on Chromosome 1, and two candidate genes involving in ion homeostasis were identified within the confidence interval of this QTL. The detection of the major QTL in adult maize plant establishes the basis for the map-based cloning of genes associated with salt tolerance and provides a potential target for marker assisted selection in developing maize varieties with salt tolerance.

QTL fine mapping with Bayes C(π): a simulation study.

PubMed

van den Berg, Irene; Fritz, Sébastien; Boichard, Didier

2013-06-19

Accurate QTL mapping is a prerequisite in the search for causative mutations. Bayesian genomic selection models that analyse many markers simultaneously should provide more accurate QTL detection results than single-marker models. Our objectives were to (a) evaluate by simulation the influence of heritability, number of QTL and number of records on the accuracy of QTL mapping with Bayes Cπ and Bayes C; (b) estimate the QTL status (homozygous vs. heterozygous) of the individuals analysed. This study focussed on the ten largest detected QTL, assuming they are candidates for further characterization. Our simulations were based on a true dairy cattle population genotyped for 38,277 phased markers. Some of these markers were considered biallelic QTL and used to generate corresponding phenotypes. Different numbers of records (4387 and 1500), heritability values (0.1, 0.4 and 0.7) and numbers of QTL (10, 100 and 1000) were studied. QTL detection was based on the posterior inclusion probability for individual markers, or on the sum of the posterior inclusion probabilities for consecutive markers, estimated using Bayes C or Bayes Cπ. The QTL status of the individuals was derived from the contrast between the sums of the SNP allelic effects of their chromosomal segments. The proportion of markers with null effect (π) frequently did not reach convergence, leading to poor results for Bayes Cπ in QTL detection. Fixing π led to better results. Detection of the largest QTL was most accurate for medium to high heritability, for low to moderate numbers of QTL, and with a large number of records. The QTL status was accurately inferred when the distribution of the contrast between chromosomal segment effects was bimodal. QTL detection is feasible with Bayes C. For QTL detection, it is recommended to use a large dataset and to focus on highly heritable traits and on the largest QTL. QTL statuses were inferred based on the distribution of the contrast between chromosomal segment effects.

Feasibility of Multispectral Airborne Laser Scanning for Land Cover Classification, Road Mapping and Map Updating

NASA Astrophysics Data System (ADS)

Matikainen, L.; Karila, K.; Hyyppä, J.; Puttonen, E.; Litkey, P.; Ahokas, E.

2017-10-01

This article summarises our first results and experiences on the use of multispectral airborne laser scanner (ALS) data. Optech Titan multispectral ALS data over a large suburban area in Finland were acquired on three different dates in 2015-2016. We investigated the feasibility of the data from the first date for land cover classification and road mapping. Object-based analyses with segmentation and random forests classification were used. The potential of the data for change detection of buildings and roads was also demonstrated. The overall accuracy of land cover classification results with six classes was 96 % compared with validation points. The data also showed high potential for road detection, road surface classification and change detection. The multispectral intensity information appeared to be very important for automated classifications. Compared to passive aerial images, the intensity images have interesting advantages, such as the lack of shadows. Currently, we focus on analyses and applications with the multitemporal multispectral data. Important questions include, for example, the potential and challenges of the multitemporal data for change detection.

Semi-automatic mapping of cultural heritage from airborne laser scanning using deep learning

NASA Astrophysics Data System (ADS)

Due Trier, Øivind; Salberg, Arnt-Børre; Holger Pilø, Lars; Tonning, Christer; Marius Johansen, Hans; Aarsten, Dagrun

2016-04-01

This paper proposes to use deep learning to improve semi-automatic mapping of cultural heritage from airborne laser scanning (ALS) data. Automatic detection methods, based on traditional pattern recognition, have been applied in a number of cultural heritage mapping projects in Norway for the past five years. Automatic detection of pits and heaps have been combined with visual interpretation of the ALS data for the mapping of deer hunting systems, iron production sites, grave mounds and charcoal kilns. However, the performance of the automatic detection methods varies substantially between ALS datasets. For the mapping of deer hunting systems on flat gravel and sand sediment deposits, the automatic detection results were almost perfect. However, some false detections appeared in the terrain outside of the sediment deposits. These could be explained by other pit-like landscape features, like parts of river courses, spaces between boulders, and modern terrain modifications. However, these were easy to spot during visual interpretation, and the number of missed individual pitfall traps was still low. For the mapping of grave mounds, the automatic method produced a large number of false detections, reducing the usefulness of the semi-automatic approach. The mound structure is a very common natural terrain feature, and the grave mounds are less distinct in shape than the pitfall traps. Still, applying automatic mound detection on an entire municipality did lead to a new discovery of an Iron Age grave field with more than 15 individual mounds. Automatic mound detection also proved to be useful for a detailed re-mapping of Norway's largest Iron Age grave yard, which contains almost 1000 individual graves. Combined pit and mound detection has been applied to the mapping of more than 1000 charcoal kilns that were used by an iron work 350-200 years ago. The majority of charcoal kilns were indirectly detected as either pits on the circumference, a central mound, or both. However, kilns with a flat interior and a shallow ditch along the circumference were often missed by the automatic detection method. The successfulness of automatic detection seems to depend on two factors: (1) the density of ALS ground hits on the cultural heritage structures being sought, and (2) to what extent these structures stand out from natural terrain structures. The first factor may, to some extent, be improved by using a higher number of ALS pulses per square meter. The second factor is difficult to change, and also highlights another challenge: how to make a general automatic method that is applicable in all types of terrain within a country. The mixed experience with traditional pattern recognition for semi-automatic mapping of cultural heritage led us to consider deep learning as an alternative approach. The main principle is that a general feature detector has been trained on a large image database. The feature detector is then tailored to a specific task by using a modest number of images of true and false examples of the features being sought. Results of using deep learning are compared with previous results using traditional pattern recognition.

Genome-Wide Mapping of Copy Number Variation in Humans: Comparative Analysis of High Resolution Array Platforms

PubMed Central

Haraksingh, Rajini R.; Abyzov, Alexej; Gerstein, Mark; Urban, Alexander E.; Snyder, Michael

2011-01-01

Accurate and efficient genome-wide detection of copy number variants (CNVs) is essential for understanding human genomic variation, genome-wide CNV association type studies, cytogenetics research and diagnostics, and independent validation of CNVs identified from sequencing based technologies. Numerous, array-based platforms for CNV detection exist utilizing array Comparative Genome Hybridization (aCGH), Single Nucleotide Polymorphism (SNP) genotyping or both. We have quantitatively assessed the abilities of twelve leading genome-wide CNV detection platforms to accurately detect Gold Standard sets of CNVs in the genome of HapMap CEU sample NA12878, and found significant differences in performance. The technologies analyzed were the NimbleGen 4.2 M, 2.1 M and 3×720 K Whole Genome and CNV focused arrays, the Agilent 1×1 M CGH and High Resolution and 2×400 K CNV and SNP+CGH arrays, the Illumina Human Omni1Quad array and the Affymetrix SNP 6.0 array. The Gold Standards used were a 1000 Genomes Project sequencing-based set of 3997 validated CNVs and an ultra high-resolution aCGH-based set of 756 validated CNVs. We found that sensitivity, total number, size range and breakpoint resolution of CNV calls were highest for CNV focused arrays. Our results are important for cost effective CNV detection and validation for both basic and clinical applications. PMID:22140474

Inlining 3d Reconstruction, Multi-Source Texture Mapping and Semantic Analysis Using Oblique Aerial Imagery

NASA Astrophysics Data System (ADS)

Frommholz, D.; Linkiewicz, M.; Poznanska, A. M.

2016-06-01

This paper proposes an in-line method for the simplified reconstruction of city buildings from nadir and oblique aerial images that at the same time are being used for multi-source texture mapping with minimal resampling. Further, the resulting unrectified texture atlases are analyzed for façade elements like windows to be reintegrated into the original 3D models. Tests on real-world data of Heligoland/ Germany comprising more than 800 buildings exposed a median positional deviation of 0.31 m at the façades compared to the cadastral map, a correctness of 67% for the detected windows and good visual quality when being rendered with GPU-based perspective correction. As part of the process building reconstruction takes the oriented input images and transforms them into dense point clouds by semi-global matching (SGM). The point sets undergo local RANSAC-based regression and topology analysis to detect adjacent planar surfaces and determine their semantics. Based on this information the roof, wall and ground surfaces found get intersected and limited in their extension to form a closed 3D building hull. For texture mapping the hull polygons are projected into each possible input bitmap to find suitable color sources regarding the coverage and resolution. Occlusions are detected by ray-casting a full-scale digital surface model (DSM) of the scene and stored in pixel-precise visibility maps. These maps are used to derive overlap statistics and radiometric adjustment coefficients to be applied when the visible image parts for each building polygon are being copied into a compact texture atlas without resampling whenever possible. The atlas bitmap is passed to a commercial object-based image analysis (OBIA) tool running a custom rule set to identify windows on the contained façade patches. Following multi-resolution segmentation and classification based on brightness and contrast differences potential window objects are evaluated against geometric constraints and conditionally grown, fused and filtered morphologically. The output polygons are vectorized and reintegrated into the previously reconstructed buildings by sparsely ray-tracing their vertices. Finally the enhanced 3D models get stored as textured geometry for visualization and semantically annotated "LOD-2.5" CityGML objects for GIS applications.

Algorithmic Approaches for Place Recognition in Featureless, Walled Environments

DTIC Science & Technology

2015-01-01

inertial measurement unit LIDAR light detection and ranging RANSAC random sample consensus SLAM simultaneous localization and mapping SUSAN smallest...algorithm 38 21 Typical input image for general junction based algorithm 39 22 Short exposure image of hallway junction taken by LIDAR 40 23...discipline of simultaneous localization and mapping ( SLAM ) has been studied intensively over the past several years. Many technical approaches

An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus)

PubMed Central

2014-01-01

Background Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Results Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. Conclusions The integrated map described herein enhances the utility of genomic tools over previous watermelon genetic maps. A large proportion of the markers in the integrated map are SSRs, InDels and SNPs, which are easily transferable across laboratories. Moreover, the populations used to construct the integrated map include all three watermelon subspecies, making this integrated map useful for the selection of breeding traits, identification of QTL, MAS, analysis of germplasm and commercial hybrid seed detection. PMID:24443961

Mapping the distribution of materials in hyperspectral data using the USGS Material Identification and Characterization Algorithm (MICA)

USGS Publications Warehouse

Kokaly, R.F.; King, T.V.V.; Hoefen, T.M.

2011-01-01

Identifying materials by measuring and analyzing their reflectance spectra has been an important method in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow scientists to detect materials and map their distributions across the landscape. With new satellite-borne hyperspectral sensors planned for the future, for example, HYSPIRI (HYPerspectral InfraRed Imager), robust methods are needed to fully exploit the information content of hyperspectral remote sensing data. A method of identifying and mapping materials using spectral-feature based analysis of reflectance data in an expert-system framework called MICA (Material Identification and Characterization Algorithm) is described in this paper. The core concepts and calculations of MICA are presented. A MICA command file has been developed and applied to map minerals in the full-country coverage of the 2007 Afghanistan HyMap hyperspectral data. ?? 2011 IEEE.

Global Contrast Based Salient Region Detection.

PubMed

Cheng, Ming-Ming; Mitra, Niloy J; Huang, Xiaolei; Torr, Philip H S; Hu, Shi-Min

2015-03-01

Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information.

Image denoising based on noise detection

NASA Astrophysics Data System (ADS)

Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen

2018-03-01

Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.

Early Forest Fire Detection Using Radio-Acoustic Sounding System

PubMed Central

Sahin, Yasar Guneri; Ince, Turker

2009-01-01

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires. PMID:22573967

A preliminary evaluation of land use mapping and change detection capabilities using an ERTS image covering a portion of the CARETS region

NASA Technical Reports Server (NTRS)

Fitzpatrick, K. A.; Lins, H. F., Jr.

1972-01-01

The author has identified the following significant results. A preliminary study on the capabilities of ERTS data in land use mapping and change detection was carried out in the area around Frederick County, Maryland, which lies in the northwest corner of the Central Atlantic Regional Ecological Test Site. The investigation has revealed that Level 1 (of the Anderson classification system) land use mapping can be performed and that, in some cases, land undergoing change can be identified. Results to date suggest that more work should be done in areas where land use changes are known to exist, in order to establish some form of base for recognizing the spectral signature indicative of change areas.

Remote sensing techniques for conservation and management of natural vegetation ecosystems

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Verdesio, J. J.; Dossantos, J. R.

1981-01-01

The importance of using remote sensing techniques, in the visible and near-infrared ranges, for mapping, inventory, conservation and management of natural ecosystems is discussed. Some examples realized in Brazil or other countries are given to evaluate the products from orbital platform (MSS and RBV imagery of LANDSAT) and aerial level (photography) for ecosystems study. The maximum quantitative and qualitative information which can be obtained from each sensor, at different level, are discussed. Based on the developed experiments it is concluded that the remote sensing technique is a useful tool in mapping vegetation units, estimating biomass, forecasting and evaluation of fire damage, disease detection, deforestation mapping and change detection in land-use. In addition, remote sensing techniques can be used in controling implantation and planning natural/artificial regeneration.

Recent Developments for Satellite-Based Fire Monitoring in Canada

NASA Astrophysics Data System (ADS)

Abuelgasim, A.; Fraser, R.

2002-05-01

Wildfires in Canadian forests are a major source of natural disturbance. These fires have a tremendous impact on the local environment, humans and wildlife, ecosystem function, weather, and climate. Approximately 9000 fires burn 3 million hectares per year in Canada (based on a 10-year average). While only 2 to 3 percent of these wildfires grow larger than 200 hectares in size, they account for almost 97 percent of the annual area burned. This provides an excellent opportunity to monitor active fires using a combination of low and high resolution sensors for the purpose of determining fire location and burned areas. Given the size of Canada, the use of remote sensing data is a cost-effective way to achieve a synoptic overview of large forest fire activity in near-real time. In 1998 the Canada Centre for Remote Sensing (CCRS) and the Canadian Forest Service (CFS) developed a system for Fire Monitoring, Mapping and Modelling (Fire M3;http://fms.nofc.cfs.nrcan.gc.ca/FireM3/). Fire M3 automatically identifies, monitors, and maps large forest fires on a daily basis using NOAA AVHRR data. These data are processed daily using the GEOCOMP-N satellite image processing system. This presentation will describe recent developments to Fire M3, included the addition of a set of algorithms tailored for NOAA-16 (N-16) data. The two fire detection algorithms are developed for N-16 day and night-time daily data collection. The algorithms exploit both the multi-spectral and thermal information from the AVHRR daily images. The set of N-16 day and night algorithms was used to generate daily active fire maps across North America for the 2001 fire season. Such a combined approach for fire detection leads to an improved detection rate, although day-time detection based on the new 1.6 um channel was much less effective (note - given the low detection rate with day time imagery, I don't think we can make the statement about capturing the diurnal cycle). Selected validation sites in western Canada and the United States showed reasonable correspondence with the location of fires mapped by CFS and those mapped by the USDA Forest Service using conventional means.

A comparative analysis of chaotic particle swarm optimizations for detecting single nucleotide polymorphism barcodes.

PubMed

Chuang, Li-Yeh; Moi, Sin-Hua; Lin, Yu-Da; Yang, Cheng-Hong

2016-10-01

Evolutionary algorithms could overcome the computational limitations for the statistical evaluation of large datasets for high-order single nucleotide polymorphism (SNP) barcodes. Previous studies have proposed several chaotic particle swarm optimization (CPSO) methods to detect SNP barcodes for disease analysis (e.g., for breast cancer and chronic diseases). This work evaluated additional chaotic maps combined with the particle swarm optimization (PSO) method to detect SNP barcodes using a high-dimensional dataset. Nine chaotic maps were used to improve PSO method results and compared the searching ability amongst all CPSO methods. The XOR and ZZ disease models were used to compare all chaotic maps combined with PSO method. Efficacy evaluations of CPSO methods were based on statistical values from the chi-square test (χ 2 ). The results showed that chaotic maps could improve the searching ability of PSO method when population are trapped in the local optimum. The minor allele frequency (MAF) indicated that, amongst all CPSO methods, the numbers of SNPs, sample size, and the highest χ 2 value in all datasets were found in the Sinai chaotic map combined with PSO method. We used the simple linear regression results of the gbest values in all generations to compare the all methods. Sinai chaotic map combined with PSO method provided the highest β values (β≥0.32 in XOR disease model and β≥0.04 in ZZ disease model) and the significant p-value (p-value<0.001 in both the XOR and ZZ disease models). The Sinai chaotic map was found to effectively enhance the fitness values (χ 2 ) of PSO method, indicating that the Sinai chaotic map combined with PSO method is more effective at detecting potential SNP barcodes in both the XOR and ZZ disease models. Copyright © 2016 Elsevier B.V. All rights reserved.

Integrated Georeferencing of Stereo Image Sequences Captured with a Stereovision Mobile Mapping System - Approaches and Practical Results

NASA Astrophysics Data System (ADS)

Eugster, H.; Huber, F.; Nebiker, S.; Gisi, A.

2012-07-01

Stereovision based mobile mapping systems enable the efficient capturing of directly georeferenced stereo pairs. With today's camera and onboard storage technologies imagery can be captured at high data rates resulting in dense stereo sequences. These georeferenced stereo sequences provide a highly detailed and accurate digital representation of the roadside environment which builds the foundation for a wide range of 3d mapping applications and image-based geo web-services. Georeferenced stereo images are ideally suited for the 3d mapping of street furniture and visible infrastructure objects, pavement inspection, asset management tasks or image based change detection. As in most mobile mapping systems, the georeferencing of the mapping sensors and observations - in our case of the imaging sensors - normally relies on direct georeferencing based on INS/GNSS navigation sensors. However, in urban canyons the achievable direct georeferencing accuracy of the dynamically captured stereo image sequences is often insufficient or at least degraded. Furthermore, many of the mentioned application scenarios require homogeneous georeferencing accuracy within a local reference frame over the entire mapping perimeter. To achieve these demands georeferencing approaches are presented and cost efficient workflows are discussed which allows validating and updating the INS/GNSS based trajectory with independently estimated positions in cases of prolonged GNSS signal outages in order to increase the georeferencing accuracy up to the project requirements.

Construction of an SNP-based high-density linkage map for flax (Linum usitatissimum L.) using specific length amplified fragment sequencing (SLAF-seq) technology.

PubMed

Yi, Liuxi; Gao, Fengyun; Siqin, Bateer; Zhou, Yu; Li, Qiang; Zhao, Xiaoqing; Jia, Xiaoyun; Zhang, Hui

2017-01-01

Flax is an important crop for oil and fiber, however, no high-density genetic maps have been reported for this species. Specific length amplified fragment sequencing (SLAF-seq) is a high-resolution strategy for large scale de novo discovery and genotyping of single nucleotide polymorphisms. In this study, SLAF-seq was employed to develop SNP markers in an F2 population to construct a high-density genetic map for flax. In total, 196.29 million paired-end reads were obtained. The average sequencing depth was 25.08 in male parent, 32.17 in the female parent, and 9.64 in each F2 progeny. In total, 389,288 polymorphic SLAFs were detected, from which 260,380 polymorphic SNPs were developed. After filtering, 4,638 SNPs were found suitable for genetic map construction. The final genetic map included 4,145 SNP markers on 15 linkage groups and was 2,632.94 cM in length, with an average distance of 0.64 cM between adjacent markers. To our knowledge, this map is the densest SNP-based genetic map for flax. The SNP markers and genetic map reported in here will serve as a foundation for the fine mapping of quantitative trait loci (QTLs), map-based gene cloning and marker assisted selection (MAS) for flax.

Mapping disease at an approximated individual level using aggregate data: a case study of mapping New Hampshire birth defects.

PubMed

Shi, Xun; Miller, Stephanie; Mwenda, Kevin; Onda, Akikazu; Reese, Judy; Onega, Tracy; Gui, Jiang; Karagas, Margret; Demidenko, Eugene; Moeschler, John

2013-09-06

Limited by data availability, most disease maps in the literature are for relatively large and subjectively-defined areal units, which are subject to problems associated with polygon maps. High resolution maps based on objective spatial units are needed to more precisely detect associations between disease and environmental factors. We propose to use a Restricted and Controlled Monte Carlo (RCMC) process to disaggregate polygon-level location data to achieve mapping aggregate data at an approximated individual level. RCMC assigns a random point location to a polygon-level location, in which the randomization is restricted by the polygon and controlled by the background (e.g., population at risk). RCMC allows analytical processes designed for individual data to be applied, and generates high-resolution raster maps. We applied RCMC to the town-level birth defect data for New Hampshire and generated raster maps at the resolution of 100 m. Besides the map of significance of birth defect risk represented by p-value, the output also includes a map of spatial uncertainty and a map of hot spots. RCMC is an effective method to disaggregate aggregate data. An RCMC-based disease mapping maximizes the use of available spatial information, and explicitly estimates the spatial uncertainty resulting from aggregation.

Acoustic Longitudinal Field NIF Optic Feature Detection Map Using Time-Reversal & MUSIC

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

Lehman, S K

2006-02-09

We developed an ultrasonic longitudinal field time-reversal and MUltiple SIgnal Classification (MUSIC) based detection algorithm for identifying and mapping flaws in fused silica NIF optics. The algorithm requires a fully multistatic data set, that is one with multiple, independently operated, spatially diverse transducers, each transmitter of which, in succession, launches a pulse into the optic and the scattered signal measured and recorded at every receiver. We have successfully localized engineered ''defects'' larger than 1 mm in an optic. We confirmed detection and localization of 3 mm and 5 mm features in experimental data, and a 0.5 mm in simulated datamore » with sufficiently high signal-to-noise ratio. We present the theory, experimental results, and simulated results.« less

Breast mass detection in mammography and tomosynthesis via fully convolutional network-based heatmap regression

NASA Astrophysics Data System (ADS)

Zhang, Jun; Cain, Elizabeth Hope; Saha, Ashirbani; Zhu, Zhe; Mazurowski, Maciej A.

2018-02-01

Breast mass detection in mammography and digital breast tomosynthesis (DBT) is an essential step in computerized breast cancer analysis. Deep learning-based methods incorporate feature extraction and model learning into a unified framework and have achieved impressive performance in various medical applications (e.g., disease diagnosis, tumor detection, and landmark detection). However, these methods require large-scale accurately annotated data. Unfortunately, it is challenging to get precise annotations of breast masses. To address this issue, we propose a fully convolutional network (FCN) based heatmap regression method for breast mass detection, using only weakly annotated mass regions in mammography images. Specifically, we first generate heat maps of masses based on human-annotated rough regions for breast masses. We then develop an FCN model for end-to-end heatmap regression with an F-score loss function, where the mammography images are regarded as the input and heatmaps for breast masses are used as the output. Finally, the probability map of mass locations can be estimated with the trained model. Experimental results on a mammography dataset with 439 subjects demonstrate the effectiveness of our method. Furthermore, we evaluate whether we can use mammography data to improve detection models for DBT, since mammography shares similar structure with tomosynthesis. We propose a transfer learning strategy by fine-tuning the learned FCN model from mammography images. We test this approach on a small tomosynthesis dataset with only 40 subjects, and we show an improvement in the detection performance as compared to training the model from scratch.

Herd-level prevalence of Map infection in dairy herds of southern Chile determined by culture of environmental fecal samples and bulk-tank milk qPCR.

PubMed

Kruze, J; Monti, G; Schulze, F; Mella, A; Leiva, S

2013-09-01

Paratuberculosis, an infectious disease of domestic and wild ruminants caused by Mycobacterium avium subsp. paratuberculosis (Map), is an economically important disease in dairy herds worldwide. In Chile the disease has been reported in domestic and wildlife animals. However, accurate and updated estimations of the herd-prevalence in cattle at national or regional level are not available. The objectives of this study were to determine the herd-level prevalence of dairy herds with Map infected animals of Southern Chile, based on two diagnostic tests: culture of environmental fecal samples and bulk-tank milk qPCR. Two composite environmental fecal samples and one bulk-tank milk sample were collected during September 2010 and September 2011 from 150 dairy farms in Southern Chile. Isolation of Map from environmental fecal samples was done by culture of decontaminated samples on a commercial Herrold's Egg Yolk Medium (HEYM) with and without mycobactin J. Suspicious colonies were confirmed to be Map by conventional IS900 PCR. Map detection in bulk-tank milk samples was done by real time IS900 PCR assay. PCR-confirmed Map was isolated from 58 (19.3%) of 300 environmental fecal samples. Holding pens and manure storage lagoons were the two more frequent sites found positive for Map, representing 35% and 33% of total positive samples, respectively. However, parlor exits and cow alleyways were the two sites with the highest proportion of positive samples (40% and 32%, respectively). Herd prevalence based on environmental fecal culture was 27% (true prevalence 44%) compared to 49% (true prevalence 87%) based on bulk-tank milk real time IS900 PC. In both cases herd prevalence was higher in large herds (>200 cows). These results confirm that Map infection is wide spread in dairy herds in Southern Chile with a rough herd-level prevalence of 28-100% depending on the herd size, and that IS900 PCR on bulk-tank milk samples is more sensitive than environmental fecal culture to detect Map-infected dairy herds. Copyright © 2013 Elsevier B.V. All rights reserved.

Anamolous ionospheric TEC variations prior to the Indonesian earthquake (M 7.1) of November 15, 2014

NASA Astrophysics Data System (ADS)

Alcay, Salih

2017-05-01

This paper investigates preearthquake ionospheric variations with the use of TEC of Global Ionospheric Maps (GIMs) and regional maps based on Precise Point Positioning (PPP) during the 7.1-M Indonesian earthquake that occurred on November 15, 2014. TEC maps corresponding to 10 days before to 4 days after the event were examined. In addition, a time series of TEC values according to the PPP maps were also evaluated. In addition to GIMs, it was possible to detect TEC variations with PPP maps. The results showed that ionospheric TEC decreased strikingly 4 days prior to the earthquake. This TEC variation was highly likely related to seismic activity.

Using NIR spatial illumination for detection and mapping chromophore changes during cerebral edema

NASA Astrophysics Data System (ADS)

Abookasis, David; Mathews, Marlon S.; Owen, Christopher M.; Binder, Devin K.; Linskey, Mark E.; Frostig, Ron D.; Tromberg, Bruce J.

2008-02-01

We used spatially modulated near-infrared (NIR) light to detect and map chromophore changes during cerebral edema in the rat neocortex. Cerebral edema was induced by intraperitoneal injections of free water (35% of body weight). Intracranial pressure (ICP) was measured with an optical fiber based Fabry-Perot interferometer sensor inserted into the parenchyma of the right frontal lobe during water administration. Increase in ICP from a baseline value of 10 cm-water to 145 cm-water was observed. Following induction of cerebral edema, there was a 26+/-1.7% increase in tissue concentration of deoxyhemoglobin and a 47+/-4.7%, 17+/-3% and 37+/-3.7% decrease in oxyhemoglobin, total hemoglobin concentration and cerebral tissue oxygen saturation levels, respectively. To the best of our knowledge, this is the first report describing the use of NIR spatial modulation of light for detecting and mapping changes in tissue concentrations of physiologic chromophores over time in response to cerebral edema.

Genetic linkage map construction and QTL mapping of seedling height, basal diameter and crown width of Taxodium 'Zhongshanshan 302' × T. mucronatum.

PubMed

Wang, Ziyang; Cheng, Yanli; Yin, Yunlong; Yu, Chaoguang; Yang, Ying; Shi, Qin; Hao, Ziyuan; Li, Huogen

2016-01-01

Taxodium is a genus renowned for its fast growth, good form and tolerance of flooding, salt, alkalinity, disease and strong winds. In this study, a genetic linkage map was constructed using sequence-related amplified polymorphism (SRAP) and simple sequence repeat (SSR) markers based on an F1 population containing 148 individuals generated from a cross between T. 'Zhongshanshan 302' and T. mucronatum. The map has a total length of 976.5 cM, with a mean distance of 7.0 cM between markers, and contains 34 linkage groups with 179 markers (171 SRAPs and 8 SSRs). Quantitative trait loci (QTLs) affecting growth traits, such as seedling height, basal diameter and crown width, were detected based on the constructed linkage map. Four significant QTLs were identified, three of which, namely qtSH-1 for seedling height, qtBD-1 for basal diameter and qtCW-1 for crown width, were located at 2.659 cM of LG7 with logarithm odds values of 3.72, 3.49 and 3.93, respectively, and explained 24.9, 27.0 and 21.7 % of the total variation of the three grown traits, respectively. Another QTL for crown width (qtCW-2) was detected at 1.0 cM on LG13, with a logarithm of odds value of 3.15, and explained 31.7 % of the total variation of crown width. This is the first report on the construction of a genetic linkage map and QTL analysis in Taxodium, laying the groundwork for the construction of a high-density genetic map and QTL mapping in the genus Taxodium.

Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling

PubMed Central

Bricher, Phillippa K.; Lucieer, Arko; Shaw, Justine; Terauds, Aleks; Bergstrom, Dana M.

2013-01-01

Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6–96.3%, κ = 0.849–0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments. PMID:23940805

High resolution mapping of development in the wildland-urban interface using object based image extraction.

PubMed

Caggiano, Michael D; Tinkham, Wade T; Hoffman, Chad; Cheng, Antony S; Hawbaker, Todd J

2016-10-01

The wildland-urban interface (WUI), the area where human development encroaches on undeveloped land, is expanding throughout the western United States resulting in increased wildfire risk to homes and communities. Although census based mapping efforts have provided insights into the pattern of development and expansion of the WUI at regional and national scales, these approaches do not provide sufficient detail for fine-scale fire and emergency management planning, which requires maps of individual building locations. Although fine-scale maps of the WUI have been developed, they are often limited in their spatial extent, have unknown accuracies and biases, and are costly to update over time. In this paper we assess a semi-automated Object Based Image Analysis (OBIA) approach that utilizes 4-band multispectral National Aerial Image Program (NAIP) imagery for the detection of individual buildings within the WUI. We evaluate this approach by comparing the accuracy and overall quality of extracted buildings to a building footprint control dataset. In addition, we assessed the effects of buffer distance, topographic conditions, and building characteristics on the accuracy and quality of building extraction. The overall accuracy and quality of our approach was positively related to buffer distance, with accuracies ranging from 50 to 95% for buffer distances from 0 to 100 m. Our results also indicate that building detection was sensitive to building size, with smaller outbuildings (footprints less than 75 m 2 ) having detection rates below 80% and larger residential buildings having detection rates above 90%. These findings demonstrate that this approach can successfully identify buildings in the WUI in diverse landscapes while achieving high accuracies at buffer distances appropriate for most fire management applications while overcoming cost and time constraints associated with traditional approaches. This study is unique in that it evaluates the ability of an OBIA approach to extract highly detailed data on building locations in a WUI setting.

High resolution mapping of development in the wildland-urban interface using object based image extraction

USGS Publications Warehouse

Caggiano, Michael D.; Tinkham, Wade T.; Hoffman, Chad; Cheng, Antony S.; Hawbaker, Todd J.

2016-01-01

The wildland-urban interface (WUI), the area where human development encroaches on undeveloped land, is expanding throughout the western United States resulting in increased wildfire risk to homes and communities. Although census based mapping efforts have provided insights into the pattern of development and expansion of the WUI at regional and national scales, these approaches do not provide sufficient detail for fine-scale fire and emergency management planning, which requires maps of individual building locations. Although fine-scale maps of the WUI have been developed, they are often limited in their spatial extent, have unknown accuracies and biases, and are costly to update over time. In this paper we assess a semi-automated Object Based Image Analysis (OBIA) approach that utilizes 4-band multispectral National Aerial Image Program (NAIP) imagery for the detection of individual buildings within the WUI. We evaluate this approach by comparing the accuracy and overall quality of extracted buildings to a building footprint control dataset. In addition, we assessed the effects of buffer distance, topographic conditions, and building characteristics on the accuracy and quality of building extraction. The overall accuracy and quality of our approach was positively related to buffer distance, with accuracies ranging from 50 to 95% for buffer distances from 0 to 100 m. Our results also indicate that building detection was sensitive to building size, with smaller outbuildings (footprints less than 75 m2) having detection rates below 80% and larger residential buildings having detection rates above 90%. These findings demonstrate that this approach can successfully identify buildings in the WUI in diverse landscapes while achieving high accuracies at buffer distances appropriate for most fire management applications while overcoming cost and time constraints associated with traditional approaches. This study is unique in that it evaluates the ability of an OBIA approach to extract highly detailed data on building locations in a WUI setting.

Reducing sojourn points from recurrence plots to improve transition detection: Application to fetal heart rate transitions.

PubMed

Zaylaa, Amira; Charara, Jamal; Girault, Jean-Marc

2015-08-01

The analysis of biomedical signals demonstrating complexity through recurrence plots is challenging. Quantification of recurrences is often biased by sojourn points that hide dynamic transitions. To overcome this problem, time series have previously been embedded at high dimensions. However, no one has quantified the elimination of sojourn points and rate of detection, nor the enhancement of transition detection has been investigated. This paper reports our on-going efforts to improve the detection of dynamic transitions from logistic maps and fetal hearts by reducing sojourn points. Three signal-based recurrence plots were developed, i.e. embedded with specific settings, derivative-based and m-time pattern. Determinism, cross-determinism and percentage of reduced sojourn points were computed to detect transitions. For logistic maps, an increase of 50% and 34.3% in sensitivity of detection over alternatives was achieved by m-time pattern and embedded recurrence plots with specific settings, respectively, and with a 100% specificity. For fetal heart rates, embedded recurrence plots with specific settings provided the best performance, followed by derivative-based recurrence plot, then unembedded recurrence plot using the determinism parameter. The relative errors between healthy and distressed fetuses were 153%, 95% and 91%. More than 50% of sojourn points were eliminated, allowing better detection of heart transitions triggered by gaseous exchange factors. This could be significant in improving the diagnosis of fetal state. Copyright © 2014 Elsevier Ltd. All rights reserved.

Scanning electron microscopy coupled with energy-dispersive X-ray spectrometry for quick detection of sulfur-oxidizing bacteria in environmental water samples

NASA Astrophysics Data System (ADS)

Sun, Chengjun; Jiang, Fenghua; Gao, Wei; Li, Xiaoyun; Yu, Yanzhen; Yin, Xiaofei; Wang, Yong; Ding, Haibing

2017-01-01

Detection of sulfur-oxidizing bacteria has largely been dependent on targeted gene sequencing technology or traditional cell cultivation, which usually takes from days to months to carry out. This clearly does not meet the requirements of analysis for time-sensitive samples and/or complicated environmental samples. Since energy-dispersive X-ray spectrometry (EDS) can be used to simultaneously detect multiple elements in a sample, including sulfur, with minimal sample treatment, this technology was applied to detect sulfur-oxidizing bacteria using their high sulfur content within the cell. This article describes the application of scanning electron microscopy imaging coupled with EDS mapping for quick detection of sulfur oxidizers in contaminated environmental water samples, with minimal sample handling. Scanning electron microscopy imaging revealed the existence of dense granules within the bacterial cells, while EDS identified large amounts of sulfur within them. EDS mapping localized the sulfur to these granules. Subsequent 16S rRNA gene sequencing showed that the bacteria detected in our samples belonged to the genus Chromatium, which are sulfur oxidizers. Thus, EDS mapping made it possible to identify sulfur oxidizers in environmental samples based on localized sulfur within their cells, within a short time (within 24 h of sampling). This technique has wide ranging applications for detection of sulfur bacteria in environmental water samples.

Subtracting the sequence bias from partially digested MNase-seq data reveals a general contribution of TFIIS to nucleosome positioning.

PubMed

Gutiérrez, Gabriel; Millán-Zambrano, Gonzalo; Medina, Daniel A; Jordán-Pla, Antonio; Pérez-Ortín, José E; Peñate, Xenia; Chávez, Sebastián

2017-12-07

TFIIS stimulates RNA cleavage by RNA polymerase II and promotes the resolution of backtracking events. TFIIS acts in the chromatin context, but its contribution to the chromatin landscape has not yet been investigated. Co-transcriptional chromatin alterations include subtle changes in nucleosome positioning, like those expected to be elicited by TFIIS, which are elusive to detect. The most popular method to map nucleosomes involves intensive chromatin digestion by micrococcal nuclease (MNase). Maps based on these exhaustively digested samples miss any MNase-sensitive nucleosomes caused by transcription. In contrast, partial digestion approaches preserve such nucleosomes, but introduce noise due to MNase sequence preferences. A systematic way of correcting this bias for massively parallel sequencing experiments is still missing. To investigate the contribution of TFIIS to the chromatin landscape, we developed a refined nucleosome-mapping method in Saccharomyces cerevisiae. Based on partial MNase digestion and a sequence-bias correction derived from naked DNA cleavage, the refined method efficiently mapped nucleosomes in promoter regions rich in MNase-sensitive structures. The naked DNA correction was also important for mapping gene body nucleosomes, particularly in those genes whose core promoters contain a canonical TATA element. With this improved method, we analyzed the global nucleosomal changes caused by lack of TFIIS. We detected a general increase in nucleosomal fuzziness and more restricted changes in nucleosome occupancy, which concentrated in some gene categories. The TATA-containing genes were preferentially associated with decreased occupancy in gene bodies, whereas the TATA-like genes did so with increased fuzziness. The detected chromatin alterations correlated with functional defects in nascent transcription, as revealed by genomic run-on experiments. The combination of partial MNase digestion and naked DNA correction of the sequence bias is a precise nucleosomal mapping method that does not exclude MNase-sensitive nucleosomes. This method is useful for detecting subtle alterations in nucleosome positioning produced by lack of TFIIS. Their analysis revealed that TFIIS generally contributed to nucleosome positioning in both gene promoters and bodies. The independent effect of lack of TFIIS on nucleosome occupancy and fuzziness supports the existence of alternative chromatin dynamics during transcription elongation.

Sensitive and specific detection of viable Mycobacterium avium subsp. paratuberculosis in raw milk by the peptide-mediated magnetic separation-phage assay.

PubMed

Foddai, A C G; Grant, I R

2017-05-01

To validate an optimized peptide-mediated magnetic separation (PMS)-phage assay for detection of viable Mycobacterium avium subsp. paratuberculosis (MAP) in milk. Inclusivity, specificity and limit of detection 50% (LOD 50 ) of the optimized PMS-phage assay were assessed. Plaques were obtained for all 43 MAP strains tested. Of 12 other Mycobacterium sp. tested, only Mycobacterium bovis BCG produced small numbers of plaques. LOD 50 of the PMS-phage assay was 0·93 MAP cells per 50 ml milk, which was better than both PMS-qPCR and PMS-culture. When individual milks (n = 146) and bulk tank milk (BTM, n = 22) obtained from Johne's affected herds were tested by the PMS-phage assay, viable MAP were detected in 31 (21·2%) of 146 individual milks and 13 (59·1%) of 22 BTM, with MAP numbers detected ranging from 6-948 plaque-forming-units per 50 ml milk. PMS-qPCR and PMS-MGIT culture proved to be less sensitive tests than the PMS-phage assay. The optimized PMS-phage assay is the most sensitive and specific method available for the detection of viable MAP in milk. Further work is needed to streamline the PMS-phage assay, because the assay's multistep format currently makes it unsuitable for adoption by the dairy industry as a screening test. The inclusivity (ability to detect all MAP strains), specificity (ability to detect only MAP) and detection sensitivity (ability to detect low numbers of MAP) of the optimized PMS-phage assay have been comprehensively demonstrated for the first time. © 2017 The Society for Applied Microbiology.

Spatial and spectral resolution necessary for remotely sensed vegetation studies

NASA Technical Reports Server (NTRS)

Rock, B. N.

1982-01-01

An outline is presented of the required spatial and spectral resolution needed for accurate vegetation discrimination and mapping studies as well as for determination of state of health (i.e., detection of stress symptoms) of actively growing vegetation. Good success was achieved in vegetation discrimination and mapping of a heterogeneous forest cover in the ridge and valley portion of the Appalachians using multispectral data acquired with a spatial resolution of 15 m (IFOV). A sensor system delivering 10 to 15 m spatial resolution is needed for both vegetation mapping and detection of stress symptoms. Based on the vegetation discrimination and mapping exercises conducted at the Lost River site, accurate products (vegetation maps) are produced using broad-band spectral data ranging from the .500 to 2.500 micron portion of the spectrum. In order of decreasing utility for vegetation discrimination, the four most valuable TM simulator VNIR bands are: 6 (1.55 to 1.75 microns), 3 (0.63 to 0.69 microns), 5 (1.00 to 1.30 microns) and 4 (0.76 to 0.90 microns).

Design and synthesis of multiple antigenic peptides and their application for dengue diagnosis.

PubMed

Rai, Reeta; Dubey, Sameer; Santosh, K V; Biswas, Ashutosh; Mehrotra, Vinit; Rao, D N

2017-09-01

Major difficulty in development of dengue diagnostics is availability of suitable antigens. To overcome this, we made an attempt to develop a peptide based diagnosis which offers significant advantage over other methods. With the help of in silico methods, two epitopes were selected from envelope protein and three from NS1 protein of dengue virus. These were synthesized in combination as three multiple antigenic peptides (MAPs). We have tested 157 dengue positive sera confirmed for NS1 antigen. MAP1 showed 96.81% sera positive for IgM and 68.15% positive for IgG. MAP2 detected 94.90% IgM and 59.23% IgG positive sera. MAP3 also detected 96.17% IgM and 59.87% IgG positive sera. To the best of our knowledge this is the first study describing the use of synthetic multiple antigenic peptides for the diagnosis of dengue infection. This study describes MAPs as a promising tool for the use in serodiagnosis of dengue. Copyright © 2017 International Alliance for Biological Standardization. Published by Elsevier Ltd. All rights reserved.

Imaging tree roots with borehole radar

Treesearch

John R. Butnor; Kurt H. Johnsen; Per Wikstrom; Tomas Lundmark; Sune Linder

2006-01-01

Ground-penetrating radar has been used to de-tect and map tree roots using surface-based antennas in reflection mode. On amenable soils these methods can accurately detect lateral tree roots. In some tree species (e.g. Pinus taeda, Pinus palustris), vertically orientated tap roots directly beneath the tree, comprise most of the root mass. It is...

Early detection of sporadic pancreatic cancer: strategic map for innovation--a white paper.

PubMed

Kenner, Barbara J; Chari, Suresh T; Cleeter, Deborah F; Go, Vay Liang W

2015-07-01

Innovation leading to significant advances in research and subsequent translation to clinical practice is urgently necessary in early detection of sporadic pancreatic cancer. Addressing this need, the Early Detection of Sporadic Pancreatic Cancer Summit Conference was conducted by Kenner Family Research Fund in conjunction with the 2014 American Pancreatic Association and Japan Pancreas Society Meeting. International interdisciplinary scientific representatives engaged in strategic facilitated conversations based on distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. Ideas generated from the summit have led to the development of a Strategic Map for Innovation built upon 3 components: formation of an international collaborative effort, design of an actionable strategic plan, and implementation of operational standards, research priorities, and first-phase initiatives. Through invested and committed efforts of leading researchers and institutions, philanthropic partners, government agencies, and supportive business entities, this endeavor will change the future of the field and consequently the survival rate of those diagnosed with pancreatic cancer.

Updating National Topographic Data Base Using Change Detection Methods

NASA Astrophysics Data System (ADS)

Keinan, E.; Felus, Y. A.; Tal, Y.; Zilberstien, O.; Elihai, Y.

2016-06-01

The traditional method for updating a topographic database on a national scale is a complex process that requires human resources, time and the development of specialized procedures. In many National Mapping and Cadaster Agencies (NMCA), the updating cycle takes a few years. Today, the reality is dynamic and the changes occur every day, therefore, the users expect that the existing database will portray the current reality. Global mapping projects which are based on community volunteers, such as OSM, update their database every day based on crowdsourcing. In order to fulfil user's requirements for rapid updating, a new methodology that maps major interest areas while preserving associated decoding information, should be developed. Until recently, automated processes did not yield satisfactory results, and a typically process included comparing images from different periods. The success rates in identifying the objects were low, and most were accompanied by a high percentage of false alarms. As a result, the automatic process required significant editorial work that made it uneconomical. In the recent years, the development of technologies in mapping, advancement in image processing algorithms and computer vision, together with the development of digital aerial cameras with NIR band and Very High Resolution satellites, allow the implementation of a cost effective automated process. The automatic process is based on high-resolution Digital Surface Model analysis, Multi Spectral (MS) classification, MS segmentation, object analysis and shape forming algorithms. This article reviews the results of a novel change detection methodology as a first step for updating NTDB in the Survey of Israel.

