[Detection of recombinant-DNA in foods from stacked genetically modified plants].

PubMed

Sorokina, E Iu; Chernyshova, O N

2012-01-01

A quantitative real-time multiplex polymerase chain reaction method was applied to the detection and quantification of MON863 and MON810 in stacked genetically modified maize MON 810xMON 863. The limit of detection was approximately 0,1%. The accuracy of the quantification, measured as bias from the accepted value and the relative repeatability standard deviation, which measures the intra-laboratory variability, were within 25% at each GM-level. A method verification has demonstrated that the MON 863 and the MON810 methods can be equally applied in quantification of the respective events in stacked MON810xMON 863.

A scan statistic for binary outcome based on hypergeometric probability model, with an application to detecting spatial clusters of Japanese encephalitis.

PubMed

Zhao, Xing; Zhou, Xiao-Hua; Feng, Zijian; Guo, Pengfei; He, Hongyan; Zhang, Tao; Duan, Lei; Li, Xiaosong

2013-01-01

As a useful tool for geographical cluster detection of events, the spatial scan statistic is widely applied in many fields and plays an increasingly important role. The classic version of the spatial scan statistic for the binary outcome is developed by Kulldorff, based on the Bernoulli or the Poisson probability model. In this paper, we apply the Hypergeometric probability model to construct the likelihood function under the null hypothesis. Compared with existing methods, the likelihood function under the null hypothesis is an alternative and indirect method to identify the potential cluster, and the test statistic is the extreme value of the likelihood function. Similar with Kulldorff's methods, we adopt Monte Carlo test for the test of significance. Both methods are applied for detecting spatial clusters of Japanese encephalitis in Sichuan province, China, in 2009, and the detected clusters are identical. Through a simulation to independent benchmark data, it is indicated that the test statistic based on the Hypergeometric model outweighs Kulldorff's statistics for clusters of high population density or large size; otherwise Kulldorff's statistics are superior.

Astrometric Research of Asteroidal Satellites

NASA Astrophysics Data System (ADS)

Kikwaya, J.-B.; Thuillot, W.; Rocher, P.; Vieira Martins, R.; Arlot, J.-E.; Angeli, Cl.

2002-09-01

Several observational methods have been applied in order to detect asteroidal satellites. Some of them were rather successful, such as the stellar occultations and mutual eclipse methods. Recently other techniques such as the space imaging, the adaptive optics and the radar imaging inferred a great improvement in the search for these objects. However several limitations appear in the type of data that each of them allow us to access. We propose to apply an astrometric method in order as well to detect new asteroidal satellites as to get complementary data of some already detected objects (mainly their orbital period). This method is founded on the search of the reflex effect of the primary object due to the orbital motion of a possible satellite. Such an astrometric signature, already searched by Monet & Monet (1998), may reach several tens of MAS. Only a spectral analysis could then detect this signal under good conditions of signal/noise ratio and thanks to high quality astrometric measurements and coverage by different sites of observation. We have applied such a method for several asteroids. A preliminary result is obtained thanks to 377 CCD observations of 146 Lucina made at the Haute-Provence Observatory in South of France. A periodical signal appears in this analysis, leading to data compatible with a first detection of a probable satellite made previously (Arlot et al. 1985) by the occultation method.

VizieR Online Data Catalog: Bayesian method for detecting stellar flares (Pitkin+, 2014)

NASA Astrophysics Data System (ADS)

Pitkin, M.; Williams, D.; Fletcher, L.; Grant, S. D. T.

2015-05-01

We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light-curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model required to fit underlying light-curve variations in the data, which could otherwise partially mimic a flare. We characterize the false alarm probability and efficiency of this method under the assumption that any unmodelled noise in the data is Gaussian, and compare it with a simpler thresholding method based on that used in Walkowicz et al. We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95 per cent of flares with S/N less than 20, as compared to S/N of 25 for the simpler method. We also test how well the assumption of Gaussian noise holds by applying the method to a selection of 'quiet' Kepler stars. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have made preliminary characterizations of their durations and and S/N. (1 data file).

A Bayesian method for detecting stellar flares

NASA Astrophysics Data System (ADS)

Pitkin, M.; Williams, D.; Fletcher, L.; Grant, S. D. T.

2014-12-01

We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light-curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model required to fit underlying light-curve variations in the data, which could otherwise partially mimic a flare. We characterize the false alarm probability and efficiency of this method under the assumption that any unmodelled noise in the data is Gaussian, and compare it with a simpler thresholding method based on that used in Walkowicz et al. We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95 per cent of flares with S/N less than 20, as compared to S/N of 25 for the simpler method. We also test how well the assumption of Gaussian noise holds by applying the method to a selection of `quiet' Kepler stars. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have made preliminary characterizations of their durations and and S/N.

Acquiring 3-D information about thick objects from differential interference contrast images using texture extraction

NASA Astrophysics Data System (ADS)

Sierra, Heidy; Brooks, Dana; Dimarzio, Charles

2010-07-01

The extraction of 3-D morphological information about thick objects is explored in this work. We extract this information from 3-D differential interference contrast (DIC) images by applying a texture detection method. Texture extraction methods have been successfully used in different applications to study biological samples. A 3-D texture image is obtained by applying a local entropy-based texture extraction method. The use of this method to detect regions of blastocyst mouse embryos that are used in assisted reproduction techniques such as in vitro fertilization is presented as an example. Results demonstrate the potential of using texture detection methods to improve morphological analysis of thick samples, which is relevant to many biomedical and biological studies. Fluorescence and optical quadrature microscope phase images are used for validation.

Cause-specific mortality time series analysis: a general method to detect and correct for abrupt data production changes

PubMed Central

2011-01-01

Background Monitoring the time course of mortality by cause is a key public health issue. However, several mortality data production changes may affect cause-specific time trends, thus altering the interpretation. This paper proposes a statistical method that detects abrupt changes ("jumps") and estimates correction factors that may be used for further analysis. Methods The method was applied to a subset of the AMIEHS (Avoidable Mortality in the European Union, toward better Indicators for the Effectiveness of Health Systems) project mortality database and considered for six European countries and 13 selected causes of deaths. For each country and cause of death, an automated jump detection method called Polydect was applied to the log mortality rate time series. The plausibility of a data production change associated with each detected jump was evaluated through literature search or feedback obtained from the national data producers. For each plausible jump position, the statistical significance of the between-age and between-gender jump amplitude heterogeneity was evaluated by means of a generalized additive regression model, and correction factors were deduced from the results. Results Forty-nine jumps were detected by the Polydect method from 1970 to 2005. Most of the detected jumps were found to be plausible. The age- and gender-specific amplitudes of the jumps were estimated when they were statistically heterogeneous, and they showed greater by-age heterogeneity than by-gender heterogeneity. Conclusion The method presented in this paper was successfully applied to a large set of causes of death and countries. The method appears to be an alternative to bridge coding methods when the latter are not systematically implemented because they are time- and resource-consuming. PMID:21929756

Breast cancer evaluation by fluorescent dot detection using combined mathematical morphology and multifractal techniques

PubMed Central

2011-01-01

Background Fluorescence in situ hybridization (FISH) is very accurate method for measuring HER2 gene copies, as a sign of potential breast cancer. This method requires small tissue samples, and has a high sensitivity to detect abnormalities from a histological section. By using multiple colors, this method allows the detection of multiple targets simultaneously. The target parts in the cells become visible as colored dots. The HER-2 probes are visible as orange stained spots under a fluorescent microscope while probes for centromere 17 (CEP-17), the chromosome on which the gene HER-2/neu is located, are visible as green spots. Methods The conventional analysis involves the scoring of the ratio of HER-2/neu over CEP 17 dots within each cell nucleus and then averaging the scores for a number of 60 cells. A ratio of 2.0 of HER-2/neu to CEP 17 copy number denotes amplification. Several methods have been proposed for the detection and automated evaluation (dot counting) of FISH signals. In this paper the combined method based on the mathematical morphology (MM) and inverse multifractal (IMF) analysis is suggested. Similar method was applied recently in detection of microcalcifications in digital mammograms, and was very successful. Results The combined MM using top-hat and bottom-hat filters, and the IMF method was applied to FISH images from Molecular Biology Lab, Department of Pathology, Wielkoposka Cancer Center, Poznan. Initial results indicate that this method can be applied to FISH images for the evaluation of HER2/neu status. Conclusions Mathematical morphology and multifractal approach are used for colored dot detection and counting in FISH images. Initial results derived on clinical cases are promising. Note that the overlapping of colored dots, particularly red/orange dots, needs additional improvements in post-processing. PMID:21489192

The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer.

PubMed

Aghdam, Rosa; Baghfalaki, Taban; Khosravi, Pegah; Saberi Ansari, Elnaz

2017-12-01

Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM) method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/. Copyright © 2017. Production and hosting by Elsevier B.V.

Seismic data fusion anomaly detection

NASA Astrophysics Data System (ADS)

Harrity, Kyle; Blasch, Erik; Alford, Mark; Ezekiel, Soundararajan; Ferris, David

2014-06-01

Detecting anomalies in non-stationary signals has valuable applications in many fields including medicine and meteorology. These include uses such as identifying possible heart conditions from an Electrocardiography (ECG) signals or predicting earthquakes via seismographic data. Over the many choices of anomaly detection algorithms, it is important to compare possible methods. In this paper, we examine and compare two approaches to anomaly detection and see how data fusion methods may improve performance. The first approach involves using an artificial neural network (ANN) to detect anomalies in a wavelet de-noised signal. The other method uses a perspective neural network (PNN) to analyze an arbitrary number of "perspectives" or transformations of the observed signal for anomalies. Possible perspectives may include wavelet de-noising, Fourier transform, peak-filtering, etc.. In order to evaluate these techniques via signal fusion metrics, we must apply signal preprocessing techniques such as de-noising methods to the original signal and then use a neural network to find anomalies in the generated signal. From this secondary result it is possible to use data fusion techniques that can be evaluated via existing data fusion metrics for single and multiple perspectives. The result will show which anomaly detection method, according to the metrics, is better suited overall for anomaly detection applications. The method used in this study could be applied to compare other signal processing algorithms.

Algorithm Summary and Evaluation: Automatic Implementation of Ringdown Analysis for Electromechanical Mode Identification from Phasor Measurements

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

Zhou, Ning; Huang, Zhenyu; Tuffner, Francis K.

2010-02-28

Small signal stability problems are one of the major threats to grid stability and reliability. Prony analysis has been successfully applied on ringdown data to monitor electromechanical modes of a power system using phasor measurement unit (PMU) data. To facilitate an on-line application of mode estimation, this paper develops a recursive algorithm for implementing Prony analysis and proposed an oscillation detection method to detect ringdown data in real time. By automatically detecting ringdown data, the proposed method helps guarantee that Prony analysis is applied properly and timely on the ringdown data. Thus, the mode estimation results can be performed reliablymore » and timely. The proposed method is tested using Monte Carlo simulations based on a 17-machine model and is shown to be able to properly identify the oscillation data for on-line application of Prony analysis. In addition, the proposed method is applied to field measurement data from WECC to show the performance of the proposed algorithm.« less

A New Moving Object Detection Method Based on Frame-difference and Background Subtraction

NASA Astrophysics Data System (ADS)

Guo, Jiajia; Wang, Junping; Bai, Ruixue; Zhang, Yao; Li, Yong

2017-09-01

Although many methods of moving object detection have been proposed, moving object extraction is still the core in video surveillance. However, with the complex scene in real world, false detection, missed detection and deficiencies resulting from cavities inside the body still exist. In order to solve the problem of incomplete detection for moving objects, a new moving object detection method combined an improved frame-difference and Gaussian mixture background subtraction is proposed in this paper. To make the moving object detection more complete and accurate, the image repair and morphological processing techniques which are spatial compensations are applied in the proposed method. Experimental results show that our method can effectively eliminate ghosts and noise and fill the cavities of the moving object. Compared to other four moving object detection methods which are GMM, VIBE, frame-difference and a literature's method, the proposed method improve the efficiency and accuracy of the detection.

Using pyramids to define local thresholds for blob detection.

PubMed

Shneier, M

1983-03-01

A method of detecting blobs in images is described. The method involves building a succession of lower resolution images and looking for spots in these images. A spot in a low resolution image corresponds to a distinguished compact region in a known position in the original image. Further, it is possible to calculate thresholds in the low resolution image, using very simple methods, and to apply those thresholds to the region of the original image corresponding to the spot. Examples are shown in which variations of the technique are applied to several images.

Unsupervised Approaches for Post-Processing in Computationally Efficient Waveform-Similarity-Based Earthquake Detection

NASA Astrophysics Data System (ADS)

Bergen, K.; Yoon, C. E.; OReilly, O. J.; Beroza, G. C.

2015-12-01

Recent improvements in computational efficiency for waveform correlation-based detections achieved by new methods such as Fingerprint and Similarity Thresholding (FAST) promise to allow large-scale blind search for similar waveforms in long-duration continuous seismic data. Waveform similarity search applied to datasets of months to years of continuous seismic data will identify significantly more events than traditional detection methods. With the anticipated increase in number of detections and associated increase in false positives, manual inspection of the detection results will become infeasible. This motivates the need for new approaches to process the output of similarity-based detection. We explore data mining techniques for improved detection post-processing. We approach this by considering similarity-detector output as a sparse similarity graph with candidate events as vertices and similarities as weighted edges. Image processing techniques are leveraged to define candidate events and combine results individually processed at multiple stations. Clustering and graph analysis methods are used to identify groups of similar waveforms and assign a confidence score to candidate detections. Anomaly detection and classification are applied to waveform data for additional false detection removal. A comparison of methods will be presented and their performance will be demonstrated on a suspected induced and non-induced earthquake sequence.

HF Surface Wave Radar Tests at the Eastern China Sea

NASA Astrophysics Data System (ADS)

Wu, Xiong Bin; Cheng, Feng; Wu, Shi Cai; Yang, Zi Jie; Wen, Biyang; Shi, Zhen Hua; Tian, Jiansheng; Ke, Hengyu; Gao, Huotao

2005-01-01

The HF surface wave radar system OSMAR2000 adopts Frequency Modulated Interrupted Continuous Waveform (FMICW) and its 120m-antenna array is transmitting/receiving co-used. MUSIC and MVM are applied to obtain sea echo's direction of arrival (DOA) when extracting currents information. Verification tests of OSMAR2000 ocean surface dynamics detection against in-situ measurements had been accomplished on Oct. 23~29, 2000. Ship detection test was carried out on Dec.24, 2001. It shows that OSMAR2000 is capable of detecting 1000 tons ships with a wide beam out to 70 km. This paper introduces the radar system and the applied DOA estimation methods in the first, and then presents ship detection results and some sea state measurement results of surface currents and waves. The results indicate the validity of the developed radar system and the effectiveness of the applied signal processing methods.

Method for the detection of nitro-containing compositions using ultraviolet photolysis

DOEpatents

Reagen, William K.; Lancaster, Gregory D.; Partin, Judy K.; Moore, Glenn A.

2000-01-01

A method for detecting nitro-containing compositions (e.g. nitrate/nitrite materials) in water samples and on solid substrates. In a water sample, ultraviolet light is applied to the sample so that dissolved nitro compositions therein will photolytically dissociate into gaseous nitrogen oxides (NO.sub.2(g) and/or NO.sub.(g)). A carrier gas is then introduced into the sample to generate a gaseous stream which includes the carrier gas combined with any gaseous nitrogen oxides. The carrier gas is thereafter directed into a detector. To detect nitro-compositions on solid substrates, ultraviolet light is applied thereto. A detector is then used to detect any gaseous nitrogen oxides which are photolytically generated during ultraviolet illumination. An optional carrier gas may be applied to the substrate during illumination to produce a gaseous stream which includes the carrier gas and any gaseous nitrogen oxides. The gaseous stream is then supplied to the detector.

Vitamin K

USDA-ARS?s Scientific Manuscript database

A wide range of analytical techniques are available for the detection, quantitation, and evaluation of vitamin K in foods. The methods vary from simple to complex depending on extraction, separation, identification and detection of the analyte. Among the extraction methods applied for vitamin K anal...

Potential of DNA barcoding for detecting quarantine fungi.

PubMed

Gao, Ruifang; Zhang, Guiming

2013-11-01

The detection of live quarantine pathogenic fungi plays an important role in guaranteeing regional biological safety. DNA barcoding, an emerging species identification technology, holds promise for the reliable, quick, and accurate detection of quarantine fungi. International standards for phytosanitary guidelines are urgently needed. The varieties of quarantine fungi listed for seven countries/regions, the currently applied detection methods, and the status of DNA barcoding for detecting quarantine fungi are summarized in this study. Two approaches have been proposed to apply DNA barcoding to fungal quarantine procedures: (i) to verify the reliability of known internal transcribed spacer (ITS)/cytochrome c oxidase subunit I (COI) data for use as barcodes, and (ii) to determine other barcodes for species that cannot be identified by ITS/COI. As a unique, standardizable, and universal species identification tool, DNA barcoding offers great potential for integrating detection methods used in various countries/regions and establishing international detection standards based on accepted DNA barcodes. Through international collaboration, interstate disputes can be eased and many problems related to routine quarantine detection methods can be solved for global trade.

[Development of selective determination methods for quinones with fluorescence and chemiluminescence detection and their application to environmental and biological samples].

PubMed

Kishikawa, Naoya

2010-10-01

Quinones are compounds that have various characteristics such as a biological electron transporter, an industrial product and a harmful environmental pollutant. Therefore, an effective determination method for quinones is required in many fields. This review describes the development of sensitive and selective determination methods for quinones based on some detection principles and their application to analyses in environmental, pharmaceutical and biological samples. Firstly, a fluorescence method was developed based on fluorogenic derivatization of quinones and applied to environmental analysis. Secondly, a luminol chemiluminescence method was developed based on generation of reactive oxygen species through the redox cycle of quinone and applied to pharmaceutical analysis. Thirdly, a photo-induced chemiluminescence method was developed based on formation of reactive oxygen species and fluorophore or chemiluminescence enhancer by the photoreaction of quinones and applied to biological and environmental analyses.

A method for detecting nonlinear determinism in normal and epileptic brain EEG signals.

PubMed

Meghdadi, Amir H; Fazel-Rezai, Reza; Aghakhani, Yahya

2007-01-01

A robust method of detecting determinism for short time series is proposed and applied to both healthy and epileptic EEG signals. The method provides a robust measure of determinism through characterizing the trajectories of the signal components which are obtained through singular value decomposition. Robustness of the method is shown by calculating proposed index of determinism at different levels of white and colored noise added to a simulated chaotic signal. The method is shown to be able to detect determinism at considerably high levels of additive noise. The method is then applied to both intracranial and scalp EEG recordings collected in different data sets for healthy and epileptic brain signals. The results show that for all of the studied EEG data sets there is enough evidence of determinism. The determinism is more significant for intracranial EEG recordings particularly during seizure activity.

Using Policy-Capturing to Measure Attitudes in Organizational Diagnosis.

ERIC Educational Resources Information Center

Madden, Joseph M.

1981-01-01

Discusses an indirect method of attitude measurement, policy-capturing, that can be applied on an individual basis. In three experiments this method detected prejudicial attitudes toward females not detected with traditional methods. Can be used as a self-improvement diagnostic tool for developing awareness of behavior influences. (JAC)

Nuclear Power Plant Thermocouple Sensor-Fault Detection and Classification Using Deep Learning and Generalized Likelihood Ratio Test

NASA Astrophysics Data System (ADS)

Mandal, Shyamapada; Santhi, B.; Sridhar, S.; Vinolia, K.; Swaminathan, P.

2017-06-01

In this paper, an online fault detection and classification method is proposed for thermocouples used in nuclear power plants. In the proposed method, the fault data are detected by the classification method, which classifies the fault data from the normal data. Deep belief network (DBN), a technique for deep learning, is applied to classify the fault data. The DBN has a multilayer feature extraction scheme, which is highly sensitive to a small variation of data. Since the classification method is unable to detect the faulty sensor; therefore, a technique is proposed to identify the faulty sensor from the fault data. Finally, the composite statistical hypothesis test, namely generalized likelihood ratio test, is applied to compute the fault pattern of the faulty sensor signal based on the magnitude of the fault. The performance of the proposed method is validated by field data obtained from thermocouple sensors of the fast breeder test reactor.

Geophysical techniques in detection to river embankments - A case study: To locate sites of potential leaks using surface-wave and electrical methods

USGS Publications Warehouse

Chen, C.; Liu, J.; Xu, S.; Xia, J.; ,

2004-01-01

Geophysical technologies are very effective in environmental, engineering and groundwater applications. Parameters of delineating nature of near-surface materials such as compressional-wave velocity, shear-wave velocity can be obtained using shallow seismic methods. Electric methods are primary approaches for investigating groundwater and detecting leakage. Both of methods are applied to detect embankment in hope of obtaining evidences of the strength and moisture inside the body. A technological experiment has done for detecting and discovering the hidden troubles in the embankment of Yangtze River, Songzi, Hubei, China in 2003. Surface-wave and DC multi-channel array resistivity sounding techniques were used to detect hidden trouble inside and under dike like pipe-seeps. This paper discusses the exploration strategy and the effect of geological characteristics. A practical approach of combining seismic and electric resistivity measurements was applied to locate potential pipe-seeps in embankment in the experiment. The method presents a potential leak factor based on the shear-wave velocity and the resistivity of the medium to evaluate anomalies. An anomaly found in a segment of embankment detected was verified, where occurred a pipe-seep during the 98' flooding.

Optical detection of random features for high security applications

NASA Astrophysics Data System (ADS)

Haist, T.; Tiziani, H. J.

1998-02-01

Optical detection of random features in combination with digital signatures based on public key codes in order to recognize counterfeit objects will be discussed. Without applying expensive production techniques objects are protected against counterfeiting. Verification is done off-line by optical means without a central authority. The method is applied for protecting banknotes. Experimental results for this application are presented. The method is also applicable for identity verification of a credit- or chip-card holder.

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

PubMed

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

2009-02-02

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

[Detecting fire smoke based on the multispectral image].

PubMed

Wei, Ying-Zhuo; Zhang, Shao-Wu; Liu, Yan-Wei

2010-04-01

Smoke detection is very important for preventing forest-fire in the fire early process. Because the traditional technologies based on video and image processing are easily affected by the background dynamic information, three limitations exist in these technologies, i. e. lower anti-interference ability, higher false detection rate and the fire smoke and water fog being not easily distinguished. A novel detection method for detecting smoke based on the multispectral image was proposed in the present paper. Using the multispectral digital imaging technique, the multispectral image series of fire smoke and water fog were obtained in the band scope of 400 to 720 nm, and the images were divided into bins. The Euclidian distance among the bins was taken as a measurement for showing the difference of spectrogram. After obtaining the spectral feature vectors of dynamic region, the regions of fire smoke and water fog were extracted according to the spectrogram feature difference between target and background. The indoor and outdoor experiments show that the smoke detection method based on multispectral image can be applied to the smoke detection, which can effectively distinguish the fire smoke and water fog. Combined with video image processing method, the multispectral image detection method can also be applied to the forest fire surveillance, reducing the false alarm rate in forest fire detection.

Crop Row Detection in Maize Fields Inspired on the Human Visual Perception

PubMed Central

Romeo, J.; Pajares, G.; Montalvo, M.; Guerrero, J. M.; Guijarro, M.; Ribeiro, A.

2012-01-01

This paper proposes a new method, oriented to image real-time processing, for identifying crop rows in maize fields in the images. The vision system is designed to be installed onboard a mobile agricultural vehicle, that is, submitted to gyros, vibrations, and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of two main processes: image segmentation and crop row detection. The first one applies a threshold to separate green plants or pixels (crops and weeds) from the rest (soil, stones, and others). It is based on a fuzzy clustering process, which allows obtaining the threshold to be applied during the normal operation process. The crop row detection applies a method based on image perspective projection that searches for maximum accumulation of segmented green pixels along straight alignments. They determine the expected crop lines in the images. The method is robust enough to work under the above-mentioned undesired effects. It is favorably compared against the well-tested Hough transformation for line detection. PMID:22623899

An affordable and easy-to-use diagnostic method for keratoconus detection using a smartphone

NASA Astrophysics Data System (ADS)

Askarian, Behnam; Tabei, Fatemehsadat; Askarian, Amin; Chong, Jo Woon

2018-02-01

Recently, smartphones are used for disease diagnosis and healthcare. In this paper, we propose a novel affordable diagnostic method of detecting keratoconus using a smartphone. Keratoconus is usually detected in clinics with ophthalmic devices, which are large, expensive and not portable, and need to be operated by trained technicians. However, our proposed smartphone-based eye disease detection method is small, affordable, portable, and it can be operated by patients in a convenient way. The results show that the proposed keratoconus detection method detects severe, advanced, and moderate keratoconus with accuracies of 93%, 86%, 67%, respectively. Due to its convenience with these accuracies, the proposed keratoconus detection method is expected to be applied in detecting keratoconus at an earlier stage in an affordable way.

Text Line Detection from Rectangle Traffic Panels of Natural Scene

NASA Astrophysics Data System (ADS)

Wang, Shiyuan; Huang, Linlin; Hu, Jian

2018-01-01

Traffic sign detection and recognition is very important for Intelligent Transportation. Among traffic signs, traffic panel contains rich information. However, due to low resolution and blur in the rectangular traffic panel, it is difficult to extract the character and symbols. In this paper, we propose a coarse-to-fine method to detect the Chinese character on traffic panels from natural scenes. Given a traffic panel Color Quantization is applied to extract candidate regions of Chinese characters. Second, a multi-stage filter based on learning is applied to discard the non-character regions. Third, we aggregate the characters for text lines by Distance Metric Learning method. Experimental results on real traffic images from Baidu Street View demonstrate the effectiveness of the proposed method.

The detection of local irreversibility in time series based on segmentation

NASA Astrophysics Data System (ADS)

Teng, Yue; Shang, Pengjian

2018-06-01

We propose a strategy for the detection of local irreversibility in stationary time series based on multiple scale. The detection is beneficial to evaluate the displacement of irreversibility toward local skewness. By means of this method, we can availably discuss the local irreversible fluctuations of time series as the scale changes. The method was applied to simulated nonlinear signals generated by the ARFIMA process and logistic map to show how the irreversibility functions react to the increasing of the multiple scale. The method was applied also to series of financial markets i.e., American, Chinese and European markets. The local irreversibility for different markets demonstrate distinct characteristics. Simulations and real data support the need of exploring local irreversibility.

Development and evaluation of modified envelope correlation method for deep tectonic tremor

NASA Astrophysics Data System (ADS)

Mizuno, N.; Ide, S.

2017-12-01

We develop a new location method for deep tectonic tremors, as an improvement of widely used envelope correlation method, and applied it to construct a tremor catalog in western Japan. Using the cross-correlation functions as objective functions and weighting components of data by the inverse of error variances, the envelope cross-correlation method is redefined as a maximum likelihood method. This method is also capable of multiple source detection, because when several events occur almost simultaneously, they appear as local maxima of likelihood.The average of weighted cross-correlation functions, defined as ACC, is a nonlinear function whose variable is a position of deep tectonic tremor. The optimization method has two steps. First, we fix the source depth to 30 km and use a grid search with 0.2 degree intervals to find the maxima of ACC, which are candidate event locations. Then, using each of the candidate locations as initial values, we apply a gradient method to determine horizontal and vertical components of a hypocenter. Sometimes, several source locations are determined in a time window of 5 minutes. We estimate the resolution, which is defined as a distance of sources to be detected separately by the location method, is about 100 km. The validity of this estimation is confirmed by a numerical test using synthetic waveforms. Applying to continuous seismograms in western Japan for over 10 years, the new method detected 27% more tremors than a previous method, owing to the multiple detection and improvement of accuracy by appropriate weighting scheme.

Recent developments in optical detection methods for microchip separations.

PubMed

Götz, Sebastian; Karst, Uwe

2007-01-01

This paper summarizes the features and performances of optical detection systems currently applied in order to monitor separations on microchip devices. Fluorescence detection, which delivers very high sensitivity and selectivity, is still the most widely applied method of detection. Instruments utilizing laser-induced fluorescence (LIF) and lamp-based fluorescence along with recent applications of light-emitting diodes (LED) as excitation sources are also covered in this paper. Since chemiluminescence detection can be achieved using extremely simple devices which no longer require light sources and optical components for focusing and collimation, interesting approaches based on this technique are presented, too. Although UV/vis absorbance is a detection method that is commonly used in standard desktop electrophoresis and liquid chromatography instruments, it has not yet reached the same level of popularity for microchip applications. Current applications of UV/vis absorbance detection to microchip separations and innovative approaches that increase sensitivity are described. This article, which contains 85 references, focuses on developments and applications published within the last three years, points out exciting new approaches, and provides future perspectives on this field.

GPS/DR Error Estimation for Autonomous Vehicle Localization.

PubMed

Lee, Byung-Hyun; Song, Jong-Hwa; Im, Jun-Hyuck; Im, Sung-Hyuck; Heo, Moon-Beom; Jee, Gyu-In

2015-08-21

Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level.

GPS/DR Error Estimation for Autonomous Vehicle Localization

PubMed Central

Lee, Byung-Hyun; Song, Jong-Hwa; Im, Jun-Hyuck; Im, Sung-Hyuck; Heo, Moon-Beom; Jee, Gyu-In

2015-01-01

Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level. PMID:26307997

Simultaneous Multi-band Detection of Low Surface Brightness Galaxies with Markovian Modeling

NASA Astrophysics Data System (ADS)

Vollmer, B.; Perret, B.; Petremand, M.; Lavigne, F.; Collet, Ch.; van Driel, W.; Bonnarel, F.; Louys, M.; Sabatini, S.; MacArthur, L. A.

2013-02-01

We present to the astronomical community an algorithm for the detection of low surface brightness (LSB) galaxies in images, called MARSIAA (MARkovian Software for Image Analysis in Astronomy), which is based on multi-scale Markovian modeling. MARSIAA can be applied simultaneously to different bands. It segments an image into a user-defined number of classes, according to their surface brightness and surroundings—typically, one or two classes contain the LSB structures. We have developed an algorithm, called DetectLSB, which allows the efficient identification of LSB galaxies from among the candidate sources selected by MARSIAA. The application of the method to two and three bands simultaneously was tested on simulated images. Based on our tests, we are confident that we can detect LSB galaxies down to a central surface brightness level of only 1.5 times the standard deviation from the mean pixel value in the image background. To assess the robustness of our method, the method was applied to a set of 18 B- and I-band images (covering 1.3 deg2 in total) of the Virgo Cluster to which Sabatini et al. previously applied a matched-filter dwarf LSB galaxy search algorithm. We have detected all 20 objects from the Sabatini et al. catalog which we could classify by eye as bona fide LSB galaxies. Our method has also detected four additional Virgo Cluster LSB galaxy candidates undetected by Sabatini et al. To further assess the completeness of the results of our method, both MARSIAA, SExtractor, and DetectLSB were applied to search for (1) mock Virgo LSB galaxies inserted into a set of deep Next Generation Virgo Survey (NGVS) gri-band subimages and (2) Virgo LSB galaxies identified by eye in a full set of NGVS square degree gri images. MARSIAA/DetectLSB recovered ~20% more mock LSB galaxies and ~40% more LSB galaxies identified by eye than SExtractor/DetectLSB. With a 90% fraction of false positives from an entirely unsupervised pipeline, a completeness of 90% is reached for sources with r e > 3'' at a mean surface brightness level of μg = 27.7 mag arcsec-2 and a central surface brightness of μ0 g = 26.7 mag arcsec-2. About 10% of the false positives are artifacts, the rest being background galaxies. We have found our proposed Markovian LSB galaxy detection method to be complementary to the application of matched filters and an optimized use of SExtractor, and to have the following advantages: it is scale free, can be applied simultaneously to several bands, and is well adapted for crowded regions on the sky. .

Evaluation of MTANNs for eliminating false-positive with different computer aided pulmonary nodules detection software.

PubMed

Shi, Zhenghao; Ma, Jiejue; Feng, Yaning; He, Lifeng; Suzuki, Kenji

2015-11-01

MTANN (Massive Training Artificial Neural Network) is a promising tool, which applied to eliminate false-positive for thoracic CT in recent years. In order to evaluate whether this method is feasible to eliminate false-positive of different CAD schemes, especially, when it is applied to commercial CAD software, this paper evaluate the performance of the method for eliminating false-positives produced by three different versions of commercial CAD software for lung nodules detection in chest radiographs. Experimental results demonstrate that the approach is useful in reducing FPs for different computer aided lung nodules detection software in chest radiographs.

Detection of Yersinia Enterocolitica Species in Pig Tonsils and Raw Pork Meat by the Real-Time Pcr and Culture Methods.

PubMed

Stachelska, M A

2017-09-26

The aim of the present study was to establish a rapid and accurate real-time PCR method to detect pathogenic Yersinia enterocolitica in pork. Yersinia enterocolitica is considered to be a crucial zoonosis, which can provoke diseases both in humans and animals. The classical culture methods designated to detect Y. enterocolitica species in food matrices are often very time-consuming. The chromosomal locus _tag CH49_3099 gene, that appears in pathogenic Y. enterocolitica strains, was applied as DNA target for the 5' nuclease PCR protocol. The probe was labelled at the 5' end with the fluorescent reporter dye (FAM) and at the 3' end with the quencher dye (TAMRA). The real-time PCR cycling parameters included 41 cycles. A Ct value which reached a value higher than 40 constituted a negative result. The developed for the needs of this study qualitative real-time PCR method appeared to give very specific and reliable results. The detection rate of locus _tag CH49_3099 - positive Y. enterocolitica in 150 pig tonsils was 85 % and 32 % with PCR and culture methods, respectively. Both the Real-time PCR results and culture method results were obtained from material that was enriched during overnight incubation. The subject of the study were also raw pork meat samples. Among 80 samples examined, 7 ones were positive when real-time PCR was applied, and 6 ones were positive when classical culture method was applied. The application of molecular techniques based on the analysis of DNA sequences such as the Real-time PCR enables to detect this pathogenic bacteria very rapidly and with higher specificity, sensitivity and reliability in comparison to classical culture methods.

Comparison of two filtration-elution procedures to improve the standard methods ISO 10705-1 & 2 for bacteriophage detection in groundwater, surface water and finished water samples.

PubMed

Helmi, K; Jacob, P; Charni-Ben-Tabassi, N; Delabre, K; Arnal, C

2011-09-01

To select a reliable method for bacteriophage concentration prior detection by culture from surface water, groundwater and drinking water to enhance the sensitivity of the standard methods ISO 10705-1 & 2. Artificially contaminated (groundwater and drinking water) and naturally contaminated (surface water) 1-litre samples were processed for bacteriophages detection. The spiked samples were inoculated with about 150 PFU of F-specific RNA bacteriophages and somatic coliphages using wastewater. Bacteriophage detection in the water samples was achieved using the standard method without and with a concentration step (electropositive Anodisc membrane or a pretreated electronegative Micro Filtration membrane, MF). For artificially contaminated matrices (drinking and ground waters), recovery rates using the concentration step were superior to 70% whilst analyses without concentration step mainly led to false negative results. Besides, the MF membrane presented higher performances compared with the Anodisc membrane. The concentration of a large volume of water (up to one litre) on a filter membrane avoids false negative results obtained by direct analysis as it allows detecting low number of bacteriophages in water samples. The addition of concentration step before applying the standard method could be useful to enhance the reliability of bacteriophages monitoring in water samples as bio-indicators to highlight faecal pollution. © No claim to French Government works. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.

A hybrid symplectic principal component analysis and central tendency measure method for detection of determinism in noisy time series with application to mechanomyography

NASA Astrophysics Data System (ADS)

Xie, Hong-Bo; Dokos, Socrates

2013-06-01

We present a hybrid symplectic geometry and central tendency measure (CTM) method for detection of determinism in noisy time series. CTM is effective for detecting determinism in short time series and has been applied in many areas of nonlinear analysis. However, its performance significantly degrades in the presence of strong noise. In order to circumvent this difficulty, we propose to use symplectic principal component analysis (SPCA), a new chaotic signal de-noising method, as the first step to recover the system dynamics. CTM is then applied to determine whether the time series arises from a stochastic process or has a deterministic component. Results from numerical experiments, ranging from six benchmark deterministic models to 1/f noise, suggest that the hybrid method can significantly improve detection of determinism in noisy time series by about 20 dB when the data are contaminated by Gaussian noise. Furthermore, we apply our algorithm to study the mechanomyographic (MMG) signals arising from contraction of human skeletal muscle. Results obtained from the hybrid symplectic principal component analysis and central tendency measure demonstrate that the skeletal muscle motor unit dynamics can indeed be deterministic, in agreement with previous studies. However, the conventional CTM method was not able to definitely detect the underlying deterministic dynamics. This result on MMG signal analysis is helpful in understanding neuromuscular control mechanisms and developing MMG-based engineering control applications.

A hybrid symplectic principal component analysis and central tendency measure method for detection of determinism in noisy time series with application to mechanomyography.

PubMed

Xie, Hong-Bo; Dokos, Socrates

2013-06-01

We present a hybrid symplectic geometry and central tendency measure (CTM) method for detection of determinism in noisy time series. CTM is effective for detecting determinism in short time series and has been applied in many areas of nonlinear analysis. However, its performance significantly degrades in the presence of strong noise. In order to circumvent this difficulty, we propose to use symplectic principal component analysis (SPCA), a new chaotic signal de-noising method, as the first step to recover the system dynamics. CTM is then applied to determine whether the time series arises from a stochastic process or has a deterministic component. Results from numerical experiments, ranging from six benchmark deterministic models to 1/f noise, suggest that the hybrid method can significantly improve detection of determinism in noisy time series by about 20 dB when the data are contaminated by Gaussian noise. Furthermore, we apply our algorithm to study the mechanomyographic (MMG) signals arising from contraction of human skeletal muscle. Results obtained from the hybrid symplectic principal component analysis and central tendency measure demonstrate that the skeletal muscle motor unit dynamics can indeed be deterministic, in agreement with previous studies. However, the conventional CTM method was not able to definitely detect the underlying deterministic dynamics. This result on MMG signal analysis is helpful in understanding neuromuscular control mechanisms and developing MMG-based engineering control applications.

Early warning by near-real time disturbance monitoring (Invited)

NASA Astrophysics Data System (ADS)

Verbesselt, J.; Zeileis, A.; Herold, M.

2013-12-01

Near real-time monitoring of ecosystem disturbances is critical for rapidly assessing and addressing impacts on carbon dynamics, biodiversity, and socio-ecological processes. Satellite remote sensing enables cost-effective and accurate monitoring at frequent time steps over large areas. Yet, generic methods to detect disturbances within newly captured satellite images are lacking. We propose a multi-purpose time-series-based disturbance detection approach that identifies and models stable historical variation to enable change detection within newly acquired data. Satellite image time series of vegetation greenness provide a global record of terrestrial vegetation productivity over the past decades. Here, we assess and demonstrate the method by applying it to (1) real-world satellite greenness image time series between February 2000 and July 2011 covering Somalia to detect drought-related vegetation disturbances (2) landsat image time series to detect forest disturbances. First, results illustrate that disturbances are successfully detected in near real-time while being robust to seasonality and noise. Second, major drought-related disturbance corresponding with most drought-stressed regions in Somalia are detected from mid-2010 onwards. Third, the method can be applied to landsat image time series having a lower temporal data density. Furthermore the method can analyze in-situ or satellite data time series of biophysical indicators from local to global scale since it is fast, does not depend on thresholds and does not require time series gap filling. While the data and methods used are appropriate for proof-of-concept development of global scale disturbance monitoring, specific applications (e.g., drought or deforestation monitoring) mandates integration within an operational monitoring framework. Furthermore, the real-time monitoring method is implemented in open-source environment and is freely available in the BFAST package for R software. Information illustrating how to apply the method on satellite image time series are available at http://bfast.R-Forge.R-project.org/ and the example section of the bfastmonitor() function within the BFAST package.

Robust Observation Detection for Single Object Tracking: Deterministic and Probabilistic Patch-Based Approaches

PubMed Central

Zulkifley, Mohd Asyraf; Rawlinson, David; Moran, Bill

2012-01-01

In video analytics, robust observation detection is very important as the content of the videos varies a lot, especially for tracking implementation. Contrary to the image processing field, the problems of blurring, moderate deformation, low illumination surroundings, illumination change and homogenous texture are normally encountered in video analytics. Patch-Based Observation Detection (PBOD) is developed to improve detection robustness to complex scenes by fusing both feature- and template-based recognition methods. While we believe that feature-based detectors are more distinctive, however, for finding the matching between the frames are best achieved by a collection of points as in template-based detectors. Two methods of PBOD—the deterministic and probabilistic approaches—have been tested to find the best mode of detection. Both algorithms start by building comparison vectors at each detected points of interest. The vectors are matched to build candidate patches based on their respective coordination. For the deterministic method, patch matching is done in 2-level test where threshold-based position and size smoothing are applied to the patch with the highest correlation value. For the second approach, patch matching is done probabilistically by modelling the histograms of the patches by Poisson distributions for both RGB and HSV colour models. Then, maximum likelihood is applied for position smoothing while a Bayesian approach is applied for size smoothing. The result showed that probabilistic PBOD outperforms the deterministic approach with average distance error of 10.03% compared with 21.03%. This algorithm is best implemented as a complement to other simpler detection methods due to heavy processing requirement. PMID:23202226

Detection of hidden explosives in different scenarios with the use of nuclear probes

NASA Astrophysics Data System (ADS)

Nebbia, G.; Pesente, S.; Lunardon, M.; Moretto, S.; Viesti, G.; Cinausero, M.; Barbui, M.; Fioretto, E.; Filippini, V.; Sudac, D.; Nađ, K.; Blagus, S.; Valković, V.

2005-04-01

The detection of landmines by using available technologies is a time consuming, expensive and extremely dangerous job, so that there is a need for a technological breakthrough in this field. Atomic and nuclear physics based sensors might offer new possibilities in de-mining. Technology and methods derived from the studies applied to the detection of landmines can be successfully applied to the screening of cargo in customs inspections.

a Comparison of Empirical and Inteligent Methods for Dust Detection Using Modis Satellite Data

NASA Astrophysics Data System (ADS)

Shahrisvand, M.; Akhoondzadeh, M.

2013-09-01

Nowadays, dust storm in one of the most important natural hazards which is considered as a national concern in scientific communities. This paper considers the capabilities of some classical and intelligent methods for dust detection from satellite imagery around the Middle East region. In the study of dust detection, MODIS images have been a good candidate due to their suitable spectral and temporal resolution. In this study, physical-based and intelligent methods including decision tree, ANN (Artificial Neural Network) and SVM (Support Vector Machine) have been applied to detect dust storms. Among the mentioned approaches, in this paper, SVM method has been implemented for the first time in domain of dust detection studies. Finally, AOD (Aerosol Optical Depth) images, which are one the referenced standard products of OMI (Ozone Monitoring Instrument) sensor, have been used to assess the accuracy of all the implemented methods. Since the SVM method can distinguish dust storm over lands and oceans simultaneously, therefore the accuracy of SVM method is achieved better than the other applied approaches. As a conclusion, this paper shows that SVM can be a powerful tool for production of dust images with remarkable accuracy in comparison with AOT (Aerosol Optical Thickness) product of NASA.

A line transect model for aerial surveys

USGS Publications Warehouse

Quang, Pham Xuan; Lanctot, Richard B.

1991-01-01

We employ a line transect method to estimate the density of the common and Pacific loon in the Yukon Flats National Wildlife Refuge from aerial survey data. Line transect methods have the advantage of automatically taking into account “visibility bias” due to detectability difference of animals at different distances from the transect line. However, line transect methods must overcome two difficulties when applied to inaccurate recording of sighting distances due to high travel speeds, so that in fact only a few reliable distance class counts are available. We propose a unimodal detection function that provides an estimate of the effective area lost due to the blind strip, under the assumption that a line of perfect detection exists parallel to the transect line. The unimodal detection function can also be applied when a blind strip is absent, and in certain instances when the maximum probability of detection is less than 100%. A simple bootstrap procedure to estimate standard error is illustrated. Finally, we present results from a small set of Monte Carlo experiments.

Signal Amplification by Glyco-qPCR for Ultrasensitive Detection of Carbohydrates: Applications in Glycobiology**

PubMed Central

Kwon, Seok Joon; Lee, Kyung Bok; Solakyildirim, Kemal; Masuko, Sayaka; Ly, Mellisa; Zhang, Fuming; Li, Lingyun; Dordick, Jonathan S.; Linhardt, Robert J.

2012-01-01

Tiny amounts of carbohydrates (ca. 1 zmol) can be detected quantitatively by a real-time method based on the conjugation of carbohydrates with DNA markers (see picture). The proposed method (glyco-qPCR) provides uniform, ultrasensitive detection of carbohydrates, which can be applied to glycobiology, as well as carbohydrate-based drug discovery. PMID:23073897

A multiscale method for a robust detection of the default mode network

NASA Astrophysics Data System (ADS)

Baquero, Katherine; Gómez, Francisco; Cifuentes, Christian; Guldenmund, Pieter; Demertzi, Athena; Vanhaudenhuyse, Audrey; Gosseries, Olivia; Tshibanda, Jean-Flory; Noirhomme, Quentin; Laureys, Steven; Soddu, Andrea; Romero, Eduardo

2013-11-01

The Default Mode Network (DMN) is a resting state network widely used for the analysis and diagnosis of mental disorders. It is normally detected in fMRI data, but for its detection in data corrupted by motion artefacts or low neuronal activity, the use of a robust analysis method is mandatory. In fMRI it has been shown that the signal-to-noise ratio (SNR) and the detection sensitivity of neuronal regions is increased with di erent smoothing kernels sizes. Here we propose to use a multiscale decomposition based of a linear scale-space representation for the detection of the DMN. Three main points are proposed in this methodology: rst, the use of fMRI data at di erent smoothing scale-spaces, second, detection of independent neuronal components of the DMN at each scale by using standard preprocessing methods and ICA decomposition at scale-level, and nally, a weighted contribution of each scale by the Goodness of Fit measurement. This method was applied to a group of control subjects and was compared with a standard preprocesing baseline. The detection of the DMN was improved at single subject level and at group level. Based on these results, we suggest to use this methodology to enhance the detection of the DMN in data perturbed with artefacts or applied to subjects with low neuronal activity. Furthermore, the multiscale method could be extended for the detection of other resting state neuronal networks.

Ultraviolet resonance Raman spectroscopy for the detection of cocaine in oral fluid

NASA Astrophysics Data System (ADS)

D'Elia, Valentina; Montalvo, Gemma; Ruiz, Carmen García; Ermolenkov, Vladimir V.; Ahmed, Yasmine; Lednev, Igor K.

2018-01-01

Detecting and quantifying cocaine in oral fluid is of significant importance for practical forensics. Up to date, mainly destructive methods or biochemical tests have been used, while spectroscopic methods were only applied to pretreated samples. In this work, the possibility of using resonance Raman spectroscopy to detect cocaine in oral fluid without pretreating samples was tested. It was found that ultraviolet resonance Raman spectroscopy with 239-nm excitation allows for the detection of cocaine in oral fluid at 10 μg/mL level. Further method development will be needed for reaching the practically useful levels of cocaine detection.

Application of Terahertz Radiation to the Detection of Corrosion Under the Shuttle's Thermal Protection System

NASA Astrophysics Data System (ADS)

Madaras, Eric I.; Anastasi, Robert F.; Smith, Stephen W.; Seebo, Jeffrey P.; Walker, James L.; Lomness, Janice K.; Hintze, Paul E.; Kammerer, Catherine C.; Winfree, William P.; Russell, Richard W.

2008-02-01

There is currently no method for detecting corrosion under Shuttle tiles except for the expensive process of tile removal and replacement; hence NASA is investigating new NDE methods for detecting hidden corrosion. Time domain terahertz radiation has been applied to corrosion detection under tiles in samples ranging from small lab samples to a Shuttle with positive results. Terahertz imaging methods have been able to detect corrosion at thicknesses of 5 mils or greater under 1" thick Shuttle tiles and 7-12 mils or greater under 2" thick Shuttle tiles.

Detecting the sampling rate through observations

NASA Astrophysics Data System (ADS)

Shoji, Isao

2018-09-01

This paper proposes a method to detect the sampling rate of discrete time series of diffusion processes. Using the maximum likelihood estimates of the parameters of a diffusion process, we establish a criterion based on the Kullback-Leibler divergence and thereby estimate the sampling rate. Simulation studies are conducted to check whether the method can detect the sampling rates from data and their results show a good performance in the detection. In addition, the method is applied to a financial time series sampled on daily basis and shows the detected sampling rate is different from the conventional rates.

Application of Terahertz Radiation to the Detection of Corrosion under the Shuttle's Thermal Protection System

NASA Technical Reports Server (NTRS)

Madaras, Eric I.; Anastasi, Robert F.; Smith, Stephen W.; Seebo, Jeffrey P.; Walker, James L.; Lomness, Janice K.; Hintze, Paul E.; Kammerer, Catherine C.; Winfree, William P.; Russell, Richard W.

2007-01-01

There is currently no method for detecting corrosion under Shuttle tiles except for the expensive process of tile removal and replacement; hence NASA is investigating new NDE methods for detecting hidden corrosion. Time domain terahertz radiation has been applied to corrosion detection under tiles in samples ranging from small lab samples to a Shuttle with positive results. Terahertz imaging methods have been able to detect corrosion at thicknesses of 5 mils or greater under 1" thick Shuttle tiles and 7-12 mils or greater under 2" thick Shuttle tiles.

Edge Detection Method Based on Neural Networks for COMS MI Images

NASA Astrophysics Data System (ADS)

Lee, Jin-Ho; Park, Eun-Bin; Woo, Sun-Hee

2016-12-01

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

Ship Detection in Optical Satellite Image Based on RX Method and PCAnet

NASA Astrophysics Data System (ADS)

Shao, Xiu; Li, Huali; Lin, Hui; Kang, Xudong; Lu, Ting

2017-12-01

In this paper, we present a novel method for ship detection in optical satellite image based on the ReedXiaoli (RX) method and the principal component analysis network (PCAnet). The proposed method consists of the following three steps. First, the spatially adjacent pixels in optical image are arranged into a vector, transforming the optical image into a 3D cube image. By taking this process, the contextual information of the spatially adjacent pixels can be integrated to magnify the discrimination between ship and background. Second, the RX anomaly detection method is adopted to preliminarily extract ship candidates from the produced 3D cube image. Finally, real ships are further confirmed among ship candidates by applying the PCAnet and the support vector machine (SVM). Specifically, the PCAnet is a simple deep learning network which is exploited to perform feature extraction, and the SVM is applied to achieve feature pooling and decision making. Experimental results demonstrate that our approach is effective in discriminating between ships and false alarms, and has a good ship detection performance.

Improved wheal detection from skin prick test images

NASA Astrophysics Data System (ADS)

Bulan, Orhan

2014-03-01

Skin prick test is a commonly used method for diagnosis of allergic diseases (e.g., pollen allergy, food allergy, etc.) in allergy clinics. The results of this test are erythema and wheal provoked on the skin where the test is applied. The sensitivity of the patient against a specific allergen is determined by the physical size of the wheal, which can be estimated from images captured by digital cameras. Accurate wheal detection from these images is an important step for precise estimation of wheal size. In this paper, we propose a method for improved wheal detection on prick test images captured by digital cameras. Our method operates by first localizing the test region by detecting calibration marks drawn on the skin. The luminance variation across the localized region is eliminated by applying a color transformation from RGB to YCbCr and discarding the luminance channel. We enhance the contrast of the captured images for the purpose of wheal detection by performing principal component analysis on the blue-difference (Cb) and red-difference (Cr) color channels. We finally, perform morphological operations on the contrast enhanced image to detect the wheal on the image plane. Our experiments performed on images acquired from 36 different patients show the efficiency of the proposed method for wheal detection from skin prick test images captured in an uncontrolled environment.

Method for remote detection of trace contaminants

DOEpatents

Simonson, Robert J.; Hance, Bradley G.

2003-09-09

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

75 FR 76742 - Detecting Oil Leaks From Vessels Into the Water

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-09

... to detect leaks from oil tanks into the water? (E) What is the threshold for detection, accuracy... than leak detection from oil cargo tanks into the water? (H) Are methods or equipment being applied for... DEPARTMENT OF HOMELAND SECURITY Coast Guard [Docket No. USCG-2010-1085] Detecting Oil Leaks From...

RETROSPECTIVE DETECTION OF INTERLEAVED SLICE ACQUISITION PARAMETERS FROM FMRI DATA

PubMed Central

Parker, David; Rotival, Georges; Laine, Andrew; Razlighi, Qolamreza R.

