A new method of small target detection based on neural network

NASA Astrophysics Data System (ADS)

Hu, Jing; Hu, Yongli; Lu, Xinxin

2018-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array.

PubMed

Li, Miao; Li, Jun; Zhou, Yiyu

2015-12-08

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts-MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array

PubMed Central

Li, Miao; Li, Jun; Zhou, Yiyu

2015-01-01

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts—MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing. PMID:26670234

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.

Salient target detection based on pseudo-Wigner-Ville distribution and Rényi entropy.

PubMed

Xu, Yuannan; Zhao, Yuan; Jin, Chenfei; Qu, Zengfeng; Liu, Liping; Sun, Xiudong

2010-02-15

We present what we believe to be a novel method based on pseudo-Wigner-Ville distribution (PWVD) and Rényi entropy for salient targets detection. In the foundation of studying the statistical property of Rényi entropy via PWVD, the residual entropy-based saliency map of an input image can be obtained. From the saliency map, target detection is completed by the simple and convenient threshold segmentation. Experimental results demonstrate the proposed method can detect targets effectively in complex ground scenes.

Research on Aircraft Target Detection Algorithm Based on Improved Radial Gradient Transformation

NASA Astrophysics Data System (ADS)

Zhao, Z. M.; Gao, X. M.; Jiang, D. N.; Zhang, Y. Q.

2018-04-01

Aiming at the problem that the target may have different orientation in the unmanned aerial vehicle (UAV) image, the target detection algorithm based on the rotation invariant feature is studied, and this paper proposes a method of RIFF (Rotation-Invariant Fast Features) based on look up table and polar coordinate acceleration to be used for aircraft target detection. The experiment shows that the detection performance of this method is basically equal to the RIFF, and the operation efficiency is greatly improved.

Development and validation of a 48-target analytical method for high-throughput monitoring of genetically modified organisms.

PubMed

Li, Xiaofei; Wu, Yuhua; Li, Jun; Li, Yunjing; Long, Likun; Li, Feiwu; Wu, Gang

2015-01-05

The rapid increase in the number of genetically modified (GM) varieties has led to a demand for high-throughput methods to detect genetically modified organisms (GMOs). We describe a new dynamic array-based high throughput method to simultaneously detect 48 targets in 48 samples on a Fludigm system. The test targets included species-specific genes, common screening elements, most of the Chinese-approved GM events, and several unapproved events. The 48 TaqMan assays successfully amplified products from both single-event samples and complex samples with a GMO DNA amount of 0.05 ng, and displayed high specificity. To improve the sensitivity of detection, a preamplification step for 48 pooled targets was added to enrich the amount of template before performing dynamic chip assays. This dynamic chip-based method allowed the synchronous high-throughput detection of multiple targets in multiple samples. Thus, it represents an efficient, qualitative method for GMO multi-detection.

Development and Validation of A 48-Target Analytical Method for High-throughput Monitoring of Genetically Modified Organisms

PubMed Central

Li, Xiaofei; Wu, Yuhua; Li, Jun; Li, Yunjing; Long, Likun; Li, Feiwu; Wu, Gang

2015-01-01

The rapid increase in the number of genetically modified (GM) varieties has led to a demand for high-throughput methods to detect genetically modified organisms (GMOs). We describe a new dynamic array-based high throughput method to simultaneously detect 48 targets in 48 samples on a Fludigm system. The test targets included species-specific genes, common screening elements, most of the Chinese-approved GM events, and several unapproved events. The 48 TaqMan assays successfully amplified products from both single-event samples and complex samples with a GMO DNA amount of 0.05 ng, and displayed high specificity. To improve the sensitivity of detection, a preamplification step for 48 pooled targets was added to enrich the amount of template before performing dynamic chip assays. This dynamic chip-based method allowed the synchronous high-throughput detection of multiple targets in multiple samples. Thus, it represents an efficient, qualitative method for GMO multi-detection. PMID:25556930

Camouflage target detection via hyperspectral imaging plus information divergence measurement

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

Research on infrared ship detection method in sea-sky background

NASA Astrophysics Data System (ADS)

Tang, Da; Sun, Gang; Wang, Ding-he; Niu, Zhao-dong; Chen, Zeng-ping

2013-09-01

An approach to infrared ship detection based on sea-sky-line(SSL) detection, ROI extraction and feature recognition is proposed in this paper. Firstly, considering that far ships are expected to be adjacent to the SSL, SSL is detected to find potential target areas. Radon transform is performed on gradient image to choose candidate SSLs, and detection result is given by fuzzy synthetic evaluation values. Secondly, in view of recognizable condition that there should be enough differences between target and background in infrared image, two gradient masks have been created and improved as practical guidelines in eliminating false alarm. Thirdly, extract ROI near the SSL by using multi-grade segmentation and fusion method after image sharpening, and unsuitable candidates are screened out according to the gradient masks and ROI shape. Finally, we segment the rest of ROIs by two-stage modified OTSU, and calculate target confidence as a standard measuring the facticity of target. Compared with other ship detection methods, proposed method is suitable for bipolar targets, which offers a good practicability and accuracy, and achieves a satisfying detection speed. Detection experiments with 200 thousand frames show that the proposed method is widely applicable, powerful in resistance to interferences and noises with a detection rate of above 95%, which satisfies the engineering needs commendably.

Scan statistics with local vote for target detection in distributed system

NASA Astrophysics Data System (ADS)

Luo, Junhai; Wu, Qi

2017-12-01

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

Detection and isolation of nucleic acid sequences using competitive hybridization probes

DOEpatents

Lucas, Joe N.; Straume, Tore; Bogen, Kenneth T.

1997-01-01

A method for detecting a target nucleic acid sequence in a sample is provided using hybridization probes which competitively hybridize to a target nucleic acid. According to the method, a target nucleic acid sequence is hybridized to first and second hybridization probes which are complementary to overlapping portions of the target nucleic acid sequence, the first hybridization probe including a first complexing agent capable of forming a binding pair with a second complexing agent and the second hybridization probe including a detectable marker. The first complexing agent attached to the first hybridization probe is contacted with a second complexing agent, the second complexing agent being attached to a solid support such that when the first and second complexing agents are attached, target nucleic acid sequences hybridized to the first hybridization probe become immobilized on to the solid support. The immobilized target nucleic acids are then separated and detected by detecting the detectable marker attached to the second hybridization probe. A kit for performing the method is also provided.

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

PubMed

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

2012-01-01

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

Detection and isolation of nucleic acid sequences using competitive hybridization probes

DOEpatents

Lucas, J.N.; Straume, T.; Bogen, K.T.

1997-04-01

A method for detecting a target nucleic acid sequence in a sample is provided using hybridization probes which competitively hybridize to a target nucleic acid. According to the method, a target nucleic acid sequence is hybridized to first and second hybridization probes which are complementary to overlapping portions of the target nucleic acid sequence, the first hybridization probe including a first complexing agent capable of forming a binding pair with a second complexing agent and the second hybridization probe including a detectable marker. The first complexing agent attached to the first hybridization probe is contacted with a second complexing agent, the second complexing agent being attached to a solid support such that when the first and second complexing agents are attached, target nucleic acid sequences hybridized to the first hybridization probe become immobilized on to the solid support. The immobilized target nucleic acids are then separated and detected by detecting the detectable marker attached to the second hybridization probe. A kit for performing the method is also provided. 7 figs.

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing.

PubMed

Li, Jun; Lin, Qiu-Hua; Kang, Chun-Yu; Wang, Kai; Yang, Xiu-Ting

2018-03-18

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets.

Moving target detection method based on improved Gaussian mixture model

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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

NASA Astrophysics Data System (ADS)

Zhang, Mo; Jin, Weiqi; Li, Li

2016-10-01

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

A long-term target detection approach in infrared image sequence

NASA Astrophysics Data System (ADS)

Li, Hang; Zhang, Qi; Wang, Xin; Hu, Chao

2016-10-01

An automatic target detection method used in long term infrared (IR) image sequence from a moving platform is proposed. Firstly, based on POME(the principle of maximum entropy), target candidates are iteratively segmented. Then the real target is captured via two different selection approaches. At the beginning of image sequence, the genuine target with litter texture is discriminated from other candidates by using contrast-based confidence measure. On the other hand, when the target becomes larger, we apply online EM method to estimate and update the distributions of target's size and position based on the prior detection results, and then recognize the genuine one which satisfies both the constraints of size and position. Experimental results demonstrate that the presented method is accurate, robust and efficient.

Method for remote detection of trace contaminants

DOEpatents

Simonson, Robert J.; Hance, Bradley G.

2003-09-09

A method for remote detection of trace contaminants in a target area comprises applying sensor particles that preconcentrate the trace contaminant to the target area and detecting the contaminant-sensitive fluorescence from the sensor particles. The sensor particles can have contaminant-sensitive and contaminant-insensitive fluorescent compounds to enable the determination of the amount of trace contaminant present in the target are by relative comparison of the emission of the fluorescent compounds by a local or remote fluorescence detector. The method can be used to remotely detect buried minefields.

Detection and identification of human targets in radar data

NASA Astrophysics Data System (ADS)

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

2007-04-01

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

Complex background suppression using global-local registration strategy for the detection of small-moving target on moving platform

NASA Astrophysics Data System (ADS)

Zou, Tianhao; Zuo, Zhengrong

2018-02-01

Target detection is a very important and basic problem of computer vision and image processing. The most often case we meet in real world is a detection task for a moving-small target on moving platform. The commonly used methods, such as Registration-based suppression, can hardly achieve a desired result. To crack this hard nut, we introduce a Global-local registration based suppression method. Differ from the traditional ones, the proposed Global-local Registration Strategy consider both the global consistency and the local diversity of the background, obtain a better performance than normal background suppression methods. In this paper, we first discussed the features about the small-moving target detection on unstable platform. Then we introduced a new strategy and conducted an experiment to confirm its noisy stability. In the end, we confirmed the background suppression method based on global-local registration strategy has a better perform in moving target detection on moving platform.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Improving detection of low SNR targets using moment-based detection

NASA Astrophysics Data System (ADS)

Young, Shannon R.; Steward, Bryan J.; Hawks, Michael; Gross, Kevin C.

2016-05-01

Increases in the number of cameras deployed, frame rate, and detector array sizes have led to a dramatic increase in the volume of motion imagery data that is collected. Without a corresponding increase in analytical manpower, much of the data is not analyzed to full potential. This creates a need for fast, automated, and robust methods for detecting signals of interest. Current approaches fall into two categories: detect-before-track (DBT), which are fast but often poor at detecting dim targets, and track-before-detect (TBD) methods which can offer better performance but are typically much slower. This research seeks to contribute to the near real time detection of low SNR, unresolved moving targets through an extension of earlier work on higher order moments anomaly detection, a method that exploits both spatial and temporal information but is still computationally efficient and massively parallelizable. It was found that intelligent selection of parameters can improve probability of detection by as much as 25% compared to earlier work with higherorder moments. The present method can reduce detection thresholds by 40% compared to the Reed-Xiaoli anomaly detector for low SNR targets (for a given probability of detection and false alarm).

Applying the Multiple Signal Classification Method to Silent Object Detection Using Ambient Noise

NASA Astrophysics Data System (ADS)

Mori, Kazuyoshi; Yokoyama, Tomoki; Hasegawa, Akio; Matsuda, Minoru

2004-05-01

The revolutionary concept of using ocean ambient noise positively to detect objects, called acoustic daylight imaging, has attracted much attention. The authors attempted the detection of a silent target object using ambient noise and a wide-band beam former consisting of an array of receivers. In experimental results obtained in air, using the wide-band beam former, we successfully applied the delay-sum array (DSA) method to detect a silent target object in an acoustic noise field generated by a large number of transducers. This paper reports some experimental results obtained by applying the multiple signal classification (MUSIC) method to a wide-band beam former to detect silent targets. The ocean ambient noise was simulated by transducers decentralized to many points in air. Both MUSIC and DSA detected a spherical target object in the noise field. The relative power levels near the target obtained with MUSIC were compared with those obtained by DSA. Then the effectiveness of the MUSIC method was evaluated according to the rate of increase in the maximum and minimum relative power levels.

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

NASA Astrophysics Data System (ADS)

Zhang, He; Niu, Yanxiong; Zhang, Hao

2017-12-01

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

Faint Debris Detection by Particle Based Track-Before-Detect Method

NASA Astrophysics Data System (ADS)

Uetsuhara, M.; Ikoma, N.

2014-09-01

This study proposes a particle method to detect faint debris, which is hardly seen in single frame, from an image sequence based on the concept of track-before-detect (TBD). The most widely used detection method is detect-before-track (DBT), which firstly detects signals of targets from single frame by distinguishing difference of intensity between foreground and background then associate the signals for each target between frames. DBT is capable of tracking bright targets but limited. DBT is necessary to consider presence of false signals and is difficult to recover from false association. On the other hand, TBD methods try to track targets without explicitly detecting the signals followed by evaluation of goodness of each track and obtaining detection results. TBD has an advantage over DBT in detecting weak signals around background level in single frame. However, conventional TBD methods for debris detection apply brute-force search over candidate tracks then manually select true one from the candidates. To reduce those significant drawbacks of brute-force search and not-fully automated process, this study proposes a faint debris detection algorithm by a particle based TBD method consisting of sequential update of target state and heuristic search of initial state. The state consists of position, velocity direction and magnitude, and size of debris over the image at a single frame. The sequential update process is implemented by a particle filter (PF). PF is an optimal filtering technique that requires initial distribution of target state as a prior knowledge. An evolutional algorithm (EA) is utilized to search the initial distribution. The EA iteratively applies propagation and likelihood evaluation of particles for the same image sequences and resulting set of particles is used as an initial distribution of PF. This paper describes the algorithm of the proposed faint debris detection method. The algorithm demonstrates performance on image sequences acquired during observation campaigns dedicated to GEO breakup fragments, which would contain a sufficient number of faint debris images. The results indicate the proposed method is capable of tracking faint debris with moderate computational costs at operational level.

Appraisal of an Array TEM Method in Detecting a Mined-Out Area Beneath a Conductive Layer

NASA Astrophysics Data System (ADS)

Li, Hai; Xue, Guo-qiang; Zhou, Nan-nan; Chen, Wei-ying

2015-10-01

The transient electromagnetic method has been extensively used for the detection of mined-out area in China for the past few years. In the cases that the mined-out area is overlain by a conductive layer, the detection of the target layer is difficult with a traditional loop source TEM method. In order to detect the target layer in this condition, this paper presents a newly developed array TEM method, which uses a grounded wire source. The underground current density distribution and the responses of the grounded wire source TEM configuration are modeled to demonstrate that the target layer is detectable in this condition. The 1D OCCAM inversion routine is applied to the synthetic single station data and common middle point gather. The result reveals that the electric source TEM method is capable of recovering the resistive target layer beneath the conductive overburden. By contrast, the conductive target layer cannot be recovered unless the distance between the target layer and the conductive overburden is large. Compared with inversion result of the single station data, the inversion of common middle point gather can better recover the resistivity of the target layer. Finally, a case study illustrates that the array TEM method is successfully applied in recovering a water-filled mined-out area beneath a conductive overburden.

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing

PubMed Central

2018-01-01

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets. PMID:29562642

Detection and isolation of nucleic acid sequences using a bifunctional hybridization probe

DOEpatents

Lucas, Joe N.; Straume, Tore; Bogen, Kenneth T.

2000-01-01

A method for detecting and isolating a target sequence in a sample of nucleic acids is provided using a bifunctional hybridization probe capable of hybridizing to the target sequence that includes a detectable marker and a first complexing agent capable of forming a binding pair with a second complexing agent. A kit is also provided for detecting a target sequence in a sample of nucleic acids using a bifunctional hybridization probe according to this method.

Initial study of Schroedinger eigenmaps for spectral target detection

NASA Astrophysics Data System (ADS)

Dorado-Munoz, Leidy P.; Messinger, David W.

2016-08-01

Spectral target detection refers to the process of searching for a specific material with a known spectrum over a large area containing materials with different spectral signatures. Traditional target detection methods in hyperspectral imagery (HSI) require assuming the data fit some statistical or geometric models and based on the model, to estimate parameters for defining a hypothesis test, where one class (i.e., target class) is chosen over the other classes (i.e., background class). Nonlinear manifold learning methods such as Laplacian eigenmaps (LE) have extensively shown their potential use in HSI processing, specifically in classification or segmentation. Recently, Schroedinger eigenmaps (SE), which is built upon LE, has been introduced as a semisupervised classification method. In SE, the former Laplacian operator is replaced by the Schroedinger operator. The Schroedinger operator includes by definition, a potential term V that steers the transformation in certain directions improving the separability between classes. In this regard, we propose a methodology for target detection that is not based on the traditional schemes and that does not need the estimation of statistical or geometric parameters. This method is based on SE, where the potential term V is taken into consideration to include the prior knowledge about the target class and use it to steer the transformation in directions where the target location in the new space is known and the separability between target and background is augmented. An initial study of how SE can be used in a target detection scheme for HSI is shown here. In-scene pixel and spectral signature detection approaches are presented. The HSI data used comprise various target panels for testing simultaneous detection of multiple objects with different complexities.

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

PubMed

Huang, Dayu; Xue, Anke; Guo, Yunfei

2012-01-01

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

Detection of proteins using a colorimetric bio-barcode assay.

PubMed

Nam, Jwa-Min; Jang, Kyung-Jin; Groves, Jay T

2007-01-01

The colorimetric bio-barcode assay is a red-to-blue color change-based protein detection method with ultrahigh sensitivity. This assay is based on both the bio-barcode amplification method that allows for detecting miniscule amount of targets with attomolar sensitivity and gold nanoparticle-based colorimetric DNA detection method that allows for a simple and straightforward detection of biomolecules of interest (here we detect interleukin-2, an important biomarker (cytokine) for many immunodeficiency-related diseases and cancers). The protocol is composed of the following steps: (i) conjugation of target capture molecules and barcode DNA strands onto silica microparticles, (ii) target capture with probes, (iii) separation and release of barcode DNA strands from the separated probes, (iv) detection of released barcode DNA using DNA-modified gold nanoparticle probes and (v) red-to-blue color change analysis with a graphic software. Actual target detection and quantification steps with premade probes take approximately 3 h (whole protocol including probe preparations takes approximately 3 days).

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

PubMed

Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

PubMed Central

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

Image change detection systems, methods, and articles of manufacture

DOEpatents

Jones, James L.; Lassahn, Gordon D.; Lancaster, Gregory D.

2010-01-05

Aspects of the invention relate to image change detection systems, methods, and articles of manufacture. According to one aspect, a method of identifying differences between a plurality of images is described. The method includes loading a source image and a target image into memory of a computer, constructing source and target edge images from the source and target images to enable processing of multiband images, displaying the source and target images on a display device of the computer, aligning the source and target edge images, switching displaying of the source image and the target image on the display device, to enable identification of differences between the source image and the target image.

Comparing scat detection dogs, cameras, and hair snares for surveying carnivores

USGS Publications Warehouse

Long, Robert A.; Donovan, T.M.; MacKay, Paula; Zielinski, William J.; Buzas, Jeffrey S.

2007-01-01

Carnivores typically require large areas of habitat, exist at low natural densities, and exhibit elusive behavior - characteristics that render them difficult to study. Noninvasive survey methods increasingly provide means to collect extensive data on carnivore occupancy, distribution, and abundance. During the summers of 2003-2004, we compared the abilities of scat detection dogs, remote cameras, and hair snares to detect black bears (Ursus americanus), fishers (Martes pennanti), and bobcats (Lynx rufus) at 168 sites throughout Vermont. All 3 methods detected black bears; neither fishers nor bobcats were detected by hair snares. Scat detection dogs yielded the highest raw detection rate and probability of detection (given presence) for each of the target species, as well as the greatest number of unique detections (i.e., occasions when only one method detected the target species). We estimated that the mean probability of detecting the target species during a single visit to a site with a detection dog was 0.87 for black bears, 0.84 for fishers, and 0.27 for bobcats. Although the cost of surveying with detection dogs was higher than that of remote cameras or hair snares, the efficiency of this method rendered it the most cost-effective survey method.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

A long-term target detection approach in infrared image sequence

NASA Astrophysics Data System (ADS)

Li, Hang; Zhang, Qi; Li, Yuanyuan; Wang, Liqiang

2015-12-01

An automatic target detection method used in long term infrared (IR) image sequence from a moving platform is proposed. Firstly, based on non-linear histogram equalization, target candidates are coarse-to-fine segmented by using two self-adapt thresholds generated in the intensity space. Then the real target is captured via two different selection approaches. At the beginning of image sequence, the genuine target with litter texture is discriminated from other candidates by using contrast-based confidence measure. On the other hand, when the target becomes larger, we apply online EM method to iteratively estimate and update the distributions of target's size and position based on the prior detection results, and then recognize the genuine one which satisfies both the constraints of size and position. Experimental results demonstrate that the presented method is accurate, robust and efficient.

Search by photo methodology for signature properties assessment by human observers

NASA Astrophysics Data System (ADS)

Selj, Gorm K.; Heinrich, Daniela H.

2015-05-01

Reliable, low-cost and simple methods for assessment of signature properties for military purposes are very important. In this paper we present such an approach that uses human observers in a search by photo assessment of signature properties of generic test targets. The method was carried out by logging a large number of detection times of targets recorded in relevant terrain backgrounds. The detection times were harvested by using human observers searching for targets in scene images shown by a high definition pc screen. All targets were identically located in each "search image", allowing relative comparisons (and not just rank by order) of targets. To avoid biased detections, each observer only searched for one target per scene. Statistical analyses were carried out for the detection times data. Analysis of variance was chosen if detection times distribution associated with all targets satisfied normality, and non-parametric tests, such as Wilcoxon's rank test, if otherwise. The new methodology allows assessment of signature properties in a reproducible, rapid and reliable setting. Such assessments are very complex as they must sort out what is of relevance in a signature test, but not loose information of value. We believe that choosing detection times as the primary variable for a comparison of signature properties, allows a careful and necessary inspection of observer data as the variable is continuous rather than discrete. Our method thus stands in opposition to approaches based on detections by subsequent, stepwise reductions in distance to target, or based on probability of detection.

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

PubMed

Nguyen, Van-Han; Pyun, Jae-Young

2015-03-19

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

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Heterogeneous CPU-GPU moving targets detection for UAV video

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Research on infrared dim-point target detection and tracking under sea-sky-line complex background

NASA Astrophysics Data System (ADS)

Dong, Yu-xing; Li, Yan; Zhang, Hai-bo

2011-08-01

Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system, the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties .There are some traditional point target detection algorithms, such as adaptive background prediction detecting method. When background has dispersion-decreasing structure, the traditional target detection algorithms would be more useful. But when the background has large gray gradient, such as sea-sky-line, sea waves etc .The bigger false-alarm rate will be taken in these local area .It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature ,in our opinion , from the perspective of mathematics, the detection of dim-point targets in image is about singular function analysis .And from the perspective image processing analysis , the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection, its essence is a separation of target and background of different singularity characteristics .The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore, the purpose of the image preprocessing is to reduce the effects from noise, also to raise the SNR of image, and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics , the median filter is used to eliminate noise, improve signal-to-noise ratio, then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line ,so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Applied Genomics: Data Mining Reveals Species-Specific Malaria Diagnostic Targets More Sensitive than 18S rRNA▿†‡

PubMed Central

Demas, Allison; Oberstaller, Jenna; DeBarry, Jeremy; Lucchi, Naomi W.; Srinivasamoorthy, Ganesh; Sumari, Deborah; Kabanywanyi, Abdunoor M.; Villegas, Leopoldo; Escalante, Ananias A.; Kachur, S. Patrick; Barnwell, John W.; Peterson, David S.; Udhayakumar, Venkatachalam; Kissinger, Jessica C.

2011-01-01

Accurate and rapid diagnosis of malaria infections is crucial for implementing species-appropriate treatment and saving lives. Molecular diagnostic tools are the most accurate and sensitive method of detecting Plasmodium, differentiating between Plasmodium species, and detecting subclinical infections. Despite available whole-genome sequence data for Plasmodium falciparum and P. vivax, the majority of PCR-based methods still rely on the 18S rRNA gene targets. Historically, this gene has served as the best target for diagnostic assays. However, it is limited in its ability to detect mixed infections in multiplex assay platforms without the use of nested PCR. New diagnostic targets are needed. Ideal targets will be species specific, highly sensitive, and amenable to both single-step and multiplex PCRs. We have mined the genomes of P. falciparum and P. vivax to identify species-specific, repetitive sequences that serve as new PCR targets for the detection of malaria. We show that these targets (Pvr47 and Pfr364) exist in 14 to 41 copies and are more sensitive than 18S rRNA when utilized in a single-step PCR. Parasites are routinely detected at levels of 1 to 10 parasites/μl. The reaction can be multiplexed to detect both species in a single reaction. We have examined 7 P. falciparum strains and 91 P. falciparum clinical isolates from Tanzania and 10 P. vivax strains and 96 P. vivax clinical isolates from Venezuela, and we have verified a sensitivity and specificity of ∼100% for both targets compared with a nested 18S rRNA approach. We show that bioinformatics approaches can be successfully applied to identify novel diagnostic targets and improve molecular methods for pathogen detection. These novel targets provide a powerful alternative molecular diagnostic method for the detection of P. falciparum and P. vivax in conventional or multiplex PCR platforms. PMID:21525225

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

PubMed

Zou, Zhengxia; Shi, Zhenwei

2018-03-01

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

PCR-Free Detection of Genetically Modified Organisms Using Magnetic Capture Technology and Fluorescence Cross-Correlation Spectroscopy

PubMed Central

Zhou, Xiaoming; Xing, Da; Tang, Yonghong; Chen, Wei R.

2009-01-01

The safety of genetically modified organisms (GMOs) has attracted much attention recently. Polymerase chain reaction (PCR) amplification is a common method used in the identification of GMOs. However, a major disadvantage of PCR is the potential amplification of non-target DNA, causing false-positive identification. Thus, there remains a need for a simple, reliable and ultrasensitive method to identify and quantify GMO in crops. This report is to introduce a magnetic bead-based PCR-free method for rapid detection of GMOs using dual-color fluorescence cross-correlation spectroscopy (FCCS). The cauliflower mosaic virus 35S (CaMV35S) promoter commonly used in transgenic products was targeted. CaMV35S target was captured by a biotin-labeled nucleic acid probe and then purified using streptavidin-coated magnetic beads through biotin-streptavidin linkage. The purified target DNA fragment was hybridized with two nucleic acid probes labeled respectively by Rhodamine Green and Cy5 dyes. Finally, FCCS was used to detect and quantify the target DNA fragment through simultaneously detecting the fluorescence emissions from the two dyes. In our study, GMOs in genetically engineered soybeans and tomatoes were detected, using the magnetic bead-based PCR-free FCCS method. A detection limit of 50 pM GMOs target was achieved and PCR-free detection of GMOs from 5 µg genomic DNA with magnetic capture technology was accomplished. Also, the accuracy of GMO determination by the FCCS method is verified by spectrophotometry at 260 nm using PCR amplified target DNA fragment from GM tomato. The new method is rapid and effective as demonstrated in our experiments and can be easily extended to high-throughput and automatic screening format. We believe that the new magnetic bead-assisted FCCS detection technique will be a useful tool for PCR-free GMOs identification and other specific nucleic acids. PMID:19956680

A new comprehensive method for detection of livestock-related pathogenic viruses using a target enrichment system.

PubMed

Oba, Mami; Tsuchiaka, Shinobu; Omatsu, Tsutomu; Katayama, Yukie; Otomaru, Konosuke; Hirata, Teppei; Aoki, Hiroshi; Murata, Yoshiteru; Makino, Shinji; Nagai, Makoto; Mizutani, Tetsuya

2018-01-08

We tested usefulness of a target enrichment system SureSelect, a comprehensive viral nucleic acid detection method, for rapid identification of viral pathogens in feces samples of cattle, pigs and goats. This system enriches nucleic acids of target viruses in clinical/field samples by using a library of biotinylated RNAs with sequences complementary to the target viruses. The enriched nucleic acids are amplified by PCR and subjected to next generation sequencing to identify the target viruses. In many samples, SureSelect target enrichment method increased efficiencies for detection of the viruses listed in the biotinylated RNA library. Furthermore, this method enabled us to determine nearly full-length genome sequence of porcine parainfluenza virus 1 and greatly increased Breadth, a value indicating the ratio of the mapping consensus length in the reference genome, in pig samples. Our data showed usefulness of SureSelect target enrichment system for comprehensive analysis of genomic information of various viruses in field samples. Copyright © 2017 Elsevier Inc. All rights reserved.

Sensitive fluorescence detection of nucleic acids based on isothermal circular strand-displacement polymerization reaction.

PubMed

Guo, Qiuping; Yang, Xiaohai; Wang, Kemin; Tan, Weihong; Li, Wei; Tang, Hongxing; Li, Huimin

2009-02-01

Here we have developed a sensitive DNA amplified detection method based on isothermal strand-displacement polymerization reaction. This method takes advantage of both the hybridization property of DNA and the strand-displacement property of polymerase. Importantly, we demonstrate that our method produces a circular polymerization reaction activated by the target, which essentially allows it to self-detect. Functionally, this DNA system consists of a hairpin fluorescence probe, a short primer and polymerase. Upon recognition and hybridization with the target ssDNA, the stem of the hairpin probe is opened, after which the opened probe anneals with the primer and triggers the polymerization reaction. During this process of the polymerization reaction, a complementary DNA is synthesized and the hybridized target is displaced. Finally, the displaced target recognizes and hybridizes with another probe, triggering the next round of polymerization reaction, reaching a target detection limit of 6.4 x 10(-15) M.

Identifying Minefields and Verifying Clearance: Adapting Statistical Methods for UXO Target Detection

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

Gilbert, Richard O.; O'Brien, Robert F.; Wilson, John E.

2003-09-01

It may not be feasible to completely survey large tracts of land suspected of containing minefields. It is desirable to develop a characterization protocol that will confidently identify minefields within these large land tracts if they exist. Naturally, surveying areas of greatest concern and most likely locations would be necessary but will not provide the needed confidence that an unknown minefield had not eluded detection. Once minefields are detected, methods are needed to bound the area that will require detailed mine detection surveys. The US Department of Defense Strategic Environmental Research and Development Program (SERDP) is sponsoring the development ofmore » statistical survey methods and tools for detecting potential UXO targets. These methods may be directly applicable to demining efforts. Statistical methods are employed to determine the optimal geophysical survey transect spacing to have confidence of detecting target areas of a critical size, shape, and anomaly density. Other methods under development determine the proportion of a land area that must be surveyed to confidently conclude that there are no UXO present. Adaptive sampling schemes are also being developed as an approach for bounding the target areas. These methods and tools will be presented and the status of relevant research in this area will be discussed.« less

Label-free optical detection of single-base mismatches by the combination of nuclease and gold nanoparticles.

PubMed

Liu, Meiying; Yuan, Min; Lou, Xinhui; Mao, Hongju; Zheng, Dongmei; Zou, Ruxing; Zou, Nengli; Tang, Xiangrong; Zhao, Jianlong

2011-07-15

We report here an optical approach that enables highly selective and colorimetric single-base mismatch detection without the need of target modification, precise temperature control or stringent washes. The method is based on the finding that nucleoside monophosphates (dNMPs), which are digested elements of DNA, can better stabilize unmodified gold nanoparticles (AuNPs) than single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) with the same base-composition and concentration. The method combines the exceptional mismatch discrimination capability of the structure-selective nucleases with the attractive optical property of AuNPs. Taking S1 nuclease as one example, the perfectly matched 16-base synthetic DNA target was distinctively differentiated from those with single-base mutation located at any position of the 16-base synthetic target. Single-base mutations present in targets with varied length up to 80-base, located either in the middle or near to the end of the targets, were all effectively detected. In order to prove that the method can be potentially used for real clinic samples, the single-base mismatch detections with two HBV genomic DNA samples were conducted. To further prove the generality of this method and potentially overcome the limitation on the detectable lengths of the targets of the S1 nuclease-based method, we also demonstrated the use of a duplex-specific nuclease (DSN) for color reversed single-base mismatch detection. The main limitation of the demonstrated methods is that it is limited to detect mutations in purified ssDNA targets. However, the method coupled with various convenient ssDNA generation and purification techniques, has the potential to be used for the future development of detector-free testing kits in single nucleotide polymorphism screenings for disease diagnostics and treatments. Copyright © 2011 Elsevier B.V. All rights reserved.

Portable and sensitive quantitative detection of DNA based on personal glucose meters and isothermal circular strand-displacement polymerization reaction.

PubMed

Xu, Xue-tao; Liang, Kai-yi; Zeng, Jia-ying

2015-02-15

A portable and sensitive quantitative DNA detection method based on personal glucose meters and isothermal circular strand-displacement polymerization reaction was developed. The target DNA triggered target recycling process, which opened capture DNA. The released target then found another capture DNA to trigger another polymerization cycle, which was repeated for many rounds, resulting in the multiplication of the DNA-invertase conjugation on the surface of Streptavidin-MNBs. The DNA-invertase was used to catalyze the hydrolysis of sucrose into glucose for PGM readout. There was a liner relationship between the signal of PGM and the concentration of target DNA in the range of 5.0 to 1000 fM, which is lower than some DNA detection method. In addition, the method exhibited excellent sequence selectivity and there was almost no effect of biological complex to the detection performance, which suggested our method can be successfully applied to DNA detection in real biological samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Nucleic Acid Detection Methods

DOEpatents

Smith, Cassandra L.; Yaar, Ron; Szafranski, Przemyslaw; Cantor, Charles R.

1998-05-19

The invention relates to methods for rapidly determining the sequence and/or length a target sequence. The target sequence may be a series of known or unknown repeat sequences which are hybridized to an array of probes. The hybridized array is digested with a single-strand nuclease and free 3'-hydroxyl groups extended with a nucleic acid polymerase. Nuclease cleaved heteroduplexes can be easily distinguish from nuclease uncleaved heteroduplexes by differential labeling. Probes and target can be differentially labeled with detectable labels. Matched target can be detected by cleaving resulting loops from the hybridized target and creating free 3-hydroxyl groups. These groups are recognized and extended by polymerases added into the reaction system which also adds or releases one label into solution. Analysis of the resulting products using either solid phase or solution. These methods can be used to detect characteristic nucleic acid sequences, to determine target sequence and to screen for genetic defects and disorders. Assays can be conducted on solid surfaces allowing for multiple reactions to be conducted in parallel and, if desired, automated.

Background suppression of infrared small target image based on inter-frame registration

NASA Astrophysics Data System (ADS)

Ye, Xiubo; Xue, Bindang

2018-04-01

We propose a multi-frame background suppression method for remote infrared small target detection. Inter-frame information is necessary when the heavy background clutters make it difficult to distinguish real targets and false alarms. A registration procedure based on points matching in image patches is used to compensate the local deformation of background. Then the target can be separated by background subtraction. Experiments show our method serves as an effective preliminary of target detection.

Point target detection utilizing super-resolution strategy for infrared scanning oversampling system

NASA Astrophysics Data System (ADS)

Wang, Longguang; Lin, Zaiping; Deng, Xinpu; An, Wei

2017-11-01

To improve the resolution of remote sensing infrared images, infrared scanning oversampling system is employed with information amount quadrupled, which contributes to the target detection. Generally the image data from double-line detector of infrared scanning oversampling system is shuffled to a whole oversampled image to be post-processed, whereas the aliasing between neighboring pixels leads to image degradation with a great impact on target detection. This paper formulates a point target detection method utilizing super-resolution (SR) strategy concerning infrared scanning oversampling system, with an accelerated SR strategy proposed to realize fast de-aliasing of the oversampled image and an adaptive MRF-based regularization designed to achieve the preserving and aggregation of target energy. Extensive experiments demonstrate the superior detection performance, robustness and efficiency of the proposed method compared with other state-of-the-art approaches.

Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems

PubMed Central

Huang, Dayu; Xue, Anke; Guo, Yunfei

2012-01-01

In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations. PMID:22666074

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

A fast automatic target detection method for detecting ships in infrared scenes

NASA Astrophysics Data System (ADS)

Özertem, Kemal Arda

2016-05-01

Automatic target detection in infrared scenes is a vital task for many application areas like defense, security and border surveillance. For anti-ship missiles, having a fast and robust ship detection algorithm is crucial for overall system performance. In this paper, a straight-forward yet effective ship detection method for infrared scenes is introduced. First, morphological grayscale reconstruction is applied to the input image, followed by an automatic thresholding onto the suppressed image. For the segmentation step, connected component analysis is employed to obtain target candidate regions. At this point, it can be realized that the detection is defenseless to outliers like small objects with relatively high intensity values or the clouds. To deal with this drawback, a post-processing stage is introduced. For the post-processing stage, two different methods are used. First, noisy detection results are rejected with respect to target size. Second, the waterline is detected by using Hough transform and the detection results that are located above the waterline with a small margin are rejected. After post-processing stage, there are still undesired holes remaining, which cause to detect one object as multi objects or not to detect an object as a whole. To improve the detection performance, another automatic thresholding is implemented only to target candidate regions. Finally, two detection results are fused and post-processing stage is repeated to obtain final detection result. The performance of overall methodology is tested with real world infrared test data.

Methods of DNA methylation detection

NASA Technical Reports Server (NTRS)

Maki, Wusi Chen (Inventor); Filanoski, Brian John (Inventor); Mishra, Nirankar (Inventor); Rastogi, Shiva (Inventor)

2010-01-01

The present invention provides for methods of DNA methylation detection. The present invention provides for methods of generating and detecting specific electronic signals that report the methylation status of targeted DNA molecules in biological samples.Two methods are described, direct and indirect detection of methylated DNA molecules in a nano transistor based device. In the direct detection, methylated target DNA molecules are captured on the sensing surface resulting in changes in the electrical properties of a nano transistor. These changes generate detectable electronic signals. In the indirect detection, antibody-DNA conjugates are used to identify methylated DNA molecules. RNA signal molecules are generated through an in vitro transcription process. These RNA molecules are captured on the sensing surface change the electrical properties of nano transistor thereby generating detectable electronic signals.

Combination of atomic force microscopy and mass spectrometry for the detection of target protein in the serum samples of children with autism spectrum disorders

NASA Astrophysics Data System (ADS)

Kaysheva, A. L.; Pleshakova, T. O.; Kopylov, A. T.; Shumov, I. D.; Iourov, I. Y.; Vorsanova, S. G.; Yurov, Y. B.; Ziborov, V. S.; Archakov, A. I.; Ivanov, Y. D.

2017-10-01

Possibility of detection of target proteins associated with development of autistic disorders in children with use of combined atomic force microscopy and mass spectrometry (AFM/MS) method is demonstrated. The proposed method is based on the combination of affine enrichment of proteins from biological samples and visualization of these proteins by AFM and MS analysis with quantitative detection of target proteins.

PCR-free quantitative detection of genetically modified organism from raw materials – A novel electrochemiluminescence-based bio-barcode method

PubMed Central

Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R.

2018-01-01

Bio-barcode assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio-barcode assay requires lengthy experimental procedures including the preparation and release of barcode DNA probes from the target-nanoparticle complex, and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio-barcode assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2’2’-bipyridyl) ruthenium (TBR)-labele barcode DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products. PMID:18386909

PCR-free quantitative detection of genetically modified organism from raw materials. An electrochemiluminescence-based bio bar code method.

PubMed

Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R

2008-05-15

A bio bar code assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio bar code assay requires lengthy experimental procedures including the preparation and release of bar code DNA probes from the target-nanoparticle complex and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio bar code assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2,2'-bipyridyl) ruthenium (TBR)-labeled bar code DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products.

Camouflage target reconnaissance based on hyperspectral imaging technology

NASA Astrophysics Data System (ADS)

Hua, Wenshen; Guo, Tong; Liu, Xun

2015-08-01

Efficient camouflaged target reconnaissance technology makes great influence on modern warfare. Hyperspectral images can provide large spectral range and high spectral resolution, which are invaluable in discriminating between camouflaged targets and backgrounds. Hyperspectral target detection and classification technology are utilized to achieve single class and multi-class camouflaged targets reconnaissance respectively. Constrained energy minimization (CEM), a widely used algorithm in hyperspectral target detection, is employed to achieve one class camouflage target reconnaissance. Then, support vector machine (SVM), a classification method, is proposed to achieve multi-class camouflage target reconnaissance. Experiments have been conducted to demonstrate the efficiency of the proposed method.

Geometric shapes inversion method of space targets by ISAR image segmentation

NASA Astrophysics Data System (ADS)

Huo, Chao-ying; Xing, Xiao-yu; Yin, Hong-cheng; Li, Chen-guang; Zeng, Xiang-yun; Xu, Gao-gui

2017-11-01

The geometric shape of target is an effective characteristic in the process of space targets recognition. This paper proposed a method of shape inversion of space target based on components segmentation from ISAR image. The Radon transformation, Hough transformation, K-means clustering, triangulation will be introduced into ISAR image processing. Firstly, we use Radon transformation and edge detection to extract space target's main body spindle and solar panel spindle from ISAR image. Then the targets' main body, solar panel, rectangular and circular antenna are segmented from ISAR image based on image detection theory. Finally, the sizes of every structural component are computed. The effectiveness of this method is verified using typical targets' simulation data.

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

PubMed Central

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

2016-01-01

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets. PMID:27801795

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

PubMed

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

2016-10-27

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

Detection technology of polarization target based on curvelet transform in turbid liquid

NASA Astrophysics Data System (ADS)

Zhang, Su; Duan, Jin; Fu, Qiang; Zhan, Juntong; Ma, Wanzhuo

2015-08-01

To suppress the interference of the target detecting in the turbid medium, a kind of polarization detection technology based on Curvelet transform was applied. This method firstly adjusts the angles of polarizing film to get the intensity images of the situations at 0°,60° and 120°, then deduces the images of Stokes vectors, degree of polarization (DOP) and polarization angle (PA) according to the Mueller matrix. At last the DOP and intensity images can be decomposed by Curvelet transform to realize the fusion of the high and low coefficients respectively, after the processed coefficients are reconstructed, the target which is easier to detect can be achieved. To prove this method, many targets in turbid medium have been detected by polarization method and fused their DOP and intensity images with Curvelet transform algorithm. As an example screws in moderate and high concentration liquid are presented respectively, from which we can see the unpolarized targets are less obvious in higher concentration liquid. When the DOP and intensity images are fused by Curvelet transform, the targets are emerged clearly out of the turbid medium, and the values of the quality evaluation parameters in clarity, degree of contract and spatial frequency are prominently enhanced comparing with the unpolarized images, which can show the feasibility of this method.

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

NASA Astrophysics Data System (ADS)

Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

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

Microfluidic platform for multiplexed detection in single cells and methods thereof

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

Wu, Meiye; Singh, Anup K.

The present invention relates to a microfluidic device and platform configured to conduct multiplexed analysis within the device. In particular, the device allows multiple targets to be detected on a single-cell level. Also provided are methods of performing multiplexed analyses to detect one or more target nucleic acids, proteins, and post-translational modifications.

Ship detection in panchromatic images: a new method and its DSP implementation

NASA Astrophysics Data System (ADS)

Yao, Yuan; Jiang, Zhiguo; Zhang, Haopeng; Wang, Mengfei; Meng, Gang

2016-03-01

In this paper, a new ship detection method is proposed after analyzing the characteristics of panchromatic remote sensing images and ship targets. Firstly, AdaBoost(Adaptive Boosting) classifiers trained by Haar features are utilized to make coarse detection of ship targets. Then LSD (Line Segment Detector) is adopted to extract the line features in target slices to make fine detection. Experimental results on a dataset of panchromatic remote sensing images with a spatial resolution of 2m show that the proposed algorithm can achieve high detection rate and low false alarm rate. Meanwhile, the algorithm can meet the needs of practical applications on DSP (Digital Signal Processor).

Marine Targets Detection in Pol-SAR Data

NASA Astrophysics Data System (ADS)

Chen, Peng; Yang, Jingsong

2016-08-01

In this poster, we present a new method of marine target detection in Pol-SAR data. One band SAR image, like HH, VV or VH, can be used to find marine target using a Contant False Alarm Ratio (CFAR) algorithm. But some false detection may happen, as the sidelobe of antenna, Azimuth ambiguity, strong speckle noise and so on in the single band SAR image. Pol-SAR image can get more information of targets. After decomposition and false color composite, the sidelobe of antenna and Azimuth ambiguity could be deleted. So, the method presented include three steps, decomposion, false color composite and supervised classification. The result of Radarsat-2 SAR image test indicates a good accuracy. The detection results are compared with Automatic Indentify Sistem (AIS) data, the accuracy of right detection is above 95% and false detection ratio is below 5%.

Marine Targets Classification in PolInSAR Data

NASA Astrophysics Data System (ADS)

Chen, Peng; Yang, Jingsong; Ren, Lin

2014-11-01

In this paper, marine stationary targets and moving targets are studied by Pol-In-SAR data of Radarsat-2. A new method of stationary targets detection is proposed. The method get the correlation coefficient image of the In-SAR data, and using the histogram of correlation coefficient image. Then, A Constant False Alarm Rate (CFAR) algorithm and The Probabilistic Neural Network model are imported to detect stationary targets. To find the moving targets, Azimuth Ambiguity is show as an important feature. We use the length of azimuth ambiguity to get the target's moving direction and speed. Make further efforts, Targets classification is studied by rebuild the surface elevation of marine targets.

Marine Targets Classification in PolInSAR Data

NASA Astrophysics Data System (ADS)

Chen, Peng; Yang, Jingsong; Ren, Lin

2014-11-01

In this paper, marine stationary targets and moving targets are studied by Pol-In-SAR data of Radarsat-2. A new method of stationary targets detection is proposed. The method get the correlation coefficient image of the In-SAR data, and using the histogram of correlation coefficient image. Then , A Constant False Alarm Rate (CFAR) algorithm and The Probabilistic Neural Network model are imported to detect stationary targets. To find the moving targets, Azimuth Ambiguity is show as an important feature. We use the length of azimuth ambiguity to get the target's moving direction and speed. Make further efforts, Targets classification is studied by rebuild the surface elevation of marine targets.

Robust skin color-based moving object detection for video surveillance

NASA Astrophysics Data System (ADS)

Kaliraj, Kalirajan; Manimaran, Sudha

2016-07-01

Robust skin color-based moving object detection for video surveillance is proposed. The objective of the proposed algorithm is to detect and track the target under complex situations. The proposed framework comprises four stages, which include preprocessing, skin color-based feature detection, feature classification, and target localization and tracking. In the preprocessing stage, the input image frame is smoothed using averaging filter and transformed into YCrCb color space. In skin color detection, skin color regions are detected using Otsu's method of global thresholding. In the feature classification, histograms of both skin and nonskin regions are constructed and the features are classified into foregrounds and backgrounds based on Bayesian skin color classifier. The foreground skin regions are localized by a connected component labeling process. Finally, the localized foreground skin regions are confirmed as a target by verifying the region properties, and nontarget regions are rejected using the Euler method. At last, the target is tracked by enclosing the bounding box around the target region in all video frames. The experiment was conducted on various publicly available data sets and the performance was evaluated with baseline methods. It evidently shows that the proposed algorithm works well against slowly varying illumination, target rotations, scaling, fast, and abrupt motion changes.

Accurate and exact CNV identification from targeted high-throughput sequence data.

PubMed

Nord, Alex S; Lee, Ming; King, Mary-Claire; Walsh, Tom

2011-04-12

Massively parallel sequencing of barcoded DNA samples significantly increases screening efficiency for clinically important genes. Short read aligners are well suited to single nucleotide and indel detection. However, methods for CNV detection from targeted enrichment are lacking. We present a method combining coverage with map information for the identification of deletions and duplications in targeted sequence data. Sequencing data is first scanned for gains and losses using a comparison of normalized coverage data between samples. CNV calls are confirmed by testing for a signature of sequences that span the CNV breakpoint. With our method, CNVs can be identified regardless of whether breakpoints are within regions targeted for sequencing. For CNVs where at least one breakpoint is within targeted sequence, exact CNV breakpoints can be identified. In a test data set of 96 subjects sequenced across ~1 Mb genomic sequence using multiplexing technology, our method detected mutations as small as 31 bp, predicted quantitative copy count, and had a low false-positive rate. Application of this method allows for identification of gains and losses in targeted sequence data, providing comprehensive mutation screening when combined with a short read aligner.

Search Radar Track-Before-Detect Using the Hough Transform.

DTIC Science & Technology

1995-03-01

before - detect processing method which allows previous data to help in target detection. The technique provides many advantages compared to...improved target detection scheme, applicable to search radars, using the Hough transform image processing technique. The system concept involves a track

Lifting wavelet method of target detection

NASA Astrophysics Data System (ADS)

Han, Jun; Zhang, Chi; Jiang, Xu; Wang, Fang; Zhang, Jin

2009-11-01

Image target recognition plays a very important role in the areas of scientific exploration, aeronautics and space-to-ground observation, photography and topographic mapping. Complex environment of the image noise, fuzzy, all kinds of interference has always been to affect the stability of recognition algorithm. In this paper, the existence of target detection in real-time, accuracy problems, as well as anti-interference ability, using lifting wavelet image target detection methods. First of all, the use of histogram equalization, the goal difference method to obtain the region, on the basis of adaptive threshold and mathematical morphology operations to deal with the elimination of the background error. Secondly, the use of multi-channel wavelet filter wavelet transform of the original image de-noising and enhancement, to overcome the general algorithm of the noise caused by the sensitive issue of reducing the rate of miscarriage of justice will be the multi-resolution characteristics of wavelet and promotion of the framework can be designed directly in the benefits of space-time region used in target detection, feature extraction of targets. The experimental results show that the design of lifting wavelet has solved the movement of the target due to the complexity of the context of the difficulties caused by testing, which can effectively suppress noise, and improve the efficiency and speed of detection.

Single molecule targeted sequencing for cancer gene mutation detection.

PubMed

Gao, Yan; Deng, Liwei; Yan, Qin; Gao, Yongqian; Wu, Zengding; Cai, Jinsen; Ji, Daorui; Li, Gailing; Wu, Ping; Jin, Huan; Zhao, Luyang; Liu, Song; Ge, Liangjin; Deem, Michael W; He, Jiankui

2016-05-19

With the rapid decline in cost of sequencing, it is now affordable to examine multiple genes in a single disease-targeted clinical test using next generation sequencing. Current targeted sequencing methods require a separate step of targeted capture enrichment during sample preparation before sequencing. Although there are fast sample preparation methods available in market, the library preparation process is still relatively complicated for physicians to use routinely. Here, we introduced an amplification-free Single Molecule Targeted Sequencing (SMTS) technology, which combined targeted capture and sequencing in one step. We demonstrated that this technology can detect low-frequency mutations using artificially synthesized DNA sample. SMTS has several potential advantages, including simple sample preparation thus no biases and errors are introduced by PCR reaction. SMTS has the potential to be an easy and quick sequencing technology for clinical diagnosis such as cancer gene mutation detection, infectious disease detection, inherited condition screening and noninvasive prenatal diagnosis.

Nucleic acid detection methods

DOEpatents

Smith, C.L.; Yaar, R.; Szafranski, P.; Cantor, C.R.

1998-05-19

The invention relates to methods for rapidly determining the sequence and/or length a target sequence. The target sequence may be a series of known or unknown repeat sequences which are hybridized to an array of probes. The hybridized array is digested with a single-strand nuclease and free 3{prime}-hydroxyl groups extended with a nucleic acid polymerase. Nuclease cleaved heteroduplexes can be easily distinguish from nuclease uncleaved heteroduplexes by differential labeling. Probes and target can be differentially labeled with detectable labels. Matched target can be detected by cleaving resulting loops from the hybridized target and creating free 3-hydroxyl groups. These groups are recognized and extended by polymerases added into the reaction system which also adds or releases one label into solution. Analysis of the resulting products using either solid phase or solution. These methods can be used to detect characteristic nucleic acid sequences, to determine target sequence and to screen for genetic defects and disorders. Assays can be conducted on solid surfaces allowing for multiple reactions to be conducted in parallel and, if desired, automated. 18 figs.

Automatic small target detection in synthetic infrared images

NASA Astrophysics Data System (ADS)

Yardımcı, Ozan; Ulusoy, Ä.°lkay

2017-05-01

Automatic detection of targets from far distances is a very challenging problem. Background clutter and small target size are the main difficulties which should be solved while reaching a high detection performance as well as a low computational load. The pre-processing, detection and post-processing approaches are very effective on the final results. In this study, first of all, various methods in the literature were evaluated separately for each of these stages using the simulated test scenarios. Then, a full system of detection was constructed among available solutions which resulted in the best performance in terms of detection. However, although a precision rate as 100% was reached, the recall values stayed low around 25-45%. Finally, a post-processing method was proposed which increased the recall value while keeping the precision at 100%. The proposed post-processing method, which is based on local operations, increased the recall value to 65-95% in all test scenarios.

Dangerous gas detection based on infrared video

NASA Astrophysics Data System (ADS)

Ding, Kang; Hong, Hanyu; Huang, Likun

2018-03-01

As the gas leak infrared imaging detection technology has significant advantages of high efficiency and remote imaging detection, in order to enhance the detail perception of observers and equivalently improve the detection limit, we propose a new type of gas leak infrared image detection method, which combines background difference methods and multi-frame interval difference method. Compared to the traditional frame methods, the multi-frame interval difference method we proposed can extract a more complete target image. By fusing the background difference image and the multi-frame interval difference image, we can accumulate the information of infrared target image of the gas leak in many aspect. The experiment demonstrate that the completeness of the gas leakage trace information is enhanced significantly, and the real-time detection effect can be achieved.

Target Detection and Classification Using Seismic and PIR Sensors

DTIC Science & Technology

2012-06-01

time series analysis via wavelet - based partitioning,” Signal Process...regard, this paper presents a wavelet - based method for target detection and classification. The proposed method has been validated on data sets of...The work reported in this paper makes use of a wavelet - based feature extraction method , called Symbolic Dynamic Filtering (SDF) [12]–[14]. The

Wavelength band selection method for multispectral target detection.

PubMed

Karlholm, Jörgen; Renhorn, Ingmar

2002-11-10

A framework is proposed for the selection of wavelength bands for multispectral sensors by use of hyperspectral reference data. Using the results from the detection theory we derive a cost function that is minimized by a set of spectral bands optimal in terms of detection performance for discrimination between a class of small rare targets and clutter with known spectral distribution. The method may be used, e.g., in the design of multispectral infrared search and track and electro-optical missile warning sensors, where a low false-alarm rate and a high-detection probability for detection of small targets against a clutter background are of critical importance, but the required high frame rate prevents the use of hyperspectral sensors.

Methods and kits for nucleic acid analysis using fluorescence resonance energy transfer

DOEpatents

Kwok, Pui-Yan; Chen, Xiangning

1999-01-01

A method for detecting the presence of a target nucleotide or sequence of nucleotides in a nucleic acid is disclosed. The method is comprised of forming an oligonucleotide labeled with two fluorophores on the nucleic acid target site. The doubly labeled oligonucleotide is formed by addition of a singly labeled dideoxynucleoside triphosphate to a singly labeled polynucleotide or by ligation of two singly labeled polynucleotides. Detection of fluorescence resonance energy transfer upon denaturation indicates the presence of the target. Kits are also provided. The method is particularly applicable to genotyping.

Using personal glucose meters and functional DNA sensors to quantify a variety of analytical targets

PubMed Central

Xiang, Yu; Lu, Yi

2012-01-01

Portable, low-cost and quantitative detection of a broad range of targets at home and in the field has the potential to revolutionize medical diagnostics and environmental monitoring. Despite many years of research, very few such devices are commercially available. Taking advantage of the wide availability and low cost of the pocket-sized personal glucose meter—used worldwide by diabetes sufferers—we demonstrate a method to use such meters to quantify non-glucose targets, ranging from a recreational drug (cocaine, 3.4 μM detection limit) to an important biological cofactor (adenosine, 18 μM detection limit), to a disease marker (interferon-gamma of tuberculosis, 2.6 nM detection limit) and a toxic metal ion (uranium, 9.1 nM detection limit). The method is based on the target-induced release of invertase from a functional-DNA–invertase conjugate. The released invertase converts sucrose into glucose, which is detectable using the meter. The approach should be easily applicable to the detection of many other targets through the use of suitable functional-DNA partners (aptamers DNAzymes or aptazymes). PMID:21860458

Using personal glucose meters and functional DNA sensors to quantify a variety of analytical targets

NASA Astrophysics Data System (ADS)

Xiang, Yu; Lu, Yi

2011-09-01

Portable, low-cost and quantitative detection of a broad range of targets at home and in the field has the potential to revolutionize medical diagnostics and environmental monitoring. Despite many years of research, very few such devices are commercially available. Taking advantage of the wide availability and low cost of the pocket-sized personal glucose meter—used worldwide by diabetes sufferers—we demonstrate a method to use such meters to quantify non-glucose targets, ranging from a recreational drug (cocaine, 3.4 µM detection limit) to an important biological cofactor (adenosine, 18 µM detection limit), to a disease marker (interferon-gamma of tuberculosis, 2.6 nM detection limit) and a toxic metal ion (uranium, 9.1 nM detection limit). The method is based on the target-induced release of invertase from a functional-DNA-invertase conjugate. The released invertase converts sucrose into glucose, which is detectable using the meter. The approach should be easily applicable to the detection of many other targets through the use of suitable functional-DNA partners (aptamers, DNAzymes or aptazymes).

