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.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2006-05-01

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

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.

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

PubMed Central

Kim, Sungho

2015-01-01

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

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.

Infrared moving small target detection based on saliency extraction and image sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Xiaomin; Ren, Kan; Gao, Jin; Li, Chaowei; Gu, Guohua; Wan, Minjie

2016-10-01

Moving small target detection in infrared image is a crucial technique of infrared search and tracking system. This paper present a novel small target detection technique based on frequency-domain saliency extraction and image sparse representation. First, we exploit the features of Fourier spectrum image and magnitude spectrum of Fourier transform to make a rough extract of saliency regions and use a threshold segmentation system to classify the regions which look salient from the background, which gives us a binary image as result. Second, a new patch-image model and over-complete dictionary were introduced to the detection system, then the infrared small target detection was converted into a problem solving and optimization process of patch-image information reconstruction based on sparse representation. More specifically, the test image and binary image can be decomposed into some image patches follow certain rules. We select the target potential area according to the binary patch-image which contains salient region information, then exploit the over-complete infrared small target dictionary to reconstruct the test image blocks which may contain targets. The coefficients of target image patch satisfy sparse features. Finally, for image sequence, Euclidean distance was used to reduce false alarm ratio and increase the detection accuracy of moving small targets in infrared images due to the target position correlation between frames.

Statistical-Mechanics-Inspired Optimization of Sensor Field Configuration for Detection of Mobile Targets (PREPRINT)

DTIC Science & Technology

2010-11-01

pected target motion. Along this line, Wettergren [5] analyzed the performance of the track - before - detect schemes for the sensor networks. Furthermore...dressed by Baumgartner and Ferrari [11] for the reorganization of the sensor field to achieve the maximum coverage. The track - before - detect -based optimal...confirming a target. In accordance with the track - before - detect paradigm [4], a moving target is detected if the kd (typically kd = 3 or 4) sensors detect

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).

Synthetic aperture radar target detection, feature extraction, and image formation techniques

NASA Technical Reports Server (NTRS)

Li, Jian

1994-01-01

This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

Remote sensing based on hyperspectral data analysis

NASA Astrophysics Data System (ADS)

Sharifahmadian, Ershad

In remote sensing, accurate identification of far objects, especially concealed objects is difficult. In this study, to improve object detection from a distance, the hyperspecral imaging and wideband technology are employed with the emphasis on wideband radar. As the wideband data includes a broad range of frequencies, it can reveal information about both the surface of the object and its content. Two main contributions are made in this study: 1) Developing concept of return loss for target detection: Unlike typical radar detection methods which uses radar cross section to detect an object, it is possible to enhance the process of detection and identification of concealed targets using the wideband radar based on the electromagnetic characteristics --conductivity, permeability, permittivity, and return loss-- of materials. During the identification process, collected wideband data is evaluated with information from wideband signature library which has already been built. In fact, several classes (e.g. metal, wood, etc.) and subclasses (ex. metals with high conductivity) have been defined based on their electromagnetic characteristics. Materials in a scene are then classified based on these classes. As an example, materials with high electrical conductivity can be conveniently detected. In fact, increasing relative conductivity leads to a reduction in the return loss. Therefore, metals with high conductivity (ex. copper) shows stronger radar reflections compared with metals with low conductivity (ex. stainless steel). Thus, it is possible to appropriately discriminate copper from stainless steel. 2) Target recognition techniques: To detect and identify targets, several techniques have been proposed, in particular the Multi-Spectral Wideband Radar Image (MSWRI) which is able to localize and identify concealed targets. The MSWRI is based on the theory of robust capon beamformer. During identification process, information from wideband signature library is utilized. The WB signature library includes such parameters as conductivity, permeability, permittivity, and return loss at different frequencies for possible materials related to a target. In the MSWRI approach, identification procedure is performed by calculating the RLs at different selected frequencies. Based on similarity of the calculated RLs and RL from WB signature library, targets are detected and identified. Based on the simulation and experimental results, it is concluded that the MSWRI technique is a promising approach for standoff target detection.

Object detection in natural scenes: Independent effects of spatial and category-based attention.

PubMed

Stein, Timo; Peelen, Marius V

2017-04-01

Humans are remarkably efficient in detecting highly familiar object categories in natural scenes, with evidence suggesting that such object detection can be performed in the (near) absence of attention. Here we systematically explored the influences of both spatial attention and category-based attention on the accuracy of object detection in natural scenes. Manipulating both types of attention additionally allowed for addressing how these factors interact: whether the requirement for spatial attention depends on the extent to which observers are prepared to detect a specific object category-that is, on category-based attention. The results showed that the detection of targets from one category (animals or vehicles) was better than the detection of targets from two categories (animals and vehicles), demonstrating the beneficial effect of category-based attention. This effect did not depend on the semantic congruency of the target object and the background scene, indicating that observers attended to visual features diagnostic of the foreground target objects from the cued category. Importantly, in three experiments the detection of objects in scenes presented in the periphery was significantly impaired when observers simultaneously performed an attentionally demanding task at fixation, showing that spatial attention affects natural scene perception. In all experiments, the effects of category-based attention and spatial attention on object detection performance were additive rather than interactive. Finally, neither spatial nor category-based attention influenced metacognitive ability for object detection performance. These findings demonstrate that efficient object detection in natural scenes is independently facilitated by spatial and category-based attention.

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.

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.

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.

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 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.

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

NASA Astrophysics Data System (ADS)

Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

2017-11-01

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

Space moving target detection using time domain feature

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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.

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.

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.

Infrared small target detection based on directional zero-crossing measure

NASA Astrophysics Data System (ADS)

Zhang, Xiangyue; Ding, Qinghai; Luo, Haibo; Hui, Bin; Chang, Zheng; Zhang, Junchao

2017-12-01

Infrared small target detection under complex background and low signal-to-clutter ratio (SCR) condition is of great significance to the development on precision guidance and infrared surveillance. In order to detect targets precisely and extract targets from intricate clutters effectively, a detection method based on zero-crossing saliency (ZCS) map is proposed. The original map is first decomposed into different first-order directional derivative (FODD) maps by using FODD filters. Then the ZCS map is obtained by fusing all directional zero-crossing points. At last, an adaptive threshold is adopted to segment targets from the ZCS map. Experimental results on a series of images show that our method is effective and robust for detection under complex backgrounds. Moreover, compared with other five state-of-the-art methods, our method achieves better performance in terms of detection rate, SCR gain and background suppression factor.

Shifting attention in viewer- and object-based reference frames after unilateral brain injury.

PubMed

List, Alexandra; Landau, Ayelet N; Brooks, Joseph L; Flevaris, Anastasia V; Fortenbaugh, Francesca C; Esterman, Michael; Van Vleet, Thomas M; Albrecht, Alice R; Alvarez, Bryan D; Robertson, Lynn C; Schendel, Krista

2011-06-01

The aims of the present study were to investigate the respective roles that object- and viewer-based reference frames play in reorienting visual attention, and to assess their influence after unilateral brain injury. To do so, we studied 16 right hemisphere injured (RHI) and 13 left hemisphere injured (LHI) patients. We used a cueing design that manipulates the location of cues and targets relative to a display comprised of two rectangles (i.e., objects). Unlike previous studies with patients, we presented all cues at midline rather than in the left or right visual fields. Thus, in the critical conditions in which targets were presented laterally, reorienting of attention was always from a midline cue. Performance was measured for lateralized target detection as a function of viewer-based (contra- and ipsilesional sides) and object-based (requiring reorienting within or between objects) reference frames. As expected, contralesional detection was slower than ipsilesional detection for the patients. More importantly, objects influenced target detection differently in the contralesional and ipsilesional fields. Contralesionally, reorienting to a target within the cued object took longer than reorienting to a target in the same location but in the uncued object. This finding is consistent with object-based neglect. Ipsilesionally, the means were in the opposite direction. Furthermore, no significant difference was found in object-based influences between the patient groups (RHI vs. LHI). These findings are discussed in the context of reference frames used in reorienting attention for target detection. Published by Elsevier Ltd.

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.

Research on vehicle detection based on background feature analysis in SAR images

NASA Astrophysics Data System (ADS)

Zhang, Bochuan; Tang, Bo; Zhang, Cong; Hu, Ruiguang; Yun, Hongquan; Xiao, Liping

2017-10-01

Aiming at vehicle detection on the ground through low resolution SAR images, a method is proposed for determining the region of the vehicles first and then detecting the target in the specific region. The experimental results show that this method not only reduces the target detection area, but also reduces the influence of terrain clutter on the detection, which greatly improves the reliability of the target detection.

Glint-induced false alarm reduction in signature adaptive target detection

NASA Astrophysics Data System (ADS)

Crosby, Frank J.

2002-07-01

The signal adaptive target detection algorithm developed by Crosby and Riley uses target geometry to discern anomalies in local backgrounds. Detection is not restricted based on specific target signatures. The robustness of the algorithm is limited by an increased false alarm potential. The base algorithm is extended to eliminate one common source of false alarms in a littoral environment. This common source is glint reflected on the surface of water. The spectral and spatial transience of glint prevent straightforward characterization and complicate exclusion. However, the statistical basis of the detection algorithm and its inherent computations allow for glint discernment and the removal of its influence.

Texture orientation-based algorithm for detecting infrared maritime targets.

PubMed

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

2015-05-20

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

A novel infrared small moving target detection method based on tracking interest points under complicated background

NASA Astrophysics Data System (ADS)

Dong, Xiabin; Huang, Xinsheng; Zheng, Yongbin; Bai, Shengjian; Xu, Wanying

2014-07-01

Infrared moving target detection is an important part of infrared technology. We introduce a novel infrared small moving target detection method based on tracking interest points under complicated background. Firstly, Difference of Gaussians (DOG) filters are used to detect a group of interest points (including the moving targets). Secondly, a sort of small targets tracking method inspired by Human Visual System (HVS) is used to track these interest points for several frames, and then the correlations between interest points in the first frame and the last frame are obtained. Last, a new clustering method named as R-means is proposed to divide these interest points into two groups according to the correlations, one is target points and another is background points. In experimental results, the target-to-clutter ratio (TCR) and the receiver operating characteristics (ROC) curves are computed experimentally to compare the performances of the proposed method and other five sophisticated methods. From the results, the proposed method shows a better discrimination of targets and clutters and has a lower false alarm rate than the existing moving target detection methods.

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.

Natural gas pipeline leak detector based on NIR diode laser absorption spectroscopy.

PubMed

Gao, Xiaoming; Fan, Hong; Huang, Teng; Wang, Xia; Bao, Jian; Li, Xiaoyun; Huang, Wei; Zhang, Weijun

2006-09-01

The paper reports on the development of an integrated natural gas pipeline leak detector based on diode laser absorption spectroscopy. The detector transmits a 1.653 microm DFB diode laser with 10 mW and detects a fraction of the backscatter reflected from the topographic targets. To eliminate the effect of topographic scatter targets, a ratio detection technique was used. Wavelength modulation and harmonic detection were used to improve the detection sensitivity. The experimental detection limit is 50 ppmm, remote detection for a distance up to 20 m away topographic scatter target is demonstrated. Using a known simulative leak pipe, minimum detectable pipe leak flux is less than 10 ml/min.

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.

Texture metric that predicts target detection performance

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.

2015-12-01

Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.

A saliency-based approach to detection of infrared target

NASA Astrophysics Data System (ADS)

Chen, Yanfei; Sang, Nong; Dan, Zhiping

2013-10-01

Automatic target detection in infrared images is a hot research field of national defense technology. We propose a new saliency-based infrared target detection model in this paper, which is based on the fact that human focus of attention is directed towards the relevant target to interpret the most promising information. For a given image, the convolution of the image log amplitude spectrum with a low-pass Gaussian kernel of an appropriate scale is equivalent to an image saliency detector in the frequency domain. At the same time, orientation and shape features extracted are combined into a saliency map in the spatial domain. Our proposed model decides salient targets based on a final saliency map, which is generated by integration of the saliency maps in the frequency and spatial domain. At last, the size of each salient target is obtained by maximizing entropy of the final saliency map. Experimental results show that the proposed model can highlight both small and large salient regions in infrared image, as well as inhibit repeated distractors in cluttered image. In addition, its detecting efficiency has improved significantly.

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

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.

A novel technology for the detection, enrichment, and separation of trace amounts of target DNA based on amino-modified fluorescent magnetic composite nanoparticles.

PubMed

Wang, Guannan; Su, Xingguang

2010-06-01

A novel, highly sensitive technology for the detection, enrichment, and separation of trace amounts of target DNA was developed on the basis of amino-modified fluorescent magnetic composite nanoparticles (AFMN). In this study, the positively charged amino-modified composite nanoparticles conjugate with the negatively charged capture DNA through electrostatic binding. The optimal combination of AFMN and capture DNA was measured by dynamic light scattering (DLS) and UV-vis absorption spectroscopy. The highly sensitive detection of trace amounts of target DNA was achieved through enrichment by means of AFMN. The detection limit for target DNA is 0.4 pM, which could be further improved by using a more powerful magnet. Because of their different melting temperatures, single-base mismatched target DNA could be separated from perfectly complementary target DNA. In addition, the photoluminescence (PL) signals of perfectly complementary target DNA and single-base mismatched DNA as well as the hybridization kinetics of different concentrations of target DNA at different reaction times have also been studied. Most importantly, the detection, enrichment, and separation ability of AFMN was further verified with milk. Simple and satisfactory results were obtained, which show the great potential in the fields of mutation identification and clinical diagnosis.

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.

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.

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.

Biomimetic nanochannels based biosensor for ultrasensitive and label-free detection of nucleic acids.

PubMed

Sun, Zhongyue; Liao, Tangbin; Zhang, Yulin; Shu, Jing; Zhang, Hong; Zhang, Guo-Jun

2016-12-15

A very simple sensing device based on biomimetic nanochannels has been developed for label-free, ultrasensitive and highly sequence-specific detection of DNA. Probe DNA was modified on the inner wall of the nanochannel surface by layer-by-layer (LBL) assembly. After probe DNA immobilization, DNA detection was realized by monitoring the rectified ion current when hybridization occurred. Due to three dimensional (3D) nanoscale environment of the nanochannel, this special geometry dramatically increased the surface area of the nanochannel for immobilization of probe molecules on the inner-surface and enlarged contact area between probes and target-molecules. Thus, the unique sensor reached a reliable detection limit of 10 fM for target DNA. In addition, this DNA sensor could discriminate complementary DNA (c-DNA) from non-complementary DNA (nc-DNA), two-base mismatched DNA (2bm-DNA) and one-base mismatched DNA (1bm-DNA) with high specificity. Moreover, the nanochannel-based biosensor was also able to detect target DNA even in an interfering environment and serum samples. This approach will provide a novel biosensing platform for detection and discrimination of disease-related molecular targets and unknown sequence DNA. Copyright © 2016 Elsevier B.V. All rights reserved.

Detection and tracking of a moving target using SAR images with the particle filter-based track-before-detect algorithm.

PubMed

Gao, Han; Li, Jingwen

2014-06-19

A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB.

Detection and Tracking of a Moving Target Using SAR Images with the Particle Filter-Based Track-Before-Detect Algorithm

PubMed Central

Gao, Han; Li, Jingwen

2014-01-01

A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB. PMID:24949640

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.

129 Xe NMR Relaxation-Based Macromolecular Sensing

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

Gomes, Muller D.; Dao, Phuong; Jeong, Keunhong

2016-07-29

A 129Xe NMR relaxation-based sensing approach is reported on that exploits changes in the bulk xenon relaxation rate induced by slowed tumbling of a cryptophane-based sensor upon target binding. The amplification afforded by detection of the bulk dissolved xenon allows sensitive detection of targets. The sensor comprises a xenon-binding cryptophane cage, a target interaction element, and a metal chelating agent. Xenon associated with the target-bound cryptophane cage is rapidly relaxed and then detected after exchange with the bulk. Here we show that large macromolecular targets increase the rotational correlation time of xenon, increasing its relaxation rate. Upon binding of amore » biotin-containing sensor to avidin at 1.5 μM concentration, the free xenon T 2 is reduced by a factor of 4.« less

Development of a microcapillary column for detecting targeted messenger RNA molecules.

PubMed

Ohnishi, Michihiro

2006-03-24

A capillary column in a rapid-flow system has been developed for detecting targeted messenger RNA (mRNA) molecules. The column has a structure made of two beds-one bed of porous microbeads and one bed of microbeads with a polythymidine base sequence. The targeted eukaryotic mRNA molecules are detected by two-step hybridization (sandwich hybridization) composed of polyadenosine selection of mRNA molecules and formation of a probe-target (targeted mRNA) hybrid. The sandwich hybridization, which is accomplished within 1 h, was tested using synthetic polydeoxynucleotides. Ten picomoles of the targeted polydeoxynucleotide were detected.

Detection of Sub-fM DNA with Target Recycling and Self-Assembly Amplification on Graphene Field-Effect Biosensors

PubMed Central

2018-01-01

All-electronic DNA biosensors based on graphene field-effect transistors (GFETs) offer the prospect of simple and cost-effective diagnostics. For GFET sensors based on complementary probe DNA, the sensitivity is limited by the binding affinity of the target oligonucleotide, in the nM range for 20 mer targets. We report a ∼20 000× improvement in sensitivity through the use of engineered hairpin probe DNA that allows for target recycling and hybridization chain reaction. This enables detection of 21 mer target DNA at sub-fM concentration and provides superior specificity against single-base mismatched oligomers. The work is based on a scalable fabrication process for biosensor arrays that is suitable for multiplexed detection. This approach overcomes the binding-affinity-dependent sensitivity of nucleic acid biosensors and offers a pathway toward multiplexed and label-free nucleic acid testing with high accuracy and selectivity. PMID:29768011

Detection of Sub-fM DNA with Target Recycling and Self-Assembly Amplification on Graphene Field-Effect Biosensors.

PubMed

Gao, Zhaoli; Xia, Han; Zauberman, Jonathan; Tomaiuolo, Maurizio; Ping, Jinglei; Zhang, Qicheng; Ducos, Pedro; Ye, Huacheng; Wang, Sheng; Yang, Xinping; Lubna, Fahmida; Luo, Zhengtang; Ren, Li; Johnson, Alan T Charlie

2018-06-13

All-electronic DNA biosensors based on graphene field-effect transistors (GFETs) offer the prospect of simple and cost-effective diagnostics. For GFET sensors based on complementary probe DNA, the sensitivity is limited by the binding affinity of the target oligonucleotide, in the nM range for 20 mer targets. We report a ∼20 000× improvement in sensitivity through the use of engineered hairpin probe DNA that allows for target recycling and hybridization chain reaction. This enables detection of 21 mer target DNA at sub-fM concentration and provides superior specificity against single-base mismatched oligomers. The work is based on a scalable fabrication process for biosensor arrays that is suitable for multiplexed detection. This approach overcomes the binding-affinity-dependent sensitivity of nucleic acid biosensors and offers a pathway toward multiplexed and label-free nucleic acid testing with high accuracy and selectivity.

Estimate of the influence of muzzle smoke on function range of infrared system

NASA Astrophysics Data System (ADS)

Luo, Yan-ling; Wang, Jun; Wu, Jiang-hui; Wu, Jun; Gao, Meng; Gao, Fei; Zhao, Yu-jie; Zhang, Lei

2013-09-01

Muzzle smoke produced by weapons shooting has important influence on infrared (IR) system while detecting targets. Based on the theoretical model of detecting spot targets and surface targets of IR system while there is muzzle smoke, the function range for detecting spot targets and surface targets are deduced separately according to the definition of noise equivalent temperature difference(NETD) and minimum resolution temperature difference(MRTD). Also parameters of muzzle smoke affecting function range of IR system are analyzed. Base on measured data of muzzle smoke for single shot, the function range of an IR system for detecting typical targets are calculated separately while there is muzzle smoke and there is no muzzle smoke at 8-12 micron waveband. For our IR system function range has reduced by over 10% for detecting tank if muzzle smoke exists. The results will provide evidence for evaluating the influence of muzzle smoke on IR system and will help researchers to improve ammo craftwork.

On-chip wavelength multiplexed detection of cancer DNA biomarkers in blood

PubMed Central

Cai, H.; Stott, M. A.; Ozcelik, D.; Parks, J. W.; Hawkins, A. R.; Schmidt, H.

2016-01-01

We have developed an optofluidic analysis system that processes biomolecular samples starting from whole blood and then analyzes and identifies multiple targets on a silicon-based molecular detection platform. We demonstrate blood filtration, sample extraction, target enrichment, and fluorescent labeling using programmable microfluidic circuits. We detect and identify multiple targets using a spectral multiplexing technique based on wavelength-dependent multi-spot excitation on an antiresonant reflecting optical waveguide chip. Specifically, we extract two types of melanoma biomarkers, mutated cell-free nucleic acids —BRAFV600E and NRAS, from whole blood. We detect and identify these two targets simultaneously using the spectral multiplexing approach with up to a 96% success rate. These results point the way toward a full front-to-back chip-based optofluidic compact system for high-performance analysis of complex biological samples. PMID:28058082

Spatial Probability Dynamically Modulates Visual Target Detection in Chickens

PubMed Central

Sridharan, Devarajan; Ramamurthy, Deepa L.; Knudsen, Eric I.

2013-01-01

The natural world contains a rich and ever-changing landscape of sensory information. To survive, an organism must be able to flexibly and rapidly locate the most relevant sources of information at any time. Humans and non-human primates exploit regularities in the spatial distribution of relevant stimuli (targets) to improve detection at locations of high target probability. Is the ability to flexibly modify behavior based on visual experience unique to primates? Chickens (Gallus domesticus) were trained on a multiple alternative Go/NoGo task to detect a small, briefly-flashed dot (target) in each of the quadrants of the visual field. When targets were presented with equal probability (25%) in each quadrant, chickens exhibited a distinct advantage for detecting targets at lower, relative to upper, hemifield locations. Increasing the probability of presentation in the upper hemifield locations (to 80%) dramatically improved detection performance at these locations to be on par with lower hemifield performance. Finally, detection performance in the upper hemifield changed on a rapid timescale, improving with successive target detections, and declining with successive detections at the diagonally opposite location in the lower hemifield. These data indicate the action of a process that in chickens, as in primates, flexibly and dynamically modulates detection performance based on the spatial probabilities of sensory stimuli as well as on recent performance history. PMID:23734188

Magnetic wire trap arrays for biomarker-based molecular detection

NASA Astrophysics Data System (ADS)

Vieira, Gregory; Mahajan, Kalpesh; Ruan, Gang; Winter, Jessica; Sooryakumar, R.

2012-02-01

Submicrometer-scale magnetic devices built on chip-based platforms have recently been shown to present opportunities for new particle trapping and manipulation technologies. Meanwhile, advances in nanoparticle fabrication allow for the building of custom-made particles with precise control of their size, composition, and other properties such as magnetism, fluorescence, and surface biomarker characteristics. In particular, carefully tailored surface biomarkers facilitate precise binding to targeted molecules, self-actuated construction of hybrid structures, and fluorescence-based detection schemes. Based on these progresses, we present an on-chip detection mechanism for molecules with known surface markers. Hybrid nanostructures consisting of micelle nanoparticles, fluorescent quantum dots, and superparamagnetic iron oxide nanoparticles are used to detect proteins or DNA molecules. The target is detected by the magnetic and fluorescent functionalities of the composite nanostructure, whereas in the absence of the target these signals are not present. Underlying this approach is the simultaneous manipulation via ferromagnetic zigzag nanowire arrays and imaging via quantum dot excitation. This chip-based detection technique could provide a powerful, low cost tool for ultrasensitive molecule detection with ramifications in healthcare diagnostics and small-scale chemical synthesis.

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.

Fire flame detection based on GICA and target tracking

NASA Astrophysics Data System (ADS)

Rong, Jianzhong; Zhou, Dechuang; Yao, Wei; Gao, Wei; Chen, Juan; Wang, Jian

2013-04-01

To improve the video fire detection rate, a robust fire detection algorithm based on the color, motion and pattern characteristics of fire targets was proposed, which proved a satisfactory fire detection rate for different fire scenes. In this fire detection algorithm: (a) a rule-based generic color model was developed based on analysis on a large quantity of flame pixels; (b) from the traditional GICA (Geometrical Independent Component Analysis) model, a Cumulative Geometrical Independent Component Analysis (C-GICA) model was developed for motion detection without static background and (c) a BP neural network fire recognition model based on multi-features of the fire pattern was developed. Fire detection tests on benchmark fire video clips of different scenes have shown the robustness, accuracy and fast-response of the algorithm.

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

PubMed

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

2014-12-01

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

Expanded Processing Techniques for EMI Systems

DTIC Science & Technology

2012-07-01

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

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

Double-hairpin molecular-beacon-based amplification detection for gene diagnosis linked to cancer.

PubMed

Xu, Huo; Zhang, Rongbo; Li, Feng; Zhou, Yingying; Peng, Ting; Wang, Xuedong; Shen, Zhifa

2016-09-01

A powerful double-hairpin molecular beacon (DHMB) was developed for cancer-related KRAS gene detection based on the one-to-two stoichiometry. During target DNA detection, DHMB can execute signal transduction even if no any exogenous element is involved. Unlike the conventional molecular beacon based on the one-to-one interaction, one target DNA not only hybridizes with one DHMB and opens its hairpin but also promotes the interaction between two DHMBs, causing the separation of two fluorophores from quenchers. This leads to an enhanced fluorescence signal. As a result, the target KRAS gene is able to be detected within a wide dynamic range from 0.05 to 200 nM with the detection limit of 50 pM, indicating a dramatic improvement compared with traditional molecular beacons. Moreover, the point mutations existing in target DNAs can be easily screened. The potential application for target species in real samples was indicated by the analysis of PCR amplicons of DNAs from the DNA extracted from SW620 cell. Besides becoming a promising candidate probe for molecular biology research and clinical diagnosis of genetic diseases, the DHMB is expected to provide a significant insight into the design of DNA probe-based homogenous sensing systems. Graphical Abstract A powerful double-hairpin molecular beacon (DHMB) was developed for cancer-related gene KRAS detection based on the one-to-two stoichiometry. Without the help of any exogenous probe, the point mutation is easily screened, and the target DNA can be quantified down to 50 pM, indicating a dramatic improvement compared with traditional molecular beacons.

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

Waveform design for detection of weapons based on signature exploitation

NASA Astrophysics Data System (ADS)

Ahmad, Fauzia; Amin, Moeness G.; Dogaru, Traian

2010-04-01

We present waveform design based on signature exploitation techniques for improved detection of weapons in urban sensing applications. A single-antenna monostatic radar system is considered. Under the assumption of exact knowledge of the target orientation and, hence, known impulse response, matched illumination approach is used for optimal target detection. For the case of unknown target orientation, we analyze the target signatures as random processes and perform signal-to-noise-ratio based waveform optimization. Numerical electromagnetic modeling is used to provide the impulse responses of an AK-47 assault rifle for various target aspect angles relative to the radar. Simulation results depict an improvement in the signal-to-noise-ratio at the output of the matched filter receiver for both matched illumination and stochastic waveforms as compared to a chirp waveform of the same duration and energy.

Domain Adaptation for Pedestrian Detection Based on Prediction Consistency

PubMed Central

Huan-ling, Tang; Zhi-yong, An

2014-01-01

Pedestrian detection is an active area of research in computer vision. It remains a quite challenging problem in many applications where many factors cause a mismatch between source dataset used to train the pedestrian detector and samples in the target scene. In this paper, we propose a novel domain adaptation model for merging plentiful source domain samples with scared target domain samples to create a scene-specific pedestrian detector that performs as well as rich target domain simples are present. Our approach combines the boosting-based learning algorithm with an entropy-based transferability, which is derived from the prediction consistency with the source classifications, to selectively choose the samples showing positive transferability in source domains to the target domain. Experimental results show that our approach can improve the detection rate, especially with the insufficient labeled data in target scene. PMID:25013850

Simple Monitoring of Gene Targeting Efficiency in Human Somatic Cell Lines Using the PIGA Gene

PubMed Central

Karnan, Sivasundaram; Konishi, Yuko; Ota, Akinobu; Takahashi, Miyuki; Damdindorj, Lkhagvasuren; Hosokawa, Yoshitaka; Konishi, Hiroyuki

2012-01-01

Gene targeting in most of human somatic cell lines has been labor-intensive because of low homologous recombination efficiency. The development of an experimental system that permits a facile evaluation of gene targeting efficiency in human somatic cell lines is the first step towards the improvement of this technology and its application to a broad range of cell lines. In this study, we utilized phosphatidylinositol glycan anchor biosynthesis class A (PIGA), a gene essential for the synthesis of glycosylphosphatidyl inositol (GPI) anchors, as a reporter of gene targeting events in human somatic cell lines. Targeted disruption of PIGA was quantitatively detected with FLAER, a reagent that specifically binds to GPI anchors. Using this PIGA-based reporter system, we successfully detected adeno-associated virus (AAV)-mediated gene targeting events both with and without promoter-trap enrichment of gene-targeted cell population. The PIGA-based reporter system was also capable of reproducing previous findings that an AAV-mediated gene targeting achieves a remarkably higher ratio of homologous versus random integration (H/R ratio) of targeting vectors than a plasmid-mediated gene targeting. The PIGA-based system also detected an approximately 2-fold increase in the H/R ratio achieved by a small negative selection cassette introduced at the end of the AAV-based targeting vector with a promoter-trap system. Thus, our PIGA-based system is useful for monitoring AAV-mediated gene targeting and will assist in improving gene targeting technology in human somatic cell lines. PMID:23056640

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

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

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.

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.

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

NASA Astrophysics Data System (ADS)

Zhou, Yi-Tong; Crawshaw, Richard D.

1991-08-01

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

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.

Detection of Non-Nucleic Acid Targets with an Unmodified Aptamer and a Fluorogenic Competitor

PubMed Central

Li, Na

2010-01-01

Aptamers are oligonucleotides that can bind to various non-nucleic acid targets, ranging from proteins to small molecules, with a specificity and affinity comparable to that of antibodies. Most aptamer-based detection strategies require modification on the aptamer, which could lead to a significant loss in its affinity and specificity to the target. Here we reported a generic strategy to design aptamer-based optical probes. An unmodified aptamer specific to the target and a fluorogenic competitor complementary to the aptamer are utilized for target recognition and signal generation, respectively. The competitor is a hairpin oligonucleotide with a fluorophore attached on one end and a quencher attached on the other. When no target is present, the competitor binds to the aptamer. However, when the target is introduced, the competitor will be displaced from the aptamer by the target, thus resulting in a target-specific decrease in fluorescence signal. Successful application of this strategy to different types of targets (small molecules and proteins) as well as different types of aptamers (DNA and RNA) has been demonstrated. Furthermore, a thermodynamics-based prediction model was established to further rationalize the optimization process. Due to its rapidness and simplicity, this aptamer-based detection strategy holds great promise in high throughput applications. PMID:20563298

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.

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.

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.

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

DTIC Science & Technology

2014-06-01

Radon -Fourier transform has been introduced to realize long- term coherent integration of the moving targets with range migration [8, 9]. Radon ...2010) Long-time coherent integration for radar target detection base on Radon -Fourier transform, in Proceedings of the IEEE Radar Conference, pp...432–436. 9. Xu, J., Yu, J., Peng, Y. & Xia, X. (2011) Radon -Fourier transform for radar target detection, I: Generalized Doppler filter bank, IEEE

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

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.

Dual signal amplification for highly sensitive electrochemical detection of uropathogens via enzyme-based catalytic target recycling.

PubMed

Su, Jiao; Zhang, Haijie; Jiang, Bingying; Zheng, Huzhi; Chai, Yaqin; Yuan, Ruo; Xiang, Yun

2011-11-15

We report an ultrasensitive electrochemical approach for the detection of uropathogen sequence-specific DNA target. The sensing strategy involves a dual signal amplification process, which combines the signal enhancement by the enzymatic target recycling technique with the sensitivity improvement by the quantum dot (QD) layer-by-layer (LBL) assembled labels. The enzyme-based catalytic target DNA recycling process results in the use of each target DNA sequence for multiple times and leads to direct amplification of the analytical signal. Moreover, the LBL assembled QD labels can further enhance the sensitivity of the sensing system. The coupling of these two effective signal amplification strategies thus leads to low femtomolar (5fM) detection of the target DNA sequences. The proposed strategy also shows excellent discrimination between the target DNA and the single-base mismatch sequences. The advantageous intrinsic sequence-independent property of exonuclease III over other sequence-dependent enzymes makes our new dual signal amplification system a general sensing platform for monitoring ultralow level of various types of target DNA sequences. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

Ship detection from high-resolution imagery based on land masking and cloud filtering

NASA Astrophysics Data System (ADS)

Jin, Tianming; Zhang, Junping

2015-12-01

High resolution satellite images play an important role in target detection application presently. This article focuses on the ship target detection from the high resolution panchromatic images. Taking advantage of geographic information such as the coastline vector data provided by NOAA Medium Resolution Coastline program, the land region is masked which is a main noise source in ship detection process. After that, the algorithm tries to deal with the cloud noise which appears frequently in the ocean satellite images, which is another reason for false alarm. Based on the analysis of cloud noise's feature in frequency domain, we introduce a windowed noise filter to get rid of the cloud noise. With the help of morphological processing algorithms adapted to target detection, we are able to acquire ship targets in fine shapes. In addition, we display the extracted information such as length and width of ship targets in a user-friendly way i.e. a KML file interpreted by Google Earth.

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

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.

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.

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.

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.

Electrochemical detection of leukemia oncogenes using enzyme-loaded carbon nanotube labels

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

Lee, Ai Cheng; Du, Dan; Chen, Baowei

2014-09-07

Here we describe an ultrasensitive electrochemical nucleic acids assay amplified by carbon nanotubes (CNTs)-based labels for the detection of human acute lymphocytic leukemia (ALL) related p185 BCR-ABL fusion transcript. The carboxylated CNTs were functionalized with horseradish peroxidase (HRP) molecules and target-specific detection probes (DP) via diimide-activated amidation, and used to label and amplify target hybridization signal. The activity of captured HRP was monitored by square-wave voltammetry measuring the electroactive enzymatic product in the presence of 2-aminophenol and hydrogen peroxide substrate solution. The effect of DP and HRP loading of the CNT-based labels on its signal-to-noise ratio of electrochemical detection wasmore » studied systematically for the first time. Under optimized conditions, the signal-amplified assay achieved a detection limit of 83 fM targets oligonuecleotides and a 4-order wide dynamic range of target concentration. The resulting assay allowed a robust discrimination between the perfect match and a three-base mismatch sequence. When subjected to full-length (491 bp) DNA oncogene, the approach demonstrated a detection limit of approximately 33 pg of the target gene. The high sensitivity and specificity of assay enabled PCR-free detection of target transcripts in as little as 65 ng of mRNA extracted from positive ALL cell lines SUP-B15, in comparison to those obtained from negative cell lines HL-60. The approach holds promise for simple, low cost and ultrasensitive electrochemical nucleic acids detection in portable devices, point-of-care and early disease diagnostic applications.« less

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

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.

A Novel Method of Aircraft Detection Based on High-Resolution Panchromatic Optical Remote Sensing Images.

PubMed

Wang, Wensheng; Nie, Ting; Fu, Tianjiao; Ren, Jianyue; Jin, Longxu

2017-05-06

In target detection of optical remote sensing images, two main obstacles for aircraft target detection are how to extract the candidates in complex gray-scale-multi background and how to confirm the targets in case the target shapes are deformed, irregular or asymmetric, such as that caused by natural conditions (low signal-to-noise ratio, illumination condition or swaying photographing) and occlusion by surrounding objects (boarding bridge, equipment). To solve these issues, an improved active contours algorithm, namely region-scalable fitting energy based threshold (TRSF), and a corner-convex hull based segmentation algorithm (CCHS) are proposed in this paper. Firstly, the maximal variance between-cluster algorithm (Otsu's algorithm) and region-scalable fitting energy (RSF) algorithm are combined to solve the difficulty of targets extraction in complex and gray-scale-multi backgrounds. Secondly, based on inherent shapes and prominent corners, aircrafts are divided into five fragments by utilizing convex hulls and Harris corner points. Furthermore, a series of new structure features, which describe the proportion of targets part in the fragment to the whole fragment and the proportion of fragment to the whole hull, are identified to judge whether the targets are true or not. Experimental results show that TRSF algorithm could improve extraction accuracy in complex background, and that it is faster than some traditional active contours algorithms. The CCHS is effective to suppress the detection difficulties caused by the irregular shape.

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.

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.

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

PubMed

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

2018-06-29

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

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.

Familiarity facilitates feature-based face processing.

PubMed

Visconti di Oleggio Castello, Matteo; Wheeler, Kelsey G; Cipolli, Carlo; Gobbini, M Ida

2017-01-01

Recognition of personally familiar faces is remarkably efficient, effortless and robust. We asked if feature-based face processing facilitates detection of familiar faces by testing the effect of face inversion on a visual search task for familiar and unfamiliar faces. Because face inversion disrupts configural and holistic face processing, we hypothesized that inversion would diminish the familiarity advantage to the extent that it is mediated by such processing. Subjects detected personally familiar and stranger target faces in arrays of two, four, or six face images. Subjects showed significant facilitation of personally familiar face detection for both upright and inverted faces. The effect of familiarity on target absent trials, which involved only rejection of unfamiliar face distractors, suggests that familiarity facilitates rejection of unfamiliar distractors as well as detection of familiar targets. The preserved familiarity effect for inverted faces suggests that facilitation of face detection afforded by familiarity reflects mostly feature-based processes.

An Improved Vision-based Algorithm for Unmanned Aerial Vehicles Autonomous Landing

NASA Astrophysics Data System (ADS)

Zhao, Yunji; Pei, Hailong

In vision-based autonomous landing system of UAV, the efficiency of target detecting and tracking will directly affect the control system. The improved algorithm of SURF(Speed Up Robust Features) will resolve the problem which is the inefficiency of the SURF algorithm in the autonomous landing system. The improved algorithm is composed of three steps: first, detect the region of the target using the Camshift; second, detect the feature points in the region of the above acquired using the SURF algorithm; third, do the matching between the template target and the region of target in frame. The results of experiment and theoretical analysis testify the efficiency of the algorithm.

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.

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.

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.

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.

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.

Improved PCR-Based Detection of Soil Transmitted Helminth Infections Using a Next-Generation Sequencing Approach to Assay Design.

PubMed

Pilotte, Nils; Papaiakovou, Marina; Grant, Jessica R; Bierwert, Lou Ann; Llewellyn, Stacey; McCarthy, James S; Williams, Steven A

2016-03-01

The soil transmitted helminths are a group of parasitic worms responsible for extensive morbidity in many of the world's most economically depressed locations. With growing emphasis on disease mapping and eradication, the availability of accurate and cost-effective diagnostic measures is of paramount importance to global control and elimination efforts. While real-time PCR-based molecular detection assays have shown great promise, to date, these assays have utilized sub-optimal targets. By performing next-generation sequencing-based repeat analyses, we have identified high copy-number, non-coding DNA sequences from a series of soil transmitted pathogens. We have used these repetitive DNA elements as targets in the development of novel, multi-parallel, PCR-based diagnostic assays. Utilizing next-generation sequencing and the Galaxy-based RepeatExplorer web server, we performed repeat DNA analysis on five species of soil transmitted helminths (Necator americanus, Ancylostoma duodenale, Trichuris trichiura, Ascaris lumbricoides, and Strongyloides stercoralis). Employing high copy-number, non-coding repeat DNA sequences as targets, novel real-time PCR assays were designed, and assays were tested against established molecular detection methods. Each assay provided consistent detection of genomic DNA at quantities of 2 fg or less, demonstrated species-specificity, and showed an improved limit of detection over the existing, proven PCR-based assay. The utilization of next-generation sequencing-based repeat DNA analysis methodologies for the identification of molecular diagnostic targets has the ability to improve assay species-specificity and limits of detection. By exploiting such high copy-number repeat sequences, the assays described here will facilitate soil transmitted helminth diagnostic efforts. We recommend similar analyses when designing PCR-based diagnostic tests for the detection of other eukaryotic pathogens.