2015-01-01

To minimize slice excitation leakage to adjacent slices, interleaved slice acquisition is nowadays performed regularly in fMRI scanners. In interleaved slice acquisition, the number of slices skipped between two consecutive slice acquisitions is often referred to as the ‘interleave parameter’; the loss of this parameter can be catastrophic for the analysis of fMRI data. In this article we present a method to retrospectively detect the interleave parameter and the axis in which it is applied. Our method relies on the smoothness of the temporal-distance correlation function, which becomes disrupted along the axis on which interleaved slice acquisition is applied. We examined this method on simulated and real data in the presence of fMRI artifacts such as physiological noise, motion, etc. We also examined the reliability of this method in detecting different types of interleave parameters and demonstrated an accuracy of about 94% in more than 1000 real fMRI scans. PMID:26161244

Spectral analysis method for detecting an element

DOEpatents

Blackwood, Larry G [Idaho Falls, ID; Edwards, Andrew J [Idaho Falls, ID; Jewell, James K [Idaho Falls, ID; Reber, Edward L [Idaho Falls, ID; Seabury, Edward H [Idaho Falls, ID

2008-02-12

A method for detecting an element is described and which includes the steps of providing a gamma-ray spectrum which has a region of interest which corresponds with a small amount of an element to be detected; providing nonparametric assumptions about a shape of the gamma-ray spectrum in the region of interest, and which would indicate the presence of the element to be detected; and applying a statistical test to the shape of the gamma-ray spectrum based upon the nonparametric assumptions to detect the small amount of the element to be detected.

Weak photoacoustic signal detection based on the differential duffing oscillator

NASA Astrophysics Data System (ADS)

Li, Chenjing; Xu, Xuemei; Ding, Yipeng; Yin, Linzi; Dou, Beibei

2018-04-01

In view of photoacoustic spectroscopy theory, the relationship between weak photoacoustic signal and gas concentration is described. The studies, on the principle of Duffing oscillator for identifying state transition as well as determining the threshold value, have proven the feasibility of applying the Duffing oscillator in weak signal detection. An improved differential Duffing oscillator is proposed to identify weak signals with any frequency and ameliorate the signal-to-noise ratio. The analytical methods and numerical experiments of the novel model are introduced in detail to confirm its superiority. Then the signal detection system of weak photoacoustic based on differential Duffing oscillator is constructed, it is the first time that the weak signal detection method with differential Duffing oscillator is applied triumphantly in photoacoustic spectroscopy gas monitoring technology.

Use of the Box-Cox Transformation in Detecting Changepoints in Daily Precipitation Data Series

NASA Astrophysics Data System (ADS)

Wang, X. L.; Chen, H.; Wu, Y.; Pu, Q.

2009-04-01

This study integrates a Box-Cox power transformation procedure into two statistical tests for detecting changepoints in Gaussian data series, to make the changepoint detection methods applicable to non-Gaussian data series, such as daily precipitation amounts. The detection power aspects of transformed methods in a common trend two-phase regression setting are assessed by Monte Carlo simulations for data of a log-normal or Gamma distribution. The results show that the transformed methods have increased the power of detection, in comparison with the corresponding original (untransformed) methods. The transformed data much better approximate to a Gaussian distribution. As an example of application, the new methods are applied to a series of daily precipitation amounts recorded at a station in Canada, showing satisfactory detection power.

Spatial scan statistics for detection of multiple clusters with arbitrary shapes.

PubMed

Lin, Pei-Sheng; Kung, Yi-Hung; Clayton, Murray

2016-12-01

In applying scan statistics for public health research, it would be valuable to develop a detection method for multiple clusters that accommodates spatial correlation and covariate effects in an integrated model. In this article, we connect the concepts of the likelihood ratio (LR) scan statistic and the quasi-likelihood (QL) scan statistic to provide a series of detection procedures sufficiently flexible to apply to clusters of arbitrary shape. First, we use an independent scan model for detection of clusters and then a variogram tool to examine the existence of spatial correlation and regional variation based on residuals of the independent scan model. When the estimate of regional variation is significantly different from zero, a mixed QL estimating equation is developed to estimate coefficients of geographic clusters and covariates. We use the Benjamini-Hochberg procedure (1995) to find a threshold for p-values to address the multiple testing problem. A quasi-deviance criterion is used to regroup the estimated clusters to find geographic clusters with arbitrary shapes. We conduct simulations to compare the performance of the proposed method with other scan statistics. For illustration, the method is applied to enterovirus data from Taiwan. © 2016, The International Biometric Society.

Ground-based measurements of ionospheric dynamics

NASA Astrophysics Data System (ADS)

Kouba, Daniel; Chum, Jaroslav

2018-05-01

Different methods are used to research and monitor the ionospheric dynamics using ground measurements: Digisonde Drift Measurements (DDM) and Continuous Doppler Sounding (CDS). For the first time, we present comparison between both methods on specific examples. Both methods provide information about the vertical drift velocity component. The DDM provides more information about the drift velocity vector and detected reflection points. However, the method is limited by the relatively low time resolution. In contrast, the strength of CDS is its high time resolution. The discussed methods can be used for real-time monitoring of medium scale travelling ionospheric disturbances. We conclude that it is advantageous to use both methods simultaneously if possible. The CDS is then applied for the disturbance detection and analysis, and the DDM is applied for the reflection height control.

Theory of chromatic noise masking applied to testing linearity of S-cone detection mechanisms.

PubMed

Giulianini, Franco; Eskew, Rhea T

2007-09-01

A method for testing the linearity of cone combination of chromatic detection mechanisms is applied to S-cone detection. This approach uses the concept of mechanism noise, the noise as seen by a postreceptoral neural mechanism, to represent the effects of superposing chromatic noise components in elevating thresholds and leads to a parameter-free prediction for a linear mechanism. The method also provides a test for the presence of multiple linear detectors and off-axis looking. No evidence for multiple linear mechanisms was found when using either S-cone increment or decrement tests. The results for both S-cone test polarities demonstrate that these mechanisms combine their cone inputs nonlinearly.

Design of a Multi-Sensor Cooperation Travel Environment Perception System for Autonomous Vehicle

PubMed Central

Chen, Long; Li, Qingquan; Li, Ming; Zhang, Liang; Mao, Qingzhou

2012-01-01

This paper describes the environment perception system designed for intelligent vehicle SmartV-II, which won the 2010 Future Challenge. This system utilizes the cooperation of multiple lasers and cameras to realize several necessary functions of autonomous navigation: road curb detection, lane detection and traffic sign recognition. Multiple single scan lasers are integrated to detect the road curb based on Z-variance method. Vision based lane detection is realized by two scans method combining with image model. Haar-like feature based method is applied for traffic sign detection and SURF matching method is used for sign classification. The results of experiments validate the effectiveness of the proposed algorithms and the whole system.

Unsupervised change detection in a particular vegetation land cover type using spectral angle mapper

NASA Astrophysics Data System (ADS)

Renza, Diego; Martinez, Estibaliz; Molina, Iñigo; Ballesteros L., Dora M.

2017-04-01

This paper presents a new unsupervised change detection methodology for multispectral images applied to specific land covers. The proposed method involves comparing each image against a reference spectrum, where the reference spectrum is obtained from the spectral signature of the type of coverage you want to detect. In this case the method has been tested using multispectral images (SPOT5) of the community of Madrid (Spain), and multispectral images (Quickbird) of an area over Indonesia that was impacted by the December 26, 2004 tsunami; here, the tests have focused on the detection of changes in vegetation. The image comparison is obtained by applying Spectral Angle Mapper between the reference spectrum and each multitemporal image. Then, a threshold to produce a single image of change is applied, which corresponds to the vegetation zones. The results for each multitemporal image are combined through an exclusive or (XOR) operation that selects vegetation zones that have changed over time. Finally, the derived results were compared against a supervised method based on classification with the Support Vector Machine. Furthermore, the NDVI-differencing and the Spectral Angle Mapper techniques were selected as unsupervised methods for comparison purposes. The main novelty of the method consists in the detection of changes in a specific land cover type (vegetation), therefore, for comparison purposes, the best scenario is to compare it with methods that aim to detect changes in a specific land cover type (vegetation). This is the main reason to select NDVI-based method and the post-classification method (SVM implemented in a standard software tool). To evaluate the improvements using a reference spectrum vector, the results are compared with the basic-SAM method. In SPOT5 image, the overall accuracy was 99.36% and the κ index was 90.11%; in Quickbird image, the overall accuracy was 97.5% and the κ index was 82.16%. Finally, the precision results of the method are comparable to those of a supervised method, supported by low detection of false positives and false negatives, along with a high overall accuracy and a high kappa index. On the other hand, the execution times were comparable to those of unsupervised methods of low computational load.

Development of gas chromatographic methods for the analyses of organic carbonate-based electrolytes

NASA Astrophysics Data System (ADS)

Terborg, Lydia; Weber, Sascha; Passerini, Stefano; Winter, Martin; Karst, Uwe; Nowak, Sascha

2014-01-01

In this work, novel methods based on gas chromatography (GC) for the investigation of common organic carbonate-based electrolyte systems are presented, which are used in lithium ion batteries. The methods were developed for flame ionization detection (FID), mass spectrometric detection (MS). Further, headspace (HS) sampling for the investigation of solid samples like electrodes is reported. Limits of detection are reported for FID. Finally, the developed methods were applied to the electrolyte system of commercially available lithium ion batteries as well as on in-house assembled cells.

Validation of the Applied Biosystems RapidFinder Shiga Toxin-Producing E. coli (STEC) Detection Workflow.

PubMed

Cloke, Jonathan; Matheny, Sharon; Swimley, Michelle; Tebbs, Robert; Burrell, Angelia; Flannery, Jonathan; Bastin, Benjamin; Bird, Patrick; Benzinger, M Joseph; Crowley, Erin; Agin, James; Goins, David; Salfinger, Yvonne; Brodsky, Michael; Fernandez, Maria Cristina

2016-11-01

The Applied Biosystems™ RapidFinder™ STEC Detection Workflow (Thermo Fisher Scientific) is a complete protocol for the rapid qualitative detection of Escherichia coli (E. coli) O157:H7 and the "Big 6" non-O157 Shiga-like toxin-producing E. coli (STEC) serotypes (defined as serogroups: O26, O45, O103, O111, O121, and O145). The RapidFinder STEC Detection Workflow makes use of either the automated preparation of PCR-ready DNA using the Applied Biosystems PrepSEQ™ Nucleic Acid Extraction Kit in conjunction with the Applied Biosystems MagMAX™ Express 96-well magnetic particle processor or the Applied Biosystems PrepSEQ Rapid Spin kit for manual preparation of PCR-ready DNA. Two separate assays comprise the RapidFinder STEC Detection Workflow, the Applied Biosystems RapidFinder STEC Screening Assay and the Applied Biosystems RapidFinder STEC Confirmation Assay. The RapidFinder STEC Screening Assay includes primers and probes to detect the presence of stx1 (Shiga toxin 1), stx2 (Shiga toxin 2), eae (intimin), and E. coli O157 gene targets. The RapidFinder STEC Confirmation Assay includes primers and probes for the "Big 6" non-O157 STEC and E. coli O157:H7. The use of these two assays in tandem allows a user to detect accurately the presence of the "Big 6" STECs and E. coli O157:H7. The performance of the RapidFinder STEC Detection Workflow was evaluated in a method comparison study, in inclusivity and exclusivity studies, and in a robustness evaluation. The assays were compared to the U.S. Department of Agriculture (USDA), Food Safety and Inspection Service (FSIS) Microbiology Laboratory Guidebook (MLG) 5.09: Detection, Isolation and Identification of Escherichia coli O157:H7 from Meat Products and Carcass and Environmental Sponges for raw ground beef (73% lean) and USDA/FSIS-MLG 5B.05: Detection, Isolation and Identification of Escherichia coli non-O157:H7 from Meat Products and Carcass and Environmental Sponges for raw beef trim. No statistically significant differences were observed between the reference method and the individual or combined kits forming the candidate assay using either of the DNA preparation kits (manual or automated extraction). For the inclusivity and exclusivity evaluation, the RapidFinder STEC Detection Workflow, comprising both RapidFinder STEC screening and confirmation kits, correctly identified all 50 target organism isolates and correctly excluded all 30 nontarget strains for both of the assays evaluated. The results of these studies demonstrate the sensitivity and selectivity of the RapidFinder STEC Detection Workflow for the detection of E. coli O157:H7 and the "Big 6" STEC serotypes in both raw ground beef and beef trim. The robustness testing demonstrated that minor variations in the method parameters did not impact the accuracy of the assay and highlighted the importance of following the correct incubation temperatures.

HYPOTHESIS SETTING AND ORDER STATISTIC FOR ROBUST GENOMIC META-ANALYSIS.

PubMed

Song, Chi; Tseng, George C

2014-01-01

Meta-analysis techniques have been widely developed and applied in genomic applications, especially for combining multiple transcriptomic studies. In this paper, we propose an order statistic of p-values ( r th ordered p-value, rOP) across combined studies as the test statistic. We illustrate different hypothesis settings that detect gene markers differentially expressed (DE) "in all studies", "in the majority of studies", or "in one or more studies", and specify rOP as a suitable method for detecting DE genes "in the majority of studies". We develop methods to estimate the parameter r in rOP for real applications. Statistical properties such as its asymptotic behavior and a one-sided testing correction for detecting markers of concordant expression changes are explored. Power calculation and simulation show better performance of rOP compared to classical Fisher's method, Stouffer's method, minimum p-value method and maximum p-value method under the focused hypothesis setting. Theoretically, rOP is found connected to the naïve vote counting method and can be viewed as a generalized form of vote counting with better statistical properties. The method is applied to three microarray meta-analysis examples including major depressive disorder, brain cancer and diabetes. The results demonstrate rOP as a more generalizable, robust and sensitive statistical framework to detect disease-related markers.

Applying a 2D based CAD scheme for detecting micro-calcification clusters using digital breast tomosynthesis images: an assessment

NASA Astrophysics Data System (ADS)

Park, Sang Cheol; Zheng, Bin; Wang, Xiao-Hui; Gur, David

2008-03-01

Digital breast tomosynthesis (DBT) has emerged as a promising imaging modality for screening mammography. However, visually detecting micro-calcification clusters depicted on DBT images is a difficult task. Computer-aided detection (CAD) schemes for detecting micro-calcification clusters depicted on mammograms can achieve high performance and the use of CAD results can assist radiologists in detecting subtle micro-calcification clusters. In this study, we compared the performance of an available 2D based CAD scheme with one that includes a new grouping and scoring method when applied to both projection and reconstructed DBT images. We selected a dataset involving 96 DBT examinations acquired on 45 women. Each DBT image set included 11 low dose projection images and a varying number of reconstructed image slices ranging from 18 to 87. In this dataset 20 true-positive micro-calcification clusters were visually detected on the projection images and 40 were visually detected on the reconstructed images, respectively. We first applied the CAD scheme that was previously developed in our laboratory to the DBT dataset. We then tested a new grouping method that defines an independent cluster by grouping the same cluster detected on different projection or reconstructed images. We then compared four scoring methods to assess the CAD performance. The maximum sensitivity level observed for the different grouping and scoring methods were 70% and 88% for the projection and reconstructed images with a maximum false-positive rate of 4.0 and 15.9 per examination, respectively. This preliminary study demonstrates that (1) among the maximum, the minimum or the average CAD generated scores, using the maximum score of the grouped cluster regions achieved the highest performance level, (2) the histogram based scoring method is reasonably effective in reducing false-positive detections on the projection images but the overall CAD sensitivity is lower due to lower signal-to-noise ratio, and (3) CAD achieved higher sensitivity and higher false-positive rate (per examination) on the reconstructed images. We concluded that without changing the detection threshold or performing pre-filtering to possibly increase detection sensitivity, current CAD schemes developed and optimized for 2D mammograms perform relatively poorly and need to be re-optimized using DBT datasets and new grouping and scoring methods need to be incorporated into the schemes if these are to be used on the DBT examinations.

Why conventional detection methods fail in identifying the existence of contamination events.

PubMed

Liu, Shuming; Li, Ruonan; Smith, Kate; Che, Han

2016-04-15

Early warning systems are widely used to safeguard water security, but their effectiveness has raised many questions. To understand why conventional detection methods fail to identify contamination events, this study evaluates the performance of three contamination detection methods using data from a real contamination accident and two artificial datasets constructed using a widely applied contamination data construction approach. Results show that the Pearson correlation Euclidean distance (PE) based detection method performs better for real contamination incidents, while the Euclidean distance method (MED) and linear prediction filter (LPF) method are more suitable for detecting sudden spike-like variation. This analysis revealed why the conventional MED and LPF methods failed to identify existence of contamination events. The analysis also revealed that the widely used contamination data construction approach is misleading. Copyright © 2016 Elsevier Ltd. All rights reserved.

Determination of Sinkholes with Different Geophysical Techniques; A Case Study in Yarımburgaz, Küçükçekmece Lake NW Istanbul, Turkey

NASA Astrophysics Data System (ADS)

Karabulut, Savas; Cengiz Cinku, Mualla; Tezel, Okan; Dedecan, Hasan; Oygo, Azat

2016-04-01

The Yarımburgaz cave which is located in the city of Istanbul, NW Turkey plays an important host to the first human culture and preserve significant archaeological and paleontological resources. The cave was formed as a result of a subterranean stream erosion on the limestones of the Eocene Kırklareli formation. It has been reported that a double cave with upper and lower entrance chambers exist, although no geophysical research was conducted to detect the cave's trunk passages and the extend of the sediment fill inside the cave. The aim of this study was to test the preferred order for detection the response to different geophysical methods applied on the cave. We therefore carried out an a series of geophysical study to determine the size, position, and depth of sinkholes inside the caves. Integrated methodological approaches including multichannel analysis of surface wave (MASW) 2- microtremor array method, 3-single station microtremor measurements, 4- electrical tomography (ET) measuruments and 5-microgravity imaging showed that the geophysical response was succesfully applied. Based upon the flow-chart we concluded that the microgravity survey should be applied as a first step to detect the air-filled void and the geometry of the cave. The electric tomography method was well applied showing high resistivity values across the voids. The surface wave method showed that the low-velocity zones are detected in various locations of the cave. In addition we the results of MASW and ReMi methods showed clearly the density variation in the lateral direction. Fundamental frequency value above void decraese according the properties of geological units in lateral directional, especially when they are engineering rock like limestone.

Method development for the determination of coumarin compounds by capillary electrophoresis with indirect laser-induced fluorescence detection.

PubMed

Wang, Weiping; Tang, Jianghong; Wang, Shumin; Zhou, Lei; Hu, Zhide

2007-04-27

A capillary zone electrophoresis (CZE) with indirect laser-induced fluorescence detection (ILIFD) method is described for the simultaneous determination of esculin, esculetin, isofraxidin, genistein, naringin and sophoricoside. The baseline separation was achieved within 5 min with running buffer (pH 9.4) composed of 5mM borate, 20% methanol (v/v) as organic modifier, 10(-7)M fluorescein sodium as background fluorophore and 20 kV of applied voltage at 30 degrees C of cartridge temperature. Good linearity relationships (correlation coefficients >0.9900) between the second-order derivative peak-heights (RFU) and concentrations of the analytes (mol L(-1)) were obtained. The detection limits for all analytes in second-order derivative electrophoregrams were in the range of 3.8-15 microM. The RSD data of intra-day for migration times and second-order derivative peak-height were less than 0.95 and 5.02%, respectively. This developed method was applied to the analysis of the courmin compounds in herb plants with recoveries in the range of 94.7-102.1%. In this work, although the detection sensitivity was lower than that of direct LIF, yet the method would extend the application range of LIF detection.

A Rapid Protocol of Crude RNA/DNA Extraction for RT-qPCR Detection and Quantification of 'Candidatus Phytoplasma prunorum'

PubMed Central

Minguzzi, Stefano; Terlizzi, Federica; Lanzoni, Chiara; Poggi Pollini, Carlo; Ratti, Claudio

2016-01-01

Many efforts have been made to develop a rapid and sensitive method for phytoplasma and virus detection. Taking our cue from previous works, different rapid sample preparation methods have been tested and applied to Candidatus Phytoplasma prunorum (‘Ca. P. prunorum’) detection by RT-qPCR. A duplex RT-qPCR has been optimized using the crude sap as a template to simultaneously amplify a fragment of 16S rRNA of the pathogen and 18S rRNA of the host plant. The specific plant 18S rRNA internal control allows comparison and relative quantification of samples. A comparison between DNA and RNA contribution to qPCR detection is provided, showing higher contribution of the latter. The method presented here has been validated on more than a hundred samples of apricot, plum and peach trees. Since 2013, this method has been successfully applied to monitor ‘Ca. P. prunorum’ infections in field and nursery. A triplex RT-qPCR assay has also been optimized to simultaneously detect ‘Ca. P. prunorum’ and Plum pox virus (PPV) in Prunus. PMID:26742106

How to detect carbapenemase producers? A literature review of phenotypic and molecular methods.

PubMed

Hammoudi, D; Moubareck, C Ayoub; Sarkis, D Karam

2014-12-01

This review describes the current state-of-art of carbapenemase detection methods. Identification of carbapenemases is first based on conventional phenotypic tests including antimicrobial susceptibility testing, modified-Hodge test and carbapenemase-inhibitor culture tests. Second, molecular characterization of carbapenemase genes by PCR sequencing is essential. Third, innovative biochemical and spectrometric detection may be applied. Copyright © 2014 Elsevier B.V. All rights reserved.

Online Detection of Broken Rotor Bar Fault in Induction Motors by Combining Estimation of Signal Parameters via Min-norm Algorithm and Least Square Method

NASA Astrophysics Data System (ADS)

Wang, Pan-Pan; Yu, Qiang; Hu, Yong-Jun; Miao, Chang-Xin

2017-11-01

Current research in broken rotor bar (BRB) fault detection in induction motors is primarily focused on a high-frequency resolution analysis of the stator current. Compared with a discrete Fourier transformation, the parametric spectrum estimation technique has a higher frequency accuracy and resolution. However, the existing detection methods based on parametric spectrum estimation cannot realize online detection, owing to the large computational cost. To improve the efficiency of BRB fault detection, a new detection method based on the min-norm algorithm and least square estimation is proposed in this paper. First, the stator current is filtered using a band-pass filter and divided into short overlapped data windows. The min-norm algorithm is then applied to determine the frequencies of the fundamental and fault characteristic components with each overlapped data window. Next, based on the frequency values obtained, a model of the fault current signal is constructed. Subsequently, a linear least squares problem solved through singular value decomposition is designed to estimate the amplitudes and phases of the related components. Finally, the proposed method is applied to a simulated current and an actual motor, the results of which indicate that, not only parametric spectrum estimation technique.

Simultaneous determination of ezetimibe and simvastatin in pharmaceutical preparations by MEKC.

PubMed

Yardimci, Ceren; Ozaltin, Nuran

2010-02-01

A micellar electrokinetic capillary chromatography method was developed and validated for the simultaneous determination of ezetimibe and simvastatin in pharmaceutical preparations. The influence of buffer concentration, buffer pH, sodium dodecyl sulphate (SDS) concentration, organic modifier, capillary temperature, applied voltage, and injection time was investigated, and the method validation studies were performed. The optimum separation for these analytes was achieved in less than 10 min at 30 degrees C with a fused-silica capillary column (56 cm x 50 microm i.d.) and a 25mM borate buffer at pH 9.0 containing 25mM SDS and 10% (v/v) acetonitrile. The samples were injected hydrodynamically for 3 s at 50 mbar, and the applied voltage was +30.0 kV. Detection wavelength was set at 238 nm. Diflunisal was used as internal standard. The method was suitably validated with respect to stability, specificity, linearity, limits of detection and quantification, accuracy, precision, and robustness. The limits of detection and quantification were 1.0 and 2.0 microg/mL for both ezetimibe and simvastatin, respectively. The method developed was successfully applied to the simultaneous determination of ezetimibe and simvastatin in pharmaceutical preparations.

Split luciferase complementation assay to detect regulated protein-protein interactions in rice protoplasts in a large-scale format

PubMed Central

2014-01-01

Background The rice interactome, in which a network of protein-protein interactions has been elucidated in rice, is a useful resource to identify functional modules of rice signal transduction pathways. Protein-protein interactions occur in cells in two ways, constitutive and regulative. While a yeast-based high-throughput method has been widely used to identify the constitutive interactions, a method to detect the regulated interactions is rarely developed for a large-scale analysis. Results A split luciferase complementation assay was applied to detect the regulated interactions in rice. A transformation method of rice protoplasts in a 96-well plate was first established for a large-scale analysis. In addition, an antibody that specifically recognizes a carboxyl-terminal fragment of Renilla luciferase was newly developed. A pair of antibodies that recognize amino- and carboxyl- terminal fragments of Renilla luciferase, respectively, was then used to monitor quality and quantity of interacting recombinant-proteins accumulated in the cells. For a proof-of-concept, the method was applied to detect the gibberellin-dependent interaction between GIBBERELLIN INSENSITIVE DWARF1 and SLENDER RICE 1. Conclusions A method to detect regulated protein-protein interactions was developed towards establishment of the rice interactome. PMID:24987490

Comparative analysis of techniques for detection of quiescent Botrytis cinerea in grapes by quantitative PCR

USDA-ARS?s Scientific Manuscript database

Quantitative PCR (qPCR) can be used to detect and monitor pathogen colonization, but early attempts to apply the technology to quiescent Botrytis cinerea infections of grape berries identified some specific limitations. In this study, four DNA extraction methods, two tissue-grinding methods, two gra...

Speciation of chromium using reversed phase-high performance liquid chromatography coupled to different spectrometric detection methods

NASA Astrophysics Data System (ADS)

Andrle, C. M.; Jakubowski, N.; Broekaert, J. A. C.

1997-02-01

Speciation of Cr(III) and Cr(VI) based on the formation of different complexes with ammonium-pyrrolidinedithioate (APDC) in a continuous flow technique and their preconcentration using solid phase extraction (SPE) have been elaborated and applied to the analysis of waste waters from the galvanic industry. The Cr complexes were separated and determined using reversed phase-high performance liquid chromatography (RP-HPLC) coupled to different detection methods, namely UV-detection, graphite furnace-atomic absorption spectrometry (GF-AAS) and inductively coupled plasma mass spectrometry with hydraulic high pressure nebulization (HHPN/ICP-MS). After optimization the detection limits for Cr(III) and Cr(VI) of all methods are at the μg 1 -1 level and the precision in terms of RSD is 5% ( cCr = 100 μg 1 -1, N = 10). The procedure was applied to the determination of Cr(III) and Cr(VI) at the μg 1 -1 level in galvanic waste waters, and its accuracy was approved by comparing the results with those of independent methods.

Development of Measurement Methods for Detection of Special Nuclear Materials using D-D Pulsed Neutron Source

NASA Astrophysics Data System (ADS)

Misawa, Tsuyoshi; Takahashi, Yoshiyuki; Yagi, Takahiro; Pyeon, Cheol Ho; Kimura, Masaharu; Masuda, Kai; Ohgaki, Hideaki

2015-10-01

For detection of hidden special nuclear materials (SNMs), we have developed an active neutron-based interrogation system combined with a D-D fusion pulsed neutron source and a neutron detection system. In the detection scheme, we have adopted new measurement techniques simultaneously; neutron noise analysis and neutron energy spectrum analysis. The validity of neutron noise analysis method has been experimentally studied in the Kyoto University Critical Assembly (KUCA), and was applied to a cargo container inspection system by simulation.

Region-based automatic building and forest change detection on Cartosat-1 stereo imagery

NASA Astrophysics Data System (ADS)

Tian, J.; Reinartz, P.; d'Angelo, P.; Ehlers, M.

2013-05-01

In this paper a novel region-based method is proposed for change detection using space borne panchromatic Cartosat-1 stereo imagery. In the first step, Digital Surface Models (DSMs) from two dates are generated by semi-global matching. The geometric lateral resolution of the DSMs is 5 m × 5 m and the height accuracy is in the range of approximately 3 m (RMSE). In the second step, mean-shift segmentation is applied on the orthorectified images of two dates to obtain initial regions. A region intersection following a merging strategy is proposed to get minimum change regions and multi-level change vectors are extracted for these regions. Finally change detection is achieved by combining these features with weighted change vector analysis. The result evaluations demonstrate that the applied DSM generation method is well suited for Cartosat-1 imagery, and the extracted height values can largely improve the change detection accuracy, moreover it is shown that the proposed change detection method can be used robustly for both forest and industrial areas.

Challenging a bioinformatic tool's ability to detect microbial contaminants using in silico whole genome sequencing data.

PubMed

Olson, Nathan D; Zook, Justin M; Morrow, Jayne B; Lin, Nancy J

2017-01-01

High sensitivity methods such as next generation sequencing and polymerase chain reaction (PCR) are adversely impacted by organismal and DNA contaminants. Current methods for detecting contaminants in microbial materials (genomic DNA and cultures) are not sensitive enough and require either a known or culturable contaminant. Whole genome sequencing (WGS) is a promising approach for detecting contaminants due to its sensitivity and lack of need for a priori assumptions about the contaminant. Prior to applying WGS, we must first understand its limitations for detecting contaminants and potential for false positives. Herein we demonstrate and characterize a WGS-based approach to detect organismal contaminants using an existing metagenomic taxonomic classification algorithm. Simulated WGS datasets from ten genera as individuals and binary mixtures of eight organisms at varying ratios were analyzed to evaluate the role of contaminant concentration and taxonomy on detection. For the individual genomes the false positive contaminants reported depended on the genus, with Staphylococcus , Escherichia , and Shigella having the highest proportion of false positives. For nearly all binary mixtures the contaminant was detected in the in-silico datasets at the equivalent of 1 in 1,000 cells, though F. tularensis was not detected in any of the simulated contaminant mixtures and Y. pestis was only detected at the equivalent of one in 10 cells. Once a WGS method for detecting contaminants is characterized, it can be applied to evaluate microbial material purity, in efforts to ensure that contaminants are characterized in microbial materials used to validate pathogen detection assays, generate genome assemblies for database submission, and benchmark sequencing methods.

Bayesian microsaccade detection

PubMed Central

Mihali, Andra; van Opheusden, Bas; Ma, Wei Ji

2017-01-01

Microsaccades are high-velocity fixational eye movements, with special roles in perception and cognition. The default microsaccade detection method is to determine when the smoothed eye velocity exceeds a threshold. We have developed a new method, Bayesian microsaccade detection (BMD), which performs inference based on a simple statistical model of eye positions. In this model, a hidden state variable changes between drift and microsaccade states at random times. The eye position is a biased random walk with different velocity distributions for each state. BMD generates samples from the posterior probability distribution over the eye state time series given the eye position time series. Applied to simulated data, BMD recovers the “true” microsaccades with fewer errors than alternative algorithms, especially at high noise. Applied to EyeLink eye tracker data, BMD detects almost all the microsaccades detected by the default method, but also apparent microsaccades embedded in high noise—although these can also be interpreted as false positives. Next we apply the algorithms to data collected with a Dual Purkinje Image eye tracker, whose higher precision justifies defining the inferred microsaccades as ground truth. When we add artificial measurement noise, the inferences of all algorithms degrade; however, at noise levels comparable to EyeLink data, BMD recovers the “true” microsaccades with 54% fewer errors than the default algorithm. Though unsuitable for online detection, BMD has other advantages: It returns probabilities rather than binary judgments, and it can be straightforwardly adapted as the generative model is refined. We make our algorithm available as a software package. PMID:28114483

Detection and enumeration of Salmonella enteritidis in homemade ice cream associated with an outbreak: comparison of conventional and real-time PCR methods.

PubMed

Seo, K H; Valentin-Bon, I E; Brackett, R E

2006-03-01

Salmonellosis caused by Salmonella Enteritidis (SE) is a significant cause of foodborne illnesses in the United States. Consumption of undercooked eggs and egg-containing products has been the primary risk factor for the disease. The importance of the bacterial enumeration technique has been enormously stressed because of the quantitative risk analysis of SE in shell eggs. Traditional enumeration methods mainly depend on slow and tedious most-probable-number (MPN) methods. Therefore, specific, sensitive, and rapid methods for SE quantitation are needed to collect sufficient data for risk assessment and food safety policy development. We previously developed a real-time quantitative PCR assay for the direct detection and enumeration of SE and, in this study, applied it to naturally contaminated ice cream samples with and without enrichment. The detection limit of the real-time PCR assay was determined with artificially inoculated ice cream. When applied to the direct detection and quantification of SE in ice cream, the real-time PCR assay was as sensitive as the conventional plate count method in frequency of detection. However, populations of SE derived from real-time quantitative PCR were approximately 1 log higher than provided by MPN and CFU values obtained by conventional culture methods. The detection and enumeration of SE in naturally contaminated ice cream can be completed in 3 h by this real-time PCR method, whereas the cultural enrichment method requires 5 to 7 days. A commercial immunoassay for the specific detection of SE was also included in the study. The real-time PCR assay proved to be a valuable tool that may be useful to the food industry in monitoring its processes to improve product quality and safety.

An Adaptive Network-based Fuzzy Inference System for the detection of thermal and TEC anomalies around the time of the Varzeghan, Iran, (Mw = 6.4) earthquake of 11 August 2012

NASA Astrophysics Data System (ADS)

Akhoondzadeh, M.

2013-09-01

Anomaly detection is extremely important for forecasting the date, location and magnitude of an impending earthquake. In this paper, an Adaptive Network-based Fuzzy Inference System (ANFIS) has been proposed to detect the thermal and Total Electron Content (TEC) anomalies around the time of the Varzeghan, Iran, (Mw = 6.4) earthquake jolted in 11 August 2012 NW Iran. ANFIS is the famous hybrid neuro-fuzzy network for modeling the non-linear complex systems. In this study, also the detected thermal and TEC anomalies using the proposed method are compared to the results dealing with the observed anomalies by applying the classical and intelligent methods including Interquartile, Auto-Regressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and Support Vector Machine (SVM) methods. The duration of the dataset which is comprised from Aqua-MODIS Land Surface Temperature (LST) night-time snapshot images and also Global Ionospheric Maps (GIM), is 62 days. It can be shown that, if the difference between the predicted value using the ANFIS method and the observed value, exceeds the pre-defined threshold value, then the observed precursor value in the absence of non seismic effective parameters could be regarded as precursory anomaly. For two precursors of LST and TEC, the ANFIS method shows very good agreement with the other implemented classical and intelligent methods and this indicates that ANFIS is capable of detecting earthquake anomalies. The applied methods detected anomalous occurrences 1 and 2 days before the earthquake. This paper indicates that the detection of the thermal and TEC anomalies derive their credibility from the overall efficiencies and potentialities of the five integrated methods.

Validation of PCR methods for quantitation of genetically modified plants in food.

PubMed

Hübner, P; Waiblinger, H U; Pietsch, K; Brodmann, P

2001-01-01

For enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients, quantitative detection methods such as quantitative competitive (QC-PCR) and real-time PCR are applied by official food control laboratories. The experiences of 3 European food control laboratories in validating such methods were compared to describe realistic performance characteristics of quantitative PCR detection methods. The limit of quantitation (LOQ) of GMO-specific, real-time PCR was experimentally determined to reach 30-50 target molecules, which is close to theoretical prediction. Starting PCR with 200 ng genomic plant DNA, the LOQ depends primarily on the genome size of the target plant and ranges from 0.02% for rice to 0.7% for wheat. The precision of quantitative PCR detection methods, expressed as relative standard deviation (RSD), varied from 10 to 30%. Using Bt176 corn containing test samples and applying Bt176 specific QC-PCR, mean values deviated from true values by -7to 18%, with an average of 2+/-10%. Ruggedness of real-time PCR detection methods was assessed in an interlaboratory study analyzing commercial, homogeneous food samples. Roundup Ready soybean DNA contents were determined in the range of 0.3 to 36%, relative to soybean DNA, with RSDs of about 25%. Taking the precision of quantitative PCR detection methods into account, suitable sample plans and sample sizes for GMO analysis are suggested. Because quantitative GMO detection methods measure GMO contents of samples in relation to reference material (calibrants), high priority must be given to international agreements and standardization on certified reference materials.

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.

Ultrasound Based Method and Apparatus for Stone Detection and to Facilitate Clearance Thereof

NASA Technical Reports Server (NTRS)

Bailey, Michael (Inventor); Kaczkowski, Peter (Inventor); Illian, Paul (Inventor); Kucewicz, John (Inventor); Sapozhnikov, Oleg (Inventor); Shah, Anup (Inventor); Dunmire, Barbrina (Inventor); Lu, Wei (Inventor); Owen, Neil (Inventor); Cunitz, Bryan (Inventor)

2015-01-01

Described herein are methods and apparatus for detecting stones by ultrasound, in which the ultrasound reflections from a stone are preferentially selected and accentuated relative to the ultrasound reflections from blood or tissue. Also described herein are methods and apparatus for applying pushing ultrasound to in vivo stones or other objects, to facilitate the removal of such in vivo objects.

A Complex Systems Approach to Causal Discovery in Psychiatry.

PubMed

Saxe, Glenn N; Statnikov, Alexander; Fenyo, David; Ren, Jiwen; Li, Zhiguo; Prasad, Meera; Wall, Dennis; Bergman, Nora; Briggs, Ernestine C; Aliferis, Constantin

2016-01-01

Conventional research methodologies and data analytic approaches in psychiatric research are unable to reliably infer causal relations without experimental designs, or to make inferences about the functional properties of the complex systems in which psychiatric disorders are embedded. This article describes a series of studies to validate a novel hybrid computational approach--the Complex Systems-Causal Network (CS-CN) method-designed to integrate causal discovery within a complex systems framework for psychiatric research. The CS-CN method was first applied to an existing dataset on psychopathology in 163 children hospitalized with injuries (validation study). Next, it was applied to a much larger dataset of traumatized children (replication study). Finally, the CS-CN method was applied in a controlled experiment using a 'gold standard' dataset for causal discovery and compared with other methods for accurately detecting causal variables (resimulation controlled experiment). The CS-CN method successfully detected a causal network of 111 variables and 167 bivariate relations in the initial validation study. This causal network had well-defined adaptive properties and a set of variables was found that disproportionally contributed to these properties. Modeling the removal of these variables resulted in significant loss of adaptive properties. The CS-CN method was successfully applied in the replication study and performed better than traditional statistical methods, and similarly to state-of-the-art causal discovery algorithms in the causal detection experiment. The CS-CN method was validated, replicated, and yielded both novel and previously validated findings related to risk factors and potential treatments of psychiatric disorders. The novel approach yields both fine-grain (micro) and high-level (macro) insights and thus represents a promising approach for complex systems-oriented research in psychiatry.

Highly sensitive screening method for nitroaromatic, nitramine and nitrate ester explosives by high performance liquid chromatography-atmospheric pressure ionization-mass spectrometry (HPLC-API-MS) in forensic applications.

PubMed

Xu, Xiaoma; van de Craats, Anick M; de Bruyn, Peter C A M

2004-11-01

A highly sensitive screening method based on high performance liquid chromatography atmospheric pressure ionization mass spectrometry (HPLC-API-MS) has been developed for the analysis of 21 nitroaromatic, nitramine and nitrate ester explosives, which include the explosives most commonly encountered in forensic science. Two atmospheric pressure ionization (API) methods, atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI), and various experimental conditions have been applied to allow for the detection of all 21 explosive compounds. The limit of detection (LOD) in the full-scan mode has been found to be 0.012-1.2 ng on column for the screening of most explosives investigated. For nitrobenzene, an LOD of 10 ng was found with the APCI method in the negative mode. Although the detection of nitrobenzene, 2-, 3-, and 4-nitrotoluene is hindered by the difficult ionization of these compounds, we have found that by forming an adduct with glycine, LOD values in the range of 3-16 ng on column can be achieved. Compared with previous screening methods with thermospray ionization, the API method has distinct advantages, including simplicity and stability of the method applied, an extended screening range and a low detection limit for the explosives studied.

Application of fluorescence spectroscopy and imaging in the detection of a photosensitizer in photodynamic therapy

NASA Astrophysics Data System (ADS)

Zang, Lixin; Zhao, Huimin; Zhang, Zhiguo; Cao, Wenwu

2017-02-01

Photodynamic therapy (PDT) is currently an advanced optical technology in medical applications. However, the application of PDT is limited by the detection of photosensitizers. This work focuses on the application of fluorescence spectroscopy and imaging in the detection of an effective photosenzitizer, hematoporphyrin monomethyl ether (HMME). Optical properties of HMME were measured and analyzed based on its absorption and fluorescence spectra. The production mechanism of its fluorescence emission was analyzed. The detection device for HMME based on fluorescence spectroscopy was designed. Ratiometric method was applied to eliminate the influence of intensity change of excitation sources, fluctuates of excitation sources and photo detectors, and background emissions. The detection limit of this device is 6 μg/L, and it was successfully applied to the diagnosis of the metabolism of HMME in the esophageal cancer cells. To overcome the limitation of the point measurement using fluorescence spectroscopy, a two-dimensional (2D) fluorescence imaging system was established. The algorithm of the 2D fluorescence imaging system is deduced according to the fluorescence ratiometric method using bandpass filters. The method of multiple pixel point addition (MPPA) was used to eliminate fluctuates of signals. Using the method of MPPA, SNR was improved by about 30 times. The detection limit of this imaging system is 1.9 μg/L. Our systems can be used in the detection of porphyrins to improve the PDT effect.

High-resolution melting (HRM) re-analysis of a polyposis patients cohort reveals previously undetected heterozygous and mosaic APC gene mutations.

PubMed

Out, Astrid A; van Minderhout, Ivonne J H M; van der Stoep, Nienke; van Bommel, Lysette S R; Kluijt, Irma; Aalfs, Cora; Voorendt, Marsha; Vossen, Rolf H A M; Nielsen, Maartje; Vasen, Hans F A; Morreau, Hans; Devilee, Peter; Tops, Carli M J; Hes, Frederik J

2015-06-01

Familial adenomatous polyposis is most frequently caused by pathogenic variants in either the APC gene or the MUTYH gene. The detection rate of pathogenic variants depends on the severity of the phenotype and sensitivity of the screening method, including sensitivity for mosaic variants. For 171 patients with multiple colorectal polyps without previously detectable pathogenic variant, APC was reanalyzed in leukocyte DNA by one uniform technique: high-resolution melting (HRM) analysis. Serial dilution of heterozygous DNA resulted in a lowest detectable allelic fraction of 6% for the majority of variants. HRM analysis and subsequent sequencing detected pathogenic fully heterozygous APC variants in 10 (6%) of the patients and pathogenic mosaic variants in 2 (1%). All these variants were previously missed by various conventional scanning methods. In parallel, HRM APC scanning was applied to DNA isolated from polyp tissue of two additional patients with apparently sporadic polyposis and without detectable pathogenic APC variant in leukocyte DNA. In both patients a pathogenic mosaic APC variant was present in multiple polyps. The detection of pathogenic APC variants in 7% of the patients, including mosaics, illustrates the usefulness of a complete APC gene reanalysis of previously tested patients, by a supplementary scanning method. HRM is a sensitive and fast pre-screening method for reliable detection of heterozygous and mosaic variants, which can be applied to leukocyte and polyp derived DNA.

A randomized approach to speed up the analysis of large-scale read-count data in the application of CNV detection.

PubMed

Wang, WeiBo; Sun, Wei; Wang, Wei; Szatkiewicz, Jin

2018-03-01

The application of high-throughput sequencing in a broad range of quantitative genomic assays (e.g., DNA-seq, ChIP-seq) has created a high demand for the analysis of large-scale read-count data. Typically, the genome is divided into tiling windows and windowed read-count data is generated for the entire genome from which genomic signals are detected (e.g. copy number changes in DNA-seq, enrichment peaks in ChIP-seq). For accurate analysis of read-count data, many state-of-the-art statistical methods use generalized linear models (GLM) coupled with the negative-binomial (NB) distribution by leveraging its ability for simultaneous bias correction and signal detection. However, although statistically powerful, the GLM+NB method has a quadratic computational complexity and therefore suffers from slow running time when applied to large-scale windowed read-count data. In this study, we aimed to speed up substantially the GLM+NB method by using a randomized algorithm and we demonstrate here the utility of our approach in the application of detecting copy number variants (CNVs) using a real example. We propose an efficient estimator, the randomized GLM+NB coefficients estimator (RGE), for speeding up the GLM+NB method. RGE samples the read-count data and solves the estimation problem on a smaller scale. We first theoretically validated the consistency and the variance properties of RGE. We then applied RGE to GENSENG, a GLM+NB based method for detecting CNVs. We named the resulting method as "R-GENSENG". Based on extensive evaluation using both simulated and empirical data, we concluded that R-GENSENG is ten times faster than the original GENSENG while maintaining GENSENG's accuracy in CNV detection. Our results suggest that RGE strategy developed here could be applied to other GLM+NB based read-count analyses, i.e. ChIP-seq data analysis, to substantially improve their computational efficiency while preserving the analytic power.

Green preparation of carbon dots with mangosteen pulp for the selective detection of Fe3+ ions and cell imaging

NASA Astrophysics Data System (ADS)

Yang, Rui; Guo, Xiangfeng; Jia, Lihua; Zhang, Yu; Zhao, Zhenlong; Lonshakov, Fedor

2017-11-01

A simple method was developed in the synthesis of fluorescent carbon dots (referred to as M-CDs), calcined treatment of mangosteen pulp in air, without the assistance of any chemical reagent. The M-CDs possess good-solubility, satisfactory chemical stability and can be applied as the fluorescent temperature probe. More strikingly, the fluorescence of M-CDs can be fleetly and selectively quenched by Fe3+ ions. The phenomenon was used to develop a fluorescent method for facile detection of Fe3+ with a linear range of 0-0.18 mM and a detection limit of 52 nM. Eventually, the M-CDs were applied for cell imaging, demonstrating their potential toward diverse applications.

Coronary arteries segmentation based on the 3D discrete wavelet transform and 3D neutrosophic transform.

PubMed

Chen, Shuo-Tsung; Wang, Tzung-Dau; Lee, Wen-Jeng; Huang, Tsai-Wei; Hung, Pei-Kai; Wei, Cheng-Yu; Chen, Chung-Ming; Kung, Woon-Man

2015-01-01

Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Yang et al., 2007. Results indicate that the proposed method is better in terms of efficiency analyzed. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Determination of penicillamine in pharmaceuticals and human plasma by capillary electrophoresis with in-column fiber optics light-emitting diode induced fluorescence detection.

PubMed

Yang, Xiupei; Yuan, Hongyan; Wang, Chunling; Su, Xiaodong; Hu, Li; Xiao, Dan

2007-10-18

In this paper, a capillary electrophoresis (CE) system with in-column fiber optics light-emitting diode (LED) induced fluorescence detection was developed for the determination of penicillamine (PA). The influence of buffer concentration, buffer pH, applied voltage and injection time was systematically investigated. Optimum separation conditions were obtained with 10 mM borate buffer at pH 9.1, applied voltage 20 kV and 8 s hydrodynamic injection at 30 mbar. The detection system displayed linear dynamic range from 3.2 x 10(-7) to 4.8 x 10(-5) mol L(-1) with a correlation coefficient of 0.9991 and good repeatability (R.S.D.=2.46%). The method was applied to the determination of PA in commercial tablets and human plasma, which the recoveries of standard PA added to tablets and human plasma sample were found to be in the range of 96.26-102.68 and 91.10-99.35%, respectively. The proposed method is cheap, rapid, easy, and accurate, and can be successfully applied to the formulation analysis and bioanalysis.

Detection Progress of Selected Drugs in TLC

PubMed Central

Pyka, Alina

2014-01-01

This entry describes applications of known indicators and dyes as new visualizing reagents and various visualizing systems as well as photocatalytic reactions and bioautography method for the detection of bioactive compounds including drugs and compounds isolated from herbal extracts. Broadening index, detection index, characteristics of densitometric band, modified contrast index, limit of detection, densitometric visualizing index, and linearity range of detected compounds were used for the evaluation of visualizing effects of applied visualizing reagents. It was shown that visualizing effect depends on the chemical structure of the visualizing reagent, the structure of the substance detected, and the chromatographic adsorbent applied. The usefulness of densitometry to direct detection of some drugs was also shown. Quoted papers indicate the detection progress of selected drugs investigated by thin-layer chromatography (TLC). PMID:24551853

Comparative studies by IR, Raman, and surface-enhanced Raman spectroscopy of azodicarbonamide, biurea and semicarbazide hydrochloride

NASA Astrophysics Data System (ADS)

Xie, Yunfei; Li, Pei; Zhang, Jin; Wang, Heya; Qian, He; Yao, Weirong

2013-10-01

Azodicarbonamide is widely applied in the food industry as a new flour gluten fortifier in China, Canada, the United States, and some other countries, whose metabolites of biurea and semicarbazide hydrochloride are reaction products during baking. In this study, IR, Raman and surface-enhanced Raman scattering (SERS) spectra of azodicarbonamide, biurea, and semicarbazide hydrochloride have been studied, and vibrational bands have been assigned on the basis of density functional theory (DFT) calculations. The calculated Raman spectra were in good agreement with experimental Raman spectra. The SERS method coupled with active gold substrates has also been applied for detection of the three chemicals with pure water as solvent, with the limit of detection of this method being as low as 10 μg/mL (less than 45 μg/mL). These results showed that azodicarbonamide and its metabolites could be detected by the vibrational spectra technique, which might be applied as a powerful tool for the rapid detection on these species derived from agents added to flour.

Robust vehicle detection under various environmental conditions using an infrared thermal camera and its application to road traffic flow monitoring.

PubMed

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2013-06-17

We have already proposed a method for detecting vehicle positions and their movements (henceforth referred to as "our previous method") using thermal images taken with an infrared thermal camera. Our experiments have shown that our previous method detects vehicles robustly under four different environmental conditions which involve poor visibility conditions in snow and thick fog. Our previous method uses the windshield and its surroundings as the target of the Viola-Jones detector. Some experiments in winter show that the vehicle detection accuracy decreases because the temperatures of many windshields approximate those of the exterior of the windshields. In this paper, we propose a new vehicle detection method (henceforth referred to as "our new method"). Our new method detects vehicles based on tires' thermal energy reflection. We have done experiments using three series of thermal images for which the vehicle detection accuracies of our previous method are low. Our new method detects 1,417 vehicles (92.8%) out of 1,527 vehicles, and the number of false detection is 52 in total. Therefore, by combining our two methods, high vehicle detection accuracies are maintained under various environmental conditions. Finally, we apply the traffic information obtained by our two methods to traffic flow automatic monitoring, and show the effectiveness of our proposal.

Automatic Authorship Detection Using Textual Patterns Extracted from Integrated Syntactic Graphs

PubMed Central

Gómez-Adorno, Helena; Sidorov, Grigori; Pinto, David; Vilariño, Darnes; Gelbukh, Alexander

2016-01-01

We apply the integrated syntactic graph feature extraction methodology to the task of automatic authorship detection. This graph-based representation allows integrating different levels of language description into a single structure. We extract textual patterns based on features obtained from shortest path walks over integrated syntactic graphs and apply them to determine the authors of documents. On average, our method outperforms the state of the art approaches and gives consistently high results across different corpora, unlike existing methods. Our results show that our textual patterns are useful for the task of authorship attribution. PMID:27589740

Mode synthesizing atomic force microscopy and mode-synthesizing sensing

DOEpatents

Passian, Ali; Thundat, Thomas George; Tetard, Laurene

2013-05-17

A method of analyzing a sample that includes applying a first set of energies at a first set of frequencies to a sample and applying, simultaneously with the applying the first set of energies, a second set of energies at a second set of frequencies, wherein the first set of energies and the second set of energies form a multi-mode coupling. The method further includes detecting an effect of the multi-mode coupling.

Mode-synthesizing atomic force microscopy and mode-synthesizing sensing

DOEpatents

Passain, Ali; Thundat, Thomas George; Tetard, Laurene

2014-07-22

A method of analyzing a sample that includes applying a first set of energies at a first set of frequencies to a sample and applying, simultaneously with the applying the first set of energies, a second set of energies at a second set of frequencies, wherein the first set of energies and the second set of energies form a multi-mode coupling. The method further includes detecting an effect of the multi-mode coupling.

The Need and Potential of Biosensors to Detect Dioxins and Dioxin-Like Polychlorinated Biphenyls along the Milk, Eggs and Meat Food Chain

PubMed Central

Chobtang, Jeerasak; de Boer, Imke J. M.; Hoogenboom, Ron L. A. P.; Haasnoot, Willem; Kijlstra, Aize; Meerburg, Bastiaan G.