G-CNV: A GPU-Based Tool for Preparing Data to Detect CNVs with Read-Depth Methods.

PubMed

Manconi, Andrea; Manca, Emanuele; Moscatelli, Marco; Gnocchi, Matteo; Orro, Alessandro; Armano, Giuliano; Milanesi, Luciano

2015-01-01

Copy number variations (CNVs) are the most prevalent types of structural variations (SVs) in the human genome and are involved in a wide range of common human diseases. Different computational methods have been devised to detect this type of SVs and to study how they are implicated in human diseases. Recently, computational methods based on high-throughput sequencing (HTS) are increasingly used. The majority of these methods focus on mapping short-read sequences generated from a donor against a reference genome to detect signatures distinctive of CNVs. In particular, read-depth based methods detect CNVs by analyzing genomic regions with significantly different read-depth from the other ones. The pipeline analysis of these methods consists of four main stages: (i) data preparation, (ii) data normalization, (iii) CNV regions identification, and (iv) copy number estimation. However, available tools do not support most of the operations required at the first two stages of this pipeline. Typically, they start the analysis by building the read-depth signal from pre-processed alignments. Therefore, third-party tools must be used to perform most of the preliminary operations required to build the read-depth signal. These data-intensive operations can be efficiently parallelized on graphics processing units (GPUs). In this article, we present G-CNV, a GPU-based tool devised to perform the common operations required at the first two stages of the analysis pipeline. G-CNV is able to filter low-quality read sequences, to mask low-quality nucleotides, to remove adapter sequences, to remove duplicated read sequences, to map the short-reads, to resolve multiple mapping ambiguities, to build the read-depth signal, and to normalize it. G-CNV can be efficiently used as a third-party tool able to prepare data for the subsequent read-depth signal generation and analysis. Moreover, it can also be integrated in CNV detection tools to generate read-depth signals.

Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate plus nitrate as nitrogen in ground water in the Idaho part of the western Snake River Plain

USGS Publications Warehouse

Donato, Mary M.

2000-01-01

As ground water continues to provide an ever-growing proportion of Idaho?s drinking water, concerns about the quality of that resource are increasing. Pesticides (most commonly, atrazine/desethyl-atrazine, hereafter referred to as atrazine) and nitrite plus nitrate as nitrogen (hereafter referred to as nitrate) have been detected in many aquifers in the State. To provide a sound hydrogeologic basis for atrazine and nitrate management in southern Idaho—the largest region of land and water use in the State—the U.S. Geological Survey produced maps showing the probability of detecting these contaminants in ground water in the upper Snake River Basin (published in a 1998 report) and the western Snake River Plain (published in this report). The atrazine probability map for the western Snake River Plain was constructed by overlaying ground-water quality data with hydrogeologic and anthropogenic data in a geographic information system (GIS). A data set was produced in which each well had corresponding information on land use, geology, precipitation, soil characteristics, regional depth to ground water, well depth, water level, and atrazine use. These data were analyzed by logistic regression using a statistical software package. Several preliminary multivariate models were developed and those that best predicted the detection of atrazine were selected. The multivariate models then were entered into a GIS and the probability maps were produced. Land use, precipitation, soil hydrologic group, and well depth were significantly correlated with atrazine detections in the western Snake River Plain. These variables also were important in the 1998 probability study of the upper Snake River Basin. The effectiveness of the probability models for atrazine might be improved if more detailed data were available for atrazine application. A preliminary atrazine probability map for the entire Snake River Plain in Idaho, based on a data set representing that region, also was produced. In areas where this map overlaps the 1998 map of the upper Snake River Basin, the two maps show broadly similar probabilities of detecting atrazine. Logistic regression also was used to develop a preliminary statistical model that predicts the probability of detecting elevated nitrate in the western Snake River Plain. A nitrate probability map was produced from this model. Results showed that elevated nitrate concentrations were correlated with land use, soil organic content, well depth, and water level. Detailed information on nitrate input, specifically fertilizer application, might have improved the effectiveness of this model.

The artificial object detection and current velocity measurement using SAR ocean surface images

NASA Astrophysics Data System (ADS)

Alpatov, Boris; Strotov, Valery; Ershov, Maksim; Muraviev, Vadim; Feldman, Alexander; Smirnov, Sergey

2017-10-01

Due to the fact that water surface covers wide areas, remote sensing is the most appropriate way of getting information about ocean environment for vessel tracking, security purposes, ecological studies and others. Processing of synthetic aperture radar (SAR) images is extensively used for control and monitoring of the ocean surface. Image data can be acquired from Earth observation satellites, such as TerraSAR-X, ERS, and COSMO-SkyMed. Thus, SAR image processing can be used to solve many problems arising in this field of research. This paper discusses some of them including ship detection, oil pollution control and ocean currents mapping. Due to complexity of the problem several specialized algorithm are necessary to develop. The oil spill detection algorithm consists of the following main steps: image preprocessing, detection of dark areas, parameter extraction and classification. The ship detection algorithm consists of the following main steps: prescreening, land masking, image segmentation combined with parameter measurement, ship orientation estimation and object discrimination. The proposed approach to ocean currents mapping is based on Doppler's law. The results of computer modeling on real SAR images are presented. Based on these results it is concluded that the proposed approaches can be used in maritime applications.

Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

NASA Astrophysics Data System (ADS)

Althuwaynee, Omar F.; Pradhan, Biswajeet; Ahmad, Noordin

2014-06-01

This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies.

Subclinical keratoconus detection by pattern analysis of corneal and epithelial thickness maps with optical coherence tomography

PubMed Central

Li, Yan; Chamberlain, Winston; Tan, Ou; Brass, Robert; Weiss, Jack L.; Huang, David

2016-01-01

PURPOSE To screen for subclinical keratoconus by analyzing corneal, epithelial, and stromal thickness map patterns with Fourier-domain optical coherence tomography (OCT). SETTING Four centers in the United States. DESIGN Cross-sectional observational study. METHODS Eyes of normal subjects, subclinical keratoconus eyes, and the topographically normal eye of a unilateral keratoconus patient were studied. Corneas were scanned using a 26 000 Hz Fourier-domain OCT system (RTVue). Normal subjects were divided into training and evaluation groups. Corneal, epithelial, and stromal thickness maps and derived diagnostic indices, including pattern standard deviation (PSD) variables and pachymetric map–based keratoconus risk scores were calculated from the OCT data. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the diagnostic accuracy of the indices. RESULTS The study comprised 150 eyes of 83 normal subjects, 50 subclinical keratoconus eyes of 32 patients, and 1 topographically normal eye of a unilateral keratoconus patient. Subclinical keratoconus was characterized by inferotemporal thinning of the cornea, epithelium, and stroma. The PSD values for corneal (P < .001), epithelial (P < .001), and stromal (P = .049) thickness maps were all significantly higher in subclinical keratoconic eyes than in the normal group. The diagnostic accuracy was significantly higher for PSD variables (pachymetric PSD, AUC = 0.941; epithelial PSD, AUC = 0.985; stromal PSD, AUC = 0.924) than for the pachymetric map–based keratoconus risk score (AUC = 0.735). CONCLUSIONS High-resolution Fourier-domain OCT could map corneal, epithelial, and stromal thicknesses. Corneal and sublayer thickness changes in subclinical keratoconus could be detected with high accuracy using PSD variables. These new diagnostic variables might be useful in the detection of early keratoconus. PMID:27026454

Performance metrics for state-of-the-art airborne magnetic and electromagnetic systems for mapping and detection of unexploded ordnance

NASA Astrophysics Data System (ADS)

Doll, William E.; Bell, David T.; Gamey, T. Jeffrey; Beard, Les P.; Sheehan, Jacob R.; Norton, Jeannemarie

2010-04-01

Over the past decade, notable progress has been made in the performance of airborne geophysical systems for mapping and detection of unexploded ordnance in terrestrial and shallow marine environments. For magnetometer systems, the most significant improvements include development of denser magnetometer arrays and vertical gradiometer configurations. In prototype analyses and recent Environmental Security Technology Certification Program (ESTCP) assessments using new production systems the greatest sensitivity has been achieved with a vertical gradiometer configuration, despite model-based survey design results which suggest that dense total-field arrays would be superior. As effective as magnetometer systems have proven to be at many sites, they are inadequate at sites where basalts and other ferrous geologic formations or soils produce anomalies that approach or exceed those of target ordnance items. Additionally, magnetometer systems are ineffective where detection of non-ferrous ordnance items is of primary concern. Recent completion of the Battelle TEM-8 airborne time-domain electromagnetic system represents the culmination of nearly nine years of assessment and development of airborne electromagnetic systems for UXO mapping and detection. A recent ESTCP demonstration of this system in New Mexico showed that it was able to detect 99% of blind-seeded ordnance items, 81mm and larger, and that it could be used to map in detail a bombing target on a basalt flow where previous airborne magnetometer surveys had failed. The probability of detection for the TEM-8 in the blind-seeded study area was better than that reported for a dense-array total-field magnetometer demonstration of the same blind-seeded site, and the TEM-8 system successfully detected these items with less than half as many anomaly picks as the dense-array total-field magnetometer system.

Using airborne LiDAR in geoarchaeological contexts: Assessment of an automatic tool for the detection and the morphometric analysis of grazing archaeological structures (French Massif Central).

NASA Astrophysics Data System (ADS)

Roussel, Erwan; Toumazet, Jean-Pierre; Florez, Marta; Vautier, Franck; Dousteyssier, Bertrand

2014-05-01

Airborne laser scanning (ALS) of archaeological regions of interest is nowadays a widely used and established method for accurate topographic and microtopographic survey. The penetration of the vegetation cover by the laser beam allows the reconstruction of reliable digital terrain models (DTM) of forested areas where traditional prospection methods are inefficient, time-consuming and non-exhaustive. The ALS technology provides the opportunity to discover new archaeological features hidden by vegetation and provides a comprehensive survey of cultural heritage sites within their environmental context. However, the post-processing of LiDAR points clouds produces a huge quantity of data in which relevant archaeological features are not easily detectable with common visualizing and analysing tools. Undoubtedly, there is an urgent need for automation of structures detection and morphometric extraction techniques, especially for the "archaeological desert" in densely forested areas. This presentation deals with the development of automatic detection procedures applied to archaeological structures located in the French Massif Central, in the western forested part of the Puy-de-Dôme volcano between 950 and 1100 m a.s.l.. These unknown archaeological sites were discovered by the March 2011 ALS mission and display a high density of subcircular depressions with a corridor access. The spatial organization of these depressions vary from isolated to aggregated or aligned features. Functionally, they appear to be former grazing constructions built from the medieval to the modern period. Similar grazing structures are known in other locations of the French Massif Central (Sancy, Artense, Cézallier) where the ground is vegetation-free. In order to develop a reliable process of automatic detection and mapping of these archaeological structures, a learning zone has been delineated within the ALS surveyed area. The grazing features were mapped and typical morphometric attributes were calculated based on 2 methods: (i) The mapping of the archaeological structures by a human operator using common visualisation tools (DTM, multi-direction hillshading & local relief models) within a GIS environment; (ii) The automatic detection and mapping performed by a recognition algorithm based on a user defined geometric pattern of the grazing structures. The efficiency of the automatic tool has been assessed by comparing the number of structures detected and the morphometric attributes calculated by the two methods. Our results indicate that the algorithm is efficient for the detection and the location of grazing structures. Concerning the morphometric results, there is still a discrepancy between automatic and expert calculations, due to both the expert mapping choices and the algorithm calibration.

Physical mapping of the genomic DNA of the Oryctes rhinoceros baculovirus, KI.

PubMed

Mohan, K S; Gopinathan, K P

1991-11-15

A non-occluded baculovirus, OBV-KI has been isolated from the insect pest, Oryctes rhinoceros. The viral genome is estimated to be 123 kb, with a G + C content of 43 mol% and no detectible methylated bases. A restriction map of the OBV-KI genome for BamHI, EcoRI, HindIII, PstI, SalI and XbaI has been constructed.

HealthCyberMap: a semantic visual browser of medical Internet resources based on clinical codes and the human body metaphor.

PubMed

Kamel Boulos, Maged N; Roudsari, Abdul V; Carso N, Ewart R

2002-12-01

HealthCyberMap (HCM-http://healthcybermap.semanticweb.org) is a web-based service for healthcare professionals and librarians, patients and the public in general that aims at mapping parts of the health information resources in cyberspace in novel ways to improve their retrieval and navigation. HCM adopts a clinical metadata framework built upon a clinical coding ontology for the semantic indexing, classification and browsing of Internet health information resources. A resource metadata base holds information about selected resources. HCM then uses GIS (Geographic Information Systems) spatialization methods to generate interactive navigational cybermaps from the metadata base. These visual cybermaps are based on familiar medical metaphors. HCM cybermaps can be considered as semantically spatialized, ontology-based browsing views of the underlying resource metadata base. Using a clinical coding scheme as a metric for spatialization ('semantic distance') is unique to HCM and is very much suited for the semantic categorization and navigation of Internet health information resources. Clinical codes ensure reliable and unambiguous topical indexing of these resources. HCM also introduces a useful form of cyberspatial analysis for the detection of topical coverage gaps in the resource metadata base using choropleth (shaded) maps of human body systems.

Mycobacterium avium subspecies paratuberculosis in bioaerosols after depopulation and cleaning of two cattle barns.

PubMed

Eisenberg, S; Nielen, M; Hoeboer, J; Bouman, M; Heederik, D; Koets, A

2011-06-04

Settled dust samples were collected on a commercial dairy farm in the Netherlands with a high prevalence of Mycobacterium avium subspecies paratuberculosis (MAP) (barn A) and on a Dutch experimental cattle farm (barn B) stocked with cattle confirmed to be MAP shedders. Barns were sampled while animals were present, after both barns were destocked and cleaned by cold high-pressure cleaning, and after being kept empty for two weeks (barn A) or after additional disinfection (barn B). MAP DNA was detected by IS900 real-time PCR and viable MAP were detected by liquid culture. MAP DNA was detected in 78 per cent of samples from barn A and 86 per cent of samples from barn B collected while animals were still present. Viable MAP was detected in six of nine samples from barn A and in three of seven samples from barn B. After cold high-pressure cleaning, viable MAP could be detected in only two samples from each barn. After leaving barn A empty for two weeks, and following additional disinfection of barn B, no viable MAP could be detected in any settled dust sample.

Detection of IMRT delivery errors based on a simple constancy check of transit dose by using an EPID

NASA Astrophysics Data System (ADS)

Baek, Tae Seong; Chung, Eun Ji; Son, Jaeman; Yoon, Myonggeun

2015-11-01

Beam delivery errors during intensity modulated radiotherapy (IMRT) were detected based on a simple constancy check of the transit dose by using an electronic portal imaging device (EPID). Twenty-one IMRT plans were selected from various treatment sites, and the transit doses during treatment were measured by using an EPID. Transit doses were measured 11 times for each course of treatment, and the constancy check was based on gamma index (3%/3 mm) comparisons between a reference dose map (the first measured transit dose) and test dose maps (the following ten measured dose maps). In a simulation using an anthropomorphic phantom, the average passing rate of the tested transit dose was 100% for three representative treatment sites (head & neck, chest, and pelvis), indicating that IMRT was highly constant for normal beam delivery. The average passing rate of the transit dose for 1224 IMRT fields from 21 actual patients was 97.6% ± 2.5%, with the lower rate possibly being due to inaccuracies of patient positioning or anatomic changes. An EPIDbased simple constancy check may provide information about IMRT beam delivery errors during treatment.

[The primary research and development of software oversampling mapping system for electrocardiogram].

PubMed

Zhou, Yu; Ren, Jie

2011-04-01

We put forward a new concept of software oversampling mapping system for electrocardiogram (ECG) to assist the research of the ECG inverse problem to improve the generality of mapping system and the quality of mapping signals. We then developed a conceptual system based on the traditional ECG detecting circuit, Labview and DAQ card produced by National Instruments, and at the same time combined the newly-developed oversampling method into the system. The results indicated that the system could map ECG signals accurately and the quality of the signals was good. The improvement of hardware and enhancement of software made the system suitable for mapping in different situations. So the primary development of the software for oversampling mapping system was successful and further research and development can make the system a powerful tool for researching ECG inverse problem.

An authenticated image encryption scheme based on chaotic maps and memory cellular automata

NASA Astrophysics Data System (ADS)

Bakhshandeh, Atieh; Eslami, Ziba

2013-06-01

This paper introduces a new image encryption scheme based on chaotic maps, cellular automata and permutation-diffusion architecture. In the permutation phase, a piecewise linear chaotic map is utilized to confuse the plain-image and in the diffusion phase, we employ the Logistic map as well as a reversible memory cellular automata to obtain an efficient and secure cryptosystem. The proposed method admits advantages such as highly secure diffusion mechanism, computational efficiency and ease of implementation. A novel property of the proposed scheme is its authentication ability which can detect whether the image is tampered during the transmission or not. This is particularly important in applications where image data or part of it contains highly sensitive information. Results of various analyses manifest high security of this new method and its capability for practical image encryption.

Multiscale quantification of tissue spiculation and distortion for detection of architectural distortion and spiculated mass in mammography

NASA Astrophysics Data System (ADS)

Lao, Zhiqiang; Zheng, Xin

2011-03-01

This paper proposes a multiscale method to quantify tissue spiculation and distortion in mammography CAD systems that aims at improving the sensitivity in detecting architectural distortion and spiculated mass. This approach addresses the difficulty of predetermining the neighborhood size for feature extraction in characterizing lesions demonstrating spiculated mass/architectural distortion that may appear in different sizes. The quantification is based on the recognition of tissue spiculation and distortion pattern using multiscale first-order phase portrait model in texture orientation field generated by Gabor filter bank. A feature map is generated based on the multiscale quantification for each mammogram and two features are then extracted from the feature map. These two features will be combined with other mass features to provide enhanced discriminate ability in detecting lesions demonstrating spiculated mass and architectural distortion. The efficiency and efficacy of the proposed method are demonstrated with results obtained by applying the method to over 500 cancer cases and over 1000 normal cases.

Recurrence-plot-based measures of complexity and their application to heart-rate-variability data.

PubMed

Marwan, Norbert; Wessel, Niels; Meyerfeldt, Udo; Schirdewan, Alexander; Kurths, Jürgen

2002-08-01

The knowledge of transitions between regular, laminar or chaotic behaviors is essential to understand the underlying mechanisms behind complex systems. While several linear approaches are often insufficient to describe such processes, there are several nonlinear methods that, however, require rather long time observations. To overcome these difficulties, we propose measures of complexity based on vertical structures in recurrence plots and apply them to the logistic map as well as to heart-rate-variability data. For the logistic map these measures enable us not only to detect transitions between chaotic and periodic states, but also to identify laminar states, i.e., chaos-chaos transitions. The traditional recurrence quantification analysis fails to detect the latter transitions. Applying our measures to the heart-rate-variability data, we are able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event. Our findings could be of importance for the therapy of malignant cardiac arrhythmias.

Continuing Long Term Optical and Infrared Reverberation Mapping of 17 Sloan Digital Sky Survey Quasars

NASA Astrophysics Data System (ADS)

Gorjian, Varoujan; Barth, Aaron; Brandt, Niel; Dawson, Kyle; Green, Paul; Ho, Luis; Horne, Keith; Jiang, Linhua; McGreer, Ian; Schneider, Donald; Shen, Yue; Tao, Charling

2018-05-01

Previous Spitzer reverberation monitoring projects searching for UV/optical light absorbed and re-emitted in the IR by dust have been limited to low luminosity active galactic nuclei (AGN) that could potentially show reverberation within a single cycle ( 1 year). Cycle 11-12's two year baseline allowed for the reverberation mapping of 17 high-luminosity quasars from the Sloan Digital Sky Survey Reverberation Mapping project. We continued this monitoring in Cycle 13 and now propose to extend this program in Cycle 14. By combining ground-based monitoring from Pan-STARRS, CFHT, and Steward Observatory telescopes with Spitzer data we have for the first time detected dust reverberation in quasars. By continuing observations with this unqiue combination of resources we should detect reverberation in more objects and reduce the uncertainties for the remaining sources.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

A simple and unsupervised semi-automatic workflow to detect shallow landslides in Alpine areas based on VHR remote sensing data

NASA Astrophysics Data System (ADS)

Amato, Gabriele; Eisank, Clemens; Albrecht, Florian

2017-04-01

Landslide detection from Earth observation imagery is an important preliminary work for landslide mapping, landslide inventories and landslide hazard assessment. In this context, the object-based image analysis (OBIA) concept has been increasingly used over the last decade. Within the framework of the Land@Slide project (Earth observation based landslide mapping: from methodological developments to automated web-based information delivery) a simple, unsupervised, semi-automatic and object-based approach for the detection of shallow landslides has been developed and implemented in the InterIMAGE open-source software. The method was applied to an Alpine case study in western Austria, exploiting spectral information from pansharpened 4-bands WorldView-2 satellite imagery (0.5 m spatial resolution) in combination with digital elevation models. First, we divided the image into sub-images, i.e. tiles, and then we applied the workflow to each of them without changing the parameters. The workflow was implemented as top-down approach: at the image tile level, an over-classification of the potential landslide area was produced; the over-estimated area was re-segmented and re-classified by several processing cycles until most false positive objects have been eliminated. In every step a Baatz algorithm based segmentation generates polygons "candidates" to be landslides. At the same time, the average values of normalized difference vegetation index (NDVI) and brightness are calculated for these polygons; after that, these values are used as thresholds to perform an objects selection in order to improve the quality of the classification results. In combination, also empirically determined values of slope and roughness are used in the selection process. Results for each tile were merged to obtain the landslide map for the test area. For final validation, the landslide map was compared to a geological map and a supervised landslide classification in order to estimate its accuracy. Results for the test area showed that the proposed method is capable of accurately distinguishing landslides from roofs and trees. Implementation of the workflow into InterIMAGE was straightforward. We conclude that the method is able to extract landslides in forested areas, but that there is still room for improvements concerning the extraction in non-forested high-alpine regions.

Comparative mapping in the Fagaceae and beyond with EST-SSRs

PubMed Central

2012-01-01

Background Genetic markers and linkage mapping are basic prerequisites for comparative genetic analyses, QTL detection and map-based cloning. A large number of mapping populations have been developed for oak, but few gene-based markers are available for constructing integrated genetic linkage maps and comparing gene order and QTL location across related species. Results We developed a set of 573 expressed sequence tag-derived simple sequence repeats (EST-SSRs) and located 397 markers (EST-SSRs and genomic SSRs) on the 12 oak chromosomes (2n = 2x = 24) on the basis of Mendelian segregation patterns in 5 full-sib mapping pedigrees of two species: Quercus robur (pedunculate oak) and Quercus petraea (sessile oak). Consensus maps for the two species were constructed and aligned. They showed a high degree of macrosynteny between these two sympatric European oaks. We assessed the transferability of EST-SSRs to other Fagaceae genera and a subset of these markers was mapped in Castanea sativa, the European chestnut. Reasonably high levels of macrosynteny were observed between oak and chestnut. We also obtained diversity statistics for a subset of EST-SSRs, to support further population genetic analyses with gene-based markers. Finally, based on the orthologous relationships between the oak, Arabidopsis, grape, poplar, Medicago, and soybean genomes and the paralogous relationships between the 12 oak chromosomes, we propose an evolutionary scenario of the 12 oak chromosomes from the eudicot ancestral karyotype. Conclusions This study provides map locations for a large set of EST-SSRs in two oak species of recognized biological importance in natural ecosystems. This first step toward the construction of a gene-based linkage map will facilitate the assignment of future genome scaffolds to pseudo-chromosomes. This study also provides an indication of the potential utility of new gene-based markers for population genetics and comparative mapping within and beyond the Fagaceae. PMID:22931513

Construction of an interspecific genetic map based on InDel and SSR for mapping the QTLs affecting the initiation of flower primordia in pepper (Capsicum spp.).

PubMed

Tan, Shu; Cheng, Jiao-Wen; Zhang, Li; Qin, Cheng; Nong, Ding-Guo; Li, Wei-Peng; Tang, Xin; Wu, Zhi-Ming; Hu, Kai-Lin

2015-01-01

Re-sequencing permits the mining of genome-wide variations on a large scale and provides excellent resources for the research community. To accelerate the development and application of molecular markers and identify the QTLs affecting the flowering time-related trait in pepper, a total of 1,038 pairs of InDel and 674 SSR primers from different sources were used for genetic mapping using the F2 population (n = 154) derived from a cross between BA3 (C. annuum) and YNXML (C. frutescens). Of these, a total of 224 simple PCR-based markers, including 129 InDels and 95 SSRs, were validated and integrated into a map, which was designated as the BY map. The BY map consisted of 13 linkage groups (LGs) and spanned a total genetic distance of 1,249.77 cM with an average marker distance of 5.60 cM. Comparative analysis of the genetic and physical map based on the anchored markers showed that the BY map covered nearly the whole pepper genome. Based on the BY map, one major and five minor QTLs affecting the number of leaves on the primary axis (Nle) were detected on chromosomes P2, P7, P10 and P11 in 2012. The major QTL on P2 was confirmed based on another subset of the same F2 population (n = 147) in 2014 with selective genotyping of markers from the BY map. With the accomplishment of pepper whole genome sequencing and annotations (release 2.0), 153 candidate genes were predicted to embed in the Nle2.2 region, of which 12 important flowering related genes were obtained. The InDel/SSR-based interspecific genetic map, QTLs and candidate genes obtained by the present study will be useful for the downstream isolation of flowering time-related gene and other genetic applications for pepper.

Quantitative trait locus mapping under irrigated and drought treatments based on a novel genetic linkage map in mungbean (Vigna radiata L.).

PubMed

Liu, Changyou; Wu, Jing; Wang, Lanfen; Fan, Baojie; Cao, Zhimin; Su, Qiuzhu; Zhang, Zhixiao; Wang, Yan; Tian, Jing; Wang, Shumin

2017-11-01

A novel genetic linkage map was constructed using SSR markers and stable QTLs were identified for six drought tolerance related-traits using single-environment analysis under irrigation and drought treatments. Mungbean (Vigna radiata L.) is one of the most important leguminous food crops. However, mungbean production is seriously constrained by drought. Isolation of drought-responsive genetic elements and marker-assisted selection breeding will benefit from the detection of quantitative trait locus (QTLs) for traits related to drought tolerance. In this study, we developed a full-coverage genetic linkage map based on simple sequence repeat (SSR) markers using a recombinant inbred line (RIL) population derived from an intra-specific cross between two drought-resistant varieties. This novel map was anchored with 313 markers. The total map length was 1010.18 cM across 11 linkage groups, covering the entire genome of mungbean with a saturation of one marker every 3.23 cM. We subsequently detected 58 QTLs for plant height (PH), maximum leaf area (MLA), biomass (BM), relative water content, days to first flowering, and seed yield (Yield) and 5 for the drought tolerance index of 3 traits in irrigated and drought environments at 2 locations. Thirty-eight of these QTLs were consistently detected two or more times at similar linkage positions. Notably, qPH5A and qMLA2A were consistently identified in marker intervals from GMES5773 to MUS128 in LG05 and from Mchr11-34 to the HAAS_VR_1812 region in LG02 in four environments, contributing 6.40-20.06% and 6.97-7.94% of the observed phenotypic variation, respectively. None of these QTLs shared loci with previously identified drought-related loci from mungbean. The results of these analyses might facilitate the isolation of drought-related genes and help to clarify the mechanism of drought tolerance in mungbean.

Object-based image analysis for cadastral mapping using satellite images

NASA Astrophysics Data System (ADS)

Kohli, D.; Crommelinck, S.; Bennett, R.; Koeva, M.; Lemmen, C.

2017-10-01

Cadasters together with land registry form a core ingredient of any land administration system. Cadastral maps comprise of the extent, ownership and value of land which are essential for recording and updating land records. Traditional methods for cadastral surveying and mapping often prove to be labor, cost and time intensive: alternative approaches are thus being researched for creating such maps. With the advent of very high resolution (VHR) imagery, satellite remote sensing offers a tremendous opportunity for (semi)-automation of cadastral boundaries detection. In this paper, we explore the potential of object-based image analysis (OBIA) approach for this purpose by applying two segmentation methods, i.e. MRS (multi-resolution segmentation) and ESP (estimation of scale parameter) to identify visible cadastral boundaries. Results show that a balance between high percentage of completeness and correctness is hard to achieve: a low error of commission often comes with a high error of omission. However, we conclude that the resulting segments/land use polygons can potentially be used as a base for further aggregation into tenure polygons using participatory mapping.

AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework.

PubMed

Zheng, Qi; Grice, Elizabeth A

2016-10-01

Accurate mapping of next-generation sequencing (NGS) reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely) mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost's algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost.

QTL mapping for downy mildew resistance in cucumber via bulked segregant analysis using next-generation sequencing and conventional methods.

PubMed

Win, Khin Thanda; Vegas, Juan; Zhang, Chunying; Song, Kihwan; Lee, Sanghyeob

2017-01-01

QTL mapping using NGS-assisted BSA was successfully applied to an F 2 population for downy mildew resistance in cucumber. QTLs detected by NGS-assisted BSA were confirmed by conventional QTL analysis. Downy mildew (DM), caused by Pseudoperonospora cubensis, is one of the most destructive foliar diseases in cucumber. QTL mapping is a fundamental approach for understanding the genetic inheritance of DM resistance in cucumber. Recently, many studies have reported that a combination of bulked segregant analysis (BSA) and next-generation sequencing (NGS) can be a rapid and cost-effective way of mapping QTLs. In this study, we applied NGS-assisted BSA to QTL mapping of DM resistance in cucumber and confirmed the results by conventional QTL analysis. By sequencing two DNA pools each consisting of ten individuals showing high resistance and susceptibility to DM from a F 2 population, we identified single nucleotide polymorphisms (SNPs) between the two pools. We employed a statistical method for QTL mapping based on these SNPs. Five QTLs, dm2.2, dm4.1, dm5.1, dm5.2, and dm6.1, were detected and dm2.2 showed the largest effect on DM resistance. Conventional QTL analysis using the F 2 confirmed dm2.2 (R 2  = 10.8-24 %) and dm5.2 (R 2  = 14-27.2 %) as major QTLs and dm4.1 (R 2  = 8 %) as two minor QTLs, but could not detect dm5.1 and dm6.1. A new QTL on chromosome 2, dm2.1 (R 2  = 28.2 %) was detected by the conventional QTL method using an F 3 population. This study demonstrated the effectiveness of NGS-assisted BSA for mapping QTLs conferring DM resistance in cucumber and revealed the unique genetic inheritance of DM resistance in this population through two distinct major QTLs on chromosome 2 that mainly harbor DM resistance.

Application of remote sensing to reconnaissance geologic mapping and mineral exploration

NASA Technical Reports Server (NTRS)

Birnie, R. W.; Dykstra, J. D.

1978-01-01

A method of mapping geology at a reconnaissance scale and locating zones of possible hydrothermal alteration has been developed. This method is based on principal component analysis of Landsat digital data and is applied to the desert area of the Chagai Hills, Baluchistan, Pakistan. A method for airborne spectrometric detection of geobotanical anomalies associated with prophyry Cu-Mo mineralization at Heddleston, Montana has also been developed. This method is based on discriminants in the 0.67 micron and 0.79 micron region of the spectrum.

Identification of an EMS-induced causal mutation in a gene required for boron-mediated root development by low-coverage genome re-sequencing in Arabidopsis

PubMed Central

Tabata, Ryo; Kamiya, Takehiro; Shigenobu, Shuji; Yamaguchi, Katsushi; Yamada, Masashi; Hasebe, Mitsuyasu; Fujiwara, Toru; Sawa, Shinichiro

2013-01-01

Next-generation sequencing (NGS) technologies enable the rapid production of an enormous quantity of sequence data. These powerful new technologies allow the identification of mutations by whole-genome sequencing. However, most reported NGS-based mapping methods, which are based on bulked segregant analysis, are costly and laborious. To address these limitations, we designed a versatile NGS-based mapping method that consists of a combination of low- to medium-coverage multiplex SOLiD (Sequencing by Oligonucleotide Ligation and Detection) and classical genetic rough mapping. Using only low to medium coverage reduces the SOLiD sequencing costs and, since just 10 to 20 mutant F2 plants are required for rough mapping, the operation is simple enough to handle in a laboratory with limited space and funding. As a proof of principle, we successfully applied this method to identify the CTR1, which is involved in boron-mediated root development, from among a population of high boron requiring Arabidopsis thaliana mutants. Our work demonstrates that this NGS-based mapping method is a moderately priced and versatile method that can readily be applied to other model organisms. PMID:23104114

Fast object detection algorithm based on HOG and CNN

NASA Astrophysics Data System (ADS)

Lu, Tongwei; Wang, Dandan; Zhang, Yanduo

2018-04-01

In the field of computer vision, object classification and object detection are widely used in many fields. The traditional object detection have two main problems:one is that sliding window of the regional selection strategy is high time complexity and have window redundancy. And the other one is that Robustness of the feature is not well. In order to solve those problems, Regional Proposal Network (RPN) is used to select candidate regions instead of selective search algorithm. Compared with traditional algorithms and selective search algorithms, RPN has higher efficiency and accuracy. We combine HOG feature and convolution neural network (CNN) to extract features. And we use SVM to classify. For TorontoNet, our algorithm's mAP is 1.6 percentage points higher. For OxfordNet, our algorithm's mAP is 1.3 percentage higher.

Global Coverage Measurement Planning Strategies for Mobile Robots Equipped with a Remote Gas Sensor

PubMed Central

Arain, Muhammad Asif; Trincavelli, Marco; Cirillo, Marcello; Schaffernicht, Erik; Lilienthal, Achim J.

2015-01-01

The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose an algorithm that leverages a novel method based on convex relaxation for quickly solving sensor placement problems, and for generating an efficient exploration plan for the robot. To demonstrate the applicability of our method to real-world environments, we performed a large number of experimental trials, both on randomly generated maps and on the map of a real environment. Our approach proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions. PMID:25803707

Global coverage measurement planning strategies for mobile robots equipped with a remote gas sensor.

PubMed

Arain, Muhammad Asif; Trincavelli, Marco; Cirillo, Marcello; Schaffernicht, Erik; Lilienthal, Achim J

2015-03-20

The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose an algorithm that leverages a novel method based on convex relaxation for quickly solving sensor placement problems, and for generating an efficient exploration plan for the robot. To demonstrate the applicability of our method to real-world environments, we performed a large number of experimental trials, both on randomly generated maps and on the map of a real environment. Our approach proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions.

Active Fire Mapping Program

MedlinePlus

Active Fire Mapping Program Current Large Incidents (Home) New Large Incidents Fire Detection Maps MODIS Satellite Imagery VIIRS Satellite Imagery Fire Detection GIS Data Fire Data in Google Earth ...

Structured product labeling improves detection of drug-intolerance issues.

PubMed

Schadow, Gunther

2009-01-01

This study sought to assess the value of the Health Level 7/U.S. Food and Drug Administration Structured Product Labeling (SPL) drug knowledge representation standard and its associated terminology sources for drug-intolerance (allergy) decision support in computerized provider order entry (CPOE) systems. The Regenstrief Institute CPOE drug-intolerance issue detection system and its knowledge base was compared with a method based on existing SPL label content enriched with knowledge sources used with SPL (NDF-RT/MeSH). Both methods were applied to a large set of drug-intolerance (allergy) records, drug orders, and medication dispensing records covering >50,000 patients over 30 years. The number of drug-intolerance issues detected by both methods was counted, as well as the number of patients with issues, number of distinct drugs, and number of distinct intolerances. The difference between drug-intolerance issues detected or missed by either method was qualitatively analyzed. Although <70% of terms were mapped to SPL, the new approach detected four times as many drug-intolerance issues on twice as many patients. The SPL-based approach is more sensitive and suggests that mapping local dictionaries to SPL, and enhancing the depth and breadth of coverage of SPL content are worth accelerating. The study also highlights specificity problems known to trouble drug-intolerance decision support and suggests how terminology and methods of recording drug intolerances could be improved.

Structured Product Labeling Improves Detection of Drug-intolerance Issues

PubMed Central

Schadow, Gunther

2009-01-01

Objectives This study sought to assess the value of the Health Level 7/U.S. Food and Drug Administration Structured Product Labeling (SPL) drug knowledge representation standard and its associated terminology sources for drug-intolerance (allergy) decision support in computerized provider order entry (CPOE) systems. Design The Regenstrief Institute CPOE drug-intolerance issue detection system and its knowledge base was compared with a method based on existing SPL label content enriched with knowledge sources used with SPL (NDF-RT/MeSH). Both methods were applied to a large set of drug-intolerance (allergy) records, drug orders, and medication dispensing records covering >50,000 patients over 30 years. Measurements The number of drug-intolerance issues detected by both methods was counted, as well as the number of patients with issues, number of distinct drugs, and number of distinct intolerances. The difference between drug-intolerance issues detected or missed by either method was qualitatively analyzed. Results Although <70% of terms were mapped to SPL, the new approach detected four times as many drug-intolerance issues on twice as many patients. Conclusion The SPL-based approach is more sensitive and suggests that mapping local dictionaries to SPL, and enhancing the depth and breadth of coverage of SPL content are worth accelerating. The study also highlights specificity problems known to trouble drug-intolerance decision support and suggests how terminology and methods of recording drug intolerances could be improved. PMID:18952933

Calculating Higher-Order Moments of Phylogenetic Stochastic Mapping Summaries in Linear Time.

PubMed

Dhar, Amrit; Minin, Vladimir N

2017-05-01

Stochastic mapping is a simulation-based method for probabilistically mapping substitution histories onto phylogenies according to continuous-time Markov models of evolution. This technique can be used to infer properties of the evolutionary process on the phylogeny and, unlike parsimony-based mapping, conditions on the observed data to randomly draw substitution mappings that do not necessarily require the minimum number of events on a tree. Most stochastic mapping applications simulate substitution mappings only to estimate the mean and/or variance of two commonly used mapping summaries: the number of particular types of substitutions (labeled substitution counts) and the time spent in a particular group of states (labeled dwelling times) on the tree. Fast, simulation-free algorithms for calculating the mean of stochastic mapping summaries exist. Importantly, these algorithms scale linearly in the number of tips/leaves of the phylogenetic tree. However, to our knowledge, no such algorithm exists for calculating higher-order moments of stochastic mapping summaries. We present one such simulation-free dynamic programming algorithm that calculates prior and posterior mapping variances and scales linearly in the number of phylogeny tips. Our procedure suggests a general framework that can be used to efficiently compute higher-order moments of stochastic mapping summaries without simulations. We demonstrate the usefulness of our algorithm by extending previously developed statistical tests for rate variation across sites and for detecting evolutionarily conserved regions in genomic sequences.

Calculating Higher-Order Moments of Phylogenetic Stochastic Mapping Summaries in Linear Time

PubMed Central

Dhar, Amrit

2017-01-01

Abstract Stochastic mapping is a simulation-based method for probabilistically mapping substitution histories onto phylogenies according to continuous-time Markov models of evolution. This technique can be used to infer properties of the evolutionary process on the phylogeny and, unlike parsimony-based mapping, conditions on the observed data to randomly draw substitution mappings that do not necessarily require the minimum number of events on a tree. Most stochastic mapping applications simulate substitution mappings only to estimate the mean and/or variance of two commonly used mapping summaries: the number of particular types of substitutions (labeled substitution counts) and the time spent in a particular group of states (labeled dwelling times) on the tree. Fast, simulation-free algorithms for calculating the mean of stochastic mapping summaries exist. Importantly, these algorithms scale linearly in the number of tips/leaves of the phylogenetic tree. However, to our knowledge, no such algorithm exists for calculating higher-order moments of stochastic mapping summaries. We present one such simulation-free dynamic programming algorithm that calculates prior and posterior mapping variances and scales linearly in the number of phylogeny tips. Our procedure suggests a general framework that can be used to efficiently compute higher-order moments of stochastic mapping summaries without simulations. We demonstrate the usefulness of our algorithm by extending previously developed statistical tests for rate variation across sites and for detecting evolutionarily conserved regions in genomic sequences. PMID:28177780

MS lesion segmentation using a multi-channel patch-based approach with spatial consistency

NASA Astrophysics Data System (ADS)

Mechrez, Roey; Goldberger, Jacob; Greenspan, Hayit

2015-03-01

This paper presents an automatic method for segmentation of Multiple Sclerosis (MS) in Magnetic Resonance Images (MRI) of the brain. The approach is based on similarities between multi-channel patches (T1, T2 and FLAIR). An MS lesion patch database is built using training images for which the label maps are known. For each patch in the testing image, k similar patches are retrieved from the database. The matching labels for these k patches are then combined to produce an initial segmentation map for the test case. Finally a novel iterative patch-based label refinement process based on the initial segmentation map is performed to ensure spatial consistency of the detected lesions. A leave-one-out evaluation is done for each testing image in the MS lesion segmentation challenge of MICCAI 2008. Results are shown to compete with the state-of-the-art methods on the MICCAI 2008 challenge.

Invasive species detection in Hawaiian rainforests using airborne imaging spectroscopy and LiDAR

Treesearch

Gregory P. Asner; David E. Knapp; Ty Kennedy-Bodoin; Matthew O. Jones; Roberta E. Martin; Joseph Boardman; Flint Hughes

2008-01-01

Remote sensing of invasive species is a critical component of conservation and management efforts, but reliable methods for the detection of invaders have not been widely established. In Hawaiian forests, we recently found that invasive trees often have hyperspectral signatures unique from that of native trees, but mapping based on spectral reflectance properties alone...

Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection.

Treesearch

Sean P. Healey; Warren B. Cohen; Yang Zhiqiang; Olga N. Krankina

2005-01-01

Landsat satellite data has become ubiquitous in regional-scale forest disturbance detection. The Tasseled Cap (TC) transformation for Landsat data has been used in several disturbance-mapping projects because of its ability to highlight relevant vegetation changes. We used an automated composite analysis procedure to test four multi-date variants of the TC...

Detecting changes in student teachers' conceptions of teaching science to adolescent English language learners

NASA Astrophysics Data System (ADS)

Pomeroy, Jonathon Richard

2000-10-01

This research study investigated the changes that occurred in six student teachers' conceptions of teaching science to adolescent English language learners over the duration of their participation in a one-year, graduate level, science teacher education program. Cases were created for each of the student teachers based on their concept maps, writing samples, interviews, lesson plans, informal interviews with cooperating teachers, and observation notes collected on biweekly visitations. The cases were divided into three dyads each consisting of two student teachers with similar preprogram and student teaching experiences. Cross case analysis revealed the existence of seven themes related to teaching science to adolescent English language learners. Further analysis suggested that student teachers that worked with experienced cooperating teachers and who had achieved a sense of autonomy over their student teaching demonstrated broad and sophisticated growth across all seven themes. Student teachers who had not achieved a sense of autonomy, demonstrated growth in two to three themes. Student teachers who demonstrated broad and sophisticated growth were able to clearly articulate their conceptions of teaching science to English language learners where as those who demonstrated limited growth were not. This research establishes the use of concept maps as a tool for detecting changes in student teachers' conceptions of teaching science to adolescent English language learners as well as the sensitivity of concept maps to detect the types of changes historically detected by writing samples and interviews. Recommendations based on the implications from are included.

Vision based speed breaker detection for autonomous vehicle

NASA Astrophysics Data System (ADS)

C. S., Arvind; Mishra, Ritesh; Vishal, Kumar; Gundimeda, Venugopal

2018-04-01

In this paper, we are presenting a robust and real-time, vision-based approach to detect speed breaker in urban environments for autonomous vehicle. Our method is designed to detect the speed breaker using visual inputs obtained from a camera mounted on top of a vehicle. The method performs inverse perspective mapping to generate top view of the road and segment out region of interest based on difference of Gaussian and median filter images. Furthermore, the algorithm performs RANSAC line fitting to identify the possible speed breaker candidate region. This initial guessed region via RANSAC, is validated using support vector machine. Our algorithm can detect different categories of speed breakers on cement, asphalt and interlock roads at various conditions and have achieved a recall of 0.98.