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.

Small target pre-detection with an attention mechanism

NASA Astrophysics Data System (ADS)

Wang, Yuehuan; Zhang, Tianxu; Wang, Guoyou

2002-04-01

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

The relationship study between image features and detection probability based on psychology experiments

NASA Astrophysics Data System (ADS)

Lin, Wei; Chen, Yu-hua; Wang, Ji-yuan; Gao, Hong-sheng; Wang, Ji-jun; Su, Rong-hua; Mao, Wei

2011-04-01

Detection probability is an important index to represent and estimate target viability, which provides basis for target recognition and decision-making. But it will expend a mass of time and manpower to obtain detection probability in reality. At the same time, due to the different interpretation of personnel practice knowledge and experience, a great difference will often exist in the datum obtained. By means of studying the relationship between image features and perception quantity based on psychology experiments, the probability model has been established, in which the process is as following.Firstly, four image features have been extracted and quantified, which affect directly detection. Four feature similarity degrees between target and background were defined. Secondly, the relationship between single image feature similarity degree and perception quantity was set up based on psychological principle, and psychological experiments of target interpretation were designed which includes about five hundred people for interpretation and two hundred images. In order to reduce image features correlativity, a lot of artificial synthesis images have been made which include images with single brightness feature difference, images with single chromaticity feature difference, images with single texture feature difference and images with single shape feature difference. By analyzing and fitting a mass of experiments datum, the model quantitys have been determined. Finally, by applying statistical decision theory and experimental results, the relationship between perception quantity with target detection probability has been found. With the verification of a great deal of target interpretation in practice, the target detection probability can be obtained by the model quickly and objectively.

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 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

The signature-based radiation-scanning approach to standoff detection of improvised explosive devices.

PubMed

Brewer, R L; Dunn, W L; Heider, S; Matthew, C; Yang, X

2012-07-01

The signature-based radiation-scanning technique for detection of improvised explosive devices is described. The technique seeks to detect nitrogen-rich chemical explosives present in a target. The technology compares a set of "signatures" obtained from a test target to a collection of "templates", sets of signatures for a target that contain an explosive in a specific configuration. Interrogation of nitrogen-rich fertilizer samples, which serve as surrogates for explosives, is shown experimentally to be able to discriminate samples of 3.8L and larger. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

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.

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.

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.

Compact and cost effective instrument for detecting drug precursors in different environments based on fluorescence polarization

NASA Astrophysics Data System (ADS)

Antolín-Urbaneja, J. C.; Eguizabal, I.; Briz, N.; Dominguez, A.; Estensoro, P.; Secchi, A.; Varriale, A.; Di Giovanni, S.; D'Auria, S.

2013-05-01

Several techniques for detecting chemical drug precursors have been developed in the last decade. Most of them are able to identify molecules at very low concentration under lab conditions. Other commercial devices are able to detect a fixed number and type of target substances based on a single detection technique providing an absence of flexibility with respect to target compounds. The construction of compact and easy to use detection systems providing screening for a large number of compounds being able to discriminate them with low false alarm rate and high probability of detection is still an open concern. Under CUSTOM project, funded by the European Commission within the FP7, a stand-alone portable sensing device based on multiple techniques is being developed. One of these techniques is based on the LED induced fluorescence polarization to detect Ephedrine and Benzyl Methyl Keton (BMK) as a first approach. This technique is highly selective with respect to the target compounds due to the generation of properly engineered fluorescent proteins which are able to bind the target analytes, as it happens in an "immune-type reaction". This paper deals with the advances in the design, construction and validation of the LED induced fluorescence sensor to detect BMK analytes. This sensor includes an analysis module based on high performance LED and PMT detector, a fluidic system to dose suitable quantities of reagents and some printed circuit boards, all of them fixed in a small structure (167mm × 193mm × 228mm) with the capability of working as a stand-alone application.

Decision-level fusion of SAR and IR sensor information for automatic target detection

NASA Astrophysics Data System (ADS)

Cho, Young-Rae; Yim, Sung-Hyuk; Cho, Hyun-Woong; Won, Jin-Ju; Song, Woo-Jin; Kim, So-Hyeon

2017-05-01

We propose a decision-level architecture that combines synthetic aperture radar (SAR) and an infrared (IR) sensor for automatic target detection. We present a new size-based feature, called target-silhouette to reduce the number of false alarms produced by the conventional target-detection algorithm. Boolean Map Visual Theory is used to combine a pair of SAR and IR images to generate the target-enhanced map. Then basic belief assignment is used to transform this map into a belief map. The detection results of sensors are combined to build the target-silhouette map. We integrate the fusion mass and the target-silhouette map on the decision level to exclude false alarms. The proposed algorithm is evaluated using a SAR and IR synthetic database generated by SE-WORKBENCH simulator, and compared with conventional algorithms. The proposed fusion scheme achieves higher detection rate and lower false alarm rate than the conventional algorithms.

Space-based IR tracking bias removal using background star observations

NASA Astrophysics Data System (ADS)

Clemons, T. M., III; Chang, K. C.

2009-05-01

This paper provides the results of a proposed methodology for removing sensor bias from a space-based infrared (IR) tracking system through the use of stars detected in the background field of the tracking sensor. The tracking system consists of two satellites flying in a lead-follower formation tracking a ballistic target. Each satellite is equipped with a narrow-view IR sensor that provides azimuth and elevation to the target. The tracking problem is made more difficult due to a constant, non-varying or slowly varying bias error present in each sensor's line of sight measurements. As known stars are detected during the target tracking process, the instantaneous sensor pointing error can be calculated as the difference between star detection reading and the known position of the star. The system then utilizes a separate bias filter to estimate the bias value based on these detections and correct the target line of sight measurements to improve the target state vector. The target state vector is estimated through a Linearized Kalman Filter (LKF) for the highly non-linear problem of tracking a ballistic missile. Scenarios are created using Satellite Toolkit(C) for trajectories with associated sensor observations. Mean Square Error results are given for tracking during the period when the target is in view of the satellite IR sensors. The results of this research provide a potential solution to bias correction while simultaneously tracking a target.

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.

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.

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.

Antenna Allocation in MIMO Radar with Widely Separated Antennas for Multi-Target Detection

PubMed Central

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

2014-01-01

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes. PMID:25350505

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

PubMed

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

2014-10-27

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

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.

Shape and texture fused recognition of flying targets

NASA Astrophysics Data System (ADS)

Kovács, Levente; Utasi, Ákos; Kovács, Andrea; Szirányi, Tamás

2011-06-01

This paper presents visual detection and recognition of flying targets (e.g. planes, missiles) based on automatically extracted shape and object texture information, for application areas like alerting, recognition and tracking. Targets are extracted based on robust background modeling and a novel contour extraction approach, and object recognition is done by comparisons to shape and texture based query results on a previously gathered real life object dataset. Application areas involve passive defense scenarios, including automatic object detection and tracking with cheap commodity hardware components (CPU, camera and GPS).

Application of passive imaging polarimetry in the discrimination and detection of different color targets of identical shapes using color-blind imaging sensors

NASA Astrophysics Data System (ADS)

El-Saba, A. M.; Alam, M. S.; Surpanani, A.

2006-05-01

Important aspects of automatic pattern recognition systems are their ability to efficiently discriminate and detect proper targets with low false alarms. In this paper we extend the applications of passive imaging polarimetry to effectively discriminate and detect different color targets of identical shapes using color-blind imaging sensor. For this case of study we demonstrate that traditional color-blind polarization-insensitive imaging sensors that rely only on the spatial distribution of targets suffer from high false detection rates, especially in scenarios where multiple identical shape targets are present. On the other hand we show that color-blind polarization-sensitive imaging sensors can successfully and efficiently discriminate and detect true targets based on their color only. We highlight the main advantages of using our proposed polarization-encoded imaging sensor.

Target Detection of Quantum Illumination Receiver Based on Photon-subtracted Entanglement State

NASA Astrophysics Data System (ADS)

Chi, Jiao; Liu, HongJun; Huang, Nan; Wang, ZhaoLu

2017-12-01

We theoretically propose a quantum illumination receiver based on the ideal photon-subtracted two-mode squeezed state (PSTMSS) to efficiently detect the noise-hidden target. This receiver is generated by applying an optical parametric amplifier (OPA) to the cross correlation detection. With analyzing the output performance, it is found that OPA as a preposition technology of the receiver can contribute to the PSTMSS by significantly reducing the error probability than that of the general two-mode squeezed state (TMSS). Comparing with TMSS, the signal-to-noise ratio of quantum illumination based on ideal PSTMSS and OPA is improved more than 4 dB under an optimal gain of OPA. This work may provide a potential improvement in the application of accurate target detection when two kinds of resource have the identical real squeezing parameter.

A new method for detecting small and dim targets in starry background

NASA Astrophysics Data System (ADS)

Yao, Rui; Zhang, Yanning; Jiang, Lei

2011-08-01

Small visible optical space targets detection is one of the key issues in the research of long-range early warning and space debris surveillance. The SNR(Signal to Noise Ratio) of the target is very low because of the self influence of image device. Random noise and background movement also increase the difficulty of target detection. In order to detect small visible optical space targets effectively and rapidly, we bring up a novel detecting method based on statistic theory. Firstly, we get a reasonable statistical model of visible optical space image. Secondly, we extract SIFT(Scale-Invariant Feature Transform) feature of the image frames, and calculate the transform relationship, then use the transform relationship to compensate whole visual field's movement. Thirdly, the influence of star was wiped off by using interframe difference method. We find segmentation threshold to differentiate candidate targets and noise by using OTSU method. Finally, we calculate statistical quantity to judge whether there is the target for every pixel position in the image. Theory analysis shows the relationship of false alarm probability and detection probability at different SNR. The experiment result shows that this method could detect target efficiently, even the target passing through stars.

Two novel motion-based algorithms for surveillance video analysis on embedded platforms

NASA Astrophysics Data System (ADS)

Vijverberg, Julien A.; Loomans, Marijn J. H.; Koeleman, Cornelis J.; de With, Peter H. N.

2010-05-01

This paper proposes two novel motion-vector based techniques for target detection and target tracking in surveillance videos. The algorithms are designed to operate on a resource-constrained device, such as a surveillance camera, and to reuse the motion vectors generated by the video encoder. The first novel algorithm for target detection uses motion vectors to construct a consistent motion mask, which is combined with a simple background segmentation technique to obtain a segmentation mask. The second proposed algorithm aims at multi-target tracking and uses motion vectors to assign blocks to targets employing five features. The weights of these features are adapted based on the interaction between targets. These algorithms are combined in one complete analysis application. The performance of this application for target detection has been evaluated for the i-LIDS sterile zone dataset and achieves an F1-score of 0.40-0.69. The performance of the analysis algorithm for multi-target tracking has been evaluated using the CAVIAR dataset and achieves an MOTP of around 9.7 and MOTA of 0.17-0.25. On a selection of targets in videos from other datasets, the achieved MOTP and MOTA are 8.8-10.5 and 0.32-0.49 respectively. The execution time on a PC-based platform is 36 ms. This includes the 20 ms for generating motion vectors, which are also required by the video encoder.

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.

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.

Toehold-mediated strand displacement reaction triggered isothermal DNA amplification for highly sensitive and selective fluorescent detection of single-base mutation.

PubMed

Zhu, Jing; Ding, Yongshun; Liu, Xingti; Wang, Lei; Jiang, Wei

2014-09-15

Highly sensitive and selective detection strategy for single-base mutations is essential for risk assessment of malignancy and disease prognosis. In this work, a fluorescent detection method for single-base mutation was proposed based on high selectivity of toehold-mediated strand displacement reaction (TSDR) and powerful signal amplification capability of isothermal DNA amplification. A discrimination probe was specially designed with a stem-loop structure and an overhanging toehold domain. Hybridization between the toehold domain and the perfect matched target initiated the TSDR along with the unfolding of the discrimination probe. Subsequently, the target sequence acted as a primer to initiate the polymerization and nicking reactions, which released a great abundant of short sequences. Finally, the released strands were annealed with the reporter probe, launching another polymerization and nicking reaction to produce lots of G-quadruplex DNA, which could bind the N-methyl mesoporphyrin IX to yield an enhanced fluorescence response. However, when there was even a single base mismatch in the target DNA, the TSDR was suppressed and so subsequent isothermal DNA amplification and fluorescence response process could not occur. The proposed approach has been successfully implemented for the identification of the single-base mutant sequences in the human KRAS gene with a detection limit of 1.8 pM. Furthermore, a recovery of 90% was obtained when detecting the target sequence in spiked HeLa cells lysate, demonstrating the feasibility of this detection strategy for single-base mutations in biological samples. Copyright © 2014 Elsevier B.V. All rights reserved.

A Novel Method of Aircraft Detection Based on High-Resolution Panchromatic Optical Remote Sensing Images

PubMed Central

Wang, Wensheng; Nie, Ting; Fu, Tianjiao; Ren, Jianyue; Jin, Longxu

2017-01-01

In target detection of optical remote sensing images, two main obstacles for aircraft target detection are how to extract the candidates in complex gray-scale-multi background and how to confirm the targets in case the target shapes are deformed, irregular or asymmetric, such as that caused by natural conditions (low signal-to-noise ratio, illumination condition or swaying photographing) and occlusion by surrounding objects (boarding bridge, equipment). To solve these issues, an improved active contours algorithm, namely region-scalable fitting energy based threshold (TRSF), and a corner-convex hull based segmentation algorithm (CCHS) are proposed in this paper. Firstly, the maximal variance between-cluster algorithm (Otsu’s algorithm) and region-scalable fitting energy (RSF) algorithm are combined to solve the difficulty of targets extraction in complex and gray-scale-multi backgrounds. Secondly, based on inherent shapes and prominent corners, aircrafts are divided into five fragments by utilizing convex hulls and Harris corner points. Furthermore, a series of new structure features, which describe the proportion of targets part in the fragment to the whole fragment and the proportion of fragment to the whole hull, are identified to judge whether the targets are true or not. Experimental results show that TRSF algorithm could improve extraction accuracy in complex background, and that it is faster than some traditional active contours algorithms. The CCHS is effective to suppress the detection difficulties caused by the irregular shape. PMID:28481260

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

Carbon nanotube-based labels for highly sensitive colorimetric and aggregation-based visual detection of nucleic acids

NASA Astrophysics Data System (ADS)

Lee, Ai Cheng; Ye, Jian-Shan; Ngin Tan, Swee; Poenar, Daniel P.; Sheu, Fwu-Shan; Kiat Heng, Chew; Meng Lim, Tit

2007-11-01

A novel carbon nanotube (CNT) derived label capable of dramatic signal amplification of nucleic acid detection and direct visual detection of target hybridization has been developed. Highly sensitive colorimetric detection of human acute lymphocytic leukemia (ALL) related oncogene sequences amplified by the novel CNT-based label was demonstrated. Atomic force microscope (AFM) images confirmed that a monolayer of horseradish peroxidase and detection probe molecules was immobilized along the carboxylated CNT carrier. The resulting CNT labels significantly enhanced the nucleic acid assay sensitivity by at least 1000 times compared to that of conventional labels used in enzyme-linked oligosorbent assay (ELOSA). An excellent detection limit of 1 × 10-12 M (60 × 10-18 mol in 60 µl) and a four-order wide dynamic range of target concentration were achieved. Hybridizations using these labels were coupled to a concentration-dependent formation of visible dark aggregates. Targets can thus be detected simply with visual inspection, eliminating the need for expensive and sophisticated detection systems. The approach holds promise for ultrasensitive and low cost visual inspection and colorimetric nucleic acid detection in point-of-care and early disease diagnostic application.

DNA-based species detection capabilities using laser transmission spectroscopy

PubMed Central

Mahon, A. R.; Barnes, M. A.; Li, F.; Egan, S. P.; Tanner, C. E.; Ruggiero, S. T.; Feder, J. L.; Lodge, D. M.

2013-01-01

Early detection of invasive species is critical for effective biocontrol to mitigate potential ecological and economic damage. Laser transmission spectroscopy (LTS) is a powerful solution offering real-time, DNA-based species detection in the field. LTS can measure the size, shape and number of nanoparticles in a solution and was used here to detect size shifts resulting from hybridization of the polymerase chain reaction product to nanoparticles functionalized with species-specific oligonucleotide probes or with the species-specific oligonucleotide probes alone. We carried out a series of DNA detection experiments using the invasive freshwater quagga mussel (Dreissena bugensis) to evaluate the capability of the LTS platform for invasive species detection. Specifically, we tested LTS sensitivity to (i) DNA concentrations of a single target species, (ii) the presence of a target species within a mixed sample of other closely related species, (iii) species-specific functionalized nanoparticles versus species-specific oligonucleotide probes alone, and (iv) amplified DNA fragments versus unamplified genomic DNA. We demonstrate that LTS is a highly sensitive technique for rapid target species detection, with detection limits in the picomolar range, capable of successful identification in multispecies samples containing target and non-target species DNA. These results indicate that the LTS DNA detection platform will be useful for field application of target species. Additionally, we find that LTS detection is effective with species-specific oligonucleotide tags alone or when they are attached to polystyrene nanobeads and with both amplified and unamplified DNA, indicating that the technique may also have versatility for broader applications. PMID:23015524

Investigations of internal noise levels for different target sizes, contrasts, and noise structures

NASA Astrophysics Data System (ADS)

Han, Minah; Choi, Shinkook; Baek, Jongduk

2014-03-01

To describe internal noise levels for different target sizes, contrasts, and noise structures, Gaussian targets with four different sizes (i.e., standard deviation of 2,4,6 and 8) and three different noise structures(i.e., white, low-pass, and highpass) were generated. The generated noise images were scaled to have standard deviation of 0.15. For each noise type, target contrasts were adjusted to have the same detectability based on NPW, and the detectability of CHO was calculated accordingly. For human observer study, 3 trained observers performed 2AFC detection tasks, and correction rate, Pc, was calculated for each task. By adding proper internal noise level to numerical observer (i.e., NPW and CHO), detectability of human observer was matched with that of numerical observers. Even though target contrasts were adjusted to have the same detectability of NPW observer, detectability of human observer decreases as the target size increases. The internal noise level varies for different target sizes, contrasts, and noise structures, demonstrating different internal noise levels should be considered in numerical observer to predict the detection performance of human observer.

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.

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.

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.

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.

Discriminating between camouflaged targets by their time of detection by a human-based observer assessment method

NASA Astrophysics Data System (ADS)

Selj, G. K.; Søderblom, M.

2015-10-01

Detection of a camouflaged object in natural sceneries requires the target to be distinguishable from its local background. The development of any new camouflage pattern therefore has to rely on a well-founded test methodology - which has to be correlated with the final purpose of the pattern - as well as an evaluation procedure, containing the optimal criteria for i) discriminating between the targets and then eventually ii) for a final rank of the targets. In this study we present results from a recent camouflage assessment trial where human observers were used in a search by photo methodology to assess generic test camouflage patterns. We conducted a study to investigate possible improvements in camouflage patterns for battle dress uniforms. The aim was to do a comparative study of potential, and generic patterns intended for use in arid areas (sparsely vegetated, semi desert). We developed a test methodology that was intended to be simple, reliable and realistic with respect to the operational benefit of camouflage. Therefore we chose to conduct a human based observer trial founded on imagery of realistic targets in natural backgrounds. Inspired by a recent and similar trial in the UK, we developed new and purpose-based software to be able to conduct the observer trial. Our preferred assessment methodology - the observer trial - was based on target recordings in 12 different, but operational relevant scenes, collected in a dry and sparsely vegetated area (Rhodes). The scenes were chosen with the intention to span as broadly as possible. The targets were human-shaped mannequins and were situated identically in each of the scenes to allow for a relative comparison of camouflage effectiveness in each scene. Test of significance, among the targets' performance, was carried out by non-parametric tests as the corresponding time of detection distributions in overall were found to be difficult to parameterize. From the trial, containing 12 different scenes from sparsely vegetated areas we collected detection time's distributions for 6 generic targets through visual search by 148 observers. We found that the different targets performed differently, given by their corresponding time of detection distributions, within a single scene. Furthermore, we gained an overall ranking over all the 12 scenes by performing a weighted sum over all scenes, intended to keep as much of the vital information on the targets' signature effectiveness as possible. Our results show that it was possible to measure the targets performance relatively to another also when summing over all scenes. We also compared our ranking based on our preferred criterion (detection time) with a secondary (probability of detection) to assess the sensitivity of a final ranking based upon the test set-up and evaluation criterion. We found our observer-based approach to be well suited regarding its ability to discriminate between similar targets and to assign numeric values to the observed differences in performance. We believe our approach will be well suited as a tool whenever different aspects of camouflage are to be evaluated and understood further.

Geo-Referenced Dynamic Pushbroom Stereo Mosaics for 3D and Moving Target Extraction - A New Geometric Approach

DTIC Science & Technology

2009-12-01

facilitating reliable stereo matching, occlusion handling, accurate 3D reconstruction and robust moving target detection . We use the fact that all the...a moving platform, we will have to naturally and effectively handle obvious motion parallax and object occlusions in order to be able to detect ...facilitating reliable stereo matching, occlusion handling, accurate 3D reconstruction and robust moving target detection . Based on the above two

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.

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.

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

Research on capability of detecting ballistic missile by near space infrared system

NASA Astrophysics Data System (ADS)

Lu, Li; Sheng, Wen; Jiang, Wei; Jiang, Feng

2018-01-01

The infrared detection technology of ballistic missile based on near space platform can effectively make up the shortcomings of high-cost of traditional early warning satellites and the limited earth curvature of ground-based early warning radar. In terms of target detection capability, aiming at the problem that the formula of the action distance based on contrast performance ignores the background emissivity in the calculation process and the formula is only valid for the monochromatic light, an improved formula of the detecting range based on contrast performance is proposed. The near space infrared imaging system parameters are introduced, the expression of the contrastive action distance formula based on the target detection of the near space platform is deduced. The detection range of the near space infrared system for the booster stage ballistic missile skin, the tail nozzle and the tail flame is calculated. The simulation results show that the near-space infrared system has the best effect on the detection of tail-flame radiation.

Rare targets are less susceptible to attention capture once detection has begun.

PubMed

Hon, Nicholas; Ng, Gavin; Chan, Gerald

2016-04-01

Rare or low probability targets are detected more slowly and/ or less accurately than higher probability counterparts. Various proposals have implicated perceptual and response-based processes in this deficit. Recent evidence, however, suggests that it is attentional in nature, with low probability targets requiring more attentional resources than high probability ones to detect. This difference in attentional requirements, in turn, suggests the possibility that low and high probability targets may have different susceptibilities to attention capture, which is also known to be resource-dependent. Supporting this hypothesis, we found that, once attentional resources have begun to be engaged by detection processes, low, but not high, probability targets have a reduced susceptibility to capture. Our findings speak to several issues. First, they indicate that the likelihood of attention capture occurring when a given task-relevant stimulus is being processed is dependent, to some extent, on how said stimulus is represented within mental task sets. Second, they provide added support for the idea that the behavioural deficit associated with low probability targets is attention-based. Finally, the current data point to reduced top-down biasing of target templates as a likely mechanism underlying the attentional locus of the deficit in question.

Highly sensitive detection of target molecules using a new fluorescence-based bead assay

NASA Astrophysics Data System (ADS)

Scheffler, Silvia; Strauß, Denis; Sauer, Markus

2007-07-01

Development of immunoassays with improved sensitivity, specificity and reliability are of major interest in modern bioanalytical research. We describe the development of a new immunomagnetic fluorescence detection (IM-FD) assay based on specific antigen/antibody interactions and on accumulation of the fluorescence signal on superparamagnetic PE beads in combination with the use of extrinsic fluorescent labels. IM-FD can be easily modified by varying the order of coatings and assay conditions. Depending on the target molecule, antibodies (ABs), entire proteins, or small protein epitopes can be used as capture molecules. The presence of target molecules is detected by fluorescence microscopy using fluorescently labeled secondary or detection antibodies. Here, we demonstrate the potential of the new assay detecting the two tumor markers IGF-I and p53 antibodies in the clinically relevant concentration range. Our data show that the fluorescence-based bead assay exhibits a large dynamic range and a high sensitivity down to the subpicomolar level.

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.

An Underwater Target Detection System for Electro-Optical Imagery Data

DTIC Science & Technology

2010-06-01

detection and segmentation of underwater mine-like objects in the EO images captured with a CCD-based image sensor. The main focus of this research is to...develop a robust detection algorithm that can be used to detect low contrast and partial underwater objects from the EO imagery with low false alarm rate...underwater target detection I. INTRODUCTION Automatic detection and recognition of underwater objects from EO imagery poses a serious challenge due to poor

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

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 DNA detection using cascade amplification strategy based on hybridization chain reaction and enzyme-induced metallization

PubMed Central

Yu, Xu; Zhang, Zhi-Ling; Zheng, Si-Yang

2014-01-01

A novel highly sensitive colorimetric assay for DNA detection using cascade amplification strategy based on hybridization chain reaction and enzyme-induced metallization was established. The DNA modified superparamagnetic beads were demonstrated to capture and enrich the target DNA in the hybridization buffer or human plasma. The hybridization chain reaction and enzyme-induced silver metallization on the gold nanoparticles were used as cascade signal amplification for the detection of target DNA. The metalization of silver on the gold nanoparticles induced a significant colour change from red to yellow until black depending on the concentration of the target DNA, which could be recognized by naked eyes. This method showed a good specificity for the target DNA detection, with the capabilty to discriminate single-base-pair mismatched DNA mutation (single nucleotide polymorphism). Meanwhile, this approach exhibited an excellent anti-interference capability with the convenience of the magentic seperation and washing, which enabled its usage in complex biological systems such as human blood plasma. As an added benefit, the utilization of hybridization chain reaction and enzyme-induced metallization improved detection sensitivity down to 10 pM, which is about 100-fold lower than that of traditional unamplified homogeneous assays. PMID:25500528

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

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.

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.

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.

Analysis of Infrared Signature Variation and Robust Filter-Based Supersonic Target Detection

PubMed Central

Sun, Sun-Gu; Kim, Kyung-Tae

2014-01-01

The difficulty of small infrared target detection originates from the variations of infrared signatures. This paper presents the fundamental physics of infrared target variations and reports the results of variation analysis of infrared images acquired using a long wave infrared camera over a 24-hour period for different types of backgrounds. The detection parameters, such as signal-to-clutter ratio were compared according to the recording time, temperature and humidity. Through variation analysis, robust target detection methodologies are derived by controlling thresholds and designing a temporal contrast filter to achieve high detection rate and low false alarm rate. Experimental results validate the robustness of the proposed scheme by applying it to the synthetic and real infrared sequences. PMID:24672290

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.

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.

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.

Design and Evaluation of Perceptual-based Object Group Selection Techniques

NASA Astrophysics Data System (ADS)

Dehmeshki, Hoda

Selecting groups of objects is a frequent task in graphical user interfaces. It is required prior to many standard operations such as deletion, movement, or modification. Conventional selection techniques are lasso, rectangle selection, and the selection and de-selection of items through the use of modifier keys. These techniques may become time-consuming and error-prone when target objects are densely distributed or when the distances between target objects are large. Perceptual-based selection techniques can considerably improve selection tasks when targets have a perceptual structure, for example when arranged along a line. Current methods to detect such groups use ad hoc grouping algorithms that are not based on results from perception science. Moreover, these techniques do not allow selecting groups with arbitrary arrangements or permit modifying a selection. This dissertation presents two domain-independent perceptual-based systems that address these issues. Based on established group detection models from perception research, the proposed systems detect perceptual groups formed by the Gestalt principles of good continuation and proximity. The new systems provide gesture-based or click-based interaction techniques for selecting groups with curvilinear or arbitrary structures as well as clusters. Moreover, the gesture-based system is adapted for the graph domain to facilitate path selection. This dissertation includes several user studies that show the proposed systems outperform conventional selection techniques when targets form salient perceptual groups and are still competitive when targets are semi-structured.

Post-Translational Modification of Bionanoparticles as a Modular Platform for Biosensor Assembly.

PubMed

Sun, Qing; Chen, Qi; Blackstock, Daniel; Chen, Wilfred

2015-08-25

Context driven biosensor assembly with modular targeting and detection moieties is gaining significant attentions. Although protein-based nanoparticles have emerged as an excellent platform for biosensor assembly, current strategies of decorating bionanoparticles with targeting and detection moieties often suffer from unfavorable spacing and orientation as well as bionanoparticle aggregation. Herein, we report a highly modular post-translational modification approach for biosensor assembly based on sortase A-mediated ligation. This approach enables the simultaneous modifications of the Bacillus stearothermophilus E2 nanoparticles with different functional moieties for antibody, enzyme, DNA aptamer, and dye decoration. The resulting easy-purification platform offers a high degree of targeting and detection modularity with signal amplification. This flexibility is demonstrated for the detection of both immobilized antigens and cancer cells.

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.

Enhanced DNA Sensing via Catalytic Aggregation of Gold Nanoparticles

PubMed Central

Huttanus, Herbert M.; Graugnard, Elton; Yurke, Bernard; Knowlton, William B.; Kuang, Wan; Hughes, William L.; Lee, Jeunghoon

2014-01-01

A catalytic colorimetric detection scheme that incorporates a DNA-based hybridization chain reaction into gold nanoparticles was designed and tested. While direct aggregation forms an inter-particle linkage from only ones target DNA strand, the catalytic aggregation forms multiple linkages from a single target DNA strand. Gold nanoparticles were functionalized with thiol-modified DNA strands capable of undergoing hybridization chain reactions. The changes in their absorption spectra were measured at different times and target concentrations and compared against direct aggregation. Catalytic aggregation showed a multifold increase in sensitivity at low target concentrations when compared to direct aggregation. Gel electrophoresis was performed to compare DNA hybridization reactions in catalytic and direct aggregation schemes, and the product formation was confirmed in the catalytic aggregation scheme at low levels of target concentrations. The catalytic aggregation scheme also showed high target specificity. This application of a DNA reaction network to gold nanoparticle-based colorimetric detection enables highly-sensitive, field-deployable, colorimetric readout systems capable of detecting a variety of biomolecules. PMID:23891867

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

PubMed

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

2016-09-29

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

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

PubMed Central

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

2016-01-01

The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system’s capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications. PMID:27690051

Radiation and Electromagnetic Induction Data Fusion for Detection of Buried Radioactive Metal Waste - 12282

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

Long, Zhiling; Wei, Wei; Turlapaty, Anish

2012-07-01

At the United States Army's test sites, fired penetrators made of Depleted Uranium (DU) have been buried under ground and become hazardous waste. Previously, we developed techniques for detecting buried radioactive targets. We also developed approaches for locating buried paramagnetic metal objects by utilizing the electromagnetic induction (EMI) sensor data. In this paper, we apply data fusion techniques to combine results from both the radiation detection and the EMI detection, so that we can further distinguish among DU penetrators, DU oxide, and non- DU metal debris. We develop a two-step fusion approach for the task, and test it with surveymore » data collected on simulation targets. In this work, we explored radiation and EMI data fusion for detecting DU, oxides, and non-DU metals. We developed a two-step fusion approach based on majority voting and a set of decision rules. With this approach, we fuse results from radiation detection based on the RX algorithm and EMI detection based on a 3-step analysis. Our fusion approach has been tested successfully with data collected on simulation targets. In the future, we will need to further verify the effectiveness of this fusion approach with field data. (authors)« less

Autonomous Exploration for Gathering Increased Science

NASA Technical Reports Server (NTRS)

Bornstein, Benjamin J.; Castano, Rebecca; Estlin, Tara A.; Gaines, Daniel M.; Anderson, Robert C.; Thompson, David R.; DeGranville, Charles K.; Chien, Steve A.; Tang, Benyang; Burl, Michael C.;

Target scattering characteristics for OAM-based radar

NASA Astrophysics Data System (ADS)

Liu, Kang; Gao, Yue; Li, Xiang; Cheng, Yongqiang

2018-02-01

The target scattering characteristics are crucial for radar systems. However, there is very little study conducted for the recently developed orbital angular momentum (OAM) based radar system. To illustrate the role of OAM-based radar cross section (ORCS), conventional radar equation is modified by taking characteristics of the OAM waves into account. Subsequently, the ORCS is defined in analogy to classical radar cross section (RCS). The unique features of the incident OAM-carrying field are analyzed. The scattered field is derived, and the analytical expressions of ORCSs for metal plate and cylinder targets are obtained. Furthermore, the ORCS and RCS are compared to illustrate the influences of OAM mode number, target size and signal frequency on the ORCS. Analytical studies demonstrate that the mirror-reflection phenomenon disappears and peak values of ORCS are in the non-specular direction. Finally, the ORCS features are summarized to show its advantages in radar target detection. This work can provide theoretical guidance to the design of OAM-based radar as well as the target detection and identification applications.

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.

A molecular beacon based on DNA-templated silver nanoclusters for the highly sensitive and selective multiplexed detection of virulence genes.

PubMed

Han, Dan; Wei, Chunying

2018-05-01

In this work, we develop a fluorescent molecular beacon based on the DNA-templated silver nanoclusters (DNA-Ag NCs). The skillfully designed molecular beacon can be conveniently used for detection of diverse virulence genes as long as the corresponding recognition sequences are embedded. Importantly, the constructed detection system allows simultaneous detection of multiple nucleic acids, which is attributed to non-overlapping emission spectra of the as-synthesized silver nanoclusters. Based on the target-induced fluorescence enhancement, three infectious disease-related genes HIV, H1N1, and H5N1 are detected, and the corresponding detection limits are 3.53, 0.12 and 3.95nM, respectively. This design allows specific, versatile and simultaneous detection of diverse targets with easy operation and low cost. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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.

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

PubMed

Lin, Douglas I; Hecht, Jonathan L

2016-06-01

Endometrial cancer is associated with Lynch syndrome in 2% to 6% of cases. Adequate screening may prevent of a second cancer and incident cancers in family members via risk-reducing strategies. The goal of the study was to evaluate the detection rate of Lynch syndrome via a targeted screening approach. In 2009, we incorporated targeted Lynch syndrome screening via immunohistochemistry for MLH1, PMS2, MSH2, and MSH6, followed by MLH1 promoter hypermethylation, in select cases of endometrial carcinoma. Criteria for patient selection included (1) all patients <50 years; (2) patients of any age with tumors showing features of microsatellite instability (lower uterine segment-centered tumors, hard to classify carcinomas, increased peritumoral or tumor infiltrating lymphocytes and cases with synchronous ovarian carcinomas); (3) clinician's request based on family or personal history; and (4) ad hoc retrospective testing based on the established criteria on patients discovered on follow-up visits. By using a targeted screening approach in a 4.5-year period, approximately 2.1% of endometrial cancers (7 of 328) were potentially associated with Lynch syndrome. Therefore, targeted screening with combined age and morphology based criteria enriches detection of Lynch syndrome in endometrial cancer. However, the detection rate is lower than the rates from published series that offer universal screening. © The Author(s) 2016.

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.

High-throughput screening based on label-free detection of small molecule microarrays

NASA Astrophysics Data System (ADS)

Zhu, Chenggang; Fei, Yiyan; Zhu, Xiangdong

2017-02-01

Based on small-molecule microarrays (SMMs) and oblique-incidence reflectivity difference (OI-RD) scanner, we have developed a novel high-throughput drug preliminary screening platform based on label-free monitoring of direct interactions between target proteins and immobilized small molecules. The screening platform is especially attractive for screening compounds against targets of unknown function and/or structure that are not compatible with functional assay development. In this screening platform, OI-RD scanner serves as a label-free detection instrument which is able to monitor about 15,000 biomolecular interactions in a single experiment without the need to label any biomolecule. Besides, SMMs serves as a novel format for high-throughput screening by immobilization of tens of thousands of different compounds on a single phenyl-isocyanate functionalized glass slide. Based on the high-throughput screening platform, we sequentially screened five target proteins (purified target proteins or cell lysate containing target protein) in high-throughput and label-free mode. We found hits for respective target protein and the inhibition effects for some hits were confirmed by following functional assays. Compared to traditional high-throughput screening assay, the novel high-throughput screening platform has many advantages, including minimal sample consumption, minimal distortion of interactions through label-free detection, multi-target screening analysis, which has a great potential to be a complementary screening platform in the field of drug discovery.

An amplified graphene oxide-based fluorescence aptasensor based on target-triggered aptamer hairpin switch and strand-displacement polymerization recycling for bioassays.

PubMed

Hu, Kun; Liu, Jinwen; Chen, Jia; Huang, Yong; Zhao, Shulin; Tian, Jianniao; Zhang, Guohai

2013-04-15

An amplified graphene oxide (GO) based fluorescence aptasensor based on target-triggered aptamer hairpin switch and strand-displacement polymerization recycling is developed for bioassays. The dye-labeled single-strand DNA (aptamer hairpin) was adsorbed on the surface of GO, which result in the fluorescence quenching of dye, and exhibiting minimal background fluorescence. Upon the target, primer and polymerase, the stem of the aptamer hairpin was opened, and binds with the primer to triggers the circular target strand-displacement polymerization reaction, which produces huge amounts of duplex helixes DNA and lead to strong fluorescence emission due to shielding of nucelobases within its double-helix structure. During the polymerization reaction, the primer was extended, and target was displaced. And the displaced target recognizes and hybridizes with another hairpin probe, triggering the next round of polymerization reaction, and the circle process induces fluorescence signal amplification for the detection of analyte. To test the feasibility of the aptasensor systems, interferon-gamma (IFN-γ) was employed as a model analyte. A detection limit as low as 1.5 fM is obtained based on the GO aptasensor with a linear range of three orders of magnitude. The present method was successfully applied for the detection of IFN-γ in human plasma. Copyright © 2012 Elsevier B.V. All rights reserved.

Space-based infrared sensors of space target imaging effect analysis

NASA Astrophysics Data System (ADS)

Dai, Huayu; Zhang, Yasheng; Zhou, Haijun; Zhao, Shuang

2018-02-01

Target identification problem is one of the core problem of ballistic missile defense system, infrared imaging simulation is an important means of target detection and recognition. This paper first established the space-based infrared sensors ballistic target imaging model of point source on the planet's atmosphere; then from two aspects of space-based sensors camera parameters and target characteristics simulated atmosphere ballistic target of infrared imaging effect, analyzed the camera line of sight jitter, camera system noise and different imaging effects of wave on the target.

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.

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.

Quantum Illumination-Based Target Detection and Discrimination

DTIC Science & Technology

2014-06-30

amplifier (EDFA) was combined with the signal to simulate a high-noise environment, with a noise photon number per mode NB in the range 40–300. The...Research Triangle Park, NC 27709-2211 quantum communication, target detection, entanglement , parametric downconversion, optical parametric amplifiers...laser system of the same average transmitted photon number, when the target return has random-amplitude behavior. Receiver operating characteristic

Improved detection and false alarm rejection using FLGPR and color imagery in a forward-looking system

NASA Astrophysics Data System (ADS)

Havens, Timothy C.; Spain, Christopher J.; Ho, K. C.; Keller, James M.; Ton, Tuan T.; Wong, David C.; Soumekh, Mehrdad

2010-04-01

Forward-looking ground-penetrating radar (FLGPR) has received a significant amount of attention for use in explosivehazards detection. A drawback to FLGPR is that it results in an excessive number of false detections. This paper presents our analysis of the explosive-hazards detection system tested by the U.S. Army Night Vision and Electronic Sensors Directorate (NVESD). The NVESD system combines an FLGPR with a visible-spectrum color camera. We present a target detection algorithm that uses a locally-adaptive detection scheme with spectrum-based features. The remaining FLGPR detections are then projected into the camera imagery and image-based features are collected. A one-class classifier is then used to reduce the number of false detections. We show that our proposed FLGPR target detection algorithm, coupled with our camera-based false alarm (FA) reduction method, is effective at reducing the number of FAs in test data collected at a US Army test facility.