Target attribute-based false alarm rejection in small infrared target detection

NASA Astrophysics Data System (ADS)

Kim, Sungho

2012-11-01

Infrared search and track is an important research area in military applications. Although there are a lot of works on small infrared target detection methods, we cannot apply them in real field due to high false alarm rate caused by clutters. This paper presents a novel target attribute extraction and machine learning-based target discrimination method. Eight kinds of target features are extracted and analyzed statistically. Learning-based classifiers such as SVM and Adaboost are developed and compared with conventional classifiers for real infrared images. In addition, the generalization capability is also inspected for various infrared clutters.

Targeted resequencing reveals ALK fusions in non-small cell lung carcinomas detected by FISH, immunohistochemistry, and real-time RT-PCR: a comparison of four methods.

PubMed

Tuononen, Katja; Sarhadi, Virinder Kaur; Wirtanen, Aino; Rönty, Mikko; Salmenkivi, Kaisa; Knuuttila, Aija; Remes, Satu; Telaranta-Keerie, Aino I; Bloor, Stuart; Ellonen, Pekka; Knuutila, Sakari

2013-01-01

Anaplastic lymphoma receptor tyrosine kinase (ALK) gene rearrangements occur in a subgroup of non-small cell lung carcinomas (NSCLCs). The identification of these rearrangements is important for guiding treatment decisions. The aim of our study was to screen ALK gene fusions in NSCLCs and to compare the results detected by targeted resequencing with results detected by commonly used methods, including fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and real-time reverse transcription-PCR (RT-PCR). Furthermore, we aimed to ascertain the potential of targeted resequencing in detection of ALK-rearranged lung carcinomas. We assessed ALK fusion status for 95 formalin-fixed paraffin-embedded tumor tissue specimens from 87 patients with NSCLC by FISH and real-time RT-PCR, for 57 specimens from 56 patients by targeted resequencing, and for 14 specimens from 14 patients by IHC. All methods were performed successfully on formalin-fixed paraffin-embedded tumor tissue material. We detected ALK fusion in 5.7% (5 out of 87) of patients examined. The results obtained from resequencing correlated significantly with those from FISH, real-time RT-PCR, and IHC. Targeted resequencing proved to be a promising method for ALK gene fusion detection in NSCLC. Means to reduce the material and turnaround time required for analysis are, however, needed.

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

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Bal, Abdullah

2016-05-01

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

Discreet passive explosive detection through 2-sided waveguided fluorescence

DOEpatents

Harper, Ross James [Stillwater, OK; la Grone, Marcus [Cushing, OK; Fisher, Mark [Stillwater, OK

2011-10-18

The current invention provides a passive sampling device suitable for collecting and detecting the presence of target analytes. In particular, the passive sampling device is suitable for detecting nitro-aromatic compounds. The current invention further provides a passive sampling device reader suitable for determining the collection of target analytes. Additionally, the current invention provides methods for detecting target analytes using the passive sampling device and the passive sampling device reader.

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

NASA Astrophysics Data System (ADS)

Ye, Han; Pei, Jihong

2018-02-01

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

The ship edge feature detection based on high and low threshold for remote sensing image

NASA Astrophysics Data System (ADS)

Li, Xuan; Li, Shengyang

2018-05-01

In this paper, a method based on high and low threshold is proposed to detect the ship edge feature due to the low accuracy rate caused by the noise. Analyze the relationship between human vision system and the target features, and to determine the ship target by detecting the edge feature. Firstly, using the second-order differential method to enhance the quality of image; Secondly, to improvement the edge operator, we introduction of high and low threshold contrast to enhancement image edge and non-edge points, and the edge as the foreground image, non-edge as a background image using image segmentation to achieve edge detection, and remove the false edges; Finally, the edge features are described based on the result of edge features detection, and determine the ship target. The experimental results show that the proposed method can effectively reduce the number of false edges in edge detection, and has the high accuracy of remote sensing ship edge detection.

Feature Transformation Detection Method with Best Spectral Band Selection Process for Hyper-spectral Imaging

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike; Brickhouse, Mark

2015-11-01

We present a newly developed feature transformation (FT) detection method for hyper-spectral imagery (HSI) sensors. In essence, the FT method, by transforming the original features (spectral bands) to a different feature domain, may considerably increase the statistical separation between the target and background probability density functions, and thus may significantly improve the target detection and identification performance, as evidenced by the test results in this paper. We show that by differentiating the original spectral, one can completely separate targets from the background using a single spectral band, leading to perfect detection results. In addition, we have proposed an automated best spectral band selection process with a double-threshold scheme that can rank the available spectral bands from the best to the worst for target detection. Finally, we have also proposed an automated cross-spectrum fusion process to further improve the detection performance in lower spectral range (<1000 nm) by selecting the best spectral band pair with multivariate analysis. Promising detection performance has been achieved using a small background material signature library for concept-proving, and has then been further evaluated and verified using a real background HSI scene collected by a HYDICE sensor.

A high-throughput multiplex method adapted for GMO detection.

PubMed

Chaouachi, Maher; Chupeau, Gaëlle; Berard, Aurélie; McKhann, Heather; Romaniuk, Marcel; Giancola, Sandra; Laval, Valérie; Bertheau, Yves; Brunel, Dominique

2008-12-24

A high-throughput multiplex assay for the detection of genetically modified organisms (GMO) was developed on the basis of the existing SNPlex method designed for SNP genotyping. This SNPlex assay allows the simultaneous detection of up to 48 short DNA sequences (approximately 70 bp; "signature sequences") from taxa endogenous reference genes, from GMO constructions, screening targets, construct-specific, and event-specific targets, and finally from donor organisms. This assay avoids certain shortcomings of multiplex PCR-based methods already in widespread use for GMO detection. The assay demonstrated high specificity and sensitivity. The results suggest that this assay is reliable, flexible, and cost- and time-effective for high-throughput GMO detection.

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

NASA Astrophysics Data System (ADS)

Zhou, Anran; Xie, Weixin; Pei, Jihong

2018-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

Automatic detection of multiple UXO-like targets using magnetic anomaly inversion and self-adaptive fuzzy c-means clustering

NASA Astrophysics Data System (ADS)

Yin, Gang; Zhang, Yingtang; Fan, Hongbo; Ren, Guoquan; Li, Zhining

2017-12-01

We have developed a method for automatically detecting UXO-like targets based on magnetic anomaly inversion and self-adaptive fuzzy c-means clustering. Magnetic anomaly inversion methods are used to estimate the initial locations of multiple UXO-like sources. Although these initial locations have some errors with respect to the real positions, they form dense clouds around the actual positions of the magnetic sources. Then we use the self-adaptive fuzzy c-means clustering algorithm to cluster these initial locations. The estimated number of cluster centroids represents the number of targets and the cluster centroids are regarded as the locations of magnetic targets. Effectiveness of the method has been demonstrated using synthetic datasets. Computational results show that the proposed method can be applied to the case of several UXO-like targets that are randomly scattered within in a confined, shallow subsurface, volume. A field test was carried out to test the validity of the proposed method and the experimental results show that the prearranged magnets can be detected unambiguously and located precisely.

Comparison of 16S rDNA-based PCR and checkerboard DNA-DNA hybridisation for detection of selected endodontic pathogens.

PubMed

Siqueira, José F; Rôças, Isabela N; De Uzeda, Milton; Colombo, Ana P; Santos, Kátia R N

2002-12-01

Molecular methods have been used recently to investigate the bacteria encountered in human endodontic infections. The aim of the present study was to compare the ability of a 16S rDNA-based PCR assay and checkerboard DNA-DNA hybridisation in detecting Actinobacillus actinomycetemcomitans, Bacteroides forsythus, Peptostreptococcus micros, Porphyromonas endodontalis, Por. gingivalis and Treponema denticola directly from clinical samples. Specimens were obtained from 50 cases of endodontic infections and the presence of the target species was investigated by whole genomic DNA probes and checkerboard DNA-DNA hybridisation or taxon-specific oligonucleotides with PCR assay. Prevalence of the target species was based on data obtained by each method. The sensitivity and specificity of each molecular method was compared with the data generated by the other method as the reference--a value of 1.0 representing total agreement with the chosen standard. The methods were also compared with regard to the prevalence values for each target species. Regardless of the detection method used, T. denticola, Por. gingivalis, Por. endodontalis and B. forsythus were the most prevalent species. If the checkerboard data for these four species were used as the reference, PCR detection sensitivities ranged from 0.53 to 1.0, and specificities from 0.5 to 0.88, depending on the target bacterial species. When PCR data for the same species were used as the reference, the detection sensitivities for the checkerboard method ranged from 0.17 to 0.73, and specificities from 0.75 to 1.0. Accuracy values ranged from 0.6 to 0.74. On the whole, matching results between the two molecular methods ranged from 60% to 97.5%, depending on the target species. The major discrepancies between the methods comprised a number of PCR-positive but checkerboard-negative results. Significantly higher prevalence figures for Por. endodontalis and T. denticola were observed after PCR assessment. There was no further significant difference between the methods with regard to detection of the other target species.

Low-Rank Matrix Recovery Approach for Clutter Rejection in Real-Time IR-UWB Radar-Based Moving Target Detection

PubMed Central

Sabushimike, Donatien; Na, Seung You; Kim, Jin Young; Bui, Ngoc Nam; Seo, Kyung Sik; Kim, Gil Gyeom

2016-01-01

The detection of a moving target using an IR-UWB Radar involves the core task of separating the waves reflected by the static background and by the moving target. This paper investigates the capacity of the low-rank and sparse matrix decomposition approach to separate the background and the foreground in the trend of UWB Radar-based moving target detection. Robust PCA models are criticized for being batched-data-oriented, which makes them inconvenient in realistic environments where frames need to be processed as they are recorded in real time. In this paper, a novel method based on overlapping-windows processing is proposed to cope with online processing. The method consists of processing a small batch of frames which will be continually updated without changing its size as new frames are captured. We prove that RPCA (via its Inexact Augmented Lagrange Multiplier (IALM) model) can successfully separate the two subspaces, which enhances the accuracy of target detection. The overlapping-windows processing method converges on the optimal solution with its batch counterpart (i.e., processing batched data with RPCA), and both methods prove the robustness and efficiency of the RPCA over the classic PCA and the commonly used exponential averaging method. PMID:27598159

Target 3-D reconstruction of streak tube imaging lidar based on Gaussian fitting

NASA Astrophysics Data System (ADS)

Yuan, Qingyu; Niu, Lihong; Hu, Cuichun; Wu, Lei; Yang, Hongru; Yu, Bing

2018-02-01

Streak images obtained by the streak tube imaging lidar (STIL) contain the distance-azimuth-intensity information of a scanned target, and a 3-D reconstruction of the target can be carried out through extracting the characteristic data of multiple streak images. Significant errors will be caused in the reconstruction result by the peak detection method due to noise and other factors. So as to get a more precise 3-D reconstruction, a peak detection method based on Gaussian fitting of trust region is proposed in this work. Gaussian modeling is performed on the returned wave of single time channel of each frame, then the modeling result which can effectively reduce the noise interference and possesses a unique peak could be taken as the new returned waveform, lastly extracting its feature data through peak detection. The experimental data of aerial target is for verifying this method. This work shows that the peak detection method based on Gaussian fitting reduces the extraction error of the feature data to less than 10%; utilizing this method to extract the feature data and reconstruct the target make it possible to realize the spatial resolution with a minimum 30 cm in the depth direction, and improve the 3-D imaging accuracy of the STIL concurrently.

Staircase-scene-based nonuniformity correction in aerial point target detection systems.

PubMed

Huo, Lijun; Zhou, Dabiao; Wang, Dejiang; Liu, Rang; He, Bin

2016-09-01

Focal-plane arrays (FPAs) are often interfered by heavy fixed-pattern noise, which severely degrades the detection rate and increases the false alarms in airborne point target detection systems. Thus, high-precision nonuniformity correction is an essential preprocessing step. In this paper, a new nonuniformity correction method is proposed based on a staircase scene. This correction method can compensate for the nonlinear response of the detector and calibrate the entire optical system with computational efficiency and implementation simplicity. Then, a proof-of-concept point target detection system is established with a long-wave Sofradir FPA. Finally, the local standard deviation of the corrected image and the signal-to-clutter ratio of the Airy disk of a Boeing B738 are measured to evaluate the performance of the proposed nonuniformity correction method. Our experimental results demonstrate that the proposed correction method achieves high-quality corrections.

Detection of nucleic acids by multiple sequential invasive cleavages

DOEpatents

Hall, Jeff G.; Lyamichev, Victor I.; Mast, Andrea L.; Brow, Mary Ann D.

1999-01-01

The present invention relates to means for the detection and characterization of nucleic acid sequences, as well as variations in nucleic acid sequences. The present invention also relates to methods for forming a nucleic acid cleavage structure on a target sequence and cleaving the nucleic acid cleavage structure in a site-specific manner. The structure-specific nuclease activity of a variety of enzymes is used to cleave the target-dependent cleavage structure, thereby indicating the presence of specific nucleic acid sequences or specific variations thereof. The present invention further relates to methods and devices for the separation of nucleic acid molecules based on charge. The present invention also provides methods for the detection of non-target cleavage products via the formation of a complete and activated protein binding region. The invention further provides sensitive and specific methods for the detection of human cytomegalovirus nucleic acid in a sample.

Nucleic acid detection kits

DOEpatents

Hall, Jeff G.; Lyamichev, Victor I.; Mast, Andrea L.; Brow, Mary Ann; Kwiatkowski, Robert W.; Vavra, Stephanie H.

2005-03-29

The present invention relates to means for the detection and characterization of nucleic acid sequences, as well as variations in nucleic acid sequences. The present invention also relates to methods for forming a nucleic acid cleavage structure on a target sequence and cleaving the nucleic acid cleavage structure in a site-specific manner. The structure-specific nuclease activity of a variety of enzymes is used to cleave the target-dependent cleavage structure, thereby indicating the presence of specific nucleic acid sequences or specific variations thereof. The present invention further relates to methods and devices for the separation of nucleic acid molecules based on charge. The present invention also provides methods for the detection of non-target cleavage products via the formation of a complete and activated protein binding region. The invention further provides sensitive and specific methods for the detection of nucleic acid from various viruses in a sample.

Detection of nucleic acids by multiple sequential invasive cleavages 02

DOEpatents

Hall, Jeff G.; Lyamichev, Victor I.; Mast, Andrea L.; Brow, Mary Ann D.

2002-01-01

The present invention relates to means for the detection and characterization of nucleic acid sequences, as well as variations in nucleic acid sequences. The present invention also relates to methods for forming a nucleic acid cleavage structure on a target sequence and cleaving the nucleic acid cleavage structure in a site-specific manner. The structure-specific nuclease activity of a variety of enzymes is used to cleave the target-dependent cleavage structure, thereby indicating the presence of specific nucleic acid sequences or specific variations thereof. The present invention further relates to methods and devices for the separation of nucleic acid molecules based on charge. The present invention also provides methods for the detection of non-target cleavage products via the formation of a complete and activated protein binding region. The invention further provides sensitive and specific methods for the detection of human cytomegalovirus nucleic acid in a sample.

Detection of nucleic acids by multiple sequential invasive cleavages

DOEpatents

Hall, Jeff G; Lyamichev, Victor I; Mast, Andrea L; Brow, Mary Ann D

2012-10-16

The present invention relates to means for the detection and characterization of nucleic acid sequences, as well as variations in nucleic acid sequences. The present invention also relates to methods for forming a nucleic acid cleavage structure on a target sequence and cleaving the nucleic acid cleavage structure in a site-specific manner. The structure-specific nuclease activity of a variety of enzymes is used to cleave the target-dependent cleavage structure, thereby indicating the presence of specific nucleic acid sequences or specific variations thereof. The present invention further relates to methods and devices for the separation of nucleic acid molecules based on charge. The present invention also provides methods for the detection of non-target cleavage products via the formation of a complete and activated protein binding region. The invention further provides sensitive and specific methods for the detection of human cytomegalovirus nucleic acid in a sample.

Development of a qualitative real-time PCR method to detect 19 targets for identification of genetically modified organisms.

PubMed

Peng, Cheng; Wang, Pengfei; Xu, Xiaoli; Wang, Xiaofu; Wei, Wei; Chen, Xiaoyun; Xu, Junfeng

2016-01-01

As the amount of commercially available genetically modified organisms (GMOs) grows recent years, the diversity of target sequences for molecular detection techniques are eagerly needed. Considered as the gold standard for GMO analysis, the real-time PCR technology was optimized to produce a high-throughput GMO screening method. With this method we can detect 19 transgenic targets. The specificity of the assays was demonstrated to be 100 % by the specific amplification of DNA derived from reference material from 20 genetically modified crops and 4 non modified crops. Furthermore, most assays showed a very sensitive detection, reaching the limit of ten copies. The 19 assays are the most frequently used genetic elements present in GM crops and theoretically enable the screening of the known GMO described in Chinese markets. Easy to use, fast and cost efficient, this method approach fits the purpose of GMO testing laboratories.

A real-time tracking system of infrared dim and small target based on FPGA and DSP

NASA Astrophysics Data System (ADS)

Rong, Sheng-hui; Zhou, Hui-xin; Qin, Han-lin; Wang, Bing-jian; Qian, Kun

2014-11-01

A core technology in the infrared warning system is the detection tracking of dim and small targets with complicated background. Consequently, running the detection algorithm on the hardware platform has highly practical value in the military field. In this paper, a real-time detection tracking system of infrared dim and small target which is used FPGA (Field Programmable Gate Array) and DSP (Digital Signal Processor) as the core was designed and the corresponding detection tracking algorithm and the signal flow is elaborated. At the first stage, the FPGA obtain the infrared image sequence from the sensor, then it suppresses background clutter by mathematical morphology method and enhances the target intensity by Laplacian of Gaussian operator. At the second stage, the DSP obtain both the original image and the filtered image form the FPGA via the video port. Then it segments the target from the filtered image by an adaptive threshold segmentation method and gets rid of false target by pipeline filter. Experimental results show that our system can achieve higher detection rate and lower false alarm rate.

Method of detecting luminescent target ions with modified magnetic microspheres

DOEpatents

Shkrob, Ilya A; Kaminski, Michael D

2014-05-13

This invention provides methods of using modified magnetic microspheres to extract target ions from a sample in order to detect their presence in a microfluidic environment. In one or more embodiments, the microspheres are modified with molecules on the surface that allow the target ions in the sample to form complexes with specific ligand molecules on the microsphere surface. In one or more embodiments, the microspheres are modified with molecules that sequester the target ions from the sample, but specific ligand molecules in solution subsequently re-extract the target ions from the microspheres into the solution, where the complexes form independent of the microsphere surface. Once the complexes form, they are exposed to an excitation wavelength light source suitable for exciting the target ion to emit a luminescent signal pattern. Detection of the luminescent signal pattern allows for determination of the presence of the target ions in the sample.

A statistical approach to detection of copy number variations in PCR-enriched targeted sequencing data.

PubMed

Demidov, German; Simakova, Tamara; Vnuchkova, Julia; Bragin, Anton

2016-10-22

Multiplex polymerase chain reaction (PCR) is a common enrichment technique for targeted massive parallel sequencing (MPS) protocols. MPS is widely used in biomedical research and clinical diagnostics as the fast and accurate tool for the detection of short genetic variations. However, identification of larger variations such as structure variants and copy number variations (CNV) is still being a challenge for targeted MPS. Some approaches and tools for structural variants detection were proposed, but they have limitations and often require datasets of certain type, size and expected number of amplicons affected by CNVs. In the paper, we describe novel algorithm for high-resolution germinal CNV detection in the PCR-enriched targeted sequencing data and present accompanying tool. We have developed a machine learning algorithm for the detection of large duplications and deletions in the targeted sequencing data generated with PCR-based enrichment step. We have performed verification studies and established the algorithm's sensitivity and specificity. We have compared developed tool with other available methods applicable for the described data and revealed its higher performance. We showed that our method has high specificity and sensitivity for high-resolution copy number detection in targeted sequencing data using large cohort of samples.

Non-Enzymatic Detection of Bacterial Genomic DNA Using the Bio-Barcode Assay

PubMed Central

Hill, Haley D.; Vega, Rafael A.; Mirkin, Chad A.

2011-01-01

The detection of bacterial genomic DNA through a non-enzymatic nanomaterials based amplification method, the bio-barcode assay, is reported. The assay utilizes oligonucleotide functionalized magnetic microparticles to capture the target of interest from the sample. A critical step in the new assay involves the use of blocking oligonucleotides during heat denaturation of the double stranded DNA. These blockers bind to specific regions of the target DNA upon cooling, and prevent the duplex DNA from re-hybridizing, which allows the particle probes to bind. Following target isolation using the magnetic particles, oligonucleotide functionalized gold nanoparticles act as target recognition agents. The oligonucleotides on the nanoparticle (barcodes) act as amplification surrogates. The barcodes are then detected using the Scanometric method. The limit of detection for this assay was determined to be 2.5 femtomolar, and this is the first demonstration of a barcode type assay for the detection of double stranded, genomic DNA. PMID:17927207

Outlier and target detection in aerial hyperspectral imagery: a comparison of traditional and percentage occupancy hit or miss transform techniques

NASA Astrophysics Data System (ADS)

Young, Andrew; Marshall, Stephen; Gray, Alison

2016-05-01

The use of aerial hyperspectral imagery for the purpose of remote sensing is a rapidly growing research area. Currently, targets are generally detected by looking for distinct spectral features of the objects under surveillance. For example, a camouflaged vehicle, deliberately designed to blend into background trees and grass in the visible spectrum, can be revealed using spectral features in the near-infrared spectrum. This work aims to develop improved target detection methods, using a two-stage approach, firstly by development of a physics-based atmospheric correction algorithm to convert radiance into re ectance hyperspectral image data and secondly by use of improved outlier detection techniques. In this paper the use of the Percentage Occupancy Hit or Miss Transform is explored to provide an automated method for target detection in aerial hyperspectral imagery.

Underwater single beam circumferentially scanning detection system using range-gated receiver and adaptive filter

NASA Astrophysics Data System (ADS)

Tan, Yayun; Zhang, He; Zha, Bingting

2017-09-01

Underwater target detection and ranging in seawater are of interest in unmanned underwater vehicles. This study presents an underwater detection system that synchronously scans a collimated laser beam and a narrow field of view to circumferentially detect an underwater target. Hybrid methods of range-gated and variable step-size least mean squares (VSS-LMS) adaptive filter are proposed to suppress water backscattering. The range-gated receiver eliminates the backscattering of near-field water. The VSS-LMS filter extracts the target echo in the remaining backscattering and the constant fraction discriminator timing method is used to improve ranging accuracy. The optimal constant fraction is selected by analysing the jitter noise and slope of the target echo. The prototype of the underwater detection system is constructed and tested in coastal seawater, then the effectiveness of backscattering suppression and high-ranging accuracy is verified through experimental results and analysis discussed in this paper.

Current Challenges in Detecting Food Allergens by Shotgun and Targeted Proteomic Approaches: A Case Study on Traces of Peanut Allergens in Baked Cookies

PubMed Central

Pedreschi, Romina; Nørgaard, Jørgen; Maquet, Alain

2012-01-01

There is a need for selective and sensitive methods to detect the presence of food allergens at trace levels in highly processed food products. In this work, a combination of non-targeted and targeted proteomics approaches are used to illustrate the difficulties encountered in the detection of the major peanut allergens Ara h 1, Ara h 2 and Ara h 3 from a representative processed food matrix. Shotgun proteomics was employed for selection of the proteotypic peptides for targeted approaches via selective reaction monitoring. Peanut presence through detection of the proteotypic Ara h 3/4 peptides AHVQVVDSNGNR (m/z 432.5, 3+) and SPDIYNPQAGSLK (m/z 695.4, 2+) was confirmed and the developed method was able to detect peanut presence at trace levels (≥10 μg peanut g−1 matrix) in baked cookies. PMID:22413066

Elaborately designed diblock nanoprobes for simultaneous multicolor detection of microRNAs

NASA Astrophysics Data System (ADS)

Wang, Chenguang; Zhang, Huan; Zeng, Dongdong; Sun, Wenliang; Zhang, Honglu; Aldalbahi, Ali; Wang, Yunsheng; San, Lili; Fan, Chunhai; Zuo, Xiaolei; Mi, Xianqiang

2015-09-01

Simultaneous detection of multiple biomarkers has important prospects in the biomedical field. In this work, we demonstrated a novel strategy for the detection of multiple microRNAs (miRNAs) based on gold nanoparticles (Au NPs) and polyadenine (polyA) mediated nanoscale molecular beacon (MB) probes (denoted p-nanoMBs). Novel fluorescent labeled p-nanoMBs bearing consecutive adenines were designed, of which polyA served as an effective anchoring block binding to the surface of Au NPs, and the appended hairpin block formed an upright conformation that favored the hybridization with targets. Using the co-assembling method and the improved hybridization conformation of the hairpin probes, we achieved high selectivity for specifically distinguishing DNA targets from single-base mismatched DNA targets. We also realized multicolor detection of three different synthetic miRNAs in a wide dynamic range from 0.01 nM to 200 nM with a detection limit of 10 pM. What's more, we even detected miRNAs in a simulated serum environment, which indicated that our method could be used in complex media. Compared with the traditional method, our strategy provides a promising alternative method for the qualitative and quantitative detection of miRNAs.Simultaneous detection of multiple biomarkers has important prospects in the biomedical field. In this work, we demonstrated a novel strategy for the detection of multiple microRNAs (miRNAs) based on gold nanoparticles (Au NPs) and polyadenine (polyA) mediated nanoscale molecular beacon (MB) probes (denoted p-nanoMBs). Novel fluorescent labeled p-nanoMBs bearing consecutive adenines were designed, of which polyA served as an effective anchoring block binding to the surface of Au NPs, and the appended hairpin block formed an upright conformation that favored the hybridization with targets. Using the co-assembling method and the improved hybridization conformation of the hairpin probes, we achieved high selectivity for specifically distinguishing DNA targets from single-base mismatched DNA targets. We also realized multicolor detection of three different synthetic miRNAs in a wide dynamic range from 0.01 nM to 200 nM with a detection limit of 10 pM. What's more, we even detected miRNAs in a simulated serum environment, which indicated that our method could be used in complex media. Compared with the traditional method, our strategy provides a promising alternative method for the qualitative and quantitative detection of miRNAs. Electronic supplementary information (ESI) available: Sequences for oligonucleotides used for this work, dynamic light scattering (DLS) measurements, fluorescent signal intensity with different ratios between p-MBs and A5 oligonucleotides, quantification of the fluorescent p-MB, and UV-Vis spectra for naked AuNPs and the p-nanoMB. See DOI: 10.1039/c5nr04618a

Discreet passive explosive detection through 2-sided wave guided fluorescence

DOEpatents

Harper, Ross James; la Grone, Marcus; Fisher, Mark

2012-10-16

The current invention provides a passive sampling device suitable for collecting and detecting the presence of target analytes. In particular, the passive sampling device is suitable for detecting nitro-aromatic compounds. The current invention further provides a passive sampling device reader suitable for determining the collection of target analytes. Additionally, the current invention provides methods for detecting target analytes using the passive sampling device and the passive sampling device reader.

Mass Spectrometry Based Ultrasensitive DNA Methylation Profiling Using Target Fragmentation Assay.

PubMed

Lin, Xiang-Cheng; Zhang, Ting; Liu, Lan; Tang, Hao; Yu, Ru-Qin; Jiang, Jian-Hui

2016-01-19

Efficient tools for profiling DNA methylation in specific genes are essential for epigenetics and clinical diagnostics. Current DNA methylation profiling techniques have been limited by inconvenient implementation, requirements of specific reagents, and inferior accuracy in quantifying methylation degree. We develop a novel mass spectrometry method, target fragmentation assay (TFA), which enable to profile methylation in specific sequences. This method combines selective capture of DNA target from restricted cleavage of genomic DNA using magnetic separation with MS detection of the nonenzymatic hydrolysates of target DNA. This method is shown to be highly sensitive with a detection limit as low as 0.056 amol, allowing direct profiling of methylation using genome DNA without preamplification. Moreover, this method offers a unique advantage in accurately determining DNA methylation level. The clinical applicability was demonstrated by DNA methylation analysis using prostate tissue samples, implying the potential of this method as a useful tool for DNA methylation profiling in early detection of related diseases.

B-spline based image tracking by detection

NASA Astrophysics Data System (ADS)

Balaji, Bhashyam; Sithiravel, Rajiv; Damini, Anthony; Kirubarajan, Thiagalingam; Rajan, Sreeraman

2016-05-01

Visual image tracking involves the estimation of the motion of any desired targets in a surveillance region using a sequence of images. A standard method of isolating moving targets in image tracking uses background subtraction. The standard background subtraction method is often impacted by irrelevant information in the images, which can lead to poor performance in image-based target tracking. In this paper, a B-Spline based image tracking is implemented. The novel method models the background and foreground using the B-Spline method followed by a tracking-by-detection algorithm. The effectiveness of the proposed algorithm is demonstrated.

Protein detection through different platforms of immuno-loop-mediated isothermal amplification

NASA Astrophysics Data System (ADS)

Pourhassan-Moghaddam, Mohammad; Rahmati-Yamchi, Mohammad; Akbarzadeh, Abolfazl; Daraee, Hadis; Nejati-Koshki, Kazem; Hanifehpour, Younes; Joo, Sang Woo

2013-11-01

Different immunoassay-based methods have been devised to detect protein targets. These methods have some challenges that make them inefficient for assaying ultra-low-amounted proteins. ELISA, iPCR, iRCA, and iNASBA are the common immunoassay-based methods of protein detection, each of which has specific and common technical challenges making it necessary to introduce a novel method in order to avoid their problems for detection of target proteins. Here we propose a new method nominated as `immuno-loop-mediated isothermal amplification' or `iLAMP'. This new method is free from the problems of the previous methods and has significant advantages over them. In this paper we also offer various configurations in order to improve the applicability of this method in real-world sample analyses. Important potential applications of this method are stated as well.

Amplification of biological targets via on-chip culture for biosensing

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

Harper, Jason C.; Edwards, Thayne L.; Carson, Bryan

The present invention, in part, relates to methods and apparatuses for on-chip amplification and/or detection of various targets, including biological targets and any amplifiable targets. In some examples, the microculture apparatus includes a single-use, normally-closed fluidic valve that is initially maintained in the closed position by a valve element bonded to an adhesive coating. The valve is opened using a magnetic force. The valve element includes a magnetic material or metal. Such apparatuses and methods are useful for in-field or real-time detection of targets, especially in limited resource settings.

Comparison of PCR-based methods for the simultaneous detection of Neisseria meningitidis, Haemophilus influenzae, and Streptococcus pneumoniae in clinical samples.

PubMed

de Filippis, Ivano; de Andrade, Claudia Ferreira; Caldeira, Nathalia; de Azevedo, Aline Carvalho; de Almeida, Antonio Eugenio

2016-01-01

Several in-house PCR-based assays have been described for the detection of bacterial meningitis caused by Neisseria meningitidis, Streptococcus pneumoniae, and Haemophilus influenzae from clinical samples. PCR-based methods targeting different bacterial genes are frequently used by different laboratories worldwide, but no standard method has ever been established. The aim of our study was to compare different in-house and a commercial PCR-based tests for the detection of bacterial pathogens causing meningitis and invasive disease in humans. A total of 110 isolates and 134 clinical samples (99 cerebrospinal fluid and 35 blood samples) collected from suspected cases of invasive disease were analyzed. Specific sets of primers frequently used for PCR-diagnosis of the three pathogens were used and compared with the results achieved using the multiplex approach described here. Several different gene targets were used for each microorganism, namely ctrA, crgA and nspA for N. meningitidis, ply for S. pneumoniae, P6 and bexA for H. influenzae. All used methods were fast, specific and sensitive, while some of the targets used for the in-house PCR assay detected lower concentrations of genomic DNA than the commercial method. An additional PCR reaction is described for the differentiation of capsulated and non-capsulated H. influenzae strains, the while commercial method only detects capsulated strains. The in-house PCR methods here compared showed to be rapid, sensitive, highly specific, and cheaper than commercial methods. The in-house PCR methods could be easily adopted by public laboratories of developing countries for diagnostic purposes. The best results were achieved using primers targeting the genes nspA, ply, and P6 which were able to detect the lowest DNA concentrations for each specific target. Copyright © 2016 Elsevier Editora Ltda. All rights reserved.

Development of a general method for detection and quantification of the P35S promoter based on assessment of existing methods

PubMed Central

Wu, Yuhua; Wang, Yulei; Li, Jun; Li, Wei; Zhang, Li; Li, Yunjing; Li, Xiaofei; Li, Jun; Zhu, Li; Wu, Gang

2014-01-01

The Cauliflower mosaic virus (CaMV) 35S promoter (P35S) is a commonly used target for detection of genetically modified organisms (GMOs). There are currently 24 reported detection methods, targeting different regions of the P35S promoter. Initial assessment revealed that due to the absence of primer binding sites in the P35S sequence, 19 of the 24 reported methods failed to detect P35S in MON88913 cotton, and the other two methods could only be applied to certain GMOs. The rest three reported methods were not suitable for measurement of P35S in some testing events, because SNPs in binding sites of the primer/probe would result in abnormal amplification plots and poor linear regression parameters. In this study, we discovered a conserved region in the P35S sequence through sequencing of P35S promoters from multiple transgenic events, and developed new qualitative and quantitative detection systems targeting this conserved region. The qualitative PCR could detect the P35S promoter in 23 unique GMO events with high specificity and sensitivity. The quantitative method was suitable for measurement of P35S promoter, exhibiting good agreement between the amount of template and Ct values for each testing event. This study provides a general P35S screening method, with greater coverage than existing methods. PMID:25483893

Multi-Target State Extraction for the SMC-PHD Filter

PubMed Central

Si, Weijian; Wang, Liwei; Qu, Zhiyu

2016-01-01

The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter has been demonstrated to be a favorable method for multi-target tracking. However, the time-varying target states need to be extracted from the particle approximation of the posterior PHD, which is difficult to implement due to the unknown relations between the large amount of particles and the PHD peaks representing potential target locations. To address this problem, a novel multi-target state extraction algorithm is proposed in this paper. By exploiting the information of measurements and particle likelihoods in the filtering stage, we propose a validation mechanism which aims at selecting effective measurements and particles corresponding to detected targets. Subsequently, the state estimates of the detected and undetected targets are performed separately: the former are obtained from the particle clusters directed by effective measurements, while the latter are obtained from the particles corresponding to undetected targets via clustering method. Simulation results demonstrate that the proposed method yields better estimation accuracy and reliability compared to existing methods. PMID:27322274

Compact Surface Plasmon Resonance Biosensor for Fieldwork Environmental Detection

NASA Astrophysics Data System (ADS)

Boyd, Margrethe; Drake, Madison; Stipe, Kristian; Serban, Monica; Turner, Ivana; Thomas, Aaron; Macaluso, David

2017-04-01

The ability to accurately and reliably detect biomolecular targets is important in innumerable applications, including the identification of food-borne parasites, viral pathogens in human tissue, and environmental pollutants. While detection methods do exist, they are typically slow, expensive, and restricted to laboratory use. The method of surface plasmon resonance based biosensing offers a unique opportunity to characterize molecular targets while avoiding these constraints. By incorporating a plasmon-supporting gold film within a prism/laser optical system, it is possible to reliably detect and quantify the presence of specific biomolecules of interest in real time. This detection is accomplished by observing shifts in plasmon formation energies corresponding to optical absorption due to changes in index of refraction near the gold-prism interface caused by the binding of target molecules. A compact, inexpensive, battery-powered surface plasmon resonance biosensor based on this method is being developed at the University of Montana to detect waterborne pollutants in field-based environmental research.

Development of a candidate reference material for adventitious virus detection in vaccine and biologicals manufacturing by deep sequencing

PubMed Central

Mee, Edward T.; Preston, Mark D.; Minor, Philip D.; Schepelmann, Silke; Huang, Xuening; Nguyen, Jenny; Wall, David; Hargrove, Stacey; Fu, Thomas; Xu, George; Li, Li; Cote, Colette; Delwart, Eric; Li, Linlin; Hewlett, Indira; Simonyan, Vahan; Ragupathy, Viswanath; Alin, Voskanian-Kordi; Mermod, Nicolas; Hill, Christiane; Ottenwälder, Birgit; Richter, Daniel C.; Tehrani, Arman; Jacqueline, Weber-Lehmann; Cassart, Jean-Pol; Letellier, Carine; Vandeputte, Olivier; Ruelle, Jean-Louis; Deyati, Avisek; La Neve, Fabio; Modena, Chiara; Mee, Edward; Schepelmann, Silke; Preston, Mark; Minor, Philip; Eloit, Marc; Muth, Erika; Lamamy, Arnaud; Jagorel, Florence; Cheval, Justine; Anscombe, Catherine; Misra, Raju; Wooldridge, David; Gharbia, Saheer; Rose, Graham; Ng, Siemon H.S.; Charlebois, Robert L.; Gisonni-Lex, Lucy; Mallet, Laurent; Dorange, Fabien; Chiu, Charles; Naccache, Samia; Kellam, Paul; van der Hoek, Lia; Cotten, Matt; Mitchell, Christine; Baier, Brian S.; Sun, Wenping; Malicki, Heather D.

2016-01-01

Background Unbiased deep sequencing offers the potential for improved adventitious virus screening in vaccines and biotherapeutics. Successful implementation of such assays will require appropriate control materials to confirm assay performance and sensitivity. Methods A common reference material containing 25 target viruses was produced and 16 laboratories were invited to process it using their preferred adventitious virus detection assay. Results Fifteen laboratories returned results, obtained using a wide range of wet-lab and informatics methods. Six of 25 target viruses were detected by all laboratories, with the remaining viruses detected by 4–14 laboratories. Six non-target viruses were detected by three or more laboratories. Conclusion The study demonstrated that a wide range of methods are currently used for adventitious virus detection screening in biological products by deep sequencing and that they can yield significantly different results. This underscores the need for common reference materials to ensure satisfactory assay performance and enable comparisons between laboratories. PMID:26709640

Controllable assembly and disassembly of nanoparticle systems via protein and DNA agents

DOEpatents

Lee, Soo-Kwan; Gang, Oleg; van der Lelie, Daniel

2014-05-20

The invention relates to the use of peptides, proteins, and other oligomers to provide a means by which normally quenched nanoparticle fluorescence may be recovered upon detection of a target molecule. Further, the inventive technology provides a structure and method to carry out detection of target molecules without the need to label the target molecules before detection. In another aspect, a method for forming arbitrarily shaped two- and three-dimensional protein-mediated nanoparticle structures and the resulting structures are described. Proteins mediating structure formation may themselves be functionalized with a variety of useful moieties, including catalytic functional groups.

Personal glucose meters for detection and quantification of a broad range of analytes

DOEpatents

Lu, Yi; Xiang, Yu

2015-02-03

A general methodology for the development of highly sensitive and selective sensors that can achieve portable, low-cost and quantitative detection of a broad range of targets using only a personal glucose meter (PGM) is disclosed. The method uses recognition molecules that are specific for a target agent, enzymes that can convert an enzyme substrate into glucose, and PGM. Also provided are sensors, which can include a solid support to which is attached a recognition molecule that permits detection of a target agent, wherein the recognition molecule specifically binds to the target agent in the presence of the target agent but not significantly to other agents as well as an enzyme that can catalyze the conversion of a substance into glucose, wherein the enzyme is attached directly or indirectly to the recognition molecule, and wherein in the presence of the target agent the enzyme can convert the substance into glucose. The disclosed sensors can be part of a lateral flow device. Methods of using such sensors for detecting target agents are also provided.

Target-triggering multiple-cycle signal amplification strategy for ultrasensitive detection of DNA based on QCM and SPR.

PubMed

Song, Weiling; Yin, Wenshuo; Sun, Wenbo; Guo, Xiaoyan; He, Peng; Yang, Xiaoyan; Zhang, Xiaoru

2018-04-24

Detection of ultralow concentrations of nucleic acid sequences is a central challenge in the early diagnosis of genetic diseases. Herein, we developed a target-triggering cascade multiple cycle amplification for ultrasensitive DNA detection using quartz crystal microbalance (QCM) and surface plasmon resonance (SPR). It was based on the exonuclease Ⅲ (Exo Ⅲ)-assisted signal amplification and the hybridization chain reaction (HCR). The streptavidin-coated Au-NPs (Au-NPs-SA) were assembled on the HCR products as recognition element. Upon sensing of target DNA, the duplex DNA probe triggered the Exo Ⅲ cleavage process, accompanied by generating a new secondary target DNA and releasing target DNA. The released target DNA and the secondary target DNA were recycled. Simultaneously, numerous single strands were liberated and acted as the trigger of HCR to generate further signal amplification, resulting in the immobilization of abundant Au-NPs-SA on the gold substrate. The QCM sensor results were found to be comparable to that achieved using a SPR sensor platform. This method exhibited a high sensitivity toward target DNA with a detection limit of 0.70 fM. The high sensitivity and specificity make this method a great potential for detecting DNA with trace amounts in bioanalysis and clinical biomedicine. Copyright © 2018 Elsevier Inc. All rights reserved.

Mini-lidar sensor for the remote stand-off sensing of chemical/biological substances and method for sensing same

DOEpatents

Ray, Mark D.; Sedlacek, Arthur J.

2003-08-19

A method and apparatus for remote, stand-off, and high efficiency spectroscopic detection of biological and chemical substances. The apparatus including an optical beam transmitter which transmits a beam having an axis of transmission to a target, the beam comprising at least a laser emission. An optical detector having an optical detection path to the target is provided for gathering optical information. The optical detection path has an axis of optical detection. A beam alignment device fixes the transmitter proximal to the detector and directs the beam to the target along the optical detection path such that the axis of transmission is within the optical detection path. Optical information gathered by the optical detector is analyzed by an analyzer which is operatively connected to the detector.

Ship detection in optical remote sensing images based on deep convolutional neural networks

NASA Astrophysics Data System (ADS)

Yao, Yuan; Jiang, Zhiguo; Zhang, Haopeng; Zhao, Danpei; Cai, Bowen

2017-10-01

Automatic ship detection in optical remote sensing images has attracted wide attention for its broad applications. Major challenges for this task include the interference of cloud, wave, wake, and the high computational expenses. We propose a fast and robust ship detection algorithm to solve these issues. The framework for ship detection is designed based on deep convolutional neural networks (CNNs), which provide the accurate locations of ship targets in an efficient way. First, the deep CNN is designed to extract features. Then, a region proposal network (RPN) is applied to discriminate ship targets and regress the detection bounding boxes, in which the anchors are designed by intrinsic shape of ship targets. Experimental results on numerous panchromatic images demonstrate that, in comparison with other state-of-the-art ship detection methods, our method is more efficient and achieves higher detection accuracy and more precise bounding boxes in different complex backgrounds.

Method and apparatus for detection of fluorescently labeled materials

DOEpatents

Stern, David; Fiekowsky, Peter

2004-05-25

Fluorescently marked targets bind to a substrate 230 synthesized with polymer sequences at known locations. The targets are detected by exposing selected regions of the substrate 230 to light from a light source 100 and detecting the photons from the light fluoresced therefrom, and repeating the steps of exposure and detection until the substrate 230 is completely examined. The resulting data can be used to determine binding affinity of the targets to specific polymer sequences.

Multi-laboratory evaluations of the performance of Catellicoccus marimammalium PCR assays developed to target gull fecal sources

USGS Publications Warehouse

Sinigalliano, Christopher D.; Ervin, Jared S.; Van De Werfhorst, Laurie C.; Badgley, Brian D.; Ballestée, Elisenda; Bartkowiaka, Jakob; Boehm, Alexandria B.; Byappanahalli, Muruleedhara N.; Goodwin, Kelly D.; Gourmelon, Michèle; Griffith, John; Holden, Patricia A.; Jay, Jenny; Layton, Blythe; Lee, Cheonghoon; Lee, Jiyoung; Meijer, Wim G.; Noble, Rachel; Raith, Meredith; Ryu, Hodon; Sadowsky, Michael J.; Schriewer, Alexander; Wang, Dan; Wanless, David; Whitman, Richard; Wuertz, Stefan; Santo Domingo, Jorge W.

2013-01-01

Here we report results from a multi-laboratory (n = 11) evaluation of four different PCR methods targeting the 16S rRNA gene of Catellicoccus marimammalium originally developed to detect gull fecal contamination in coastal environments. The methods included a conventional end-point PCR method, a SYBR® Green qPCR method, and two TaqMan® qPCR methods. Different techniques for data normalization and analysis were tested. Data analysis methods had a pronounced impact on assay sensitivity and specificity calculations. Across-laboratory standardization of metrics including the lower limit of quantification (LLOQ), target detected but not quantifiable (DNQ), and target not detected (ND) significantly improved results compared to results submitted by individual laboratories prior to definition standardization. The unit of measure used for data normalization also had a pronounced effect on measured assay performance. Data normalization to DNA mass improved quantitative method performance as compared to enterococcus normalization. The MST methods tested here were originally designed for gulls but were found in this study to also detect feces from other birds, particularly feces composited from pigeons. Sequencing efforts showed that some pigeon feces from California contained sequences similar to C. marimammalium found in gull feces. These data suggest that the prevalence, geographic scope, and ecology of C. marimammalium in host birds other than gulls require further investigation. This study represents an important first step in the multi-laboratory assessment of these methods and highlights the need to broaden and standardize additional evaluations, including environmentally relevant target concentrations in ambient waters from diverse geographic regions.

An Algorithm Based Wavelet Entropy for Shadowing Effect of Human Detection Using Ultra-Wideband Bio-Radar

PubMed Central

Liu, Miao; Zhang, Yang; Liang, Fulai; Qi, Fugui; Lv, Hao; Wang, Jianqi; Zhang, Yang

2017-01-01

Ultra-wide band (UWB) radar for short-range human target detection is widely used to find and locate survivors in some rescue missions after a disaster. The results of the application of bistatic UWB radar for detecting multi-stationary human targets have shown that human targets close to the radar antennas are very often visible, while those farther from radar antennas are detected with less reliability. In this paper, on account of the significant difference of frequency content between the echo signal of the human target and that of noise in the shadowing region, an algorithm based on wavelet entropy is proposed to detect multiple targets. Our findings indicate that the entropy value of human targets was much lower than that of noise. Compared with the method of adaptive filtering and the energy spectrum, wavelet entropy can accurately detect the person farther from the radar antennas, and it can be employed as a useful tool in detecting multiple targets by bistatic UWB radar. PMID:28973988

An Algorithm Based Wavelet Entropy for Shadowing Effect of Human Detection Using Ultra-Wideband Bio-Radar.

PubMed

Xue, Huijun; Liu, Miao; Zhang, Yang; Liang, Fulai; Qi, Fugui; Chen, Fuming; Lv, Hao; Wang, Jianqi; Zhang, Yang

2017-09-30

Ultra-wide band (UWB) radar for short-range human target detection is widely used to find and locate survivors in some rescue missions after a disaster. The results of the application of bistatic UWB radar for detecting multi-stationary human targets have shown that human targets close to the radar antennas are very often visible, while those farther from radar antennas are detected with less reliability. In this paper, on account of the significant difference of frequency content between the echo signal of the human target and that of noise in the shadowing region, an algorithm based on wavelet entropy is proposed to detect multiple targets. Our findings indicate that the entropy value of human targets was much lower than that of noise. Compared with the method of adaptive filtering and the energy spectrum, wavelet entropy can accurately detect the person farther from the radar antennas, and it can be employed as a useful tool in detecting multiple targets by bistatic UWB radar.

[The establishment of a novel method of nano-immunomagnetic separation and Real-time PCR for detecting Vibrio cholerae from seafood].

PubMed

Cheng, Jinxia; Zeng, Jing; Liu, Li; Wei, Haiyan; Zhao, Xiaojuan; Zhang, Ximeng; Zhang, Lei; Zhang, Haiyu

2014-02-01

A novel method of Nano-Immunomagnetic Separation (Nano-IMS) plus Real-time PCR was established for detecting Vibrio cholerae. The Nano-Immunomagnetic Beads were created by using the monoclonal antibody of Vibrio cholerae, which was named Nano-IMB-Vc. Nano-IMB-Vc has specific adsorption of Vibrio cholerae, combined with Real-time PCR technology, a method for rapid detection of Vibrio cholerae was established. The capture specificity of Nano-IMB-Vc was tested by using 15 bacteria strains. The specificity of Real-time PCR method was tested by using 102 targets and 101 non-targets bacteria strains. The sensitivity of Nano-IMS plus Real-time PCR were tested in pure culture and in artificial samples and compared with NMKL No.156. The capture ratio of Nano-IMB-Vc was reached 70.2% at the level of 10(3) CFU/ml. In pure culture, the sensitivity of Nano-IMS plus Real-time PCR was reached at 5.4×10(2) CFU/ml. The specific of Real-time PCR method was tested by using 102 targets and 101 non-targets bacteria. The results showed that 102 strains of Vibrio cholerae test results were all positive, and the rest of the 101 strains of non-target bacteria test results were negative. No cross-reaction was founded. Add 1 CFU vibrio cholerae per 25 g sample, it could be detect with Nano-IMS plus Real-time PCR method after 8 hours enrichment. The Nano-IMS plus Real-time PCR method of Vibrio cholerae established in this study has good specificity and sensitivity, which could be applied to the rapid detection of Vibrio cholerae.

Triplex in-situ hybridization

DOEpatents

Fresco, Jacques R.; Johnson, Marion D.

2002-01-01

Disclosed are methods for detecting in situ the presence of a target sequence in a substantially double-stranded nucleic acid segment, which comprises: a) contacting in situ under conditions suitable for hybridization a substantially double-stranded nucleic acid segment with a detectable third strand, said third strand being capable of hybridizing to at least a portion of the target sequence to form a triple-stranded structure, if said target sequence is present; and b) detecting whether hybridization between the third strand and the target sequence has occured.

Infrared small target detection with kernel Fukunaga Koontz transform

NASA Astrophysics Data System (ADS)

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

2007-09-01

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

High-Speed Incoming Infrared Target Detection by Fusion of Spatial and Temporal Detectors

PubMed Central

Kim, Sungho

2015-01-01

This paper presents a method for detecting high-speed incoming targets by the fusion of spatial and temporal detectors to achieve a high detection rate for an active protection system (APS). The incoming targets have different image velocities according to the target-camera geometry. Therefore, single-target detector-based approaches, such as a 1D temporal filter, 2D spatial filter and 3D matched filter, cannot provide a high detection rate with moderate false alarms. The target speed variation was analyzed according to the incoming angle and target velocity. The speed of the distant target at the firing time is almost stationary and increases slowly. The speed varying targets are detected stably by fusing the spatial and temporal filters. The stationary target detector is activated by an almost zero temporal contrast filter (TCF) and identifies targets using a spatial filter called the modified mean subtraction filter (M-MSF). A small motion (sub-pixel velocity) target detector is activated by a small TCF value and finds targets using the same spatial filter. A large motion (pixel-velocity) target detector works when the TCF value is high. The final target detection is terminated by fusing the three detectors based on the threat priority. The experimental results of the various target sequences show that the proposed fusion-based target detector produces the highest detection rate with an acceptable false alarm rate. PMID:25815448

Optimization of OT-MACH Filter Generation for Target Recognition

NASA Technical Reports Server (NTRS)

Johnson, Oliver C.; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin

2009-01-01

An automatic Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter generator for use in a gray-scale optical correlator (GOC) has been developed for improved target detection at JPL. While the OT-MACH filter has been shown to be an optimal filter for target detection, actually solving for the optimum is too computationally intensive for multiple targets. Instead, an adaptive step gradient descent method was tested to iteratively optimize the three OT-MACH parameters, alpha, beta, and gamma. The feedback for the gradient descent method was a composite of the performance measures, correlation peak height and peak to side lobe ratio. The automated method generated and tested multiple filters in order to approach the optimal filter quicker and more reliably than the current manual method. Initial usage and testing has shown preliminary success at finding an approximation of the optimal filter, in terms of alpha, beta, gamma values. This corresponded to a substantial improvement in detection performance where the true positive rate increased for the same average false positives per image.

Evaluation of Targeted Next-Generation Sequencing for Detection of Bovine Pathogens in Clinical Samples.

PubMed

Anis, Eman; Hawkins, Ian K; Ilha, Marcia R S; Woldemeskel, Moges W; Saliki, Jeremiah T; Wilkes, Rebecca P

2018-07-01

The laboratory diagnosis of infectious diseases, especially those caused by mixed infections, is challenging. Routinely, it requires submission of multiple samples to separate laboratories. Advances in next-generation sequencing (NGS) have provided the opportunity for development of a comprehensive method to identify infectious agents. This study describes the use of target-specific primers for PCR-mediated amplification with the NGS technology in which pathogen genomic regions of interest are enriched and selectively sequenced from clinical samples. In the study, 198 primers were designed to target 43 common bovine and small-ruminant bacterial, fungal, viral, and parasitic pathogens, and a bioinformatics tool was specifically constructed for the detection of targeted pathogens. The primers were confirmed to detect the intended pathogens by testing reference strains and isolates. The method was then validated using 60 clinical samples (including tissues, feces, and milk) that were also tested with other routine diagnostic techniques. The detection limits of the targeted NGS method were evaluated using 10 representative pathogens that were also tested by quantitative PCR (qPCR), and the NGS method was able to detect the organisms from samples with qPCR threshold cycle ( C T ) values in the 30s. The method was successful for the detection of multiple pathogens in the clinical samples, including some additional pathogens missed by the routine techniques because the specific tests needed for the particular organisms were not performed. The results demonstrate the feasibility of the approach and indicate that it is possible to incorporate NGS as a diagnostic tool in a cost-effective manner into a veterinary diagnostic laboratory. Copyright © 2018 Anis et al.

On-line bolt-loosening detection method of key components of running trains using binocular vision

NASA Astrophysics Data System (ADS)

Xie, Yanxia; Sun, Junhua

2017-11-01

Bolt loosening, as one of hidden faults, affects the running quality of trains and even causes serious safety accidents. However, the developed fault detection approaches based on two-dimensional images cannot detect bolt-loosening due to lack of depth information. Therefore, we propose a novel online bolt-loosening detection method using binocular vision. Firstly, the target detection model based on convolutional neural network (CNN) is used to locate the target regions. And then, stereo matching and three-dimensional reconstruction are performed to detect bolt-loosening faults. The experimental results show that the looseness of multiple bolts can be characterized by the method simultaneously. The measurement repeatability and precision are less than 0.03mm, 0.09mm respectively, and its relative error is controlled within 1.09%.

Applications of independent component analysis in SAR images

NASA Astrophysics Data System (ADS)

Huang, Shiqi; Cai, Xinhua; Hui, Weihua; Xu, Ping

2009-07-01

The detection of faint, small and hidden targets in synthetic aperture radar (SAR) image is still an issue for automatic target recognition (ATR) system. How to effectively separate these targets from the complex background is the aim of this paper. Independent component analysis (ICA) theory can enhance SAR image targets and improve signal clutter ratio (SCR), which benefits to detect and recognize faint targets. Therefore, this paper proposes a new SAR image target detection algorithm based on ICA. In experimental process, the fast ICA (FICA) algorithm is utilized. Finally, some real SAR image data is used to test the method. The experimental results verify that the algorithm is feasible, and it can improve the SCR of SAR image and increase the detection rate for the faint small targets.

Optimised padlock probe ligation and microarray detection of multiple (non-authorised) GMOs in a single reaction

PubMed Central

Prins, Theo W; van Dijk, Jeroen P; Beenen, Henriek G; Van Hoef, AM Angeline; Voorhuijzen, Marleen M; Schoen, Cor D; Aarts, Henk JM; Kok, Esther J

2008-01-01

Background To maintain EU GMO regulations, producers of new GM crop varieties need to supply an event-specific method for the new variety. As a result methods are nowadays available for EU-authorised genetically modified organisms (GMOs), but only to a limited extent for EU-non-authorised GMOs (NAGs). In the last decade the diversity of genetically modified (GM) ingredients in food and feed has increased significantly. As a result of this increase GMO laboratories currently need to apply many different methods to establish to potential presence of NAGs in raw materials and complex derived products. Results In this paper we present an innovative method for detecting (approved) GMOs as well as the potential presence of NAGs in complex DNA samples containing different crop species. An optimised protocol has been developed for padlock probe ligation in combination with microarray detection (PPLMD) that can easily be scaled up. Linear padlock probes targeted against GMO-events, -elements and -species have been developed that can hybridise to their genomic target DNA and are visualised using microarray hybridisation. In a tenplex PPLMD experiment, different genomic targets in Roundup-Ready soya, MON1445 cotton and Bt176 maize were detected down to at least 1%. In single experiments, the targets were detected down to 0.1%, i.e. comparable to standard qPCR. Conclusion Compared to currently available methods this is a significant step forward towards multiplex detection in complex raw materials and derived products. It is shown that the PPLMD approach is suitable for large-scale detection of GMOs in real-life samples and provides the possibility to detect and/or identify NAGs that would otherwise remain undetected. PMID:19055784

Optimised padlock probe ligation and microarray detection of multiple (non-authorised) GMOs in a single reaction.