An overload behavior detection system for engineering transport vehicles based on deep learning

NASA Astrophysics Data System (ADS)

Zhou, Libo; Wu, Gang

2018-04-01

This paper builds an overloaded truck detect system called ITMD to help traffic department automatically identify the engineering transport vehicles (commonly known as `dirt truck') in CCTV and determine whether the truck is overloaded or not. We build the ITMD system based on the Single Shot MultiBox Detector (SSD) model. By constructing the image dataset of the truck and adjusting hyper-parameters of the original SSD neural network, we successfully trained a basic network model which the ITMD system depends on. The basic ITMD system achieves 83.01% mAP on classifying overload/non-overload truck, which is a not bad result. Still, some shortcomings of basic ITMD system have been targeted to enhance: it is easy for the ITMD system to misclassify other similar vehicle as truck. In response to this problem, we optimized the basic ITMD system, which effectively reduced basic model's false recognition rate. The optimized ITMD system achieved 86.18% mAP on the test set, which is better than the 83.01% mAP of the basic ITMD system.

Exploiting rice-sorghum synteny for targeted development of EST-SSRs to enrich the sorghum genetic linkage map.

PubMed

Ramu, P; Kassahun, B; Senthilvel, S; Ashok Kumar, C; Jayashree, B; Folkertsma, R T; Reddy, L Ananda; Kuruvinashetti, M S; Haussmann, B I G; Hash, C T

2009-11-01

The sequencing and detailed comparative functional analysis of genomes of a number of select botanical models open new doors into comparative genomics among the angiosperms, with potential benefits for improvement of many orphan crops that feed large populations. In this study, a set of simple sequence repeat (SSR) markers was developed by mining the expressed sequence tag (EST) database of sorghum. Among the SSR-containing sequences, only those sharing considerable homology with rice genomic sequences across the lengths of the 12 rice chromosomes were selected. Thus, 600 SSR-containing sorghum EST sequences (50 homologous sequences on each of the 12 rice chromosomes) were selected, with the intention of providing coverage for corresponding homologous regions of the sorghum genome. Primer pairs were designed and polymorphism detection ability was assessed using parental pairs of two existing sorghum mapping populations. About 28% of these new markers detected polymorphism in this 4-entry panel. A subset of 55 polymorphic EST-derived SSR markers were mapped onto the existing skeleton map of a recombinant inbred population derived from cross N13 x E 36-1, which is segregating for Striga resistance and the stay-green component of terminal drought tolerance. These new EST-derived SSR markers mapped across all 10 sorghum linkage groups, mostly to regions expected based on prior knowledge of rice-sorghum synteny. The ESTs from which these markers were derived were then mapped in silico onto the aligned sorghum genome sequence, and 88% of the best hits corresponded to linkage-based positions. This study demonstrates the utility of comparative genomic information in targeted development of markers to fill gaps in linkage maps of related crop species for which sufficient genomic tools are not available.

TU-EF-204-03: Task-Based KV and MAs Optimization for Radiation Dose Reduction in CT: From FBP to Statistical Model-Based Iterative Reconstruction (MBIR)

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

Gomez-Cardona, D; Li, K; Lubner, M G

Purpose: The introduction of the highly nonlinear MBIR algorithm to clinical CT systems has made CNR an invalid metric for kV optimization. The purpose of this work was to develop a task-based framework to unify kV and mAs optimization for both FBP- and MBIR-based CT systems. Methods: The kV-mAs optimization was formulated as a constrained minimization problem: to select kV and mAs to minimize dose under the constraint of maintaining the detection performance as clinically prescribed. To experimentally solve this optimization problem, exhaustive measurements of detectability index (d’) for a hepatic lesion detection task were performed at 15 different mAmore » levels and 4 kV levels using an anthropomorphic phantom. The measured d’ values were used to generate an iso-detectability map; similarly, dose levels recorded at different kV-mAs combinations were used to generate an iso-dose map. The iso-detectability map was overlaid on top of the iso-dose map so that for a prescribed detectability level d’, the optimal kV-mA can be determined from the crossing between the d’ contour and the dose contour that corresponds to the minimum dose. Results: Taking d’=16 as an example: the kV-mAs combinations on the measured iso-d’ line of MBIR are 80–150 (3.8), 100–140 (6.6), 120–150 (11.3), and 140–160 (17.2), where values in the parentheses are measured dose values. As a Result, the optimal kV was 80 and optimal mA was 150. In comparison, the optimal kV and mA for FBP were 100 and 500, which corresponded to a dose level of 24 mGy. Results of in vivo animal experiments were consistent with the phantom results. Conclusion: A new method to optimize kV and mAs selection has been developed. This method is applicable to both linear and nonlinear CT systems such as those using MBIR. Additional dose savings can be achieved by combining MBIR with this method. This work was partially supported by an NIH grant R01CA169331 and GE Healthcare. K. Li, D. Gomez-Cardona, M. G. Lubner: Nothing to disclose. P. J. Pickhardt: Co-founder, VirtuoCTC, LLC Stockholder, Cellectar Biosciences, Inc. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.« less

Anti-impulse-noise Edge Detection via Anisotropic Morphological Directional Derivatives.

PubMed

Shui, Peng-Lang; Wang, Fu-Ping

2017-07-13

Traditional differential-based edge detection suffers from abrupt degradation in performance when images are corrupted by impulse noises. The morphological operators such as the median filters and weighted median filters possess the intrinsic ability to counteract impulse noise. In this paper, by combining the biwindow configuration with weighted median filters, anisotropic morphological directional derivatives (AMDD) robust to impulse noise are proposed to measure the local grayscale variation around a pixel. For ideal step edges, the AMDD spatial response and directional representation are derived. The characteristics and edge resolution of two kinds of typical biwindows are analyzed thoroughly. In terms of the AMDD spatial response and directional representation of ideal step edges, the spatial matched filter is used to extract the edge strength map (ESM) from the AMDDs of an image. The spatial and directional matched filters are used to extract the edge direction map (EDM). Embedding the extracted ESM and EDM into the standard route of the differential-based edge detection, an anti-impulse-noise AMDD-based edge detector is constructed. It is compared with the existing state-of-the-art detectors on a recognized image dataset for edge detection evaluation. The results show that it attains competitive performance in noise-free and Gaussian noise cases and the best performance in impulse noise cases.

GPU-BSM: A GPU-Based Tool to Map Bisulfite-Treated Reads

PubMed Central

Manconi, Andrea; Orro, Alessandro; Manca, Emanuele; Armano, Giuliano; Milanesi, Luciano

2014-01-01

Cytosine DNA methylation is an epigenetic mark implicated in several biological processes. Bisulfite treatment of DNA is acknowledged as the gold standard technique to study methylation. This technique introduces changes in the genomic DNA by converting cytosines to uracils while 5-methylcytosines remain nonreactive. During PCR amplification 5-methylcytosines are amplified as cytosine, whereas uracils and thymines as thymine. To detect the methylation levels, reads treated with the bisulfite must be aligned against a reference genome. Mapping these reads to a reference genome represents a significant computational challenge mainly due to the increased search space and the loss of information introduced by the treatment. To deal with this computational challenge we devised GPU-BSM, a tool based on modern Graphics Processing Units. Graphics Processing Units are hardware accelerators that are increasingly being used successfully to accelerate general-purpose scientific applications. GPU-BSM is a tool able to map bisulfite-treated reads from whole genome bisulfite sequencing and reduced representation bisulfite sequencing, and to estimate methylation levels, with the goal of detecting methylation. Due to the massive parallelization obtained by exploiting graphics cards, GPU-BSM aligns bisulfite-treated reads faster than other cutting-edge solutions, while outperforming most of them in terms of unique mapped reads. PMID:24842718

Geographic Information Technologies as an outreach activity in geo-scientific education

NASA Astrophysics Data System (ADS)

Maman, Shimrit; Isaacson, Sivan; Blumberg, Dan G.

2016-04-01

In recent years, a decline in the rates of examinees in the academic track that were entitled to an enhanced matriculation certificate in scientific-technological education was reported in Israel. To confront this problem the Earth and Planetary Image Facility (EPIF) at Ben-Gurion University of the Negev fosters interdisciplinary exploration through educational programs that make use of the facility and its equipment and enable the empowerment of the community by understanding and appreciating science and technology. This is achieved by using Geographic Information Technologies (GIT) such as remote sensing and Geographical Information Systems (GIS) for geo-physical sciences in activities that combine theoretical background with hands-on activities. Monitoring Earth from space by satellites, digital atlases and virtual-based positioning applications are examples for fusion of spatial information (geographic) and technology that the activity is based on. GIT opens a new chapter and a recent history of Cartography starting from the collection of spatial data to its presentation and analysis. GIS have replaced the use of classical atlas books and offer a variety of Web-based applications that provide maps and display up-to-date imagery. The purpose of this workshop is to expose teachers and students to GITs which are applicable in every classroom. The activity imparts free geographic information systems that exist in cyberspace and accessible to single users as the Israeli national GIS and Google earth, which are based on a spatial data and long term local and global satellite imagery coverage. In this paper, our "Think global-Map Local" activity is presented. The activity uses GIS and change detection technologies as means to encourage students to explore environmental issues both around the globe and close to their surroundings. The students detect changes by comparing multi temporal images of a chosen site and learn how to map the alterations and produce change detection maps with simple and user friendly tools. The activity is offered both for students and supervised projects for teachers and youth.

Integrated optical sensors for 2D spatial chemical mapping (Conference Presentation)

NASA Astrophysics Data System (ADS)

Flores, Raquel; Janeiro, Ricardo; Viegas, Jaime

2017-02-01

Sensors based on optical waveguides for chemical sensing have attracted increasing interest over the last two decades, fueled by potential applications in commercial lab-on-a-chip devices for medical and food safety industries. Even though the early studies were oriented for single-point detection, progress in device size reduction and device yield afforded by photonics foundries have opened the opportunity for distributed dynamic chemical sensing at the microscale. This will allow researchers to follow the dynamics of chemical species in field of microbiology, and microchemistry, with a complementary method to current technologies based on microfluorescence and hyperspectral imaging. The study of the chemical dynamics at the surface of photoelectrodes in water splitting cells are a good candidate to benefit from such optochemical sensing devices that includes a photonic integrated circuit (PIC) with multiple sensors for real-time detection and spatial mapping of chemical species. In this project, we present experimental results on a prototype integrated optical system for chemical mapping based on the interaction of cascaded resonant optical devices, spatially covered with chemically sensitive polymers and plasmon-enhanced nanostructured metal/metal-oxide claddings offering chemical selectivity in a pixelated surface. In order to achieve a compact footprint, the prototype is based in a silicon photonics platform. A discussion on the relative merits of a photonic platform based on large bandgap metal oxides and nitrides which have higher chemical resistance than silicon is also presented.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Updating Landsat-derived land-cover maps using change detection and masking techniques

NASA Technical Reports Server (NTRS)

Likens, W.; Maw, K.

1982-01-01

The California Integrated Remote Sensing System's San Bernardino County Project was devised to study the utilization of a data base at a number of jurisdictional levels. The present paper discusses the implementation of change-detection and masking techniques in the updating of Landsat-derived land-cover maps. A baseline landcover classification was first created from a 1976 image, then the adjusted 1976 image was compared with a 1979 scene by the techniques of (1) multidate image classification, (2) difference image-distribution tails thresholding, (3) difference image classification, and (4) multi-dimensional chi-square analysis of a difference image. The union of the results of methods 1, 3 and 4 was used to create a mask of possible change areas between 1976 and 1979, which served to limit analysis of the update image and reduce comparison errors in unchanged areas. The techniques of spatial smoothing of change-detection products, and of combining results of difference change-detection algorithms are also shown to improve Landsat change-detection accuracies.

a Weighted Closed-Form Solution for Rgb-D Data Registration

NASA Astrophysics Data System (ADS)

Vestena, K. M.; Dos Santos, D. R.; Oilveira, E. M., Jr.; Pavan, N. L.; Khoshelham, K.

2016-06-01

Existing 3D indoor mapping of RGB-D data are prominently point-based and feature-based methods. In most cases iterative closest point (ICP) and its variants are generally used for pairwise registration process. Considering that the ICP algorithm requires an relatively accurate initial transformation and high overlap a weighted closed-form solution for RGB-D data registration is proposed. In this solution, we weighted and normalized the 3D points based on the theoretical random errors and the dual-number quaternions are used to represent the 3D rigid body motion. Basically, dual-number quaternions provide a closed-form solution by minimizing a cost function. The most important advantage of the closed-form solution is that it provides the optimal transformation in one-step, it does not need to calculate good initial estimates and expressively decreases the demand for computer resources in contrast to the iterative method. Basically, first our method exploits RGB information. We employed a scale invariant feature transformation (SIFT) for extracting, detecting, and matching features. It is able to detect and describe local features that are invariant to scaling and rotation. To detect and filter outliers, we used random sample consensus (RANSAC) algorithm, jointly with an statistical dispersion called interquartile range (IQR). After, a new RGB-D loop-closure solution is implemented based on the volumetric information between pair of point clouds and the dispersion of the random errors. The loop-closure consists to recognize when the sensor revisits some region. Finally, a globally consistent map is created to minimize the registration errors via a graph-based optimization. The effectiveness of the proposed method is demonstrated with a Kinect dataset. The experimental results show that the proposed method can properly map the indoor environment with an absolute accuracy around 1.5% of the travel of a trajectory.

Interactive remote data processing using Pixelize Wavelet Filtration (PWF-method) and PeriodMap analysis

NASA Astrophysics Data System (ADS)

Sych, Robert; Nakariakov, Valery; Anfinogentov, Sergey

Wavelet analysis is suitable for investigating waves and oscillating in solar atmosphere, which are limited in both time and frequency. We have developed an algorithms to detect this waves by use the Pixelize Wavelet Filtration (PWF-method). This method allows to obtain information about the presence of propagating and non-propagating waves in the data observation (cube images), and localize them precisely in time as well in space. We tested the algorithm and found that the results of coronal waves detection are consistent with those obtained by visual inspection. For fast exploration of the data cube, in addition, we applied early-developed Period- Map analysis. This method based on the Fast Fourier Transform and allows on initial stage quickly to look for "hot" regions with the peak harmonic oscillations and determine spatial distribution at the significant harmonics. We propose the detection procedure of coronal waves separate on two parts: at the first part, we apply the PeriodMap analysis (fast preparation) and than, at the second part, use information about spatial distribution of oscillation sources to apply the PWF-method (slow preparation). There are two possible algorithms working with the data: in automatic and hands-on operation mode. Firstly we use multiply PWF analysis as a preparation narrowband maps at frequency subbands multiply two and/or harmonic PWF analysis for separate harmonics in a spectrum. Secondly we manually select necessary spectral subband and temporal interval and than construct narrowband maps. For practical implementation of the proposed methods, we have developed the remote data processing system at Institute of Solar-Terrestrial Physics, Irkutsk. The system based on the data processing server - http://pwf.iszf.irk.ru. The main aim of this resource is calculation in remote access through the local and/or global network (Internet) narrowband maps of wave's sources both in whole spectral band and at significant harmonics. In addition, we can obtain temporal dynamics (mpeg- files) of the main oscillation characteristics: amplitude, power and phase as a spatial-temporal coordinates. For periodogram mapping of data cubes as a method for the pre-analysis, we developed preparation of the color maps where the pixel's colour corresponds to the frequency of the power spectrum maximum. The computer system based on applications ION-scripts, algorithmic languages IDL and PHP, and Apache WEB server. The IDL ION-scripts use for preparation and configuration of network requests at the central data server with subsequent connection to IDL run-unit software and graphic output on FTP-server and screen. Web page is constructed using PHP language.

A Robust Crowdsourcing-Based Indoor Localization System.

PubMed

Zhou, Baoding; Li, Qingquan; Mao, Qingzhou; Tu, Wei

2017-04-14

WiFi fingerprinting-based indoor localization has been widely used due to its simplicity and can be implemented on the smartphones. The major drawback of WiFi fingerprinting is that the radio map construction is very labor-intensive and time-consuming. Another drawback of WiFi fingerprinting is the Received Signal Strength (RSS) variance problem, caused by environmental changes and device diversity. RSS variance severely degrades the localization accuracy. In this paper, we propose a robust crowdsourcing-based indoor localization system (RCILS). RCILS can automatically construct the radio map using crowdsourcing data collected by smartphones. RCILS abstracts the indoor map as the semantics graph in which the edges are the possible user paths and the vertexes are the location where users may take special activities. RCILS extracts the activity sequence contained in the trajectories by activity detection and pedestrian dead-reckoning. Based on the semantics graph and activity sequence, crowdsourcing trajectories can be located and a radio map is constructed based on the localization results. For the RSS variance problem, RCILS uses the trajectory fingerprint model for indoor localization. During online localization, RCILS obtains an RSS sequence and realizes localization by matching the RSS sequence with the radio map. To evaluate RCILS, we apply RCILS in an office building. Experiment results demonstrate the efficiency and robustness of RCILS.

A Robust Crowdsourcing-Based Indoor Localization System

PubMed Central

Zhou, Baoding; Li, Qingquan; Mao, Qingzhou; Tu, Wei

2017-01-01

WiFi fingerprinting-based indoor localization has been widely used due to its simplicity and can be implemented on the smartphones. The major drawback of WiFi fingerprinting is that the radio map construction is very labor-intensive and time-consuming. Another drawback of WiFi fingerprinting is the Received Signal Strength (RSS) variance problem, caused by environmental changes and device diversity. RSS variance severely degrades the localization accuracy. In this paper, we propose a robust crowdsourcing-based indoor localization system (RCILS). RCILS can automatically construct the radio map using crowdsourcing data collected by smartphones. RCILS abstracts the indoor map as the semantics graph in which the edges are the possible user paths and the vertexes are the location where users may take special activities. RCILS extracts the activity sequence contained in the trajectories by activity detection and pedestrian dead-reckoning. Based on the semantics graph and activity sequence, crowdsourcing trajectories can be located and a radio map is constructed based on the localization results. For the RSS variance problem, RCILS uses the trajectory fingerprint model for indoor localization. During online localization, RCILS obtains an RSS sequence and realizes localization by matching the RSS sequence with the radio map. To evaluate RCILS, we apply RCILS in an office building. Experiment results demonstrate the efficiency and robustness of RCILS. PMID:28420108

Synchrotron-based FTIR microspectroscopy for the mapping of photo-oxidation and additives in acrylonitrile-butadiene-styrene model samples and historical objects.

PubMed

Saviello, Daniela; Pouyet, Emeline; Toniolo, Lucia; Cotte, Marine; Nevin, Austin

2014-09-16

Synchrotron-based Fourier transform infrared micro-spectroscopy (SR-μFTIR) was used to map photo-oxidative degradation of acrylonitrile-butadiene-styrene (ABS) and to investigate the presence and the migration of additives in historical samples from important Italian design objects. High resolution (3×3 μm(2)) molecular maps were obtained by FTIR microspectroscopy in transmission mode, using a new method for the preparation of polymer thin sections. The depth of photo-oxidation in samples was evaluated and accompanied by the formation of ketones, aldehydes, esters, and unsaturated carbonyl compounds. This study demonstrates selective surface oxidation and a probable passivation of material against further degradation. In polymer fragments from design objects made of ABS from the 1960s, UV-stabilizers were detected and mapped, and microscopic inclusions of proteinaceous material were identified and mapped for the first time. Copyright © 2014 Elsevier B.V. All rights reserved.

Patellar cartilage lesions: comparison of magnetic resonance imaging and T2 relaxation-time mapping.

PubMed

Hannila, I; Nieminen, M T; Rauvala, E; Tervonen, O; Ojala, R

2007-05-01

To evaluate the detection and the size of focal patellar cartilage lesions in T2 mapping as compared to standard clinical magnetic resonance imaging (MRI) at 1.5T. Fifty-five consecutive clinical patients referred to knee MRI were imaged both with a standard knee MRI protocol (proton-density-weighted sagittal and axial series, T2-weighted sagittal and coronal series, and T1-weighted coronal series) and with an axial multislice multi-echo spin-echo measurement to determine the T2 relaxation time of the patellar cartilage. MR images and T2 maps of patellar cartilage were evaluated for focal lesions. The lesions were evaluated for lesion width (mm), lesion depth (1/3, 2/3, or 3/3 of cartilage thickness), and T2 value (20-40 ms, 40-60 ms, or 60-80 ms) based on visual evaluation. Altogether, 36 focal patellar cartilage lesions were detected from 20 human subjects (11 male, nine female, mean age 40+/-15 years). Twenty-eight lesions were detected both on MRI and T2 maps, while eight lesions were only visible on T2 maps. Cartilage lesions were significantly wider (P = 0.001) and thicker (P<0.001) on T2 maps as compared to standard knee MRI. Most lesions 27 had moderately (T2 40-60 ms) increased T2 values, while two lesions had slightly (T2 20-40 ms) and seven lesions remarkably (T2 60-80 ms) increased T2 relaxation times. T2 mapping of articular cartilage is feasible in the clinical setting and may reveal early cartilage lesions not visible with standard clinical MRI.

Increased detection of precancerous cervical lesions with adjunctive dynamic spectral imaging.

PubMed

DeNardis, Sara A; Lavin, Philip T; Livingston, Jeff; Salter, William R; James-Patrick, Nanette; Papagiannakis, Emmanouil; Olson, Christopher G; Weinberg, Lori

2017-01-01

To validate, in US community-based colposcopy clinics, previous reports of increased detection of high-grade cervical intraepithelial neoplasia (CIN2+) with biopsies selected using dynamic spectral imaging (DSI) mapping after standard colposcopy. Cross-sectional observational study of 26 colposcopists across nine clinics recruiting consecutive colposcopy patients. Standard assessment with biopsy selections was completed before seeing the DSI map which was subsequently interpreted and used for additional biopsies per clinical judgment. Primary measure was the number of women with CIN2+ detected by DSI-assisted biopsies, over those detected by standard colposcopy biopsies. A total of 887 women were recruited. After exclusions, 881 women and 1,189 biopsies were analyzed. Standard biopsy detected 78 women with CIN2+ and DSI-assisted biopsies another 34, increasing the detection rate from 8.85% to 12.71% ( p =0.00016). This was achieved with 16.16% of DSI-assisted biopsies finding CIN2+ compared to 13.24% for the preceding standard biopsies. For secondary specificity analysis, 431 women had only

Increased detection of precancerous cervical lesions with adjunctive dynamic spectral imaging

PubMed Central

DeNardis, Sara A; Lavin, Philip T; Livingston, Jeff; Salter, William R; James-Patrick, Nanette; Papagiannakis, Emmanouil; Olson, Christopher G; Weinberg, Lori

2017-01-01

Objective To validate, in US community-based colposcopy clinics, previous reports of increased detection of high-grade cervical intraepithelial neoplasia (CIN2+) with biopsies selected using dynamic spectral imaging (DSI) mapping after standard colposcopy. Study design Cross-sectional observational study of 26 colposcopists across nine clinics recruiting consecutive colposcopy patients. Standard assessment with biopsy selections was completed before seeing the DSI map which was subsequently interpreted and used for additional biopsies per clinical judgment. Primary measure was the number of women with CIN2+ detected by DSI-assisted biopsies, over those detected by standard colposcopy biopsies. Results A total of 887 women were recruited. After exclusions, 881 women and 1,189 biopsies were analyzed. Standard biopsy detected 78 women with CIN2+ and DSI-assisted biopsies another 34, increasing the detection rate from 8.85% to 12.71% (p=0.00016). This was achieved with 16.16% of DSI-assisted biopsies finding CIN2+ compared to 13.24% for the preceding standard biopsies. For secondary specificity analysis, 431 women had only

Fusion of pixel and object-based features for weed mapping using unmanned aerial vehicle imagery

NASA Astrophysics Data System (ADS)

Gao, Junfeng; Liao, Wenzhi; Nuyttens, David; Lootens, Peter; Vangeyte, Jürgen; Pižurica, Aleksandra; He, Yong; Pieters, Jan G.

2018-05-01

The developments in the use of unmanned aerial vehicles (UAVs) and advanced imaging sensors provide new opportunities for ultra-high resolution (e.g., less than a 10 cm ground sampling distance (GSD)) crop field monitoring and mapping in precision agriculture applications. In this study, we developed a strategy for inter- and intra-row weed detection in early season maize fields from aerial visual imagery. More specifically, the Hough transform algorithm (HT) was applied to the orthomosaicked images for inter-row weed detection. A semi-automatic Object-Based Image Analysis (OBIA) procedure was developed with Random Forests (RF) combined with feature selection techniques to classify soil, weeds and maize. Furthermore, the two binary weed masks generated from HT and OBIA were fused for accurate binary weed image. The developed RF classifier was evaluated by 5-fold cross validation, and it obtained an overall accuracy of 0.945, and Kappa value of 0.912. Finally, the relationship of detected weeds and their ground truth densities was quantified by a fitted linear model with a coefficient of determination of 0.895 and a root mean square error of 0.026. Besides, the importance of input features was evaluated, and it was found that the ratio of vegetation length and width was the most significant feature for the classification model. Overall, our approach can yield a satisfactory weed map, and we expect that the obtained accurate and timely weed map from UAV imagery will be applicable to realize site-specific weed management (SSWM) in early season crop fields for reducing spraying non-selective herbicides and costs.

Detection and Alert of muscle fatigue considering a Surface Electromyography Chaotic Model

NASA Astrophysics Data System (ADS)

Herrera, V.; Romero, J. F.; Amestegui, M.

2011-03-01

This work propose a detection and alert algorithm for muscle fatigue in paraplegic patients undergoing electro-therapy sessions. The procedure is based on a mathematical chaotic model emulating physiological signals and Continuous Wavelet Transform (CWT). The chaotic model developed is based on a logistic map that provides suitable data accomplishing some physiological signal class patterns. The CWT was applied to signals generated by the model and the resulting vector was obtained through Total Wavelet Entropy (TWE). In this sense, the presented work propose a viable and practical alert and detection algorithm for muscle fatigue.

Glaucoma diagnosis by mapping macula with Fourier domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Tan, Ou; Lu, Ake; Chopra, Vik; Varma, Rohit; Hiroshi, Ishikawa; Schuman, Joel; Huang, David

2008-03-01

A new image segmentation method was developed to detect macular retinal sub-layers boundary on newly-developed Fourier-Domain Optical Coherence Tomography (FD-OCT) with macular grid scan pattern. The segmentation results were used to create thickness map of macular ganglion cell complex (GCC), which contains the ganglion cell dendrites, cell bodies and axons. Overall average and several pattern analysis parameters were defined on the GCC thickness map and compared for the diagnosis of glaucoma. Intraclass correlation (ICC) is used to compare the reproducibility of the parameters. Area under receiving operative characteristic curve (AROC) was calculated to compare the diagnostic power. The result is also compared to the output of clinical time-domain OCT (TD-OCT). We found that GCC based parameters had good repeatability and comparable diagnostic power with circumpapillary nerve fiber layer (cpNFL) thickness. Parameters based on pattern analysis can increase the diagnostic power of GCC macular mapping.

Quantile rank maps: a new tool for understanding individual brain development.

PubMed

Chen, Huaihou; Kelly, Clare; Castellanos, F Xavier; He, Ye; Zuo, Xi-Nian; Reiss, Philip T

2015-05-01

We propose a novel method for neurodevelopmental brain mapping that displays how an individual's values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are proposed for the quantile rank estimates. We also propose a recalibrated Kolmogorov-Smirnov test for detecting group differences in the age-varying distribution. This test is shown to be more robust to model misspecification than a linear regression-based test. The proposed methods are applied to brain imaging data from the Nathan Kline Institute Rockland Sample and from the Autism Brain Imaging Data Exchange (ABIDE) sample. Copyright © 2015 Elsevier Inc. All rights reserved.

Estimation of reservoir storage capacity using multibeam sonar and terrestrial lidar, Randy Poynter Lake, Rockdale County, Georgia, 2012

USGS Publications Warehouse

Lee, K.G.

2013-01-01

The U.S. Geological Survey, in cooperation with the Rockdale County Department of Water Resources, conducted a bathymetric and topographic survey of Randy Poynter Lake in northern Georgia in 2012. The Randy Poynter Lake watershed drains surface area from Rockdale, Gwinnett, and Walton Counties. The reservoir serves as the water supply for the Conyers-Rockdale Big Haynes Impoundment Authority. The Randy Poynter reservoir was surveyed to prepare a current bathymetric map and determine storage capacities at specified water-surface elevations. Topographic and bathymetric data were collected using a marine-based mobile mapping unit to estimate storage capacity. The marine-based mobile mapping unit operates with several components: multibeam echosounder, singlebeam echosounder, light detection and ranging system, navigation and motion-sensing system, and data acquisition computer. All data were processed and combined to develop a triangulated irregular network, a reservoir capacity table, and a bathymetric contour map.

The art and science of weed mapping

USGS Publications Warehouse

Barnett, David T.; Stohlgren, Thomas J.; Jarnevich, Catherine S.; Chong, Geneva W.; Ericson, Jenny A.; Davern, Tracy R.; Simonson, Sara E.

2007-01-01

Land managers need cost-effective and informative tools for non-native plant species management. Many local, state, and federal agencies adopted mapping systems designed to collect comparable data for the early detection and monitoring of non-native species. We compared mapping information to statistically rigorous, plot-based methods to better understand the benefits and compatibility of the two techniques. Mapping non-native species locations provided a species list, associated species distributions, and infested area for subjectively selected survey sites. The value of this information may be compromised by crude estimates of cover and incomplete or biased estimations of species distributions. Incorporating plot-based assessments guided by a stratified-random sample design provided a less biased description of non-native species distributions and increased the comparability of data over time and across regions for the inventory, monitoring, and management of non-native and native plant species.

Object-Based Classification and Change Detection of Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Park, J. G.; Harada, I.; Kwak, Y.

2016-06-01

Topography and geology are factors to characterize the distribution of natural vegetation. Topographic contour is particularly influential on the living conditions of plants such as soil moisture, sunlight, and windiness. Vegetation associations having similar characteristics are present in locations having similar topographic conditions unless natural disturbances such as landslides and forest fires or artificial disturbances such as deforestation and man-made plantation bring about changes in such conditions. We developed a vegetation map of Japan using an object-based segmentation approach with topographic information (elevation, slope, slope direction) that is closely related to the distribution of vegetation. The results found that the object-based classification is more effective to produce a vegetation map than the pixel-based classification.

All-optical mapping of barrel cortex circuits based on simultaneous voltage-sensitive dye imaging and channelrhodopsin-mediated photostimulation

PubMed Central

Lo, Shun Qiang; Koh, Dawn X. P.; Sng, Judy C. G.; Augustine, George J.

2015-01-01

Abstract. We describe an experimental approach that uses light to both control and detect neuronal activity in mouse barrel cortex slices: blue light patterned by a digital micromirror array system allowed us to photostimulate specific layers and columns, while a red-shifted voltage-sensitive dye was used to map out large-scale circuit activity. We demonstrate that such all-optical mapping can interrogate various circuits in somatosensory cortex by sequentially activating different layers and columns. Further, mapping in slices from whisker-deprived mice demonstrated that chronic sensory deprivation did not significantly alter feedforward inhibition driven by layer 5 pyramidal neurons. Further development of voltage-sensitive optical probes should allow this all-optical mapping approach to become an important and high-throughput tool for mapping circuit interactions in the brain. PMID:26158003

Simulation of seagrass bed mapping by satellite images based on the radiative transfer model

NASA Astrophysics Data System (ADS)

Sagawa, Tatsuyuki; Komatsu, Teruhisa

2015-06-01

Seagrass and seaweed beds play important roles in coastal marine ecosystems. They are food sources and habitats for many marine organisms, and influence the physical, chemical, and biological environment. They are sensitive to human impacts such as reclamation and pollution. Therefore, their management and preservation are necessary for a healthy coastal environment. Satellite remote sensing is a useful tool for mapping and monitoring seagrass beds. The efficiency of seagrass mapping, seagrass bed classification in particular, has been evaluated by mapping accuracy using an error matrix. However, mapping accuracies are influenced by coastal environments such as seawater transparency, bathymetry, and substrate type. Coastal management requires sufficient accuracy and an understanding of mapping limitations for monitoring coastal habitats including seagrass beds. Previous studies are mainly based on case studies in specific regions and seasons. Extensive data are required to generalise assessments of classification accuracy from case studies, which has proven difficult. This study aims to build a simulator based on a radiative transfer model to produce modelled satellite images and assess the visual detectability of seagrass beds under different transparencies and seagrass coverages, as well as to examine mapping limitations and classification accuracy. Our simulations led to the development of a model of water transparency and the mapping of depth limits and indicated the possibility for seagrass density mapping under certain ideal conditions. The results show that modelling satellite images is useful in evaluating the accuracy of classification and that establishing seagrass bed monitoring by remote sensing is a reliable tool.

Magnetic resonance imaging-directed transperineal limited-mapping prostatic biopsies to diagnose prostate cancer: a Scottish experience.

PubMed

Mukherjee, Ankur; Morton, Simon; Fraser, Sioban; Salmond, Jonathan; Baxter, Grant; Leung, Hing Y

2014-11-01

Transperineal prostatic biopsy is firmly established as an important tool in the diagnosis of prostate cancer. The benefit of additional imaging (magnetic resonance imaging) to target biopsy remains to be fully addressed. Using a cohort of consecutive patients undergoing transperineal template mapping biopsies, we studied positive biopsies in the context of magnetic resonance imaging findings and examined the accuracy of magnetic resonance imaging in predicting the location of transperineal template mapping biopsies-detected prostate cancer. Forty-four patients (mean age: 65 years, range 53-78) underwent transperineal template mapping biopsies. Thirty-four patients had 1-2 and 10 patients had ≥3 previous transrectal ultrasound scan-guided biopsies. The mean prostate-specific antigen was 15 ng/mL (range 2.5-79 ng/mL). High-grade prostatic intraepithelial neoplasia was found in 12 (27%) patients and prostate cancer with Gleason <7, 7 and >7 in 13, 10 and 8 patients, respectively. Suspicious lesions on magnetic resonance imaging scans were scored from 1 to 5. In 28 patients, magnetic resonance imaging detected lesions with score ≥3. Magnetic resonance imaging correctly localised transperineal template mapping biopsies-detected prostate cancer in a hemi-gland approach, particularly in a right to left manner (79% positive prediction rate), but not in a quadrant approach (33% positive prediction rate). Our findings support the notion of magnetic resonance imaging-based selection of patients for transperineal template mapping biopsies and that lesions revealed by magnetic resonance imaging are likely useful for targeted biopsies. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Dynamic approximate entropy electroanatomic maps detect rotors in a simulated atrial fibrillation model.

PubMed

Ugarte, Juan P; Orozco-Duque, Andrés; Tobón, Catalina; Kremen, Vaclav; Novak, Daniel; Saiz, Javier; Oesterlein, Tobias; Schmitt, Clauss; Luik, Armin; Bustamante, John

2014-01-01

There is evidence that rotors could be drivers that maintain atrial fibrillation. Complex fractionated atrial electrograms have been located in rotor tip areas. However, the concept of electrogram fractionation, defined using time intervals, is still controversial as a tool for locating target sites for ablation. We hypothesize that the fractionation phenomenon is better described using non-linear dynamic measures, such as approximate entropy, and that this tool could be used for locating the rotor tip. The aim of this work has been to determine the relationship between approximate entropy and fractionated electrograms, and to develop a new tool for rotor mapping based on fractionation levels. Two episodes of chronic atrial fibrillation were simulated in a 3D human atrial model, in which rotors were observed. Dynamic approximate entropy maps were calculated using unipolar electrogram signals generated over the whole surface of the 3D atrial model. In addition, we optimized the approximate entropy calculation using two real multi-center databases of fractionated electrogram signals, labeled in 4 levels of fractionation. We found that the values of approximate entropy and the levels of fractionation are positively correlated. This allows the dynamic approximate entropy maps to localize the tips from stable and meandering rotors. Furthermore, we assessed the optimized approximate entropy using bipolar electrograms generated over a vicinity enclosing a rotor, achieving rotor detection. Our results suggest that high approximate entropy values are able to detect a high level of fractionation and to locate rotor tips in simulated atrial fibrillation episodes. We suggest that dynamic approximate entropy maps could become a tool for atrial fibrillation rotor mapping.

In Vivo Volatile Organic Compound Signatures of Mycobacterium avium subsp. paratuberculosis

PubMed Central

Bergmann, Andreas; Trefz, Phillip; Fischer, Sina; Klepik, Klaus; Walter, Gudrun; Steffens, Markus; Ziller, Mario; Schubert, Jochen K.; Reinhold, Petra; Köhler, Heike; Miekisch, Wolfram

2015-01-01

Mycobacterium avium ssp. paratuberculosis (MAP) is the causative agent of a chronic enteric disease of ruminants. Available diagnostic tests are complex and slow. In vitro, volatile organic compound (VOC) patterns emitted from MAP cultures mirrored bacterial growth and enabled distinction of different strains. This study was intended to determine VOCs in vivo in the controlled setting of an animal model. VOCs were pre-concentrated from breath and feces of 42 goats (16 controls and 26 MAP-inoculated animals) by means of needle trap microextraction (breath) and solid phase microextraction (feces) and analyzed by gas chromatography/ mass spectrometry. Analyses were performed 18, 29, 33, 41 and 48 weeks after inoculation. MAP-specific antibodies and MAP-specific interferon-γ-response were determined from blood. Identities of all marker-VOCs were confirmed through analysis of pure reference substances. Based on detection limits in the high pptV and linear ranges of two orders of magnitude more than 100 VOCs could be detected in breath and in headspace over feces. Twenty eight substances differed between inoculated and non-inoculated animals. Although patterns of most prominent substances such as furans, oxygenated substances and hydrocarbons changed in the course of infection, differences between inoculated and non-inoculated animals remained detectable at any time for 16 substances in feces and 3 VOCs in breath. Differences of VOC concentrations over feces reflected presence of MAP bacteria. Differences in VOC profiles from breath were linked to the host response in terms of interferon-γ-response. In a perspective in vivo analysis of VOCs may help to overcome limitations of established tests. PMID:25915653

Modeling stream fish distributions using interval-censored detection times.

PubMed

Ferreira, Mário; Filipe, Ana Filipa; Bardos, David C; Magalhães, Maria Filomena; Beja, Pedro

2016-08-01

Controlling for imperfect detection is important for developing species distribution models (SDMs). Occupancy-detection models based on the time needed to detect a species can be used to address this problem, but this is hindered when times to detection are not known precisely. Here, we extend the time-to-detection model to deal with detections recorded in time intervals and illustrate the method using a case study on stream fish distribution modeling. We collected electrofishing samples of six fish species across a Mediterranean watershed in Northeast Portugal. Based on a Bayesian hierarchical framework, we modeled the probability of water presence in stream channels, and the probability of species occupancy conditional on water presence, in relation to environmental and spatial variables. We also modeled time-to-first detection conditional on occupancy in relation to local factors, using modified interval-censored exponential survival models. Posterior distributions of occupancy probabilities derived from the models were used to produce species distribution maps. Simulations indicated that the modified time-to-detection model provided unbiased parameter estimates despite interval-censoring. There was a tendency for spatial variation in detection rates to be primarily influenced by depth and, to a lesser extent, stream width. Species occupancies were consistently affected by stream order, elevation, and annual precipitation. Bayesian P-values and AUCs indicated that all models had adequate fit and high discrimination ability, respectively. Mapping of predicted occupancy probabilities showed widespread distribution by most species, but uncertainty was generally higher in tributaries and upper reaches. The interval-censored time-to-detection model provides a practical solution to model occupancy-detection when detections are recorded in time intervals. This modeling framework is useful for developing SDMs while controlling for variation in detection rates, as it uses simple data that can be readily collected by field ecologists.

Asymptotically stable phase synchronization revealed by autoregressive circle maps

NASA Astrophysics Data System (ADS)

Drepper, F. R.

2000-11-01

A specially designed of nonlinear time series analysis is introduced based on phases, which are defined as polar angles in spaces spanned by a finite number of delayed coordinates. A canonical choice of the polar axis and a related implicit estimation scheme for the potentially underlying autoregressive circle map (next phase map) guarantee the invertibility of reconstructed phase space trajectories to the original coordinates. The resulting Fourier approximated, invertibility enforcing phase space map allows us to detect conditional asymptotic stability of coupled phases. This comparatively general synchronization criterion unites two existing generalizations of the old concept and can successfully be applied, e.g., to phases obtained from electrocardiogram and airflow recordings characterizing cardiorespiratory interaction.

Investigation of methods to search for the boundaries on the image and their use on lung hardware of methods finding saliency map

NASA Astrophysics Data System (ADS)

Semenishchev, E. A.; Marchuk, V. I.; Fedosov, V. P.; Stradanchenko, S. G.; Ruslyakov, D. V.

2015-05-01

This work aimed to study computationally simple method of saliency map calculation. Research in this field received increasing interest for the use of complex techniques in portable devices. A saliency map allows increasing the speed of many subsequent algorithms and reducing the computational complexity. The proposed method of saliency map detection based on both image and frequency space analysis. Several examples of test image from the Kodak dataset with different detalisation considered in this paper demonstrate the effectiveness of the proposed approach. We present experiments which show that the proposed method providing better results than the framework Salience Toolbox in terms of accuracy and speed.

Testing statistical isotropy in cosmic microwave background polarization maps

NASA Astrophysics Data System (ADS)

Rath, Pranati K.; Samal, Pramoda Kumar; Panda, Srikanta; Mishra, Debesh D.; Aluri, Pavan K.

2018-04-01

We apply our symmetry based Power tensor technique to test conformity of PLANCK Polarization maps with statistical isotropy. On a wide range of angular scales (l = 40 - 150), our preliminary analysis detects many statistically anisotropic multipoles in foreground cleaned full sky PLANCK polarization maps viz., COMMANDER and NILC. We also study the effect of residual foregrounds that may still be present in the Galactic plane using both common UPB77 polarization mask, as well as the individual component separation method specific polarization masks. However, some of the statistically anisotropic modes still persist, albeit significantly in NILC map. We further probed the data for any coherent alignments across multipoles in several bins from the chosen multipole range.

Mapping sea ice leads with a coupled numeric/symbolic system

NASA Technical Reports Server (NTRS)

Key, J.; Schweiger, A. J.; Maslanik, J. A.

1990-01-01

A method is presented which facilitates the detection and delineation of leads with single-channel Landsat data by coupling numeric and symbolic procedures. The procedure consists of three steps: (1) using the dynamic threshold method, an image is mapped to a lead/no lead binary image; (2) the likelihood of fragments to be real leads is examined with a set of numeric rules; and (3) pairs of objects are examined geometrically and merged where possible. The processing ends when all fragments are merged and statistical characteristics are determined, and a map of valid lead objects are left which summarizes useful physical in the lead complexes. Direct implementation of domain knowledge and rapid prototyping are two benefits of the rule-based system. The approach is found to be more successfully applied to mid- and high-level processing, and the system can retrieve statistics about sea-ice leads as well as detect the leads.

Clearance detector and method for motion and distance

DOEpatents

Xavier, Patrick G [Albuquerque, NM

2011-08-09

A method for correct and efficient detection of clearances between three-dimensional bodies in computer-based simulations, where one or both of the volumes is subject to translation and/or rotations. The method conservatively determines of the size of such clearances and whether there is a collision between the bodies. Given two bodies, each of which is undergoing separate motions, the method utilizes bounding-volume hierarchy representations for the two bodies and, mappings and inverse mappings for the motions of the two bodies. The method uses the representations, mappings and direction vectors to determine the directionally furthest locations of points on the convex hulls of the volumes virtually swept by the bodies and hence the clearance between the bodies, without having to calculate the convex hulls of the bodies. The method includes clearance detection for bodies comprising convex geometrical primitives and more specific techniques for bodies comprising convex polyhedra.

Detection of long duration cloud contamination in hyper-temporal NDVI imagery

NASA Astrophysics Data System (ADS)

Ali, A.; de Bie, C. A. J. M.; Skidmore, A. K.; Scarrott, R. G.