A Sensitive DNA Capacitive Biosensor Using Interdigitated Electrodes

PubMed Central

Wang, Lei; Veselinovic, Milena; Yang, Lang; Geiss, Brian J.; Dandy, David S.; Chen, Tom

2017-01-01

This paper presents a label-free affinity-based capacitive biosensor using interdigitated electrodes. Using an optimized process of DNA probe preparation to minimize the effect of contaminants in commercial thiolated DNA probe, the electrode surface was functionalized with the 24-nucleotide DNA probes based on the West Nile virus sequence (Kunjin strain). The biosensor has the ability to detect complementary DNA fragments with a detection limit down to 20 DNA target molecules (1.5 aM range), making it suitable for a practical point-of-care (POC) platform for low target count clinical applications without the need for amplification. The reproducibility of the biosensor detection was improved with efficient covalent immobilization of purified single-stranded DNA probe oligomers on cleaned gold microelectrodes. In addition to the low detection limit, the biosensor showed a dynamic range of detection from 1 μL−1 to 105 μL−1 target molecules (20 to 2 million targets), making it suitable for sample analysis in a typical clinical application environment. The binding results presented in this paper were validated using fluorescent oligomers. PMID:27619528

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-05-01

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

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-09-01

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

Object tracking algorithm based on the color histogram probability distribution

NASA Astrophysics Data System (ADS)

Li, Ning; Lu, Tongwei; Zhang, Yanduo

2018-04-01

In order to resolve tracking failure resulted from target's being occlusion and follower jamming caused by objects similar to target in the background, reduce the influence of light intensity. This paper change HSV and YCbCr color channel correction the update center of the target, continuously updated image threshold self-adaptive target detection effect, Clustering the initial obstacles is roughly range, shorten the threshold range, maximum to detect the target. In order to improve the accuracy of detector, this paper increased the Kalman filter to estimate the target state area. The direction predictor based on the Markov model is added to realize the target state estimation under the condition of background color interference and enhance the ability of the detector to identify similar objects. The experimental results show that the improved algorithm more accurate and faster speed of processing.

Real Time Intelligent Target Detection and Analysis with Machine Vision

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

2000-01-01

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

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.

Laser based in-situ and standoff detection of chemical warfare agents and explosives

NASA Astrophysics Data System (ADS)

Patel, C. Kumar N.

2009-09-01

Laser based detection of gaseous, liquid and solid residues and trace amounts has been developed ever since lasers were invented. However, the lack of availability of reasonably high power tunable lasers in the spectral regions where the relevant targets can be interrogated as well as appropriate techniques for high sensitivity, high selectivity detection has hampered the practical exploitation of techniques for the detection of targets important for homeland security and defense applications. Furthermore, emphasis has been on selectivity without particular attention being paid to the impact of interfering species on the quality of detection. Having high sensitivity is necessary but not a sufficient condition. High sensitivity assures a high probability of detection of the target species. However, it is only recently that the sensor community has come to recognize that any measure of probability of detection must be associated with a probability of false alarm, if it is to have any value as a measure of performance. This is especially true when one attempts to compare performance characteristics of different sensors based on different physical principles. In this paper, I will provide a methodology for characterizing the performance of sensors utilizing optical absorption measurement techniques. However, the underlying principles are equally application to all other sensors. While most of the current progress in high sensitivity, high selectivity detection of CWAs, TICs and explosives involve identifying and quantifying the target species in-situ, there is an urgent need for standoff detection of explosives from safe distances. I will describe our results on CO2 and quantum cascade laser (QCL) based photoacoustic sensors for the detection of CWAs, TICs and explosives as well the very new results on stand-off detection of explosives at distances up to 150 meters. The latter results are critically important for assuring safety of military personnel in battlefield environment, especially from improvised explosive devices (IEDs), and of civilian personnel from terrorist attacks in metropolitan areas.

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.

A manifold learning approach to target detection in high-resolution hyperspectral imagery

NASA Astrophysics Data System (ADS)

Ziemann, Amanda K.

Imagery collected from airborne platforms and satellites provide an important medium for remotely analyzing the content in a scene. In particular, the ability to detect a specific material within a scene is of high importance to both civilian and defense applications. This may include identifying "targets" such as vehicles, buildings, or boats. Sensors that process hyperspectral images provide the high-dimensional spectral information necessary to perform such analyses. However, for a d-dimensional hyperspectral image, it is typical for the data to inherently occupy an m-dimensional space, with m << d. In the remote sensing community, this has led to a recent increase in the use of manifold learning, which aims to characterize the embedded lower-dimensional, non-linear manifold upon which the hyperspectral data inherently lie. Classic hyperspectral data models include statistical, linear subspace, and linear mixture models, but these can place restrictive assumptions on the distribution of the data; this is particularly true when implementing traditional target detection approaches, and the limitations of these models are well-documented. With manifold learning based approaches, the only assumption is that the data reside on an underlying manifold that can be discretely modeled by a graph. The research presented here focuses on the use of graph theory and manifold learning in hyperspectral imagery. Early work explored various graph-building techniques with application to the background model of the Topological Anomaly Detection (TAD) algorithm, which is a graph theory based approach to anomaly detection. This led towards a focus on target detection, and in the development of a specific graph-based model of the data and subsequent dimensionality reduction using manifold learning. An adaptive graph is built on the data, and then used to implement an adaptive version of locally linear embedding (LLE). We artificially induce a target manifold and incorporate it into the adaptive LLE transformation; the artificial target manifold helps to guide the separation of the target data from the background data in the new, lower-dimensional manifold coordinates. Then, target detection is performed in the manifold space.

Hairpin DNA Switch for Ultrasensitive Spectrophotometric Detection of DNA Hybridization Based on Gold Nanoparticles and Enzyme Signal Amplification

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

Zhang, Youyu; Tang, Zhiwen; Wang, Jun

2010-08-01

A novel DNA detection platform based on a hairpin-DNA switch, nanoparticles, and enzyme signal amplification for ultrasensitive detection of DNA hybridization has been developed in this work. In this DNA assay, a “stem-loop” DNA probe dually labeled with a thiol at its 5’ end and a biotin at its 3’ end, respectively, was used. This probe was immobilized on the gold nanoparticles (AuNPs) anchored by a protein, globulin, on a 96-well microplate. In the absence of target DNA, the immobilized probe with the stem-loop structure shields the biotin from being approached by a bulky horseradish peroxidase linked-avidin (avidin-HRP) conjugate duemore » to the steric hindrance. However, in the presence of target DNA, the hybridization between the hairpin DNA probe and the target DNA causes significant conformational change of the probe, which forces biotin away from the surface of AuNPs. As a result, the biotin becomes accessible by the avidin-HRP, and the target hybridization event can be sensitively detected via the HRP catalyzed substrate 3, 3', 5, 5'-tetramethylbenzidine using spectrophometric method. Some experimental parameters governing the performance of the assay have been optimized. At optimal conditions, this DNA assay can detect DNA at the concentration of femtomolar level by means of a signal amplification strategy based on the combination of enzymes and nanoparticles. This approach also has shown excellent specificity to distinguish single-base mismatches of DNA targets because of the intrinsic high selectivity of the hairpin DNA probe.« less

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.

Utilizing Intrinsic Properties of Polyaniline to Detect Nucleic Acid Hybridization through UV-Enhanced Electrostatic Interaction.

PubMed

Sengupta, Partha Pratim; Gloria, Jared N; Amato, Dahlia N; Amato, Douglas V; Patton, Derek L; Murali, Beddhu; Flynt, Alex S

2015-10-12

Detection of specific RNA or DNA molecules by hybridization to "probe" nucleic acids via complementary base-pairing is a powerful method for analysis of biological systems. Here we describe a strategy for transducing hybridization events through modulating intrinsic properties of the electroconductive polymer polyaniline (PANI). When DNA-based probes electrostatically interact with PANI, its fluorescence properties are increased, a phenomenon that can be enhanced by UV irradiation. Hybridization of target nucleic acids results in dissociation of probes causing PANI fluorescence to return to basal levels. By monitoring restoration of base PANI fluorescence as little as 10(-11) M (10 pM) of target oligonucleotides could be detected within 15 min of hybridization. Detection of complementary oligos was specific, with introduction of a single mismatch failing to form a target-probe duplex that would dissociate from PANI. Furthermore, this approach is robust and is capable of detecting specific RNAs in extracts from animals. This sensor system improves on previously reported strategies by transducing highly specific probe dissociation events through intrinsic properties of a conducting polymer without the need for additional labels.

A novel track-before-detect algorithm based on optimal nonlinear filtering for detecting and tracking infrared dim target

NASA Astrophysics Data System (ADS)

Tian, Yuexin; Gao, Kun; Liu, Ying; Han, Lu

2015-08-01

Aiming at the nonlinear and non-Gaussian features of the real infrared scenes, an optimal nonlinear filtering based algorithm for the infrared dim target tracking-before-detecting application is proposed. It uses the nonlinear theory to construct the state and observation models and uses the spectral separation scheme based Wiener chaos expansion method to resolve the stochastic differential equation of the constructed models. In order to improve computation efficiency, the most time-consuming operations independent of observation data are processed on the fore observation stage. The other observation data related rapid computations are implemented subsequently. Simulation results show that the algorithm possesses excellent detection performance and is more suitable for real-time processing.

The Monitoring, Detection, Isolation and Assessment of Information Warfare Attacks Through Multi-Level, Multi-Scale System Modeling and Model Based Technology

DTIC Science & Technology

2004-01-01

login identity to the one under which the system call is executed, the parameters of the system call execution - file names including full path...Anomaly detection COAST-EIMDT Distributed on target hosts EMERALD Distributed on target hosts and security servers Signature recognition Anomaly...uses a centralized architecture, and employs an anomaly detection technique for intrusion detection. The EMERALD project [80] proposes a

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.

Ultrasensitive and Multiple Disease-Related MicroRNA Detection Based on Tetrahedral DNA Nanostructures and Duplex-Specific Nuclease-Assisted Signal Amplification.

PubMed

Xu, Fang; Dong, Haifeng; Cao, Yu; Lu, Huiting; Meng, Xiangdan; Dai, Wenhao; Zhang, Xueji; Al-Ghanim, Khalid Abdullah; Mahboob, Shahid

2016-12-14

A highly sensitive and multiple microRNA (miRNA) detection method by combining three-dimensional (3D) DNA tetrahedron-structured probes (TSPs) to increase the probe reactivity and accessibility with duplex-specific nuclease (DSN) for signal amplification for sensitive miRNA detection was proposed. Briefly, 3D DNA TSPs labeled with different fluorescent dyes for specific target miRNA recognition were modified on a gold nanoparticle (GNP) surface to increase the reactivity and accessibility. Upon hybridization with a specific target, the TSPs immobilized on the GNP surface hybridized with the corresponding target miRNA to form DNA-RNA heteroduplexes, and the DSN can recognize the formed DNA-RNA heteroduplexes to hydrolyze the DNA in the heteroduplexes to produce a specific fluorescent signal corresponding to a specific miRNA, while the released target miRNA strands can initiate another cycle, resulting in a significant signal amplification for sensitive miRNA detection. Different targets can produce different fluorescent signals, leading to the development of a sensitive detection for multiple miRNAs in a homogeneous solution. Under optimized conditions, the proposed assay can simultaneously detect three different miRNAs in a homogeneous solution with a logarithmic linear range spanning 5 magnitudes (10 -12 -10 -16 ) and achieving a limit of detection down to attomolar concentrations. Meanwhile, the proposed miRNA assay exhibited the capability of discriminating single bases (three bases mismatched miRNAs) and showed good eligibility in the analysis of miRNAs extracted from cell lysates and miRNAs in cell incubation media, which indicates its potential use in biomedical research and clinical analysis.

Continuous, Real-Time Monitoring of Cocaine in Undiluted Blood Serum via a Microfluidic, Electrochemical Aptamer-Based Sensor

PubMed Central

Swensen, James S.; Xiao, Yi; Ferguson, Brian S.; Lubin, Arica A.; Lai, Rebecca Y.; Heeger, Alan J.; Plaxco, Kevin W.; Soh, H. Tom.

2009-01-01

The development of a biosensor system capable of continuous, real-time measurement of small-molecule analytes directly in complex, unprocessed aqueous samples has been a significant challenge, and successful implementation has been achieved for only a limited number of targets. Towards a general solution to this problem, we report here the Microfluidic Electrochemical Aptamer-based Sensor (MECAS) chip wherein we integrate target-specific DNA aptamers that fold, and thus generate an electrochemical signal, in response to the analyte with a microfluidic detection system. As a model, we demonstrate the continuous, real-time (~1 minute time resolution) detection of the small molecule drug cocaine at near physiological, low micromolar concentrations directly in undiluted, otherwise unmodified blood serum. We believe our approach of integrating folding-based electrochemical sensors with miniaturized detection systems may lay the ground work for the real-time, point-of-care detection of a wide variety of molecular targets. PMID:19271708

Preparation of genosensor for detection of specific DNA sequence of the hepatitis B virus

NASA Astrophysics Data System (ADS)

Honorato Castro, Ana C.; França, Erick G.; de Paula, Lucas F.; Soares, Marcia M. C. N.; Goulart, Luiz R.; Madurro, João M.; Brito-Madurro, Ana G.

2014-09-01

An electrochemical genosensor was constructed for detection of specific DNA sequence of the hepatitis B virus, based on graphite electrodes modified with poly(4-aminophenol) and incorporating a specific oligonucleotide probe. The modified electrode containing the probe was evaluated by differential pulse voltammetry, before and after incubation with the complementary oligonucleotide target. Detection was performed by monitoring oxidizable DNA bases (direct detection) or using ethidium bromide as indicator of the hybridization process (indirect detection). The device showed a detection limit for the oligonucleotide target of 2.61 nmol L-1. Indirect detection using ethidium bromide was promising in discriminating mismatches, which is a very desirable attribute for detection of disease-related point mutations. In addition, it was possible to observe differences between hybridized and non-hybridized surfaces by atomic force microscopy.

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

PubMed

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

2007-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2007-11-01

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

Simulation of target interpretation based on infrared image features and psychology principle

NASA Astrophysics Data System (ADS)

Lin, Wei; Chen, Yu-hua; Gao, Hong-sheng; Wang, Zhan-feng; Wang, Ji-jun; Su, Rong-hua; Huang, Yan-ping

2009-07-01

It's an important and complicated process in target interpretation that target features extraction and identification, which effect psychosensorial quantity of interpretation person to target infrared image directly, and decide target viability finally. Using statistical decision theory and psychology principle, designing four psychophysical experiment, the interpretation model of the infrared target is established. The model can get target detection probability by calculating four features similarity degree between target region and background region, which were plotted out on the infrared image. With the verification of a great deal target interpretation in practice, the model can simulate target interpretation and detection process effectively, get the result of target interpretation impersonality, which can provide technique support for target extraction, identification and decision-making.

A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units

PubMed Central

Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik

2017-01-01

This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions. PMID:28208684

A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units.

PubMed

Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik

2017-02-12

This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions.

A cooperative-binding split aptamer assay for rapid, specific and ultra-sensitive fluorescence detection of cocaine in saliva† †Electronic supplementary information (ESI) available: Optimization of Mg2+ and ATMND concentrations for our CBSA-based ATMND-binding assay; ATMND-reported calibration curve for CBSA-5325 at various cocaine concentrations; ATMND binding affinity for the cocaine-assembled CBSA-5325; K D of 38-GC and different 38-GC mutants for cocaine as characterized by ITC; stem length effects on cocaine-induced CBSA assembly; spectra of CBSA-5335-based fluorescence detection of cocaine in 1× binding buffer; characterization of cocaine binding affinity of CBSA-5335 and PSA using ITC; fluorescence detection of cocaine in saliva with our fluorophore/quencher modified CBSA-5335; calibration curve of our CBSA-5335-based fluorophore/quencher assay in 1× binding buffer and 10% saliva at cocaine concentrations ranging from 0 to 10 μM; bias and precision of the CBSA-5335-based fluorophore/quencher assay; comparison of amplification-free split-aptamer assays for cocaine detection; sequence ID and DNA sequences used in this work. See DOI: 10.1039/c6sc01833e Click here for additional data file.

PubMed Central

Yu, Haixiang; Canoura, Juan; Guntupalli, Bhargav; Lou, Xinhui

2017-01-01

Sensors employing split aptamers that reassemble in the presence of a target can achieve excellent specificity, but the accompanying reduction of target affinity mitigates any overall gains in sensitivity. We for the first time have developed a split aptamer that achieves enhanced target-binding affinity through cooperative binding. We have generated a split cocaine-binding aptamer that incorporates two binding domains, such that target binding at one domain greatly increases the affinity of the second domain. We experimentally demonstrate that the resulting cooperative-binding split aptamer (CBSA) exhibits higher target binding affinity and is far more responsive in terms of target-induced aptamer assembly compared to the single-domain parent split aptamer (PSA) from which it was derived. We further confirm that the target-binding affinity of our CBSA can be affected by the cooperativity of its binding domains and the intrinsic affinity of its PSA. To the best of our knowledge, CBSA-5335 has the highest cocaine affinity of any split aptamer described to date. The CBSA-based assay also demonstrates excellent performance in target detection in complex samples. Using this CBSA, we achieved specific, ultra-sensitive, one-step fluorescence detection of cocaine within fifteen minutes at concentrations as low as 50 nM in 10% saliva without signal amplification. This limit of detection meets the standards recommended by the European Union's Driving under the Influence of Drugs, Alcohol and Medicines program. Our assay also demonstrates excellent reproducibility of results, confirming that this CBSA-platform represents a robust and sensitive means for cocaine detection in actual clinical samples. PMID:28451157

Truncated feature representation for automatic target detection using transformed data-based decomposition

NASA Astrophysics Data System (ADS)

Riasati, Vahid R.

2016-05-01

In this work, the data covariance matrix is diagonalized to provide an orthogonal bases set using the eigen vectors of the data. The eigen-vector decomposition of the data is transformed and filtered in the transform domain to truncate the data for robust features related to a specified set of targets. These truncated eigen features are then combined and reconstructed to utilize in a composite filter and consequently utilized for the automatic target detection of the same class of targets. The results associated with the testing of the current technique are evaluated using the peak-correlation and peak-correlation energy metrics and are presented in this work. The inverse transformed eigen-bases of the current technique may be thought of as an injected sparsity to minimize data in representing the skeletal data structure information associated with the set of targets under consideration.

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).

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

PubMed

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

2018-02-23

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

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.

Knowledge-based tracking algorithm

NASA Astrophysics Data System (ADS)

Corbeil, Allan F.; Hawkins, Linda J.; Gilgallon, Paul F.

1990-10-01

This paper describes the Knowledge-Based Tracking (KBT) algorithm for which a real-time flight test demonstration was recently conducted at Rome Air Development Center (RADC). In KBT processing, the radar signal in each resolution cell is thresholded at a lower than normal setting to detect low RCS targets. This lower threshold produces a larger than normal false alarm rate. Therefore, additional signal processing including spectral filtering, CFAR and knowledge-based acceptance testing are performed to eliminate some of the false alarms. TSC's knowledge-based Track-Before-Detect (TBD) algorithm is then applied to the data from each azimuth sector to detect target tracks. In this algorithm, tentative track templates are formed for each threshold crossing and knowledge-based association rules are applied to the range, Doppler, and azimuth measurements from successive scans. Lastly, an M-association out of N-scan rule is used to declare a detection. This scan-to-scan integration enhances the probability of target detection while maintaining an acceptably low output false alarm rate. For a real-time demonstration of the KBT algorithm, the L-band radar in the Surveillance Laboratory (SL) at RADC was used to illuminate a small Cessna 310 test aircraft. The received radar signal wa digitized and processed by a ST-100 Array Processor and VAX computer network in the lab. The ST-100 performed all of the radar signal processing functions, including Moving Target Indicator (MTI) pulse cancelling, FFT Doppler filtering, and CFAR detection. The VAX computers performed the remaining range-Doppler clustering, beamsplitting and TBD processing functions. The KBT algorithm provided a 9.5 dB improvement relative to single scan performance with a nominal real time delay of less than one second between illumination and display.

Application of a SERS-based lateral flow immunoassay strip for the rapid and sensitive detection of staphylococcal enterotoxin B

NASA Astrophysics Data System (ADS)

Hwang, Joonki; Lee, Sangyeop; Choo, Jaebum

2016-06-01

A novel surface-enhanced Raman scattering (SERS)-based lateral flow immunoassay (LFA) biosensor was developed to resolve problems associated with conventional LFA strips (e.g., limits in quantitative analysis and low sensitivity). In our SERS-based biosensor, Raman reporter-labeled hollow gold nanospheres (HGNs) were used as SERS detection probes instead of gold nanoparticles. With the proposed SERS-based LFA strip, the presence of a target antigen can be identified through a colour change in the test zone. Furthermore, highly sensitive quantitative evaluation is possible by measuring SERS signals from the test zone. To verify the feasibility of the SERS-based LFA strip platform, an immunoassay of staphylococcal enterotoxin B (SEB) was performed as a model reaction. The limit of detection (LOD) for SEB, as determined with the SERS-based LFA strip, was estimated to be 0.001 ng mL-1. This value is approximately three orders of magnitude more sensitive than that achieved with the corresponding ELISA-based method. The proposed SERS-based LFA strip sensor shows significant potential for the rapid and sensitive detection of target markers in a simplified manner.A novel surface-enhanced Raman scattering (SERS)-based lateral flow immunoassay (LFA) biosensor was developed to resolve problems associated with conventional LFA strips (e.g., limits in quantitative analysis and low sensitivity). In our SERS-based biosensor, Raman reporter-labeled hollow gold nanospheres (HGNs) were used as SERS detection probes instead of gold nanoparticles. With the proposed SERS-based LFA strip, the presence of a target antigen can be identified through a colour change in the test zone. Furthermore, highly sensitive quantitative evaluation is possible by measuring SERS signals from the test zone. To verify the feasibility of the SERS-based LFA strip platform, an immunoassay of staphylococcal enterotoxin B (SEB) was performed as a model reaction. The limit of detection (LOD) for SEB, as determined with the SERS-based LFA strip, was estimated to be 0.001 ng mL-1. This value is approximately three orders of magnitude more sensitive than that achieved with the corresponding ELISA-based method. The proposed SERS-based LFA strip sensor shows significant potential for the rapid and sensitive detection of target markers in a simplified manner. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr07243c

Constrained sampling experiments reveal principles of detection in natural scenes.

PubMed

Sebastian, Stephen; Abrams, Jared; Geisler, Wilson S

2017-07-11

A fundamental everyday visual task is to detect target objects within a background scene. Using relatively simple stimuli, vision science has identified several major factors that affect detection thresholds, including the luminance of the background, the contrast of the background, the spatial similarity of the background to the target, and uncertainty due to random variations in the properties of the background and in the amplitude of the target. Here we use an experimental approach based on constrained sampling from multidimensional histograms of natural stimuli, together with a theoretical analysis based on signal detection theory, to discover how these factors affect detection in natural scenes. We sorted a large collection of natural image backgrounds into multidimensional histograms, where each bin corresponds to a particular luminance, contrast, and similarity. Detection thresholds were measured for a subset of bins spanning the space, where a natural background was randomly sampled from a bin on each trial. In low-uncertainty conditions, both the background bin and the amplitude of the target were fixed, and, in high-uncertainty conditions, they varied randomly on each trial. We found that thresholds increase approximately linearly along all three dimensions and that detection accuracy is unaffected by background bin and target amplitude uncertainty. The results are predicted from first principles by a normalized matched-template detector, where the dynamic normalizing gain factor follows directly from the statistical properties of the natural backgrounds. The results provide an explanation for classic laws of psychophysics and their underlying neural mechanisms.

Multi-color IR sensors based on QWIP technology for security and surveillance applications

NASA Astrophysics Data System (ADS)

Sundaram, Mani; Reisinger, Axel; Dennis, Richard; Patnaude, Kelly; Burrows, Douglas; Cook, Robert; Bundas, Jason

2006-05-01

Room-temperature targets are detected at the furthest distance by imaging them in the long wavelength (LW: 8-12 μm) infrared spectral band where they glow brightest. Focal plane arrays (FPAs) based on quantum well infrared photodetectors (QWIPs) have sensitivity, noise, and cost metrics that have enabled them to become the best commercial solution for certain security and surveillance applications. Recently, QWIP technology has advanced to provide pixelregistered dual-band imaging in both the midwave (MW: 3-5 μm) and longwave infrared spectral bands in a single chip. This elegant technology affords a degree of target discrimination as well as the ability to maximize detection range for hot targets (e.g. missile plumes) by imaging in the midwave and for room-temperature targets (e.g. humans, trucks) by imaging in the longwave with one simple camera. Detection-range calculations are illustrated and FPA performance is presented.

Biosensors based on DNA-Functionalized Graphene

NASA Astrophysics Data System (ADS)

Vishnubhotla, Ramya; Ping, Jinglei; Vrudhula, Amey; Johnson, A. T. Charlie

Since its discovery, graphene has been used for sensing applications due to its outstanding electrical properties and biocompatibility. Here, we demonstrate the capabilities of field effect transistors (FETs) based on CVD-grown graphene functionalized with commercially obtained DNA oligomers and aptamers for detection of various biomolecular targets (e.g., complementary DNA and small molecule drug targets). Graphene FETs were created with a scalable photolithography process that produces arrays consisting of 50-100 FETs with a layout suitable for multiplexed detection of four molecular targets. FETs were characterized via AFM to confirm the presence of the aptamer. From the measured electrical characteristics, it was determined that binding of molecular targets by the DNA chemical recognition element led to a reproducible, concentration-dependent shift in the Dirac voltage. This biosensor class is potentially suitable for applications in drug detection. This work is funded by NIH through the Center for AIDS Research at the University of Pennsylvania.

The feature extraction of "cat-eye" targets based on bi-spectrum

NASA Astrophysics Data System (ADS)

Zhang, Tinghua; Fan, Guihua; Sun, Huayan

2016-10-01

In order to resolve the difficult problem of detection and identification of optical targets in complex background or in long-distance transmission, this paper mainly study the range profiles of "cat-eye" targets using bi-spectrum. For the problems of laser echo signal attenuation serious and low Signal-Noise Ratio (SNR), the multi-pulse laser signal echo signal detection algorithm which is based on high-order cumulant, filter processing and the accumulation of multi-pulse is proposed. This could improve the detection range effectively. In order to extract the stable characteristics of the one-dimensional range profile coming from the cat-eye targets, a method is proposed which extracts the bi-spectrum feature, and uses the singular value decomposition to simplify the calculation. Then, by extracting data samples of different distance, type and incidence angle, verify the stability of the eigenvector and effectiveness extracted by bi-spectrum.

Improving Target Detection in Visual Search Through the Augmenting Multi-Sensory Cues

DTIC Science & Technology

2013-01-01

target detection, visual search James Merlo, Joseph E. Mercado , Jan B.F. Van Erp, Peter A. Hancock University of Central Florida 12201 Research Parkway...were controlled by a purpose-created, LabView- based software computer program that synchronised the respective displays and recorded response times and

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

PubMed

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-11-24

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

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

PubMed Central

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-01-01

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

Research on regional intrusion prevention and control system based on target tracking

NASA Astrophysics Data System (ADS)

Liu, Yanfei; Wang, Jieling; Jiang, Ke; He, Yanhui; Wu, Zhilin

2017-08-01

In view of the fact that China’s border is very long and the border prevention and control measures are single, we designed a regional intrusion prevention and control system which based on target-tracking. The system consists of four parts: solar panel, radar, electro-optical equipment, unmanned aerial vehicle and intelligent tracking platform. The solar panel provides independent power for the entire system. The radar detects the target in real time and realizes the high precision positioning of suspicious targets, then through the linkage of electro-optical equipment, it can achieve full-time automatic precise tracking of targets. When the target appears within the range of detection, the drone will be launched to continue the tracking. The system is mainly to realize the full time, full coverage, whole process integration and active realtime control of the border area.

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.

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

NASA Astrophysics Data System (ADS)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

Navy Acquisition: Development of the AN/BSY-1 Combat System

DTIC Science & Technology

1992-01-01

AN/BSY-1, a computer-based combat system, is designed to detect, classify, track, and launch weapons at enemy surface, subsurface, and land targets. The Navy expects the AN/BSY-1 system to locate targets sooner than previous systems, allow operators to perform multiple tasks and address multiple targets concurrently, and reduce the time between detecting a target and launching weapons. The Navy has contracted with the International Business Machines (IBM) Corporation for 23 AN/BSY-1 systems, maintenance and operational trainers, and a software

Design and application of a structured phantom for detection performance comparison between breast tomosynthesis and digital mammography

NASA Astrophysics Data System (ADS)

Cockmartin, L.; Marshall, N. W.; Zhang, G.; Lemmens, K.; Shaheen, E.; Van Ongeval, C.; Fredenberg, E.; Dance, D. R.; Salvagnini, E.; Michielsen, K.; Bosmans, H.

2017-02-01

This paper introduces and applies a structured phantom with inserted target objects for the comparison of detection performance of digital breast tomosynthesis (DBT) against 2D full field digital mammography (FFDM). The phantom consists of a 48 mm thick breast-shaped polymethyl methacrylate (PMMA) container filled with water and PMMA spheres of different diameters. Three-dimensionally (3D) printed spiculated masses (diameter range: 3.8-9.7 mm) and non-spiculated masses (1.6-6.2 mm) along with microcalcifications (90-250 µm) were inserted as targets. Reproducibility of the phantom application was studied on a single system using 30 acquisitions. Next, the phantom was evaluated on five different combined FFDM & DBT systems and target detection was compared for FFDM and DBT modes. Ten phantom images in both FFDM and DBT modes were acquired on these 5 systems using automatic exposure control. Five readers evaluated target detectability. Images were read with the four-alternative forced-choice (4-AFC) paradigm, with always one segment including a target and 3 normal background segments. The percentage of correct responses (PC) was assessed based on 10 trials of each reader for each object type, size and imaging modality. Additionally, detection threshold diameters at 62.5 PC were assessed via non-linear regression fitting of the psychometric curve. The reproducibility study showed no significant differences in PC values. Evaluation of target detection in FFDM showed that microcalcification detection thresholds ranged between 110 and 118 µm and were similar compared to the detection in DBT (range of 106-158 µm). In DBT, detection of both mass types increased significantly (p  =  0.0001 and p  =  0.0002 for non-spiculated and spiculated masses respectively) compared to FFDM, achieving almost 100% detection for all spiculated mass diameters. In conclusion, a structured phantom with inserted targets was able to show evidence for detectability differences between FFDM and DBT modes for five commercial systems. This phantom has potential for application in task-based assessment at acceptance and commissioning testing of DBT systems.

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

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%.

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.

Target Coverage in Wireless Sensor Networks with Probabilistic Sensors

PubMed Central

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao

2016-01-01

Sensing coverage is a fundamental problem in wireless sensor networks (WSNs), which has attracted considerable attention. Conventional research on this topic focuses on the 0/1 coverage model, which is only a coarse approximation to the practical sensing model. In this paper, we study the target coverage problem, where the objective is to find the least number of sensor nodes in randomly-deployed WSNs based on the probabilistic sensing model. We analyze the joint detection probability of target with multiple sensors. Based on the theoretical analysis of the detection probability, we formulate the minimum ϵ-detection coverage problem. We prove that the minimum ϵ-detection coverage problem is NP-hard and present an approximation algorithm called the Probabilistic Sensor Coverage Algorithm (PSCA) with provable approximation ratios. To evaluate our design, we analyze the performance of PSCA theoretically and also perform extensive simulations to demonstrate the effectiveness of our proposed algorithm. PMID:27618902

Measured Visual Motion Sensitivity at Fixed Contrast in the Periphery and Far Periphery

DTIC Science & Technology

2017-08-01

group Soldier performance. Soldier performance depends on visual detection of enemy personnel and materiel. Vision modeling in IWARS is neither...a highly time-critical and order- dependent activity, these unrealistic characterizations of target detection time and order severely limit the...recognize that MVTs should depend on target contrast, so we selected a target design different from that used in the Monaco et al. (2007) study. Based

Progress of new label-free techniques for biosensors: a review.

PubMed

Sang, Shengbo; Wang, Yajun; Feng, Qiliang; Wei, Ye; Ji, Jianlong; Zhang, Wendong

2016-01-01

The detection techniques used in biosensors can be broadly classified into label-based and label-free. Label-based detection relies on the specific properties of labels for detecting a particular target. In contrast, label-free detection is suitable for the target molecules that are not labeled or the screening of analytes which are not easy to tag. Also, more types of label-free biosensors have emerged with developments in biotechnology. The latest developed techniques in label-free biosensors, such as field-effect transistors-based biosensors including carbon nanotube field-effect transistor biosensors, graphene field-effect transistor biosensors and silicon nanowire field-effect transistor biosensors, magnetoelastic biosensors, optical-based biosensors, surface stress-based biosensors and other type of biosensors based on the nanotechnology are discussed. The sensing principles, configurations, sensing performance, applications, advantages and restriction of different label-free based biosensors are considered and discussed in this review. Most concepts included in this survey could certainly be applied to the development of this kind of biosensor in the future.

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

Detection and Characterization of Viral Species/Subspecies Using Isothermal Recombinase Polymerase Amplification (RPA) Assays.

PubMed

Glais, Laurent; Jacquot, Emmanuel

2015-01-01

Numerous molecular-based detection protocols include an amplification step of the targeted nucleic acids. This step is important to reach the expected sensitive detection of pathogens in diagnostic procedures. Amplifications of nucleic acid sequences are generally performed, in the presence of appropriate primers, using thermocyclers. However, the time requested to amplify molecular targets and the cost of the thermocycler machines could impair the use of these methods in routine diagnostics. Recombinase polymerase amplification (RPA) technique allows rapid (short-term incubation of sample and primers in an enzymatic mixture) and simple (isothermal) amplification of molecular targets. RPA protocol requires only basic molecular steps such as extraction procedures and agarose gel electrophoresis. Thus, RPA can be considered as an interesting alternative to standard molecular-based diagnostic tools. In this paper, the complete procedures to set up an RPA assay, applied to detection of RNA (Potato virus Y, Potyvirus) and DNA (Wheat dwarf virus, Mastrevirus) viruses, are described. The proposed procedure allows developing species- or subspecies-specific detection assay.

A label-free and high-efficient GO-based aptasensor for cancer cells based on cyclic enzymatic signal amplification.

PubMed

Xiao, Kunyi; Liu, Juan; Chen, Hui; Zhang, Song; Kong, Jilie

2017-05-15

A label-free and high-efficient graphene oxide (GO)-based aptasensor was developed for the detection of low quantity cancer cells based on cell-triggered cyclic enzymatic signal amplification (CTCESA). In the absence of target cells, hairpin aptamer probes (HAPs) and dye-labeled linker DNAs stably coexisted in solution, and the fluorescence was quenched by the GO-based FÖrster resonance energy transfer (FRET) process. In the presence of target cells, the specific binding of HAPs with the target cells triggered a conformational alternation, which resulted in linker DNA complementary pairing and cleavage by nicking endonuclease-strand scission cycles. Consequently, more cleaved fragments of linker DNAs with more the terminal labeled dyes could show the enhanced fluorescence because these cleaved DNA fragments hardly combine with GOs and prevent the FRET process. Fluorescence analysis demonstrated that this GO-based aptasensor exhibited selective and sensitive response to the presence of target CCRF-CEM cells in the concentration range from 50 to 10 5 cells. The detection limit of this method was 25 cells, which was approximately 20 times lower than the detection limit of normal fluorescence aptasensors without amplification. With high sensitivity and specificity, it provided a simple and cost-effective approach for early cancer diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Signal-on electrochemical detection of antibiotics at zeptomole level based on target-aptamer binding triggered multiple recycling amplification.

PubMed

Wang, Hongzhi; Wang, Yu; Liu, Su; Yu, Jinghua; Guo, Yuna; Xu, Ying; Huang, Jiadong

2016-06-15

In the work, a signal-on electrochemical DNA sensor based on multiple amplification for ultrasensitive detection of antibiotics has been reported. In the presence of target, the ingeniously designed hairpin probe (HP1) is opened and the polymerase-assisted target recycling amplification is triggered, resulting in autonomous generation of secondary target. It is worth noting that the produced secondary target could not only hybridize with other HP1, but also displace the Helper from the electrode. Consequently, methylene blue labeled HP2 forms a "close" probe structure, and the increase of signal is monitored. The increasing current provides an ultrasensitive electrochemical detection for antibiotics down to 1.3 fM. To our best knowledge, such work is the first report about multiple recycling amplification combing with signal-on sensing strategy, which has been utilized for quantitative determination of antibiotics. It would be further used as a general strategy associated with more analytical techniques toward the detection of a wide spectrum of analytes. Thus, it holds great potential for the development of ultrasensitive biosensing platform for the applications in bioanalysis, disease diagnostics, and clinical biomedicine. Copyright © 2016 Elsevier B.V. All rights reserved.

Resolution Enhanced Magnetic Sensing System for Wide Coverage Real Time UXO Detection

NASA Astrophysics Data System (ADS)

Zalevsky, Zeev; Bregman, Yuri; Salomonski, Nizan; Zafrir, Hovav

2012-09-01

In this paper we present a new high resolution automatic detection algorithm based upon a Wavelet transform and then validate it in marine related experiments. The proposed approach allows obtaining an automatic detection in a very low signal to noise ratios. The amount of calculations is reduced, the magnetic trend is depressed and the probability of detection/ false alarm rate can easily be controlled. Moreover, the algorithm enables to distinguish between close targets. In the algorithm we use the physical dependence of the magnetic field of a magnetic dipole in order to define a Wavelet mother function that later on can detect magnetic targets modeled as dipoles and embedded in noisy surrounding, at improved resolution. The proposed algorithm was realized on synthesized targets and then validated in field experiments involving a marine surface-floating system for wide coverage real time unexploded ordinance (UXO) detection and mapping. The detection probability achieved in the marine experiment was above 90%. The horizontal radial error of most of the detected targets was only 16 m and two baseline targets that were immersed about 20 m one to another could easily be distinguished.

Electrochemical detection of sequence-specific DNA based on formation of G-quadruplex-hemin through continuous hybridization chain reaction.

PubMed

Sun, Xiaofan; Chen, Haohan; Wang, Shuling; Zhang, Yiping; Tian, Yaping; Zhou, Nandi

2018-08-27

A high-sensitive detection of sequence-specific DNA was established based on the formation of G-quadruplex-hemin complex through continuous hybridization chain reaction (HCR). Taking HIV DNA sequence as an example, a capture probe complementary to part of HIV DNA was firstly self-assembled onto the surface of Au electrode. Then a specially designed assistant probe with both terminals complementary to the target DNA and a G-quadruplex-forming sequence in the center was introduced into the detection solution. In the presence of both the target DNA and the assistant probe, the target DNA can be captured on the electrode surface and then a continuous HCR can be conducted due to the mutual recognition of the target DNA and the assistant probe, leading to the formation of a large number of G-quadruplex on the electrode surface. With the help of hemin, a pronounced electrochemical signal can be observed in differential pulse voltammetry (DPV), due to the formation of G-quadruplex-hemin complex. The peak current is linearly related with the logarithm of the concentration of the target DNA in the range from 10 fM to 10 pM. The electrochemical sensor has high selectivity to clearly discriminate single-base mismatched and three-base mismatched sequences from the original HIV DNA sequence. Moreover, the established DNA sensor was challenged by detection of HIV DNA in human serum samples, which showed the low detection limit of 6.3 fM. Thus it has great application prospect in the field of clinical diagnosis and environmental monitoring. Copyright © 2018 Elsevier B.V. All rights reserved.