PubMed

Prins, Theo W; van Dijk, Jeroen P; Beenen, Henriek G; Van Hoef, Am Angeline; Voorhuijzen, Marleen M; Schoen, Cor D; Aarts, Henk J M; Kok, Esther J

2008-12-04

To maintain EU GMO regulations, producers of new GM crop varieties need to supply an event-specific method for the new variety. As a result methods are nowadays available for EU-authorised genetically modified organisms (GMOs), but only to a limited extent for EU-non-authorised GMOs (NAGs). In the last decade the diversity of genetically modified (GM) ingredients in food and feed has increased significantly. As a result of this increase GMO laboratories currently need to apply many different methods to establish to potential presence of NAGs in raw materials and complex derived products. In this paper we present an innovative method for detecting (approved) GMOs as well as the potential presence of NAGs in complex DNA samples containing different crop species. An optimised protocol has been developed for padlock probe ligation in combination with microarray detection (PPLMD) that can easily be scaled up. Linear padlock probes targeted against GMO-events, -elements and -species have been developed that can hybridise to their genomic target DNA and are visualised using microarray hybridisation.In a tenplex PPLMD experiment, different genomic targets in Roundup-Ready soya, MON1445 cotton and Bt176 maize were detected down to at least 1%. In single experiments, the targets were detected down to 0.1%, i.e. comparable to standard qPCR. Compared to currently available methods this is a significant step forward towards multiplex detection in complex raw materials and derived products. It is shown that the PPLMD approach is suitable for large-scale detection of GMOs in real-life samples and provides the possibility to detect and/or identify NAGs that would otherwise remain undetected.

Fractal analysis of seafloor textures for target detection in synthetic aperture sonar imagery

NASA Astrophysics Data System (ADS)

Nabelek, T.; Keller, J.; Galusha, A.; Zare, A.

2018-04-01

Fractal analysis of an image is a mathematical approach to generate surface related features from an image or image tile that can be applied to image segmentation and to object recognition. In undersea target countermeasures, the targets of interest can appear as anomalies in a variety of contexts, visually different textures on the seafloor. In this paper, we evaluate the use of fractal dimension as a primary feature and related characteristics as secondary features to be extracted from synthetic aperture sonar (SAS) imagery for the purpose of target detection. We develop three separate methods for computing fractal dimension. Tiles with targets are compared to others from the same background textures without targets. The different fractal dimension feature methods are tested with respect to how well they can be used to detect targets vs. false alarms within the same contexts. These features are evaluated for utility using a set of image tiles extracted from a SAS data set generated by the U.S. Navy in conjunction with the Office of Naval Research. We find that all three methods perform well in the classification task, with a fractional Brownian motion model performing the best among the individual methods. We also find that the secondary features are just as useful, if not more so, in classifying false alarms vs. targets. The best classification accuracy overall, in our experimentation, is found when the features from all three methods are combined into a single feature vector.

Ship detection based on rotation-invariant HOG descriptors for airborne infrared images

NASA Astrophysics Data System (ADS)

Xu, Guojing; Wang, Jinyan; Qi, Shengxiang

2018-03-01

Infrared thermal imagery is widely used in various kinds of aircraft because of its all-time application. Meanwhile, detecting ships from infrared images attract lots of research interests in recent years. In the case of downward-looking infrared imagery, in order to overcome the uncertainty of target imaging attitude due to the unknown position relationship between the aircraft and the target, we propose a new infrared ship detection method which integrates rotation invariant gradient direction histogram (Circle Histogram of Oriented Gradient, C-HOG) descriptors and the support vector machine (SVM) classifier. In details, the proposed method uses HOG descriptors to express the local feature of infrared images to adapt to changes in illumination and to overcome sea clutter effects. Different from traditional computation of HOG descriptor, we subdivide the image into annular spatial bins instead of rectangle sub-regions, and then Radial Gradient Transform (RGT) on the gradient is applied to achieve rotation invariant histogram information. Considering the engineering application of airborne and real-time requirements, we use SVM for training ship target and non-target background infrared sample images to discriminate real ships from false targets. Experimental results show that the proposed method has good performance in both the robustness and run-time for infrared ship target detection with different rotation angles.

Micro Ring Grating Spectrometer with Adjustable Aperture

NASA Technical Reports Server (NTRS)

Park, Yeonjoon (Inventor); King, Glen C. (Inventor); Elliott, James R. (Inventor); Choi, Sang H. (Inventor)

2012-01-01

A spectrometer includes a micro-ring grating device having coaxially-aligned ring gratings for diffracting incident light onto a target focal point, a detection device for detecting light intensity, one or more actuators, and an adjustable aperture device defining a circular aperture. The aperture circumscribes a target focal point, and directs a light to the detection device. The aperture device is selectively adjustable using the actuators to select a portion of a frequency band for transmission to the detection device. A method of detecting intensity of a selected band of incident light includes directing incident light onto coaxially-aligned ring gratings of a micro-ring grating device, and diffracting the selected band onto a target focal point using the ring gratings. The method includes using an actuator to adjust an aperture device and pass a selected portion of the frequency band to a detection device for measuring the intensity of the selected portion.

Small target detection using objectness and saliency

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Evaluation of camouflage effectiveness using hyperspectral images

NASA Astrophysics Data System (ADS)

Zavvartorbati, Ahmad; Dehghani, Hamid; Rashidi, Ali Jabar

2017-10-01

Recent advances in camouflage engineering have made it more difficult to detect targets. Assessing the effectiveness of camouflage against different target detection methods leads to identifying the strengths and weaknesses of camouflage designs. One of the target detection methods is to analyze the content of the scene using remote sensing hyperspectral images. In the process of evaluating camouflage designs, there must be comprehensive and efficient evaluation criteria. Three parameters were considered as the main factors affecting the target detection and based on these factors, camouflage effectiveness assessment criteria were proposed. To combine the criteria in the form of a single equation, the equation used in target visual search models was employed and for determining the criteria, a model was presented based on the structure of the computational visual attention systems. Also, in software implementations on the HyMap hyperspectral image, a variety of camouflage levels were created for the real targets in the image. Assessing the camouflage levels using the proposed criteria, comparing and analyzing the results can show that the provided criteria and model are effective for the evaluation of camouflage designs using hyperspectral images.

Respiration-rate estimation of a moving target using impulse-based ultra wideband radars.

PubMed

Sharafi, Azadeh; Baboli, Mehran; Eshghi, Mohammad; Ahmadian, Alireza

2012-03-01

Recently, Ultra-wide band signals have become attractive for their particular advantage of having high spatial resolution and good penetration ability which makes them suitable in medical applications. One of these applications is wireless detection of heart rate and respiration rate. Two hypothesis of static environment and fixed patient are considered in the method presented in previous literatures which are not valid for long term monitoring of ambulant patients. In this article, a new method to detect the respiration rate of a moving target is presented. The first algorithm is applied to the simulated and experimental data for detecting respiration rate of a fixed target. Then, the second algorithm is developed to detect respiration rate of a moving target. The proposed algorithm uses correlation for body movement cancellation, and then detects the respiration rate based on energy in frequency domain. The results of algorithm prove an accuracy of 98.4 and 97% in simulated and experimental data, respectively.

Algorithm research on infrared imaging target extraction based on GAC model

NASA Astrophysics Data System (ADS)

Li, Yingchun; Fan, Youchen; Wang, Yanqing

2016-10-01

Good target detection and tracking technique is significantly meaningful to increase infrared target detection distance and enhance resolution capacity. For the target detection problem about infrared imagining, firstly, the basic principles of level set method and GAC model are is analyzed in great detail. Secondly, "convergent force" is added according to the defect that GAC model is stagnant outside the deep concave region and cannot reach deep concave edge to build the promoted GAC model. Lastly, the self-adaptive detection method in combination of Sobel operation and GAC model is put forward by combining the advantages that subject position of the target could be detected with Sobel operator and the continuous edge of the target could be obtained through GAC model. In order to verify the effectiveness of the model, the two groups of experiments are carried out by selecting the images under different noise effects. Besides, the comparative analysis is conducted with LBF and LIF models. The experimental result shows that target could be better locked through LIF and LBF algorithms for the slight noise effect. The accuracy of segmentation is above 0.8. However, as for the strong noise effect, the target and noise couldn't be distinguished under the strong interference of GAC, LIF and LBF algorithms, thus lots of non-target parts are extracted during iterative process. The accuracy of segmentation is below 0.8. The accurate target position is extracted through the algorithm proposed in this paper. Besides, the accuracy of segmentation is above 0.8.

Detection of dual-band infrared small target based on joint dynamic sparse representation

NASA Astrophysics Data System (ADS)

Zhou, Jinwei; Li, Jicheng; Shi, Zhiguang; Lu, Xiaowei; Ren, Dongwei

2015-10-01

Infrared small target detection is a crucial and yet still is a difficult issue in aeronautic and astronautic applications. Sparse representation is an important mathematic tool and has been used extensively in image processing in recent years. Joint sparse representation is applied in dual-band infrared dim target detection in this paper. Firstly, according to the characters of dim targets in dual-band infrared images, 2-dimension Gaussian intensity model was used to construct target dictionary, then the dictionary was classified into different sub-classes according to different positions of Gaussian function's center point in image block; The fact that dual-band small targets detection can use the same dictionary and the sparsity doesn't lie in atom-level but in sub-class level was utilized, hence the detection of targets in dual-band infrared images was converted to be a joint dynamic sparse representation problem. And the dynamic active sets were used to describe the sparse constraint of coefficients. Two modified sparsity concentration index (SCI) criteria was proposed to evaluate whether targets exist in the images. In experiments, it shows that the proposed algorithm can achieve better detecting performance and dual-band detection is much more robust to noise compared with single-band detection. Moreover, the proposed method can be expanded to multi-spectrum small target detection.

Detection of shallow buried objects using an autoregressive model on the ground penetrating radar signal

NASA Astrophysics Data System (ADS)

Nabelek, Daniel P.; Ho, K. C.

2013-06-01

The detection of shallow buried low-metal content objects using ground penetrating radar (GPR) is a challenging task. This is because these targets are right underneath the ground and the ground bounce reflection interferes with their detections. They do not create distinctive hyperbolic signatures as required by most existing GPR detection algorithms due to their special geometric shapes and low metal content. This paper proposes the use of the Autoregressive (AR) modeling method for the detection of these targets. We fit an A-scan of the GPR data to an AR model. It is found that the fitting error will be small when such a target is present and large when it is absent. The ratio of the energy in an Ascan before and after AR model fitting is used as the confidence value for detection. We also apply AR model fitting over scans and utilize the fitting residual energies over several scans to form a feature vector for improving the detections. Using the data collected from a government test site, the proposed method can improve the detection of this kind of targets by 30% compared to the pre-screener, at a false alarm rate of 0.002/m2.

Manifold structure preservative for hyperspectral target detection

NASA Astrophysics Data System (ADS)

Imani, Maryam

2018-05-01

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

Covariance descriptor fusion for target detection

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

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

PubMed Central

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

2014-01-01

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

Fast Vessel Detection in Gaofen-3 SAR Images with Ultrafine Strip-Map Mode

PubMed Central

Liu, Lei; Qiu, Xiaolan; Lei, Bin

2017-01-01

This study aims to detect vessels with lengths ranging from about 70 to 300 m, in Gaofen-3 (GF-3) SAR images with ultrafine strip-map (UFS) mode as fast as possible. Based on the analysis of the characteristics of vessels in GF-3 SAR imagery, an effective vessel detection method is proposed in this paper. Firstly, the iterative constant false alarm rate (CFAR) method is employed to detect the potential ship pixels. Secondly, the mean-shift operation is applied on each potential ship pixel to identify the candidate target region. During the mean-shift process, we maintain a selection matrix recording which pixels can be taken, and these pixels are called as the valid points of the candidate target. The l1 norm regression is used to extract the principal axis and detect the valid points. Finally, two kinds of false alarms, the bright line and the azimuth ambiguity, are removed by comparing the valid area of the candidate target with a pre-defined value and computing the displacement between the true target and the corresponding replicas respectively. Experimental results on three GF-3 SAR images with UFS mode demonstrate the effectiveness and efficiency of the proposed method. PMID:28678197

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

PubMed

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

2014-08-08

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

Highly sensitive fluorescence quantitative detection of specific DNA sequences with molecular beacons and nucleic acid dye SYBR Green I.

PubMed

Xiang, Dongshan; Zhai, Kun; Xiang, Wenjun; Wang, Lianzhi

2014-11-01

A highly sensitive fluorescence method of quantitative detection for specific DNA sequence is developed based on molecular beacon (MB) and nucleic acid dye SYBR Green I by synchronous fluorescence analysis. It is demonstrated by an oligonucleotide sequence of wild-type HBV (target DNA) as a model system. In this strategy, the fluorophore of MB is designed to be 6-carboxyfluorescein group (FAM), and the maximum excitation wavelength and maximum emission wavelength are both very close to that of SYBR Green I. In the presence of targets DNA, the MBs hybridize with the targets DNA and form double-strand DNA (dsDNA), the fluorophore FAM is separated from the quencher BHQ-1, thus the fluorophore emit fluorescence. At the same time, SYBR Green I binds to dsDNA, the fluorescence intensity of SYBR Green I is significantly enhanced. When targets DNA are detected by synchronous fluorescence analysis, the fluorescence peaks of FAM and SYBR Green I overlap completely, so the fluorescence signal of system will be significantly enhanced. Thus, highly sensitive fluorescence quantitative detection for DNA can be realized. Under the optimum conditions, the total fluorescence intensity of FAM and SYBR Green I exhibits good linear dependence on concentration of targets DNA in the range from 2×10(-11) to 2.5×10(-9)M. The detection limit of target DNA is estimated to be 9×10(-12)M (3σ). Compared with previously reported methods of detection DNA with MB, the proposed method can significantly enhance the detection sensitivity. Copyright © 2014 Elsevier B.V. All rights reserved.

Signal Amplification Technologies for the Detection of Nucleic Acids: from Cell-Free Analysis to Live-Cell Imaging.

PubMed

Fozooni, Tahereh; Ravan, Hadi; Sasan, Hosseinali

2017-12-01

Due to their unique properties, such as programmability, ligand-binding capability, and flexibility, nucleic acids can serve as analytes and/or recognition elements for biosensing. To improve the sensitivity of nucleic acid-based biosensing and hence the detection of a few copies of target molecule, different modern amplification methodologies, namely target-and-signal-based amplification strategies, have already been developed. These recent signal amplification technologies, which are capable of amplifying the signal intensity without changing the targets' copy number, have resulted in fast, reliable, and sensitive methods for nucleic acid detection. Working in cell-free settings, researchers have been able to optimize a variety of complex and quantitative methods suitable for deploying in live-cell conditions. In this study, a comprehensive review of the signal amplification technologies for the detection of nucleic acids is provided. We classify the signal amplification methodologies into enzymatic and non-enzymatic strategies with a primary focus on the methods that enable us to shift away from in vitro detecting to in vivo imaging. Finally, the future challenges and limitations of detection for cellular conditions are discussed.

Highly Sensitive Detection of Low-Abundance White Spot Syndrome Virus by a Pre-Amplification PCR Method.

PubMed

Pan, Xiaoming; Zhang, Yanfang; Sha, Xuejiao; Wang, Jing; Li, Jing; Dong, Ping; Liang, Xingguo

2017-03-28

White spot syndrome virus (WSSV) is a major threat to the shrimp farming industry and so far there is no effective therapy for it, and thus early diagnostic of WSSV is of great importance. However, at the early stage of infection, the extremely low-abundance of WSSV DNA challenges the detection sensitivity and accuracy of PCR. To effectively detect low-abundance WSSV, here we developed a pre-amplification PCR (pre-amp PCR) method to amplify trace amounts of WSSV DNA from massive background genomic DNA. Combining with normal specific PCR, 10 copies of target WSSV genes were detected from ~10 10 magnitude of backgrounds. In particular, multiple target genes were able to be balanced amplified with similar efficiency due to the usage of the universal primer. The efficiency of the pre-amp PCR was validated by nested-PCR and quantitative PCR, and pre-amp PCR showed higher efficiency than nested-PCR when multiple targets were detected. The developed method is particularly suitable for the super early diagnosis of WSSV, and has potential to be applied in other low-abundance sample detection cases.

Detection and analysis of protein ISGylation.

PubMed

Takeuchi, Tomoharu; Yokosawa, Hideyoshi

2008-01-01

ISG15 is a ubiquitin-like modifi er that is conjugated to target proteins by a sequential reaction catalyzed by E1/E2/E3 enzymes (protein ISGylation). ISG15 and protein ISGylation are upregulated by interferon stimuli. ISG15 functions as an antiviral protein against Sindbis virus and HIV-1, but the molecular mechanism remains unknown. Here we describe in detail methods for detecting and analyzing protein ISGylation. The methods consist of plasmid transfection and affi nity purifi cation of ISGylated proteins. In addition, we describe a method for detecting ISGylation of a target protein, Ubc13.

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

PubMed

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

2013-07-08

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

Evaluation of microplate immunocapture method for detection of Vibrio cholerae, Salmonella Typhi and Shigella flexneri from food.

PubMed

Fakruddin, Md; Hossain, Md Nur; Ahmed, Monzur Morshed

2017-08-29

Improved methods with better separation and concentration ability for detection of foodborne pathogens are in constant need. The aim of this study was to evaluate microplate immunocapture (IC) method for detection of Salmonella Typhi, Shigella flexneri and Vibrio cholerae from food samples to provide a better alternative to conventional culture based methods. The IC method was optimized for incubation time, bacterial concentration, and capture efficiency. 6 h incubation and log 6 CFU/ml cell concentration provided optimal results. The method was shown to be highly specific for the pathogens concerned. Capture efficiency (CE) was around 100% of the target pathogens, whereas CE was either zero or very low for non-target pathogens. The IC method also showed better pathogen detection ability at different concentrations of cells from artificially contaminated food samples in comparison with culture based methods. Performance parameter of the method was also comparable (Detection limit- 25 CFU/25 g; sensitivity 100%; specificity-96.8%; Accuracy-96.7%), even better than culture based methods (Detection limit- 125 CFU/25 g; sensitivity 95.9%; specificity-97%; Accuracy-96.2%). The IC method poses to be the potential to be used as a method of choice for detection of foodborne pathogens in routine laboratory practice after proper validation.

Efficient and Specific Detection of Salmonella in Food Samples Using a stn-Based Loop-Mediated Isothermal Amplification Method

PubMed Central

2015-01-01

The Salmonella enterotoxin (stn) gene exhibits high homology among S. enterica serovars and S. bongori. A set of 6 specific primers targeting the stn gene were designed for detection of Salmonella spp. using the loop-mediated isothermal amplification (LAMP) method. The primers amplified target sequences in all 102 strains of 87 serovars of Salmonella tested and no products were detected in 57 non-Salmonella strains. The detection limit in pure cultures was 5 fg DNA/reaction when amplified at 65°C for 25 min. The LAMP assay could detect Salmonella in artificially contaminated food samples as low as 220 cells/g of food without a preenrichment step. However, the sensitivity was increased 100-fold (~2 cells/g) following 5 hr preenrichment at 35°C. The LAMP technique, with a preenrichment step for 5 and 16 hr, was shown to give 100% specificity with food samples compared to the reference culture method in which 67 out of 90 food samples gave positive results. Different food matrixes did not interfere with LAMP detection which employed a simple boiling method for DNA template preparation. The results indicate that the LAMP method, targeting the stn gene, has great potential for detection of Salmonella in food samples with both high specificity and high sensitivity. PMID:26543859

Targeted Quantification of Isoforms of a Thylakoid-Bound Protein: MRM Method Development.

PubMed

Bru-Martínez, Roque; Martínez-Márquez, Ascensión; Morante-Carriel, Jaime; Sellés-Marchart, Susana; Martínez-Esteso, María José; Pineda-Lucas, José Luis; Luque, Ignacio

2018-01-01

Targeted mass spectrometric methods such as selected/multiple reaction monitoring (SRM/MRM) have found intense application in protein detection and quantification which competes with classical immunoaffinity techniques. It provides a universal procedure to develop a fast, highly specific, sensitive, accurate, and cheap methodology for targeted detection and quantification of proteins based on the direct analysis of their surrogate peptides typically generated by tryptic digestion. This methodology can be advantageously applied in the field of plant proteomics and particularly for non-model species since immunoreagents are scarcely available. Here, we describe the issues to take into consideration in order to develop a MRM method to detect and quantify isoforms of the thylakoid-bound protein polyphenol oxidase from the non-model and database underrepresented species Eriobotrya japonica Lindl.

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

PubMed

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

2013-12-01

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

TINS, target immobilized NMR screening: an efficient and sensitive method for ligand discovery.

PubMed

Vanwetswinkel, Sophie; Heetebrij, Robert J; van Duynhoven, John; Hollander, Johan G; Filippov, Dmitri V; Hajduk, Philip J; Siegal, Gregg

2005-02-01

We propose a ligand screening method, called TINS (target immobilized NMR screening), which reduces the amount of target required for the fragment-based approach to drug discovery. Binding is detected by comparing 1D NMR spectra of compound mixtures in the presence of a target immobilized on a solid support to a control sample. The method has been validated by the detection of a variety of ligands for protein and nucleic acid targets (K(D) from 60 to 5000 muM). The ligand binding capacity of a protein was undiminished after 2000 different compounds had been applied, indicating the potential to apply the assay for screening typical fragment libraries. TINS can be used in competition mode, allowing rapid characterization of the ligand binding site. TINS may allow screening of targets that are difficult to produce or that are insoluble, such as membrane proteins.

Image Discrimination Models for Object Detection in Natural Backgrounds

NASA Technical Reports Server (NTRS)

Ahumada, A. J., Jr.

2000-01-01

This paper reviews work accomplished and in progress at NASA Ames relating to visual target detection. The focus is on image discrimination models, starting with Watson's pioneering development of a simple spatial model and progressing through this model's descendents and extensions. The application of image discrimination models to target detection will be described and results reviewed for Rohaly's vehicle target data and the Search 2 data. The paper concludes with a description of work we have done to model the process by which observers learn target templates and methods for elucidating those templates.

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.

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

PubMed

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

2017-12-21

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

Environmental DNA detection of rare and invasive fish species in two Great Lakes tributaries.

PubMed

Balasingham, Katherine D; Walter, Ryan P; Mandrak, Nicholas E; Heath, Daniel D

2018-01-01

The extraction and characterization of DNA from aquatic environmental samples offers an alternative, noninvasive approach for the detection of rare species. Environmental DNA, coupled with PCR and next-generation sequencing ("metabarcoding"), has proven to be very sensitive for the detection of rare aquatic species. Our study used a custom-designed group-specific primer set and next-generation sequencing for the detection of three species at risk (Eastern Sand Darter, Ammocrypta pellucida; Northern Madtom, Noturus stigmosus; and Silver Shiner, Notropis photogenis), one invasive species (Round Goby, Neogobius melanostomus) and an additional 78 native species from two large Great Lakes tributary rivers in southern Ontario, Canada: the Grand River and the Sydenham River. Of 82 fish species detected in both rivers using capture-based and eDNA methods, our eDNA method detected 86.2% and 72.0% of the fish species in the Grand River and the Sydenham River, respectively, which included our four target species. Our analyses also identified significant positive and negative species co-occurrence patterns between our target species and other identified species. Our results demonstrate that eDNA metabarcoding that targets the fish community as well as individual species of interest provides a better understanding of factors affecting the target species spatial distribution in an ecosystem than possible with only target species data. Additionally, eDNA is easily implemented as an initial survey tool, or alongside capture-based methods, for improved mapping of species distribution patterns. © 2017 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

Wu, Binlin

New near-infrared (NIR) diffuse optical tomography (DOT) approaches were developed to detect, locate, and image small targets embedded in highly scattering turbid media. The first approach, referred to as time reversal optical tomography (TROT), is based on time reversal (TR) imaging and multiple signal classification (MUSIC). The second approach uses decomposition methods of non-negative matrix factorization (NMF) and principal component analysis (PCA) commonly used in blind source separation (BSS) problems, and compare the outcomes with that of optical imaging using independent component analysis (OPTICA). The goal is to develop a safe, affordable, noninvasive imaging modality for detection and characterization of breast tumors in early growth stages when those are more amenable to treatment. The efficacy of the approaches was tested using simulated data, and experiments involving model media and absorptive, scattering, and fluorescent targets, as well as, "realistic human breast model" composed of ex vivo breast tissues with embedded tumors. The experimental arrangements realized continuous wave (CW) multi-source probing of samples and multi-detector acquisition of diffusely transmitted signal in rectangular slab geometry. A data matrix was generated using the perturbation in the transmitted light intensity distribution due to the presence of absorptive or scattering targets. For fluorescent targets the data matrix was generated using the diffusely transmitted fluorescence signal distribution from the targets. The data matrix was analyzed using different approaches to detect and characterize the targets. The salient features of the approaches include ability to: (a) detect small targets; (b) provide three-dimensional location of the targets with high accuracy (~within a millimeter or 2); and (c) assess optical strength of the targets. The approaches are less computation intensive and consequently are faster than other inverse image reconstruction methods that attempt to reconstruct the optical properties of every voxel of the sample volume. The location of a target was estimated to be the weighted center of the optical property of the target. Consequently, the locations of small targets were better specified than those of the extended targets. It was more difficult to retrieve the size and shape of a target. The fluorescent measurements seemed to provide better accuracy than the transillumination measurements. In the case of ex vivo detection of tumors embedded in human breast tissue, measurements using multiple wavelengths provided more robust results, and helped suppress artifacts (false positives) than that from single wavelength measurements. The ability to detect and locate small targets, speedier reconstruction, combined with fluorophore-specific multi-wavelength probing has the potential to make these approaches suitable for breast cancer detection and diagnosis.

Spectrophotometric, colorimetric and visually detection of Pseudomonas aeruginosa ETA gene based gold nanoparticles DNA probe and endonuclease enzyme

NASA Astrophysics Data System (ADS)

Amini, Bahram; Kamali, Mehdi; Salouti, Mojtaba; Yaghmaei, Parichehreh

2018-06-01

Colorimetric DNA detection is preferred over other methods for clinical molecular diagnosis because it does not require expensive equipment. In the present study, the colorimetric method based on gold nanoparticles (GNPs) and endonuclease enzyme was used for the detection of P. aeruginosa ETA gene. Firstly, the primers and probe for P. aeruginosa exotoxin A (ETA) gene were designed and checked for specificity by the PCR method. Then, GNPs were synthesized using the citrate reduction method and conjugated with the prepared probe to develop the new nano-biosensor. Next, the extracted target DNA of the bacteria was added to GNP-probe complex to check its efficacy for P. aeruginosa ETA gene diagnosis. A decrease in absorbance was seen when GNP-probe-target DNA cleaved into the small fragments of BamHI endonuclease due to the weakened electrostatic interaction between GNPs and the shortened DNA. The right shift of the absorbance peak from 530 to 562 nm occurred after adding the endonuclease. It was measured using a UV-VIS absorption spectroscopy that indicates the existence of the P. aeruginosa ETA gene. Sensitivity was determined in the presence of different concentrations of target DNA of P. aeruginosa. The results obtained from the optimized conditions showed that the absorbance value has linear correlation with concentration of target DNA (R: 0.9850) in the range of 10-50 ng mL-1 with the limit detection of 9.899 ng mL-1. Thus, the specificity of the new method for detection of P. aeruginosa was established in comparison with other bacteria. Additionally, the designed assay was quantitatively applied to detect the P. aeruginosa ETA gene from 103 to 108 CFU mL-1 in real samples with a detection limit of 320 CFU mL-1.

Automatic target detection using binary template matching

NASA Astrophysics Data System (ADS)

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

2005-03-01

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

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

PubMed

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

2016-04-07

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

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

PubMed Central

Li, Bin; Chen, Lianping; Li, Li

2017-01-01

In this article, we propose a novel detection method for underwater moving targets by detecting their extremely low frequency (ELF) emissions with inductive sensors. The ELF field source of the targets is modeled by a horizontal electric dipole at distances more than several times of the targets’ length. The formulas for the fields produced in air are derived with a three-layer model (air, seawater and seafloor) and are evaluated with a complementary numerical integration technique. A proof of concept measurement is presented. The ELF emissions from a surface ship were detected by inductive electronic and magnetic sensors as the ship was leaving a harbor. ELF signals are of substantial strength and have typical characteristic of harmonic line spectrum, and the fundamental frequency has a direct relationship with the ship’s speed. Due to the high sensitivity and low noise level of our sensors, it is capable of resolving weak ELF signals at long distance. In our experiment, a detection distance of 1300 m from the surface ship above the sea surface was realized, which shows that this method would be an appealing complement to the usual acoustic detection and magnetic anomaly detection capability. PMID:28788097

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

PubMed

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

2018-05-01

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

Statistical sensor fusion analysis of near-IR polarimetric and thermal imagery for the detection of minelike targets

NASA Astrophysics Data System (ADS)

Weisenseel, Robert A.; Karl, William C.; Castanon, David A.; DiMarzio, Charles A.

1999-02-01

We present an analysis of statistical model based data-level fusion for near-IR polarimetric and thermal data, particularly for the detection of mines and mine-like targets. Typical detection-level data fusion methods, approaches that fuse detections from individual sensors rather than fusing at the level of the raw data, do not account rationally for the relative reliability of different sensors, nor the redundancy often inherent in multiple sensors. Representative examples of such detection-level techniques include logical AND/OR operations on detections from individual sensors and majority vote methods. In this work, we exploit a statistical data model for the detection of mines and mine-like targets to compare and fuse multiple sensor channels. Our purpose is to quantify the amount of knowledge that each polarimetric or thermal channel supplies to the detection process. With this information, we can make reasonable decisions about the usefulness of each channel. We can use this information to improve the detection process, or we can use it to reduce the number of required channels.

Visual and highly sensitive detection of cancer cells by a colorimetric aptasensor based on cell-triggered cyclic enzymatic signal amplification.

PubMed

Zhang, Xianxia; Xiao, Kunyi; Cheng, Liwei; Chen, Hui; Liu, Baohong; Zhang, Song; Kong, Jilie

2014-06-03

Rapid and efficient detection of cancer cells at their earliest stages is one of the central challenges in cancer diagnostics. We developed a simple, cost-effective, and highly sensitive colorimetric method for visually detecting rare cancer cells based on cell-triggered cyclic enzymatic signal amplification (CTCESA). In the absence of target cells, hairpin aptamer probes (HAPs) and linker DNAs stably coexist in solution, and the linker DNA assembles DNA-AuNPs, producing a purple solution. In the presence of target cells, the specific binding of HAPs to the target cells triggers a conformational switch that results in linker DNA hybridization and cleavage by nicking endonuclease-strand scission cycles. Consequently, the cleaved fragments of linker DNA can no longer assemble into DNA-AuNPs, resulting in a red color. UV-vis spectrometry and photograph analyses demonstrated that this CTCESA-based method exhibited selective and sensitive colorimetric responses to the presence of target CCRF-CEM cells, which could be detected by the naked eye. The linear response for CCRF-CEM cells in a concentration range from 10(2) to 10(4) cells was obtained with a detection limit of 40 cells, which is approximately 20 times lower than the detection limit of normal AuNP-based methods without amplification. Given the high specificity and sensitivity of CTCESA, this colorimetric method provides a sensitive, label-free, and cost-effective approach for early cancer diagnosis and point-to-care applications.

Manmade target extraction based on multistage decision and its application for change detection in polarimetric synthetic aperture radar image

NASA Astrophysics Data System (ADS)

Cong, Runmin; Han, Ping; Li, Chongyi; He, Jiaji; Zhang, Zaiji

2016-09-01

Targets of interest are different in various applications in which manmade targets, such as aircraft, ships, and buildings, are given more attention. Manmade target extraction methods using synthetic aperture radar (SAR) images are designed in response to various demands, which include civil uses, business purposes, and military industries. This plays an increasingly vital role in monitoring, military reconnaissance, and precision strikes. Achieving accurate and complete results through traditional methods is becoming more challenging because of the scattered complexity of polarization in polarimetric synthetic aperture radar (PolSAR) image. A multistage decision-based method is proposed composed of power decision, dominant scattering mechanism decision, and reflection symmetry decision. In addition, the theories of polarimetric contrast enhancement, generalized Y decomposition, and maximum eigenvalue ratio are applied to assist the decision. Fully PolSAR data are adopted to evaluate and verify the approach. Experimental results show that the method can achieve an effective result with a lower false alarm rate and clear contours. Finally, on this basis, a universal framework of change detection for manmade targets is presented as an application of our method. Two sets of measured data are also used to evaluate and verify the effectiveness of the change-detection algorithm.

The electromagnetic-trait imaging computation of traveling wave method in breast tumor microwave sensor system.

PubMed

Tao, Zhi-Fu; Han, Zhong-Ling; Yao, Meng

2011-01-01

Using the difference of dielectric constant between malignant tumor tissue and normal breast tissue, breast tumor microwave sensor system (BRATUMASS) determines the detected target of imaging electromagnetic trait by analyzing the properties of target tissue back wave obtained after near-field microwave radicalization (conelrad). The key of obtained target properties relationship and reconstructed detected space is to analyze the characteristics of the whole process from microwave transmission to back wave reception. Using traveling wave method, we derive spatial transmission properties and the relationship of the relation detected points distances, and valuate the properties of each unit by statistical valuation theory. This chapter gives the experimental data analysis results.

Clever eye algorithm for target detection of remote sensing imagery

NASA Astrophysics Data System (ADS)

Geng, Xiurui; Ji, Luyan; Sun, Kang

2016-04-01

Target detection algorithms for hyperspectral remote sensing imagery, such as the two most commonly used remote sensing detection algorithms, the constrained energy minimization (CEM) and matched filter (MF), can usually be attributed to the inner product between a weight filter (or detector) and a pixel vector. CEM and MF have the same expression except that MF requires data centralization first. However, this difference leads to a difference in the target detection results. That is to say, the selection of the data origin could directly affect the performance of the detector. Therefore, does there exist another data origin other than the zero and mean-vector points for a better target detection performance? This is a very meaningful issue in the field of target detection, but it has not been paid enough attention yet. In this study, we propose a novel objective function by introducing the data origin as another variable, and the solution of the function is corresponding to the data origin with the minimal output energy. The process of finding the optimal solution can be vividly regarded as a clever eye automatically searching the best observing position and direction in the feature space, which corresponds to the largest separation between the target and background. Therefore, this new algorithm is referred to as the clever eye algorithm (CE). Based on the Sherman-Morrison formula and the gradient ascent method, CE could derive the optimal target detection result in terms of energy. Experiments with both synthetic and real hyperspectral data have verified the effectiveness of our method.

Antibody-Mediated Small Molecule Detection Using Programmable DNA-Switches.

PubMed

Rossetti, Marianna; Ippodrino, Rudy; Marini, Bruna; Palleschi, Giuseppe; Porchetta, Alessandro

2018-06-13

The development of rapid, cost-effective, and single-step methods for the detection of small molecules is crucial for improving the quality and efficiency of many applications ranging from life science to environmental analysis. Unfortunately, current methodologies still require multiple complex, time-consuming washing and incubation steps, which limit their applicability. In this work we present a competitive DNA-based platform that makes use of both programmable DNA-switches and antibodies to detect small target molecules. The strategy exploits both the advantages of proximity-based methods and structure-switching DNA-probes. The platform is modular and versatile and it can potentially be applied for the detection of any small target molecule that can be conjugated to a nucleic acid sequence. Here the rational design of programmable DNA-switches is discussed, and the sensitive, rapid, and single-step detection of different environmentally relevant small target molecules is demonstrated.

Detection and Tracking of Moving Targets Behind Cluttered Environments Using Compressive Sensing

NASA Astrophysics Data System (ADS)

Dang, Vinh Quang

Detection and tracking of moving targets (target's motion, vibration, etc.) in cluttered environments have been receiving much attention in numerous applications, such as disaster search-and-rescue, law enforcement, urban warfare, etc. One of the popular techniques is the use of stepped frequency continuous wave radar due to its low cost and complexity. However, the stepped frequency radar suffers from long data acquisition time. This dissertation focuses on detection and tracking of moving targets and vibration rates of stationary targets behind cluttered medium such as wall using stepped frequency radar enhanced by compressive sensing. The application of compressive sensing enables the reconstruction of the target space using fewer random frequencies, which decreases the acquisition time. Hardware-accelerated parallelization on GPU is investigated for the Orthogonal Matching Pursuit reconstruction algorithm. For simulation purpose, two hybrid methods have been developed to calculate the scattered fields from the targets through the wall approaching the antenna system, and to convert the incoming fields into voltage signals at terminals of the receive antenna. The first method is developed based on the plane wave spectrum approach for calculating the scattered fields of targets behind the wall. The method uses Fast Multiple Method (FMM) to calculate scattered fields on a particular source plane, decomposes them into plane wave components, and propagates the plane wave spectrum through the wall by integrating wall transmission coefficients before constructing the fields on a desired observation plane. The second method allows one to calculate the complex output voltage at terminals of a receiving antenna which fully takes into account the antenna effects. This method adopts the concept of complex antenna factor in Electromagnetic Compatibility (EMC) community for its calculation.

Automated multiple target detection and tracking in UAV videos

NASA Astrophysics Data System (ADS)

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

2010-04-01

In this paper, a novel system is presented to detect and track multiple targets in Unmanned Air Vehicles (UAV) video sequences. Since the output of the system is based on target motion, we first segment foreground moving areas from the background in each video frame using background subtraction. To stabilize the video, a multi-point-descriptor-based image registration method is performed where a projective model is employed to describe the global transformation between frames. For each detected foreground blob, an object model is used to describe its appearance and motion information. Rather than immediately classifying the detected objects as targets, we track them for a certain period of time and only those with qualified motion patterns are labeled as targets. In the subsequent tracking process, a Kalman filter is assigned to each tracked target to dynamically estimate its position in each frame. Blobs detected at a later time are used as observations to update the state of the tracked targets to which they are associated. The proposed overlap-rate-based data association method considers the splitting and merging of the observations, and therefore is able to maintain tracks more consistently. Experimental results demonstrate that the system performs well on real-world UAV video sequences. Moreover, careful consideration given to each component in the system has made the proposed system feasible for real-time applications.

Molecular methods for pathogen detection and quantification

USDA-ARS?s Scientific Manuscript database

Ongoing interest in convenient, inexpensive, fast, sensitive and accurate techniques for detecting and/or quantifying the presence of soybean pathogens has resulted in increased usage of molecular tools. The method of extracting a molecular target (usually DNA or RNA) for detection depends wholly up...

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

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

Expanded Target-Chemical Analysis Reveals Extensive Mixed-Organic-Contaminant Exposure in U.S. Streams

EPA Science Inventory

Surface-water from 38 streams nation-wide was assessed using 14 target-organic methods (719 compounds). Designedbioactive anthropogenic contaminants (biocides, pharmaceuticals) comprised 57% of 406 organics detected at least once. The 10 most-frequently detected anthropogenic-org...

Performance Comparison of Bench-Top Next Generation Sequencers Using Microdroplet PCR-Based Enrichment for Targeted Sequencing in Patients with Autism Spectrum Disorder

PubMed Central

Okamoto, Nobuhiko; Nakashima, Mitsuko; Tsurusaki, Yoshinori; Miyake, Noriko; Saitsu, Hirotomo; Matsumoto, Naomichi

2013-01-01

Next-generation sequencing (NGS) combined with enrichment of target genes enables highly efficient and low-cost sequencing of multiple genes for genetic diseases. The aim of this study was to validate the accuracy and sensitivity of our method for comprehensive mutation detection in autism spectrum disorder (ASD). We assessed the performance of the bench-top Ion Torrent PGM and Illumina MiSeq platforms as optimized solutions for mutation detection, using microdroplet PCR-based enrichment of 62 ASD associated genes. Ten patients with known mutations were sequenced using NGS to validate the sensitivity of our method. The overall read quality was better with MiSeq, largely because of the increased indel-related error associated with PGM. The sensitivity of SNV detection was similar between the two platforms, suggesting they are both suitable for SNV detection in the human genome. Next, we used these methods to analyze 28 patients with ASD, and identified 22 novel variants in genes associated with ASD, with one mutation detected by MiSeq only. Thus, our results support the combination of target gene enrichment and NGS as a valuable molecular method for investigating rare variants in ASD. PMID:24066114

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

PubMed

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

2013-08-01

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

Method for detecting binding efficiencies of synthetic oligonucleotides: Targeting bacteria and insects

USDA-ARS?s Scientific Manuscript database

Expanding applications of gene-based targeting biotechnology in functional genomics and the treatment of plants, animals, and microbes has synergized the need for new methods to measure binding efficiencies of these products to their genetic targets. The adaptation and innovative use of Cell–Penetra...

Detection of Babesia bovis carrier cattle by using polymerase chain reaction amplification of parasite DNA.

PubMed Central

Fahrimal, Y; Goff, W L; Jasmer, D P

1992-01-01

Carrier cattle infected with Babesia bovis are difficult to detect because of the low numbers of parasites that occur in peripheral blood. However, diagnosis of low-level infections with the parasite is important for evaluating the efficacies of vaccines and in transmission and epidemiological studies. We used the polymerase chain reaction (PCR) to amplify a portion of the apocytochrome b gene from the parasite and tested the ability of this method to detect carrier cattle. The target sequence is associated with a 7.4-kb DNA element in undigested B. bovis genomic DNA (as shown previously), and the amplified product was detected by Southern and dot blot hybridization. The assay was specific for B. bovis, since no amplification was detected with Babesia bigemina, Trypanosoma brucei, Anaplasma marginale, or leukocyte DNA. The target sequence was amplified in DNA from B. bovis Mexico, Texas, and Australia S and L strains, demonstrating the applicability of the method to strains from different geographic regions. The sensitivity of the method ranged from 1 to 10 infected erythrocytes extracted from 0.5 ml of blood. This sensitivity was about 1,000 times greater than that from the use of unamplified parasite DNA. By the PCR method, six B. bovis carrier cattle were detected 86% of the time (range, 66 to 100%) when they were tested 11 times, while with microscopic examination of thick blood smears, the same carrier cattle were detected only 36% of the time (range, 17 to 66%). The method provides a useful diagnostic tool for detecting B. bovis carrier cattle, and the sensitivity is significantly improved over that of current methods. The results also suggest that characteristics of the apocytchrome b gene may make this a valuable target DNA for PCR-based detection of other hemoparasites. Images PMID:1624551

Sensitive detection of unlabeled oligonucleotides using a paired surface plasma waves biosensor.

PubMed

Li, Ying-Chang; Chiou, Chiuan-Chian; Luo, Ji-Dung; Chen, Wei-Ju; Su, Li-Chen; Chang, Ying-Feng; Chang, Yu-Sun; Lai, Chao-Sung; Lee, Cheng-Chung; Chou, Chien

2012-05-15

Detection of unlabeled oligonucleotides using surface plasmon resonance (SPR) is difficult because of the oligonucleotides' relatively lower molecular weight compared with proteins. In this paper, we describe a method for detecting unlabeled oligonucleotides at low concentration using a paired surface plasma waves biosensor (PSPWB). The biosensor uses a sensor chip with an immobilized probe to detect a target oligonucleotide via sequence-specific hybridization. PSPWB measures the demodulated amplitude of the heterodyne signal in real time. In the meantime, the ratio of the amplitudes between the detected output signal and reference can reduce the excess noise from the laser intensity fluctuation. Also, the common-path propagation of p and s waves cancels the common phase noise induced by temperature variation. Thus, a high signal-to-noise ratio (SNR) of the heterodyne signal is detected. The sequence specificity of oligonucleotide hybridization ensures that the platform is precisely discriminating between target and non-target oligonucleotides. Under optimized experimental conditions, the detected heterodyne signal increases linearly with the logarithm of the concentration of target oligonucleotide over the range 0.5-500 pM. The detection limit is 0.5 pM in this experiment. In addition, the non-target oligonucleotide at concentrations of 10 pM and 10nM generated signals only slightly higher than background, indicating the high selectivity and specificity of this method. Different length of perfectly matched oligonucleotide targets at 10-mer, 15-mer and 20-mer were identified at the concentration of 150 pM. Copyright © 2012 Elsevier B.V. All rights reserved.

A novel ship CFAR detection algorithm based on adaptive parameter enhancement and wake-aided detection in SAR images

NASA Astrophysics Data System (ADS)

Meng, Siqi; Ren, Kan; Lu, Dongming; Gu, Guohua; Chen, Qian; Lu, Guojun

2018-03-01

Synthetic aperture radar (SAR) is an indispensable and useful method for marine monitoring. With the increase of SAR sensors, high resolution images can be acquired and contain more target structure information, such as more spatial details etc. This paper presents a novel adaptive parameter transform (APT) domain constant false alarm rate (CFAR) to highlight targets. The whole method is based on the APT domain value. Firstly, the image is mapped to the new transform domain by the algorithm. Secondly, the false candidate target pixels are screened out by the CFAR detector to highlight the target ships. Thirdly, the ship pixels are replaced by the homogeneous sea pixels. And then, the enhanced image is processed by Niblack algorithm to obtain the wake binary image. Finally, normalized Hough transform (NHT) is used to detect wakes in the binary image, as a verification of the presence of the ships. Experiments on real SAR images validate that the proposed transform does enhance the target structure and improve the contrast of the image. The algorithm has a good performance in the ship and ship wake detection.

A new multi-spectral feature level image fusion method for human interpretation

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-03-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in a three-task experiment using MSSF against two established methods: averaging and principle components analysis (PCA), and against its two source bands, visible and infrared. The three tasks that we studied were: (1) simple target detection, (2) spatial orientation, and (3) camouflaged target detection. MSSF proved superior to the other fusion methods in all three tests; MSSF also outperformed the source images in the spatial orientation and camouflaged target detection tasks. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

Possible methods for distinguishing icebergs from ships by aerial remote sensing

NASA Technical Reports Server (NTRS)

Howes, W. L.

1979-01-01

The simplest methods for aerial remote sensing which are least affected by atmospheric opacities are summarized. Radar is preferred for targets off the flight path, and microwave radiometry for targets along the flight path. Radar methods are classified by ability to resolve targets. Techniques which do not require target resolution are preferred. Among these techniques, polarization methods appear most promising, specifically those which differentiate the expected relatively greater depolarization by icebergs from that by ships or which detect doubly-reversed circular polarization.

A Volterra series-based method for extracting target echoes in the seafloor mining environment.

PubMed

Zhao, Haiming; Ji, Yaqian; Hong, Yujiu; Hao, Qi; Ma, Liyong

2016-09-01

The purpose of this research was to evaluate the applicability of the Volterra adaptive method to predict the target echo of an ultrasonic signal in an underwater seafloor mining environment. There is growing interest in mining of seafloor minerals because they offer an alternative source of rare metals. Mining the minerals cause the seafloor sediments to be stirred up and suspended in sea water. In such an environment, the target signals used for seafloor mapping are unable to be detected because of the unavoidable presence of volume reverberation induced by the suspended sediments. The detection of target signals in reverberation is currently performed using a stochastic model (for example, the autoregressive (AR) model) based on the statistical characterisation of reverberation. However, we examined a new method of signal detection in volume reverberation based on the Volterra series by confirming that the reverberation is a chaotic signal and generated by a deterministic process. The advantage of this method over the stochastic model is that attributions of the specific physical process are considered in the signal detection problem. To test the Volterra series based method and its applicability to target signal detection in the volume reverberation environment derived from the seafloor mining process, we simulated the real-life conditions of seafloor mining in a water filled tank of dimensions of 5×3×1.8m. The bottom of the tank was covered with 10cm of an irregular sand layer under which 5cm of an irregular cobalt-rich crusts layer was placed. The bottom was interrogated by an acoustic wave generated as 16μs pulses of 500kHz frequency. This frequency is demonstrated to ensure a resolution on the order of one centimetre, which is adequate in exploration practice. Echo signals were collected with a data acquisition card (PCI 1714 UL, 12-bit). Detection of the target echo in these signals was performed by both the Volterra series based model and the AR model. The results obtained confirm that the Volterra series based method is more efficient in the detection of the signal in reverberation than the conventional AR model (the accuracy is 80% for the PIM-Volterra prediction model versus 40% for the AR model). Copyright © 2016 Elsevier B.V. All rights reserved.

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...

A target detection multi-layer matched filter for color and hyperspectral cameras

NASA Astrophysics Data System (ADS)

Miyanishi, Tomoya; Preece, Bradley L.; Reynolds, Joseph P.

2018-05-01

In this article, a method for applying matched filters to a 3-dimentional hyperspectral data cube is discussed. In many applications, color visible cameras or hyperspectral cameras are used for target detection where the color or spectral optical properties of the imaged materials are partially known in advance. Therefore, the use of matched filtering with spectral data along with shape data is an effective method for detecting certain targets. Since many methods for 2D image filtering have been researched, we propose a multi-layer filter where ordinary spatially matched filters are used before the spectral filters. We discuss a way to layer the spectral filters for a 3D hyperspectral data cube, accompanied by a detectability metric for calculating the SNR of the filter. This method is appropriate for visible color cameras and hyperspectral cameras. We also demonstrate an analysis using the Night Vision Integrated Performance Model (NV-IPM) and a Monte Carlo simulation in order to confirm the effectiveness of the filtering in providing a higher output SNR and a lower false alarm rate.

Current and New Approaches in GMO Detection: Challenges and Solutions

PubMed Central

Fraiture, Marie-Alice; Herman, Philippe; Taverniers, Isabel; Deforce, Dieter; Roosens, Nancy H.

2015-01-01

In many countries, genetically modified organisms (GMO) legislations have been established in order to guarantee the traceability of food/feed products on the market and to protect the consumer freedom of choice. Therefore, several GMO detection strategies, mainly based on DNA, have been developed to implement these legislations. Due to its numerous advantages, the quantitative PCR (qPCR) is the method of choice for the enforcement laboratories in GMO routine analysis. However, given the increasing number and diversity of GMO developed and put on the market around the world, some technical hurdles could be encountered with the qPCR technology, mainly owing to its inherent properties. To address these challenges, alternative GMO detection methods have been developed, allowing faster detections of single GM target (e.g., loop-mediated isothermal amplification), simultaneous detections of multiple GM targets (e.g., PCR capillary gel electrophoresis, microarray, and Luminex), more accurate quantification of GM targets (e.g., digital PCR), or characterization of partially known (e.g., DNA walking and Next Generation Sequencing (NGS)) or unknown (e.g., NGS) GMO. The benefits and drawbacks of these methods are discussed in this review. PMID:26550567

Current and new approaches in GMO detection: challenges and solutions.

PubMed

Fraiture, Marie-Alice; Herman, Philippe; Taverniers, Isabel; De Loose, Marc; Deforce, Dieter; Roosens, Nancy H

2015-01-01

In many countries, genetically modified organisms (GMO) legislations have been established in order to guarantee the traceability of food/feed products on the market and to protect the consumer freedom of choice. Therefore, several GMO detection strategies, mainly based on DNA, have been developed to implement these legislations. Due to its numerous advantages, the quantitative PCR (qPCR) is the method of choice for the enforcement laboratories in GMO routine analysis. However, given the increasing number and diversity of GMO developed and put on the market around the world, some technical hurdles could be encountered with the qPCR technology, mainly owing to its inherent properties. To address these challenges, alternative GMO detection methods have been developed, allowing faster detections of single GM target (e.g., loop-mediated isothermal amplification), simultaneous detections of multiple GM targets (e.g., PCR capillary gel electrophoresis, microarray, and Luminex), more accurate quantification of GM targets (e.g., digital PCR), or characterization of partially known (e.g., DNA walking and Next Generation Sequencing (NGS)) or unknown (e.g., NGS) GMO. The benefits and drawbacks of these methods are discussed in this review.

A robust and versatile signal-on fluorescence sensing strategy based on SYBR Green I dye and graphene oxide

PubMed Central

Qiu, Huazhang; Wu, Namei; Zheng, Yanjie; Chen, Min; Weng, Shaohuang; Chen, Yuanzhong; Lin, Xinhua

2015-01-01

A robust and versatile signal-on fluorescence sensing strategy was developed to provide label-free detection of various target analytes. The strategy used SYBR Green I dye and graphene oxide as signal reporter and signal-to-background ratio enhancer, respectively. Multidrug resistance protein 1 (MDR1) gene and mercury ion (Hg2+) were selected as target analytes to investigate the generality of the method. The linear relationship and specificity of the detections showed that the sensitive and selective analyses of target analytes could be achieved by the proposed strategy with low detection limits of 0.5 and 2.2 nM for MDR1 gene and Hg2+, respectively. Moreover, the strategy was used to detect real samples. Analytical results of MDR1 gene in the serum indicated that the developed method is a promising alternative approach for real applications in complex systems. Furthermore, the recovery of the proposed method for Hg2+ detection was acceptable. Thus, the developed label-free signal-on fluorescence sensing strategy exhibited excellent universality, sensitivity, and handling convenience. PMID:25565810

Application of Hybrid Along-Track Interferometry/Displaced Phase Center Antenna Method for Moving Human Target Detection in Forest Environments

DTIC Science & Technology

2016-10-01

ARL-TR-7846 ● OCT 2016 US Army Research Laboratory Application of Hybrid Along-Track Interferometry/ Displaced Phase Center...Research Laboratory Application of Hybrid Along-Track Interferometry/ Displaced Phase Center Antenna Method for Moving Human Target Detection...TYPE Technical Report 3. DATES COVERED (From - To) 2015–2016 4. TITLE AND SUBTITLE Application of Hybrid Along-Track Interferometry/ Displaced

Small Infrared Target Detection by Region-Adaptive Clutter Rejection for Sea-Based Infrared Search and Track

PubMed Central

Kim, Sungho; Lee, Joohyoung

2014-01-01

This paper presents a region-adaptive clutter rejection method for small target detection in sea-based infrared search and track. In the real world, clutter normally generates many false detections that impede the deployment of such detection systems. Incoming targets (missiles, boats, etc.) can be located in the sky, horizon and sea regions, which have different types of clutters, such as clouds, a horizontal line and sea-glint. The characteristics of regional clutter were analyzed after the geometrical analysis-based region segmentation. The false detections caused by cloud clutter were removed by the spatial attribute-based classification. Those by the horizontal line were removed using the heterogeneous background removal filter. False alarms by sun-glint were rejected using the temporal consistency filter, which is the most difficult part. The experimental results of the various cluttered background sequences show that the proposed region adaptive clutter rejection method produces fewer false alarms than that of the mean subtraction filter (MSF) with an acceptable degradation detection rate. PMID:25054633

Dual gated PET/CT imaging of small targets of the heart: method description and testing with a dynamic heart phantom.

PubMed

Kokki, Tommi; Sipilä, Hannu T; Teräs, Mika; Noponen, Tommi; Durand-Schaefer, Nicolas; Klén, Riku; Knuuti, Juhani

2010-01-01

In PET imaging respiratory and cardiac contraction motions interfere the imaging of heart. The aim was to develop and evaluate dual gating method for improving the detection of small targets of the heart. The method utilizes two independent triggers which are sent periodically into list mode data based on respiratory and ECG cycles. An algorithm for generating dual gated segments from list mode data was developed. The test measurements showed that rotational and axial movements of point source can be separated spatially to different segments with well-defined borders. The effect of dual gating on detection of small moving targets was tested with a moving heart phantom. Dual gated images showed 51% elimination (3.6 mm out of 7.0 mm) of contraction motion of hot spot (diameter 3 mm) and 70% elimination (14 mm out of 20 mm) of respiratory motion. Averaged activity value of hot spot increases by 89% when comparing to non-gated images. Patient study of suspected cardiac sarcoidosis shows sharper spatial myocardial uptake profile and improved detection of small myocardial structures such as papillary muscles. The dual gating method improves detection of small moving targets in a phantom and it is feasible in clinical situations.

Portable apparatus for separating sample and detecting target analytes

DOEpatents

Renzi, Ronald F.; Wally, Karl; Crocker, Robert W.; Stamps, James F.; Griffiths; Stewart K. ,; Fruetel, Julia A.; Horn, Brent A.; Shokair, Isaac R.; Yee, Daniel D.; VanderNoot, Victoria A.; Wiedenman, Boyd J.; West, Jason A. A.; Ferko, Scott M.