2012-04-01

NDVI time series imagery are commonly used as a reliable source for land use and land cover mapping and monitoring. However long duration cloud can significantly influence its precision in areas where persistent clouds prevails. Therefore quantifying errors related to cloud contamination are essential for accurate land cover mapping and monitoring. This study aims to detect long duration cloud contamination in hyper-temporal NDVI imagery based land cover mapping and monitoring. MODIS-Terra NDVI imagery (250 m; 16-day; Feb'03-Dec'09) were used after necessary pre-processing using quality flags and upper envelope filter (ASAVOGOL). Subsequently stacked MODIS-Terra NDVI image (161 layers) was classified for 10 to 100 clusters using ISODATA. After classifications, 97 clusters image was selected as best classified with the help of divergence statistics. To detect long duration cloud contamination, mean NDVI class profiles of 97 clusters image was analyzed for temporal artifacts. Results showed that long duration clouds affect the normal temporal progression of NDVI and caused anomalies. Out of total 97 clusters, 32 clusters were found with cloud contamination. Cloud contamination was found more prominent in areas where high rainfall occurs. This study can help to stop error propagation in regional land cover mapping and monitoring, caused by long duration cloud contamination.

Detection and Tracking Based on a Dynamical Hierarchical Occupancy Map in Agent-Based Simulations

DTIC Science & Technology

2008-09-01

describes various techniques for targeting with probabilty reasoning. Advantages and disadvantages of the different methods will be discussed...Psum. Such an algorithm could decrease the performance of the prototype itself and therefore was not considered. Probabilty over time 0 0.2 0.4 0.6

A Critique of Patch-Based Landscape Indicators for Detection of Temporal Change in Fragmentation

EPA Science Inventory

Since O’Neill et al. (1988), analysis of landscape indicators based on measurements from land-cover maps has been a core area of research in landscape ecology. Landscape indicator research has focused on development of new measurements, statistical properties, and indictor behav...

Stochastic formulation of patient positioning using linac-mounted cone beam imaging with prior knowledge

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

Hoegele, W.; Loeschel, R.; Dobler, B.

2011-02-15

Purpose: In this work, a novel stochastic framework for patient positioning based on linac-mounted CB projections is introduced. Based on this formulation, the most probable shifts and rotations of the patient are estimated, incorporating interfractional deformations of patient anatomy and other uncertainties associated with patient setup. Methods: The target position is assumed to be defined by and is stochastically determined from positions of various features such as anatomical landmarks or markers in CB projections, i.e., radiographs acquired with a CB-CT system. The patient positioning problem of finding the target location from CB projections is posed as an inverse problem withmore » prior knowledge and is solved using a Bayesian maximum a posteriori (MAP) approach. The prior knowledge is three-fold and includes the accuracy of an initial patient setup (such as in-room laser and skin marks), the plasticity of the body (relative shifts between target and features), and the feature detection error in CB projections (which may vary depending on specific detection algorithm and feature type). For this purpose, MAP estimators are derived and a procedure of using them in clinical practice is outlined. Furthermore, a rule of thumb is theoretically derived, relating basic parameters of the prior knowledge (initial setup accuracy, plasticity of the body, and number of features) and the parameters of CB data acquisition (number of projections and accuracy of feature detection) to the expected estimation accuracy. Results: MAP estimation can be applied to arbitrary features and detection algorithms. However, to experimentally demonstrate its applicability and to perform the validation of the algorithm, a water-equivalent, deformable phantom with features represented by six 1 mm chrome balls were utilized. These features were detected in the cone beam projections (XVI, Elekta Synergy) by a local threshold method for demonstration purposes only. The accuracy of estimation (strongly varying for different plasticity parameters of the body) agreed with the rule of thumb formula. Moreover, based on this rule of thumb formula, about 20 projections for 6 detectable features seem to be sufficient for a target estimation accuracy of 0.2 cm, even for relatively large feature detection errors with standard deviation of 0.5 cm and spatial displacements of the features with standard deviation of 0.5 cm. Conclusions: The authors have introduced a general MAP-based patient setup algorithm accounting for different sources of uncertainties, which are utilized as the prior knowledge in a transparent way. This new framework can be further utilized for different clinical sites, as well as theoretical developments in the field of patient positioning for radiotherapy.« less

Absence of rotational activity detected using 2-dimensional phase mapping in the corresponding 3-dimensional phase maps in human persistent atrial fibrillation.

PubMed

Pathik, Bhupesh; Kalman, Jonathan M; Walters, Tomos; Kuklik, Pawel; Zhao, Jichao; Madry, Andrew; Sanders, Prashanthan; Kistler, Peter M; Lee, Geoffrey

2018-02-01

Current phase mapping systems for atrial fibrillation create 2-dimensional (2D) maps. This process may affect the accurate detection of rotors. We developed a 3-dimensional (3D) phase mapping technique that uses the 3D locations of basket electrodes to project phase onto patient-specific left atrial 3D surface anatomy. We sought to determine whether rotors detected in 2D phase maps were present at the corresponding time segments and anatomical locations in 3D phase maps. One-minute left atrial atrial fibrillation recordings were obtained in 14 patients using the basket catheter and analyzed off-line. Using the same phase values, 2D and 3D phase maps were created. Analysis involved determining the dominant propagation patterns in 2D phase maps and evaluating the presence of rotors detected in 2D phase maps in the corresponding 3D phase maps. Using 2D phase mapping, the dominant propagation pattern was single wavefront (36.6%) followed by focal activation (34.0%), disorganized activity (23.7%), rotors (3.3%), and multiple wavefronts (2.4%). Ten transient rotors were observed in 9 of 14 patients (64%). The mean rotor duration was 1.1 ± 0.7 seconds. None of the 10 rotors observed in 2D phase maps were seen at the corresponding time segments and anatomical locations in 3D phase maps; 4 of 10 corresponded with single wavefronts in 3D phase maps, 2 of 10 with 2 simultaneous wavefronts, 1 of 10 with disorganized activity, and in 3 of 10 there was no coverage by the basket catheter at the corresponding 3D anatomical location. Rotors detected in 2D phase maps were not observed in the corresponding 3D phase maps. These findings may have implications for current systems that use 2D phase mapping. Copyright © 2017 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Level crossing analysis of cosmic microwave background radiation: a method for detecting cosmic strings

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

Movahed, M. Sadegh; Khosravi, Shahram, E-mail: m.s.movahed@ipm.ir, E-mail: khosravi@ipm.ir

2011-03-01

In this paper we study the footprint of cosmic string as the topological defects in the very early universe on the cosmic microwave background radiation. We develop the method of level crossing analysis in the context of the well-known Kaiser-Stebbins phenomenon for exploring the signature of cosmic strings. We simulate a Gaussian map by using the best fit parameter given by WMAP-7 and then superimpose cosmic strings effects on it as an incoherent and active fluctuations. In order to investigate the capability of our method to detect the cosmic strings for the various values of tension, Gμ, a simulated puremore » Gaussian map is compared with that of including cosmic strings. Based on the level crossing analysis, the superimposed cosmic string with Gμ∼>4 × 10{sup −9} in the simulated map without instrumental noise and the resolution R = 1' could be detected. In the presence of anticipated instrumental noise the lower bound increases just up to Gμ∼>5.8 × 10{sup −9}.« less

Distributed multimodal data fusion for large scale wireless sensor networks

NASA Astrophysics Data System (ADS)

Ertin, Emre

2006-05-01

Sensor network technology has enabled new surveillance systems where sensor nodes equipped with processing and communication capabilities can collaboratively detect, classify and track targets of interest over a large surveillance area. In this paper we study distributed fusion of multimodal sensor data for extracting target information from a large scale sensor network. Optimal tracking, classification, and reporting of threat events require joint consideration of multiple sensor modalities. Multiple sensor modalities improve tracking by reducing the uncertainty in the track estimates as well as resolving track-sensor data association problems. Our approach to solving the fusion problem with large number of multimodal sensors is construction of likelihood maps. The likelihood maps provide a summary data for the solution of the detection, tracking and classification problem. The likelihood map presents the sensory information in an easy format for the decision makers to interpret and is suitable with fusion of spatial prior information such as maps, imaging data from stand-off imaging sensors. We follow a statistical approach to combine sensor data at different levels of uncertainty and resolution. The likelihood map transforms each sensor data stream to a spatio-temporal likelihood map ideally suitable for fusion with imaging sensor outputs and prior geographic information about the scene. We also discuss distributed computation of the likelihood map using a gossip based algorithm and present simulation results.

Syntax-directed content analysis of videotext: application to a map detection recognition system

NASA Astrophysics Data System (ADS)

Aradhye, Hrishikesh; Herson, James A.; Myers, Gregory

2003-01-01

Video is an increasingly important and ever-growing source of information to the intelligence and homeland defense analyst. A capability to automatically identify the contents of video imagery would enable the analyst to index relevant foreign and domestic news videos in a convenient and meaningful way. To this end, the proposed system aims to help determine the geographic focus of a news story directly from video imagery by detecting and geographically localizing political maps from news broadcasts, using the results of videotext recognition in lieu of a computationally expensive, scale-independent shape recognizer. Our novel method for the geographic localization of a map is based on the premise that the relative placement of text superimposed on a map roughly corresponds to the geographic coordinates of the locations the text represents. Our scheme extracts and recognizes videotext, and iteratively identifies the geographic area, while allowing for OCR errors and artistic freedom. The fast and reliable recognition of such maps by our system may provide valuable context and supporting evidence for other sources, such as speech recognition transcripts. The concepts of syntax-directed content analysis of videotext presented here can be extended to other content analysis systems.

Copy-move forgery detection utilizing Fourier-Mellin transform log-polar features

NASA Astrophysics Data System (ADS)

Dixit, Rahul; Naskar, Ruchira

2018-03-01

In this work, we address the problem of region duplication or copy-move forgery detection in digital images, along with detection of geometric transforms (rotation and rescale) and postprocessing-based attacks (noise, blur, and brightness adjustment). Detection of region duplication, following conventional techniques, becomes more challenging when an intelligent adversary brings about such additional transforms on the duplicated regions. In this work, we utilize Fourier-Mellin transform with log-polar mapping and a color-based segmentation technique using K-means clustering, which help us to achieve invariance to all the above forms of attacks in copy-move forgery detection of digital images. Our experimental results prove the efficiency of the proposed method and its superiority to the current state of the art.

Hydroacoustic basis for detection and characterization of eelgrass (Zostera marina)

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

Sabol, B.; McCarthy, E.; Rocha, K.

1997-06-01

Understanding the distribution and density of seagrasses is important for a variety of environmental applications. Physical techniques for detection and characterization are labor and cost intensive and provide little insight into spatial distribution. optical-based techniques are limited by water clarity - frequently resulting in systematic underestimation of the extent of seagrasses. Active hydroacoustic techniques have shown the ability to detect seagrasses but the phenomenology behind detection is poorly understood. Laboratory and in-situ hydroacoustic measurements are presented for eelgrass (Zostera marina), a common seagrass in the United States. Based on these data, hydroacoustic approaches for wide area detection and mapping aremore » discussed and several are demonstrated within areas of established eelgrass beds in Narragansett Bay, Rhode Island.« less

A neural-network based estimator to search for primordial non-Gaussianity in Planck CMB maps

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

Novaes, C.P.; Bernui, A.; Ferreira, I.S.

2015-09-01

We present an upgraded combined estimator, based on Minkowski Functionals and Neural Networks, with excellent performance in detecting primordial non-Gaussianity in simulated maps that also contain a weighted mixture of Galactic contaminations, besides real pixel's noise from Planck cosmic microwave background radiation data. We rigorously test the efficiency of our estimator considering several plausible scenarios for residual non-Gaussianities in the foreground-cleaned Planck maps, with the intuition to optimize the training procedure of the Neural Network to discriminate between contaminations with primordial and secondary non-Gaussian signatures. We look for constraints of primordial local non-Gaussianity at large angular scales in the foreground-cleanedmore » Planck maps. For the SMICA map we found f{sub NL} = 33 ± 23, at 1σ confidence level, in excellent agreement with the WMAP-9yr and Planck results. In addition, for the other three Planck maps we obtain similar constraints with values in the interval f{sub NL}  element of  [33, 41], concomitant with the fact that these maps manifest distinct features in reported analyses, like having different pixel's noise intensities.« less

AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework

PubMed Central

Zheng, Qi; Grice, Elizabeth A.

2016-01-01

Accurate mapping of next-generation sequencing (NGS) reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely) mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost’s algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost. PMID:27706155

Comparison of CT perfusion summary maps to early diffusion-weighted images in suspected acute middle cerebral artery stroke.

PubMed

Benson, John; Payabvash, Seyedmehdi; Salazar, Pascal; Jagadeesan, Bharathi; Palmer, Christopher S; Truwit, Charles L; McKinney, Alexander M

2015-04-01

To assess the accuracy and reliability of one vendor's (Vital Images, Toshiba Medical, Minnetonka, MN) automated CT perfusion (CTP) summary maps in identification and volume estimation of infarcted tissue in patients with acute middle cerebral artery (MCA) distribution infarcts. From 1085 CTP examinations over 5.5 years, 43 diffusion-weighted imaging (DWI)-positive patients were included who underwent both CTP and DWI <12 h after symptom onset, with another 43 age-matched patients as controls (DWI-negative). Automated delay-corrected postprocessing software (DC-SVD) generated both infarct "core only" and "core+penumbra" CTP summary maps. Three reviewers independently tabulated Alberta Stroke Program Early CT scores (ASPECTS) of both CTP summary maps and coregistered DWI. Of 86 included patients, 36 had DWI infarct volumes ≤70 ml, 7 had volumes >70 ml, and 43 were negative; the automated CTP "core only" map correctly classified each as >70 ml or ≤70 ml, while the "core+penumbra" map misclassified 4 as >70 ml. There were strong correlations between DWI volume with both summary map-based volumes: "core only" (r=0.93), and "core+penumbra" (r=0.77) (both p<0.0001). Agreement between ASPECTS scores of infarct core on DWI with summary maps was 0.65-0.74 for "core only" map, and 0.61-0.65 for "core+penumbra" (both p<0.0001). Using DWI-based ASPECTS scores as the standard, the accuracy of the CTP-based maps were 79.1-86.0% for the "core only" map, and 83.7-88.4% for "core+penumbra." Automated CTP summary maps appear to be relatively accurate in both the detection of acute MCA distribution infarcts, and the discrimination of volumes using a 70 ml threshold. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

An integrated approach to flood hazard assessment on alluvial fans using numerical modeling, field mapping, and remote sensing

USGS Publications Warehouse

Pelletier, J.D.; Mayer, L.; Pearthree, P.A.; House, P.K.; Demsey, K.A.; Klawon, J.K.; Vincent, K.R.

2005-01-01

Millions of people in the western United States live near the dynamic, distributary channel networks of alluvial fans where flood behavior is complex and poorly constrained. Here we test a new comprehensive approach to alluvial-fan flood hazard assessment that uses four complementary methods: two-dimensional raster-based hydraulic modeling, satellite-image change detection, fieldbased mapping of recent flood inundation, and surficial geologic mapping. Each of these methods provides spatial detail lacking in the standard method and each provides critical information for a comprehensive assessment. Our numerical model simultaneously solves the continuity equation and Manning's equation (Chow, 1959) using an implicit numerical method. It provides a robust numerical tool for predicting flood flows using the large, high-resolution Digital Elevation Models (DEMs) necessary to resolve the numerous small channels on the typical alluvial fan. Inundation extents and flow depths of historic floods can be reconstructed with the numerical model and validated against field- and satellite-based flood maps. A probabilistic flood hazard map can also be constructed by modeling multiple flood events with a range of specified discharges. This map can be used in conjunction with a surficial geologic map to further refine floodplain delineation on fans. To test the accuracy of the numerical model, we compared model predictions of flood inundation and flow depths against field- and satellite-based flood maps for two recent extreme events on the southern Tortolita and Harquahala piedmonts in Arizona. Model predictions match the field- and satellite-based maps closely. Probabilistic flood hazard maps based on the 10 yr, 100 yr, and maximum floods were also constructed for the study areas using stream gage records and paleoflood deposits. The resulting maps predict spatially complex flood hazards that strongly reflect small-scale topography and are consistent with surficial geology. In contrast, FEMA Flood Insurance Rate Maps (FIRMs) based on the FAN model predict uniformly high flood risk across the study areas without regard for small-scale topography and surficial geology. ?? 2005 Geological Society of America.

Deep Spatial-Temporal Joint Feature Representation for Video Object Detection.

PubMed

Zhao, Baojun; Zhao, Boya; Tang, Linbo; Han, Yuqi; Wang, Wenzheng

2018-03-04

With the development of deep neural networks, many object detection frameworks have shown great success in the fields of smart surveillance, self-driving cars, and facial recognition. However, the data sources are usually videos, and the object detection frameworks are mostly established on still images and only use the spatial information, which means that the feature consistency cannot be ensured because the training procedure loses temporal information. To address these problems, we propose a single, fully-convolutional neural network-based object detection framework that involves temporal information by using Siamese networks. In the training procedure, first, the prediction network combines the multiscale feature map to handle objects of various sizes. Second, we introduce a correlation loss by using the Siamese network, which provides neighboring frame features. This correlation loss represents object co-occurrences across time to aid the consistent feature generation. Since the correlation loss should use the information of the track ID and detection label, our video object detection network has been evaluated on the large-scale ImageNet VID dataset where it achieves a 69.5% mean average precision (mAP).

Detection and mapping of delays in early cortical folding derived from in utero MRI

NASA Astrophysics Data System (ADS)

Habas, Piotr A.; Rajagopalan, Vidya; Scott, Julia A.; Kim, Kio; Roosta, Ahmad; Rousseau, Francois; Barkovich, A. James; Glenn, Orit A.; Studholme, Colin

2011-03-01

Understanding human brain development in utero and detecting cortical abnormalities related to specific clinical conditions is an important area of research. In this paper, we describe and evaluate methodology for detection and mapping of delays in early cortical folding from population-based studies of fetal brain anatomies imaged in utero. We use a general linear modeling framework to describe spatiotemporal changes in curvature of the developing brain and explore the ability to detect and localize delays in cortical folding in the presence of uncertainty in estimation of the fetal age. We apply permutation testing to examine which regions of the brain surface provide the most statistical power to detect a given folding delay at a given developmental stage. The presented methodology is evaluated using MR scans of fetuses with normal brain development and gestational ages ranging from 20.57 to 27.86 weeks. This period is critical in early cortical folding and the formation of the primary and secondary sulci. Finally, we demonstrate a clinical application of the framework for detection and localization of folding delays in fetuses with isolated mild ventriculomegaly.

Understanding of Object Detection Based on CNN Family and YOLO

NASA Astrophysics Data System (ADS)

Du, Juan

2018-04-01

As a key use of image processing, object detection has boomed along with the unprecedented advancement of Convolutional Neural Network (CNN) and its variants since 2012. When CNN series develops to Faster Region with CNN (R-CNN), the Mean Average Precision (mAP) has reached 76.4, whereas, the Frame Per Second (FPS) of Faster R-CNN remains 5 to 18 which is far slower than the real-time effect. Thus, the most urgent requirement of object detection improvement is to accelerate the speed. Based on the general introduction to the background and the core solution CNN, this paper exhibits one of the best CNN representatives You Only Look Once (YOLO), which breaks through the CNN family’s tradition and innovates a complete new way of solving the object detection with most simple and high efficient way. Its fastest speed has achieved the exciting unparalleled result with FPS 155, and its mAP can also reach up to 78.6, both of which have surpassed the performance of Faster R-CNN greatly. Additionally, compared with the latest most advanced solution, YOLOv2 achieves an excellent tradeoff between speed and accuracy as well as an object detector with strong generalization ability to represent the whole image.

Assessment of Data Fusion Algorithms for Earth Observation Change Detection Processes.

PubMed

Molina, Iñigo; Martinez, Estibaliz; Morillo, Carmen; Velasco, Jesus; Jara, Alvaro

2016-09-30

In this work a parametric multi-sensor Bayesian data fusion approach and a Support Vector Machine (SVM) are used for a Change Detection problem. For this purpose two sets of SPOT5-PAN images have been used, which are in turn used for Change Detection Indices (CDIs) calculation. For minimizing radiometric differences, a methodology based on zonal "invariant features" is suggested. The choice of one or the other CDI for a change detection process is a subjective task as each CDI is probably more or less sensitive to certain types of changes. Likewise, this idea might be employed to create and improve a "change map", which can be accomplished by means of the CDI's informational content. For this purpose, information metrics such as the Shannon Entropy and "Specific Information" have been used to weight the changes and no-changes categories contained in a certain CDI and thus introduced in the Bayesian information fusion algorithm. Furthermore, the parameters of the probability density functions (pdf's) that best fit the involved categories have also been estimated. Conversely, these considerations are not necessary for mapping procedures based on the discriminant functions of a SVM. This work has confirmed the capabilities of probabilistic information fusion procedure under these circumstances.

Revealing phenotype-associated functional differences by genome-wide scan of ancient haplotype blocks

PubMed Central

Onuki, Ritsuko; Yamaguchi, Rui; Shibuya, Tetsuo; Kanehisa, Minoru; Goto, Susumu

2017-01-01

Genome-wide scans for positive selection have become important for genomic medicine, and many studies aim to find genomic regions affected by positive selection that are associated with risk allele variations among populations. Most such studies are designed to detect recent positive selection. However, we hypothesize that ancient positive selection is also important for adaptation to pathogens, and has affected current immune-mediated common diseases. Based on this hypothesis, we developed a novel linkage disequilibrium-based pipeline, which aims to detect regions associated with ancient positive selection across populations from single nucleotide polymorphism (SNP) data. By applying this pipeline to the genotypes in the International HapMap project database, we show that genes in the detected regions are enriched in pathways related to the immune system and infectious diseases. The detected regions also contain SNPs reported to be associated with cancers and metabolic diseases, obesity-related traits, type 2 diabetes, and allergic sensitization. These SNPs were further mapped to biological pathways to determine the associations between phenotypes and molecular functions. Assessments of candidate regions to identify functions associated with variations in incidence rates of these diseases are needed in the future. PMID:28445522

Privacy-Aware Image Encryption Based on Logistic Map and Data Hiding

NASA Astrophysics Data System (ADS)

Sun, Jianglin; Liao, Xiaofeng; Chen, Xin; Guo, Shangwei

The increasing need for image communication and storage has created a great necessity for securely transforming and storing images over a network. Whereas traditional image encryption algorithms usually consider the security of the whole plain image, region of interest (ROI) encryption schemes, which are of great importance in practical applications, protect the privacy regions of plain images. Existing ROI encryption schemes usually adopt approximate techniques to detect the privacy region and measure the quality of encrypted images; however, their performance is usually inconsistent with a human visual system (HVS) and is sensitive to statistical attacks. In this paper, we propose a novel privacy-aware ROI image encryption (PRIE) scheme based on logistical mapping and data hiding. The proposed scheme utilizes salient object detection to automatically, adaptively and accurately detect the privacy region of a given plain image. After private pixels have been encrypted using chaotic cryptography, the significant bits are embedded into the nonprivacy region of the plain image using data hiding. Extensive experiments are conducted to illustrate the consistency between our automatic ROI detection and HVS. Our experimental results also demonstrate that the proposed scheme exhibits satisfactory security performance.

Lunar Prospector: a Preliminary Surface Remote Sensing Resource Assessment for the Moon

NASA Technical Reports Server (NTRS)

Mardon, A. A.

1992-01-01

The potential existence of lunar volatiles is a scientific discovery that could distinctly change the direction of pathways of inner solar system human expansion. With a dedicated germanium gamma ray spectrometer launched in the early 1990's, surface water concentrations of 0.7 percent could be detected immediately upon full lunar polar orbit operations. The expense of lunar base construction and operation would be dramatically reduced over a scenario with no lunar volatile resources. Global surface mineral distribution could be mapped out and integrated into a GIS database for lunar base site selection. Extensive surface lunar mapping would also result in the utilization of archived Apollo images. A variety of remote sensing systems and their parameters have been proposed for use in the detection of these lunar ice masses. The detection or nondetection of subsurface and surface ice masses in lunar polar crater floors could dramatically direct the development pathways that the human race might follow in its radiation from the Earth to habitable locales in the inner terran solar system. Potential sources of lunar volatiles are described. The use of remote sensing to detect lunar volatiles is addressed.

Double-cladding-fiber-based detection system for intravascular mapping of fluorescent molecular probes

NASA Astrophysics Data System (ADS)

Razansky, R. Nika; Rozental, Amir; Mueller, Mathias S.; Deliolanis, Nikolaos; Jaffer, Farouc A.; Koch, Alexander W.; Ntziachristos, Vasilis

2011-03-01

Early detection of high-risk coronary atherosclerosis remains an unmet clinical challenge. We have previously demonstrated a near-infrared fluorescence catheter system for two-dimensional intravascular detection of fluorescence molecular probes [1]. In this work we improve the system performance by introducing a novel high resolution sensor. The main challenge of the intravascular sensor is to provide a highly focused spot at an application relevant distance on one hand and a highly efficient collection of emitted light on the other. We suggest employing a double cladding optical fiber (DCF) in combination with focusing optics to provide a sensor with both highly focused excitation light and highly efficient fluorescent light collection. The excitation laser is coupled into the single mode core of DCF and guided through a focusing element and a right angle prism. The resulting side-fired beam exhibits a small spot diameter (50 μm) throughout a distance of up to 2 mm from the sensor. This is the distance of interest for intravascular coronary imaging application, determined by an average human coronary artery diameter. At the blood vessel wall, an activatable fluorescence molecular probe is excited in the diseased lesions. Next light of slightly shifted wavelength emits only in the places of the inflammations, associated with dangerous plaques [2]. The emitted light is collected by the cladding of the DCF, with a large collection angle (NA=0.4). The doublecladding acts as multimodal fiber and guides the collected light to the photo detection elements. The sensor automatically rotates and pulled-back, while each scanned point is mapped according to the amount of detected fluorescent emission. The resulting map of fluorescence activity helps to associate the atherosclerotic plaques with the inflammation process. The presented detection system is a valuable tool in the intravascular plaque detection and can help to differentiate the atherosclerotic plaques based on their biological activity, identify the ones that prone to rupture and therefore require more medical attention.

Registering Ground and Satellite Imagery for Visual Localization

DTIC Science & Technology

2012-08-01

reckoning, inertial, stereo, light detection and ranging ( LIDAR ), cellular radio, and visual. As no sensor or algorithm provides perfect localization in...by metric localization approaches to confine the region of a map that needs to be searched. Simultaneous Localization and Mapping ( SLAM ) (5, 6), using...estimate the metric location of the camera. Se et al. (7) use SIFT features for both appearance-based global localization and incremental 3D SLAM . Johns and

Robust and fast characterization of OCT-based optical attenuation using a novel frequency-domain algorithm for brain cancer detection

NASA Astrophysics Data System (ADS)

Yuan, Wu; Kut, Carmen; Liang, Wenxuan; Li, Xingde

2017-03-01

Cancer is known to alter the local optical properties of tissues. The detection of OCT-based optical attenuation provides a quantitative method to efficiently differentiate cancer from non-cancer tissues. In particular, the intraoperative use of quantitative OCT is able to provide a direct visual guidance in real time for accurate identification of cancer tissues, especially these without any obvious structural layers, such as brain cancer. However, current methods are suboptimal in providing high-speed and accurate OCT attenuation mapping for intraoperative brain cancer detection. In this paper, we report a novel frequency-domain (FD) algorithm to enable robust and fast characterization of optical attenuation as derived from OCT intensity images. The performance of this FD algorithm was compared with traditional fitting methods by analyzing datasets containing images from freshly resected human brain cancer and from a silica phantom acquired by a 1310 nm swept-source OCT (SS-OCT) system. With graphics processing unit (GPU)-based CUDA C/C++ implementation, this new attenuation mapping algorithm can offer robust and accurate quantitative interpretation of OCT images in real time during brain surgery.

Spectroscopic detection and mapping of vinyl cyanide on Titan

NASA Astrophysics Data System (ADS)

Cordiner, Martin; Yukiko Palmer, Maureen; Lai, James; Nixon, Conor A.; Teanby, Nicholas; Charnley, Steven B.; Vuitton, Veronique; Kisiel, Zbigniew; Irwin, Patrick; Molter, Ned; Mumma, Michael J.

2017-10-01

The first spectroscopic detection of vinyl cyanide (otherwise known as acrylonitrile; C2H3CN) on Titan was obtained by Palmer et al. (2017), based on three rotational emission lines observed with ALMA at millimeter wavelengths (in receiver band 6). The astrobiological significance of this detection was highlighted due to the theorized ability of C2H3CN molecules to combine into cell membrane-like structures under the cold conditions found in Titan's hydrocarbon lakes. Here we report the detection of three additional C2H3CN transitions at higher frequencies (from ALMA band 7 flux calibration data). We present the first emission maps for this gas on Titan, and compare the molecular distribution with that of other nitriles observed with ALMA including HC3N, CH3CN, C2H5CN and HNC. The molecular abundance patterns are interpreted based on our understanding of Titan's high-altitude photochemistry and time-variable global circulation. Similar to the short-lived HC3N molecule, vinyl cyanide is found to be most abundant in the vicinity of the southern (winter) pole, whereas the longer-lived CH3CN is more concentrated in the north. The vertical abundance profile of C2H3CN (from radiative transfer modeling), as well as its latitudinal distribution, are consistent with a short photochemical lifetime for this species. Complementary results from our more recent (2017) nitrile mapping studies at higher spatial resolution will also be discussed.REFERENCES:Palmer, M. Y., Cordiner, M. A., Nixon, C. A. et al. "ALMA detection and astrobiological potential of vinyl cyanide on Titan", Sci. Adv. 2017, 3, e1700022

Searching for filaments and large-scale structure around DAFT/FADA clusters

NASA Astrophysics Data System (ADS)

Durret, F.; Márquez, I.; Acebrón, A.; Adami, C.; Cabrera-Lavers, A.; Capelato, H.; Martinet, N.; Sarron, F.; Ulmer, M. P.

2016-04-01

Context. Clusters of galaxies are located at the intersection of cosmic filaments and are still accreting galaxies and groups along these preferential directions. However, because of their relatively low contrast on the sky, filaments are difficult to detect (unless a large amount of spectroscopic data are available), and unambiguous detections have been limited until now to relatively low redshifts (z< ~ 0.3). Aims: This project is aimed at searching for extensions and filaments around clusters, traced by galaxies selected to be at the cluster redshift based on the red sequence. In the 0.4

Singlet oxygen Triplet Energy Transfer based imaging technology for mapping protein-protein proximity in intact cells

PubMed Central

To, Tsz-Leung; Fadul, Michael J.; Shu, Xiaokun

2014-01-01

Many cellular processes are carried out by large protein complexes that can span several tens of nanometers. Whereas Forster resonance energy transfer has a detection range of <10 nm, here we report the theoretical development and experimental demonstration of a new fluorescence imaging technology with a detection range of up to several tens of nanometers: singlet oxygen triplet energy transfer. We demonstrate that our method confirms the topology of a large protein complex in intact cells, which spans from the endoplasmic reticulum to the outer mitochondrial membrane and the matrix. This new method is thus suited for mapping protein proximity in large protein complexes. PMID:24905026

Novelty Detection Classifiers in Weed Mapping: Silybum marianum Detection on UAV Multispectral Images.

PubMed

Alexandridis, Thomas K; Tamouridou, Afroditi Alexandra; Pantazi, Xanthoula Eirini; Lagopodi, Anastasia L; Kashefi, Javid; Ovakoglou, Georgios; Polychronos, Vassilios; Moshou, Dimitrios

2017-09-01

In the present study, the detection and mapping of Silybum marianum (L.) Gaertn. weed using novelty detection classifiers is reported. A multispectral camera (green-red-NIR) on board a fixed wing unmanned aerial vehicle (UAV) was employed for obtaining high-resolution images. Four novelty detection classifiers were used to identify S. marianum between other vegetation in a field. The classifiers were One Class Support Vector Machine (OC-SVM), One Class Self-Organizing Maps (OC-SOM), Autoencoders and One Class Principal Component Analysis (OC-PCA). As input features to the novelty detection classifiers, the three spectral bands and texture were used. The S. marianum identification accuracy using OC-SVM reached an overall accuracy of 96%. The results show the feasibility of effective S. marianum mapping by means of novelty detection classifiers acting on multispectral UAV imagery.

Edge-directed inference for microaneurysms detection in digital fundus images

NASA Astrophysics Data System (ADS)

Huang, Ke; Yan, Michelle; Aviyente, Selin

2007-03-01

Microaneurysms (MAs) detection is a critical step in diabetic retinopathy screening, since MAs are the earliest visible warning of potential future problems. A variety of algorithms have been proposed for MAs detection in mass screening. Different methods have been proposed for MAs detection. The core technology for most of existing methods is based on a directional mathematical morphological operation called "Top-Hat" filter that requires multiple filtering operations at each pixel. Background structure, uneven illumination and noise often cause confusion between MAs and some non-MA structures and limits the applicability of the filter. In this paper, a novel detection framework based on edge directed inference is proposed for MAs detection. The candidate MA regions are first delineated from the edge map of a fundus image. Features measuring shape, brightness and contrast are extracted for each candidate MA region to better exclude false detection from true MAs. Algorithmic analysis and empirical evaluation reveal that the proposed edge directed inference outperforms the "Top-Hat" based algorithm in both detection accuracy and computational speed.

Improving estimates of genetic maps: a meta-analysis-based approach.

PubMed

Stewart, William C L

2007-07-01

Inaccurate genetic (or linkage) maps can reduce the power to detect linkage, increase type I error, and distort haplotype and relationship inference. To improve the accuracy of existing maps, I propose a meta-analysis-based method that combines independent map estimates into a single estimate of the linkage map. The method uses the variance of each independent map estimate to combine them efficiently, whether the map estimates use the same set of markers or not. As compared with a joint analysis of the pooled genotype data, the proposed method is attractive for three reasons: (1) it has comparable efficiency to the maximum likelihood map estimate when the pooled data are homogeneous; (2) relative to existing map estimation methods, it can have increased efficiency when the pooled data are heterogeneous; and (3) it avoids the practical difficulties of pooling human subjects data. On the basis of simulated data modeled after two real data sets, the proposed method can reduce the sampling variation of linkage maps commonly used in whole-genome linkage scans. Furthermore, when the independent map estimates are also maximum likelihood estimates, the proposed method performs as well as or better than when they are estimated by the program CRIMAP. Since variance estimates of maps may not always be available, I demonstrate the feasibility of three different variance estimators. Overall, the method should prove useful to investigators who need map positions for markers not contained in publicly available maps, and to those who wish to minimize the negative effects of inaccurate maps. Copyright 2007 Wiley-Liss, Inc.

Object-based change detection method using refined Markov random field

NASA Astrophysics Data System (ADS)

Peng, Daifeng; Zhang, Yongjun

2017-01-01

In order to fully consider the local spatial constraints between neighboring objects in object-based change detection (OBCD), an OBCD approach is presented by introducing a refined Markov random field (MRF). First, two periods of images are stacked and segmented to produce image objects. Second, object spectral and textual histogram features are extracted and G-statistic is implemented to measure the distance among different histogram distributions. Meanwhile, object heterogeneity is calculated by combining spectral and textual histogram distance using adaptive weight. Third, an expectation-maximization algorithm is applied for determining the change category of each object and the initial change map is then generated. Finally, a refined change map is produced by employing the proposed refined object-based MRF method. Three experiments were conducted and compared with some state-of-the-art unsupervised OBCD methods to evaluate the effectiveness of the proposed method. Experimental results demonstrate that the proposed method obtains the highest accuracy among the methods used in this paper, which confirms its validness and effectiveness in OBCD.

Optimized static and video EEG rapid serial visual presentation (RSVP) paradigm based on motion surprise computation

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Huber, David J.; Bhattacharyya, Rajan

2017-05-01

In this paper, we describe an algorithm and system for optimizing search and detection performance for "items of interest" (IOI) in large-sized images and videos that employ the Rapid Serial Visual Presentation (RSVP) based EEG paradigm and surprise algorithms that incorporate motion processing to determine whether static or video RSVP is used. The system works by first computing a motion surprise map on image sub-regions (chips) of incoming sensor video data and then uses those surprise maps to label the chips as either "static" or "moving". This information tells the system whether to use a static or video RSVP presentation and decoding algorithm in order to optimize EEG based detection of IOI in each chip. Using this method, we are able to demonstrate classification of a series of image regions from video with an azimuth value of 1, indicating perfect classification, over a range of display frequencies and video speeds.

A Minimum Spanning Forest Based Method for Noninvasive Cancer Detection with Hyperspectral Imaging

PubMed Central

Pike, Robert; Lu, Guolan; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2016-01-01

Goal The purpose of this paper is to develop a classification method that combines both spectral and spatial information for distinguishing cancer from healthy tissue on hyperspectral images in an animal model. Methods An automated algorithm based on a minimum spanning forest (MSF) and optimal band selection has been proposed to classify healthy and cancerous tissue on hyperspectral images. A support vector machine (SVM) classifier is trained to create a pixel-wise classification probability map of cancerous and healthy tissue. This map is then used to identify markers that are used to compute mutual information for a range of bands in the hyperspectral image and thus select the optimal bands. An MSF is finally grown to segment the image using spatial and spectral information. Conclusion The MSF based method with automatically selected bands proved to be accurate in determining the tumor boundary on hyperspectral images. Significance Hyperspectral imaging combined with the proposed classification technique has the potential to provide a noninvasive tool for cancer detection. PMID:26285052

A Toolkit for bulk PCR-based marker design from next-generation sequence data: application for development of a framework linkage map in bulb onion (Allium cepa L.)

PubMed Central

2012-01-01

Background Although modern sequencing technologies permit the ready detection of numerous DNA sequence variants in any organisms, converting such information to PCR-based genetic markers is hampered by a lack of simple, scalable tools. Onion is an example of an under-researched crop with a complex, heterozygous genome where genome-based research has previously been hindered by limited sequence resources and genetic markers. Results We report the development of generic tools for large-scale web-based PCR-based marker design in the Galaxy bioinformatics framework, and their application for development of next-generation genetics resources in a wide cross of bulb onion (Allium cepa L.). Transcriptome sequence resources were developed for the homozygous doubled-haploid bulb onion line ‘CUDH2150’ and the genetically distant Indian landrace ‘Nasik Red’, using 454™ sequencing of normalised cDNA libraries of leaf and shoot. Read mapping of ‘Nasik Red’ reads onto ‘CUDH2150’ assemblies revealed 16836 indel and SNP polymorphisms that were mined for portable PCR-based marker development. Tools for detection of restriction polymorphisms and primer set design were developed in BioPython and adapted for use in the Galaxy workflow environment, enabling large-scale and targeted assay design. Using PCR-based markers designed with these tools, a framework genetic linkage map of over 800cM spanning all chromosomes was developed in a subset of 93 F2 progeny from a very large F2 family developed from the ‘Nasik Red’ x ‘CUDH2150’ inter-cross. The utility of tools and genetic resources developed was tested by designing markers to transcription factor-like polymorphic sequences. Bin mapping these markers using a subset of 10 progeny confirmed the ability to place markers within 10 cM bins, enabling increased efficiency in marker assignment and targeted map refinement. The major genetic loci conditioning red bulb colour (R) and fructan content (Frc) were located on this map by QTL analysis. Conclusions The generic tools developed for the Galaxy environment enable rapid development of sets of PCR assays targeting sequence variants identified from Illumina and 454 sequence data. They enable non-specialist users to validate and exploit large volumes of next-generation sequence data using basic equipment. PMID:23157543

A toolkit for bulk PCR-based marker design from next-generation sequence data: application for development of a framework linkage map in bulb onion (Allium cepa L.).

PubMed

Baldwin, Samantha; Revanna, Roopashree; Thomson, Susan; Pither-Joyce, Meeghan; Wright, Kathryn; Crowhurst, Ross; Fiers, Mark; Chen, Leshi; Macknight, Richard; McCallum, John A

2012-11-19

Although modern sequencing technologies permit the ready detection of numerous DNA sequence variants in any organisms, converting such information to PCR-based genetic markers is hampered by a lack of simple, scalable tools. Onion is an example of an under-researched crop with a complex, heterozygous genome where genome-based research has previously been hindered by limited sequence resources and genetic markers. We report the development of generic tools for large-scale web-based PCR-based marker design in the Galaxy bioinformatics framework, and their application for development of next-generation genetics resources in a wide cross of bulb onion (Allium cepa L.). Transcriptome sequence resources were developed for the homozygous doubled-haploid bulb onion line 'CUDH2150' and the genetically distant Indian landrace 'Nasik Red', using 454™ sequencing of normalised cDNA libraries of leaf and shoot. Read mapping of 'Nasik Red' reads onto 'CUDH2150' assemblies revealed 16836 indel and SNP polymorphisms that were mined for portable PCR-based marker development. Tools for detection of restriction polymorphisms and primer set design were developed in BioPython and adapted for use in the Galaxy workflow environment, enabling large-scale and targeted assay design. Using PCR-based markers designed with these tools, a framework genetic linkage map of over 800cM spanning all chromosomes was developed in a subset of 93 F(2) progeny from a very large F(2) family developed from the 'Nasik Red' x 'CUDH2150' inter-cross. The utility of tools and genetic resources developed was tested by designing markers to transcription factor-like polymorphic sequences. Bin mapping these markers using a subset of 10 progeny confirmed the ability to place markers within 10 cM bins, enabling increased efficiency in marker assignment and targeted map refinement. The major genetic loci conditioning red bulb colour (R) and fructan content (Frc) were located on this map by QTL analysis. The generic tools developed for the Galaxy environment enable rapid development of sets of PCR assays targeting sequence variants identified from Illumina and 454 sequence data. They enable non-specialist users to validate and exploit large volumes of next-generation sequence data using basic equipment.

The evolution of mapping habitat for northern spotted owls (Strix occidentalis caurina): A comparison of photo-interpreted, Landsat-based, and lidar-based habitat maps

USGS Publications Warehouse

Ackers, Steven H.; Davis, Raymond J.; Olsen, K.; Dugger, Catherine

2015-01-01

Wildlife habitat mapping has evolved at a rapid pace over the last few decades. Beginning with simple, often subjective, hand-drawn maps, habitat mapping now involves complex species distribution models (SDMs) using mapped predictor variables derived from remotely sensed data. For species that inhabit large geographic areas, remote sensing technology is often essential for producing range wide maps. Habitat monitoring for northern spotted owls (Strix occidentalis caurina), whose geographic covers about 23 million ha, is based on SDMs that use Landsat Thematic Mapper imagery to create forest vegetation data layers using gradient nearest neighbor (GNN) methods. Vegetation data layers derived from GNN are modeled relationships between forest inventory plot data, climate and topographic data, and the spectral signatures acquired by the satellite. When used as predictor variables for SDMs, there is some transference of the GNN modeling error to the final habitat map.Recent increases in the use of light detection and ranging (lidar) data, coupled with the need to produce spatially accurate and detailed forest vegetation maps have spurred interest in its use for SDMs and habitat mapping. Instead of modeling predictor variables from remotely sensed spectral data, lidar provides direct measurements of vegetation height for use in SDMs. We expect a SDM habitat map produced from directly measured predictor variables to be more accurate than one produced from modeled predictors.We used maximum entropy (Maxent) SDM modeling software to compare predictive performance and estimates of habitat area between Landsat-based and lidar-based northern spotted owl SDMs and habitat maps. We explored the differences and similarities between these maps, and to a pre-existing aerial photo-interpreted habitat map produced by local wildlife biologists. The lidar-based map had the highest predictive performance based on 10 bootstrapped replicate models (AUC = 0.809 ± 0.011), but the performance of the Landsat-based map was within acceptable limits (AUC = 0.717 ± 0.021). As is common with photo-interpreted maps, there was no accuracy assessment available for comparison. The photo-interpreted map produced the highest and lowest estimates of habitat area, depending on which habitat classes were included (nesting, roosting, and foraging habitat = 9962 ha, nesting habitat only = 6036 ha). The Landsat-based map produced an estimate of habitat area that was within this range (95% CI: 6679–9592 ha), while the lidar-based map produced an area estimate similar to what was interpreted by local wildlife biologists as nesting (i.e., high quality) habitat using aerial imagery (95% CI: 5453–7216). Confidence intervals of habitat area estimates from the SDMs based on Landsat and lidar overlapped.We concluded that both Landsat- and lidar-based SDMs produced reasonable maps and area estimates for northern spotted owl habitat within the study area. The lidar-based map was more precise and spatially similar to what local wildlife biologists considered spotted owl nesting habitat. The Landsat-based map provided a less precise spatial representation of habitat within the relatively small geographic confines of the study area, but habitat area estimates were similar to both the photo-interpreted and lidar-based maps.Photo-interpreted maps are time consuming to produce, subjective in nature, and difficult to replicate. SDMs provide a framework for efficiently producing habitat maps that can be replicated as habitat conditions change over time, provided that comparable remotely sensed data are available. When the SDM uses predictor variables extracted from lidar data, it can produce a habitat map that is both accurate and useful at large and small spatial scales. In comparison, SDMs using Landsat-based data are more appropriate for large scale analyses of amounts and general spatial patterns of habitat at regional scales.