Real-time classification of vehicles by type within infrared imagery

NASA Astrophysics Data System (ADS)

Kundegorski, Mikolaj E.; Akçay, Samet; Payen de La Garanderie, Grégoire; Breckon, Toby P.

2016-10-01

Real-time classification of vehicles into sub-category types poses a significant challenge within infra-red imagery due to the high levels of intra-class variation in thermal vehicle signatures caused by aspects of design, current operating duration and ambient thermal conditions. Despite these challenges, infra-red sensing offers significant generalized target object detection advantages in terms of all-weather operation and invariance to visual camouflage techniques. This work investigates the accuracy of a number of real-time object classification approaches for this task within the wider context of an existing initial object detection and tracking framework. Specifically we evaluate the use of traditional feature-driven bag of visual words and histogram of oriented gradient classification approaches against modern convolutional neural network architectures. Furthermore, we use classical photogrammetry, within the context of current target detection and classification techniques, as a means of approximating 3D target position within the scene based on this vehicle type classification. Based on photogrammetric estimation of target position, we then illustrate the use of regular Kalman filter based tracking operating on actual 3D vehicle trajectories. Results are presented using a conventional thermal-band infra-red (IR) sensor arrangement where targets are tracked over a range of evaluation scenarios.

Strip biosensor for amplified detection of nerve growth factor-beta based on a molecular translator and catalytic DNA circuit.

PubMed

Liu, Jun; Lai, Ting; Mu, Kejie; Zhou, Zheng

2014-10-07

We have demonstrated a new visual detection approach based on a molecular translator and a catalytic DNA circuit for the detection of nerve growth factor-beta (NGF-β). In this assay, a molecular translator based on the binding-induced DNA strand-displacement reaction was employed to convert the input protein to an output DNA signal. The molecular translator is composed of a target recognition element and a signal output element. Target recognition is achieved by the binding of the anti-NGF-β antibody to the target protein. Polyclonal anti-NGF-β antibody is conjugated to DNA1 and DNA2. The antibody conjugated DNA1 is initially hybridized to DNA3 to form a stable DNA1/DNA3 duplex. In the presence of NGF-β, the binding of the same target protein brings DNA1 and DNA2 into close proximity, resulting in an increase in their local effective concentration. This process triggers the strand-displacement reaction between DNA2 and DNA3 and releases the output DNA3. The released DNA3 is further amplified by a catalytic DNA circuit. The product of the catalytic DNA circuit is detected by a strip biosensor. This proposed assay has high sensitivity and selectivity with a dynamic response ranging from 10 fM to 10 pM, and its detection limit is 10 fM of NGF-β. This work provides a sensitive, enzyme-free, and universal strategy for the detection of other proteins.

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.

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

Wavelet detection of singularities in the presence of fractal noise

NASA Astrophysics Data System (ADS)

Noel, Steven E.; Gohel, Yogesh J.; Szu, Harold H.

1997-04-01

Here we detect singularities with generalized quadrature processing using the recently developed Hermitian Hat wavelet. Our intended application is radar target detection for the optimal fuzzing of ship self-defense munitions. We first develop a wavelet-based fractal noise model to represent sea clutter. We then investigate wavelet shrinkage as a way to reduce and smooth the noise before attempting wavelet detection. Finally, we use the complex phase of the Hermitian Hat wavelet to detect a simulated target singularity in the presence of our fractal noise.

Plasmonic SERS nanochips and nanoprobes for medical diagnostics and bio-energy applications

NASA Astrophysics Data System (ADS)

Ngo, Hoan T.; Wang, Hsin-Neng; Crawford, Bridget M.; Fales, Andrew M.; Vo-Dinh, Tuan

2017-02-01

The development of rapid, easy-to-use, cost-effective, high accuracy, and high sensitive DNA detection methods for molecular diagnostics has been receiving increasing interest. Over the last five years, our laboratory has developed several chip-based DNA detection techniques including the molecular sentinel-on-chip (MSC), the multiplex MSC, and the inverse molecular sentinel-on-chip (iMS-on-Chip). In these techniques, plasmonic surface-enhanced Raman scattering (SERS) Nanowave chips were functionalized with DNA probes for single-step DNA detection. Sensing mechanisms were based on hybridization of target sequences and DNA probes, resulting in a distance change between SERS reporters and the Nanowave chip's gold surface. This distance change resulted in change in SERS intensity, thus indicating the presence and capture of the target sequences. Our techniques were single-step DNA detection techniques. Target sequences were detected by simple delivery of sample solutions onto DNA probe-functionalized Nanowave chips and SERS signals were measured after 1h - 2h incubation. Target sequence labeling or washing to remove unreacted components was not required, making the techniques simple, easy-to-use, and cost effective. The usefulness of the techniques for medical diagnostics was illustrated by the detection of genetic biomarkers for respiratory viral infection and of dengue virus 4 DNA.

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.

Application of a molecular beacon based real-time isothermal amplification (MBRTIA) technology for simultaneous detection of Bacillus cereus and Staphylococcus aureus.

PubMed

Mandappa, I M; Joglekar, Prasanna; Manonmani, H K

2015-07-01

A multiplex real-time isothermal amplification assay was developed using molecular beacons for the detection of Bacillus cereus and Staphylococcus aureus by targeting four important virulence genes. A correlation between targeting highly accessible DNA sequences and isothermal amplification based molecular beacon efficiency and sensitivity was demonstrated using phi(Φ)29 DNA polymerase at a constant isothermal temperature of 30 °C. It was very selective and consistently detected down to 10(1) copies of DNA. The specificity and sensitivity of this assay, when tested with pure culture were high, surpassing those of currently used PCR assays for the detection of these organisms. The molecular beacon based real-time isothermal amplification (MBRTIA) assay could be carried out entirely in 96 well plates or well strips, enabling a rapid and high-throughput detection of food borne pathogens.

Fluorescent aptasensor for detection of four tetracycline veterinary drugs in milk based on catalytic hairpin assembly reaction and displacement of G-quadruplex.

PubMed

Zhou, Chen; Zou, Haimin; Sun, Chengjun; Ren, Dongxia; Xiong, Wei; Li, Yongxin

2018-05-01

Based on a novel signal amplification strategy by catalytic hairpin assembly and displacement of G-quadruplex DNA, an enzyme-free, non-label fluorescent aptasensing approach was established for sensitive detection of four tetracycline veterinary drugs in milk. The network consisted of a pair of partially complementary DNA hairpins (HP1 and HP2). The DNA aptamer of four tetracycline veterinary drugs was located at the sticky end of the HP1. The ring region of HP1 rich in G and C could form a stable G-quadruplex structure, which could emit specific fluorescence signal after binding with the fluorescent dye and N-methylmesoporphyrin IX (NMM). When presented in the system, the target analytes would be repeatedly used to trigger a recycling procedure between the hairpins, generating numerous HP1-HP2 duplex complexes and displacing G-quadruplex DNA. Thus, the sensitive detection of target analytes was achieved in a wide linear range (0-1000 μg/L) with the detection limit of 4.6 μg/L. Moreover, this proposed method showed high discrimination efficiency towards target analytes against other common mismatched veterinary drugs, and could be successfully applied to the analysis of milk samples. Graphical abstract Schematic of target analyte detection based on catalytic hairpin assembly reaction and displacement of G-quadruplex.

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.

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.

Fast iterative censoring CFAR algorithm for ship detection from SAR images

NASA Astrophysics Data System (ADS)

Gu, Dandan; Yue, Hui; Zhang, Yuan; Gao, Pengcheng

2017-11-01

Ship detection is one of the essential techniques for ship recognition from synthetic aperture radar (SAR) images. This paper presents a fast iterative detection procedure to eliminate the influence of target returns on the estimation of local sea clutter distributions for constant false alarm rate (CFAR) detectors. A fast block detector is first employed to extract potential target sub-images; and then, an iterative censoring CFAR algorithm is used to detect ship candidates from each target blocks adaptively and efficiently, where parallel detection is available, and statistical parameters of G0 distribution fitting local sea clutter well can be quickly estimated based on an integral image operator. Experimental results of TerraSAR-X images demonstrate the effectiveness of the proposed technique.

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.

Automatic detection of small surface targets with electro-optical sensors in a harbor environment

NASA Astrophysics Data System (ADS)

Bouma, Henri; de Lange, Dirk-Jan J.; van den Broek, Sebastiaan P.; Kemp, Rob A. W.; Schwering, Piet B. W.

2008-10-01

In modern warfare scenarios naval ships must operate in coastal environments. These complex environments, in bays and narrow straits, with cluttered littoral backgrounds and many civilian ships may contain asymmetric threats of fast targets, such as rhibs, cabin boats and jet-skis. Optical sensors, in combination with image enhancement and automatic detection, assist an operator to reduce the response time, which is crucial for the protection of the naval and land-based supporting forces. In this paper, we present our work on automatic detection of small surface targets which includes multi-scale horizon detection and robust estimation of the background intensity. To evaluate the performance of our detection technology, data was recorded with both infrared and visual-light cameras in a coastal zone and in a harbor environment. During these trials multiple small targets were used. Results of this evaluation are shown in this paper.

Development of Real Time PCR Using Novel Genomic Target for Detection of Multiple Salmonella Serovars from Milk and Chickens

USDA-ARS?s Scientific Manuscript database

Background: A highly sensitive and specific novel genomic and plasmid target-based PCR platform was developed to detect multiple Salmonella serovars (S. Heidelberg, S. Dublin, S. Hadar, S. Kentucky and S. Enteritidis). Through extensive genome mining of protein databases of these serovars and compar...

Nonlinear optimization-based device-free localization with outlier link rejection.

PubMed

Xiao, Wendong; Song, Biao; Yu, Xiting; Chen, Peiyuan

2015-04-07

Device-free localization (DFL) is an emerging wireless technique for estimating the location of target that does not have any attached electronic device. It has found extensive use in Smart City applications such as healthcare at home and hospitals, location-based services at smart spaces, city emergency response and infrastructure security. In DFL, wireless devices are used as sensors that can sense the target by transmitting and receiving wireless signals collaboratively. Many DFL systems are implemented based on received signal strength (RSS) measurements and the location of the target is estimated by detecting the changes of the RSS measurements of the wireless links. Due to the uncertainty of the wireless channel, certain links may be seriously polluted and result in erroneous detection. In this paper, we propose a novel nonlinear optimization approach with outlier link rejection (NOOLR) for RSS-based DFL. It consists of three key strategies, including: (1) affected link identification by differential RSS detection; (2) outlier link rejection via geometrical positional relationship among links; (3) target location estimation by formulating and solving a nonlinear optimization problem. Experimental results demonstrate that NOOLR is robust to the fluctuation of the wireless signals with superior localization accuracy compared with the existing Radio Tomographic Imaging (RTI) approach.

Optical fiber extrinsic Fabry-Perot interferometric (EFPI)-based biosensors

NASA Astrophysics Data System (ADS)

Elster, Jennifer L.; Jones, Mark E.; Evans, Mishell K.; Lenahan, Shannon M.; Boyce, Christopher A.; Velander, William H.; VanTassell, Roger

2000-05-01

A novel system incorporating optical fiber extrinsic Fabry- Perot interferometric (EFPI)-based sensors for rapid detection of biological targets is presented. With the appropriate configuration, the EFPI senor is able to measure key environmental parameters by monitoring the interferometric fringes resulting from an optical path differences of reflected signals. The optical fiber EFPI sensor has been demonstrated for strain, pressure, and temperature measurements and can be readily modified for refractive index measurements by allowing solutions to flow into an open cavity. The sensor allows for highly sensitive, real-time, refractive index measurements and by applying affinity coatings containing ligands within this cavity, specific binding of target molecules can be accomplished. As target molecules bind to the coating, there is an increased density within the film, causing a measurable refractive index change that correlates to the concentration of detected target molecules. This sensor platform offers enhanced sensing capabilities for clinical diagnostics, pharmaceutical screening, environmental monitoring, food pathogen detection, biological warfare agent detection, and industrial bioprocessing. Promising applications also exist for process monitoring within the food/beverage, petroleum, and chemical industry.

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).

An enhanced chemiluminescence resonance energy transfer system based on target recycling G-guadruplexes/hemin DNAzyme catalysis and its application in ultrasensitive detection of DNA.

PubMed

Chen, Jia; Huang, Yong; Vdovenko, Marina; Sakharov, Ivan Yu; Su, Guifa; Zhao, Shulin

2015-06-01

An enhanced chemiluminescence resonance energy transfer (CRET) system based on target recycling G-guadruplexes/hemin DNAzyme catalysis was developed for ultrasensitive detection of DNA. CRET system consists of luminol as chemiluminescent donor, and fluorescein isothiocyanate (FITC) as acceptor. The sensitive detection was achieved by using the system consisted of G-riched DNA, blocker DNA, and the Nb.BbvCI biocatalyst. Upon addition of target DNA to the system, target DNA hybridizes with the quasi-circular DNA structure, and forms a DNA duplex. The formation of DNA duplex triggers selective enzymatic cleavage of quasi-circular DNA by Nb.BbvCI, resulting in the release of target DNA and two G-riched DNAzyme segments. Released target DNA then hybridizes with another quasi-circular DNA structure to initiate the cleavage of the quasi-circular DNA structure. Eventually, each target DNA can go through many cycles, resulting in the digestion of many quasi-circular DNA structures, generating many G-riched DNAzyme segments. G-riched DNAzyme segment products assemble with hemin to form stable hemin/G-quadruplexes that exhibit peroxidase-like activity which can catalyze the oxidation of luminol by H2O2 to produce CL signals. In the presence of FITC, CL of luminol can excite FITC molecules, and thus produced CRET between the luminol and FITC. This unique analysis strategy gives a detection limit down to 80 fM, which is at least four orders of magnitude lower than that of unamplified DNA detection methods. Copyright © 2015 Elsevier B.V. All rights reserved.

Assessing the performance of a motion tracking system based on optical joint transform correlation

NASA Astrophysics Data System (ADS)

Elbouz, M.; Alfalou, A.; Brosseau, C.; Ben Haj Yahia, N.; Alam, M. S.

2015-08-01

We present an optimized system specially designed for the tracking and recognition of moving subjects in a confined environment (such as an elderly remaining at home). In the first step of our study, we use a VanderLugt correlator (VLC) with an adapted pre-processing treatment of the input plane and a postprocessing of the correlation plane via a nonlinear function allowing us to make a robust decision. The second step is based on an optical joint transform correlation (JTC)-based system (NZ-NL-correlation JTC) for achieving improved detection and tracking of moving persons in a confined space. The proposed system has been found to have significantly superior discrimination and robustness capabilities allowing to detect an unknown target in an input scene and to determine the target's trajectory when this target is in motion. This system offers robust tracking performance of a moving target in several scenarios, such as rotational variation of input faces. Test results obtained using various real life video sequences show that the proposed system is particularly suitable for real-time detection and tracking of moving objects.

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.

An enzyme-free and label-free surface plasmon resonance biosensor for ultrasensitive detection of fusion gene based on DNA self-assembly hydrogel with streptavidin encapsulation.

PubMed

Guo, Bin; Wen, Bo; Cheng, Wei; Zhou, Xiaoyan; Duan, Xiaolei; Zhao, Min; Xia, Qianfeng; Ding, Shijia

2018-07-30

In this research, an enzyme-free and label-free surface plasmon resonance (SPR) biosensing strategy has been developed for ultrasensitive detection of fusion gene based on the heterogeneous target-triggered DNA self-assembly aptamer-based hydrogel with streptavidin (SA) encapsulation. In the presence of target, the capture probes (Cp) immobilized on the chip surface can capture the PML/RARα, forming a Cp-PML/RARα duplex. After that, the aptamer-based network hydrogel nanostructure is formed on the gold surface via target-triggered self-assembly of X shaped polymers. Subsequently, the SA can be encapsulated into hydrogel by the specific binding of SA aptamer, forming the complex with super molecular weight. Thus, the developed strategy achieves dramatic enhancement of the SPR signal. Using PML/RARα "S" subtype as model analyte, the developed biosensing method can detect target down to 45.22 fM with a wide linear range from 100 fM to 10 nM. Moreover, the high efficiency biosensing method shows excellent practical ability to identify the clinical PCR products of PML/RARα. Thus, this proposed strategy presents a powerful platform for ultrasensitive detection of fusion gene and early diagnosis and monitoring of disease. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Effects of Resolution, Range, and Image Contrast on Target Acquisition Performance.

PubMed

Hollands, Justin G; Terhaar, Phil; Pavlovic, Nada J

2018-05-01

We sought to determine the joint influence of resolution, target range, and image contrast on the detection and identification of targets in simulated naturalistic scenes. Resolution requirements for target acquisition have been developed based on threshold values obtained using imaging systems, when target range was fixed, and image characteristics were determined by the system. Subsequent work has examined the influence of factors like target range and image contrast on target acquisition. We varied the resolution and contrast of static images in two experiments. Participants (soldiers) decided whether a human target was located in the scene (detection task) or whether a target was friendly or hostile (identification task). Target range was also varied (50-400 m). In Experiment 1, 30 participants saw color images with a single target exemplar. In Experiment 2, another 30 participants saw monochrome images containing different target exemplars. The effects of target range and image contrast were qualitatively different above and below 6 pixels per meter of target for both tasks in both experiments. Target detection and identification performance were a joint function of image resolution, range, and contrast for both color and monochrome images. The beneficial effects of increasing resolution for target acquisition performance are greater for closer (larger) targets.

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 Fluorescence Resonance Energy Transfer (FRET)-Based DNA Biosensor for Detection of Synthetic Oligonucleotide of Ganoderma boninense.

PubMed

Bakhori, Noremylia Mohd; Yusof, Nor Azah; Abdullah, Abdul Halim; Hussein, Mohd Zobir

2013-12-12

An optical DNA biosensor based on fluorescence resonance energy transfer (FRET) utilizing synthesized quantum dot (QD) has been developed for the detection of specific-sequence of DNA for Ganoderma boninense, an oil palm pathogen. Modified QD that contained carboxylic groups was conjugated with a single-stranded DNA probe (ssDNA) via amide-linkage. Hybridization of the target DNA with conjugated QD-ssDNA and reporter probe labeled with Cy5 allows for the detection of related synthetic DNA sequence of Ganoderma boninense gene based on FRET signals. Detection of FRET emission before and after hybridization was confirmed through the capability of the system to produce FRET at 680 nm for hybridized sandwich with complementary target DNA. No FRET emission was observed for non-complementary system. Hybridization time, temperature and effect of different concentration of target DNA were studied in order to optimize the developed system. The developed biosensor has shown high sensitivity with detection limit of 3.55 × 10-9 M. TEM results show that the particle size of QD varies in the range between 5 to 8 nm after ligand modification and conjugation with ssDNA. This approach is capable of providing a simple, rapid and sensitive method for detection of related synthetic DNA sequence of Ganoderma boninense.

Development of a Fluorescence Resonance Energy Transfer (FRET)-Based DNA Biosensor for Detection of Synthetic Oligonucleotide of Ganoderma boninense.

PubMed

Mohd Bakhori, Noremylia; Yusof, Nor Azah; Abdullah, Abdul Halim; Hussein, Mohd Zobir

2013-12-01

An optical DNA biosensor based on fluorescence resonance energy transfer (FRET) utilizing synthesized quantum dot (QD) has been developed for the detection of specific-sequence of DNA for Ganoderma boninense, an oil palm pathogen. Modified QD that contained carboxylic groups was conjugated with a single-stranded DNA probe (ssDNA) via amide-linkage. Hybridization of the target DNA with conjugated QD-ssDNA and reporter probe labeled with Cy5 allows for the detection of related synthetic DNA sequence of Ganoderma boninense gene based on FRET signals. Detection of FRET emission before and after hybridization was confirmed through the capability of the system to produce FRET at 680 nm for hybridized sandwich with complementary target DNA. No FRET emission was observed for non-complementary system. Hybridization time, temperature and effect of different concentration of target DNA were studied in order to optimize the developed system. The developed biosensor has shown high sensitivity with detection limit of 3.55 × 10(-9) M. TEM results show that the particle size of QD varies in the range between 5 to 8 nm after ligand modification and conjugation with ssDNA. This approach is capable of providing a simple, rapid and sensitive method for detection of related synthetic DNA sequence of Ganoderma boninense.

A label-free aptamer-fluorophore assembly for rapid and specific detection of cocaine in biofluids.

PubMed

Roncancio, Daniel; Yu, Haixiang; Xu, Xiaowen; Wu, Shuo; Liu, Ran; Debord, Joshua; Lou, Xinhui; Xiao, Yi

2014-11-18

We report a rapid and specific aptamer-based method for one-step cocaine detection with minimal reagent requirements. The feasibility of aptamer-based detection has been demonstrated with sensors that operate via target-induced conformational change mechanisms, but these have generally exhibited limited target sensitivity. We have discovered that the cocaine-binding aptamer MNS-4.1 can also bind the fluorescent molecule 2-amino-5,6,7-trimethyl-1,8-naphthyridine (ATMND) and thereby quench its fluorescence. We subsequently introduced sequence changes into MNS-4.1 to engineer a new cocaine-binding aptamer (38-GC) that exhibits higher affinity to both ligands, with reduced background signal and increased signal gain. Using this aptamer, we have developed a new sensor platform that relies on the cocaine-mediated displacement of ATMND from 38-GC as a result of competitive binding. We demonstrate that our sensor can detect cocaine within seconds at concentrations as low as 200 nM, which is 50-fold lower than existing assays based on target-induced conformational change. More importantly, our assay achieves successful cocaine detection in body fluids, with a limit of detection of 10.4, 18.4, and 36 μM in undiluted saliva, urine, and serum samples, respectively.

Multimode electromagnetic target discriminator: preliminary data results

NASA Astrophysics Data System (ADS)

Black, Christopher J.; McMichael, Ian T.; Nelson, Carl V.

2004-09-01

This paper describes the Multi-mode Electromagnetic Target Discriminator (METD) sensor and presents preliminary results from recent field experiments. The METD sensor was developed for the US Army RDECOM NVESD by The Johns Hopkins University Applied Physics Laboratory. The METD, based on the technology of the previously developed Electromagnetic Target Discriminator (ETD), is a spatial scanning electromagnetic induction (EMI) sensor that uses both the time-domain (TD) and the frequency-domain (FD) for target detection and classification. Data is collected with a custom data acquisition system and wirelessly transmitted to a base computer. We show that the METD has a high signal-to-noise ratio (SNR), the ability to detect voids created by plastic anti-tank (AT) mines, and is practical for near real-time data processing.

Quantitative Detection of Small Molecule/DNA Complexes Employing a Force-Based and Label-Free DNA-Microarray

PubMed Central

Ho, Dominik; Dose, Christian; Albrecht, Christian H.; Severin, Philip; Falter, Katja; Dervan, Peter B.; Gaub, Hermann E.

2009-01-01

Force-based ligand detection is a promising method to characterize molecular complexes label-free at physiological conditions. Because conventional implementations of this technique, e.g., based on atomic force microscopy or optical traps, are low-throughput and require extremely sensitive and sophisticated equipment, this approach has to date found only limited application. We present a low-cost, chip-based assay, which combines high-throughput force-based detection of dsDNA·ligand interactions with the ease of fluorescence detection. Within the comparative unbinding force assay, many duplicates of a target DNA duplex are probed against a defined reference DNA duplex each. The fractions of broken target and reference DNA duplexes are determined via fluorescence. With this assay, we investigated the DNA binding behavior of artificial pyrrole-imidazole polyamides. These small compounds can be programmed to target specific dsDNA sequences and distinguish between D- and L-DNA. We found that titration with polyamides specific for a binding motif, which is present in the target DNA duplex and not in the reference DNA duplex, reliably resulted in a shift toward larger fractions of broken reference bonds. From the concentration dependence nanomolar to picomolar dissociation constants of dsDNA·ligand complexes were determined, agreeing well with prior quantitative DNAase footprinting experiments. This finding corroborates that the forced unbinding of dsDNA in presence of a ligand is a nonequilibrium process that produces a snapshot of the equilibrium distribution between dsDNA and dsDNA·ligand complexes. PMID:19486688

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.

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

PubMed Central

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

2014-01-01

It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively. PMID:24871988

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

PubMed

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

2014-05-27

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

Shilling Attacks Detection in Recommender Systems Based on Target Item Analysis

PubMed Central

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

2015-01-01

Recommender systems are highly vulnerable to shilling attacks, both by individuals and groups. Attackers who introduce biased ratings in order to affect recommendations, have been shown to negatively affect collaborative filtering (CF) algorithms. Previous research focuses only on the differences between genuine profiles and attack profiles, ignoring the group characteristics in attack profiles. In this paper, we study the use of statistical metrics to detect rating patterns of attackers and group characteristics in attack profiles. Another question is that most existing detecting methods are model specific. Two metrics, Rating Deviation from Mean Agreement (RDMA) and Degree of Similarity with Top Neighbors (DegSim), are used for analyzing rating patterns between malicious profiles and genuine profiles in attack models. Building upon this, we also propose and evaluate a detection structure called RD-TIA for detecting shilling attacks in recommender systems using a statistical approach. In order to detect more complicated attack models, we propose a novel metric called DegSim’ based on DegSim. The experimental results show that our detection model based on target item analysis is an effective approach for detecting shilling attacks. PMID:26222882

Capture-based next-generation sequencing reveals multiple actionable mutations in cancer patients failed in traditional testing.

PubMed

Xie, Jing; Lu, Xiongxiong; Wu, Xue; Lin, Xiaoyi; Zhang, Chao; Huang, Xiaofang; Chang, Zhili; Wang, Xinjing; Wen, Chenlei; Tang, Xiaomei; Shi, Minmin; Zhan, Qian; Chen, Hao; Deng, Xiaxing; Peng, Chenghong; Li, Hongwei; Fang, Yuan; Shao, Yang; Shen, Baiyong

2016-05-01

Targeted therapies including monoclonal antibodies and small molecule inhibitors have dramatically changed the treatment of cancer over past 10 years. Their therapeutic advantages are more tumor specific and with less side effects. For precisely tailoring available targeted therapies to each individual or a subset of cancer patients, next-generation sequencing (NGS) has been utilized as a promising diagnosis tool with its advantages of accuracy, sensitivity, and high throughput. We developed and validated a NGS-based cancer genomic diagnosis targeting 115 prognosis and therapeutics relevant genes on multiple specimen including blood, tumor tissue, and body fluid from 10 patients with different cancer types. The sequencing data was then analyzed by the clinical-applicable analytical pipelines developed in house. We have assessed analytical sensitivity, specificity, and accuracy of the NGS-based molecular diagnosis. Also, our developed analytical pipelines were capable of detecting base substitutions, indels, and gene copy number variations (CNVs). For instance, several actionable mutations of EGFR,PIK3CA,TP53, and KRAS have been detected for indicating drug susceptibility and resistance in the cases of lung cancer. Our study has shown that NGS-based molecular diagnosis is more sensitive and comprehensive to detect genomic alterations in cancer, and supports a direct clinical use for guiding targeted therapy.

Microwave-Accelerated Method for Ultra-Rapid Extraction of Neisseria gonorrhoeae DNA for Downstream Detection

PubMed Central

Melendez, Johan H.; Santaus, Tonya M.; Brinsley, Gregory; Kiang, Daniel; Mali, Buddha; Hardick, Justin; Gaydos, Charlotte A.; Geddes, Chris D.

2016-01-01

Nucleic acid-based detection of gonorrhea infections typically require a two-step process involving isolation of the nucleic acid, followed by the detection of the genomic target often involving PCR-based approaches. In an effort to improve on current detection approaches, we have developed a unique two-step microwave-accelerated approach for rapid extraction and detection of Neisseria gonorrhoeae (GC) DNA. Our approach is based on the use of highly-focused microwave radiation to rapidly lyse bacterial cells, release, and subsequently fragment microbial DNA. The DNA target is then detected by a process known as microwave-accelerated metal-enhanced fluorescence (MAMEF), an ultra-sensitive direct DNA detection analytical technique. In the present study, we show that highly focused microwaves at 2.45 GHz, using 12.3 mm gold film equilateral triangles, are able to rapidly lyse both bacteria cells and fragment DNA in a time- and microwave power-dependent manner. Detection of the extracted DNA can be performed by MAMEF, without the need for DNA amplification in less than 10 minutes total time or by other PCR-based approaches. Collectively, the use of a microwave-accelerated method for the release and detection of DNA represents a significant step forward towards the development of a point-of-care (POC) platform for detection of gonorrhea infections. PMID:27325503

Autonomous replication of nucleic acids by polymerization/nicking enzyme/DNAzyme cascades for the amplified detection of DNA and the aptamer-cocaine complex.

PubMed

Wang, Fuan; Freage, Lina; Orbach, Ron; Willner, Itamar

2013-09-03

The progressive development of amplified DNA sensors and aptasensors using replication/nicking enzymes/DNAzyme machineries is described. The sensing platforms are based on the tailoring of a DNA template on which the recognition of the target DNA or the formation of the aptamer-substrate complex trigger on the autonomous isothermal replication/nicking processes and the displacement of a Mg(2+)-dependent DNAzyme that catalyzes the generation of a fluorophore-labeled nucleic acid acting as readout signal for the analyses. Three different DNA sensing configurations are described, where in the ultimate configuration the target sequence is incorporated into a nucleic acid blocker structure associated with the sensing template. The target-triggered isothermal autonomous replication/nicking process on the modified template results in the formation of the Mg(2+)-dependent DNAzyme tethered to a free strand consisting of the target sequence. This activates additional template units for the nucleic acid self-replication process, resulting in the ultrasensitive detection of the target DNA (detection limit 1 aM). Similarly, amplified aptamer-based sensing platforms for cocaine are developed along these concepts. The modification of the cocaine-detection template by the addition of a nucleic acid sequence that enables the autonomous secondary coupled activation of a polymerization/nicking machinery and DNAzyme generation path leads to an improved analysis of cocaine (detection limit 10 nM).

Automatic three-dimensional measurement of large-scale structure based on vision metrology.

PubMed

Zhu, Zhaokun; Guan, Banglei; Zhang, Xiaohu; Li, Daokui; Yu, Qifeng

2014-01-01

All relevant key techniques involved in photogrammetric vision metrology for fully automatic 3D measurement of large-scale structure are studied. A new kind of coded target consisting of circular retroreflective discs is designed, and corresponding detection and recognition algorithms based on blob detection and clustering are presented. Then a three-stage strategy starting with view clustering is proposed to achieve automatic network orientation. As for matching of noncoded targets, the concept of matching path is proposed, and matches for each noncoded target are found by determination of the optimal matching path, based on a novel voting strategy, among all possible ones. Experiments on a fixed keel of airship have been conducted to verify the effectiveness and measuring accuracy of the proposed methods.

A label-free DNA hairpin biosensor for colorimetric detection of target with suitable functional DNA partners.

PubMed

Nie, Ji; Zhang, De-Wen; Tie, Cai; Zhou, Ying-Lin; Zhang, Xin-Xiang

2013-11-15

The combination of aptamer and peroxidase-mimicking DNAzyme within a hairpin structure can form a functional DNA probe. The activities of both aptamer (as biorecognition element) and DNAzyme (as signal amplification element) are blocked via base pairing in the hairpin structure. The presence of target triggers the opening of the hairpin to form target/aptamer complex and releases G-quadruplex sequence which can generate amplified colorimetric signals. In this work, we elaborated a universal and simple procedure to design an efficient and sensitive hairpin probe with suitable functional DNA partners. A fill-in-the-blank process was developed for sequence design, and two key points including the pretreatment of the hairpin probe and the selection of suitable signal transducer sequence were proved to enhance the detection sensitivity. Cocaine was chosen as a model target for a proof of concept. A series of hairpins with different numbers of base pairs in the stem region were prepared. Hairpin-C10 with ten base pairs was screened out and a lowest detectable cocaine concentration of 5 μM by colorimetry was obtained. The proposed functional DNA hairpin showed good selectivity and satisfactory analysis in spiked biologic fluid. The whole "mix-and-measure" detection based on DNA hairpin without the need of immobilization and labeling was indicated to be time and labor saving. The strategy has potential to be transplanted into more smart hairpins toward other targets for general application in bioanalytical chemistry. Copyright © 2013 Elsevier B.V. All rights reserved.

Object acquisition and tracking for space-based surveillance

NASA Astrophysics Data System (ADS)

1991-11-01

This report presents the results of research carried out by Space Computer Corporation under the U.S. government's Small Business Innovation Research (SBIR) Program. The work was sponsored by the Strategic Defense Initiative Organization and managed by the Office of Naval Research under Contracts N00014-87-C-0801 (Phase 1) and N00014-89-C-0015 (Phase 2). The basic purpose of this research was to develop and demonstrate a new approach to the detection of, and initiation of track on, moving targets using data from a passive infrared or visual sensor. This approach differs in very significant ways from the traditional approach of dividing the required processing into time dependent, object dependent, and data dependent processing stages. In that approach individual targets are first detected in individual image frames, and the detections are then assembled into tracks. That requires that the signal to noise ratio in each image frame be sufficient for fairly reliable target detection. In contrast, our approach bases detection of targets on multiple image frames, and, accordingly, requires a smaller signal to noise ratio. It is sometimes referred to as track before detect, and can lead to a significant reduction in total system cost. For example, it can allow greater detection range for a single sensor, or it can allow the use of smaller sensor optics. Both the traditional and track before detect approaches are applicable to systems using scanning sensors, as well as those which use staring sensors.

Object acquisition and tracking for space-based surveillance. Final report, Dec 88-May 90

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

Not Available

1991-11-27

This report presents the results of research carried out by Space Computer Corporation under the U.S. government's Small Business Innovation Research (SBIR) Program. The work was sponsored by the Strategic Defense Initiative Organization and managed by the Office of Naval Research under Contracts N00014-87-C-0801 (Phase I) and N00014-89-C-0015 (Phase II). The basic purpose of this research was to develop and demonstrate a new approach to the detection of, and initiation of track on, moving targets using data from a passive infrared or visual sensor. This approach differs in very significant ways from the traditional approach of dividing the required processingmore » into time dependent, object-dependent, and data-dependent processing stages. In that approach individual targets are first detected in individual image frames, and the detections are then assembled into tracks. That requires that the signal to noise ratio in each image frame be sufficient for fairly reliable target detection. In contrast, our approach bases detection of targets on multiple image frames, and, accordingly, requires a smaller signal to noise ratio. It is sometimes referred to as track before detect, and can lead to a significant reduction in total system cost. For example, it can allow greater detection range for a single sensor, or it can allow the use of smaller sensor optics. Both the traditional and track before detect approaches are applicable to systems using scanning sensors, as well as those which use staring sensors.« less

Aptamer-based microfluidic beads array sensor for simultaneous detection of multiple analytes employing multienzyme-linked nanoparticle amplification and quantum dots labels.

PubMed

Zhang, He; Hu, Xinjiang; Fu, Xin

2014-07-15

This study reports the development of an aptamer-mediated microfluidic beads-based sensor for multiple analytes detection and quantification using multienzyme-linked nanoparticle amplification and quantum dots labels. Adenosine and cocaine were selected as the model analytes to validate the assay design based on strand displacement induced by target-aptamer complex. Microbeads functionalized with the aptamers and modified electron rich proteins were arrayed within a microfluidic channel and were connected with the horseradish peroxidases (HRP) and capture DNA probe derivative gold nanoparticles (AuNPs) via hybridization. The conformational transition of aptamer induced by target-aptamer complex contributes to the displacement of functionalized AuNPs and decreases the fluorescence signal of microbeads. In this approach, increased binding events of HRP on each nanosphere and enhanced mass transport capability inherent from microfluidics are integrated for enhancing the detection sensitivity of analytes. Based on the dual signal amplification strategy, the developed aptamer-based microfluidic bead array sensor could discriminate as low as 0.1 pM of adenosine and 0.5 pM cocaine, and showed a 500-fold increase in detection limit of adenosine compared to the off-chip test. The results proved the microfluidic-based method was a rapid and efficient system for aptamer-based targets assays (adenosine (0.1 pM) and cocaine (0.5 pM)), requiring only minimal (microliter) reagent use. This work demonstrated the successful application of aptamer-based microfluidic beads array sensor for detection of important molecules in biomedical fields. Copyright © 2014 Elsevier B.V. All rights reserved.

[A review on polarization information in the remote sensing detection].

PubMed

Gong, Jie-Qiong; Zhan, Hai-Gang; Liu, Da-Zhao

2010-04-01

Polarization is one of the inherent characteristics. Because the surface of the target structure, internal structure, and the angle of incident light are different, the earth's surface and any target in atmosphere under optical interaction process will have their own characteristic nature of polarization. Polarimetric characteristics of radiation energy from the targets are used in polarization remote sensing detection as detective information. Polarization remote sensing detection can get the seven-dimensional information of targets in complicated backgrounds, detect well-resolved outline of targets and low-reflectance region of objectives, and resolve the problems of atmospheric detection and identification camouflage detection which the traditional remote sensing detection can not solve, having good foreground in applications. This paper introduces the development of polarization information in the remote sensing detection from the following four aspects. The rationale of polarization remote sensing detection is the base of polarization remote sensing detection, so it is firstly introduced. Secondly, the present researches on equipments that are used in polarization remote sensing detection are particularly and completely expatiated. Thirdly, the present exploration of theoretical simulation of polarization remote sensing detection is well detailed. Finally, the authors present the applications research home and abroad of the polarization remote sensing detection technique in the fields of remote sensing, atmospheric sounding, sea surface and underwater detection, biology and medical diagnosis, astronomical observation and military, summing up the current problems in polarization remote sensing detection. The development trend of polarization remote sensing detection technology in the future is pointed out in order to provide a reference for similar studies.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Magnetic-Particle-Sensing Based Diagnostic Protocols and Applications

PubMed Central

Takamura, Tsukasa; Ko, Pil Ju; Sharma, Jaiyam; Yukino, Ryoji; Ishizawa, Shunji; Sandhu, Adarsh

2015-01-01

Magnetic particle-labeled biomaterial detection has attracted much attention in recent years for a number of reasons; easy manipulation by external magnetic fields, easy functionalization of the surface, and large surface-to-volume ratio, to name but a few. In this review, we report on our recent investigations into the detection of nano-sized magnetic particles. First, the detection by Hall magnetic sensor with lock-in amplifier and alternative magnetic field is summarized. Then, our approach to detect sub-200 nm diameter target magnetic particles via relatively large micoro-sized “columnar particles” by optical microscopy is described. Subsequently, we summarize magnetic particle detection based on optical techniques; one method is based on the scattering of the magnetically-assembled nano-sized magnetic bead chain in rotating magnetic fields and the other one is based on the reflection of magnetic target particles and porous silicon. Finally, we report recent works with reference to more familiar industrial products (such as smartphone-based medical diagnosis systems and magnetic removal of unspecific-binded nano-sized particles, or “magnetic washing”). PMID:26053747

A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors

PubMed Central

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao; Wang, Wensheng

2017-01-01

Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ-connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA) with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm. PMID:28587084

A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors.

PubMed

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao; Wang, Wensheng

2017-05-25

Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ -connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA) with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm.

A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes

PubMed Central

Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-yung

2016-01-01

Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency. PMID:27792156

A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes.

PubMed

Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-Yung

2016-10-25

Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency.

Multiplexed detection of DNA sequences using a competitive displacement assay in a microfluidic SERRS-based device.