2011-01-01

Dioxins and dioxin-like polychlorinated biphenyls (DL-PCBs) are hazardous toxic, ubiquitous and persistent chemical compounds, which can enter the food chain and accumulate up to higher trophic levels. Their determination requires sophisticated methods, expensive facilities and instruments, well-trained personnel and expensive chemical reagents. Ideally, real-time monitoring using rapid detection methods should be applied to detect possible contamination along the food chain in order to prevent human exposure. Sensor technology may be promising in this respect. This review gives the state of the art for detecting possible contamination with dioxins and DL-PCBs along the food chain of animal-source foods. The main detection methods applied (i.e., high resolution gas-chromatography combined with high resolution mass-spectrometry (HRGC/HRMS) and the chemical activated luciferase gene expression method (CALUX bioassay)), each have their limitations. Biosensors for detecting dioxins and related compounds, although still under development, show potential to overcome these limitations. Immunosensors and biomimetic-based biosensors potentially offer increased selectivity and sensitivity for dioxin and DL-PCB detection, while whole cell-based biosensors present interpretable biological results. The main shortcoming of current biosensors, however, is their detection level: this may be insufficient as limits for dioxins and DL-PCBs for food and feedstuffs are in pg per gram level. In addition, these contaminants are normally present in fat, a difficult matrix for biosensor detection. Therefore, simple and efficient extraction and clean-up procedures are required which may enable biosensors to detect dioxins and DL-PCBs contamination along the food chain. PMID:22247688

The need and potential of biosensors to detect dioxins and dioxin-like polychlorinated biphenyls along the milk, eggs and meat food chain.

PubMed

Chobtang, Jeerasak; de Boer, Imke J M; Hoogenboom, Ron L A P; Haasnoot, Willem; Kijlstra, Aize; Meerburg, Bastiaan G

2011-01-01

Dioxins and dioxin-like polychlorinated biphenyls (DL-PCBs) are hazardous toxic, ubiquitous and persistent chemical compounds, which can enter the food chain and accumulate up to higher trophic levels. Their determination requires sophisticated methods, expensive facilities and instruments, well-trained personnel and expensive chemical reagents. Ideally, real-time monitoring using rapid detection methods should be applied to detect possible contamination along the food chain in order to prevent human exposure. Sensor technology may be promising in this respect. This review gives the state of the art for detecting possible contamination with dioxins and DL-PCBs along the food chain of animal-source foods. The main detection methods applied (i.e., high resolution gas-chromatography combined with high resolution mass-spectrometry (HRGC/HRMS) and the chemical activated luciferase gene expression method (CALUX bioassay)), each have their limitations. Biosensors for detecting dioxins and related compounds, although still under development, show potential to overcome these limitations. Immunosensors and biomimetic-based biosensors potentially offer increased selectivity and sensitivity for dioxin and DL-PCB detection, while whole cell-based biosensors present interpretable biological results. The main shortcoming of current biosensors, however, is their detection level: this may be insufficient as limits for dioxins and DL-PCBs for food and feedstuffs are in pg per gram level. In addition, these contaminants are normally present in fat, a difficult matrix for biosensor detection. Therefore, simple and efficient extraction and clean-up procedures are required which may enable biosensors to detect dioxins and DL-PCBs contamination along the food chain.

Method and compositions for detecting of bloodstains using fluorescin-fluorescein reaction

DOEpatents

Di Benedetto, John; Kyle, Kevin; Boan, Terry; Marie, Charlene

2004-02-17

A method, compositions and kit are set forth for detecting blood stains. A reactant solution includes fluorescin solubilized (reduced) in acetic acid in ethanol. The solution may be buffered to a pH of approximately 9. After spraying the reactant solution on the suspected area an oxidizer is applied to promote the fluorescin to fluorescein reaction with the blood. The reacted fluorescein is then detected through luminescence for capture by photography.

Supervised machine learning on a network scale: application to seismic event classification and detection

NASA Astrophysics Data System (ADS)

Reynen, Andrew; Audet, Pascal

2017-09-01

A new method using a machine learning technique is applied to event classification and detection at seismic networks. This method is applicable to a variety of network sizes and settings. The algorithm makes use of a small catalogue of known observations across the entire network. Two attributes, the polarization and frequency content, are used as input to regression. These attributes are extracted at predicted arrival times for P and S waves using only an approximate velocity model, as attributes are calculated over large time spans. This method of waveform characterization is shown to be able to distinguish between blasts and earthquakes with 99 per cent accuracy using a network of 13 stations located in Southern California. The combination of machine learning with generalized waveform features is further applied to event detection in Oklahoma, United States. The event detection algorithm makes use of a pair of unique seismic phases to locate events, with a precision directly related to the sampling rate of the generalized waveform features. Over a week of data from 30 stations in Oklahoma, United States are used to automatically detect 25 times more events than the catalogue of the local geological survey, with a false detection rate of less than 2 per cent. This method provides a highly confident way of detecting and locating events. Furthermore, a large number of seismic events can be automatically detected with low false alarm, allowing for a larger automatic event catalogue with a high degree of trust.

Implementation of a novel efficient low cost method in structural health monitoring

NASA Astrophysics Data System (ADS)

Asadi, S.; Sepehry, N.; Shamshirsaz, M.; Vaghasloo, Y. A.

2017-05-01

In active structural health monitoring (SHM) methods, it is necessary to excite the structure with a preselected signal. More studies in the field of active SHM are focused on applying SHM on higher frequency ranges since it is possible to detect smaller damages, using higher excitation frequency. Also, to increase spatial domain of measurements and enhance signal to noise ratio (SNR), the amplitude of excitation signal is usually amplified. These issues become substantial where piezoelectric transducers with relatively high capacitance are used and consequently, need to utilize high power amplifiers becomes predominant. In this paper, a novel method named Step Excitation Method (SEM) is proposed and implemented for Lamb wave and transfer impedance-based SHM for damage detection in structures. Three different types of structure are studied: beam, plate and pipe. The related hardware is designed and fabricated which eliminates high power analog amplifiers and decreases complexity of driver significantly. Spectral Finite Element Method (SFEM) is applied to examine performance of proposed SEM. In proposed method, by determination of impulse response of the system, any input could be applied to the system by both finite element simulations and experiments without need for multiple measurements. The experimental results using SEM are compared with those obtained by conventional direct excitation method for healthy and damaged structures. The results show an improvement of amplitude resolution in damage detection comparing to conventional method which is due to achieving an SNR improvement up to 50%.

Automatic Implementation of Prony Analysis for Electromechanical Mode Identification from Phasor Measurements

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

Zhou, Ning; Huang, Zhenyu; Tuffner, Francis K.

2010-07-31

Small signal stability problems are one of the major threats to grid stability and reliability. Prony analysis has been successfully applied on ringdown data to monitor electromechanical modes of a power system using phasor measurement unit (PMU) data. To facilitate an on-line application of mode estimation, this paper developed a recursive algorithm for implementing Prony analysis and proposed an oscillation detection method to detect ringdown data in real time. By automatically detect ringdown data, the proposed method helps guarantee that Prony analysis is applied properly and timely on the ringdown data. Thus, the mode estimation results can be performed reliablymore » and timely. The proposed method is tested using Monte Carlo simulations based on a 17-machine model and is shown to be able to properly identify the oscillation data for on-line application of Prony analysis.« less

An evaluation of computer-aided disproportionality analysis for post-marketing signal detection.

PubMed

Lehman, H P; Chen, J; Gould, A L; Kassekert, R; Beninger, P R; Carney, R; Goldberg, M; Goss, M A; Kidos, K; Sharrar, R G; Shields, K; Sweet, A; Wiholm, B E; Honig, P K

2007-08-01

To understand the value of computer-aided disproportionality analysis (DA) in relation to current pharmacovigilance signal detection methods, four products were retrospectively evaluated by applying an empirical Bayes method to Merck's post-marketing safety database. Findings were compared with the prior detection of labeled post-marketing adverse events. Disproportionality ratios (empirical Bayes geometric mean lower 95% bounds for the posterior distribution (EBGM05)) were generated for product-event pairs. Overall (1993-2004 data, EBGM05> or =2, individual terms) results of signal detection using DA compared to standard methods were sensitivity, 31.1%; specificity, 95.3%; and positive predictive value, 19.9%. Using groupings of synonymous labeled terms, sensitivity improved (40.9%). More of the adverse events detected by both methods were detected earlier using DA and grouped (versus individual) terms. With 1939-2004 data, diagnostic properties were similar to those from 1993 to 2004. DA methods using Merck's safety database demonstrate sufficient sensitivity and specificity to be considered for use as an adjunct to conventional signal detection methods.

A Method Based on Wavelet Transforms for Source Detection in Photon-counting Detector Images. II. Application to ROSAT PSPC Images

NASA Astrophysics Data System (ADS)

Damiani, F.; Maggio, A.; Micela, G.; Sciortino, S.

1997-07-01

We apply to the specific case of images taken with the ROSAT PSPC detector our wavelet-based X-ray source detection algorithm presented in a companion paper. Such images are characterized by the presence of detector ``ribs,'' strongly varying point-spread function, and vignetting, so that their analysis provides a challenge for any detection algorithm. First, we apply the algorithm to simulated images of a flat background, as seen with the PSPC, in order to calibrate the number of spurious detections as a function of significance threshold and to ascertain that the spatial distribution of spurious detections is uniform, i.e., unaffected by the ribs; this goal was achieved using the exposure map in the detection procedure. Then, we analyze simulations of PSPC images with a realistic number of point sources; the results are used to determine the efficiency of source detection and the accuracy of output quantities such as source count rate, size, and position, upon a comparison with input source data. It turns out that sources with 10 photons or less may be confidently detected near the image center in medium-length (~104 s), background-limited PSPC exposures. The positions of sources detected near the image center (off-axis angles < 15') are accurate to within a few arcseconds. Output count rates and sizes are in agreement with the input quantities, within a factor of 2 in 90% of the cases. The errors on position, count rate, and size increase with off-axis angle and for detections of lower significance. We have also checked that the upper limits computed with our method are consistent with the count rates of undetected input sources. Finally, we have tested the algorithm by applying it on various actual PSPC images, among the most challenging for automated detection procedures (crowded fields, extended sources, and nonuniform diffuse emission). The performance of our method in these images is satisfactory and outperforms those of other current X-ray detection techniques, such as those employed to produce the MPE and WGA catalogs of PSPC sources, in terms of both detection reliability and efficiency. We have also investigated the theoretical limit for point-source detection, with the result that even sources with only 2-3 photons may be reliably detected using an efficient method in images with sufficiently high resolution and low background.

Research on intrusion detection based on Kohonen network and support vector machine

NASA Astrophysics Data System (ADS)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

In view of the problem of low detection accuracy and the long detection time of support vector machine, which directly applied to the network intrusion detection system. Optimization of SVM parameters can greatly improve the detection accuracy, but it can not be applied to high-speed network because of the long detection time. a method based on Kohonen neural network feature selection is proposed to reduce the optimization time of support vector machine parameters. Firstly, this paper is to calculate the weights of the KDD99 network intrusion data by Kohonen network and select feature by weight. Then, after the feature selection is completed, genetic algorithm (GA) and grid search method are used for parameter optimization to find the appropriate parameters and classify them by support vector machines. By comparing experiments, it is concluded that feature selection can reduce the time of parameter optimization, which has little influence on the accuracy of classification. The experiments suggest that the support vector machine can be used in the network intrusion detection system and reduce the missing rate.

Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.

ERIC Educational Resources Information Center

Muraki, Eiji

1999-01-01

Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…

Preliminary study of the use of radiotracers for leak detection in industrial applications

NASA Astrophysics Data System (ADS)

Wetchagarun, S.; Petchrak, A.; Tippayakul, C.

2015-05-01

One of the most widespread uses of radiotracers in the industrial applications is the leak detection of the systems. This technique can be applied, for example, to detect leak in heat exchangers or along buried industrial pipelines. The ability to perform online investigation is one of the most important advantages of the radiotracer technique over other non-radioactive leak detection methods. In this paper, a preliminary study of the leak detection using radiotracer in the laboratory scale was presented. Br-82 was selected for this work due to its chemical property, its suitable half-life and its on-site availability. The NH4Br in the form of aqueous solution was injected into the experimental system as the radiotracer. Three NaI detectors were placed along the pipelines to measure system flow rate and to detect the leakage from the piping system. The results obtained from the radiotracer technique were compared to those measured by other methods. It is found that the flow rate obtained from the radiotracer technique agreed well with the one obtained from the flow meter. The leak rate result, however, showed discrepancy between results obtained from two different measuring methods indicating further study on leak detection was required before applying this technique in the industrial system.

Detection of Melanoma Skin Cancer in Dermoscopy Images

NASA Astrophysics Data System (ADS)

Eltayef, Khalid; Li, Yongmin; Liu, Xiaohui

2017-02-01

Malignant melanoma is the most hazardous type of human skin cancer and its incidence has been rapidly increasing. Early detection of malignant melanoma in dermoscopy images is very important and critical, since its detection in the early stage can be helpful to cure it. Computer Aided Diagnosis systems can be very helpful to facilitate the early detection of cancers for dermatologists. In this paper, we present a novel method for the detection of melanoma skin cancer. To detect the hair and several noises from images, pre-processing step is carried out by applying a bank of directional filters. And therefore, Image inpainting method is implemented to fill in the unknown regions. Fuzzy C-Means and Markov Random Field methods are used to delineate the border of the lesion area in the images. The method was evaluated on a dataset of 200 dermoscopic images, and superior results were produced compared to alternative methods.

A comparison of automated crater detection methods

NASA Astrophysics Data System (ADS)

Bandeira, L.; Barreira, C.; Pina, P.; Saraiva, J.

2008-09-01

Abstract This work presents early results of a comparison between some common methodologies for automated crater detection. The three procedures considered were applied to images of the surface of Mars, thus illustrating some pros and cons of their use. We aim to establish the clear advantages in using this type of methods in the study of planetary surfaces.

Freeze-thaw method improves the detection of volatile compounds in insects using Headspace Solid-Phase Microextraction (HS-SPME)

USDA-ARS?s Scientific Manuscript database

Headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography–mass spectrometry (GC-MS) is commonly used in analyzing insect volatiles. In order to improve the detection of volatiles in insects, a freeze-thaw method was applied to insect samples before the HS-SPME-GC-MS analysis. ...

Determination of patulin in commercial apple juice by micellar electrokinetic chromatography.

PubMed

Murillo, M; González-Peñas, E; Amézqueta, S

2008-01-01

A novel and validated micellar electrokinetic capillary chromatography (MEKC) method using ultraviolet detection (UV) has been applied to the quantitative analysis of patulin (PAT) in commercial apple juice. Patulin was extracted from samples with an ethylacetate solution. The micellar electrokinetic capillary chromatography (MECK) parameters studied for method optimization were buffer composition, voltage, temperature, and a separation between PAT and 5-hydroxymethylfurfural (HMF) (main interference in apple juice PAT analysis) peaks until reaching baseline. The method passes a series of validation tests including selectivity, linearity, limit of detection and quantification (0.7 and 2.5 microgL(-1), respectively), precision (within and between-day variability) and recovery (80.2% RSD=4%), accuracy, and robustness. This method was successfully applied to the measurement of 20 apple juice samples obtained from different supermarkets. One hundred percent of the samples were contaminated with a level greater than the limit of detection, with mean and median values of 41.3 and 35.7 microgL(-1), respectively.

Feature-Based Methods for Landmine Detection with Ground Penetrating Radar

DTIC Science & Technology

2012-09-27

of abstraction without having to resort to assumptions about the events. DS fusion was applied to handwriting recognition [67], decision making [68...has been applied to landmine detection [80], and (in a different way) to handwriting recognition [46], and fusion of social choices (voting...applications to handwriting recognition, IEEE Transactions on Systems, Man and Cybernetics 22 (3) (1992) 418–435. [68] M. Beynon, D. Cosker, A.D. Marshall

Surveillance theory applied to virus detection: a case for targeted discovery

USGS Publications Warehouse

Bogich, Tiffany L.; Anthony, Simon J.; Nichols, James D.

2013-01-01

Virus detection and mathematical modeling have gone through rapid developments in the past decade. Both offer new insights into the epidemiology of infectious disease and characterization of future risk; however, modeling has not yet been applied to designing the best surveillance strategies for viral and pathogen discovery. We review recent developments and propose methods to integrate viral and pathogen discovery and mathematical modeling through optimal surveillance theory, arguing for a more targeted approach to novel virus detection guided by the principles of adaptive management and structured decision-making.

Improving space debris detection in GEO ring using image deconvolution

NASA Astrophysics Data System (ADS)

Núñez, Jorge; Núñez, Anna; Montojo, Francisco Javier; Condominas, Marta

2015-07-01

In this paper we present a method based on image deconvolution to improve the detection of space debris, mainly in the geostationary ring. Among the deconvolution methods we chose the iterative Richardson-Lucy (R-L), as the method that achieves better goals with a reasonable amount of computation. For this work, we used two sets of real 4096 × 4096 pixel test images obtained with the Telescope Fabra-ROA at Montsec (TFRM). Using the first set of data, we establish the optimal number of iterations in 7, and applying the R-L method with 7 iterations to the images, we show that the astrometric accuracy does not vary significantly while the limiting magnitude of the deconvolved images increases significantly compared to the original ones. The increase is in average about 1.0 magnitude, which means that objects up to 2.5 times fainter can be detected after deconvolution. The application of the method to the second set of test images, which includes several faint objects, shows that, after deconvolution, up to four previously undetected faint objects are detected in a single frame. Finally, we carried out a study of some economic aspects of applying the deconvolution method, showing that an important economic impact can be envisaged.

Polarization-based and specular-reflection-based noncontact latent fingerprint imaging and lifting

NASA Astrophysics Data System (ADS)

Lin, Shih-Schön; Yemelyanov, Konstantin M.; Pugh, Edward N., Jr.; Engheta, Nader

2006-09-01

In forensic science the finger marks left unintentionally by people at a crime scene are referred to as latent fingerprints. Most existing techniques to detect and lift latent fingerprints require application of a certain material directly onto the exhibit. The chemical and physical processing applied to the fingerprint potentially degrades or prevents further forensic testing on the same evidence sample. Many existing methods also have deleterious side effects. We introduce a method to detect and extract latent fingerprint images without applying any powder or chemicals on the object. Our method is based on the optical phenomena of polarization and specular reflection together with the physiology of fingerprint formation. The recovered image quality is comparable to existing methods. In some cases, such as the sticky side of tape, our method shows unique advantages.

Evaluation of two outlier-detection-based methods for detecting tissue-selective genes from microarray data.

PubMed

Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

2007-05-01

Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent's non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent's method is not suitable for ROKU.

Validation of the Applied Biosystems 7500 Fast Instrument for Detection of Listeria Species with the SureTect Listeria Species PCR Assay.

PubMed

Cloke, Jonathan; Arizanova, Julia; Crabtree, David; Simpson, Helen; Evans, Katharine; Vaahtoranta, Laura; Palomäki, Jukka-Pekka; Artimo, Paulus; Huang, Feng; Liikanen, Maria; Koskela, Suvi; Chen, Yi

2016-01-01

The Thermo Scientific™ SureTect™ Listeria species Real-Time PCR Assay was certified during 2013 by the AOAC Research Institute (RI) Performance Tested Methods(SM) program as a rapid method for the detection of Listeria species from a wide range of food matrixes and surface samples. A method modification study was conducted in 2015 to extend the matrix claims of the product to a wider range of food matrixes. This report details the method modification study undertaken to extend the use of this PCR kit to the Applied Biosystems™ 7500 Fast PCR Instrument and Applied Biosystems RapidFinder™ Express 2.0 software allowing use of the assay on a 96-well format PCR cycler in addition to the current workflow, using the 24-well Thermo Scientific PikoReal™ PCR Instrument and Thermo Scientific SureTect software. The method modification study presented in this report was assessed by the AOAC-RI as being a level 2 method modification study, necessitating a method developer study on a representative range of food matrixes covering raw ground turkey, 2% fat pasteurized milk, and bagged lettuce as well as stainless steel surface samples. All testing was conducted in comparison to the reference method detailed in International Organization for Standardization (ISO) 6579:2002. No significant difference by probability of detection statistical analysis was found between the SureTect Listeria species PCR Assay or the ISO reference method methods for any of the three food matrixes and the surface samples analyzed during the study.

Reliably detectable flaw size for NDE methods that use calibration

NASA Astrophysics Data System (ADS)

Koshti, Ajay M.

2017-04-01

Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-1823 and associated mh18232 POD software gives most common methods of POD analysis. In this paper, POD analysis is applied to an NDE method, such as eddy current testing, where calibration is used. NDE calibration standards have known size artificial flaws such as electro-discharge machined (EDM) notches and flat bottom hole (FBH) reflectors which are used to set instrument sensitivity for detection of real flaws. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. Therefore, it is important to correlate signal responses from real flaws with signal responses form artificial flaws used in calibration process to determine reliably detectable flaw size.

Reliably Detectable Flaw Size for NDE Methods that Use Calibration

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

2017-01-01

Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-1823 and associated mh1823 POD software gives most common methods of POD analysis. In this paper, POD analysis is applied to an NDE method, such as eddy current testing, where calibration is used. NDE calibration standards have known size artificial flaws such as electro-discharge machined (EDM) notches and flat bottom hole (FBH) reflectors which are used to set instrument sensitivity for detection of real flaws. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. Therefore, it is important to correlate signal responses from real flaws with signal responses form artificial flaws used in calibration process to determine reliably detectable flaw size.

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

PubMed

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

Detection of artifacts from high energy bursts in neonatal EEG.

PubMed

Bhattacharyya, Sourya; Biswas, Arunava; Mukherjee, Jayanta; Majumdar, Arun Kumar; Majumdar, Bandana; Mukherjee, Suchandra; Singh, Arun Kumar

2013-11-01

Detection of non-cerebral activities or artifacts, intermixed within the background EEG, is essential to discard them from subsequent pattern analysis. The problem is much harder in neonatal EEG, where the background EEG contains spikes, waves, and rapid fluctuations in amplitude and frequency. Existing artifact detection methods are mostly limited to detect only a subset of artifacts such as ocular, muscle or power line artifacts. Few methods integrate different modules, each for detection of one specific category of artifact. Furthermore, most of the reference approaches are implemented and tested on adult EEG recordings. Direct application of those methods on neonatal EEG causes performance deterioration, due to greater pattern variation and inherent complexity. A method for detection of a wide range of artifact categories in neonatal EEG is thus required. At the same time, the method should be specific enough to preserve the background EEG information. The current study describes a feature based classification approach to detect both repetitive (generated from ECG, EMG, pulse, respiration, etc.) and transient (generated from eye blinking, eye movement, patient movement, etc.) artifacts. It focuses on artifact detection within high energy burst patterns, instead of detecting artifacts within the complete background EEG with wide pattern variation. The objective is to find true burst patterns, which can later be used to identify the Burst-Suppression (BS) pattern, which is commonly observed during newborn seizure. Such selective artifact detection is proven to be more sensitive to artifacts and specific to bursts, compared to the existing artifact detection approaches applied on the complete background EEG. Several time domain, frequency domain, statistical features, and features generated by wavelet decomposition are analyzed to model the proposed bi-classification between burst and artifact segments. A feature selection method is also applied to select the feature subset producing highest classification accuracy. The suggested feature based classification method is executed using our recorded neonatal EEG dataset, consisting of burst and artifact segments. We obtain 78% sensitivity and 72% specificity as the accuracy measures. The accuracy obtained using the proposed method is found to be about 20% higher than that of the reference approaches. Joint use of the proposed method with our previous work on burst detection outperforms reference methods on simultaneous burst and artifact detection. As the proposed method supports detection of a wide range of artifact patterns, it can be improved to incorporate the detection of artifacts within other seizure patterns and background EEG information as well. © 2013 Elsevier Ltd. All rights reserved.

Novel Application of FTIR Spectroscopy for the Passive Standoff Detection of Radiological Materials

DTIC Science & Technology

2006-08-01

possibility of applying the long-wave passive standoff detection technique to the identification of radiological materials. This work is based on...infrared (FTIR) radiometry is a well-known technique for detecting and identifying chemical warfare agents. In addition to these potential threats...necessary tools and techniques available for detecting and identifying radioactive products. At present, the main detection techniques depend on methods

Semi-Supervised Novelty Detection with Adaptive Eigenbases, and Application to Radio Transients

NASA Technical Reports Server (NTRS)

Thompson, David R.; Majid, Walid A.; Reed, Colorado J.; Wagstaff, Kiri L.

2011-01-01

We present a semi-supervised online method for novelty detection and evaluate its performance for radio astronomy time series data. Our approach uses adaptive eigenbases to combine 1) prior knowledge about uninteresting signals with 2) online estimation of the current data properties to enable highly sensitive and precise detection of novel signals. We apply the method to the problem of detecting fast transient radio anomalies and compare it to current alternative algorithms. Tests based on observations from the Parkes Multibeam Survey show both effective detection of interesting rare events and robustness to known false alarm anomalies.

Development of a complex of instrumental nuclear-physical methods to detect PGE, Re, Au, and Ag in hard-to-analyze rocks and complex ores

NASA Astrophysics Data System (ADS)

Kolmogorov, Yu. P.; Mezentsev, N. A.; Mironov, A. G.; Parkhomenko, V. S.; Spiridonov, A. M.; Shaporenko, A. D.; Yusupov, T. S.; Zhmodik, S. M.; Zolotarev, K. V.; Anoshin, G. N.

2009-05-01

A system of methods to detect platinum group elements (PGE): Re, Au, and Ag in hard-to-analyze rocks and complex ores has been developed. It applies the SRXRF for Ru, Rh, Pd, and Ag and the INAA method for Os, Ir, Pt and Ag and implies mechanoactivation of probes to study. The results of measurement of standard samples of carbonaceous rocks and ores in order to PGE, gold, and silver confirm the possibility of detecting some of the above-listed elements with a detection limit of 10 ppb.

Challenging a bioinformatic tool’s ability to detect microbial contaminants using in silico whole genome sequencing data

PubMed Central

Zook, Justin M.; Morrow, Jayne B.; Lin, Nancy J.

2017-01-01

High sensitivity methods such as next generation sequencing and polymerase chain reaction (PCR) are adversely impacted by organismal and DNA contaminants. Current methods for detecting contaminants in microbial materials (genomic DNA and cultures) are not sensitive enough and require either a known or culturable contaminant. Whole genome sequencing (WGS) is a promising approach for detecting contaminants due to its sensitivity and lack of need for a priori assumptions about the contaminant. Prior to applying WGS, we must first understand its limitations for detecting contaminants and potential for false positives. Herein we demonstrate and characterize a WGS-based approach to detect organismal contaminants using an existing metagenomic taxonomic classification algorithm. Simulated WGS datasets from ten genera as individuals and binary mixtures of eight organisms at varying ratios were analyzed to evaluate the role of contaminant concentration and taxonomy on detection. For the individual genomes the false positive contaminants reported depended on the genus, with Staphylococcus, Escherichia, and Shigella having the highest proportion of false positives. For nearly all binary mixtures the contaminant was detected in the in-silico datasets at the equivalent of 1 in 1,000 cells, though F. tularensis was not detected in any of the simulated contaminant mixtures and Y. pestis was only detected at the equivalent of one in 10 cells. Once a WGS method for detecting contaminants is characterized, it can be applied to evaluate microbial material purity, in efforts to ensure that contaminants are characterized in microbial materials used to validate pathogen detection assays, generate genome assemblies for database submission, and benchmark sequencing methods. PMID:28924496

Non-destructive scanning for applied stress by the continuous magnetic Barkhausen noise method

NASA Astrophysics Data System (ADS)

Franco Grijalba, Freddy A.; Padovese, L. R.

2018-01-01

This paper reports the use of a non-destructive continuous magnetic Barkhausen noise technique to detect applied stress on steel surfaces. The stress profile generated in a sample of 1070 steel subjected to a three-point bending test is analyzed. The influence of different parameters such as pickup coil type, scanner speed, applied magnetic field and frequency band analyzed on the effectiveness of the technique is investigated. A moving smoothing window based on a second-order statistical moment is used to analyze the time signal. The findings show that the technique can be used to detect applied stress profiles.

Eye pupil detection system using an ensemble of regression forest and fast radial symmetry transform with a near infrared camera

NASA Astrophysics Data System (ADS)

Jeong, Mira; Nam, Jae-Yeal; Ko, Byoung Chul

2017-09-01

In this paper, we focus on pupil center detection in various video sequences that include head poses and changes in illumination. To detect the pupil center, we first find four eye landmarks in each eye by using cascade local regression based on a regression forest. Based on the rough location of the pupil, a fast radial symmetric transform is applied using the previously found pupil location to rearrange the fine pupil center. As the final step, the pupil displacement is estimated between the previous frame and the current frame to maintain the level of accuracy against a false locating result occurring in a particular frame. We generated a new face dataset, called Keimyung University pupil detection (KMUPD), with infrared camera. The proposed method was successfully applied to the KMUPD dataset, and the results indicate that its pupil center detection capability is better than that of other methods and with a shorter processing time.

SEMICONDUCTOR TECHNOLOGY A signal processing method for the friction-based endpoint detection system of a CMP process

NASA Astrophysics Data System (ADS)

Chi, Xu; Dongming, Guo; Zhuji, Jin; Renke, Kang

2010-12-01

A signal processing method for the friction-based endpoint detection system of a chemical mechanical polishing (CMP) process is presented. The signal process method uses the wavelet threshold denoising method to reduce the noise contained in the measured original signal, extracts the Kalman filter innovation from the denoised signal as the feature signal, and judges the CMP endpoint based on the feature of the Kalman filter innovation sequence during the CMP process. Applying the signal processing method, the endpoint detection experiments of the Cu CMP process were carried out. The results show that the signal processing method can judge the endpoint of the Cu CMP process.

Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

NASA Technical Reports Server (NTRS)

Bedka, Kristopher M.; Dworak, Richard; Brunner, Jason; Feltz, Wayne

2012-01-01

Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

Detecting multiple outliers in linear functional relationship model for circular variables using clustering technique

NASA Astrophysics Data System (ADS)

Mokhtar, Nurkhairany Amyra; Zubairi, Yong Zulina; Hussin, Abdul Ghapor

2017-05-01

Outlier detection has been used extensively in data analysis to detect anomalous observation in data and has important application in fraud detection and robust analysis. In this paper, we propose a method in detecting multiple outliers for circular variables in linear functional relationship model. Using the residual values of the Caires and Wyatt model, we applied the hierarchical clustering procedure. With the use of tree diagram, we illustrate the graphical approach of the detection of outlier. A simulation study is done to verify the accuracy of the proposed method. Also, an illustration to a real data set is given to show its practical applicability.

Outlier Detection in Urban Air Quality Sensor Networks.

PubMed

van Zoest, V M; Stein, A; Hoek, G

2018-01-01

Low-cost urban air quality sensor networks are increasingly used to study the spatio-temporal variability in air pollutant concentrations. Recently installed low-cost urban sensors, however, are more prone to result in erroneous data than conventional monitors, e.g., leading to outliers. Commonly applied outlier detection methods are unsuitable for air pollutant measurements that have large spatial and temporal variations as occur in urban areas. We present a novel outlier detection method based upon a spatio-temporal classification, focusing on hourly NO 2 concentrations. We divide a full year's observations into 16 spatio-temporal classes, reflecting urban background vs. urban traffic stations, weekdays vs. weekends, and four periods per day. For each spatio-temporal class, we detect outliers using the mean and standard deviation of the normal distribution underlying the truncated normal distribution of the NO 2 observations. Applying this method to a low-cost air quality sensor network in the city of Eindhoven, the Netherlands, we found 0.1-0.5% of outliers. Outliers could reflect measurement errors or unusual high air pollution events. Additional evaluation using expert knowledge is needed to decide on treatment of the identified outliers. We conclude that our method is able to detect outliers while maintaining the spatio-temporal variability of air pollutant concentrations in urban areas.

Procedure for rapid concentration and detection of enteric viruses from berries and vegetables.

PubMed

Butot, S; Putallaz, T; Sánchez, G

2007-01-01

Several hepatitis A virus (HAV) and norovirus (NV) outbreaks due to consumption of berries and vegetables have been reported during recent years. To facilitate the detection of enteric viruses that may be present on different fresh and frozen products, we developed a rapid and sensitive detection method for HAV, NV, and rotavirus (RV). Initial experiments focused on optimizing the composition of the elution buffer, improving the viral concentration method, and evaluating the performance of various extraction kits. Viruses were extracted from the food surface by a direct elution method in a glycine-Tris (pH 9.5) buffer containing 1% beef extract and concentrated by ultrafiltration. Occasionally, PCR inhibitors were present in the processed berry samples, which gave relatively poor detection limits. However, this problem was overcome by adding a pectinase treatment in the protocol, which markedly improved the sensitivity of the method. After optimization, this concentration method was applied in combination with real-time reverse transcription-PCR (RT-PCR) using specific primers in various types of berries and vegetables. The average detection limits were 1 50% tissue culture infective dose (TCID(50)), 54 RT-PCR units, and 0.02 TCID(50) per 15 g of food for HAV, NV, and RV, respectively. Based on our results, it is concluded that this procedure is suitable to detect and quantify enteric viruses within 6 h and can be applied for surveillance of enteric viruses in fresh and frozen products.

Detection of Salmonella invA gene in shrimp enrichment culture by polymerase chain reaction.

PubMed

Upadhyay, Bishnu Prasad; Utrarachkij, Fuangfa; Thongshoob, Jarinee; Mahakunkijcharoen, Yuvadee; Wongchinda, Niracha; Suthienkul, Orasa; Khusmith, Srisin

2010-03-01

Contamination of seafood with salmonellae is a major public health concern. Detection of Salmonella by standard culture methods is time consuming. In this study, an enrichment culture step prior to polymerase chain reaction (PCR) was applied to detect 284 bp fragment of Salmonella invA in comparison with the conventional culture method in 100 shrimp samples collected from four different shrimp farms and fresh food markets around Bangkok. Samples were pre-enriched in non-selective lactose broth (LB) and selective tetrathionate broth (TTB). PCR detection limit was 10 pg and 10(4) cfu/ml of viable salmonellae with 100% specificity. PCR assay detected 19 different Salmonella serovars belonging to 8 serogroups (B, C1, C2-C3, D1, E1, E4 and K) commonly found in clinical and environmental samples in Thailand. The detection rate of PCR following TTB enrichment (24%) was higher than conventional culture method (19%). PCR following TTB, but not in LB enrichment allowed salmonella detection with 84% sensitivity, 90% specificity and 89% accuracy. Shrimp samples collected from fresh food markets had higher levels of contaminated salmonellae than those from shrimp farms. The results indicated that incorporation of an enrichment step prior to PCR has the potential to be applied for detection of naturally contaminated salmonellae in food, environment and clinical samples.

Exploring supervised and unsupervised methods to detect topics in biomedical text

PubMed Central

Lee, Minsuk; Wang, Weiqing; Yu, Hong

2006-01-01

Background Topic detection is a task that automatically identifies topics (e.g., "biochemistry" and "protein structure") in scientific articles based on information content. Topic detection will benefit many other natural language processing tasks including information retrieval, text summarization and question answering; and is a necessary step towards the building of an information system that provides an efficient way for biologists to seek information from an ocean of literature. Results We have explored the methods of Topic Spotting, a task of text categorization that applies the supervised machine-learning technique naïve Bayes to assign automatically a document into one or more predefined topics; and Topic Clustering, which apply unsupervised hierarchical clustering algorithms to aggregate documents into clusters such that each cluster represents a topic. We have applied our methods to detect topics of more than fifteen thousand of articles that represent over sixteen thousand entries in the Online Mendelian Inheritance in Man (OMIM) database. We have explored bag of words as the features. Additionally, we have explored semantic features; namely, the Medical Subject Headings (MeSH) that are assigned to the MEDLINE records, and the Unified Medical Language System (UMLS) semantic types that correspond to the MeSH terms, in addition to bag of words, to facilitate the tasks of topic detection. Our results indicate that incorporating the MeSH terms and the UMLS semantic types as additional features enhances the performance of topic detection and the naïve Bayes has the highest accuracy, 66.4%, for predicting the topic of an OMIM article as one of the total twenty-five topics. Conclusion Our results indicate that the supervised topic spotting methods outperformed the unsupervised topic clustering; on the other hand, the unsupervised topic clustering methods have the advantages of being robust and applicable in real world settings. PMID:16539745

Fluorometric method for inorganic pyrophosphatase activity detection and inhibitor screening based on click chemistry.

PubMed

Xu, Kefeng; Chen, Zhonghui; Zhou, Ling; Zheng, Ou; Wu, Xiaoping; Guo, Longhua; Qiu, Bin; Lin, Zhenyu; Chen, Guonan

2015-01-06

A fluorometric method for pyrophosphatase (PPase) activity detection was developed based on click chemistry. Cu(II) can coordinate with pyrophosphate (PPi), the addition of pyrophosphatase (PPase) into the above system can destroy the coordinate compound because PPase catalyzes the hydrolysis of PPi into inorganic phosphate and produces free Cu(II), and free Cu(II) can be reduced by sodium ascorbate (SA) to form Cu(I), which in turn initiates the ligating reaction between nonfluorescent 3-azidocoumarins and terminal alkynes to produce a highly fluorescent triazole complex, based on which, a simple and sensitive turn on fluorometric method for PPase can be developed. The fluorescence intensity of the system has a linear relationship with the logarithm of the PPase concentration in the range of 0.5 and 10 mU with a detection limit down to 0.2 mU (S/N = 3). This method is cost-effective and convenient without any labels or complicated operations. The proposed system was applied to screen the potential PPase inhibitor with high efficiency. The proposed method can be applied to diagnosis of PPase-related diseases.

Analysis of phenolic acids by ionic liquid-in-water microemulsion liquid chromatography coupled with ultraviolet and electrochemical detector.

PubMed

Peng, Li-Qing; Cao, Jun; Du, Li-Jing; Zhang, Qi-Dong; Shi, Yu-Tin; Xu, Jing-Jing

2017-05-26

An environmentally friendly ionic liquid-in-water (IL/W) microemulsion was established and applied as mobile phase in microemulsion liquid chromatography (MELC) with ultraviolet (UV) detection or electrochemical detector (ECD) for analysis of phenolic compounds in real samples. The optimal condition of the method was using the best composition of microemulsion (0.2% w/v [HMIM]PF 6 , 1.0% w/v SDS, 3.0% w/v n-butanol, 95.8% v/v water, pH 2.5) with UV detection. The validation results indicated that the method provided high degree of sensitivity, precision and accuracy with the low limit of detections ranged from 17.9-238ng/mL, satisfactory mean recovery values in the range of 80.1-105% and good linearity (r 2 >0.9994). Additionally, this method exhibited high selectivity and resolution for the analytes and was more eco-friendly compared with traditional MELC method. Consequently, the established IL/W MELC method was successfully applied to simultaneously separate and determine target compounds in Danshen sample and its preparation. Copyright © 2017 Elsevier B.V. All rights reserved.

An improved PCA method with application to boiler leak detection.

PubMed

Sun, Xi; Marquez, Horacio J; Chen, Tongwen; Riaz, Muhammad

2005-07-01

Principal component analysis (PCA) is a popular fault detection technique. It has been widely used in process industries, especially in the chemical industry. In industrial applications, achieving a sensitive system capable of detecting incipient faults, which maintains the false alarm rate to a minimum, is a crucial issue. Although a lot of research has been focused on these issues for PCA-based fault detection and diagnosis methods, sensitivity of the fault detection scheme versus false alarm rate continues to be an important issue. In this paper, an improved PCA method is proposed to address this problem. In this method, a new data preprocessing scheme and a new fault detection scheme designed for Hotelling's T2 as well as the squared prediction error are developed. A dynamic PCA model is also developed for boiler leak detection. This new method is applied to boiler water/steam leak detection with real data from Syncrude Canada's utility plant in Fort McMurray, Canada. Our results demonstrate that the proposed method can effectively reduce false alarm rate, provide effective and correct leak alarms, and give early warning to operators.

An electromagnetic induction method for underground target detection and characterization

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

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

1997-01-01

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

An effective hair detection algorithm for dermoscopic melanoma images of skin lesions

NASA Astrophysics Data System (ADS)

Chakraborti, Damayanti; Kaur, Ravneet; Umbaugh, Scott; LeAnder, Robert

2016-09-01

Dermoscopic images are obtained using the method of skin surface microscopy. Pigmented skin lesions are evaluated in terms of texture features such as color and structure. Artifacts, such as hairs, bubbles, black frames, ruler-marks, etc., create obstacles that prevent accurate detection of skin lesions by both clinicians and computer-aided diagnosis. In this article, we propose a new algorithm for the automated detection of hairs, using an adaptive, Canny edge-detection method, followed by morphological filtering and an arithmetic addition operation. The algorithm was applied to 50 dermoscopic melanoma images. In order to ascertain this method's relative detection accuracy, it was compared to the Razmjooy hair-detection method [1], using segmentation error (SE), true detection rate (TDR) and false positioning rate (FPR). The new method produced 6.57% SE, 96.28% TDR and 3.47% FPR, compared to 15.751% SE, 86.29% TDR and 11.74% FPR produced by the Razmjooy method [1]. Because of the 7.27-9.99% improvement in those parameters, we conclude that the new algorithm produces much better results for detecting thick, thin, dark and light hairs. The new method proposed here, shows an appreciable difference in the rate of detecting bubbles, as well.

A novel strategy for rapid detection of NT-proBNP

NASA Astrophysics Data System (ADS)

Cui, Qiyao; Sun, Honghao; Zhu, Hui

2017-09-01

In order to establish a simple, rapid, sensitive, and specific quantitative assay to detect the biomarkers of heart failure, in this study, biotin-streptavidin technology was employed with fluorescence immunochromatographic assay to detect the concentration of the biomarkers in serum, and this method was applied to detect NT-proBNP, which is valuable for diagnostic evaluation of heart failure.

Datasets of Odontocete Sounds Annotated for Developing Automatic Detection Methods

DTIC Science & Technology

2010-12-01

Passive acoustic detection of Minke whales (Balaenoptera acutorostrata) off the West Coast of Kauai, HI. Book of abstracts, Fourth International...Workshop on Detection , Classification and Localization of Marine Mammals using Passive Acoustics , Pavia, Italy, Sept. 10- 13, 2009, p. 57. Roch, M., Y...Mellinger, and D. Gillespie. 2010. Comparison of beaked whale detection algorithms. Applied Acoustics 71:1043-1049. 8 References

Novel method for edge detection of retinal vessels based on the model of the retinal vascular network and mathematical morphology

NASA Astrophysics Data System (ADS)

Xu, Lei; Zheng, Xiaoxiang; Zhang, Hengyi; Yu, Yajun

1998-09-01

Accurate edge detection of retinal vessels is a prerequisite for quantitative analysis of subtle morphological changes of retinal vessels under different pathological conditions. A novel method for edge detection of retinal vessels is presented in this paper. Methods: (1) Wavelet-based image preprocessing. (2) The signed edge detection algorithm and mathematical morphological operation are applied to get the approximate regions that contain retinal vessels. (3) By convolving the preprocessed image with a LoG operator only on the detected approximate regions of retinal vessels, followed by edges refining, clear edge maps of the retinal vessels are fast obtained. Results: A detailed performance evaluation together with the existing techniques is given to demonstrate the strong features of our method. Conclusions: True edge locations of retinal vessels can be fast detected with continuous structures of retinal vessels, less non- vessel segments left and insensitivity to noise. The method is also suitable for other application fields such as road edge detection.

Efficient method for events detection in phonocardiographic signals

NASA Astrophysics Data System (ADS)

Martinez-Alajarin, Juan; Ruiz-Merino, Ramon

2005-06-01

The auscultation of the heart is still the first basic analysis tool used to evaluate the functional state of the heart, as well as the first indicator used to submit the patient to a cardiologist. In order to improve the diagnosis capabilities of auscultation, signal processing algorithms are currently being developed to assist the physician at primary care centers for adult and pediatric population. A basic task for the diagnosis from the phonocardiogram is to detect the events (main and additional sounds, murmurs and clicks) present in the cardiac cycle. This is usually made by applying a threshold and detecting the events that are bigger than the threshold. However, this method usually does not allow the detection of the main sounds when additional sounds and murmurs exist, or it may join several events into a unique one. In this paper we present a reliable method to detect the events present in the phonocardiogram, even in the presence of heart murmurs or additional sounds. The method detects relative maxima peaks in the amplitude envelope of the phonocardiogram, and computes a set of parameters associated with each event. Finally, a set of characteristics is extracted from each event to aid in the identification of the events. Besides, the morphology of the murmurs is also detected, which aids in the differentiation of different diseases that can occur in the same temporal localization. The algorithms have been applied to real normal heart sounds and murmurs, achieving satisfactory results.

Nonrigid registration of 3D longitudinal optical coherence tomography volumes with choroidal neovascularization

NASA Astrophysics Data System (ADS)

Wei, Qiangding; Shi, Fei; Zhu, Weifang; Xiang, Dehui; Chen, Haoyu; Chen, Xinjian

2017-02-01

In this paper, we propose a 3D registration method for retinal optical coherence tomography (OCT) volumes. The proposed method consists of five main steps: First, a projection image of the 3D OCT scan is created. Second, the vessel enhancement filter is applied on the projection image to detect vessel shadow. Third, landmark points are extracted based on both vessel positions and layer information. Fourth, the coherent point drift method is used to align retinal OCT volumes. Finally, a nonrigid B-spline-based registration method is applied to find the optimal transform to match the data. We applied this registration method on 15 3D OCT scans of patients with Choroidal Neovascularization (CNV). The Dice coefficients (DSC) between layers are greatly improved after applying the nonrigid registration.

Ship heading and velocity analysis by wake detection in SAR images

NASA Astrophysics Data System (ADS)

Graziano, Maria Daniela; D'Errico, Marco; Rufino, Giancarlo

2016-11-01

With the aim of ship-route estimation, a wake detection method is developed and applied to COSMO/SkyMed and TerraSAR-X Stripmap SAR images over the Gulf of Naples, Italy. In order to mitigate the intrinsic limitations of the threshold logic, the algorithm identifies the wake features according to the hydrodynamic theory. A post-detection validation phase is performed to classify the features as real wake structures by means of merit indexes defined in the intensity domain. After wake reconstruction, ship heading is evaluated on the basis of turbulent wake direction and ship velocity is estimated by both techniques of azimuth shift and Kelvin pattern wavelength. The method is tested over 34 ship wakes identified by visual inspection in both HH and VV images at different incidence angles. For all wakes, no missed detections are reported and at least the turbulent and one narrow-V wakes are correctly identified, with ship heading successfully estimated. Also, the azimuth shift method is applied to estimate velocity for the 10 ships having route with sufficient angular separation from the satellite ground track. In one case ship velocity is successfully estimated with both methods, showing agreement within 14%.

Vital sign sensing method based on EMD in terahertz band

NASA Astrophysics Data System (ADS)

Xu, Zhengwu; Liu, Tong

2014-12-01

Non-contact respiration and heartbeat rates detection could be applied to find survivors trapped in the disaster or the remote monitoring of the respiration and heartbeat of a patient. This study presents an improved algorithm that extracts the respiration and heartbeat rates of humans by utilizing the terahertz radar, which further lessens the effects of noise, suppresses the cross-term, and enhances the detection accuracy. A human target echo model for the terahertz radar is first presented. Combining the over-sampling method, low-pass filter, and Empirical Mode Decomposition improves the signal-to-noise ratio. The smoothed pseudo Wigner-Ville distribution time-frequency technique and the centroid of the spectrogram are used to estimate the instantaneous velocity of the target's cardiopulmonary motion. The down-sampling method is adopted to prevent serious distortion. Finally, a second time-frequency analysis is applied to the centroid curve to extract the respiration and heartbeat rates of the individual. Simulation results show that compared with the previously presented vital sign sensing method, the improved algorithm enhances the signal-to-noise ratio to 1 dB with a detection accuracy of 80%. The improved algorithm is an effective approach for the detection of respiration and heartbeat signal in a complicated environment.

Spectral methods to detect surface mines

NASA Astrophysics Data System (ADS)

Winter, Edwin M.; Schatten Silvious, Miranda

2008-04-01

Over the past five years, advances have been made in the spectral detection of surface mines under minefield detection programs at the U. S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD). The problem of detecting surface land mines ranges from the relatively simple, the detection of large anti-vehicle mines on bare soil, to the very difficult, the detection of anti-personnel mines in thick vegetation. While spatial and spectral approaches can be applied to the detection of surface mines, spatial-only detection requires many pixels-on-target such that the mine is actually imaged and shape-based features can be exploited. This method is unreliable in vegetated areas because only part of the mine may be exposed, while spectral detection is possible without the mine being resolved. At NVESD, hyperspectral and multi-spectral sensors throughout the reflection and thermal spectral regimes have been applied to the mine detection problem. Data has been collected on mines in forest and desert regions and algorithms have been developed both to detect the mines as anomalies and to detect the mines based on their spectral signature. In addition to the detection of individual mines, algorithms have been developed to exploit the similarities of mines in a minefield to improve their detection probability. In this paper, the types of spectral data collected over the past five years will be summarized along with the advances in algorithm development.

Universal ligation-detection-reaction microarray applied for compost microbes

PubMed Central

Hultman, Jenni; Ritari, Jarmo; Romantschuk, Martin; Paulin, Lars; Auvinen, Petri

2008-01-01

Background Composting is one of the methods utilised in recycling organic communal waste. The composting process is dependent on aerobic microbial activity and proceeds through a succession of different phases each dominated by certain microorganisms. In this study, a ligation-detection-reaction (LDR) based microarray method was adapted for species-level detection of compost microbes characteristic of each stage of the composting process. LDR utilises the specificity of the ligase enzyme to covalently join two adjacently hybridised probes. A zip-oligo is attached to the 3'-end of one probe and fluorescent label to the 5'-end of the other probe. Upon ligation, the probes are combined in the same molecule and can be detected in a specific location on a universal microarray with complementary zip-oligos enabling equivalent hybridisation conditions for all probes. The method was applied to samples from Nordic composting facilities after testing and optimisation with fungal pure cultures and environmental clones. Results Probes targeted for fungi were able to detect 0.1 fmol of target ribosomal PCR product in an artificial reaction mixture containing 100 ng competing fungal ribosomal internal transcribed spacer (ITS) area or herring sperm DNA. The detection level was therefore approximately 0.04% of total DNA. Clone libraries were constructed from eight compost samples. The LDR microarray results were in concordance with the clone library sequencing results. In addition a control probe was used to monitor the per-spot hybridisation efficiency on the array. Conclusion This study demonstrates that the LDR microarray method is capable of sensitive and accurate species-level detection from a complex microbial community. The method can detect key species from compost samples, making it a basis for a tool for compost process monitoring in industrial facilities. PMID:19116002

Daily Reportable Disease Spatiotemporal Cluster Detection, New York City, New York, USA, 2014-2015.

PubMed

Greene, Sharon K; Peterson, Eric R; Kapell, Deborah; Fine, Annie D; Kulldorff, Martin

2016-10-01

Each day, the New York City Department of Health and Mental Hygiene uses the free SaTScan software to apply prospective space-time permutation scan statistics to strengthen early outbreak detection for 35 reportable diseases. This method prompted early detection of outbreaks of community-acquired legionellosis and shigellosis.

Image classification of unlabeled malaria parasites in red blood cells.

PubMed

Zheng Zhang; Ong, L L Sharon; Kong Fang; Matthew, Athul; Dauwels, Justin; Ming Dao; Asada, Harry

2016-08-01

This paper presents a method to detect unlabeled malaria parasites in red blood cells. The current "gold standard" for malaria diagnosis is microscopic examination of thick blood smear, a time consuming process requiring extensive training. Our goal is to develop an automate process to identify malaria infected red blood cells. Major issues in automated analysis of microscopy images of unstained blood smears include overlapping cells and oddly shaped cells. Our approach creates robust templates to detect infected and uninfected red cells. Histogram of Oriented Gradients (HOGs) features are extracted from templates and used to train a classifier offline. Next, the ViolaJones object detection framework is applied to detect infected and uninfected red cells and the image background. Results show our approach out-performs classification approaches with PCA features by 50% and cell detection algorithms applying Hough transforms by 24%. Majority of related work are designed to automatically detect stained parasites in blood smears where the cells are fixed. Although it is more challenging to design algorithms for unstained parasites, our methods will allow analysis of parasite progression in live cells under different drug treatments.

Detection of DNA Sequences Refractory to PCR Amplification Using a Biophysical SERRS Assay (Surface Enhanced Resonant Raman Spectroscopy)

PubMed Central

Feuillie, Cécile; Merheb, Maxime M.; Gillet, Benjamin; Montagnac, Gilles; Daniel, Isabelle; Hänni, Catherine

2014-01-01

The analysis of ancient or processed DNA samples is often a great challenge, because traditional Polymerase Chain Reaction – based amplification is impeded by DNA damage. Blocking lesions such as abasic sites are known to block the bypass of DNA polymerases, thus stopping primer elongation. In the present work, we applied the SERRS-hybridization assay, a fully non-enzymatic method, to the detection of DNA refractory to PCR amplification. This method combines specific hybridization with detection by Surface Enhanced Resonant Raman Scattering (SERRS). It allows the detection of a series of double-stranded DNA molecules containing a varying number of abasic sites on both strands, when PCR failed to detect the most degraded sequences. Our SERRS approach can quickly detect DNA molecules without any need for DNA repair. This assay could be applied as a pre-requisite analysis prior to enzymatic reparation or amplification. A whole new set of samples, both forensic and archaeological, could then deliver information that was not yet available due to a high degree of DNA damage. PMID:25502338

Detection of DNA sequences refractory to PCR amplification using a biophysical SERRS assay (Surface Enhanced Resonant Raman Spectroscopy).