2008-11-18

Portable devices and methods for determining the presence of a target analyte using a portable device are provided. The portable device is preferably hand-held. A sample is injected to the portable device. A microfluidic separation is performed within the portable device and at least one separated component detected by a detection module within the portable device, in embodiments of the invention. A target analyte is identified, based on the separated component, and the presence of the target analyte is indicated on an output interface of the portable device, in accordance with embodiments of the invention.

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

PubMed

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

2007-10-30

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

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

PubMed Central

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

2007-01-01

We report a method to detect label-free oligonucleotide targets. The conformation of surface-tethered probe nucleic acids is modulated by alternating electric fields, which cause the molecules to extend away from or fold onto the biased surface. Binding (hybridization) of targets to the single-stranded probes results in a pronounced enhancement of the layer-height modulation amplitude, monitored optically in real time. The method features an exceptional detection limit of <3 × 108 bound targets per cm2 sensor area. Single base-pair mismatches in the sequences of DNA complements may readily be identified; moreover, binding kinetics and binding affinities can be determined with high accuracy. When driving the DNA to oscillate at frequencies in the kHz regime, distinct switching kinetics are revealed for single- and double-stranded DNA. Molecular dynamics are used to identify the binding state of molecules according to their characteristic kinetic fingerprints by using a chip-compatible detection format. PMID:17951434

Target detection in GPR data using joint low-rank and sparsity constraints

NASA Astrophysics Data System (ADS)

Bouzerdoum, Abdesselam; Tivive, Fok Hing Chi; Abeynayake, Canicious

2016-05-01

In ground penetrating radars, background clutter, which comprises the signals backscattered from the rough, uneven ground surface and the background noise, impairs the visualization of buried objects and subsurface inspections. In this paper, a clutter mitigation method is proposed for target detection. The removal of background clutter is formulated as a constrained optimization problem to obtain a low-rank matrix and a sparse matrix. The low-rank matrix captures the ground surface reflections and the background noise, whereas the sparse matrix contains the target reflections. An optimization method based on split-Bregman algorithm is developed to estimate these two matrices from the input GPR data. Evaluated on real radar data, the proposed method achieves promising results in removing the background clutter and enhancing the target signature.

Discovery, detection and use of biomarkers

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

Swanson, Basil I.; Mukundan, Harshini; Sakamuri, Rama Murthy

Provided herein are systems for and methods of capturing, detecting, quantifying, and characterizing target moieties that are characterized by having a lipophilic portion of sufficient size and chemical composition whereby the target moiety inserts (or partitions) into a lipid assembly. Examples of such assays employ synthetic lipid constructs such as supported bilayers which are used to capture target moieties; other example assays exploit the natural absorption of compounds into natural lipid constructs such as HDL or LDL particles or cell membranes to capture target moieties. In specific embodiments, the target moieties are bacterial pathogen associated molecular pattern (PAMP) molecules ormore » compounds not yet identified as PAMP molecules. Also provided are methods of determining PAMP molecule fingerprints and profiles that are linked to (indicative of) bacterial infection, disease states or progression, development of antibiotic resistance, and so forth, as well as these fingerprints, profiles and methods of using them.« less

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method

PubMed Central

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-01-01

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis. PMID:28029121

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method.

PubMed

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-12-24

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis.

Electrochemical Aptamer Scaffold Biosensors for Detection of Botulism and Ricin Proteins.

PubMed

Daniel, Jessica; Fetter, Lisa; Jett, Susan; Rowland, Teisha J; Bonham, Andrew J

2017-01-01

Electrochemical DNA (E-DNA) biosensors enable the detection and quantification of a variety of molecular targets, including oligonucleotides, small molecules, heavy metals, antibodies, and proteins. Here we describe the design, electrode preparation and sensor attachment, and voltammetry conditions needed to generate and perform measurements using E-DNA biosensors against two protein targets, the biological toxins ricin and botulinum neurotoxin. This method can be applied to generate E-DNA biosensors for the detection of many other protein targets, with potential advantages over other systems including sensitive detection limits typically in the nanomolar range, real-time monitoring, and reusable biosensors.

An electromagnetic induction method for underground target detection and characterization

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

Bartel, L.C.; Cress, D.H.

1997-01-01

An improved capability for subsurface structure detection is needed to support military and nonproliferation requirements for inspection and for surveillance of activities of threatening nations. As part of the DOE/NN-20 program to apply geophysical methods to detect and characterize underground facilities, Sandia National Laboratories (SNL) initiated an electromagnetic induction (EMI) project to evaluate low frequency electromagnetic (EM) techniques for subsurface structure detection. Low frequency, in this case, extended from kilohertz to hundreds of kilohertz. An EMI survey procedure had already been developed for borehole imaging of coal seams and had successfully been applied in a surface mode to detect amore » drug smuggling tunnel. The SNL project has focused on building upon the success of that procedure and applying it to surface and low altitude airborne platforms. Part of SNL`s work has focused on improving that technology through improved hardware and data processing. The improved hardware development has been performed utilizing Laboratory Directed Research and Development (LDRD) funding. In addition, SNL`s effort focused on: (1) improvements in modeling of the basic geophysics of the illuminating electromagnetic field and its coupling to the underground target (partially funded using LDRD funds) and (2) development of techniques for phase-based and multi-frequency processing and spatial processing to support subsurface target detection and characterization. The products of this project are: (1) an evaluation of an improved EM gradiometer, (2) an improved gradiometer concept for possible future development, (3) an improved modeling capability, (4) demonstration of an EM wave migration method for target recognition, and a demonstration that the technology is capable of detecting targets to depths exceeding 25 meters.« less

Dim target trajectory-associated detection in bright earth limb background

NASA Astrophysics Data System (ADS)

Chen, Penghui; Xu, Xiaojian; He, Xiaoyu; Jiang, Yuesong

2015-09-01

The intensive emission of earth limb in the field of view of sensors contributes much to the observation images. Due to the low signal-to-noise ratio (SNR), it is a challenge to detect small targets in earth limb background, especially for the detection of point-like targets from a single frame. To improve the target detection, track before detection (TBD) based on the frame sequence is performed. In this paper, a new technique is proposed to determine the target associated trajectories, which jointly carries out background removing, maximum value projection (MVP) and Hough transform. The background of the bright earth limb in the observation images is removed according to the profile characteristics. For a moving target, the corresponding pixels in the MVP image are shifting approximately regularly in time sequence. And the target trajectory is determined by Hough transform according to the pixel characteristics of the target and the clutter and noise. Comparing with traditional frame-by-frame methods, determining associated trajectories from MVP reduces the computation load. Numerical simulations are presented to demonstrate the effectiveness of the approach proposed.

Road-Aided Ground Slowly Moving Target 2D Motion Estimation for Single-Channel Synthetic Aperture Radar.

PubMed

Wang, Zhirui; Xu, Jia; Huang, Zuzhen; Zhang, Xudong; Xia, Xiang-Gen; Long, Teng; Bao, Qian

2016-03-16

To detect and estimate ground slowly moving targets in airborne single-channel synthetic aperture radar (SAR), a road-aided ground moving target indication (GMTI) algorithm is proposed in this paper. First, the road area is extracted from a focused SAR image based on radar vision. Second, after stationary clutter suppression in the range-Doppler domain, a moving target is detected and located in the image domain via the watershed method. The target's position on the road as well as its radial velocity can be determined according to the target's offset distance and traffic rules. Furthermore, the target's azimuth velocity is estimated based on the road slope obtained via polynomial fitting. Compared with the traditional algorithms, the proposed method can effectively cope with slowly moving targets partly submerged in a stationary clutter spectrum. In addition, the proposed method can be easily extended to a multi-channel system to further improve the performance of clutter suppression and motion estimation. Finally, the results of numerical experiments are provided to demonstrate the effectiveness of the proposed algorithm.

Non-targeted analysis of unexpected food contaminants using LC-HRMS.

PubMed

Kunzelmann, Marco; Winter, Martin; Åberg, Magnus; Hellenäs, Karl-Erik; Rosén, Johan

2018-03-29

A non-target analysis method for unexpected contaminants in food is described. Many current methods referred to as "non-target" are capable of detecting hundreds or even thousands of contaminants. However, they will typically still miss all other possible contaminants. Instead, a metabolomics approach might be used to obtain "true non-target" analysis. In the present work, such a method was optimized for improved detection capability at low concentrations. The method was evaluated using 19 chemically diverse model compounds spiked into milk samples to mimic unknown contamination. Other milk samples were used as reference samples. All samples were analyzed with UHPLC-TOF-MS (ultra-high-performance liquid chromatography time-of-flight mass spectrometry), using reversed-phase chromatography and electrospray ionization in positive mode. Data evaluation was performed by the software TracMass 2. No target lists of specific compounds were used to search for the contaminants. Instead, the software was used to sort out all features only occurring in the spiked sample data, i.e., the workflow resembled a metabolomics approach. Procedures for chemical identification of peaks were outside the scope of the study. Method, study design, and settings in the software were optimized to minimize manual evaluation and faulty or irrelevant hits and to maximize hit rate of the spiked compounds. A practical detection limit was established at 25 μg/kg. At this concentration, most compounds (17 out of 19) were detected as intact precursor ions, as fragments or as adducts. Only 2 irrelevant hits, probably natural compounds, were obtained. Limitations and possible practical use of the approach are discussed.

Unlabeled probes for the detection and typing of herpes simplex virus.

PubMed

Dames, Shale; Pattison, David C; Bromley, L Kathryn; Wittwer, Carl T; Voelkerding, Karl V

2007-10-01

Unlabeled probe detection with a double-stranded DNA (dsDNA) binding dye is one method to detect and confirm target amplification after PCR. Unlabeled probes and amplicon melting have been used to detect small deletions and single-nucleotide polymorphisms in assays where template is in abundance. Unlabeled probes have not been applied to low-level target detection, however. Herpes simplex virus (HSV) was chosen as a model to compare the unlabeled probe method to an in-house reference assay using dual-labeled, minor groove binding probes. A saturating dsDNA dye (LCGreen Plus) was used for real-time PCR. HSV-1, HSV-2, and an internal control were differentiated by PCR amplicon and unlabeled probe melting analysis after PCR. The unlabeled probe technique displayed 98% concordance with the reference assay for the detection of HSV from a variety of archived clinical samples (n = 182). HSV typing using unlabeled probes was 99% concordant (n = 104) to sequenced clinical samples and allowed for the detection of sequence polymorphisms in the amplicon and under the probe. Unlabeled probes and amplicon melting can be used to detect and genotype as few as 10 copies of target per reaction, restricted only by stochastic limitations. The use of unlabeled probes provides an attractive alternative to conventional fluorescence-labeled, probe-based assays for genotyping and detection of HSV and might be useful for other low-copy targets where typing is informative.

A new method of inshore ship detection in high-resolution optical remote sensing images

NASA Astrophysics Data System (ADS)

Hu, Qifeng; Du, Yaling; Jiang, Yunqiu; Ming, Delie

2015-10-01

Ship as an important military target and water transportation, of which the detection has great significance. In the military field, the automatic detection of ships can be used to monitor ship dynamic in the harbor and maritime of enemy, and then analyze the enemy naval power. In civilian field, the automatic detection of ships can be used in monitoring transportation of harbor and illegal behaviors such as illegal fishing, smuggling and pirates, etc. In recent years, research of ship detection is mainly concentrated in three categories: forward-looking infrared images, downward-looking SAR image, and optical remote sensing images with sea background. Little research has been done into ship detection of optical remote sensing images with harbor background, as the gray-scale and texture features of ships are similar to the coast in high-resolution optical remote sensing images. In this paper, we put forward an effective harbor ship target detection method. First of all, in order to overcome the shortage of the traditional difference method in obtaining histogram valley as the segmentation threshold, we propose an iterative histogram valley segmentation method which separates the harbor and ships from the water quite well. Secondly, as landing ships in optical remote sensing images usually lead to discontinuous harbor edges, we use Hough Transform method to extract harbor edges. First, lines are detected by Hough Transform. Then, lines that have similar slope are connected into a new line, thus we access continuous harbor edges. Secondary segmentation on the result of the land-and-sea separation, we eventually get the ships. At last, we calculate the aspect ratio of the ROIs, thereby remove those targets which are not ship. The experiment results show that our method has good robustness and can tolerate a certain degree of noise and occlusion.

Small target detection using bilateral filter and temporal cross product in infrared images

NASA Astrophysics Data System (ADS)

Bae, Tae-Wuk

2011-09-01

We introduce a spatial and temporal target detection method using spatial bilateral filter (BF) and temporal cross product (TCP) of temporal pixels in infrared (IR) image sequences. At first, the TCP is presented to extract the characteristics of temporal pixels by using temporal profile in respective spatial coordinates of pixels. The TCP represents the cross product values by the gray level distance vector of a current temporal pixel and the adjacent temporal pixel, as well as the horizontal distance vector of the current temporal pixel and a temporal pixel corresponding to potential target center. The summation of TCP values of temporal pixels in spatial coordinates makes the temporal target image (TTI), which represents the temporal target information of temporal pixels in spatial coordinates. And then the proposed BF filter is used to extract the spatial target information. In order to predict background without targets, the proposed BF filter uses standard deviations obtained by an exponential mapping of the TCP value corresponding to the coordinate of a pixel processed spatially. The spatial target image (STI) is made by subtracting the predicted image from the original image. Thus, the spatial and temporal target image (STTI) is achieved by multiplying the STI and the TTI, and then targets finally are detected in STTI. In experimental result, the receiver operating characteristics (ROC) curves were computed experimentally to compare the objective performance. From the results, the proposed algorithm shows better discrimination of target and clutters and lower false alarm rates than the existing target detection methods.

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

PubMed Central

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

2014-01-01

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

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

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

Lee, C; Han, M; Baek, J

Purpose: To investigate the detectability of a small target for different slice direction of a volumetric cone beam CT image and its impact on dose reduction. Methods: Analytic projection data of a sphere object (1 mm diameter, 0.2/cm attenuation coefficient) were generated and reconstructed by FDK algorithm. In this work, we compared the detectability of the small target from four different backprojection Methods: hanning weighted ramp filter with linear interpolation (RECON 1), hanning weighted ramp filter with Fourier interpolation (RECON2), ramp filter with linear interpolation (RECON 3), and ramp filter with Fourier interpolation (RECON4), respectively. For noise simulation, 200 photonsmore » per measurement were used, and the noise only data were reconstructed using FDK algorithm. For each reconstructed volume, axial and coronal slice were extracted and detection-SNR was calculated using channelized Hotelling observer (CHO) with dense difference-of-Gaussian (D-DOG) channels. Results: Detection-SNR of coronal images varies for different backprojection methods, while axial images have a similar detection-SNR. Detection-SNR{sup 2} ratios of coronal and axial images in RECON1 and RECON2 are 1.33 and 1.15, implying that the coronal image has a better detectability than axial image. In other words, using coronal slices for the small target detection can reduce the patient dose about 33% and 15% compared to using axial slices in RECON 1 and RECON 2. Conclusion: In this work, we investigated slice direction dependent detectability of a volumetric cone beam CT image. RECON 1 and RECON 2 produced the highest detection-SNR, with better detectability in coronal slices. These results indicate that it is more beneficial to use coronal slice to improve detectability of a small target in a volumetric cone beam CT image. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (NIPA-2014-H0201-14-1002) supervised by the NIPA (National IT Industry Promotion Agency). Authors declares that s/he has no conflict of Interest in relation to the work in this abstract.« less

Fast cat-eye effect target recognition based on saliency extraction

NASA Astrophysics Data System (ADS)

Li, Li; Ren, Jianlin; Wang, Xingbin

2015-09-01

Background complexity is a main reason that results in false detection in cat-eye target recognition. Human vision has selective attention property which can help search the salient target from complex unknown scenes quickly and precisely. In the paper, we propose a novel cat-eye effect target recognition method named Multi-channel Saliency Processing before Fusion (MSPF). This method combines traditional cat-eye target recognition with the selective characters of visual attention. Furthermore, parallel processing enables it to achieve fast recognition. Experimental results show that the proposed method performs better in accuracy, robustness and speed compared to other methods.

Low-resolution ship detection from high-altitude aerial images

NASA Astrophysics Data System (ADS)

Qi, Shengxiang; Wu, Jianmin; Zhou, Qing; Kang, Minyang

2018-02-01

Ship detection from optical images taken by high-altitude aircrafts such as unmanned long-endurance airships and unmanned aerial vehicles has broad applications in marine fishery management, ship monitoring and vessel salvage. However, the major challenge is the limited capability of information processing on unmanned high-altitude platforms. Furthermore, in order to guarantee the wide detection range, unmanned aircrafts generally cruise at high altitudes, resulting in imagery with low-resolution targets and strong clutters suffered by heavy clouds. In this paper, we propose a low-resolution ship detection method to extract ships from these high-altitude optical images. Inspired by a recent research on visual saliency detection indicating that small salient signals could be well detected by a gradient enhancement operation combined with Gaussian smoothing, we propose the facet kernel filtering to rapidly suppress cluttered backgrounds and delineate candidate target regions from the sea surface. Then, the principal component analysis (PCA) is used to compute the orientation of the target axis, followed by a simplified histogram of oriented gradient (HOG) descriptor to characterize the ship shape property. Finally, support vector machine (SVM) is applied to discriminate real targets and false alarms. Experimental results show that the proposed method actually has high efficiency in low-resolution ship detection.

Homogenous assay for protein detection based on proximity DNA hybridization and isothermal circular strand displacement amplification reaction.

PubMed

Zhang, Manjun; Li, Ruimin; Ling, Liansheng

2017-06-01

This work proposed a homogenous fluorescence assay for proteins, based on the target-triggered proximity DNA hybridization in combination with strand displacement amplification (SDA). It benefited from target-triggered proximity DNA hybridization to specifically recognize the target and SDA making recycling signal amplification. The system included a molecular beacon (MB), an extended probe (EP), and an assistant probe (AP), which were not self-assembly in the absence of target proteins, due to the short length of the designed complementary sequence among MB, EP, and AP. Upon addition of the target proteins, EP and AP are bound to the target proteins, which induced the occurrence of proximity hybridization between MB, EP, and AP and followed by strand displacement amplification. Through the primer extension, a tripartite complex of probes and target was displaced and recycled to hybridize with another MB, and the more opened MB enabled the detection signal to amplify. Under optimum conditions, it was used for the detection of streptavidin and thrombin. Fluorescence intensity was proportional to the concentration of streptavidin and thrombin in the range of 0.2-30 and 0.2-35 nmol/L, respectively. Furthermore, this fluorescent method has a good selectivity, in which the fluorescence intensity of thrombin was ~37-fold or even larger than that of the other proteins at the same concentration. It is a new and simple method for SDA-involved target protein detection and possesses a great potential for other protein detection in the future. Graphical abstract A homogenous assay for protein detection is based on proximity DNA hybridization and strand displacement amplification reaction.

A Track Initiation Method for the Underwater Target Tracking Environment

NASA Astrophysics Data System (ADS)

Li, Dong-dong; Lin, Yang; Zhang, Yao

2018-04-01

A novel efficient track initiation method is proposed for the harsh underwater target tracking environment (heavy clutter and large measurement errors): track splitting, evaluating, pruning and merging method (TSEPM). Track initiation demands that the method should determine the existence and initial state of a target quickly and correctly. Heavy clutter and large measurement errors certainly pose additional difficulties and challenges, which deteriorate and complicate the track initiation in the harsh underwater target tracking environment. There are three primary shortcomings for the current track initiation methods to initialize a target: (a) they cannot eliminate the turbulences of clutter effectively; (b) there may be a high false alarm probability and low detection probability of a track; (c) they cannot estimate the initial state for a new confirmed track correctly. Based on the multiple hypotheses tracking principle and modified logic-based track initiation method, in order to increase the detection probability of a track, track splitting creates a large number of tracks which include the true track originated from the target. And in order to decrease the false alarm probability, based on the evaluation mechanism, track pruning and track merging are proposed to reduce the false tracks. TSEPM method can deal with the track initiation problems derived from heavy clutter and large measurement errors, determine the target's existence and estimate its initial state with the least squares method. What's more, our method is fully automatic and does not require any kind manual input for initializing and tuning any parameter. Simulation results indicate that our new method improves significantly the performance of the track initiation in the harsh underwater target tracking environment.

A man-made object detection for underwater TV

NASA Astrophysics Data System (ADS)

Cheng, Binbin; Wang, Wenwu; Chen, Yao

2018-03-01

It is a great challenging task to complete an automatic search of objects underwater. Usually the forward looking sonar is used to find the target, and then the initial identification of the target is completed by the side-scan sonar, and finally the confirmation of the target is accomplished by underwater TV. This paper presents an efficient method for automatic extraction of man-made sensitive targets in underwater TV. Firstly, the image of underwater TV is simplified with taking full advantage of the prior knowledge of the target and the background; then template matching technology is used for target detection; finally the target is confirmed by extracting parallel lines on the target contour. The algorithm is formulated for real-time execution on limited-memory commercial-of-the-shelf platforms and is capable of detection objects in underwater TV.

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.

Enhanced Reliability and Accuracy for Field Deployable Bioforensic Detection and Discrimination of Xylella fastidiosa subsp. pauca, Causal Agent of Citrus Variegated Chlorosis Using Razor Ex Technology and TaqMan Quantitative PCR

PubMed Central

Fletcher, Jacqueline; Melcher, Ulrich; Ochoa Corona, Francisco Manuel

2013-01-01

A reliable, accurate and rapid multigene-based assay combining real time quantitative PCR (qPCR) and a Razor Ex BioDetection System (Razor Ex) was validated for detection of Xylella fastidiosa subsp. pauca (Xfp, a xylem-limited bacterium that causes citrus variegated chlorosis [CVC]). CVC, which is exotic to the United States, has spread through South and Central America and could significantly impact U.S. citrus if it arrives. A method for early, accurate and sensitive detection of Xfp in plant tissues is needed by plant health officials for inspection of products from quarantined locations, and by extension specialists for detection, identification and management of disease outbreaks and reservoir hosts. Two sets of specific PCR primers and probes, targeting Xfp genes for fimbrillin and the periplasmic iron-binding protein were designed. A third pair of primers targeting the conserved cobalamin synthesis protein gene was designed to detect all possible X. fastidiosa (Xf) strains. All three primer sets detected as little as 1 fg of plasmid DNA carrying X. fastidiosa target sequences and genomic DNA of Xfp at as little as 1 - 10 fg. The use of Razor Ex facilitates a rapid (about 30 min) in-field assay capability for detection of all Xf strains, and for specific detection of Xfp. Combined use of three primer sets targeting different genes increased the assay accuracy and broadened the range of detection. To our knowledge, this is the first report of a field-deployable rapid and reliable bioforensic detection and discrimination method for a bacterial phytopathogen based on multigene targets. PMID:24312333

Enhanced reliability and accuracy for field deployable bioforensic detection and discrimination of Xylella fastidiosa subsp. pauca, causal agent of citrus variegated chlorosis using razor ex technology and TaqMan quantitative PCR.

PubMed

Ouyang, Ping; Arif, Mohammad; Fletcher, Jacqueline; Melcher, Ulrich; Ochoa Corona, Francisco Manuel

2013-01-01

A reliable, accurate and rapid multigene-based assay combining real time quantitative PCR (qPCR) and a Razor Ex BioDetection System (Razor Ex) was validated for detection of Xylella fastidiosa subsp. pauca (Xfp, a xylem-limited bacterium that causes citrus variegated chlorosis [CVC]). CVC, which is exotic to the United States, has spread through South and Central America and could significantly impact U.S. citrus if it arrives. A method for early, accurate and sensitive detection of Xfp in plant tissues is needed by plant health officials for inspection of products from quarantined locations, and by extension specialists for detection, identification and management of disease outbreaks and reservoir hosts. Two sets of specific PCR primers and probes, targeting Xfp genes for fimbrillin and the periplasmic iron-binding protein were designed. A third pair of primers targeting the conserved cobalamin synthesis protein gene was designed to detect all possible X. fastidiosa (Xf) strains. All three primer sets detected as little as 1 fg of plasmid DNA carrying X. fastidiosa target sequences and genomic DNA of Xfp at as little as 1 - 10 fg. The use of Razor Ex facilitates a rapid (about 30 min) in-field assay capability for detection of all Xf strains, and for specific detection of Xfp. Combined use of three primer sets targeting different genes increased the assay accuracy and broadened the range of detection. To our knowledge, this is the first report of a field-deployable rapid and reliable bioforensic detection and discrimination method for a bacterial phytopathogen based on multigene targets.

Improved target detection by IR dual-band image fusion

NASA Astrophysics Data System (ADS)

Adomeit, U.; Ebert, R.

2009-09-01

Dual-band thermal imagers acquire information simultaneously in both the 8-12 μm (long-wave infrared, LWIR) and the 3-5 μm (mid-wave infrared, MWIR) spectral range. Compared to single-band thermal imagers they are expected to have several advantages in military applications. These advantages include the opportunity to use the best band for given atmospheric conditions (e. g. cold climate: LWIR, hot and humid climate: MWIR), the potential to better detect camouflaged targets and an improved discrimination between targets and decoys. Most of these advantages have not yet been verified and/or quantified. It is expected that image fusion allows better exploitation of the information content available with dual-band imagers especially with respect to detection of targets. We have developed a method for dual-band image fusion based on the apparent temperature differences in the two bands. This method showed promising results in laboratory tests. In order to evaluate its performance under operational conditions we conducted a field trial in an area with high thermal clutter. In such areas, targets are hardly to detect in single-band images because they vanish in the clutter structure. The image data collected in this field trial was used for a perception experiment. This perception experiment showed an enhanced target detection range and reduced false alarm rate for the fused images compared to the single-band images.

Systems and Methods for Correcting Optical Reflectance Measurements

NASA Technical Reports Server (NTRS)

Yang, Ye (Inventor); Shear, Michael A. (Inventor); Soller, Babs R. (Inventor); Soyemi, Olusola O. (Inventor)

2014-01-01

We disclose measurement systems and methods for measuring analytes in target regions of samples that also include features overlying the target regions. The systems include: (a) a light source; (b) a detection system; (c) a set of at least first, second, and third light ports which transmit light from the light source to a sample and receive and direct light reflected from the sample to the detection system, generating a first set of data including information corresponding to both an internal target within the sample and features overlying the internal target, and a second set of data including information corresponding to features overlying the internal target; and (d) a processor configured to remove information characteristic of the overlying features from the first set of data using the first and second sets of data to produce corrected information representing the internal target.

Systems and methods for correcting optical reflectance measurements

NASA Technical Reports Server (NTRS)

Yang, Ye (Inventor); Soller, Babs R. (Inventor); Soyemi, Olusola O. (Inventor); Shear, Michael A. (Inventor)

2009-01-01

We disclose measurement systems and methods for measuring analytes in target regions of samples that also include features overlying the target regions. The systems include: (a) a light source; (b) a detection system; (c) a set of at least first, second, and third light ports which transmit light from the light source to a sample and receive and direct light reflected from the sample to the detection system, generating a first set of data including information corresponding to both an internal target within the sample and features overlying the internal target, and a second set of data including information corresponding to features overlying the internal target; and (d) a processor configured to remove information characteristic of the overlying features from the first set of data using the first and second sets of data to produce corrected information representing the internal target.

Calibration Method for IATS and Application in Multi-Target Monitoring Using Coded Targets

NASA Astrophysics Data System (ADS)

Zhou, Yueyin; Wagner, Andreas; Wunderlich, Thomas; Wasmeier, Peter

2017-06-01

The technique of Image Assisted Total Stations (IATS) has been studied for over ten years and is composed of two major parts: one is the calibration procedure which combines the relationship between the camera system and the theodolite system; the other is the automatic target detection on the image by various methods of photogrammetry or computer vision. Several calibration methods have been developed, mostly using prototypes with an add-on camera rigidly mounted on the total station. However, these prototypes are not commercially available. This paper proposes a calibration method based on Leica MS50 which has two built-in cameras each with a resolution of 2560 × 1920 px: an overview camera and a telescope (on-axis) camera. Our work in this paper is based on the on-axis camera which uses the 30-times magnification of the telescope. The calibration consists of 7 parameters to estimate. We use coded targets, which are common tools in photogrammetry for orientation, to detect different targets in IATS images instead of prisms and traditional ATR functions. We test and verify the efficiency and stability of this monitoring method with multi-target.

Multi-Frequency Signal Detection Based on Frequency Exchange and Re-Scaling Stochastic Resonance and Its Application to Weak Fault Diagnosis.

PubMed

Liu, Jinjun; Leng, Yonggang; Lai, Zhihui; Fan, Shengbo

2018-04-25

Mechanical fault diagnosis usually requires not only identification of the fault characteristic frequency, but also detection of its second and/or higher harmonics. However, it is difficult to detect a multi-frequency fault signal through the existing Stochastic Resonance (SR) methods, because the characteristic frequency of the fault signal as well as its second and higher harmonics frequencies tend to be large parameters. To solve the problem, this paper proposes a multi-frequency signal detection method based on Frequency Exchange and Re-scaling Stochastic Resonance (FERSR). In the method, frequency exchange is implemented using filtering technique and Single SideBand (SSB) modulation. This new method can overcome the limitation of "sampling ratio" which is the ratio of the sampling frequency to the frequency of target signal. It also ensures that the multi-frequency target signals can be processed to meet the small-parameter conditions. Simulation results demonstrate that the method shows good performance for detecting a multi-frequency signal with low sampling ratio. Two practical cases are employed to further validate the effectiveness and applicability of this method.

The simulation study on optical target laser active detection performance

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

a Coarse-To Model for Airplane Detection from Large Remote Sensing Images Using Saliency Modle and Deep Learning

NASA Astrophysics Data System (ADS)

Song, Z. N.; Sui, H. G.

2018-04-01

High resolution remote sensing images are bearing the important strategic information, especially finding some time-sensitive-targets quickly, like airplanes, ships, and cars. Most of time the problem firstly we face is how to rapidly judge whether a particular target is included in a large random remote sensing image, instead of detecting them on a given image. The problem of time-sensitive-targets target finding in a huge image is a great challenge: 1) Complex background leads to high loss and false alarms in tiny object detection in a large-scale images. 2) Unlike traditional image retrieval, what we need to do is not just compare the similarity of image blocks, but quickly find specific targets in a huge image. In this paper, taking the target of airplane as an example, presents an effective method for searching aircraft targets in large scale optical remote sensing images. Firstly, we used an improved visual attention model utilizes salience detection and line segment detector to quickly locate suspected regions in a large and complicated remote sensing image. Then for each region, without region proposal method, a single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation is adopted to search small airplane objects. Unlike sliding window and region proposal-based techniques, we can do entire image (region) during training and test time so it implicitly encodes contextual information about classes as well as their appearance. Experimental results show the proposed method is quickly identify airplanes in large-scale images.

A Method of Character Detection and Segmentation for Highway Guide Signs

NASA Astrophysics Data System (ADS)

Xu, Jiawei; Zhang, Chongyang

2018-01-01

In this paper, a method of character detection and segmentation for highway signs in China is proposed. It consists of four steps. Firstly, the highway sign area is detectedby colour and geometric features, andthe possible character region is obtained by multi-level projection strategy. Secondly, pseudo target character region is removed by local binary patterns (LBP) feature. Thirdly, convolutional neural network (CNN)is used to classify target regions. Finally, adaptive projection strategies are used to segment characters strings. Experimental results indicate that the proposed method achieves new state-of-the-art results.

Infrared small target detection based on Danger Theory

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Yang, Xiao

2009-11-01

To solve the problem that traditional method can't detect the small objects whose local SNR is less than 2 in IR images, a Danger Theory-based model to detect infrared small target is presented in this paper. First, on the analog with immunology, the definition is given, in this paper, to such terms as dangerous signal, antigens, APC, antibodies. Besides, matching rule between antigen and antibody is improved. Prior to training the detection model and detecting the targets, the IR images are processed utilizing adaptive smooth filter to decrease the stochastic noise. Then at the training process, deleting rule, generating rule, crossover rule and the mutation rule are established after a large number of experiments in order to realize immediate convergence and obtain good antibodies. The Danger Theory-based model is built after the training process, and this model can detect the target whose local SNR is only 1.5.

Method and system for evaluating integrity of adherence of a conductor bond to a mating surface of a substrate

DOEpatents

Telschow, K.L.; Siu, B.K.

1996-07-09

A method of evaluating integrity of adherence of a conductor bond to a substrate includes: (a) impinging a plurality of light sources onto a substrate; (b) detecting optical reflective signatures emanating from the substrate from the impinged light; (c) determining location of a selected conductor bond on the substrate from the detected reflective signatures; (d) determining a target site on the selected conductor bond from the detected reflective signatures; (e) optically imparting an elastic wave at the target site through the selected conductor bond and into the substrate; (f) optically detecting an elastic wave signature emanating from the substrate resulting from the optically imparting step; and (g) determining integrity of adherence of the selected conductor bond to the substrate from the detected elastic wave signature emanating from the substrate. A system is disclosed which is capable of conducting the method. 13 figs.

Method and system for evaluating integrity of adherence of a conductor bond to a mating surface of a substrate

DOEpatents

Telschow, Kenneth L.; Siu, Bernard K.

1996-01-01

A method of evaluating integrity of adherence of a conductor bond to a substrate includes: a) impinging a plurality of light sources onto a substrate; b) detecting optical reflective signatures emanating from the substrate from the impinged light; c) determining location of a selected conductor bond on the substrate from the detected reflective signatures; d) determining a target site on the selected conductor bond from the detected reflective signatures; e) optically imparting an elastic wave at the target site through the selected conductor bond and into the substrate; f) optically detecting an elastic wave signature emanating from the substrate resulting from the optically imparting step; and g) determining integrity of adherence of the selected conductor bond to the substrate from the detected elastic wave signature emanating from the substrate. A system is disclosed which is capable of conducting the method.

Demonstration of a Speckle Based Sensing with Pulse-Doppler Radar for Vibration Detection.

PubMed

Ozana, Nisan; Bauer, Reuven; Ashkenazy, Koby; Sasson, Nissim; Schwarz, Ariel; Shemer, Amir; Zalevsky, Zeev

2018-05-03

In previous works, an optical technique for extraction and separation of remote static vibrations has been demonstrated. In this paper, we will describe an approach in which RF speckle movement is used to extract remote vibrations of a static target. The use of conventional radar Doppler methods is not suitable for detecting vibrations of static targets. In addition, the speckle method has an important advantage, in that it is able to detect vibrations at far greater distances than what is normally detected in classical optical methods. The experiment described in this paper was done using a motorized vehicle, which engine was turned on and off. The results showed that the system was able to distinguish between the different engine states, and in addition, was able to determine the vibration frequency of the engine. The first step towards real time detection of human vital signs using RF speckle patterns is presented.

A novel polydopamine-based chemiluminescence resonance energy transfer method for microRNA detection coupling duplex-specific nuclease-aided target recycling strategy.

PubMed

Wang, Qian; Yin, Bin-Cheng; Ye, Bang-Ce

2016-06-15

MicroRNAs (miRNAs), functioning as oncogenes or tumor suppressors, play significant regulatory roles in regulating gene expression and become as biomarkers for disease diagnostics and therapeutics. In this work, we have coupled a polydopamine (PDA) nanosphere-assisted chemiluminescence resonance energy transfer (CRET) platform and a duplex-specific nuclease (DSN)-assisted signal amplification strategy to develop a novel method for specific miRNA detection. With the assistance of hemin, luminol, and H2O2, the horseradish peroxidase (HRP)-mimicking G-rich sequence in the sensing probe produces chemiluminescence, which is quickly quenched by the CRET effect between PDA as energy acceptor and excited luminol as energy donor. The target miRNA triggers DSN to partially degrade the sensing probe in the DNA-miRNA heteroduplex to repeatedly release G-quadruplex formed by G-rich sequence from PDA for the production of chemiluminescence. The method allows quantitative detection of target miRNA in the range of 80 pM-50 nM with a detection limit of 49.6 pM. The method also shows excellent specificity to discriminate single-base differences, and can accurately quantify miRNA in biological samples, with good agreement with the result from a commercial miRNA detection kit. The procedure requires no organic dyes or labels, and is a simple and cost-effective method for miRNA detection for early clinical diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Research on polarization imaging information parsing method

NASA Astrophysics Data System (ADS)

Yuan, Hongwu; Zhou, Pucheng; Wang, Xiaolong

2016-11-01

Polarization information parsing plays an important role in polarization imaging detection. This paper focus on the polarization information parsing method: Firstly, the general process of polarization information parsing is given, mainly including polarization image preprocessing, multiple polarization parameters calculation, polarization image fusion and polarization image tracking, etc.; And then the research achievements of the polarization information parsing method are presented, in terms of polarization image preprocessing, the polarization image registration method based on the maximum mutual information is designed. The experiment shows that this method can improve the precision of registration and be satisfied the need of polarization information parsing; In terms of multiple polarization parameters calculation, based on the omnidirectional polarization inversion model is built, a variety of polarization parameter images are obtained and the precision of inversion is to be improve obviously; In terms of polarization image fusion , using fuzzy integral and sparse representation, the multiple polarization parameters adaptive optimal fusion method is given, and the targets detection in complex scene is completed by using the clustering image segmentation algorithm based on fractal characters; In polarization image tracking, the average displacement polarization image characteristics of auxiliary particle filtering fusion tracking algorithm is put forward to achieve the smooth tracking of moving targets. Finally, the polarization information parsing method is applied to the polarization imaging detection of typical targets such as the camouflage target, the fog and latent fingerprints.

Development of a real-time PCR assay for rapid detection and quantification of Photobacterium damselae subsp. piscicida in fish tissues.

PubMed

Carraro, R; Dalla Rovere, G; Ferraresso, S; Carraro, L; Franch, R; Toffan, A; Pascoli, F; Patarnello, T; Bargelloni, L

2018-02-01

The availability of a rapid and accurate method for the diagnosis of Photobacterium damselae subsp. piscicida (Phdp), able to discriminate its strictly correlated subsp. damselae (Phdd), formally known as Vibrio damsela, is essential for managing fish pasteurellosis outbreaks in farmed fish. A single-step, high-sensitivity real-time PCR assay for simultaneous detection and quantification of P. damselae was designed targeting partial of the sequence of the bamB gene and tested for specificity and sensitivity on laboratory-generated samples as well as on experimentally infected seabream tissue samples. With a limit of detection (LOD) of one copy in pure bacterial DNA, the sensitivity was higher than all methods previously reported. Validation in target and non-target bacterial species proved the assay was able to discriminate Phdd-Phdp subspecies from diverse hosts/geographical origins and between non-target species. In addition, two SNPs in the target amplicon region determine two distinctive qPCR dissociation curves distinguishing between Phdp-Phdd. This is the first time that a molecular method for P. damselae diagnosis combines detection, quantification and subspecies identification in one step. The assay holds the potential to improve the knowledge of infection dynamics and the development of better strategies to control an important fish disease. © 2017 John Wiley & Sons Ltd.

Imaging of targeted lipid microbubbles to detect cancer cells using third harmonic generation microscopy

PubMed Central

Harpel, Kaitlin; Baker, Robert Dawson; Amirsolaimani, Babak; Mehravar, Soroush; Vagner, Josef; Matsunaga, Terry O.; Banerjee, Bhaskar; Kieu, Khanh

2016-01-01

The use of receptor-targeted lipid microbubbles imaged by ultrasound is an innovative method of detecting and localizing disease. However, since ultrasound requires a medium between the transducer and the object being imaged, it is impractical to apply to an exposed surface in a surgical setting where sterile fields need be maintained and ultrasound gel may cause the bubbles to collapse. Multiphoton microscopy (MPM) is an emerging tool for accurate, label-free imaging of tissues and cells with high resolution and contrast. We have recently determined a novel application of MPM to be used for detecting targeted microbubble adherence to the upregulated plectin-receptor on pancreatic tumor cells. Specifically, the third-harmonic generation response can be used to detect bound microbubbles to various cell types presenting MPM as an alternative and useful imaging method. This is an interesting technique that can potentially be translated as a diagnostic tool for the early detection of cancer and inflammatory disorders. PMID:27446711

Electrochemical Biosensor for Rapid and Sensitive Detection of Magnetically Extracted Bacterial Pathogens

PubMed Central

Setterington, Emma B.; Alocilja, Evangelyn C.

2012-01-01

Biological defense and security applications demand rapid, sensitive detection of bacterial pathogens. This work presents a novel qualitative electrochemical detection technique which is applied to two representative bacterial pathogens, Bacillus cereus (as a surrogate for B. anthracis) and Escherichia coli O157:H7, resulting in detection limits of 40 CFU/mL and 6 CFU/mL, respectively, from pure culture. Cyclic voltammetry is combined with immunomagnetic separation in a rapid method requiring approximately 1 h for presumptive positive/negative results. An immunofunctionalized magnetic/polyaniline core/shell nano-particle (c/sNP) is employed to extract target cells from the sample solution and magnetically position them on a screen-printed carbon electrode (SPCE) sensor. The presence of target cells significantly inhibits current flow between the electrically active c/sNPs and SPCE. This method has the potential to be adapted for a wide variety of target organisms and sample matrices, and to become a fully portable system for routine monitoring or emergency detection of bacterial pathogens. PMID:25585629

Optimized signal detection and analysis methods for in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Wang, Qiyan; Zhou, Quanyu; Yang, Ping; Wang, Xiaoling; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Gao, Wenyuan; Tang, Shuo; Wei, Xunbin

2017-02-01

Melanoma is known as a malignant tumor of melanocytes, which usually appear in the blood circulation at the metastasis stage of cancer. Thus the detection of circulating melanoma cells is useful for early diagnosis and therapy of cancer. Here we have developed an in vivo photoacoustic flow cytometry (PAFC) based on the photoacoustic effect to detect melanoma cells. However, the raw signals we obtain from the target cells contain noises such as environmental sonic noises and electronic noises. Therefore we apply correlation comparison and feature separation methods to the detection and verification of the in vivo signals. Due to similar shape and structure of cells, the photoacoustic signals usually have similar vibration mode. By analyzing the correlations and the signal features in time domain and frequency domain, we are able to provide a method for separating photoacoustic signals generated by target cells from background noises. The method introduced here has proved to optimize the signal acquisition and signal processing, which can improve the detection accuracy in PAFC.

Rapid detection of multiple class pharmaceuticals in both municipal wastewater and sludge with ultra high performance liquid chromatography tandem mass spectrometry.

PubMed

Yuan, Xiangjuan; Qiang, Zhimin; Ben, Weiwei; Zhu, Bing; Liu, Junxin

2014-09-01

This work described the development, optimization and validation of an analytical method for rapid detection of multiple-class pharmaceuticals in both municipal wastewater and sludge samples based on ultrasonic solvent extraction, solid-phase extraction, and ultra high performance liquid chromatography-tandem mass spectrometry quantification. The results indicated that the developed method could effectively extract all the target pharmaceuticals (25) in a single process and analyze them within 24min. The recoveries of the target pharmaceuticals were in the range of 69%-131% for wastewater and 54%-130% for sludge at different spiked concentration levels. The method quantification limits in wastewater and sludge ranged from 0.02 to 0.73ng/L and from 0.02 to 1.00μg/kg, respectively. Subsequently, this method was validated and applied for residual pharmaceutical analysis in a wastewater treatment plant located in Beijing, China. All the target pharmaceuticals were detected in the influent samples with concentrations varying from 0.09ng/L (tiamulin) to 15.24μg/L (caffeine); meanwhile, up to 23 pharmaceuticals were detected in sludge samples with concentrations varying from 60ng/kg (sulfamethizole) to 8.55mg/kg (ofloxacin). The developed method demonstrated its selectivity, sensitivity, and reliability for detecting multiple-class pharmaceuticals in complex matrices such as municipal wastewater and sludge. Copyright © 2014. Published by Elsevier B.V.

Methods for point-of-care detection of nucleic acid in a sample

DOEpatents

Bearinger, Jane P.; Dugan, Lawrence C.

2015-12-29

Provided herein are methods and apparatus for detecting a target nucleic acid in a sample and related methods and apparatus for diagnosing a condition in an individual. The condition is associated with presence of nucleic acid produced by certain pathogens in the individual.

In Situ Detection of MicroRNA Expression with RNAscope Probes.

PubMed

Yin, Viravuth P

2018-01-01

Elucidating the spatial resolution of gene transcripts provides important insight into potential gene function. MicroRNAs are short, singled-stranded noncoding RNAs that control gene expression through base-pair complementarity with target mRNAs in the 3' untranslated region (UTR) and inhibiting protein expression. However, given their small size of ~22- to 24-nt and low expression levels, standard in situ hybridization detection methods are not amendable for microRNA spatial resolution. Here, I describe a technique that employs RNAscope probe design and propriety amplification technology that provides simultaneous single molecule detection of individual microRNA and its target gene. This method allows for rapid and sensitive detection of noncoding RNA transcripts in frozen tissue sections.

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

PubMed

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

2012-07-01

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

Spectrophotometric, colorimetric and visually detection of Pseudomonas aeruginosa ETA gene based gold nanoparticles DNA probe and endonuclease enzyme.

PubMed

Amini, Bahram; Kamali, Mehdi; Salouti, Mojtaba; Yaghmaei, Parichehreh

2018-06-15

Colorimetric DNA detection is preferred over other methods for clinical molecular diagnosis because it does not require expensive equipment. In the present study, the colorimetric method based on gold nanoparticles (GNPs) and endonuclease enzyme was used for the detection of P. aeruginosa ETA gene. Firstly, the primers and probe for P. aeruginosa exotoxin A (ETA) gene were designed and checked for specificity by the PCR method. Then, GNPs were synthesized using the citrate reduction method and conjugated with the prepared probe to develop the new nano-biosensor. Next, the extracted target DNA of the bacteria was added to GNP-probe complex to check its efficacy for P. aeruginosa ETA gene diagnosis. A decrease in absorbance was seen when GNP-probe-target DNA cleaved into the small fragments of BamHI endonuclease due to the weakened electrostatic interaction between GNPs and the shortened DNA. The right shift of the absorbance peak from 530 to 562nm occurred after adding the endonuclease. It was measured using a UV-VIS absorption spectroscopy that indicates the existence of the P. aeruginosa ETA gene. Sensitivity was determined in the presence of different concentrations of target DNA of P. aeruginosa. The results obtained from the optimized conditions showed that the absorbance value has linear correlation with concentration of target DNA (R: 0.9850) in the range of 10-50ngmL -1 with the limit detection of 9.899ngmL -1 . Thus, the specificity of the new method for detection of P. aeruginosa was established in comparison with other bacteria. Additionally, the designed assay was quantitatively applied to detect the P. aeruginosa ETA gene from 10 3 to 10 8 CFUmL -1 in real samples with a detection limit of 320CFUmL -1 . Copyright © 2018 Elsevier B.V. All rights reserved.

Discriminative correlation filter tracking with occlusion detection

NASA Astrophysics Data System (ADS)

Zhang, Shuo; Chen, Zhong; Yu, XiPeng; Zhang, Ting; He, Jing

2018-03-01

Aiming at the problem that the correlation filter-based tracking algorithm can not track the target of severe occlusion, a target re-detection mechanism is proposed. First of all, based on the ECO, we propose the multi-peak detection model and the response value to distinguish the occlusion and deformation in the target tracking, which improve the success rate of tracking. And then we add the confidence model to update the mechanism to effectively prevent the model offset problem which due to similar targets or background during the tracking process. Finally, the redetection mechanism of the target is added, and the relocation is performed after the target is lost, which increases the accuracy of the target positioning. The experimental results demonstrate that the proposed tracker performs favorably against state-of-the-art methods in terms of robustness and accuracy.

Isothermal circular-strand-displacement polymerization of DNA and microRNA in digital microfluidic devices.

PubMed

Giuffrida, Maria Chiara; Zanoli, Laura Maria; D'Agata, Roberta; Finotti, Alessia; Gambari, Roberto; Spoto, Giuseppe

2015-02-01

Nucleic-acid amplification is a crucial step in nucleic-acid-sequence-detection assays. The use of digital microfluidic devices to miniaturize amplification techniques reduces the required sample volume and the analysis time and offers new possibilities for process automation and integration in a single device. The recently introduced droplet polymerase-chain-reaction (PCR) amplification methods require repeated cycles of two or three temperature-dependent steps during the amplification of the nucleic-acid target sequence. In contrast, low-temperature isothermal-amplification methods have no need for thermal cycling, thus requiring simplified microfluidic-device features. Here, the combined use of digital microfluidics and molecular-beacon (MB)-assisted isothermal circular-strand-displacement polymerization (ICSDP) to detect microRNA-210 sequences is described. MicroRNA-210 has been described as the most consistently and predominantly upregulated hypoxia-inducible factor. The nmol L(-1)-pmol L(-1) detection capabilities of the method were first tested by targeting single-stranded DNA sequences from the genetically modified Roundup Ready soybean. The ability of the droplet-ICSDP method to discriminate between full-matched, single-mismatched, and unrelated sequences was also investigated. The detection of a range of nmol L(-1)-pmol L(-1) microRNA-210 solutions compartmentalized in nanoliter-sized droplets was performed, establishing the ability of the method to detect as little as 10(-18) mol of microRNA target sequences compartmentalized in 20 nL droplets. The suitability of the method for biological samples was tested by detecting microRNA-210 from transfected K562 cells.

A novel data-driven learning method for radar target detection in nonstationary environments

DOE PAGES

Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

2016-04-12

Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detectmore » changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.« less

Real Time Corner Detection for Miniaturized Electro-Optical Sensors Onboard Small Unmanned Aerial Systems

PubMed Central

Forlenza, Lidia; Carton, Patrick; Accardo, Domenico; Fasano, Giancarmine; Moccia, Antonio

2012-01-01

This paper describes the target detection algorithm for the image processor of a vision-based system that is installed onboard an unmanned helicopter. It has been developed in the framework of a project of the French national aerospace research center Office National d’Etudes et de Recherches Aérospatiales (ONERA) which aims at developing an air-to-ground target tracking mission in an unknown urban environment. In particular, the image processor must detect targets and estimate ground motion in proximity of the detected target position. Concerning the target detection function, the analysis has dealt with realizing a corner detection algorithm and selecting the best choices in terms of edge detection methods, filtering size and type and the more suitable criterion of detection of the points of interest in order to obtain a very fast algorithm which fulfills the computation load requirements. The compared criteria are the Harris-Stephen and the Shi-Tomasi, ones, which are the most widely used in literature among those based on intensity. Experimental results which illustrate the performance of the developed algorithm and demonstrate that the detection time is fully compliant with the requirements of the real-time system are discussed. PMID:22368499

Three-dimensional microscope tracking system using the astigmatic lens method and a profile sensor

NASA Astrophysics Data System (ADS)

Kibata, Hiroki; Ishii, Katsuhiro

2018-03-01

We developed a three-dimensional microscope tracking system using the astigmatic lens method and a profile sensor, which provides three-dimensional position detection over a wide range at the rate of 3.2 kHz. First, we confirmed the range of target detection of the developed system, where the range of target detection was shown to be ± 90 µm in the horizontal plane and ± 9 µm in the vertical plane for a 10× objective lens. Next, we attempted to track a motion-controlled target. The developed system kept the target at the center of the field of view and in focus up to a target speed of 50 µm/s for a 20× objective lens. Finally, we tracked a freely moving target. We successfully demonstrated the tracking of a 10-µm-diameter polystyrene bead suspended in water for 40 min. The target was kept in the range of approximately 4.9 µm around the center of the field of view. In addition, the vertical direction was maintained in the range of ± 0.84 µm, which was sufficiently within the depth of focus.

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

PubMed

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

2008-10-01

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

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

PubMed Central

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

2008-01-01

We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1–25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification. PMID:18710880

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Statistical Algorithms Accounting for Background Density in the Detection of UXO Target Areas at DoD Munitions Sites

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

Matzke, Brett D.; Wilson, John E.; Hathaway, J.

2008-02-12

Statistically defensible methods are presented for developing geophysical detector sampling plans and analyzing data for munitions response sites where unexploded ordnance (UXO) may exist. Detection methods for identifying areas of elevated anomaly density from background density are shown. Additionally, methods are described which aid in the choice of transect pattern and spacing to assure with degree of confidence that a target area (TA) of specific size, shape, and anomaly density will be identified using the detection methods. Methods for evaluating the sensitivity of designs to variation in certain parameters are also discussed. Methods presented have been incorporated into the Visualmore » Sample Plan (VSP) software (free at http://dqo.pnl.gov/vsp) and demonstrated at multiple sites in the United States. Application examples from actual transect designs and surveys from the previous two years are demonstrated.« less

OPTICAL correlation identification technology applied in underwater laser imaging target identification

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

Optical Molecular Imaging for Diagnosing Intestinal Diseases

PubMed Central

Kim, Sang-Yeob

2013-01-01

Real-time visualization of the molecular signature of cells can be achieved with advanced targeted imaging techniques using molecular probes and fluorescence endoscopy. This molecular optical imaging in gastrointestinal endoscopy is promising for improving the detection of neoplastic lesions, their characterization for patient stratification, and the assessment of their response to molecular targeted therapy and radiotherapy. In inflammatory bowel disease, this method can be used to detect dysplasia in the presence of background inflammation and to visualize inflammatory molecular targets for assessing disease severity and prognosis. Several preclinical and clinical trials have applied this method in endoscopy; however, this field has just started to evolve. Hence, many problems have yet to be solved to enable the clinical application of this novel method. PMID:24340254

Rapid detection of proteins in transgenic crops without protein reference standards by targeted proteomic mass spectrometry.

PubMed

Schacherer, Lindsey J; Xie, Weiping; Owens, Michaela A; Alarcon, Clara; Hu, Tiger X

2016-09-01

Liquid chromatography coupled with tandem mass spectrometry is increasingly used for protein detection for transgenic crops research. Currently this is achieved with protein reference standards which may take a significant time or efforts to obtain and there is a need for rapid protein detection without protein reference standards. A sensitive and specific method was developed to detect target proteins in transgenic maize leaf crude extract at concentrations as low as ∼30 ng mg(-1) dry leaf without the need of reference standards or any sample enrichment. A hybrid Q-TRAP mass spectrometer was used to monitor all potential tryptic peptides of the target proteins in both transgenic and non-transgenic samples. The multiple reaction monitoring-initiated detection and sequencing (MIDAS) approach was used for initial peptide/protein identification via Mascot database search. Further confirmation was achieved by direct comparison between transgenic and non-transgenic samples. Definitive confirmation was provided by running the same experiments of synthetic peptides or protein standards, if available. A targeted proteomic mass spectrometry method using MIDAS approach is an ideal methodology for detection of new proteins in early stages of transgenic crop research and development when neither protein reference standards nor antibodies are available. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Use of amplicon sequencing to improve sensitivity in PCR-based detection of microbial pathogen in environmental samples.

PubMed

Saingam, Prakit; Li, Bo; Yan, Tao

2018-06-01

DNA-based molecular detection of microbial pathogens in complex environments is still plagued by sensitivity, specificity and robustness issues. We propose to address these issues by viewing them as inadvertent consequences of requiring specific and adequate amplification (SAA) of target DNA molecules by current PCR methods. Using the invA gene of Salmonella as the model system, we investigated if next generation sequencing (NGS) can be used to directly detect target sequences in false-negative PCR reaction (PCR-NGS) in order to remove the SAA requirement from PCR. False-negative PCR and qPCR reactions were first created using serial dilutions of laboratory-prepared Salmonella genomic DNA and then analyzed directly by NGS. Target invA sequences were detected in all false-negative PCR and qPCR reactions, which lowered the method detection limits near the theoretical minimum of single gene copy detection. The capability of the PCR-NGS approach in correcting false negativity was further tested and confirmed under more environmentally relevant conditions using Salmonella-spiked stream water and sediment samples. Finally, the PCR-NGS approach was applied to ten urban stream water samples and detected invA sequences in eight samples that would be otherwise deemed Salmonella negative. Analysis of the non-target sequences in the false-negative reactions helped to identify primer dime-like short sequences as the main cause of the false negativity. Together, the results demonstrated that the PCR-NGS approach can significantly improve method sensitivity, correct false-negative detections, and enable sequence-based analysis for failure diagnostics in complex environmental samples. Copyright © 2018 Elsevier B.V. All rights reserved.

Modulation Detection Interference for Asynchronous Presentation of Masker and Target in Listeners with Normal and Impaired Hearing

ERIC Educational Resources Information Center

Koopman, Jan; Houtgast, Tammo; Dreschler, Wouter A.

2008-01-01

Purpose: The sensitivity to sinusoidal amplitude modulations (SAMs) is reduced when other modulated maskers are presented simultaneously at a distant frequency (also referred to as "modulation detection interference" [MDI]). This article describes the results of onset differences between masker and target as a parameter. Method: Carrier…

Single Laboratory Comparison of Host-Specific PCR Assays for the Detection of Bovine Fecal Pollution

EPA Science Inventory

There are numerous PCR-based methods available to detect bovine fecal pollution in ambient waters. Each method targets a different gene and microorganism leading to differences in method performance, making it difficult to determine which approach is most suitable for field appl...