PubMed

Yazdi, Soroush H; Giles, Kristen L; White, Ian M

2013-11-05

We demonstrate sensitive and multiplexed detection of DNA sequences through a surface enhanced resonance Raman spectroscopy (SERRS)-based competitive displacement assay in an integrated microsystem. The use of the competitive displacement scheme, in which the target DNA sequence displaces a Raman-labeled reporter sequence that has lower affinity for the immobilized probe, enables detection of unlabeled target DNA sequences with a simple single-step procedure. In our implementation, the displacement reaction occurs in a microporous packed column of silica beads prefunctionalized with probe-reporter pairs. The use of a functionalized packed-bead column in a microfluidic channel provides two major advantages: (i) immobilization surface chemistry can be performed as a batch process instead of on a chip-by-chip basis, and (ii) the microporous network eliminates the diffusion limitations of a typical biological assay, which increases the sensitivity. Packed silica beads are also leveraged to improve the SERRS detection of the Raman-labeled reporter. Following displacement, the reporter adsorbs onto aggregated silver nanoparticles in a microfluidic mixer; the nanoparticle-reporter conjugates are then trapped and concentrated in the silica bead matrix, which leads to a significant increase in plasmonic nanoparticles and adsorbed Raman reporters within the detection volume as compared to an open microfluidic channel. The experimental results reported here demonstrate detection down to 100 pM of the target DNA sequence, and the experiments are shown to be specific, repeatable, and quantitative. Furthermore, we illustrate the advantage of using SERRS by demonstrating multiplexed detection. The sensitivity of the assay, combined with the advantages of multiplexed detection and single-step operation with unlabeled target sequences makes this method attractive for practical applications. Importantly, while we illustrate DNA sequence detection, the SERRS-based competitive displacement assay is applicable to detection of a variety of biological macromolecules, including proteins and proteolytic enzymes.

Wireless sensor

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

Lamberti, Vincent E.; Howell, JR, Layton N.; Mee, David K.

Disclosed is a sensor for detecting a target material. The sensor includes a ferromagnetic metal and a molecular recognition reagent coupled to the ferromagnetic metal. The molecular recognition reagent is operable to expand upon exposure to vapor or liquid from the target material such that the molecular recognition reagent changes a tensile stress upon the ferromagnetic metal. The target material is detected based on changes in the magnetic switching characteristics of the ferromagnetic metal caused by the changes in the tensile stress.

Science of Land Target Spectral Signatures

DTIC Science & Technology

2013-04-03

F. Meriaudeau, T. Downey , A. Wig , A. Passian, M. Buncick, T.L. Ferrell, Fiber optic sensor based on gold island plasmon resonance , Sensors and...processing, detection algorithms, sensor fusion, spectral signature modeling Dr. J. Michael Cathcart Georgia Tech Research Corporation Office of...target detection and sensor fusion. The phenomenology research continued to focus on spectroscopic soil measurements, optical property analyses, field

Novel label-free and high-throughput microchip electrophoresis platform for multiplex antibiotic residues detection based on aptamer probes and target catalyzed hairpin assembly for signal amplification.

PubMed

Wang, Ye; Gan, Ning; Zhou, You; Li, Tianhua; Hu, Futao; Cao, Yuting; Chen, Yinji

2017-11-15

Novel label-free and multiplex aptasensors have been developed for simultaneous detection of several antibiotics based on a microchip electrophoresis (MCE) platform and target catalyzed hairpin assembly (CHA) for signal amplification. Kanamycin (Kana) and oxytetracycline (OTC) were employed as models for testing the system. These aptasensors contained six DNA strands termed as Kana aptamer-catalysis strand (Kana apt-C), Kana inhibit strand (Kana inh), OTC aptamer-catalysis strand (OTC apt-C), OTC inhibit strand (OTC inh), hairpin structures H1 and H2 which were partially complementary. Upon the addition of Kana or OTC, the binding event of aptamer and target triggered the self-assembly between H1 and H2, resulting in the formation of many H1-H2 complexes. They could show strong signals which represented the concentration of Kana or OTC respectively in the MCE system. With the help of the well-designed and high-quality CHA amplification, the assay could yield 300-fold amplified signal comparing that from non-amplified system. Under optimal conditions, this assay exhibited a linear correlation in the ranges from 0.001ngmL -1 to 10ngmL -1 , with the detection limits of 0.7pgmL -1 and 0.9pgmL -1 (S/N=3) toward Kana and OTC, respectively. The platform has the following advantages: firstly, the aptamer probes can be fabricated easily without labeling signal tags for MCE detection; Secondly, the targets can just react with probes and produce the amplified signal in one-pot. Finally, the targets can be simultaneously detected within 10min in different channels, thus high-throughput measurement can be achieved. Based on this work, it is estimated that this detection platform will be universally served as a simple, sensitive and portable platform for antibiotic contaminants detection in biological and environmental samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects-Based Operations in the Cyber Domain

DTIC Science & Technology

2017-05-03

as the joint targeting methodology . The description that Batschelet gave the traditional targeting methodology included a process of, “Decide, Detect...technology, requires new planning and methodology to fight back. This paper evaluates current Department of Defense doctrine to look at ways to conduct...developing its cyber tactics, techniques, and procedures, which, includes various targeting methodologies , such as the use of effects-based

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.

DBSCAN-based ROI extracted from SAR images and the discrimination of multi-feature ROI

NASA Astrophysics Data System (ADS)

He, Xin Yi; Zhao, Bo; Tan, Shu Run; Zhou, Xiao Yang; Jiang, Zhong Jin; Cui, Tie Jun

2009-10-01

The purpose of the paper is to extract the region of interest (ROI) from the coarse detected synthetic aperture radar (SAR) images and discriminate if the ROI contains a target or not, so as to eliminate the false alarm, and prepare for the target recognition. The automatic target clustering is one of the most difficult tasks in the SAR-image automatic target recognition system. The density-based spatial clustering of applications with noise (DBSCAN) relies on a density-based notion of clusters which is designed to discover clusters of arbitrary shape. DBSCAN was first used in the SAR image processing, which has many excellent features: only two insensitivity parameters (radius of neighborhood and minimum number of points) are needed; clusters of arbitrary shapes which fit in with the coarse detected SAR images can be discovered; and the calculation time and memory can be reduced. In the multi-feature ROI discrimination scheme, we extract several target features which contain the geometry features such as the area discriminator and Radon-transform based target profile discriminator, the distribution characteristics such as the EFF discriminator, and the EM scattering property such as the PPR discriminator. The synthesized judgment effectively eliminates the false alarms.

Detection and Characterization of Cancer Cells and Pathogenic Bacteria Using Aptamer-Based Nano-Conjugates

PubMed Central

Gedi, Vinayakumar; Kim, Young-Pil

2014-01-01

Detection and characterization of cells using aptamers and aptamer-conjugated nanoprobes has evolved a great deal over the past few decades. This evolution has been driven by the easy selection of aptamers via in vitro cell-SELEX, permitting sensitive discrimination between target and normal cells, which includes pathogenic prokaryotic and cancerous eukaryotic cells. Additionally, when the aptamer-based strategies are used in conjunction with nanomaterials, there is the potential for cell targeting and therapeutic effects with improved specificity and sensitivity. Here we review recent advances in aptamer-based nano-conjugates and their applications for detecting cancer cells and pathogenic bacteria. The multidisciplinary research utilized in this field will play an increasingly significant role in clinical medicine and drug discovery. PMID:25268922

Polarization differences in airborne ground penetrating radar performance for landmine detection

NASA Astrophysics Data System (ADS)

Dogaru, Traian; Le, Calvin

2016-05-01

The U.S. Army Research Laboratory (ARL) has investigated the ultra-wideband (UWB) radar technology for detection of landmines, improvised explosive devices and unexploded ordnance, for over two decades. This paper presents a phenomenological study of the radar signature of buried landmines in realistic environments and the performance of airborne synthetic aperture radar (SAR) in detecting these targets as a function of multiple parameters: polarization, depression angle, soil type and burial depth. The investigation is based on advanced computer models developed at ARL. The analysis includes both the signature of the targets of interest and the clutter produced by rough surface ground. Based on our numerical simulations, we conclude that low depression angles and H-H polarization offer the highest target-to-clutter ratio in the SAR images and therefore the best radar performance of all the scenarios investigated.

Diode/magnetic tunnel junction cell for fully scalable matrix-based biochip

NASA Astrophysics Data System (ADS)

Cardoso, F. A.; Ferreira, H. A.; Conde, J. P.; Chu, V.; Freitas, P. P.; Vidal, D.; Germano, J.; Sousa, L.; Piedade, M. S.; Costa, B. A.; Lemos, J. M.

2006-04-01

Magnetoresistive biochips have been recently introduced for the detection of biomolecular recognition. In this work, the detection site incorporates a thin-film diode in series with a magnetic tunnel junction (MTJ), leading to a matrix-based biochip that can be easily scaled up to screen large numbers of different target analytes. The fabricated 16×16 cell matrix integrates hydrogenated amorphous silicon (a-Si:H) diodes with aluminum oxide barrier MTJ. Each detection site also includes a U-shaped current line for magnetically assisted target concentration at probe sites. The biochip is being integrated in a portable, credit card size electronics control platform. Detection of 250 nm diameter magnetic nanoparticles by one of the matrix cells is demonstrated.

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).

Quantum-dot-based quantitative identification of pathogens in complex mixture

NASA Astrophysics Data System (ADS)

Lim, Sun Hee; Bestwater, Felix; Buchy, Philippe; Mardy, Sek; Yu, Alexey Dan Chin

2010-02-01

In the present study we describe sandwich design hybridization probes consisting of magnetic particles (MP) and quantum dots (QD) with target DNA, and their application in the detection of avian influenza virus (H5N1) sequences. Hybridization of 25-, 40-, and 100-mer target DNA with both probes was analyzed and quantified by flow cytometry and fluorescence microscopy on the scale of single particles. The following steps were used in the assay: (i) target selection by MP probes and (ii) target detection by QD probes. Hybridization efficiency between MP conjugated probes and target DNA hybrids was controlled by a fluorescent dye specific for nucleic acids. Fluorescence was detected by flow cytometry to distinguish differences in oligo sequences as short as 25-mer capturing in target DNA and by gel-electrophoresis in the case of QD probes. This report shows that effective manipulation and control of micro- and nanoparticles in hybridization assays is possible.

A ratiometric electrochemical biosensor for the exosomal microRNAs detection based on bipedal DNA walkers propelled by locked nucleic acid modified toehold mediate strand displacement reaction.

PubMed

Zhang, Jing; Wang, Liang-Liang; Hou, Mei-Feng; Xia, Yao-Kun; He, Wen-Hui; Yan, An; Weng, Yun-Ping; Zeng, Lu-Peng; Chen, Jing-Hua

2018-04-15

Sensitive and selective detection of microRNAs (miRNAs) in cancer cells derived exosomes have attracted rapidly growing interest owing to their potential in diagnostic and prognostic applications. Here, we design a ratiometric electrochemical biosensor based on bipedal DNA walkers for the attomolar detection of exosomal miR-21. In the presence of miR-21, DNA walkers are activated to walk continuously along DNA tracks, resulting in conformational changes as well as considerable increases of the signal ratio produced by target-respond and target-independent reporters. With the signal cascade amplification of DNA walkers, the biosensor exhibits ultrahigh sensitivity with the limit of detection (LOD) down to 67 aM. Furthermore, owing to the background-correcting function of target-independent reporters termed as reference reporters, the biosensor is robust and stable enough to be applied in the detection of exosomal miR-21 extracted from breast cancer cell lines and serums. In addition, because locked nucleic acid (LNA) modified toehold mediate strand displacement reaction (TMSDR) has extraordinary discriminative ability, the biosensor displays excellent selectivity even against the single-base-mismatched target. It is worth mentioning that our sensor is regenerative and stable for at least 5 cycles without diminution in sensitivity. In brief, the high sensitivity, selectivity and reproducibility, together with cheap, make the proposed biosensor a promising approach for exosomal miRNAs detection, in conjunction with early point-of-care testing (POCT) of cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

A novel magneto-DNA duplex probe for bacterial DNA detection based on exonuclease III-aided cycling amplification.

PubMed

Zeng, Yan; Wan, Yi; Zhang, Dun; Qi, Peng

2015-01-01

A novel magneto-DNA duplex probe for bacterial DNA detection based on exonuclease III (Exo-III) aided cycling amplification has been developed. This magneto-DNA duplex probe contains a partly hybrid fluorophore-modified capture probe and a fluorophore-modified signal probe with magnetic microparticle as carrier. In the presence of a perfectly matched target bacterial DNA, blunt 3'-terminus of the capture probe is formed, activating the Exo-III aided cycling amplification. Thus, Exo-III catalyzes the stepwise removal of mononucleotides from this terminus, releasing both fluorophore-modified signal probe, fluorescent dyes of the capture probe and target DNA. The released target DNA then starts a new cycle, while released fluorescent fragments are recovered with magnetic separation for fluorescence signal collection. This system exhibited sensitive detection of bacterial DNA, with a detection limit of 14 pM because of the unique cleavage function of Exo-III, high fluorescence intensity, and separating function of magneto-DNA duplex probes. Besides this sensitivity, this strategy exhibited excellent selectivity with mismatched bacterial DNA targets and other bacterial species targets and good applicability in real seawater samples, hence, this strategy could be potentially used for qualitative and quantitative analysis of bacteria. Copyright © 2014 Elsevier B.V. All rights reserved.

Exploring target-specific primer extension in combination with a bead-based suspension array for multiplexed detection and typing using Streptococcus suis as a model pathogen

PubMed Central

van der Wal, Fimme J.; Achterberg, René P.; van Solt-Smits, Conny; Bergervoet, Jan H. W.; de Weerdt, Marjanne; Wisselink, Henk J.

2017-01-01

We investigated the feasibility of an assay based on target-specific primer extension, combined with a suspension array, for the multiplexed detection and typing of a veterinary pathogen in animal samples, using Streptococcus suis as a model pathogen. A procedure was established for simultaneous detection of 6 S. suis targets in pig tonsil samples (i.e., 4 genes associated with serotype 1, 2, 7, or 9, the generic S. suis glutamate dehydrogenase gene [gdh], and the gene encoding the extracellular protein factor [epf]). The procedure was set up as a combination of protocols: DNA isolation from porcine tonsils, a multiplex PCR, a multiplex target-specific primer extension, and finally a suspension array as the readout. The resulting assay was compared with a panel of conventional PCR assays. The proposed multiplex assay can correctly identify the serotype of isolates and is capable of simultaneous detection of multiple targets in porcine tonsillar samples. The assay is not as sensitive as the current conventional PCR assays, but with the correct sampling strategy, the assay can be useful for screening pig herds to establish which S. suis serotypes are circulating in a pig population. PMID:28980519

Multiple-Targeted Graphene-based Nanocarrier for Intracellular Imaging of mRNAs

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

Wang, Ying; Li, Zhaohui; Liu, Misha

Simultaneous detection and imaging of multiple intracellular messenger RNA (mRNAs) hold great significant for early cancer diagnostics and preventive medicine development. Herein, we propose a multiple-targeted graphene oxide (GO) nanocarrier that can simultaneously detect and image different type mRNAs in living cells. First of all, in vitro detection of multiple targets have been realized successfully based on the multiple-targeted GO nanocarrier with linear relationship ranging from 3 nM to 200 nM, as well as sensitive detection limit of 1.84 nM for manganese superoxide dismutase (Mn-SOD) mRNA and 2.45 nM for β-actin mRNA. Additionally, this nanosensing platform composed of fluorescent labeledmore » single strand DNA probes and GO nanocarrier can identify Mn-SOD mRNA and endogenous mRNA of β-actin in living cancer cells, showing rapid response, high specificity, nuclease stability, and good biocompatibility during the cell imaging. Thirdly, changes of the expression levels of mRNA in living cells before or after the drug treatment can be monitored successfully. By using multiple ssDNA as probes and GO nanocarrier as the cellular delivery cargo, the proposed simultaneous multiple-targeted sensing platform will be of great potential as a powerful tool for intracellular trafficking process from basic research to clinical diagnosis.« less

Lectin functionalized ZnO nanoarrays as a 3D nano-biointerface for bacterial detection.

PubMed

Zheng, Laibao; Wan, Yi; Qi, Peng; Sun, Yan; Zhang, Dun; Yu, Liangmin

2017-05-15

The detection of pathogenic bacteria is essential in various fields, such as food safety, water environmental analysis, or clinical diagnosis. Although rapid and selective techniques have been achieved based on the fast and specific binding of recognitions elements and target, the sensitive detection of bacterial pathogens was limited by their low targets-binding efficiency. The three-dimensional (3D) nano-biointerface, compared with the two-dimensional (2D) flat substrate, has a much higher binding capacity, which can offer more reactive sites to bind with bacterial targets, resulting in a great improvement of detection sensitivity. Herein, a lectin functionalized ZnO nanorod (ZnO-NR) array has been fabricated and employed as a 3D nano-biointerface for Escherichia coli (E. coli) capture and detection by multivalent binding of concanavalin A (ConA) with polysaccharides on the cellular surface of E. coli. The 3D lectin functionalized ZnO-NR array-based assay shows reasonable detection limit and efficiently expanded linear range (1.0×10 3 to 1.0×10 7 cfumL -1 ) for pathogen detection. The platform has a potential for further applications and provides an excellent sensitivity approach for detection of pathogenic bacteria. Copyright © 2017 Elsevier B.V. All rights reserved.

Homogeneous assay of target molecules based on chemiluminescence resonance energy transfer (CRET) using DNAzyme-linked aptamers.

PubMed

Mun, Hyoyoung; Jo, Eun-Jung; Li, Taihua; Joung, Hyou-Arm; Hong, Dong-Gu; Shim, Won-Bo; Jung, Cheulhee; Kim, Min-Gon

2014-08-15

We have designed a single-stranded DNAzyme-aptamer sensor for homogeneous target molecular detection based on chemiluminescence resonance energy transfer (CRET). The structure of the engineered single-stranded DNA (ssDNA) includes the horseradish peroxidase (HRP)-like DNAzyme, optimum-length linker (10-mer-length DNA), and target-specific aptamer sequences. A quencher dye was modified at the 3' end of the aptamer sequence. The incorporation of hemin into the G-quadruplex structure of DNAzyme yields an active HRP-like activity that catalyzes luminol to generate a chemiluminescence (CL) signal. In the presence of target molecules, such as ochratoxin A (OTA), adenosine triphosphate (ATP), or thrombin, the aptamer sequence was folded due to the formation of the aptamer/analyte complex, which induced the quencher dye close to the DNAzyme structure. Consequently, the CRET occurred between a DNAzyme-catalyzed chemiluminescence reaction and the quencher dye. Our results showed that CRET-based DNAzyme-aptamer biosensing enabled specific OTA analysis with a limit of detection of 0.27ng/mL. The CRET platform needs no external light source and avoids autofluorescence and photobleaching, and target molecules can be detected specifically and sensitively in a homogeneous manner. Copyright © 2014 Elsevier B.V. All rights reserved.

A framework for small infrared target real-time visual enhancement

NASA Astrophysics Data System (ADS)

Sun, Xiaoliang; Long, Gucan; Shang, Yang; Liu, Xiaolin

2015-03-01

This paper proposes a framework for small infrared target real-time visual enhancement. The framework is consisted of three parts: energy accumulation for small infrared target enhancement, noise suppression and weighted fusion. Dynamic programming based track-before-detection algorithm is adopted in the energy accumulation to detect the target accurately and enhance the target's intensity notably. In the noise suppression, the target region is weighted by a Gaussian mask according to the target's Gaussian shape. In order to fuse the processed target region and unprocessed background smoothly, the intensity in the target region is treated as weight in the fusion. Experiments on real small infrared target images indicate that the framework proposed in this paper can enhances the small infrared target markedly and improves the image's visual quality notably. The proposed framework outperforms tradition algorithms in enhancing the small infrared target, especially for image in which the target is hardly visible.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Highly sensitive surface plasmon resonance biosensor for the detection of HIV-related DNA based on dynamic and structural DNA nanodevices.

PubMed

Diao, Wei; Tang, Min; Ding, Shijia; Li, Xinmin; Cheng, Wenbin; Mo, Fei; Yan, Xiaoyu; Ma, Hongmin; Yan, Yurong

2018-02-15

Early detection, diagnosis and treatment of human immune deficiency virus (HIV) infection is the key to reduce acquired immunodeficiency syndrome (AIDS) mortality. In our research, an innovative surface plasmon resonance (SPR) biosensing strategy has been developed for highly sensitive detection of HIV-related DNA based on entropy-driven strand displacement reactions (ESDRs) and double-layer DNA tetrahedrons (DDTs). ESDRs as enzyme-free and label-free signal amplification circuit can be specifically triggered by target DNA, leading to the cyclic utilization of target DNA and the formation of plentiful double-stranded DNA (dsDNA) products. Subsequently, the dsDNA products bind to the immobilized hairpin capture probes and further combine with DDTs nanostructures. Due to the high efficiency of ESDRs and large molecular weight of DDTs, the SPR response signal was enhanced dramatically. The proposed SPR biosensor could detect target DNA sensitively and specifically in a linear range from 1pM to 150nM with a detection limit of 48fM. In addition, the whole detecting process can be accomplished in 60min with high accuracy and duplicability. In particular, the developed SPR biosensor was successfully used to analyze target DNA in complex biological sample, indicating that the developed strategy is promising for rapid and early clinical diagnosis of HIV infection. Copyright © 2017 Elsevier B.V. All rights reserved.

Target-protecting dumbbell molecular probe against exonucleases digestion for sensitive detection of ATP and streptavidin.

PubMed

Chen, Jinyang; Liu, Yucheng; Ji, Xinghu; He, Zhike

2016-09-15

In this work, a versatile dumbbell molecular (DM) probe was designed and employed in the sensitively homogeneous bioassay. In the presence of target molecule, the DM probe was protected from the digestion of exonucleases. Subsequently, the protected DM probe specifically bound to the intercalation dye and resulted in obvious fluorescence signal which was used to determine the target molecule in return. This design allows specific and versatile detection of diverse targets with easy operation and no sophisticated fluorescence labeling. Integrating the idea of target-protecting DM probe with adenosine triphosphate (ATP) involved ligation reaction, the DM probe with 5'-end phosphorylation was successfully constructed for ATP detection, and the limitation of detection was found to be 4.8 pM. Thanks to its excellent selectivity and sensitivity, this sensing strategy was used to detect ATP spiked in human serum as well as cellular ATP. Moreover, the proposed strategy was also applied in the visual detection of ATP in droplet-based microfluidic platform with satisfactory results. Similarly, combining the principle of target-protecting DM probe with streptavidin (SA)-biotin interaction, the DM probe with 3'-end biotinylation was developed for selective and sensitive SA determination, which demonstrated the robustness and versatility of this design. Copyright © 2016 Elsevier B.V. All rights reserved.

A benchmark for vehicle detection on wide area motion imagery

NASA Astrophysics Data System (ADS)

Catrambone, Joseph; Amzovski, Ismail; Liang, Pengpeng; Blasch, Erik; Sheaff, Carolyn; Wang, Zhonghai; Chen, Genshe; Ling, Haibin

2015-05-01

Wide area motion imagery (WAMI) has been attracting an increased amount of research attention due to its large spatial and temporal coverage. An important application includes moving target analysis, where vehicle detection is often one of the first steps before advanced activity analysis. While there exist many vehicle detection algorithms, a thorough evaluation of them on WAMI data still remains a challenge mainly due to the lack of an appropriate benchmark data set. In this paper, we address a research need by presenting a new benchmark for wide area motion imagery vehicle detection data. The WAMI benchmark is based on the recently available Wright-Patterson Air Force Base (WPAFB09) dataset and the Temple Resolved Uncertainty Target History (TRUTH) associated target annotation. Trajectory annotations were provided in the original release of the WPAFB09 dataset, but detailed vehicle annotations were not available with the dataset. In addition, annotations of static vehicles, e.g., in parking lots, are also not identified in the original release. Addressing these issues, we re-annotated the whole dataset with detailed information for each vehicle, including not only a target's location, but also its pose and size. The annotated WAMI data set should be useful to community for a common benchmark to compare WAMI detection, tracking, and identification methods.

Simple and rapid chemiluminescence aptasensor for Hg2+ in contaminated samples: A new signal amplification mechanism.

PubMed

Qi, Yingying; Xiu, Fu-Rong; Yu, Gending; Huang, Lili; Li, Baoxin

2017-01-15

Detection of ultralow concentration of heavy metal ion Hg 2+ is important for human health protection and environment monitoring because of the gradual accumulation in environmental and biological fields. Herein, we report a convenient chemiluminescence (CL) biosensing platform for ultrasensitive Hg 2+ detection by signal amplification mechanism from positively charged gold nanoparticles ((+)AuNPs). It is based on (+)AuNPs charge effect and aptamer conformation change induced by target to stimulate the generation of CL in the presence of H 2 O 2 and luminol without high salt medium. Notably particularly, the typical problem of the high salt medium from (-) AuNPs system, like influencing aptamers' bind with target and hindering CL reaction can be effectively addressed through the direct introduction of (+)AuNPs. Therefore, the proposed biosensing exhibits a high sensitivity toward target Hg 2+ with a detection limit of 16 pM, which is far below the limit (10nM) defined by the U.S. Environmental Protection Agency in drinkable water, and is about 10-fold lower than the previously reported aptamer-based assays for Hg 2+ . This sensing platform provides a simple, rapid, and cost-effective approach for label-free sensitive detection of Hg 2+ . Moreover, it is universal for the detection of other targets. Undoubtedly, such a direct utilizing of (+)AuNPs' charge effect will provide a new signal amplification way for label-free aptamer-based CL analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Real-time label-free quantitative fluorescence microscopy-based detection of ATP using a tunable fluorescent nano-aptasensor platform

NASA Astrophysics Data System (ADS)

Shrivastava, Sajal; Sohn, Il-Yung; Son, Young-Min; Lee, Won-Il; Lee, Nae-Eung

2015-11-01

Although real-time label-free fluorescent aptasensors based on nanomaterials are increasingly recognized as a useful strategy for the detection of target biomolecules with high fidelity, the lack of an imaging-based quantitative measurement platform limits their implementation with biological samples. Here we introduce an ensemble strategy for a real-time label-free fluorescent graphene (Gr) aptasensor platform. This platform employs aptamer length-dependent tunability, thus enabling the reagentless quantitative detection of biomolecules through computational processing coupled with real-time fluorescence imaging data. We demonstrate that this strategy effectively delivers dose-dependent quantitative readouts of adenosine triphosphate (ATP) concentration on chemical vapor deposited (CVD) Gr and reduced graphene oxide (rGO) surfaces, thereby providing cytotoxicity assessment. Compared with conventional fluorescence spectrometry methods, our highly efficient, universally applicable, and rational approach will facilitate broader implementation of imaging-based biosensing platforms for the quantitative evaluation of a range of target molecules.Although real-time label-free fluorescent aptasensors based on nanomaterials are increasingly recognized as a useful strategy for the detection of target biomolecules with high fidelity, the lack of an imaging-based quantitative measurement platform limits their implementation with biological samples. Here we introduce an ensemble strategy for a real-time label-free fluorescent graphene (Gr) aptasensor platform. This platform employs aptamer length-dependent tunability, thus enabling the reagentless quantitative detection of biomolecules through computational processing coupled with real-time fluorescence imaging data. We demonstrate that this strategy effectively delivers dose-dependent quantitative readouts of adenosine triphosphate (ATP) concentration on chemical vapor deposited (CVD) Gr and reduced graphene oxide (rGO) surfaces, thereby providing cytotoxicity assessment. Compared with conventional fluorescence spectrometry methods, our highly efficient, universally applicable, and rational approach will facilitate broader implementation of imaging-based biosensing platforms for the quantitative evaluation of a range of target molecules. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr05839b

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.

Highly sensitive "signal-on" electrochemiluminescent biosensor for the detection of DNA based on dual quenching and strand displacement reaction.

PubMed

Lou, Jing; Wang, Zhaoyin; Wang, Xiao; Bao, Jianchun; Tu, Wenwen; Dai, Zhihui

2015-10-07

A "signal-on" electrochemiluminescent DNA biosensing platform was proposed based on the dual quenching and strand displacement reaction. This novel "signal-on" detection strategy revealed its sensitivity in achieving a detection limit of 2.4 aM and its selectivity in distinguishing single nucleotide polymorphism of target DNA.

Clustering analysis of moving target signatures

NASA Astrophysics Data System (ADS)

Martone, Anthony; Ranney, Kenneth; Innocenti, Roberto

2010-04-01

Previously, we developed a moving target indication (MTI) processing approach to detect and track slow-moving targets inside buildings, which successfully detected moving targets (MTs) from data collected by a low-frequency, ultra-wideband radar. Our MTI algorithms include change detection, automatic target detection (ATD), clustering, and tracking. The MTI algorithms can be implemented in a real-time or near-real-time system; however, a person-in-the-loop is needed to select input parameters for the clustering algorithm. Specifically, the number of clusters to input into the cluster algorithm is unknown and requires manual selection. A critical need exists to automate all aspects of the MTI processing formulation. In this paper, we investigate two techniques that automatically determine the number of clusters: the adaptive knee-point (KP) algorithm and the recursive pixel finding (RPF) algorithm. The KP algorithm is based on a well-known heuristic approach for determining the number of clusters. The RPF algorithm is analogous to the image processing, pixel labeling procedure. Both algorithms are used to analyze the false alarm and detection rates of three operational scenarios of personnel walking inside wood and cinderblock buildings.

PECAN: Library Free Peptide Detection for Data-Independent Acquisition Tandem Mass Spectrometry Data

PubMed Central

Ting, Ying S.; Egertson, Jarrett D.; Bollinger, James G.; Searle, Brian C.; Payne, Samuel H.; Noble, William Stafford; MacCoss, Michael J.

2017-01-01

In mass spectrometry-based shogun proteomics, data-independent acquisition (DIA) is an emerging technique for unbiased and reproducible measurement of protein mixtures. Without targeting a specific precursor ion, DIA MS/MS spectra are often highly multiplexed, containing product ions from multiple co-fragmenting precursors. Thus, detecting peptides directly from DIA data is challenging; most DIA data analyses require spectral libraries. Here we present a new library-free, peptide-centric tool PECAN that detects peptides directly from DIA data. PECAN reports evidence of detection based on product ion scoring, enabling detection of low abundance analytes with poor precursor ion signal. We benchmarked PECAN with chromatographic peak picking accuracy and peptide detection capability. We further validated PECAN detection with data-dependent acquisition and targeted analyses. Last, we used PECAN to build a library from DIA data and to query sequence variants. Together, these results show that PECAN detects peptides robustly and accurately from DIA data without using a library. PMID:28783153

Experimental evaluation of penetration capabilities of a Geiger-mode APD array laser radar system

NASA Astrophysics Data System (ADS)

Jonsson, Per; Tulldahl, Michael; Hedborg, Julia; Henriksson, Markus; Sjöqvist, Lars

2017-10-01

Laser radar 3D imaging has the potential to improve target recognition in many scenarios. One case that is challenging for most optical sensors is to recognize targets hidden in vegetation or behind camouflage. The range resolution of timeof- flight 3D sensors allows segmentation of obscuration and target if the surfaces are separated far enough so that they can be resolved as two distances. Systems based on time-correlated single-photon counting (TCSPC) have the potential to resolve surfaces closer to each other compared to laser radar systems based on proportional mode detection technologies and is therefore especially interesting. Photon counting detection is commonly performed with Geigermode Avalanche Photodiodes (GmAPD) that have the disadvantage that they can only detect one photon per laser pulse per pixel. A strong return from an obscuring object may saturate the detector and thus limit the possibility to detect the hidden target even if photons from the target reach the detector. The operational range where good foliage penetration is observed is therefore relatively narrow for GmAPD systems. In this paper we investigate the penetration capability through semi-transparent surfaces for a laser radar with a 128×32 pixel GmAPD array and a 1542 nm wavelength laser operating at a pulse repetition frequency of 90 kHz. In the evaluation a screen was placed behind different canvases with varying transmissions and the detected signals from the surfaces for different laser intensities were measured. The maximum return from the second surface occurs when the total detection probability is around 0.65-0.75 per pulse. At higher laser excitation power the signal from the second surface decreases. To optimize the foliage penetration capability it is thus necessary to adaptively control the laser power to keep the returned signal within this region. In addition to the experimental results, simulations to study the influence of the pulse energy on penetration through foliage in a scene with targets behind vegetation are presented. The optimum detection of targets occurs here at a slightly higher total photon count rate probability because a number of pixel have no obscuration in front the target in their field of view.

Multi-Stage System for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

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

2010-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

A graphene-based biosensing platform based on the release of DNA probes and rolling circle amplification.

PubMed

Liu, Meng; Song, Jinping; Shuang, Shaomin; Dong, Chuan; Brennan, John D; Li, Yingfu

2014-06-24

We report a versatile biosensing platform capable of achieving ultrasensitive detection of both small-molecule and macromolecular targets. The system features three components: reduced graphene oxide for its ability to adsorb single-stranded DNA molecules nonspecifically, DNA aptamers for their ability to bind reduced graphene oxide but undergo target-induced conformational changes that facilitate their release from the reduced graphene oxide surface, and rolling circle amplification (RCA) for its ability to amplify a primer-template recognition event into repetitive sequence units that can be easily detected. The key to the design is the tagging of a short primer to an aptamer sequence, which results in a small DNA probe that allows for both effective probe adsorption onto the reduced graphene oxide surface to mask the primer domain in the absence of the target, as well as efficient probe release in the presence of the target to make the primer available for template binding and RCA. We also made an observation that the circular template, which on its own does not cause a detectable level of probe release from the reduced graphene oxide, augments target-induced probe release. The synergistic release of DNA probes is interpreted to be a contributing factor for the high detection sensitivity. The broad utility of the platform is illustrated though engineering three different sensors that are capable of achieving ultrasensitive detection of a protein target, a DNA sequence and a small-molecule analyte. We envision that the approach described herein will find useful applications in the biological, medical, and environmental fields.

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.

An integrated paper-based sample-to-answer biosensor for nucleic acid testing at the point of care.

PubMed

Choi, Jane Ru; Hu, Jie; Tang, Ruihua; Gong, Yan; Feng, Shangsheng; Ren, Hui; Wen, Ting; Li, XiuJun; Wan Abas, Wan Abu Bakar; Pingguan-Murphy, Belinda; Xu, Feng

2016-02-07

With advances in point-of-care testing (POCT), lateral flow assays (LFAs) have been explored for nucleic acid detection. However, biological samples generally contain complex compositions and low amounts of target nucleic acids, and currently require laborious off-chip nucleic acid extraction and amplification processes (e.g., tube-based extraction and polymerase chain reaction (PCR)) prior to detection. To the best of our knowledge, even though the integration of DNA extraction and amplification into a paper-based biosensor has been reported, a combination of LFA with the aforementioned steps for simple colorimetric readout has not yet been demonstrated. Here, we demonstrate for the first time an integrated paper-based biosensor incorporating nucleic acid extraction, amplification and visual detection or quantification using a smartphone. A handheld battery-powered heating device was specially developed for nucleic acid amplification in POC settings, which is coupled with this simple assay for rapid target detection. The biosensor can successfully detect Escherichia coli (as a model analyte) in spiked drinking water, milk, blood, and spinach with a detection limit of as low as 10-1000 CFU mL(-1), and Streptococcus pneumonia in clinical blood samples, highlighting its potential use in medical diagnostics, food safety analysis and environmental monitoring. As compared to the lengthy conventional assay, which requires more than 5 hours for the entire sample-to-answer process, it takes about 1 hour for our integrated biosensor. The integrated biosensor holds great potential for detection of various target analytes for wide applications in the near future.

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.

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.

A Technique for Real-Time Ionospheric Ranging Error Correction Based On Radar Dual-Frequency Detection

NASA Astrophysics Data System (ADS)

Lyu, Jiang-Tao; Zhou, Chen

2017-12-01

Ionospheric refraction is one of the principal error sources for limiting the accuracy of radar systems for space target detection. High-accuracy measurement of the ionospheric electron density along the propagation path of radar wave is the most important procedure for the ionospheric refraction correction. Traditionally, the ionospheric model and the ionospheric detection instruments, like ionosonde or GPS receivers, are employed for obtaining the electron density. However, both methods are not capable of satisfying the requirements of correction accuracy for the advanced space target radar system. In this study, we propose a novel technique for ionospheric refraction correction based on radar dual-frequency detection. Radar target range measurements at two adjacent frequencies are utilized for calculating the electron density integral exactly along the propagation path of the radar wave, which can generate accurate ionospheric range correction. The implementation of radar dual-frequency detection is validated by a P band radar located in midlatitude China. The experimental results present that the accuracy of this novel technique is more accurate than the traditional ionospheric model correction. The technique proposed in this study is very promising for the high-accuracy radar detection and tracking of objects in geospace.

Application of multivariate Gaussian detection theory to known non-Gaussian probability density functions

NASA Astrophysics Data System (ADS)

Schwartz, Craig R.; Thelen, Brian J.; Kenton, Arthur C.

1995-06-01

A statistical parametric multispectral sensor performance model was developed by ERIM to support mine field detection studies, multispectral sensor design/performance trade-off studies, and target detection algorithm development. The model assumes target detection algorithms and their performance models which are based on data assumed to obey multivariate Gaussian probability distribution functions (PDFs). The applicability of these algorithms and performance models can be generalized to data having non-Gaussian PDFs through the use of transforms which convert non-Gaussian data to Gaussian (or near-Gaussian) data. An example of one such transform is the Box-Cox power law transform. In practice, such a transform can be applied to non-Gaussian data prior to the introduction of a detection algorithm that is formally based on the assumption of multivariate Gaussian data. This paper presents an extension of these techniques to the case where the joint multivariate probability density function of the non-Gaussian input data is known, and where the joint estimate of the multivariate Gaussian statistics, under the Box-Cox transform, is desired. The jointly estimated multivariate Gaussian statistics can then be used to predict the performance of a target detection algorithm which has an associated Gaussian performance model.

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.

Automated Threshold Selection for Template-Based Sonar Target Detection

DTIC Science & Technology

2017-08-01

test based on the distribution of the matched filter correlations. From the matched filter output we evaluate target sized areas and surrounding...synthetic aperture sonar data that were part of the evaluation . Figure 3 shows a nearly uniform seafloor. Figure 4 is more complex, with

A Paper-Based Sandwich Format Hybridization Assay for Unlabeled Nucleic Acid Detection Using Upconversion Nanoparticles as Energy Donors in Luminescence Resonance Energy Transfer.

PubMed

Zhou, Feng; Noor, M Omair; Krull, Ulrich J

2015-09-24

Bioassays based on cellulose paper substrates are gaining increasing popularity for the development of field portable and low-cost diagnostic applications. Herein, we report a paper-based nucleic acid hybridization assay using immobilized upconversion nanoparticles (UCNPs) as donors in luminescence resonance energy transfer (LRET). UCNPs with intense green emission served as donors with Cy3 dye as the acceptor. The avidin functionalized UCNPs were immobilized on cellulose paper and subsequently bioconjugated to biotinylated oligonucleotide probes. Introduction of unlabeled oligonucleotide targets resulted in a formation of probe-target duplexes. A subsequent hybridization of Cy3 labeled reporter with the remaining single stranded portion of target brought the Cy3 dye in close proximity to the UCNPs to trigger a LRET-sensitized emission from the acceptor dye. The hybridization assays provided a limit of detection (LOD) of 146.0 fmol and exhibited selectivity for one base pair mismatch discrimination. The assay was functional even in undiluted serum samples. This work embodies important progress in developing DNA hybridization assays on paper. Detection of unlabeled targets is achieved using UCNPs as LRET donors, with minimization of background signal from paper substrates owing to the implementation of low energy near-infrared (NIR) excitation.