PubMed

Feuillie, Cécile; Merheb, Maxime M; Gillet, Benjamin; Montagnac, Gilles; Daniel, Isabelle; Hänni, Catherine

2014-01-01

The analysis of ancient or processed DNA samples is often a great challenge, because traditional Polymerase Chain Reaction - based amplification is impeded by DNA damage. Blocking lesions such as abasic sites are known to block the bypass of DNA polymerases, thus stopping primer elongation. In the present work, we applied the SERRS-hybridization assay, a fully non-enzymatic method, to the detection of DNA refractory to PCR amplification. This method combines specific hybridization with detection by Surface Enhanced Resonant Raman Scattering (SERRS). It allows the detection of a series of double-stranded DNA molecules containing a varying number of abasic sites on both strands, when PCR failed to detect the most degraded sequences. Our SERRS approach can quickly detect DNA molecules without any need for DNA repair. This assay could be applied as a pre-requisite analysis prior to enzymatic reparation or amplification. A whole new set of samples, both forensic and archaeological, could then deliver information that was not yet available due to a high degree of DNA damage.

Cell tracking for cell image analysis

NASA Astrophysics Data System (ADS)

Bise, Ryoma; Sato, Yoichi

2017-04-01

Cell image analysis is important for research and discovery in biology and medicine. In this paper, we present our cell tracking methods, which is capable of obtaining fine-grain cell behavior metrics. In order to address difficulties under dense culture conditions, where cell detection cannot be done reliably since cell often touch with blurry intercellular boundaries, we proposed two methods which are global data association and jointly solving cell detection and association. We also show the effectiveness of the proposed methods by applying the method to the biological researches.

Change Point Detection in Correlation Networks

NASA Astrophysics Data System (ADS)

Barnett, Ian; Onnela, Jukka-Pekka

2016-01-01

Many systems of interacting elements can be conceptualized as networks, where network nodes represent the elements and network ties represent interactions between the elements. In systems where the underlying network evolves, it is useful to determine the points in time where the network structure changes significantly as these may correspond to functional change points. We propose a method for detecting change points in correlation networks that, unlike previous change point detection methods designed for time series data, requires minimal distributional assumptions. We investigate the difficulty of change point detection near the boundaries of the time series in correlation networks and study the power of our method and competing methods through simulation. We also show the generalizable nature of the method by applying it to stock price data as well as fMRI data.

Anomaly detection of turbopump vibration in Space Shuttle Main Engine using statistics and neural networks

NASA Technical Reports Server (NTRS)

Lo, C. F.; Wu, K.; Whitehead, B. A.

1993-01-01

The statistical and neural networks methods have been applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. The anomalies are detected based on the amplitude of peaks of fundamental and harmonic frequencies in the power spectral density. These data are reduced to the proper format from sensor data measured by strain gauges and accelerometers. Both methods are feasible to detect the vibration anomalies. The statistical method requires sufficient data points to establish a reasonable statistical distribution data bank. This method is applicable for on-line operation. The neural networks method also needs to have enough data basis to train the neural networks. The testing procedure can be utilized at any time so long as the characteristics of components remain unchanged.

Analysis of Braking Behavior of Train Drivers to Detect Unusual Driving

NASA Astrophysics Data System (ADS)

Marumo, Yoshitaka; Tsunashima, Hitoshi; Kojima, Takashi; Hasegawa, Yasushi

The safety devices for train systems are activated in emergency situations when a risk becomes obvious, and the emergency brake is applied. If such systems are faulty, the drivers' operating errors may cause immediate accidents. So it is necessary to evaluate potential risks by detecting improper driving behavior before overt risks appear. This study analyzes the driving behavior of train drivers using a train-driving simulator. We focus on braking behavior when approaching a station. Two methods for detecting unusual braking operation are examined by giving drivers mental calculation problems as a mental workload. The first is a method monitoring the driver's brake handle operation, and the second is a method measuring vehicle deceleration. These methods make it possible to detect unusual driving.

Automatic evaluation of skin histopathological images for melanocytic features

NASA Astrophysics Data System (ADS)

Koosha, Mohaddeseh; Hoseini Alinodehi, S. Pourya; Nicolescu, Mircea; Safaei Naraghi, Zahra

2017-03-01

Successfully detecting melanocyte cells in the skin epidermis has great significance in skin histopathology. Because of the existence of cells with similar appearance to melanocytes in hematoxylin and eosin (HE) images of the epidermis, detecting melanocytes becomes a challenging task. This paper proposes a novel technique for the detection of melanocytes in HE images of the epidermis, based on the melanocyte color features, in the HSI color domain. Initially, an effective soft morphological filter is applied to the HE images in the HSI color domain to remove noise. Then a novel threshold-based technique is applied to distinguish the candidate melanocytes' nuclei. Similarly, the method is applied to find the candidate surrounding halos of the melanocytes. The candidate nuclei are associated with their surrounding halos using the suggested logical and statistical inferences. Finally, a fuzzy inference system is proposed, based on the HSI color information of a typical melanocyte in the epidermis, to calculate the similarity ratio of each candidate cell to a melanocyte. As our review on the literature shows, this is the first method evaluating epidermis cells for melanocyte similarity ratio. Experimental results on various images with different zooming factors show that the proposed method improves the results of previous works.

Homogeneous Biosensing Based on Magnetic Particle Labels

PubMed Central

Schrittwieser, Stefan; Pelaz, Beatriz; Parak, Wolfgang J.; Lentijo-Mozo, Sergio; Soulantica, Katerina; Dieckhoff, Jan; Ludwig, Frank; Guenther, Annegret; Tschöpe, Andreas; Schotter, Joerg

2016-01-01

The growing availability of biomarker panels for molecular diagnostics is leading to an increasing need for fast and sensitive biosensing technologies that are applicable to point-of-care testing. In that regard, homogeneous measurement principles are especially relevant as they usually do not require extensive sample preparation procedures, thus reducing the total analysis time and maximizing ease-of-use. In this review, we focus on homogeneous biosensors for the in vitro detection of biomarkers. Within this broad range of biosensors, we concentrate on methods that apply magnetic particle labels. The advantage of such methods lies in the added possibility to manipulate the particle labels by applied magnetic fields, which can be exploited, for example, to decrease incubation times or to enhance the signal-to-noise-ratio of the measurement signal by applying frequency-selective detection. In our review, we discriminate the corresponding methods based on the nature of the acquired measurement signal, which can either be based on magnetic or optical detection. The underlying measurement principles of the different techniques are discussed, and biosensing examples for all techniques are reported, thereby demonstrating the broad applicability of homogeneous in vitro biosensing based on magnetic particle label actuation. PMID:27275824

Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)

NASA Astrophysics Data System (ADS)

Javanshir Moghaddam, Mandana; Tan, Tao; Karssemeijer, Nico; Platel, Bram

2014-03-01

Recent studies have demonstrated that applying Automated Breast Ultrasound in addition to mammography in women with dense breasts can lead to additional detection of small, early stage breast cancers which are occult in corresponding mammograms. In this paper, we proposed a fully automatic method for detecting the nipple location in 3D ultrasound breast images acquired from Automated Breast Ultrasound Systems. The nipple location is a valuable landmark to report the position of possible abnormalities in a breast or to guide image registration. To detect the nipple location, all images were normalized. Subsequently, features have been extracted in a multi scale approach and classification experiments were performed using a gentle boost classifier to identify the nipple location. The method was applied on a dataset of 100 patients with 294 different 3D ultrasound views from Siemens and U-systems acquisition systems. Our database is a representative sample of cases obtained in clinical practice by four medical centers. The automatic method could accurately locate the nipple in 90% of AP (Anterior-Posterior) views and in 79% of the other views.

Gold Nanoparticle-Aptamer-Based LSPR Sensing of Ochratoxin A at a Widened Detection Range by Double Calibration Curve Method

NASA Astrophysics Data System (ADS)

Liu, Boshi; Huang, Renliang; Yu, Yanjun; Su, Rongxin; Qi, Wei; He, Zhimin

2018-04-01

Ochratoxin A (OTA) is a type of mycotoxin generated from the metabolism of Aspergillus and Penicillium, and is extremely toxic to humans, livestock, and poultry. However, traditional assays for the detection of OTA are expensive and complicated. Other than OTA aptamer, OTA itself at high concentration can also adsorb on the surface of gold nanoparticles (AuNPs), and further inhibit AuNPs salt aggregation. We herein report a new OTA assay by applying the localized surface plasmon resonance effect of AuNPs and their aggregates. The result obtained from only one single linear calibration curve is not reliable, and so we developed a “double calibration curve” method to address this issue and widen the OTA detection range. A number of other analytes were also examined, and the structural properties of analytes that bind with the AuNPs were further discussed. We found that various considerations must be taken into account in the detection of these analytes when applying AuNP aggregation-based methods due to their different binding strengths.

Using occupancy modelling to compare environmental DNA to traditional field methods for regional-scale monitoring of an endangered aquatic species.

PubMed

Schmelzle, Molly C; Kinziger, Andrew P

2016-07-01

Environmental DNA (eDNA) monitoring approaches promise to greatly improve detection of rare, endangered and invasive species in comparison with traditional field approaches. Herein, eDNA approaches and traditional seining methods were applied at 29 research locations to compare method-specific estimates of detection and occupancy probabilities for endangered tidewater goby (Eucyclogobius newberryi). At each location, multiple paired seine hauls and water samples for eDNA analysis were taken, ranging from two to 23 samples per site, depending upon habitat size. Analysis using a multimethod occupancy modelling framework indicated that the probability of detection using eDNA was nearly double (0.74) the rate of detection for seining (0.39). The higher detection rates afforded by eDNA allowed determination of tidewater goby occupancy at two locations where they have not been previously detected and at one location considered to be locally extirpated. Additionally, eDNA concentration was positively related to tidewater goby catch per unit effort, suggesting eDNA could potentially be used as a proxy for local tidewater goby abundance. Compared to traditional field sampling, eDNA provided improved occupancy parameter estimates and can be applied to increase management efficiency across a broad spatial range and within a diversity of habitats. © 2015 John Wiley & Sons Ltd.

Protein Detection Using the Multiplexed Proximity Extension Assay (PEA) from Plasma and Vaginal Fluid Applied to the Indicating FTA Elute Micro Card™

PubMed Central

Berggrund, Malin; Ekman, Daniel; Gustavsson, Inger; Sundfeldt, Karin; Olovsson, Matts; Enroth, Stefan; Gyllensten, Ulf

2016-01-01

The indicating FTA elute micro card™ has been developed to collect and stabilize the nucleic acid in biological samples and is widely used in human and veterinary medicine and other disciplines. This card is not recommended for protein analyses, since surface treatment may denature proteins. We studied the ability to analyse proteins in human plasma and vaginal fluid as applied to the indicating FTA elute micro card™ using the sensitive proximity extension assay (PEA). Among 92 proteins in the Proseek Multiplex Oncology Iv2 panel, 87 were above the limit of detection (LOD) in liquid plasma and 56 among 92 above LOD in plasma applied to FTA cards. Washing and protein elution protocols were compared to identify an optimal method. Liquid-based cytology samples showed a lower number of proteins above LOD than FTA cards with vaginal fluid samples applied. Our results demonstrate that samples applied to the indicating FTA elute micro card™ are amendable to protein analyses, given that a sensitive protein detection assay is used. The results imply that biological samples applied to FTA cards can be used for DNA, RNA and protein detection. PMID:28936257

Protein Detection Using the Multiplexed Proximity Extension Assay (PEA) from Plasma and Vaginal Fluid Applied to the Indicating FTA Elute Micro Card™.

PubMed

Berggrund, Malin; Ekman, Daniel; Gustavsson, Inger; Sundfeldt, Karin; Olovsson, Matts; Enroth, Stefan; Gyllensten, Ulf

2016-01-01

The indicating FTA elute micro card™ has been developed to collect and stabilize the nucleic acid in biological samples and is widely used in human and veterinary medicine and other disciplines. This card is not recommended for protein analyses, since surface treatment may denature proteins. We studied the ability to analyse proteins in human plasma and vaginal fluid as applied to the indicating FTA elute micro card™ using the sensitive proximity extension assay (PEA). Among 92 proteins in the Proseek Multiplex Oncology Iv2 panel, 87 were above the limit of detection (LOD) in liquid plasma and 56 among 92 above LOD in plasma applied to FTA cards. Washing and protein elution protocols were compared to identify an optimal method. Liquid-based cytology samples showed a lower number of proteins above LOD than FTA cards with vaginal fluid samples applied. Our results demonstrate that samples applied to the indicating FTA elute micro card™ are amendable to protein analyses, given that a sensitive protein detection assay is used. The results imply that biological samples applied to FTA cards can be used for DNA, RNA and protein detection.

Detecting Earthquakes over a Seismic Network using Single-Station Similarity Measures

NASA Astrophysics Data System (ADS)

Bergen, Karianne J.; Beroza, Gregory C.

2018-03-01

New blind waveform-similarity-based detection methods, such as Fingerprint and Similarity Thresholding (FAST), have shown promise for detecting weak signals in long-duration, continuous waveform data. While blind detectors are capable of identifying similar or repeating waveforms without templates, they can also be susceptible to false detections due to local correlated noise. In this work, we present a set of three new methods that allow us to extend single-station similarity-based detection over a seismic network; event-pair extraction, pairwise pseudo-association, and event resolution complete a post-processing pipeline that combines single-station similarity measures (e.g. FAST sparse similarity matrix) from each station in a network into a list of candidate events. The core technique, pairwise pseudo-association, leverages the pairwise structure of event detections in its network detection model, which allows it to identify events observed at multiple stations in the network without modeling the expected move-out. Though our approach is general, we apply it to extend FAST over a sparse seismic network. We demonstrate that our network-based extension of FAST is both sensitive and maintains a low false detection rate. As a test case, we apply our approach to two weeks of continuous waveform data from five stations during the foreshock sequence prior to the 2014 Mw 8.2 Iquique earthquake. Our method identifies nearly five times as many events as the local seismicity catalog (including 95% of the catalog events), and less than 1% of these candidate events are false detections.

Development of capillary electrophoresis methods for quantitative determination of taurine in vehicle system and biological media.

PubMed

da Silva, Dayse L P; Rüttinger, Hans H; Mrestani, Yahia; Baum, Walter F; Neubert, Reinhard H H

2006-06-01

CE methods have been developed for the determination of taurine in pharmaceutical formulation (microemulsion) and in biological media such as sweat. The CE system with end-column pulsed amperometric detection has been found to be an interesting method in comparison with UV and fluorescence detection for its simplicity and rapidity. A gold-disk electrode of 100 mm diameter was used as the working electrode. The effects of a field decoupler at the end of the capillary, separation voltage, injection and pressure times were investigated. A detection limit of 4 x 10(-5) mol/L was reached using integrated pulsed amperometric detection, a method successfully applied to taurine analysis of the biological samples such as sweat. For taurine analysis of oil-in-water microemulsion, fluorescence detector was the favored method, the detection limit of which was 4 x 10(-11) mol/L.

A new method for skin color enhancement

NASA Astrophysics Data System (ADS)

Zeng, Huanzhao; Luo, Ronnier

2012-01-01

Skin tone is the most important color category in memory colors. Reproducing it pleasingly is an important factor in photographic color reproduction. Moving skin colors toward their preferred skin color center improves the skin color preference on photographic color reproduction. Two key factors to successfully enhance skin colors are: a method to detect original skin colors effectively even if they are shifted far away from the regular skin color region, and a method to morph skin colors toward a preferred skin color region properly without introducing artifacts. A method for skin color enhancement presented by the authors in the same conference last year applies a static skin color model for skin color detection, which may miss to detect skin colors that are far away from regular skin tones. In this paper, a new method using the combination of face detection and statistical skin color modeling is proposed to effectively detect skin pixels and to enhance skin colors more effectively.

Remote logo detection using angle-distance histograms

NASA Astrophysics Data System (ADS)

Youn, Sungwook; Ok, Jiheon; Baek, Sangwook; Woo, Seongyoun; Lee, Chulhee

2016-05-01

Among all the various computer vision applications, automatic logo recognition has drawn great interest from industry as well as various academic institutions. In this paper, we propose an angle-distance map, which we used to develop a robust logo detection algorithm. The proposed angle-distance histogram is invariant against scale and rotation. The proposed method first used shape information and color characteristics to find the candidate regions and then applied the angle-distance histogram. Experiments show that the proposed method detected logos of various sizes and orientations.

Detection of Antibiotics and Evaluation of Antibacterial Activity with Screen-Printed Electrodes

PubMed Central

Titoiu, Ana Maria; Marty, Jean-Louis

2018-01-01

This review provides a brief overview of the fabrication and properties of screen-printed electrodes and details the different opportunities to apply them for the detection of antibiotics, detection of bacteria and antibiotic susceptibility. Among the alternative approaches to costly chromatographic or ELISA methods for antibiotics detection and to lengthy culture methods for bacteria detection, electrochemical biosensors based on screen-printed electrodes present some distinctive advantages. Chemical and (bio)sensors for the detection of antibiotics and assays coupling detection with screen-printed electrodes with immunomagnetic separation are described. With regards to detection of bacteria, the emphasis is placed on applications targeting viable bacterial cells. While the electrochemical sensors and biosensors face many challenges before replacing standard analysis methods, the potential of screen-printed electrodes is increasingly exploited and more applications are anticipated to advance towards commercial analytical tools. PMID:29562637

A combination of direct viable count and fluorescence in situ hybridization for specific enumeration of viable Lactobacillus delbrueckii subsp.bulgaricus and Streptococcus thermophilus.

PubMed

García-Hernández, J; Moreno, Y; Amorocho, C M; Hernández, M

2012-03-01

We have developed a direct viable count (DVC)-FISH procedure for quickly and easily discriminating between viable and nonviable cells of Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus strains, the traditional yogurt bacteria. direct viable count method has been modified and adapted for Lact. delbrueckii subsp. bulgaricus and Strep. thermophilus analysis by testing different times of incubation and concentrations of DNA-gyrase inhibitors. DVC procedure has been combined with fluorescent in situ hybridization (FISH) for the specific detection of viable cells of both bacteria with specific rRNA oligonucleotide probes (DVC-FISH). Of the four antibiotics tested (novobiocin, nalidixic acid, pipemidic acid and ciprofloxacin), novobiocin was the most effective for DVC method and the optimum incubation time was 7 h for both bacteria. The number of viable cells was obtained by the enumeration of specific hybridized cells that were elongated at least twice their original length for Lactobacillus and twice their original size for Streptococcus. This technique was successfully applied to detect viable cells in inoculated faeces. Results showed that this DVC-FISH procedure is a quick and culture-independent useful method to specifically detect viable Lact. delbrueckii subsp. bulgaricus and Strep. thermophilus in different samples, being applied for the first time to lactic acid bacteria. © 2011 The Authors. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.

SERS as an analytical tool in environmental science: The detection of sulfamethoxazole in the nanomolar range by applying a microfluidic cartridge setup.

PubMed

Patze, Sophie; Huebner, Uwe; Liebold, Falk; Weber, Karina; Cialla-May, Dana; Popp, Juergen

2017-01-01

Sulfamethoxazole (SMX) is a commonly applied antibiotic for treating urinary tract infections; however, allergic reactions and skin eczema are known side effects that are observed for all sulfonamides. Today, this molecule is present in drinking and surface water sources. The allowed concentration in tap water is 2·10 -7  mol L -1 . SMX could unintentionally be ingested by healthy people when drinking contaminated tap water, representing unnecessary drug intake. To assess the quality of tap water, fast, specific and sensitive detection methods are required, in which consequence measures for improving the purification of water might be initiated in the short term. Herein, the quantitative detection of SMX down to environmentally and physiologically relevant concentrations in the nanomolar range by employing surface-enhanced Raman spectroscopy (SERS) and a microfluidic cartridge system is presented. By applying surface-water samples as matrices, the detection of SMX down to 2.2·10 -9  mol L -1 is achieved, which illustrates the great potential of our proposed method in environmental science. Copyright © 2016 Elsevier B.V. All rights reserved.

Optical method for the determination of stress in thin films

DOEpatents

Maris, H.J.

1999-01-26

A method and optical system is disclosed for measuring an amount of stress in a film layer disposed over a substrate. The method includes steps of: (A) applying a sequence of optical pump pulses to the film layer, individual ones of said optical pump pulses inducing a propagating strain pulse in the film layer, and for each of the optical pump pulses, applying at least one optical probe pulse, the optical probe pulses being applied with different time delays after the application of the corresponding optical probe pulses; (B) detecting variations in an intensity of a reflection of portions of the optical probe pulses, the variations being due at least in part to the propagation of the strain pulse in the film layer; (C) determining, from the detected intensity variations, a sound velocity in the film layer; and (D) calculating, using the determined sound velocity, the amount of stress in the film layer. In one embodiment of this invention the step of detecting measures a period of an oscillation in the intensity of the reflection of portions of the optical probe pulses, while in another embodiment the step of detecting measures a change in intensity of the reflection of portions of the optical probe pulses and determines a time at which the propagating strain pulse reflects from a boundary of the film layer. 16 figs.

Optical method for the determination of stress in thin films

DOEpatents

Maris, Humphrey J.

1999-01-01

A method and optical system is disclosed for measuring an amount of stress in a film layer disposed over a substrate. The method includes steps of: (A) applying a sequence of optical pump pulses to the film layer, individual ones of said optical pump pulses inducing a propagating strain pulse in the film layer, and for each of the optical pump pulses, applying at least one optical probe pulse, the optical probe pulses being applied with different time delays after the application of the corresponding optical probe pulses; (B) detecting variations in an intensity of a reflection of portions of the optical probe pulses, the variations being due at least in part to the propagation of the strain pulse in the film layer; (C) determining, from the detected intensity variations, a sound velocity in the film layer; and (D) calculating, using the determined sound velocity, the amount of stress in the film layer. In one embodiment of this invention the step of detecting measures a period of an oscillation in the intensity of the reflection of portions of the optical probe pulses, while in another embodiment the step of detecting measures a change in intensity of the reflection of portions of the optical probe pulses and determines a time at which the propagating strain pulse reflects from a boundary of the film layer.

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

PubMed Central

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-01-01

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

PubMed

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-08-19

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

Analytical method development for the determination of emerging contaminants in water using supercritical-fluid chromatography coupled with diode-array detection.

PubMed

Del Carmen Salvatierra-Stamp, Vilma; Ceballos-Magaña, Silvia G; Gonzalez, Jorge; Ibarra-Galván, Valentin; Muñiz-Valencia, Roberto

2015-05-01

An analytical method using supercritical-fluid chromatography coupled with diode-array detection for the determination of seven emerging contaminants-two pharmaceuticals (carbamazepine and glyburide), three endocrine disruptors (17α-ethinyl estradiol, bisphenol A, and 17β-estradiol), one bactericide (triclosan), and one pesticide (diuron)-was developed and validated. These contaminants were chosen because of their frequency of use and their toxic effects on both humans and the environment. The optimized chromatographic separation on a Viridis BEH 2-EP column achieved baseline resolution for all compounds in less than 10 min. This separation was applied to environmental water samples after sample preparation. The optimized sample treatment involved a preconcentration step by means of solid-phase extraction using C18-OH cartridges. The proposed method was validated, finding recoveries higher than 94 % and limits of detection and limits of quantification in the range of 0.10-1.59 μg L(-1) and 0.31-4.83 μg L(-1), respectively. Method validation established the proposed method to be selective, linear, accurate, and precise. Finally, the method was successfully applied to environmental water samples.

Effective PCR detection of animal species in highly processed animal byproducts and compound feeds.

PubMed

Fumière, Olivier; Dubois, Marc; Baeten, Vincent; von Holst, Christoph; Berben, Gilbert

2006-07-01

In this paper we present a polymerase chain reaction (PCR)-based method for detecting meat and bone meal (MBM) in compound feedingstuffs. By choosing adequate DNA targets from an appropriate localisation in the genome, the real-time PCR method developed here proved to be robust to severe heat treatment of the MBM, showing high sensitivity in the detection of MBM. The method developed here permits the specific detection of processed pig and cattle materials treated at 134 degrees C in various feed matrices down to a limit of detection of about 0.1%. This technique has also been successfully applied to well-characterised MBM samples heated to as high as 141 degrees C, as well as to various blind feed samples with very low MBM contents. Finally, the method also passed several official European ring trials.

A competitive chemiluminescence enzyme immunoassay method for β-defensin-2 detection in transgenic mice.

PubMed

Yang, Xi; Zhou, Tao; Yu, Lei; Tan, Wenwen; Zhou, Rui; Hu, Yonggang

2015-03-01

A competitive chemiluminescence enzyme immunoassay (CLEIA) method for porcine β-defensin-2 (pBD-2) detection in transgenic mice was established. Several factors that affect detection, including luminol, p-iodophenol and hydrogen peroxide concentrations, as well as pH, were studied and optimized. The linear range of the proposed method for pBD-2 detection under optimal conditions was 0.05-80 ng/mL with a correlation coefficient of 0.9960. Eleven detections of a 30 ng/mL pBD-2 standard sample were performed. Reproducible results were obtained with a relative standard deviation of 3.94%. The limit of detection of the method for pBD-2 was 3.5 pg/mL (3σ). The proposed method was applied to determine pBD-2 expression levels in the tissues of pBD-2 transgenic mice, and compared with LC-MS/MS and quantitative real-time reverse-transcriptase polymerase chain reaction. This suggests that the CLEIA can be used as a valuable method to detect and quantify pBD-2. Copyright © 2014 John Wiley & Sons, Ltd.

A Review of Transmission Diagnostics Research at NASA Lewis Research Center

NASA Technical Reports Server (NTRS)

Zakajsek, James J.

1994-01-01

This paper presents a summary of the transmission diagnostics research work conducted at NASA Lewis Research Center over the last four years. In 1990, the Transmission Health and Usage Monitoring Research Team at NASA Lewis conducted a survey to determine the critical needs of the diagnostics community. Survey results indicated that experimental verification of gear and bearing fault detection methods, improved fault detection in planetary systems, and damage magnitude assessment and prognostics research were all critical to a highly reliable health and usage monitoring system. In response to this, a variety of transmission fault detection methods were applied to experimentally obtained fatigue data. Failure modes of the fatigue data include a variety of gear pitting failures, tooth wear, tooth fracture, and bearing spalling failures. Overall results indicate that, of the gear fault detection techniques, no one method can successfully detect all possible failure modes. The more successful methods need to be integrated into a single more reliable detection technique. A recently developed method, NA4, in addition to being one of the more successful gear fault detection methods, was also found to exhibit damage magnitude estimation capabilities.

Detection of Adulterated Vegetable Oils Containing Waste Cooking Oils Based on the Contents and Ratios of Cholesterol, β-Sitosterol, and Campesterol by Gas Chromatography/Mass Spectrometry.

PubMed

Zhao, Haixiang; Wang, Yongli; Xu, Xiuli; Ren, Heling; Li, Li; Xiang, Li; Zhong, Weike

2015-01-01

A simple and accurate authentication method for the detection of adulterated vegetable oils that contain waste cooking oil (WCO) was developed. This method is based on the determination of cholesterol, β-sitosterol, and campesterol in vegetable oils and WCO by GC/MS without any derivatization. A total of 148 samples involving 12 types of vegetable oil and WCO were analyzed. According to the results, the contents and ratios of cholesterol, β-sitosterol, and campesterol were found to be criteria for detecting vegetable oils adulterated with WCO. This method could accurately detect adulterated vegetable oils containing 5% refined WCO. The developed method has been successfully applied to multilaboratory analysis of 81 oil samples. Seventy-five samples were analyzed correctly, and only six adulterated samples could not be detected. This method could not yet be used for detection of vegetable oils adulterated with WCO that are used for frying non-animal foods. It provides a quick method for detecting adulterated edible vegetable oils containing WCO.

Scintillator assembly for alpha radiation detection and an associated method of making

DOEpatents

Lauf, R.J.; McElhaney, S.A.; Bates, J.B.

1994-07-26

A scintillator assembly for use in conjunction with a photomultiplier or the like in the detection of alpha radiation utilizes a substrate or transparent yttrium aluminum garnet and a relatively thin film of cerium-doped yttrium aluminum garnet coated upon the substrate. The film material is applied to the substrate in a sputtering process, and the applied film and substrate are annealed to effect crystallization of the film upon the substrate. The resultant assembly provides relatively high energy resolution during use in a detection instrument and is sufficiently rugged for use in field environments. 4 figs.

Scintillator assembly for alpha radiation detection and an associated method of making

DOEpatents

Lauf, Robert J.; McElhaney, Stephanie A.; Bates, John B.

1994-01-01

A scintillator assembly for use in conjunction with a photomultiplier or the like in the detection of alpha radiation utilizes a substrate or transparent yttrium aluminum garnet and a relatively thin film of cerium-doped yttrium aluminum garnet coated upon the substrate. The film material is applied to the substrate in a sputtering process, and the applied film and substrate are annealed to effect crystallization of the film upon the substrate. The resultant assembly provides relatively high energy resolution during use in a detection instrument and is sufficiently rugged for use in field environments.

Preceding Vehicle Detection and Tracking Adaptive to Illumination Variation in Night Traffic Scenes Based on Relevance Analysis

PubMed Central

Guo, Junbin; Wang, Jianqiang; Guo, Xiaosong; Yu, Chuanqiang; Sun, Xiaoyan

2014-01-01

Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation. PMID:25195855

Preceding vehicle detection and tracking adaptive to illumination variation in night traffic scenes based on relevance analysis.

PubMed

Guo, Junbin; Wang, Jianqiang; Guo, Xiaosong; Yu, Chuanqiang; Sun, Xiaoyan

2014-08-19

Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation.

Abnormality detection of mammograms by discriminative dictionary learning on DSIFT descriptors.

PubMed

Tavakoli, Nasrin; Karimi, Maryam; Nejati, Mansour; Karimi, Nader; Reza Soroushmehr, S M; Samavi, Shadrokh; Najarian, Kayvan

2017-07-01

Detection and classification of breast lesions using mammographic images are one of the most difficult studies in medical image processing. A number of learning and non-learning methods have been proposed for detecting and classifying these lesions. However, the accuracy of the detection/classification still needs improvement. In this paper we propose a powerful classification method based on sparse learning to diagnose breast cancer in mammograms. For this purpose, a supervised discriminative dictionary learning approach is applied on dense scale invariant feature transform (DSIFT) features. A linear classifier is also simultaneously learned with the dictionary which can effectively classify the sparse representations. Our experimental results show the superior performance of our method compared to existing approaches.

Robust Vehicle Detection under Various Environmental Conditions Using an Infrared Thermal Camera and Its Application to Road Traffic Flow Monitoring

PubMed Central

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2013-01-01

We have already proposed a method for detecting vehicle positions and their movements (henceforth referred to as “our previous method”) using thermal images taken with an infrared thermal camera. Our experiments have shown that our previous method detects vehicles robustly under four different environmental conditions which involve poor visibility conditions in snow and thick fog. Our previous method uses the windshield and its surroundings as the target of the Viola-Jones detector. Some experiments in winter show that the vehicle detection accuracy decreases because the temperatures of many windshields approximate those of the exterior of the windshields. In this paper, we propose a new vehicle detection method (henceforth referred to as “our new method”). Our new method detects vehicles based on tires' thermal energy reflection. We have done experiments using three series of thermal images for which the vehicle detection accuracies of our previous method are low. Our new method detects 1,417 vehicles (92.8%) out of 1,527 vehicles, and the number of false detection is 52 in total. Therefore, by combining our two methods, high vehicle detection accuracies are maintained under various environmental conditions. Finally, we apply the traffic information obtained by our two methods to traffic flow automatic monitoring, and show the effectiveness of our proposal. PMID:23774988

Research on Daily Objects Detection Based on Deep Neural Network

NASA Astrophysics Data System (ADS)

Ding, Sheng; Zhao, Kun

2018-03-01

With the rapid development of deep learning, great breakthroughs have been made in the field of object detection. In this article, the deep learning algorithm is applied to the detection of daily objects, and some progress has been made in this direction. Compared with traditional object detection methods, the daily objects detection method based on deep learning is faster and more accurate. The main research work of this article: 1. collect a small data set of daily objects; 2. in the TensorFlow framework to build different models of object detection, and use this data set training model; 3. the training process and effect of the model are improved by fine-tuning the model parameters.

Applying inventory methods to estimate aboveground biomass from satellite light detection and ranging (LiDAR) forest height data

Treesearch

Sean P. Healey; Paul L. Patterson; Sassan Saatchi; Michael A. Lefsky; Andrew J. Lister; Elizabeth A. Freeman; Gretchen G. Moisen

2012-01-01

Light Detection and Ranging (LiDAR) returns from the spaceborne Geoscience Laser Altimeter (GLAS) sensor may offer an alternative to solely field-based forest biomass sampling. Such an approach would rely upon model-based inference, which can account for the uncertainty associated with using modeled, instead of field-collected, measurements. Model-based methods have...

Watertight cataract incision closure using fibrin tissue adhesive.

PubMed

Hovanesian, John A; Karageozian, Vicken H

2007-08-01

To determine whether a simple method for applying fibrin tissue adhesive to a clear corneal cataract incision can create a watertight seal. Laboratory investigation. Clear corneal cataract incisions were simulated in 8 eye-bank eyes. In 4 eyes, fibrin adhesive was applied to the incision in a simple manner; the other 4 eyes were controls with no adhesive. Each eye was tested under low pressure conditions to detect fluid ingress of India Ink on the eye's surface. The eyes were tested again with external compression to distort the incision to detect fluid egress. In the eyes with fibrin adhesive, there was no egress of fluid with incision distortion and no ingress of India Ink. In the 4 eyes without adhesive, there was ingress and egress of fluid. A simple method of applying fibrin adhesive to cataract incisions created a watertight seal.

A fuzzy pattern matching method based on graph kernel for lithography hotspot detection

NASA Astrophysics Data System (ADS)

Nitta, Izumi; Kanazawa, Yuzi; Ishida, Tsutomu; Banno, Koji

2017-03-01

In advanced technology nodes, lithography hotspot detection has become one of the most significant issues in design for manufacturability. Recently, machine learning based lithography hotspot detection has been widely investigated, but it has trade-off between detection accuracy and false alarm. To apply machine learning based technique to the physical verification phase, designers require minimizing undetected hotspots to avoid yield degradation. They also need a ranking of similar known patterns with a detected hotspot to prioritize layout pattern to be corrected. To achieve high detection accuracy and to prioritize detected hotspots, we propose a novel lithography hotspot detection method using Delaunay triangulation and graph kernel based machine learning. Delaunay triangulation extracts features of hotspot patterns where polygons locate irregularly and closely one another, and graph kernel expresses inner structure of graphs. Additionally, our method provides similarity between two patterns and creates a list of similar training patterns with a detected hotspot. Experiments results on ICCAD 2012 benchmarks show that our method achieves high accuracy with allowable range of false alarm. We also show the ranking of the similar known patterns with a detected hotspot.

Design of a species-specific PCR method for the detection of the heat-resistant fungi Talaromyces macrosporus and Talaromyces trachyspermus.

PubMed

Yamashita, S; Nakagawa, H; Sakaguchi, T; Arima, T-H; Kikoku, Y

2018-01-01

Heat-resistant fungi occur sporadically and are a continuing problem for the food and beverage industry. The genus Talaromyces, as a typical fungus, is capable of producing the heat-resistant ascospores responsible for the spoilage of processed food products. Isocitrate lyase, a signature enzyme of the glyoxylate cycle, is required for the metabolism of non-fermentable carbon compounds, like acetate and ethanol. Here, species-specific primer sets for detection and identification of DNA derived from Talaromyces macrosporus and Talaromyces trachyspermus were designed based on the nucleotide sequences of their isocitrate lyase genes. Polymerase chain reaction (PCR) using a species-specific primer set amplified products specific to T. macrosporus and T. trachyspermus. Other fungal species, such as Byssochlamys fulva and Hamigera striata, which cause food spoilage, were not detected using the Talaromyces-specific primer sets. The detection limit for each species-specific primer set was determined as being 50 pg of template DNA, without using a nested PCR method. The specificity of each species-specific primer set was maintained in the presence of 1,000-fold amounts of genomic DNA from other fungi. The method also detected fungal DNA extracted from blueberry inoculated with T. macrosporus. This PCR method provides a quick, simple, powerful and reliable way to detect T. macrosporus and T. trachyspermus. Polymerase chain reaction (PCR)-based detection is rapid, convenient and sensitive compared with traditional methods of detecting heat-resistant fungi. In this study, a PCR-based method was developed for the detection and identification of amplification products from Talaromyces macrosporus and Talaromyces trachyspermus using primer sets that target the isocitrate lyase gene. This method could be used for the on-site detection of T. macrosporus and T. trachyspermus in the near future, and will be helpful in the safety control of raw materials and in food and beverage production. © 2017 The Authors. Letters in Applied Microbiology published by John Wiley & Sons Ltd on behalf of The Society for Applied Microbiology.

Data analysis and detection methods for on-line health monitoring of bridge structures

DOT National Transportation Integrated Search

2002-06-01

Developing an efficient structural health monitoring (SHM) technique is important for reducing potential hazards posed : to the public by damaged civil structures. The ultimate goal of applying SHM is to real-time detect, localize, and quantify : the...

Evaluation of Two Outlier-Detection-Based Methods for Detecting Tissue-Selective Genes from Microarray Data

PubMed Central

Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

2007-01-01

Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent’s non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent’s method is not suitable for ROKU. PMID:19936074

Moving human full body and body parts detection, tracking, and applications on human activity estimation, walking pattern and face recognition

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike

2016-05-01

We have developed a new way for detection and tracking of human full-body and body-parts with color (intensity) patch morphological segmentation and adaptive thresholding for security surveillance cameras. An adaptive threshold scheme has been developed for dealing with body size changes, illumination condition changes, and cross camera parameter changes. Tests with the PETS 2009 and 2014 datasets show that we can obtain high probability of detection and low probability of false alarm for full-body. Test results indicate that our human full-body detection method can considerably outperform the current state-of-the-art methods in both detection performance and computational complexity. Furthermore, in this paper, we have developed several methods using color features for detection and tracking of human body-parts (arms, legs, torso, and head, etc.). For example, we have developed a human skin color sub-patch segmentation algorithm by first conducting a RGB to YIQ transformation and then applying a Subtractive I/Q image Fusion with morphological operations. With this method, we can reliably detect and track human skin color related body-parts such as face, neck, arms, and legs. Reliable body-parts (e.g. head) detection allows us to continuously track the individual person even in the case that multiple closely spaced persons are merged. Accordingly, we have developed a new algorithm to split a merged detection blob back to individual detections based on the detected head positions. Detected body-parts also allow us to extract important local constellation features of the body-parts positions and angles related to the full-body. These features are useful for human walking gait pattern recognition and human pose (e.g. standing or falling down) estimation for potential abnormal behavior and accidental event detection, as evidenced with our experimental tests. Furthermore, based on the reliable head (face) tacking, we have applied a super-resolution algorithm to enhance the face resolution for improved human face recognition performance.

Weld leaks rapidly and safely detected

NASA Technical Reports Server (NTRS)

1965-01-01

Test method detects leaks that occur during hydrostatic pressure testing of welded joints in metal tanks. A strip of aluminum foil and a strip of water-soluble paper are placed over the weld. A voltage applied between the tank wall and the foil strip is monitored to detect a decrease in ohmic resistance caused by water leakage into the paper layer.

Enhanced multifunctional paint for detection of radiation

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

Farmer, Joseph C.; Moses, Edward Ira; Rubenchik, Alexander M.

An enhanced multifunctional paint apparatus, systems, and methods for detecting radiation on a surface include providing scintillation particles; providing an enhance neutron absorptive material; providing a binder; combining the scintillation particles, the enhance neutron absorptive material, and the binder creating a multifunctional paint; applying the multifunctional paint to the surface; and monitoring the surface for detecting radiation.

Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier

PubMed Central

Akram, M. Usman; Khan, Shoab A.; Javed, Muhammad Younus

2014-01-01

National security has gained vital importance due to increasing number of suspicious and terrorist events across the globe. Use of different subfields of information technology has also gained much attraction of researchers and practitioners to design systems which can detect main members which are actually responsible for such kind of events. In this paper, we present a novel method to predict key players from a covert network by applying a hybrid framework. The proposed system calculates certain centrality measures for each node in the network and then applies novel hybrid classifier for detection of key players. Our system also applies anomaly detection to predict any terrorist activity in order to help law enforcement agencies to destabilize the involved network. As a proof of concept, the proposed framework has been implemented and tested using different case studies including two publicly available datasets and one local network. PMID:25136674

Conjugated polymer nanoparticles-based fluorescent biosensor for ultrasensitive detection of hydroquinone.

PubMed

Liu, Yuan; Wang, Yu-Min; Zhu, Wu-Yang; Zhang, Chong-Hua; Tang, Hao; Jiang, Jian-Hui

2018-07-05

This work describes a simple and sensitive fluorescent method for detection of hydroquinone utilizing conjugated polymer nanoparticles (CPNs). The CPNs serve both as a catalyst to accelerate the conversion of hydroquinone to benzoquinone and a fluorescent probe. In the presence of hydroquinone, the fluorescence of CPNs can be effectively quenched by benzoquinone. The detection limit of hydroquinone was down to 5 nM and excellent selectivity toward possible interferences was obtained. This method was successfully applied for hydroquinone detection in lake water and satisfactory results were achieved. Copyright © 2018 Elsevier B.V. All rights reserved.

Change detection of bitemporal multispectral images based on FCM and D-S theory

NASA Astrophysics Data System (ADS)

Shi, Aiye; Gao, Guirong; Shen, Shaohong

2016-12-01

In this paper, we propose a change detection method of bitemporal multispectral images based on the D-S theory and fuzzy c-means (FCM) algorithm. Firstly, the uncertainty and certainty regions are determined by thresholding method applied to the magnitudes of difference image (MDI) and spectral angle information (SAI) of bitemporal images. Secondly, the FCM algorithm is applied to the MDI and SAI in the uncertainty region, respectively. Then, the basic probability assignment (BPA) functions of changed and unchanged classes are obtained by the fuzzy membership values from the FCM algorithm. In addition, the optimal value of fuzzy exponent of FCM is adaptively determined by conflict degree between the MDI and SAI in uncertainty region. Finally, the D-S theory is applied to obtain the new fuzzy partition matrix for uncertainty region and further the change map is obtained. Experiments on bitemporal Landsat TM images and bitemporal SPOT images validate that the proposed method is effective.

Determination of chlorpyrifos and its metabolites in cells and culture media by liquid chromatography-electrospray ionization tandem mass spectrometry.

PubMed

Yang, Xiangkun; Wu, Xian; Brown, Kyle A; Le, Thao; Stice, Steven L; Bartlett, Michael G

2017-09-15

A sensitive method to simultaneously quantitate chlorpyrifos, chlorpyrifos oxon and the detoxified product 3,5,6-trichloro-2-pyridinol (TCP) was developed using either liquid-liquid extraction for culture media samples, or protein precipitation for cell samples. Multiple reaction monitoring in positive ion mode was applied for the detection of chlorpyrifos and chlorpyrifos oxon, and selected ion recording in negative mode was applied to detect TCP. The method provided linear ranges from 5 to 500, 0.2-20 and 20-2000ng/mL for media samples and from 0.5-50, 0.02-2 and 2-200ng/million cells for CPF, CPO and TCP, respectively. The method was validated using selectivity, linearity, precision, accuracy, recovery, stability and dilution tests. All relative standard deviations (RSDs) and relative errors (REs) for QC samples were within 15% (except for LLOQ, within 20%). This method has been successfully applied to study the neurotoxicity and metabolism of chlorpyrifos in a human neuronal model. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating site occupancy rates for aquatic plants using spatial sub-sampling designs when detection probabilities are less than one

USGS Publications Warehouse

Nielson, Ryan M.; Gray, Brian R.; McDonald, Lyman L.; Heglund, Patricia J.

2011-01-01

Estimation of site occupancy rates when detection probabilities are <1 is well established in wildlife science. Data from multiple visits to a sample of sites are used to estimate detection probabilities and the proportion of sites occupied by focal species. In this article we describe how site occupancy methods can be applied to estimate occupancy rates of plants and other sessile organisms. We illustrate this approach and the pitfalls of ignoring incomplete detection using spatial data for 2 aquatic vascular plants collected under the Upper Mississippi River's Long Term Resource Monitoring Program (LTRMP). Site occupancy models considered include: a naïve model that ignores incomplete detection, a simple site occupancy model assuming a constant occupancy rate and a constant probability of detection across sites, several models that allow site occupancy rates and probabilities of detection to vary with habitat characteristics, and mixture models that allow for unexplained variation in detection probabilities. We used information theoretic methods to rank competing models and bootstrapping to evaluate the goodness-of-fit of the final models. Results of our analysis confirm that ignoring incomplete detection can result in biased estimates of occupancy rates. Estimates of site occupancy rates for 2 aquatic plant species were 19–36% higher compared to naive estimates that ignored probabilities of detection <1. Simulations indicate that final models have little bias when 50 or more sites are sampled, and little gains in precision could be expected for sample sizes >300. We recommend applying site occupancy methods for monitoring presence of aquatic species.

Laser-ultrasound spectroscopy apparatus and method with detection of shear resonances for measuring anisotropy, thickness, and other properties

DOEpatents

Levesque, Daniel; Moreau, Andre; Dubois, Marc; Monchalin, Jean-Pierre; Bussiere, Jean; Lord, Martin; Padioleau, Christian

2000-01-01

Apparatus and method for detecting shear resonances includes structure and steps for applying a radiation pulse from a pulsed source of radiation to an object to generate elastic waves therein, optically detecting the elastic waves generated in the object, and analyzing the elastic waves optically detected in the object. These shear resonances, alone or in combination with other information, may be used in the present invention to improve thickness measurement accuracy and to determine geometrical, microstructural, and physical properties of the object. At least one shear resonance in the object is detected with the elastic waves optically detected in the object. Preferably, laser-ultrasound spectroscopy is utilized to detect the shear resonances.

Physical interpretation and development of ultrasonic nondestructive evaluation techniques applied to the quantitative characterization of textile composite materials

NASA Technical Reports Server (NTRS)

Miller, James G.

1993-01-01

In this Progress Report, we describe our current research activities concerning the development and implementation of advanced ultrasonic nondestructive evaluation methods applied to the characterization of stitched composite materials and bonded aluminum plate specimens. One purpose of this investigation is to identify and characterize specific features of polar backscatter interrogation which enhance the ability of ultrasound to detect flaws in a stitched composite laminate. Another focus is to explore the feasibility of implementing medical linear array imaging technology as a viable ultrasonic-based nondestructive evaluation method to inspect and characterize bonded aluminum lap joints. As an approach to implementing quantitative ultrasonic inspection methods to both of these materials, we focus on the physics that underlies the detection of flaws in such materials.

Aircraft Flight Envelope Determination using Upset Detection and Physical Modeling Methods

NASA Technical Reports Server (NTRS)

Keller, Jeffrey D.; McKillip, Robert M. Jr.; Kim, Singwan

2009-01-01

The development of flight control systems to enhance aircraft safety during periods of vehicle impairment or degraded operations has been the focus of extensive work in recent years. Conditions adversely affecting aircraft flight operations and safety may result from a number of causes, including environmental disturbances, degraded flight operations, and aerodynamic upsets. To enhance the effectiveness of adaptive and envelope limiting controls systems, it is desirable to examine methods for identifying the occurrence of anomalous conditions and for assessing the impact of these conditions on the aircraft operational limits. This paper describes initial work performed toward this end, examining the use of fault detection methods applied to the aircraft for aerodynamic performance degradation identification and model-based methods for envelope prediction. Results are presented in which a model-based fault detection filter is applied to the identification of aircraft control surface and stall departure failures/upsets. This application is supported by a distributed loading aerodynamics formulation for the flight dynamics system reference model. Extensions for estimating the flight envelope due to generalized aerodynamic performance degradation are also described.

Incremental Principal Component Analysis Based Outlier Detection Methods for Spatiotemporal Data Streams

NASA Astrophysics Data System (ADS)

Bhushan, A.; Sharker, M. H.; Karimi, H. A.

2015-07-01

In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA) is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

A PVC/polypyrrole sensor designed for beef taste detection using electrochemical methods and sensory evaluation.

PubMed

Zhu, Lingtao; Wang, Xiaodan; Han, Yunxiu; Cai, Yingming; Jin, Jiahui; Wang, Hongmei; Xu, Liping; Wu, Ruijia

2018-03-01

An electrochemical sensor for detection of beef taste was designed in this study. This sensor was based on the structure of polyvinyl chloride/polypyrrole (PVC/PPy), which was polymerized onto the surface of a platinum (Pt) electrode to form a Pt-PPy-PVC film. Detecting by electrochemical methods, the sensor was well characterized by electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The sensor was applied to detect 10 rib-eye beef samples and the accuracy of the new sensor was validated by sensory evaluation and ion sensor detection. Several cluster analysis methods were used in the study to distinguish the beef samples. According to the obtained results, the designed sensor showed a high degree of association of electrochemical detection and sensory evaluation, which proved a fast and precise sensor for beef taste detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Using State Estimation Residuals to Detect Abnormal SCADA Data

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

Ma, Jian; Chen, Yousu; Huang, Zhenyu

2010-04-30

Detection of abnormal supervisory control and data acquisition (SCADA) data is critically important for safe and secure operation of modern power systems. In this paper, a methodology of abnormal SCADA data detection based on state estimation residuals is presented. Preceded with a brief overview of outlier detection methods and bad SCADA data detection for state estimation, the framework of the proposed methodology is described. Instead of using original SCADA measurements as the bad data sources, the residuals calculated based on the results of the state estimator are used as the input for the outlier detection algorithm. The BACON algorithm ismore » applied to the outlier detection task. The IEEE 118-bus system is used as a test base to evaluate the effectiveness of the proposed methodology. The accuracy of the BACON method is compared with that of the 3-σ method for the simulated SCADA measurements and residuals.« less

A Three-Dimensional Receiver Operator Characteristic Surface Diagnostic Metric

NASA Technical Reports Server (NTRS)

Simon, Donald L.

2011-01-01

Receiver Operator Characteristic (ROC) curves are commonly applied as metrics for quantifying the performance of binary fault detection systems. An ROC curve provides a visual representation of a detection system s True Positive Rate versus False Positive Rate sensitivity as the detection threshold is varied. The area under the curve provides a measure of fault detection performance independent of the applied detection threshold. While the standard ROC curve is well suited for quantifying binary fault detection performance, it is not suitable for quantifying the classification performance of multi-fault classification problems. Furthermore, it does not provide a measure of diagnostic latency. To address these shortcomings, a novel three-dimensional receiver operator characteristic (3D ROC) surface metric has been developed. This is done by generating and applying two separate curves: the standard ROC curve reflecting fault detection performance, and a second curve reflecting fault classification performance. A third dimension, diagnostic latency, is added giving rise to 3D ROC surfaces. Applying numerical integration techniques, the volumes under and between the surfaces are calculated to produce metrics of the diagnostic system s detection and classification performance. This paper will describe the 3D ROC surface metric in detail, and present an example of its application for quantifying the performance of aircraft engine gas path diagnostic methods. Metric limitations and potential enhancements are also discussed

The Impact of the Implementation of Edge Detection Methods on the Accuracy of Automatic Voltage Reading

NASA Astrophysics Data System (ADS)

Sidor, Kamil; Szlachta, Anna

2017-04-01

The article presents the impact of the edge detection method in the image analysis on the reading accuracy of the measured value. In order to ensure the automatic reading of the measured value by an analog meter, a standard webcam and the LabVIEW programme were applied. NI Vision Development tools were used. The Hough transform was used to detect the indicator. The programme output was compared during the application of several methods of edge detection. Those included: the Prewitt operator, the Roberts cross, the Sobel operator and the Canny edge detector. The image analysis was made for an analog meter indicator with the above-mentioned methods, and the results of that analysis were compared with each other and presented.

Rapid detection of mecA and spa by the loop-mediated isothermal amplification (LAMP) method.