Major quality trait analysis and QTL detection in hexaploid wheat in humid rain-fed agriculture.

PubMed

Li, H M; Tang, Z X; Zhang, H Q; Yan, B J; Ren, Z L

2013-05-21

Humid rain-fed agriculture is a special environment for wheat (Triticum aestivum) culture that tends to negatively affect wheat yield and quality. To identify quality characters of wheat in a humid environment, we conducted quality analysis and quantitative trait loci (QTL) detection in a recombinant inbred line whose parent had a high level of quality for several years. We found that high-quality wheat had less gluten content and lower protein content. Apparently, wheat quality and associated quantity traits were in a dynamic state of equilibrium. We detected 83 QTL for 10 wheat quality traits in this recombinant inbred line population. Nine QTL were detected in both evaluation years; Q.DT.scau-2A, linked to Xwmc522-2A, was detected at the same genetic location in both years. Other QTL for different traits were detected simultaneously in more than one location. Consequently, there appeared to be pleiotropic genes that control wheat quality. Based on previous studies and our research on QTL analysis of grain protein content, we conclude that there must be one or more genes for grain protein content on chromosome 6B, whose expression was little affected by environment. We constructed a consensus map and projected the QTL on it. It was useful for choosing optimal markers for marker-assisted breeding and map-based cloning.

Development of a Global Agricultural Hotspot Detection and Early Warning System

NASA Astrophysics Data System (ADS)

Lemoine, G.; Rembold, F.; Urbano, F.; Csak, G.

2015-12-01

The number of web based platforms for crop monitoring has grown rapidly over the last years and anomaly maps and time profiles of remote sensing derived indicators can be accessed online thanks to a number of web based portals. However, while these systems make available a large amount of crop monitoring data to the agriculture and food security analysts, there is no global platform which provides agricultural production hotspot warning in a highly automatic and timely manner. Therefore a web based system providing timely warning evidence as maps and short narratives is currently under development by the Joint Research Centre. The system (called "HotSpot Detection System of Agriculture Production Anomalies", HSDS) will focus on water limited agricultural systems worldwide. The automatic analysis of relevant meteorological and vegetation indicators at selected administrative units (Gaul 1 level) will trigger warning messages for the areas where anomalous conditions are observed. The level of warning (ranging from "watch" to "alert") will depend on the nature and number of indicators for which an anomaly is detected. Information regarding the extent of the agricultural areas concerned by the anomaly and the progress of the agricultural season will complement the warning label. In addition, we are testing supplementary detailed information from other sources for the areas triggering a warning. These regard the automatic web-based and food security-tailored analysis of media (using the JRC Media Monitor semantic search engine) and the automatic detection of active crop area using Sentinel 1, upcoming Sentinel-2 and Landsat 8 imagery processed in Google Earth Engine. The basic processing will be fully automated and updated every 10 days exploiting low resolution rainfall estimates and satellite vegetation indices. Maps, trend graphs and statistics accompanied by short narratives edited by a team of crop monitoring experts, will be made available on the website on a monthly basis.

Construction of a high-density genetic map using specific length amplified fragment markers and identification of a quantitative trait locus for anthracnose resistance in walnut (Juglans regia L.).

PubMed

Zhu, Yufeng; Yin, Yanfei; Yang, Keqiang; Li, Jihong; Sang, Yalin; Huang, Long; Fan, Shu

2015-08-18

Walnut (Juglans regia, 2n = 32, approximately 606 Mb per 1C genome) is an economically important tree crop. Resistance to anthracnose, caused by Colletotrichum gloeosporioides, is a major objective of walnut genetic improvement in China. The recently developed specific length amplified fragment sequencing (SLAF-seq) is an efficient strategy that can obtain large numbers of markers with sufficient sequence information to construct high-density genetic maps and permits detection of quantitative trait loci (QTLs) for molecular breeding. SLAF-seq generated 161.64 M paired-end reads. 153,820 SLAF markers were obtained, of which 49,174 were polymorphic. 13,635 polymorphic markers were sorted into five segregation types and 2,577 markers of them were used to construct genetic linkage maps: 2,395 of these fell into 16 linkage groups (LGs) for the female map, 448 markers for the male map, and 2,577 markers for the integrated map. Taking into account the size of all LGs, the marker coverage was 2,664.36 cM for the female map, 1,305.58 cM for the male map, and 2,457.82 cM for the integrated map. The average intervals between two adjacent mapped markers were 1.11 cM, 2.91 cM and 0.95 cM for three maps, respectively. 'SNP_only' markers accounted for 89.25% of the markers on the integrated map. Mapping markers contained 5,043 single nucleotide polymorphisms (SNPs) loci, which corresponded to two SNP loci per SLAF marker. According to the integrated map, we used interval mapping (Logarithm of odds, LOD > 3.0) to detect our quantitative trait. One QTL was detected for anthracnose resistance. The interval of this QTL ranged from 165.51 cM to 176.33 cM on LG14, and ten markers in this interval that were above the threshold value were considered to be linked markers to the anthracnose resistance trait. The phenotypic variance explained by each marker ranged from 16.2 to 19.9%, and their LOD scores varied from 3.22 to 4.04. High-density genetic maps for walnut containing 16 LGs were constructed using the SLAF-seq method with an F1 population. One QTL for walnut anthracnose resistance was identified based on the map. The results will aid molecular marker-assisted breeding and walnut resistance genes identification.

Tree crown mapping in managed woodlands (parklands) of semi-arid West Africa using WorldView-2 imagery and geographic object based image analysis.

PubMed

Karlson, Martin; Reese, Heather; Ostwald, Madelene

2014-11-28

Detailed information on tree cover structure is critical for research and monitoring programs targeting African woodlands, including agroforestry parklands. High spatial resolution satellite imagery represents a potentially effective alternative to field-based surveys, but requires the development of accurate methods to automate information extraction. This study presents a method for tree crown mapping based on Geographic Object Based Image Analysis (GEOBIA) that use spectral and geometric information to detect and delineate individual tree crowns and crown clusters. The method was implemented on a WorldView-2 image acquired over the parklands of Saponé, Burkina Faso, and rigorously evaluated against field reference data. The overall detection rate was 85.4% for individual tree crowns and crown clusters, with lower accuracies in areas with high tree density and dense understory vegetation. The overall delineation error (expressed as the difference between area of delineated object and crown area measured in the field) was 45.6% for individual tree crowns and 61.5% for crown clusters. Delineation accuracies were higher for medium (35-100 m(2)) and large (≥100 m(2)) trees compared to small (<35 m(2)) trees. The results indicate potential of GEOBIA and WorldView-2 imagery for tree crown mapping in parkland landscapes and similar woodland areas.

Tree Crown Mapping in Managed Woodlands (Parklands) of Semi-Arid West Africa Using WorldView-2 Imagery and Geographic Object Based Image Analysis

PubMed Central

Karlson, Martin; Reese, Heather; Ostwald, Madelene

2014-01-01

Detailed information on tree cover structure is critical for research and monitoring programs targeting African woodlands, including agroforestry parklands. High spatial resolution satellite imagery represents a potentially effective alternative to field-based surveys, but requires the development of accurate methods to automate information extraction. This study presents a method for tree crown mapping based on Geographic Object Based Image Analysis (GEOBIA) that use spectral and geometric information to detect and delineate individual tree crowns and crown clusters. The method was implemented on a WorldView-2 image acquired over the parklands of Saponé, Burkina Faso, and rigorously evaluated against field reference data. The overall detection rate was 85.4% for individual tree crowns and crown clusters, with lower accuracies in areas with high tree density and dense understory vegetation. The overall delineation error (expressed as the difference between area of delineated object and crown area measured in the field) was 45.6% for individual tree crowns and 61.5% for crown clusters. Delineation accuracies were higher for medium (35–100 m2) and large (≥100 m2) trees compared to small (<35 m2) trees. The results indicate potential of GEOBIA and WorldView-2 imagery for tree crown mapping in parkland landscapes and similar woodland areas. PMID:25460815

Rapid detection methods for viable Mycobacterium avium subspecies paratuberculosis in milk and cheese.

PubMed

Botsaris, George; Slana, Iva; Liapi, Maria; Dodd, Christine; Economides, Constantinos; Rees, Catherine; Pavlik, Ivo

2010-07-31

Mycobacterium avium subsp. paratuberculosis (MAP) may have a role in the development of Crohn's disease in humans via the consumption of contaminated milk and milk products. Detection of MAP from milk and dairy products has been reported from countries on the European continent, Argentina, the UK and Australia. In this study three different methods (quantitative real time PCR, combined phage IS900 PCR and conventional cultivation) were used to detect the presence of MAP in bulk tank milk (BTM) and cheese originating from sheep, goat and mixed milks from farms and products in Cyprus. During the first survey the presence of MAP was detected in 63 (28.6%) of cows' BTM samples by quantitative real time PCR. A second survey of BTM used a new combined phage IS900 PCR assay, and in this case MAP was detected in 50 (22.2%) samples showing a good level of agreement by both methods. None of the herds tested were known to be affected by Johne's disease and the presence of viable MAP was confirmed by conventional culture in only two cases of cows BTM. This suggests that either rapid method used is more sensitive than the conventional culture when testing raw milk samples for MAP. The two isolates recovered from BTM were identified by IS1311 PCR REA as cattle and sheep strains, respectively. In contrast when cheese samples were tested, MAP DNA was detected by quantitative real time PCR in seven (25.0%) samples (n=28). However no viable MAP was detected when either the combined phage IS900 PCR or conventional culture methods were used. Copyright 2010 Elsevier B.V. All rights reserved.

Hierarchical Kohonenen net for anomaly detection in network security.

PubMed

Sarasamma, Suseela T; Zhu, Qiuming A; Huff, Julie

2005-04-01

A novel multilevel hierarchical Kohonen Net (K-Map) for an intrusion detection system is presented. Each level of the hierarchical map is modeled as a simple winner-take-all K-Map. One significant advantage of this multilevel hierarchical K-Map is its computational efficiency. Unlike other statistical anomaly detection methods such as nearest neighbor approach, K-means clustering or probabilistic analysis that employ distance computation in the feature space to identify the outliers, our approach does not involve costly point-to-point computation in organizing the data into clusters. Another advantage is the reduced network size. We use the classification capability of the K-Map on selected dimensions of data set in detecting anomalies. Randomly selected subsets that contain both attacks and normal records from the KDD Cup 1999 benchmark data are used to train the hierarchical net. We use a confidence measure to label the clusters. Then we use the test set from the same KDD Cup 1999 benchmark to test the hierarchical net. We show that a hierarchical K-Map in which each layer operates on a small subset of the feature space is superior to a single-layer K-Map operating on the whole feature space in detecting a variety of attacks in terms of detection rate as well as false positive rate.

Early warning smartphone diagnostics for water security and analysis using real-time pH mapping

NASA Astrophysics Data System (ADS)

Hossain, Md. Arafat; Canning, John; Ast, Sandra; Rutledge, Peter J.; Jamalipour, Abbas

2015-12-01

Early detection of environmental disruption, unintentional or otherwise, is increasingly desired to ensure hazard minimization in many settings. Here, using a field-portable, smartphone fluorimeter to assess water quality based on the pH response of a designer probe, a map of pH of public tap water sites has been obtained. A custom designed Android application digitally processed and mapped the results utilizing the global positioning system (GPS) service of the smartphone. The map generated indicates no disruption in pH for all sites measured, and all the data are assessed to fall inside the upper limit of local government regulations, consistent with authority reported measurements. This implementation demonstrates a new security concept: network environmental forensics utilizing the potential of novel smartgrid analysis with wireless sensors for the detection of potential disruption to water quality at any point in the city. This concept is applicable across all smartgrid strategies within the next generation of the Internet of Things and can be extended on national and global scales to address a range of target analytes, both chemical and biological.

Application of the High Resolution Melting analysis for genetic mapping of Sequence Tagged Site markers in narrow-leafed lupin (Lupinus angustifolius L.).

PubMed

Kamel, Katarzyna A; Kroc, Magdalena; Święcicki, Wojciech

2015-01-01

Sequence tagged site (STS) markers are valuable tools for genetic and physical mapping that can be successfully used in comparative analyses among related species. Current challenges for molecular markers genotyping in plants include the lack of fast, sensitive and inexpensive methods suitable for sequence variant detection. In contrast, high resolution melting (HRM) is a simple and high-throughput assay, which has been widely applied in sequence polymorphism identification as well as in the studies of genetic variability and genotyping. The present study is the first attempt to use the HRM analysis to genotype STS markers in narrow-leafed lupin (Lupinus angustifolius L.). The sensitivity and utility of this method was confirmed by the sequence polymorphism detection based on melting curve profiles in the parental genotypes and progeny of the narrow-leafed lupin mapping population. Application of different approaches, including amplicon size and a simulated heterozygote analysis, has allowed for successful genetic mapping of 16 new STS markers in the narrow-leafed lupin genome.

Mycobacterium avium Subspecies paratuberculosis: Human Exposure through Environmental and Domestic Aerosols

PubMed Central

Rhodes, Glenn; Richardson, Hollian; Hermon-Taylor, John; Weightman, Andrew; Higham, Andrew; Pickup, Roger

2014-01-01

Mycobacterium avium subspecies paratuberculosis (Map) causes Johne’s disease in animals and is significantly associated with Crohn’s disease (CD) in humans. Our previous studies have shown Map to be present in U.K. rivers due to land deposition from chronic livestock infection and runoff driven by rainfall. The epidemiology of CD in Cardiff showed a significant association with the River Taff, in which Map can be detected on a regular basis. We have previously hypothesized that aerosols from the river might influence the epidemiology of CD. In this preliminary study, we detected Map by quantitative PCR in one of five aerosol samples collected above the River Taff. In addition, we examined domestic showers from different regions in the U.K. and detected Map in three out of 30 independent samples. In detecting Map in river aerosols and those from domestic showers, this is the first study to provide evidence that aerosols are an exposure route for Map to humans and may play a role in the epidemiology of CD. PMID:25438013

Chemical mapping of cytosines enzymatically flipped out of the DNA helix

PubMed Central

Liutkevičiūtė, Zita; Tamulaitis, Gintautas; Klimašauskas, Saulius

2008-01-01

Haloacetaldehydes can be employed for probing unpaired DNA structures involving cytosine and adenine residues. Using an enzyme that was structurally proven to flip its target cytosine out of the DNA helix, the HhaI DNA methyltransferase (M.HhaI), we demonstrate the suitability of the chloroacetaldehyde modification for mapping extrahelical (flipped-out) cytosine bases in protein–DNA complexes. The generality of this method was verified with two other DNA cytosine-5 methyltransferases, M.AluI and M.SssI, as well as with two restriction endonucleases, R.Ecl18kI and R.PspGI, which represent a novel class of base-flipping enzymes. Our results thus offer a simple and convenient laboratory tool for detection and mapping of flipped-out cytosines in protein–DNA complexes. PMID:18450817

Uncovering Spatial Variation in Acoustic Environments Using Sound Mapping.

PubMed

Job, Jacob R; Myers, Kyle; Naghshineh, Koorosh; Gill, Sharon A

2016-01-01

Animals select and use habitats based on environmental features relevant to their ecology and behavior. For animals that use acoustic communication, the sound environment itself may be a critical feature, yet acoustic characteristics are not commonly measured when describing habitats and as a result, how habitats vary acoustically over space and time is poorly known. Such considerations are timely, given worldwide increases in anthropogenic noise combined with rapidly accumulating evidence that noise hampers the ability of animals to detect and interpret natural sounds. Here, we used microphone arrays to record the sound environment in three terrestrial habitats (forest, prairie, and urban) under ambient conditions and during experimental noise introductions. We mapped sound pressure levels (SPLs) over spatial scales relevant to diverse taxa to explore spatial variation in acoustic habitats and to evaluate the number of microphones needed within arrays to capture this variation under both ambient and noisy conditions. Even at small spatial scales and over relatively short time spans, SPLs varied considerably, especially in forest and urban habitats, suggesting that quantifying and mapping acoustic features could improve habitat descriptions. Subset maps based on input from 4, 8, 12 and 16 microphones differed slightly (< 2 dBA/pixel) from those based on full arrays of 24 microphones under ambient conditions across habitats. Map differences were more pronounced with noise introductions, particularly in forests; maps made from only 4-microphones differed more (> 4 dBA/pixel) from full maps than the remaining subset maps, but maps with input from eight microphones resulted in smaller differences. Thus, acoustic environments varied over small spatial scales and variation could be mapped with input from 4-8 microphones. Mapping sound in different environments will improve understanding of acoustic environments and allow us to explore the influence of spatial variation in sound on animal ecology and behavior.

Bedside risk estimation of morbidly adherent placenta using simple calculator.

PubMed

Maymon, R; Melcer, Y; Pekar-Zlotin, M; Shaked, O; Cuckle, H; Tovbin, J

2018-03-01

To construct a calculator for 'bedside' estimation of morbidly adherent placenta (MAP) risk based on ultrasound (US) findings. This retrospective study included all pregnant women with at least one previous cesarean delivery attending in our US unit between December 2013 and January 2017. The examination was based on a scoring system which determines the probability for MAP. The study population included 471 pregnant women, and 41 of whom (8.7%) were diagnosed with MAP. Based on ROC curve, the most effective US criteria for detection of MAP were the presence of the placental lacunae, obliteration of the utero-placental demarcation, and placenta previa. On the multivariate logistic regression analysis, US findings of placental lacunae (OR = 3.5; 95% CI, 1.2-9.5; P = 0.01), obliteration of the utero-placental demarcation (OR = 12.4; 95% CI, 3.7-41.6; P < 0.0001), and placenta previa (OR = 10.5; 95% CI, 3.5-31.3; P < 0.0001) were associated with MAP. By combining these three parameters, the receiver operating characteristic curve was calculated, yielding an area under the curve of 0.93 (95% CI, 0.87-0.97). Accordingly, we have constructed a simple calculator for 'bedside' estimation of MAP risk. The calculator is mounted on the hospital's internet website ( http://www.assafh.org/Pages/PPCalc/index.html ). The risk estimation of MAP varies between 1.5 and 87%. The present calculator enables a simple 'bedside' MAP estimation, facilitating accurate and adequate antenatal risk assessment.

Imputation of variants from the 1000 Genomes Project modestly improves known associations and can identify low-frequency variant-phenotype associations undetected by HapMap based imputation.

PubMed

Wood, Andrew R; Perry, John R B; Tanaka, Toshiko; Hernandez, Dena G; Zheng, Hou-Feng; Melzer, David; Gibbs, J Raphael; Nalls, Michael A; Weedon, Michael N; Spector, Tim D; Richards, J Brent; Bandinelli, Stefania; Ferrucci, Luigi; Singleton, Andrew B; Frayling, Timothy M

2013-01-01

Genome-wide association (GWA) studies have been limited by the reliance on common variants present on microarrays or imputable from the HapMap Project data. More recently, the completion of the 1000 Genomes Project has provided variant and haplotype information for several million variants derived from sequencing over 1,000 individuals. To help understand the extent to which more variants (including low frequency (1% ≤ MAF <5%) and rare variants (<1%)) can enhance previously identified associations and identify novel loci, we selected 93 quantitative circulating factors where data was available from the InCHIANTI population study. These phenotypes included cytokines, binding proteins, hormones, vitamins and ions. We selected these phenotypes because many have known strong genetic associations and are potentially important to help understand disease processes. We performed a genome-wide scan for these 93 phenotypes in InCHIANTI. We identified 21 signals and 33 signals that reached P<5×10(-8) based on HapMap and 1000 Genomes imputation, respectively, and 9 and 11 that reached a stricter, likely conservative, threshold of P<5×10(-11) respectively. Imputation of 1000 Genomes genotype data modestly improved the strength of known associations. Of 20 associations detected at P<5×10(-8) in both analyses (17 of which represent well replicated signals in the NHGRI catalogue), six were captured by the same index SNP, five were nominally more strongly associated in 1000 Genomes imputed data and one was nominally more strongly associated in HapMap imputed data. We also detected an association between a low frequency variant and phenotype that was previously missed by HapMap based imputation approaches. An association between rs112635299 and alpha-1 globulin near the SERPINA gene represented the known association between rs28929474 (MAF = 0.007) and alpha1-antitrypsin that predisposes to emphysema (P = 2.5×10(-12)). Our data provide important proof of principle that 1000 Genomes imputation will detect novel, low frequency-large effect associations.

Imputation of Variants from the 1000 Genomes Project Modestly Improves Known Associations and Can Identify Low-frequency Variant - Phenotype Associations Undetected by HapMap Based Imputation

PubMed Central

Wood, Andrew R.; Perry, John R. B.; Tanaka, Toshiko; Hernandez, Dena G.; Zheng, Hou-Feng; Melzer, David; Gibbs, J. Raphael; Nalls, Michael A.; Weedon, Michael N.; Spector, Tim D.; Richards, J. Brent; Bandinelli, Stefania; Ferrucci, Luigi; Singleton, Andrew B.; Frayling, Timothy M.

2013-01-01

Genome-wide association (GWA) studies have been limited by the reliance on common variants present on microarrays or imputable from the HapMap Project data. More recently, the completion of the 1000 Genomes Project has provided variant and haplotype information for several million variants derived from sequencing over 1,000 individuals. To help understand the extent to which more variants (including low frequency (1% ≤ MAF <5%) and rare variants (<1%)) can enhance previously identified associations and identify novel loci, we selected 93 quantitative circulating factors where data was available from the InCHIANTI population study. These phenotypes included cytokines, binding proteins, hormones, vitamins and ions. We selected these phenotypes because many have known strong genetic associations and are potentially important to help understand disease processes. We performed a genome-wide scan for these 93 phenotypes in InCHIANTI. We identified 21 signals and 33 signals that reached P<5×10−8 based on HapMap and 1000 Genomes imputation, respectively, and 9 and 11 that reached a stricter, likely conservative, threshold of P<5×10−11 respectively. Imputation of 1000 Genomes genotype data modestly improved the strength of known associations. Of 20 associations detected at P<5×10−8 in both analyses (17 of which represent well replicated signals in the NHGRI catalogue), six were captured by the same index SNP, five were nominally more strongly associated in 1000 Genomes imputed data and one was nominally more strongly associated in HapMap imputed data. We also detected an association between a low frequency variant and phenotype that was previously missed by HapMap based imputation approaches. An association between rs112635299 and alpha-1 globulin near the SERPINA gene represented the known association between rs28929474 (MAF = 0.007) and alpha1-antitrypsin that predisposes to emphysema (P = 2.5×10−12). Our data provide important proof of principle that 1000 Genomes imputation will detect novel, low frequency-large effect associations. PMID:23696881

Detection and Spatial Mapping of Mercury Contamination in Water Samples Using a Smart-Phone

PubMed Central

2014-01-01

Detection of environmental contamination such as trace-level toxic heavy metal ions mostly relies on bulky and costly analytical instruments. However, a considerable global need exists for portable, rapid, specific, sensitive, and cost-effective detection techniques that can be used in resource-limited and field settings. Here we introduce a smart-phone-based hand-held platform that allows the quantification of mercury(II) ions in water samples with parts per billion (ppb) level of sensitivity. For this task, we created an integrated opto-mechanical attachment to the built-in camera module of a smart-phone to digitally quantify mercury concentration using a plasmonic gold nanoparticle (Au NP) and aptamer based colorimetric transmission assay that is implemented in disposable test tubes. With this smart-phone attachment that weighs <40 g, we quantified mercury(II) ion concentration in water samples by using a two-color ratiometric method employing light-emitting diodes (LEDs) at 523 and 625 nm, where a custom-developed smart application was utilized to process each acquired transmission image on the same phone to achieve a limit of detection of ∼3.5 ppb. Using this smart-phone-based detection platform, we generated a mercury contamination map by measuring water samples at over 50 locations in California (USA), taken from city tap water sources, rivers, lakes, and beaches. With its cost-effective design, field-portability, and wireless data connectivity, this sensitive and specific heavy metal detection platform running on cellphones could be rather useful for distributed sensing, tracking, and sharing of water contamination information as a function of both space and time. PMID:24437470

Quantitative architectural analysis: a new approach to cortical mapping.

PubMed

Schleicher, A; Palomero-Gallagher, N; Morosan, P; Eickhoff, S B; Kowalski, T; de Vos, K; Amunts, K; Zilles, K

2005-12-01

Recent progress in anatomical and functional MRI has revived the demand for a reliable, topographic map of the human cerebral cortex. Till date, interpretations of specific activations found in functional imaging studies and their topographical analysis in a spatial reference system are, often, still based on classical architectonic maps. The most commonly used reference atlas is that of Brodmann and his successors, despite its severe inherent drawbacks. One obvious weakness in traditional, architectural mapping is the subjective nature of localising borders between cortical areas, by means of a purely visual, microscopical examination of histological specimens. To overcome this limitation, more objective, quantitative mapping procedures have been established in the past years. The quantification of the neocortical, laminar pattern by defining intensity line profiles across the cortical layers, has a long tradition. During the last years, this method has been extended to enable a reliable, reproducible mapping of the cortex based on image analysis and multivariate statistics. Methodological approaches to such algorithm-based, cortical mapping were published for various architectural modalities. In our contribution, principles of algorithm-based mapping are described for cyto- and receptorarchitecture. In a cytoarchitectural parcellation of the human auditory cortex, using a sliding window procedure, the classical areal pattern of the human superior temporal gyrus was modified by a replacing of Brodmann's areas 41, 42, 22 and parts of area 21, with a novel, more detailed map. An extension and optimisation of the sliding window procedure to the specific requirements of receptorarchitectonic mapping, is also described using the macaque central sulcus and adjacent superior parietal lobule as a second, biologically independent example. Algorithm-based mapping procedures, however, are not limited to these two architectural modalities, but can be applied to all images in which a laminar cortical pattern can be detected and quantified, e.g. myeloarchitectonic and in vivo high resolution MR imaging. Defining cortical borders, based on changes in cortical lamination in high resolution, in vivo structural MR images will result in a rapid increase of our knowledge on the structural parcellation of the human cerebral cortex.

Towards a Quasi-global precipitation-induced Landslide Detection System using Remote Sensing Information

NASA Astrophysics Data System (ADS)

Adler, B.; Hong, Y.; Huffman, G.; Negri, A.; Pando, M.

2006-05-01

Landslides and debris flows are one of the most widespread natural hazards on Earth, responsible for thousands of deaths and billions of dollars in property damage per year. Currently, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides. In this study, global landslide susceptibility is mapped using USGS GTOPO30 Digital Elevation, hydrological derivatives (slopes and wetness index etc.) from HYDRO1k data, soil type information downscaled from Digital Soil Map of the World (Sand, Loam, Silt, or Clay etc.), and MODIS land cover/use classification data. These variables are then combined with empirical landslide inventory data, if available, to derive a global landslide susceptibility map at elemental resolution of 1 x 1 km. This map can then be overlain with the driving force, namely rainfall estimates from the TRMM-based Multiple-satellite Precipitation Analysis to identify when areas with significant landslide potential receive heavy rainfall. The relations between rainfall intensity and rainstorm duration are regionally specific and often take the form of a power-law relation. Several empirical landslide-triggering Rainfall Intensity-Duration thresholds are implemented regionally using the 8-year TRMM-based precipitation with or without the global landslide susceptibility map at continuous space and time domain. Finally, the effectiveness of this system is validated by studying several recent deadly landslide/mudslide events. This study aims to build up a prototype quasi-global potential landslide warning system. Spatially-distributed landslide susceptibility maps and regional empirical rainfall intensity-duration thresholds, in combination with real-time rainfall measurements from space and rainfall forecasts from models, will be the basis for this experimental system.

Mapping on Slope Seepage Problem using Electrical Resistivity Imaging (ERI)

NASA Astrophysics Data System (ADS)

Hazreek, Z. A. M.; Nizam, Z. M.; Aziman, M.; Dan, M. F. Md; Shaylinda, M. Z. N.; Faizal, T. B. M.; Aishah, M. A. N.; Ambak, K.; Rosli, S.; Rais, Y.; Ashraf, M. I. M.; Alel, M. N. A.

2018-04-01

The stability of slope may influenced by several factors such as its geomaterial properties, geometry and environmental factors. Problematic slope due to seepage phenomenon will influenced the slope strength thus promoting to its failure. In the past, slope seepage mapping suffer from several limitation due to cost, time and data coverage. Conventional engineering tools to detect or mapped the seepage on slope experienced those problems involving large and high elevation of slope design. As a result, this study introduced geophysical tools for slope seepage mapping based on electrical resistivity method. Two spread lines of electrical resistivity imaging were performed on the slope crest using ABEM SAS 4000 equipment. Data acquisition configuration was based on long and short arrangement, schlumberger array and 2.5 m of equal electrode spacing interval. Raw data obtained from data acquisition was analyzed using RES2DINV software. Both of the resistivity results show that the slope studied consists of three different anomalies representing top soil (200 – 1000 Ωm), perched water (10 – 100 Ωm) and hard/dry layer (> 200 Ωm). It was found that seepage problem on slope studied was derived from perched water zones with electrical resistivity value of 10 – 100 Ωm. Perched water zone has been detected at 6 m depth from the ground level with varying thickness at 5 m and over. Resistivity results have shown some good similarity output with reference to borehole data, geological map and site observation thus verified the resistivity results interpretation. Hence, this study has shown that the electrical resistivity imaging was applicable in slope seepage mapping which consider efficient in term of cost, time, data coverage and sustainability.

Real-time method for establishing a detection map for a network of sensors

DOEpatents

Nguyen, Hung D; Koch, Mark W; Giron, Casey; Rondeau, Daniel M; Russell, John L

2012-09-11

A method for establishing a detection map of a dynamically configurable sensor network. This method determines an appropriate set of locations for a plurality of sensor units of a sensor network and establishes a detection map for the network of sensors while the network is being set up; the detection map includes the effects of the local terrain and individual sensor performance. Sensor performance is characterized during the placement of the sensor units, which enables dynamic adjustment or reconfiguration of the placement of individual elements of the sensor network during network set-up to accommodate variations in local terrain and individual sensor performance. The reconfiguration of the network during initial set-up to accommodate deviations from idealized individual sensor detection zones improves the effectiveness of the sensor network in detecting activities at a detection perimeter and can provide the desired sensor coverage of an area while minimizing unintentional gaps in coverage.

Development and validation of a triplex real-time PCR for rapid detection and specific identification of M. avium sub sp. paratuberculosis in faecal samples.

PubMed

Irenge, Léonid M; Walravens, Karl; Govaerts, Marc; Godfroid, Jacques; Rosseels, Valérie; Huygen, Kris; Gala, Jean-Luc

2009-04-14

A triplex real-time (TRT-PCR) assay was developed to ensure a rapid and reliable detection of Mycobacterium avium subsp. paratuberculosis (Map) in faecal samples and to allow routine detection of Map in farmed livestock and wildlife species. The TRT-PCR assay was designed using IS900, ISMAP02 and f57 molecular targets. Specificity of TRT-PCR was first confirmed on a panel of control mycobacterial Map and non-Map strains and on faecal samples from Map-negative cows (n=35) and from Map-positive cows (n=20). The TRT-PCR assay was compared to direct examination after Ziehl-Neelsen (ZN) staining and to culture on 197 faecal samples collected serially from five calves experimentally exposed to Map over a 3-year period during the sub-clinical phase of the disease. The data showed a good agreement between culture and TRT-PCR (kappa score=0.63), with the TRT-PCR limit of detection of 2.5 x 10(2)microorganisms/g of faeces spiked with Map. ZN agreement with TRT-PCR was not good (kappa=0.02). Sequence analysis of IS900 amplicons from three single IS900 positive samples confirmed the true Map positivity of the samples. Highly specific IS900 amplification suggests therefore that each single IS900 positive sample from experimentally exposed animals was a true Map-positive specimen. In this controlled experimental setting, the TRT-PCT was rapid, specific and displayed a very high sensitivity for Map detection in faecal samples compared to conventional methods.

Change Detection in High-Resolution Remote Sensing Images Using Levene-Test and Fuzzy Evaluation

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Liu, H. J.

2018-04-01

High-resolution remote sensing images possess complex spatial structure and rich texture information, according to these, this paper presents a new method of change detection based on Levene-Test and Fuzzy Evaluation. It first got map-spots by segmenting two overlapping images which had been pretreated, extracted features such as spectrum and texture. Then, changed information of all map-spots which had been treated by the Levene-Test were counted to obtain the candidate changed regions, hue information (H component) was extracted through the IHS Transform and conducted change vector analysis combined with the texture information. Eventually, the threshold was confirmed by an iteration method, the subject degrees of candidate changed regions were calculated, and final change regions were determined. In this paper experimental results on multi-temporal ZY-3 high-resolution images of some area in Jiangsu Province show that: Through extracting map-spots of larger difference as the candidate changed regions, Levene-Test decreases the computing load, improves the precision of change detection, and shows better fault-tolerant capacity for those unchanged regions which are of relatively large differences. The combination of Hue-texture features and fuzzy evaluation method can effectively decrease omissions and deficiencies, improve the precision of change detection.

Model based rib-cage unfolding for trauma CT

NASA Astrophysics Data System (ADS)

von Berg, Jens; Klinder, Tobias; Lorenz, Cristian

2018-03-01

A CT rib-cage unfolding method is proposed that does not require to determine rib centerlines but determines the visceral cavity surface by model base segmentation. Image intensities are sampled across this surface that is flattened using a model based 3D thin-plate-spline registration. An average rib centerline model projected onto this surface serves as a reference system for registration. The flattening registration is designed so that ribs similar to the centerline model are mapped onto parallel lines preserving their relative length. Ribs deviating from this model appear deviating from straight parallel ribs in the unfolded view, accordingly. As the mapping is continuous also the details in intercostal space and those adjacent to the ribs are rendered well. The most beneficial application area is Trauma CT where a fast detection of rib fractures is a crucial task. Specifically in trauma, automatic rib centerline detection may not be guaranteed due to fractures and dislocations. The application by visual assessment on the large public LIDC data base of lung CT proved general feasibility of this early work.

Spatio Temporal Detection and Virtual Mapping of Landslide Using High-Resolution Airborne Laser Altimetry (lidar) in Densely Vegetated Areas of Tropics

NASA Astrophysics Data System (ADS)

Bibi, T.; Azahari Razak, K.; Rahman, A. Abdul; Latif, A.

2017-10-01

Landslides are an inescapable natural disaster, resulting in massive social, environmental and economic impacts all over the world. The tropical, mountainous landscape in generally all over Malaysia especially in eastern peninsula (Borneo) is highly susceptible to landslides because of heavy rainfall and tectonic disturbances. The purpose of the Landslide hazard mapping is to identify the hazardous regions for the execution of mitigation plans which can reduce the loss of life and property from future landslide incidences. Currently, the Malaysian research bodies e.g. academic institutions and government agencies are trying to develop a landslide hazard and risk database for susceptible areas to backing the prevention, mitigation, and evacuation plan. However, there is a lack of devotion towards landslide inventory mapping as an elementary input of landslide susceptibility, hazard and risk mapping. The developing techniques based on remote sensing technologies (satellite, terrestrial and airborne) are promising techniques to accelerate the production of landslide maps, shrinking the time and resources essential for their compilation and orderly updates. The aim of the study is to provide a better perception regarding the use of virtual mapping of landslides with the help of LiDAR technology. The focus of the study is spatio temporal detection and virtual mapping of landslide inventory via visualization and interpretation of very high-resolution data (VHR) in forested terrain of Mesilau river, Kundasang. However, to cope with the challenges of virtual inventory mapping on in forested terrain high resolution LiDAR derivatives are used. This study specifies that the airborne LiDAR technology can be an effective tool for mapping landslide inventories in a complex climatic and geological conditions, and a quick way of mapping regional hazards in the tropics.

Approach for scene reconstruction from the analysis of a triplet of still images

NASA Astrophysics Data System (ADS)

Lechat, Patrick; Le Mestre, Gwenaelle; Pele, Danielle

1997-03-01

Three-dimensional modeling of a scene from the automatic analysis of 2D image sequences is a big challenge for future interactive audiovisual services based on 3D content manipulation such as virtual vests, 3D teleconferencing and interactive television. We propose a scheme that computes 3D objects models from stereo analysis of image triplets shot by calibrated cameras. After matching the different views with a correlation based algorithm, a depth map referring to a given view is built by using a fusion criterion taking into account depth coherency, visibility constraints and correlation scores. Because luminance segmentation helps to compute accurate object borders and to detect and improve the unreliable depth values, a two steps segmentation algorithm using both depth map and graylevel image is applied to extract the objects masks. First an edge detection segments the luminance image in regions and a multimodal thresholding method selects depth classes from the depth map. Then the regions are merged and labelled with the different depth classes numbers by using a coherence test on depth values according to the rate of reliable and dominant depth values and the size of the regions. The structures of the segmented objects are obtained with a constrained Delaunay triangulation followed by a refining stage. Finally, texture mapping is performed using open inventor or VRML1.0 tools.

Application of a new IBD-based QTL mapping method to common wheat breeding population: analysis of kernel hardness and dough strength.

PubMed

Crepieux, Sebastien; Lebreton, Claude; Flament, Pascal; Charmet, Gilles

2005-11-01

Mapping quantitative trait loci (QTL) in plants is usually conducted using a population derived from a cross between two inbred lines. The power of such QTL detection and the estimation of the effects highly depend on the choice of the two parental lines. Thus, the QTL found represent only a small part of the genetic architecture and can be of limited economical interest in marker-assisted selection. On the other hand, applied breeding programmes evaluate large numbers of progeny derived from multiple-related crosses for a wide range of agronomic traits. It is assumed that the development of statistical techniques to deal with pedigrees in existing plant populations would increase the relevance and cost effectiveness of QTL mapping in a breeding context. In this study, we applied a two-step IBD-based-variance component method to a real wheat breeding population, composed of 374 F6 lines derived from 80 different parents. Two bread wheat quality related traits were analysed by the method. Results obtained show very close agreement with major genes and QTL already known for those two traits. With this new QTL mapping strategy, inferences about QTL can be drawn across the breeding programme rather than being limited to the sample of progeny from a single cross and thus the use of the detected QTL in assisting breeding would be facilitated.

The 1991 International Aerospace and Ground Conference on Lightning and Static Electricity, volume 2

NASA Technical Reports Server (NTRS)

1991-01-01

The proceedings of the conference are reported. The conference focussed on lightning protection, detection, and forecasting. The conference was divided into 26 sessions based on research in lightning, static electricity, modeling, and mapping. These sessions spanned the spectrum from basic science to engineering, concentrating on lightning prediction and detection and on safety for ground facilities, aircraft, and aerospace vehicles.

Cross-correlating Planck tSZ with RCSLenS weak lensing: implications for cosmology and AGN feedback

NASA Astrophysics Data System (ADS)

Hojjati, Alireza; Tröster, Tilman; Harnois-Déraps, Joachim; McCarthy, Ian G.; van Waerbeke, Ludovic; Choi, Ami; Erben, Thomas; Heymans, Catherine; Hildebrandt, Hendrik; Hinshaw, Gary; Ma, Yin-Zhe; Miller, Lance; Viola, Massimo; Tanimura, Hideki

2017-10-01

We present measurements of the spatial mapping between (hot) baryons and the total matter in the Universe, via the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) map from Planck and the weak gravitational lensing maps from the Red Cluster Sequence Lensing Survey (RCSLenS). The cross-correlations are performed on the map level where all the sources (including diffuse intergalactic gas) contribute to the signal. We consider two configuration-space correlation function estimators, ξy-κ and ξ ^ {y-γ t}, and a Fourier-space estimator, C_{ℓ}^{y-κ}, in our analysis. We detect a significant correlation out to 3° of angular separation on the sky. Based on statistical noise only, we can report 13σ and 17σ detections of the cross-correlation using the configuration-space y-κ and y-γt estimators, respectively. Including a heuristic estimate of the sampling variance yields a detection significance of 7σ and 8σ, respectively. A similar level of detection is obtained from the Fourier-space estimator, C_{ℓ}^{y-κ}. As each estimator probes different dynamical ranges, their combination improves the significance of the detection. We compare our measurements with predictions from the cosmo-OverWhelmingly Large Simulations suite of cosmological hydrodynamical simulations, where different galactic feedback models are implemented. We find that a model with considerable active galactic nuclei (AGN) feedback that removes large quantities of hot gas from galaxy groups and Wilkinson Microwave Anisotropy Probe 7-yr best-fitting cosmological parameters provides the best match to the measurements. All baryonic models in the context of a Planck cosmology overpredict the observed signal. Similar cosmological conclusions are drawn when we employ a halo model with the observed 'universal' pressure profile.

A plastic scintillator-based 2D thermal neutron mapping system for use in BNCT studies.

PubMed

Ghal-Eh, N; Green, S

2016-06-01

In this study, a scintillator-based measurement instrument is proposed which is capable of measuring a two-dimensional map of thermal neutrons within a phantom based on the detection of 2.22MeV gamma rays generated via nth+H→D+γ reaction. The proposed instrument locates around a small rectangular water phantom (14cm×15cm×20cm) used in Birmingham BNCT facility. The whole system has been simulated using MCNPX 2.6. The results confirm that the thermal flux peaks somewhere between 2cm and 4cm distance from the system entrance which is in agreement with previous studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assisting the visually impaired: obstacle detection and warning system by acoustic feedback.

PubMed

Rodríguez, Alberto; Yebes, J Javier; Alcantarilla, Pablo F; Bergasa, Luis M; Almazán, Javier; Cela, Andrés

2012-12-17

The aim of this article is focused on the design of an obstacle detection system for assisting visually impaired people. A dense disparity map is computed from the images of a stereo camera carried by the user. By using the dense disparity map, potential obstacles can be detected in 3D in indoor and outdoor scenarios. A ground plane estimation algorithm based on RANSAC plus filtering techniques allows the robust detection of the ground in every frame. A polar grid representation is proposed to account for the potential obstacles in the scene. The design is completed with acoustic feedback to assist visually impaired users while approaching obstacles. Beep sounds with different frequencies and repetitions inform the user about the presence of obstacles. Audio bone conducting technology is employed to play these sounds without interrupting the visually impaired user from hearing other important sounds from its local environment. A user study participated by four visually impaired volunteers supports the proposed system.