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.

One-step detection of microRNA with high sensitivity and specificity via target-triggered loop-mediated isothermal amplification (TT-LAMP).

PubMed

Sun, Yuanyuan; Tian, Hui; Liu, Chenghui; Sun, Yueying; Li, Zhengping

2017-10-05

A novel one-step microRNA assay is developed based on a target-triggered loop-mediated isothermal amplification (TT-LAMP) mechanism, which enables the accurate detection of as low as 100 aM (1 zmol) microRNA with simple one-step operation by using only one-type of DNA polymerase.

Multiplexed target detection using DNA-binding dye chemistry in droplet digital PCR.

PubMed

McDermott, Geoffrey P; Do, Duc; Litterst, Claudia M; Maar, Dianna; Hindson, Christopher M; Steenblock, Erin R; Legler, Tina C; Jouvenot, Yann; Marrs, Samuel H; Bemis, Adam; Shah, Pallavi; Wong, Josephine; Wang, Shenglong; Sally, David; Javier, Leanne; Dinio, Theresa; Han, Chunxiao; Brackbill, Timothy P; Hodges, Shawn P; Ling, Yunfeng; Klitgord, Niels; Carman, George J; Berman, Jennifer R; Koehler, Ryan T; Hiddessen, Amy L; Walse, Pramod; Bousse, Luc; Tzonev, Svilen; Hefner, Eli; Hindson, Benjamin J; Cauly, Thomas H; Hamby, Keith; Patel, Viresh P; Regan, John F; Wyatt, Paul W; Karlin-Neumann, George A; Stumbo, David P; Lowe, Adam J

2013-12-03

Two years ago, we described the first droplet digital PCR (ddPCR) system aimed at empowering all researchers with a tool that removes the substantial uncertainties associated with using the analogue standard, quantitative real-time PCR (qPCR). This system enabled TaqMan hydrolysis probe-based assays for the absolute quantification of nucleic acids. Due to significant advancements in droplet chemistry and buoyed by the multiple benefits associated with dye-based target detection, we have created a "second generation" ddPCR system compatible with both TaqMan-probe and DNA-binding dye detection chemistries. Herein, we describe the operating characteristics of DNA-binding dye based ddPCR and offer a side-by-side comparison to TaqMan probe detection. By partitioning each sample prior to thermal cycling, we demonstrate that it is now possible to use a DNA-binding dye for the quantification of multiple target species from a single reaction. The increased resolution associated with partitioning also made it possible to visualize and account for signals arising from nonspecific amplification products. We expect that the ability to combine the precision of ddPCR with both DNA-binding dye and TaqMan probe detection chemistries will further enable the research community to answer complex and diverse genetic questions.

Foliage penetration by using 4-D point cloud data

NASA Astrophysics Data System (ADS)

Méndez Rodríguez, Javier; Sánchez-Reyes, Pedro J.; Cruz-Rivera, Sol M.

2012-06-01

Real-time awareness and rapid target detection are critical for the success of military missions. New technologies capable of detecting targets concealed in forest areas are needed in order to track and identify possible threats. Currently, LAser Detection And Ranging (LADAR) systems are capable of detecting obscured targets; however, tracking capabilities are severely limited. Now, a new LADAR-derived technology is under development to generate 4-D datasets (3-D video in a point cloud format). As such, there is a new need for algorithms that are able to process data in real time. We propose an algorithm capable of removing vegetation and other objects that may obfuscate concealed targets in a real 3-D environment. The algorithm is based on wavelets and can be used as a pre-processing step in a target recognition algorithm. Applications of the algorithm in a real-time 3-D system could help make pilots aware of high risk hidden targets such as tanks and weapons, among others. We will be using a 4-D simulated point cloud data to demonstrate the capabilities of our algorithm.

The Detection of Protein via ZnO Resonant Raman Scattering Signal

NASA Astrophysics Data System (ADS)

Shan, Guiye; Yang, Guoliang; Wang, Shuang; Liu, Yichun

2008-03-01

Detecting protein with high sensitivity and specificity is essential for disease diagnostics, drug screening and other application. Semiconductor nanoparticles show better properties than organic dye molecules when used as markers for optical measurements. We used ZnO nanoparticles as markers for detecting protein in resonant Raman scattering measurements. The highly sensitive detection of proteins was achieved by an antibody-based sandwich assay. A probe for the target protein was constructed by binding the ZnO/Au nanoparticles to a primary antibody by eletrostatic interaction between Au and the antibody. A secondary antibody, which could be specifically recognized by target protein, was attached to a solid surface. The ZnO/Au-antibody probe could specifically recognize and bind to the complex of the target protein and secondary antibody. Our measurements using the resonant Raman scattering signal of ZnO nanoparticles showed good selectivity and sensitivity for the target protein.

Mitochondrial DNA Targets Increase Sensitivity of Malaria Detection Using Loop-Mediated Isothermal Amplification ▿

PubMed Central

Polley, Spencer D.; Mori, Yasuyoshi; Watson, Julie; Perkins, Mark D.; González, Iveth J.; Notomi, Tsugunori; Chiodini, Peter L.; Sutherland, Colin J.

2010-01-01

Loop-mediated isothermal amplification (LAMP) of DNA offers the ability to detect very small quantities of pathogen DNA following minimal tissue sample processing and is thus an attractive methodology for point-of-care diagnostics. Previous attempts to diagnose malaria by the use of blood samples and LAMP have targeted the parasite small-subunit rRNA gene, with a resultant sensitivity for Plasmodium falciparum of around 100 parasites per μl. Here we describe the use of mitochondrial targets for LAMP-based detection of any Plasmodium genus parasite and of P. falciparum specifically. These new targets allow routine amplification from samples containing as few as five parasites per μl of blood. Amplification is complete within 30 to 40 min and is assessed by real-time turbidimetry, thereby offering rapid diagnosis with greater sensitivity than is achieved by the most skilled microscopist or antigen detection using lateral flow immunoassays. PMID:20554824

Target detection cycle criteria when using the targeting task performance metric

NASA Astrophysics Data System (ADS)

Hixson, Jonathan G.; Jacobs, Eddie L.; Vollmerhausen, Richard H.

2004-12-01

The US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate of the US Army (NVESD) has developed a new target acquisition metric to better predict the performance of modern electro-optical imagers. The TTP metric replaces the Johnson criteria. One problem with transitioning to the new model is that the difficulty of searching in a terrain has traditionally been quantified by an "N50." The N50 is the number of Johnson criteria cycles needed for the observer to detect the target half the time, assuming that the observer is not time limited. In order to make use of this empirical data base, a conversion must be found relating Johnson cycles for detection to TTP cycles for detection. This paper describes how that relationship is established. We have found that the relationship between Johnson and TTP is 1:2.7 for the recognition and identification tasks.

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.

Incorporating signal-dependent noise for hyperspectral target detection

NASA Astrophysics Data System (ADS)

Morman, Christopher J.; Meola, Joseph

2015-05-01

The majority of hyperspectral target detection algorithms are developed from statistical data models employing stationary background statistics or white Gaussian noise models. Stationary background models are inaccurate as a result of two separate physical processes. First, varying background classes often exist in the imagery that possess different clutter statistics. Many algorithms can account for this variability through the use of subspaces or clustering techniques. The second physical process, which is often ignored, is a signal-dependent sensor noise term. For photon counting sensors that are often used in hyperspectral imaging systems, sensor noise increases as the measured signal level increases as a result of Poisson random processes. This work investigates the impact of this sensor noise on target detection performance. A linear noise model is developed describing sensor noise variance as a linear function of signal level. The linear noise model is then incorporated for detection of targets using data collected at Wright Patterson Air Force Base.

Quantum Dot-Fullerene Based Molecular Beacon Nanosensors for Rapid, Highly Sensitive Nucleic Acid Detection.

PubMed

Liu, Ye; Kannegulla, Akash; Wu, Bo; Cheng, Li-Jing

2018-05-15

Spherical fullerene (C 60 ) can quench the fluorescence of a quantum dot (QD) through energy transfer and charge transfer processes, with the quenching efficiency regulated by the number of proximate C 60 on each QD. With the quenching property and its small size compared with other nanoparticle-based quenchers, it is advantageous to group a QD reporter and multiple C 60 -labeled oligonucleotide probes to construct a molecular beacon (MB) probe for sensitive, robust nucleic acid detection. We demonstrated a rapid, high-sensitivity DNA detection method using the nanosensors composed of QD-C 60 based MBs carried by magnetic nanoparticles (MNPs). The assay was accelerated by first dispersing the nanosensors in analytes for highly efficient DNA capture resulting from short-distance 3-dimensional diffusion of targets to the sensor surface and then concentrating the nanosensors to a substrate by magnetic force to amplify the fluorescence signal for target quantification. The enhanced mass transport enabled a rapid detection (< 10 min) with a small sample volume (1-10 µl). The high signal-to-noise ratio produced by the QD-C 60 pairs and magnetic concentration yielded a detection limit of 100 fM (~106 target DNA copies for a 10 µl analyte). The rapid, sensitive, label-free detection method will benefit the applications in point-of-care molecular diagnostic technologies.

Development of a Fluorescence Resonance Energy Transfer (FRET)-Based DNA Biosensor for Detection of Synthetic Oligonucleotide of Ganoderma boninense

PubMed Central

Mohd Bakhori, Noremylia; Yusof, Nor Azah; Abdullah, Abdul Halim; Hussein, Mohd Zobir

2013-01-01

An optical DNA biosensor based on fluorescence resonance energy transfer (FRET) utilizing synthesized quantum dot (QD) has been developed for the detection of specific-sequence of DNA for Ganoderma boninense, an oil palm pathogen. Modified QD that contained carboxylic groups was conjugated with a single-stranded DNA probe (ssDNA) via amide-linkage. Hybridization of the target DNA with conjugated QD-ssDNA and reporter probe labeled with Cy5 allows for the detection of related synthetic DNA sequence of Ganoderma boninense gene based on FRET signals. Detection of FRET emission before and after hybridization was confirmed through the capability of the system to produce FRET at 680 nm for hybridized sandwich with complementary target DNA. No FRET emission was observed for non-complementary system. Hybridization time, temperature and effect of different concentration of target DNA were studied in order to optimize the developed system. The developed biosensor has shown high sensitivity with detection limit of 3.55 × 10−9 M. TEM results show that the particle size of QD varies in the range between 5 to 8 nm after ligand modification and conjugation with ssDNA. This approach is capable of providing a simple, rapid and sensitive method for detection of related synthetic DNA sequence of Ganoderma boninense. PMID:25587406

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.

Constrained motion model of mobile robots and its applications.

PubMed

Zhang, Fei; Xi, Yugeng; Lin, Zongli; Chen, Weidong

2009-06-01

Target detecting and dynamic coverage are fundamental tasks in mobile robotics and represent two important features of mobile robots: mobility and perceptivity. This paper establishes the constrained motion model and sensor model of a mobile robot to represent these two features and defines the k -step reachable region to describe the states that the robot may reach. We show that the calculation of the k-step reachable region can be reduced from that of 2(k) reachable regions with the fixed motion styles to k + 1 such regions and provide an algorithm for its calculation. Based on the constrained motion model and the k -step reachable region, the problems associated with target detecting and dynamic coverage are formulated and solved. For target detecting, the k-step detectable region is used to describe the area that the robot may detect, and an algorithm for detecting a target and planning the optimal path is proposed. For dynamic coverage, the k-step detected region is used to represent the area that the robot has detected during its motion, and the dynamic-coverage strategy and algorithm are proposed. Simulation results demonstrate the efficiency of the coverage algorithm in both convex and concave environments.

DNA-magnetic bead detection using disposable cards and the anisotropic magnetoresistive sensor

NASA Astrophysics Data System (ADS)

Hien, L. T.; Quynh, L. K.; Huyen, V. T.; Tu, B. D.; Hien, N. T.; Phuong, D. M.; Nhung, P. H.; Giang, D. T. H.; Duc, N. H.

2016-12-01

A disposable card incorporating specific DNA probes targeting the 16 S rRNA gene of Streptococcus suis was developed for magnetically labeled target DNA detection. A single-stranded target DNA was hybridized with the DNA probe on the SPA/APTES/PDMS/Si as-prepared card, which was subsequently magnetically labeled with superparamagnetic beads for detection using an anisotropic magnetoresistive (AMR) sensor. An almost linear response between the output signal of the AMR sensor and amount of single-stranded target DNA varied from 4.5 to 18 pmol was identified. From the sensor output signal response towards the mass of magnetic beads which were directly immobilized on the disposable card surface, the limit of detection was estimated about 312 ng ferrites, which corresponds to 3.8 μemu. In comparison with DNA detection by conventional biosensor based on magnetic bead labeling, disposable cards are featured with higher efficiency and performances, ease of use and less running cost with respects to consumables for biosensor in biomedical analysis systems operating with immobilized bioreceptor.

Hybridization chain reaction-based instantaneous derivatization technology for chemiluminescence detection of specific DNA sequences.

PubMed

Wang, Xin; Lau, Choiwan; Kai, Masaaki; Lu, Jianzhong

2013-05-07

We propose here a new amplifying strategy that uses hybridization chain reaction (HCR) to detect specific sequences of DNA, where stable DNA monomers assemble on the magnetic beads only upon exposure to a target DNA. Briefly, in the HCR process, two complementary stable species of hairpins coexist in solution until the introduction of initiator reporter strands triggers a cascade of hybridization events that yield nicked double helices analogous to alternating copolymers. Moreover, a "sandwich-type" detection strategy is employed in our design. Magnetic beads, which are functionalized with capture DNA, are reacted with the target, and sandwiched with the above nicked double helices. Then, chemiluminescence (CL) detection proceeds via an instantaneous derivatization reaction between a specific CL reagent, 3,4,5-trimethoxylphenylglyoxal (TMPG), and the guanine nucleotides within the target DNA, reporter strands and DNA monomers for the generation of light. Our results clearly show that the amplification detection of specific sequences of DNA achieves a better performance (e.g. wide linear response range, low detection limit, and high specificity) as compared to the traditional sandwich type (capture/target/reporter) assays. Upon modification, the approach presented could be extended to detect other types of targets. We believe that this simple technique is promising for improving medical diagnosis and treatment.

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.

Evaluating De-centralised and Distributional Options for the Distributed Electronic Warfare Situation Awareness and Response Test Bed

DTIC Science & Technology

2013-12-01

effectors (deployed on ground based or aerial platforms) to detect , identify, locate, track or suppress stationary or slow moving surface based RF...ground based or aerial platforms) to detect , identify, locate, track or suppress stationary or slow moving surface based RF emitting targets. In the...Electronic Support EO Electro-Optic FPGAs Field Programmable Gate Arrays IR Infra-red LADAR Laser Detection and Ranging OSX Mac OS X; the apple

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

Microwave-accelerated method for ultra-rapid extraction of Neisseria gonorrhoeae DNA for downstream detection.

PubMed

Melendez, Johan H; Santaus, Tonya M; Brinsley, Gregory; Kiang, Daniel; Mali, Buddha; Hardick, Justin; Gaydos, Charlotte A; Geddes, Chris D

2016-10-01

Nucleic acid-based detection of gonorrhea infections typically require a two-step process involving isolation of the nucleic acid, followed by detection of the genomic target often involving polymerase chain reaction (PCR)-based approaches. In an effort to improve on current detection approaches, we have developed a unique two-step microwave-accelerated approach for rapid extraction and detection of Neisseria gonorrhoeae (gonorrhea, GC) DNA. Our approach is based on the use of highly focused microwave radiation to rapidly lyse bacterial cells, release, and subsequently fragment microbial DNA. The DNA target is then detected by a process known as microwave-accelerated metal-enhanced fluorescence (MAMEF), an ultra-sensitive direct DNA detection analytical technique. In the current study, we show that highly focused microwaves at 2.45 GHz, using 12.3-mm gold film equilateral triangles, are able to rapidly lyse both bacteria cells and fragment DNA in a time- and microwave power-dependent manner. Detection of the extracted DNA can be performed by MAMEF, without the need for DNA amplification, in less than 10 min total time or by other PCR-based approaches. Collectively, the use of a microwave-accelerated method for the release and detection of DNA represents a significant step forward toward the development of a point-of-care (POC) platform for detection of gonorrhea infections. Copyright © 2016 Elsevier Inc. All rights reserved.

Aerial surveillance based on hierarchical object classification for ground target detection

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Research on photodiode detector-based spatial transient light detection and processing system

NASA Astrophysics Data System (ADS)

Liu, Meiying; Wang, Hu; Liu, Yang; Zhao, Hui; Nan, Meng

2016-10-01

In order to realize real-time signal identification and processing of spatial transient light, the features and the energy of the captured target light signal are first described and quantitatively calculated. Considering that the transient light signal has random occurrence, a short duration and an evident beginning and ending, a photodiode detector based spatial transient light detection and processing system is proposed and designed in this paper. This system has a large field of view and is used to realize non-imaging energy detection of random, transient and weak point target under complex background of spatial environment. Weak signal extraction under strong background is difficult. In this paper, considering that the background signal changes slowly and the target signal changes quickly, filter is adopted for signal's background subtraction. A variable speed sampling is realized by the way of sampling data points with a gradually increased interval. The two dilemmas that real-time processing of large amount of data and power consumption required by the large amount of data needed to be stored are solved. The test results with self-made simulative signal demonstrate the effectiveness of the design scheme. The practical system could be operated reliably. The detection and processing of the target signal under the strong sunlight background was realized. The results indicate that the system can realize real-time detection of target signal's characteristic waveform and monitor the system working parameters. The prototype design could be used in a variety of engineering applications.

TargetVue: Visual Analysis of Anomalous User Behaviors in Online Communication Systems.

PubMed

Cao, Nan; Shi, Conglei; Lin, Sabrina; Lu, Jie; Lin, Yu-Ru; Lin, Ching-Yung

2016-01-01

Users with anomalous behaviors in online communication systems (e.g. email and social medial platforms) are potential threats to society. Automated anomaly detection based on advanced machine learning techniques has been developed to combat this issue; challenges remain, though, due to the difficulty of obtaining proper ground truth for model training and evaluation. Therefore, substantial human judgment on the automated analysis results is often required to better adjust the performance of anomaly detection. Unfortunately, techniques that allow users to understand the analysis results more efficiently, to make a confident judgment about anomalies, and to explore data in their context, are still lacking. In this paper, we propose a novel visual analysis system, TargetVue, which detects anomalous users via an unsupervised learning model and visualizes the behaviors of suspicious users in behavior-rich context through novel visualization designs and multiple coordinated contextual views. Particularly, TargetVue incorporates three new ego-centric glyphs to visually summarize a user's behaviors which effectively present the user's communication activities, features, and social interactions. An efficient layout method is proposed to place these glyphs on a triangle grid, which captures similarities among users and facilitates comparisons of behaviors of different users. We demonstrate the power of TargetVue through its application in a social bot detection challenge using Twitter data, a case study based on email records, and an interview with expert users. Our evaluation shows that TargetVue is beneficial to the detection of users with anomalous communication behaviors.

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

Stimulus-response mesoporous silica nanoparticle-based chemiluminescence biosensor for cocaine determination.

PubMed

Chen, Zhonghui; Tan, Yue; Xu, Kefeng; Zhang, Lan; Qiu, Bin; Guo, Longhua; Lin, Zhenyu; Chen, Guonan

2016-01-15

Mesoporous silica nanoparticles (MSN) based controlled release system had been coupled with diverse detection technologies to establish biosensors for different targets. Chemiluminescence (CL) system of luminol/H2O2 owns the characters of simplicity, low cost and high sensitivity, but the targets of which are mostly focused on some oxidants or which can participate in a chemical reaction that yields a product with a role in the CL reaction. In this study, chemiluminescent detection technique had been coupled with mesoporous silica-based controlled released system for the first time to develop a sensitive biosensor for the target which does not cause effect to the CL system itself. Cocaine had been chosen a model target, the MSN support was firstly loaded with glucose, then the positively charged MSN interacted with negatively charged oligonucleotides (the aptamer cocaine) to close the mesopores of MSN. At the present of target, cocaine binds with its aptamer with high affinity; the flexible linear aptamer structured will become stems structured through currently well-defined non-Waston-Crick interactions and causes the releasing of entrapped glucose into the solution. With the assistant of glucose oxidase (GOx), the released glucose can react with the dissolved oxgen to produce gluconic acid and H2O2, the latter can enhance the CL of luminol in the NaOH solution. The enhanced CL intensity has a relationship with the cocaine concentration in the range of 5.0-60μM with the detection limit of 1.43μM. The proposed method had been successfully applied to detect cocaine in serum samples with high selectivity. The same strategy can be applied to develop biosensors for different targets. Copyright © 2015 Elsevier B.V. All rights reserved.

Neurotechnology for intelligence analysts

NASA Astrophysics Data System (ADS)

Kruse, Amy A.; Boyd, Karen C.; Schulman, Joshua J.

2006-05-01

Geospatial Intelligence Analysts are currently faced with an enormous volume of imagery, only a fraction of which can be processed or reviewed in a timely operational manner. Computer-based target detection efforts have failed to yield the speed, flexibility and accuracy of the human visual system. Rather than focus solely on artificial systems, we hypothesize that the human visual system is still the best target detection apparatus currently in use, and with the addition of neuroscience-based measurement capabilities it can surpass the throughput of the unaided human severalfold. Using electroencephalography (EEG), Thorpe et al1 described a fast signal in the brain associated with the early detection of targets in static imagery using a Rapid Serial Visual Presentation (RSVP) paradigm. This finding suggests that it may be possible to extract target detection signals from complex imagery in real time utilizing non-invasive neurophysiological assessment tools. To transform this phenomenon into a capability for defense applications, the Defense Advanced Research Projects Agency (DARPA) currently is sponsoring an effort titled Neurotechnology for Intelligence Analysts (NIA). The vision of the NIA program is to revolutionize the way that analysts handle intelligence imagery, increasing both the throughput of imagery to the analyst and overall accuracy of the assessments. Successful development of a neurobiologically-based image triage system will enable image analysts to train more effectively and process imagery with greater speed and precision.

EDIM-TKTL1/Apo10 Blood Test: An Innate Immune System Based Liquid Biopsy for the Early Detection, Characterization and Targeted Treatment of Cancer.

PubMed

Coy, Johannes F

2017-04-20

Epitope detection in monocytes (EDIM) represents a liquid biopsy exploiting the innate immune system. Activated monocytes (macrophages) phagocytose unwanted cells/cell fragments from the whole body including solid tissues. As they return to the blood, macrophages can be used for a non-invasive detection of biomarkers, thereby providing high sensitivity and specificity, because the intracellular presence of biomarkers is due to an innate immune response. Flow cytometry analysis of blood enables the detection of macrophages and phagocytosed intracellular biomarkers. In order to establish a pan-cancer test, biomarkers for two fundamental biophysical mechanisms have been exploited. The DNaseX/Apo10 protein epitope is a characteristic of tumor cells with abnormal apoptosis and proliferation. Transketolase-like 1 (TKTL1) is a marker for an anaerobic glucose metabolism (Warburg effect), which is concomitant with invasive growth/metastasis and resistant to radical and apoptosis inducing therapies. The detection of Apo10 and TKTL1 in blood macrophages allowed a sensitive (95.8%) and specific (97.3%) detection of prostate, breast and oral squamous cell carcinomas. Since TKTL1 represents a drugable target, the EDIM based detection of TKTL1 enables a targeted cancer therapy using the vitamin derivatives oxythiamine or benfo-oxythiamine.

Fluorescence bio-barcode DNA assay based on gold and magnetic nanoparticles for detection of Exotoxin A gene sequence.

PubMed

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

2017-06-15

Bio-barcode DNA based on gold nanoparticle (bDNA-GNPs) as a new generation of biosensor based detection tools, holds promise for biological science studies. They are of enormous importance in the emergence of rapid and sensitive procedures for detecting toxins of microorganisms. Exotoxin A (ETA) is the most toxic virulence factor of Pseudomonas aeruginosa. ETA has ADP-ribosylation activity and decisively affects the protein synthesis of the host cells. In the present study, we developed a fluorescence bio-barcode technology to trace P. aeruginosa ETA. The GNPs were coated with the first target-specific DNA probe 1 (1pDNA) and bio-barcode DNA, which acted as a signal reporter. The magnetic nanoparticles (MNPs) were coated with the second target-specific DNA probe 2 (2pDNA) that was able to recognize the other end of the target DNA. After binding the nanoparticles with the target DNA, the following sandwich structure was formed: MNP 2pDNA/tDNA/1pDNA-GNP-bDNA. After isolating the sandwiches by a magnetic field, the DNAs of the probes which have been hybridized to their complementary DNA, GNPs and MNPs, via the hydrogen, electrostatic and covalently bonds, were released from the sandwiches after dissolving in dithiothreitol solution (DTT 0.8M). This bio-barcode DNA with known DNA sequence was then detected by fluorescence spectrophotometry. The findings showed that the new method has the advantages of fast, high sensitivity (the detection limit was 1.2ng/ml), good selectivity, and wide linear range of 5-200ng/ml. The regression analysis also showed that there was a good linear relationship (∆F=0.57 [target DNA]+21.31, R 2 =0.9984) between the fluorescent intensity and the target DNA concentration in the samples. Copyright © 2016. Published by Elsevier B.V.

Label-free DNA hybridization detection and single base-mismatch discrimination using CE-ICP-MS assay.

PubMed

Li, Yan; Sun, Shao-kai; Yang, Jia-lin; Jiang, Yan

2011-12-07

Detecting a specific DNA sequence and discriminating single base-mismatch is critical to clinical diagnosis, paternity testing, forensic sciences, food and drug industry, pathology, genetics, environmental monitoring, and anti-bioterrorism. To this end, capillary electrophoresis (CE) coupled with the inductively coupled plasma mass spectrometry (ICP-MS) method is developed using the displacing interaction between the target ssDNA and the competitor Hg(2+) for the first time. The thymine-rich capture ssDNA 1 is interacted with the competitor Hg(2+), forming an assembled complex in a hairpin-structure between the thymine bases arrangement at both sides of the capture ssDNA 1. In the presence of a target ssDNA with stronger affinity than that of the competitor Hg(2+), the energetically favorable hybridization between capture ssDNA 1 and the target ssDNA destroys the hairpin-structure and releases the competitor as free Hg(2+), which was then read out and accurately quantified by CE-ICP-MS assay. Under the optimal CE separation conditions, free Hg(2+) ions and its capture ssDNA 1 adduct were baseline separated and detected on-line by ICP-MS; the increased peak intensity of free Hg(2+) against the concentration of perfectly complementary target ssDNA was linear over the concentration range of 30-600 nmol L(-1) with a limit of detection of 8 nmol L(-1) (3s, n = 11) in the pre-incubated mixture containing 1 μmol L(-1) Hg(2+) and 0.2 μmol L(-1) capture ssDNA 1. This new assay method is simple in design since any target ssDNA binding can in principle result in free Hg(2+) release by 6-fold Hg(2+) signal amplification, avoiding oligonucleotide labeling or assistance by excess signal transducer and signal reporter to read out the target. Due to element-specific detection of ICP-MS in our assay procedure, the interference from the autofluorescence of substrata was eliminated.

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.

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.

Clutter attenuation using the Doppler effect in standoff electromagnetic quantum sensing

NASA Astrophysics Data System (ADS)

Lanzagorta, Marco; Jitrik, Oliverio; Uhlmann, Jeffrey; Venegas, Salvador

2016-05-01

In the context of traditional radar systems, the Doppler effect is crucial to detect and track moving targets in the presence of clutter. In the quantum radar context, however, most theoretical performance analyses to date have assumed static targets. In this paper we consider the Doppler effect at the single photon level. In particular, we describe how the Doppler effect produced by clutter and moving targets modifies the quantum distinguishability and the quantum radar error detection probability equations. Furthermore, we show that Doppler-based delayline cancelers can reduce the effects of clutter in the context of quantum radar, but only in the low-brightness regime. Thus, quantum radar may prove to be an important technology if the electronic battlefield requires stealthy tracking and detection of moving targets in the presence of clutter.

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.

A new FOD recognition algorithm based on multi-source information fusion and experiment analysis

NASA Astrophysics Data System (ADS)

Li, Yu; Xiao, Gang

2011-08-01

Foreign Object Debris (FOD) is a kind of substance, debris or article alien to an aircraft or system, which would potentially cause huge damage when it appears on the airport runway. Due to the airport's complex circumstance, quick and precise detection of FOD target on the runway is one of the important protections for airplane's safety. A multi-sensor system including millimeter-wave radar and Infrared image sensors is introduced and a developed new FOD detection and recognition algorithm based on inherent feature of FOD is proposed in this paper. Firstly, the FOD's location and coordinate can be accurately obtained by millimeter-wave radar, and then according to the coordinate IR camera will take target images and background images. Secondly, in IR image the runway's edges which are straight lines can be extracted by using Hough transformation method. The potential target region, that is, runway region, can be segmented from the whole image. Thirdly, background subtraction is utilized to localize the FOD target in runway region. Finally, in the detailed small images of FOD target, a new characteristic is discussed and used in target classification. The experiment results show that this algorithm can effectively reduce the computational complexity, satisfy the real-time requirement and possess of high detection and recognition probability.

Nanoparticle-facilitated functional and molecular imaging for the early detection of cancer

PubMed Central

Sivasubramanian, Maharajan; Hsia, Yu; Lo, Leu-Wei

2014-01-01

Cancer detection in its early stages is imperative for effective cancer treatment and patient survival. In recent years, biomedical imaging techniques, such as magnetic resonance imaging, computed tomography and ultrasound have been greatly developed and have served pivotal roles in clinical cancer management. Molecular imaging (MI) is a non-invasive imaging technique that monitors biological processes at the cellular and sub-cellular levels. To achieve these goals, MI uses targeted imaging agents that can bind targets of interest with high specificity and report on associated abnormalities, a task that cannot be performed by conventional imaging techniques. In this respect, MI holds great promise as a potential therapeutic tool for the early diagnosis of cancer. Nevertheless, the clinical applications of targeted imaging agents are limited due to their inability to overcome biological barriers inside the body. The use of nanoparticles has made it possible to overcome these limitations. Hence, nanoparticles have been the subject of a great deal of recent studies. Therefore, developing nanoparticle-based imaging agents that can target tumors via active or passive targeting mechanisms is desirable. This review focuses on the applications of various functionalized nanoparticle-based imaging agents used in MI for the early detection of cancer. PMID:25988156

Active interrogation using low-energy nuclear reactions

NASA Astrophysics Data System (ADS)

Antolak, Arlyn; Doyle, Barney; Leung, Ka-Ngo; Morse, Daniel; Provencio, Paula

2005-09-01

High-energy photons and neutrons can be used to interrogate for heavily shielded fissile materials inside sealed cargo containers by detecting their prompt and/or delayed fission signatures. The FIND (Fissmat Inspection for Nuclear Detection) active interrogation system is based on a dual neutron+gamma source that uses low-energy (< 500 keV) proton- or deuteron-induced nuclear reactions to produce high intensities of mono-energetic gamma rays and/or neutrons. The source can be operated in either pulsed (e.g., to detect delayed photofission neutrons and gammas) or continuous (e.g., detecting prompt fission signatures) modes. For the gamma-rays, the source target can be segmented to incorporate different (p,γ) isotopes for producing gamma-rays at selective energies, thereby improving the probability of detection. The design parameters for the FIND system are discussed and preliminary accelerator-based measurements of gamma and neutron yields, background levels, and fission signals for several target materials under consideration are presented.

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.

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.

Electro-optic tracking R&D for defense surveillance

NASA Astrophysics Data System (ADS)

Sutherland, Stuart; Woodruff, Chris J.

1995-09-01

Two aspects of work on automatic target detection and tracking for electro-optic (EO) surveillance are described. Firstly, a detection and tracking algorithm test-bed developed by DSTO and running on a PC under Windows NT is being used to assess candidate algorithms for unresolved and minimally resolved target detection. The structure of this test-bed is described and examples are given of its user interfaces and outputs. Secondly, a development by Australian industry under a Defence-funded contract, of a reconfigurable generic track processor (GTP) is outlined. The GTP will include reconfigurable image processing stages and target tracking algorithms. It will be used to demonstrate to the Australian Defence Force automatic detection and tracking capabilities, and to serve as a hardware base for real time algorithm refinement.

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.

Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery

PubMed Central

Alam, Mohammad S.; Bhuiyan, Sharif M. A.

2014-01-01

In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences. PMID:25061840

Inside-the-wall detection of objects with low metal content using the GPR sensor: effects of different wall structures on the detection performance

NASA Astrophysics Data System (ADS)

Dogan, Mesut; Yesilyurt, Omer; Turhan-Sayan, Gonul

2018-04-01

Ground penetrating radar (GPR) is an ultra-wideband electromagnetic sensor used not only for subsurface sensing but also for the detection of objects which may be hidden behind a wall or inserted within the wall. Such applications of the GPR technology are used in both military and civilian operations such as mine or IED (improvised explosive device) detection, rescue missions after earthquakes and investigation of archeological sites. Detection of concealed objects with low metal content is known to be a challenging problem in general. Use of A-scan, B-scan and C-scan GPR data in combination provides valuable information for target recognition in such applications. In this paper, we study the problem of target detection for potentially explosive objects embedded inside a wall. GPR data is numerically simulated by using an FDTD-based numerical computation tool when dielectric targets and targets with low metal content are inserted into different types of walls. A small size plastic bottle filled with trinitrotoluene (TNT) is used as the target with and without a metal fuse in it. The targets are buried into two different types of wall; a homogeneous brick wall and an inhomogeneous wall constructed by bricks having periodically located air holes in it. Effects of using an inhomogeneous wall structure with internal boundaries are investigated as a challenging scenario, paying special attention to preprocessing.

Dimension- and space-based intertrial effects in visual pop-out search: modulation by task demands for focal-attentional processing.

PubMed

Krummenacher, Joseph; Müller, Hermann J; Zehetleitner, Michael; Geyer, Thomas

2009-03-01

Two experiments compared reaction times (RTs) in visual search for singleton feature targets defined, variably across trials, in either the color or the orientation dimension. Experiment 1 required observers to simply discern target presence versus absence (simple-detection task); Experiment 2 required them to respond to a detection-irrelevant form attribute of the target (compound-search task). Experiment 1 revealed a marked dimensional intertrial effect of 34 ms for an target defined in a changed versus a repeated dimension, and an intertrial target distance effect, with an 4-ms increase in RTs (per unit of distance) as the separation of the current relative to the preceding target increased. Conversely, in Experiment 2, the dimension change effect was markedly reduced (11 ms), while the intertrial target distance effect was markedly increased (11 ms per unit of distance). The results suggest that dimension change/repetition effects are modulated by the amount of attentional focusing required by the task, with space-based attention altering the integration of dimension-specific feature contrast signals at the level of the overall-saliency map.

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.

Aptamer-Based Paper Strip Sensor for Detecting Vibrio fischeri.

PubMed

Shin, Woo-Ri; Sekhon, Simranjeet Singh; Rhee, Sung-Keun; Ko, Jung Ho; Ahn, Ji-Young; Min, Jiho; Kim, Yang-Hoon

2018-05-14

Aptamer-based paper strip sensor for detecting Vibrio fischeri was developed. Our method was based on the aptamer sandwich assay between whole live cells, V. fischeri and DNA aptamer probes. Following 9 rounds of Cell-SELEX and one of the negative-SELEX, V. fischeri Cell Aptamer (VFCA)-02 and -03 were isolated, with the former showing approximately 10-fold greater avidity (in the subnanomolar range) for the target cells when arrayed on a surface. The colorimetric response of a paper sensor based on VFCA-02 was linear in the range of 4 × 10 1 to 4 × 10 5 CFU/mL of target cell by using scanning reader. The linear regression correlation coefficient ( R 2 ) was 0.9809. This system shows promise for use in aptamer-conjugated gold nanoparticle probes in paper strip format for in-field detection of marine bioindicating bacteria.

Real-time label-free quantitative fluorescence microscopy-based detection of ATP using a tunable fluorescent nano-aptasensor platform.

PubMed

Shrivastava, Sajal; Sohn, Il-Yung; Son, Young-Min; Lee, Won-Il; Lee, Nae-Eung

2015-12-14

Although real-time label-free fluorescent aptasensors based on nanomaterials are increasingly recognized as a useful strategy for the detection of target biomolecules with high fidelity, the lack of an imaging-based quantitative measurement platform limits their implementation with biological samples. Here we introduce an ensemble strategy for a real-time label-free fluorescent graphene (Gr) aptasensor platform. This platform employs aptamer length-dependent tunability, thus enabling the reagentless quantitative detection of biomolecules through computational processing coupled with real-time fluorescence imaging data. We demonstrate that this strategy effectively delivers dose-dependent quantitative readouts of adenosine triphosphate (ATP) concentration on chemical vapor deposited (CVD) Gr and reduced graphene oxide (rGO) surfaces, thereby providing cytotoxicity assessment. Compared with conventional fluorescence spectrometry methods, our highly efficient, universally applicable, and rational approach will facilitate broader implementation of imaging-based biosensing platforms for the quantitative evaluation of a range of target molecules.

Improved relocatable over-the-horizon radar detection and tracking using the maximum likelihood adaptive neural system algorithm

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.; Webb, Virgil H.; Bradley, Scott R.; Hansen, Christopher A.

1998-07-01

An advanced detection and tracking system is being developed for the U.S. Navy's Relocatable Over-the-Horizon Radar (ROTHR) to provide improved tracking performance against small aircraft typically used in drug-smuggling activities. The development is based on the Maximum Likelihood Adaptive Neural System (MLANS), a model-based neural network that combines advantages of neural network and model-based algorithmic approaches. The objective of the MLANS tracker development effort is to address user requirements for increased detection and tracking capability in clutter and improved track position, heading, and speed accuracy. The MLANS tracker is expected to outperform other approaches to detection and tracking for the following reasons. It incorporates adaptive internal models of target return signals, target tracks and maneuvers, and clutter signals, which leads to concurrent clutter suppression, detection, and tracking (track-before-detect). It is not combinatorial and thus does not require any thresholding or peak picking and can track in low signal-to-noise conditions. It incorporates superresolution spectrum estimation techniques exceeding the performance of conventional maximum likelihood and maximum entropy methods. The unique spectrum estimation method is based on the Einsteinian interpretation of the ROTHR received energy spectrum as a probability density of signal frequency. The MLANS neural architecture and learning mechanism are founded on spectrum models and maximization of the "Einsteinian" likelihood, allowing knowledge of the physical behavior of both targets and clutter to be injected into the tracker algorithms. The paper describes the addressed requirements and expected improvements, theoretical foundations, engineering methodology, and results of the development effort to date.

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.

Colorimetric Detection of Small Molecules in Complex Matrixes via Target-Mediated Growth of Aptamer-Functionalized Gold Nanoparticles.

PubMed

Soh, Jun Hui; Lin, Yiyang; Rana, Subinoy; Ying, Jackie Y; Stevens, Molly M

2015-08-04

A versatile and sensitive colorimetric assay that allows the rapid detection of small-molecule targets using the naked eye is demonstrated. The working principle of the assay integrates aptamer-target recognition and the aptamer-controlled growth of gold nanoparticles (Au NPs). Aptamer-target interactions modulate the amount of aptamer strands adsorbed on the surface of aptamer-functionalized Au NPs via desorption of the aptamer strands when target molecules bind with the aptamer. Depending on the resulting aptamer coverage, Au NPs grow into morphologically varied nanostructures, which give rise to different colored solutions. Au NPs with low aptamer coverage grow into spherical NPs, which produce red-colored solutions, whereas Au NPs with high aptamer coverage grow into branched NPs, which produce blue-colored solutions. We achieved visible colorimetric response and nanomolar detection limits for the detection of ochratoxin A (1 nM) in red wine samples, as well as cocaine (1 nM) and 17β-estradiol (0.2 nM) in spiked synthetic urine and saliva, respectively. The detection limits were well within clinically and physiologically relevant ranges, and below the maximum food safety limits. The assay is highly sensitive, specific, and able to detect an array of analytes rapidly without requiring sophisticated equipment, making it relevant for many applications, such as high-throughput drug and clinical screening, food sampling, and diagnostics. Furthermore, the assay is easily adapted as a chip-based platform for rapid and portable target detection.