PubMed

Koide, Y; Maeda, H; Yamabe, K; Naruishi, K; Yamamoto, T; Kokeguchi, S; Takashiba, S

2010-04-01

To develop a detection assay for staphylococcal mecA and spa by using loop-mediated isothermal amplification (LAMP) method. Staphylococcus aureus and other related species were subjected to the detection of mecA and spa by both PCR and LAMP methods. The LAMP successfully amplified the genes under isothermal conditions at 64 degrees C within 60 min, and demonstrated identical results with the conventional PCR methods. The detection limits of the LAMP for mecA and spa, by gel electrophoresis, were 10(2) and 10 cells per tube, respectively. The naked-eye inspections were possible with 10(3) and 10 cells for detection of mecA and spa, respectively. The LAMP method was then applied to sputum and dental plaque samples. The LAMP and PCR demonstrated identical results for the plaque samples, although frequency in detection of mecA and spa by the LAMP was relatively lower for the sputum samples when compared to the PCR methods. Application of the LAMP enabled a rapid detection assay for mecA and spa. The assay may be applicable to clinical plaque samples. The LAMP offers an alternative detection assay for mecA and spa with a great advantage of the rapidity.

Development of a specific immunomagnetic capture-PCR for rapid detection of viable Mycoplasma agalactiae in sheep milk samples.

PubMed

Sanna, G; Lecca, V; Foddai, A; Tola, S

2014-12-01

To develop an immunomagnetic capture (IMC) to detect viable Mycoplasma agalactiae in routine ovine milk samples. Polyclonal antibodies against two M. agalactiae membrane surface proteins (P80 and P55) were covalently conjugated to magnetic beads (MBs) to form MB-Ab80 and MB-Ab55. Mycoplasma agalactiae cells were captured by a specific antigen-antibody reaction and magnetic separation. Immunomagnetic capture (IMC) was used to isolate and concentrate M. agalactiae in serial decimal dilutions and in artificially contaminated milk to facilitate subsequent detection by PCR. A 375-bp fragment of M. agalactiae was amplified using a pair of M. agalactiae-specific primers in PCR. The limit of detection of IMC-PCR method ranged from 10 to 10(2)  CCU ml(-1) when mycoplasmas were resuspended in PBS and from 10(2) to 10(3)  CCU ml(-1) when mycoplasmas were resuspended in uncontaminated ovine milk. This study also describes the application of IMC-PCR method to test for M. agalactiae in 516 milk samples collected from sheep with suspected contagious agalactia. Its performance was evaluated relative to culture. This report has demonstrated for the first time, the effective use of rapid and reliable IMC combined with PCR assay for the detection of viable M. agalactiae. The method IMC-PCR provides an alternative to conventional microbiological detection, method and it could be applied to quick detection of M. agalactiae in routine sheep milk samples. © 2014 The Authors published by John Wiley & Sons Ltd on behalf of Society for Applied Microbiology.

Anomaly and signature filtering improve classifier performance for detection of suspicious access to EHRs.

PubMed

Kim, Jihoon; Grillo, Janice M; Boxwala, Aziz A; Jiang, Xiaoqian; Mandelbaum, Rose B; Patel, Bhakti A; Mikels, Debra; Vinterbo, Staal A; Ohno-Machado, Lucila

2011-01-01

Our objective is to facilitate semi-automated detection of suspicious access to EHRs. Previously we have shown that a machine learning method can play a role in identifying potentially inappropriate access to EHRs. However, the problem of sampling informative instances to build a classifier still remained. We developed an integrated filtering method leveraging both anomaly detection based on symbolic clustering and signature detection, a rule-based technique. We applied the integrated filtering to 25.5 million access records in an intervention arm, and compared this with 8.6 million access records in a control arm where no filtering was applied. On the training set with cross-validation, the AUC was 0.960 in the control arm and 0.998 in the intervention arm. The difference in false negative rates on the independent test set was significant, P=1.6×10(-6). Our study suggests that utilization of integrated filtering strategies to facilitate the construction of classifiers can be helpful.

Anomaly and Signature Filtering Improve Classifier Performance For Detection Of Suspicious Access To EHRs

PubMed Central

Kim, Jihoon; Grillo, Janice M; Boxwala, Aziz A; Jiang, Xiaoqian; Mandelbaum, Rose B; Patel, Bhakti A; Mikels, Debra; Vinterbo, Staal A; Ohno-Machado, Lucila

2011-01-01

Our objective is to facilitate semi-automated detection of suspicious access to EHRs. Previously we have shown that a machine learning method can play a role in identifying potentially inappropriate access to EHRs. However, the problem of sampling informative instances to build a classifier still remained. We developed an integrated filtering method leveraging both anomaly detection based on symbolic clustering and signature detection, a rule-based technique. We applied the integrated filtering to 25.5 million access records in an intervention arm, and compared this with 8.6 million access records in a control arm where no filtering was applied. On the training set with cross-validation, the AUC was 0.960 in the control arm and 0.998 in the intervention arm. The difference in false negative rates on the independent test set was significant, P=1.6×10−6. Our study suggests that utilization of integrated filtering strategies to facilitate the construction of classifiers can be helpful. PMID:22195129

Simple and sensitive HPLC method with fluorescence detection for the measurement of ibuprofen in rat plasma: application to a long-lasting dosage form.

PubMed

Hassan, Ahmed Sheikh; Sapin, Anne; Ubrich, Nathalie; Maincent, Philippe; Bolzan, Claire; Leroy, Pierre

2008-10-01

A simple and sensitive high-performance liquid chromatography (HPLC) assay applied to the measurement of ibuprofen in rat plasma has been developed. Two parameters have been investigated to improve ibuprofen detectability using fluorescence detection: variation of mobile phase pH and the use of beta-cyclodextrin (beta-CD). Increasing the pH value from 2.5 to 6.5 and adding 5 mM beta-CD enhanced the fluorescence signal (lambda(exc) = 224 nm; lambda(em) = 290 nm) by 2.5 and 1.3-fold, respectively, when using standards. In the case of plasma samples, only pH variation significantly lowered detection and quantification limits, down to 10 and 35 ng/mL, respectively. Full selectivity was obtained with a single step for plasma treatment, that is, protein precipitation with acidified acetonitrile. The validated method was applied to a pharmacokinetic study of ibuprofen encapsulated in microspheres and subcutaneously administered to rats.

Establishment and application of cross-priming isothermal amplification coupled with lateral flow dipstick (CPA-LFD) for rapid and specific detection of red-spotted grouper nervous necrosis virus.

PubMed

Su, Zi Dan; Shi, Cheng Yin; Huang, Jie; Shen, Gui Ming; Li, Jin; Wang, Sheng Qiang; Fan, Chao

2015-09-26

Red-spotted grouper nervous necrosis virus (RGNNV) is an important pathogen that causes diseases in many species of fish in marine aquaculture. The larvae and juveniles are more easily infected by RGNNV and the cumulative mortality is as high as 100 % after being infected with RGNNV. This virus imposes a serious threat to aquaculture of grouper fry. This study aimed to establish a simple, accurate and highly sensitive method for rapid detection of RGNNV on the spot. In this study, the primers specifically targeting RGNNV were designed and cross-priming isothermal amplification (CPA) system was established. The product amplified by CPA was detected through visualization with lateral flow dipstick (LFD). Three important parameters, including the amplification temperature, the concentration of dNTPs and the concentration of Mg(2+) for the CPA system, were optimized. The sensitivity and specificity of this method for RGNNV were tested and compared with those of the conventional RT-PCR and real-time quantitative RT-PCR (qRT-PCR). The optimized conditions for the CPA amplification system were determined as follows: the optimal amplification temperature, the optimized concentration of dNTPs and the concentration for Mg(2+) were 69 °C, 1.2 mmol/L and 5 mmol/L, respectively. The lowest limit of detection (LLOD) of this method for RGNNV was 10(1) copies/μL of RNA sample, which was 10 times lower than that of conventional RT-PCR and comparable to that of RT-qPCR. This method was specific for RGNNV in combination with SJNNV and had no cross-reactions with 8 types of virus and bacterial strains tested. This method was successfully applied to detect RGNNV in fish samples. This study established a CPA-LFD method for detection of RGNNV. This method is simple and rapid with high sensitivity and good specificity and can be widely applied for rapid detection of this virus on the spot.

Frequency domain phase-shifted confocal microscopy (FDPCM) with array detection

NASA Astrophysics Data System (ADS)

Ge, Baoliang; Huang, Yujia; Fang, Yue; Kuang, Cuifang; Xiu, Peng; Liu, Xu

2017-09-01

We proposed a novel method to reconstruct images taken by array detected confocal microscopy without prior knowledge about its detector distribution. The proposed frequency domain phase-shifted confocal microscopy (FDPCM) shifts the image from each detection channel to its corresponding place by substituting the phase information in Fourier domain. Theoretical analysis shows that our method could approach the resolution nearly twofold of wide-field microscopy. Simulation and experiment results are also shown to verify the applicability and effectiveness of our method. Compared to Airyscan, our method holds the advantage of simplicity and convenience to be applied to array detectors with different structure, which makes FDPCM have great potential in the application of biomedical observation in the future.

Detection of Foreign Matter in Transfusion Solution Based on Gaussian Background Modeling and an Optimized BP Neural Network

PubMed Central

Zhou, Fuqiang; Su, Zhen; Chai, Xinghua; Chen, Lipeng

2014-01-01

This paper proposes a new method to detect and identify foreign matter mixed in a plastic bottle filled with transfusion solution. A spin-stop mechanism and mixed illumination style are applied to obtain high contrast images between moving foreign matter and a static transfusion background. The Gaussian mixture model is used to model the complex background of the transfusion image and to extract moving objects. A set of features of moving objects are extracted and selected by the ReliefF algorithm, and optimal feature vectors are fed into the back propagation (BP) neural network to distinguish between foreign matter and bubbles. The mind evolutionary algorithm (MEA) is applied to optimize the connection weights and thresholds of the BP neural network to obtain a higher classification accuracy and faster convergence rate. Experimental results show that the proposed method can effectively detect visible foreign matter in 250-mL transfusion bottles. The misdetection rate and false alarm rate are low, and the detection accuracy and detection speed are satisfactory. PMID:25347581

The design method and research status of vehicle detection system based on geomagnetic detection principle

NASA Astrophysics Data System (ADS)

Lin, Y. H.; Bai, R.; Qian, Z. H.

2018-03-01

Vehicle detection systems are applied to obtain real-time information of vehicles, realize traffic control and reduce traffic pressure. This paper reviews geomagnetic sensors as well as the research status of the vehicle detection system. Presented in the paper are also our work on the vehicle detection system, including detection algorithms and experimental results. It is found that the GMR based vehicle detection system has a detection accuracy up to 98% with a high potential for application in the road traffic control area.

Entropyology: the application of bioinformatics and data modeling to digital virus and malware recognition

NASA Astrophysics Data System (ADS)

Jaenisch, Holger M.; Handley, James W.

2010-04-01

Malware are analogs of viruses. Viruses are comprised of large numbers of polypeptide proteins. The shape and function of the protein strands determines the functionality of the segment, similar to a subroutine in malware. The full combination of subroutines is the malware organism, in analogous fashion as a collection of polypeptides forms protein structures that are information bearing. We propose to apply the methods of Bioinformatics to analyze malware to provide a rich feature set for creating a unique and novel detection and classification scheme that is originally applied to Bioinformatics amino acid sequencing. Our proposed methods enable real time in situ (in contrast to in vivo) detection applications.

Can fractal methods applied to video tracking detect the effects of deltamethrin pesticide or mercury on the locomotion behavior of shrimps?

PubMed

Tenorio, Bruno Mendes; da Silva Filho, Eurípedes Alves; Neiva, Gentileza Santos Martins; da Silva, Valdemiro Amaro; Tenorio, Fernanda das Chagas Angelo Mendes; da Silva, Themis de Jesus; Silva, Emerson Carlos Soares E; Nogueira, Romildo de Albuquerque

2017-08-01

Shrimps can accumulate environmental toxicants and suffer behavioral changes. However, methods to quantitatively detect changes in the behavior of these shrimps are still needed. The present study aims to verify whether mathematical and fractal methods applied to video tracking can adequately describe changes in the locomotion behavior of shrimps exposed to low concentrations of toxic chemicals, such as 0.15µgL -1 deltamethrin pesticide or 10µgL -1 mercuric chloride. Results showed no change after 1min, 4, 24, and 48h of treatment. However, after 72 and 96h of treatment, both the linear methods describing the track length, mean speed, mean distance from the current to the previous track point, as well as the non-linear methods of fractal dimension (box counting or information entropy) and multifractal analysis were able to detect changes in the locomotion behavior of shrimps exposed to deltamethrin. Analysis of angular parameters of the track points vectors and lacunarity were not sensitive to those changes. None of the methods showed adverse effects to mercury exposure. These mathematical and fractal methods applicable to software represent low cost useful tools in the toxicological analyses of shrimps for quality of food, water and biomonitoring of ecosystems. Copyright © 2017 Elsevier Inc. All rights reserved.

Self-Sensing TDR with Micro-Strip Line

DTIC Science & Technology

2015-06-11

detect impact damage of a CFRP plate in the second year (Todoroki A, et al., Impact damage detection of a carbon- fibre -reinforced-polymer plate...inspection methods is self-sensing technology that uses carbon fibres as sensors [1]-[11]. The self-sensing technology applies electric current to the...Time Domain Reflectometry (TDR) for damage detection [15]-[17]. Authors have developed a self-sensing TDR for detection of fibre breakages using a

A Novel Method for Pulsometry Based on Traditional Iranian Medicine

PubMed Central

Yousefipoor, Farzane; Nafisi, Vahidreza

2015-01-01

Arterial pulse measurement is one of the most important methods for evaluation of healthy conditions. In traditional Iranian medicine (TIM), physician may detect radial pulse by holding four fingers on the patient's wrist. By using this method, under standard condition, the detected pulses are subjective and erroneous, in case of weak and/or abnormal pulses, the ambiguity of diagnosis may rise. In this paper, we present an equipment which is designed and implemented for automation of traditional pulse detection method. By this novel system, the developed noninvasive diagnostic method and database based on the TIM are way forward to apply traditional medicine and diagnose patients with present technology. The accuracy for period measuring is 76% and systolic peak is 72%. PMID:26955566

Detection of osmotic damages in GRP boat hulls

NASA Astrophysics Data System (ADS)

Krstulović-Opara, L.; Domazet, Ž.; Garafulić, E.

2013-09-01

Infrared thermography as a tool of non-destructive testing is method enabling visualization and estimation of structural anomalies and differences in structure's topography. In presented paper problem of osmotic damage in submerged glass reinforced polymer structures is addressed. The osmotic damage can be detected by a simple humidity gauging, but for proper evaluation and estimation testing methods are restricted and hardly applicable. In this paper it is demonstrated that infrared thermography, based on estimation of heat wave propagation, can be used. Three methods are addressed; Pulsed thermography, Fast Fourier Transform and Continuous Morlet Wavelet. An additional image processing based on gradient approach is applied on all addressed methods. It is shown that the Continuous Morlet Wavelet is the most appropriate method for detection of osmotic damage.

Left ventricular endocardial surface detection based on real-time 3D echocardiographic data

NASA Technical Reports Server (NTRS)

Corsi, C.; Borsari, M.; Consegnati, F.; Sarti, A.; Lamberti, C.; Travaglini, A.; Shiota, T.; Thomas, J. D.

2001-01-01

OBJECTIVE: A new computerized semi-automatic method for left ventricular (LV) chamber segmentation is presented. METHODS: The LV is imaged by real-time three-dimensional echocardiography (RT3DE). The surface detection model, based on level set techniques, is applied to RT3DE data for image analysis. The modified level set partial differential equation we use is solved by applying numerical methods for conservation laws. The initial conditions are manually established on some slices of the entire volume. The solution obtained for each slice is a contour line corresponding with the boundary between LV cavity and LV endocardium. RESULTS: The mathematical model has been applied to sequences of frames of human hearts (volume range: 34-109 ml) imaged by 2D and reconstructed off-line and RT3DE data. Volume estimation obtained by this new semi-automatic method shows an excellent correlation with those obtained by manual tracing (r = 0.992). Dynamic change of LV volume during the cardiac cycle is also obtained. CONCLUSION: The volume estimation method is accurate; edge based segmentation, image completion and volume reconstruction can be accomplished. The visualization technique also allows to navigate into the reconstructed volume and to display any section of the volume.

Study of SEM induced current and voltage contrast modes to assess semiconductor reliability

NASA Technical Reports Server (NTRS)

Beall, J. R.

1976-01-01

The purpose of the scanning electron microscopy study was to review the failure history of existing integrated circuit technologies to identify predominant failure mechanisms, and to evaluate the feasibility of their detection using SEM application techniques. The study investigated the effects of E-beam irradiation damage and contamination deposition rates; developed the necessary methods for applying the techniques to the detection of latent defects and weaknesses in integrated circuits; and made recommendations for applying the techniques.

Traffic Pattern Detection Using the Hough Transformation for Anomaly Detection to Improve Maritime Domain Awareness

DTIC Science & Technology

2013-12-01

Programming code in the Python language used in AIS data preprocessing is contained in Appendix A. The MATLAB programming code used to apply the Hough...described in Chapter III is applied to archived AIS data in this chapter. The implementation of the method, including programming techniques used, is...is contained in the second. To provide a proof of concept for the algorithm described in Chapter III, the PYTHON programming language was used for

Comparison of ultraviolet detection and charged aerosol detection methods for liquid-chromatographic determination of protoescigenin.

PubMed

Filip, Katarzyna; Grynkiewicz, Grzegorz; Gruza, Mariusz; Jatczak, Kamil; Zagrodzki, Bogdan

2014-01-01

Escin, a complex mixture of pentacyclic triterpene saponins obtained from horse chestnut seeds extract (HCSE; Aesculus hippocastanum L.), constitutes a traditional herbal active substance of preparations (drugs) used for a treatment of chronic venous insufficiency and capillary blood vessel leakage. A new approach to exploitation of pharmacological potential of this saponin complex has been recently proposed, in which the β-escin mixture is perceived as a source of a hitherto unavailable raw material, pentacyclic triterpene aglycone-protoescigenin. Although many liquid chromatography methods are described in the literature for saponins determination, analysis of protoescigenin is barely mentioned. In this work, a new ultra-high performance liquid chromatography (UHPLC) method developed for protoescigenin quantification has been described. CAD (charged aerosol detection), as a relatively new detection method based on aerosol charging, has been applied in this method as an alternative to ultraviolet (UV) detection. The influence of individual parameters on CAD response and sensitivity was studied. The detection was performed using CAD and UV (200 nm) simultaneously and the results were compared with reference to linearity, accuracy, precision and limit of detection.

Long-Term Persistence of Pesticides and TPs in Archived Agricultural Soil Samples and Comparison with Pesticide Application.

PubMed

Chiaia-Hernandez, Aurea C; Keller, Armin; Wächter, Daniel; Steinlin, Christine; Camenzuli, Louise; Hollender, Juliane; Krauss, Martin

2017-09-19

For polar and more degradable pesticides, not many data on long-term persistence in soil under field conditions and real application practices exist. To assess the persistence of pesticides in soil, a multiple-compound screening method (log K ow 1.7-5.5) was developed based on pressurized liquid extraction, QuEChERS and LC-HRMS. The method was applied to study 80 polar pesticides and >90 transformation products (TPs) in archived topsoil samples from the Swiss Soil Monitoring Network (NABO) from 1995 to 2008 with known pesticide application patterns. The results reveal large variations between crop type and field sites. For the majority of the sites 10-15 pesticides were identified with a detection rate of 45% at concentrations between 1 and 330 μg/kg dw in soil. Furthermore, TPs were detected in 47% of the cases where the "parent-compound" was applied. Overall, residues of about 80% of all applied pesticides could be detected with half of these found as TPs with a persistence of more than a decade.

Application of virtual phase-shifting speckle-interferometry for detection of polymorphism in the Chlamydia trachomatis omp1 gene

NASA Astrophysics Data System (ADS)

Feodorova, Valentina A.; Saltykov, Yury V.; Zaytsev, Sergey S.; Ulyanov, Sergey S.; Ulianova, Onega V.

2018-04-01

Method of phase-shifting speckle-interferometry has been used as a new tool with high potency for modern bioinformatics. Virtual phase-shifting speckle-interferometry has been applied for detection of polymorphism in the of Chlamydia trachomatis omp1 gene. It has been shown, that suggested method is very sensitive to natural genetic mutations as single nucleotide polymorphism (SNP). Effectiveness of proposed method has been compared with effectiveness of the newest bioinformatic tools, based on nucleotide sequence alignment.

Isotopic abundance in atom trap trace analysis

DOEpatents

Lu, Zheng-Tian; Hu, Shiu-Ming; Jiang, Wei; Mueller, Peter

2014-03-18

A method and system for detecting ratios and amounts of isotopes of noble gases. The method and system is constructed to be able to measure noble gas isotopes in water and ice, which helps reveal the geological age of the samples and understand their movements. The method and system uses a combination of a cooled discharge source, a beam collimator, a beam slower and magneto-optic trap with a laser to apply resonance frequency energy to the noble gas to be quenched and detected.

Simultaneous identification of natural dyes in the collection of drawings and maps from The Royal Chancellery Archives in Granada (Spain) by CE.

PubMed

López-Montes, Ana; Blanc García, Rosario; Espejo, Teresa; Huertas-Perez, José F; Navalón, Alberto; Vílchez, José Luis

2007-04-01

A simple and rapid capillary electrophoretic method with UV detection (CE-UV) has been developed for the identification of five natural dyes namely, carmine, indigo, saffron, gamboge and Rubia tinctoria root. The separation was performed in a fused-silica capillary of 64.5 cm length and 50 microm id. The running buffer was 40 mM sodium tetraborate buffer solution (pH 9.25). The applied potential was 30 kV, the temperature was 25 degrees C and detections were performed at 196, 232, 252, 300 and 356 nm. The injections were under pressure of 50 mbar during 13 s. The method was applied to the identification of carminic acid, gambogic acid, crocetin, indigotin, alizarin and purpurin in the collection of drawings and maps at the Royal Chancellery Archives in Granada (Spain). The method was validated by using HPLC as a reference method.

Reducing the number of templates for aligned-spin compact binary coalescence gravitational wave searches using metric-agnostic template nudging

NASA Astrophysics Data System (ADS)

Indik, Nathaniel; Fehrmann, Henning; Harke, Franz; Krishnan, Badri; Nielsen, Alex B.

2018-06-01

Efficient multidimensional template placement is crucial in computationally intensive matched-filtering searches for gravitational waves (GWs). Here, we implement the neighboring cell algorithm (NCA) to improve the detection volume of an existing compact binary coalescence (CBC) template bank. This algorithm has already been successfully applied for a binary millisecond pulsar search in data from the Fermi satellite. It repositions templates from overdense regions to underdense regions and reduces the number of templates that would have been required by a stochastic method to achieve the same detection volume. Our method is readily generalizable to other CBC parameter spaces. Here we apply this method to the aligned-single-spin neutron star-black hole binary coalescence inspiral-merger-ringdown gravitational wave parameter space. We show that the template nudging algorithm can attain the equivalent effectualness of the stochastic method with 12% fewer templates.

Fault detection of Tennessee Eastman process based on topological features and SVM

NASA Astrophysics Data System (ADS)

Zhao, Huiyang; Hu, Yanzhu; Ai, Xinbo; Hu, Yu; Meng, Zhen

2018-03-01

Fault detection in industrial process is a popular research topic. Although the distributed control system(DCS) has been introduced to monitor the state of industrial process, it still cannot satisfy all the requirements for fault detection of all the industrial systems. In this paper, we proposed a novel method based on topological features and support vector machine(SVM), for fault detection of industrial process. The proposed method takes global information of measured variables into account by complex network model and predicts whether a system has generated some faults or not by SVM. The proposed method can be divided into four steps, i.e. network construction, network analysis, model training and model testing respectively. Finally, we apply the model to Tennessee Eastman process(TEP). The results show that this method works well and can be a useful supplement for fault detection of industrial process.

Capillary electrophoresis method for the analysis of organic acids and amino acids in the presence of strongly alternating concentrations of aqueous lactic acid.

PubMed

Laube, Hendrik; Boden, Jana; Schneider, Roland

2017-07-01

During the production of bio-based bulk chemicals, such as lactic acid (LA), organic impurities have to be removed to produce a ready-to-market product. A capillary electrophoresis method for the simultaneous detection of LA and organic impurities in less than 10 min was developed. LA and organic impurities were detected using a direct UV detection method with micellar background electrolyte, which consisted of borate and sodium dodecyl sulfate. We investigated the effects of electrolyte composition and temperature on the speed, sensitivity, and robustness of the separation. A few validation parameters, such as linearity, limit of detection, and internal and external standards, were evaluated under optimized conditions. The method was applied for the detection of LA and organic impurities, including tyrosine, phenylalanine, and pyroglutamic acid, in samples from a continuous LA fermentation process from post-extraction tapioca starch and yeast extract.

Improving surface EMG burst detection in infrahyoid muscles during swallowing using digital filters and discrete wavelet analysis.

PubMed

Restrepo-Agudelo, Sebastian; Roldan-Vasco, Sebastian; Ramirez-Arbelaez, Lina; Cadavid-Arboleda, Santiago; Perez-Giraldo, Estefania; Orozco-Duque, Andres

2017-08-01

The visual inspection is a widely used method for evaluating the surface electromyographic signal (sEMG) during deglutition, a process highly dependent of the examiners expertise. It is desirable to have a less subjective and automated technique to improve the onset detection in swallowing related muscles, which have a low signal-to-noise ratio. In this work, we acquired sEMG measured in infrahyoid muscles with high baseline noise of ten healthy adults during water swallowing tasks. Two methods were applied to find the combination of cutoff frequencies that achieve the most accurate onset detection: discrete wavelet decomposition based method and fixed steps variations of low and high cutoff frequencies of a digital bandpass filter. Teager-Kaiser Energy operator, root mean square and simple threshold method were applied for both techniques. Results show a narrowing of the effective bandwidth vs. the literature recommended parameters for sEMG acquisition. Both level 3 decomposition with mother wavelet db4 and bandpass filter with cutoff frequencies between 130 and 180Hz were optimal for onset detection in infrahyoid muscles. The proposed methodologies recognized the onset time with predictive power above 0.95, that is similar to previous findings but in larger and more superficial muscles in limbs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simultaneous analysis of six aldehyde-DNA adducts in salivary DNA of nonsmokers and smokers using stable isotope dilution liquid chromatography electrospray ionization-tandem mass spectrometry.

PubMed

Li, Xiangyu; Liu, Lujuan; Wang, Hongjuan; Chen, Jian; Zhu, Beibei; Chen, Huan; Hou, Hongwei; Hu, Qingyuan

2017-08-15

A stable method, using isotope dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS), to simultaneously determine six aldehyde-DNA adducts was developed and applied to the analysis of human salivary DNA samples. The detection limit of these six DNA adducts was in the range of 0.006-0.014ng/mL and that of the quantification limit was 0.017-0.026ng/mL. The intra-day and inter-day precision of all aldehyde-DNA adducts was <10%. The analysis was completed within 25min. Additionally, a noninvasive technique was used to collect the DNA samples from human saliva. The new method was successfully applied for the analysis of salivary DNA of nonsmokers and smokers. Five aldehyde-DNA adducts were detected in both smoker and nonsmoker salivary DNA, while α-Acr-dG was not detected in all the samples. Among these detected DNA adducts, no significant differences were found between smoker and nonsmoker (p>0.05). This may due to the individual detoxifying differences or environmental and endogenous exposure. Our study provides a rapid and selective method to simultaneously detect six aldehyde-DNA adducts and to assess potential DNA damage induced by aldehydes. Copyright © 2017 Elsevier B.V. All rights reserved.

Irradiation dose detection of irradiated milk powder using visible and near-infrared spectroscopy and chemometrics.

PubMed

Kong, W W; Zhang, C; Liu, F; Gong, A P; He, Y

2013-08-01

The objective of this study was to examine the possibility of applying visible and near-infrared spectroscopy to the quantitative detection of irradiation dose of irradiated milk powder. A total of 150 samples were used: 100 for the calibration set and 50 for the validation set. The samples were irradiated at 5 different dose levels in the dose range 0 to 6.0 kGy. Six different pretreatment methods were compared. The prediction results of full spectra given by linear and nonlinear calibration methods suggested that Savitzky-Golay smoothing and first derivative were suitable pretreatment methods in this study. Regression coefficient analysis was applied to select effective wavelengths (EW). Less than 10 EW were selected and they were useful for portable detection instrument or sensor development. Partial least squares, extreme learning machine, and least squares support vector machine were used. The best prediction performance was achieved by the EW-extreme learning machine model with first-derivative spectra, and correlation coefficients=0.97 and root mean square error of prediction=0.844. This study provided a new approach for the fast detection of irradiation dose of milk powder. The results could be helpful for quality detection and safety monitoring of milk powder. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

SvABA: genome-wide detection of structural variants and indels by local assembly.

PubMed

Wala, Jeremiah A; Bandopadhayay, Pratiti; Greenwald, Noah F; O'Rourke, Ryan; Sharpe, Ted; Stewart, Chip; Schumacher, Steve; Li, Yilong; Weischenfeldt, Joachim; Yao, Xiaotong; Nusbaum, Chad; Campbell, Peter; Getz, Gad; Meyerson, Matthew; Zhang, Cheng-Zhong; Imielinski, Marcin; Beroukhim, Rameen

2018-04-01

Structural variants (SVs), including small insertion and deletion variants (indels), are challenging to detect through standard alignment-based variant calling methods. Sequence assembly offers a powerful approach to identifying SVs, but is difficult to apply at scale genome-wide for SV detection due to its computational complexity and the difficulty of extracting SVs from assembly contigs. We describe SvABA, an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements. We evaluated SvABA's performance on the NA12878 human genome and in simulated and real cancer genomes. SvABA demonstrates superior sensitivity and specificity across a large spectrum of SVs and substantially improves detection performance for variants in the 20-300 bp range, compared with existing methods. SvABA also identifies complex somatic rearrangements with chains of short (<1000 bp) templated-sequence insertions copied from distant genomic regions. We applied SvABA to 344 cancer genomes from 11 cancer types and found that short templated-sequence insertions occur in ∼4% of all somatic rearrangements. Finally, we demonstrate that SvABA can identify sites of viral integration and cancer driver alterations containing medium-sized (50-300 bp) SVs. © 2018 Wala et al.; Published by Cold Spring Harbor Laboratory Press.

Detecting earthquakes over a seismic network using single-station similarity measures

NASA Astrophysics Data System (ADS)

Bergen, Karianne J.; Beroza, Gregory C.

2018-06-01

New blind waveform-similarity-based detection methods, such as Fingerprint and Similarity Thresholding (FAST), have shown promise for detecting weak signals in long-duration, continuous waveform data. While blind detectors are capable of identifying similar or repeating waveforms without templates, they can also be susceptible to false detections due to local correlated noise. In this work, we present a set of three new methods that allow us to extend single-station similarity-based detection over a seismic network; event-pair extraction, pairwise pseudo-association, and event resolution complete a post-processing pipeline that combines single-station similarity measures (e.g. FAST sparse similarity matrix) from each station in a network into a list of candidate events. The core technique, pairwise pseudo-association, leverages the pairwise structure of event detections in its network detection model, which allows it to identify events observed at multiple stations in the network without modeling the expected moveout. Though our approach is general, we apply it to extend FAST over a sparse seismic network. We demonstrate that our network-based extension of FAST is both sensitive and maintains a low false detection rate. As a test case, we apply our approach to 2 weeks of continuous waveform data from five stations during the foreshock sequence prior to the 2014 Mw 8.2 Iquique earthquake. Our method identifies nearly five times as many events as the local seismicity catalogue (including 95 per cent of the catalogue events), and less than 1 per cent of these candidate events are false detections.

An automatic system to detect and extract texts in medical images for de-identification

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Singh, P. D.; Siddiqui, Khan; Gillam, Michael

2010-03-01

Recently, there is an increasing need to share medical images for research purpose. In order to respect and preserve patient privacy, most of the medical images are de-identified with protected health information (PHI) before research sharing. Since manual de-identification is time-consuming and tedious, so an automatic de-identification system is necessary and helpful for the doctors to remove text from medical images. A lot of papers have been written about algorithms of text detection and extraction, however, little has been applied to de-identification of medical images. Since the de-identification system is designed for end-users, it should be effective, accurate and fast. This paper proposes an automatic system to detect and extract text from medical images for de-identification purposes, while keeping the anatomic structures intact. First, considering the text have a remarkable contrast with the background, a region variance based algorithm is used to detect the text regions. In post processing, geometric constraints are applied to the detected text regions to eliminate over-segmentation, e.g., lines and anatomic structures. After that, a region based level set method is used to extract text from the detected text regions. A GUI for the prototype application of the text detection and extraction system is implemented, which shows that our method can detect most of the text in the images. Experimental results validate that our method can detect and extract text in medical images with a 99% recall rate. Future research of this system includes algorithm improvement, performance evaluation, and computation optimization.

The use of experimental design for the development of a capillary zone electrophoresis method for the quantitation of captopril.

PubMed

Mukozhiwa, S Y; Khamanga, S M M; Walker, R B

2017-09-01

A capillary zone electrophoresis (CZE) method for the quantitation of captopril (CPT) using UV detection was developed. Influence of electrolyte concentration and system variables on electrophoretic separation was evaluated and a central composite design (CCD) was used to optimize the method. Variables investigated were pH, molarity, applied voltage and capillary length. The influence of sodium metabisulphite on the stability of test solutions was also investigated. The use of sodium metabisulphite prevented degradation of CPT over 24 hours. A fused uncoated silica capillary of 67.5cm total and 57.5 cm effective length was used for analysis. The applied voltage and capillary length affected the migration time of CPT significantly. A 20 mM phosphate buffer adjusted to pH 7.0 was used as running buffer and an applied voltage of 23.90 kV was suitable to effect a separation. The optimized electrophoretic conditions produced sharp, well-resolved peaks for CPT and sodium metabisulphite. Linear regression analysis of the response for CPT standards revealed the method was linear (R2 = 0.9995) over the range 5-70 μg/mL. The limits of quantitation and detection were 5 and 1.5 μg/mL. A simple, rapid and reliable CZE method has been developed and successfully applied to the analysis of commercially available CPT products.

Partially reduced graphene oxide based FRET on fiber optic interferometer for biochemical detection

NASA Astrophysics Data System (ADS)

Yao, B. C.; Wu, Y.; Yu, C. B.; He, J. R.; Rao, Y. J.; Gong, Y.; Chen, Y. F.; Li, Y. R.

2017-04-01

An all-fiber graphene oxide (GO) based 'FRET on Fiber' concept is proposed and applied in biochemical detections. This method is of both good selectivity and high sensitivity, with detection limits of 1.2 nM, 1.3 μM and 1 pM, for metal ion, dopamine and single-stranded DNA (ssDNA), respectively.

How Do Teachers Perceive Cheating Students? Beliefs about Cues to Deception and Detection Accuracy in the Educational Field

ERIC Educational Resources Information Center

Marksteiner, Tamara; Reinhard, Marc-Andre; Dickhauser, Oliver; Sporer, Siegfried Ludwig

2012-01-01

The present study explores how well teacher trainees can detect liars. Moreover, a new method was applied to investigate beliefs that teacher trainees hold about liars. The results indicate that, overall, teacher trainees were not better than chance in detecting true and invented stories. Generally, participants reported to have used only a few…

Vehicle detection in aerial surveillance using dynamic Bayesian networks.

PubMed

Cheng, Hsu-Yung; Weng, Chih-Chia; Chen, Yi-Ying

2012-04-01

We present an automatic vehicle detection system for aerial surveillance in this paper. In this system, we escape from the stereotype and existing frameworks of vehicle detection in aerial surveillance, which are either region based or sliding window based. We design a pixelwise classification method for vehicle detection. The novelty lies in the fact that, in spite of performing pixelwise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and nonvehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixelwise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.

The methods of formaldehyde emission testing of engine: A review

NASA Astrophysics Data System (ADS)

Zhang, Chunhui; Geng, Peng; Cao, Erming; Wei, Lijiang

2015-12-01

A number of measurements have been provided to detect formaldehyde in the atmosphere, but there are no clear unified standards in engine exhaust. Nowadays, formaldehyde, an unregulated emission from methanol engine, has been attracting increasing attention by researchers. This paper presents the detection techniques for formaldehyde emitted from the engines applied in recent market, introducing the approaches in terms of unregulated emission tests of formaldehyde, which involved gas chromatography, liquid chromatography, chromatography-mass spectrometry, chromatography-spectrum, Fourier infrared spectroscopy and spectrophotometry. The author also introduces the comparison regarding to the advantages of the existing detection techniques based on the principle, to compare with engine exhaust sampling method, the treatment in advance of detection, obtaining approaches accessing to the qualitative and quantitative analysis of chromatograms or spectra. The accuratest result obtained was chromatography though it cannot be used continuously. It also can be utilized to develop high requirements of emissions and other regulations. Fourier infrared spectroscopy has the advantage of continuous detection for a variety of unregulated emissions and can be applied to the bench in variable condition. However, its accuracy is not as good as chromatography. As the conclusion, a detection technique is chosen based on different requirements.

Acquiring information about neutrino parameters by detecting supernova neutrinos

NASA Astrophysics Data System (ADS)

Huang, Ming-Yang; Guo, Xin-Heng; Young, Bing-Lin

2010-08-01

We consider the supernova shock effects, the Mikheyev-Smirnov-Wolfenstein effects, the collective effects, and the Earth matter effects in the detection of type II supernova neutrinos on the Earth. It is found that the event number of supernova neutrinos depends on the neutrino mass hierarchy, the neutrino mixing angle θ13, and neutrino masses. Therefore, we propose possible methods to identify the mass hierarchy and acquire information about θ13 and neutrino masses by detecting supernova neutrinos. We apply these methods to some current neutrino experiments.

A method of real-time detection for distant moving obstacles by monocular vision

NASA Astrophysics Data System (ADS)

Jia, Bao-zhi; Zhu, Ming

2013-12-01

In this paper, we propose an approach for detection of distant moving obstacles like cars and bicycles by a monocular camera to cooperate with ultrasonic sensors in low-cost condition. We are aiming at detecting distant obstacles that move toward our autonomous navigation car in order to give alarm and keep away from them. Method of frame differencing is applied to find obstacles after compensation of camera's ego-motion. Meanwhile, each obstacle is separated from others in an independent area and given a confidence level to indicate whether it is coming closer. The results on an open dataset and our own autonomous navigation car have proved that the method is effective for detection of distant moving obstacles in real-time.

Invasive species change detection using artificial neural networks and CASI hyperspectral imagery

USDA-ARS?s Scientific Manuscript database

For monitoring and controlling the extent and intensity of an invasive species, a direct multi-date image classification method was applied in invasive species (saltcedar) change detection in the study area of Lovelock, Nevada. With multi-date Compact Airborne Spectrographic Imager (CASI) hyperspec...

Incomplete Detection of Nonclassical Phase-Space Distributions

NASA Astrophysics Data System (ADS)

Bohmann, M.; Tiedau, J.; Bartley, T.; Sperling, J.; Silberhorn, C.; Vogel, W.

2018-02-01

We implement the direct sampling of negative phase-space functions via unbalanced homodyne measurement using click-counting detectors. The negativities significantly certify nonclassical light in the high-loss regime using a small number of detectors which cannot resolve individual photons. We apply our method to heralded single-photon states and experimentally demonstrate the most significant certification of nonclassicality for only two detection bins. By contrast, the frequently applied Wigner function fails to directly indicate such quantum characteristics for the quantum efficiencies present in our setup without applying additional reconstruction algorithms. Therefore, we realize a robust and reliable approach to characterize nonclassical light in phase space under realistic conditions.

Image change detection using paradoxical theory for patient follow-up quantitation and therapy assessment.

PubMed

David, Simon; Visvikis, Dimitris; Quellec, Gwénolé; Le Rest, Catherine Cheze; Fernandez, Philippe; Allard, Michèle; Roux, Christian; Hatt, Mathieu

2012-09-01

In clinical oncology, positron emission tomography (PET) imaging can be used to assess therapeutic response by quantifying the evolution of semi-quantitative values such as standardized uptake value, early during treatment or after treatment. Current guidelines do not include metabolically active tumor volume (MATV) measurements and derived parameters such as total lesion glycolysis (TLG) to characterize the response to the treatment. To achieve automatic MATV variation estimation during treatment, we propose an approach based on the change detection principle using the recent paradoxical theory, which models imprecision, uncertainty, and conflict between sources. It was applied here simultaneously to pre- and post-treatment PET scans. The proposed method was applied to both simulated and clinical datasets, and its performance was compared to adaptive thresholding applied separately on pre- and post-treatment PET scans. On simulated datasets, the adaptive threshold was associated with significantly higher classification errors than the developed approach. On clinical datasets, the proposed method led to results more consistent with the known partial responder status of these patients. The method requires accurate rigid registration of both scans which can be obtained only in specific body regions and does not explicitly model uptake heterogeneity. In further investigations, the change detection of intra-MATV tracer uptake heterogeneity will be developed by incorporating textural features into the proposed approach.

Evaluation of image features and classification methods for Barrett's cancer detection using VLE imaging

NASA Astrophysics Data System (ADS)

Klomp, Sander; van der Sommen, Fons; Swager, Anne-Fré; Zinger, Svitlana; Schoon, Erik J.; Curvers, Wouter L.; Bergman, Jacques J.; de With, Peter H. N.

2017-03-01

Volumetric Laser Endomicroscopy (VLE) is a promising technique for the detection of early neoplasia in Barrett's Esophagus (BE). VLE generates hundreds of high resolution, grayscale, cross-sectional images of the esophagus. However, at present, classifying these images is a time consuming and cumbersome effort performed by an expert using a clinical prediction model. This paper explores the feasibility of using computer vision techniques to accurately predict the presence of dysplastic tissue in VLE BE images. Our contribution is threefold. First, a benchmarking is performed for widely applied machine learning techniques and feature extraction methods. Second, three new features based on the clinical detection model are proposed, having superior classification accuracy and speed, compared to earlier work. Third, we evaluate automated parameter tuning by applying simple grid search and feature selection methods. The results are evaluated on a clinically validated dataset of 30 dysplastic and 30 non-dysplastic VLE images. Optimal classification accuracy is obtained by applying a support vector machine and using our modified Haralick features and optimal image cropping, obtaining an area under the receiver operating characteristic of 0.95 compared to the clinical prediction model at 0.81. Optimal execution time is achieved using a proposed mean and median feature, which is extracted at least factor 2.5 faster than alternative features with comparable performance.

ConvNetQuake: Convolutional Neural Network for Earthquake Detection and Location

NASA Astrophysics Data System (ADS)

Denolle, M.; Perol, T.; Gharbi, M.

2017-12-01

Over the last decades, the volume of seismic data has increased exponentially, creating a need for efficient algorithms to reliably detect and locate earthquakes. Today's most elaborate methods scan through the plethora of continuous seismic records, searching for repeating seismic signals. In this work, we leverage the recent advances in artificial intelligence and present ConvNetQuake, a highly scalable convolutional neural network for probabilistic earthquake detection and location from single stations. We apply our technique to study two years of induced seismicity in Oklahoma (USA). We detect 20 times more earthquakes than previously cataloged by the Oklahoma Geological Survey. Our algorithm detection performances are at least one order of magnitude faster than other established methods.

Intelligent identification of remnant ridge edges in region west of Yongxing Island, South China Sea

NASA Astrophysics Data System (ADS)

Wang, Weiwei; Guo, Jing; Cai, Guanqiang; Wang, Dawei

2018-02-01

Edge detection enables identification of geomorphologic unit boundaries and thus assists with geomorphical mapping. In this paper, an intelligent edge identification method is proposed and image processing techniques are applied to multi-beam bathymetry data. To accomplish this, a color image is generated by the bathymetry, and a weighted method is used to convert the color image to a gray image. As the quality of the image has a significant influence on edge detection, different filter methods are applied to the gray image for de-noising. The peak signal-to-noise ratio and mean square error are calculated to evaluate which filter method is most appropriate for depth image filtering and the edge is subsequently detected using an image binarization method. Traditional image binarization methods cannot manage the complicated uneven seafloor, and therefore a binarization method is proposed that is based on the difference between image pixel values; the appropriate threshold for image binarization is estimated according to the probability distribution of pixel value differences between two adjacent pixels in horizontal and vertical directions, respectively. Finally, an eight-neighborhood frame is adopted to thin the binary image, connect the intermittent edge, and implement contour extraction. Experimental results show that the method described here can recognize the main boundaries of geomorphologic units. In addition, the proposed automatic edge identification method avoids use of subjective judgment, and reduces time and labor costs.

The 1064 nm laser-induced breakdown spectroscopy (LIBS) inspection to detect the nutrient elements in freshly cut carrot samples

NASA Astrophysics Data System (ADS)

Yudasari, N.; Prasetyo, S.; Suliyanti, M. M.

2018-03-01

The laser-induced breakdown spectroscopy (LIBS) technique was applied to detect the nutrient elements contained in fresh carrot. Nd:YAG laser the wavelength of 1064 nm was employed in the experiments for ablation. Employing simple set-up of LIBS and preparing the sample with less step method, we are able to detect 18 chemical elements including some fundamental element of carrot, i.e Mg, Al, Fe, Mn, Ti, Ca, and Mn. By applying normalized profiles calculation on some of the element, we are able to compare the concentration level of each element of the outer and inner part of carrot.

Irradiation influence on the detection of genetic-modified soybeans

NASA Astrophysics Data System (ADS)

Villavicencio, A. L. C. H.; Araújo, M. M.; Baldasso, J. G.; Aquino, S.; Konietzny, U.; Greiner, R.

2004-09-01

Three soybean varieties were analyzed to evaluate the irradiation influence on the detection of genetic modification. Samples were treated in a 60Co facility at dose levels of 0, 500, 800, and 1000Gy. The seeds were at first analyzed by Comet Assay as a rapid screening irradiation detection method. Secondly, germination test was performed to detect the viability of irradiated soybeans. Finally, because of its high sensitivity, its specificity and rapidity the polimerase chain reaction was the method applied for genetic modified organism detection. The analysis of DNA by the single technique of microgel electrophoresis of single cells (DNA Comet Assay) showed that DNA damage increased with increasing radiation doses. No negative influence of irradiation on the genetic modification detection was found.

Detection of Posaconazole by Surface-Assisted Laser Desorption/Ionization Mass Spectrometry with Dispersive Liquid-Liquid Microextraction

NASA Astrophysics Data System (ADS)

Lin, Sheng-Yu; Chen, Pin-Shiuan; Chang, Sarah Y.

2015-03-01

A simple, rapid, and sensitive method for the detection of posaconazole using dispersive liquid-liquid microextraction (DLLME) coupled to surface-assisted laser desorption/ionization mass spectrometric detection (SALDI/MS) was developed. After the DLLME, posaconazole was detected using SALDI/MS with colloidal gold and α-cyano-4-hydroxycinnamic acid (CHCA) as the co-matrix. Under optimal extraction and detection conditions, the calibration curve, which ranged from 1.0 to 100.0 nM for posaconazole, was observed to be linear. The limit of detection (LOD) at a signal-to-noise ratio of 3 was 0.3 nM for posaconazole. This novel method was successfully applied to the determination of posaconazole in human urine samples.

Rectal swab sampling followed by an enrichment culture-based real-time PCR assay to detect Salmonella enterocolitis in children.

PubMed

Lin, L-H; Tsai, C-Y; Hung, M-H; Fang, Y-T; Ling, Q-D

2011-09-01

Although routine bacterial culture is the traditional reference standard method for the detection of Salmonella infection in children with diarrhoea, it is a time-consuming procedure that usually only gives results after 3-4 days. Some molecular detection methods can improve the turn-around time to within 24 h, but these methods are not applied directly from stool or rectal swab specimens as routine diagnostic methods for the detection of gastrointestinal pathogens. In this study, we tested the feasibility of a bacterial enrichment culture-based real-time PCR assay method for detecting and screening for diarrhoea in children caused by Salmonella. Our results showed that the minimum real-time PCR assay time required to detect enriched bacterial culture from a swab was 3 h. In all children with suspected Salmonella diarrhoea, the enrichment culture-based real-time PCR achieved 85.4% sensitivity and 98.1% specificity, as compared with the 53.7% sensitivity and 100% specificity of detection with the routine bacterial culture method. We suggest that rectal swab sampling followed by enrichment culture-based real-time PCR is suitable as a rapid method for detecting and screening for Salmonella in paediatric patients. © 2011 The Authors. Clinical Microbiology and Infection © 2011 European Society of Clinical Microbiology and Infectious Diseases.

IAEA Sampling Plan

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

Geist, William H.

2017-09-15

The objectives for this presentation are to describe the method that the IAEA uses to determine a sampling plan for nuclear material measurements; describe the terms detection probability and significant quantity; list the three nuclear materials measurement types; describe the sampling method applied to an item facility; and describe multiple method sampling.

Procedure for short-lived particle detection in the OPERA experiment and its application to charm decays

NASA Astrophysics Data System (ADS)

Agafonova, N.; Aleksandrov, A.; Anokhina, A.; Aoki, S.; Ariga, A.; Ariga, T.; Bender, D.; Bertolin, A.; Bozza, C.; Brugnera, R.; Buonaura, A.; Buontempo, S.; Büttner, B.; Chernyavsky, M.; Chukanov, A.; Consiglio, L.; D'Ambrosio, N.; De Lellis, G.; De Serio, M.; Del Amo Sanchez, P.; Di Crescenzo, A.; Di Ferdinando, D.; Di Marco, N.; Dmitrievski, S.; Dracos, M.; Duchesneau, D.; Dusini, S.; Dzhatdoev, T.; Ebert, J.; Ereditato, A.; Fini, R. A.; Fukuda, T.; Galati, G.; Garfagnini, A.; Giacomelli, G.; Göllnitz, C.; Goldberg, J.; Gornushkin, Y.; Grella, G.; Guler, M.; Gustavino, C.; Hagner, C.; Hara, T.; Hollnagel, A.; Hosseini, B.; Ishida, H.; Ishiguro, K.; Jakovcic, K.; Jollet, C.; Kamiscioglu, C.; Kamiscioglu, M.; Kawada, J.; Kim, J. H.; Kim, S. H.; Kitagawa, N.; Klicek, B.; Kodama, K.; Komatsu, M.; Kose, U.; Kreslo, I.; Lauria, A.; Lenkeit, J.; Ljubicic, A.; Longhin, A.; Loverre, P.; Malgin, A.; Malenica, M.; Mandrioli, G.; Matsuo, T.; Matveev, V.; Mauri, N.; Medinaceli, E.; Meregaglia, A.; Mikado, S.; Monacelli, P.; Montesi, M. C.; Morishima, K.; Muciaccia, M. T.; Naganawa, N.; Naka, T.; Nakamura, M.; Nakano, T.; Nakatsuka, Y.; Niwa, K.; Ogawa, S.; Okateva, N.; Olshevsky, A.; Omura, T.; Ozaki, K.; Paoloni, A.; Park, B. D.; Park, I. G.; Pasqualini, L.; Pastore, A.; Patrizii, L.; Pessard, H.; Pistillo, C.; Podgrudkov, D.; Polukhina, N.; Pozzato, M.; Pupilli, F.; Roda, M.; Rokujo, H.; Roganova, T.; Rosa, G.; Ryazhskaya, O.; Sato, O.; Schembri, A.; Shakiryanova, I.; Shchedrina, T.; Sheshukov, A.; Shibuya, H.; Shiraishi, T.; Shoziyoev, G.; Simone, S.; Sioli, M.; Sirignano, C.; Sirri, G.; Spinetti, M.; Stanco, L.; Starkov, N.; Stellacci, S. M.; Stipcevic, M.; Strauss, T.; Strolin, P.; Takahashi, S.; Tenti, M.; Terranova, F.; Tioukov, V.; Tufanli, S.; Vilain, P.; Vladimirov, M.; Votano, L.; Vuilleumier, J. L.; Wilquet, G.; Wonsak, B.; Yoon, C. S.; Zemskova, S.; Zghiche, A.

2014-08-01

The OPERA experiment, designed to perform the first observation of oscillations in appearance mode through the detection of the leptons produced in charged current interactions, has collected data from 2008 to 2012. In the present paper, the procedure developed to detect particle decays, occurring over distances of the order of from the neutrino interaction point, is described in detail and applied to the search for charmed hadrons, showing similar decay topologies as the lepton. In the analysed sample, 50 charm decay candidate events are observed while are expected, proving that the detector performance and the analysis chain applied to neutrino events are well reproduced by the OPERA simulation and thus validating the methods for appearance detection.

Sleep spindle detection using deep learning: A validation study based on crowdsourcing.

PubMed

Dakun Tan; Rui Zhao; Jinbo Sun; Wei Qin

2015-08-01

Sleep spindles are significant transient oscillations observed on the electroencephalogram (EEG) in stage 2 of non-rapid eye movement sleep. Deep belief network (DBN) gaining great successes in images and speech is still a novel method to develop sleep spindle detection system. In this paper, crowdsourcing replacing gold standard was applied to generate three different labeled samples and constructed three classes of datasets with a combination of these samples. An F1-score measure was estimated to compare the performance of DBN to other three classifiers on classifying these samples, with the DBN obtaining an result of 92.78%. Then a comparison of two feature extraction methods based on power spectrum density was made on same dataset using DBN. In addition, the DBN trained in dataset was applied to detect sleep spindle from raw EEG recordings and performed a comparable capacity to expert group consensus.