Multi-Target Tracking Using an Improved Gaussian Mixture CPHD Filter.

PubMed

Si, Weijian; Wang, Liwei; Qu, Zhiyu

2016-11-23

The cardinalized probability hypothesis density (CPHD) filter is an alternative approximation to the full multi-target Bayesian filter for tracking multiple targets. However, although the joint propagation of the posterior intensity and cardinality distribution in its recursion allows more reliable estimates of the target number than the PHD filter, the CPHD filter suffers from the spooky effect where there exists arbitrary PHD mass shifting in the presence of missed detections. To address this issue in the Gaussian mixture (GM) implementation of the CPHD filter, this paper presents an improved GM-CPHD filter, which incorporates a weight redistribution scheme into the filtering process to modify the updated weights of the Gaussian components when missed detections occur. In addition, an efficient gating strategy that can adaptively adjust the gate sizes according to the number of missed detections of each Gaussian component is also presented to further improve the computational efficiency of the proposed filter. Simulation results demonstrate that the proposed method offers favorable performance in terms of both estimation accuracy and robustness to clutter and detection uncertainty over the existing methods.

Electrochemical impedimetric sensor based on molecularly imprinted polymers/sol-gel chemistry for methidathion organophosphorous insecticide recognition.

PubMed

Bakas, Idriss; Hayat, Akhtar; Piletsky, Sergey; Piletska, Elena; Chehimi, Mohamed M; Noguer, Thierry; Rouillon, Régis

2014-12-01

We report here a novel method to detect methidathion organophosphorous insecticides. The sensing platform was architected by the combination of molecularly imprinted polymers and sol-gel technique on inexpensive, portable and disposable screen printed carbon electrodes. Electrochemical impedimetric detection technique was employed to perform the label free detection of the target analyte on the designed MIP/sol-gel integrated platform. The selection of the target specific monomer by electrochemical impedimetric methods was consistent with the results obtained by the computational modelling method. The prepared electrochemical MIP/sol-gel based sensor exhibited a high recognition capability toward methidathion, as well as a broad linear range and a low detection limit under the optimized conditions. Satisfactory results were also obtained for the methidathion determination in waste water samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Size-based cell sorting with a resistive pulse sensor and an electromagnetic pump in a microfluidic chip.

PubMed

Song, Yongxin; Li, Mengqi; Pan, Xinxiang; Wang, Qi; Li, Dongqing

2015-02-01

An electrokinetic microfluidic chip is developed to detect and sort target cells by size from human blood samples. Target-cell detection is achieved by a differential resistive pulse sensor (RPS) based on the size difference between the target cell and other cells. Once a target cell is detected, the detected RPS signal will automatically actuate an electromagnetic pump built in a microchannel to push the target cell into a collecting channel. This method was applied to automatically detect and sort A549 cells and T-lymphocytes from a peripheral fingertip blood sample. The viability of A549 cells sorted in the collecting well was verified by Hoechst33342 and propidium iodide staining. The results show that as many as 100 target cells per minute can be sorted out from the sample solution and thus is particularly suitable for sorting very rare target cells, such as circulating tumor cells. The actuation of the electromagnetic valve has no influence on RPS cell detection and the consequent cell-sorting process. The viability of the collected A549 cell is not impacted by the applied electric field when the cell passes the RPS detection area. The device described in this article is simple, automatic, and label-free and has wide applications in size-based rare target cell sorting for medical diagnostics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Tracking single membrane targets of human autoantibodies using single nanoparticle imaging.

PubMed

Jézéquel, Julie; Dupuis, Julien P; Maingret, François; Groc, Laurent

2018-04-21

Over the past decade, an increasing number of neurological and neuropsychiatric diseases have been associated with the expression of autoantibodies directed against neuronal targets, including neurotransmitter receptors. Although cell-based assays are routinely used in clinics to detect the presence of immunoglobulins, such tests often provide heterogeneous outcomes due to their limited sensitivity, especially at low titers. Thus, there is an urging need for new methods allowing the detection of autoantibodies in seropositive patients that cannot always be clinically distinguished from seronegative ones. Here we make a case for single nanoparticle imaging approaches as a highly sensitive antibody detection assay. Through high-affinity interactions between functionalized nanoparticles and autoantibodies that recognize extracellular domains of membrane neuronal targets, single nanoparticle imaging allows a live surface staining of transmembrane proteins and gives access to their surface dynamics. We show here that this method is well-suited to detect low titers of purified immunoglobulin G (IgG) from first-episode psychotic patients and demonstrate that these IgG target glutamatergic N-Methyl-d-Aspartate receptors (NMDAR) in live hippocampal neurons. The molecular behaviors of targeted membrane receptors were indistinguishable from those of endogenous GluN1 NMDAR subunit and were virtually independent of the IgG concentration present in the sample contrary to classical cell-based assays. Single nanoparticle imaging emerges as a real-time sensitive method to detect IgG directed against neuronal surface proteins, which could be used as an additional step to rule out ambiguous seropositivity diagnoses. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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

2009-02-02

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

Detection and identification of Brettanomyces/Dekkera sp. yeasts with a loop-mediated isothermal amplification method.

PubMed

Hayashi, Nobuyuki; Arai, Ritsuko; Tada, Setsuzo; Taguchi, Hiroshi; Ogawa, Yutaka

2007-01-01

Primer sets for a loop-mediated isothermal amplification (LAMP) method were developed to specifically identify each of the four Brettanomyces/Dekkera species, Dekkera anomala, Dekkera bruxellensis, Dekkera custersiana and Brettanomyces naardenensis. Each primer set was designed with target sequences in the ITS region of the four species and could specifically amplify the target DNA of isolates from beer, wine and soft drinks. Furthermore, the primer sets differentiated strains of the target species from strains belonging to other species, even within the genus Brettanomyces/Dekkera. Moreover, the LAMP method with these primer sets could detect about 1 x 10(1) cfu/ml of Brettanomyces/Dekkera yeasts from suspensions in distilled water, wine and beer. This LAMP method with primer sets for the identification of Brettanomyces/Dekkera yeasts is advantageous in terms of specificity, sensitivity and ease of operation compared with standard PCR methods.

A novel visual saliency detection method for infrared video sequences

NASA Astrophysics Data System (ADS)

Wang, Xin; Zhang, Yuzhen; Ning, Chen

2017-12-01

Infrared video applications such as target detection and recognition, moving target tracking, and so forth can benefit a lot from visual saliency detection, which is essentially a method to automatically localize the ;important; content in videos. In this paper, a novel visual saliency detection method for infrared video sequences is proposed. Specifically, for infrared video saliency detection, both the spatial saliency and temporal saliency are considered. For spatial saliency, we adopt a mutual consistency-guided spatial cues combination-based method to capture the regions with obvious luminance contrast and contour features. For temporal saliency, a multi-frame symmetric difference approach is proposed to discriminate salient moving regions of interest from background motions. Then, the spatial saliency and temporal saliency are combined to compute the spatiotemporal saliency using an adaptive fusion strategy. Besides, to highlight the spatiotemporal salient regions uniformly, a multi-scale fusion approach is embedded into the spatiotemporal saliency model. Finally, a Gestalt theory-inspired optimization algorithm is designed to further improve the reliability of the final saliency map. Experimental results demonstrate that our method outperforms many state-of-the-art saliency detection approaches for infrared videos under various backgrounds.

Methods, microfluidic devices, and systems for detection of an active enzymatic agent

DOEpatents

Sommer, Gregory J; Hatch, Anson V; Singh, Anup K; Wang, Ying-Chih

2014-10-28

Embodiments of the present invention provide methods, microfluidic devices, and systems for the detection of an active target agent in a fluid sample. A substrate molecule is used that contains a sequence which may cleave in the presence of an active target agent. A SNAP25 sequence is described, for example, that may be cleaved in the presence of Botulinum Neurotoxin. The substrate molecule includes a reporter moiety. The substrate molecule is exposed to the sample, and resulting reaction products separated using electrophoretic separation. The elution time of the reporter moiety may be utilized to identify the presence or absence of the active target agent.

Moving target detection for frequency agility radar by sparse reconstruction

NASA Astrophysics Data System (ADS)

Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

2016-09-01

Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

Moving target detection for frequency agility radar by sparse reconstruction.

PubMed

Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

2016-09-01

Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

Autonomous space target recognition and tracking approach using star sensors based on a Kalman filter.

PubMed

Ye, Tao; Zhou, Fuqiang

2015-04-10

When imaged by detectors, space targets (including satellites and debris) and background stars have similar point-spread functions, and both objects appear to change as detectors track targets. Therefore, traditional tracking methods cannot separate targets from stars and cannot directly recognize targets in 2D images. Consequently, we propose an autonomous space target recognition and tracking approach using a star sensor technique and a Kalman filter (KF). A two-step method for subpixel-scale detection of star objects (including stars and targets) is developed, and the combination of the star sensor technique and a KF is used to track targets. The experimental results show that the proposed method is adequate for autonomously recognizing and tracking space targets.

Detection of target-probe oligonucleotide hybridization using synthetic nanopore resistive pulse sensing.

PubMed

Booth, Marsilea Adela; Vogel, Robert; Curran, James M; Harbison, SallyAnn; Travas-Sejdic, Jadranka

2013-07-15

Despite the plethora of DNA sensor platforms available, a portable, sensitive, selective and economic sensor able to rival current fluorescence-based techniques would find use in many applications. In this research, probe oligonucleotide-grafted particles are used to detect target DNA in solution through a resistive pulse nanopore detection technique. Using carbodiimide chemistry, functionalized probe DNA strands are attached to carboxylated dextran-based magnetic particles. Subsequent incubation with complementary target DNA yields a change in surface properties as the two DNA strands hybridize. Particle-by-particle analysis with resistive pulse sensing is performed to detect these changes. A variable pressure method allows identification of changes in the surface charge of particles. As proof-of-principle, we demonstrate that target hybridization is selectively detected at micromolar concentrations (nanomoles of target) using resistive pulse sensing, confirmed by fluorescence and phase analysis light scattering as complementary techniques. The advantages, feasibility and limitations of using resistive pulse sensing for sample analysis are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

Fuzzy System-Based Target Selection for a NIR Camera-Based Gaze Tracker

PubMed Central

Naqvi, Rizwan Ali; Arsalan, Muhammad; Park, Kang Ryoung

2017-01-01

Gaze-based interaction (GBI) techniques have been a popular subject of research in the last few decades. Among other applications, GBI can be used by persons with disabilities to perform everyday tasks, as a game interface, and can play a pivotal role in the human computer interface (HCI) field. While gaze tracking systems have shown high accuracy in GBI, detecting a user’s gaze for target selection is a challenging problem that needs to be considered while using a gaze detection system. Past research has used the blinking of the eyes for this purpose as well as dwell time-based methods, but these techniques are either inconvenient for the user or requires a long time for target selection. Therefore, in this paper, we propose a method for fuzzy system-based target selection for near-infrared (NIR) camera-based gaze trackers. The results of experiments performed in addition to tests of the usability and on-screen keyboard use of the proposed method show that it is better than previous methods. PMID:28420114

PCR technology for screening and quantification of genetically modified organisms (GMOs).

PubMed

Holst-Jensen, Arne; Rønning, Sissel B; Løvseth, Astrid; Berdal, Knut G

2003-04-01

Although PCR technology has obvious limitations, the potentially high degree of sensitivity and specificity explains why it has been the first choice of most analytical laboratories interested in detection of genetically modified (GM) organisms (GMOs) and derived materials. Because the products that laboratories receive for analysis are often processed and refined, the quality and quantity of target analyte (e.g. protein or DNA) frequently challenges the sensitivity of any detection method. Among the currently available methods, PCR methods are generally accepted as the most sensitive and reliable methods for detection of GM-derived material in routine applications. The choice of target sequence motif is the single most important factor controlling the specificity of the PCR method. The target sequence is normally a part of the modified gene construct, for example a promoter, a terminator, a gene, or a junction between two of these elements. However, the elements may originate from wildtype organisms, they may be present in more than one GMO, and their copy number may also vary from one GMO to another. They may even be combined in a similar way in more than one GMO. Thus, the choice of method should fit the purpose. Recent developments include event-specific methods, particularly useful for identification and quantification of GM content. Thresholds for labelling are now in place in many countries including those in the European Union. The success of the labelling schemes is dependent upon the efficiency with which GM-derived material can be detected. We will present an overview of currently available PCR methods for screening and quantification of GM-derived DNA, and discuss their applicability and limitations. In addition, we will discuss some of the major challenges related to determination of the limits of detection (LOD) and quantification (LOQ), and to validation of methods.

An enzyme free electrochemical biosensor for sensitive detection of miRNA with a high discrimination factor by coupling the strand displacement reaction and catalytic hairpin assembly recycling.

PubMed

Yao, Juan; Zhang, Zhang; Deng, Zhenghua; Wang, Youqiang; Guo, Yongcan

2017-10-23

An isothermal, enzyme free, ultra-specific and ultra-sensitive protocol for electrochemical detection of miRNAs is proposed based on the toehold-mediated strand displacement reaction (SDR) and non-enzymatic catalytic hairpin reaction (CHA) recycling. The SDR was first triggered only in the presence of target miRNA and this process also affects other miRNA interferences having similar target sequences, thus guaranteeing a high discrimination factor and could be used in rare content miRNA detection with various amounts of interferences having similar target sequences. The output protector strand then triggered enzyme free CHA amplification and generates plenty of hairpin self-assembly products. This process in turn influences SDR equilibrium to move to the right and generates large amounts of protector output to ensure analysis sensitivity. Compared with traditional CHA, our proposed method greatly improved the signal to noise ratio and shows excellent performance in rare miRNA detection with miRNA analogue interference. Under the optimal experimental conditions and using square wave voltammetry, the established biosensor could detect target miRNA-21 down to 30 fM (S/N = 3) with a dynamic range from 100 fM to 2 nM, and discriminate rare target miRNA-21 from mismatched miRNA with high selectivity. This method holds great promise in miRNA detection from human cancer cell lines and would be a versatile and powerful tool for clinical molecular diagnostics.

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

NASA Astrophysics Data System (ADS)

Grossman, S.

2015-05-01

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

Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling

PubMed Central

Zhao, Liang; Chen, Feng; Dai, Jing; Hua, Ting; Lu, Chang-Tien; Ramakrishnan, Naren

2014-01-01

Twitter has become a popular data source as a surrogate for monitoring and detecting events. Targeted domains such as crime, election, and social unrest require the creation of algorithms capable of detecting events pertinent to these domains. Due to the unstructured language, short-length messages, dynamics, and heterogeneity typical of Twitter data streams, it is technically difficult and labor-intensive to develop and maintain supervised learning systems. We present a novel unsupervised approach for detecting spatial events in targeted domains and illustrate this approach using one specific domain, viz. civil unrest modeling. Given a targeted domain, we propose a dynamic query expansion algorithm to iteratively expand domain-related terms, and generate a tweet homogeneous graph. An anomaly identification method is utilized to detect spatial events over this graph by jointly maximizing local modularity and spatial scan statistics. Extensive experiments conducted in 10 Latin American countries demonstrate the effectiveness of the proposed approach. PMID:25350136

Multi-Frequency Signal Detection Based on Frequency Exchange and Re-Scaling Stochastic Resonance and Its Application to Weak Fault Diagnosis

PubMed Central

Leng, Yonggang; Fan, Shengbo

2018-01-01

Mechanical fault diagnosis usually requires not only identification of the fault characteristic frequency, but also detection of its second and/or higher harmonics. However, it is difficult to detect a multi-frequency fault signal through the existing Stochastic Resonance (SR) methods, because the characteristic frequency of the fault signal as well as its second and higher harmonics frequencies tend to be large parameters. To solve the problem, this paper proposes a multi-frequency signal detection method based on Frequency Exchange and Re-scaling Stochastic Resonance (FERSR). In the method, frequency exchange is implemented using filtering technique and Single SideBand (SSB) modulation. This new method can overcome the limitation of "sampling ratio" which is the ratio of the sampling frequency to the frequency of target signal. It also ensures that the multi-frequency target signals can be processed to meet the small-parameter conditions. Simulation results demonstrate that the method shows good performance for detecting a multi-frequency signal with low sampling ratio. Two practical cases are employed to further validate the effectiveness and applicability of this method. PMID:29693577

A fluorescence method for detection of DNA and DNA methylation based on graphene oxide and restriction endonuclease HpaII.

PubMed

Wei, Wei; Gao, Chunyan; Xiong, Yanxiang; Zhang, Yuanjian; Liu, Songqin; Pu, Yuepu

2015-01-01

DNA methylation plays an important role in many biological events and is associated with various diseases. Most traditional methods for detection of DNA methylation are based on the complex and expensive bisulfite method. In this paper, we report a novel fluorescence method to detect DNA and DNA methylation based on graphene oxide (GO) and restriction endonuclease HpaII. The skillfully designed probe DNA labeled with 5-carboxyfluorescein (FAM) and optimized GO concentration keep the probe/target DNA still adsorbed on the GO. After the cleavage action of HpaII the labeled FAM is released from the GO surface and its fluorescence recovers, which could be used to detect DNA in the linear range of 50 pM-50 nM with a detection limit of 43 pM. DNA methylation induced by transmethylase (Mtase) or other chemical reagents prevents HpaII from recognizing and cleaving the specific site; as a result, fluorescence cannot recover. The fluorescence recovery efficiency is closely related to the DNA methylation level, which can be used to detect DNA methylation by comparing it with the fluorescence in the presence of intact target DNA. The method for detection of DNA and DNA methylation is simple, reliable and accurate. Copyright © 2014 Elsevier B.V. All rights reserved.

Selectivity enhancement in photoacoustic gas analysis via phase-sensitive detection at high modulation frequency

NASA Technical Reports Server (NTRS)

Kosterev, Anatoliy (Inventor)

2010-01-01

A method for detecting a target fluid in a fluid sample comprising a first fluid and the target fluid using photoacoustic spectroscopy (PAS), comprises a) providing a light source configured to introduce an optical signal having at least one wavelength into the fluid sample; b) modulating the optical signal at a desired modulation frequency such that the optical signal generates an acoustic signal in the fluid sample; c) measuring the acoustic signal in a resonant acoustic detector; and d) using the phase of the acoustic signal to detect the presence of the target fluid.

A novel procedure for detecting and focusing moving objects with SAR based on the Wigner-Ville distribution

NASA Astrophysics Data System (ADS)

Barbarossa, S.; Farina, A.

A novel scheme for detecting moving targets with synthetic aperture radar (SAR) is presented. The proposed approach is based on the use of the Wigner-Ville distribution (WVD) for simultaneously detecting moving targets and estimating their motion kinematic parameters. The estimation plays a key role for focusing the target and correctly locating it with respect to the stationary background. The method has a number of advantages: (i) the detection is efficiently performed on the samples in the time-frequency domain, provided the WVD, without resorting to the use of a bank of filters, each one matched to possible values of the unknown target motion parameters; (ii) the estimation of the target motion parameters can be done on the same time-frequency domain by locating the line where the maximum energy of the WVD is concentrated. A validation of the approach is given by both analytical and simulation means. In addition, the estimation of the target kinematic parameters and the corresponding image focusing are also demonstrated.

Generic Sensor Modeling Using Pulse Method

NASA Technical Reports Server (NTRS)

Helder, Dennis L.; Choi, Taeyoung

2005-01-01

Recent development of high spatial resolution satellites such as IKONOS, Quickbird and Orbview enable observation of the Earth's surface with sub-meter resolution. Compared to the 30 meter resolution of Landsat 5 TM, the amount of information in the output image was dramatically increased. In this era of high spatial resolution, the estimation of spatial quality of images is gaining attention. Historically, the Modulation Transfer Function (MTF) concept has been used to estimate an imaging system's spatial quality. Sometimes classified by target shapes, various methods were developed in laboratory environment utilizing sinusoidal inputs, periodic bar patterns and narrow slits. On-orbit sensor MTF estimation was performed on 30-meter GSD Landsat4 Thematic Mapper (TM) data from the bridge pulse target as a pulse input . Because of a high resolution sensor s small Ground Sampling Distance (GSD), reasonably sized man-made edge, pulse, and impulse targets can be deployed on a uniform grassy area with accurate control of ground targets using tarps and convex mirrors. All the previous work cited calculated MTF without testing the MTF estimator's performance. In previous report, a numerical generic sensor model had been developed to simulate and improve the performance of on-orbit MTF estimating techniques. Results from the previous sensor modeling report that have been incorporated into standard MTF estimation work include Fermi edge detection and the newly developed 4th order modified Savitzky-Golay (MSG) interpolation technique. Noise sensitivity had been studied by performing simulations on known noise sources and a sensor model. Extensive investigation was done to characterize multi-resolution ground noise. Finally, angle simulation was tested by using synthetic pulse targets with angles from 2 to 15 degrees, several brightness levels, and different noise levels from both ground targets and imaging system. As a continuing research activity using the developed sensor model, this report was dedicated to MTF estimation via pulse input method characterization using the Fermi edge detection and 4th order MSG interpolation method. The relationship between pulse width and MTF value at Nyquist was studied including error detection and correction schemes. Pulse target angle sensitivity was studied by using synthetic targets angled from 2 to 12 degrees. In this report, from the ground and system noise simulation, a minimum SNR value was suggested for a stable MTF value at Nyquist for the pulse method. Target width error detection and adjustment technique based on a smooth transition of MTF profile is presented, which is specifically applicable only to the pulse method with 3 pixel wide targets.

Reverse transcription strand invasion based amplification (RT-SIBA): a method for rapid detection of influenza A and B.

PubMed

Eboigbodin, Kevin; Filén, Sanna; Ojalehto, Tuomas; Brummer, Mirko; Elf, Sonja; Pousi, Kirsi; Hoser, Mark

2016-06-01

Rapid and accurate diagnosis of influenza viruses plays an important role in infection control, as well as in preventing the misuse of antibiotics. Isothermal nucleic acid amplification methods offer significant advantages over the polymerase chain reaction (PCR), since they are more rapid and do not require the sophisticated instruments needed for thermal cycling. We previously described a novel isothermal nucleic acid amplification method, 'Strand Invasion Based Amplification' (SIBA®), with high analytical sensitivity and specificity, for the detection of DNA. In this study, we describe the development of a variant of the SIBA method, namely, reverse transcription SIBA (RT-SIBA), for the rapid detection of viral RNA targets. The RT-SIBA method includes a reverse transcriptase enzyme that allows one-step reverse transcription of RNA to complementary DNA (cDNA) and simultaneous amplification and detection of the cDNA by SIBA under isothermal reaction conditions. The RT-SIBA method was found to be more sensitive than PCR for the detection of influenza A and B and could detect 100 copies of influenza RNA within 15 min. The development of RT-SIBA will enable rapid and accurate diagnosis of viral RNA targets within point-of-care or central laboratory settings.

Detection and differentiation of Fusarium oxysporum f. sp. lycopersici race 1 using loop-mediated isothermal amplification with three primer sets.

PubMed

Ayukawa, Y; Komatsu, K; Kashiwa, T; Akai, K; Yamada, M; Teraoka, T; Arie, T

2016-09-01

Fusarium oxysporum f. sp. lycopersici (Fol) causes tomato wilt. Based on the difference in pathogenicity towards tomato cultivars, Fol is classified into three races. In this study, a rapid method is developed for the detection and discrimination of Fol race 1 using a loop-mediated isothermal amplification (LAMP) assay with two primer sets targeting a region of the nucleotide sequence of the SIX4 gene specific for race 1 and a primer set targeting the SIX5 gene, conserved in all known Fol isolates. Upon LAMP reaction, amplification using all three primer sets was observed only when DNA of Fol race 1 was used as a template, and not when DNA of other Fol races or other fungal species was used. This method could detect 300 fg of Fol race 1 DNA, a 100-fold higher sensitivity than that obtained by conventional PCR. The method can also detect DNA extracted from soil artificially infested with Fol race 1. It is now possible to detect Fol race 1 in colonies and infected tomato stems without DNA isolation. This method is a rapid and simple tool for discrimination of Fol race 1. This study developed a loop-mediated isothermal amplification (LAMP) assay for detection and differentiation of Fusarium oxysporum f. sp. lycopersici (Fol) race 1 by using three primer sets targeting for the SIX4 and SIX5 genes. These genes are present together only in Fol race 1. This method can detect Fol race 1 in infected tomato stems without DNA extraction, affording an efficient diagnosis of Fusarium wilt on tomatoes in the field. © 2016 The Society for Applied Microbiology.

Single-Step qPCR and dPCR Detection of Diverse CRISPR-Cas9 Gene Editing Events In Vivo.

PubMed

Falabella, Micol; Sun, Linqing; Barr, Justin; Pena, Andressa Z; Kershaw, Erin E; Gingras, Sebastien; Goncharova, Elena A; Kaufman, Brett A

2017-10-05

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR-associated protein 9 (Cas9)-based technology is currently the most flexible means to create targeted mutations by recombination or indel mutations by nonhomologous end joining. During mouse transgenesis, recombinant and indel alleles are often pursued simultaneously. Multiple alleles can be formed in each animal to create significant genetic complexity that complicates the CRISPR-Cas9 approach and analysis. Currently, there are no rapid methods to measure the extent of on-site editing with broad mutation sensitivity. In this study, we demonstrate the allelic diversity arising from targeted CRISPR editing in founder mice. Using this DNA sample collection, we validated specific quantitative and digital PCR methods (qPCR and dPCR, respectively) for measuring the frequency of on-target editing in founder mice. We found that locked nucleic acid (LNA) probes combined with an internal reference probe (Drop-Off Assay) provide accurate measurements of editing rates. The Drop-Off LNA Assay also detected on-target CRISPR-Cas9 gene editing in blastocysts with a sensitivity comparable to PCR-clone sequencing. Lastly, we demonstrate that the allele-specific LNA probes used in qPCR competitor assays can accurately detect recombinant mutations in founder mice. In summary, we show that LNA-based qPCR and dPCR assays provide a rapid method for quantifying the extent of on-target genome editing in vivo , testing RNA guides, and detecting recombinant mutations. Copyright © 2017 Falabella et al.

Occurrence of naproxen, ibuprofen, and diclofenac residues in wastewater and river water of KwaZulu-Natal Province in South Africa.

PubMed

Madikizela, Lawrence Mzukisi; Chimuka, Luke

2017-07-01

The present paper reports a detailed study that is based on the monitoring of naproxen, ibuprofen, and diclofenac in Mbokodweni River and wastewater treatment plants (WWTPs) located around the city of Durban in KwaZulu-Natal Province of South Africa. Target compounds were extracted from water samples using a multi-template molecularly imprinted solid-phase extraction prior to separation and quantification on a high-performance liquid chromatography equipped with photo diode array detector. The analytical method yielded the detection limits of 0.15, 1.00, and 0.63 μg/L for naproxen, ibuprofen, and diclofenac, respectively. Solid-phase extraction method was evaluated for its performance using deionized water samples that were spiked with 5 and 50 μg/L of target compounds. Recoveries were greater than 80% for all target compounds with RSD values in the range of 4.1 to 10%. Target compounds were detected in most wastewater and river water samples with ibuprofen being the most frequently detected pharmaceutical. Maximum concentrations detected in river water for naproxen, ibuprofen, and diclofenac were 6.84, 19.2, and 9.69 μg/L, respectively. The concentrations of target compounds found in effluent and river water samples compared well with some studies. The analytical method employed in this work is fast, selective, sensitive, and affordable; therefore, it can be used routinely to evaluate the occurrence of acidic pharmaceuticals in South African water resources.

Beyond the Sparsity-Based Target Detector: A Hybrid Sparsity and Statistics Based Detector for Hyperspectral Images.

PubMed

Du, Bo; Zhang, Yuxiang; Zhang, Liangpei; Tao, Dacheng

2016-08-18

Hyperspectral images provide great potential for target detection, however, new challenges are also introduced for hyperspectral target detection, resulting that hyperspectral target detection should be treated as a new problem and modeled differently. Many classical detectors are proposed based on the linear mixing model and the sparsity model. However, the former type of model cannot deal well with spectral variability in limited endmembers, and the latter type of model usually treats the target detection as a simple classification problem and pays less attention to the low target probability. In this case, can we find an efficient way to utilize both the high-dimension features behind hyperspectral images and the limited target information to extract small targets? This paper proposes a novel sparsitybased detector named the hybrid sparsity and statistics detector (HSSD) for target detection in hyperspectral imagery, which can effectively deal with the above two problems. The proposed algorithm designs a hypothesis-specific dictionary based on the prior hypotheses for the test pixel, which can avoid the imbalanced number of training samples for a class-specific dictionary. Then, a purification process is employed for the background training samples in order to construct an effective competition between the two hypotheses. Next, a sparse representation based binary hypothesis model merged with additive Gaussian noise is proposed to represent the image. Finally, a generalized likelihood ratio test is performed to obtain a more robust detection decision than the reconstruction residual based detection methods. Extensive experimental results with three hyperspectral datasets confirm that the proposed HSSD algorithm clearly outperforms the stateof- the-art target detectors.

Targeted Analyte Detection by Standard Addition Improves Detection Limits in MALDI Mass Spectrometry

PubMed Central

Eshghi, Shadi Toghi; Li, Xingde; Zhang, Hui

2014-01-01

Matrix-assisted laser desorption/ionization has proven an effective tool for fast and accurate determination of many molecules. However, the detector sensitivity and chemical noise compromise the detection of many invaluable low-abundance molecules from biological and clinical samples. To challenge this limitation, we developed a targeted analyte detection (TAD) technique. In TAD, the target analyte is selectively elevated by spiking a known amount of that analyte into the sample, thereby raising its concentration above the noise level, where we take advantage of the improved sensitivity to detect the presence of the endogenous analyte in the sample. We assessed TAD on three peptides in simple and complex background solutions with various exogenous analyte concentrations in two MALDI matrices. TAD successfully improved the limit of detection (LOD) of target analytes when the target peptides were added to the sample in a concentration close to optimum concentration. The optimum exogenous concentration was estimated through a quantitative method to be approximately equal to the original LOD for each target. Also, we showed that TAD could achieve LOD improvements on an average of 3-fold in a simple and 2-fold in a complex sample. TAD provides a straightforward assay to improve the LOD of generic target analytes without the need for costly hardware modifications. PMID:22877355

Targeted analyte detection by standard addition improves detection limits in matrix-assisted laser desorption/ionization mass spectrometry.

PubMed

Toghi Eshghi, Shadi; Li, Xingde; Zhang, Hui

2012-09-18

Matrix-assisted laser desorption/ionization (MALDI) has proven an effective tool for fast and accurate determination of many molecules. However, the detector sensitivity and chemical noise compromise the detection of many invaluable low-abundance molecules from biological and clinical samples. To challenge this limitation, we developed a targeted analyte detection (TAD) technique. In TAD, the target analyte is selectively elevated by spiking a known amount of that analyte into the sample, thereby raising its concentration above the noise level, where we take advantage of the improved sensitivity to detect the presence of the endogenous analyte in the sample. We assessed TAD on three peptides in simple and complex background solutions with various exogenous analyte concentrations in two MALDI matrices. TAD successfully improved the limit of detection (LOD) of target analytes when the target peptides were added to the sample in a concentration close to optimum concentration. The optimum exogenous concentration was estimated through a quantitative method to be approximately equal to the original LOD for each target. Also, we showed that TAD could achieve LOD improvements on an average of 3-fold in a simple and 2-fold in a complex sample. TAD provides a straightforward assay to improve the LOD of generic target analytes without the need for costly hardware modifications.

Development of three-dimensional tracking system using astigmatic lens method for microscopes

NASA Astrophysics Data System (ADS)

Kibata, Hiroki; Ishii, Katsuhiro

2017-07-01

We have developed a three-dimensional tracking system for microscopes. Using the astigmatic lens method and a CMOS image sensor, we realize a rapid detection of a target position in a wide range. We demonstrate a target tracking using the developed system.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

A Parallel Finite Set Statistical Simulator for Multi-Target Detection and Tracking

NASA Astrophysics Data System (ADS)

Hussein, I.; MacMillan, R.

2014-09-01

Finite Set Statistics (FISST) is a powerful Bayesian inference tool for the joint detection, classification and tracking of multi-target environments. FISST is capable of handling phenomena such as clutter, misdetections, and target birth and decay. Implicit within the approach are solutions to the data association and target label-tracking problems. Finally, FISST provides generalized information measures that can be used for sensor allocation across different types of tasks such as: searching for new targets, and classification and tracking of known targets. These FISST capabilities have been demonstrated on several small-scale illustrative examples. However, for implementation in a large-scale system as in the Space Situational Awareness problem, these capabilities require a lot of computational power. In this paper, we implement FISST in a parallel environment for the joint detection and tracking of multi-target systems. In this implementation, false alarms and misdetections will be modeled. Target birth and decay will not be modeled in the present paper. We will demonstrate the success of the method for as many targets as we possibly can in a desktop parallel environment. Performance measures will include: number of targets in the simulation, certainty of detected target tracks, computational time as a function of clutter returns and number of targets, among other factors.

A novel method for extracting nucleic acids from dried blood spots for ultrasensitive detection of low-density Plasmodium falciparum and Plasmodium vivax infections.

PubMed

Zainabadi, Kayvan; Adams, Matthew; Han, Zay Yar; Lwin, Hnin Wai; Han, Kay Thwe; Ouattara, Amed; Thura, Si; Plowe, Christopher V; Nyunt, Myaing M

2017-09-18

Greater Mekong Subregion countries are committed to eliminating Plasmodium falciparum malaria by 2025. Current elimination interventions target infections at parasite densities that can be detected by standard microscopy or rapid diagnostic tests (RDTs). More sensitive detection methods have been developed to detect lower density "asymptomatic" infections that may represent an important transmission reservoir. These ultrasensitive polymerase chain reaction (usPCR) tests have been used to identify target populations for mass drug administration (MDA). To date, malaria usPCR tests have used either venous or capillary blood sampling, which entails complex sample collection, processing and shipping requirements. An ultrasensitive method performed on standard dried blood spots (DBS) would greatly facilitate the molecular surveillance studies needed for targeting elimination interventions. A highly sensitive method for detecting Plasmodium falciparum and P. vivax 18S ribosomal RNA from DBS was developed by empirically optimizing nucleic acid extraction conditions. The limit of detection (LoD) was determined using spiked DBS samples that were dried and stored under simulated field conditions. Further, to assess its utility for routine molecular surveillance, two cross-sectional surveys were performed in Myanmar during the wet and dry seasons. The lower LoD of the DBS-based ultrasensitive assay was 20 parasites/mL for DBS collected on Whatman 3MM filter paper and 23 parasites/mL for Whatman 903 Protein Saver cards-equivalent to 1 parasite per 50 µL DBS. This is about 5000-fold more sensitive than standard RDTs and similar to the LoD of ≤16-22 parasites/mL reported for other ultrasensitive methods based on whole blood. In two cross-sectional surveys in Myanmar, nearly identical prevalence estimates were obtained from contemporaneous DBS samples and capillary blood samples collected during the wet and dry season. The DBS-based ultrasensitive method described in this study shows equal sensitivity as previously described methods based on whole blood, both in its limit of detection and prevalence estimates in two field surveys. The reduced cost and complexity of this method will allow for the scale-up of surveillance studies to target MDA and other malaria elimination interventions, and help lead to a better understanding of the epidemiology of low-density malaria infections.

Detection of respiratory viruses and bacteria in children using a twenty-two target reverse-transcription real-time PCR (RT-qPCR) panel.

PubMed

Ellis, Chelsey; Misir, Amita; Hui, Charles; Jabbour, Mona; Barrowman, Nicholas; Langill, Jonathan; Bowes, Jennifer; Slinger, Robert

2016-05-01

Rapid detection of the wide range of viruses and bacteria that cause respiratory infection in children is important for patient care and antibiotic stewardship. We therefore designed and evaluated a ready-to-use 22 target respiratory infection reverse-transcription real-time polymerase chain reaction (RT-qPCR) panel to determine if this would improve detection of these agents at our pediatric hospital. RT-qPCR assays for twenty-two target organisms were dried-down in individual wells of 96 well plates and saved at room temperature. Targets included 18 respiratory viruses and 4 bacteria. After automated nucleic acid extraction of nasopharyngeal aspirate (NPA) samples, rapid qPCR was performed. RT-qPCR results were compared with those obtained by the testing methods used at our hospital laboratories. One hundred fifty-nine pediatric NPA samples were tested with the RT-qPCR panel. One or more respiratory pathogens were detected in 132/159 (83%) samples. This was significantly higher than the detection rate of standard methods (94/159, 59%) (P<0.001). This difference was mainly due to improved RT-qPCR detection of rhinoviruses, parainfluenza viruses, bocavirus, and coronaviruses. The panel internal control assay performance remained stable at room temperature storage over a two-month testing period. The RT-qPCR panel was able to identify pathogens in a high proportion of respiratory samples. The panel detected more positive specimens than the methods in use at our hospital. The pre-made panel format was easy to use and rapid, with results available in approximately 90 minutes. We now plan to determine if use of this panel improves patient care and antibiotic stewardship.

The detection methods of dynamic objects

NASA Astrophysics Data System (ADS)

Knyazev, N. L.; Denisova, L. A.

2018-01-01

The article deals with the application of cluster analysis methods for solving the task of aircraft detection on the basis of distribution of navigation parameters selection into groups (clusters). The modified method of cluster analysis for search and detection of objects and then iterative combining in clusters with the subsequent count of their quantity for increase in accuracy of the aircraft detection have been suggested. The course of the method operation and the features of implementation have been considered. In the conclusion the noted efficiency of the offered method for exact cluster analysis for finding targets has been shown.

Electromagnetic Induction Spectroscopy for the Detection of Subsurface Targets

DTIC Science & Technology

2012-12-01

curves of the proposed method and that of Fails et al.. For the kNN ROC curve, k = 7. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81...et al. [6] and Ramachandran et al. [7] both demonstrated success in detecting mines using the k-nearest-neighbor ( kNN ) algorithm based on the EMI...error is also included in the feature vector. The kNN labels an unknown target based on the closest targets in a training set. Collins et al. [2] and

Comparison between target magnetic resonance imaging (MRI) in-gantry and cognitively directed transperineal or transrectal-guided prostate biopsies for Prostate Imaging-Reporting and Data System (PI-RADS) 3-5 MRI lesions.

PubMed

Yaxley, Anna J; Yaxley, John W; Thangasamy, Isaac A; Ballard, Emma; Pokorny, Morgan R

2017-11-01

To compare the detection rates of prostate cancer (PCa) in men with Prostate Imaging-Reporting and Data System (PI-RADS) 3-5 abnormalities on 3-Tesla multiparametric (mp) magnetic resonance imaging (MRI) using in-bore MRI-guided biopsy compared with cognitively directed transperineal (cTP) biopsy and transrectal ultrasonography (cTRUS) biopsy. This was a retrospective single-centre study of consecutive men attending the private practice clinic of an experienced urologist performing MRI-guided biopsy and an experienced urologist performing cTP and cTRUS biopsy techniques for PI-RADS 3-5 lesions identified on 3-Tesla mpMRI. There were 595 target mpMRI lesions from 482 men with PI-RADS 3-5 regions of interest during 483 episodes of biopsy. The abnormal mpMRI target lesion was biopsied using the MRI-guided method for 298 biopsies, the cTP method for 248 biopsies and the cTRUS method for 49 biopsies. There were no significant differences in PCa detection among the three biopsy methods in PI-RADS 3 (48.9%, 40.0% and 44.4%, respectively), PI-RADS 4 (73.2%, 81.0% and 85.0%, respectively) or PI-RADS 5 (95.2, 92.0% and 95.0%, respectively) lesions, and there was no significant difference in detection of significant PCa among the biopsy methods in PI-RADS 3 (42.2%, 30.0% and 33.3%, respectively), PI-RADS 4 (66.8%, 66.0% and 80.0%, respectively) or PI-RADS 5 (90.5%, 89.8% and 90.0%, respectively) lesions. There were also no differences in PCa or significant PCa detection based on lesion location or size among the methods. We found no significant difference in the ability to detect PCa or significant PCa using targeted MRI-guided, cTP or cTRUS biopsy methods. Identification of an abnormal area on mpMRI appears to be more important in increasing the detection of PCa than the technique used to biopsy an MRI abnormality. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Moving Object Detection on a Vehicle Mounted Back-Up Camera

PubMed Central

Kim, Dong-Sun; Kwon, Jinsan

2015-01-01

In the detection of moving objects from vision sources one usually assumes that the scene has been captured by stationary cameras. In case of backing up a vehicle, however, the camera mounted on the vehicle moves according to the vehicle’s movement, resulting in ego-motions on the background. This results in mixed motion in the scene, and makes it difficult to distinguish between the target objects and background motions. Without further treatments on the mixed motion, traditional fixed-viewpoint object detection methods will lead to many false-positive detection results. In this paper, we suggest a procedure to be used with the traditional moving object detection methods relaxing the stationary cameras restriction, by introducing additional steps before and after the detection. We also decribe the implementation as a FPGA platform along with the algorithm. The target application of this suggestion is use with a road vehicle’s rear-view camera systems. PMID:26712761

An Automated Directed Spectral Search Methodology for Small Target Detection

NASA Astrophysics Data System (ADS)

Grossman, Stanley I.

Much of the current efforts in remote sensing tackle macro-level problems such as determining the extent of wheat in a field, the general health of vegetation or the extent of mineral deposits in an area. However, for many of the remaining remote sensing challenges being studied currently, such as border protection, drug smuggling, treaty verification, and the war on terror, most targets are very small in nature - a vehicle or even a person. While in typical macro-level problems the objective vegetation is in the scene, for small target detection problems it is not usually known if the desired small target even exists in the scene, never mind finding it in abundance. The ability to find specific small targets, such as vehicles, typifies this problem. Complicating the analyst's life, the growing number of available sensors is generating mountains of imagery outstripping the analysts' ability to visually peruse them. This work presents the important factors influencing spectral exploitation using multispectral data and suggests a different approach to small target detection. The methodology of directed search is presented, including the use of scene-modeled spectral libraries, various search algorithms, and traditional statistical and ROC curve analysis. The work suggests a new metric to calibrate analysis labeled the analytic sweet spot as well as an estimation method for identifying the sweet spot threshold for an image. It also suggests a new visualization aid for highlighting the target in its entirety called nearest neighbor inflation (NNI). It brings these all together to propose that these additions to the target detection arena allow for the construction of a fully automated target detection scheme. This dissertation next details experiments to support the hypothesis that the optimum detection threshold is the analytic sweet spot and that the estimation method adequately predicts it. Experimental results and analysis are presented for the proposed directed search techniques of spectral image based small target detection. It offers evidence of the functionality of the NNI visualization and also provides evidence that the increased spectral dimensionality of the 8-band Worldview-2 datasets provides noteworthy improvement in results over traditional 4-band multispectral datasets. The final experiment presents the results from a prototype fully automated target detection scheme in support of the overarching premise. This work establishes the analytic sweet spot as the optimum threshold defined as the point where error detection rate curves -- false detections vs. missing detections -- cross. At this point the errors are minimized while the detection rate is maximized. It then demonstrates that taking the first moment statistic of the histogram of calculated target detection values from a detection search with test threshold set arbitrarily high will estimate the analytic sweet spot for that image. It also demonstrates that directed search techniques -- when utilized with appropriate scene-specific modeled signatures and atmospheric compensations -- perform at least as well as in-scene search techniques 88% of the time and grossly under-performing only 11% of the time; the in-scene only performs as well or better 50% of the time. It further demonstrates the clear advantage increased multispectral dimensionality brings to detection searches improving performance in 50% of the cases while performing at least as well 72% of the time. Lastly, it presents evidence that a fully automated prototype performs as anticipated laying the groundwork for further research into fully automated processes for small target detection.

Aptasensors for rapid detection of Escherichia coli O157:H7 and Salmonella typhimurium

NASA Astrophysics Data System (ADS)

Wu, Wen-he; Li, Min; Wang, Yue; Ouyang, Hou-xian; Wang, Lin; Li, Ci-xiu; Cao, Yu-chen; Meng, Qing-he; Lu, Jian-xin

2012-11-01

Herein we reported the development of aptamer-based biosensors (aptasensors) based on label-free aptamers and gold nanoparticles (AuNPs) for detection of Escherichia coli ( E. coli) O157:H7 and Salmonella typhimurium. Target bacteria binding aptamers are adsorbed on the surface of unmodified AuNPs to capture target bacteria, and the detection was accomplished by target bacteria-induced aggregation of the aptasensor which is associated as red-to-purple color change upon high-salt conditions. By employing anti- E. coli O157:H7 aptamer and anti- S. typhimurium aptamer, we developed a convenient and rapid approach that could selectively detect bacteria without specialized instrumentation and pretreatment steps such as cell lysis. The aptasensor could detect as low as 105colony-forming units (CFU)/ml target bacteria within 20 min or less and its specificity was 100%. This novel method has a great potential application in rapid detection of bacteria in the near future.

Aptamer binding to celiac disease-triggering hydrophobic proteins: a sensitive gluten detection approach.

PubMed

Amaya-González, Sonia; de-Los-Santos-Álvarez, Noemí; Miranda-Ordieres, Arturo J; Lobo-Castañón, M Jesús

2014-03-04

Celiac disease represents a significant public health problem in large parts of the world. A major hurdle in the effective management of the disease by celiac sufferers is the sensitivity of the current available methods for assessing gluten contents in food. In response, we report a highly sensitive approach for gluten analysis using aptamers as specific receptors. Gliadins, a fraction of gluten proteins, are the main constituent responsible for triggering the disease. However, they are highly hydrophobic and large molecules, regarded as difficult targets for in vitro evolution of aptamers without nucleobase modification. We describe the successful selection of aptamers for these water insoluble prolamins that was achieved choosing the immunodominant apolar peptide from α2-gliadin as a target for selection. All aptamers evolved are able to bind the target in its native environment within the natural protein. The best nonprotein receptor is the basis for an electrochemical competitive enzyme-linked assay on magnetic particles, which allows the measurement of as low as 0.5 ppb of gliadin standard (0.5 ppm of gluten). Reference immunoassay for detecting the same target has a limit of detection of 3 ppm, 6 times less sensitive than this method. Importantly, it also displays high specificity, detecting the other three prolamins toxic for celiac patients and not showing cross-reactivity to nontoxic proteins such as maize, soya, and rice. These features make the proposed method a valuable tool for gluten detection in foods.

Driver genes in non-small cell lung cancer: Characteristics, detection methods, and targeted therapies

PubMed Central

He, Bing; Zhang, Hu-Qin

2017-01-01

Lung cancer is one of the most common causes of cancer-related death in the world. The large number of lung cancer cases is non-small cell lung cancer (NSCLC), which approximately accounting for 75% of lung cancer. Over the past years, our comprehensive knowledge about the molecular biology of NSCLC has been rapidly enriching, which has promoted the discovery of driver genes in NSCLC and directed FDA-approved targeted therapies. Of course, the targeted therapies based on driver genes provide a more exact option for advanced non-small cell lung cancer, improving the survival rate of patients. Now, we will review the landscape of driver genes in NSCLC including the characteristics, detection methods, the application of target therapy and challenges. PMID:28915704

Method and apparatus for staining immobilized nucleic acids

DOEpatents

Ramsey, J. Michael; Foote, Robert S.; Jacobson, Stephen C.

2000-01-01

A method for staining immobilized nucleic acids includes the steps of affixing DNA probes to a solid substrate, moving target DNA material into proximity with the DNA probes, whereby the target DNA hybridized with specific ones of the DNA probes, and moving a fluorescent dye into proximity with the hybridized target DNA, whereby the fluorescent dye binds to the hybridized DNA to enable subsequent detection of fluorescence.

Recombinant plasmid-based quantitative Real-Time PCR analysis of Salmonella enterica serotypes and its application to milk samples.

PubMed

Gokduman, Kurtulus; Avsaroglu, M Dilek; Cakiris, Aris; Ustek, Duran; Gurakan, G Candan

2016-03-01

The aim of the current study was to develop, a new, rapid, sensitive and quantitative Salmonella detection method using a Real-Time PCR technique based on an inexpensive, easy to produce, convenient and standardized recombinant plasmid positive control. To achieve this, two recombinant plasmids were constructed as reference molecules by cloning the two most commonly used Salmonella-specific target gene regions, invA and ttrRSBC. The more rapid detection enabled by the developed method (21 h) compared to the traditional culture method (90 h) allows the quantitative evaluation of Salmonella (quantification limits of 10(1)CFU/ml and 10(0)CFU/ml for the invA target and the ttrRSBC target, respectively), as illustrated using milk samples. Three advantages illustrated by the current study demonstrate the potential of the newly developed method to be used in routine analyses in the medical, veterinary, food and water/environmental sectors: I--The method provides fast analyses including the simultaneous detection and determination of correct pathogen counts; II--The method is applicable to challenging samples, such as milk; III--The method's positive controls (recombinant plasmids) are reproducible in large quantities without the need to construct new calibration curves. Copyright © 2016 Elsevier B.V. All rights reserved.

Enzyme-free detection of sequence-specific microRNAs based on nanoparticle-assisted signal amplification strategy.

PubMed

Li, Ru-Dong; Wang, Qian; Yin, Bin-Cheng; Ye, Bang-Ce

2016-03-15

Developing direct and convenient methods for microRNAs (miRNAs) analysis is of great significance in understanding biological functions of miRNAs, and early diagnosis of cancers. We have developed a rapid, enzyme-free method for miRNA detection based on nanoparticle-assisted signal amplification coupling fluorescent metal nanoclusters as signal output. The proposed method involves two processes: target miRNA-mediated nanoparticle capture, which consists of magnetic microparticle (MMP) probe and CuO nanoparticle (NP) probe, and nanoparticle-mediated amplification for signal generation, which consists of fluorescent DNA-Cu/Ag nanocluster (NC) and 3-mercaptopropionic acid (MPA). In the presence of target miRNA, MMP probe and NP probe sandwich-capture the target miRNA via their respective complementary sequence. The resultant sandwich complex (MMP probe-miRNA-CuO NP probe) is separated using a magnetic field and further dissolved by acidolysis to turn CuO NP into a great amount of copper (II) ions (Cu(2+)). Cu(2+) could disrupt the interactions between thiol moiety of MPA and the fluorescent Cu/Ag NCs by preferentially reacting with MPA to form a disulfide compound as intermediate. By this way, the fluorescence emission of the DNA-Cu/Ag NCs in the presence of MPA increases upon the increasing concentration of Cu(2+), which is directly proportional to the amount of target miRNA. The proposed method allows quantitative detection of a liver-specific miR-221-5p in the range of 5 pM to 1000 pM with a detection limit of ~0.73 pM, and shows a good ability to discriminate single-base difference. Moreover, the detection assay can be applied to detect miRNA in cancerous cell lysates in excellent agreement with that from a commercial miRNA detection kit. Copyright © 2015 Elsevier B.V. All rights reserved.

Ratiometric spectral imaging for fast tumor detection and chemotherapy monitoring in vivo

PubMed Central

Hwang, Jae Youn; Gross, Zeev; Gray, Harry B.; Medina-Kauwe, Lali K.; Farkas, Daniel L.

2011-01-01

We report a novel in vivo spectral imaging approach to cancer detection and chemotherapy assessment. We describe and characterize a ratiometric spectral imaging and analysis method and evaluate its performance for tumor detection and delineation by quantitatively monitoring the specific accumulation of targeted gallium corrole (HerGa) into HER2-positive (HER2 +) breast tumors. HerGa temporal accumulation in nude mice bearing HER2 + breast tumors was monitored comparatively by a. this new ratiometric imaging and analysis method; b. established (reflectance and fluorescence) spectral imaging; c. more commonly used fluorescence intensity imaging. We also tested the feasibility of HerGa imaging in vivo using the ratiometric spectral imaging method for tumor detection and delineation. Our results show that the new method not only provides better quantitative information than typical spectral imaging, but also better specificity than standard fluorescence intensity imaging, thus allowing enhanced in vivo outlining of tumors and dynamic, quantitative monitoring of targeted chemotherapy agent accumulation into them. PMID:21721808

Multiband tissue classification for ultrasonic transmission tomography using spectral profile detection

NASA Astrophysics Data System (ADS)

Jeong, Jeong-Won; Kim, Tae-Seong; Shin, Dae-Chul; Do, Synho; Marmarelis, Vasilis Z.

2004-04-01

Recently it was shown that soft tissue can be differentiated with spectral unmixing and detection methods that utilize multi-band information obtained from a High-Resolution Ultrasonic Transmission Tomography (HUTT) system. In this study, we focus on tissue differentiation using the spectral target detection method based on Constrained Energy Minimization (CEM). We have developed a new tissue differentiation method called "CEM filter bank". Statistical inference on the output of each CEM filter of a filter bank is used to make a decision based on the maximum statistical significance rather than the magnitude of each CEM filter output. We validate this method through 3-D inter/intra-phantom soft tissue classification where target profiles obtained from an arbitrary single slice are used for differentiation in multiple tomographic slices. Also spectral coherence between target and object profiles of an identical tissue at different slices and phantoms is evaluated by conventional cross-correlation analysis. The performance of the proposed classifier is assessed using Receiver Operating Characteristic (ROC) analysis. Finally we apply our method to classify tiny structures inside a beef kidney such as Styrofoam balls (~1mm), chicken tissue (~5mm), and vessel-duct structures.

In Vivo Biomarkers for Targeting Colorectal Neoplasms

PubMed Central

Hsiung, Pei-Lin; Wang, Thomas

2011-01-01

Summary Colorectal carcinoma continues to be a leading cause of cancer morbidity and mortality despite widespread adoption of screening methods. Targeted detection and therapy using recent advances in our knowledge of in vivo cancer biomarkers promise to significantly improve methods for early detection, risk stratification, and therapeutic intervention. The behavior of molecular targets in transformed tissues is being comprehensively assessed using new techniques of gene expression profiling and high throughput analyses. The identification of promising targets is stimulating the development of novel molecular probes, including significant progress in the field of activatable and peptide probes. These probes are being evaluated in small animal models of colorectal neoplasia and recently in the clinic. Furthermore, innovations in optical imaging instrumentation are resulting in the scaling down of size for endoscope compatibility. Advances in target identification, probe development, and novel instruments are progressing rapidly, and the integration of these technologies has a promising future in molecular medicine. PMID:19126961

Infrared small target detection in heavy sky scene clutter based on sparse representation

NASA Astrophysics Data System (ADS)

Liu, Depeng; Li, Zhengzhou; Liu, Bing; Chen, Wenhao; Liu, Tianmei; Cao, Lei

2017-09-01

A novel infrared small target detection method based on sky clutter and target sparse representation is proposed in this paper to cope with the representing uncertainty of clutter and target. The sky scene background clutter is described by fractal random field, and it is perceived and eliminated via the sparse representation on fractal background over-complete dictionary (FBOD). The infrared small target signal is simulated by generalized Gaussian intensity model, and it is expressed by the generalized Gaussian target over-complete dictionary (GGTOD), which could describe small target more efficiently than traditional structured dictionaries. Infrared image is decomposed on the union of FBOD and GGTOD, and the sparse representation energy that target signal and background clutter decomposed on GGTOD differ so distinctly that it is adopted to distinguish target from clutter. Some experiments are induced and the experimental results show that the proposed approach could improve the small target detection performance especially under heavy clutter for background clutter could be efficiently perceived and suppressed by FBOD and the changing target could also be represented accurately by GGTOD.

Sparsity based target detection for compressive spectral imagery

NASA Astrophysics Data System (ADS)

Boada, David Alberto; Arguello Fuentes, Henry

2016-09-01

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

Nanostructured Tip-Shaped Biosensors: Application of Six Sigma Approach for Enhanced Manufacturing.

PubMed

Kahng, Seong-Joong; Kim, Jong-Hoon; Chung, Jae-Hyun

2016-12-23

Nanostructured tip-shaped biosensors have drawn attention for biomolecule detection as they are promising for highly sensitive and specific detection of a target analyte. Using a nanostructured tip, the sensitivity is increased to identify individual molecules because of the high aspect ratio structure. Various detection methods, such as electrochemistry, fluorescence microcopy, and Raman spectroscopy, have been attempted to enhance the sensitivity and the specificity. Due to the confined path of electrons, electrochemical measurement using a nanotip enables the detection of single molecules. When an electric field is combined with capillary action and fluid flow, target molecules can be effectively concentrated onto a nanotip surface for detection. To enhance the concentration efficacy, a dendritic nanotip rather than a single tip could be used to detect target analytes, such as nanoparticles, cells, and DNA. However, reproducible fabrication with relation to specific detection remains a challenge due to the instability of a manufacturing method, resulting in inconsistent shape. In this paper, nanostructured biosensors are reviewed with our experimental results using dendritic nanotips for sequence specific detection of DNA. By the aid of the Six Sigma approach, the fabrication yield of dendritic nanotips increases from 20.0% to 86.6%. Using the nanotips, DNA is concentrated and detected in a sequence specific way with the detection limit equivalent to 1000 CFU/mL. The pros and cons of a nanotip biosensor are evaluated in conjunction with future prospects.