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.

Lateral Flow Assay Based on Paper-Hydrogel Hybrid Material for Sensitive Point-of-Care Detection of Dengue Virus.

PubMed

Choi, Jane Ru; Yong, Kar Wey; Tang, Ruihua; Gong, Yan; Wen, Ting; Yang, Hui; Li, Ang; Chia, Yook Chin; Pingguan-Murphy, Belinda; Xu, Feng

2017-01-01

Paper-based devices have been broadly used for the point-of-care detection of dengue viral nucleic acids due to their simplicity, cost-effectiveness, and readily observable colorimetric readout. However, their moderate sensitivity and functionality have limited their applications. Despite the above-mentioned advantages, paper substrates are lacking in their ability to control fluid flow, in contrast to the flow control enabled by polymer substrates (e.g., agarose) with readily tunable pore size and porosity. Herein, taking the benefits from both materials, the authors propose a strategy to create a hybrid substrate by incorporating agarose into the test strip to achieve flow control for optimal biomolecule interactions. As compared to the unmodified test strip, this strategy allows sensitive detection of targets with an approximately tenfold signal improvement. Additionally, the authors showcase the potential of functionality improvement by creating multiple test zones for semi-quantification of targets, suggesting that the number of visible test zones is directly proportional to the target concentration. The authors further demonstrate the potential of their proposed strategy for clinical assessment by applying it to their prototype sample-to-result test strip to sensitively and semi-quantitatively detect dengue viral RNA from the clinical blood samples. This proposed strategy holds significant promise for detecting various targets for diverse future applications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Palindromic Molecule Beacon-Based Cascade Amplification for Colorimetric Detection of Cancer Genes.

PubMed

Shen, Zhi-Fa; Li, Feng; Jiang, Yi-Fan; Chen, Chang; Xu, Huo; Li, Cong-Cong; Yang, Zhe; Wu, Zai-Sheng

2018-03-06

A highly sensitive and selective colorimetric assay based on a multifunctional molecular beacon with palindromic tail (PMB) was proposed for the detection of target p53 gene. The PMB probe can serve as recognition element, primer, and polymerization template and contains a nicking site and a C-rich region complementary to a DNAzyme. In the presence of target DNA, the hairpin of PMB is opened, and the released palindromic tails intermolecularly hybridize with each other, triggering the autonomous polymerization/nicking/displacement cycles. Although only one type of probe is involved, the system can execute triple and continuous polymerization strand displacement amplifications, generating large amounts of G-quadruplex fragments. These G-rich fragments can bind to hemin and form the DNAzymes that possess the catalytic activity similar to horseradish peroxidase, catalyzing the oxidation of ABTS by H 2 O 2 and producing the colorimetric signal. Utilizing the newly proposed sensing system, target DNA can be detected down to 10 pM with a linear response range from 10 pM to 200 nM, and mutant target DNAs are able to be distinguished even by the naked eye. The desirable detection sensitivity, high specificity, and operation convenience without any separation step and chemical modification demonstrate that the palindromic molecular beacon holds the potential for detecting and monitoring a variety of nucleic acid-related biomarkers.

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.

Using more different and more familiar targets improves the detection of concealed information.

PubMed

Suchotzki, Kristina; De Houwer, Jan; Kleinberg, Bennett; Verschuere, Bruno

2018-04-01

When embedded among a number of plausible irrelevant options, the presentation of critical (e.g., crime-related or autobiographical) information is associated with a marked increase in response time (RT). This RT effect crucially depends on the inclusion of a target/non-target discrimination task with targets being a dedicated set of items that require a unique response (press YES; for all other items press NO). Targets may be essential because they share a feature - familiarity - with the critical items. Whereas irrelevant items have not been encountered before, critical items are known from the event or the facts of the investigation. Target items are usually learned before the test, and thereby made familiar to the participants. Hence, familiarity-based responding needs to be inhibited on the critical items and may therefore explain the RT increase on the critical items. This leads to the hypothesis that the more participants rely on familiarity, the more pronounced the RT increase on critical items may be. We explored two ways to increase familiarity-based responding: (1) Increasing the number of different target items, and (2) using familiar targets. In two web-based studies (n = 357 and n = 499), both the number of different targets and the use of familiar targets facilitated concealed information detection. The effect of the number of different targets was small yet consistent across both studies, the effect of target familiarity was large in both studies. Our results support the role of familiarity-based responding in the Concealed Information Test and point to ways on how to improve validity of the Concealed Information Test. Copyright © 2018 Elsevier B.V. All rights reserved.

Carbon-based nanocomposites with aptamer-templated silver nanoclusters for the highly sensitive and selective detection of platelet-derived growth factor.

PubMed

Zhang, Zhihong; Guo, Chuanpan; Zhang, Shuai; He, Linghao; Wang, Minghua; Peng, Donglai; Tian, Junfeng; Fang, Shaoming

2017-03-15

We synthesized two kinds of carbon-based nanocomposites of silver nanoclusters (AgNCs). An aptamer for targeted platelet-derived growth factor-BB (PDGF-BB) detection was used as the organic phase to produce AgNCs@Apt, three dimensional reduced graphene oxide@AgNCs@Aptamer (3D-rGO@AgNCs@Apt), and graphene quantum dots@AgNCs@Aptamer (GQD@AgNCs@Apt) nanocomposites. The formation mechanism of the developed nanocomposites was described by detailed characterizations of their chemical and crystal structures. Subsequently, the as-synthesized nanoclusters containing aptamer strands were applied as the sensitive layers to fabricate a novel electrochemical aptasensor for the detection of PDGF-BB, which may be directly used to determine the target protein. Electrochemical impedance spectra showed that the developed 3D-rGO@AgNCs@Apt-based biosensor exhibited the highest sensitivity for PDGF-BB detection among three kinds of fabricated aptasensors, with an extremely low detection limit of 0.82pgmL -1 . In addition, the 3D-rGO@AgNCs@Apt-based biosensor showed high selectivity, stability, and applicability for the detection of PDGF-BB. This finding indicated that the AgNC-based nanocomposites prepared by a one-step method could be used as an electrochemical biosensor for various detection procedures in the biomedical field. Copyright © 2016 Elsevier B.V. All rights reserved.

Enhanced Detection of Bacteria in Environmental Waters: an RNA-based Approach

EPA Science Inventory

Molecular assays (i.e., PCR and qPCR) used in microbial water quality studies often target ribosomal RNA genes (rDNA). However, using DNA as the PCR template does not discriminate between active and dead cells. The use of RNA-based detection methods has recently been proposed as ...

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...

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.

Clarifying the role of target similarity, task relevance and feature-based suppression during sustained inattentional blindness.

PubMed

Drew, Trafton; Stothart, Cary

2016-12-01

How is feature-based attention distributed when engaged in a challenging attentional task? Thanks to formative electrophysiological and psychophysical work, we know a great deal about the spatial distribution of attention, but much less is known about how feature-based attention is allocated. In a large-scale online study, we investigated the distribution of attention to color space using a sustained inattentional blindness task. In order to query what parts of color space were being attended or inhibited, we varied the color of an unexpected stimulus on the final trial. Noticing rates for this stimulus indicate that when engaged in a difficult task that involves tracking items of one color and ignoring items of two different colors, observers attend the target color and inhibit the to-be ignored colors. Further, similarity to the target drives detection such that colors more similar to the target are more likely to be detected. Finally, our data suggest that when possible, observers inhibit regions of color space rather than individuating specific colors and adjusting the level of inhibition for a particular color accordingly. Together, our data support the notion of feature-based suppression for task relevant (to-be ignored) information, but we found no evidence of an inhibitory surround based on target color similarity.

Sensor Systems for Biological Agent Attacks: Protecting Buildings and Military Bases

DTIC Science & Technology

2004-01-01

simple aerosol detectors, to those that identify an agent based on its genetic, structural, or chemical properties , to so- called "functional...Cytometry, 122 Target Binding That Changes Detectable Properties of Smart Sensor Surfaces, 124 Colorimetric Detection, 124 Fluorescence Detection, 125 One...microscopy. In addition to particles directly derived from living organisms, other particles in air may also share properties with the bioaerosols

Detection and Delineation of Oral Cancer With a PARP1-Targeted Optical Imaging Agent.

PubMed

Kossatz, Susanne; Weber, Wolfgang; Reiner, Thomas

2017-01-01

More sensitive and specific methods for early detection are imperative to improve survival rates in oral cancer. However, oral cancer detection is still largely based on visual examination and histopathology of biopsy material, offering no molecular selectivity or spatial resolution. Intuitively, the addition of optical contrast could improve oral cancer detection and delineation, but so far no molecularly targeted approach has been translated. Our fluorescently labeled small-molecule inhibitor PARPi-FL binds to the DNA repair enzyme poly(ADP-ribose)polymerase 1 (PARP1) and is a potential diagnostic aid for oral cancer delineation. Based on our preclinical work, a clinical phase I/II trial opened in March 2017 to evaluate PARPi-FL as a contrast agent for oral cancer imaging. In this commentary, we discuss why we chose PARP1 as a biomarker for tumor detection and which particular characteristics make PARPi-FL an excellent candidate to image PARP1 in optically guided applications. We also comment on the potential benefits of our molecularly targeted PARPi-FL-guided imaging approach in comparison to existing oral cancer screening adjuncts and mention the adaptability of PARPi-FL imaging to other environments and tumor types.

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

Fluorescent quenching-based quantitative detection of specific DNA/RNA using a BODIPY® FL-labeled probe or primer

PubMed Central

Kurata, Shinya; Kanagawa, Takahiro; Yamada, Kazutaka; Torimura, Masaki; Yokomaku, Toyokazu; Kamagata, Yoichi; Kurane, Ryuichiro

2001-01-01

We have developed a simple method for the quantitative detection of specific DNA or RNA molecules based on the finding that BODIPY® FL fluorescence was quenched by its interaction with a uniquely positioned guanine. This approach makes use of an oligonucleotide probe or primer containing a BODIPY® FL-modified cytosine at its 5′-end. When such a probe was hybridized with a target DNA, its fluorescence was quenched by the guanine in the target, complementary to the modified cytosine, and the quench rate was proportional to the amount of target DNA. This widely applicable technique will be used directly with larger samples or in conjunction with the polymerase chain reaction to quantify small DNA samples. PMID:11239011

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.

Fluorescent carbon nanoparticle-based lateral flow biosensor for ultrasensitive detection of DNA.

PubMed

Takalkar, Sunitha; Baryeh, Kwaku; Liu, Guodong

2017-12-15

We report a fluorescent carbon nanoparticle (FCN)-based lateral flow biosensor for ultrasensitive detection of DNA. Fluorescent carbon nanoparticle with a diameter of around 15nm was used as a tag to label a detection DNA probe, which was complementary with the part of target DNA. A capture DNA probe was immobilized on the test zone of the lateral flow biosensor. Sandwich-type hybridization reactions among the FCN-labeled DNA probe, target DNA and capture DNA probe were performed on the lateral flow biosensor. In the presence of target DNA, FCNs were captured on the test zone of the biosensor and the fluorescent intensity of the captured FCNs was measured with a portable fluorescent reader. After systematic optimizations of experimental parameters (the components of running buffers, the concentration of detection DNA probe used in the preparation of FCN-DNA conjugates, the amount of FCN-DNA dispensed on the conjugate pad and the dispensing cycles of the capture DNA probes on the test-zone), the biosensor could detect a minimum concentration of 0.4 fM DNA. This study provides a rapid and low-cost approach for DNA detection with high sensitivity, showing great promise for clinical application and biomedical diagnosis. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Object detection from images obtained through underwater turbulence medium

NASA Astrophysics Data System (ADS)

Furhad, Md. Hasan; Tahtali, Murat; Lambert, Andrew

2017-09-01

Imaging through underwater experiences severe distortions due to random fluctuations of temperature and salinity in water, which produces underwater turbulence through diffraction limited blur. Lights reflecting from objects perturb and attenuate contrast, making the recognition of objects of interest difficult. Thus, the information available for detecting underwater objects of interest becomes a challenging task as they have inherent confusion among the background, foreground and other image properties. In this paper, a saliency-based approach is proposed to detect the objects acquired through an underwater turbulent medium. This approach has drawn attention among a wide range of computer vision applications, such as image retrieval, artificial intelligence, neuro-imaging and object detection. The image is first processed through a deblurring filter. Next, a saliency technique is used on the image for object detection. In this step, a saliency map that highlights the target regions is generated and then a graph-based model is proposed to extract these target regions for object detection.

DNA detection on ultrahigh-density optical fiber-based nanoarrays.

PubMed

Tam, Jenny M; Song, Linan; Walt, David R

2009-04-15

Nanoarrays for DNA detection were fabricated on etched nanofiber bundles based on recently developed techniques for microscale arrays. Two different-sized nanoarrays were created: one with 700 nm feature sizes and a 1 microm center-to-center pitch (approximately 1x10(6) array elements/mm(2)) and one with 300 nm feature sizes and a 500 nm center-to-center pitch (4.6x10(6) array elements/mm(2)). A random, multiplexed array composed of oligonucleotide-functionalized nanospheres was constructed and used for parallel detection and analysis of fluorescently labeled DNA targets. We have used these arrays to detect a variety of target sequences including Bacillus thuringiensis kurstaki and vaccina virus sequences, two potential biowarfare agents, as well as interleukin-2 sequences, an immune system modulator that has been used for the diagnosis of HIV.

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.

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.

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.

Biosensing of BCR/ABL fusion gene using an intensity-interrogation surface plasmon resonance imaging system

NASA Astrophysics Data System (ADS)

Wu, Jiangling; Huang, Yu; Bian, Xintong; Li, DanDan; Cheng, Quan; Ding, Shijia

2016-10-01

In this work, a custom-made intensity-interrogation surface plasmon resonance imaging (SPRi) system has been developed to directly detect a specific sequence of BCR/ABL fusion gene in chronic myelogenous leukemia (CML). The variation in the reflected light intensity detected from the sensor chip composed of gold islands array is proportional to the change of refractive index due to the selective hybridization of surface-bound DNA probes with target ssDNA. SPRi measurements were performed with different concentrations of synthetic target DNA sequence. The calibration curve of synthetic target sequence shows a good relationship between the concentration of synthetic target and the change of reflected light intensity. The detection limit of this SPRi measurement could approach 10.29 nM. By comparing SPRi images, the target ssDNA and non-complementary DNA sequence are able to be distinguished. This SPRi system has been applied for assay of BCR/ABL fusion gene extracted from real samples. This nucleic acid-based SPRi biosensor therefore offers an alternative high-effective, high-throughput label-free tool for DNA detection in biomedical research and molecular diagnosis.

Feature-aided multiple target tracking in the image plane

NASA Astrophysics Data System (ADS)

Brown, Andrew P.; Sullivan, Kevin J.; Miller, David J.

2006-05-01

Vast quantities of EO and IR data are collected on airborne platforms (manned and unmanned) and terrestrial platforms (including fixed installations, e.g., at street intersections), and can be exploited to aid in the global war on terrorism. However, intelligent preprocessing is required to enable operator efficiency and to provide commanders with actionable target information. To this end, we have developed an image plane tracker which automatically detects and tracks multiple targets in image sequences using both motion and feature information. The effects of platform and camera motion are compensated via image registration, and a novel change detection algorithm is applied for accurate moving target detection. The contiguous pixel blob on each moving target is segmented for use in target feature extraction and model learning. Feature-based target location measurements are used for tracking through move-stop-move maneuvers, close target spacing, and occlusion. Effective clutter suppression is achieved using joint probabilistic data association (JPDA), and confirmed target tracks are indicated for further processing or operator review. In this paper we describe the algorithms implemented in the image plane tracker and present performance results obtained with video clips from the DARPA VIVID program data collection and from a miniature unmanned aerial vehicle (UAV) flight.

Enhanced photoelectrochemical DNA sensor based on TiO2/Au hybrid structure.

PubMed

Liu, Xing-Pei; Chen, Jing-Shuai; Mao, Chang-Jie; Niu, He-Lin; Song, Ji-Ming; Jin, Bao-Kang

2018-05-23

A novel enhanced photoelectrochemical DNA sensor, based on a TiO 2 /Au hybrid electrode structure, was developed to detect target DNA. The sensor was developed by successively modifying fluorine-tin oxide (FTO) electrodes with TiO 2 nanoparticles, gold (Au) nanoparticles, hairpin DNA (DNA1), and CdSe-COOH quantum dots (QDs), which acted as signal amplification factors. In the absence of target DNA, the incubated DNA1 hairpin and the CdSe-COOH QDs were in close contact with the TiO 2 /Au electrode surface, leading to an enhanced photocurrent intensity due to the sensitization effect. After incubation of the modified electrode with the target DNA, the hairpin DNA changed into a double helix structure, and the CdSe QDs moved away from the TiO 2 /Au electrode surface, leading to a decreased sensitization effect and photoelectrochemical signal intensity. This novel DNA sensor exhibited stable, sensitive and reproducible detection of DNA from 0.1 μM to 10 fM, with a lower detection limit of 3 fM. It provided good specificity, reproducibility, stability and is a promising strategy for the detection of a variety of other DNA targets, for early clinical diagnosis of various diseases. Copyright © 2018 Elsevier B.V. All rights reserved.

Highly-sensitive microRNA detection based on bio-bar-code assay and catalytic hairpin assembly two-stage amplification.

PubMed

Tang, Songsong; Gu, Yuan; Lu, Huiting; Dong, Haifeng; Zhang, Kai; Dai, Wenhao; Meng, Xiangdan; Yang, Fan; Zhang, Xueji

2018-04-03

Herein, a highly-sensitive microRNA (miRNA) detection strategy was developed by combining bio-bar-code assay (BBA) with catalytic hairpin assembly (CHA). In the proposed system, two nanoprobes of magnetic nanoparticles functionalized with DNA probes (MNPs-DNA) and gold nanoparticles with numerous barcode DNA (AuNPs-DNA) were designed. In the presence of target miRNA, the MNP-DNA and AuNP-DNA hybridized with target miRNA to form a "sandwich" structure. After "sandwich" structures were separated from the solution by the magnetic field and dehybridized by high temperature, the barcode DNA sequences were released by dissolving AuNPs. The released barcode DNA sequences triggered the toehold strand displacement assembly of two hairpin probes, leading to recycle of barcode DNA sequences and producing numerous fluorescent CHA products for miRNA detection. Under the optimal experimental conditions, the proposed two-stage amplification system could sensitively detect target miRNA ranging from 10 pM to 10 aM with a limit of detection (LOD) down to 97.9 zM. It displayed good capability to discriminate single base and three bases mismatch due to the unique sandwich structure. Notably, it presented good feasibility for selective multiplexed detection of various combinations of synthetic miRNA sequences and miRNAs extracted from different cell lysates, which were in agreement with the traditional polymerase chain reaction analysis. The two-stage amplification strategy may be significant implication in the biological detection and clinical diagnosis. Copyright © 2017 Elsevier B.V. All rights reserved.

Assay Portal | Office of Cancer Clinical Proteomics Research

Cancer.gov

The CPTAC Assay Portal serves as a centralized public repository of "fit-for-purpose," multiplexed quantitative mass spectrometry-based proteomic targeted assays. Targeted proteomic assays eliminate issues that are commonly observed using conventional protein detection systems.

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.

The Novel Immunobiosensors for Detection of Escherichia coli O157:H7 Using Electrochemical Impedance Spectroscopy.

PubMed

Zhang, Deng; Chen, Songyue; Qin, Lifeng; Li, Rong; Wang, Ping; Li, Yanbin

2005-01-01

Immunobiosensors were developed for detection of Escherichia coli O157:H7 based on the surface immobilization of monoclone antibodies onto indium tin oxide (ITO) electrodes. The immobilization of antibodies onto ITO chips was carried out by silanization. The effects of epoxysilane monolayer, the antibody layer on the electrochemical properties of the electrode, and the combined target bacteria were analyzed through cyclic voltammetry and electrochemical impedance spectroscopy. By using Randles model as the equivalent circuit, the concentration of the target bacteria can be quantitatively analyzed in terms of the change of electron transfer resistance. The biosensor could detect the target bacteria with a detection limit of 4×10³CFU/mL. A linear response was found between 4×10³- 4×10⁶CFU/mL. This biosensor was characterized with high sensitivity, excellent selectivity, short detection time and easy operation It has a promising application in clinical laboratory diagnoses, environmental detection and food safety.

Discriminating Famous from Fictional Names Based on Lifetime Experience: Evidence in Support of a Signal-Detection Model Based on Finite Mixture Distributions

ERIC Educational Resources Information Center

Bowles, Ben; Harlow, Iain M.; Meeking, Melissa M.; Kohler, Stefan

2012-01-01

It is widely accepted that signal-detection mechanisms contribute to item-recognition memory decisions that involve discriminations between targets and lures based on a controlled laboratory study episode. Here, the authors employed mathematical modeling of receiver operating characteristics (ROC) to determine whether and how a signal-detection…

Real-time, multiplexed electrochemical DNA detection using an active complementary metal-oxide-semiconductor biosensor array with integrated sensor electronics.

PubMed

Levine, Peter M; Gong, Ping; Levicky, Rastislav; Shepard, Kenneth L

2009-03-15

Optical biosensing based on fluorescence detection has arguably become the standard technique for quantifying extents of hybridization between surface-immobilized probes and fluorophore-labeled analyte targets in DNA microarrays. However, electrochemical detection techniques are emerging which could eliminate the need for physically bulky optical instrumentation, enabling the design of portable devices for point-of-care applications. Unlike fluorescence detection, which can function well using a passive substrate (one without integrated electronics), multiplexed electrochemical detection requires an electronically active substrate to analyze each array site and benefits from the addition of integrated electronic instrumentation to further reduce platform size and eliminate the electromagnetic interference that can result from bringing non-amplified signals off chip. We report on an active electrochemical biosensor array, constructed with a standard complementary metal-oxide-semiconductor (CMOS) technology, to perform quantitative DNA hybridization detection on chip using targets conjugated with ferrocene redox labels. A 4 x 4 array of gold working electrodes and integrated potentiostat electronics, consisting of control amplifiers and current-input analog-to-digital converters, on a custom-designed 5 mm x 3 mm CMOS chip drive redox reactions using cyclic voltammetry, sense DNA binding, and transmit digital data off chip for analysis. We demonstrate multiplexed and specific detection of DNA targets as well as real-time monitoring of hybridization, a task that is difficult, if not impossible, with traditional fluorescence-based microarrays.

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.

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.

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

PubMed

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

2018-07-15

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

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

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.

Comparative genome analysis identifies novel nucleic acid diagnostic targets for use in the specific detection of Haemophilus influenzae.

PubMed

Coughlan, Helena; Reddington, Kate; Tuite, Nina; Boo, Teck Wee; Cormican, Martin; Barrett, Louise; Smith, Terry J; Clancy, Eoin; Barry, Thomas

2015-10-01

Haemophilus influenzae is recognised as an important human pathogen associated with invasive infections, including bloodstream infection and meningitis. Currently used molecular-based diagnostic assays lack specificity in correctly detecting and identifying H. influenzae. As such, there is a need to develop novel diagnostic assays for the specific identification of H. influenzae. Whole genome comparative analysis was performed to identify putative diagnostic targets, which are unique in nucleotide sequence to H. influenzae. From this analysis, we identified 2H. influenzae putative diagnostic targets, phoB and pstA, for use in real-time PCR diagnostic assays. Real-time PCR diagnostic assays using these targets were designed and optimised to specifically detect and identify all 55H. influenzae strains tested. These novel rapid assays can be applied to the specific detection and identification of H. influenzae for use in epidemiological studies and could also enable improved monitoring of invasive disease caused by these bacteria. Copyright © 2015 Elsevier Inc. All rights reserved.

Microbial identification by immunohybridization assay of artificial RNA labels

NASA Technical Reports Server (NTRS)

Kourentzi, Katerina D.; Fox, George E.; Willson, Richard C.

2002-01-01

Ribosomal RNA (rRNA) and engineered stable artificial RNAs (aRNAs) are frequently used to monitor bacteria in complex ecosystems. In this work, we describe a solid-phase immunocapture hybridization assay that can be used with low molecular weight RNA targets. A biotinylated DNA probe is efficiently hybridized in solution with the target RNA, and the DNA-RNA hybrids are captured on streptavidin-coated plates and quantified using a DNA-RNA heteroduplex-specific antibody conjugated to alkaline phosphatase. The assay was shown to be specific for both 5S rRNA and low molecular weight (LMW) artificial RNAs and highly sensitive, allowing detection of as little as 5.2 ng (0.15 pmol) in the case of 5S rRNA. Target RNAs were readily detected even in the presence of excess nontarget RNA. Detection using DNA probes as small as 17 bases targeting a repetitive artificial RNA sequence in an engineered RNA was more efficient than the detection of a unique sequence.

Carbon nanosphere-based fluorescence aptasensor for targeted detection of breast cancer cell MCF-7.

PubMed

Yang, Dandan; Liu, Mei; Xu, Jing; Yang, Chao; Wang, Xiaoxiao; Lou, Yongbing; He, Nongyue; Wang, Zhifei

2018-08-01

In this work, carbon nanosphere (CNS)-based fluorescence "turn off/on" aptasensor was developed for targeted detection of breast cancer cell MCF-7 by conjugation with FAM (a dye)-labeled mucin1 (MUC1) aptamer P0 (P0-FAM), which can recognize MUC1 protein overexpressed on the surface of MCF-7. Different from other carbon based fluorescence quenching materials, CNSs prepared by the carbonization of glucose not only have the high fluorescence quenching efficiency (98.8%), but also possess negligible cytotoxicity (in the concentration range of 0-1 mg/mL, which is 10 times higher than that of traditional carbon nanotubes or graphene oxide (0-100 µg/mL)). As for the detection of the mimic of the tumor antigen MUC1, the resulting fluorescence intensity increases nearly linearly in the range of 0-6 μM with the limit of detection (LOD) of 25 nM. Copyright © 2018 Elsevier B.V. All rights reserved.

The Efficacy of Multiparametric Magnetic Resonance Imaging and Magnetic Resonance Imaging Targeted Biopsy in Risk Classification for Patients with Prostate Cancer on Active Surveillance.

PubMed

Recabal, Pedro; Assel, Melissa; Sjoberg, Daniel D; Lee, Daniel; Laudone, Vincent P; Touijer, Karim; Eastham, James A; Vargas, Hebert A; Coleman, Jonathan; Ehdaie, Behfar

2016-08-01

We determined whether multiparametric magnetic resonance imaging targeted biopsies may replace systematic biopsies to detect higher grade prostate cancer (Gleason score 7 or greater) and whether biopsy may be avoided based on multiparametric magnetic resonance imaging among men with Gleason 3+3 prostate cancer on active surveillance. We identified men with previously diagnosed Gleason score 3+3 prostate cancer on active surveillance who underwent multiparametric magnetic resonance imaging and a followup prostate biopsy. Suspicion for higher grade cancer was scored on a standardized 5-point scale. All patients underwent a systematic biopsy. Patients with multiparametric magnetic resonance imaging regions of interest also underwent magnetic resonance imaging targeted biopsy. The detection rate of higher grade cancer was estimated for different multiparametric magnetic resonance imaging scores with the 3 biopsy strategies of systematic, magnetic resonance imaging targeted and combined. Of 206 consecutive men on active surveillance 135 (66%) had a multiparametric magnetic resonance imaging region of interest. Overall, higher grade cancer was detected in 72 (35%) men. A higher multiparametric magnetic resonance imaging score was associated with an increased probability of detecting higher grade cancer (Wilcoxon-type trend test p <0.0001). Magnetic resonance imaging targeted biopsy detected higher grade cancer in 23% of men. Magnetic resonance imaging targeted biopsy alone missed higher grade cancers in 17%, 12% and 10% of patients with multiparametric magnetic resonance imaging scores of 3, 4 and 5, respectively. Magnetic resonance imaging targeted biopsies increased the detection of higher grade cancer among men on active surveillance compared to systematic biopsy alone. However, a clinically relevant proportion of higher grade cancer was detected using only systematic biopsy. Despite the improved detection of disease progression using magnetic resonance imaging targeted biopsy, systematic biopsy cannot be excluded as part of surveillance for men with low risk prostate cancer. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

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 rational development of molecularly imprinted polymer-based sensors for protein detection.

PubMed

Whitcombe, Michael J; Chianella, Iva; Larcombe, Lee; Piletsky, Sergey A; Noble, James; Porter, Robert; Horgan, Adrian

2011-03-01

The detection of specific proteins as biomarkers of disease, health status, environmental monitoring, food quality, control of fermenters and civil defence purposes means that biosensors for these targets will become increasingly more important. Among the technologies used for building specific recognition properties, molecularly imprinted polymers (MIPs) are attracting much attention. In this critical review we describe many methods used for imprinting recognition for protein targets in polymers and their incorporation with a number of transducer platforms with the aim of identifying the most promising approaches for the preparation of MIP-based protein sensors (277 references).

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.

FRET-based quantum dot immunoassay for rapid and sensitive detection of Aspergillus amstelodami.

PubMed

Kattke, Michele D; Gao, Elizabeth J; Sapsford, Kim E; Stephenson, Larry D; Kumar, Ashok

2011-01-01

In this study, a fluorescence resonance energy transfer (FRET)-based quantum dot (QD) immunoassay for detection and identification of Aspergillus amstelodami was developed. Biosensors were formed by conjugating QDs to IgG antibodies and incubating with quencher-labeled analytes; QD energy was transferred to the quencher species through FRET, resulting in diminished fluorescence from the QD donor. During a detection event, quencher-labeled analytes are displaced by higher affinity target analytes, creating a detectable fluorescence signal increase from the QD donor. Conjugation and the resulting antibody:QD ratios were characterized with UV-Vis spectroscopy and QuantiT protein assay. The sensitivity of initial fluorescence experiments was compromised by inherent autofluorescence of mold spores, which produced low signal-to-noise and inconsistent readings. Therefore, excitation wavelength, QD, and quencher were adjusted to provide optimal signal-to-noise over spore background. Affinities of anti-Aspergillus antibody for different mold species were estimated with sandwich immunoassays, which identified A. fumigatus and A. amstelodami for use as quencher-labeled- and target-analytes, respectively. The optimized displacement immunoassay detected A. amstelodami concentrations as low as 10(3) spores/mL in five minutes or less. Additionally, baseline fluorescence was produced in the presence of 10(5) CFU/mL heat-killed E. coli O157:H7, demonstrating high specificity. This sensing modality may be useful for identification and detection of other biological threat agents, pending identification of suitable antibodies. Overall, these FRET-based QD-antibody biosensors represent a significant advancement in detection capabilities, offering sensitive and reliable detection of targets with applications in areas from biological terrorism defense to clinical analysis.

FRET-Based Quantum Dot Immunoassay for Rapid and Sensitive Detection of Aspergillus amstelodami

PubMed Central

Kattke, Michele D.; Gao, Elizabeth J.; Sapsford, Kim E.; Stephenson, Larry D.; Kumar, Ashok

2011-01-01

In this study, a fluorescence resonance energy transfer (FRET)-based quantum dot (QD) immunoassay for detection and identification of Aspergillus amstelodami was developed. Biosensors were formed by conjugating QDs to IgG antibodies and incubating with quencher-labeled analytes; QD energy was transferred to the quencher species through FRET, resulting in diminished fluorescence from the QD donor. During a detection event, quencher-labeled analytes are displaced by higher affinity target analytes, creating a detectable fluorescence signal increase from the QD donor. Conjugation and the resulting antibody:QD ratios were characterized with UV-Vis spectroscopy and QuantiT protein assay. The sensitivity of initial fluorescence experiments was compromised by inherent autofluorescence of mold spores, which produced low signal-to-noise and inconsistent readings. Therefore, excitation wavelength, QD, and quencher were adjusted to provide optimal signal-to-noise over spore background. Affinities of anti-Aspergillus antibody for different mold species were estimated with sandwich immunoassays, which identified A. fumigatus and A. amstelodami for use as quencher-labeled- and target-analytes, respectively. The optimized displacement immunoassay detected A. amstelodami concentrations as low as 103 spores/mL in five minutes or less. Additionally, baseline fluorescence was produced in the presence of 105 CFU/mL heat-killed E. coli O157:H7, demonstrating high specificity. This sensing modality may be useful for identification and detection of other biological threat agents, pending identification of suitable antibodies. Overall, these FRET-based QD-antibody biosensors represent a significant advancement in detection capabilities, offering sensitive and reliable detection of targets with applications in areas from biological terrorism defense to clinical analysis. PMID:22163961

Mechanism-based Proteomic Screening Identifies Targets of Thioredoxin-like Proteins*

PubMed Central

Nakao, Lia S.; Everley, Robert A.; Marino, Stefano M.; Lo, Sze M.; de Souza, Luiz E.; Gygi, Steven P.; Gladyshev, Vadim N.

2015-01-01

Thioredoxin (Trx)-fold proteins are protagonists of numerous cellular pathways that are subject to thiol-based redox control. The best characterized regulator of thiols in proteins is Trx1 itself, which together with thioredoxin reductase 1 (TR1) and peroxiredoxins (Prxs) comprises a key redox regulatory system in mammalian cells. However, there are numerous other Trx-like proteins, whose functions and redox interactors are unknown. It is also unclear if the principles of Trx1-based redox control apply to these proteins. Here, we employed a proteomic strategy to four Trx-like proteins containing CXXC motifs, namely Trx1, Rdx12, Trx-like protein 1 (Txnl1) and nucleoredoxin 1 (Nrx1), whose cellular targets were trapped in vivo using mutant Trx-like proteins, under conditions of low endogenous expression of these proteins. Prxs were detected as key redox targets of Trx1, but this approach also supported the detection of TR1, which is the Trx1 reductant, as well as mitochondrial intermembrane proteins AIF and Mia40. In addition, glutathione peroxidase 4 was found to be a Rdx12 redox target. In contrast, no redox targets of Txnl1 and Nrx1 could be detected, suggesting that their CXXC motifs do not engage in mixed disulfides with cellular proteins. For some Trx-like proteins, the method allowed distinguishing redox and non-redox interactions. Parallel, comparative analyses of multiple thiol oxidoreductases revealed differences in the functions of their CXXC motifs, providing important insights into thiol-based redox control of cellular processes. PMID:25561728

Oligonucleotide-based biosensors for in vitro diagnostics and environmental hazard detection.

PubMed

Jung, Il Young; Lee, Eun Hee; Suh, Ah Young; Lee, Seung Jin; Lee, Hyukjin

2016-04-01

Oligonucleotide-based biosensors have drawn much attention because of their broad applications in in vitro diagnostics and environmental hazard detection. They are particularly of interest to many researchers because of their high specificity as well as excellent sensitivity. Recently, oligonucleotide-based biosensors have been used to achieve not only genetic detection of targets but also the detection of small molecules, peptides, and proteins. This has further broadened the applications of these sensors in the medical and health care industry. In this review, we highlight various examples of oligonucleotide-based biosensors for the detection of diseases, drugs, and environmentally hazardous chemicals. Each example is provided with detailed schematics of the detection mechanism in addition to the supporting experimental results. Furthermore, future perspectives and new challenges in oligonucleotide-based biosensors are discussed.

Photoacoustic microcantilevers

DOEpatents

Thundat, Thomas G [Knoxville, TN; Van Neste, Charles W [Kingston, TN; Brown, Gilbert M [Knoxville, TN; Senesac, Lawrence R [Knoxville, TN

2012-06-05

A system generates a photoacoustic spectrum in an open or closed environment with reduced noise. A source focuses a beam on a target substance disposed on a base. The base supports a cantilever that measures acoustic waves generated as light is absorbed by the target substance. By focusing a chopped/pulsed light beam on the target substance, a range of optical absorbance may be measured as the wavelength of light changes. An identifying spectrum of the target may detected by monitoring the vibration intensity variation of the cantilever as a function of illuminating wavelength or color.

Plasmon-Based Colorimetric Nanosensors for Ultrasensitive Molecular Diagnostics.

PubMed

Tang, Longhua; Li, Jinghong

2017-07-28

Colorimetric detection of target analytes with high specificity and sensitivity is of fundamental importance to clinical and personalized point-of-care diagnostics. Because of their extraordinary optical properties, plasmonic nanomaterials have been introduced into colorimetric sensing systems, which provide significantly improved sensitivity in various biosensing applications. Here we review the recent progress on these plasmonic nanoparticles-based colorimetric nanosensors for ultrasensitive molecular diagnostics. According to their different colorimetric signal generation mechanisms, these plasmonic nanosensors are classified into two categories: (1) interparticle distance-dependent colorimetric assay based on target-induced forming cross-linking assembly/aggregate of plasmonic nanoparticles; and (2) size/morphology-dependent colorimetric assay by target-controlled growth/etching of the plasmonic nanoparticles. The sensing fundamentals and cutting-edge applications will be provided for each of them, particularly focusing on signal generation and/or amplification mechanisms that realize ultrasensitive molecular detection. Finally, we also discuss the challenge and give our future perspective in this emerging field.

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.

Research on the strategy of underwater united detection fusion and communication using multi-sensor

NASA Astrophysics Data System (ADS)

Xu, Zhenhua; Huang, Jianguo; Huang, Hai; Zhang, Qunfei

2011-09-01

In order to solve the distributed detection fusion problem of underwater target detection, when the signal to noise ratio (SNR) of the acoustic channel is low, a new strategy for united detection fusion and communication using multiple sensors was proposed. The performance of detection fusion was studied and compared based on the Neyman-Pearson principle when the binary phase shift keying (BPSK) and on-off keying (OOK) modes were used by the local sensors. The comparative simulation and analysis between the optimal likelihood ratio test and the proposed strategy was completed, and both the theoretical analysis and simulation indicate that using the proposed new strategy could improve the detection performance effectively. In theory, the proposed strategy of united detection fusion and communication is of great significance to the establishment of an underwater target detection system.

A nucleic acid strand displacement system for the multiplexed detection of tuberculosis-specific mRNA using quantum dots

NASA Astrophysics Data System (ADS)

Gliddon, H. D.; Howes, P. D.; Kaforou, M.; Levin, M.; Stevens, M. M.