Face Liveness Detection Using Defocus

PubMed Central

Kim, Sooyeon; Ban, Yuseok; Lee, Sangyoun

2015-01-01

In order to develop security systems for identity authentication, face recognition (FR) technology has been applied. One of the main problems of applying FR technology is that the systems are especially vulnerable to attacks with spoofing faces (e.g., 2D pictures). To defend from these attacks and to enhance the reliability of FR systems, many anti-spoofing approaches have been recently developed. In this paper, we propose a method for face liveness detection using the effect of defocus. From two images sequentially taken at different focuses, three features, focus, power histogram and gradient location and orientation histogram (GLOH), are extracted. Afterwards, we detect forged faces through the feature-level fusion approach. For reliable performance verification, we develop two databases with a handheld digital camera and a webcam. The proposed method achieves a 3.29% half total error rate (HTER) at a given depth of field (DoF) and can be extended to camera-equipped devices, like smartphones. PMID:25594594

Comparison of four different methods for detection of biofilm formation by uropathogens.

PubMed

Panda, Pragyan Swagatika; Chaudhary, Uma; Dube, Surya K

2016-01-01

Urinary tract infection (UTI) is one of the most common infectious diseases encountered in clinical practice. Emerging resistance of the uropathogens to the antimicrobial agents due to biofilm formation is a matter of concern while treating symptomatic UTI. However, studies comparing different methods for detection of biofilm by uropathogens are scarce. To compare four different methods for detection of biofilm formation by uropathogens. Prospective observational study conducted in a tertiary care hospital. Totally 300 isolates from urinary samples were analyzed for biofilm formation by four methods, that is, tissue culture plate (TCP) method, tube method (TM), Congo Red Agar (CRA) method and modified CRA (MCRA) method. Chi-square test was applied when two or more set of variables were compared. P < 0.05 considered as statistically significant. Considering TCP to be a gold standard method for our study we calculated other statistical parameters. The rate of biofilm detection was 45.6%, 39.3% and 11% each by TCP, TM, CRA and MCRA methods, respectively. The difference between TCP and only CRA/MCRA was significant, but not that between TCP and TM. There was no difference in the rate of biofilm detection between CRA and MCRA in other isolates, but MCRA is superior to CRA for detection of the staphylococcal biofilm formation. TCP method is the ideal method for detection of bacterial biofilm formation by uropathogens. MCRA method is superior only to CRA for detection of staphylococcal biofilm formation.

A chemiluminescence method to detect hydroquinone with water-soluble sulphonato-(salen)manganese(III) complex as catalyst.

PubMed

Zhang, Guangbin; Tang, Yuhai; Sun, Yang; Yu, Hua; Du, Wei; Fu, Qiang

2016-02-01

A water-soluble sulphonato-(salen)manganese(III) complex with excellent catalytic properties was synthesized and demonstrated to greatly enhance the chemiluminescence signal of the hydrogen peroxide - luminol reaction. Coupled with flow-injection technique, a simple and sensitive chemiluminescence method was first developed to detect hydroquinone based on the chemiluminescence system of the hydrogen peroxide-luminol-sulphonato-(salen)manganese(III) complex. Under optimal conditions, the assay exhibited a wide linear range from 0.1 to 10 ng mL(-1) with a detection limit of 0.05 ng mL(-1) for hydroquinone. The method was applied successfully to detect hydroquinone in tap-water and mineral-water, with a sampling frequency of 120 times per hour. The relative standard deviation for determination of hydroquinone was less than 5.6%, and the recoveries ranged from 96.8 to 103.0%. The ultraviolet spectra, chemiluminescence spectra, and the reaction kinetics for the peroxide-luminol-sulphonato-(salen)manganese(III) complex system were employed to study the possible chemiluminescence mechanism. The proposed chemiluminescence analysis technique is rapid and sensitive, with low cost, and could be easily extended and applied to other compounds. Copyright © 2015 John Wiley & Sons, Ltd.

A Tensor-Based Structural Damage Identification and Severity Assessment

PubMed Central

Anaissi, Ali; Makki Alamdari, Mehrisadat; Rakotoarivelo, Thierry; Khoa, Nguyen Lu Dang

2018-01-01

Early damage detection is critical for a large set of global ageing infrastructure. Structural Health Monitoring systems provide a sensor-based quantitative and objective approach to continuously monitor these structures, as opposed to traditional engineering visual inspection. Analysing these sensed data is one of the major Structural Health Monitoring (SHM) challenges. This paper presents a novel algorithm to detect and assess damage in structures such as bridges. This method applies tensor analysis for data fusion and feature extraction, and further uses one-class support vector machine on this feature to detect anomalies, i.e., structural damage. To evaluate this approach, we collected acceleration data from a sensor-based SHM system, which we deployed on a real bridge and on a laboratory specimen. The results show that our tensor method outperforms a state-of-the-art approach using the wavelet energy spectrum of the measured data. In the specimen case, our approach succeeded in detecting 92.5% of induced damage cases, as opposed to 61.1% for the wavelet-based approach. While our method was applied to bridges, its algorithm and computation can be used on other structures or sensor-data analysis problems, which involve large series of correlated data from multiple sensors. PMID:29301314

Applying ISO 11929:2010 Standard to detection limit calculation in least-squares based multi-nuclide gamma-ray spectrum evaluation

NASA Astrophysics Data System (ADS)

Kanisch, G.

2017-05-01

The concepts of ISO 11929 (2010) are applied to evaluation of radionuclide activities from more complex multi-nuclide gamma-ray spectra. From net peak areas estimated by peak fitting, activities and their standard uncertainties are calculated by weighted linear least-squares method with an additional step, where uncertainties of the design matrix elements are taken into account. A numerical treatment of the standard's uncertainty function, based on ISO 11929 Annex C.5, leads to a procedure for deriving decision threshold and detection limit values. The methods shown allow resolving interferences between radionuclide activities also in case of calculating detection limits where they can improve the latter by including more than one gamma line per radionuclide. The co"mmon single nuclide weighted mean is extended to an interference-corrected (generalized) weighted mean, which, combined with the least-squares method, allows faster detection limit calculations. In addition, a new grouped uncertainty budget was inferred, which for each radionuclide gives uncertainty budgets from seven main variables, such as net count rates, peak efficiencies, gamma emission intensities and others; grouping refers to summation over lists of peaks per radionuclide.

A clustering algorithm for determining community structure in complex networks

NASA Astrophysics Data System (ADS)

Jin, Hong; Yu, Wei; Li, ShiJun

2018-02-01

Clustering algorithms are attractive for the task of community detection in complex networks. DENCLUE is a representative density based clustering algorithm which has a firm mathematical basis and good clustering properties allowing for arbitrarily shaped clusters in high dimensional datasets. However, this method cannot be directly applied to community discovering due to its inability to deal with network data. Moreover, it requires a careful selection of the density parameter and the noise threshold. To solve these issues, a new community detection method is proposed in this paper. First, we use a spectral analysis technique to map the network data into a low dimensional Euclidean Space which can preserve node structural characteristics. Then, DENCLUE is applied to detect the communities in the network. A mathematical method named Sheather-Jones plug-in is chosen to select the density parameter which can describe the intrinsic clustering structure accurately. Moreover, every node on the network is meaningful so there were no noise nodes as a result the noise threshold can be ignored. We test our algorithm on both benchmark and real-life networks, and the results demonstrate the effectiveness of our algorithm over other popularity density based clustering algorithms adopted to community detection.

An insight into the isolation, enumeration, and molecular detection of Listeria monocytogenes in food

PubMed Central

Law, Jodi Woan-Fei; Ab Mutalib, Nurul-Syakima; Chan, Kok-Gan; Lee, Learn-Han

2015-01-01

Listeria monocytogenes, a foodborne pathogen that can cause listeriosis through the consumption of food contaminated with this pathogen. The ability of L. monocytogenes to survive in extreme conditions and cause food contaminations have become a major concern. Hence, routine microbiological food testing is necessary to prevent food contamination and outbreaks of foodborne illness. This review provides insight into the methods for cultural detection, enumeration, and molecular identification of L. monocytogenes in various food samples. There are a number of enrichment and plating media that can be used for the isolation of L. monocytogenes from food samples. Enrichment media such as buffered Listeria enrichment broth, Fraser broth, and University of Vermont Medium (UVM) Listeria enrichment broth are recommended by regulatory agencies such as Food and Drug Administration-bacteriological and analytical method (FDA-BAM), US Department of Agriculture-Food and Safety (USDA-FSIS), and International Organization for Standardization (ISO). Many plating media are available for the isolation of L. monocytogenes, for instance, polymyxin acriflavin lithium-chloride ceftazidime aesculin mannitol, Oxford, and other chromogenic media. Besides, reference methods like FDA-BAM, ISO 11290 method, and USDA-FSIS method are usually applied for the cultural detection or enumeration of L. monocytogenes. most probable number technique is applied for the enumeration of L. monocytogenes in the case of low level contamination. Molecular methods including polymerase chain reaction, multiplex polymerase chain reaction, real-time/quantitative polymerase chain reaction, nucleic acid sequence-based amplification, loop-mediated isothermal amplification, DNA microarray, and next generation sequencing technology for the detection and identification of L. monocytogenes are discussed in this review. Overall, molecular methods are rapid, sensitive, specific, time- and labor-saving. In future, there are chances for the development of new techniques for the detection and identification of foodborne with improved features. PMID:26579116

Detection and 3D representation of pulmonary air bubbles in HRCT volumes

NASA Astrophysics Data System (ADS)

Silva, Jose S.; Silva, Augusto F.; Santos, Beatriz S.; Madeira, Joaquim

2003-05-01

Bubble emphysema is a disease characterized by the presence of air bubbles within the lungs. With the purpose of identifying pulmonary air bubbles, two alternative methods were developed, using High Resolution Computer Tomography (HRCT) exams. The search volume is confined to the pulmonary volume through a previously developed pulmonary contour detection algorithm. The first detection method follows a slice by slice approach and uses selection criteria based on the Hounsfield levels, dimensions, shape and localization of the bubbles. Candidate regions that do not exhibit axial coherence along at least two sections are excluded. Intermediate sections are interpolated for a more realistic representation of lungs and bubbles. The second detection method, after the pulmonary volume delimitation, follows a fully 3D approach. A global threshold is applied to the entire lung volume returning candidate regions. 3D morphologic operators are used to remove spurious structures and to circumscribe the bubbles. Bubble representation is accomplished by two alternative methods. The first generates bubble surfaces based on the voxel volumes previously detected; the second method assumes that bubbles are approximately spherical. In order to obtain better 3D representations, fits super-quadrics to bubble volume. The fitting process is based on non-linear least squares optimization method, where a super-quadric is adapted to a regular grid of points defined on each bubble. All methods were applied to real and semi-synthetical data where artificial and randomly deformed bubbles were embedded in the interior of healthy lungs. Quantitative results regarding bubble geometric features are either similar to a priori known values used in simulation tests, or indicate clinically acceptable dimensions and locations when dealing with real data.

An insight into the isolation, enumeration, and molecular detection of Listeria monocytogenes in food.

PubMed

Law, Jodi Woan-Fei; Ab Mutalib, Nurul-Syakima; Chan, Kok-Gan; Lee, Learn-Han

2015-01-01

Listeria monocytogenes, a foodborne pathogen that can cause listeriosis through the consumption of food contaminated with this pathogen. The ability of L. monocytogenes to survive in extreme conditions and cause food contaminations have become a major concern. Hence, routine microbiological food testing is necessary to prevent food contamination and outbreaks of foodborne illness. This review provides insight into the methods for cultural detection, enumeration, and molecular identification of L. monocytogenes in various food samples. There are a number of enrichment and plating media that can be used for the isolation of L. monocytogenes from food samples. Enrichment media such as buffered Listeria enrichment broth, Fraser broth, and University of Vermont Medium (UVM) Listeria enrichment broth are recommended by regulatory agencies such as Food and Drug Administration-bacteriological and analytical method (FDA-BAM), US Department of Agriculture-Food and Safety (USDA-FSIS), and International Organization for Standardization (ISO). Many plating media are available for the isolation of L. monocytogenes, for instance, polymyxin acriflavin lithium-chloride ceftazidime aesculin mannitol, Oxford, and other chromogenic media. Besides, reference methods like FDA-BAM, ISO 11290 method, and USDA-FSIS method are usually applied for the cultural detection or enumeration of L. monocytogenes. most probable number technique is applied for the enumeration of L. monocytogenes in the case of low level contamination. Molecular methods including polymerase chain reaction, multiplex polymerase chain reaction, real-time/quantitative polymerase chain reaction, nucleic acid sequence-based amplification, loop-mediated isothermal amplification, DNA microarray, and next generation sequencing technology for the detection and identification of L. monocytogenes are discussed in this review. Overall, molecular methods are rapid, sensitive, specific, time- and labor-saving. In future, there are chances for the development of new techniques for the detection and identification of foodborne with improved features.

Gas chromatographic quadrupole time-of-flight full scan high resolution mass spectrometric screening of human urine in antidoping analysis.

PubMed

Abushareeda, Wadha; Lyris, Emmanouil; Kraiem, Suhail; Wahaibi, Aisha Al; Alyazidi, Sameera; Dbes, Najib; Lommen, Arjen; Nielen, Michel; Horvatovich, Peter L; Alsayrafi, Mohammed; Georgakopoulos, Costas

2017-09-15

This paper presents the development and validation of a high-resolution full scan (FS) electron impact ionization (EI) gas chromatography coupled to quadrupole Time-of-Flight mass spectrometry (GC/QTOF) platform for screening anabolic androgenic steroids (AAS) in human urine samples. The World Antidoping Agency (WADA) enlists AAS as prohibited doping agents in sports, and our method has been developed to comply with the qualitative specifications of WADA to be applied for the detection of sports antidoping prohibited substances, mainly for AAS. The method also comprises of the quantitative analysis of the WADA's Athlete Biological Passport (ABP) endogenous steroidal parameters. The applied preparation of urine samples includes enzymatic hydrolysis for the cleavage of the Phase II glucuronide conjugates, generic liquid-liquid extraction and trimethylsilyl (TMS) derivatization steps. Tandem mass spectrometry (MS/MS) acquisition was applied on few selected ions to enhance the specificity and sensitivity of GC/TOF signal of few compounds. The full scan high resolution acquisition of analytical signal, for known and unknown TMS derivatives of AAS provides the antidoping system with a new analytical tool for the detection designer drugs and novel metabolites, which prolongs the AAS detection, after electronic data files' reprocessing. The current method is complementary to the respective liquid chromatography coupled to mass spectrometry (LC/MS) methodology widely used to detect prohibited molecules in sport, which cannot be efficiently ionized with atmospheric pressure ionization interface. Copyright © 2017 Elsevier B.V. All rights reserved.

Stepwise and stagewise approaches for spatial cluster detection

PubMed Central

Xu, Jiale

2016-01-01

Spatial cluster detection is an important tool in many areas such as sociology, botany and public health. Previous work has mostly taken either hypothesis testing framework or Bayesian framework. In this paper, we propose a few approaches under a frequentist variable selection framework for spatial cluster detection. The forward stepwise methods search for multiple clusters by iteratively adding currently most likely cluster while adjusting for the effects of previously identified clusters. The stagewise methods also consist of a series of steps, but with tiny step size in each iteration. We study the features and performances of our proposed methods using simulations on idealized grids or real geographic area. From the simulations, we compare the performance of the proposed methods in terms of estimation accuracy and power of detections. These methods are applied to the the well-known New York leukemia data as well as Indiana poverty data. PMID:27246273

A model-guided symbolic execution approach for network protocol implementations and vulnerability detection.

PubMed

Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing

2017-01-01

Formal techniques have been devoted to analyzing whether network protocol specifications violate security policies; however, these methods cannot detect vulnerabilities in the implementations of the network protocols themselves. Symbolic execution can be used to analyze the paths of the network protocol implementations, but for stateful network protocols, it is difficult to reach the deep states of the protocol. This paper proposes a novel model-guided approach to detect vulnerabilities in network protocol implementations. Our method first abstracts a finite state machine (FSM) model, then utilizes the model to guide the symbolic execution. This approach achieves high coverage of both the code and the protocol states. The proposed method is implemented and applied to test numerous real-world network protocol implementations. The experimental results indicate that the proposed method is more effective than traditional fuzzing methods such as SPIKE at detecting vulnerabilities in the deep states of network protocol implementations.

Wavelet Fusion for Concealed Object Detection Using Passive Millimeter Wave Sequence Images

NASA Astrophysics Data System (ADS)

Chen, Y.; Pang, L.; Liu, H.; Xu, X.

2018-04-01

PMMW imaging system can create interpretable imagery on the objects concealed under clothing, which gives the great advantage to the security check system. Paper addresses wavelet fusion to detect concealed objects using passive millimeter wave (PMMW) sequence images. According to PMMW real-time imager acquired image characteristics and storage methods firstly, using the sum of squared difference (SSD) as the image-related parameters to screen the sequence images. Secondly, the selected images are optimized using wavelet fusion algorithm. Finally, the concealed objects are detected by mean filter, threshold segmentation and edge detection. The experimental results show that this method improves the detection effect of concealed objects by selecting the most relevant images from PMMW sequence images and using wavelet fusion to enhance the information of the concealed objects. The method can be effectively applied to human body concealed object detection in millimeter wave video.

Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

2018-03-01

High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

Rapid and sensitive detection of human astrovirus in water samples by loop-mediated isothermal amplification with hydroxynaphthol blue dye.

PubMed

Yang, Bo-Yun; Liu, Xiao-Lu; Wei, Yu-Mei; Wang, Jing-Qi; He, Xiao-Qing; Jin, Yi; Wang, Zi-Jian

2014-02-14

The aim of this paper was to develop a reverse transcription loop-mediated isothermal amplification (RT-LAMP) method for rapid, sensitive and inexpensive detection of astrovirus. The detection limit of LAMP using in vitro RNA transcripts was 3.6 × 10 copies·μL⁻¹, which is as sensitive as the presently used PCR assays. However, the LAMP products could be identified as different colors with the naked eye following staining with hydroxynaphthol blue dye (HNB). No cross-reactivity with other gastroenteric viruses (rotavirus and norovirus) was observed, indicating the relatively high specificity of LAMP. The RT-LAMP method with HNB was used to effectively detect astrovirus in reclaimed water samples. The LAMP technique described in this study is a cheap, sensitive, specific and rapid method for the detection of astrovirus. The RT-LAMP method can be simply applied for the specific detection of astrovirus and has the potential to be utilized in the field as a screening test.

Structural health monitoring using DOG multi-scale space: an approach for analyzing damage characteristics

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-03-01

Measurement noise is inevitable in practice; thus, it is difficult to identify defects, cracks or damage in a structure while suppressing noise simultaneously. In this work, a novel method is introduced to detect multiple damage in noisy environments. Based on multi-scale space analysis for discrete signals, a method for extracting damage characteristics from the measured displacement mode shape is illustrated. Moreover, the proposed method incorporates a data fusion algorithm to further eliminate measurement noise-based interference. The effectiveness of the method is verified by numerical and experimental methods applied to different structural types. The results demonstrate that there are two advantages to the proposed method. First, damage features are extracted by the difference of the multi-scale representation; this step is taken such that the interference of noise amplification can be avoided. Second, a data fusion technique applied to the proposed method provides a global decision, which retains the damage features while maximally eliminating the uncertainty. Monte Carlo simulations are utilized to validate that the proposed method has a higher accuracy in damage detection.

Human ear detection in the thermal infrared spectrum

NASA Astrophysics Data System (ADS)

Abaza, Ayman; Bourlai, Thirimachos

2012-06-01

In this paper the problem of human ear detection in the thermal infrared (IR) spectrum is studied in order to illustrate the advantages and limitations of the most important steps of ear-based biometrics that can operate in day and night time environments. The main contributions of this work are two-fold: First, a dual-band database is assembled that consists of visible and thermal profile face images. The thermal data was collected using a high definition middle-wave infrared (3-5 microns) camera that is capable of acquiring thermal imprints of human skin. Second, a fully automated, thermal imaging based ear detection method is developed for real-time segmentation of human ears in either day or night time environments. The proposed method is based on Haar features forming a cascaded AdaBoost classifier (our modified version of the original Viola-Jones approach1 that was designed to be applied mainly in visible band images). The main advantage of the proposed method, applied on our profile face image data set collected in the thermal-band, is that it is designed to reduce the learning time required by the original Viola-Jones method from several weeks to several hours. Unlike other approaches reported in the literature, which have been tested but not designed to operate in the thermal band, our method yields a high detection accuracy that reaches ~ 91.5%. Further analysis on our data set yielded that: (a) photometric normalization techniques do not directly improve ear detection performance. However, when using a certain photometric normalization technique (CLAHE) on falsely detected images, the detection rate improved by ~ 4%; (b) the high detection accuracy of our method did not degrade when we lowered down the original spatial resolution of thermal ear images. For example, even after using one third of the original spatial resolution (i.e. ~ 20% of the original computational time) of the thermal profile face images, the high ear detection accuracy of our method remained unaffected. This resulted also in speeding up the detection time of an ear image from 265 to 17 milliseconds per image. To the best of our knowledge this is the first time that the problem of human ear detection in the thermal band is being investigated in the open literature.

Quantification of ethanol in plasma by electrochemical detection with an unmodified screen printed carbon electrode

NASA Astrophysics Data System (ADS)

Tian, Gang; Zhang, Xiao-Qing; Zhu, Ming-Song; Zhang, Zhong; Shi, Zheng-Hu; Ding, Min

2016-03-01

Simple, rapid and accurate detection of ethanol concentration in blood is very crucial in the diagnosis and management of potential acute ethanol intoxication patients. A novel electrochemical detection method was developed for the quantification of ethanol in human plasma with disposable unmodified screen-printed carbon electrode (SPCE) without sample preparation procedure. Ethanol was detected indirectly by the reaction product of ethanol dehydrogenase (ADH) and cofactor nicotinamide adenine dinucleotide (NAD+). Method validation indicated good quantitation precisions with intra-day and inter-day relative standard deviations of ≤9.4% and 8.0%, respectively. Ethanol concentration in plasma is linear ranging from 0.10 to 3.20 mg/mL, and the detection limit is 40.0 μg/mL (S/N > 3). The method shows satisfactory correlation with the reference method of headspace gas chromatography in twenty human plasma samples (correlation coefficient 0.9311). The proposed method could be applied to diagnose acute ethanol toxicity or ethanol-related death.

Development and application of a selective detection method for genetically modified soy and soy-derived products.

PubMed

Hoef, A M; Kok, E J; Bouw, E; Kuiper, H A; Keijer, J

1998-10-01

A method has been developed to distinguish between traditional soy beans and transgenic Roundup Ready soy beans, i.e. the glyphosate ('Roundup') resistant soy bean variety developed by Monsanto Company. Glyphosate resistance results from the incorporation of an Agrobacterium-derived 5-enol-pyruvyl-shikimate-3-phosphatesynthase (EPSPS) gene. The detection method developed is based on a nested Polymerase Chain Reaction (PCR) procedure. Ten femtograms of soy bean DNA can be detected, while, starting from whole soy beans, Roundup Ready DNA can be detected at a level of 1 Roundup Ready soy bean in 5000 non-GM soy beans (0.02% Roundup Ready soy bean). The method has been applied to samples of soy bean, soy-meal pellets and soy bean flour, as well as a number of processed complex products such as infant formula based on soy, tofu, tempeh, soy-based desserts, bakery products and complex meat and meat-replacing products. The results obtained are discussed with respect to practical application of the detection method developed.

Quantification of ethanol in plasma by electrochemical detection with an unmodified screen printed carbon electrode

PubMed Central

Tian, Gang; Zhang, Xiao-Qing; Zhu, Ming-Song; Zhang, Zhong; Shi, Zheng-Hu; Ding, Min

2016-01-01

Simple, rapid and accurate detection of ethanol concentration in blood is very crucial in the diagnosis and management of potential acute ethanol intoxication patients. A novel electrochemical detection method was developed for the quantification of ethanol in human plasma with disposable unmodified screen-printed carbon electrode (SPCE) without sample preparation procedure. Ethanol was detected indirectly by the reaction product of ethanol dehydrogenase (ADH) and cofactor nicotinamide adenine dinucleotide (NAD+). Method validation indicated good quantitation precisions with intra-day and inter-day relative standard deviations of ≤9.4% and 8.0%, respectively. Ethanol concentration in plasma is linear ranging from 0.10 to 3.20 mg/mL, and the detection limit is 40.0 μg/mL (S/N > 3). The method shows satisfactory correlation with the reference method of headspace gas chromatography in twenty human plasma samples (correlation coefficient 0.9311). The proposed method could be applied to diagnose acute ethanol toxicity or ethanol-related death. PMID:27006081

Multiple-Bit Differential Detection of OQPSK

NASA Technical Reports Server (NTRS)

Simon, Marvin

2005-01-01

A multiple-bit differential-detection method has been proposed for the reception of radio signals modulated with offset quadrature phase-shift keying (offset QPSK or OQPSK). The method is also applicable to other spectrally efficient offset quadrature modulations. This method is based partly on the same principles as those of a multiple-symbol differential-detection method for M-ary QPSK, which includes QPSK (that is, non-offset QPSK) as a special case. That method was introduced more than a decade ago by the author of the present method as a means of improving performance relative to a traditional (two-symbol observation) differential-detection scheme. Instead of symbol-by-symbol detection, both that method and the present one are based on a concept of maximum-likelihood sequence estimation (MLSE). As applied to the modulations in question, MLSE involves consideration of (1) all possible binary data sequences that could have been received during an observation time of some number, N, of symbol periods and (2) selection of the sequence that yields the best match to the noise-corrupted signal received during that time. The performance of the prior method was shown to range from that of traditional differential detection for short observation times (small N) to that of ideal coherent detection (with differential encoding) for long observation times (large N).

Detection of Unknown Crypts under the Floor in the Holy Trinity Church (Dominican Monastery) in Krakow, Poland

NASA Astrophysics Data System (ADS)

Strzępowicz, Anna; Łyskowski, Mikołaj; Ziętek, Jerzy; Tomecka-Suchoń, Sylwia

2018-03-01

The GPR surveying method belongs to non-invasive and quick geophysical methods, applied also in archaeological prospection. It allows for detecting archaeological artefacts buried under historical layers, and also those which can be found within buildings of historical value. Most commonly, just as in this particular case, it is used in churches, where other non-invasive localisation methods cannot be applied. In a majority of cases, surveys bring about highly positive results, enabling the site and size of a specific object to be indicated. A good example are the results obtained from the measurements carried out in the Basilica of Holy Trinity, belonging to the Dominican Monastery in Krakow. They allowed for confirming the location of the already existing crypts and for indicating so-far unidentified objects.

Time-domain reflectance diffuse optical tomography with Mellin-Laplace transform for experimental detection and depth localization of a single absorbing inclusion

PubMed Central

Puszka, Agathe; Hervé, Lionel; Planat-Chrétien, Anne; Koenig, Anne; Derouard, Jacques; Dinten, Jean-Marc

2013-01-01

We show how to apply the Mellin-Laplace transform to process time-resolved reflectance measurements for diffuse optical tomography. We illustrate this method on simulated signals incorporating the main sources of experimental noise and suggest how to fine-tune the method in order to detect the deepest absorbing inclusions and optimize their localization in depth, depending on the dynamic range of the measurement. To finish, we apply this method to measurements acquired with a setup including a femtosecond laser, photomultipliers and a time-correlated single photon counting board. Simulations and experiments are illustrated for a probe featuring the interfiber distance of 1.5 cm and show the potential of time-resolved techniques for imaging absorption contrast in depth with this geometry. PMID:23577292

Vortex flows in the solar chromosphere. I. Automatic detection method

NASA Astrophysics Data System (ADS)

Kato, Y.; Wedemeyer, S.

2017-05-01

Solar "magnetic tornadoes" are produced by rotating magnetic field structures that extend from the upper convection zone and the photosphere to the corona of the Sun. Recent studies show that these kinds of rotating features are an integral part of atmospheric dynamics and occur on a large range of spatial scales. A systematic statistical study of magnetic tornadoes is a necessary next step towards understanding their formation and their role in mass and energy transport in the solar atmosphere. For this purpose, we develop a new automatic detection method for chromospheric swirls, meaning the observable signature of solar tornadoes or, more generally, chromospheric vortex flows and rotating motions. Unlike existing studies that rely on visual inspections, our new method combines a line integral convolution (LIC) imaging technique and a scalar quantity that represents a vortex flow on a two-dimensional plane. We have tested two detection algorithms, based on the enhanced vorticity and vorticity strength quantities, by applying them to three-dimensional numerical simulations of the solar atmosphere with CO5BOLD. We conclude that the vorticity strength method is superior compared to the enhanced vorticity method in all aspects. Applying the method to a numerical simulation of the solar atmosphere reveals very abundant small-scale, short-lived chromospheric vortex flows that have not been found previously by visual inspection.

Detection of alpha radiation in a beta radiation field

DOEpatents

Mohagheghi, Amir H.; Reese, Robert P.

2001-01-01

An apparatus and method for detecting alpha particles in the presence of high activities of beta particles utilizing an alpha spectrometer. The apparatus of the present invention utilizes a magnetic field applied around the sample in an alpha spectrometer to deflect the beta particles from the sample prior to reaching the detector, thus permitting detection of low concentrations of alpha particles. In the method of the invention, the strength of magnetic field required to adequately deflect the beta particles and permit alpha particle detection is given by an algorithm that controls the field strength as a function of sample beta energy and the distance of the sample to the detector.

Using Quenching to Detect Corrosion on Sculptural Metalwork: A Real-World Application of Fluorescence Spectroscopy

ERIC Educational Resources Information Center

Hensen, Cory; Clare, Tami Lasseter; Barbera, Jack

2018-01-01

Fluorescence spectroscopy experiments are a frequently taught as part of upper-division teaching laboratories. To expose undergraduate students to an applied fluorescence technique, a corrosion detection method, using quenching, was adapted from authentic research for an instrumental analysis laboratory. In the experiment, students acquire…

Current and state-of-the-art approaches for detecting mycotoxins in commodities

USDA-ARS?s Scientific Manuscript database

The tools that have been applied to detection of mycotoxins in commodities are numerous and powerful. These include everything from simple to use diagnostic test strips to complex, instrument intensive, methods such as ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS). This wi...

An on-board pedestrian detection and warning system with features of side pedestrian

NASA Astrophysics Data System (ADS)

Cheng, Ruzhong; Zhao, Yong; Wong, ChupChung; Chan, KwokPo; Xu, Jiayao; Wang, Xin'an

2012-01-01

Automotive Active Safety(AAS) is the main branch of intelligence automobile study and pedestrian detection is the key problem of AAS, because it is related with the casualties of most vehicle accidents. For on-board pedestrian detection algorithms, the main problem is to balance efficiency and accuracy to make the on-board system available in real scenes, so an on-board pedestrian detection and warning system with the algorithm considered the features of side pedestrian is proposed. The system includes two modules, pedestrian detecting and warning module. Haar feature and a cascade of stage classifiers trained by Adaboost are first applied, and then HOG feature and SVM classifier are used to refine false positives. To make these time-consuming algorithms available in real-time use, a divide-window method together with operator context scanning(OCS) method are applied to increase efficiency. To merge the velocity information of the automotive, the distance of the detected pedestrian is also obtained, so the system could judge if there is a potential danger for the pedestrian in the front. With a new dataset captured in urban environment with side pedestrians on zebra, the embedded system and its algorithm perform an on-board available result on side pedestrian detection.

Development and validation of an MEKC method for determination of nitrogen-containing drugs in pharmaceutical preparations.

PubMed

Buiarelli, Francesca; Coccioli, Franco; Jasionowska, Renata; Terracciano, Alessandro

2008-09-01

A fast and accurate micellar electrokinetic capillary chromatography method was developed for quality control of pharmaceutical preparations containing cold remedies as acetaminophen, salicylamide, caffeine, phenylephrine, pseudoephedrine, norephedrine and chlorpheniramine. The method optimization was realized on a Beckman P/ACE System MDQ instrument. The baseline separation of seven analytes was performed in an uncoated fused silica capillary internal diameter (ID)=50 microm using tris-borate (20 mM, pH=8.5) containing sodium dodecyl sulphate 30 mM BGE. On line-UV detection at 214 nm was performed and the applied voltage was 10 kV. The operating temperature was 25 degrees C. After experimental conditions optimization, the proposed method was validated. The evaluated parameters were: precision of migration time and of corrected peak area ratio, linearity range, limit of detection, limit of quantification, accuracy (recovery), ruggedness and applicability. The method was then successfully applied for the analysis of three pharmaceutical preparations containing some of the analytes listed before.

Improving Magnitude Detection Thresholds Using Multi-Station Multi-Event, and Multi-Phase Methods

DTIC Science & Technology

2008-07-31

applied to different tectonic settings and for what percentage of the seismicity. 111 million correlations were performed on Lg-waves for the events in...x xi Acknowledgments We’d like to thank the operators of the Chinese Digital Seismograph Network, the U.S. Geological Survey, and...applicable correlation methods can be applied to different tectonic settings and for what percentage of the seismicity. 111 million correlations were

Detection and classification of Breast Cancer in Wavelet Sub-bands of Fractal Segmented Cancerous Zones.

PubMed

Shirazinodeh, Alireza; Noubari, Hossein Ahmadi; Rabbani, Hossein; Dehnavi, Alireza Mehri

2015-01-01

Recent studies on wavelet transform and fractal modeling applied on mammograms for the detection of cancerous tissues indicate that microcalcifications and masses can be utilized for the study of the morphology and diagnosis of cancerous cases. It is shown that the use of fractal modeling, as applied to a given image, can clearly discern cancerous zones from noncancerous areas. In this paper, for fractal modeling, the original image is first segmented into appropriate fractal boxes followed by identifying the fractal dimension of each windowed section using a computationally efficient two-dimensional box-counting algorithm. Furthermore, using appropriate wavelet sub-bands and image Reconstruction based on modified wavelet coefficients, it is shown that it is possible to arrive at enhanced features for detection of cancerous zones. In this paper, we have attempted to benefit from the advantages of both fractals and wavelets by introducing a new algorithm. By using a new algorithm named F1W2, the original image is first segmented into appropriate fractal boxes, and the fractal dimension of each windowed section is extracted. Following from that, by applying a maximum level threshold on fractal dimensions matrix, the best-segmented boxes are selected. In the next step, the segmented Cancerous zones which are candidates are then decomposed by utilizing standard orthogonal wavelet transform and db2 wavelet in three different resolution levels, and after nullifying wavelet coefficients of the image at the first scale and low frequency band of the third scale, the modified reconstructed image is successfully utilized for detection of breast cancer regions by applying an appropriate threshold. For detection of cancerous zones, our simulations indicate the accuracy of 90.9% for masses and 88.99% for microcalcifications detection results using the F1W2 method. For classification of detected mictocalcification into benign and malignant cases, eight features are identified and utilized in radial basis function neural network. Our simulation results indicate the accuracy of 92% classification using F1W2 method.

Method and apparatus for detecting and/or imaging clusters of small scattering centers in the body

DOEpatents

Perez-Mendez, V.; Sommer, F.G.

1982-07-13

An ultrasonic method and apparatus are provided for detecting and imaging clusters of small scattering centers in the breast wherein periodic pulses are applied to an ultrasound emitting transducer and projected into the body, thereafter being received by at least one receiving transducer positioned to receive scattering from the scattering center clusters. The signals are processed to provide an image showing cluster extent and location. 6 figs.

Method and apparatus for detecting and/or imaging clusters of small scattering centers in the body

DOEpatents

Perez-Mendez, Victor; Sommer, Frank G.

1982-01-01

An ultrasonic method and apparatus are provided for detecting and imaging clusters of small scattering centers in the breast wherein periodic pulses are applied to an ultrasound emitting transducer and projected into the body, thereafter being received by at least one receiving transducer positioned to receive scattering from the scattering center clusters. The signals are processed to provide an image showing cluster extent and location.

Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

NASA Astrophysics Data System (ADS)

Abdulbaqi, Hayder Saad; Jafri, Mohd Zubir Mat; Omar, Ahmad Fairuz; Mustafa, Iskandar Shahrim Bin; Abood, Loay Kadom

2015-04-01

Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introduce a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.

Latent component-based gear tooth fault detection filter using advanced parametric modeling

NASA Astrophysics Data System (ADS)

Ettefagh, M. M.; Sadeghi, M. H.; Rezaee, M.; Chitsaz, S.

2009-10-01

In this paper, a new parametric model-based filter is proposed for gear tooth fault detection. The designing of the filter consists of identifying the most proper latent component (LC) of the undamaged gearbox signal by analyzing the instant modules (IMs) and instant frequencies (IFs) and then using the component with lowest IM as the proposed filter output for detecting fault of the gearbox. The filter parameters are estimated by using the LC theory in which an advanced parametric modeling method has been implemented. The proposed method is applied on the signals, extracted from simulated gearbox for detection of the simulated gear faults. In addition, the method is used for quality inspection of the produced Nissan-Junior vehicle gearbox by gear profile error detection in an industrial test bed. For evaluation purpose, the proposed method is compared with the previous parametric TAR/AR-based filters in which the parametric model residual is considered as the filter output and also Yule-Walker and Kalman filter are implemented for estimating the parameters. The results confirm the high performance of the new proposed fault detection method.

Peripleural lung disease detection based on multi-slice CT images

NASA Astrophysics Data System (ADS)

Matsuhiro, M.; Suzuki, H.; Kawata, Y.; Niki, N.; Nakano, Y.; Ohmatsu, H.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.

2015-03-01

With the development of multi-slice CT technology, obtaining accurate 3D images of lung field in a short time become possible. To support that, a lot of image processing methods need to be developed. Detection peripleural lung disease is difficult due to its existence out of lung region, because lung extraction is often performed based on threshold processing. The proposed method uses thoracic inner region extracted by inner cavity of bone as well as air region, covers peripleural lung diseased cases such as lung nodule, calcification, pleural effusion and pleural plaque. We applied this method to 50 cases including 39 peripleural lung diseased cases. This method was able to detect 39 peripleural lung disease with 2.9 false positive per case.

Incorporating profile information in community detection for online social networks

NASA Astrophysics Data System (ADS)

Fan, W.; Yeung, K. H.

2014-07-01

Community structure is an important feature in the study of complex networks. It is because nodes of the same community may have similar properties. In this paper we extend two popular community detection methods to partition online social networks. In our extended methods, the profile information of users is used for partitioning. We apply the extended methods in several sample networks of Facebook. Compared with the original methods, the community structures we obtain have higher modularity. Our results indicate that users' profile information is consistent with the community structure of their friendship network to some extent. To the best of our knowledge, this paper is the first to discuss how profile information can be used to improve community detection in online social networks.

Vertebra identification using template matching modelmp and K-means clustering.

PubMed

Larhmam, Mohamed Amine; Benjelloun, Mohammed; Mahmoudi, Saïd

2014-03-01

Accurate vertebra detection and segmentation are essential steps for automating the diagnosis of spinal disorders. This study is dedicated to vertebra alignment measurement, the first step in a computer-aided diagnosis tool for cervical spine trauma. Automated vertebral segment alignment determination is a challenging task due to low contrast imaging and noise. A software tool for segmenting vertebrae and detecting subluxations has clinical significance. A robust method was developed and tested for cervical vertebra identification and segmentation that extracts parameters used for vertebra alignment measurement. Our contribution involves a novel combination of a template matching method and an unsupervised clustering algorithm. In this method, we build a geometric vertebra mean model. To achieve vertebra detection, manual selection of the region of interest is performed initially on the input image. Subsequent preprocessing is done to enhance image contrast and detect edges. Candidate vertebra localization is then carried out by using a modified generalized Hough transform (GHT). Next, an adapted cost function is used to compute local voted centers and filter boundary data. Thereafter, a K-means clustering algorithm is applied to obtain clusters distribution corresponding to the targeted vertebrae. These clusters are combined with the vote parameters to detect vertebra centers. Rigid segmentation is then carried out by using GHT parameters. Finally, cervical spine curves are extracted to measure vertebra alignment. The proposed approach was successfully applied to a set of 66 high-resolution X-ray images. Robust detection was achieved in 97.5 % of the 330 tested cervical vertebrae. An automated vertebral identification method was developed and demonstrated to be robust to noise and occlusion. This work presents a first step toward an automated computer-aided diagnosis system for cervical spine trauma detection.

Usability Methods for Ensuring Health Information Technology Safety: Evidence-Based Approaches. Contribution of the IMIA Working Group Health Informatics for Patient Safety.

PubMed

Borycki, E; Kushniruk, A; Nohr, C; Takeda, H; Kuwata, S; Carvalho, C; Bainbridge, M; Kannry, J

2013-01-01

Issues related to lack of system usability and potential safety hazards continue to be reported in the health information technology (HIT) literature. Usability engineering methods are increasingly used to ensure improved system usability and they are also beginning to be applied more widely for ensuring the safety of HIT applications. These methods are being used in the design and implementation of many HIT systems. In this paper we describe evidence-based approaches to applying usability engineering methods. A multi-phased approach to ensuring system usability and safety in healthcare is described. Usability inspection methods are first described including the development of evidence-based safety heuristics for HIT. Laboratory-based usability testing is then conducted under artificial conditions to test if a system has any base level usability problems that need to be corrected. Usability problems that are detected are corrected and then a new phase is initiated where the system is tested under more realistic conditions using clinical simulations. This phase may involve testing the system with simulated patients. Finally, an additional phase may be conducted, involving a naturalistic study of system use under real-world clinical conditions. The methods described have been employed in the analysis of the usability and safety of a wide range of HIT applications, including electronic health record systems, decision support systems and consumer health applications. It has been found that at least usability inspection and usability testing should be applied prior to the widespread release of HIT. However, wherever possible, additional layers of testing involving clinical simulations and a naturalistic evaluation will likely detect usability and safety issues that may not otherwise be detected prior to widespread system release. The framework presented in the paper can be applied in order to develop more usable and safer HIT, based on multiple layers of evidence.

Detection and quantification of ionophore antibiotics in runoff, soil and poultry litter.

PubMed

Sun, Peizhe; Barmaz, Delphine; Cabrera, Miguel L; Pavlostathis, Spyros G; Huang, Ching-Hua

2013-10-18

Ionophore antibiotics (IPAs) are widely used as coccidiostats in poultry and other livestock industries to promote growth and prevent infections. Because most of the ingested IPAs are excreted in poultry litter, which is primarily applied as grassland fertilizer, a significant amount of IPAs can be released into the litter-soil-water environment. A robust analytical method has been developed to quantify IPAs (monensin (MON), salinomycin (SAL) and narasin (NAR)) in complex environmental compartments including surface runoff, soil and poultry litter, with success to minimize matrix interference. The method for water samples involves solid-phase extraction (SPE) followed by liquid-liquid extraction (LLE) post-clean up steps. The method for solid samples involves bi-solvent LLE. IPAs were detected by HPLC-MS, with optimized parameters to achieve the highest sensitivity. Nigericin (NIG), an IPA not used in livestock industry, is successfully applied and validated as a surrogate standard. The method recoveries were at 92-95% and 81-85% in runoff samples from unfertilized and litter-fertilized fields, respectively. For solids, the method recoveries were at 93-99% in soils, and 79-83% in poultry litter samples. SAL was detected at up to 22mg/kg and MON and NAR at up to 4mg/kg in broiler litter from different farms. Up to 183μg/kg of MON was detected in litter-fertilized soils. All three IPAs were detected in the rainfall runoff from litter-fertilized lands at concentrations up to 9μg/L. Copyright © 2013 Elsevier B.V. All rights reserved.

Infrared Laser Optoacoustic Detection Of Gases And Vapours

NASA Astrophysics Data System (ADS)

Johnson, S. A.; Cummins, P. G.; Bone, S. A.; Davies, P. B.

1988-10-01

Mid-infrared laser optoacoustic spectroscopy has been used to detect a variety of gases and vapours. Performance was calibrated using the signal from a known concentration of ethene, and then the method applied to the perfume alcohol geraniol. Detection limits were found to be 1 ppb for ethene and 70 ppb for geraniol on their strongest absorption lines for a few seconds measurement time.

Cest Analysis: Automated Change Detection from Very-High Remote Sensing Images

NASA Astrophysics Data System (ADS)

Ehlers, M.; Klonus, S.; Jarmer, T.; Sofina, N.; Michel, U.; Reinartz, P.; Sirmacek, B.

2012-08-01

A fast detection, visualization and assessment of change in areas of crisis or catastrophes are important requirements for coordination and planning of help. Through the availability of new satellites and/or airborne sensors with very high spatial resolutions (e.g., WorldView, GeoEye) new remote sensing data are available for a better detection, delineation and visualization of change. For automated change detection, a large number of algorithms has been proposed and developed. From previous studies, however, it is evident that to-date no single algorithm has the potential for being a reliable change detector for all possible scenarios. This paper introduces the Combined Edge Segment Texture (CEST) analysis, a decision-tree based cooperative suite of algorithms for automated change detection that is especially designed for the generation of new satellites with very high spatial resolution. The method incorporates frequency based filtering, texture analysis, and image segmentation techniques. For the frequency analysis, different band pass filters can be applied to identify the relevant frequency information for change detection. After transforming the multitemporal images via a fast Fourier transform (FFT) and applying the most suitable band pass filter, different methods are available to extract changed structures: differencing and correlation in the frequency domain and correlation and edge detection in the spatial domain. Best results are obtained using edge extraction. For the texture analysis, different 'Haralick' parameters can be calculated (e.g., energy, correlation, contrast, inverse distance moment) with 'energy' so far providing the most accurate results. These algorithms are combined with a prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination (CEST) of the change algorithms is applied to calculate the probability of change for a particular location. CEST was tested with high-resolution satellite images of the crisis areas of Darfur (Sudan). CEST results are compared with a number of standard algorithms for automated change detection such as image difference, image ratioe, principal component analysis, delta cue technique and post classification change detection. The new combined method shows superior results averaging between 45% and 15% improvement in accuracy.

HPLC and chemometrics-assisted UV-spectroscopy methods for the simultaneous determination of ambroxol and doxycycline in capsule

NASA Astrophysics Data System (ADS)

Hadad, Ghada M.; El-Gindy, Alaa; Mahmoud, Waleed M. M.

2008-08-01

High-performance liquid chromatography (HPLC) and multivariate spectrophotometric methods are described for the simultaneous determination of ambroxol hydrochloride (AM) and doxycycline (DX) in combined pharmaceutical capsules. The chromatographic separation was achieved on reversed-phase C 18 analytical column with a mobile phase consisting of a mixture of 20 mM potassium dihydrogen phosphate, pH 6-acetonitrile in ratio of (1:1, v/v) and UV detection at 245 nm. Also, the resolution has been accomplished by using numerical spectrophotometric methods as classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS-1) applied to the UV spectra of the mixture and graphical spectrophotometric method as first derivative of the ratio spectra ( 1DD) method. Analytical figures of merit (FOM), such as sensitivity, selectivity, analytical sensitivity, limit of quantitation and limit of detection were determined for CLS, PLS-1 and PCR methods. The proposed methods were validated and successfully applied for the analysis of pharmaceutical formulation and laboratory-prepared mixtures containing the two component combination.

HPLC and chemometrics-assisted UV-spectroscopy methods for the simultaneous determination of ambroxol and doxycycline in capsule.

PubMed

Hadad, Ghada M; El-Gindy, Alaa; Mahmoud, Waleed M M

2008-08-01

High-performance liquid chromatography (HPLC) and multivariate spectrophotometric methods are described for the simultaneous determination of ambroxol hydrochloride (AM) and doxycycline (DX) in combined pharmaceutical capsules. The chromatographic separation was achieved on reversed-phase C(18) analytical column with a mobile phase consisting of a mixture of 20mM potassium dihydrogen phosphate, pH 6-acetonitrile in ratio of (1:1, v/v) and UV detection at 245 nm. Also, the resolution has been accomplished by using numerical spectrophotometric methods as classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS-1) applied to the UV spectra of the mixture and graphical spectrophotometric method as first derivative of the ratio spectra ((1)DD) method. Analytical figures of merit (FOM), such as sensitivity, selectivity, analytical sensitivity, limit of quantitation and limit of detection were determined for CLS, PLS-1 and PCR methods. The proposed methods were validated and successfully applied for the analysis of pharmaceutical formulation and laboratory-prepared mixtures containing the two component combination.

Effect of the sequence data deluge on the performance of methods for detecting protein functional residues.

PubMed

Garrido-Martín, Diego; Pazos, Florencio

2018-02-27

The exponential accumulation of new sequences in public databases is expected to improve the performance of all the approaches for predicting protein structural and functional features. Nevertheless, this was never assessed or quantified for some widely used methodologies, such as those aimed at detecting functional sites and functional subfamilies in protein multiple sequence alignments. Using raw protein sequences as only input, these approaches can detect fully conserved positions, as well as those with a family-dependent conservation pattern. Both types of residues are routinely used as predictors of functional sites and, consequently, understanding how the sequence content of the databases affects them is relevant and timely. In this work we evaluate how the growth and change with time in the content of sequence databases affect five sequence-based approaches for detecting functional sites and subfamilies. We do that by recreating historical versions of the multiple sequence alignments that would have been obtained in the past based on the database contents at different time points, covering a period of 20 years. Applying the methods to these historical alignments allows quantifying the temporal variation in their performance. Our results show that the number of families to which these methods can be applied sharply increases with time, while their ability to detect potentially functional residues remains almost constant. These results are informative for the methods' developers and final users, and may have implications in the design of new sequencing initiatives.

Online in-tube microextractor coupled with UV-Vis spectrophotometer for bisphenol A detection.

PubMed

Poorahong, Sujittra; Thammakhet, Chongdee; Thavarungkul, Panote; Kanatharana, Proespichaya

2013-01-01

A simple and high extraction efficiency online in-tube microextractor (ITME) was developed for bisphenol A (BPA) detection in water samples. The ITME was fabricated by a stepwise electrodeposition of polyaniline, polyethylene glycol and polydimethylsiloxane composite (CPANI) inside a silico-steel tube. The obtained ITME coupled with UV-Vis detection at 278 nm was investigated. By this method, the extraction and pre-concentration of BPA in water were carried out in a single step. Under optimum conditions, the system provided a linear dynamic range of 0.1 to 100 μM with a limit of detection of 20 nM (S/N ≥3). A single in-tube microextractor had a good stability of more than 60 consecutive injections for 10.0 μM BPA with a relative standard deviation of less than 4%. Moreover, a good tube-to-tube reproducibility and precision were obtained. The system was applied to detect BPA in water samples from six brands of baby bottles and the results showed good agreement with those obtained from the conventional GC-MS method. Acceptable percentage recoveries from the spiked water samples were obtained, ranging from 83-102% for this new method compared with 73-107% for the GC-MS standard method. This new in-tube CPANI microextractor provided an excellent extraction efficiency and a good reproducibility. In addition, it can also be easily applied for the analysis of other polar organic compounds contaminated in water sample.

A cost-effective screening method for pesticide residue analysis in fruits, vegetables, and cereal grains.

PubMed

Ambrus, A; Füzesi, I; Susán, M; Dobi, D; Lantos, J; Zakar, F; Korsós, I; Oláh, J; Beke, B B; Katavics, L

2005-01-01

This paper reports the results of studies performed to investigate the potential of applying thin layer chromatography (TLC) detection in combination with selected extraction and cleanup methods, for providing an alternative cost-effective analytical procedure for screening and confirmation of pesticide residues in plant commodities. The extraction was carried out with ethyl acetate and an on-line extraction method applying an acetone-dichloromethane mixture. The extracts were cleaned up with SX-3 gel, an adsorbent mixture of active carbon, magnesia, and diatomaceous earth, and on silica micro cartridges. The Rf values of 118 pesticides were tested in eleven elution systems with UV, and eight biotest methods and chemical detection reagents. Cabbage, green peas, orange, and tomatoes were selected as representative sample matrices for fruits and vegetables, while maize, rice, and wheat represented cereal grains. As an internal quality control measure, marker compounds were applied on each plate to verify the proper elution and detection conditions. The Rf values varied in the different elution systems. The best separation (widest Rf range) was achieved with silica gel (SG)--ethyl acetate (0.05-0.7), SG--benzene, (0.02-0.7) and reverse phase RP-18 F-254S layer with acetone: methanol: water/30:30:30 (v/v) (0.1-0.8). The relative standard deviation of Rf values (CV(Rf)) within laboratory reproducibility was generally less than 20%, except below 0.2 Rf, where the CVRf rapidly increased with decreasing Rf values. The fungi spore inhibition, chloroplast inhibition, and enzyme inhibition were found most suitable for detection of pesticides primarily for confirming their identity or screening for known substances. Their use for determination of pesticide residues in samples of unknown origin is not recommended.