Assisting the Visually Impaired: Obstacle Detection and Warning System by Acoustic Feedback

PubMed Central

Rodríguez, Alberto; Yebes, J. Javier; Alcantarilla, Pablo F.; Bergasa, Luis M.; Almazán, Javier; Cela, Andrés

2012-01-01

The aim of this article is focused on the design of an obstacle detection system for assisting visually impaired people. A dense disparity map is computed from the images of a stereo camera carried by the user. By using the dense disparity map, potential obstacles can be detected in 3D in indoor and outdoor scenarios. A ground plane estimation algorithm based on RANSAC plus filtering techniques allows the robust detection of the ground in every frame. A polar grid representation is proposed to account for the potential obstacles in the scene. The design is completed with acoustic feedback to assist visually impaired users while approaching obstacles. Beep sounds with different frequencies and repetitions inform the user about the presence of obstacles. Audio bone conducting technology is employed to play these sounds without interrupting the visually impaired user from hearing other important sounds from its local environment. A user study participated by four visually impaired volunteers supports the proposed system. PMID:23247413

Genome survey and high-density genetic map construction provide genomic and genetic resources for the Pacific White Shrimp Litopenaeus vannamei

PubMed Central

Yu, Yang; Zhang, Xiaojun; Yuan, Jianbo; Li, Fuhua; Chen, Xiaohan; Zhao, Yongzhen; Huang, Long; Zheng, Hongkun; Xiang, Jianhai

2015-01-01

The Pacific white shrimp Litopenaeus vannamei is the dominant crustacean species in global seafood mariculture. Understanding the genome and genetic architecture is useful for deciphering complex traits and accelerating the breeding program in shrimp. In this study, a genome survey was conducted and a high-density linkage map was constructed using a next-generation sequencing approach. The genome survey was used to identify preliminary genome characteristics and to generate a rough reference for linkage map construction. De novo SNP discovery resulted in 25,140 polymorphic markers. A total of 6,359 high-quality markers were selected for linkage map construction based on marker coverage among individuals and read depths. For the linkage map, a total of 6,146 markers spanning 4,271.43 cM were mapped to 44 sex-averaged linkage groups, with an average marker distance of 0.7 cM. An integration analysis linked 5,885 genome scaffolds and 1,504 BAC clones to the linkage map. Based on the high-density linkage map, several QTLs for body weight and body length were detected. This high-density genetic linkage map reveals basic genomic architecture and will be useful for comparative genomics research, genome assembly and genetic improvement of L. vannamei and other penaeid shrimp species. PMID:26503227

Uav-Based 3d Urban Environment Monitoring

NASA Astrophysics Data System (ADS)

Boonpook, Wuttichai; Tan, Yumin; Liu, Huaqing; Zhao, Binbin; He, Lingfeng

2018-04-01

Unmanned Aerial Vehicle (UAV) based remote sensing can be used to make three-dimensions (3D) mapping with great flexibility, besides the ability to provide high resolution images. In this paper we propose a quick-change detection method on UAV images by combining altitude from Digital Surface Model (DSM) and texture analysis from images. Cases of UAV images with and without georeferencing are both considered. Research results show that the accuracy of change detection can be enhanced with georeferencing procedure, and the accuracy and precision of change detection on UAV images which are collected both vertically and obliquely but without georeferencing also have a good performance.

Dynamic Approximate Entropy Electroanatomic Maps Detect Rotors in a Simulated Atrial Fibrillation Model

PubMed Central

Ugarte, Juan P.; Orozco-Duque, Andrés; Tobón, Catalina; Kremen, Vaclav; Novak, Daniel; Saiz, Javier; Oesterlein, Tobias; Schmitt, Clauss; Luik, Armin; Bustamante, John

2014-01-01

There is evidence that rotors could be drivers that maintain atrial fibrillation. Complex fractionated atrial electrograms have been located in rotor tip areas. However, the concept of electrogram fractionation, defined using time intervals, is still controversial as a tool for locating target sites for ablation. We hypothesize that the fractionation phenomenon is better described using non-linear dynamic measures, such as approximate entropy, and that this tool could be used for locating the rotor tip. The aim of this work has been to determine the relationship between approximate entropy and fractionated electrograms, and to develop a new tool for rotor mapping based on fractionation levels. Two episodes of chronic atrial fibrillation were simulated in a 3D human atrial model, in which rotors were observed. Dynamic approximate entropy maps were calculated using unipolar electrogram signals generated over the whole surface of the 3D atrial model. In addition, we optimized the approximate entropy calculation using two real multi-center databases of fractionated electrogram signals, labeled in 4 levels of fractionation. We found that the values of approximate entropy and the levels of fractionation are positively correlated. This allows the dynamic approximate entropy maps to localize the tips from stable and meandering rotors. Furthermore, we assessed the optimized approximate entropy using bipolar electrograms generated over a vicinity enclosing a rotor, achieving rotor detection. Our results suggest that high approximate entropy values are able to detect a high level of fractionation and to locate rotor tips in simulated atrial fibrillation episodes. We suggest that dynamic approximate entropy maps could become a tool for atrial fibrillation rotor mapping. PMID:25489858

Decoding fMRI events in sensorimotor motor network using sparse paradigm free mapping and activation likelihood estimates.

PubMed

Tan, Francisca M; Caballero-Gaudes, César; Mullinger, Karen J; Cho, Siu-Yeung; Zhang, Yaping; Dryden, Ian L; Francis, Susan T; Gowland, Penny A

2017-11-01

Most functional MRI (fMRI) studies map task-driven brain activity using a block or event-related paradigm. Sparse paradigm free mapping (SPFM) can detect the onset and spatial distribution of BOLD events in the brain without prior timing information, but relating the detected events to brain function remains a challenge. In this study, we developed a decoding method for SPFM using a coordinate-based meta-analysis method of activation likelihood estimation (ALE). We defined meta-maps of statistically significant ALE values that correspond to types of events and calculated a summation overlap between the normalized meta-maps and SPFM maps. As a proof of concept, this framework was applied to relate SPFM-detected events in the sensorimotor network (SMN) to six motor functions (left/right fingers, left/right toes, swallowing, and eye blinks). We validated the framework using simultaneous electromyography (EMG)-fMRI experiments and motor tasks with short and long duration, and random interstimulus interval. The decoding scores were considerably lower for eye movements relative to other movement types tested. The average successful rate for short and long motor events were 77 ± 13% and 74 ± 16%, respectively, excluding eye movements. We found good agreement between the decoding results and EMG for most events and subjects, with a range in sensitivity between 55% and 100%, excluding eye movements. The proposed method was then used to classify the movement types of spontaneous single-trial events in the SMN during resting state, which produced an average successful rate of 22 ± 12%. Finally, this article discusses methodological implications and improvements to increase the decoding performance. Hum Brain Mapp 38:5778-5794, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Decoding fMRI events in Sensorimotor Motor Network using Sparse Paradigm Free Mapping and Activation Likelihood Estimates

PubMed Central

Tan, Francisca M.; Caballero-Gaudes, César; Mullinger, Karen J.; Cho, Siu-Yeung; Zhang, Yaping; Dryden, Ian L.; Francis, Susan T.; Gowland, Penny A.

2017-01-01

Most fMRI studies map task-driven brain activity using a block or event-related paradigm. Sparse Paradigm Free Mapping (SPFM) can detect the onset and spatial distribution of BOLD events in the brain without prior timing information; but relating the detected events to brain function remains a challenge. In this study, we developed a decoding method for SPFM using a coordinate-based meta-analysis method of Activation Likelihood Estimation (ALE). We defined meta-maps of statistically significant ALE values that correspond to types of events and calculated a summation overlap between the normalized meta-maps and SPFM maps. As a proof of concept, this framework was applied to relate SPFM-detected events in the Sensorimotor Network (SMN) to six motor function (left/right fingers, left/right toes, swallowing and eye blinks). We validated the framework using simultaneous Electromyography-fMRI experiments and motor tasks with short and long duration, and random inter-stimulus interval. The decoding scores were considerably lower for eye movements relative to other movement types tested. The average successful rate for short and long motor events was 77 ± 13% and 74 ± 16% respectively, excluding eye movements. We found good agreement between the decoding results and EMG for most events and subjects, with a range in sensitivity between 55 and 100%, excluding eye movements. The proposed method was then used to classify the movement types of spontaneous single-trial events in the SMN during resting state, which produced an average successful rate of 22 ± 12%. Finally, this paper discusses methodological implications and improvements to increase the decoding performance. PMID:28815863

Genetic mapping of QTL for the sizes of eight consecutive leaves below the tassel in maize (Zea mays L.).

PubMed

Yang, Cong; Tang, Dengguo; Qu, Jingtao; Zhang, Ling; Zhang, Lei; Chen, Zhengjie; Liu, Jian

2016-11-01

A set of RIL population was used to detect QTL associated with the sizes of eight consecutive leaves, across different environments, and ten QTL clusters were identified as main QTLs. One of the important parameters of the maize leaf architecture that affects light penetration into the canopy, leaf size, has long attracted breeders' attention for optimizing the plant type of maize and for maximizing the grain yield (GY). In this study, we used 253 RIL lines derived from a cross between B73 and SICAU1212 to investigate the leaf widths (LWs), leaf lengths (LLs), and leaf areas (LAs) of eight consecutive leaves of maize below the tassel and GY across different environments and to identify quantitative traits loci (QTLs) controlling the above-mentioned traits, using inclusive interval mapping for single-environment analysis plus a mixed-model-based composite interval mapping for joint analysis. A total of 171 and 159 putative QTLs were detected through these two mapping methods, respectively. Single-environment mapping revealed that 39 stable QTLs explained more than 10 % of the phenotypic variance, and 35 of the 39 QTLs were also detected by joint analysis. In addition, joint analysis showed that nine of the 159 QTLs exhibited significant QTL × environment interaction and 15 significant epistatic interactions were identified. Approximately 47.17 % of the QTLs for leaf architectural traits in joint analysis were concentrated in ten main chromosomal regions, namely, bins 1.07, 2.02, 3.06, 4.09, 5.01, 5.02, 5.03-5.04, 5.07, 6.07, and 8.05. This study should provide a basis for further fine-mapping of these main genetic regions and improvement of maize leaf architecture.

Oil Spill Detection along the Gulf of Mexico Coastline based on Airborne Imaging Spectrometer Data

NASA Astrophysics Data System (ADS)

Arslan, M. D.; Filippi, A. M.; Guneralp, I.

2013-12-01

The Deepwater Horizon oil spill in the Gulf of Mexico between April and July 2010 demonstrated the importance of synoptic oil-spill monitoring in coastal environments via remote-sensing methods. This study focuses on terrestrial oil-spill detection and thickness estimation based on hyperspectral images acquired along the coastline of the Gulf of Mexico. We use AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) imaging spectrometer data collected over Bay Jimmy and Wilkinson Bay within Barataria Bay, Louisiana, USA during September 2010. We also employ field-based observations of the degree of oil accumulation along the coastline, as well as in situ measurements from the literature. As part of our proposed spectroscopic approach, we operate on atmospherically- and geometrically-corrected hyperspectral AVIRIS data to extract image-derived endmembers via Minimum Noise Fraction transform, Pixel Purity Index-generation, and n-dimensional visualization. Extracted endmembers are then used as input to endmember-mapping algorithms to yield fractional-abundance images and crisp classification images. We also employ Multiple Endmember Spectral Mixture Analysis (MESMA) for oil detection and mapping in order to enable the number and types of endmembers to vary on a per-pixel basis, in contast to simple Spectral Mixture Analysis (SMA). MESMA thus better allows accounting for spectral variabiltiy of oil (e.g., due to varying oil thicknesses, states of degradation, and the presence of different oil types, etc.) and other materials, including soils and salt marsh vegetation of varying types, which may or may not be affected by the oil spill. A decision-tree approach is also utilized for comparison. Classification results do indicate that MESMA provides advantageous capabilities for mapping several oil-thickness classes for affected vegetation and soils along the Gulf of Mexico coastline, relative to the conventional approaches tested. Oil thickness-mapping results from MESMA and the decision tree demonstrate that such products can be accurately generated in complex coastal enviroments.

A nation-wide system for landslide mapping and risk management in Italy: The second Not-ordinary Plan of Environmental Remote Sensing

NASA Astrophysics Data System (ADS)

Di Martire, D.; Paci, M.; Confuorto, P.; Costabile, S.; Guastaferro, F.; Verta, A.; Calcaterra, D.

2017-12-01

Landslides are frequent events that may cause human casualties and injuries as well as damage to urban and man-made structures, with extensive loss of economic resources. For this reason, landslide mapping is a primary tool for hazard and risk assessment. Italian Ministry of Environment, thanks to great availability and functionality of Synthetic Aperture Radar (SAR) data promoted the Not-ordinary Plan of Environmental Remote Sensing (Piano Straordinario di Telerilevamento Ambientale, PST-A in Italian) in 2008, as to constitute a national database of active or potential instability phenomena affecting the Italian territory, based on the exploitation of interferometric products (ERS and ENVISAT). In this paper, the PST-A-3 is described. A procedure based on the integration of engineering-geological approaches and SAR interferometry data belonging to COSMO-SkyMed constellation (100 frames 40 × 40 km) has been here implemented over 7,400 km2 of the Italian territory. First, landslides have been mapped by field geologists, defining type and state of activity. Simultaneously to field surveys, remote sensing data have been analyzed as to detect areas with considerable displacement registered by the satellite. Both products have been overlaid, also quantifying the coincidence between the events reported according to the two detection methodologies and subtracting those landslide not recordable by the satellite, finally obtaining an updated landslide inventory map with 4,522 newly detected phenomena. Therefore, PST-A-3 proves to be a valuable system for local authorities, in order to provide a contribution to risk management but also for the forecasting of landslide events, as testified by two case studies selected. Thanks to the PST-A experience, the use of such strategy to other countries could represent a valid contribution to land management at worldwide scale.

Identification of stable QTLs causing chalk in rice grains in nine environments.

PubMed

Zhao, Xiangqian; Daygon, Venea D; McNally, Kenneth L; Hamilton, Ruaraidh Sackville; Xie, Fangming; Reinke, Russell F; Fitzgerald, Melissa A

2016-01-01

A novel QTL cluster for chalkiness on Chr04 was identified using single environment analysis and joint mapping across 9 environments in Asia and South American. QTL NILs showed that each had a significant effect on chalk. Chalk in rice grains leads to a significant loss in the proportion of marketable grains in a harvested crop, leading to a significant financial loss to rice farmers and traders. To identify the genetic basis of chalkiness, two sets of recombinant inbred lines (RILs) derived from reciprocal crosses between Lemont and Teqing were used to find stable QTLs for chalkiness. The RILs were grown in seven locations in Asia and Latin American and in two controlled environments in phytotrons. A total of 32 (21) and 46 (22) QTLs for DEC and PGWC, most of them explaining more than 10% of phenotypic variation, were detected based on single environment analysis in T/L (L/T) population, respectively. Seven (2) and 7 (3) QTLs for DEC and PGWC were identified in the T/L (L/T) population using joined analysis across all environments, respectively. Six major QTLs clusters were found on five chromosomes: 1, 2, 4, 5 and 11. The biggest cluster at id4007289-RM252 on Chr04 was a novelty, including 16 and 4 QTLs detected by single environment analysis and joint mapping across all environments, respectively. The detected digenic epistatic QTLs explained up to 13% of phenotypic variation, suggesting that epistasis play an important role in the genetic control of chalkiness in rice. QTL NILs showed that each QTL cluster had a significant effect on chalk. These chromosomal regions could be targets for MAS, fine mapping and map-based cloning for low chalkiness breeding.

Real-time 3D change detection of IEDs

NASA Astrophysics Data System (ADS)

Wathen, Mitch; Link, Norah; Iles, Peter; Jinkerson, John; Mrstik, Paul; Kusevic, Kresimir; Kovats, David

2012-06-01

Road-side bombs are a real and continuing threat to soldiers in theater. CAE USA recently developed a prototype Volume based Intelligence Surveillance Reconnaissance (VISR) sensor platform for IED detection. This vehicle-mounted, prototype sensor system uses a high data rate LiDAR (1.33 million range measurements per second) to generate a 3D mapping of roadways. The mapped data is used as a reference to generate real-time change detection on future trips on the same roadways. The prototype VISR system is briefly described. The focus of this paper is the methodology used to process the 3D LiDAR data, in real-time, to detect small changes on and near the roadway ahead of a vehicle traveling at moderate speeds with sufficient warning to stop the vehicle at a safe distance from the threat. The system relies on accurate navigation equipment to geo-reference the reference run and the change-detection run. Since it was recognized early in the project that detection of small changes could not be achieved with accurate navigation solutions alone, a scene alignment algorithm was developed to register the reference run with the change detection run prior to applying the change detection algorithm. Good success was achieved in simultaneous real time processing of scene alignment plus change detection.

Fast Drawing of Traffic Sign Using Mobile Mapping System

NASA Astrophysics Data System (ADS)

Yao, Q.; Tan, B.; Huang, Y.

2016-06-01

Traffic sign provides road users with the specified instruction and information to enhance traffic safety. Automatic detection of traffic sign is important for navigation, autonomous driving, transportation asset management, etc. With the advance of laser and imaging sensors, Mobile Mapping System (MMS) becomes widely used in transportation agencies to map the transportation infrastructure. Although many algorithms of traffic sign detection are developed in the literature, they are still a tradeoff between the detection speed and accuracy, especially for the large-scale mobile mapping of both the rural and urban roads. This paper is motivated to efficiently survey traffic signs while mapping the road network and the roadside landscape. Inspired by the manual delineation of traffic sign, a drawing strategy is proposed to quickly approximate the boundary of traffic sign. Both the shape and color prior of the traffic sign are simultaneously involved during the drawing process. The most common speed-limit sign circle and the statistic color model of traffic sign are studied in this paper. Anchor points of traffic sign edge are located with the local maxima of color and gradient difference. Starting with the anchor points, contour of traffic sign is drawn smartly along the most significant direction of color and intensity consistency. The drawing process is also constrained by the curvature feature of the traffic sign circle. The drawing of linear growth is discarded immediately if it fails to form an arc over some steps. The Kalman filter principle is adopted to predict the temporal context of traffic sign. Based on the estimated point,we can predict and double check the traffic sign in consecutive frames.The event probability of having a traffic sign over the consecutive observations is compared with the null hypothesis of no perceptible traffic sign. The temporally salient traffic sign is then detected statistically and automatically as the rare event of having a traffic sign.The proposed algorithm is tested with a diverse set of images that are taken inWuhan, China with theMMS ofWuhan University. Experimental results demonstrate that the proposed algorithm can detect traffic signs at the rate of over 80% in around 10 milliseconds. It is promising for the large-scale traffic sign survey and change detection using the mobile mapping system.

Data Processing and Quality Evaluation of a Boat-Based Mobile Laser Scanning System

PubMed Central

Vaaja, Matti; Kukko, Antero; Kaartinen, Harri; Kurkela, Matti; Kasvi, Elina; Flener, Claude; Hyyppä, Hannu; Hyyppä, Juha; Järvelä, Juha; Alho, Petteri

2013-01-01

Mobile mapping systems (MMSs) are used for mapping topographic and urban features which are difficult and time consuming to measure with other instruments. The benefits of MMSs include efficient data collection and versatile usability. This paper investigates the data processing steps and quality of a boat-based mobile mapping system (BoMMS) data for generating terrain and vegetation points in a river environment. Our aim in data processing was to filter noise points, detect shorelines as well as points below water surface and conduct ground point classification. Previous studies of BoMMS have investigated elevation accuracies and usability in detection of fluvial erosion and deposition areas. The new findings concerning BoMMS data are that the improved data processing approach allows for identification of multipath reflections and shoreline delineation. We demonstrate the possibility to measure bathymetry data in shallow (0–1 m) and clear water. Furthermore, we evaluate for the first time the accuracy of the BoMMS ground points classification compared to manually classified data. We also demonstrate the spatial variations of the ground point density and assess elevation and vertical accuracies of the BoMMS data. PMID:24048340

Data processing and quality evaluation of a boat-based mobile laser scanning system.

PubMed

Vaaja, Matti; Kukko, Antero; Kaartinen, Harri; Kurkela, Matti; Kasvi, Elina; Flener, Claude; Hyyppä, Hannu; Hyyppä, Juha; Järvelä, Juha; Alho, Petteri

2013-09-17

Mobile mapping systems (MMSs) are used for mapping topographic and urban features which are difficult and time consuming to measure with other instruments. The benefits of MMSs include efficient data collection and versatile usability. This paper investigates the data processing steps and quality of a boat-based mobile mapping system (BoMMS) data for generating terrain and vegetation points in a river environment. Our aim in data processing was to filter noise points, detect shorelines as well as points below water surface and conduct ground point classification. Previous studies of BoMMS have investigated elevation accuracies and usability in detection of fluvial erosion and deposition areas. The new findings concerning BoMMS data are that the improved data processing approach allows for identification of multipath reflections and shoreline delineation. We demonstrate the possibility to measure bathymetry data in shallow (0-1 m) and clear water. Furthermore, we evaluate for the first time the accuracy of the BoMMS ground points classification compared to manually classified data. We also demonstrate the spatial variations of the ground point density and assess elevation and vertical accuracies of the BoMMS data.

Partial Deconvolution with Inaccurate Blur Kernel.

PubMed

Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei

2017-10-17

Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.

Probing Neutrino Hierarchy and Chirality via Wakes.

PubMed

Zhu, Hong-Ming; Pen, Ue-Li; Chen, Xuelei; Inman, Derek

2016-04-08

The relic neutrinos are expected to acquire a bulk relative velocity with respect to the dark matter at low redshifts, and neutrino wakes are expected to develop downstream of the dark matter halos. We propose a method of measuring the neutrino mass based on this mechanism. This neutrino wake will cause a dipole distortion of the galaxy-galaxy lensing pattern. This effect could be detected by combining upcoming lensing surveys with a low redshift galaxy survey or a 21 cm intensity mapping survey, which can map the neutrino flow field. The data obtained with LSST and Euclid should enable us to make a positive detection if the three neutrino masses are quasidegenerate with each neutrino mass of ∼0.1  eV, and a future high precision 21 cm lensing survey would allow the normal hierarchy and inverted hierarchy cases to be distinguished, and even the right-handed Dirac neutrinos may be detectable.

Varying face occlusion detection and iterative recovery for face recognition

NASA Astrophysics Data System (ADS)

Wang, Meng; Hu, Zhengping; Sun, Zhe; Zhao, Shuhuan; Sun, Mei

2017-05-01

In most sparse representation methods for face recognition (FR), occlusion problems were usually solved via removing the occlusion part of both query samples and training samples to perform the recognition process. This practice ignores the global feature of facial image and may lead to unsatisfactory results due to the limitation of local features. Considering the aforementioned drawback, we propose a method called varying occlusion detection and iterative recovery for FR. The main contributions of our method are as follows: (1) to detect an accurate occlusion area of facial images, an image processing and intersection-based clustering combination method is used for occlusion FR; (2) according to an accurate occlusion map, the new integrated facial images are recovered iteratively and put into a recognition process; and (3) the effectiveness on recognition accuracy of our method is verified by comparing it with three typical occlusion map detection methods. Experiments show that the proposed method has a highly accurate detection and recovery performance and that it outperforms several similar state-of-the-art methods against partial contiguous occlusion.

Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text.

PubMed

Park, Albert; Hartzler, Andrea L; Huh, Jina; McDonald, David W; Pratt, Wanda

2015-08-31

The prevalence and value of patient-generated health text are increasing, but processing such text remains problematic. Although existing biomedical natural language processing (NLP) tools are appealing, most were developed to process clinician- or researcher-generated text, such as clinical notes or journal articles. In addition to being constructed for different types of text, other challenges of using existing NLP include constantly changing technologies, source vocabularies, and characteristics of text. These continuously evolving challenges warrant the need for applying low-cost systematic assessment. However, the primarily accepted evaluation method in NLP, manual annotation, requires tremendous effort and time. The primary objective of this study is to explore an alternative approach-using low-cost, automated methods to detect failures (eg, incorrect boundaries, missed terms, mismapped concepts) when processing patient-generated text with existing biomedical NLP tools. We first characterize common failures that NLP tools can make in processing online community text. We then demonstrate the feasibility of our automated approach in detecting these common failures using one of the most popular biomedical NLP tools, MetaMap. Using 9657 posts from an online cancer community, we explored our automated failure detection approach in two steps: (1) to characterize the failure types, we first manually reviewed MetaMap's commonly occurring failures, grouped the inaccurate mappings into failure types, and then identified causes of the failures through iterative rounds of manual review using open coding, and (2) to automatically detect these failure types, we then explored combinations of existing NLP techniques and dictionary-based matching for each failure cause. Finally, we manually evaluated the automatically detected failures. From our manual review, we characterized three types of failure: (1) boundary failures, (2) missed term failures, and (3) word ambiguity failures. Within these three failure types, we discovered 12 causes of inaccurate mappings of concepts. We used automated methods to detect almost half of 383,572 MetaMap's mappings as problematic. Word sense ambiguity failure was the most widely occurring, comprising 82.22% of failures. Boundary failure was the second most frequent, amounting to 15.90% of failures, while missed term failures were the least common, making up 1.88% of failures. The automated failure detection achieved precision, recall, accuracy, and F1 score of 83.00%, 92.57%, 88.17%, and 87.52%, respectively. We illustrate the challenges of processing patient-generated online health community text and characterize failures of NLP tools on this patient-generated health text, demonstrating the feasibility of our low-cost approach to automatically detect those failures. Our approach shows the potential for scalable and effective solutions to automatically assess the constantly evolving NLP tools and source vocabularies to process patient-generated text.

A matched filter approach for blind joint detection of galaxy clusters in X-ray and SZ surveys

NASA Astrophysics Data System (ADS)

Tarrío, P.; Melin, J.-B.; Arnaud, M.

2018-06-01

The combination of X-ray and Sunyaev-Zeldovich (SZ) observations can potentially improve the cluster detection efficiency, when compared to using only one of these probes, since both probe the same medium, the hot ionized gas of the intra-cluster medium. We present a method based on matched multifrequency filters (MMF) for detecting galaxy clusters from SZ and X-ray surveys. This method builds on a previously proposed joint X-ray-SZ extraction method and allows the blind detection of clusters, that is finding new clusters without knowing their position, size, or redshift, by searching on SZ and X-ray maps simultaneously. The proposed method is tested using data from the ROSAT all-sky survey and from the Planck survey. The evaluation is done by comparison with existing cluster catalogues in the area of the sky covered by the deep SPT survey. Thanks to the addition of the X-ray information, the joint detection method is able to achieve simultaneously better purity, better detection efficiency, and better position accuracy than its predecessor Planck MMF, which is based on SZ maps alone. For a purity of 85%, the X-ray-SZ method detects 141 confirmed clusters in the SPT region; to detect the same number of confirmed clusters with Planck MMF, we would need to decrease its purity to 70%. We provide a catalogue of 225 sources selected by the proposed method in the SPT footprint, with masses ranging between 0.7 and 14.5 ×1014 M⊙ and redshifts between 0.01 and 1.2.

Wide-Field Lensing Mass Maps from Dark Energy Survey Science Verification Data

DOE PAGES

Chang, C.

2015-07-29

We present a mass map reconstructed from weak gravitational lensing shear measurements over 139 deg 2 from the Dark Energy Survey science verification data. The mass map probes both luminous and dark matter, thus providing a tool for studying cosmology. We also find good agreement between the mass map and the distribution of massive galaxy clusters identified using a red-sequence cluster finder. Potential candidates for superclusters and voids are identified using these maps. We measure the cross-correlation between the mass map and a magnitude-limited foreground galaxy sample and find a detection at the 6.8σ level with 20 arc min smoothing.more » These measurements are consistent with simulated galaxy catalogs based on N-body simulations from a cold dark matter model with a cosmological constant. This suggests low systematics uncertainties in the map. Finally, we summarize our key findings in this Letter; the detailed methodology and tests for systematics are presented in a companion paper.« less

Wide-Field Lensing Mass Maps from Dark Energy Survey Science Verification Data.

PubMed

Chang, C; Vikram, V; Jain, B; Bacon, D; Amara, A; Becker, M R; Bernstein, G; Bonnett, C; Bridle, S; Brout, D; Busha, M; Frieman, J; Gaztanaga, E; Hartley, W; Jarvis, M; Kacprzak, T; Kovács, A; Lahav, O; Lin, H; Melchior, P; Peiris, H; Rozo, E; Rykoff, E; Sánchez, C; Sheldon, E; Troxel, M A; Wechsler, R; Zuntz, J; Abbott, T; Abdalla, F B; Allam, S; Annis, J; Bauer, A H; Benoit-Lévy, A; Brooks, D; Buckley-Geer, E; Burke, D L; Capozzi, D; Carnero Rosell, A; Carrasco Kind, M; Castander, F J; Crocce, M; D'Andrea, C B; Desai, S; Diehl, H T; Dietrich, J P; Doel, P; Eifler, T F; Evrard, A E; Fausti Neto, A; Flaugher, B; Fosalba, P; Gruen, D; Gruendl, R A; Gutierrez, G; Honscheid, K; James, D; Kent, S; Kuehn, K; Kuropatkin, N; Maia, M A G; March, M; Martini, P; Merritt, K W; Miller, C J; Miquel, R; Neilsen, E; Nichol, R C; Ogando, R; Plazas, A A; Romer, A K; Roodman, A; Sako, M; Sanchez, E; Sevilla, I; Smith, R C; Soares-Santos, M; Sobreira, F; Suchyta, E; Tarle, G; Thaler, J; Thomas, D; Tucker, D; Walker, A R

2015-07-31

We present a mass map reconstructed from weak gravitational lensing shear measurements over 139  deg2 from the Dark Energy Survey science verification data. The mass map probes both luminous and dark matter, thus providing a tool for studying cosmology. We find good agreement between the mass map and the distribution of massive galaxy clusters identified using a red-sequence cluster finder. Potential candidates for superclusters and voids are identified using these maps. We measure the cross-correlation between the mass map and a magnitude-limited foreground galaxy sample and find a detection at the 6.8σ level with 20 arc min smoothing. These measurements are consistent with simulated galaxy catalogs based on N-body simulations from a cold dark matter model with a cosmological constant. This suggests low systematics uncertainties in the map. We summarize our key findings in this Letter; the detailed methodology and tests for systematics are presented in a companion paper.

Automatic Detection of Lung and Liver Lesions in 3-D Positron Emission Tomography Images: A Pilot Study

NASA Astrophysics Data System (ADS)

Lartizien, Carole; Marache-Francisco, Simon; Prost, Rémy

2012-02-01

Positron emission tomography (PET) using fluorine-18 deoxyglucose (18F-FDG) has become an increasingly recommended tool in clinical whole-body oncology imaging for the detection, diagnosis, and follow-up of many cancers. One way to improve the diagnostic utility of PET oncology imaging is to assist physicians facing difficult cases of residual or low-contrast lesions. This study aimed at evaluating different schemes of computer-aided detection (CADe) systems for the guided detection and localization of small and low-contrast lesions in PET. These systems are based on two supervised classifiers, linear discriminant analysis (LDA) and the nonlinear support vector machine (SVM). The image feature sets that serve as input data consisted of the coefficients of an undecimated wavelet transform. An optimization study was conducted to select the best combination of parameters for both the SVM and the LDA. Different false-positive reduction (FPR) methods were evaluated to reduce the number of false-positive detections per image (FPI). This includes the removal of small detected clusters and the combination of the LDA and SVM detection maps. The different CAD schemes were trained and evaluated based on a simulated whole-body PET image database containing 250 abnormal cases with 1230 lesions and 250 normal cases with no lesion. The detection performance was measured on a separate series of 25 testing images with 131 lesions. The combination of the LDA and SVM score maps was shown to produce very encouraging detection performance for both the lung lesions, with 91% sensitivity and 18 FPIs, and the liver lesions, with 94% sensitivity and 10 FPIs. Comparison with human performance indicated that the different CAD schemes significantly outperformed human detection sensitivities, especially regarding the low-contrast lesions.

Sci—Thur AM: YIS - 08: Constructing an Attenuation map for a PET/MR Breast coil

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

Patrick, John C.; Imaging, Lawson Health Research Institute, Knoxville, TN; London Regional Cancer Program, Knoxville, TN

2014-08-15

In 2013, around 23000 Canadian women and 200 Canadian men were diagnosed with breast cancer. An estimated 5100 women and 55 men died from the disease. Using the sensitivity of MRI with the selectivity of PET, PET/MRI combines anatomical and functional information within the same scan and could help with early detection in high-risk patients. MRI requires radiofrequency coils for transmitting energy and receiving signal but the breast coil attenuates PET signal. To correct for this PET attenuation, a 3-dimensional map of linear attenuation coefficients (μ-map) of the breast coil must be created and incorporated into the PET reconstruction process.more » Several approaches have been proposed for building hardware μ-maps, some of which include the use of conventional kVCT and Dual energy CT. These methods can produce high resolution images based on the electron densities of materials that can be converted into μ-maps. However, imaging hardware containing metal components with photons in the kV range is susceptible to metal artifacts. These artifacts can compromise the accuracy of the resulting μ-map and PET reconstruction; therefore high-Z components should be removed. We propose a method for calculating μ-maps without removing coil components, based on megavoltage (MV) imaging with a linear accelerator that has been detuned for imaging at 1.0MeV. Containers of known geometry with F18 were placed in the breast coil for imaging. A comparison between reconstructions based on the different μ-map construction methods was made. PET reconstructions with our method show a maximum of 6% difference over the existing kVCT-based reconstructions.« less

USGS Tweet Earthquake Dispatch (@USGSted): Using Twitter for Earthquake Detection and Characterization

NASA Astrophysics Data System (ADS)

Liu, S. B.; Bouchard, B.; Bowden, D. C.; Guy, M.; Earle, P.

2012-12-01

The U.S. Geological Survey (USGS) is investigating how online social networking services like Twitter—a microblogging service for sending and reading public text-based messages of up to 140 characters—can augment USGS earthquake response products and the delivery of hazard information. The USGS Tweet Earthquake Dispatch (TED) system is using Twitter not only to broadcast seismically-verified earthquake alerts via the @USGSted and @USGSbigquakes Twitter accounts, but also to rapidly detect widely felt seismic events through a real-time detection system. The detector algorithm scans for significant increases in tweets containing the word "earthquake" or its equivalent in other languages and sends internal alerts with the detection time, tweet text, and the location of the city where most of the tweets originated. It has been running in real-time for 7 months and finds, on average, two or three felt events per day with a false detection rate of less than 10%. The detections have reasonable coverage of populated areas globally. The number of detections is small compared to the number of earthquakes detected seismically, and only a rough location and qualitative assessment of shaking can be determined based on Tweet data alone. However, the Twitter detections are generally caused by widely felt events that are of more immediate interest than those with no human impact. The main benefit of the tweet-based detections is speed, with most detections occurring between 19 seconds and 2 minutes from the origin time. This is considerably faster than seismic detections in poorly instrumented regions of the world. Going beyond the initial detection, the USGS is developing data mining techniques to continuously archive and analyze relevant tweets for additional details about the detected events. The information generated about an event is displayed on a web-based map designed using HTML5 for the mobile environment, which can be valuable when the user is not able to access a desktop computer at the time of the detections. The continuously updating map displays geolocated tweets arriving after the detection and plots epicenters of recent earthquakes. When available, seismograms from nearby stations are displayed as an additional form of verification. A time series of tweets-per-minute is also shown to illustrate the volume of tweets being generated for the detected event. Future additions are being investigated to provide a more in-depth characterization of the seismic events based on an analysis of tweet text and content from other social media sources.

Global Detection of Live Virtual Machine Migration Based on Cellular Neural Networks

PubMed Central

Xie, Kang; Yang, Yixian; Zhang, Ling; Jing, Maohua; Xin, Yang; Li, Zhongxian

2014-01-01

In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation allowing the VM migration detection to be performed better. PMID:24959631

Global detection of live virtual machine migration based on cellular neural networks.

PubMed

Xie, Kang; Yang, Yixian; Zhang, Ling; Jing, Maohua; Xin, Yang; Li, Zhongxian

2014-01-01

In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation allowing the VM migration detection to be performed better.

Correlated ion and neutral time of flight technique combined with velocity map imaging: Quantitative measurements for dissociation processes in excited molecular nano-systems

NASA Astrophysics Data System (ADS)

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

2018-01-01

The combination of the Dispositif d'Irradiation d'Agrégats Moléculaire with the correlated ion and neutral time of flight-velocity map imaging technique provides a new way to explore processes occurring subsequent to the excitation of charged nano-systems. The present contribution describes in detail the methods developed for the quantitative measurement of branching ratios and cross sections for collision-induced dissociation processes of water cluster nano-systems. These methods are based on measurements of the detection efficiency of neutral fragments produced in these dissociation reactions. Moreover, measured detection efficiencies are used here to extract the number of neutral fragments produced for a given charged fragment.

Attempting to detect and record brushland in the northeastern United States using MSS data - Schoharie County, N.Y., as a case study

NASA Technical Reports Server (NTRS)

Baumann, Paul R.

1990-01-01

Before county and local governments will utilize satellite data extensively for landcover inventories, digital image processing techniques must be developed to identify transitional land-use conditions and create large-scale, readable land-cover maps. This study examines a satellite-based land-cover inventory done for Schoharie County, New York and reviews the problems encountered in identifying and mapping brushland - a significant transitional land use - within the county and region. Brushland throughout the Northeast represents a barometer for measuring the shift away from agricultural land use to second-home property. Detecting and locating brushland on a regular basis can greatly assist county and local government officials in planning and managing a county's future.

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

Treesearch

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...

Detection of Mycobacterium avium subspecies paratuberculosis in tie-stall dairy herds using a standardized environmental sampling technique and targeted pooled samples.

PubMed

Arango-Sabogal, Juan C; Côté, Geneviève; Paré, Julie; Labrecque, Olivia; Roy, Jean-Philippe; Buczinski, Sébastien; Doré, Elizabeth; Fairbrother, Julie H; Bissonnette, Nathalie; Wellemans, Vincent; Fecteau, Gilles

2016-07-01

Mycobacterium avium ssp. paratuberculosis (MAP) is the etiologic agent of Johne's disease, a chronic contagious enteritis of ruminants that causes major economic losses. Several studies, most involving large free-stall herds, have found environmental sampling to be a suitable method for detecting MAP-infected herds. In eastern Canada, where small tie-stall herds are predominant, certain conditions and management practices may influence the survival and transmission of MAP and recovery (isolation). Our objective was to estimate the performance of a standardized environmental and targeted pooled sampling technique for the detection of MAP-infected tie-stall dairy herds. Twenty-four farms (19 MAP-infected and 5 non-infected) were enrolled, but only 20 were visited twice in the same year, to collect 7 environmental samples and 2 pooled samples (sick cows and cows with poor body condition). Concurrent individual sampling of all adult cows in the herds was also carried out. Isolation of MAP was achieved using the MGIT Para TB culture media and the BACTEC 960 detection system. Overall, MAP was isolated in 7% of the environmental cultures. The sensitivity of the environmental culture was 44% [95% confidence interval (CI): 20% to 70%] when combining results from 2 different herd visits and 32% (95% CI: 13% to 57%) when results from only 1 random herd visit were used. The best sampling strategy was to combine samples from the manure pit, gutter, sick cows, and cows with poor body condition. The standardized environmental sampling technique and the targeted pooled samples presented in this study is an alternative sampling strategy to costly individual cultures for detecting MAP-infected tie-stall dairies. Repeated samplings may improve the detection of MAP-infected herds.

Field-based Information Technology in Geology Education: GeoPads

NASA Astrophysics Data System (ADS)

Knoop, P. A.; van der Pluijm, B.

2004-12-01

During the past two summers, we have successfully incorporated a field-based information technology component into our senior-level, field geology course (GS-440) at the University of Michigan's Camp Davis Geology Field Station, near Jackson, WY. Using GeoPads -- rugged TabletPCs equipped with electronic notebook software, GIS, GPS, and wireless networking -- we have significantly enhanced our field mapping exercises and field trips. While fully retaining the traditional approaches and advantages of field instruction, GeoPads offer important benefits in the development of students' spatial reasoning skills. GeoPads enable students to record observations and directly create geologic maps in the field, using a combination of an electronic field notebook (Microsoft OneNote) tightly integrated with pen-enabled GIS software (ArcGIS-ArcMap). Specifically, this arrangement permits students to analyze and manipulate their data in multiple contexts and representations -- while still in the field -- using both traditional 2-D map views, as well as richer 3-D contexts. Such enhancements provide students with powerful exploratory tools that aid the development of spatial reasoning skills, allowing more intuitive interactions with 2-D representations of our 3-D world. Additionally, field-based GIS mapping enables better error-detection, through immediate interaction with current observations in the context of both supporting data (e.g., topographic maps, aerial photos, magnetic surveys) and students' ongoing observations. The overall field-based IT approach also provides students with experience using tools that are increasingly relevant to their future academic or professional careers.

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

USGS Publications Warehouse

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

2003-01-01

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

SNP discovery by high-throughput sequencing in soybean

PubMed Central

2010-01-01

Background With the advance of new massively parallel genotyping technologies, quantitative trait loci (QTL) fine mapping and map-based cloning become more achievable in identifying genes for important and complex traits. Development of high-density genetic markers in the QTL regions of specific mapping populations is essential for fine-mapping and map-based cloning of economically important genes. Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variation existing between any diverse genotypes that are usually used for QTL mapping studies. The massively parallel sequencing technologies (Roche GS/454, Illumina GA/Solexa, and ABI/SOLiD), have been widely applied to identify genome-wide sequence variations. However, it is still remains unclear whether sequence data at a low sequencing depth are enough to detect the variations existing in any QTL regions of interest in a crop genome, and how to prepare sequencing samples for a complex genome such as soybean. Therefore, with the aims of identifying SNP markers in a cost effective way for fine-mapping several QTL regions, and testing the validation rate of the putative SNPs predicted with Solexa short sequence reads at a low sequencing depth, we evaluated a pooled DNA fragment reduced representation library and SNP detection methods applied to short read sequences generated by Solexa high-throughput sequencing technology. Results A total of 39,022 putative SNPs were identified by the Illumina/Solexa sequencing system using a reduced representation DNA library of two parental lines of a mapping population. The validation rates of these putative SNPs predicted with low and high stringency were 72% and 85%, respectively. One hundred sixty four SNP markers resulted from the validation of putative SNPs and have been selectively chosen to target a known QTL, thereby increasing the marker density of the targeted region to one marker per 42 K bp. Conclusions We have demonstrated how to quickly identify large numbers of SNPs for fine mapping of QTL regions by applying massively parallel sequencing combined with genome complexity reduction techniques. This SNP discovery approach is more efficient for targeting multiple QTL regions in a same genetic population, which can be applied to other crops. PMID:20701770

Computer-aided teniae coli detection using height maps from computed tomographic colonography images

NASA Astrophysics Data System (ADS)

Wei, Zhuoshi; Yao, Jianhua; Wang, Shijun; Summers, Ronald M.

2011-03-01

Computed tomographic colonography (CTC) is a minimally invasive technique for colonic polyps and cancer screening. Teniae coli are three bands of longitudinal smooth muscle on the colon surface. They are parallel, equally distributed on the colon wall, and form a triple helix structure from the appendix to the sigmoid colon. Because of their characteristics, teniae coli are important anatomical meaningful landmarks on human colon. This paper proposes a novel method for teniae coli detection on CT colonography. We first unfold the three-dimensional (3D) colon using a reversible projection technique and compute the two-dimensional (2D) height map of the unfolded colon. The height map records the elevation of colon surface relative to the unfolding plane, where haustral folds corresponding to high elevation points and teniae to low elevation points. The teniae coli are detected on the height map and then projected back to the 3D colon. Since teniae are located where the haustral folds meet, we break down the problem by first detecting haustral folds. We apply 2D Gabor filter banks to extract fold features. The maximum response of the filter banks is then selected as the feature image. The fold centers are then identified based on piecewise thresholding on the feature image. Connecting the fold centers yields a path of the folds. Teniae coli are finally extracted as lines running between the fold paths. Experiments were carried out on 7 cases. The proposed method yielded a promising result with an average normalized RMSE of 5.66% and standard deviation of 4.79% of the circumference of the colon.

Determination of phosphate phases in sewage sludge ash-based fertilizers by Raman microspectroscopy.

PubMed

Vogel, Christian; Adam, Christian; McNaughton, Don

2013-09-01

The chemical form of phosphate phases in sewage sludge ash (SSA)-based fertilizers was determined by Raman microspectroscopy. Raman mapping with a lateral resolution of 5 × 5 μm(2) easily detected different compounds present in the fertilizers with the help of recorded reference spectra of pure substances. Quartz and aluminosilicates showed Raman bands in the range of 450-520 cm(-1). Phosphates with apatite structure and magnesium triphosphate were determined at around 960 and 980 cm(-1), respectively. Furthermore, calcium/magnesium pyrophosphates were detected in some samples.