2016-05-01

The development of rapid, robust and high performance point-of-care diagnostics relies on the advancement and combination of various areas of research. We have developed an assay for the detection of multiple mRNA molecules that combines DNA nanotechnology with fluorescent nanomaterials. The core switching mechanism is toehold-mediated strand displacement. We have used fluorescent quantum dots (QDs) as signal transducers in this assay, as they bring many benefits including bright fluorescence and multiplexing abilities. The resulting assay is capable of multiplexed detection of long RNA targets against a high concentration of background non-target RNA, with high sensitivity and specificity and limits of detection in the nanomolar range using only a standard laboratory plate reader. We demonstrate the utility of our QD-based system for the detection of two genes selected from a microarray-derived tuberculosis-specific gene expression signature. Levels of up- and downregulated gene transcripts comprising this signature can be combined to give a disease risk score, making the signature more amenable for use as a diagnostic marker. Our QD-based approach to detect these transcripts could pave the way for novel diagnostic assays for tuberculosis.The development of rapid, robust and high performance point-of-care diagnostics relies on the advancement and combination of various areas of research. We have developed an assay for the detection of multiple mRNA molecules that combines DNA nanotechnology with fluorescent nanomaterials. The core switching mechanism is toehold-mediated strand displacement. We have used fluorescent quantum dots (QDs) as signal transducers in this assay, as they bring many benefits including bright fluorescence and multiplexing abilities. The resulting assay is capable of multiplexed detection of long RNA targets against a high concentration of background non-target RNA, with high sensitivity and specificity and limits of detection in the nanomolar range using only a standard laboratory plate reader. We demonstrate the utility of our QD-based system for the detection of two genes selected from a microarray-derived tuberculosis-specific gene expression signature. Levels of up- and downregulated gene transcripts comprising this signature can be combined to give a disease risk score, making the signature more amenable for use as a diagnostic marker. Our QD-based approach to detect these transcripts could pave the way for novel diagnostic assays for tuberculosis. Electronic supplementary information (ESI) available: Base pair mismatch tuning of CProbes. Binding capacity of the QDs. Theoretical limit of detection (LOD) for the monoplex systems. Kinetics of strand displacement. Kinetics of QProbe-CProbe binding. LOD and saturation point calculations. See DOI: 10.1039/c6nr00484a

Fast range estimation based on active range-gated imaging for coastal surveillance

NASA Astrophysics Data System (ADS)

Kong, Qingshan; Cao, Yinan; Wang, Xinwei; Tong, Youwan; Zhou, Yan; Liu, Yuliang

2012-11-01

Coastal surveillance is very important because it is useful for search and rescue, illegal immigration, or harbor security and so on. Furthermore, range estimation is critical for precisely detecting the target. Range-gated laser imaging sensor is suitable for high accuracy range especially in night and no moonlight. Generally, before detecting the target, it is necessary to change delay time till the target is captured. There are two operating mode for range-gated imaging sensor, one is passive imaging mode, and the other is gate viewing mode. Firstly, the sensor is passive mode, only capturing scenes by ICCD, once the object appears in the range of monitoring area, we can obtain the course range of the target according to the imaging geometry/projecting transform. Then, the sensor is gate viewing mode, applying micro second laser pulses and sensor gate width, we can get the range of targets by at least two continuous images with trapezoid-shaped range intensity profile. This technique enables super-resolution depth mapping with a reduction of imaging data processing. Based on the first step, we can calculate the rough value and quickly fix delay time which the target is detected. This technique has overcome the depth resolution limitation for 3D active imaging and enables super-resolution depth mapping with a reduction of imaging data processing. By the two steps, we can quickly obtain the distance between the object and sensor.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Locating Sensors for Detecting Source-to-Target Patterns of Special Nuclear Material Smuggling: A Spatial Information Theoretic Approach

PubMed Central

Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

2010-01-01

In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy. PMID:22163641

Locating sensors for detecting source-to-target patterns of special nuclear material smuggling: a spatial information theoretic approach.

PubMed

Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

2010-01-01

In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.

Laser range profiling for small target recognition

NASA Astrophysics Data System (ADS)

Steinvall, Ove; Tulldahl, Michael

2016-05-01

The detection and classification of small surface and airborne targets at long ranges is a growing need for naval security. Long range ID or ID at closer range of small targets has its limitations in imaging due to the demand on very high transverse sensor resolution. It is therefore motivated to look for 1D laser techniques for target ID. These include vibrometry, and laser range profiling. Vibrometry can give good results but is also sensitive to certain vibrating parts on the target being in the field of view. Laser range profiling is attractive because the maximum range can be substantial, especially for a small laser beam width. A range profiler can also be used in a scanning mode to detect targets within a certain sector. The same laser can also be used for active imaging when the target comes closer and is angular resolved. The present paper will show both experimental and simulated results for laser range profiling of small boats out to 6-7 km range and a UAV mockup at close range (1.3 km). We obtained good results with the profiling system both for target detection and recognition. Comparison of experimental and simulated range waveforms based on CAD models of the target support the idea of having a profiling system as a first recognition sensor and thus narrowing the search space for the automatic target recognition based on imaging at close ranges. The naval experiments took place in the Baltic Sea with many other active and passive EO sensors beside the profiling system. Discussion of data fusion between laser profiling and imaging systems will be given. The UAV experiments were made from the rooftop laboratory at FOI.

Target-catalyzed hairpin assembly and metal-organic frameworks mediated nonenzymatic co-reaction for multiple signal amplification detection of miR-122 in human serum.

PubMed

Li, Yuliang; Yu, Chao; Yang, Bo; Liu, Zhirui; Xia, Peiyuan; Wang, Qian

2018-04-15

Herein, a new type of multifunctional iron based metal-organic frameworks (PdNPs@Fe-MOFs) has been synthesized by assembly palladium nanoparticles on the surface of Fe-MIL-88NH 2 MOFs microcrystals, and first applied in electrochemical biosensor for ultrasensitive detection of microRNA-122 (miR-122, a biomarker of drug-induced liver injury). The nanohybrids have not only been utilized as ideal nanocarriers for immobilization of signal probes, but also used as redox probes and electrocatalysts. In this biosensor, two hairpin probes were designed as capture probes and signal probes, respectively. The nanohybrids conjugated with streptavidin and biotinylated signal probes were used as the tracer labels, target miR-122 was sandwiched between the tracer labels and thiol-terminated capture probes inserted in MCH monolayer on the gold nanoparticles-functionalized nitrogen-doped graphene sheets (AuNPs@N-G) modified electrode. Based on target-catalyzed hairpin assembly, target miR-122 could trigger the hybridization of capture probes and signal probes to further be released to initiate the next reaction process resulted in numerous tracer indicators anchored onto the sensing interfaces. Thus, the detection signal could be dramatically enhanced towards the electrocatalytic oxidation of 3,3',5,5'-tetramethylbenzidine in the presence of H 2 O 2 owing to the intrinsic and intriguing peroxidase-like activity of the nanohybrids. With the assist of target-catalyzed hairpin assembly and PdNPs@Fe-MOFs mimetic co-reaction for signal amplification, a wide detection range from 0.01fM to 10pM was achieved with a low detection limit of 0.003fM (S/N =3). Furthermore, the proposed biosensor exhibited excellent specificity and recovery in spiked serum samples, and was successfully used for detecting miR-122 in real biological samples, which provided a rapid and efficient method for detecting drug-induced liver injury at an early stage. Copyright © 2017. Published by Elsevier B.V.

A microsensor for the detection of a single pathogenic bacterium using magnetotactic bacteria-based bio-carriers: simulations and preliminary experiments.

PubMed

Denomme, Ryan C; Lu, Zhao; Martel, Sylvain

2007-01-01

The proposed Magnetotactic Bacteria (MTB) based bio-carrier has the potential to greatly improve pathogenic bacteria detection time, specificity, and sensitivity. Microbeads are attached to the MTB and are modified with a coating of an antibody or phage that is specific to the target pathogenic bacteria. Using magnetic fields, the modified MTB are swept through a solution and the target bacteria present become attached to the microbeads (due to the coating). Then, the MTB are brought to the detection region and the number of pathogenic bacteria is determined. The high swimming speed and controllability of the MTB make this method ideal for the fast detection of small concentrations of specific bacteria. This paper focuses on an impedimetric detection system that will be used to identify if a target bacterium is attached to the microbead. The proposed detection system measures changes in electrical impedance as objects (MTB, microbeads, and pathogenic bacteria) pass through a set of microelectrodes embedded in a microfluidic device. FEM simulation is used to acquire the optimized parameters for the design of such a system. Specifically, factors such as electrode/detection channel geometry, object size and position, which have direct effects on the detection sensitivity for a single bacterium or microparticle, are investigated. Polymer microbeads and the MTB system with an E. coli bacterium are considered to investigate their impedance variations. Furthermore, preliminary experimental data using a microfabricated microfluidic device connected to an impedance analyzer are presented.

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.

Pilot study on real-time motion detection in UAS video data by human observer and image exploitation algorithm

NASA Astrophysics Data System (ADS)

Hild, Jutta; Krüger, Wolfgang; Brüstle, Stefan; Trantelle, Patrick; Unmüßig, Gabriel; Voit, Michael; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2017-05-01

Real-time motion video analysis is a challenging and exhausting task for the human observer, particularly in safety and security critical domains. Hence, customized video analysis systems providing functions for the analysis of subtasks like motion detection or target tracking are welcome. While such automated algorithms relieve the human operators from performing basic subtasks, they impose additional interaction duties on them. Prior work shows that, e.g., for interaction with target tracking algorithms, a gaze-enhanced user interface is beneficial. In this contribution, we present an investigation on interaction with an independent motion detection (IDM) algorithm. Besides identifying an appropriate interaction technique for the user interface - again, we compare gaze-based and traditional mouse-based interaction - we focus on the benefit an IDM algorithm might provide for an UAS video analyst. In a pilot study, we exposed ten subjects to the task of moving target detection in UAS video data twice, once performing with automatic support, once performing without it. We compare the two conditions considering performance in terms of effectiveness (correct target selections). Additionally, we report perceived workload (measured using the NASA-TLX questionnaire) and user satisfaction (measured using the ISO 9241-411 questionnaire). The results show that a combination of gaze input and automated IDM algorithm provides valuable support for the human observer, increasing the number of correct target selections up to 62% and reducing workload at the same time.

Mucin-1-Antibody-Conjugated Mesoporous Silica Nanoparticles for Selective Breast Cancer Detection in a Mucin-1 Transgenic Murine Mouse Model.

PubMed

Dréau, Didier; Moore, Laura Jeffords; Alvarez-Berrios, Merlis P; Tarannum, Mubin; Mukherjee, Pinku; Vivero-Escoto, Juan L

2016-12-01

Mucin-1 (MUC1), a transmembrane glycoprotein is aberrantly expressed on ~90% of breast cancer and is an excellent target for nanoparticulate targeted imaging. In this study, the development of a dye-doped NIR emitting mesoporous silica nanoparticles platform conjugated to tumor-specific MUC1 antibody (ab-tMUC1-NIR-MSN) for in vivo optical detection of breast adenocarcinoma tissue is reported. The structural properties, the in vitro and in vivo performance of this nanoparticle-based probe were evaluated. In vitro studies showed that the MSN-based optical imaging nanoprobe is non-cytotoxic and targets efficiently mammary cancer cells overexpressing human tMUC1 protein. In vivo experiments with female C57BL/6 mice indicated that this platform accumulates mainly in the liver and did not induce short-term toxicity. In addition, we demonstrated that the ab-tMUC1-NIR-MSN nanoprobe specifically detects mammary gland tumors overexpressing human tMUC1 in a human MUC1 transgenic mouse model.

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.

Visual detection following retinal damage: predictions of an inhomogeneous retino-cortical model

NASA Astrophysics Data System (ADS)

Arnow, Thomas L.; Geisler, Wilson S.

1996-04-01

A model of human visual detection performance has been developed, based on available anatomical and physiological data for the primate visual system. The inhomogeneous retino- cortical (IRC) model computes detection thresholds by comparing simulated neural responses to target patterns with responses to a uniform background of the same luminance. The model incorporates human ganglion cell sampling distributions; macaque monkey ganglion cell receptive field properties; macaque cortical cell contrast nonlinearities; and a optical decision rule based on ideal observer theory. Spatial receptive field properties of cortical neurons were not included. Two parameters were allowed to vary while minimizing the squared error between predicted and observed thresholds. One parameter was decision efficiency, the other was the relative strength of the ganglion-cell center and surround. The latter was only allowed to vary within a small range consistent with known physiology. Contrast sensitivity was measured for sinewave gratings as a function of spatial frequency, target size and eccentricity. Contrast sensitivity was also measured for an airplane target as a function of target size, with and without artificial scotomas. The results of these experiments, as well as contrast sensitivity data from the literature were compared to predictions of the IRC model. Predictions were reasonably good for grating and airplane targets.

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

NASA Astrophysics Data System (ADS)

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

2008-03-01

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

Simplified Real-Time Multiplex Detection of Loop-Mediated Isothermal Amplification Using Novel Mediator Displacement Probes with Universal Reporters.

PubMed

Becherer, Lisa; Bakheit, Mohammed; Frischmann, Sieghard; Stinco, Silvina; Borst, Nadine; Zengerle, Roland; von Stetten, Felix

2018-04-03

A variety of real-time detection techniques for loop-mediated isothermal amplification (LAMP) based on the change in fluorescence intensity during DNA amplification enable simultaneous detection of multiple targets. However, these techniques depend on fluorogenic probes containing target-specific sequences. That complicates the adaption to different targets leading to time-consuming assay optimization. Here, we present the first universal real-time detection technique for multiplex LAMP. The novel approach allows simple assay design and is easy to implement for various targets. The innovation features a mediator displacement probe and a universal reporter. During amplification of target DNA the mediator is displaced from the mediator displacement probe. Then it hybridizes to the reporter generating a fluorescence signal. The novel mediator displacement (MD) detection was validated against state-of-the-art molecular beacon (MB) detection by means of a HIV-1 RT-LAMP: MD surpassed MB detection by accelerated probe design (MD: 10 min, MB: 3-4 h), shorter times to positive (MD 4.1 ± 0.1 min shorter than MB, n = 36), improved signal-to-noise fluorescence ratio (MD: 5.9 ± 0.4, MB: 2.7 ± 0.4; n = 15), and showed equally good or better analytical performance parameters. The usability of one universal mediator-reporter set in different multiplex assays was successfully demonstrated for a biplex RT-LAMP of HIV-1 and HTLV-1 and a biplex LAMP of Haemophilus ducreyi and Treponema pallidum, both showing good correlation between target concentration and time to positive. Due to its simple implementation it is suggested to extend the use of the universal mediator-reporter sets to the detection of various other diagnostic panels.

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.

A comparison study of visually stimulated brain-computer and eye-tracking interfaces

NASA Astrophysics Data System (ADS)

Suefusa, Kaori; Tanaka, Toshihisa

2017-06-01

Objective. Brain-computer interfacing (BCI) based on visual stimuli detects the target on a screen on which a user is focusing. The detection of the gazing target can be achieved by tracking gaze positions with a video camera, which is called eye-tracking or eye-tracking interfaces (ETIs). The two types of interface have been developed in different communities. Thus, little work on a comprehensive comparison between these two types of interface has been reported. This paper quantitatively compares the performance of these two interfaces on the same experimental platform. Specifically, our study is focused on two major paradigms of BCI and ETI: steady-state visual evoked potential-based BCIs and dwelling-based ETIs. Approach. Recognition accuracy and the information transfer rate were measured by giving subjects the task of selecting one of four targets by gazing at it. The targets were displayed in three different sizes (with sides 20, 40 and 60 mm long) to evaluate performance with respect to the target size. Main results. The experimental results showed that the BCI was comparable to the ETI in terms of accuracy and the information transfer rate. In particular, when the size of a target was relatively small, the BCI had significantly better performance than the ETI. Significance. The results on which of the two interfaces works better in different situations would not only enable us to improve the design of the interfaces but would also allow for the appropriate choice of interface based on the situation. Specifically, one can choose an interface based on the size of the screen that displays the 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.

The G-BHQ synergistic effect: Improved double quenching molecular beacons based on guanine and Black Hole Quencher for sensitive simultaneous detection of two DNAs.

PubMed

Xiang, Dongshan; Li, Fengquan; Wu, Chenyi; Shi, Boan; Zhai, Kun

2017-11-01

We designed two double quenching molecular beacons (MBs) with simple structure based on guanine (G base) and Black Hole Quencher (BHQ), and developed a new analytical method for sensitive simultaneous detection of two DNAs by synchronous fluorescence analysis. In this analytical method, carboxyl fluorescein (FAM) and tetramethyl-6-carboxyrhodamine (TAMRA) were respectively selected as fluorophore of two MBs, Black Hole Quencher 1 (BHQ-1) and Black Hole Quencher 2 (BHQ-2) were respectively selected as organic quencher, and three continuous nucleotides with G base were connected to organic quencher (BHQ-1 and BHQ-2). In the presence of target DNAs, the two MBs hybridize with the corresponding target DNAs, the fluorophores are separated from organic quenchers and G bases, leading to recovery of fluorescence of FAM and TAMRA. Under a certain conditions, the fluorescence intensities of FAM and TAMRA all exhibited good linear dependence on their concentration of target DNAs (T1 and T2) in the range from 4 × 10 -10 to 4 × 10 -8 molL -1 (M). The detection limit (3σ, n = 13) of T1 was 3 × 10 -10 M and that of T2 was 2×10 -10 M, respectively. Compared with the existing analysis methods for multiplex DNA with MBs, this proposed method based on double quenching MBs is not only low fluorescence background, short analytical time and low detection cost, but also easy synthesis and good stability of MB probes. Copyright © 2017 Elsevier B.V. All rights reserved.

Advantages and application of label-free detection assays in drug screening.

PubMed

Cunningham, Brian T; Laing, Lance G

2008-08-01

Adoption is accelerating for a new family of label-free optical biosensors incorporated into standard format microplates owing to their ability to enable highly sensitive detection of small molecules, proteins and cells for high-throughput drug discovery applications. Label-free approaches are displacing other detection technologies owing to their ability to provide simple assay procedures for hit finding/validation, accessing difficult target classes, screening the interaction of cells with drugs and analyzing the affinity of small molecule inhibitors to target proteins. This review describes several new drug discovery applications that are under development for microplate-based photonic crystal optical biosensors and the key issues that will drive adoption of the technology. Microplate-based optical biosensors are enabling a variety of cell-based assays, inhibition assays, protein-protein binding assays and protein-small molecule binding assays to be performed with high-throughput and high sensitivity.

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.

Track-Before-Detect Algorithm for Faint Moving Objects based on Random Sampling and Consensus

NASA Astrophysics Data System (ADS)

Dao, P.; Rast, R.; Schlaegel, W.; Schmidt, V.; Dentamaro, A.

2014-09-01

There are many algorithms developed for tracking and detecting faint moving objects in congested backgrounds. One obvious application is detection of targets in images where each pixel corresponds to the received power in a particular location. In our application, a visible imager operated in stare mode observes geostationary objects as fixed, stars as moving and non-geostationary objects as drifting in the field of view. We would like to achieve high sensitivity detection of the drifters. The ability to improve SNR with track-before-detect (TBD) processing, where target information is collected and collated before the detection decision is made, allows respectable performance against dim moving objects. Generally, a TBD algorithm consists of a pre-processing stage that highlights potential targets and a temporal filtering stage. However, the algorithms that have been successfully demonstrated, e.g. Viterbi-based and Bayesian-based, demand formidable processing power and memory. We propose an algorithm that exploits the quasi constant velocity of objects, the predictability of the stellar clutter and the intrinsically low false alarm rate of detecting signature candidates in 3-D, based on an iterative method called "RANdom SAmple Consensus” and one that can run real-time on a typical PC. The technique is tailored for searching objects with small telescopes in stare mode. Our RANSAC-MT (Moving Target) algorithm estimates parameters of a mathematical model (e.g., linear motion) from a set of observed data which contains a significant number of outliers while identifying inliers. In the pre-processing phase, candidate blobs were selected based on morphology and an intensity threshold that would normally generate unacceptable level of false alarms. The RANSAC sampling rejects candidates that conform to the predictable motion of the stars. Data collected with a 17 inch telescope by AFRL/RH and a COTS lens/EM-CCD sensor by the AFRL/RD Satellite Assessment Center is used to assess the performance of the algorithm. In the second application, a visible imager operated in sidereal mode observes geostationary objects as moving, stars as fixed except for field rotation, and non-geostationary objects as drifting. RANSAC-MT is used to detect the drifter. In this set of data, the drifting space object was detected at a distance of 13800 km. The AFRL/RH set of data, collected in the stare mode, contained the signature of two geostationary satellites. The signature of a moving object was simulated and added to the sequence of frames to determine the sensitivity in magnitude. The performance compares well with the more intensive TBD algorithms reported in the literature.

Nanoporous-Gold-Based Electrode Morphology Libraries for Investigating Structure-Property Relationships in Nucleic Acid Based Electrochemical Biosensors.

PubMed

Matharu, Zimple; Daggumati, Pallavi; Wang, Ling; Dorofeeva, Tatiana S; Li, Zidong; Seker, Erkin

2017-04-19

Nanoporous gold (np-Au) electrode coatings significantly enhance the performance of electrochemical nucleic acid biosensors because of their three-dimensional nanoscale network, high electrical conductivity, facile surface functionalization, and biocompatibility. Contrary to planar electrodes, the np-Au electrodes also exhibit sensitive detection in the presence of common biofouling media due to their porous structure. However, the pore size of the nanomatrix plays a critical role in dictating the extent of biomolecular capture and transport. Small pores perform better in the case of target detection in complex samples by filtering out the large nonspecific proteins. On the other hand, larger pores increase the accessibility of target nucleic acids in the nanoporous structure, enhancing the detection limits of the sensor at the expense of more interference from biofouling molecules. Here, we report a microfabricated np-Au multiple electrode array that displays a range of electrode morphologies on the same chip for identifying feature sizes that reduce the nonspecific adsorption of proteins but facilitate the permeation of target DNA molecules into the pores. We demonstrate the utility of the electrode morphology library in studying DNA functionalization and target detection in complex biological media with a special emphasis on revealing ranges of electrode morphologies that mutually enhance the limit of detection and biofouling resilience. We expect this technique to assist in the development of high-performance biosensors for point-of-care diagnostics and facilitate studies on the electrode structure-property relationships in potential applications ranging from neural electrodes to catalysts.

A cooperative-binding split aptamer assay for rapid, specific and ultra-sensitive fluorescence detection of cocaine in saliva.

PubMed

Yu, Haixiang; Canoura, Juan; Guntupalli, Bhargav; Lou, Xinhui; Xiao, Yi

2017-01-01

Sensors employing split aptamers that reassemble in the presence of a target can achieve excellent specificity, but the accompanying reduction of target affinity mitigates any overall gains in sensitivity. We for the first time have developed a split aptamer that achieves enhanced target-binding affinity through cooperative binding. We have generated a split cocaine-binding aptamer that incorporates two binding domains, such that target binding at one domain greatly increases the affinity of the second domain. We experimentally demonstrate that the resulting cooperative-binding split aptamer (CBSA) exhibits higher target binding affinity and is far more responsive in terms of target-induced aptamer assembly compared to the single-domain parent split aptamer (PSA) from which it was derived. We further confirm that the target-binding affinity of our CBSA can be affected by the cooperativity of its binding domains and the intrinsic affinity of its PSA. To the best of our knowledge, CBSA-5335 has the highest cocaine affinity of any split aptamer described to date. The CBSA-based assay also demonstrates excellent performance in target detection in complex samples. Using this CBSA, we achieved specific, ultra-sensitive, one-step fluorescence detection of cocaine within fifteen minutes at concentrations as low as 50 nM in 10% saliva without signal amplification. This limit of detection meets the standards recommended by the European Union's Driving under the Influence of Drugs, Alcohol and Medicines program. Our assay also demonstrates excellent reproducibility of results, confirming that this CBSA-platform represents a robust and sensitive means for cocaine detection in actual clinical samples.

NaEuF4/Au@Ag2S nanoparticles-based fluorescence resonant transfer DNA sensor for ultrasensitive detection of DNA energy.

PubMed

Liu, Yuhong; Zhao, Linlin; Zhang, Jin; Zhang, Jinzha; Zhao, Wenbo; Mao, Chun

2016-12-01

The work investigates a new fluorescence resonance energy transfer (FRET) system using NaEuF 4 nanoparticles (NPs) and Au@Ag 2 S NPs as the energy donor-acceptor pair for the first time. The NaEuF 4 /Au@Ag 2 S NPs-based FRET DNA sensor was constructed with NaEuF 4 NPs as the fluorescence (FL) donor and Au@Ag 2 S core-shell NPs as FL acceptor. In order to find the matching energy acceptor, the amount of AgNO 3 and Na 2 S were controlled in the synthesis process to overlap the absorption spectrum of energy acceptor with the emission spectrum of energy donors. The sensitivity of FRET-based DNA sensor can be enhanced and the self-absorption of ligand as well as the background of signals can be decreased because of Eu 3+ which owns large Stokes shifts and narrow emission bands due to f-f electronic transitions of 4f shell. We obtained the efficient FRET system by studying suitable distance between the donor and acceptor. Then the FRET-based DNA sensor was used for the design of specific and sensitive detection of target DNA and the quenching efficiency (ΔFL/F 0 , ΔFL=F-F 0 ) of FL was logarithmically related to the concentration of the target DNA, ranging from 100aM to 100pM. We can realize an ultrasensitive detection of target DNA with a detection limit of 32 aM. This proposed method was feasible to analyse target DNA in real samples with satisfactory results. Copyright © 2016 Elsevier B.V. All rights reserved.

Ultrasensitive sensing platform for platelet-derived growth factor BB detection based on layered molybdenum selenide-graphene composites and Exonuclease III assisted signal amplification.

PubMed

Huang, Ke-Jing; Shuai, Hong-Lei; Zhang, Ji-Zong

2016-03-15

A highly sensitive and ultrasensitive electrochemical aptasensor for platelet-derived growth factor BB (PDGF-BB) detection is fabricated based on layered molybdenum selenide-graphene (MoSe2-Gr) composites and Exonuclease III (Exo III)-aided signal amplification. MoSe2-Gr is prepared by a simple hydrothermal method and used as a promising sensing platform. Exo III has a specifical exo-deoxyribonuclease activity for duplex DNAs in the direction from 3' to 5' terminus, however its activity is limited on the duplex DNAs with more than 4 mismatched terminal bases at 3' ends. Herein, aptamer and complementary DNA (cDNA) sequences are designed with four thymine bases on 3' ends. In the presence of target protein, the aptamer associates with it and facilitates the formation of duplex DNA between cDNA and signal DNA. The duplex DNA then is digested by Exo III and releases cDNA, which hybridizes with signal DNA to perform a new cleavage process. Nevertheless, in the absence of target protein, the aptamer hybridizes with cDNA will inhibit the Exo III-assisted nucleotides cleavage. The signal DNA then hybridizes with capture DNA on the electrode. Subsequently, horse radish peroxidase is fixed on electrode by avidin-biotin reaction and then catalyzes hydrogen peroxide and hydroquinone to produce electrochemical response. Therefore, a bridge can be established between the concentration of target protein and the degree of the attenuation of the obtained signal, providing a quantitative measure of target protein with a broad detection range of 0.0001-1 nM and a detection limit of 20 fM. Copyright © 2015 Elsevier B.V. All rights reserved.

Detection of multiple airborne targets from multisensor data

NASA Astrophysics Data System (ADS)

Foltz, Mark A.; Srivastava, Anuj; Miller, Michael I.; Grenander, Ulf

1995-08-01

Previously we presented a jump-diffusion based random sampling algorithm for generating conditional mean estimates of scene representations for the tracking and recongition of maneuvering airborne targets. These representations include target positions and orientations along their trajectories and the target type associated with each trajectory. Taking a Bayesian approach, a posterior measure is defined on the parameter space by combining sensor models with a sophisticated prior based on nonlinear airplane dynamics. The jump-diffusion algorithm constructs a Markov process which visits the elements of the parameter space with frequencies proportional to the posterior probability. It consititutes both the infinitesimal, local search via a sample path continuous diffusion transform and the larger, global steps through discrete jump moves. The jump moves involve the addition and deletion of elements from the scene configuration or changes in the target type assoviated with each target trajectory. One such move results in target detection by the addition of a track seed to the inference set. This provides initial track data for the tracking/recognition algorithm to estimate linear graph structures representing tracks using the other jump moves and the diffusion process, as described in our earlier work. Target detection ideally involves a continuous research over a continuum of the observation space. In this work we conclude that for practical implemenations the search space must be discretized with lattice granularity comparable to sensor resolution, and discuss how fast Fourier transforms are utilized for efficient calcuation of sufficient statistics given our array models. Some results are also presented from our implementation on a networked system including a massively parallel machine architecture and a silicon graphics onyx workstation.

M13 phage-functionalized single-walled carbon nanotubes as nanoprobes for second near-infrared window fluorescence imaging of targeted tumors

PubMed Central

HAM, MOON-HO; QI, JIFA; BARONE, PAUL W.; STRANO, MICHAEL S.; BELCHER, ANGELA M.

2014-01-01

Second near-infrared (NIR) window light (950-1,400 nm) is attractive for in vivo fluorescence imaging due to its deep penetration depth in tissues and low tissue autofluorescence. Here we show genetically engineered multifunctional M13 phage can assemble fluorescent single-walled carbon nanotubes (SWNTs) and ligands for targeted fluorescence imaging of tumors. M13-SWNT probe is detectable in deep tissues even at a low dosage of 2 μg/mL and up to 2.5 cm in tissue-like phantoms. Moreover, targeted probes show specific and up to four-fold improved uptake in prostate specific membrane antigen positive prostate tumors compared to control non-targeted probes. This M13 phage-based second NIR window fluorescence imaging probe has great potential for specific detection and therapy monitoring of hard-to-detect areas. PMID:22268625

Target oriented dimensionality reduction of hyperspectral data by Kernel Fukunaga-Koontz Transform

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Ochilov, Shuhrat; Alam, Mohammad S.; Bal, Abdullah

2017-02-01

Principal component analysis (PCA) is a popular technique in remote sensing for dimensionality reduction. While PCA is suitable for data compression, it is not necessarily an optimal technique for feature extraction, particularly when the features are exploited in supervised learning applications (Cheriyadat and Bruce, 2003) [1]. Preserving features belonging to the target is very crucial to the performance of target detection/recognition techniques. Fukunaga-Koontz Transform (FKT) based supervised band reduction technique can be used to provide this requirement. FKT achieves feature selection by transforming into a new space in where feature classes have complimentary eigenvectors. Analysis of these eigenvectors under two classes, target and background clutter, can be utilized for target oriented band reduction since each basis functions best represent target class while carrying least information of the background class. By selecting few eigenvectors which are the most relevant to the target class, dimension of hyperspectral data can be reduced and thus, it presents significant advantages for near real time target detection applications. The nonlinear properties of the data can be extracted by kernel approach which provides better target features. Thus, we propose constructing kernel FKT (KFKT) to present target oriented band reduction. The performance of the proposed KFKT based target oriented dimensionality reduction algorithm has been tested employing two real-world hyperspectral data and results have been reported consequently.

Digital DNA detection based on a compact optofluidic laser with ultra-low sample consumption.

PubMed

Lee, Wonsuk; Chen, Qiushu; Fan, Xudong; Yoon, Dong Ki

2016-11-29

DNA lasers self-amplify optical signals from a DNA analyte as well as thermodynamic differences between sequences, allowing quasi-digital DNA detection. However, these systems have drawbacks, such as relatively large sample consumption and complicated dye labelling. Moreover, although the lasing signal can detect the target DNA, it is superimposed on an unintended fluorescence background, which persists for non-target DNA samples as well. From an optical point of view, it is thus not truly digital detection and requires spectral analysis to identify the target. In this work, we propose and demonstrate an optofluidic laser that has a single layer of DNA molecules as the gain material. A target DNA produces intensive laser emission comparable to existing DNA lasers, while any unnecessary fluorescence background is successfully suppressed. As a result, the target DNA can be detected with a single laser pulse, in a truly digital manner. Since the DNA molecules cover only a single layer on the surface of the laser microcavity, the DNA sample consumption is a few orders of magnitude lower than that of existing DNA lasers. Furthermore, the DNA molecules are stained by simply immersing the microcavity in the intercalating dye solution, and thus the proposed DNA laser is free of any complex dye-labelling process prior to analysis.

An electrochemical aptasensor for multiplex antibiotics detection based on metal ions doped nanoscale MOFs as signal tracers and RecJf exonuclease-assisted targets recycling amplification.

PubMed

Chen, Meng; Gan, Ning; Zhou, You; Li, Tianhua; Xu, Qing; Cao, Yuting; Chen, Yinji

2016-12-01

An ultrasensitive electrochemical aptasensor for simultaneous detection of oxytetracycline (OTC) and kanamycin (KAN) has been developed based on metal ions doped metal organic frame materials (MOFs) as signal tracers and RecJ f exonuclease-catalyzed targets recycling amplification. The aptasensor consists of capture beads (the anti-single-stranded DNA Antibody, as anti-ssDNA Ab, labeled on Dynabeads) and nanoscale MOF (NMOF) based signal tracers (simplified as Apts-MNM, the NMOF labeled with metal ions and the aptamers). Particularly, the MOF (UiO-66-NH 2 ), with large internal surface areas, ultrahigh porosity and abundant amine groups in the pores, was employed as substrates to carry plenty of metal ions (Pb 2+ or Cd 2+ ) and label aptamers of OTC or KAN. Thus, the aptasensor is formed by the specific recognition between anti-ssDNA Ab and aptamers. In the presence of targets (OTC and KAN), aptamers prefer to form targets-Apts-MNM complexes in lieu of anti-ssDNA Ab-aptamer complexes, which results in the dissociation of Apts-MNM from capture beads. With the employment of RecJ f exonuclease, targets-Apts-MNM in supernatant was digested into mononucleotides and liberated the target, which can further participate in the next reaction cycling to produce more signal tracers. After magnetic separation, the enhanced square wave voltammetry (SWV) signals were produced from signal tracers. The aptasensor exhibited a linear correlation in the range from 0.5pM to 50nM, with detection limits of 0.18pM and 0.15pM (S/N=3) toward OTC and KAN respectively. This strategy provides specificity and sensitive approach for multiplex antibiotics detection and has promising applications in food analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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.

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.

Analysis of the development of missile-borne IR imaging detecting technologies

NASA Astrophysics Data System (ADS)

Fan, Jinxiang; Wang, Feng

2017-10-01

Today's infrared imaging guiding missiles are facing many challenges. With the development of targets' stealth, new-style IR countermeasures and penetrating technologies as well as the complexity of the operational environments, infrared imaging guiding missiles must meet the higher requirements of efficient target detection, capability of anti-interference and anti-jamming and the operational adaptability in complex, dynamic operating environments. Missileborne infrared imaging detecting systems are constrained by practical considerations like cost, size, weight and power (SWaP), and lifecycle requirements. Future-generation infrared imaging guiding missiles need to be resilient to changing operating environments and capable of doing more with fewer resources. Advanced IR imaging detecting and information exploring technologies are the key technologies that affect the future direction of IR imaging guidance missiles. Infrared imaging detecting and information exploring technologies research will support the development of more robust and efficient missile-borne infrared imaging detecting systems. Novelty IR imaging technologies, such as Infrared adaptive spectral imaging, are the key to effectively detect, recognize and track target under the complicated operating and countermeasures environments. Innovative information exploring techniques for the information of target, background and countermeasures provided by the detection system is the base for missile to recognize target and counter interference, jamming and countermeasure. Modular hardware and software development is the enabler for implementing multi-purpose, multi-function solutions. Uncooled IRFPA detectors and High-operating temperature IRFPA detectors as well as commercial-off-the-shelf (COTS) technology will support the implementing of low-cost infrared imaging guiding missiles. In this paper, the current status and features of missile-borne IR imaging detecting technologies are summarized. The key technologies and its development trends of missiles' IR imaging detecting technologies are analyzed.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

A sensitive electrochemical aptasensor for multiplex antibiotics detection based on high-capacity magnetic hollow porous nanotracers coupling exonuclease-assisted cascade target recycling.

PubMed

Yan, Zhongdan; Gan, Ning; Li, Tianhua; Cao, Yuting; Chen, Yinji

2016-04-15

A multiplex electrochemical aptasensor was developed for simultaneous detection of two antibiotics such as chloramphenicol (CAP) and oxytetracycline (OTC), and high-capacity magnetic hollow porous nanotracers coupling exonuclease-assisted target recycling was used to improve sensitivity. The cascade amplification process consists of the exonuclease-assisted target recycling amplification and metal ions encoded magnetic hollow porous nanoparticles (MHPs) to produce voltammetry signals. Upon the specific recognition of aptamers to targets (CAP and OTC), exonuclease I (Exo I) selectively digested the aptamers which were bound with CAP and OTC, then the released CAP and OTC participated new cycling to produce more single DNA, which can act as trigger strands to hybrid with nanotracers to generate further signal amplification. MHPs were used as carriers to load more amounts of metal ions and coupling with Exo I assisted cascade target recycling can amplify the signal for about 12 folds compared with silica based nanotracers. Owing to the dual signal amplification, the linear range between signals and the concentrations of CAP and OTC were obtained in the range of 0.0005-50 ng mL(-1). The detection limits of CAP and OTC were 0.15 and 0.10 ng mL(-1) (S/N=3) which is more than 2 orders lower than commercial enzyme-linked immunosorbent immunoassay (ELISA) method, respectively. The proposed method was successfully applied to simultaneously detection of CAP and OTC in milk samples. Besides, this aptasensor can be applied to other antibiotics detection by changing the corresponding aptamer. The whole scheme is facile, selective and sensitive enough for antibiotics screening in food safety. Copyright © 2015 Elsevier B.V. All rights reserved.

Target-responsive DNA-capped nanocontainer used for fabricating universal detector and performing logic operations

PubMed Central

Wu, Li; Ren, Jinsong; Qu, Xiaogang

2014-01-01

Nucleic acids have become a powerful tool in nanotechnology because of their controllable diverse conformational transitions and adaptable higher-order nanostructure. Using single-stranded DNA probes as the pore-caps for various target recognition, here we present an ultrasensitive universal electrochemical detection system based on graphene and mesoporous silica, and achieve sensitivity with all of the major classes of analytes and simultaneously realize DNA logic gate operations. The concept is based on the locking of the pores and preventing the signal-reporter molecules from escape by target-induced the conformational change of the tailored DNA caps. The coupling of ‘waking up’ gatekeeper with highly specific biochemical recognition is an innovative strategy for the detection of various targets, able to compete with classical methods which need expensive instrumentation and sophisticated experimental operations. The present study has introduced a new electrochemical signal amplification concept and also adds a new dimension to the function of graphene-mesoporous materials hybrids as multifunctional nanoscale logic devices. More importantly, the development of this approach would spur further advances in important areas, such as point-of-care diagnostics or detection of specific biological contaminations, and hold promise for use in field analysis. PMID:25249622

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.

Rapid detection of aflatoxigenic Aspergillus sp. in herbal specimens by a simple, bendable, paper-based lab-on-a-chip.

PubMed

Chaumpluk, Piyasak; Plubcharoensook, Pattra; Prasongsuk, Sehanat

2016-06-01

Postharvest herbal product contamination with mycotoxins and mycotoxin-producing fungi represents a potentially carcinogenic hazard. Aspergillus flavus is a major cause of this issue. Available mold detection methods are PCR-based and rely heavily on laboratories; thus, they are unsuitable for on-site monitoring. In this study, a bendable, paper-based lab-on-a-chip platform was developed to rapidly detect toxigenic Aspergillus spp. DNA. The 3.0-4.0 cm(2) chip is fabricated using Whatman™ filter paper, fishing line and a simple plastic lamination process and has nucleic acid amplification and signal detection components. The Aspergillus assay specifically amplifies the aflatoxin biosynthesis gene, aflR, using loop-mediated isothermal amplification (LAMP); hybridization between target DNA and probes on blue silvernanoplates (AgNPls) yields colorimetric results. Positive results are indicated by the detection pad appearing blue due to dispersed blue AgNPls; negative results are indicated by the detection pad appearing colorless or pale yellow due to probe/target DNA hybridization and AgNPls aggregation. Assay completion requires less than 40 min, has a limit of detection (LOD) of 100 aflR copies, and has high specificity (94.47%)and sensitivity (100%). Contamination was identified in 14 of 32 herbal samples tested (43.75%). This work demonstrates the fabrication of a simple, low-cost, paper-based lab-on-a-chip platform suitable for rapid-detection applications. Copyright © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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