Applying independent component analysis to detect silent speech in magnetic resonance imaging signals.

PubMed

Abe, Kazuhiro; Takahashi, Toshimitsu; Takikawa, Yoriko; Arai, Hajime; Kitazawa, Shigeru

2011-10-01

Independent component analysis (ICA) can be usefully applied to functional imaging studies to evaluate the spatial extent and temporal profile of task-related brain activity. It requires no a priori assumptions about the anatomical areas that are activated or the temporal profile of the activity. We applied spatial ICA to detect a voluntary but hidden response of silent speech. To validate the method against a standard model-based approach, we used the silent speech of a tongue twister as a 'Yes' response to single questions that were delivered at given times. In the first task, we attempted to estimate one number that was chosen by a participant from 10 possibilities. In the second task, we increased the possibilities to 1000. In both tasks, spatial ICA was as effective as the model-based method for determining the number in the subject's mind (80-90% correct per digit), but spatial ICA outperformed the model-based method in terms of time, especially in the 1000-possibility task. In the model-based method, calculation time increased by 30-fold, to 15 h, because of the necessity of testing 1000 possibilities. In contrast, the calculation time for spatial ICA remained as short as 30 min. In addition, spatial ICA detected an unexpected response that occurred by mistake. This advantage was validated in a third task, with 13 500 possibilities, in which participants had the freedom to choose when to make one of four responses. We conclude that spatial ICA is effective for detecting the onset of silent speech, especially when it occurs unexpectedly. © 2011 The Authors. European Journal of Neuroscience © 2011 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Analysis of microdialysate monoamines, including noradrenaline, dopamine and serotonin, using capillary ultra-high performance liquid chromatography and electrochemical detection.

PubMed

Ferry, Barbara; Gifu, Elena-Patricia; Sandu, Ioana; Denoroy, Luc; Parrot, Sandrine

2014-03-01

Electrochemical methods are very often used to detect catecholamine and indolamine neurotransmitters separated by conventional reverse-phase high performance liquid chromatography (HPLC). The present paper presents the development of a chromatographic method to detect monoamines present in low-volume brain dialysis samples using a capillary column filled with sub-2μm particles. Several parameters (repeatability, linearity, accuracy, limit of detection) for this new ultrahigh performance liquid chromatography (UHPLC) method with electrochemical detection were examined after optimization of the analytical conditions. Noradrenaline, adrenaline, serotonin, dopamine and its metabolite 3-methoxytyramine were separated in 1μL of injected sample volume; they were detected above concentrations of 0.5-1nmol/L, with 2.1-9.5% accuracy and intra-assay repeatability equal to or less than 6%. The final method was applied to very low volume dialysates from rat brain containing monoamine traces. The study demonstrates that capillary UHPLC with electrochemical detection is suitable for monitoring dialysate monoamines collected at high sampling rate. Copyright © 2014 Elsevier B.V. All rights reserved.

On-line MSPD-SPE-HPLC/FLD analysis of polycyclic aromatic hydrocarbons in bovine tissues.

PubMed

Gutiérrez-Valencia, Tania M; García de Llasera, Martha P

2017-05-15

A fast method was optimized and validated for simultaneous trace determination of four polycyclic aromatic hydrocarbons: benzo[a]anthracene, benzo[b]fluoranthene, benzo[k]fluoranthene and benzo[a]pyrene in bovine tissues. The determination was performed by matrix solid-phase dispersion (MSPD) coupled on-line to solid phase extraction (SPE) and high performance liquid chromatography (HPLC) with fluorescence detection (FLD). The sample was dispersed on C 18 silica sorbent and then the on-line MSPD-SPE-HPLC/FLD method was applied. Several parameters were optimized: cleaning and elution sequences applied to the MSPD cartridge, the flow rate and dilution of extract used for SPE loading. The on-line method was validated over a concentration range of 0.1-0.6ngg -1 obtaining good linearity (r⩾0.998) and precision (RSD)⩽10%. Recovery ranged from 96 to 99% and the limits of detection were 0.012ngg -1 . This methodology was applied to liver samples from unhealthy animals. The results demonstrate that MSDP-SPE-HPLC/FLD method provides reliable, sensitive, accurate and fast data to the food control. Copyright © 2016 Elsevier Ltd. All rights reserved.

Regularized non-stationary morphological reconstruction algorithm for weak signal detection in microseismic monitoring: methodology

NASA Astrophysics Data System (ADS)

Huang, Weilin; Wang, Runqiu; Chen, Yangkang

2018-05-01

Microseismic signal is typically weak compared with the strong background noise. In order to effectively detect the weak signal in microseismic data, we propose a mathematical morphology based approach. We decompose the initial data into several morphological multiscale components. For detection of weak signal, a non-stationary weighting operator is proposed and introduced into the process of reconstruction of data by morphological multiscale components. The non-stationary weighting operator can be obtained by solving an inversion problem. The regularized non-stationary method can be understood as a non-stationary matching filtering method, where the matching filter has the same size as the data to be filtered. In this paper, we provide detailed algorithmic descriptions and analysis. The detailed algorithm framework, parameter selection and computational issue for the regularized non-stationary morphological reconstruction (RNMR) method are presented. We validate the presented method through a comprehensive analysis through different data examples. We first test the proposed technique using a synthetic data set. Then the proposed technique is applied to a field project, where the signals induced from hydraulic fracturing are recorded by 12 three-component geophones in a monitoring well. The result demonstrates that the RNMR can improve the detectability of the weak microseismic signals. Using the processed data, the short-term-average over long-term average picking algorithm and Geiger's method are applied to obtain new locations of microseismic events. In addition, we show that the proposed RNMR method can be used not only in microseismic data but also in reflection seismic data to detect the weak signal. We also discussed the extension of RNMR from 1-D to 2-D or a higher dimensional version.

SpeCond: a method to detect condition-specific gene expression

PubMed Central

2011-01-01

Transcriptomic studies routinely measure expression levels across numerous conditions. These datasets allow identification of genes that are specifically expressed in a small number of conditions. However, there are currently no statistically robust methods for identifying such genes. Here we present SpeCond, a method to detect condition-specific genes that outperforms alternative approaches. We apply the method to a dataset of 32 human tissues to determine 2,673 specifically expressed genes. An implementation of SpeCond is freely available as a Bioconductor package at http://www.bioconductor.org/packages/release/bioc/html/SpeCond.html. PMID:22008066

Efficient subtle motion detection from high-speed video for sound recovery and vibration analysis using singular value decomposition-based approach

NASA Astrophysics Data System (ADS)

Zhang, Dashan; Guo, Jie; Jin, Yi; Zhu, Chang'an

2017-09-01

High-speed cameras provide full field measurement of structure motions and have been applied in nondestructive testing and noncontact structure monitoring. Recently, a phase-based method has been proposed to extract sound-induced vibrations from phase variations in videos, and this method provides insights into the study of remote sound surveillance and material analysis. An efficient singular value decomposition (SVD)-based approach is introduced to detect sound-induced subtle motions from pixel intensities in silent high-speed videos. A high-speed camera is initially applied to capture a video of the vibrating objects stimulated by sound fluctuations. Then, subimages collected from a small region on the captured video are reshaped into vectors and reconstructed to form a matrix. Orthonormal image bases (OIBs) are obtained from the SVD of the matrix; available vibration signal can then be obtained by projecting subsequent subimages onto specific OIBs. A simulation test is initiated to validate the effectiveness and efficiency of the proposed method. Two experiments are conducted to demonstrate the potential applications in sound recovery and material analysis. Results show that the proposed method efficiently detects subtle motions from the video.

Electronic system for floor surface type detection in robotics applications

NASA Astrophysics Data System (ADS)

Tarapata, Grzegorz; Paczesny, Daniel; Tarasiuk, Łukasz

2016-11-01

The paper reports a recognizing method base on ultrasonic transducers utilized for the surface types detection. Ultra-sonic signal is transmitted toward the examined substrate, then reflected and scattered signal goes back to another ultra-sonic receiver. Thee measuring signal is generated by a piezo-electric transducer located at specified distance from the tested substrate. The detector is a second piezo-electric transducer located next to the transmitter. Depending on thee type of substrate which is exposed by an ultrasonic wave, the signal is partially absorbed inn the material, diffused and reflected towards the receiver. To measure the level of received signal, the dedicated electronic circuit was design and implemented in the presented systems. Such system was designed too recognize two types of floor surface: solid (like concrete, ceramic stiles, wood) and soft (carpets, floor coverings). The method will be applied in electronic detection system dedicated to autonomous cleaning robots due to selection of appropriate cleaning method. This work presents the concept of ultrasonic signals utilization, the design of both the measurement system and the measuring stand and as well number of wide tests results which validates correctness of applied ultrasonic method.

Polyvinylidene fluoride sensor-based method for unconstrained snoring detection.

PubMed

Hwang, Su Hwan; Han, Chung Min; Yoon, Hee Nam; Jung, Da Woon; Lee, Yu Jin; Jeong, Do-Un; Park, Kwang Suk

2015-07-01

We established and tested a snoring detection method using a polyvinylidene fluoride (PVDF) sensor for accurate, fast, and motion-artifact-robust monitoring of snoring events during sleep. Twenty patients with obstructive sleep apnea participated in this study. The PVDF sensor was located between a mattress cover and mattress, and the patients' snoring signals were unconstrainedly measured with the sensor during polysomnography. The power ratio and peak frequency from the short-time Fourier transform were used to extract spectral features from the PVDF data. A support vector machine was applied to the spectral features to classify the data into either the snore or non-snore class. The performance of the method was assessed using manual labelling by three human observers as a reference. For event-by-event snoring detection, PVDF data that contained 'snoring' (SN), 'snoring with movement' (SM), and 'normal breathing' epochs were selected for each subject. As a result, the overall sensitivity and the positive predictive values were 94.6% and 97.5%, respectively, and there was no significant difference between the SN and SM results. The proposed method can be applied in both residential and ambulatory snoring monitoring systems.

Simultaneous determination of cyanogen chloride and cyanogen bromide in treated water at sub-microg/L levels by a new solid-phase microextraction-gas chromatographic-electron-capture detection method.

PubMed

Cancho, B; Ventur, F; Galceran, M

2000-11-03

A headspace solid-phase microextraction (HS-SPME) procedure has been developed and applied for the determination of cyanogen halides in treated water samples at microg/L concentrations. Several SPME coatings were tested, the divinylbenzene-Carboxen-polydimethylsiloxane fiber being the most appropriate coating. GC-electron-capture detection was used for separation and quantitation. Experimental parameters such as sample volume, addition of a salt, extraction time and desorption conditions were studied. The optimized method has an acceptable linearity, good precision, with RSD values <10% for both compounds, and it is sufficiently sensitive to detect ng/L levels. HS-SPME was compared with liquid-liquid microextraction (US Environmental Protection Agency Method 551.1) for the analysis of spiked ultrapure and granular activated carbon filtered water samples. There was good agreement between the results from both methods. Finally, the optimized procedure was applied to determine both compounds at the Barcelona water treatment plant (N.E. Spain). Cyanogen chloride in treated water was <1.0 microg/L and cyanogen bromide ranged from 3.2 to 6.4 microg/L.

Rapid method for controlling the correct labeling of products containing common octopus (Octopus vulgaris) and main substitute species (Eledone cirrhosa and Dosidicus gigas) by fast real-time PCR.

PubMed

Espiñeira, Montserrat; Vieites, Juan M

2012-12-15

The TaqMan real-time PCR has the highest potential for automation, therefore representing the currently most suitable method for screening, allowing the detection of fraudulent or unintentional mislabeling of species. This work describes the development of a real-time polymerase chain reaction (RT-PCR) system for the detection and identification of common octopus (Octopus vulgaris) and main substitute species (Eledone cirrhosa and Dosidicus gigas). This technique is notable for the combination of simplicity, speed, sensitivity and specificity in an homogeneous assay. The method can be applied to all kinds of products; fresh, frozen and processed, including those undergoing intensive processes of transformation. This methodology was validated to check how the degree of food processing affects the method and the detection of each species. Moreover, it was applied to 34 commercial samples to evaluate the labeling of products made from them. The methodology herein developed is useful to check the fulfillment of labeling regulations for seafood products and to verify traceability in commercial trade and for fisheries control. Copyright © 2012 Elsevier Ltd. All rights reserved.

Edge guided image reconstruction in linear scan CT by weighted alternating direction TV minimization.

PubMed

Cai, Ailong; Wang, Linyuan; Zhang, Hanming; Yan, Bin; Li, Lei; Xi, Xiaoqi; Li, Jianxin

2014-01-01

Linear scan computed tomography (CT) is a promising imaging configuration with high scanning efficiency while the data set is under-sampled and angularly limited for which high quality image reconstruction is challenging. In this work, an edge guided total variation minimization reconstruction (EGTVM) algorithm is developed in dealing with this problem. The proposed method is modeled on the combination of total variation (TV) regularization and iterative edge detection strategy. In the proposed method, the edge weights of intermediate reconstructions are incorporated into the TV objective function. The optimization is efficiently solved by applying alternating direction method of multipliers. A prudential and conservative edge detection strategy proposed in this paper can obtain the true edges while restricting the errors within an acceptable degree. Based on the comparison on both simulation studies and real CT data set reconstructions, EGTVM provides comparable or even better quality compared to the non-edge guided reconstruction and adaptive steepest descent-projection onto convex sets method. With the utilization of weighted alternating direction TV minimization and edge detection, EGTVM achieves fast and robust convergence and reconstructs high quality image when applied in linear scan CT with under-sampled data set.

Border preserving skin lesion segmentation

NASA Astrophysics Data System (ADS)

Kamali, Mostafa; Samei, Golnoosh

2008-03-01

Melanoma is a fatal cancer with a growing incident rate. However it could be cured if diagnosed in early stages. The first step in detecting melanoma is the separation of skin lesion from healthy skin. There are particular features associated with a malignant lesion whose successful detection relies upon accurately extracted borders. We propose a two step approach. First, we apply K-means clustering method (to 3D RGB space) that extracts relatively accurate borders. In the second step we perform an extra refining step for detecting the fading area around some lesions as accurately as possible. Our method has a number of novelties. Firstly as the clustering method is directly applied to the 3D color space, we do not overlook the dependencies between different color channels. In addition, it is capable of extracting fine lesion borders up to pixel level in spite of the difficulties associated with fading areas around the lesion. Performing clustering in different color spaces reveals that 3D RGB color space is preferred. The application of the proposed algorithm to an extensive data-base of skin lesions shows that its performance is superior to that of existing methods both in terms of accuracy and computational complexity.

Single photon detection and signal analysis for high sensitivity dosimetry based on optically stimulated luminescence with beryllium oxide

NASA Astrophysics Data System (ADS)

Radtke, J.; Sponner, J.; Jakobi, C.; Schneider, J.; Sommer, M.; Teichmann, T.; Ullrich, W.; Henniger, J.; Kormoll, T.

2018-01-01

Single photon detection applied to optically stimulated luminescence (OSL) dosimetry is a promising approach due to the low level of luminescence light and the known statistical behavior of single photon events. Time resolved detection allows to apply a variety of different and independent data analysis methods. Furthermore, using amplitude modulated stimulation impresses time- and frequency information into the OSL light and therefore allows for additional means of analysis. Considering the impressed frequency information, data analysis by using Fourier transform algorithms or other digital filters can be used for separating the OSL signal from unwanted light or events generated by other phenomena. This potentially lowers the detection limits of low dose measurements and might improve the reproducibility and stability of obtained data. In this work, an OSL system based on a single photon detector, a fast and accurate stimulation unit and an FPGA is presented. Different analysis algorithms which are applied to the single photon data are discussed.

Spatial-time-state fusion algorithm for defect detection through eddy current pulsed thermography

NASA Astrophysics Data System (ADS)

Xiao, Xiang; Gao, Bin; Woo, Wai Lok; Tian, Gui Yun; Xiao, Xiao Ting

2018-05-01

Eddy Current Pulsed Thermography (ECPT) has received extensive attention due to its high sensitive of detectability on surface and subsurface cracks. However, it remains as a difficult challenge in unsupervised detection as to identify defects without knowing any prior knowledge. This paper presents a spatial-time-state features fusion algorithm to obtain fully profile of the defects by directional scanning. The proposed method is intended to conduct features extraction by using independent component analysis (ICA) and automatic features selection embedding genetic algorithm. Finally, the optimal feature of each step is fused to obtain defects reconstruction by applying common orthogonal basis extraction (COBE) method. Experiments have been conducted to validate the study and verify the efficacy of the proposed method on blind defect detection.

Polarization switching detection method using a ferroelectric liquid crystal for dichroic atomic vapor laser lock frequency stabilization techniques.

PubMed

Dudzik, Grzegorz; Rzepka, Janusz; Abramski, Krzysztof M

2015-04-01

We present a concept of the polarization switching detection method implemented for frequency-stabilized lasers, called the polarization switching dichroic atomic vapor laser lock (PSDAVLL) technique. It is a combination of the well-known dichroic atomic vapor laser lock method for laser frequency stabilization with a synchronous detection system based on the surface-stabilized ferroelectric liquid crystal (SSFLC).The SSFLC is a polarization switch and quarter wave-plate component. This technique provides a 9.6 dB better dynamic range ratio (DNR) than the well-known two-photodiode detection configuration known as the balanced polarimeter. This paper describes the proposed method used practically in the VCSEL laser frequency stabilization system. The applied PSDAVLL method has allowed us to obtain a frequency stability of 2.7×10⁻⁹ and a reproducibility of 1.2×10⁻⁸, with a DNR of detected signals of around 81 dB. It has been shown that PSDAVLL might be successfully used as a method for spectra-stable laser sources.

Simultaneous determination of flavonoids, isochlorogenic acids and triterpenoids in Ilex hainanensis Using high performance liquid chromatography coupled with diode array and evaporative light scattering detection.

PubMed

Peng, Bo; Qiao, Chun-Feng; Zhao, Jing; Huang, Wei-Hua; Hu, De-Jun; Liu, Hua-Gang; Li, Shao-Ping

2013-03-04

A high performance liquid chromatography coupled with diode array and evaporative light scattering detection (HPLC-DAD-ELSD) method for simultaneous determination of eight major bioactive compounds including two flavonoids (rutin and eriodictyol-7-O-β-D-glucopyranoside), two isochlorogenic acids (isochlorogenic acid A and isochlorogenic acid C) and four triterpenoids (ilexhainanoside D, ilexsaponin A1, ilexgenin A and ursolic acid) in Ilex hainanensis has been developed for the first time. The 283 nm wavelength was chosen for determination of two flavonoids and two isochlorogenic acids. ELSD was applied to determine four triterpenoids. The analysis was performed on an Agilent Zorbax SB-C18 column (250 × 4.6 mm i.d., 5 µm) with gradient elution of 0.2% formic acid in water and acetonitrile. The method was validated for linearity, limit of detection, limit of quantification, precision, repeatability and accuracy. The proposed method has been successfully applied for simultaneous quantification of the analytes in four samples of Ilex hainanensis, which is helpful for quality control of this plant.

Peptide Peak Detection for Low Resolution MALDI-TOF Mass Spectrometry.

PubMed

Yao, Jingwen; Utsunomiya, Shin-Ichi; Kajihara, Shigeki; Tabata, Tsuyoshi; Aoshima, Ken; Oda, Yoshiya; Tanaka, Koichi

2014-01-01

A new peak detection method has been developed for rapid selection of peptide and its fragment ion peaks for protein identification using tandem mass spectrometry. The algorithm applies classification of peak intensities present in the defined mass range to determine the noise level. A threshold is then given to select ion peaks according to the determined noise level in each mass range. This algorithm was initially designed for the peak detection of low resolution peptide mass spectra, such as matrix-assisted laser desorption/ionization Time-of-Flight (MALDI-TOF) mass spectra. But it can also be applied to other type of mass spectra. This method has demonstrated obtaining a good rate of number of real ions to noises for even poorly fragmented peptide spectra. The effect of using peak lists generated from this method produces improved protein scores in database search results. The reliability of the protein identifications is increased by finding more peptide identifications. This software tool is freely available at the Mass++ home page (http://www.first-ms3d.jp/english/achievement/software/).

Peptide Peak Detection for Low Resolution MALDI-TOF Mass Spectrometry

PubMed Central

Yao, Jingwen; Utsunomiya, Shin-ichi; Kajihara, Shigeki; Tabata, Tsuyoshi; Aoshima, Ken; Oda, Yoshiya; Tanaka, Koichi

2014-01-01

A new peak detection method has been developed for rapid selection of peptide and its fragment ion peaks for protein identification using tandem mass spectrometry. The algorithm applies classification of peak intensities present in the defined mass range to determine the noise level. A threshold is then given to select ion peaks according to the determined noise level in each mass range. This algorithm was initially designed for the peak detection of low resolution peptide mass spectra, such as matrix-assisted laser desorption/ionization Time-of-Flight (MALDI-TOF) mass spectra. But it can also be applied to other type of mass spectra. This method has demonstrated obtaining a good rate of number of real ions to noises for even poorly fragmented peptide spectra. The effect of using peak lists generated from this method produces improved protein scores in database search results. The reliability of the protein identifications is increased by finding more peptide identifications. This software tool is freely available at the Mass++ home page (http://www.first-ms3d.jp/english/achievement/software/). PMID:26819872

Relevant Scatterers Characterization in SAR Images

NASA Astrophysics Data System (ADS)

Chaabouni, Houda; Datcu, Mihai

2006-11-01

Recognizing scenes in a single look meter resolution Synthetic Aperture Radar (SAR) images, requires the capability to identify relevant signal signatures in condition of variable image acquisition geometry, arbitrary objects poses and configurations. Among the methods to detect relevant scatterers in SAR images, we can mention the internal coherence. The SAR spectrum splitted in azimuth generates a series of images which preserve high coherence only for particular object scattering. The detection of relevant scatterers can be done by correlation study or Independent Component Analysis (ICA) methods. The present article deals with the state of the art for SAR internal correlation analysis and proposes further extensions using elements of inference based on information theory applied to complex valued signals. The set of azimuth looks images is analyzed using mutual information measures and an equivalent channel capacity is derived. The localization of the "target" requires analysis in a small image window, thus resulting in imprecise estimation of the second order statistics of the signal. For a better precision, a Hausdorff measure is introduced. The method is applied to detect and characterize relevant objects in urban areas.

Assessment of strobilurin fungicides' content in soya-based drinks by liquid micro-extraction and liquid chromatography with tandem mass spectrometry.

PubMed

Campillo, Natalia; Iniesta, María Jesús; Viñas, Pilar; Hernández-Córdoba, Manuel

2015-01-01

Seven strobilurin fungicides were pre-concentrated from soya-based drinks using dispersive liquid-liquid micro-extraction (DLLME) with a prior protein precipitation step in acid medium. The enriched phase was analysed by liquid chromatography (LC) with dual detection, using diode array detection (DAD) and electrospray-ion trap tandem mass spectrometry (ESI-IT-MS/MS). After selecting 1-undecanol and methanol as the extractant and disperser solvents, respectively, for DLLME, the Taguchi experimental method, an orthogonal array design, was applied to select the optimal solvent volumes and salt concentration in the aqueous phase. The matrix effect was evaluated and quantification was carried out using external aqueous calibration for DAD and matrix-matched calibration method for MS/MS. Detection limits in the 4-130 and 0.8-4.5 ng g(-1) ranges were obtained for DAD and MS/MS, respectively. The DLLME-LC-DAD-MS method was applied to the analysis of 10 different samples, none of which was found to contain residues of the studied fungicides.

Determination of adenine based on the fluorescence recovery of the L-Tryptophan-Cu(2+) complex.

PubMed

Duan, Ruilin; Li, Chunyan; Liu, Shaopu; Liu, Zhongfang; Li, Yuanfang; Yuan, Yusheng; Hu, Xiaoli

2016-01-05

A simple and sensitive method for determination of adenine was developed based on fluorescence quenching and recovery of L-Tryptophan (L-Trp). The fluorescence of L-Trp could efficiently quenched by copper ion compared with other common metal ions. Upon addition of adenine (Ade) in L-Trp-Cu(II) system, the fluorescence was reoccurred. Under the optimum conditions, the recovery fluorescence intensity was linearly correlated with the concentration of adenine in the range from 0.34 to 25.0μmolL(-1), with a correlation coefficient (R(2)) of 0.9994. The detection limit (3σ/k) was 0.046μmolL(-1), indicating that this method could applied to detect trace adenine. In this study, amino acids including L-Trp, D-Trp, L-Tyr, D-Tyr, L-Phe, D-Phe were investigated and only L-Trp could well chelated copper ion. Additionally, the mechanism of quench and recovery also were discussed and the method was successfully applied to detect the adenine in DNA with satisfactory results. Copyright © 2015 Elsevier B.V. All rights reserved.

A new HPLC method for the detection of iodine applied to natural samples of edible seaweeds and commercial seaweed food products.

PubMed

Nitschke, Udo; Stengel, Dagmar B

2015-04-01

Rich in micronutrients and considered to contain high iodine levels, seaweeds have multiple applications as food/supplements and nutraceuticals with potential health implications. Here, we describe the development and validation of a new analytical method to quantify iodine as iodide (I(-)) using an isocratic HPLC system with UV detection; algal iodine was converted to I(-) via dry alkaline incineration. The method was successfully applied to 19 macroalgal species from three taxonomic groups and five commercially available seaweed food products. Fesh kelps contained highest levels, reaching >1.0% per dry weight (DW), but concentrations differed amongst thallus parts. In addition to kelps, other brown (Fucales: ∼ 0.05% DW) and some red species (∼ 0.05% DW) can also serve as a rich source of iodine; lowest iodine concentrations were detected in green macroalgae (∼ 0.005% DW), implying that quantities recommended for seaweed consumption may require species-specific re-evaluation to reach adequate daily intake levels. Copyright © 2014 Elsevier Ltd. All rights reserved.

Validation of a LC-fluorescence method for determination of free captopril in human plasma, using a pre-column derivatization reaction with monobromobimane.

PubMed

Tache, Florentin; Farca, Alexandru; Medvedovici, Andrei; David, Victor

2002-05-15

Both derivatization of free captopril in human plasma samples using monobromobimane as fluorescent label and the corresponding HPLC-fluorescence detection (FLD) method were validated. Calibration curve for the fluorescent captopril derivative in plasma samples is linear in the ppb-ppm range with a detection limit of 4 ppb and an identification limit of 10 ppb (P%: 90; nu > or = 5). These methods were successfully applied on bioequivalence studies carried out on some marketed pharmaceutical formulations.

Charge gradient microscopy

DOEpatents

Roelofs, Andreas; Hong, Seungbum

2018-02-06

A method for rapid imaging of a material specimen includes positioning a tip to contact the material specimen, and applying a force to a surface of the material specimen via the tip. In addition, the method includes moving the tip across the surface of the material specimen while removing electrical charge therefrom, generating a signal produced by contact between the tip and the surface, and detecting, based on the data, the removed electrical charge induced through the tip during movement of the tip across the surface. The method further includes measuring the detected electrical charge.

Damage localization and quantification of composite stratified beam Structures using residual force method

NASA Astrophysics Data System (ADS)

Behtani, A.; Bouazzouni, A.; Khatir, S.; Tiachacht, S.; Zhou, Y.-L.; Abdel Wahab, M.

2017-05-01

In this paper, the problem of using measured modal parameters to detect and locate damage in beam composite stratified structures with four layers of graphite/epoxy [0°/902°/0°] is investigated. A technique based on the residual force method is applied to composite stratified structure with different boundary conditions, the results of damage detection for several damage cases demonstrate that using residual force method as damage index, the damage location can be identified correctly and the damage extents can be estimated as well.

A rapid and simple method of detection of Blepharisma japonicum using PCR and immobilisation on FTA paper

PubMed Central

Hide, Geoff; Hughes, Jacqueline M; McNuff, Robert

2003-01-01

Background The rapid expansion in the availability of genome and DNA sequence information has opened up new possibilities for the development of methods for detecting free-living protozoa in environmental samples. The protozoan Blepharisma japonicum was used to investigate a rapid and simple detection system based on polymerase chain reaction amplification (PCR) from organisms immobilised on FTA paper. Results Using primers designed from the α-tubulin genes of Blepharisma, specific and sensitive detection to the equivalent of a single Blepharisma cell could be achieved. Similar detection levels were found using water samples, containing Blepharisma, which were dried onto Whatman FTA paper. Conclusion This system has potential as a sensitive convenient detection system for Blepharisma and could be applied to other protozoan organisms. PMID:14516472

Integration of single-molecule detection with magnetic separation for multiplexed detection of DNA glycosylases.

PubMed

Li, Chen-Chen; Zhang, Yan; Tang, Bo; Zhang, Chun-Yang

2018-06-05

We combine single-molecule detection with magnetic separation for simultaneous measurement of human 8-oxoG DNA glycosylase 1 (hOGG1) and uracil DNA glycosylase (UDG) based on excision repair-initiated endonuclease IV (Endo IV)-assisted signal amplification. This method can sensitively detect multiple DNA glycosylases, and it can be further applied for the simultaneous measurement of enzyme kinetic parameters and screening of both hOGG1 and UDG inhibitors.

The correct estimate of the probability of false detection of the matched filter in weak-signal detection problems . II. Further results with application to a set of ALMA and ATCA data

NASA Astrophysics Data System (ADS)

Vio, R.; Vergès, C.; Andreani, P.

2017-08-01

The matched filter (MF) is one of the most popular and reliable techniques to the detect signals of known structure and amplitude smaller than the level of the contaminating noise. Under the assumption of stationary Gaussian noise, MF maximizes the probability of detection subject to a constant probability of false detection or false alarm (PFA). This property relies upon a priori knowledge of the position of the searched signals, which is usually not available. Recently, it has been shown that when applied in its standard form, MF may severely underestimate the PFA. As a consequence the statistical significance of features that belong to noise is overestimated and the resulting detections are actually spurious. For this reason, an alternative method of computing the PFA has been proposed that is based on the probability density function (PDF) of the peaks of an isotropic Gaussian random field. In this paper we further develop this method. In particular, we discuss the statistical meaning of the PFA and show that, although useful as a preliminary step in a detection procedure, it is not able to quantify the actual reliability of a specific detection. For this reason, a new quantity is introduced called the specific probability of false alarm (SPFA), which is able to carry out this computation. We show how this method works in targeted simulations and apply it to a few interferometric maps taken with the Atacama Large Millimeter/submillimeter Array (ALMA) and the Australia Telescope Compact Array (ATCA). We select a few potential new point sources and assign an accurate detection reliability to these sources.

Detection and mapping of trace explosives on surfaces under ambient conditions using multiphoton electron extraction spectroscopy (MEES).

PubMed

Tang, Shisong; Vinerot, Nataly; Fisher, Danny; Bulatov, Valery; Yavetz-Chen, Yehuda; Schechter, Israel

2016-08-01

Multiphoton electron extraction spectroscopy (MEES) is an analytical method in which UV laser pulses are utilized for extracting electrons from solid surfaces in multiphoton processes under ambient conditions. Counting the emitted electrons as a function of laser wavelength results in detailed spectral features, which can be used for material identification. The method has been applied to detection of trace explosives on a variety of surfaces. Detection was possible on dusty swabs spiked with explosives and also in the standard dry-transfer contamination procedure. Plastic explosives could also be detected. The analytical limits of detection (LODs) are in the sub pmole range, which indicates that MEES is one of the most sensitive detection methods for solid surface under ambient conditions. Scanning the surface with the laser allows for its imaging, such that explosives (as well as other materials) can be located. The imaging mode is also useful in forensic applications, such as detection of explosives in human fingerprints. Copyright © 2016 Elsevier B.V. All rights reserved.

SAR Image Change Detection Based on Fuzzy Markov Random Field Model

NASA Astrophysics Data System (ADS)

Zhao, J.; Huang, G.; Zhao, Z.

2018-04-01

Most existing SAR image change detection algorithms only consider single pixel information of different images, and not consider the spatial dependencies of image pixels. So the change detection results are susceptible to image noise, and the detection effect is not ideal. Markov Random Field (MRF) can make full use of the spatial dependence of image pixels and improve detection accuracy. When segmenting the difference image, different categories of regions have a high degree of similarity at the junction of them. It is difficult to clearly distinguish the labels of the pixels near the boundaries of the judgment area. In the traditional MRF method, each pixel is given a hard label during iteration. So MRF is a hard decision in the process, and it will cause loss of information. This paper applies the combination of fuzzy theory and MRF to the change detection of SAR images. The experimental results show that the proposed method has better detection effect than the traditional MRF method.

Contact angle determination procedure and detection of an invisible surface film

NASA Technical Reports Server (NTRS)

Meyer, G.; Grat, R.

1990-01-01

The contact angle value, i.e., the tangent angle of liquid resting on a planar solid surface, is a basic parameter which can be applied to a wide range of applications. The goal is to provide a basic understanding of the contact angle measurement technique and to present a simple illustration that can be applied as a quality control method; namely, detection of a surface contaminant which exists on a surface that appears clean to the unaided eye. The equipment and experimental procedures are detailed.

Unsupervised Structure Detection in Biomedical Data.

PubMed

Vogt, Julia E

2015-01-01

A major challenge in computational biology is to find simple representations of high-dimensional data that best reveal the underlying structure. In this work, we present an intuitive and easy-to-implement method based on ranked neighborhood comparisons that detects structure in unsupervised data. The method is based on ordering objects in terms of similarity and on the mutual overlap of nearest neighbors. This basic framework was originally introduced in the field of social network analysis to detect actor communities. We demonstrate that the same ideas can successfully be applied to biomedical data sets in order to reveal complex underlying structure. The algorithm is very efficient and works on distance data directly without requiring a vectorial embedding of data. Comprehensive experiments demonstrate the validity of this approach. Comparisons with state-of-the-art clustering methods show that the presented method outperforms hierarchical methods as well as density based clustering methods and model-based clustering. A further advantage of the method is that it simultaneously provides a visualization of the data. Especially in biomedical applications, the visualization of data can be used as a first pre-processing step when analyzing real world data sets to get an intuition of the underlying data structure. We apply this model to synthetic data as well as to various biomedical data sets which demonstrate the high quality and usefulness of the inferred structure.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

System and method for anomaly detection

DOEpatents

Scherrer, Chad

2010-06-15

A system and method for detecting one or more anomalies in a plurality of observations is provided. In one illustrative embodiment, the observations are real-time network observations collected from a stream of network traffic. The method includes performing a discrete decomposition of the observations, and introducing derived variables to increase storage and query efficiencies. A mathematical model, such as a conditional independence model, is then generated from the formatted data. The formatted data is also used to construct frequency tables which maintain an accurate count of specific variable occurrence as indicated by the model generation process. The formatted data is then applied to the mathematical model to generate scored data. The scored data is then analyzed to detect anomalies.

Survey of Anomaly Detection Methods

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

Ng, B

This survey defines the problem of anomaly detection and provides an overview of existing methods. The methods are categorized into two general classes: generative and discriminative. A generative approach involves building a model that represents the joint distribution of the input features and the output labels of system behavior (e.g., normal or anomalous) then applies the model to formulate a decision rule for detecting anomalies. On the other hand, a discriminative approach aims directly to find the decision rule, with the smallest error rate, that distinguishes between normal and anomalous behavior. For each approach, we will give an overview ofmore » popular techniques and provide references to state-of-the-art applications.« less

Detection and quantification of ginsenoside Re in ginseng samples by a chromatographic immunostaining method using monoclonal antibody against ginsenoside Re.

PubMed

Morinaga, Osamu; Tanaka, Hiroyuki; Shoyama, Yukihiro

2006-01-02

A chromatographic immunostaining method has been developed for the determination of ginsenoside Re (G-Re) in ginseng samples on a polyethersulphone (PES) membrane. G-Re standard and the extracts of ginseng roots were applied to a PES membrane and developed by methanol-water-acetic acid (45:55:1, by volume). G-Re was clearly detected by an immunostaining method using a monoclonal antibody against G-Re. The coloring spots of G-Re were analyzed quantitatively using NIH Image software indicating at least 0.125 microg of G-Re was detectable. G-Re can be analyzed quantitatively between 0.25 and 4.0 microg.

EVALUATION OF METHODS FOR SAMPLING, RECOVERY, AND ENUMERATION OF BACTERIA APPLIED TO THE PHYLLOPANE

EPA Science Inventory

Determining the fate and survival of genetically engineered microorganisms released into the environment requires the development and application of accurate and practical methods of detection and enumeration. everal experiments were performed to examine quantitative recovery met...

Detection of banned meat and bone meal in feedstuffs by near-infrared microscopic analysis of the dense sediment fraction.

PubMed

Baeten, Vincent; von Holst, Christoph; Garrido, Ana; Vancutsem, Jeroen; Michotte Renier, Antoine; Dardenne, Pierre

2005-05-01

In this paper we present an alternative method for detection of meat and bone meal (MBM) in feedstuffs by near-infrared microscopic (NIRM) analysis of the particles in the sediment fraction (dense fraction (d >1.62) from dichloroethylene) of compound feeds. To apply this method the particles of the sediment fraction are spread on a sample holder and presented to the NIR microscope. By using the pointer of the microscope the infrared beam is focussed on each particle and the NIR spectrum (1112-2500 nm) is collected. This method can be used to detect the presence of MBM at concentrations as low as 0.05% mass fraction. When results from the NIRM method were compared with the classical microscopic method, a coefficient of determination (R2) of 0.87 was obtained. The results of this study demonstrated that this method could be proposed as a complementary tool for the detection of banned MBM in feedstuffs by reinforcement of the monitoring of feeds.

A geometrical defect detection method for non-silicon MEMS part based on HU moment invariants of skeleton image

NASA Astrophysics Data System (ADS)

Cheng, Xu; Jin, Xin; Zhang, Zhijing; Lu, Jun

2014-01-01

In order to improve the accuracy of geometrical defect detection, this paper presented a method based on HU moment invariants of skeleton image. This method have four steps: first of all, grayscale images of non-silicon MEMS parts are collected and converted into binary images, secondly, skeletons of binary images are extracted using medialaxis- transform method, and then HU moment invariants of skeleton images are calculated, finally, differences of HU moment invariants between measured parts and qualified parts are obtained to determine whether there are geometrical defects. To demonstrate the availability of this method, experiments were carried out between skeleton images and grayscale images, and results show that: when defects of non-silicon MEMS part are the same, HU moment invariants of skeleton images are more sensitive than that of grayscale images, and detection accuracy is higher. Therefore, this method can more accurately determine whether non-silicon MEMS parts qualified or not, and can be applied to nonsilicon MEMS part detection system.

Method for the depth corrected detection of ionizing events from a co-planar grids sensor

DOEpatents

De Geronimo, Gianluigi [Syosset, NY; Bolotnikov, Aleksey E [South Setauket, NY; Carini, Gabriella [Port Jefferson, NY

2009-05-12

A method for the detection of ionizing events utilizing a co-planar grids sensor comprising a semiconductor substrate, cathode electrode, collecting grid and non-collecting grid. The semiconductor substrate is sensitive to ionizing radiation. A voltage less than 0 Volts is applied to the cathode electrode. A voltage greater than the voltage applied to the cathode is applied to the non-collecting grid. A voltage greater than the voltage applied to the non-collecting grid is applied to the collecting grid. The collecting grid and the non-collecting grid are summed and subtracted creating a sum and difference respectively. The difference and sum are divided creating a ratio. A gain coefficient factor for each depth (distance between the ionizing event and the collecting grid) is determined, whereby the difference between the collecting electrode and the non-collecting electrode multiplied by the corresponding gain coefficient is the depth corrected energy of an ionizing event. Therefore, the energy of each ionizing event is the difference between the collecting grid and the non-collecting grid multiplied by the corresponding gain coefficient. The depth of the ionizing event can also be determined from the ratio.

Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design

PubMed Central

2017-01-01

Background Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic “big data” from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. Objective The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. Methods An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. Results The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning of a winter influenza season has an exponential growth of infected individuals. For prediction modeling, linear regression was applied on 7-day periods at the time in order to find the peak timing, whereas a derivate of a normal distribution density function was used to find the peak intensity. We found that the integrated detection and prediction method detected the 2008-09 winter influenza season on its starting day (optimal timeliness 0 days), whereas the predicted peak was estimated to occur 7 days ahead of the factual peak and the predicted peak intensity was estimated to be 26% lower than the factual intensity (6.3 compared with 8.5 influenza-diagnosis cases/100,000). Conclusions Our detection and prediction method is one of the first integrated methods specifically designed for local application on influenza data electronically available for surveillance. The performance of the method in a retrospective study indicates that further prospective evaluations of the methods are justified. PMID:28619700

Optic disc detection and boundary extraction in retinal images.

PubMed

Basit, A; Fraz, Muhammad Moazam

2015-04-10

With the development of digital image processing, analysis and modeling techniques, automatic retinal image analysis is emerging as an important screening tool for early detection of ophthalmologic disorders such as diabetic retinopathy and glaucoma. In this paper, a robust method for optic disc detection and extraction of the optic disc boundary is proposed to help in the development of computer-assisted diagnosis and treatment of such ophthalmic disease. The proposed method is based on morphological operations, smoothing filters, and the marker controlled watershed transform. Internal and external markers are used to first modify the gradient magnitude image and then the watershed transformation is applied on this modified gradient magnitude image for boundary extraction. This method has shown significant improvement over existing methods in terms of detection and boundary extraction of the optic disc. The proposed method has optic disc detection success rate of 100%, 100%, 100% and 98.9% for the DRIVE, Shifa, CHASE_DB1, and DIARETDB1 databases, respectively. The optic disc boundary detection achieved an average spatial overlap of 61.88%, 70.96%, 45.61%, and 54.69% for these databases, respectively, which are higher than currents methods.

Algorithms for Autonomous Plume Detection on Outer Planet Satellites

NASA Astrophysics Data System (ADS)

Lin, Y.; Bunte, M. K.; Saripalli, S.; Greeley, R.

2011-12-01

We investigate techniques for automated detection of geophysical events (i.e., volcanic plumes) from spacecraft images. The algorithms presented here have not been previously applied to detection of transient events on outer planet satellites. We apply Scale Invariant Feature Transform (SIFT) to raw images of Io and Enceladus from the Voyager, Galileo, Cassini, and New Horizons missions. SIFT produces distinct interest points in every image; feature descriptors are reasonably invariant to changes in illumination, image noise, rotation, scaling, and small changes in viewpoint. We classified these descriptors as plumes using the k-nearest neighbor (KNN) algorithm. In KNN, an object is classified by its similarity to examples in a training set of images based on user defined thresholds. Using the complete database of Io images and a selection of Enceladus images where 1-3 plumes were manually detected in each image, we successfully detected 74% of plumes in Galileo and New Horizons images, 95% in Voyager images, and 93% in Cassini images. Preliminary tests yielded some false positive detections; further iterations will improve performance. In images where detections fail, plumes are less than 9 pixels in size or are lost in image glare. We compared the appearance of plumes and illuminated mountain slopes to determine the potential for feature classification. We successfully differentiated features. An advantage over other methods is the ability to detect plumes in non-limb views where they appear in the shadowed part of the surface; improvements will enable detection against the illuminated background surface where gradient changes would otherwise preclude detection. This detection method has potential applications to future outer planet missions for sustained plume monitoring campaigns and onboard automated prioritization of all spacecraft data. The complementary nature of this method is such that it could be used in conjunction with edge detection algorithms to increase effectiveness. We have demonstrated an ability to detect transient events above the planetary limb and on the surface and to distinguish feature classes in spacecraft images.

Dew inspired breathing-based detection of genetic point mutation visualized by naked eye

PubMed Central

Xie, Liping; Wang, Tongzhou; Huang, Tianqi; Hou, Wei; Huang, Guoliang; Du, Yanan

2014-01-01

A novel label-free method based on breathing-induced vapor condensation was developed for detection of genetic point mutation. The dew-inspired detection was realized by integration of target-induced DNA ligation with rolling circle amplification (RCA). The vapor condensation induced by breathing transduced the RCA-amplified variances in DNA contents into visible contrast. The image could be recorded by a cell phone for further or even remote analysis. This green assay offers a naked-eye-reading method potentially applied for point-of-care liver cancer diagnosis in resource-limited regions. PMID:25199907

Rapid detection of methanol in artisanal alcoholic beverages

NASA Astrophysics Data System (ADS)

de Goes, R. E.; Muller, M.; Fabris, J. L.

2015-09-01

In the industry of artisanal beverages, uncontrolled production processes may result in contaminated products with methanol, leading to risks for consumers. Owing to the similar odor of methanol and ethanol, as well as their common transparency, the distinction between them is a difficult task. Contamination may also occur deliberately due to the lower price of methanol when compared to ethanol. This paper describes a spectroscopic method for methanol detection in beverages based on Raman scattering and Principal Component Analysis. Associated with a refractometric assessment of the alcohol content, the method may be applied in field for a rapid detection of methanol presence.

A method for the detection of protein-bound mutagens in food.

PubMed

Ibe, F I; Blowers, S D; Anderson, D; Massey, R

1994-01-01

To investigate the possible presence of protein-bound mutagens in food an analytical procedure has been devised in which the sample is enzymically hydrolysed, fractionated by HPLC and examined by a modified liquid incubation Ames assay. To validate the method MeIQx was added, as a model compound, to beefburger and a recovery of 82% obtained. The limit of detection for protein-bound mutagens was 1 microgram/kg, expressed as equivalents of MeIQx. No detectable mutagenicity was observed when the procedure was applied to samples of well cooked beefburger, irradiated chicken or mycoprotein.

Dew inspired breathing-based detection of genetic point mutation visualized by naked eye

NASA Astrophysics Data System (ADS)

Xie, Liping; Wang, Tongzhou; Huang, Tianqi; Hou, Wei; Huang, Guoliang; Du, Yanan

2014-09-01

A novel label-free method based on breathing-induced vapor condensation was developed for detection of genetic point mutation. The dew-inspired detection was realized by integration of target-induced DNA ligation with rolling circle amplification (RCA). The vapor condensation induced by breathing transduced the RCA-amplified variances in DNA contents into visible contrast. The image could be recorded by a cell phone for further or even remote analysis. This green assay offers a naked-eye-reading method potentially applied for point-of-care liver cancer diagnosis in resource-limited regions.

Dew inspired breathing-based detection of genetic point mutation visualized by naked eye.

PubMed

Xie, Liping; Wang, Tongzhou; Huang, Tianqi; Hou, Wei; Huang, Guoliang; Du, Yanan

2014-09-09

A novel label-free method based on breathing-induced vapor condensation was developed for detection of genetic point mutation. The dew-inspired detection was realized by integration of target-induced DNA ligation with rolling circle amplification (RCA). The vapor condensation induced by breathing transduced the RCA-amplified variances in DNA contents into visible contrast. The image could be recorded by a cell phone for further or even remote analysis. This green assay offers a naked-eye-reading method potentially applied for point-of-care liver cancer diagnosis in resource-limited regions.

Signal analysis techniques for incipient failure detection in turbomachinery

NASA Technical Reports Server (NTRS)

Coffin, T.

1985-01-01

Signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery were developed, implemented and evaluated. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques were implemented on a computer and applied to dynamic signals. A laboratory evaluation of the methods with respect to signal detection capability is described. Plans for further technique evaluation and data base development to characterize turbopump incipient failure modes from Space Shuttle main engine (SSME) hot firing measurements are outlined.

Analysis of wine volatile profile by purge-and-trap-gas chromatography-mass spectrometry. Application to the analysis of red and white wines from different Spanish regions.

PubMed

Aznar, Margarita; Arroyo, Teresa

2007-09-21

The purge-and-trap extraction method, coupled to a gas chromatograph with mass spectrometry detection, has been applied to the determination of 26 aromatic volatiles in wine. The method was optimized, validated and applied to the analyses of 40 red and white wines from 7 different Spanish regions. Principal components analyses of data showed the correlation between wines of similar origin.

Magnetic imager and method

DOEpatents

Powell, J.; Reich, M.; Danby, G.

1997-07-22

A magnetic imager includes a generator for practicing a method of applying a background magnetic field over a concealed object, with the object being effective to locally perturb the background field. The imager also includes a sensor for measuring perturbations of the background field to detect the object. In one embodiment, the background field is applied quasi-statically. And, the magnitude or rate of change of the perturbations may be measured for determining location, size, and/or condition of the object. 25 figs.

Attomolar quantitation of Mycobacterium tuberculosis by asymmetric helicase-dependent isothermal DNA-amplification and electrochemical detection.

PubMed

Barreda-García, Susana; González-Álvarez, María José; de-Los-Santos-Álvarez, Noemí; Palacios-Gutiérrez, Juan José; Miranda-Ordieres, Arturo J; Lobo-Castañón, María Jesús

2015-06-15

A highly sensitive and robust method for the quantification of specific DNA sequences based on coupling asymmetric helicase-dependent DNA amplification to electrochemical detection is described. This method relies on the entrapment of the amplified ssDNA sequences on magnetic beads followed by a post-amplification hybridization assay to provide an added degree of specificity. As a proof-of-concept a 84-bases long sequence specific of Mycobacterium tuberculosis is amplified at 65°C, providing 3×10(6) amplification after 90 min. Using this system 0.5 aM, corresponding to 15 copies of the target gene in 50 µL of sample, can be successfully detected and reliably quantified under isothermal conditions in less than 4h. The assay has been applied to the detection of M. tuberculosis in sputum, pleural fluid and urine samples. Besides this application, the proposed assays is a powerful and general tool for molecular diagnostic that can be applied to the detection of other specific DNA sequences, taking full advantage of the plethora of genomic information now available. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Colitis detection on abdominal CT scans by rich feature hierarchies

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Lay, Nathan; Wei, Zhuoshi; Lu, Le; Kim, Lauren; Turkbey, Evrim; Summers, Ronald M.

2016-03-01

Colitis is inflammation of the colon due to neutropenia, inflammatory bowel disease (such as Crohn disease), infection and immune compromise. Colitis is often associated with thickening of the colon wall. The wall of a colon afflicted with colitis is much thicker than normal. For example, the mean wall thickness in Crohn disease is 11-13 mm compared to the wall of the normal colon that should measure less than 3 mm. Colitis can be debilitating or life threatening, and early detection is essential to initiate proper treatment. In this work, we apply high-capacity convolutional neural networks (CNNs) to bottom-up region proposals to detect potential colitis on CT scans. Our method first generates around 3000 category-independent region proposals for each slice of the input CT scan using selective search. Then, a fixed-length feature vector is extracted from each region proposal using a CNN. Finally, each region proposal is classified and assigned a confidence score with linear SVMs. We applied the detection method to 260 images from 26 CT scans of patients with colitis for evaluation. The detection system can achieve 0.85 sensitivity at 1 false positive per image.

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

Real-time Series Resistance Monitoring in PV Systems; NREL (National Renewable Energy Laboratory)

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

Deceglie, M. G.; Silverman, T. J.; Marion, B.

We apply the physical principles of a familiar method, suns-Voc, to a new application: the real-time detection of series resistance changes in modules and systems operating outside. The real-time series resistance (RTSR) method that we describe avoids the need for collecting IV curves or constructing full series-resistance-free IV curves. RTSR is most readily deployable at the module level on apply the physical principles of a familiar method, suns-Voc, to a new application: the real-time detection of series resistance changes in modules and systems operating outside. The real-time series resistance (RTSR) method that we describe avoids the need for collecting IVmore » curves or constructing full series-resistance-free IV curves. RTSR is most readily deployable at the module level on micro-inverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.« less

Structural-change localization and monitoring through a perturbation-based inverse problem.

PubMed

Roux, Philippe; Guéguen, Philippe; Baillet, Laurent; Hamze, Alaa

2014-11-01

Structural-change detection and characterization, or structural-health monitoring, is generally based on modal analysis, for detection, localization, and quantification of changes in structure. Classical methods combine both variations in frequencies and mode shapes, which require accurate and spatially distributed measurements. In this study, the detection and localization of a local perturbation are assessed by analysis of frequency changes (in the fundamental mode and overtones) that are combined with a perturbation-based linear inverse method and a deconvolution process. This perturbation method is applied first to a bending beam with the change considered as a local perturbation of the Young's modulus, using a one-dimensional finite-element model for modal analysis. Localization is successful, even for extended and multiple changes. In a second step, the method is numerically tested under ambient-noise vibration from the beam support with local changes that are shifted step by step along the beam. The frequency values are revealed using the random decrement technique that is applied to the time-evolving vibrations recorded by one sensor at the free extremity of the beam. Finally, the inversion method is experimentally demonstrated at the laboratory scale with data recorded at the free end of a Plexiglas beam attached to a metallic support.

Detection of Biomarkers of Pathogenic Naegleria fowleri Through Mass Spectrometry and Proteomics

PubMed Central

Moura, Hercules; Izquierdo, Fernando; Woolfitt, Adrian R.; Wagner, Glauber; Pinto, Tatiana; del Aguila, Carmen; Barr, John R.