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map.

PubMed

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-09-11

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.

Enzyme Functionalized AuNPs and Glucometer-based Protein Detection

NASA Astrophysics Data System (ADS)

Dai, Tao; Fang, Jie; Yu, Wen; Xie, Guoming

2017-12-01

We here developed a novel method for protein detection by using protein aptamer-functionalized magnetic beads for protein recognition and invertase-functionalized AuNPs catalyze sucrose generate glucose that can be detected by a glucometer. First, the invertase and DNA probe P2 are immobilized onto the gold nanoparticles (I.P2@AuNPs). Next protein aptamer P1 are immobilized onto the streptavidin-coated Magnetic beads (P1@MB). P1 and P2 can complementary to form double-stranded DNA. When target protein presence, P1 combine with target and release I/P2@AuNPs. Then magnetic separation, take supernatant fluid and add sucrose after a period of reaction, detection of glucose concentration by glucometer, thus achieve the sensitive and selective detection of the target protein.

Development and application of a rapid and visual loop-mediated isothermal amplification for the detection of Sporisorium scitamineum in sugarcane

PubMed Central

Su, Yachun; Yang, Yuting; Peng, Qiong; Zhou, Dinggang; Chen, Yun; Wang, Zhuqing; Xu, Liping; Que, Youxiong

2016-01-01

Smut is a fungal disease with widespread prevalence in sugarcane planting areas. Early detection and proper identification of Sporisorium scitamineum are essential in smut management practices. In the present study, four specific primers targeting the core effector Pep1 gene of S. scitamineum were designed. Optimal concentrations of Mg2+, primer and Bst DNA polymerase, the three important components of the loop-mediated isothermal amplification (LAMP) reaction system, were screened using a single factor experiment method and the L16(45) orthogonal experimental design. Hence, a LAMP system suitable for detection of S. scitamineum was established. High specificity of the LAMP method was confirmed by the assay of S. scitamineum, Fusarium moniliforme, Pestalotia ginkgo, Helminthospcrium sacchari, Fusarium oxysporum and endophytes of Yacheng05-179 and ROC22. The sensitivity of the LAMP method was equal to that of the conventional PCR targeting Pep1 gene and was 100 times higher than that of the conventional PCR assay targeting bE gene in S. scitamineum. The results suggest that this novel LAMP system has strong specificity and high sensitivity. This method not only provides technological support for the epidemic monitoring of sugarcane smut, but also provides a good case for development of similar detection technology for other plant pathogens. PMID:27035751

Erwinia amylovora loop-mediated isothermal amplification (LAMP) assay for rapid pathogen detection and on-site diagnosis of fire blight.

PubMed

Bühlmann, Andreas; Pothier, Joël F; Rezzonico, Fabio; Smits, Theo H M; Andreou, Michael; Boonham, Neil; Duffy, Brion; Frey, Jürg E

2013-03-01

Several molecular methods have been developed for the detection of Erwinia amylovora, the causal agent of fire blight in pear and apple, but none are truly applicable for on-site use in the field. We developed a fast, reliable and field applicable detection method using a novel target on the E. amylovora chromosome that we identified by applying a comparative genomic pipeline. The target coding sequences (CDSs) are both uniquely specific for and all-inclusive of E. amylovora genotypes. This avoids potential false negatives that can occur with most commonly used methods based on amplification of plasmid gene targets, which can vary among strains. Loop-mediated isothermal AMPlification (LAMP) with OptiGene Genie II chemistry and instrumentation proved to be an exceptionally rapid (under 15 min) and robust method for detecting E. amylovora in orchards, as well as simple to use in the plant diagnostic laboratory. Comparative validation results using plant samples from inoculated greenhouse trials and from natural field infections (of regional and temporal diverse origin) showed that our LAMP had an equivalent or greater performance regarding sensitivity, specificity, speed and simplicity than real-time PCR (TaqMan), other LAMP assays, immunoassays and plating, demonstrating its utility for routine testing. Copyright © 2012 Elsevier B.V. All rights reserved.

Antibodies Biotinylated Using a Synthetic Z-domain from Protein A Provide Stringent In Situ Protein Detection

PubMed Central

Konrad, Anna; Ashok, Nikhil; Pontén, Fredrik; Hober, Sophia; Asplund, Anna

2013-01-01

Antibody-based protein profiling on a global scale using immunohistochemistry constitutes an emerging strategy for mapping of the human proteome, which is crucial for an increased understanding of biological processes in the cell. Immunohistochemistry is often performed indirectly using secondary antibodies for detection, with the benefit of signal amplification. Direct immunohistochemistry instead brings the advantage of multiplexing; however, it requires labeling of the primary antibody. Many antibody-labeling kits do not specifically target IgG and may therefore cause labeling of stabilizing proteins present in the antibody solution. A new conjugation method has been developed that utilizes a modified Z-domain of protein A (ZBPA) to specifically target the Fc part of antibodies. The aim of the present study was to compare the ZBPA conjugation method and a commercially available labeling kit, Lightning-Link, for in situ protein detection. Fourteen antibodies were biotinylated with each method and stained using immunohistochemistry. For all antibodies tested, ZBPA biotinylation resulted in distinct immunoreactivity without off-target staining, regardless of the presence of stabilizing proteins in the buffer, whereas the majority of the Lightning-Link biotinylated antibodies displayed a characteristic pattern of nonspecific staining. We conclude that biotinylated ZBPA domain provides a stringent method for antibody biotinylation, advantageous for in situ protein detection in tissues. PMID:23920108

Design of nuclease-based target recycling signal amplification in aptasensors.

PubMed

Yan, Mengmeng; Bai, Wenhui; Zhu, Chao; Huang, Yafei; Yan, Jiao; Chen, Ailiang

2016-03-15

Compared with conventional antibody-based immunoassay methods, aptasensors based on nucleic acid aptamer have made at least two significant breakthroughs. One is that aptamers are more easily used for developing various simple and rapid homogeneous detection methods by "sample in signal out" without multi-step washing. The other is that aptamers are more easily employed for developing highly sensitive detection methods by using various nucleic acid-based signal amplification approaches. As many substances playing regulatory roles in physiology or pathology exist at an extremely low concentration and many chemical contaminants occur in trace amounts in food or environment, aptasensors for signal amplification contribute greatly to detection of such targets. Among the signal amplification approaches in highly sensitive aptasensors, the nuclease-based target recycling signal amplification has recently become a research focus because it shows easy design, simple operation, and rapid reaction and can be easily developed for homogenous assay. In this review, we summarized recent advances in the development of various nuclease-based target recycling signal amplification with the aim to provide a general guide for the design of aptamer-based ultrasensitive biosensing assays. Copyright © 2015 Elsevier B.V. All rights reserved.

Long-term object tracking combined offline with online learning

NASA Astrophysics Data System (ADS)

Hu, Mengjie; Wei, Zhenzhong; Zhang, Guangjun

2016-04-01

We propose a simple yet effective method for long-term object tracking. Different from the traditional visual tracking method, which mainly depends on frame-to-frame correspondence, we combine high-level semantic information with low-level correspondences. Our framework is formulated in a confidence selection framework, which allows our system to recover from drift and partly deal with occlusion. To summarize, our algorithm can be roughly decomposed into an initialization stage and a tracking stage. In the initialization stage, an offline detector is trained to get the object appearance information at the category level, which is used for detecting the potential target and initializing the tracking stage. The tracking stage consists of three modules: the online tracking module, detection module, and decision module. A pretrained detector is used for maintaining drift of the online tracker, while the online tracker is used for filtering out false positive detections. A confidence selection mechanism is proposed to optimize the object location based on the online tracker and detection. If the target is lost, the pretrained detector is utilized to reinitialize the whole algorithm when the target is relocated. During experiments, we evaluate our method on several challenging video sequences, and it demonstrates huge improvement compared with detection and online tracking only.

A novel scattering switch-on detection technique for target-induced plasmon-coupling based sensing by single-particle optical anisotropy imaging.

PubMed

Peng, Lan; Cao, Xuan; Xiong, Bin; He, Yan; Yeung, Edward S

2016-06-18

We reported a novel scattering switch-on detection technique using flash-lamp polarization darkfield microscopy (FLPDM) for target-induced plasmon-coupling based sensing in homogeneous solution. With this method, we demonstrated sub-nM sensitivity for hydrogen sulfide (H2S) detection over a dynamic range of five orders of magnitude. This robust technique holds great promise for applications in toxic environmental pollutants and biological molecules.

Development and evaluation of an up-converting phosphor technology-based lateral flow assay for the rapid, simultaneous detection of Vibrio cholerae serogroups O1 and O139

PubMed Central

Li, Baisheng; Liu, Xiao; Zhao, Yong; Tan, Hailing; Sun, Chongyun; Wang, Xiaochen; Wang, Xinrui; Qiu, Haiyan; Wang, Duochun; Diao, Baowei; Jing, Huaiqi; Yang, Ruifu; Kan, Biao

2017-01-01

Vibrio cholerae serogroups O1 and O139 are etiological agents of cholera, a serious and acute diarrheal disease, and rapid detection of V. cholerae is a key method for preventing and controlling cholera epidemics. Here, a point of care testing (POCT) method called Vch-UPT-LF, which is an up-converting phosphor technology-based lateral flow (UPT-LF) assay with a dual-target detection mode, was developed to detect V. cholerae O1 and O139 simultaneously from one sample loading. Although applying an independent reaction pair made both detection results for the two Vch-UPT-LF detection channels more stable, the sensitivity slightly declined from 104 to 105 colony-forming units (CFU) mL−1 compared with that of the single-target assay, while the quantification ranges covering four orders of magnitude were maintained. The strip showed excellent specificity for seven Vibrio species that are highly related genetically, and nine food-borne species whose transmission routes are similar to those of V. cholerae. The legitimate arrangement of the two adjacent test lines lessened the mutual impact of the quantitation results between the two targets, and the quantification values did not differ by more than one order of magnitude when the samples contained high concentrations of both V. cholerae O1 and O139. Under pre-incubation conditions, 1×101 CFU mL−1 of V. cholerae O1 or O139 could be detected in fewer than 7 h, while the Vch-UPT-LF assay exhibited sensitivity as high as a real-time fluorescent polymerase chain reaction with fewer false-positive results. Therefore, successful development of Vch-UPT-LF as a dual-target assay for quantitative detection makes this assay a good candidate POCT method for the detection and surveillance of epidemic cholera. PMID:28662147

Molecular diagnostics for human leptospirosis.

PubMed

Waggoner, Jesse J; Pinsky, Benjamin A

2016-10-01

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

An Efficient Moving Target Detection Algorithm Based on Sparsity-Aware Spectrum Estimation

PubMed Central

Shen, Mingwei; Wang, Jie; Wu, Di; Zhu, Daiyin

2014-01-01

In this paper, an efficient direct data domain space-time adaptive processing (STAP) algorithm for moving targets detection is proposed, which is achieved based on the distinct spectrum features of clutter and target signals in the angle-Doppler domain. To reduce the computational complexity, the high-resolution angle-Doppler spectrum is obtained by finding the sparsest coefficients in the angle domain using the reduced-dimension data within each Doppler bin. Moreover, we will then present a knowledge-aided block-size detection algorithm that can discriminate between the moving targets and the clutter based on the extracted spectrum features. The feasibility and effectiveness of the proposed method are validated through both numerical simulations and raw data processing results. PMID:25222035

Flow method and apparatus for screening chemicals using micro x-ray fluorescence

DOEpatents

Warner, Benjamin P [Los Alamos, NM; Havrilla, George J [Los Alamos, NM; Miller, Thomasin C [Bartlesville, OK; Lewis, Cris [Los Alamos, NM; Mahan, Cynthia A [Los Alamos, NM; Wells, Cyndi A [Los Alamos, NM

2009-04-14

Method and apparatus for screening chemicals using micro x-ray fluorescence. A method for screening a mixture of potential pharmaceutical chemicals for binding to at least one target binder involves flow-separating a solution of chemicals and target binders into separated components, exposing them to an x-ray excitation beam, detecting x-ray fluorescence signals from the components, and determining from the signals whether or not a binding event between a chemical and target binder has occurred.

Flow method and apparatus for screening chemicals using micro x-ray fluorescence

DOEpatents

Warner, Benjamin P [Los Alamos, NM; Havrilla, George J [Los Alamos, NM; Miller, Thomasin C [Bartlesville, OK; Lewis, Cris [Los Alamos, NM; Mahan, Cynthia A [Los Alamos, NM; Wells, Cyndi A [Los Alamos, NM

2011-04-26

Method and apparatus for screening chemicals using micro x-ray fluorescence. A method for screening a mixture of potential pharmaceutical chemicals for binding to at least one target binder involves flow separating a solution of chemicals and target binders into separated components, exposing them to an x-ray excitation beam, detecting x-ray fluorescence signals from the components, and determining from the signals whether or not a binding event between a chemical and target binder has occurred.

Apparatus for point-of-care detection of nucleic acid in a sample

DOEpatents

Bearinger, Jane P.; Dugan, Lawrence C.

2016-04-19

Provided herein are methods and apparatus for detecting a target nucleic acid in a sample and related methods and apparatus for diagnosing a condition in an individual. The condition is associated with presence of nucleic acid produced by certain pathogens in the individual.

Receptors useful for gas phase chemical sensing

DOEpatents

Jaworski, Justyn W; Lee, Seung-Wuk; Majumdar, Arunava; Raorane, Digvijay A

2015-02-17

The invention provides for a receptor, capable of binding to a target molecule, linked to a hygroscopic polymer or hydrogel; and the use of this receptor in a device for detecting the target molecule in a gaseous and/or liquid phase. The invention also provides for a method for detecting the presence of a target molecule in the gas phase using the device. In particular, the receptor can be a peptide capable of binding a 2,4,6-trinitrotoluene (TNT) or 2,4,-dinitrotoluene (DNT).

Key parameters design of an aerial target detection system on a space-based platform

NASA Astrophysics Data System (ADS)

Zhu, Hanlu; Li, Yejin; Hu, Tingliang; Rao, Peng

2018-02-01

To ensure flight safety of an aerial aircraft and avoid recurrence of aircraft collisions, a method of multi-information fusion is proposed to design the key parameter to realize aircraft target detection on a space-based platform. The key parameters of a detection wave band and spatial resolution using the target-background absolute contrast, target-background relative contrast, and signal-to-clutter ratio were determined. This study also presented the signal-to-interference ratio for analyzing system performance. Key parameters are obtained through the simulation of a specific aircraft. And the simulation results show that the boundary ground sampling distance is 30 and 35 m in the mid- wavelength infrared (MWIR) and long-wavelength infrared (LWIR) bands for most aircraft detection, and the most reasonable detection wavebands is 3.4 to 4.2 μm and 4.35 to 4.5 μm in the MWIR bands, and 9.2 to 9.8 μm in the LWIR bands. We also found that the direction of detection has a great impact on the detection efficiency, especially in MWIR bands.

Attomolar detection of proteins via cascade strand-displacement amplification and polystyrene nanoparticle enhancement in fluorescence polarization aptasensors.

PubMed

Huang, Yong; Liu, Xiaoqian; Huang, Huakui; Qin, Jian; Zhang, Liangliang; Zhao, Shulin; Chen, Zhen-Feng; Liang, Hong

2015-08-18

Extremely sensitive and accurate measurements of protein markers for early detection and monitoring of diseases pose a formidable challenge. Herein, we develop a new type of amplified fluorescence polarization (FP) aptasensor based on allostery-triggered cascade strand-displacement amplification (CSDA) and polystyrene nanoparticle (PS NP) enhancement for ultrasensitive detection of proteins. The assay system consists of a fluorescent dye-labeled aptamer hairpin probe and a PS NP-modified DNA duplex (assistant DNA/trigger DNA duplex) probe with a single-stranded part and DNA polymerase. Two probes coexist stably in the absence of target, and the dye exhibits relatively low FP background. Upon recognition and binding with a target protein, the stem of the aptamer hairpin probe is opened, after which the opened hairpin probe hybridizes with the single-stranded part in the PS NP-modified DNA duplex probe and triggers the CSDA reaction through the polymerase-catalyzed recycling of both target protein and trigger DNA. Throughout this CSDA process, numerous massive dyes are assembled onto PS NPs, which results in a substantial FP increase that provides a readout signal for the amplified sensing process. Our newly proposed amplified FP aptasensor enables the quantitative measurement of proteins with the detection limit in attomolar range, which is about 6 orders of magnitude lower than that of traditional homogeneous aptasensors. Moreover, this sensing method also exhibits high specificity for target proteins and can be performed in homogeneous solutions. In addition, the suitability of this method for the quantification of target protein in biological samples has also been shown. Considering these distinct advantages, the proposed sensing method can be expected to provide an ultrasensitive platform for the analysis of various types of target molecules.

Multitarget detection algorithm for automotive FMCW radar

NASA Astrophysics Data System (ADS)

Hyun, Eugin; Oh, Woo-Jin; Lee, Jong-Hun

2012-06-01

Today, 77 GHz FMCW (Frequency Modulation Continuous Wave) radar has strong advantages of range and velocity detection for automotive applications. However, FMCW radar brings out ghost targets and missed targets in multi-target situations. In this paper, in order to resolve these limitations, we propose an effective pairing algorithm, which consists of two steps. In the proposed method, a waveform with different slopes in two periods is used. In the 1st pairing processing, all combinations of range and velocity are obtained in each of two wave periods. In the 2nd pairing step, using the results of the 1st pairing processing, fine range and velocity are detected. In that case, we propose the range-velocity windowing technique in order to compensate for the non-ideal beat-frequency characteristic that arises due to the non-linearity of the RF module. Based on experimental results, the performance of the proposed algorithm is improved compared with that of the typical method.

Synthetic oligonucleotide antigens modified with locked nucleic acids detect disease specific antibodies

NASA Astrophysics Data System (ADS)

Samuelsen, Simone V.; Solov'Yov, Ilia A.; Balboni, Imelda M.; Mellins, Elizabeth; Nielsen, Christoffer Tandrup; Heegaard, Niels H. H.; Astakhova, Kira

2016-10-01

New techniques to detect and quantify antibodies to nucleic acids would provide a significant advance over current methods, which often lack specificity. We investigate the potential of novel antigens containing locked nucleic acids (LNAs) as targets for antibodies. Particularly, employing molecular dynamics we predict optimal nucleotide composition for targeting DNA-binding antibodies. As a proof of concept, we address a problem of detecting anti-DNA antibodies that are characteristic of systemic lupus erythematosus, a chronic autoimmune disease with multiple manifestations. We test the best oligonucleotide binders in surface plasmon resonance studies to analyze binding and kinetic aspects of interactions between antigens and target DNA. These DNA and LNA/DNA sequences showed improved binding in enzyme-linked immunosorbent assay using human samples of pediatric lupus patients. Our results suggest that the novel method is a promising tool to create antigens for research and point-of-care monitoring of anti-DNA antibodies.

Terrain feature recognition for synthetic aperture radar (SAR) imagery employing spatial attributes of targets

NASA Astrophysics Data System (ADS)

Iisaka, Joji; Sakurai-Amano, Takako

1994-08-01

This paper describes an integrated approach to terrain feature detection and several methods to estimate spatial information from SAR (synthetic aperture radar) imagery. Spatial information of image features as well as spatial association are key elements in terrain feature detection. After applying a small feature preserving despeckling operation, spatial information such as edginess, texture (smoothness), region-likeliness and line-likeness of objects, target sizes, and target shapes were estimated. Then a trapezoid shape fuzzy membership function was assigned to each spatial feature attribute. Fuzzy classification logic was employed to detect terrain features. Terrain features such as urban areas, mountain ridges, lakes and other water bodies as well as vegetated areas were successfully identified from a sub-image of a JERS-1 SAR image. In the course of shape analysis, a quantitative method was developed to classify spatial patterns by expanding a spatial pattern through the use of a series of pattern primitives.

A sensitive mass spectrometric method for hypothesis-driven detection of peptide post-translational modifications: multiple reaction monitoring-initiated detection and sequencing (MIDAS).

PubMed

Unwin, Richard D; Griffiths, John R; Whetton, Anthony D

2009-01-01

The application of a targeted mass spectrometric workflow to the sensitive identification of post-translational modifications is described. This protocol employs multiple reaction monitoring (MRM) to search for all putative peptides specifically modified in a target protein. Positive MRMs trigger an MS/MS experiment to confirm the nature and site of the modification. This approach, termed MIDAS (MRM-initiated detection and sequencing), is more sensitive than approaches using neutral loss scanning or precursor ion scanning methodologies, due to a more efficient use of duty cycle along with a decreased background signal associated with MRM. We describe the use of MIDAS for the identification of phosphorylation, with a typical experiment taking just a couple of hours from obtaining a peptide sample. With minor modifications, the MIDAS method can be applied to other protein modifications or unmodified peptides can be used as a MIDAS target.

Identification of Buried Objects in GPR Using Amplitude Modulated Signals Extracted from Multiresolution Monogenic Signal Analysis

PubMed Central

Qiao, Lihong; Qin, Yao; Ren, Xiaozhen; Wang, Qifu

2015-01-01

It is necessary to detect the target reflections in ground penetrating radar (GPR) images, so that surface metal targets can be identified successfully. In order to accurately locate buried metal objects, a novel method called the Multiresolution Monogenic Signal Analysis (MMSA) system is applied in ground penetrating radar (GPR) images. This process includes four steps. First the image is decomposed by the MMSA to extract the amplitude component of the B-scan image. The amplitude component enhances the target reflection and suppresses the direct wave and reflective wave to a large extent. Then we use the region of interest extraction method to locate the genuine target reflections from spurious reflections by calculating the normalized variance of the amplitude component. To find the apexes of the targets, a Hough transform is used in the restricted area. Finally, we estimate the horizontal and vertical position of the target. In terms of buried object detection, the proposed system exhibits promising performance, as shown in the experimental results. PMID:26690146

Power spectrum weighted edge analysis for straight edge detection in images

NASA Astrophysics Data System (ADS)

Karvir, Hrishikesh V.; Skipper, Julie A.

2007-04-01

Most man-made objects provide characteristic straight line edges and, therefore, edge extraction is a commonly used target detection tool. However, noisy images often yield broken edges that lead to missed detections, and extraneous edges that may contribute to false target detections. We present a sliding-block approach for target detection using weighted power spectral analysis. In general, straight line edges appearing at a given frequency are represented as a peak in the Fourier domain at a radius corresponding to that frequency, and a direction corresponding to the orientation of the edges in the spatial domain. Knowing the edge width and spacing between the edges, a band-pass filter is designed to extract the Fourier peaks corresponding to the target edges and suppress image noise. These peaks are then detected by amplitude thresholding. The frequency band width and the subsequent spatial filter mask size are variable parameters to facilitate detection of target objects of different sizes under known imaging geometries. Many military objects, such as trucks, tanks and missile launchers, produce definite signatures with parallel lines and the algorithm proves to be ideal for detecting such objects. Moreover, shadow-casting objects generally provide sharp edges and are readily detected. The block operation procedure offers advantages of significant reduction in noise influence, improved edge detection, faster processing speed and versatility to detect diverse objects of different sizes in the image. With Scud missile launcher replicas as target objects, the method has been successfully tested on terrain board test images under different backgrounds, illumination and imaging geometries with cameras of differing spatial resolution and bit-depth.

Target-specific NMR detection of protein-ligand interactions with antibody-relayed 15N-group selective STD.

PubMed

Hetényi, Anasztázia; Hegedűs, Zsófia; Fajka-Boja, Roberta; Monostori, Éva; Kövér, Katalin E; Martinek, Tamás A

2016-12-01

Fragment-based drug design has been successfully applied to challenging targets where the detection of the weak protein-ligand interactions is a key element. 1 H saturation transfer difference (STD) NMR spectroscopy is a powerful technique for this work but it requires pure homogeneous proteins as targets. Monoclonal antibody (mAb)-relayed 15 N-GS STD spectroscopy has been developed to resolve the problem of protein mixtures and impure proteins. A 15 N-labelled target-specific mAb is selectively irradiated and the saturation is relayed through the target to the ligand. Tests on the anti-Gal-1 mAb/Gal-1/lactose system showed that the approach is experimentally feasible in a reasonable time frame. This method allows detection and identification of binding molecules directly from a protein mixture in a multicomponent system.

Deep kernel learning method for SAR image target recognition

NASA Astrophysics Data System (ADS)

Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

2017-10-01

With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Robust vehicle detection under various environments to realize road traffic flow surveillance using an infrared thermal camera.

PubMed

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2015-01-01

To realize road traffic flow surveillance under various environments which contain poor visibility conditions, we have already proposed two vehicle detection methods using thermal images taken with an infrared thermal camera. The first method uses pattern recognition for the windshields and their surroundings to detect vehicles. However, the first method decreases the vehicle detection accuracy in winter season. To maintain high vehicle detection accuracy in all seasons, we developed the second method. The second method uses tires' thermal energy reflection areas on a road as the detection targets. The second method did not achieve high detection accuracy for vehicles on left-hand and right-hand lanes except for two center-lanes. Therefore, we have developed a new method based on the second method to increase the vehicle detection accuracy. This paper proposes the new method and shows that the detection accuracy for vehicles on all lanes is 92.1%. Therefore, by combining the first method and the new method, high vehicle detection accuracies are maintained under various environments, and road traffic flow surveillance can be realized.

Robust Vehicle Detection under Various Environments to Realize Road Traffic Flow Surveillance Using an Infrared Thermal Camera

PubMed Central

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2015-01-01

To realize road traffic flow surveillance under various environments which contain poor visibility conditions, we have already proposed two vehicle detection methods using thermal images taken with an infrared thermal camera. The first method uses pattern recognition for the windshields and their surroundings to detect vehicles. However, the first method decreases the vehicle detection accuracy in winter season. To maintain high vehicle detection accuracy in all seasons, we developed the second method. The second method uses tires' thermal energy reflection areas on a road as the detection targets. The second method did not achieve high detection accuracy for vehicles on left-hand and right-hand lanes except for two center-lanes. Therefore, we have developed a new method based on the second method to increase the vehicle detection accuracy. This paper proposes the new method and shows that the detection accuracy for vehicles on all lanes is 92.1%. Therefore, by combining the first method and the new method, high vehicle detection accuracies are maintained under various environments, and road traffic flow surveillance can be realized. PMID:25763384

Shadow detection of moving objects based on multisource information in Internet of things

NASA Astrophysics Data System (ADS)

Ma, Zhen; Zhang, De-gan; Chen, Jie; Hou, Yue-xian

2017-05-01

Moving object detection is an important part in intelligent video surveillance under the banner of Internet of things. The detection of moving target's shadow is also an important step in moving object detection. On the accuracy of shadow detection will affect the detection results of the object directly. Based on the variety of shadow detection method, we find that only using one feature can't make the result of detection accurately. Then we present a new method for shadow detection which contains colour information, the invariance of optical and texture feature. Through the comprehensive analysis of the detecting results of three kinds of information, the shadow was effectively determined. It gets ideal effect in the experiment when combining advantages of various methods.

A Pedestrian Detection Scheme Using a Coherent Phase Difference Method Based on 2D Range-Doppler FMCW Radar

PubMed Central

Hyun, Eugin; Jin, Young-Seok; Lee, Jong-Hun

2016-01-01

For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW) radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the pedestrian may be masked by the side-lobe of the clutter even though they are notably separated in the Doppler dimension. To prevent this problem, one popular solution is the use of a windowing scheme with a weighting function. However, this method leads to a spread spectrum, so the pedestrian with weak signal power and slow Doppler may also be masked by the main-lobe of clutter. With a fast-ramp based FMCW radar, if the target is moving, the complex spectrum of the range- Fast Fourier Transform (FFT) is changed with a constant phase difference over ramps. In contrast, the clutter exhibits constant phase irrespective of the ramps. Based on this fact, in this paper we propose a pedestrian detection for highly cluttered environments using a coherent phase difference method. By detecting the coherent phase difference from the complex spectrum of the range-FFT, we first extract the range profile of the moving pedestrians. Then, through the Doppler FFT, we obtain the 2D range-Doppler map for only the pedestrian. To test the proposed detection scheme, we have developed a real-time data logging system with a 24 GHz FMCW transceiver. In laboratory tests, we verified that the signal processing results from the proposed method were much better than those expected from the conventional 2D FFT-based detection method. PMID:26805835

A Pedestrian Detection Scheme Using a Coherent Phase Difference Method Based on 2D Range-Doppler FMCW Radar.

PubMed

Hyun, Eugin; Jin, Young-Seok; Lee, Jong-Hun

2016-01-20

For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW) radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the pedestrian may be masked by the side-lobe of the clutter even though they are notably separated in the Doppler dimension. To prevent this problem, one popular solution is the use of a windowing scheme with a weighting function. However, this method leads to a spread spectrum, so the pedestrian with weak signal power and slow Doppler may also be masked by the main-lobe of clutter. With a fast-ramp based FMCW radar, if the target is moving, the complex spectrum of the range- Fast Fourier Transform (FFT) is changed with a constant phase difference over ramps. In contrast, the clutter exhibits constant phase irrespective of the ramps. Based on this fact, in this paper we propose a pedestrian detection for highly cluttered environments using a coherent phase difference method. By detecting the coherent phase difference from the complex spectrum of the range-FFT, we first extract the range profile of the moving pedestrians. Then, through the Doppler FFT, we obtain the 2D range-Doppler map for only the pedestrian. To test the proposed detection scheme, we have developed a real-time data logging system with a 24 GHz FMCW transceiver. In laboratory tests, we verified that the signal processing results from the proposed method were much better than those expected from the conventional 2D FFT-based detection method.

Single Laboratory Comparison of Quantitative Real-Time PCR Assays for the Detection of Human Fecal Pollution

EPA Science Inventory

There are numerous quantitative real-time PCR (qPCR) methods available to detect and enumerate human fecal pollution in ambient waters. Each assay employs distinct primers and/or probes and many target different genes and microorganisms leading to potential variations in method ...

Validation approach for a fast and simple targeted screening method for 75 antibiotics in meat and aquaculture products using LC-MS/MS.

PubMed

Dubreil, Estelle; Gautier, Sophie; Fourmond, Marie-Pierre; Bessiral, Mélaine; Gaugain, Murielle; Verdon, Eric; Pessel, Dominique

2017-04-01

An approach is described to validate a fast and simple targeted screening method for antibiotic analysis in meat and aquaculture products by LC-MS/MS. The strategy of validation was applied for a panel of 75 antibiotics belonging to different families, i.e., penicillins, cephalosporins, sulfonamides, macrolides, quinolones and phenicols. The samples were extracted once with acetonitrile, concentrated by evaporation and injected into the LC-MS/MS system. The approach chosen for the validation was based on the Community Reference Laboratory (CRL) guidelines for the validation of screening qualitative methods. The aim of the validation was to prove sufficient sensitivity of the method to detect all the targeted antibiotics at the level of interest, generally the maximum residue limit (MRL). A robustness study was also performed to test the influence of different factors. The validation showed that the method is valid to detect and identify 73 antibiotics of the 75 antibiotics studied in meat and aquaculture products at the validation levels.

Subpixel target detection and enhancement in hyperspectral images

NASA Astrophysics Data System (ADS)

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

2011-06-01

Hyperspectral data due to its higher information content afforded by higher spectral resolution is increasingly being used for various remote sensing applications including information extraction at subpixel level. There is however usually a lack of matching fine spatial resolution data particularly for target detection applications. Thus, there always exists a tradeoff between the spectral and spatial resolutions due to considerations of type of application, its cost and other associated analytical and computational complexities. Typically whenever an object, either manmade, natural or any ground cover class (called target, endmembers, components or class) gets spectrally resolved but not spatially, mixed pixels in the image result. Thus, numerous manmade and/or natural disparate substances may occur inside such mixed pixels giving rise to mixed pixel classification or subpixel target detection problems. Various spectral unmixing models such as Linear Mixture Modeling (LMM) are in vogue to recover components of a mixed pixel. Spectral unmixing outputs both the endmember spectrum and their corresponding abundance fractions inside the pixel. It, however, does not provide spatial distribution of these abundance fractions within a pixel. This limits the applicability of hyperspectral data for subpixel target detection. In this paper, a new inverse Euclidean distance based super-resolution mapping method has been presented that achieves subpixel target detection in hyperspectral images by adjusting spatial distribution of abundance fraction within a pixel. Results obtained at different resolutions indicate that super-resolution mapping may effectively aid subpixel target detection.

A self-assembled deoxyribonucleic acid concatemer for sensitive detection of single nucleotide polymorphism.

PubMed

Wu, Wei; Chen, Junhua; Fang, Zhiyuan; Ge, Chenchen; Xiang, Zhicheng; Ouyang, Chuanyan; Lie, Puchang; Xiao, Zhuo; Yu, Luxin; Wang, Lin; Zeng, Lingwen

2013-12-04

Polymerase-free and label-free strategies for DNA detection have shown excellent sensitivity and specificity in various biological samples. Herein, we propose a method for single nucleotide polymorphism (SNP) detection by using self-assembled DNA concatemers. Capture probes, bound to magnetic beads, can joint mediator probes by T4 DNA ligase in the presence of target DNA that is complementary to the capture probe and mediator probe. The mediator probes trigger self-assembly of two auxiliary probes on magnetic beads to form DNA concatemers. Separated by a magnetic rack, the double-stranded concatemers on beads can recruit a great amount of SYBR Green I and eventually result in amplified fluorescent signals. In comparison with reported methods for SNP detection, the concatemer-based approach has significant advantages of low background, simplicity, and ultrasensitivity, making it as a convenient platform for clinical applications. As a proof of concept, BRAF(T1799A) oncogene mutation, a SNP involved in diverse human cancers, was used as a model target. The developed approach using a fluorescent intercalator can detect as low as 0.1 fM target BRAF(T1799A) DNA, which is better than those previously published methods for SNP detection. This method is robust and can be used directly to measure the BRAF(T1799A) DNA in complex human serum with excellent recovery (94-103%). It is expected that this assay principle can be directed toward other SNP genes by simply changing the mediator probe and auxiliary probes. Copyright © 2013 Elsevier B.V. All rights reserved.

Synchronous detection of miRNAs, their targets and downstream proteins in transferred FFPE sections: applications in clinical and basic research.

PubMed

Zhao, Jin-yao; Liu, Chun-qing; Zhao, He-nan; Ding, Yan-Fang; Bi, Tie; Wang, Bo; Lin, Xing-chi; Guo, Gordon; Cui, Shi-ying

2012-10-01

After discovering new miRNAs, it is often difficult to determine their targets and effects on downstream protein expression. In situ hybridization (ISH) and immunohistochemistry (IHC) are two commonly used methods for clinical diagnosis and basic research. We used an optimized technique that simultaneously detects miRNAs, their binding targets and corresponding proteins on transferred serial formalin fixed paraffin embedded (FFPE) sections from patients. Combined with bioinformatics, this method was used to validate the reciprocal expression of specific miRNAs and targets that were detected by ISH, as well as the expression of downstream proteins that were detected by IHC. A complete analysis was performed using a limited number of transferred serial FFPE sections that had been stored for 1-4 years at room temperature. Some sections had even been previously stained with H&E. We identified a miRNA that regulates epithelial ovarian cancer, along with its candidate target and related downstream protein. These findings were directly validated using sub-cellular components obtained from the same patient sample. In addition, the expression of Nephrin (a podocyte marker) and Stmn1 (a recently identified marker related to glomerular development) were confirmed in transferred FFPE sections of mouse kidney. This procedure may be adapted for clinical diagnosis and basic research, providing a qualitative and efficient method to dissect the detailed spatial expression patterns of miRNA pathways in FFPE tissue, especially in cases where only a small biopsy sample can be obtained. Copyright © 2012 Elsevier Inc. All rights reserved.

Method for analyzing nucleic acids by means of a substrate having a microchannel structure containing immobilized nucleic acid probes

DOEpatents

Ramsey, J. Michael; Foote, Robert S.

2003-12-09

A method and apparatus for analyzing nucleic acids includes immobilizing nucleic probes at specific sites within a microchannel structure and moving target nucleic acids into proximity to the probes in order to allow hybridization and fluorescence detection of specific target sequences.

Method for analyzing nucleic acids by means of a substrate having a microchannel structure containing immobilized nucleic acid probes

DOEpatents

Ramsey, J. Michael; Foote, Robert S.

2002-01-01

A method and apparatus for analyzing nucleic acids includes immobilizing nucleic probes at specific sites within a microchannel structure and moving target nucleic acids into proximity to the probes in order to allow hybridization and fluorescence detection of specific target sequences.

Multi-laboratory evaluations of the performance of Catellicoccus marimammalium PCR assays developed to target gull fecal sources

EPA Science Inventory

Here we report results from a multi-laboratory (n=11) evaluation of four different PCR methods targeting the 16S rRNA gene of Catellicoccus marimammalium used to detect fecal contamination from birds in coastal environments. The methods included conventional end-point PCR, a SYBR...

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Compositions and methods for cancer treatment using targeted carbon nanotubes

DOEpatents

Harrison, Jr., Roger G.; Resasco, Daniel E.; Neves, Luis Filipe Ferreira

2016-11-29

Compositions for detecting and/or destroying cancer tumors and/or cancer cells via photodynamic therapy are disclosed, as well as methods of use thereof. The compositions comprise a linking protein or peptide attached to or otherwise physically associated with a carbon nanotube to form a targeted protein-carbon nanotube complex.

Coherent detection of position errors in inter-satellite laser communications

NASA Astrophysics Data System (ADS)

Xu, Nan; Liu, Liren; Liu, De'an; Sun, Jianfeng; Luan, Zhu

2007-09-01

Due to the improved receiver sensitivity and wavelength selectivity, coherent detection became an attractive alternative to direct detection in inter-satellite laser communications. A novel method to coherent detection of position errors information is proposed. Coherent communication system generally consists of receive telescope, local oscillator, optical hybrid, photoelectric detector and optical phase lock loop (OPLL). Based on the system composing, this method adds CCD and computer as position error detector. CCD captures interference pattern while detection of transmission data from the transmitter laser. After processed and analyzed by computer, target position information is obtained from characteristic parameter of the interference pattern. The position errors as the control signal of PAT subsystem drive the receiver telescope to keep tracking to the target. Theoretical deviation and analysis is presented. The application extends to coherent laser rang finder, in which object distance and position information can be obtained simultaneously.

Rapid and Inexpensive Screening of Genomic Copy Number Variations Using a Novel Quantitative Fluorescent PCR Method

PubMed Central

Han, Joan C.; Elsea, Sarah H.; Pena, Heloísa B.; Pena, Sérgio Danilo Junho

2013-01-01

Detection of human microdeletion and microduplication syndromes poses significant burden on public healthcare systems in developing countries. With genome-wide diagnostic assays frequently inaccessible, targeted low-cost PCR-based approaches are preferred. However, their reproducibility depends on equally efficient amplification using a number of target and control primers. To address this, the recently described technique called Microdeletion/Microduplication Quantitative Fluorescent PCR (MQF-PCR) was shown to reliably detect four human syndromes by quantifying DNA amplification in an internally controlled PCR reaction. Here, we confirm its utility in the detection of eight human microdeletion syndromes, including the more common WAGR, Smith-Magenis, and Potocki-Lupski syndromes with 100% sensitivity and 100% specificity. We present selection, design, and performance evaluation of detection primers using variety of approaches. We conclude that MQF-PCR is an easily adaptable method for detection of human pathological chromosomal aberrations. PMID:24288428

A rapid and convenient method for detecting a broad spectrum of malignant cells from malignant pleuroperitoneal effusion of patients using a multifunctional NIR heptamethine dye.

PubMed

Tian, Ying; Sun, Jing; Yan, Huaijiang; Teng, Zhaogang; Zeng, Leyong; Liu, Ying; Li, Yanjun; Wang, Jiandong; Wang, Shouju; Lu, Guangming

2015-02-07

Detection of malignant cells from malignant effusion is crucial to establish or adjust therapies of patients with cancer. The conventional qualitative detection in malignant pleuroperitoneal effusion is cytological analysis, which is time-consuming and complicated. Therefore, a faster and more convenient detection strategy is urgently needed. In this study, we report a rapid method to detect malignant cells from malignant pleuroperitoneal effusion (hydrothorax and ascites) of patients using IR-808, a tumor-targeted near-infrared (NIR) fluorescent heptamethine dye (tNRI dye), which exhibited superior labeling efficacy without specific conjugation to biomarkers. The targeted imaging performance toward malignant cells using IR-808 was confirmed by comparing with normal cells, and the fluorescence stability assay of IR-808 in malignant effusion was performed from 1 h to 48 h. In order to save time and dose, the incubation time and concentration were optimized to 10 min and 5 μM, which were used to detect malignant cells from 28 clinical samples of malignant pleuroperitoneal effusion. The results revealed that IR-808 could be internalized selectively by malignant cells of samples, and these malignant cells could be easily distinguished from normal cells under a fluorescence microscope. The positive rates between cytological analysis and the IR-808 staining method were 86% (24/28) and 79% (22/28), respectively. An excellent concordance level (Kappa = 0.752, P < 0.001) was observed between the two methods. Our results indicated that IR-808, a new NIR fluorescent heptamethine dye with unique optical imaging and tumor targeting properties, could provide a fast and simple way to detect a broad spectrum of malignant cells from malignant pleuroperitoneal effusion in patients.

Development of loop-mediated isothermal amplification (LAMP) assay for the rapid detection of Penicillium nordicum in dry-cured meat products.

PubMed

Ferrara, M; Perrone, G; Gallo, A; Epifani, F; Visconti, A; Susca, A

2015-06-02

The need of powerful diagnostic tools for rapid, simple, and cost-effective detection of food-borne fungi has become very important in the area of food safety. Currently, several isothermal nucleic acid amplification methods have been developed as an alternative to PCR-based analyses. Loop-mediated isothermal amplification (LAMP) is one of these innovative methods; it requires neither gel electrophoresis to separate and visualize the products nor expensive laboratory equipment and it has been applied already for detection of pathogenic organisms. In the current study, we developed a LAMP assay for the specific detection of Penicillium nordicum, the major causative agent of ochratoxin A contamination in protein-rich food, especially dry-cured meat products. The assay was based on targeting otapksPN gene, a key gene in the biosynthesis of ochratoxin A (OTA) in P. nordicum. Amplification of DNA during the reaction was detected directly in-tube by color transition of hydroxynaphthol blue from violet to sky blue, visible to the naked eye, avoiding further post amplification analyses. Only DNAs isolated from several P. nordicum strains led to positive results and no amplification was observed from non-target OTA and non OTA-producing strains. The assay was able to detect down to 100 fg of purified targeted genomic DNA or 10(2) conidia/reaction within 60 min. The LAMP assay for detection and identification of P. nordicum was combined with a rapid DNA extraction method set up on serially diluted conidia, providing an alternative rapid, specific and sensitive DNA-based method suitable for application directly "on-site", notably in key steps of dry-cured meat production. Copyright © 2015 Elsevier B.V. All rights reserved.

Detection of Waterborne Viruses Using High Affinity Molecularly Imprinted Polymers.

PubMed

Altintas, Zeynep; Gittens, Micah; Guerreiro, Antonio; Thompson, Katy-Anne; Walker, Jimmy; Piletsky, Sergey; Tothill, Ibtisam E

2015-07-07

Molecularly imprinted polymers (MIPs) are artificial receptor ligands which can recognize and specifically bind to a target molecule. They are more resistant to chemical and biological damage and inactivation than antibodies. Therefore, target specific-MIP nanoparticles are aimed to develop and implemented to biosensors for the detection of biological toxic agents such as viruses, bacteria, and fungi toxins that cause many diseases and death due to the environmental contamination. For the first time, a molecularly imprinted polymer (MIP) targeting the bacteriophage MS2 as the template was investigated using a novel solid-phase synthesis method to obtain the artificial affinity ligand for the detection and removal of waterborne viruses through optical-based sensors. A high affinity between the artificial ligand and the target was found, and a regenerative MIP-based virus detection assay was successfully developed using a new surface plasmon resonance (SPR)-biosensor which provides an alternative technology for the specific detection and removal of waterborne viruses that lead to high disease and death rates all over the world.

Novel strategy combining SYBR Green I with carbon nanotubes for highly sensitive detection of Salmonella typhimurium DNA.

PubMed

Mao, Pingdao; Ning, Yi; Li, Wenkai; Peng, Zhihui; Chen, Yongzhe; Deng, Le

2014-01-10

A simple, selective, sensitive and label-free fluorescent method for detecting trpS-harboring Salmonella typhimurium was developed in this study. This assay used the non-covalent interaction of single-stranded DNA (ssDNA) probes with SWNTs, since SWNTs can quench fluorescence. Fluorescence recovery (78% with 1.8 nM target DNA) was detected in the presence of target DNA as ssDNA probes detached from SWNTs hybridized with target DNA, and the resulting double-stranded DNA (dsDNA) intercalated with SYBR Green I (SG) dyes. The increasing fluorescence intensity reached 4.54-fold. In contrast, mismatched oligonucleotides (1- or 3-nt difference to the target DNA) did not contribute to significant fluorescent recovery, which demonstrated the specificity of the assay. The increasing fluorescence intensity increased 3.15-fold when purified PCR products containing complementary sequences of trpS gene were detected. These results confirmed the ability to use this assay for detecting real samples. Copyright © 2013 Elsevier Inc. All rights reserved.

Development and validation of the JAX Cancer Treatment Profile™ for detection of clinically actionable mutations in solid tumors

PubMed Central

Ananda, Guruprasad; Mockus, Susan; Lundquist, Micaela; Spotlow, Vanessa; Simons, Al; Mitchell, Talia; Stafford, Grace; Philip, Vivek; Stearns, Timothy; Srivastava, Anuj; Barter, Mary; Rowe, Lucy; Malcolm, Joan; Bult, Carol; Karuturi, Radha Krishna Murthy; Rasmussen, Karen; Hinerfeld, Douglas

2015-01-01

Background The continued development of targeted therapeutics for cancer treatment has required the concomitant development of more expansive methods for the molecular profiling of the patient’s tumor. We describe the validation of the JAX Cancer Treatment Profile™ (JAX-CTP™), a next generation sequencing (NGS)-based molecular diagnostic assay that detects actionable mutations in solid tumors to inform the selection of targeted therapeutics for cancer treatment. Methods NGS libraries are generated from DNA extracted from formalin fixed paraffin embedded tumors. Using hybrid capture, the genes of interest are enriched and sequenced on the Illumina HiSeq 2500 or MiSeq sequencers followed by variant detection and functional and clinical annotation for the generation of a clinical report. Results The JAX-CTP™ detects actionable variants, in the form of single nucleotide variations and small insertions and deletions (≤50bp) in 190 genes in specimens with a neoplastic cell content of ≥10%. The JAX-CTP™ is also validated for the detection of clinically actionable gene amplifications. Conclusions There is a lack of consensus in the molecular diagnostics field on the best method for the validation of NGS-based assays in oncology, thus the importance of communicating methods, as contained in this report. The growing number of targeted therapeutics and the complexity of the tumor genome necessitates continued development and refinement of advanced assays for tumor profiling to enable precision cancer treatment. PMID:25562415

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map

PubMed Central

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-01-01

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate. PMID:26378543

Improving the signal analysis for in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Niu, Zhenyu; Yang, Ping; Wei, Dan; Tang, Shuo; Wei, Xunbin

2015-03-01

At early stage of cancer, a small number of circulating tumor cells (CTCs) appear in the blood circulation. Thus, early detection of malignant circulating tumor cells has great significance for timely treatment to reduce the cancer death rate. We have developed an in vivo photoacoustic flow cytometry (PAFC) to monitor the metastatic process of CTCs and record the signals from target cells. Information of target cells which is helpful to the early therapy would be obtained through analyzing and processing the signals. The raw signal detected from target cells often contains some noise caused by electronic devices, such as background noise and thermal noise. We choose the Wavelet denoising method to effectively distinguish the target signal from background noise. Processing in time domain and frequency domain would be combined to analyze the signal after denoising. This algorithm contains time domain filter and frequency transformation. The frequency spectrum image of the signal contains distinctive features that can be used to analyze the property of target cells or particles. The PAFC technique can detect signals from circulating tumor cells or other particles. The processing methods have a great potential for analyzing signals accurately and rapidly.

Improved Tumor Targeting and Longer Retention Time of NIR Fluorescent Probes Using Bioorthogonal Chemistry.

PubMed

Zhang, Xianghan; Wang, Bo; Zhao, Na; Tian, Zuhong; Dai, Yunpeng; Nie, Yongzhan; Tian, Jie; Wang, Zhongliang; Chen, Xiaoyuan

2017-01-01

The traditional labeling method for targeted NIR fluorescence probes requires directly covalent-bonded conjugation of targeting domains and fluorophores in vitro . Although this strategy works well, it is not sufficient for detecting or treating cancers in vivo , due to steric hindrance effects that relatively large fluorophore molecules exert on the configurations and physiological functions of specific targeting domains. The copper-free, "click-chemistry"-assisted assembly of small molecules in living systems may enhance tumor accumulation of fluorescence probes by improving the binding affinities of the targeting factors. Here, we employed a vascular homing peptide, GEBP11, as a targeting factor for gastric tumors, and we demonstrate its effectiveness for in vivo imaging via click-chemistry-mediated conjugation with fluorescence molecules in tumor xenograft mouse models. This strategy showed higher binding affinities than those of the traditional conjugation method, and our results showed that the tumor accumulation of click-chemistry-mediated probes are 11-fold higher than that of directly labeled probes. The tracking life was prolonged by 12-fold, and uptake of the probes into the kidney was reduced by 6.5-fold. For lesion tumors of different sizes, click-chemistry-mediated probes can achieve sufficient signal-to-background ratios (3.5-5) for in vivo detection, and with diagnostic sensitivity approximately 3.5 times that of traditional labeling probes. The click-chemistry-assisted detection strategy utilizes the advantages of "small molecule" probes while not perturbing their physiological functions; this enables tumor detection with high sensitivity and specific selectivity.

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

PubMed

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

2017-01-01

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

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

PubMed

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

2016-03-01

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

Analytical method for the evaluation of the outdoor air contamination by emerging pollutants using tree leaves as bioindicators.

PubMed

Barroso, Pedro José; Martín, Julia; Santos, Juan Luis; Aparicio, Irene; Alonso, Esteban

2018-01-01

In this work, an analytical method, based on sonication-assisted extraction, clean-up by dispersive solid-phase extraction and determination by liquid chromatography-tandem mass spectrometry, has been developed and validated for the simultaneous determination of 15 emerging pollutants in leaves from four ornamental tree species. Target compounds include perfluorinated organic compounds, plasticizers, surfactants, brominated flame retardant, and preservatives. The method was optimized using Box-Behnken statistical experimental design with response surface methodology and validated in terms of recovery, accuracy, precision, and method detection and quantification limits. Quantification of target compounds was carried out using matrix-matched calibration curves. The highest recoveries were achieved for the perfluorinated organic compounds (mean values up to 87%) and preservatives (up to 88%). The lowest recoveries were achieved for plasticizers (51%) and brominated flame retardant (63%). Method detection and quantification limits were in the ranges 0.01-0.09 ng/g dry matter (dm) and 0.02-0.30 ng/g dm, respectively, for most of the target compounds. The method was successfully applied to the determination of the target compounds on leaves from four tree species used as urban ornamental trees (Citrus aurantium, Celtis australis, Platanus hispanica, and Jacaranda mimosifolia). Graphical abstract Analytical method for the biomonitorization of emerging pollutants in outdoor air.

Comparative Effectiveness of Targeted Prostate Biopsy Using Magnetic Resonance Imaging Ultrasound Fusion Software and Visual Targeting: a Prospective Study.

PubMed

Lee, Daniel J; Recabal, Pedro; Sjoberg, Daniel D; Thong, Alan; Lee, Justin K; Eastham, James A; Scardino, Peter T; Vargas, Hebert Alberto; Coleman, Jonathan; Ehdaie, Behfar

2016-09-01

We compared the diagnostic outcomes of magnetic resonance-ultrasound fusion and visually targeted biopsy for targeting regions of interest on prostate multiparametric magnetic resonance imaging. Patients presenting for prostate biopsy with regions of interest on multiparametric magnetic resonance imaging underwent magnetic resonance imaging targeted biopsy. For each region of interest 2 visually targeted cores were obtained, followed by 2 cores using a magnetic resonance-ultrasound fusion device. Our primary end point was the difference in the detection of high grade (Gleason 7 or greater) and any grade cancer between visually targeted and magnetic resonance-ultrasound fusion, investigated using McNemar's method. Secondary end points were the difference in detection rate by biopsy location using a logistic regression model and the difference in median cancer length using the Wilcoxon signed rank test. We identified 396 regions of interest in 286 men. The difference in the detection of high grade cancer between magnetic resonance-ultrasound fusion biopsy and visually targeted biopsy was -1.4% (95% CI -6.4 to 3.6, p=0.6) and for any grade cancer the difference was 3.5% (95% CI -1.9 to 8.9, p=0.2). Median cancer length detected by magnetic resonance-ultrasound fusion and visually targeted biopsy was 5.5 vs 5.8 mm, respectively (p=0.8). Magnetic resonance-ultrasound fusion biopsy detected 15% more cancers in the transition zone (p=0.046) and visually targeted biopsy detected 11% more high grade cancer at the prostate base (p=0.005). Only 52% of all high grade cancers were detected by both techniques. We found no evidence of a significant difference in the detection of high grade or any grade cancer between visually targeted and magnetic resonance-ultrasound fusion biopsy. However, the performance of each technique varied in specific biopsy locations and the outcomes of both techniques were complementary. Combining visually targeted biopsy and magnetic resonance-ultrasound fusion biopsy may optimize the detection of prostate cancer. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Exploration of resistive targets within shallow marine environments using the circular electrical dipole and the differential electrical dipole methods: a time-domain modelling study

NASA Astrophysics Data System (ADS)

Haroon, Amir; Mogilatov, Vladimir; Goldman, Mark; Bergers, Rainer; Tezkan, Bülent

2016-05-01

Two novel transient controlled source electromagnetic methods called circular electrical dipole (CED) and differential electrical dipole (DED) are theoretically analysed for applications in shallow marine environments. 1-D and 3-D time-domain modelling studies are used to investigate the detectability and applicability of the methods when investigating resistive layers/targets representing hydrocarbon-saturated formations. The results are compared to the conventional time-domain horizontal electrical dipole (HED) and vertical electrical dipole (VED) sources. The applied theoretical modelling studies demonstrate that CED and DED have higher signal detectability towards resistive targets compared to TD-CSEM, but demonstrate significantly poorer signal amplitudes. Future CED/DED applications will have to solve this issue prior to measuring. Furthermore, the two novel methods have very similar detectability characteristics towards 3-D resistive targets embedded in marine sediments as VED while being less susceptible towards non-verticality. Due to the complex transmitter design of CED/DED the systems are prone to geometrical errors. Modelling studies show that even small transmitter inaccuracies have strong effects on the signal characteristics of CED making an actual marine application difficult at the present time. In contrast, the DED signal is less affected by geometrical errors in comparison to CED and may therefore be more adequate for marine applications.

Research on measurement method of optical camouflage effect of moving object

NASA Astrophysics Data System (ADS)

Wang, Juntang; Xu, Weidong; Qu, Yang; Cui, Guangzhen

2016-10-01

Camouflage effectiveness measurement as an important part of the camouflage technology, which testing and measuring the camouflage effect of the target and the performance of the camouflage equipment according to the tactical and technical requirements. The camouflage effectiveness measurement of current optical band is mainly aimed at the static target which could not objectively reflect the dynamic camouflage effect of the moving target. This paper synthetical used technology of dynamic object detection and camouflage effect detection, the digital camouflage of the moving object as the research object, the adaptive background update algorithm of Surendra was improved, a method of optical camouflage effect detection using Lab-color space in the detection of moving-object was presented. The binary image of moving object is extracted by this measurement technology, in the sequence diagram, the characteristic parameters such as the degree of dispersion, eccentricity, complexity and moment invariants are constructed to construct the feature vector space. The Euclidean distance of moving target which through digital camouflage was calculated, the results show that the average Euclidean distance of 375 frames was 189.45, which indicated that the degree of dispersion, eccentricity, complexity and moment invariants of the digital camouflage graphics has a great difference with the moving target which not spray digital camouflage. The measurement results showed that the camouflage effect was good. Meanwhile with the performance evaluation module, the correlation coefficient of the dynamic target image range 0.1275 from 0.0035, and presented some ups and down. Under the dynamic condition, the adaptability of target and background was reflected. In view of the existing infrared camouflage technology, the next step, we want to carry out the camouflage effect measurement technology of the moving target based on infrared band.