Deep Whole-Genome Sequencing to Detect Mixed Infection of Mycobacterium tuberculosis

PubMed Central

Gan, Mingyu; Liu, Qingyun; Yang, Chongguang; Gao, Qian; Luo, Tao

2016-01-01

Mixed infection by multiple Mycobacterium tuberculosis (MTB) strains is associated with poor treatment outcome of tuberculosis (TB). Traditional genotyping methods have been used to detect mixed infections of MTB, however, their sensitivity and resolution are limited. Deep whole-genome sequencing (WGS) has been proved highly sensitive and discriminative for studying population heterogeneity of MTB. Here, we developed a phylogenetic-based method to detect MTB mixed infections using WGS data. We collected published WGS data of 782 global MTB strains from public database. We called homogeneous and heterogeneous single nucleotide variations (SNVs) of individual strains by mapping short reads to the ancestral MTB reference genome. We constructed a phylogenomic database based on 68,639 homogeneous SNVs of 652 MTB strains. Mixed infections were determined if multiple evolutionary paths were identified by mapping the SNVs of individual samples to the phylogenomic database. By simulation, our method could specifically detect mixed infections when the sequencing depth of minor strains was as low as 1× coverage, and when the genomic distance of two mixed strains was as small as 16 SNVs. By applying our methods to all 782 samples, we detected 47 mixed infections and 45 of them were caused by locally endemic strains. The results indicate that our method is highly sensitive and discriminative for identifying mixed infections from deep WGS data of MTB isolates. PMID:27391214

Development of a low cost unmanned aircraft system for atmospheric carbon dioxide leak detection

NASA Astrophysics Data System (ADS)

Mitchell, Taylor Austin

Carbon sequestration, the storage of carbon dioxide gas underground, has the potential to reduce global warming by removing a greenhouse gas from the atmosphere. These storage sites, however, must first be monitored to detect if carbon dioxide is leaking back out to the atmosphere. As an alternative to traditional large ground-based sensor networks to monitor CO2 levels for leaks, unmanned aircraft offer the potential to perform in-situ atmospheric leak detection over large areas for a fraction of the cost. This project developed a proof-of-concept sensor system to map relative carbon dioxide levels to detect potential leaks. The sensor system included a Sensair K-30 FR CO2 sensor, GPS, and altimeter connected an Arduino microcontroller which logged data to an onboard SD card. Ground tests were performed to verify and calibrate the system including wind tunnel tests to determine the optimal configuration of the system for the quickest response time (4-8 seconds based upon flowrate). Tests were then conducted over a controlled release of CO 2 in addition to over controlled rangeland fires which released carbon dioxide over a large area as would be expected from a carbon sequestration source. 3D maps of carbon dioxide were developed from the system telemetry that clearly illustrated increased CO2 levels from the fires. These tests demonstrated the system's ability to detect increased carbon dioxide concentrations in the atmosphere.

Anchoring Linkage Groups of the Rosa Genetic Map to Physical Chromosomes with Tyramide-FISH and EST-SNP Markers

PubMed Central

Kirov, Ilya; Van Laere, Katrijn; De Riek, Jan; De Keyser, Ellen; Van Roy, Nadine; Khrustaleva, Ludmila

2014-01-01

In order to anchor Rosa linkage groups to physical chromosomes, a combination of the Tyramide-FISH technology and the modern molecular marker system based on High Resolution Melting (HRM) is an efficient approach. Although, Tyramide-FISH is a very promising technique for the visualization of short DNA probes, it is very challenging for plant species with small chromosomes such as Rosa. In this study, we successfully applied the Tyramide-FISH technique for Rosa and compared different detection systems. An indirect detection system exploiting biotinylated tyramides was shown to be the most suitable technique for reliable signal detection. Three gene fragments with a size of 1100 pb–1700 bp (Phenylalanine Ammonia Lyase, Pyrroline-5-Carboxylate Synthase and Orcinol O-Methyl Transferase) have been physically mapped on chromosomes 7, 4 and 1, respectively, of Rosa wichurana. The signal frequency was between 25% and 40%. HRM markers of these 3 gene fragments were used to include the gene fragments on the existing genetic linkage map of Rosa wichurana. As a result, three linkage groups could be anchored to their physical chromosomes. The information was used to check for synteny between the Rosa chromosomes and Fragaria. PMID:24755945

Line segment confidence region-based string matching method for map conflation

NASA Astrophysics Data System (ADS)

Huh, Yong; Yang, Sungchul; Ga, Chillo; Yu, Kiyun; Shi, Wenzhong

2013-04-01

In this paper, a method to detect corresponding point pairs between polygon object pairs with a string matching method based on a confidence region model of a line segment is proposed. The optimal point edit sequence to convert the contour of a target object into that of a reference object was found by the string matching method which minimizes its total error cost, and the corresponding point pairs were derived from the edit sequence. Because a significant amount of apparent positional discrepancies between corresponding objects are caused by spatial uncertainty and their confidence region models of line segments are therefore used in the above matching process, the proposed method obtained a high F-measure for finding matching pairs. We applied this method for built-up area polygon objects in a cadastral map and a topographical map. Regardless of their different mapping and representation rules and spatial uncertainties, the proposed method with a confidence level at 0.95 showed a matching result with an F-measure of 0.894.

Processing the Bouguer anomaly map of Biga and the surrounding area by the cellular neural network: application to the southwestern Marmara region

NASA Astrophysics Data System (ADS)

Aydogan, D.

2007-04-01

An image processing technique called the cellular neural network (CNN) approach is used in this study to locate geological features giving rise to gravity anomalies such as faults or the boundary of two geologic zones. CNN is a stochastic image processing technique based on template optimization using the neighborhood relationships of cells. These cells can be characterized by a functional block diagram that is typical of neural network theory. The functionality of CNN is described in its entirety by a number of small matrices (A, B and I) called the cloning template. CNN can also be considered to be a nonlinear convolution of these matrices. This template describes the strength of the nearest neighbor interconnections in the network. The recurrent perceptron learning algorithm (RPLA) is used in optimization of cloning template. The CNN and standard Canny algorithms were first tested on two sets of synthetic gravity data with the aim of checking the reliability of the proposed approach. The CNN method was compared with classical derivative techniques by applying the cross-correlation method (CC) to the same anomaly map as this latter approach can detect some features that are difficult to identify on the Bouguer anomaly maps. This approach was then applied to the Bouguer anomaly map of Biga and its surrounding area, in Turkey. Structural features in the area between Bandirma, Biga, Yenice and Gonen in the southwest Marmara region are investigated by applying the CNN and CC to the Bouguer anomaly map. Faults identified by these algorithms are generally in accordance with previously mapped surface faults. These examples show that the geologic boundaries can be detected from Bouguer anomaly maps using the cloning template approach. A visual evaluation of the outputs of the CNN and CC approaches is carried out, and the results are compared with each other. This approach provides quantitative solutions based on just a few assumptions, which makes the method more powerful than the classical methods.

Sea surface temperature of the coastal zones of France

NASA Technical Reports Server (NTRS)

Deschamps, P. Y.; Crepon, M.; Monget, J. M.; Verger, F. (Principal Investigator); Frouin, R.; Cassanet, J.; Wald, L.

1982-01-01

Thermal gradients in French coastal zones for the period of one year were mapped in order to enable a coherent study of certain oceanic features detectable by the variations in the sea surface temperature field and their evolution in time. The phenomena examined were mesoscale thermal features in the English Channel, the Bay of Biscay, and the northwestern Mediterranean; thermal gradients generated by French estuary systems; and diurnal heating in the sea surface layer. The investigation was based on Heat Capacity Mapping Mission imagery.

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

Ciuca, Razvan; Hernández, Oscar F., E-mail: razvan.ciuca@mail.mcgill.ca, E-mail: oscarh@physics.mcgill.ca

There exists various proposals to detect cosmic strings from Cosmic Microwave Background (CMB) or 21 cm temperature maps. Current proposals do not aim to find the location of strings on sky maps, all of these approaches can be thought of as a statistic on a sky map. We propose a Bayesian interpretation of cosmic string detection and within that framework, we derive a connection between estimates of cosmic string locations and cosmic string tension G μ. We use this Bayesian framework to develop a machine learning framework for detecting strings from sky maps and outline how to implement this frameworkmore » with neural networks. The neural network we trained was able to detect and locate cosmic strings on noiseless CMB temperature map down to a string tension of G μ=5 ×10{sup −9} and when analyzing a CMB temperature map that does not contain strings, the neural network gives a 0.95 probability that G μ≤2.3×10{sup −9}.« less

Infrared small target enhancement: grey level mapping based on improved sigmoid transformation and saliency histogram

NASA Astrophysics Data System (ADS)

Wan, Minjie; Gu, Guohua; Qian, Weixian; Ren, Kan; Chen, Qian

2018-06-01

Infrared (IR) small target enhancement plays a significant role in modern infrared search and track (IRST) systems and is the basic technique of target detection and tracking. In this paper, a coarse-to-fine grey level mapping method using improved sigmoid transformation and saliency histogram is designed to enhance IR small targets under different backgrounds. For the stage of rough enhancement, the intensity histogram is modified via an improved sigmoid function so as to narrow the regular intensity range of background as much as possible. For the part of further enhancement, a linear transformation is accomplished based on a saliency histogram constructed by averaging the cumulative saliency values provided by a saliency map. Compared with other typical methods, the presented method can achieve both better visual performances and quantitative evaluations.

The genetic architecture of growth and fillet traits in farmed Atlantic salmon (Salmo salar).

PubMed

Tsai, Hsin Yuan; Hamilton, Alastair; Guy, Derrick R; Tinch, Alan E; Bishop, Stephen C; Houston, Ross D

2015-05-19

Performance and quality traits such as harvest weight, fillet weight and flesh color are of economic importance to the Atlantic salmon aquaculture industry. The genetic factors underlying these traits are of scientific and commercial interest. However, such traits are typically polygenic in nature, with the number and size of QTL likely to vary between studies and populations. The aim of this study was to investigate the genetic basis of several growth and fillet traits measured at harvest in a large farmed salmon population by using SNP markers. Due to the marked heterochiasmy in salmonids, an efficient two-stage mapping approach was applied whereby QTL were detected using a sire-based linkage analysis, a sparse SNP marker map and exploiting low rates of recombination, while a subsequent dam-based analysis focused on the significant chromosomes with a denser map to confirm QTL and estimate their position. The harvest traits all showed significant heritability, ranging from 0.05 for fillet yield up to 0.53 for the weight traits. In the sire-based analysis, 1695 offspring with trait records and their 20 sires were successfully genotyped for the SNPs on the sparse map. Chromosomes 13, 18, 19 and 20 were shown to harbor genome-wide significant QTL affecting several growth-related traits. The QTL on chr. 13, 18 and 20 were detected in the dam-based analysis using 512 offspring from 10 dams and explained approximately 6-7 % of the within-family variation in these traits. We have detected several QTL affecting economically important complex traits in a commercial salmon population. Overall, the results suggest that the traits are relatively polygenic and that QTL tend to be pleiotropic (affecting the weight of several components of the harvested fish). Comparison of QTL regions across studies suggests that harvest trait QTL tend to be relatively population-specific. Therefore, the application of marker or genomic selection for improvement in these traits is likely to be most effective when the discovery population is closely related to the selection candidates (e.g. within-family genomic selection).

Simulation study of amplitude-modulated (AM) harmonic motion imaging (HMI) for stiffness contrast quantification with experimental validation.

PubMed

Maleke, Caroline; Luo, Jianwen; Gamarnik, Viktor; Lu, Xin L; Konofagou, Elisa E

2010-07-01

The objective of this study is to show that Harmonic Motion Imaging (HMI) can be used as a reliable tumor-mapping technique based on the tumor's distinct stiffness at the early onset of disease. HMI is a radiation-force-based imaging method that generates a localized vibration deep inside the tissue to estimate the relative tissue stiffness based on the resulting displacement amplitude. In this paper, a finite-element model (FEM) study is presented, followed by an experimental validation in tissue-mimicking polyacrylamide gels and excised human breast tumors ex vivo. This study compares the resulting tissue motion in simulations and experiments at four different gel stiffnesses and three distinct spherical inclusion diameters. The elastic moduli of the gels were separately measured using mechanical testing. Identical transducer parameters were used in both the FEM and experimental studies, i.e., a 4.5-MHz single-element focused ultrasound (FUS) and a 7.5-MHz diagnostic (pulse-echo) transducer. In the simulation, an acoustic pressure field was used as the input stimulus to generate a localized vibration inside the target. Radiofrequency (rf) signals were then simulated using a 2D convolution model. A one-dimensional cross-correlation technique was performed on the simulated and experimental rf signals to estimate the axial displacement resulting from the harmonic radiation force. In order to measure the reliability of the displacement profiles in estimating the tissue stiffness distribution, the contrast-transfer efficiency (CTE) was calculated. For tumor mapping ex vivo, a harmonic radiation force was applied using a 2D raster-scan technique. The 2D HMI images of the breast tumor ex vivo could detect a malignant tumor (20 x 10 mm2) surrounded by glandular and fat tissues. The FEM and experimental results from both gels and breast tumors ex vivo demonstrated that HMI was capable of detecting and mapping the tumor or stiff inclusion with various diameters or stiffnesses. HMI may thus constitute a promising technique in tumor detection (>3 mm in diameter) and mapping based on its distinct stiffness.

Infrared target tracking via weighted correlation filter

NASA Astrophysics Data System (ADS)

He, Yu-Jie; Li, Min; Zhang, JinLi; Yao, Jun-Ping

2015-11-01

Design of an effective target tracker is an important and challenging task for many applications due to multiple factors which can cause disturbance in infrared video sequences. In this paper, an infrared target tracking method under tracking by detection framework based on a weighted correlation filter is presented. This method consists of two parts: detection and filtering. For the detection stage, we propose a sequential detection method for the infrared target based on low-rank representation. For the filtering stage, a new multi-feature weighted function which fuses different target features is proposed, which takes the importance of the different regions into consideration. The weighted function is then incorporated into a correlation filter to compute a confidence map more accurately, in order to indicate the best target location based on the detection results obtained from the first stage. Extensive experimental results on different video sequences demonstrate that the proposed method performs favorably for detection and tracking compared with baseline methods in terms of efficiency and accuracy.

Development of a multiplex Luminex assay for detecting swine antibodies to structural and nonstructural proteins of foot-and-mouth disease virus in Taiwan.

PubMed

Chen, Tsu-Han; Lee, Fan; Lin, Yeou-Liang; Pan, Chu-Hsiang; Shih, Chia-Ni; Tseng, Chun-Hsien; Tsai, Hsiang-Jung

2016-04-01

Foot-and-mouth disease (FMD) and swine vesicular disease (SVD) are serious vesicular diseases that have devastated swine populations throughout the world. The aim of this study was to develop a multianalyte profiling (xMAP) Luminex assay for the differential detection of antibodies to the FMD virus of structural proteins (SP) and nonstructural proteins (NSP). After the xMAP was optimized, it detected antibodies to SP-VP1 and NSP-3ABC of the FMD virus in a single serum sample. These tests were also compared with 3ABC polypeptide blocking enzyme-linked immunosorbent assay (ELISA) and virus neutralization test (VNT) methods for the differential diagnosis and assessment of immune status, respectively. To detect SP antibodies in 661 sera from infected naïve pigs and vaccinated pigs, the diagnostic sensitivity (DSn) and diagnostic specificity (DSp) of the xMAP were 90.0-98.7% and 93.0-96.5%, respectively. To detect NSP antibodies, the DSn was 90% and the DSp ranged from 93.3% to 99.1%. The xMAP can detect the immune response to SP and NSP as early as 4 days postinfection and 8 days postinfection, respectively. Furthermore, the SP and NSP antibodies in all 15 vaccinated but unprotected pigs were detected by xMAP. A comparison of SP and NSP antibodies detected in the sera of the infected samples indicated that the results from the xMAP had a high positive correlation with results from the VNT and a 3ABC polypeptide blocking ELISA assay. However, simultaneous quantitation detected that xMAP had no relationship with the VNT. Furthermore, the specificity was 93.3-94.9% with 3ABC polypeptide blocking ELISA for the FMDV-NSP antibody. The results indicated that xMAP has the potential to detect antibodies to FMDV-SP-VP1 and NSP-3ABC and to distinguish FMDV-infected pigs from pigs infected with the swine vesicular disease virus. Copyright © 2014. Published by Elsevier B.V.

Detection limit of intragenic deletions with targeted array comparative genomic hybridization

PubMed Central

2013-01-01

Background Pathogenic mutations range from single nucleotide changes to deletions or duplications that encompass a single exon to several genes. The use of gene-centric high-density array comparative genomic hybridization (aCGH) has revolutionized the detection of intragenic copy number variations. We implemented an exon-centric design of high-resolution aCGH to detect single- and multi-exon deletions and duplications in a large set of genes using the OGT 60 K and 180 K arrays. Here we describe the molecular characterization and breakpoint mapping of deletions at the smaller end of the detectable range in several genes using aCGH. Results The method initially implemented to detect single to multiple exon deletions, was able to detect deletions much smaller than anticipated. The selected deletions we describe vary in size, ranging from over 2 kb to as small as 12 base pairs. The smallest of these deletions are only detectable after careful manual review during data analysis. Suspected deletions smaller than the detection size for which the method was optimized, were rigorously followed up and confirmed with PCR-based investigations to uncover the true detection size limit of intragenic deletions with this technology. False-positive deletion calls often demonstrated single nucleotide changes or an insertion causing lower hybridization of probes demonstrating the sensitivity of aCGH. Conclusions With optimizing aCGH design and careful review process, aCGH can uncover intragenic deletions as small as dozen bases. These data provide insight that will help optimize probe coverage in array design and illustrate the true assay sensitivity. Mapping of the breakpoints confirms smaller deletions and contributes to the understanding of the mechanism behind these events. Our knowledge of the mutation spectra of several genes can be expected to change as previously unrecognized intragenic deletions are uncovered. PMID:24304607

FineSplice, enhanced splice junction detection and quantification: a novel pipeline based on the assessment of diverse RNA-Seq alignment solutions.

PubMed

Gatto, Alberto; Torroja-Fungairiño, Carlos; Mazzarotto, Francesco; Cook, Stuart A; Barton, Paul J R; Sánchez-Cabo, Fátima; Lara-Pezzi, Enrique

2014-04-01

Alternative splicing is the main mechanism governing protein diversity. The recent developments in RNA-Seq technology have enabled the study of the global impact and regulation of this biological process. However, the lack of standardized protocols constitutes a major bottleneck in the analysis of alternative splicing. This is particularly important for the identification of exon-exon junctions, which is a critical step in any analysis workflow. Here we performed a systematic benchmarking of alignment tools to dissect the impact of design and method on the mapping, detection and quantification of splice junctions from multi-exon reads. Accordingly, we devised a novel pipeline based on TopHat2 combined with a splice junction detection algorithm, which we have named FineSplice. FineSplice allows effective elimination of spurious junction hits arising from artefactual alignments, achieving up to 99% precision in both real and simulated data sets and yielding superior F1 scores under most tested conditions. The proposed strategy conjugates an efficient mapping solution with a semi-supervised anomaly detection scheme to filter out false positives and allows reliable estimation of expressed junctions from the alignment output. Ultimately this provides more accurate information to identify meaningful splicing patterns. FineSplice is freely available at https://sourceforge.net/p/finesplice/.

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

NASA Astrophysics Data System (ADS)

Kohl, B. C.; Given, J.

2017-12-01

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

Sub-pixel flood inundation mapping from multispectral remotely sensed images based on discrete particle swarm optimization

NASA Astrophysics Data System (ADS)

Li, Linyi; Chen, Yun; Yu, Xin; Liu, Rui; Huang, Chang

2015-03-01

The study of flood inundation is significant to human life and social economy. Remote sensing technology has provided an effective way to study the spatial and temporal characteristics of inundation. Remotely sensed images with high temporal resolutions are widely used in mapping inundation. However, mixed pixels do exist due to their relatively low spatial resolutions. One of the most popular approaches to resolve this issue is sub-pixel mapping. In this paper, a novel discrete particle swarm optimization (DPSO) based sub-pixel flood inundation mapping (DPSO-SFIM) method is proposed to achieve an improved accuracy in mapping inundation at a sub-pixel scale. The evaluation criterion for sub-pixel inundation mapping is formulated. The DPSO-SFIM algorithm is developed, including particle discrete encoding, fitness function designing and swarm search strategy. The accuracy of DPSO-SFIM in mapping inundation at a sub-pixel scale was evaluated using Landsat ETM + images from study areas in Australia and China. The results show that DPSO-SFIM consistently outperformed the four traditional SFIM methods in these study areas. A sensitivity analysis of DPSO-SFIM was also carried out to evaluate its performances. It is hoped that the results of this study will enhance the application of medium-low spatial resolution images in inundation detection and mapping, and thereby support the ecological and environmental studies of river basins.

Using Temporal Modulation Sensitivity to Select Stimulation Sites for Processor MAPs in Cochlear Implant Listeners

PubMed Central

Garadat, Soha N.; Zwolan, Teresa A.; Pfingst, Bryan E.

2013-01-01

Previous studies in our laboratory showed that temporal acuity as assessed by modulation detection thresholds (MDTs) varied across activation sites and that this site-to-site variability was subject specific. Using two 10-channel MAPs, the previous experiments showed that processor MAPs that had better across-site mean (ASM) MDTs yielded better speech recognition than MAPs with poorer ASM MDTs tested in the same subject. The current study extends our earlier work on developing more optimal fitting strategies to test the feasibility of using a site-selection approach in the clinical domain. This study examined the hypothesis that revising the clinical speech processor MAP for cochlear implant (CI) recipients by turning off selected sites that have poorer temporal acuity and reallocating frequencies to the remaining electrodes would lead to improved speech recognition. Twelve CI recipients participated in the experiments. We found that site selection procedure based on MDTs in the presence of a masker resulted in improved performance on consonant recognition and recognition of sentences in noise. In contrast, vowel recognition was poorer with the experimental MAP than with the clinical MAP, possibly due to reduced spectral resolution when sites were removed from the experimental MAP. Overall, these results suggest a promising path for improving recipient outcomes using personalized processor-fitting strategies based on a psychophysical measure of temporal acuity. PMID:23881208

Dual-pathway multi-echo sequence for simultaneous frequency and T2 mapping

NASA Astrophysics Data System (ADS)

Cheng, Cheng-Chieh; Mei, Chang-Sheng; Duryea, Jeffrey; Chung, Hsiao-Wen; Chao, Tzu-Cheng; Panych, Lawrence P.; Madore, Bruno

2016-04-01

Purpose: To present a dual-pathway multi-echo steady state sequence and reconstruction algorithm to capture T2, T2∗ and field map information. Methods: Typically, pulse sequences based on spin echoes are needed for T2 mapping while gradient echoes are needed for field mapping, making it difficult to jointly acquire both types of information. A dual-pathway multi-echo pulse sequence is employed here to generate T2 and field maps from the same acquired data. The approach might be used, for example, to obtain both thermometry and tissue damage information during thermal therapies, or susceptibility and T2 information from a same head scan, or to generate bonus T2 maps during a knee scan. Results: Quantitative T2, T2∗ and field maps were generated in gel phantoms, ex vivo bovine muscle, and twelve volunteers. T2 results were validated against a spin-echo reference standard: A linear regression based on ROI analysis in phantoms provided close agreement (slope/R2 = 0.99/0.998). A pixel-wise in vivo Bland-Altman analysis of R2 = 1/T2 showed a bias of 0.034 Hz (about 0.3%), as averaged over four volunteers. Ex vivo results, with and without motion, suggested that tissue damage detection based on T2 rather than temperature-dose measurements might prove more robust to motion. Conclusion: T2, T2∗ and field maps were obtained simultaneously, from the same datasets, in thermometry, susceptibility-weighted imaging and knee-imaging contexts.

Processing LiDAR Data to Predict Natural Hazards

NASA Technical Reports Server (NTRS)

Fairweather, Ian; Crabtree, Robert; Hager, Stacey

2008-01-01

ELF-Base and ELF-Hazards (wherein 'ELF' signifies 'Extract LiDAR Features' and 'LiDAR' signifies 'light detection and ranging') are developmental software modules for processing remote-sensing LiDAR data to identify past natural hazards (principally, landslides) and predict future ones. ELF-Base processes raw LiDAR data, including LiDAR intensity data that are often ignored in other software, to create digital terrain models (DTMs) and digital feature models (DFMs) with sub-meter accuracy. ELF-Hazards fuses raw LiDAR data, data from multispectral and hyperspectral optical images, and DTMs and DFMs generated by ELF-Base to generate hazard risk maps. Advanced algorithms in these software modules include line-enhancement and edge-detection algorithms, surface-characterization algorithms, and algorithms that implement innovative data-fusion techniques. The line-extraction and edge-detection algorithms enable users to locate such features as faults and landslide headwall scarps. Also implemented in this software are improved methodologies for identification and mapping of past landslide events by use of (1) accurate, ELF-derived surface characterizations and (2) three LiDAR/optical-data-fusion techniques: post-classification data fusion, maximum-likelihood estimation modeling, and hierarchical within-class discrimination. This software is expected to enable faster, more accurate forecasting of natural hazards than has previously been possible.

Mapping Secondary Forest Succession on Abandoned Agricultural Land in the Polish Carpathians

NASA Astrophysics Data System (ADS)

Kolecka, N.; Kozak, J.; Kaim, D.; Dobosz, M.; Ginzler, Ch.; Psomas, A.

2016-06-01

Land abandonment and secondary forest succession have played a significant role in land cover changes and forest cover increase in mountain areas in Europe over the past several decades. Land abandonment can be easily observed in the field over small areas, but it is difficult to map over the large areas, e.g., with remote sensing, due to its subtle and spatially dispersed character. Our previous paper presented how the LiDAR (Light Detection and Ranging) and topographic data were used to detect secondary forest succession on abandoned land in one commune located in the Polish Carpathians by means of object-based image analysis (OBIA) and GIS (Kolecka et al., 2015). This paper proposes how the method can be applied to efficiently map secondary forest succession over the entire Polish Carpathians, incorporating spatial sampling strategy supported by various ancillary data. Here we discuss the methods of spatial sampling, its limitations and results in the context of future secondary forest succession modelling.

Wide-Field Raman Imaging of Dental Lesions

PubMed Central

Yang, Shan; Li, Bolan; Akkus, Anna; Akkus, Ozan; Lang, Lisa

2014-01-01

Detection of dental caries at the onset remains as a great challenge in dentistry. Raman spectroscopy could be successfully applied towards detecting caries since it is sensitive to the amount of the Raman active mineral crystals, the most abundant component of enamel. Effective diagnosis requires full examination of a tooth surface via a Raman mapping. Point-scan Raman mapping is not clinically relevant (feasible) due to lengthy data acquisition time. In this work, a wide-field Raman imaging system was assembled based on a high-sensitivity 2D CCD camera for imaging the mineralization status of teeth with lesions. Wide-field images indicated some lesions to be hypomineralized and others to be hypermineralized. The observations of wide-field Raman imaging were in agreement with point-scan Raman mapping. Therefore, sound enamel and lesions can be discriminated by Raman imaging of the mineral content. In conclusion, wide-field Raman imaging is a potentially useful tool for visualization of dental lesions in the clinic. PMID:24781363

Fault detection in rotating machines with beamforming: Spatial visualization of diagnosis features

NASA Astrophysics Data System (ADS)

Cardenas Cabada, E.; Leclere, Q.; Antoni, J.; Hamzaoui, N.

2017-12-01

Rotating machines diagnosis is conventionally related to vibration analysis. Sensors are usually placed on the machine to gather information about its components. The recorded signals are then processed through a fault detection algorithm allowing the identification of the failing part. This paper proposes an acoustic-based diagnosis method. A microphone array is used to record the acoustic field radiated by the machine. The main advantage over vibration-based diagnosis is that the contact between the sensors and the machine is no longer required. Moreover, the application of acoustic imaging makes possible the identification of the sources of acoustic radiation on the machine surface. The display of information is then spatially continuous while the accelerometers only give it discrete. Beamforming provides the time-varying signals radiated by the machine as a function of space. Any fault detection tool can be applied to the beamforming output. Spectral kurtosis, which highlights the impulsiveness of a signal as function of frequency, is used in this study. The combination of spectral kurtosis with acoustic imaging makes possible the mapping of the impulsiveness as a function of space and frequency. The efficiency of this approach lays on the source separation in the spatial and frequency domains. These mappings make possible the localization of such impulsive sources. The faulty components of the machine have an impulsive behavior and thus will be highlighted on the mappings. The study presents experimental validations of the method on rotating machines.

High-speed polarization sensitive optical coherence tomography for retinal diagnostics

NASA Astrophysics Data System (ADS)

Yin, Biwei; Wang, Bingqing; Vemishetty, Kalyanramu; Nagle, Jim; Liu, Shuang; Wang, Tianyi; Rylander, Henry G., III; Milner, Thomas E.

2012-01-01

We report design and construction of an FPGA-based high-speed swept-source polarization-sensitive optical coherence tomography (SS-PS-OCT) system for clinical retinal imaging. Clinical application of the SS-PS-OCT system is accurate measurement and display of thickness, phase retardation and birefringence maps of the retinal nerve fiber layer (RNFL) in human subjects for early detection of glaucoma. The FPGA-based SS-PS-OCT system provides three incident polarization states on the eye and uses a bulk-optic polarization sensitive balanced detection module to record two orthogonal interference fringe signals. Interference fringe signals and relative phase retardation between two orthogonal polarization states are used to obtain Stokes vectors of light returning from each RNFL depth. We implement a Levenberg-Marquardt algorithm on a Field Programmable Gate Array (FPGA) to compute accurate phase retardation and birefringence maps. For each retinal scan, a three-state Levenberg-Marquardt nonlinear algorithm is applied to 360 clusters each consisting of 100 A-scans to determine accurate maps of phase retardation and birefringence in less than 1 second after patient measurement allowing real-time clinical imaging-a speedup of more than 300 times over previous implementations. We report application of the FPGA-based SS-PS-OCT system for real-time clinical imaging of patients enrolled in a clinical study at the Eye Institute of Austin and Duke Eye Center.

Automated Land Cover Change Detection and Mapping from Hidden Parameter Estimates of Normalized Difference Vegetation Index (NDVI) Time-Series

NASA Astrophysics Data System (ADS)

Chakraborty, S.; Banerjee, A.; Gupta, S. K. S.; Christensen, P. R.; Papandreou-Suppappola, A.

2017-12-01

Multitemporal observations acquired frequently by satellites with short revisit periods such as the Moderate Resolution Imaging Spectroradiometer (MODIS), is an important source for modeling land cover. Due to the inherent seasonality of the land cover, harmonic modeling reveals hidden state parameters characteristic to it, which is used in classifying different land cover types and in detecting changes due to natural or anthropogenic factors. In this work, we use an eight day MODIS composite to create a Normalized Difference Vegetation Index (NDVI) time-series of ten years. Improved hidden parameter estimates of the nonlinear harmonic NDVI model are obtained using the Particle Filter (PF), a sequential Monte Carlo estimator. The nonlinear estimation based on PF is shown to improve parameter estimation for different land cover types compared to existing techniques that use the Extended Kalman Filter (EKF), due to linearization of the harmonic model. As these parameters are representative of a given land cover, its applicability in near real-time detection of land cover change is also studied by formulating a metric that captures parameter deviation due to change. The detection methodology is evaluated by considering change as a rare class problem. This approach is shown to detect change with minimum delay. Additionally, the degree of change within the change perimeter is non-uniform. By clustering the deviation in parameters due to change, this spatial variation in change severity is effectively mapped and validated with high spatial resolution change maps of the given regions.

Learning to predict where human gaze is using quaternion DCT based regional saliency detection

NASA Astrophysics Data System (ADS)

Li, Ting; Xu, Yi; Zhang, Chongyang

2014-09-01

Many current visual attention approaches used semantic features to accurately capture human gaze. However, these approaches demand high computational cost and can hardly be applied to daily use. Recently, some quaternion-based saliency detection models, such as PQFT (phase spectrum of Quaternion Fourier Transform), QDCT (Quaternion Discrete Cosine Transform), have been proposed to meet real-time requirement of human gaze tracking tasks. However, current saliency detection methods used global PQFT and QDCT to locate jump edges of the input, which can hardly detect the object boundaries accurately. To address the problem, we improved QDCT-based saliency detection model by introducing superpixel-wised regional saliency detection mechanism. The local smoothness of saliency value distribution is emphasized to distinguish noises of background from salient regions. Our algorithm called saliency confidence can distinguish the patches belonging to the salient object and those of the background. It decides whether the image patches belong to the same region. When an image patch belongs to a region consisting of other salient patches, this patch should be salient as well. Therefore, we use saliency confidence map to get background weight and foreground weight to do the optimization on saliency map obtained by QDCT. The optimization is accomplished by least square method. The optimization approach we proposed unifies local and global saliency by combination of QDCT and measuring the similarity between each image superpixel. We evaluate our model on four commonly-used datasets (Toronto, MIT, OSIE and ASD) using standard precision-recall curves (PR curves), the mean absolute error (MAE) and area under curve (AUC) measures. In comparison with most state-of-art models, our approach can achieve higher consistency with human perception without training. It can get accurate human gaze even in cluttered background. Furthermore, it achieves better compromise between speed and accuracy.

Tree-centric mapping of forest carbon density from airborne laser scanning and hyperspectral data.

PubMed

Dalponte, Michele; Coomes, David A

2016-10-01

Forests are a major component of the global carbon cycle, and accurate estimation of forest carbon stocks and fluxes is important in the context of anthropogenic global change. Airborne laser scanning (ALS) data sets are increasingly recognized as outstanding data sources for high-fidelity mapping of carbon stocks at regional scales.We develop a tree-centric approach to carbon mapping, based on identifying individual tree crowns (ITCs) and species from airborne remote sensing data, from which individual tree carbon stocks are calculated. We identify ITCs from the laser scanning point cloud using a region-growing algorithm and identifying species from airborne hyperspectral data by machine learning. For each detected tree, we predict stem diameter from its height and crown-width estimate. From that point on, we use well-established approaches developed for field-based inventories: above-ground biomasses of trees are estimated using published allometries and summed within plots to estimate carbon density.We show this approach is highly reliable: tests in the Italian Alps demonstrated a close relationship between field- and ALS-based estimates of carbon stocks ( r 2  = 0·98). Small trees are invisible from the air, and a correction factor is required to accommodate this effect.An advantage of the tree-centric approach over existing area-based methods is that it can produce maps at any scale and is fundamentally based on field-based inventory methods, making it intuitive and transparent. Airborne laser scanning, hyperspectral sensing and computational power are all advancing rapidly, making it increasingly feasible to use ITC approaches for effective mapping of forest carbon density also inside wider carbon mapping programs like REDD++.

Hunting for Hydrothermal Vents at the Local-Scale Using AUV's and Machine-Learning Classification in the Earth's Oceans

NASA Astrophysics Data System (ADS)

White, S. M.

2018-05-01

New AUV-based mapping technology coupled with machine-learning methods for detecting individual vents and vent fields at the local-scale raise the possibility of understanding the geologic controls on hydrothermal venting.

DNA nanomapping using CRISPR-Cas9 as a programmable nanoparticle.

PubMed

Mikheikin, Andrey; Olsen, Anita; Leslie, Kevin; Russell-Pavier, Freddie; Yacoot, Andrew; Picco, Loren; Payton, Oliver; Toor, Amir; Chesney, Alden; Gimzewski, James K; Mishra, Bud; Reed, Jason

2017-11-21

Progress in whole-genome sequencing using short-read (e.g., <150 bp), next-generation sequencing technologies has reinvigorated interest in high-resolution physical mapping to fill technical gaps that are not well addressed by sequencing. Here, we report two technical advances in DNA nanotechnology and single-molecule genomics: (1) we describe a labeling technique (CRISPR-Cas9 nanoparticles) for high-speed AFM-based physical mapping of DNA and (2) the first successful demonstration of using DVD optics to image DNA molecules with high-speed AFM. As a proof of principle, we used this new "nanomapping" method to detect and map precisely BCL2-IGH translocations present in lymph node biopsies of follicular lymphoma patents. This HS-AFM "nanomapping" technique can be complementary to both sequencing and other physical mapping approaches.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management.

PubMed

Malmstrom, Carolyn M; Butterfield, H Scott; Planck, Laura; Long, Christopher W; Eviner, Valerie T

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management

PubMed Central

Butterfield, H. Scott; Planck, Laura; Long, Christopher W.; Eviner, Valerie T.

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics. PMID:29016604

Detection and mapping of QTL for temperature tolerance and body size in Chinook salmon (Oncorhynchus tshawytscha) using genotyping by sequencing

PubMed Central

Everett, Meredith V; Seeb, James E

2014-01-01

Understanding how organisms interact with their environments is increasingly important for conservation efforts in many species, especially in light of highly anticipated climate changes. One method for understanding this relationship is to use genetic maps and QTL mapping to detect genomic regions linked to phenotypic traits of importance for adaptation. We used high-throughput genotyping by sequencing (GBS) to both detect and map thousands of SNPs in haploid Chinook salmon (Oncorhynchus tshawytscha). We next applied this map to detect QTL related to temperature tolerance and body size in families of diploid Chinook salmon. Using these techniques, we mapped 3534 SNPs in 34 linkage groups which is consistent with the haploid chromosome number for Chinook salmon. We successfully detected three QTL for temperature tolerance and one QTL for body size at the experiment-wide level, as well as additional QTL significant at the chromosome-wide level. The use of haploids coupled with GBS provides a robust pathway to rapidly develop genomic resources in nonmodel organisms; these QTL represent preliminary progress toward linking traits of conservation interest to regions in the Chinook salmon genome. PMID:24822082

Cartographic quality of ERTS-1 images

NASA Technical Reports Server (NTRS)

Welch, R. I.

1973-01-01

Analyses of simulated and operational ERTS images have provided initial estimates of resolution, ground resolution, detectability thresholds and other measures of image quality of interest to earth scientists and cartographers. Based on these values, including an approximate ground resolution of 250 meters for both RBV and MSS systems, the ERTS-1 images appear suited to the production and/or revision of planimetric and photo maps of 1:500,000 scale and smaller for which map accuracy standards are compatible with the imaged detail. Thematic mapping, although less constrained by map accuracy standards, will be influenced by measurement thresholds and errors which have yet to be accurately determined for ERTS images. This study also indicates the desirability of establishing a quantitative relationship between image quality values and map products which will permit both engineers and cartographers/earth scientists to contribute to the design requirements of future satellite imaging systems.

Assessment of the prevalence of Mycobacterium avium subsp. paratuberculosis in commercially pasteurized milk.

PubMed

Cerf, O; Griffiths, M; Aziza, F

2007-01-01

Conflicting laboratory-acquired data have been published about the heat resistance of Mycobacterium avium subsp. paratuberculosis (MAP), the cause of the deadly paratuberculosis (Johne's disease) of ruminants. Results of surveys of the presence of MAP in industrially pasteurized milk from several countries are conflicting also. This paper critically reviews the available data on the heat resistance of MAP and, based on these studies, a quantitative model describing the probability of finding MAP in pasteurized milk under the conditions prevailing in industrialized countries was derived using Monte Carlo simulation. The simulation assesses the probability of detecting MAP in 50-mL samples of pasteurized milk as lower than 1%. Hypotheses are presented to explain why higher frequencies were found by some authors; these included improper pasteurization and cross-contamination in the analytical laboratory. Hypotheses implicating a high rate of inter- and intraherd prevalence of paratuberculosis or heavy contamination of raw milk by feces were rejected.

Construction of a high-density genetic map and lint percentage and cottonseed nutrient trait QTL identification in upland cotton (Gossypium hirsutum L.).

PubMed

Liu, Dexin; Liu, Fang; Shan, Xiaoru; Zhang, Jian; Tang, Shiyi; Fang, Xiaomei; Liu, Xueying; Wang, Wenwen; Tan, Zhaoyun; Teng, Zhonghua; Zhang, Zhengsheng; Liu, Dajun

2015-10-01

Upland cotton plays a critical role not only in the textile industry, but also in the production of important secondary metabolites, such as oil and proteins. Construction of a high-density linkage map and identifying yield and seed trait quantitative trail loci (QTL) are prerequisites for molecular marker-assisted selective breeding projects. Here, we update a high-density upland cotton genetic map from recombinant inbred lines. A total of 25,313 SSR primer pairs were screened for polymorphism between Yumian 1 and T586, and 1712 SSR primer pairs were used to genotype the mapping population and construct a map. An additional 1166 loci have been added to our previously published map with 509 SSR markers. The updated genetic map spans a total recombinant length of 3338.2 cM and contains 1675 SSR loci and nine morphological markers, with an average interval of 1.98 cM between adjacent markers. Green lint (Lg) mapped on chromosome 15 in a previous report is mapped in an interval of 2.6 cM on chromosome 21. Based on the map and phenotypic data from multiple environments, 79 lint percentage and seed nutrient trait QTL are detected. These include 8 lint percentage, 13 crude protein, 15 crude oil, 8 linoleic, 10 oleic, 13 palmitic, and 12 stearic acid content QTL. They explain 3.5-62.7 % of the phenotypic variation observed. Four morphological markers identified have a major impact on lint percentage and cottonseed nutrients traits. In this study, our genetic map provides new sights into the tetraploid cotton genome. Furthermore, the stable QTL and morphological markers could be used for fine-mapping and map-based cloning.

Automatic Rock Detection and Mapping from HiRISE Imagery

NASA Technical Reports Server (NTRS)

Huertas, Andres; Adams, Douglas S.; Cheng, Yang

2008-01-01

This system includes a C-code software program and a set of MATLAB software tools for statistical analysis and rock distribution mapping. The major functions include rock detection and rock detection validation. The rock detection code has been evolved into a production tool that can be used by engineers and geologists with minor training.

Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest

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

Liu, Jiamin; Hoffman, Joanne; Zhao, Jocelyn

2016-07-15

Purpose: To develop an automated system for mediastinal lymph node detection and station mapping for chest CT. Methods: The contextual organs, trachea, lungs, and spine are first automatically identified to locate the region of interest (ROI) (mediastinum). The authors employ shape features derived from Hessian analysis, local object scale, and circular transformation that are computed per voxel in the ROI. Eight more anatomical structures are simultaneously segmented by multiatlas label fusion. Spatial priors are defined as the relative multidimensional distance vectors corresponding to each structure. Intensity, shape, and spatial prior features are integrated and parsed by a random forest classifiermore » for lymph node detection. The detected candidates are then segmented by the following curve evolution process. Texture features are computed on the segmented lymph nodes and a support vector machine committee is used for final classification. For lymph node station labeling, based on the segmentation results of the above anatomical structures, the textual definitions of mediastinal lymph node map according to the International Association for the Study of Lung Cancer are converted into patient-specific color-coded CT image, where the lymph node station can be automatically assigned for each detected node. Results: The chest CT volumes from 70 patients with 316 enlarged mediastinal lymph nodes are used for validation. For lymph node detection, their system achieves 88% sensitivity at eight false positives per patient. For lymph node station labeling, 84.5% of lymph nodes are correctly assigned to their stations. Conclusions: Multiple-channel shape, intensity, and spatial prior features aggregated by a random forest classifier improve mediastinal lymph node detection on chest CT. Using the location information of segmented anatomic structures from the multiatlas formulation enables accurate identification of lymph node stations.« less

Mycobacterium avium ss. paratuberculosis Zoonosis – The Hundred Year War – Beyond Crohn’s Disease

PubMed Central

Sechi, Leonardo A.; Dow, Coad Thomas

2015-01-01

The factitive role of Mycobacterium avium ss. paratuberculosis (MAP) in Crohn’s disease has been debated for more than a century. The controversy is due to the fact that Crohn’s disease is so similar to a disease of MAP-infected ruminant animals, Johne’s disease; and, though MAP can be readily detected in the infected ruminants, it is much more difficult to detect in humans. Molecular techniques that can detect MAP in pathologic Crohn’s specimens as well as dedicated specialty labs successful in culturing MAP from Crohn’s patients have provided strong argument for MAP’s role in Crohn’s disease. Perhaps more incriminating for MAP as a zoonotic agent is the increasing number of diseases with which MAP has been related: Blau syndrome, type 1 diabetes, Hashimoto thyroiditis, and multiple sclerosis. In this article, we debate about genetic susceptibility to mycobacterial infection and human exposure to MAP; moreover, it suggests that molecular mimicry between protein epitopes of MAP and human proteins is a likely bridge between infection and these autoimmune disorders. PMID:25788897

Quaternion-valued single-phase model for three-phase power system

NASA Astrophysics Data System (ADS)

Gou, Xiaoming; Liu, Zhiwen; Liu, Wei; Xu, Yougen; Wang, Jiabin

2018-03-01

In this work, a quaternion-valued model is proposed in lieu of the Clarke's α, β transformation to convert three-phase quantities to a hypercomplex single-phase signal. The concatenated signal can be used for harmonic distortion detection in three-phase power systems. In particular, the proposed model maps all the harmonic frequencies into frequencies in the quaternion domain, while the Clarke's transformation-based methods will fail to detect the zero sequence voltages. Based on the quaternion-valued model, the Fourier transform, the minimum variance distortionless response (MVDR) algorithm and the multiple signal classification (MUSIC) algorithm are presented as examples to detect harmonic distortion. Simulations are provided to demonstrate the potentials of this new modeling method.