Detection of ferromagnetic target based on mobile magnetic gradient tensor system

NASA Astrophysics Data System (ADS)

Gang, Y. I. N.; Yingtang, Zhang; Zhining, Li; Hongbo, Fan; Guoquan, Ren

2016-03-01

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

Indoor detection of passive targets recast as an inverse scattering problem

NASA Astrophysics Data System (ADS)

Gottardi, G.; Moriyama, T.

2017-10-01

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

Nanostructured Tip-Shaped Biosensors: Application of Six Sigma Approach for Enhanced Manufacturing

PubMed Central

Kahng, Seong-Joong; Kim, Jong-Hoon; Chung, Jae-Hyun

2016-01-01

Nanostructured tip-shaped biosensors have drawn attention for biomolecule detection as they are promising for highly sensitive and specific detection of a target analyte. Using a nanostructured tip, the sensitivity is increased to identify individual molecules because of the high aspect ratio structure. Various detection methods, such as electrochemistry, fluorescence microcopy, and Raman spectroscopy, have been attempted to enhance the sensitivity and the specificity. Due to the confined path of electrons, electrochemical measurement using a nanotip enables the detection of single molecules. When an electric field is combined with capillary action and fluid flow, target molecules can be effectively concentrated onto a nanotip surface for detection. To enhance the concentration efficacy, a dendritic nanotip rather than a single tip could be used to detect target analytes, such as nanoparticles, cells, and DNA. However, reproducible fabrication with relation to specific detection remains a challenge due to the instability of a manufacturing method, resulting in inconsistent shape. In this paper, nanostructured biosensors are reviewed with our experimental results using dendritic nanotips for sequence specific detection of DNA. By the aid of the Six Sigma approach, the fabrication yield of dendritic nanotips increases from 20.0% to 86.6%. Using the nanotips, DNA is concentrated and detected in a sequence specific way with the detection limit equivalent to 1000 CFU/mL. The pros and cons of a nanotip biosensor are evaluated in conjunction with future prospects. PMID:28025540

Airplane detection in remote sensing images using convolutional neural networks

NASA Astrophysics Data System (ADS)

Ouyang, Chao; Chen, Zhong; Zhang, Feng; Zhang, Yifei

2018-03-01

Airplane detection in remote sensing images remains a challenging problem and has also been taking a great interest to researchers. In this paper we propose an effective method to detect airplanes in remote sensing images using convolutional neural networks. Deep learning methods show greater advantages than the traditional methods with the rise of deep neural networks in target detection, and we give an explanation why this happens. To improve the performance on detection of airplane, we combine a region proposal algorithm with convolutional neural networks. And in the training phase, we divide the background into multi classes rather than one class, which can reduce false alarms. Our experimental results show that the proposed method is effective and robust in detecting airplane.

Quality control for normal liquid-based cytology: Rescreening, high-risk HPV targeted reviewing and/or high-risk HPV detection?

PubMed Central

Depuydt, Christophe E; Arbyn, Marc; Benoy, Ina H; Vandepitte, Johan; Vereecken, Annie J; Bogers, Johannes J

2009-01-01

The objective of this prospective study was to compare the number of CIN2+cases detected in negative cytology by different quality control (QC) methods. Full rescreening, high-risk (HR) human papillomavirus (HPV)-targeted reviewing and HR HPV detection were compared. Randomly selected negative cytology detected by BD FocalPoint™ (NFR), by guided screening of the prescreened which needed further review (GS) and by manual screening (MS) was used. A 3-year follow-up period was available. Full rescreening of cytology only detected 23.5% of CIN2+ cases, whereas the cytological rescreening of oncogenic positive slides (high-risk HPV-targeted reviewing) detected 7 of 17 CIN2+ cases (41.2%). Quantitative real-time PCR for 15 oncogenic HPV types detected all CIN2+ cases. Relative sensitivity to detect histological CIN2+ was 0.24 for full rescreening, 0.41 for HR-targeted reviewing and 1.00 for HR HPV detection. In more than half of the reviewed negative cytological preparations associated with histological CIN2+cases no morphologically abnormal cells were detected despite a positive HPV test. The visual cut-off for the detection of abnormal cytology was established at 6.5 HR HPV copies/cell. High-risk HPV detection has a higher yield for detection of CIN2+ cases as compared to manual screening followed by 5% full review, or compared to targeted reviewing of smears positive for oncogenic HPV types, and show diagnostic properties that support its use as a QC procedure in cytologic laboratories. PMID:18544049

A Sensitive TLRH Targeted Imaging Technique for Ultrasonic Molecular Imaging

PubMed Central

Hu, Xiaowen; Zheng, Hairong; Kruse, Dustin E.; Sutcliffe, Patrick; Stephens, Douglas N.; Ferrara, Katherine W.

2010-01-01

The primary goals of ultrasound molecular imaging are the detection and imaging of ultrasound contrast agents (microbubbles), which are bound to specific vascular surface receptors. Imaging methods that can sensitively and selectively detect and distinguish bound microbubbles from freely circulating microbubbles (free microbubbles) and surrounding tissue are critically important for the practical application of ultrasound contrast molecular imaging. Microbubbles excited by low frequency acoustic pulses emit wide-band echoes with a bandwidth extending beyond 20 MHz; we refer to this technique as TLRH (transmission at a low frequency and reception at a high frequency). Using this wideband, transient echo, we have developed and implemented a targeted imaging technique incorporating a multi-frequency co-linear array and the Siemens Antares® imaging system. The multi-frequency co-linear array integrates a center 5.4 MHz array, used to receive echoes and produce radiation force, and two outer 1.5 MHz arrays used to transmit low frequency incident pulses. The targeted imaging technique makes use of an acoustic radiation force sub-sequence to enhance accumulation and a TLRH imaging sub-sequence to detect bound microbubbles. The radiofrequency (RF) data obtained from the TLRH imaging sub-sequence are processsed to separate echo signatures between tissue, free microbubbles, and bound microbubbles. By imaging biotin-coated microbubbles targeted to avidin-coated cellulose tubes, we demonstrate that the proposed method has a high contrast-to-tissue ratio (up to 34 dB) and a high sensitivity to bound microbubbles (with the ratio of echoes from bound microbubbles versus free microbubbles extending up to 23 dB). The effects of the imaging pulse acoustic pressure, the radiation force sub-sequence and the use of various slow-time filters on the targeted imaging quality are studied. The TLRH targeted imaging method is demonstrated in this study to provide sensitive and selective detection of bound microbubbles for ultrasound molecularly-targeted imaging. PMID:20178897

Multispecies Adulteration Detection of Camellia Oil by Chemical Markers.

PubMed

Dou, Xinjing; Mao, Jin; Zhang, Liangxiao; Xie, Huali; Chen, Lin; Yu, Li; Ma, Fei; Wang, Xiupin; Zhang, Qi; Li, Peiwu

2018-01-25

Adulteration of edible oils has attracted attention from more researchers and consumers in recent years. Complex multispecies adulteration is a commonly used strategy to mask the traditional adulteration detection methods. Most of the researchers were only concerned about single targeted adulterants, however, it was difficult to identify complex multispecies adulteration or untargeted adulterants. To detect adulteration of edible oil, identification of characteristic markers of adulterants was proposed to be an effective method, which could provide a solution for multispecies adulteration detection. In this study, a simple method of multispecies adulteration detection for camellia oil (adulterated with soybean oil, peanut oil, rapeseed oil) was developed by quantifying chemical markers including four isoflavones, trans-resveratrol and sinapic acid, which used liquid chromatography tandem mass spectrometry (LC-MS/MS) combined with solid phase extraction (SPE). In commercial camellia oil, only two of them were detected of daidzin with the average content of 0.06 ng/g while other markers were absent. The developed method was highly sensitive as the limits of detection (LODs) ranged from 0.02 ng/mL to 0.16 ng/mL and the mean recoveries ranged from 79.7% to 113.5%, indicating that this method was reliable to detect potential characteristic markers in edible oils. Six target compounds for pure camellia oils, soybean oils, peanut oils and rapeseed oils had been analyzed to get the results. The validation results indicated that this simple and rapid method was successfully employed to determine multispecies adulteration of camellia oil adulterated with soybean, peanut and rapeseed oils.

An estimation of distribution method for infrared target detection based on Copulas

NASA Astrophysics Data System (ADS)

Wang, Shuo; Zhang, Yiqun

2015-10-01

Track-before-detect (TBD) based target detection involves a hypothesis test of merit functions which measure each track as a possible target track. Its accuracy depends on the precision of the distribution of merit functions, which determines the threshold for a test. Generally, merit functions are regarded Gaussian, and on this basis the distribution is estimated, which is true for most methods such as the multiple hypothesis tracking (MHT). However, merit functions for some other methods such as the dynamic programming algorithm (DPA) are non-Guassian and cross-correlated. Since existing methods cannot reasonably measure the correlation, the exact distribution can hardly be estimated. If merit functions are assumed Guassian and independent, the error between an actual distribution and its approximation may occasionally over 30 percent, and is divergent by propagation. Hence, in this paper, we propose a novel estimation of distribution method based on Copulas, by which the distribution can be estimated precisely, where the error is less than 1 percent without propagation. Moreover, the estimation merely depends on the form of merit functions and the structure of a tracking algorithm, and is invariant to measurements. Thus, the distribution can be estimated in advance, greatly reducing the demand for real-time calculation of distribution functions.

A highly sensitive SPRi biosensing strategy for simultaneous detection of multiplex miRNAs based on strand displacement amplification and AuNP signal enhancement.

PubMed

Wei, Xiaotong; Duan, Xiaolei; Zhou, Xiaoyan; Wu, Jiangling; Xu, Hongbing; Min, Xun; Ding, Shijia

2018-06-07

Herein, a dual channel surface plasmon resonance imaging (SPRi) biosensor has been developed for the simultaneous and highly sensitive detection of multiplex miRNAs based on strand displacement amplification (SDA) and DNA-functionalized AuNP signal enhancement. In the presence of target miRNAs (miR-21 or miR-192), the miRNAs could specifically hybridize with the corresponding hairpin probes (H) and initiate the SDA, resulting in massive triggers. Subsequently, the two parts of the released triggers could hybridize with capture probes (CP) and DNA-functionalized AuNPs, assembling DNA sandwiches with great mass on the chip surface. A significantly amplified SPR signal readout was achieved. This established biosensing method was capable of simultaneously detecting multiplex miRNAs with a limit of detection down to 0.15 pM for miR-21 and 0.22 pM for miR-192. This method exhibited good specificity and acceptable reproducibility. Moreover, the developed method was applied to the determination of target miRNAs in a complex matrix. Thus, this developed SPRi biosensing method may present a potential alternative tool for miRNA detection in biomedical research and clinical diagnosis.

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

PubMed

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

2017-07-01

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

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

PubMed Central

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

2017-01-01

Abstract Targeted next‐generation‐sequencing (NGS) panels have largely replaced Sanger sequencing in clinical diagnostics. They allow for the detection of copy‐number variations (CNVs) in addition to single‐nucleotide variants and small insertions/deletions. However, existing computational CNV detection methods have shortcomings regarding accuracy, quality control (QC), incidental findings, and user‐friendliness. We developed panelcn.MOPS, a novel pipeline for detecting CNVs in targeted NGS panel data. Using data from 180 samples, we compared panelcn.MOPS with five state‐of‐the‐art methods. With panelcn.MOPS leading the field, most methods achieved comparably high accuracy. panelcn.MOPS reliably detected CNVs ranging in size from part of a region of interest (ROI), to whole genes, which may comprise all ROIs investigated in a given sample. The latter is enabled by analyzing reads from all ROIs of the panel, but presenting results exclusively for user‐selected genes, thus avoiding incidental findings. Additionally, panelcn.MOPS offers QC criteria not only for samples, but also for individual ROIs within a sample, which increases the confidence in called CNVs. panelcn.MOPS is freely available both as R package and standalone software with graphical user interface that is easy to use for clinical geneticists without any programming experience. panelcn.MOPS combines high sensitivity and specificity with user‐friendliness rendering it highly suitable for routine clinical diagnostics. PMID:28449315

Ultra-fast DNA-based multiplex convection PCR method for meat species identification with possible on-site applications.

PubMed

Song, Kyung-Young; Hwang, Hyun Jin; Kim, Jeong Hee

2017-08-15

The aim of this study was to develop an ultra-fast molecular detection method for meat identification using convection Palm polymerase chain reaction (PCR). The mitochondrial cytochrome b (Cyt b) gene was used as a target gene. Amplicon size was designed to be different for beef, lamb, and pork. When these primer sets were used, each species-specific set specifically detected the target meat species in singleplex and multiplex modes in a 24min PCR run. The detection limit was 1pg of DNA for each meat species. The convection PCR method could detect as low as 1% of meat adulteration. The stability of the assay was confirmed using thermal processed meats. We also showed that direct PCR can be successfully performed with mixed meats and food samples. These results suggest that the developed assay may be useful in the authentication of meats and meat products in laboratory and rapid on-site applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

Single Laboratory Comparison of Quantitative Real-Time PCR Assays for the Detection of Human Fecal Pollution - Poster

EPA Science Inventory

There are numerous quantitative real-time PCR (qPCR) methods available to detect and enumerate human fecal pollution in ambient waters. Each assay employs distinct primers and/or probes and many target different genes and microorganisms leading to potential variations in method p...

Peptidic β-sheet binding with Congo Red allows both reduction of error variance and signal amplification for immunoassays.

PubMed

Wang, Yunyun; Liu, Ye; Deng, Xinli; Cong, Yulong; Jiang, Xingyu

2016-12-15

Although conventional enzyme-linked immunosorbent assays (ELISA) and related assays have been widely applied for the diagnosis of diseases, many of them suffer from large error variance for monitoring the concentration of targets over time, and insufficient limit of detection (LOD) for assaying dilute targets. We herein report a readout mode of ELISA based on the binding between peptidic β-sheet structure and Congo Red. The formation of peptidic β-sheet structure is triggered by alkaline phosphatase (ALP). For the detection of P-Selectin which is a crucial indicator for evaluating thrombus diseases in clinic, the 'β-sheet and Congo Red' mode significantly decreases both the error variance and the LOD (from 9.7ng/ml to 1.1 ng/ml) of detection, compared with commercial ELISA (an existing gold-standard method for detecting P-Selectin in clinic). Considering the wide range of ALP-based antibodies for immunoassays, such novel method could be applicable to the analysis of many types of targets. Copyright © 2016 Elsevier B.V. All rights reserved.

Affinity fluorescence-labeled peptides for the early detection of cancer in Barrett's esophagus

NASA Astrophysics Data System (ADS)

Li, Meng; Lu, Shaoying; Piraka, Cyrus; Appelman, Henry; Kwon, Rich; Soetikno, Roy; Kaltenbach, Tonya; Wang, Thomas D.

2009-02-01

Fluorescence-labeled peptides that affinity bind to neoplastic mucsosa are promising for use as a specific contrast agent in the detection of pre-malignant tissue in the esophagus. This method is can be used to identify expression of biological markers associated with dysplasia on endoscopic imaging as a guide for biopsy and represents a novel method for the early detection and prevention of cancer. We demonstrate the use of phage display to select affinity peptides and identify the sequence "ASYNYDA" that binds with high target-to-background ratio to dysplastic esophageal mucosa compared to that of intestinal metaplasia. Validation of preferential binding is demonstrated for neoplasia in the setting of Barrett's esophagus. An optimal tradeoff between sensitivity and specificity of 82% and 85% was found at the relative threshold of 0.60 with a target-to-background ratio of 1.81 and an area under the ROC curve of 0.87. Peptides are a novel class of ligand for targeted detection of pre-malignant mucosa for purposes of screening and surveillance.

Feature-based RNN target recognition

NASA Astrophysics Data System (ADS)

Bakircioglu, Hakan; Gelenbe, Erol

1998-09-01

Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

Method of controlling cyclic variation in engine combustion

DOEpatents

Davis, L.I. Jr.; Daw, C.S.; Feldkamp, L.A.; Hoard, J.W.; Yuan, F.; Connolly, F.T.

1999-07-13

Cyclic variation in combustion of a lean burning engine is reduced by detecting an engine combustion event output such as torsional acceleration in a cylinder (i) at a combustion event (k), using the detected acceleration to predict a target acceleration for the cylinder at the next combustion event (k+1), modifying the target output by a correction term that is inversely proportional to the average phase of the combustion event output of cylinder (i) and calculating a control output such as fuel pulse width or spark timing necessary to achieve the target acceleration for cylinder (i) at combustion event (k+1) based on anti-correlation with the detected acceleration and spill-over effects from fueling. 27 figs.

Method of controlling cyclic variation in engine combustion

DOEpatents

Davis, Jr., Leighton Ira; Daw, Charles Stuart; Feldkamp, Lee Albert; Hoard, John William; Yuan, Fumin; Connolly, Francis Thomas

1999-01-01

Cyclic variation in combustion of a lean burning engine is reduced by detecting an engine combustion event output such as torsional acceleration in a cylinder (i) at a combustion event (k), using the detected acceleration to predict a target acceleration for the cylinder at the next combustion event (k+1), modifying the target output by a correction term that is inversely proportional to the average phase of the combustion event output of cylinder (i) and calculating a control output such as fuel pulse width or spark timing necessary to achieve the target acceleration for cylinder (i) at combustion event (k+1) based on anti-correlation with the detected acceleration and spill-over effects from fueling.

Study on a novel laser target detection system based on software radio technique

NASA Astrophysics Data System (ADS)

Song, Song; Deng, Jia-hao; Wang, Xue-tian; Gao, Zhen; Sun, Ji; Sun, Zhi-hui

2008-12-01

This paper presents that software radio technique is applied to laser target detection system with the pseudo-random code modulation. Based on the theory of software radio, the basic framework of the system, hardware platform, and the implementation of the software system are detailed. Also, the block diagram of the system, DSP circuit, block diagram of the pseudo-random code generator, and soft flow diagram of signal processing are designed. Experimental results have shown that the application of software radio technique provides a novel method to realize the modularization, miniaturization and intelligence of the laser target detection system, and the upgrade and improvement of the system will become simpler, more convenient, and cheaper.

Measuring target detection performance in paradigms with high event rates.

PubMed

Bendixen, Alexandra; Andersen, Søren K

2013-05-01

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

A high content, high throughput cellular thermal stability assay for measuring drug-target engagement in living cells.

PubMed

Massey, Andrew J

2018-01-01

Determining and understanding drug target engagement is critical for drug discovery. This can be challenging within living cells as selective readouts are often unavailable. Here we describe a novel method for measuring target engagement in living cells based on the principle of altered protein thermal stabilization / destabilization in response to ligand binding. This assay (HCIF-CETSA) utilizes high content, high throughput single cell immunofluorescent detection to determine target protein levels following heating of adherent cells in a 96 well plate format. We have used target engagement of Chk1 by potent small molecule inhibitors to validate the assay. Target engagement measured by this method was subsequently compared to target engagement measured by two alternative methods (autophosphorylation and CETSA). The HCIF-CETSA method appeared robust and a good correlation in target engagement measured by this method and CETSA for the selective Chk1 inhibitor V158411 was observed. However, these EC50 values were 23- and 12-fold greater than the autophosphorylation IC50. The described method is therefore a valuable advance in the CETSA method allowing the high throughput determination of target engagement in adherent cells.

A Functional Assay for GPR55: Envision Protocol.

PubMed

Anavi-Goffer, Sharon; Ross, Ruth A

2016-01-01

AlphaScreen(®) SureFire(®) assay is a novel technology that combines luminescent oxygen channeling technology, nano-beads, and monocloncal antibodies to detect the level of a selected protein in a volume lower than 5 μl. This method is more sensitive compared with the traditional enzyme-linked immunosorbent assays (ELISA), and can detect an increasing number of new targets. Here, we described a method for AlphaScreen(®) SureFire(®) assay that targets ERK1/2 phosphorylation, a primary downstream signaling pathway that conveys activation of GPR55 by L-α-lysophosphatidylinositol (LPI) and certain cannabinoids.

Quantification of DNA using the luminescent oxygen channeling assay.

PubMed

Patel, R; Pollner, R; de Keczer, S; Pease, J; Pirio, M; DeChene, N; Dafforn, A; Rose, S

2000-09-01

Simplified and cost-effective methods for the detection and quantification of nucleic acid targets are still a challenge in molecular diagnostics. Luminescent oxygen channeling assay (LOCI(TM)) latex particles can be conjugated to synthetic oligodeoxynucleotides and hybridized, via linking probes, to different DNA targets. These oligomer-conjugated LOCI particles survive thermocycling in a PCR reaction and allow quantified detection of DNA targets in both real-time and endpoint formats. The endpoint DNA quantification format utilized two sensitizer bead types that are sensitive to separate illumination wavelengths. These two bead types were uniquely annealed to target or control amplicons, and separate illuminations generated time-resolved chemiluminescence, which distinguished the two amplicon types. In the endpoint method, ratios of the two signals allowed determination of the target DNA concentration over a three-log range. The real-time format allowed quantification of the DNA target over a six-log range with a linear relationship between threshold cycle and log of the number of DNA targets. This is the first report of the use of an oligomer-labeled latex particle assay capable of producing DNA quantification and sequence-specific chemiluminescent signals in a homogeneous format. It is also the first report of the generation of two signals from a LOCI assay. The methods described here have been shown to be easily adaptable to new DNA targets because of the generic nature of the oligomer-labeled LOCI particles.

Time delay estimation using new spectral and adaptive filtering methods with applications to underwater target detection

NASA Astrophysics Data System (ADS)

Hasan, Mohammed A.

1997-11-01

In this dissertation, we present several novel approaches for detection and identification of targets of arbitrary shapes from the acoustic backscattered data and using the incident waveform. This problem is formulated as time- delay estimation and sinusoidal frequency estimation problems which both have applications in many other important areas in signal processing. Solving time-delay estimation problem allows the identification of the specular components in the backscattered signal from elastic and non-elastic targets. Thus, accurate estimation of these time delays would help in determining the existence of certain clues for detecting targets. Several new methods for solving these two problems in the time, frequency and wavelet domains are developed. In the time domain, a new block fast transversal filter (BFTF) is proposed for a fast implementation of the least squares (LS) method. This BFTF algorithm is derived by using data-related constrained block-LS cost function to guarantee global optimality. The new soft-constrained algorithm provides an efficient way of transferring weight information between blocks of data and thus it is computationally very efficient compared with other LS- based schemes. Additionally, the tracking ability of the algorithm can be controlled by varying the block length and/or a soft constrained parameter. The effectiveness of this algorithm is tested on several underwater acoustic backscattered data for elastic targets and non-elastic (cement chunk) objects. In the frequency domain, the time-delay estimation problem is converted to a sinusoidal frequency estimation problem by using the discrete Fourier transform. Then, the lagged sample covariance matrices of the resulting signal are computed and studied in terms of their eigen- structure. These matrices are shown to be robust and effective in extracting bases for the signal and noise subspaces. New MUSIC and matrix pencil-based methods are derived these subspaces. The effectiveness of the method is demonstrated on the problem of detection of multiple specular components in the acoustic backscattered data. Finally, a method for the estimation of time delays using wavelet decomposition is derived. The sub-band adaptive filtering uses discrete wavelet transform for multi- resolution or sub-band decomposition. Joint time delay estimation for identifying multi-specular components and subsequent adaptive filtering processes are performed on the signal in each sub-band. This would provide multiple 'look' of the signal at different resolution scale which results in more accurate estimates for delays associated with the specular components. Simulation results on the simulated and real shallow water data are provided which show the promise of this new scheme for target detection in a heavy cluttered environment.

Translation-coupling systems

DOEpatents

Pfleger, Brian; Mendez-Perez, Daniel

2013-11-05

Disclosed are systems and methods for coupling translation of a target gene to a detectable response gene. A version of the invention includes a translation-coupling cassette. The translation-coupling cassette includes a target gene, a response gene, a response-gene translation control element, and a secondary structure-forming sequence that reversibly forms a secondary structure masking the response-gene translation control element. Masking of the response-gene translation control element inhibits translation of the response gene. Full translation of the target gene results in unfolding of the secondary structure and consequent translation of the response gene. Translation of the target gene is determined by detecting presence of the response-gene protein product. The invention further includes RNA transcripts of the translation-coupling cassettes, vectors comprising the translation-coupling cassettes, hosts comprising the translation-coupling cassettes, methods of using the translation-coupling cassettes, and gene products produced with the translation-coupling cassettes.

Identification and location of catenary insulator in complex background based on machine vision

NASA Astrophysics Data System (ADS)

Yao, Xiaotong; Pan, Yingli; Liu, Li; Cheng, Xiao

2018-04-01

It is an important premise to locate insulator precisely for fault detection. Current location algorithms for insulator under catenary checking images are not accurate, a target recognition and localization method based on binocular vision combined with SURF features is proposed. First of all, because of the location of the insulator in complex environment, using SURF features to achieve the coarse positioning of target recognition; then Using binocular vision principle to calculate the 3D coordinates of the object which has been coarsely located, realization of target object recognition and fine location; Finally, Finally, the key is to preserve the 3D coordinate of the object's center of mass, transfer to the inspection robot to control the detection position of the robot. Experimental results demonstrate that the proposed method has better recognition efficiency and accuracy, can successfully identify the target and has a define application value.

Translation-coupling systems

DOEpatents

Pfleger, Brian; Mendez-Perez, Daniel

2015-05-19

Disclosed are systems and methods for coupling translation of a target gene to a detectable response gene. A version of the invention includes a translation-coupling cassette. The translation-coupling cassette includes a target gene, a response gene, a response-gene translation control element, and a secondary structure-forming sequence that reversibly forms a secondary structure masking the response-gene translation control element. Masking of the response-gene translation control element inhibits translation of the response gene. Full translation of the target gene results in unfolding of the secondary structure and consequent translation of the response gene. Translation of the target gene is determined by detecting presence of the response-gene protein product. The invention further includes RNA transcripts of the translation-coupling cassettes, vectors comprising the translation-coupling cassettes, hosts comprising the translation-coupling cassettes, methods of using the translation-coupling cassettes, and gene products produced with the translation-coupling cassettes.

Multiplexed Single Intact Cell Droplet Digital PCR (MuSIC ddPCR) Method for Specific Detection of Enterohemorrhagic E. coli (EHEC) in Food Enrichment Cultures

PubMed Central

McMahon, Tanis C.; Blais, Burton W.; Wong, Alex; Carrillo, Catherine D.

2017-01-01

Foodborne illness attributed to enterohemorrhagic E. coli (EHEC), a highly pathogenic subset of Shiga toxin-producing E. coli (STEC), is increasingly recognized as a significant public health issue. Current microbiological methods for identification of EHEC in foods often use PCR-based approaches to screen enrichment broth cultures for characteristic gene markers [i.e., Shiga toxin (stx) and intimin (eae)]. However, false positives arise when complex food matrices, such as beef, contain mixtures of eae-negative STEC and eae-positive E. coli, but no EHEC with both markers in a single cell. To reduce false-positive detection of EHEC in food enrichment samples, a Multiplexed, Single Intact Cell droplet digital PCR (MuSIC ddPCR) assay capable of detecting the co-occurrence of the stx and eae genes in a single bacterial cell was developed. This method requires: (1) dispersal of intact bacteria into droplets; (2) release of genomic DNA (gDNA) by heat lysis; and (3) amplification and detection of genetic targets (stx and eae) using standard TaqMan chemistries with ddPCR. Performance of the method was tested with panels of EHEC and non-target E. coli. By determining the linkage (i.e., the proportion of droplets in which stx and eae targets were both amplified), samples containing EHEC (typically greater than 20% linkage) could be distinguished from samples containing mixtures of eae-negative STEC and eae-positive E. coli (0–2% linkage). The use of intact cells was necessary as this linkage was not observed with gDNA extracts. EHEC could be accurately identified in enrichment broth cultures containing excess amounts of background E. coli and in enrichment cultures derived from ground beef/pork and leafy-green produce samples. To our knowledge, this is the first report of dual-target detection in single bacterial cells using ddPCR. The application of MuSIC ddPCR to enrichment-culture screening would reduce false-positives, thereby improving the cost, speed, and accuracy of current methods for EHEC detection in foods. PMID:28303131

Multiplexed Single Intact Cell Droplet Digital PCR (MuSIC ddPCR) Method for Specific Detection of Enterohemorrhagic E. coli (EHEC) in Food Enrichment Cultures.

PubMed

McMahon, Tanis C; Blais, Burton W; Wong, Alex; Carrillo, Catherine D

2017-01-01

Foodborne illness attributed to enterohemorrhagic E. coli (EHEC), a highly pathogenic subset of Shiga toxin-producing E. coli (STEC), is increasingly recognized as a significant public health issue. Current microbiological methods for identification of EHEC in foods often use PCR-based approaches to screen enrichment broth cultures for characteristic gene markers [i.e., Shiga toxin ( stx ) and intimin ( eae )]. However, false positives arise when complex food matrices, such as beef, contain mixtures of eae -negative STEC and eae -positive E. coli , but no EHEC with both markers in a single cell. To reduce false-positive detection of EHEC in food enrichment samples, a Multiplexed, Single Intact Cell droplet digital PCR (MuSIC ddPCR) assay capable of detecting the co-occurrence of the stx and eae genes in a single bacterial cell was developed. This method requires: (1) dispersal of intact bacteria into droplets; (2) release of genomic DNA (gDNA) by heat lysis; and (3) amplification and detection of genetic targets ( stx and eae ) using standard TaqMan chemistries with ddPCR. Performance of the method was tested with panels of EHEC and non-target E. coli . By determining the linkage (i.e., the proportion of droplets in which stx and eae targets were both amplified), samples containing EHEC (typically greater than 20% linkage) could be distinguished from samples containing mixtures of eae -negative STEC and eae -positive E. coli (0-2% linkage). The use of intact cells was necessary as this linkage was not observed with gDNA extracts. EHEC could be accurately identified in enrichment broth cultures containing excess amounts of background E. coli and in enrichment cultures derived from ground beef/pork and leafy-green produce samples. To our knowledge, this is the first report of dual-target detection in single bacterial cells using ddPCR. The application of MuSIC ddPCR to enrichment-culture screening would reduce false-positives, thereby improving the cost, speed, and accuracy of current methods for EHEC detection in foods.

Optimization of biological and instrumental detection of explosives and ignitable liquid residues including canines, SPME/ITMS and GC/MSn

NASA Astrophysics Data System (ADS)

Furton, Kenneth G.; Harper, Ross J.; Perr, Jeannette M.; Almirall, Jose R.

2003-09-01

A comprehensive study and comparison is underway using biological detectors and instrumental methods for the rapid detection of ignitable liquid residues (ILR) and high explosives. Headspace solid phase microextraction (SPME) has been demonstrated to be an effective sampling method helping to identify active odor signature chemicals used by detector dogs to locate forensic specimens as well as a rapid pre-concentration technique prior to instrumental detection. Common ignitable liquids and common military and industrial explosives have been studied including trinitrotoluene, tetryl, RDX, HMX, EGDN, PETN and nitroglycerine. This study focuses on identifying volatile odor signature chemicals present, which can be used to enhance the level and reliability of detection of ILR and explosives by canines and instrumental methods. While most instrumental methods currently in use focus on particles and on parent organic compounds, which are often involatile, characteristic volatile organics are generally also present and can be exploited to enhance detection particularly for well-concealed devices. Specific examples include the volatile odor chemicals 2-ethyl-1-hexanol and cyclohexanone, which are readily available in the headspace of the high explosive composition C-4; whereas, the active chemical cyclo-1,3,5-trimethylene-2,4,6-trinitramine (RDX) is not. The analysis and identification of these headspace 'fingerprint' organics is followed by double-blind dog trials of the individual components using certified teams in an attempt to isolate and understand the target compounds to which dogs are sensitive. Studies to compare commonly used training aids with the actual target explosive have also been undertaken to determine their suitability and effectiveness. The optimization of solid phase microextraction (SPME) combined with ion trap mobility spectrometry (ITMS) and gas chromatography/mass spectrometry/mass spectrometry (GC/MSn) is detailed including interface development and comparisons of limits of detection. These instrumental methods are being optimized in order to detect the same target odor chemicals used by detector dogs to reliably locate explosives and ignitable liquids.

Sonar target enhancement by shrinkage of incoherent wavelet coefficients.

PubMed

Hunter, Alan J; van Vossen, Robbert

2014-01-01

Background reverberation can obscure useful features of the target echo response in broadband low-frequency sonar images, adversely affecting detection and classification performance. This paper describes a resolution and phase-preserving means of separating the target response from the background reverberation noise using a coherence-based wavelet shrinkage method proposed recently for de-noising magnetic resonance images. The algorithm weights the image wavelet coefficients in proportion to their coherence between different looks under the assumption that the target response is more coherent than the background. The algorithm is demonstrated successfully on experimental synthetic aperture sonar data from a broadband low-frequency sonar developed for buried object detection.

Comparative evaluation of PCR amplification of RLEP, 16S rRNA, rpoT and Sod A gene targets for detection of M. leprae DNA from clinical and environmental samples.

PubMed

Turankar, Ravindra P; Pandey, Shradha; Lavania, Mallika; Singh, Itu; Nigam, Astha; Darlong, Joydeepa; Darlong, Fam; Sengupta, Utpal

2015-03-01

PCR assay is a highly sensitive, specific and reliable diagnostic tool for the identification of pathogens in many infectious diseases. Genome sequencing Mycobacterium leprae revealed several gene targets that could be used for the detection of DNA from clinical and environmental samples. The PCR sensitivity of particular gene targets for specific clinical and environmental isolates has not yet been established. The present study was conducted to compare the sensitivity of RLEP, rpoT, Sod A and 16S rRNA gene targets in the detection of M. leprae in slit skin smear (SSS), blood, soil samples of leprosy patients and their surroundings. Leprosy patients were classified into Paucibacillary (PB) and Multibacillary (MB) types. Ziehl-Neelsen (ZN) staining method for all the SSS samples and Bacteriological Index (BI) was calculated for all patients. Standard laboratory protocol was used for DNA extraction from SSS, blood and soil samples. PCR technique was performed for the detection of M. leprae DNA from all the above-mentioned samples. RLEP gene target was able to detect the presence of M. leprae in 83% of SSS, 100% of blood samples and in 36% of soil samples and was noted to be the best out of all other gene targets (rpoT, Sod A and 16S rRNA). It was noted that the RLEP gene target was able to detect the highest number (53%) of BI-negative leprosy patients amongst all the gene targets used in this study. Amongst all the gene targets used in this study, PCR positivity using RLEP gene target was the highest in all the clinical and environmental samples. Further, the RLEP gene target was able to detect 53% of blood samples as positive in BI-negative leprosy cases indicating its future standardization and use for diagnostic purposes. Copyright © 2015 Asian African Society for Mycobacteriology. Published by Elsevier Ltd. All rights reserved.

Tools for in silico target fishing.

PubMed

Cereto-Massagué, Adrià; Ojeda, María José; Valls, Cristina; Mulero, Miquel; Pujadas, Gerard; Garcia-Vallve, Santiago

2015-01-01

Computational target fishing methods are designed to identify the most probable target of a query molecule. This process may allow the prediction of the bioactivity of a compound, the identification of the mode of action of known drugs, the detection of drug polypharmacology, drug repositioning or the prediction of the adverse effects of a compound. The large amount of information regarding the bioactivity of thousands of small molecules now allows the development of these types of methods. In recent years, we have witnessed the emergence of many methods for in silico target fishing. Most of these methods are based on the similarity principle, i.e., that similar molecules might bind to the same targets and have similar bioactivities. However, the difficult validation of target fishing methods hinders comparisons of the performance of each method. In this review, we describe the different methods developed for target prediction, the bioactivity databases most frequently used by these methods, and the publicly available programs and servers that enable non-specialist users to obtain these types of predictions. It is expected that target prediction will have a large impact on drug development and on the functional food industry. Copyright © 2014 Elsevier Inc. All rights reserved.

[The application of wavelet analysis of remote detection of pollution clouds].

PubMed

Zhang, J; Jiang, F

2001-08-01

The discrete wavelet transform (DWT) is used to analyse the spectra of pollution clouds in complicated environment and extract the small-features. The DWT is a time-frequency analysis technology, which detects the subtle small changes in the target spectrum. The results show that the DWT is a quite effective method to extract features of target-cloud and improve the reliability of monitoring alarm system.

Overview of hybridization and detection techniques.

PubMed

Hilario, Elena

2007-01-01

A misconception regarding the sensitivity of nonradioactive methods for screening genomic DNA libraries often hinders the establishment of these environmentally friendly techniques in molecular biology laboratories. Nonradioactive probes, properly prepared and quantified, can detect DNA target molecules to the femtomole range. However, appropriate hybridization techniques and detection methods should also be adopted for an efficient use of nonradioactive techniques. Detailed descriptions of genomic library handling before and during the nonradioactive hybridization and detection are often omitted from publications. This chapter aims to fill this void by providing a collection of technical tips on hybridization and detection techniques.

Computational optimisation of targeted DNA sequencing for cancer detection

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

PubMed

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

2009-05-01

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

Sensitive detection of point mutation by electrochemiluminescence and DNA ligase-based assay

NASA Astrophysics Data System (ADS)

Zhou, Huijuan; Wu, Baoyan

2008-12-01

The technology of single-base mutation detection plays an increasingly important role in diagnosis and prognosis of genetic-based diseases. Here we reported a new method for the analysis of point mutations in genomic DNA through the integration of allele-specific oligonucleotide ligation assay (OLA) with magnetic beads-based electrochemiluminescence (ECL) detection scheme. In this assay the tris(bipyridine) ruthenium (TBR) labeled probe and the biotinylated probe are designed to perfectly complementary to the mutant target, thus a ligation can be generated between those two probes by Taq DNA Ligase in the presence of mutant target. If there is an allele mismatch, the ligation does not take place. The ligation products are then captured onto streptavidin-coated paramagnetic beads, and detected by measuring the ECL signal of the TBR label. Results showed that the new method held a low detection limit down to 10 fmol and was successfully applied in the identification of point mutations from ASTC-α-1, PANC-1 and normal cell lines in codon 273 of TP53 oncogene. In summary, this method provides a sensitive, cost-effective and easy operation approach for point mutation detection.

Single reaction, real time RT-PCR detection of all known avian and human metapneumoviruses.

PubMed

Lemaitre, E; Allée, C; Vabret, A; Eterradossi, N; Brown, P A

2018-01-01

Current molecular methods for the detection of avian and human metapneumovirus (AMPV, HMPV) are specifically targeted towards each virus species or individual subgroups of these. Here a broad range SYBR Green I real time RT-PCR was developed which amplified a highly conserved fragment of sequence in the N open reading frame. This method was sufficiently efficient and specific in detecting all MPVs. Its validation according to the NF U47-600 norm for the four AMPV subgroups estimated low limits of detection between 1000 and 10copies/μL, similar with detection levels described previously for real time RT-PCRs targeting specific subgroups. RNA viruses present a challenge for the design of durable molecular diagnostic test due to the rate of change in their genome sequences which can vary substantially in different areas and over time. The fact that the regions of sequence for primer hybridization in the described method have remained sufficiently conserved since the AMPV and HMPV diverged, should give the best chance of continued detection of current subgroups and of potential unknown or future emerging MPV strains. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of a Novel De Novo Heterozygous Deletion in the SOX10 Gene in Waardenburg Syndrome Type II Using Next-Generation Sequencing.

PubMed

Li, Haonan; Jin, Peng; Hao, Qian; Zhu, Wei; Chen, Xia; Wang, Ping

2017-11-01

Waardenburg syndrome (WS) is a rare autosomal dominant disorder associated with pigmentation abnormalities and sensorineural hearing loss. In this study, we investigated the genetic cause of WSII in a patient and evaluated the reliability of the targeted next-generation exome sequencing method for the genetic diagnosis of WS. Clinical evaluations were conducted on the patient and targeted next-generation sequencing (NGS) was used to identify the candidate genes responsible for WSII. Multiplex ligation-dependent probe amplification (MLPA) and real-time quantitative polymerase chain reaction (qPCR) were performed to confirm the targeted NGS results. Targeted NGS detected the entire deletion of the coding sequence (CDS) of the SOX10 gene in the WSII patient. MLPA results indicated that all exons of the SOX10 heterozygous deletion were detected; no aberrant copy number in the PAX3 and microphthalmia-associated transcription factor (MITF) genes was found. Real-time qPCR results identified the mutation as a de novo heterozygous deletion. This is the first report of using a targeted NGS method for WS candidate gene sequencing; its accuracy was verified by using the MLPA and qPCR methods. Our research provides a valuable method for the genetic diagnosis of WS.

Continuous improvement of medical test reliability using reference methods and matrix-corrected target values in proficiency testing schemes: application to glucose assay.

PubMed

Delatour, Vincent; Lalere, Beatrice; Saint-Albin, Karène; Peignaux, Maryline; Hattchouel, Jean-Marc; Dumont, Gilles; De Graeve, Jacques; Vaslin-Reimann, Sophie; Gillery, Philippe

2012-11-20

The reliability of biological tests is a major issue for patient care in terms of public health that involves high economic stakes. Reference methods, as well as regular external quality assessment schemes (EQAS), are needed to monitor the analytical performance of field methods. However, control material commutability is a major concern to assess method accuracy. To overcome material non-commutability, we investigated the possibility of using lyophilized serum samples together with a limited number of frozen serum samples to assign matrix-corrected target values, taking the example of glucose assays. Trueness of the current glucose assays was first measured against a primary reference method by using human frozen sera. Methods using hexokinase and glucose oxidase with spectroreflectometric detection proved very accurate, with bias ranging between -2.2% and +2.3%. Bias of methods using glucose oxidase with spectrophotometric detection was +4.5%. Matrix-related bias of the lyophilized materials was then determined and ranged from +2.5% to -14.4%. Matrix-corrected target values were assigned and used to assess trueness of 22 sub-peer groups. We demonstrated that matrix-corrected target values can be a valuable tool to assess field method accuracy in large scale surveys where commutable materials are not available in sufficient amount with acceptable costs. Copyright © 2012 Elsevier B.V. All rights reserved.

Research on the frequency hopping bistatic sonar system

NASA Astrophysics Data System (ADS)

Liang, Guo-long; Zhang, Yao; Zhang, Guang-pu; Liu, Kai

2011-10-01

A new model for bistatic sonar system is established, in which frequency hopping (FH) signals are used for targets detection according to some rules. This model can decrease the time between adjacent signals and obtain more information in a unit time. The receiving system will receive and process the signals of different frequency respectively, according the FH pattern, for detecting and locating targets. This method can helps yield more stable and accurate outputs, using the characteristic of the FH signals, increase the ability of anti-detection and anti partial-band jamming.

Surveillance theory applied to virus detection: a case for targeted discovery

USGS Publications Warehouse

Bogich, Tiffany L.; Anthony, Simon J.; Nichols, James D.

2013-01-01

Virus detection and mathematical modeling have gone through rapid developments in the past decade. Both offer new insights into the epidemiology of infectious disease and characterization of future risk; however, modeling has not yet been applied to designing the best surveillance strategies for viral and pathogen discovery. We review recent developments and propose methods to integrate viral and pathogen discovery and mathematical modeling through optimal surveillance theory, arguing for a more targeted approach to novel virus detection guided by the principles of adaptive management and structured decision-making.

Validation of PCR methods for quantitation of genetically modified plants in food.

PubMed

Hübner, P; Waiblinger, H U; Pietsch, K; Brodmann, P

2001-01-01

For enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients, quantitative detection methods such as quantitative competitive (QC-PCR) and real-time PCR are applied by official food control laboratories. The experiences of 3 European food control laboratories in validating such methods were compared to describe realistic performance characteristics of quantitative PCR detection methods. The limit of quantitation (LOQ) of GMO-specific, real-time PCR was experimentally determined to reach 30-50 target molecules, which is close to theoretical prediction. Starting PCR with 200 ng genomic plant DNA, the LOQ depends primarily on the genome size of the target plant and ranges from 0.02% for rice to 0.7% for wheat. The precision of quantitative PCR detection methods, expressed as relative standard deviation (RSD), varied from 10 to 30%. Using Bt176 corn containing test samples and applying Bt176 specific QC-PCR, mean values deviated from true values by -7to 18%, with an average of 2+/-10%. Ruggedness of real-time PCR detection methods was assessed in an interlaboratory study analyzing commercial, homogeneous food samples. Roundup Ready soybean DNA contents were determined in the range of 0.3 to 36%, relative to soybean DNA, with RSDs of about 25%. Taking the precision of quantitative PCR detection methods into account, suitable sample plans and sample sizes for GMO analysis are suggested. Because quantitative GMO detection methods measure GMO contents of samples in relation to reference material (calibrants), high priority must be given to international agreements and standardization on certified reference materials.

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

PubMed

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

2017-06-01

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

Sub-surface defects detection of by using active thermography and advanced image edge detection

NASA Astrophysics Data System (ADS)

Tse, Peter W.; Wang, Gaochao

2017-05-01

Active or pulsed thermography is a popular non-destructive testing (NDT) tool for inspecting the integrity and anomaly of industrial equipment. One of the recent research trends in using active thermography is to automate the process in detecting hidden defects. As of today, human effort has still been using to adjust the temperature intensity of the thermo camera in order to visually observe the difference in cooling rates caused by a normal target as compared to that by a sub-surface crack exists inside the target. To avoid the tedious human-visual inspection and minimize human induced error, this paper reports the design of an automatic method that is capable of detecting subsurface defects. The method used the technique of active thermography, edge detection in machine vision and smart algorithm. An infrared thermo-camera was used to capture a series of temporal pictures after slightly heating up the inspected target by flash lamps. Then the Canny edge detector was employed to automatically extract the defect related images from the captured pictures. The captured temporal pictures were preprocessed by a packet of Canny edge detector and then a smart algorithm was used to reconstruct the whole sequences of image signals. During the processes, noise and irrelevant backgrounds exist in the pictures were removed. Consequently, the contrast of the edges of defective areas had been highlighted. The designed automatic method was verified by real pipe specimens that contains sub-surface cracks. After applying such smart method, the edges of cracks can be revealed visually without the need of using manual adjustment on the setting of thermo-camera. With the help of this automatic method, the tedious process in manually adjusting the colour contract and the pixel intensity in order to reveal defects can be avoided.

High-sensitive electrochemical detection of point mutation based on polymerization-induced enzymatic amplification.

PubMed

Feng, Kejun; Zhao, Jingjin; Wu, Zai-Sheng; Jiang, Jianhui; Shen, Guoli; Yu, Ruqin

2011-03-15

Here a highly sensitive electrochemical method is described for the detection of point mutation in DNA. Polymerization extension reaction is applied to specifically initiate enzymatic electrochemical amplification to improve the sensitivity and enhance the performance of point mutation detection. In this work, 5'-thiolated DNA probe sequences complementary to the wild target DNA are assembled on the gold electrode. In the presence of wild target DNA, the probe is extended by DNA polymerase over the free segment of target as the template. After washing with NaOH solution, the target DNA is removed while the elongated probe sequence remains on the sensing surface. Via hybridizing to the designed biotin-labeled detection probe, the extended sequence is capable of capturing detection probe. After introducing streptavidin-conjugated alkaline phosphatase (SA-ALP), the specific binding between streptavidin and biotin mediates a catalytic reaction of ascorbic acid 2-phosphate (AA-P) substrate to produce a reducing agent ascorbic acid (AA). Then the silver ions in solution are reduced by AA, leading to the deposition of silver metal onto the electrode surface. The amount of deposited silver which is determined by the amount of wild target can be quantified by the linear sweep voltammetry (LSV). The present approach proved to be capable of detecting the wild target DNA down to a detection limit of 1.0×10(-14) M in a wide target concentration range and identifying -28 site (A to G) of the β-thalassemia gene, demonstrating that this scheme offers a highly sensitive and specific approach for point mutation detection. Copyright © 2010 Elsevier B.V. All rights reserved.

Airborne particulate discriminator

DOEpatents

Creek, Kathryn Louise [San Diego, CA; Castro, Alonso [Santa Fe, NM; Gray, Perry Clayton [Los Alamos, NM

2009-08-11

A method and apparatus for rapid and accurate detection and discrimination of biological, radiological, and chemical particles in air. A suspect aerosol of the target particulates is treated with a taggant aerosol of ultrafine particulates. Coagulation of the taggant and target particles causes a change in fluorescent properties of the cloud, providing an indication of the presence of the target.

An interlaboratory study on efficient detection of Shiga toxin-producing Escherichia coli O26, O103, O111, O121, O145, and O157 in food using real-time PCR assay and chromogenic agar.

PubMed

Hara-Kudo, Yukiko; Konishi, Noriko; Ohtsuka, Kayoko; Iwabuchi, Kaori; Kikuchi, Rie; Isobe, Junko; Yamazaki, Takumiko; Suzuki, Fumie; Nagai, Yuhki; Yamada, Hiroko; Tanouchi, Atsuko; Mori, Tetsuya; Nakagawa, Hiroshi; Ueda, Yasufumi; Terajima, Jun

2016-08-02

To establish an efficient detection method for Shiga toxin (Stx)-producing Escherichia coli (STEC) O26, O103, O111, O121, O145, and O157 in food, an interlaboratory study using all the serogroups of detection targets was firstly conducted. We employed a series of tests including enrichment, real-time PCR assays, and concentration by immunomagnetic separation, followed by plating onto selective agar media (IMS-plating methods). This study was particularly focused on the efficiencies of real-time PCR assays in detecting stx and O-antigen genes of the six serogroups and of IMS-plating methods onto selective agar media including chromogenic agar. Ground beef and radish sprouts samples were inoculated with the six STEC serogroups either at 4-6CFU/25g (low levels) or at 22-29CFU/25g (high levels). The sensitivity of stx detection in ground beef at both levels of inoculation with all six STEC serogroups was 100%. The sensitivity of stx detection was also 100% in radish sprouts at high levels of inoculation with all six STEC serogroups, and 66.7%-91.7% at low levels of inoculation. The sensitivity of detection of O-antigen genes was 100% in both ground beef and radish sprouts at high inoculation levels, while at low inoculation levels, it was 95.8%-100% in ground beef and 66.7%-91.7% in radish sprouts. The sensitivity of detection with IMS-plating was either the same or lower than those of the real-time PCR assays targeting stx and O-antigen genes. The relationship between the results of IMS-plating methods and Ct values of real-time PCR assays were firstly analyzed in detail. Ct values in most samples that tested negative in the IMS-plating method were higher than the maximum Ct values in samples that tested positive in the IMS-plating method. This study indicates that all six STEC serogroups in food contaminated with more than 29CFU/25g were detected by real-time PCR assays targeting stx and O-antigen genes and IMS-plating onto selective agar media. Therefore, screening of stx and O-antigen genes followed by isolation of STECs by IMS-plating methods may be an efficient method to detect the six STEC serogroups. Copyright © 2016 Elsevier B.V. All rights reserved.

A Reference-Free and Non-Contact Method for Detecting and Imaging Damage in Adhesive-Bonded Structures Using Air-Coupled Ultrasonic Transducers.

PubMed

Yonathan Sunarsa, Timotius; Aryan, Pouria; Jeon, Ikgeun; Park, Byeongjin; Liu, Peipei; Sohn, Hoon

2017-12-08

Adhesive bonded structures have been widely used in aerospace, automobile, and marine industries. Due to the complex nature of the failure mechanisms of bonded structures, cost-effective and reliable damage detection is crucial for these industries. Most of the common damage detection methods are not adequately sensitive to the presence of weakened bonding. This paper presents an experimental and analytical method for the in-situ detection of damage in adhesive-bonded structures. The method is fully non-contact, using air-coupled ultrasonic transducers (ACT) for ultrasonic wave generation and sensing. The uniqueness of the proposed method relies on accurate detection and localization of weakened bonding in complex adhesive bonded structures. The specimens tested in this study are parts of real-world structures with critical and complex damage types, provided by Hyundai Heavy Industries ® and IKTS Fraunhofer ® . Various transmitter and receiver configurations, including through transmission, pitch-catch scanning, and probe holder angles, were attempted, and the obtained results were analyzed. The method examines the time-of-flight of the ultrasonic waves over a target inspection area, and the spatial variation of the time-of-flight information was examined to visualize and locate damage. The proposed method works without relying on reference data obtained from the pristine condition of the target specimen. Aluminum bonded plates and triplex adhesive layers with debonding and weakened bonding were used to examine the effectiveness of the method.

A Reference-Free and Non-Contact Method for Detecting and Imaging Damage in Adhesive-Bonded Structures Using Air-Coupled Ultrasonic Transducers

PubMed Central

Yonathan Sunarsa, Timotius; Aryan, Pouria; Jeon, Ikgeun; Park, Byeongjin; Liu, Peipei

2017-01-01

Adhesive bonded structures have been widely used in aerospace, automobile, and marine industries. Due to the complex nature of the failure mechanisms of bonded structures, cost-effective and reliable damage detection is crucial for these industries. Most of the common damage detection methods are not adequately sensitive to the presence of weakened bonding. This paper presents an experimental and analytical method for the in-situ detection of damage in adhesive-bonded structures. The method is fully non-contact, using air-coupled ultrasonic transducers (ACT) for ultrasonic wave generation and sensing. The uniqueness of the proposed method relies on accurate detection and localization of weakened bonding in complex adhesive bonded structures. The specimens tested in this study are parts of real-world structures with critical and complex damage types, provided by Hyundai Heavy Industries® and IKTS Fraunhofer®. Various transmitter and receiver configurations, including through transmission, pitch-catch scanning, and probe holder angles, were attempted, and the obtained results were analyzed. The method examines the time-of-flight of the ultrasonic waves over a target inspection area, and the spatial variation of the time-of-flight information was examined to visualize and locate damage. The proposed method works without relying on reference data obtained from the pristine condition of the target specimen. Aluminum bonded plates and triplex adhesive layers with debonding and weakened bonding were used to examine the effectiveness of the method. PMID:29292752

Fluorescent trimethyl-substituted naphthyridine as a label-free signal reporter for one-step and highly sensitive fluorescent detection of DNA in serum samples.

PubMed

Wang, Jiamian; Wang, Xiuyun; Wu, Shuo; Che, Ruping; Luo, Pinchen; Meng, Changgong

2017-01-15

A facile label-free sensing method is developed for the one-step and highly sensitive fluorescent detection of DNA, which couples the specific C-C mismatch bonding and fluorescent quenching property of a trimethyl-substituted naphthyridine dye (ATMND) with the exonuclease III (Exo III) assisted cascade target recycling amplification strategy. In the absence of target DNA, the DNA hairpin probe with a C-C mismatch in the stem and more than 4 bases overhung at the 3' terminus could entrap and quench the fluorescence of ATMND and resist the digestion of Exo III, thus showing a low fluorescence background. In the presence of the target, however, the hybridization event between the two protruding segments and the target triggers the digestion reaction of Exo III, recycles the initial target, and simultaneously releases both the secondary target analogue and the ATMND caged in the stem. The released initial and secondary targets take part in another cycle of digestion, thus leading to the release of a huge amount of free ATMND for signal transducing. Based on the fluorescence recovery, the as-proposed label-free fluorescent sensing strategy shows very good analytical performances towards DNA detection, such as a wide linear range from 10pM to 1μM, a low limit of detection of 6pM, good selectivity, and a facile one-step operation at room temperature. Practical sample analysis in serum samples indicates the method has good precision and accuracy, which may thus have application potentials for point-of-care screening of DNA in complex clinical and environmental samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Method for enhancing single-trial P300 detection by introducing the complexity degree of image information in rapid serial visual presentation tasks

PubMed Central

Lin, Zhimin; Zeng, Ying; Tong, Li; Zhang, Hangming; Zhang, Chi

2017-01-01

The application of electroencephalogram (EEG) generated by human viewing images is a new thrust in image retrieval technology. A P300 component in the EEG is induced when the subjects see their point of interest in a target image under the rapid serial visual presentation (RSVP) experimental paradigm. We detected the single-trial P300 component to determine whether a subject was interested in an image. In practice, the latency and amplitude of the P300 component may vary in relation to different experimental parameters, such as target probability and stimulus semantics. Thus, we proposed a novel method, Target Recognition using Image Complexity Priori (TRICP) algorithm, in which the image information is introduced in the calculation of the interest score in the RSVP paradigm. The method combines information from the image and EEG to enhance the accuracy of single-trial P300 detection on the basis of traditional single-trial P300 detection algorithm. We defined an image complexity parameter based on the features of the different layers of a convolution neural network (CNN). We used the TRICP algorithm to compute for the complexity of an image to quantify the effect of different complexity images on the P300 components and training specialty classifier according to the image complexity. We compared TRICP with the HDCA algorithm. Results show that TRICP is significantly higher than the HDCA algorithm (Wilcoxon Sign Rank Test, p<0.05). Thus, the proposed method can be used in other and visual task-related single-trial event-related potential detection. PMID:29283998

Assessment of environmental DNA for detecting presence of imperiled aquatic amphibian species in isolated wetlands

USGS Publications Warehouse

Mckee, Anna; Calhoun, Daniel L.; Barichivich, William J.; Spear, Stephen F.; Goldberg, Caren S.; Glenn, Travis C

2015-01-01

Environmental DNA (eDNA) is an emerging tool that allows low-impact sampling for aquatic species by isolating DNA from water samples and screening for DNA sequences specific to species of interest. However, researchers have not tested this method in naturally acidic wetlands that provide breeding habitat for a number of imperiled species, including the frosted salamander (Ambystoma cingulatum), reticulated flatwoods salamanders (Ambystoma bishopi), striped newt (Notophthalmus perstriatus), and gopher frog (Lithobates capito). Our objectives for this study were to develop and optimize eDNA survey protocols and assays to complement and enhance capture-based survey methods for these amphibian species. We collected three or more water samples, dipnetted or trapped larval and adult amphibians, and conducted visual encounter surveys for egg masses for target species at 40 sites on 12 different longleaf pine (Pinus palustris) tracts. We used quantitative PCRs to screen eDNA from each site for target species presence. We detected flatwoods salamanders at three sites with eDNA but did not detect them during physical surveys. Based on the sample location we assumed these eDNA detections to indicate the presence of frosted flatwoods salamanders. We did not detect reticulated flatwoods salamanders. We detected striped newts with physical and eDNA surveys at two wetlands. We detected gopher frogs at 12 sites total, three with eDNA alone, two with physical surveys alone, and seven with physical and eDNA surveys. We detected our target species with eDNA at 9 of 11 sites where they were present as indicated from traditional surveys and at six sites where they were not detected with traditional surveys. It was, however, critical to use at least three water samples per site for eDNA. Our results demonstrate eDNA surveys can be a useful complement to traditional survey methods for detecting imperiled pond-breeding amphibians. Environmental DNA may be particularly useful in situations where detection probability using traditional survey methods is low or access by trained personnel is limited.

Comparison of four PCR methods for efficient detection of Trypanosoma cruzi in routine diagnostics.

PubMed

Seiringer, Peter; Pritsch, Michael; Flores-Chavez, María; Marchisio, Edoardo; Helfrich, Kerstin; Mengele, Carolin; Hohnerlein, Stefan; Bretzel, Gisela; Löscher, Thomas; Hoelscher, Michael; Berens-Riha, Nicole

2017-07-01

Due to increased migration, Chagas disease has become an international health problem. Reliable diagnosis of chronically infected people is crucial for prevention of non-vectorial transmission as well as treatment. This study compared four distinct PCR methods for detection of Trypanosoma cruzi DNA for the use in well-equipped routine diagnostic laboratories. DNA was extracted of T. cruzi-positive and negative patients' blood samples and cultured T. cruzi, T. rangeli as well as Leishmania spp. One conventional and two real-time PCR methods targeting a repetitive Sat-DNA sequence as well as one conventional PCR method targeting the variable region of the kDNA minicircle were compared for sensitivity, intra- and interassay precision, limit of detection, specificity and cross-reactivity. Considering the performance, costs and ease of use, an algorithm for PCR-diagnosis of patients with a positive serology for T. cruzi antibodies was developed. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

[Target and non-target screening of volatile organic compounds in industrial exhaust gas using thermal desorption-gas chromatography-mass spectrometry].

PubMed

Ma, Huilian; Jin, Jing; Li, Yun; Chen, Jiping

2017-10-08

A method of comprehensive screening of the target and non-target volatile organic compounds (VOCs) in industrial exhaust gas using thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) has been developed. In this paper, two types of solid phase adsorption column were compared, and the Tenex SS TD Tube was selected. The analytes were enriched into the adsorption tube by constant flow sampling, and detected by TD-GC-MS in full scan mode. Target compounds were quantified by internal standard method, and the quantities of non-target compounds were calculated by response coefficient of toluene. The method detection limits (MDLs) for the 24 VOCs were 1.06 to 5.44 ng, and MDLs could also be expressed as 0.004 to 0.018 mg/m 3 assuming that the sampling volume was 300 mL. The average recoveries were in the range of 78.4% to 89.4% with the relative standard deviations (RSDs) of 3.9% to 14.4% ( n =7). The established analytical method was applied for the comprehensive screening of VOCs in a waste incineration power plant in Dalian city. Twenty-nine VOCs were identified. In these compounds, only five VOCs were the target compounds set in advance, which accounted for 26.7% of the total VOCs identified. Therefore, this study further proved the importance of screening non-target compounds in the analysis of VOCs in industrial exhaust gas, and has certain reference significance for the complete determination of VOCs distribution.

Immunochemical Detection Methods for Gluten in Food Products: Where Do We Go from Here?

PubMed

Slot, I D Bruins; van der Fels-Klerx, H J; Bremer, M G E G; Hamer, R J

2016-11-17

Accurate and reliable quantification methods for gluten in food are necessary to ensure proper product labeling and thus safeguard the gluten sensitive consumer against exposure. Immunochemical detection is the method of choice, as it is sensitive, rapid and relatively easy to use. Although a wide range of detection kits are commercially available, there are still many difficulties in gluten detection that have not yet been overcome. This review gives an overview of the currently commercially available immunochemical detection methods, and discusses the problems that still exist in gluten detection in food. The largest problems are encountered in the extraction of gluten from food matrices, the choice of epitopes targeted by the detection method, and the use of a standardized reference material. By comparing the available techniques with the unmet needs in gluten detection, the possible benefit of a new multiplex immunoassay is investigated. This detection method would allow for the detection and quantification of multiple harmful gluten peptides at once and would, therefore, be a logical advancement in gluten detection in food.

A Bayesian Method for Managing Uncertainties Relating to Distributed Multistatic Sensor Search

DTIC Science & Technology

2006-07-01

before - detect process. There will also be an increased probability of high signal-to-noise ratio (SNR) detections associated with specular and near...and high target strength and high Doppler opportunities give rise to the expectation of an increased number of detections that could feed a track

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

PubMed

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

2015-04-21

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

Methods of preparing and using single chain anti-tumor antibodies

DOEpatents

Cheung, Nai-Kong; Guo, Hong-Fen

2010-02-23

This invention provides a method for identifying cells expressing a target single chain antibody (scFv) directed against a target antigen from a collection of cells that includes cells that do not express the target scFv, comprising the step of combining the collection of cells with an anti-idiotype directed to an antibody specific for the target antigen and detecting interaction, if any, of the anti-idiotype with the cells, wherein the occurrence of an interaction identifies the cell as one which expresses the target scFv. This invention also provides a method for making a single chain antibody (scFv) directed against an antigen, wherein the selection of clones is made based upon interaction of those clones with an appropriate anti-idiotype, and heretofore inaccessible scFv so made. This invention provides the above methods or any combination thereof. Finally, this invention provides various uses of these methods.

Method for preparation of single chain antibodies

DOEpatents

Cheung, Nai-Kong V [New York, NY; Guo, Hong-fen [New York, NY

2012-04-03

This invention provides a method for identifying cells expressing a target single chain antibody (scFv) directed against a target antigen from a collection of cells that includes cells that do not express the target scFv, comprising the step of combining the collection of cells with an anti-idiotype directed to an antibody specific for the target antigen and detecting interaction, if any, of the anti-idiotype with the cells, wherein the occurrence of an interaction identifies the cell as one which expresses the target scFv. This invention also provides a method for making a single chain antibody (scFv) directed against an antigen, wherein the selection of clones is made based upon interaction of those clones with an appropriate anti-idiotype, and heretofore inaccessible scFv so made. This invention provides the above methods or any combination thereof. Finally, this invention provides various uses of these methods.

Space moving target detection and tracking method in complex background

NASA Astrophysics Data System (ADS)

Lv, Ping-Yue; Sun, Sheng-Li; Lin, Chang-Qing; Liu, Gao-Rui

2018-06-01

The background of the space-borne detectors in real space-based environment is extremely complex and the signal-to-clutter ratio is very low (SCR ≈ 1), which increases the difficulty for detecting space moving targets. In order to solve this problem, an algorithm combining background suppression processing based on two-dimensional least mean square filter (TDLMS) and target enhancement based on neighborhood gray-scale difference (GSD) is proposed in this paper. The latter can filter out most of the residual background clutter processed by the former such as cloud edge. Through this procedure, both global and local SCR have obtained substantial improvement, indicating that the target has been greatly enhanced. After removing the detector's inherent clutter region through connected domain processing, the image only contains the target point and the isolated noise, in which the isolated noise could be filtered out effectively through multi-frame association. The proposed algorithm in this paper has been compared with some state-of-the-art algorithms for moving target detection and tracking tasks. The experimental results show that the performance of this algorithm is the best in terms of SCR gain, background suppression factor (BSF) and detection results.

A Simple Method for Amplifying RNA Targets (SMART)

PubMed Central

McCalla, Stephanie E.; Ong, Carmichael; Sarma, Aartik; Opal, Steven M.; Artenstein, Andrew W.; Tripathi, Anubhav

2012-01-01

We present a novel and simple method for amplifying RNA targets (named by its acronym, SMART), and for detection, using engineered amplification probes that overcome existing limitations of current RNA-based technologies. This system amplifies and detects optimal engineered ssDNA probes that hybridize to target RNA. The amplifiable probe-target RNA complex is captured on magnetic beads using a sequence-specific capture probe and is separated from unbound probe using a novel microfluidic technique. Hybridization sequences are not constrained as they are in conventional target-amplification reactions such as nucleic acid sequence amplification (NASBA). Our engineered ssDNA probe was amplified both off-chip and in a microchip reservoir at the end of the separation microchannel using isothermal NASBA. Optimal solution conditions for ssDNA amplification were investigated. Although KCl and MgCl2 are typically found in NASBA reactions, replacing 70 mmol/L of the 82 mmol/L total chloride ions with acetate resulted in optimal reaction conditions, particularly for low but clinically relevant probe concentrations (≤100 fmol/L). With the optimal probe design and solution conditions, we also successfully removed the initial heating step of NASBA, thus achieving a true isothermal reaction. The SMART assay using a synthetic model influenza DNA target sequence served as a fundamental demonstration of the efficacy of the capture and microfluidic separation system, thus bridging our system to a clinically relevant detection problem. PMID:22691910

Bidirectional reflectance distribution function based surface modeling of non-Lambertian using intensity data of light detection and ranging.

PubMed

Li, Xiaolu; Liang, Yu; Xu, Lijun

2014-09-01

To provide a credible model for light detection and ranging (LiDAR) target classification, the focus of this study is on the relationship between intensity data of LiDAR and the bidirectional reflectance distribution function (BRDF). An integration method based on the built-in-lab coaxial laser detection system was advanced. A kind of intermediary BRDF model advanced by Schlick was introduced into the integration method, considering diffuse and specular backscattering characteristics of the surface. A group of measurement campaigns were carried out to investigate the influence of the incident angle and detection range on the measured intensity data. Two extracted parameters r and S(λ) are influenced by different surface features, which illustrate the surface features of the distribution and magnitude of reflected energy, respectively. The combination of two parameters can be used to describe the surface characteristics for target classification in a more plausible way.

Detection and quantification of bacterial biofilms combining high-frequency acoustic microscopy and targeted lipid microparticles

PubMed Central

2014-01-01

Background Immuno-compromised patients such as those undergoing cancer chemotherapy are susceptible to bacterial infections leading to biofilm matrix formation. This surrounding biofilm matrix acts as a diffusion barrier that binds up antibiotics and antibodies, promoting resistance to treatment. Developing non-invasive imaging methods that detect biofilm matrix in the clinic are needed. The use of ultrasound in conjunction with targeted ultrasound contrast agents (UCAs) may provide detection of early stage biofilm matrix formation and facilitate optimal treatment. Results Ligand-targeted UCAs were investigated as a novel method for pre-clinical non-invasive molecular imaging of early and late stage biofilms. These agents were used to target, image and detect Staphylococcus aureus biofilm matrix in vitro. Binding efficacy was assessed on biofilm matrices with respect to their increasing biomass ranging from 3.126 × 103 ± 427 UCAs per mm2 of biofilm surface area within 12 h to 21.985 × 103 ± 855 per mm2 of biofilm matrix surface area at 96 h. High-frequency acoustic microscopy was used to ultrasonically detect targeted UCAs bound to a biofilm matrix and to assess biofilm matrix mechanoelastic physical properties. Acoustic impedance data demonstrated that biofilm matrices exhibit impedance values (1.9 MRayl) close to human tissue (1.35 - 1.85 MRayl for soft tissues). Moreover, the acoustic signature of mature biofilm matrices were evaluated in terms of integrated backscatter (0.0278 - 0.0848 mm-1 × sr-1) and acoustic attenuation (3.9 Np/mm for bound UCAs; 6.58 Np/mm for biofilm alone). Conclusions Early diagnosis of biofilm matrix formation is a challenge in treating cancer patients with infection-associated biofilms. We report for the first time a combined optical and acoustic evaluation of infectious biofilm matrices. We demonstrate that acoustic impedance of biofilms is similar to the impedance of human tissues, making in vivo imaging and detection of biofilm matrices difficult. The combination of ultrasound and targeted UCAs can be used to enhance biofilm imaging and early detection. Our findings suggest that the combination of targeted UCAs and ultrasound is a novel molecular imaging technique for the detection of biofilms. We show that high-frequency acoustic microscopy provides sufficient spatial resolution for quantification of biofilm mechanoelastic properties. PMID:24997588

Detection and quantification of bacterial biofilms combining high-frequency acoustic microscopy and targeted lipid microparticles.

PubMed

Anastasiadis, Pavlos; Mojica, Kristina D A; Allen, John S; Matter, Michelle L

2014-07-06

Immuno-compromised patients such as those undergoing cancer chemotherapy are susceptible to bacterial infections leading to biofilm matrix formation. This surrounding biofilm matrix acts as a diffusion barrier that binds up antibiotics and antibodies, promoting resistance to treatment. Developing non-invasive imaging methods that detect biofilm matrix in the clinic are needed. The use of ultrasound in conjunction with targeted ultrasound contrast agents (UCAs) may provide detection of early stage biofilm matrix formation and facilitate optimal treatment. Ligand-targeted UCAs were investigated as a novel method for pre-clinical non-invasive molecular imaging of early and late stage biofilms. These agents were used to target, image and detect Staphylococcus aureus biofilm matrix in vitro. Binding efficacy was assessed on biofilm matrices with respect to their increasing biomass ranging from 3.126 × 103 ± 427 UCAs per mm(2) of biofilm surface area within 12 h to 21.985 × 103 ± 855 per mm(2) of biofilm matrix surface area at 96 h. High-frequency acoustic microscopy was used to ultrasonically detect targeted UCAs bound to a biofilm matrix and to assess biofilm matrix mechanoelastic physical properties. Acoustic impedance data demonstrated that biofilm matrices exhibit impedance values (1.9 MRayl) close to human tissue (1.35 - 1.85 MRayl for soft tissues). Moreover, the acoustic signature of mature biofilm matrices were evaluated in terms of integrated backscatter (0.0278 - 0.0848 mm(-1) × sr(-1)) and acoustic attenuation (3.9 Np/mm for bound UCAs; 6.58 Np/mm for biofilm alone). Early diagnosis of biofilm matrix formation is a challenge in treating cancer patients with infection-associated biofilms. We report for the first time a combined optical and acoustic evaluation of infectious biofilm matrices. We demonstrate that acoustic impedance of biofilms is similar to the impedance of human tissues, making in vivo imaging and detection of biofilm matrices difficult. The combination of ultrasound and targeted UCAs can be used to enhance biofilm imaging and early detection. Our findings suggest that the combination of targeted UCAs and ultrasound is a novel molecular imaging technique for the detection of biofilms. We show that high-frequency acoustic microscopy provides sufficient spatial resolution for quantification of biofilm mechanoelastic properties.

A geometrically based method for automated radiosurgery planning.

PubMed

Wagner, T H; Yi, T; Meeks, S L; Bova, F J; Brechner, B L; Chen, Y; Buatti, J M; Friedman, W A; Foote, K D; Bouchet, L G

2000-12-01

A geometrically based method of multiple isocenter linear accelerator radiosurgery treatment planning optimization was developed, based on a target's solid shape. Our method uses an edge detection process to determine the optimal sphere packing arrangement with which to cover the planning target. The sphere packing arrangement is converted into a radiosurgery treatment plan by substituting the isocenter locations and collimator sizes for the spheres. This method is demonstrated on a set of 5 irregularly shaped phantom targets, as well as a set of 10 clinical example cases ranging from simple to very complex in planning difficulty. Using a prototype implementation of the method and standard dosimetric radiosurgery treatment planning tools, feasible treatment plans were developed for each target. The treatment plans generated for the phantom targets showed excellent dose conformity and acceptable dose homogeneity within the target volume. The algorithm was able to generate a radiosurgery plan conforming to the Radiation Therapy Oncology Group (RTOG) guidelines on radiosurgery for every clinical and phantom target examined. This automated planning method can serve as a valuable tool to assist treatment planners in rapidly and consistently designing conformal multiple isocenter radiosurgery treatment plans.

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

PubMed

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

2014-09-02

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

Rapid multiplex detection of 10 foodborne pathogens with an up-converting phosphor technology-based 10-channel lateral flow assay

PubMed Central

Zhao, Yong; Wang, Haoran; Zhang, Pingping; Sun, Chongyun; Wang, Xiaochen; Wang, Xinrui; Yang, Ruifu; Wang, Chengbin; Zhou, Lei

2016-01-01

The rapid high-throughput detection of foodborne pathogens is essential in controlling food safety. In this study, a 10-channel up-converting phosphor technology-based lateral flow (TC-UPT-LF) assay was established for the rapid and simultaneous detection of 10 epidemic foodborne pathogens. Ten different single-target UPT-LF strips were developed and integrated into one TC-UPT-LF disc with optimization. Without enrichment the TC-UPT-LF assay had a detection sensitivity of 104 CFU mL−1 or 105 CFU mL−1 for each pathogen, and after sample enrichment it was 10 CFU/0.6 mg. The assay also showed good linearity, allowing quantitative detection, with a linear fitting coefficient of determination (R2) of 0.916–0.998. The 10 detection channels did not cross-react, so multiple targets could be specifically detected. When 279 real food samples were tested, the assay was highly consistent (100%) with culture-based methods. The results for 110 food samples artificially contaminated with single or multiple targets showed a high detection rate (≥80%) for most target bacteria. Overall, the TC-UPT-LF assay allows the rapid, quantitative, and simultaneous detection of 10 kinds of foodborne pathogens within 20 min, and is especially suitable for the rapid detection and surveillance of foodborne pathogens in food and water. PMID:26884128

Rapid multiplex detection of 10 foodborne pathogens with an up-converting phosphor technology-based 10-channel lateral flow assay.

PubMed

Zhao, Yong; Wang, Haoran; Zhang, Pingping; Sun, Chongyun; Wang, Xiaochen; Wang, Xinrui; Yang, Ruifu; Wang, Chengbin; Zhou, Lei

2016-02-17

The rapid high-throughput detection of foodborne pathogens is essential in controlling food safety. In this study, a 10-channel up-converting phosphor technology-based lateral flow (TC-UPT-LF) assay was established for the rapid and simultaneous detection of 10 epidemic foodborne pathogens. Ten different single-target UPT-LF strips were developed and integrated into one TC-UPT-LF disc with optimization. Without enrichment the TC-UPT-LF assay had a detection sensitivity of 10(4) CFU mL(-1) or 10(5) CFU mL(-1) for each pathogen, and after sample enrichment it was 10 CFU/0.6 mg. The assay also showed good linearity, allowing quantitative detection, with a linear fitting coefficient of determination (R(2)) of 0.916-0.998. The 10 detection channels did not cross-react, so multiple targets could be specifically detected. When 279 real food samples were tested, the assay was highly consistent (100%) with culture-based methods. The results for 110 food samples artificially contaminated with single or multiple targets showed a high detection rate (≥ 80%) for most target bacteria. Overall, the TC-UPT-LF assay allows the rapid, quantitative, and simultaneous detection of 10 kinds of foodborne pathogens within 20 min, and is especially suitable for the rapid detection and surveillance of foodborne pathogens in food and water.

Multifunctional and multispectral biosensor devices and methods of use

DOEpatents

Vo-Dinh, Tuan

2004-06-01

An integrated biosensor system for the simultaneously detection of a plurality of different types of targets includes at least one sampling platform, the sampling platform including a plurality of receptors for binding to the targets. The plurality of receptors include at least one protein receptor and at least one nucleic acid receptor. At least one excitation source of electromagnetic radiation at a first frequency is provided for irradiating the receptors, wherein electromagnetic radiation at a second frequency different from the first frequency is emitted in response to irradiating when at least one of the different types of targets are bound to the receptor probes. An integrated circuit detector system having a plurality of detection channels is also provided for detecting electromagnetic radiation at said second frequency, the detection channels each including at least one detector.

An exonuclease III and graphene oxide-aided assay for DNA detection.

PubMed

Peng, Lu; Zhu, Zhi; Chen, Yan; Han, Da; Tan, Weihong

2012-05-15

We have developed a novel DNA assay based on exonuclease III (ExoIII)-induced target recycling and the fluorescence quenching ability of graphene oxide (GO). This assay consists of a linear DNA probe labeled with a fluorophore in the middle. Introduction of target sequence induces the exonuclease III catalyzed probe digestion and generation of single nucleotides. After each cycle of digestion, the target is recycled to realize the amplification. Finally, graphene oxide is added to quench the remaining probes and the signal from the resulting fluorophore labeled single nucleotides is detected. With this approach, a sub-picomolar detection limit can be achieved within 40 min at 37°C. The method was successfully applied to multicolor DNA detection and the analysis of telomerase activity in extracts from cancer cells. Copyright © 2012 Elsevier B.V. All rights reserved.

The detection of objects in a turbid underwater medium using orbital angular momentum (OAM)

NASA Astrophysics Data System (ADS)

Cochenour, Brandon; Rodgers, Lila; Laux, Alan; Mullen, Linda; Morgan, Kaitlyn; Miller, Jerome K.; Johnson, Eric G.

2017-05-01

We present an investigation of the optical property of orbital angular momentum (OAM) for use in the detection of objects obscured by a turbid underwater channel. In our experiment, a target is illuminated by a Gaussian beam. An optical vortex is formed by passing the object-reflected and backscattered light through a diffractive spiral phase plate at the receiver, which allows for the spatial separation of coherent and non-coherent light. This provides a method for discriminating target from environment. Initial laboratory results show that the ballistic target return can be detected 2-3 orders of magnitude below the backscatter clutter level. Furthermore, the detection of this coherent component is accomplished with the use of a complicated optical heterodyning scheme. The results suggest new optical sensing techniques for underwater imaging or LIDAR.

Multispectral image fusion for target detection

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-09-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in an experiment using MSSF against two established methods: Averaging and Principle Components Analysis (PCA), and against its two source bands, visible and infrared. The task that we studied was: target detection in the cluttered environment. MSSF proved superior to the other fusion methods. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

Detection and identification of 700 drugs by multi-target screening with a 3200 Q TRAP LC-MS/MS system and library searching.

PubMed

Dresen, S; Ferreirós, N; Gnann, H; Zimmermann, R; Weinmann, W

2010-04-01

The multi-target screening method described in this work allows the simultaneous detection and identification of 700 drugs and metabolites in biological fluids using a hybrid triple-quadrupole linear ion trap mass spectrometer in a single analytical run. After standardization of the method, the retention times of 700 compounds were determined and transitions for each compound were selected by a "scheduled" survey MRM scan, followed by an information-dependent acquisition using the sensitive enhanced product ion scan of a Q TRAP hybrid instrument. The identification of the compounds in the samples analyzed was accomplished by searching the tandem mass spectrometry (MS/MS) spectra against the library we developed, which contains electrospray ionization-MS/MS spectra of over 1,250 compounds. The multi-target screening method together with the library was included in a software program for routine screening and quantitation to achieve automated acquisition and library searching. With the help of this software application, the time for evaluation and interpretation of the results could be drastically reduced. This new multi-target screening method has been successfully applied for the analysis of postmortem and traffic offense samples as well as proficiency testing, and complements screening with immunoassays, gas chromatography-mass spectrometry, and liquid chromatography-diode-array detection. Other possible applications are analysis in clinical toxicology (for intoxication cases), in psychiatry (antidepressants and other psychoactive drugs), and in forensic toxicology (drugs and driving, workplace drug testing, oral fluid analysis, drug-facilitated sexual assault).

Assessment of Schrodinger Eigenmaps for target detection

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

Study on the influence factors of camouflage target polarization detection

NASA Astrophysics Data System (ADS)

Huang, Yanhua; Chen, Lei; Li, Xia; Wu, Wenyuan

2016-10-01

The degree of linear polarization (DOLP) expressions at any polarizer direction (PD) was deduced based on the Stokes vector and Mueller matrix. The outdoors experiments were carried out to demonstrate the expressions. This paper mainly explored the DOLP-image-Contrast (DOLPC) between the target image and the background image, and the PD and RGB waveband that be considered two important influence factors were studied for camouflage target polarization detection. It was found that the DOLPC of target and background was obviously higher than intensity image. When setting the reference direction that polarizer was perpendicular to the incident face, the DOLP image of interval angle 60 degree between PD and reference direction had relatively high DOLPC, the interval angle 45 degree was the second, and the interval angle 35 degree was the third. The outdoors polarization detection experiment of controlling waveband showed that the DOLPC results was significantly different to use 650nm, 550nm and 450nm waveband, and the polarization detection performance by using 650nm band was an optimization method.

Finding the joker among the maize endogenous reference genes for genetically modified organism (GMO) detection.

PubMed

Paternò, Annalisa; Marchesi, Ugo; Gatto, Francesco; Verginelli, Daniela; Quarchioni, Cinzia; Fusco, Cristiana; Zepparoni, Alessia; Amaddeo, Demetrio; Ciabatti, Ilaria

2009-12-09

The comparison of five real-time polymerase chain reaction (PCR) methods targeted at maize ( Zea mays ) endogenous sequences is reported. PCR targets were the alcohol dehydrogenase (adh) gene for three methods and high-mobility group (hmg) gene for the other two. The five real-time PCR methods have been checked under repeatability conditions at several dilution levels on both pooled DNA template from several genetically modified (GM) maize certified reference materials (CRMs) and single CRM DNA extracts. Slopes and R(2) coefficients of all of the curves obtained from the adopted regression model were compared within the same method and among all of the five methods, and the limit of detection and limit of quantitation were analyzed for each PCR system. Furthermore, method equivalency was evaluated on the basis of the ability to estimate the target haploid genome copy number at each concentration level. Results indicated that, among the five methods tested, one of the hmg-targeted PCR systems can be considered equivalent to the others but shows the best regression parameters and a higher repeteability along the dilution range. Thereby, it is proposed as a valid module to be coupled to different event-specific real-time PCR for maize genetically modified organism (GMO) quantitation. The resulting practicability improvement on the analytical control of GMOs is discussed.

Simultaneous Detection of Yersinia Enterocolitica and Listeria Monocytogenes in Foodstuffs by Capillary Electrophoresis and Microchip Capillary Electrophoresis Laser-Induced Fluorescence Detector.

PubMed

Li, Yongru; Su, Hongwei; Lan, Yajia

2018-05-29

Background: Food safety is one of the most important public health problems in the world,and pathogenic bacterium is a major factor causing serious foodborne diseases. Objective: Two methods of duplex PCR combined with capillary electrophoresis laser-induced fluorescence detector (CE-LIF) and microchip capillary electrophoresis laser-induced fluorescence detector (MCE-LIF) have been developed for the simultaneous detection of Yersinia enterocolitica and Listeria monocytogenes in various foods. The specific conservative sequences of these two bacteria were amplified. Methods: After labelled with nucleic acid dye SYBR Gold and SYBR Orange, the PCR products were analyzed by CE-LIF and MCE-LIF, respectively. Under the optimal conditions, the detection of PCR products of the target bacteria was achieved in less than 15 min by CE-LIF and within 6 min by MCE-LIF. Results: The alignment analysis demonstrated that the PCR products had good agreement with the sequences published in GenBank. The CE-LIF method could detect 10 CFU/mL Y. enterocolitica and L. monocytogenes , and the MCE-LIF method could detect 100 CFU/mL Y. enterocolitica and L. monocytogenes . The intraday precisions of migration time and peak area of DNA markers and PCR products were in the range of 1.13 to 1.18% and 1.60 to 6.29%, respectively, for CE-LIF and 1.18 to 1.48% and 2.85 to 4.06%, respectively, for MCE-LIF. Conclusions : The proposed methods could be applied to target bacterial detection infood samples rapidly, sensitively, and specifically. Highlights : Two new methods based on CE and MCE have been developed for the simultaneous detection of Y. enterocolitica and L. monocytogenes in foodstuffs, and they can detect the bacteria directly without any enrichment because of their high sensitivity.

Nonenzymatic catalytic signal amplification for nucleic acid hybridization assays

NASA Technical Reports Server (NTRS)

Fan, Wenhong (Inventor); Han, Jie (Inventor); Cassell, Alan M. (Inventor)

2006-01-01

Devices, methods, and kits for amplifying the signal from hybridization reactions between nucleic acid probes and their cognate targets are presented. The devices provide partially-duplexed, immobilized probe complexes, spatially separate from and separately addressable from immobilized docking strands. Cognate target acts catalytically to transfer probe from the site of probe complex immobilization to the site of immobilized docking strand, generating a detectable signal. The methods and kits of the present invention may be used to identify the presence of cognate target in a fluid sample.

Smart Plasmonic Glucose Nanosensors as Generic Theranostic Agents for Targeting-Free Cancer Cell Screening and Killing.

PubMed

Chen, Limei; Li, Haijuan; He, Haili; Wu, Haoxi; Jin, Yongdong

2015-07-07

Fast and accurate identification of cancer cells from healthy normal cells in a simple, generic way is very crucial for early cancer detection and treatment. Although functional nanoparticles, like fluorescent quantum dots and plasmonic Au nanoparticles (NPs), have been successfully applied for cancer cell imaging and photothermal therapy, they suffer from the main drawback of needing time-consuming targeting preparation for specific cancer cell detection and selective ablation. The lack of a generic and effective method therefore limits their potential high-throughput cancer cell preliminary screening and theranostic applications. We report herein a generic in vitro method for fast, targeting-free (avoiding time-consuming preparations of targeting moiety for specific cancer cells) visual screening and selective killing of cancer cells from normal cells, by using glucose-responsive/-sensitive glucose oxidase-modified Ag/Au nanoshells (Ag/Au-GOx NSs) as a smart plasmonic theranostic agent. The method is generic to some extent since it is based on the distinct localized surface plasmon resonance (LSPR) responses (and colors) of the smart nanoprobe with cancer cells (typically have a higher glucose uptake level) and normal cells.

Linear high-boost fusion of Stokes vector imagery for effective discrimination and recognition of real targets in the presence of multiple identical decoys

NASA Astrophysics Data System (ADS)

El-Saba, Aed; Sakla, Wesam A.

2010-04-01

Recently, the use of imaging polarimetry has received considerable attention for use in automatic target recognition (ATR) applications. In military remote sensing applications, there is a great demand for sensors that are capable of discriminating between real targets and decoys. Accurate discrimination of decoys from real targets is a challenging task and often requires the fusion of various sensor modalities that operate simultaneously. In this paper, we use a simple linear fusion technique known as the high-boost fusion method for effective discrimination of real targets in the presence of multiple decoys. The HBF assigns more weight to the polarization-based imagery in forming the final fused image that is used for detection. We have captured both intensity and polarization-based imagery from an experimental laboratory arrangement containing a mixture of sand/dirt, rocks, vegetation, and other objects for the purpose of simulating scenery that would be acquired in a remote sensing military application. A target object and three decoys that are identical in physical appearance (shape, surface structure and color) and different in material composition have also been placed in the scene. We use the wavelet-filter joint transform correlation (WFJTC) technique to perform detection between input scenery and the target object. Our results show that use of the HBF method increases the correlation performance metrics associated with the WFJTC-based detection process when compared to using either the traditional intensity or polarization-based images.

Spectral Target Detection using Schroedinger Eigenmaps

NASA Astrophysics Data System (ADS)

Dorado-Munoz, Leidy P.

Applications of optical remote sensing processes include environmental monitoring, military monitoring, meteorology, mapping, surveillance, etc. Many of these tasks include the detection of specific objects or materials, usually few or small, which are surrounded by other materials that clutter the scene and hide the relevant information. This target detection process has been boosted lately by the use of hyperspectral imagery (HSI) since its high spectral dimension provides more detailed spectral information that is desirable in data exploitation. Typical spectral target detectors rely on statistical or geometric models to characterize the spectral variability of the data. However, in many cases these parametric models do not fit well HSI data that impacts the detection performance. On the other hand, non-linear transformation methods, mainly based on manifold learning algorithms, have shown a potential use in HSI transformation, dimensionality reduction and classification. In target detection, non-linear transformation algorithms are used as preprocessing techniques that transform the data to a more suitable lower dimensional space, where the statistical or geometric detectors are applied. One of these non-linear manifold methods is the Schroedinger Eigenmaps (SE) algorithm that has been introduced as a technique for semi-supervised classification. The core tool of the SE algorithm is the Schroedinger operator that includes a potential term that encodes prior information about the materials present in a scene, and enables the embedding to be steered in some convenient directions in order to cluster similar pixels together. A completely novel target detection methodology based on SE algorithm is proposed for the first time in this thesis. The proposed methodology does not just include the transformation of the data to a lower dimensional space but also includes the definition of a detector that capitalizes on the theory behind SE. The fact that target pixels and those similar pixels are clustered in a predictable region of the low-dimensional representation is used to define a decision rule that allows one to identify target pixels over the rest of pixels in a given image. In addition, a knowledge propagation scheme is used to combine spectral and spatial information as a means to propagate the "potential constraints" to nearby points. The propagation scheme is introduced to reinforce weak connections and improve the separability between most of the target pixels and the background. Experiments using different HSI data sets are carried out in order to test the proposed methodology. The assessment is performed from a quantitative and qualitative point of view, and by comparing the SE-based methodology against two other detection methodologies that use linear/non-linear algorithms as transformations and the well-known Adaptive Coherence/Cosine Estimator (ACE) detector. Overall results show that the SE-based detector outperforms the other two detection methodologies, which indicates the usefulness of the SE transformation in spectral target detection problems.

Covert laser remote sensing and vibrometry

NASA Technical Reports Server (NTRS)

Maleki, Lutfollah (Inventor); Yu, Nan (Inventor); Matsko, Andrey B. (Inventor); Savchenkov, Anatoliy (Inventor)

2012-01-01

Designs of single-beam laser vibrometry systems and methods. For example, a method for detecting vibrations of a target based on optical sensing is provided to include operating a laser to produce a laser probe beam at a laser frequency and modulated at a modulation frequency onto a target; collecting light at or near the laser to collect light from the target while the target is being illuminated by the laser probe beam through an optical receiver aperture; using a narrow-band optical filter centered at the laser frequency to filter light collected from the optical receiver aperture to transmit light at the laser frequency while blocking light at other frequencies; using an optical detector to convert filtered light from the narrow-band optical filter to produce a receiver electrical signal; using a lock-in amplifier to detect and amplify the receiver electrical signal at the modulation frequency while rejecting signal components at other frequencies to produce an amplified receiver electrical signal; processing the amplified receiver electrical signal to extract information on vibrations of the target carried by reflected laser probe beam in the collected light; and controlling optical power of the laser probe beam at the target to follow optical power of background illumination at the target.

Comparing efficiency of American Fisheries Society standard snorkeling techniques to environmental DNA sampling techniques

USGS Publications Warehouse

Ulibarri, Roy M.; Bonar, Scott A.; Rees, Christopher B.; Amberg, Jon J.; Ladell, Bridget; Jackson, Craig

2017-01-01

Analysis of environmental DNA (eDNA) is an emerging technique used to detect aquatic species through water sampling and the extraction of biological material for amplification. Our study compared the efficacy of eDNA methodology to American Fisheries Society (AFS) standard snorkeling surveys with regard to detecting the presence of rare fish species. Knowing which method is more efficient at detecting target species will help managers to determine the best way to sample when both traditional sampling methods and eDNA sampling are available. Our study site included three Navajo Nation streams that contained Navajo Nation Genetic Subunit Bluehead Suckers Catostomus discobolus and Zuni Bluehead Suckers C. discobolus yarrowi. We first divided the entire wetted area of streams into consecutive 100-m reaches and then systematically selected 10 reaches/stream for snorkel and eDNA surveys. Surface water samples were taken in 10-m sections within each 100-m reach, while fish presence was noted via snorkeling in each 10-m section. Quantitative PCR was run on each individual water sample in quadruplicate to test for the presence or absence of the target species. With eDNA sampling techniques, we were able to positively detect both species in two out of the three streams. Snorkeling resulted in positive detection of both species in all three streams. In streams where the target species were detected with eDNA sampling, snorkeling detected fish at 11–29 sites/stream, whereas eDNA detected fish at 3–12 sites/stream. Our results suggest that AFS standard snorkeling is more effective than eDNA for detecting target fish species. To improve our eDNA procedures, the amount of water collected and tested should be increased. Additionally, filtering water on-site may improve eDNA techniques for detecting fish. Future research should focus on standardization of eDNA sampling to provide a widely operational sampling tool.

Breast cancer evaluation by fluorescent dot detection using combined mathematical morphology and multifractal techniques

PubMed Central

2011-01-01

Background Fluorescence in situ hybridization (FISH) is very accurate method for measuring HER2 gene copies, as a sign of potential breast cancer. This method requires small tissue samples, and has a high sensitivity to detect abnormalities from a histological section. By using multiple colors, this method allows the detection of multiple targets simultaneously. The target parts in the cells become visible as colored dots. The HER-2 probes are visible as orange stained spots under a fluorescent microscope while probes for centromere 17 (CEP-17), the chromosome on which the gene HER-2/neu is located, are visible as green spots. Methods The conventional analysis involves the scoring of the ratio of HER-2/neu over CEP 17 dots within each cell nucleus and then averaging the scores for a number of 60 cells. A ratio of 2.0 of HER-2/neu to CEP 17 copy number denotes amplification. Several methods have been proposed for the detection and automated evaluation (dot counting) of FISH signals. In this paper the combined method based on the mathematical morphology (MM) and inverse multifractal (IMF) analysis is suggested. Similar method was applied recently in detection of microcalcifications in digital mammograms, and was very successful. Results The combined MM using top-hat and bottom-hat filters, and the IMF method was applied to FISH images from Molecular Biology Lab, Department of Pathology, Wielkoposka Cancer Center, Poznan. Initial results indicate that this method can be applied to FISH images for the evaluation of HER2/neu status. Conclusions Mathematical morphology and multifractal approach are used for colored dot detection and counting in FISH images. Initial results derived on clinical cases are promising. Note that the overlapping of colored dots, particularly red/orange dots, needs additional improvements in post-processing. PMID:21489192

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

The development of a super-fine-grained nuclear emulsion

NASA Astrophysics Data System (ADS)

Asada, Takashi; Naka, Tatsuhiro; Kuwabara, Ken-ichi; Yoshimoto, Masahiro

2017-06-01

A nuclear emulsion with micronized crystals is required for the tracking detection of submicron ionizing particles, which are one of the targets of dark-matter detection and other techniques. We found that a new production method, called the PVA—gelatin mixing method (PGMM), could effectively control crystal size from 20 nm to 50 nm. We called the two types of emulsion produced with the new method the nano imaging tracker and the ultra-nano imaging tracker. Their composition and spatial resolution were measured, and the results indicate that these emulsions detect extremely short tracks.

A novel approach to simulate chest wall micro-motion for bio-radar life detection purpose

NASA Astrophysics Data System (ADS)

An, Qiang; Li, Zhao; Liang, Fulai; Chen, Fuming; Wang, Jianqi

2016-10-01

Volunteers are often recruited to serve as the detection targets during the research process of bio-radar life detection technology, in which the experiment results are highly susceptible to the physical status of different individuals (shape, posture, etc.). In order to objectively evaluate the radar system performance and life detection algorithms, a standard detection target is urgently needed. The paper first proposed a parameter quantitatively controllable system to simulate the chest wall micro-motion caused mainly by breathing and heart beating. Then, the paper continued to analyze the material and size selection of the scattering body mounted on the simulation system from the perspective of back scattering energy. The computational electromagnetic method was employed to determine the exact scattering body. Finally, on-site experiments were carried out to verify the reliability of the simulation platform utilizing an IR UWB bioradar. Experimental result shows that the proposed system can simulate a real human target from three aspects: respiration frequency, amplitude and body surface scattering energy. Thus, it can be utilized as a substitute for a human target in radar based non-contact life detection research in various scenarios.

Detection of coliform bacteria and Escherichia coli by multiplex polymerase chain reaction: comparison with defined substrate and plating methods for water quality monitoring.

PubMed Central

Bej, A K; McCarty, S C; Atlas, R M

1991-01-01

Multiplex polymerase chain reaction (PCR) and gene probe detection of target lacZ and uidA genes were used to detect total coliform bacteria and Escherichia coli, respectively, for determining water quality. In tests of environmental water samples, the lacZ PCR method gave results statistically equivalent to those of the plate count and defined substrate methods accepted by the U.S. Environmental Protection Agency for water quality monitoring and the uidA PCR method was more sensitive than 4-methylumbelliferyl-beta-D-glucuronide-based defined substrate tests for specific detection of E. coli. Images PMID:1768116

Transrectal real-time tissue elastography targeted biopsy coupled with peak strain index improves the detection of clinically important prostate cancer.

PubMed

Ma, Qi; Yang, Dong-Rong; Xue, Bo-Xin; Wang, Cheng; Chen, Han-Bin; Dong, Yun; Wang, Cai-Shan; Shan, Yu-Xi

2017-07-01

The focus of the present study was to evaluate transrectal real-time tissue elastography (RTE)-targeted two-core biopsy coupled with peak strain index for the detection of prostate cancer (PCa) and to compare this method with 10-core systematic biopsy. A total of 141 patients were enrolled for evaluation. The diagnostic value of peak strain index was assessed using a receiver operating characteristic curve. The cancer detection rates of the two approaches and corresponding positive cores and Gleason score were compared. The cancer detection rate per core in the RTE-targeted biopsy (44%) was higher compared with that in systematic biopsy (30%). The peak strain index value of PCa was higher compared with that of the benign lesion. PCa was detected with the highest sensitivity (87.5%) and specificity (85.5%) using the threshold value of a peak strain index of ≥5.97 with an area under the curve value of 0.95. When the Gleason score was ≥7, RTE-targeted biopsy coupled with peak strain index detected 95.6% of PCa cases, but 84.4% were detected using systematic biopsy. Peak strain index as a quantitative parameter may improve the differentiation of PCa from benign lesions in the prostate peripheral zone. Transrectal RTE-targeted biopsy coupled with peak strain index may enhance the detection of clinically significant PCa, particularly when combined with systematic biopsy.

Emerging optical methods for surveillance of Barrett's oesophagus.

PubMed

Sturm, Matthew B; Wang, Thomas D

2015-11-01

The rapid rise in incidence of oesophageal adenocarcinoma has motivated the need for improved methods for surveillance of Barrett's oesophagus. Early neoplasia is flat in morphology and patchy in distribution and is difficult to detect with conventional white light endoscopy (WLE). Light offers numerous advantages for rapidly visualising the oesophagus, and advanced optical methods are being developed for wide-field and cross-sectional imaging to guide tissue biopsy and stage early neoplasia, respectively. We review key features of these promising methods and address their potential to improve detection of Barrett's neoplasia. The clinical performance of key advanced imaging technologies is reviewed, including (1) wide-field methods, such as high-definition WLE, chromoendoscopy, narrow-band imaging, autofluorescence and trimodal imaging and (2) cross-sectional techniques, such as optical coherence tomography, optical frequency domain imaging and confocal laser endomicroscopy. Some of these instruments are being adapted for molecular imaging to detect specific biological targets that are overexpressed in Barrett's neoplasia. Gene expression profiles are being used to identify early targets that appear before morphological changes can be visualised with white light. These targets are detected in vivo using exogenous probes, such as lectins, peptides, antibodies, affibodies and activatable enzymes that are labelled with fluorescence dyes to produce high contrast images. This emerging approach has potential to provide a 'red flag' to identify regions of premalignant mucosa, outline disease margins and guide therapy based on the underlying molecular mechanisms of cancer progression. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

A novel dNTP-limited PCR and HRM assay to detect Williams-Beuren syndrome.

PubMed

Zhang, Lichen; Zhang, Xiaoqing; You, Guoling; Yu, Yongguo; Fu, Qihua

2018-06-01

Williams-Beuren syndrome (WBS) is caused by a microdeletion of chromosome arm 7q11.23. A rapid and inexpensive genotyping method to detect microdeletion on 7q11.23 needs to be developed for the diagnosis of WBS. This study describes the development of a new type of molecular diagnosis method to detect microdeletion on 7q11.23 based upon high-resolution melting (HRM). Four genes on 7q11.23 were selected as the target genes for the deletion genotyping. dNTP-limited duplex PCR was used to amplify the reference gene, CFTR, and one of the four genes respectively on 7q11.23. An HRM assay was performed on the PCR products, and the height ratio of the negative derivative peaks between the target gene and reference gene was employed to analyze the copy number variation of the target region. A new genotyping method for detecting 7q11.23 deletion was developed based upon dNTP-limited PCR and HRM, which cost only 96 min. Samples from 15 WBS patients and 12 healthy individuals were genotyped by this method in a blinded fashion, and the sensitivity and specificity was 100% (95% CI, 0.80-1, and 95% CI, 0.75-1, respectively) which was proved by CytoScan HD array. The HRM assay we developed is an rapid, inexpensive, and highly accurate method for genotyping 7q11.23 deletion. It is potentially useful in the clinical diagnosis of WBS. Copyright © 2018 Elsevier B.V. All rights reserved.

Label-free detection of circulating melanoma cells by in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Wang, Xiaoling; Yang, Ping; Liu, Rongrong; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Gao, Wenyuan; Tang, Shuo; Wei, Xunbin

2016-03-01

Melanoma is a malignant tumor of melanocytes. Melanoma cells have high light absorption due to melanin highly contained in melanoma cells. This property is employed for the detection of circulating melanoma cell by in vivo photoacoustic flow cytometry (PAFC), which is based on photoacoustic effect. Compared to in vivo flow cytometry based on fluorescence, PAFC can employ high melanin content of melanoma cells as endogenous biomarkers to detect circulating melanoma cells in vivo. We have developed in vitro experiments to prove the ability of PAFC system of detecting photoacoustic signals from melanoma cells. For in vivo experiments, we have constructed a model of melanoma tumor bearing mice by inoculating highly metastatic murine melanoma cancer cells, B16F10 with subcutaneous injection. PA signals are detected in the blood vessels of mouse ears in vivo. The raw signal detected from target cells often contains some noise caused by electronic devices, such as background noise and thermal noise. We choose the Wavelet denoising method to effectively distinguish the target signal from background noise. Processing in time domain and frequency domain would be combined to analyze the signal after denoising. This algorithm contains time domain filter and frequency transformation. The frequency spectrum image of the signal contains distinctive features that can be used to analyze the property of target cells or particles. The processing methods have a great potential for analyzing signals accurately and rapidly. By counting circulating melanoma cells termly, we obtain the number variation of circulating melanoma cells as melanoma metastasized. Those results show that PAFC is a noninvasive and label-free method to detect melanoma metastases in blood or lymph circulation.

Method modification of the Legipid® Legionella fast detection test kit.

PubMed

Albalat, Guillermo Rodríguez; Broch, Begoña Bedrina; Bono, Marisa Jiménez

2014-01-01

Legipid(®) Legionella Fast Detection is a test based on combined magnetic immunocapture and enzyme-immunoassay (CEIA) for the detection of Legionella in water. The test is based on the use of anti-Legionella antibodies immobilized on magnetic microspheres. Target microorganism is preconcentrated by filtration. Immunomagnetic analysis is applied on these preconcentrated water samples in a final test portion of 9 mL. The test kit was certified by the AOAC Research Institute as Performance Tested Method(SM) (PTM) No. 111101 in a PTM validation which certifies the performance claims of the test method in comparison to the ISO reference method 11731-1998 and the revision 11731-2004 "Water Quality: Detection and Enumeration of Legionella pneumophila" in potable water, industrial water, and waste water. The modification of this test kit has been approved. The modification includes increasing the target analyte from L. pneumophila to Legionella species and adding an optical reader to the test method. In this study, 71 strains of Legionella spp. other than L. pneumophila were tested to determine its reactivity with the kit based on CEIA. All the strains of Legionella spp. tested by the CEIA test were confirmed positive by reference standard method ISO 11731. This test (PTM 111101) has been modified to include a final optical reading. A methods comparison study was conducted to demonstrate the equivalence of this modification to the reference culture method. Two water matrixes were analyzed. Results show no statistically detectable difference between the test method and the reference culture method for the enumeration of Legionella spp. The relative level of detection was 93 CFU/volume examined (LOD50). For optical reading, the LOD was 40 CFU/volume examined and the LOQ was 60 CFU/volume examined. Results showed that the test Legipid Legionella Fast Detection is equivalent to the reference culture method for the enumeration of Legionella spp.

Glycoprotein Disease Markers and Single Protein-omics*

PubMed Central

Chandler, Kevin; Goldman, Radoslav

2013-01-01

Glycoproteins are well represented among biomarkers for inflammatory and cancer diseases. Secreted and membrane-associated glycoproteins make excellent targets for noninvasive detection. In this review, we discuss clinically applicable markers of cancer diseases and methods for their analysis. High throughput discovery continues to supply marker candidates with unusual glycan structures, altered glycoprotein abundance, or distribution of site-specific glycoforms. Improved analytical methods are needed to unlock the potential of these discoveries in validated clinical assays. A new generation of targeted quantitative assays is expected to advance the use of glycoproteins in early detection of diseases, molecular disease classification, and monitoring of therapeutic interventions. PMID:23399550

Detection of nucleic acid sequences by invader-directed cleavage

DOEpatents

Brow, Mary Ann D.; Hall, Jeff Steven Grotelueschen; Lyamichev, Victor; Olive, David Michael; Prudent, James Robert

1999-01-01

The present invention relates to means for the detection and characterization of nucleic acid sequences, as well as variations in nucleic acid sequences. The present invention also relates to methods for forming a nucleic acid cleavage structure on a target sequence and cleaving the nucleic acid cleavage structure in a site-specific manner. The 5' nuclease activity of a variety of enzymes is used to cleave the target-dependent cleavage structure, thereby indicating the presence of specific nucleic acid sequences or specific variations thereof. The present invention further relates to methods and devices for the separation of nucleic acid molecules based by charge.

Photocleavable DNA barcode-antibody conjugates allow sensitive and multiplexed protein analysis in single cells.

PubMed

Agasti, Sarit S; Liong, Monty; Peterson, Vanessa M; Lee, Hakho; Weissleder, Ralph

2012-11-14

DNA barcoding is an attractive technology, as it allows sensitive and multiplexed target analysis. However, DNA barcoding of cellular proteins remains challenging, primarily because barcode amplification and readout techniques are often incompatible with the cellular microenvironment. Here we describe the development and validation of a photocleavable DNA barcode-antibody conjugate method for rapid, quantitative, and multiplexed detection of proteins in single live cells. Following target binding, this method allows DNA barcodes to be photoreleased in solution, enabling easy isolation, amplification, and readout. As a proof of principle, we demonstrate sensitive and multiplexed detection of protein biomarkers in a variety of cancer cells.

Developing a fluorescence-coupled capillary electrophoresis based method to probe interactions between QDs and colorectal cancer targeting peptides.

PubMed

Liu, Feifei; Wang, Jianhao; Yang, Li; Liu, Li; Ding, Shumin; Fu, Minli; Deng, Linhong; Gao, Li-Qian

2016-08-01

As is well known, quantum dots (QDs) have become valuable probes for cancer imaging. In particular, QD-labeled targeting peptides are capable of identifying cancer or tumors cells. A new colorectal cancer targeting peptide, cyclo(1, 9)-CTPSPFSHC, has strong targeting ability and also shows great potential in the identification and treatment of colon cancer. Herein, we synthesized a dual functional polypeptide, cyclo(1, 9)-CTPSPFSHCD2 G2 DP9 G3 H6 (H6 -TCP), to investigate its interaction with QDs inside the capillary. Fluorescence-coupled CE was adopted and applied to characterize the self-assembly of H6 -TCP onto QDs. It was indicated that the formation of the assembly was affected by H6 -TCP/QD molar ratio and sampling time. This novel in-capillary assay greatly reduced the sample consumption and the detection time, which was beneficial for the environment. It is expected that this kind of detection method could find more applications to provide more useful information for cancer diagnosis and detection of harm and hazardous substances/organisms in the environment in the future. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detection of organic compounds with whole-cell bioluminescent bioassays.

PubMed

Xu, Tingting; Close, Dan; Smartt, Abby; Ripp, Steven; Sayler, Gary

2014-01-01

Natural and manmade organic chemicals are widely deposited across a diverse range of ecosystems including air, surface water, groundwater, wastewater, soil, sediment, and marine environments. Some organic compounds, despite their industrial values, are toxic to living organisms and pose significant health risks to humans and wildlife. Detection and monitoring of these organic pollutants in environmental matrices therefore is of great interest and need for remediation and health risk assessment. Although these detections have traditionally been performed using analytical chemical approaches that offer highly sensitive and specific identification of target compounds, these methods require specialized equipment and trained operators, and fail to describe potential bioavailable effects on living organisms. Alternatively, the integration of bioluminescent systems into whole-cell bioreporters presents a new capacity for organic compound detection. These bioreporters are constructed by incorporating reporter genes into catabolic or signaling pathways that are present within living cells and emit a bioluminescent signal that can be detected upon exposure to target chemicals. Although relatively less specific compared to analytical methods, bioluminescent bioassays are more cost-effective, more rapid, can be scaled to higher throughput, and can be designed to report not only the presence but also the bioavailability of target substances. This chapter reviews available bacterial and eukaryotic whole-cell bioreporters for sensing organic pollutants and their applications in a variety of sample matrices.

Clustered Regularly Interspaced Short Palindromic Repeats/Cas9 Triggered Isothermal Amplification for Site-Specific Nucleic Acid Detection.

PubMed

Huang, Mengqi; Zhou, Xiaoming; Wang, Huiying; Xing, Da

2018-02-06

A novel CRISPR/Cas9 triggered isothermal exponential amplification reaction (CAS-EXPAR) strategy based on CRISPR/Cas9 cleavage and nicking endonuclease (NEase) mediated nucleic acids amplification was developed for rapid and site-specific nucleic acid detection. CAS-EXPAR was primed by the target DNA fragment produced by cleavage of CRISPR/Cas9, and the amplification reaction performed cyclically to generate a large number of DNA replicates which were detected using a real-time fluorescence monitoring method. This strategy that combines the advantages of CRISPR/Cas9 and exponential amplification showed high specificity as well as rapid amplification kinetics. Unlike conventional nucleic acids amplification reactions, CAS-EXPAR does not require exogenous primers, which often cause target-independent amplification. Instead, primers are first generated by Cas9/sgRNA directed site-specific cleavage of target and accumulated during the reaction. It was demonstrated this strategy gave a detection limit of 0.82 amol and showed excellent specificity in discriminating single-base mismatch. Moreover, the applicability of this method to detect DNA methylation and L. monocytogenes total RNA was also verified. Therefore, CAS-EXPAR may provide a new paradigm for efficient nucleic acid amplification and hold the potential for molecular diagnostic applications.

Camouflaged target detection based on polarized spectral features

NASA Astrophysics Data System (ADS)

Tan, Jian; Zhang, Junping; Zou, Bin

2016-05-01

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

Statistical methods for identifying and bounding a UXO target area or minefield

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

McKinstry, Craig A.; Pulsipher, Brent A.; Gilbert, Richard O.

2003-09-18

The sampling unit for minefield or UXO area characterization is typically represented by a geographical block or transect swath that lends itself to characterization by geophysical instrumentation such as mobile sensor arrays. New spatially based statistical survey methods and tools, more appropriate for these unique sampling units have been developed and implemented at PNNL (Visual Sample Plan software, ver. 2.0) with support from the US Department of Defense. Though originally developed to support UXO detection and removal efforts, these tools may also be used in current form or adapted to support demining efforts and aid in the development of newmore » sensors and detection technologies by explicitly incorporating both sampling and detection error in performance assessments. These tools may be used to (1) determine transect designs for detecting and bounding target areas of critical size, shape, and density of detectable items of interest with a specified confidence probability, (2) evaluate the probability that target areas of a specified size, shape and density have not been missed by a systematic or meandering transect survey, and (3) support post-removal verification by calculating the number of transects required to achieve a specified confidence probability that no UXO or mines have been missed.« less