When will Low-Contrast Features be Visible in a STEM X-Ray Spectrum Image?

PubMed

Parish, Chad M

2015-06-01

When will a small or low-contrast feature, such as an embedded second-phase particle, be visible in a scanning transmission electron microscopy (STEM) X-ray map? This work illustrates a computationally inexpensive method to simulate X-ray maps and spectrum images (SIs), based upon the equations of X-ray generation and detection. To particularize the general procedure, an example of nanostructured ferritic alloy (NFA) containing nm-sized Y2Ti2O7 embedded precipitates in ferritic stainless steel matrix is chosen. The proposed model produces physically appearing simulated SI data sets, which can either be reduced to X-ray dot maps or analyzed via multivariate statistical analysis. Comparison to NFA X-ray maps acquired using three different STEM instruments match the generated simulations quite well, despite the large number of simplifying assumptions used. A figure of merit of electron dose multiplied by X-ray collection solid angle is proposed to compare feature detectability from one data set (simulated or experimental) to another. The proposed method can scope experiments that are feasible under specific analysis conditions on a given microscope. Future applications, such as spallation proton-neutron irradiations, core-shell nanoparticles, or dopants in polycrystalline photovoltaic solar cells, are proposed.

Progress and pitfalls in finding the 'missing proteins' from the human proteome map.

PubMed

Segura, Victor; Garin-Muga, Alba; Guruceaga, Elizabeth; Corrales, Fernando J

2017-01-01

The Human Proteome Project was launched with two main goals: the comprehensive and systematic definition of the human proteome map and the development of ready to use analytical tools to measure relevant proteins in their biological context in health and disease. Despite the great progress in this endeavour, there is still a group of reluctant proteins with no, or scarce, experimental evidence supporting their existence. These are called the 'missing proteins' and represent one of the biggest challenges to complete the human proteome map. Areas covered: This review focuses on the description of the missing proteome based on the HUPO standards, the analysis of the reasons explaining the difficulty of detecting missing proteins and the strategies currently used in the search for missing proteins. The present and future of the quest for the missing proteins is critically revised hereafter. Expert commentary: An overarching multidisciplinary effort is currently being done under the HUPO umbrella to allow completion of the human proteome map. It is expected that the detection of missing proteins will grow in the coming years since the methods and the best tissue/cell type sample for their search are already on the table.

Arctic lead detection using a waveform unmixing algorithm from CryoSat-2 data

NASA Astrophysics Data System (ADS)

Lee, S.; Im, J.

2016-12-01

Arctic areas consist of ice floes, leads, and polynyas. While leads and polynyas account for small parts in the Arctic Ocean, they play a key role in exchanging heat flux, moisture, and momentum between the atmosphere and ocean in wintertime because of their huge temperature difference In this study, a linear waveform unmixing approach was proposed to detect lead fraction. CryoSat-2 waveforms for pure leads, sea ice, and ocean were used as end-members based on visual interpretation of MODIS images coincident with CryoSat-2 data. The unmixing model produced lead, sea ice, and ocean abundances and a threshold (> 0.7) was applied to make a binary classification between lead and sea ice. The unmixing model produced better results than the existing models in the literature, which are based on simple thresholding approaches. The results were also comparable with our previous research using machine learning based models (i.e., decision trees and random forest). A monthly lead fraction was calculated, dividing the number of detected leads by the total number of measurements. The lead fraction around Beaufort Sea and Fram strait was high due to the anti-cyclonic rotation of Beaufort Gyre and the outflows of sea ice to the Atlantic. The lead fraction maps produced in this study were matched well with monthly lead fraction maps in the literature. The areas with thin sea ice identified from our previous research correspond to the high lead fraction areas in the present study. Furthermore, sea ice roughness from ASCAT scatterometer was compared to a lead fraction map to see the relationship between surface roughness and lead distribution.

Autonomous UAV-Based Mapping of Large-Scale Urban Firefights

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

Snarski, S; Scheibner, K F; Shaw, S

2006-03-09

This paper describes experimental results from a live-fire data collect designed to demonstrate the ability of IR and acoustic sensing systems to detect and map high-volume gunfire events from tactical UAVs. The data collect supports an exploratory study of the FightSight concept in which an autonomous UAV-based sensor exploitation and decision support capability is being proposed to provide dynamic situational awareness for large-scale battalion-level firefights in cluttered urban environments. FightSight integrates IR imagery, acoustic data, and 3D scene context data with prior time information in a multi-level, multi-step probabilistic-based fusion process to reliably locate and map the array of urbanmore » firing events and firepower movements and trends associated with the evolving urban battlefield situation. Described here are sensor results from live-fire experiments involving simultaneous firing of multiple sub/super-sonic weapons (2-AK47, 2-M16, 1 Beretta, 1 Mortar, 1 rocket) with high optical and acoustic clutter at ranges up to 400m. Sensor-shooter-target configurations and clutter were designed to simulate UAV sensing conditions for a high-intensity firefight in an urban environment. Sensor systems evaluated were an IR bullet tracking system by Lawrence Livermore National Laboratory (LLNL) and an acoustic gunshot detection system by Planning Systems, Inc. (PSI). The results demonstrate convincingly the ability for the LLNL and PSI sensor systems to accurately detect, separate, and localize multiple shooters and the associated shot directions during a high-intensity firefight (77 rounds in 5 sec) in a high acoustic and optical clutter environment with no false alarms. Preliminary fusion processing was also examined that demonstrated an ability to distinguish co-located shooters (shooter density), range to <0.5 m accuracy at 400m, and weapon type.« less

Research on facial expression simulation based on depth image

NASA Astrophysics Data System (ADS)

Ding, Sha-sha; Duan, Jin; Zhao, Yi-wu; Xiao, Bo; Wang, Hao

2017-11-01

Nowadays, face expression simulation is widely used in film and television special effects, human-computer interaction and many other fields. Facial expression is captured by the device of Kinect camera .The method of AAM algorithm based on statistical information is employed to detect and track faces. The 2D regression algorithm is applied to align the feature points. Among them, facial feature points are detected automatically and 3D cartoon model feature points are signed artificially. The aligned feature points are mapped by keyframe techniques. In order to improve the animation effect, Non-feature points are interpolated based on empirical models. Under the constraint of Bézier curves we finish the mapping and interpolation. Thus the feature points on the cartoon face model can be driven if the facial expression varies. In this way the purpose of cartoon face expression simulation in real-time is came ture. The experiment result shows that the method proposed in this text can accurately simulate the facial expression. Finally, our method is compared with the previous method. Actual data prove that the implementation efficiency is greatly improved by our method.

Optical remote sensing and correlation of office equipment functional state and stress levels via power quality disturbances inefficiencies

NASA Astrophysics Data System (ADS)

Sternberg, Oren; Bednarski, Valerie R.; Perez, Israel; Wheeland, Sara; Rockway, John D.

2016-09-01

Non-invasive optical techniques pertaining to the remote sensing of power quality disturbances (PQD) are part of an emerging technology field typically dominated by radio frequency (RF) and invasive-based techniques. Algorithms and methods to analyze and address PQD such as probabilistic neural networks and fully informed particle swarms have been explored in industry and academia. Such methods are tuned to work with RF equipment and electronics in existing power grids. As both commercial and defense assets are heavily power-dependent, understanding electrical transients and failure events using non-invasive detection techniques is crucial. In this paper we correlate power quality empirical models to the observed optical response. We also empirically demonstrate a first-order approach to map household, office and commercial equipment PQD to user functions and stress levels. We employ a physics-based image and signal processing approach, which demonstrates measured non-invasive (remote sensing) techniques to detect and map the base frequency associated with the power source to the various PQD on a calibrated source.

Unbiased Protein Association Study on the Public Human Proteome Reveals Biological Connections between Co-Occurring Protein Pairs

PubMed Central

2017-01-01

Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal ways to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targets for follow-up analysis. PMID:28480704

Detection of water bodies in Saline County, Kansas

NASA Technical Reports Server (NTRS)

Barr, B. G. (Principal Investigator)

1973-01-01

The author has identified the following significant results. A total of 2,272 water bodies were mapped in Saline County, Kansas in 1972 using ERTS-1 imagery. A topographic map of 1955 shows 1,056 water bodies in the county. The major increase took place in farm ponds. Preliminary comparison of image and maps indicates that water bodies larger than ten acres in area proved consistently detectable. Most water areas between four and ten acres are also detectable, although occasionally image context prevents detection. Water areas less than four acres in extent are sometimes detected, but the number varies greatly depending on image context and the individual interpretor.

A High-Density Consensus Map of Common Wheat Integrating Four Mapping Populations Scanned by the 90K SNP Array

PubMed Central

Wen, Weie; He, Zhonghu; Gao, Fengmei; Liu, Jindong; Jin, Hui; Zhai, Shengnan; Qu, Yanying; Xia, Xianchun

2017-01-01

A high-density consensus map is a powerful tool for gene mapping, cloning and molecular marker-assisted selection in wheat breeding. The objective of this study was to construct a high-density, single nucleotide polymorphism (SNP)-based consensus map of common wheat (Triticum aestivum L.) by integrating genetic maps from four recombinant inbred line populations. The populations were each genotyped using the wheat 90K Infinium iSelect SNP assay. A total of 29,692 SNP markers were mapped on 21 linkage groups corresponding to 21 hexaploid wheat chromosomes, covering 2,906.86 cM, with an overall marker density of 10.21 markers/cM. Compared with the previous maps based on the wheat 90K SNP chip detected 22,736 (76.6%) of the SNPs with consistent chromosomal locations, whereas 1,974 (6.7%) showed different chromosomal locations, and 4,982 (16.8%) were newly mapped. Alignment of the present consensus map and the wheat expressed sequence tags (ESTs) Chromosome Bin Map enabled assignment of 1,221 SNP markers to specific chromosome bins and 819 ESTs were integrated into the consensus map. The marker orders of the consensus map were validated based on physical positions on the wheat genome with Spearman rank correlation coefficients ranging from 0.69 (4D) to 0.97 (1A, 4B, 5B, and 6A), and were also confirmed by comparison with genetic position on the previously 40K SNP consensus map with Spearman rank correlation coefficients ranging from 0.84 (6D) to 0.99 (6A). Chromosomal rearrangements reported previously were confirmed in the present consensus map and new putative rearrangements were identified. In addition, an integrated consensus map was developed through the combination of five published maps with ours, containing 52,607 molecular markers. The consensus map described here provided a high-density SNP marker map and a reliable order of SNPs, representing a step forward in mapping and validation of chromosomal locations of SNPs on the wheat 90K array. Moreover, it can be used as a reference for quantitative trait loci (QTL) mapping to facilitate exploitation of genes and QTL in wheat breeding. PMID:28848588

Comparison of milk culture, direct and nested polymerase chain reaction (PCR) with fecal culture based on samples from dairy herds infected with Mycobacterium avium subsp. paratuberculosis

PubMed Central

Gao, Anli; Odumeru, Joseph; Raymond, Melinda; Hendrick, Steven; Duffield, Todd; Mutharia, Lucy

2009-01-01

Mycobacterium avium subsp. paratuberculosis (MAP) is the etiologic agent of Johne’s disease in cattle and other farm ruminants, and is also a suspected pathogen of Crohn’s disease in humans. Development of diagnostic methods for MAP infection has been a challenge over the last few decades. The objective of this study was to investigate the relationship between different methods for detection of MAP in milk and fecal samples. A total of 134 milk samples and 110 feces samples were collected from 146 individual cows in 14 MAP-infected herds in southwestern Ontario. Culture, IS900 polymerase chain reaction (PCR) and nested PCR methods were used for detecting MAP in milk; results were compared with those of fecal culture. A significant relationship was found between milk culture, direct PCR, and nested PCR (P < 0.05). The fecal culture results were not related to any of the 3 assay methods used for the milk samples (P > 0.10). Although fecal culture showed a higher sensitivity than the milk culture method, the difference was not significant (P = 0.2473). The number of MAP colony-forming units (CFU) isolated by culture from fecal samples was, on average, higher than that isolated from milk samples (P = 0.0083). There was no significant correlation between the number of CFU cultured from milk and from feces (Pearson correlation coefficient = 0.1957, N = 63, P = 0.1243). The animals with high numbers of CFU in milk culture may not be detected by fecal culture at all, and vise versa. A significant proportion (29% to 41%) of the positive animals would be missed if only 1 culture method, instead of both milk and feces, were to be used for diagnosis. This suggests that the shedding of MAP in feces and milk is not synchronized. Most of the infected cows were low-level shedders. The proportion of low-level shedders may even be underestimated because MAP is killed during decontamination, thus reducing the chance of detection. Therefore, to identify suspected Johne’s-infected animals using the tests in this study, both milk and feces samples should be collected in duplicate to enhance the diagnostic rate. The high MAP kill rate identified in the culture methods during decontamination may be compensated for by using the nested PCR method, which had a higher sensitivity than the IS900 PCR method used. PMID:19337397

Discovery and mapping of single feature polymorphisms in wheat using Affymetrix arrays

PubMed Central

Bernardo, Amy N; Bradbury, Peter J; Ma, Hongxiang; Hu, Shengwa; Bowden, Robert L; Buckler, Edward S; Bai, Guihua

2009-01-01

Background Wheat (Triticum aestivum L.) is a staple food crop worldwide. The wheat genome has not yet been sequenced due to its huge genome size (~17,000 Mb) and high levels of repetitive sequences; the whole genome sequence may not be expected in the near future. Available linkage maps have low marker density due to limitation in available markers; therefore new technologies that detect genome-wide polymorphisms are still needed to discover a large number of new markers for construction of high-resolution maps. A high-resolution map is a critical tool for gene isolation, molecular breeding and genomic research. Single feature polymorphism (SFP) is a new microarray-based type of marker that is detected by hybridization of DNA or cRNA to oligonucleotide probes. This study was conducted to explore the feasibility of using the Affymetrix GeneChip to discover and map SFPs in the large hexaploid wheat genome. Results Six wheat varieties of diverse origins (Ning 7840, Clark, Jagger, Encruzilhada, Chinese Spring, and Opata 85) were analyzed for significant probe by variety interactions and 396 probe sets with SFPs were identified. A subset of 164 unigenes was sequenced and 54% showed polymorphism within probes. Microarray analysis of 71 recombinant inbred lines from the cross Ning 7840/Clark identified 955 SFPs and 877 of them were mapped together with 269 simple sequence repeat markers. The SFPs were randomly distributed within a chromosome but were unevenly distributed among different genomes. The B genome had the most SFPs, and the D genome had the least. Map positions of a selected set of SFPs were validated by mapping single nucleotide polymorphism using SNaPshot and comparing with expressed sequence tags mapping data. Conclusion The Affymetrix array is a cost-effective platform for SFP discovery and SFP mapping in wheat. The new high-density map constructed in this study will be a useful tool for genetic and genomic research in wheat. PMID:19480702

Object-based Landslide Mapping: Examples, Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Hölbling, Daniel; Eisank, Clemens; Friedl, Barbara; Chang, Kang-Tsung; Tsai, Tsai-Tsung; Birkefeldt Møller Pedersen, Gro; Betts, Harley; Cigna, Francesca; Chiang, Shou-Hao; Aubrey Robson, Benjamin; Bianchini, Silvia; Füreder, Petra; Albrecht, Florian; Spiekermann, Raphael; Weinke, Elisabeth; Blaschke, Thomas; Phillips, Chris

2016-04-01

Over the last decade, object-based image analysis (OBIA) has been increasingly used for mapping landslides that occur after triggering events such as heavy rainfall. The increasing availability and quality of Earth Observation (EO) data in terms of temporal, spatial and spectral resolution allows for comprehensive mapping of landslides at multiple scales. Most often very high resolution (VHR) or high resolution (HR) optical satellite images are used in combination with a digital elevation model (DEM) and its products such as slope and curvature. Semi-automated object-based mapping makes use of various characteristics of image objects that are derived through segmentation. OBIA enables numerous spectral, spatial, contextual and textural image object properties to be applied during an analysis. This is especially useful when mapping complex natural features such as landslides and constitutes an advantage over pixel-based image analysis. However, several drawbacks in the process of object-based landslide mapping have not been overcome yet. The developed classification routines are often rather complex and limited regarding their transferability across areas and sensors. There is still more research needed to further improve present approaches and to fully exploit the capabilities of OBIA for landslide mapping. In this study several examples of object-based landslide mapping from various geographical regions with different characteristics are presented. Examples from the Austrian and Italian Alps are shown, whereby one challenge lies in the detection of small-scale landslides on steep slopes while preventing the classification of false positives with similar spectral properties (construction areas, utilized land, etc.). Further examples feature landslides mapped in Iceland, where the differentiation of landslides from other landscape-altering processes in a highly dynamic volcanic landscape poses a very distinct challenge, and in Norway, which is exposed to multiple types of landslides. Unlike in these northern European countries, landslides in Taiwan can be effectively delineated based on spectral differences as the surrounding is most often densely vegetated. In this tropical/subtropical region the fast information provision after Typhoon events is important. This need can be addressed in OBIA by automatically calculating thresholds based on vegetation indices and using them for a first rough identification of areas affected by landslides. Moreover, the differentiation in landslide source and transportation area is of high relevance in Taiwan. Finally, an example from New Zealand, where landslide inventory mapping is important for estimating surface erosion, will demonstrate the performance of OBIA compared to visual expert interpretation and on-screen mapping. The associated challenges and opportunities related to case studies in each of these regions are discussed and reviewed. In doing so, open research issues in object-based landslide mapping based on EO data are identified and highlighted.

Co-registered photoacoustic and fluorescent imaging of a switchable nanoprobe based on J-aggregates of indocyanine green

NASA Astrophysics Data System (ADS)

Dumani, Diego S.; Brecht, Hans-Peter; Ivanov, Vassili; Deschner, Ryan; Harris, Justin T.; Homan, Kimberly A.; Cook, Jason R.; Emelianov, Stanislav Y.; Ermilov, Sergey A.

2018-02-01

We introduce a preclinical imaging platform - a 3D photoacoustic/fluorescence tomography (PAFT) instrument augmented with an environmentally responsive dual-contrast biocompatible nanoprobe. The PAFT instrument was designed for simultaneous acquisition of photoacoustic and fluorescence orthogonal projections at each rotational position of a biological object, enabling direct co-registration of the two imaging modalities. The nanoprobe was based on liposomes loaded with J-aggregates of indocyanine green (PAtrace). Once PAtrace interacts with the environment, a transition from J-aggregate to monomeric ICG is induced. The subsequent recovery of monomeric ICG is characterized by dramatic changes in the optical absorption spectrum and reinstated fluorescence. In the activated state, PAtrace can be simultaneously detected by both imaging modes of the PAFT instrument using 780 nm excitation and fluorescence detection at 810 nm. The fluorescence imaging component is used to boost detection sensitivity by providing lowresolution map of activated nanoprobes, which are then more precisely mapped in 3D by the photoacoustic imaging component. Activated vs non-activated particles can be distinguished based on their different optical absorption peaks, removing the requirements for complex image registration between reference and detection scans. Preliminary phantom and in vivo animal imaging results showed successful activation and visualization of PAtrace with high sensitivity and resolution. The proposed PAFT-PAtrace imaging platform could be used in various functional and molecular imaging applications including multi-point in vivo assessment of early metastasis.

Mapping Wildfire Ignition Probability Using Sentinel 2 and LiDAR (Jerte Valley, Cáceres, Spain)

PubMed Central

Sánchez Sánchez, Yolanda; Mateos Picado, Marina

2018-01-01

Wildfire is a major threat to the environment, and this threat is aggravated by different climatic and socioeconomic factors. The availability of detailed, reliable mapping and periodic and immediate updates makes wildfire prevention and extinction work more effective. An analyst protocol has been generated that allows the precise updating of high-resolution thematic maps. For this protocol, images obtained through the Sentinel 2A satellite, with a return time of five days, have been merged with Light Detection and Ranging (LiDAR) data with a density of 0.5 points/m2 in order to obtain vegetation mapping with an accuracy of 88% (kappa = 0.86), which is then extrapolated to fuel model mapping through a decision tree. This process, which is fast and reliable, serves as a cartographic base for the later calculation of ignition-probability mapping. The generated cartography is a fundamental tool to be used in the decision making involved in the planning of preventive silvicultural treatments, extinguishing media distribution, infrastructure construction, etc. PMID:29522460

Mapping Wildfire Ignition Probability Using Sentinel 2 and LiDAR (Jerte Valley, Cáceres, Spain).

PubMed

Sánchez Sánchez, Yolanda; Martínez-Graña, Antonio; Santos Francés, Fernando; Mateos Picado, Marina

2018-03-09

Wildfire is a major threat to the environment, and this threat is aggravated by different climatic and socioeconomic factors. The availability of detailed, reliable mapping and periodic and immediate updates makes wildfire prevention and extinction work more effective. An analyst protocol has been generated that allows the precise updating of high-resolution thematic maps. For this protocol, images obtained through the Sentinel 2A satellite, with a return time of five days, have been merged with Light Detection and Ranging (LiDAR) data with a density of 0.5 points/m² in order to obtain vegetation mapping with an accuracy of 88% (kappa = 0.86), which is then extrapolated to fuel model mapping through a decision tree. This process, which is fast and reliable, serves as a cartographic base for the later calculation of ignition-probability mapping. The generated cartography is a fundamental tool to be used in the decision making involved in the planning of preventive silvicultural treatments, extinguishing media distribution, infrastructure construction, etc.

Comparison of rapid diagnostic tests to detect Mycobacterium avium subsp. paratuberculosis disseminated infection in bovine liver.

PubMed

Zarei, Mehdi; Ghorbanpour, Masoud; Tajbakhsh, Samaneh; Mosavari, Nader

2017-08-01

Mycobacterium avium subsp. paratuberculosis (MAP) causes Johne's disease, a chronic enteritis in cattle and other domestic and wild ruminants. The presence of MAP in tissues other than intestines and associated lymph nodes, such as meat and liver, is a potential public health concern. In the present study, the relationship between the results of rapid diagnostic tests of the Johne's disease, such as serum ELISA, rectal scraping PCR, and acid-fast staining, and the presence of MAP in liver was evaluated. Blood, liver, and rectal scraping samples were collected from 200 slaughtered cattle with unknown Johne's disease status. ELISA was performed to determine the MAP antibody activity in the serum. Acid-fast staining was performed on rectal scraping samples, and PCR was performed on rectal scraping and liver samples. PCR-positive liver samples were used for mycobacterial culture. Overall, the results of this study demonstrated that MAP can be detected and cultured from liver of slaughtered cattle and rapid diagnostic tests of Johne's disease have limited value in detecting cattle with MAP infection in liver. These findings show that the presence of MAP in liver tissue may occur in cows with negative results for rapid diagnostic tests and vice versa. Hence, liver might represent another possible risk of human exposure to MAP. Given concerns about a potential zoonotic role for MAP, these results show the necessity to find new methods for detecting cattle with MAP disseminated infection.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

People detection method using graphics processing units for a mobile robot with an omnidirectional camera

NASA Astrophysics Data System (ADS)

Kang, Sungil; Roh, Annah; Nam, Bodam; Hong, Hyunki

2011-12-01

This paper presents a novel vision system for people detection using an omnidirectional camera mounted on a mobile robot. In order to determine regions of interest (ROI), we compute a dense optical flow map using graphics processing units, which enable us to examine compliance with the ego-motion of the robot in a dynamic environment. Shape-based classification algorithms are employed to sort ROIs into human beings and nonhumans. The experimental results show that the proposed system detects people more precisely than previous methods.

Detection, mapping, and quantification of single walled carbon nanotubes in histological specimens with photoacoustic microscopy.

PubMed

Avti, Pramod K; Hu, Song; Favazza, Christopher; Mikos, Antonios G; Jansen, John A; Shroyer, Kenneth R; Wang, Lihong V; Sitharaman, Balaji

2012-01-01

In the present study, the efficacy of multi-scale photoacoustic microscopy (PAM) was investigated to detect, map, and quantify trace amounts [nanograms (ng) to micrograms (µg)] of SWCNTs in a variety of histological tissue specimens consisting of cancer and benign tissue biopsies (histological specimens from implanted tissue engineering scaffolds). Optical-resolution (OR) and acoustic-resolution (AR)--Photoacoustic microscopy (PAM) was employed to detect, map and quantify the SWCNTs in a variety of tissue histological specimens and compared with other optical techniques (bright-field optical microscopy, Raman microscopy, near infrared (NIR) fluorescence microscopy). Both optical-resolution and acoustic-resolution PAM, allow the detection and quantification of SWCNTs in histological specimens with scalable spatial resolution and depth penetration. The noise-equivalent detection sensitivity to SWCNTs in the specimens was calculated to be as low as ∼7 pg. Image processing analysis further allowed the mapping, distribution, and quantification of the SWCNTs in the histological sections. The results demonstrate the potential of PAM as a promising imaging technique to detect, map, and quantify SWCNTs in histological specimens, and could complement the capabilities of current optical and electron microscopy techniques in the analysis of histological specimens containing SWCNTs.

FIGO stage IIIC endometrial cancer identification among patients with complex atypical hyperplasia, grade 1 and 2 endometrioid endometrial cancer: laparoscopic indocyanine green sentinel lymph node mapping versus frozen section of the uterus, why get around the problem?

PubMed

Papadia, Andrea; Gasparri, Maria Luisa; Siegenthaler, Franziska; Imboden, Sara; Mohr, Stefan; Mueller, Michael D

2017-03-01

To compare two surgical strategies used to identify lymph node metastases in patients with preoperative diagnosis of complex atypical hyperplasia (CAH), grade 1 and 2 endometrial cancer (EC). Data on patients with preoperative diagnosis of CAH, grade 1 and 2 EC undergoing laparoscopic indocyanine green (ICG) sentinel lymph node (SLN) mapping followed by frozen section of the uterus were collected. When risk factors were identified at frozen section, patients were subjected to a systematic lymphadenectomy. False negative (FN) rates, negative predictive values (NPV), positive predictive values (PPV) and correlation with stage IIIC EC were calculated for the systematic lymphadenectomy based on frozen section of the uterus and for the SLN mapping. Six (9.5%) out of 63 patients had lymph nodal metastases. Based on frozen section of the uterus, 22 (34.9%) and 15 (22.2%) patients underwent a pelvic and a pelvic and paraaortic lymphadenectomy, respectively. Five patients with stage IIIC disease were identified with a FN rate of 16.7% and a NPV and PPV of 97.6 and 27.3%, respectively. Overall and bilateral detection rates of ICG SLN mapping were 100 and 97.6%, respectively; no FN were recorded. The identification of patients with stage IIIC disease with ICG SLN mapping showed a NPV and PPV of 100%. Correlation between indication to lymphadenectomy and stage IIIC disease was poor (κ = 0.244) when based on frozen section of the uterus and excellent (κ = 1) when based on SLN mapping. ICG SLN mapping reduces the number of unnecessary systematic lymphadenectomies and the risk of underdiagnosing patients with metastatic lymph nodes.

Mapping of QTL for bacterial cold water disease resistance in rainbow trout

USDA-ARS?s Scientific Manuscript database

Bacterial cold water disease (BCWD) causes significant economic loss in salmonids aquaculture. We previously detected genetic variation in survival following challenge with Flavobacterium psychrophilum (Fp), the causative agent of BCWD in rainbow trout, and a family-based selection program to impro...

A statistical study on seismo-ionospheric precursors in the total electron content of global ionosphere map associated with M×6.0 earthquakes in the West Pacific region during 1998-2012

NASA Astrophysics Data System (ADS)

Liu, Jann-Yenq; Chen, Koichi; Tsai, Ho-Fang; Hattori, Katsumi; Le, Huijun

2013-04-01

This paper reports statistical results of seismo-ionospheric precursors (SIPs) of the total electron content (TEC) in the global ionosphere map (GIM) over the epicenter of earthquakes with magnitude 6 and greater in China, Japan, and Taiwan during 1998-2012. To detect SIP, a quartile-based (i.e. median-based) process is performed. The earthquakes are sub-divided into various regions to have a better understanding on SIP characteristics, as well as examined with and without being led by magnetic storms to confirm the SIP existence. Results show that the SIPs mainly are the TEC significant increase in Japan, and decrease in Taiwan and China, respectively, which suggests the latitudinal effect playing an important role. Meanwhile, for a practical application of monitoring SIPs, the GIM TEC at a fixed point is tested. Results show that multi monitoring points and/or a spatial observation are required to enhance the SIP detection.

Road displacement model based on structural mechanics

NASA Astrophysics Data System (ADS)

Lu, Xiuqin; Guo, Qingsheng; Zhang, Yi

2006-10-01

Spatial conflict resolution is an important part of cartographic generalization, and it can deal with the problems of having too much information competing for too little space, while feature displacement is a primary operator of map generalization, which aims at resolving the spatial conflicts between neighbor objects especially road features. Considering the road object, this paper explains an idea of displacement based on structural mechanics. In view of spatial conflict problem after road symbolization, it is the buffer zones that are used to detect conflicts, then we focus on each conflicting region, with the finite element method, taking every triangular element for analysis, listing stiffness matrix, gathering system equations and calculating with iteration strategy, and we give the solution to road symbol conflicts. Being like this until all the conflicts in conflicting regions are solved, then we take the whole map into consideration again, conflicts are detected by reusing the buffer zones and solved by displacement operator, so as to all of them are handled.

Investigation of an Optimum Detection Scheme for a Star-Field Mapping System

NASA Technical Reports Server (NTRS)

Aldridge, M. D.; Credeur, L.

1970-01-01

An investigation was made to determine the optimum detection scheme for a star-field mapping system that uses coded detection resulting from starlight shining through specially arranged multiple slits of a reticle. The computer solution of equations derived from a theoretical model showed that the greatest probability of detection for a given star and background intensity occurred with the use of a single transparent slit. However, use of multiple slits improved the system's ability to reject the detection of undesirable lower intensity stars, but only by decreasing the probability of detection for lower intensity stars to be mapped. Also, it was found that the coding arrangement affected the root-mean-square star-position error and that detection is possible with error in the system's detected spin rate, though at a reduced probability.

Segmentation of singularity maps in the context of soil porosity

NASA Astrophysics Data System (ADS)

Martin-Sotoca, Juan J.; Saa-Requejo, Antonio; Grau, Juan; Tarquis, Ana M.

2016-04-01

Geochemical exploration have found with increasingly interests and benefits of using fractal (power-law) models to characterize geochemical distribution, including concentration-area (C-A) model (Cheng et al., 1994; Cheng, 2012) and concentration-volume (C-V) model (Afzal et al., 2011) just to name a few examples. These methods are based on the singularity maps of a measure that at each point define areas with self-similar properties that are shown in power-law relationships in Concentration-Area plots (C-A method). The C-A method together with the singularity map ("Singularity-CA" method) define thresholds that can be applied to segment the map. Recently, the "Singularity-CA" method has been applied to binarize 2D grayscale Computed Tomography (CT) soil images (Martin-Sotoca et al, 2015). Unlike image segmentation based on global thresholding methods, the "Singularity-CA" method allows to quantify the local scaling property of the grayscale value map in the space domain and determinate the intensity of local singularities. It can be used as a high-pass-filter technique to enhance high frequency patterns usually regarded as anomalies when applied to maps. In this work we will put special attention on how to select the singularity thresholds in the C-A plot to segment the image. We will compare two methods: 1) cross point of linear regressions and 2) Wavelets Transform Modulus Maxima (WTMM) singularity function detection. REFERENCES Cheng, Q., Agterberg, F. P. and Ballantyne, S. B. (1994). The separation of geochemical anomalies from background by fractal methods. Journal of Geochemical Exploration, 51, 109-130. Cheng, Q. (2012). Singularity theory and methods for mapping geochemical anomalies caused by buried sources and for predicting undiscovered mineral deposits in covered areas. Journal of Geochemical Exploration, 122, 55-70. Afzal, P., Fadakar Alghalandis, Y., Khakzad, A., Moarefvand, P. and Rashidnejad Omran, N. (2011) Delineation of mineralization zones in porphyry Cu deposits by fractal concentration-volume modeling. Journal of Geochemical Exploration, 108, 220-232. Martín-Sotoca, J. J., Tarquis, A. M., Saa-Requejo, A. and Grau, J. B. (2015). Pore detection in Computed Tomography (CT) soil images through singularity map analysis. Oral Presentation in PedoFract VIII Congress (June, La Coruña - Spain).

Applications of remote sensor data by state and Federal user agencies in Arizona

NASA Technical Reports Server (NTRS)

Schumann, H. H.

1972-01-01

The use of NASA high altitude aerial photography of south eastern Arizona to develop a natural resources information system for Federal lands is discussed. The data are to be used by local, State, and Federal agencies in connection with geologic mapping projects, water resources investigations, and land use studies to determine the alignment of a proposed major aqueduct. In addition, the data are used to confirm land ownership boundaries, detect changes in land use, and legislative reappointment mapping. Other applications include mapping vegetive cover, evaluation of changes in wildlife habitat, location of deer kills, and as a base for recording telemetry data from radio-collared big game animals.

Spectroscopy of Mars Atmosphere from Orbiting and Ground-based Observatories: Recent Results and Implications for Evolution

NASA Astrophysics Data System (ADS)

Krasnopolsky, V. A.

2003-07-01

This is a review of the ground-based and Earth-orbiting studies of Mars atmosphere in the last decade that resulted in the detections of HDO, D, H2, He, and detailed mapping of O3, O2(delta), and CO. These studies provide new insights on the history of volatiles and climate on Mars.

Comparative genome-wide mapping versus extreme pool-genotyping and development of diagnostic SNP markers linked to QTL for adult plant resistance to stripe rust in common wheat.

PubMed

Wu, Jianhui; Huang, Shuo; Zeng, Qingdong; Liu, Shengjie; Wang, Qilin; Mu, Jingmei; Yu, Shizhou; Han, Dejun; Kang, Zhensheng

2018-06-16

A major stripe rust resistance QTL on chromosome 4BL was localized to a 4.5-Mb interval using comparative QTL mapping methods and validated in 276 wheat genotypes by haplotype analysis. CYMMIT-derived wheat line P10103 was previously identified to have adult plant resistance (APR) to stripe rust in the greenhouse and field. The conventional approach for QTL mapping in common wheat is laborious. Here, we performed QTL detection of APR using a combination of genome-wide scanning and extreme pool-genotyping. SNP-based genetic maps were constructed using the Wheat55 K SNP array to genotype a recombinant inbred line (RIL) population derived from the cross Mingxian 169 × P10103. Five stable QTL were detected across multiple environments. A fter comparing SNP profiles from contrasting, extreme DNA pools of RILs six putative QTL were located to approximate chromosome positions. A major QTL on chromosome 4B was identified in F 2:4 contrasting pools from cross Zhengmai 9023 × P10103. A consensus QTL (LOD = 26-40, PVE = 42-55%), named QYr.nwafu-4BL, was defined and localized to a 4.5-Mb interval flanked by SNP markers AX-110963704 and AX-110519862 in chromosome arm 4BL. Based on stripe rust response, marker genotypes, pedigree analysis and mapping data, QYr.nwafu-4BL is likely to be a new APR QTL. The applicability of the SNP-based markers flanking QYr.nwafu-4BL was validated on a diversity panel of 276 wheat lines. The additional minor QTL on chromosomes 4A, 5A, 5B and 6A enhanced the level of resistance conferred by QYr.nwafu-4BL. Marker-assisted pyramiding of QYr.nwafu-4BL and other favorable minor QTL in new wheat cultivars should improve the level of APR to stripe rust.

A new automatic SAR-based flood mapping application hosted on the European Space Agency's grid processing on demand fast access to imagery environment

NASA Astrophysics Data System (ADS)

Hostache, Renaud; Chini, Marco; Matgen, Patrick; Giustarini, Laura

2013-04-01

There is a clear need for developing innovative processing chains based on earth observation (EO) data to generate products supporting emergency response and flood management at a global scale. Here an automatic flood mapping application is introduced. The latter is currently hosted on the Grid Processing on Demand (G-POD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver flooded areas using both recent and historical acquisitions of SAR data in an operational framework. It is worth mentioning that the method can be applied to both medium and high resolution SAR images. The flood mapping application consists of two main blocks: 1) A set of query tools for selecting the "crisis image" and the optimal corresponding pre-flood "reference image" from the G-POD archive. 2) An algorithm for extracting flooded areas using the previously selected "crisis image" and "reference image". The proposed method is a hybrid methodology, which combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Change detection with respect to a pre-flood reference image helps reducing over-detection of inundated areas. The algorithms are computationally efficient and operate with minimum data requirements, considering as input data a flood image and a reference image. Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate pre-flood reference image. Potential users will also be able to apply the implemented flood delineation algorithm. Case studies of several recent high magnitude flooding events (e.g. July 2007 Severn River flood, UK and March 2010 Red River flood, US) observed by high-resolution SAR sensors as well as airborne photography highlight advantages and limitations of the online application. A mid-term target is the exploitation of ESA SENTINEL 1 SAR data streams. In the long term it is foreseen to develop a potential extension of the application for systematically extracting flooded areas from all SAR images acquired on a daily, weekly or monthly basis. On-going research activities investigate the usefulness of the method for mapping flood hazard at global scale using databases of historic SAR remote sensing-derived flood inundation maps.

Mapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer’s disease, mild cognitive impairment and elderly controls

PubMed Central

Chou, Yi-Yu; Leporé, Natasha; Avedissian, Christina; Madsen, Sarah K.; Parikshak, Neelroop; Hua, Xue; Shaw, Leslie M.; Trojanowski, John Q.; Weiner, Michael W.; Toga, Arthur W.; Thompson, Paul M.

2009-01-01

Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer’s disease, NeuroImage 40(2): 615–630); with this method, we calculated minimal numbers of subjects needed to detect correlations between clinical scores and ventricular maps. We also assessed correlations between emerging CSF biomarkers of Alzheimer’s disease pathology and localizable deficits in the brain, in 80 AD, 80 mild cognitive impairment (MCI), and 80 healthy controls from the Alzheimer’s Disease Neuroimaging Initiative. Six expertly segmented images and their embedded parametric mesh surfaces were fluidly registered to each brain; segmentations were averaged within subjects to reduce errors. Surface-based statistical maps revealed powerful correlations between surface morphology and 4 variables: (1) diagnosis, (2) depression severity, (3) cognitive function at baseline, and (4) future cognitive decline over the following year. Cognitive function was assessed using the mini-mental state exam (MMSE), global and sum-of-boxes clinical dementia rating (CDR) scores, at baseline and 1-year follow-up. Lower CSF Aβ1–42 protein levels, a biomarker of AD pathology assessed in 138 of the 240 subjects, were correlated with lateral ventricular expansion. Using false discovery rate (FDR) methods, 40 and 120 subjects, respectively, were needed to discriminate AD and MCI from normal groups. 120 subjects were required to detect correlations between ventricular enlargement and MMSE, global CDR, sum-of-boxes CDR and clinical depression scores. Ventricular expansion maps correlate with pathological and cognitive measures in AD, and may be useful in future imaging-based clinical trials. PMID:19236926

Automated matching of multiple terrestrial laser scans for stem mapping without the use of artificial references

NASA Astrophysics Data System (ADS)

Liu, Jingbin; Liang, Xinlian; Hyyppä, Juha; Yu, Xiaowei; Lehtomäki, Matti; Pyörälä, Jiri; Zhu, Lingli; Wang, Yunsheng; Chen, Ruizhi

2017-04-01

Terrestrial laser scanning has been widely used to analyze the 3D structure of a forest in detail and to generate data at the level of a reference plot for forest inventories without destructive measurements. Multi-scan terrestrial laser scanning is more commonly applied to collect plot-level data so that all of the stems can be detected and analyzed. However, it is necessary to match the point clouds of multiple scans to yield a point cloud with automated processing. Mismatches between datasets will lead to errors during the processing of multi-scan data. Classic registration methods based on flat surfaces cannot be directly applied in forest environments; therefore, artificial reference objects have conventionally been used to assist with scan matching. The use of artificial references requires additional labor and expertise, as well as greatly increasing the cost. In this study, we present an automated processing method for plot-level stem mapping that matches multiple scans without artificial references. In contrast to previous studies, the registration method developed in this study exploits the natural geometric characteristics among a set of tree stems in a plot and combines the point clouds of multiple scans into a unified coordinate system. Integrating multiple scans improves the overall performance of stem mapping in terms of the correctness of tree detection, as well as the bias and the root-mean-square errors of forest attributes such as diameter at breast height and tree height. In addition, the automated processing method makes stem mapping more reliable and consistent among plots, reduces the costs associated with plot-based stem mapping, and enhances the efficiency.

Automated detection of snow avalanche deposits: segmentation and classification of optical remote sensing imagery

NASA Astrophysics Data System (ADS)

Lato, M. J.; Frauenfelder, R.; Bühler, Y.

2012-09-01

Snow avalanches in mountainous areas pose a significant threat to infrastructure (roads, railways, energy transmission corridors), personal property (homes) and recreational areas as well as for lives of people living and moving in alpine terrain. The impacts of snow avalanches range from delays and financial loss through road and railway closures, destruction of property and infrastructure, to loss of life. Avalanche warnings today are mainly based on meteorological information, snow pack information, field observations, historically recorded avalanche events as well as experience and expert knowledge. The ability to automatically identify snow avalanches using Very High Resolution (VHR) optical remote sensing imagery has the potential to assist in the development of accurate, spatially widespread, detailed maps of zones prone to avalanches as well as to build up data bases of past avalanche events in poorly accessible regions. This would provide decision makers with improved knowledge of the frequency and size distributions of avalanches in such areas. We used an object-oriented image interpretation approach, which employs segmentation and classification methodologies, to detect recent snow avalanche deposits within VHR panchromatic optical remote sensing imagery. This produces avalanche deposit maps, which can be integrated with other spatial mapping and terrain data. The object-oriented approach has been tested and validated against manually generated maps in which avalanches are visually recognized and digitized. The accuracy (both users and producers) are over 0.9 with errors of commission less than 0.05. Future research is directed to widespread testing of the algorithm on data generated by various sensors and improvement of the algorithm in high noise regions as well as the mapping of avalanche paths alongside their deposits.

Detection and mapping of illicit drugs and their metabolites in fingermarks by MALDI MS and compatibility with forensic techniques

NASA Astrophysics Data System (ADS)

Groeneveld, G.; de Puit, M.; Bleay, S.; Bradshaw, R.; Francese, S.

2015-06-01

Despite the proven capabilities of Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS) in laboratory settings, research is still needed to integrate this technique into current forensic fingerprinting practice. Optimised protocols enabling the compatible application of MALDI to developed fingermarks will allow additional intelligence to be gathered around a suspect’s lifestyle and activities prior to the deposition of their fingermarks while committing a crime. The detection and mapping of illicit drugs and metabolites in latent fingermarks would provide intelligence that is beneficial for both police investigations and court cases. This study investigated MALDI MS detection and mapping capabilities for a large range of drugs of abuse and their metabolites in fingermarks; the detection and mapping of a mixture of these drugs in marks, with and without prior development with cyanoacrylate fuming or Vacuum Metal Deposition, was also examined. Our findings indicate the versatility of MALDI technology and its ability to retrieve chemical intelligence either by detecting the compounds investigated or by using their ion signals to reconstruct 2D maps of fingermark ridge details.