2017-01-01

Emerging methods based on mass spectrometry (MS) can be used in the rapid identification of microorganisms. Thus far, these practical and rapidly evolving methods have mainly been applied to characterize prokaryotes. We applied matrix-assisted laser-desorption-ionization-time-of-flight mass spectrometry MALDI-TOF MS in the analysis of whole cells of 18 N. fowleri isolates belonging to three genotypes. Fourteen originated from the cerebrospinal fluid or brain tissue of primary amoebic meningoencephalitis patients and four originated from water samples of hot springs, rivers, lakes or municipal water supplies. Whole Naegleria trophozoites grown in axenic cultures were washed and mixed with MALDI matrix. Mass spectra were acquired with a 4700 TOF-TOF instrument. MALDI-TOF MS yielded consistent patterns for all isolates examined. Using a combination of novel data processing methods for visual peak comparison, statistical analysis and proteomics database searching we were able to detect several biomarkers that can differentiate all species and isolates studied, along with common biomarkers for all N. fowleri isolates. Naegleria fowleri could be easily separated from other species within the genus Naegleria. A number of peaks detected were tentatively identified. MALDI-TOF MS fingerprinting is a rapid, reproducible, high-throughput alternative method for identifying Naegleria isolates. This method has potential for studying eukaryotic agents. PMID:25231600

Determination of β-blockers in pharmaceutical and human urine by capillary electrophoresis with electrochemiluminescence detection and studies on the pharmacokinetics.

PubMed

Wang, Yuanchao; Wu, Qiong; Cheng, Meirong; Cai, Cheng

2011-04-15

A novel method for simultaneous determination of atenolol, metoprolol and esmolol was proposed by capillary electrophoresis (CE) separation and electrochemiluminescence (ECL) detection. Poly-β-cyclodextrin (Poly-β-CD) was used as an additive in the running buffer to improve the separation of three analytes. The conditions for CE separation, ECL detection and effect of Poly-β-CD were investigated in detail. The three β-blockers with very similar structures were well separated and detected under the optimum conditions. The linear ranges of the standard solution for atenolol and esmolol were 2.5-125 μmol/L with a detection limit (S/N=3) of 0.5 μmol/L, and for metoprolol was 0.5-25 μmol/L with a detection limit of 0.1 μmol/L. For three β-blockers from spiked aqueous and urine samples, the accuracy and precision including intraday and interday experiments were performed by calculating the recovery, the relative standard deviations of the ECL intensity and the migration time, respectively. The developed method was applied to the determination of metoprolol content in commercial pharmaceutical, and the analytical results are in good agreement with the nominal value with recoveries in the range of 98.7-105%. The proposed method was also applied to the monitoring of pharmacokinetics for metoprolol in human body. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

Analytical and Experimental Vibration Analysis of a Faulty Gear System.

DTIC Science & Technology

1994-10-01

Wigner - Ville Distribution ( WVD ) was used to give a comprehensive comparison of the predicted and...experimental results. The WVD method applied to the experimental results were also compared to other fault detection techniques to verify the WVD’s ability to...of the damaged test gear and the predicted vibration from the model with simulated gear tooth pitting damage. Results also verified that the WVD method can successfully detect and locate gear tooth wear and pitting damage.

Computational Electromagnetic Modeling of SansEC(Trade Mark) Sensors

NASA Technical Reports Server (NTRS)

Smith, Laura J.; Dudley, Kenneth L.; Szatkowski, George N.

2011-01-01

This paper describes the preliminary effort to apply computational design tools to aid in the development of an electromagnetic SansEC resonant sensor composite materials damage detection system. The computational methods and models employed on this research problem will evolve in complexity over time and will lead to the development of new computational methods and experimental sensor systems that demonstrate the capability to detect, diagnose, and monitor the damage of composite materials and structures on aerospace vehicles.

Improvement of statistical methods for detecting anomalies in climate and environmental monitoring systems

NASA Astrophysics Data System (ADS)

Yakunin, A. G.; Hussein, H. M.

2018-01-01

The article shows how the known statistical methods, which are widely used in solving financial problems and a number of other fields of science and technology, can be effectively applied after minor modification for solving such problems in climate and environment monitoring systems, as the detection of anomalies in the form of abrupt changes in signal levels, the occurrence of positive and negative outliers and the violation of the cycle form in periodic processes.

Remote optical configuration of pigmented lesion detection and diagnosis of bone fractures

NASA Astrophysics Data System (ADS)

Ozana, Nisan; Bishitz, Yael; Beiderman, Yevgeny; Garcia, Javier; Zalevsky, Zeev; Schwarz, Ariel

2016-02-01

In this paper we present a novel approach of realizing a safe, simple, and inexpensive sensor applicable to bone fractures and pigmented lesions detection. The approach is based on temporal tracking of back-reflected secondary speckle pattern generated while illuminating the affected area with a laser and applying periodic pressure to the surface via a controlled vibration. The use of such a concept was already demonstrated for non-contact monitoring of various bio-medical parameters such as heart rate, blood pulse pressure, concentration of alcohol and glucose in the blood stream and intraocular pressure. The presented technique is a safe and effective method of detecting bone fractures in populations at risk. When applied to pigmented lesions, the technique is superior to visual examination in avoiding many false positives and resultant unnecessary biopsies. Applying a series of different vibration frequencies at the examined tissue and analyzing the 2-D speckle pattern trajectory in response to the applied periodic pressure creates a unique signature for each and different pigmented lesion. Analyzing these signatures is the first step toward detection of malignant melanoma. In this paper we present preliminary experiments that show the validity of the developed sensor for both applications: the detection of damaged bones as well as the classification of pigmented lesions.

Weighted community detection and data clustering using message passing

NASA Astrophysics Data System (ADS)

Shi, Cheng; Liu, Yanchen; Zhang, Pan

2018-03-01

Grouping objects into clusters based on the similarities or weights between them is one of the most important problems in science and engineering. In this work, by extending message-passing algorithms and spectral algorithms proposed for an unweighted community detection problem, we develop a non-parametric method based on statistical physics, by mapping the problem to the Potts model at the critical temperature of spin-glass transition and applying belief propagation to solve the marginals corresponding to the Boltzmann distribution. Our algorithm is robust to over-fitting and gives a principled way to determine whether there are significant clusters in the data and how many clusters there are. We apply our method to different clustering tasks. In the community detection problem in weighted and directed networks, we show that our algorithm significantly outperforms existing algorithms. In the clustering problem, where the data were generated by mixture models in the sparse regime, we show that our method works all the way down to the theoretical limit of detectability and gives accuracy very close to that of the optimal Bayesian inference. In the semi-supervised clustering problem, our method only needs several labels to work perfectly in classic datasets. Finally, we further develop Thouless-Anderson-Palmer equations which heavily reduce the computation complexity in dense networks but give almost the same performance as belief propagation.

Rapid enantiomeric separation and simultaneous determination of phenethylamines by ultra high performance liquid chromatography with fluorescence and mass spectrometric detection: application to the analysis of illicit drugs distributed in the Japanese market and biological samples.

PubMed

Inagaki, Shinsuke; Hirashima, Haruo; Taniguchi, Sayuri; Higashi, Tatsuya; Min, Jun Zhe; Kikura-Hanajiri, Ruri; Goda, Yukihiro; Toyo'oka, Toshimasa

2012-12-01

A rapid enantiomeric separation and simultaneous determination method based on ultra high performance liquid chromatography (UHPLC) was developed for phenethylamine-type abused drugs using (R)-(-)-4-(N,N-dimethylaminosulfonyl)-7-(3-isothiocyanatopyrrolidin-1-yl)-2,1,3-benzoxadiazole ((R)-(-)-DBD-Py-NCS) as the chiral fluorescent derivatization reagent. The derivatives were rapidly enantiomerically separated by reversed-phase UHPLC using a column of 2.3-µm octadecylsilica (ODS) particles by isocratic elution with water-methanol or water-acetonitrile systems as the mobile phase. The proposed method was applied to the analysis of products containing illicit drugs distributed in the Japanese market. Among the products, 1-(3,4-methylenedioxyphenyl)butan-2-amine (BDB) and 1-(2-methoxy4,5-methylenedioxyphenyl)propan-2-amine (MMDA-2) were detected in racemic form. Furthermore, the method was successfully applied to the analysis of hair specimens from rats that were continuously dosed with diphenyl(pyrrolidin-2-yl)methanol (D2PM). Using UHPLC-fluorescence (FL) detection, (R)- and (S)-D2PM from hair specimens were enantiomerically separated and detected with high sensitivity. The detection limits of (R)- and (S)-D2PM were 0.12 and 0.21 ng/mg hair, respectively (signal-to-noise ratio (S/N) = 3). Copyright © 2012 John Wiley & Sons, Ltd.

Computer-aided detection of initial polyp candidates with level set-based adaptive convolution

NASA Astrophysics Data System (ADS)

Zhu, Hongbin; Duan, Chaijie; Liang, Zhengrong

2009-02-01

In order to eliminate or weaken the interference between different topological structures on the colon wall, adaptive and normalized convolution methods were used to compute the first and second order spatial derivatives of computed tomographic colonography images, which is the beginning of various geometric analyses. However, the performance of such methods greatly depends on the single-layer representation of the colon wall, which is called the starting layer (SL) in the following text. In this paper, we introduce a level set-based adaptive convolution (LSAC) method to compute the spatial derivatives, in which the level set method is employed to determine a more reasonable SL. The LSAC was applied to a computer-aided detection (CAD) scheme to detect the initial polyp candidates, and experiments showed that it benefits the CAD scheme in both the detection sensitivity and specificity as compared to our previous work.

Boosting instance prototypes to detect local dermoscopic features.

PubMed

Situ, Ning; Yuan, Xiaojing; Zouridakis, George

2010-01-01

Local dermoscopic features are useful in many dermoscopic criteria for skin cancer detection. We address the problem of detecting local dermoscopic features from epiluminescence (ELM) microscopy skin lesion images. We formulate the recognition of local dermoscopic features as a multi-instance learning (MIL) problem. We employ the method of diverse density (DD) and evidence confidence (EC) function to convert MIL to a single-instance learning (SIL) problem. We apply Adaboost to improve the classification performance with support vector machines (SVMs) as the base classifier. We also propose to boost the selection of instance prototypes through changing the data weights in the DD function. We validate the methods on detecting ten local dermoscopic features from a dataset with 360 images. We compare the performance of the MIL approach, its boosting version, and a baseline method without using MIL. Our results show that boosting can provide performance improvement compared to the other two methods.

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.

Performance evaluation for epileptic electroencephalogram (EEG) detection by using Neyman-Pearson criteria and a support vector machine

NASA Astrophysics Data System (ADS)

Wang, Chun-mei; Zhang, Chong-ming; Zou, Jun-zhong; Zhang, Jian

2012-02-01

The diagnosis of several neurological disorders is based on the detection of typical pathological patterns in electroencephalograms (EEGs). This is a time-consuming task requiring significant training and experience. A lot of effort has been devoted to developing automatic detection techniques which might help not only in accelerating this process but also in avoiding the disagreement among readers of the same record. In this work, Neyman-Pearson criteria and a support vector machine (SVM) are applied for detecting an epileptic EEG. Decision making is performed in two stages: feature extraction by computing the wavelet coefficients and the approximate entropy (ApEn) and detection by using Neyman-Pearson criteria and an SVM. Then the detection performance of the proposed method is evaluated. Simulation results demonstrate that the wavelet coefficients and the ApEn are features that represent the EEG signals well. By comparison with Neyman-Pearson criteria, an SVM applied on these features achieved higher detection accuracies.

Detection of pit fragments in fresh cherries using near infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

NIR spectroscopy in the wavelength region from 900nm to 2600nm was evaluated as the basis for a rapid, non-destructive method for the detection of pits and pit fragments in fresh cherries. Partial Least Squares discriminant analysis (PLS-DA) following various spectral pretreatments was applied to sp...

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

PubMed

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

2005-02-01

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

Sequence of eruptive events in the Vesuvio area recorded in shallow-water Ionian Sea sediments

NASA Astrophysics Data System (ADS)

Taricco, C.; Alessio, S.; Vivaldo, G.

2008-01-01

The dating of the cores we drilled from the Gallipoli terrace in the Gulf of Taranto (Ionian Sea), previously obtained by tephroanalysis, is checked by applying a method to objectively recognize volcanic events. This automatic statistical procedure allows identifying pulse-like features in a series and evaluating quantitatively the confidence level at which the significant peaks are detected. We applied it to the 2000-years-long pyroxenes series of the GT89-3 core, on which the dating is based. The method confirms the dating previously performed by detecting at a high confidence level the peaks originally used and indicates a few possible undocumented eruptions. Moreover, a spectral analysis, focussed on the long-term variability of the pyroxenes series and performed by several advanced methods, reveals that the volcanic pulses are superimposed to a millennial trend and a 400 years oscillation.

Automatic detection of magnetic flux emergings in the solar atmosphere from full-disk magnetogram sequences.

PubMed

Fu, Gang; Shih, Frank Y; Wang, Haimin

2008-11-01

In this paper, we present a novel method to detect Emerging Flux Regions (EFRs) in the solar atmosphere from consecutive full-disk Michelson Doppler Imager (MDI) magnetogram sequences. To our knowledge, this is the first developed technique for automatically detecting EFRs. The method includes several steps. First, the projection distortion on the MDI magnetograms is corrected. Second, the bipolar regions are extracted by applying multiscale circular harmonic filters. Third, the extracted bipolar regions are traced in consecutive MDI frames by Kalman filter as candidate EFRs. Fourth, the properties, such as positive and negative magnetic fluxes and distance between two polarities, are measured in each frame. Finally, a feature vector is constructed for each bipolar region using the measured properties, and the Support Vector Machine (SVM) classifier is applied to distinguish EFRs from other regions. Experimental results show that the detection rate of EFRs is 96.4% and of non-EFRs is 98.0%, and the false alarm rate is 25.7%, based on all the available MDI magnetograms in 2001 and 2002.

Pressurized capillary electrochromatographic analysis of water-soluble vitamins by combining with on-line concentration technique.

PubMed

Jia, Li; Liu, Yaling; Du, Yanyan; Xing, Da

2007-06-22

A pressurized capillary electrochromatography (pCEC) system was developed for the separation of water-soluble vitamins, in which UV absorbance was used as the detection method and a monolithic silica-ODS column as the separation column. The parameters (type and content of organic solvent in the mobile phase, type and concentration of electrolyte, pH of the electrolyte buffer, applied voltage and flow rate) affecting the separation resolution were evaluated. The combination of two on-line concentration techniques, namely, solvent gradient zone sharpening effect and field-enhanced sample stacking, was utilized to improve detection sensitivity, which proved to be beneficial to enhance the detection sensitivity by enabling the injection of large volumes of samples. Coupling electrokinetic injection with the on-line concentration techniques was much more beneficial for the concentration of positively charged vitamins. Comparing with the conventional injection mode, the enhancement in the detection sensitivities of water-soluble vitamins using the on-line concentration technique is in the range of 3 to 35-fold. The developed pCEC method was applied to evaluate water-soluble vitamins in corns.

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

PubMed

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

2018-02-01

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

Linear segmentation algorithm for detecting layer boundary with lidar.

PubMed

Mao, Feiyue; Gong, Wei; Logan, Timothy

2013-11-04

The automatic detection of aerosol- and cloud-layer boundary (base and top) is important in atmospheric lidar data processing, because the boundary information is not only useful for environment and climate studies, but can also be used as input for further data processing. Previous methods have demonstrated limitations in defining the base and top, window-size setting, and have neglected the in-layer attenuation. To overcome these limitations, we present a new layer detection scheme for up-looking lidars based on linear segmentation with a reasonable threshold setting, boundary selecting, and false positive removing strategies. Preliminary results from both real and simulated data show that this algorithm cannot only detect the layer-base as accurate as the simple multi-scale method, but can also detect the layer-top more accurately than that of the simple multi-scale method. Our algorithm can be directly applied to uncalibrated data without requiring any additional measurements or window size selections.

Highly sensitive chemiluminescent point mutation detection by circular strand-displacement amplification reaction.

PubMed

Shi, Chao; Ge, Yujie; Gu, Hongxi; Ma, Cuiping

2011-08-15

Single nucleotide polymorphism (SNP) genotyping is attracting extensive attentions owing to its direct connections with human diseases including cancers. Here, we have developed a highly sensitive chemiluminescence biosensor based on circular strand-displacement amplification and the separation by magnetic beads reducing the background signal for point mutation detection at room temperature. This method took advantage of both the T4 DNA ligase recognizing single-base mismatch with high selectivity and the strand-displacement reaction of polymerase to perform signal amplification. The detection limit of this method was 1.3 × 10(-16)M, which showed better sensitivity than that of most of those reported detection methods of SNP. Additionally, the magnetic beads as carrier of immobility was not only to reduce the background signal, but also may have potential apply in high through-put screening of SNP detection in human genome. Copyright © 2011 Elsevier B.V. All rights reserved.

Instant, Visual, and Instrument-Free Method for On-Site Screening of GTS 40-3-2 Soybean Based on Body-Heat Triggered Recombinase Polymerase Amplification.

PubMed

Wang, Rui; Zhang, Fang; Wang, Liu; Qian, Wenjuan; Qian, Cheng; Wu, Jian; Ying, Yibin

2017-04-18

On-site monitoring the plantation of genetically modified (GM) crops is of critical importance in agriculture industry throughout the world. In this paper, a simple, visual and instrument-free method for instant on-site detection of GTS 40-3-2 soybean has been developed. It is based on body-heat recombinase polymerase amplification (RPA) and followed with naked-eye detection via fluorescent DNA dye. Combining with extremely simplified sample preparation, the whole detection process can be accomplished within 10 min and the fluorescent results can be photographed by an accompanied smart phone. Results demonstrated a 100% detection rate for screening of practical GTS 40-3-2 soybean samples by 20 volunteers under different ambient temperatures. This method is not only suitable for on-site detection of GM crops but also demonstrates great potential to be applied in other fields.

DNAzyme based gap-LCR detection of single-nucleotide polymorphism.

PubMed

Zhou, Li; Du, Feng; Zhao, Yongyun; Yameen, Afshan; Chen, Haodong; Tang, Zhuo

2013-07-15

Fast and accurate detection of single-nucleotide polymorphism (SNP) is thought more and more important for understanding of human physiology and elucidating the molecular based diseases. A great deal of effort has been devoted to developing accurate, rapid, and cost-effective technologies for SNP analysis. However most of those methods developed to date incorporate complicated probe labeling and depend on advanced equipment. The DNAzyme based Gap-LCR detection method averts any chemical modification on probes and circumvents those problems by incorporating a short functional DNA sequence into one of LCR primers. Two kinds of exonuclease are utilized in our strategy to digest all the unreacted probes and release the DNAzymes embedded in the LCR product. The DNAzyme applied in our method is a versatile tool to report the result of SNP detection in colorimetric or fluorometric ways for different detection purposes. Copyright © 2013 Elsevier B.V. All rights reserved.

Optimal filtering and Bayesian detection for friction-based diagnostics in machines.

PubMed

Ray, L R; Townsend, J R; Ramasubramanian, A

2001-01-01

Non-model-based diagnostic methods typically rely on measured signals that must be empirically related to process behavior or incipient faults. The difficulty in interpreting a signal that is indirectly related to the fundamental process behavior is significant. This paper presents an integrated non-model and model-based approach to detecting when process behavior varies from a proposed model. The method, which is based on nonlinear filtering combined with maximum likelihood hypothesis testing, is applicable to dynamic systems whose constitutive model is well known, and whose process inputs are poorly known. Here, the method is applied to friction estimation and diagnosis during motion control in a rotating machine. A nonlinear observer estimates friction torque in a machine from shaft angular position measurements and the known input voltage to the motor. The resulting friction torque estimate can be analyzed directly for statistical abnormalities, or it can be directly compared to friction torque outputs of an applicable friction process model in order to diagnose faults or model variations. Nonlinear estimation of friction torque provides a variable on which to apply diagnostic methods that is directly related to model variations or faults. The method is evaluated experimentally by its ability to detect normal load variations in a closed-loop controlled motor driven inertia with bearing friction and an artificially-induced external line contact. Results show an ability to detect statistically significant changes in friction characteristics induced by normal load variations over a wide range of underlying friction behaviors.

[Application of the mixed programming with Labview and Matlab in biomedical signal analysis].

PubMed

Yu, Lu; Zhang, Yongde; Sha, Xianzheng

2011-01-01

This paper introduces the method of mixed programming with Labview and Matlab, and applies this method in a pulse wave pre-processing and feature detecting system. The method has been proved suitable, efficient and accurate, which has provided a new kind of approach for biomedical signal analysis.

Applying Ancestry and Sex Computation as a Quality Control Tool in Targeted Next-Generation Sequencing.

PubMed

Mathias, Patrick C; Turner, Emily H; Scroggins, Sheena M; Salipante, Stephen J; Hoffman, Noah G; Pritchard, Colin C; Shirts, Brian H

2016-03-01

To apply techniques for ancestry and sex computation from next-generation sequencing (NGS) data as an approach to confirm sample identity and detect sample processing errors. We combined a principal component analysis method with k-nearest neighbors classification to compute the ancestry of patients undergoing NGS testing. By combining this calculation with X chromosome copy number data, we determined the sex and ancestry of patients for comparison with self-report. We also modeled the sensitivity of this technique in detecting sample processing errors. We applied this technique to 859 patient samples with reliable self-report data. Our k-nearest neighbors ancestry screen had an accuracy of 98.7% for patients reporting a single ancestry. Visual inspection of principal component plots was consistent with self-report in 99.6% of single-ancestry and mixed-ancestry patients. Our model demonstrates that approximately two-thirds of potential sample swaps could be detected in our patient population using this technique. Patient ancestry can be estimated from NGS data incidentally sequenced in targeted panels, enabling an inexpensive quality control method when coupled with patient self-report. © American Society for Clinical Pathology, 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Detection of dependence patterns with delay.

PubMed

Chevallier, Julien; Laloë, Thomas

2015-11-01

The Unitary Events (UE) method is a popular and efficient method used this last decade to detect dependence patterns of joint spike activity among simultaneously recorded neurons. The first introduced method is based on binned coincidence count (Grün, 1996) and can be applied on two or more simultaneously recorded neurons. Among the improvements of the methods, a transposition to the continuous framework has recently been proposed by Muiño and Borgelt (2014) and fully investigated by Tuleau-Malot et al. (2014) for two neurons. The goal of the present paper is to extend this study to more than two neurons. The main result is the determination of the limit distribution of the coincidence count. This leads to the construction of an independence test between L≥2 neurons. Finally, we propose a multiple test procedure via a Benjamini and Hochberg approach (Benjamini and Hochberg, 1995). All the theoretical results are illustrated by a simulation study, and compared to the UE method proposed by Grün et al. (2002). Furthermore our method is applied on real data. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System.

PubMed

Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

2017-02-20

In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

The SPR detection of Salmonella enteritidis in food using aptamers as recongnition elements

NASA Astrophysics Data System (ADS)

Di, W. T.; Du, X. W.; Pan, M. F.; Wang, J. P.

2017-09-01

In this experiment, a fast, accurate, non-destructive, unmarked and simple-operation detection method for Salmonella enteritidis in food was established by the BI-3000 plasma resonance biosensor (SPR). This article establishes a method of using nucleic acid aptamer as immune recognition element in SPR which can be employed to detect Salmonella enteritidis in food for the first time. The experimental conditions were screened and the experimental scheme was validated and applied. The best flow rate was 5μL/min, the best concentration of the aptamers was 180mM, and the best regenerating solution was the 20mM NaOH. This method had almost no cross-reactivity. Besides, we established a standard curve of Salmonella enteritidis and SPR signal, with the detection limit of 2 cfu/mL. Finally, we tested the samples of chicken, pork, shrimp and fish purchased from supermarkets. The method has the advantages of short time, low detection limit and easy operation, which can be used for a large number of food samples.

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.

Integrated Micro-Optics for Microfluidic Detection.

PubMed

Kazama, Yuto; Hibara, Akihide

2016-01-01

A method of embedding micro-optics into a microfluidic device was proposed and demonstrated. First, the usefulness of embedded right-angle prisms was demonstrated in microscope observation. Lateral-view microscopic observation of an aqueous dye flow in a 100-μm-sized microchannel was demonstrated. Then, the embedded right-angle prisms were utilized for multi-beam laser spectroscopy. Here, crossed-beam thermal lens detection of a liquid sample was applied to glucose detection.

Molecular sieve sensors for selective detection at the nanogram level

DOEpatents

Bein, Thomas; Brown, Kelly D.; Frye, Gregory C.; Brinker, Charles J.

1992-01-01

The invention relates to a selective chemical sensor for selective detection of chemical entities even at the nanogram level. The invention further relates to methods of using the sensor. The sensor comprises: (a) a piezoelectric substrate capable of detecting mass changes resulting from adsorption of material thereon; and (b) a coating applied to the substrate, which selectively sorbs chemical entities of a size smaller than a preselected magnitude.

Improvement of charge-pumping electrically detected magnetic resonance and its application to silicon metal-oxide-semiconductor field-effect transistor

NASA Astrophysics Data System (ADS)

Hori, Masahiro; Tsuchiya, Toshiaki; Ono, Yukinori

2017-01-01

Charge-pumping electrically detected magnetic resonance (CP EDMR), or EDMR in the CP mode, is improved and applied to a silicon metal-oxide-semiconductor field-effect transistor (MOSFET). Real-time monitoring of the CP process reveals that high-frequency transient currents are an obstacle to signal amplification for EDMR. Therefore, we introduce cutoff circuitry, leading to a detection limit for the number of spins as low as 103 for Si MOS interface defects. With this improved method, we demonstrate that CP EDMR inherits one of the most important features of the CP method: the gate control of the energy window of the detectable interface defects for spectroscopy.

Presetting ECG electrodes for earlier heart rate detection in the delivery room.

PubMed

Gulati, Rashmi; Zayek, Michael; Eyal, Fabien

2018-07-01

To determine whether heart rate (HR) could be detected earlier than by pulse oximeter (POX), using a novel method of application of electrocardiogram (ECG) electrodes during neonatal resuscitation in the delivery room. ECG electrodes were set before delivery to be applied to the back of infants' thorax. Time to detect HR was recorded as soon as a numerical HR along with a recognizable and persistent QRS complex was observed on ECG monitor (HRECG) and a plethysmographic waveform was seen on POX monitor (HRPOX). Out of 334 infants, 49 were <31 weeks of gestational age. Overall, the median (interquartile range, IQR) time to detect HRECG was significantly shorter [29 (5, 60) seconds] than time by POX [60 (45,120) seconds], (p < 0.001). Similarly, in <31-week infants, the median (IQR) time to detect HRECG was 10 (2, 40) seconds compared to 60 (30,120) seconds by POX, (p < 0.001). Failure to have HR detected by 1 minute occurred in 30%, 54% and 20% of infants by ECG, POX and either of the devices, respectively. In the delivery room, electrodes applied by the study method are more effective than pulse oximetry in providing the neonatal team with timely HR information that is necessary for proper resuscitative actions. Published by Elsevier B.V.

Rapid colorimetric assay for detection of Listeria monocytogenes in food samples using LAMP formation of DNA concatemers and gold nanoparticle-DNA probe complex

NASA Astrophysics Data System (ADS)

Wachiralurpan, Sirirat; Sriyapai, Thayat; Areekit, Supatra; Sriyapai, Pichapak; Augkarawaritsawong, Suphitcha; Santiwatanakul, Somchai; Chansiri, Kosum

2018-04-01

ABSTRACT Listeria monocytogenes is a major foodborne pathogen of global health concern. Herein, the rapid diagnosis of L. monocytogenes has been achieved using loop-mediated isothermal amplification (LAMP) based on the phosphatidylcholine-phospholipase C gene (plcB). Colorimetric detection was then performed through the formation of DNA concatemers and a gold nanoparticle/DNA probe complex (GNP/DNA probe). The overall detection process was accomplished within approximately 1 h with no need for complicated equipment. The limits of detection for L. monocytogenes in the forms of purified genomic DNA and pure culture were 800 fg and 2.82 CFU mL-1, respectively. No cross reactions were observed from closely related bacteria species. The LAMP-GNP/DNA probe assay was applied to the detection of 200 raw chicken meat samples and compared to routine standard methods. The data revealed that the specificity, sensitivity and accuracy were 100%, 90.20% and 97.50%, respectively. The present assay was 100% in conformity with LAMP-agarose gel electrophoresis assay. Five samples that were negative by both assays appeared to have the pathogen at below the level of detection. The assay can be applied as a rapid direct screening method for L. monocytogenes.

Hyperspectral imaging applied to medical diagnoses and food safety

NASA Astrophysics Data System (ADS)

Carrasco, Oscar; Gomez, Richard B.; Chainani, Arun; Roper, William E.

2003-08-01

This paper analyzes the feasibility and performance of HSI systems for medical diagnosis as well as for food safety. Illness prevention and early disease detection are key elements for maintaining good health. Health care practitioners worldwide rely on innovative electronic devices to accurately identify disease. Hyperspectral imaging (HSI) is an emerging technique that may provide a less invasive procedure than conventional diagnostic imaging. By analyzing reflected and fluorescent light applied to the human body, a HSI system serves as a diagnostic tool as well as a method for evaluating the effectiveness of applied therapies. The safe supply and production of food is also of paramount importance to public health illness prevention. Although this paper will focus on imaging and spectroscopy in food inspection procedures -- the detection of contaminated food sources -- to ensure food quality, HSI also shows promise in detecting pesticide levels in food production (agriculture.)

Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design.

PubMed

Spreco, Armin; Eriksson, Olle; Dahlström, Örjan; Cowling, Benjamin John; Timpka, Toomas

2017-06-15

Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic "big data" from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning of a winter influenza season has an exponential growth of infected individuals. For prediction modeling, linear regression was applied on 7-day periods at the time in order to find the peak timing, whereas a derivate of a normal distribution density function was used to find the peak intensity. We found that the integrated detection and prediction method detected the 2008-09 winter influenza season on its starting day (optimal timeliness 0 days), whereas the predicted peak was estimated to occur 7 days ahead of the factual peak and the predicted peak intensity was estimated to be 26% lower than the factual intensity (6.3 compared with 8.5 influenza-diagnosis cases/100,000). Our detection and prediction method is one of the first integrated methods specifically designed for local application on influenza data electronically available for surveillance. The performance of the method in a retrospective study indicates that further prospective evaluations of the methods are justified. ©Armin Spreco, Olle Eriksson, Örjan Dahlström, Benjamin John Cowling, Toomas Timpka. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 15.06.2017.

Detection of Pigment Networks in Dermoscopy Images

NASA Astrophysics Data System (ADS)

Eltayef, Khalid; Li, Yongmin; Liu, Xiaohui

2017-02-01

One of the most important structures in dermoscopy images is the pigment network, which is also one of the most challenging and fundamental task for dermatologists in early detection of melanoma. This paper presents an automatic system to detect pigment network from dermoscopy images. The design of the proposed algorithm consists of four stages. First, a pre-processing algorithm is carried out in order to remove the noise and improve the quality of the image. Second, a bank of directional filters and morphological connected component analysis are applied to detect the pigment networks. Third, features are extracted from the detected image, which can be used in the subsequent stage. Fourth, the classification process is performed by applying feed-forward neural network, in order to classify the region as either normal or abnormal skin. The method was tested on a dataset of 200 dermoscopy images from Hospital Pedro Hispano (Matosinhos), and better results were produced compared to previous studies.

Detection of Nosema bombycis by FTA cards and loop-mediated isothermal amplification (LAMP).

PubMed

Yan, Wei; Shen, Zhongyuan; Tang, Xudong; Xu, Li; Li, Qianlong; Yue, Yajie; Xiao, Shengyan; Fu, Xuliang

2014-10-01

We successfully established a detection method which exhibited a markedly higher sensitivity than previously developed detection methods for Nosema bombycis by combining glass beads, FTA card, and LAMP. Spores of N. bombycis were first broken by acid-washed glass beads; the DNA was subsequently extracted and purified with the FTA card, and LAMP was performed using primers (LSU296) designed based on the sequence of the LSU rRNA of N. bombycis. The minimum detection concentration was 10 spores/mL. When this method was used to detect pebrine disease in silkworm egg, the detection rate for 500 silkworm eggs, in which only one egg was infected with N. bombycis, was 100 % under our optimized conditions. If the number of eggs in the sample increased to 800 or 1,000, the sample was divided into two equal portions, and the eggs were smashed with glass beads after the addition of 1 mL of TE buffer. The liquid in two tubes was later mixed and applied to the FTA card, and the detection rates were 100 %. Furthermore, the LAMP method established in our study could detect N. bombycis infection in silkworm 24 h earlier than microscopy.

R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope

PubMed Central

2017-01-01

Rapid automatic detection of the fiducial points—namely, the P wave, QRS complex, and T wave—is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs. PMID:29065613

R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope.

PubMed

Park, Jeong-Seon; Lee, Sang-Woong; Park, Unsang

2017-01-01

Rapid automatic detection of the fiducial points-namely, the P wave, QRS complex, and T wave-is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs.

Helicase dependent OnChip-amplification and its use in multiplex pathogen detection.

PubMed

Andresen, Dennie; von Nickisch-Rosenegk, Markus; Bier, Frank F

2009-05-01

The need for fast, specific and sensitive multiparametric detection methods is an ever growing demand in molecular diagnostics. Here we report on a newly developed method, the helicase dependent OnChip amplification (OnChip-HDA). This approach integrates the analysis and detection in one single reaction thus leading to time and cost savings in multiparametric analysis. HDA is an isothermal amplification method that is not depending on thermocycling as known from PCR due to the helicases' ability to unwind DNA double-strands. We have combined the HDA with microarray based detection, making it suitable for multiplex detection. As an example we used the OnChip HDA in single and multiplex amplifications for the detection of the two pathogens N. gonorrhoeae and S. aureus directly on surface bound primers. We have successfully shown the OnChip-HDA and applied it for single- and duplex-detection of the pathogens N. gonorrhoeae and S. aureus. We have developed a new method, the OnChip-HDA for the multiplex detection of pathogens. Its simplicity in reaction setup and potential for miniaturization and multiparametric analysis is advantageous for the integration in miniaturized Lab on Chip systems, e.g. needed in point of care diagnostics.

Rapid and sensitive method for determination of withaferin-A in human plasma by HPLC.

PubMed

Patial, Pankaj; Gota, Vikram

2011-02-01

To develop and validate a rapid and sensitive high-performance liquid chromatographic method for determination of withaferin-A in human plasma. Withaferin-A, the active molecule of a traditional Indian herb, has demonstrated several biological activities in preclinical models. A validated bioassay is not available for its pharmacokinetic evaluation. The chromatographic system used a reverse-phase C18 column with UV-visible detection at 225 nm. The mobile phase consisted of water and acetonitrile applied in a gradient flow. Withaferin-A was extracted by simple protein-precipitation technique. The calibration curve was linear in the concentration range of 0.05-1.6 µg/ml. The method has the desired sensitivity to detect the plasma concentration range of withaferin-A that is likely to show biological activity based on in vitro data. This is the first HPLC method ever described for the estimation of withaferin-A in human plasma which could be applied for pharmacokinetic studies.

Robust detection of heartbeats using association models from blood pressure and EEG signals.

PubMed

Jeon, Taegyun; Yu, Jongmin; Pedrycz, Witold; Jeon, Moongu; Lee, Boreom; Lee, Byeongcheol

2016-01-15

The heartbeat is fundamental cardiac activity which is straightforwardly detected with a variety of measurement techniques for analyzing physiological signals. Unfortunately, unexpected noise or contaminated signals can distort or cut out electrocardiogram (ECG) signals in practice, misleading the heartbeat detectors to report a false heart rate or suspend itself for a considerable length of time in the worst case. To deal with the problem of unreliable heartbeat detection, PhysioNet/CinC suggests a challenge in 2014 for developing robust heart beat detectors using multimodal signals. This article proposes a multimodal data association method that supplements ECG as a primary input signal with blood pressure (BP) and electroencephalogram (EEG) as complementary input signals when input signals are unreliable. If the current signal quality index (SQI) qualifies ECG as a reliable input signal, our method applies QRS detection to ECG and reports heartbeats. Otherwise, the current SQI selects the best supplementary input signal between BP and EEG after evaluating the current SQI of BP. When BP is chosen as a supplementary input signal, our association model between ECG and BP enables us to compute their regular intervals, detect characteristics BP signals, and estimate the locations of the heartbeat. When both ECG and BP are not qualified, our fusion method resorts to the association model between ECG and EEG that allows us to apply an adaptive filter to ECG and EEG, extract the QRS candidates, and report heartbeats. The proposed method achieved an overall score of 86.26 % for the test data when the input signals are unreliable. Our method outperformed the traditional method, which achieved 79.28 % using QRS detector and BP detector from PhysioNet. Our multimodal signal processing method outperforms the conventional unimodal method of taking ECG signals alone for both training and test data sets. To detect the heartbeat robustly, we have proposed a novel multimodal data association method of supplementing ECG with a variety of physiological signals and accounting for the patient-specific lag between different pulsatile signals and ECG. Multimodal signal detectors and data-fusion approaches such as those proposed in this article can reduce false alarms and improve patient monitoring.

A method of immediate detection of objects with a near-zero apparent motion in series of CCD-frames

NASA Astrophysics Data System (ADS)

Savanevych, V. E.; Khlamov, S. V.; Vavilova, I. B.; Briukhovetskyi, A. B.; Pohorelov, A. V.; Mkrtichian, D. E.; Kudak, V. I.; Pakuliak, L. K.; Dikov, E. N.; Melnik, R. G.; Vlasenko, V. P.; Reichart, D. E.

2018-01-01

The paper deals with a computational method for detection of the solar system minor bodies (SSOs), whose inter-frame shifts in series of CCD-frames during the observation are commensurate with the errors in measuring their positions. These objects have velocities of apparent motion between CCD-frames not exceeding three rms errors (3σ) of measurements of their positions. About 15% of objects have a near-zero apparent motion in CCD-frames, including the objects beyond the Jupiter's orbit as well as the asteroids heading straight to the Earth. The proposed method for detection of the object's near-zero apparent motion in series of CCD-frames is based on the Fisher f-criterion instead of using the traditional decision rules that are based on the maximum likelihood criterion. We analyzed the quality indicators of detection of the object's near-zero apparent motion applying statistical and in situ modeling techniques in terms of the conditional probability of the true detection of objects with a near-zero apparent motion. The efficiency of method being implemented as a plugin for the Collection Light Technology (CoLiTec) software for automated asteroids and comets detection has been demonstrated. Among the objects discovered with this plugin, there was the sungrazing comet C/2012 S1 (ISON). Within 26 min of the observation, the comet's image has been moved by three pixels in a series of four CCD-frames (the velocity of its apparent motion at the moment of discovery was equal to 0.8 pixels per CCD-frame; the image size on the frame was about five pixels). Next verification in observations of asteroids with a near-zero apparent motion conducted with small telescopes has confirmed an efficiency of the method even in bad conditions (strong backlight from the full Moon). So, we recommend applying the proposed method for series of observations with four or more frames.

REANALYSIS OF F-STATISTIC GRAVITATIONAL-WAVE SEARCHES WITH THE HIGHER CRITICISM STATISTIC

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

Bennett, M. F.; Melatos, A.; Delaigle, A.

2013-04-01

We propose a new method of gravitational-wave detection using a modified form of higher criticism, a statistical technique introduced by Donoho and Jin. Higher criticism is designed to detect a group of sparse, weak sources, none of which are strong enough to be reliably estimated or detected individually. We apply higher criticism as a second-pass method to synthetic F-statistic and C-statistic data for a monochromatic periodic source in a binary system and quantify the improvement relative to the first-pass methods. We find that higher criticism on C-statistic data is more sensitive by {approx}6% than the C-statistic alone under optimal conditionsmore » (i.e., binary orbit known exactly) and the relative advantage increases as the error in the orbital parameters increases. Higher criticism is robust even when the source is not monochromatic (e.g., phase-wandering in an accreting system). Applying higher criticism to a phase-wandering source over multiple time intervals gives a {approx}> 30% increase in detectability with few assumptions about the frequency evolution. By contrast, in all-sky searches for unknown periodic sources, which are dominated by the brightest source, second-pass higher criticism does not provide any benefits over a first-pass search.« less

Polymerase chain reaction-based discrimination of viable from non-viable Mycoplasma gallisepticum.

PubMed

Tan, Ching Giap; Ideris, Aini; Omar, Abdul R; Yii, Chen Pei; Kleven, Stanley H

2014-09-02

The present study was based on the reverse transcription polymerase chain reaction (RT-PCR) of the 16S ribosomal nucleic acid (rRNA) of Mycoplasma for detection of viable Mycoplasma gallisepticum. To determine the stability of M. gallisepticum 16S rRNA in vitro, three inactivation methods were used and the suspensions were stored at different temperatures. The 16S rRNA of M. gallisepticum was detected up to approximately 20-25 h at 37 °C, 22-25 h at 16 °C, and 23-27 h at 4 °C. The test, therefore, could detect viable or recently dead M. gallisepticum (< 20 h). The RT-PCR method was applied during an in vivo study of drug efficacy under experimental conditions, where commercial broiler-breeder eggs were inoculated with M. gallisepticum into the yolk. Hatched chicks that had been inoculated in ovo were treated with Macrolide 1. The method was then applied in a flock of day 0 chicks with naturally acquired vertical transmission of M. gallisepticum, treated with Macrolide 2. Swabs of the respiratory tract were obtained for PCR and RT-PCR evaluations to determine the viability of M. gallisepticum. This study proved that the combination of both PCR and RT-PCR enables detection and differentiation of viable from non-viable M. gallisepticum.

Detection of trans–cis flips and peptide-plane flips in protein structures

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

Touw, Wouter G., E-mail: wouter.touw@radboudumc.nl; Joosten, Robbie P.; Vriend, Gert, E-mail: wouter.touw@radboudumc.nl

A method is presented to detect peptide bonds that need either a trans–cis flip or a peptide-plane flip. A coordinate-based method is presented to detect peptide bonds that need correction either by a peptide-plane flip or by a trans–cis inversion of the peptide bond. When applied to the whole Protein Data Bank, the method predicts 4617 trans–cis flips and many thousands of hitherto unknown peptide-plane flips. A few examples are highlighted for which a correction of the peptide-plane geometry leads to a correction of the understanding of the structure–function relation. All data, including 1088 manually validated cases, are freely availablemore » and the method is available from a web server, a web-service interface and through WHAT-CHECK.« less

Damage diagnosis algorithm using a sequential change point detection method with an unknown distribution for damage

NASA Astrophysics Data System (ADS)

Noh, Hae Young; Rajagopal, Ram; Kiremidjian, Anne S.

2012-04-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method for the cases where the post-damage feature distribution is unknown a priori. This algorithm extracts features from structural vibration data using time-series analysis and then declares damage using the change point detection method. The change point detection method asymptotically minimizes detection delay for a given false alarm rate. The conventional method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori. Therefore, our algorithm estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using multiple sets of simulated data and a set of experimental data collected from a four-story steel special moment-resisting frame. Our algorithm was able to estimate the post-damage distribution consistently and resulted in detection delays only a few seconds longer than the delays from the conventional method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

Potentiometric Sensors Based on Surface Molecular Imprinting: Detection of Cancer Biomarkers and Viruses

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

Wang, Y.; Zhang, Z; Jain, V

2010-01-01

The continuing discovery of cancer biomarkers necessitates improved methods for their detection. Molecular imprinting using artificial materials provides an alternative to the detection of a wide range of substances. We applied surface molecular imprinting using self-assembled monolayers to design sensing elements for the detection of cancer biomarkers and other proteins. These elements consist of a gold-coated silicon chip onto which hydroxyl-terminated alkanethiol molecules and template biomolecule are co-adsorbed, where the thiol molecules are chemically bound to the metal substrate and self-assembled into highly ordered monolayers, the biomolecules can be removed, creating the foot-print cavities in the monolayer matrix for thismore » kind of template molecules. Re-adsorption of the biomolecules to the sensing chip changes its potential, which can be measured potentiometrically. We applied this method to the detection of carcinoembryonic antigen (CEA) in both solutions of purified CEA and in the culture medium of a CEA-producing human colon cancer cell line. The CEA assay, validated also against a standard immunoassay, was both sensitive (detection range 2.5-250 ng/mL) and specific (no cross-reactivity with hemoglobin; no response by a non-imprinted sensor). Similar results were obtained for human amylase. In addition, we detected virions of poliovirus in a specific manner (no cross-reactivity to adenovirus, no response by a non-imprinted sensor). Our findings demonstrate the application of the principles of molecular imprinting to the development of a new method for the detection of protein cancer biomarkers and to protein-based macromolecular structures such as the capsid of a virion. This approach has the potential of generating a general assay methodology that could be highly sensitive, specific, simple and likely inexpensive.« less

Bifunctional nanoparticles for surface-enhanced Raman spectroscopy-based leukemia biomarker detection

NASA Astrophysics Data System (ADS)

Mehn, Dora; Morasso, Carlo; Vanna, Renzo; Schiumarini, Domitilla; Bedoni, Marzia; Ciceri, Fabio; Gramatica, Furio

2014-03-01

The Wilms tumor gene (WT1) is a biomarker overexpressed in more than 90% of acute myeloid leukemia patients. Fast and sensitive detection of the WT1 in blood samples would allow monitoring of the minimal residual disease during clinical remission and would permit early detection of a potential relapse in acute myeloid leukemia. In this work, Surface Enhanced Raman Spectroscopy (SERS) based detection of the WT1 sequence using bifunctional, magnetic core - gold shell nanoparticles is presented. The classical co-precipitation method was applied to generate magnetic nanoparticles which were coated with a gold shell after modification with aminopropyltriethoxy silane and subsequent deposition of gold nanoparticle seeds. Simple hydroquinone based reduction procedure was applied for the shell growing in water based reaction mixture at room temperature. Thiolated ssDNA probes of the WT1 sequence were immobilized as capture oligonucleotides on the gold surface. Malachite green was applied both for testing the amplification performance of the core-shell colloidal SERS substrate and also as label dye of the target DNA sequence. The SERS enhancer efficacy of the core-shell nanomaterial was compared with the efficacy of classical spherical gold particles produced using the conventional citrate reduction method. The core-shell particles were found not only to provide an opportunity for facile separation in a heterogeneous reaction system but also to be superior regarding robustness as SERS enhancers.

A method for estimating abundance of mobile populations using telemetry and counts of unmarked animals

USGS Publications Warehouse

Clement, Matthew; O'Keefe, Joy M; Walters, Brianne

2015-01-01

While numerous methods exist for estimating abundance when detection is imperfect, these methods may not be appropriate due to logistical difficulties or unrealistic assumptions. In particular, if highly mobile taxa are frequently absent from survey locations, methods that estimate a probability of detection conditional on presence will generate biased abundance estimates. Here, we propose a new estimator for estimating abundance of mobile populations using telemetry and counts of unmarked animals. The estimator assumes that the target population conforms to a fission-fusion grouping pattern, in which the population is divided into groups that frequently change in size and composition. If assumptions are met, it is not necessary to locate all groups in the population to estimate abundance. We derive an estimator, perform a simulation study, conduct a power analysis, and apply the method to field data. The simulation study confirmed that our estimator is asymptotically unbiased with low bias, narrow confidence intervals, and good coverage, given a modest survey effort. The power analysis provided initial guidance on survey effort. When applied to small data sets obtained by radio-tracking Indiana bats, abundance estimates were reasonable, although imprecise. The proposed method has the potential to improve abundance estimates for mobile species that have a fission-fusion social structure, such as Indiana bats, because it does not condition detection on presence at survey locations and because it avoids certain restrictive assumptions.

Isocyanate exposure assessment combining industrial hygiene methods with biomonitoring for end users of orthopedic casting products.

PubMed

Pearson, Ronald L; Logan, Perry W; Kore, Anita M; Strom, Constance M; Brosseau, Lisa M; Kingston, Richard L

2013-07-01

Previous studies have suggested a potential risk to healthcare workers applying isocyanate-containing casts, but the authors reached their conclusions based on immunological or clinical pulmonology test results alone. We designed a study to assess potential exposure to methylene diphenyl diisocyanate (MDI) among medical personnel applying orthopedic casts using two different application methods. Air, dermal, surface, and glove permeation sampling methods were combined with urinary biomonitoring to assess the overall risk of occupational asthma to workers handling these materials. No MDI was detected in any of the personal and area air samples obtained. No glove permeation of MDI was detected. A small proportion of surface (3/45) and dermal wipe (1/60) samples were positive for MDI, but were all from inexperienced technicians. Urinary metabolites of MDI [methylenedianiline (MDA)] were detected in three of six study participants prior to both a 'dry' and 'wet' application method, five of six after the dry method, and three of six after the wet method. All MDA results were below levels noted in worker or general populations. Our conclusion is that the risk of MDI exposure is small, but unquantifiable. Because there is some potential risk of dermal exposure, medical personnel are instructed to wear a minimum of 5-mil-thick (5 mil = 0.005 inches) nitrile gloves and avoid contact to unprotected skin. This could include gauntlets, long sleeves, and/or a laboratory coat.

An extension of the Coconut Cream Agar method to screen Penicillium citrinum isolates for citrinin production.

PubMed

Mohamed, S; Flint, S; Palmer, J; Fletcher, G C; Pitt, J I

2013-09-01

A simple and rapid screening method was developed for the detection of citrinin in fungal cultures using Coconut Cream Agar (CCA) described previously for detecting aflatoxin and ochratoxin A. Fifteen isolates of Penicillium citrinum were inoculated onto CCA and incubated at 25 and 30°C for 10 days. All isolates produced a distinct yellow green fluorescence on CCA when the reverse side of the agar plates were viewed under long wavelength UV light. Detection was optimal at 25°C after four to 5 days of incubation. Isolates positive by the CCA method also tested positive for citrinin production by the TLC agar plug method after growth on CCA, Czapek yeast extract agar and yeast extract sucrose agar. Control cultures were negative by both methods, indicating that the CCA Petri dish method was suitable for screening cultures for citrinin production. © 2013 The Society for Applied Microbiology.

Automatically Detect and Track Multiple Fish Swimming in Shallow Water with Frequent Occlusion

PubMed Central

Qian, Zhi-Ming; Cheng, Xi En; Chen, Yan Qiu

2014-01-01

Due to its universality, swarm behavior in nature attracts much attention of scientists from many fields. Fish schools are examples of biological communities that demonstrate swarm behavior. The detection and tracking of fish in a school are of important significance for the quantitative research on swarm behavior. However, different from other biological communities, there are three problems in the detection and tracking of fish school, that is, variable appearances, complex motion and frequent occlusion. To solve these problems, we propose an effective method of fish detection and tracking. In this method, first, the fish head region is positioned through extremum detection and ellipse fitting; second, The Kalman filtering and feature matching are used to track the target in complex motion; finally, according to the feature information obtained by the detection and tracking, the tracking problems caused by frequent occlusion are processed through trajectory linking. We apply this method to track swimming fish school of different densities. The experimental results show that the proposed method is both accurate and reliable. PMID:25207811

Rapid and sensitive detection of human astrovirus in water samples by loop-mediated isothermal amplification with hydroxynaphthol blue dye

PubMed Central

2014-01-01

Background The aim of this paper was to develop a reverse transcription loop-mediated isothermal amplification (RT-LAMP) method for rapid, sensitive and inexpensive detection of astrovirus. Results The detection limit of LAMP using in vitro RNA transcripts was 3.6×10 copies·μL-1, which is as sensitive as the presently used PCR assays. However, the LAMP products could be identified as different colors with the naked eye following staining with hydroxynaphthol blue dye (HNB). No cross-reactivity with other gastroenteric viruses (rotavirus and norovirus) was observed, indicating the relatively high specificity of LAMP. The RT-LAMP method with HNB was used to effectively detect astrovirus in reclaimed water samples. Conclusions The LAMP technique described in this study is a cheap, sensitive, specific and rapid method for the detection of astrovirus. The RT-LAMP method can be simply applied for the specific detection of astrovirus and has the potential to be utilized in the field as a screening test. PMID:24524254

On-line Monitoring Device for High-voltage Switch Cabinet Partial Discharge Based on Pulse Current Method

NASA Astrophysics Data System (ADS)

Y Tao, S.; Zhang, X. Z.; Cai, H. W.; Li, P.; Feng, Y.; Zhang, T. C.; Li, J.; Wang, W. S.; Zhang, X. K.

2017-12-01

The pulse current method for partial discharge detection is generally applied in type testing and other off-line tests of electrical equipment at delivery. After intensive analysis of the present situation and existing problems of partial discharge detection in switch cabinets, this paper designed the circuit principle and signal extraction method for partial discharge on-line detection based on a high-voltage presence indicating systems (VPIS), established a high voltage switch cabinet partial discharge on-line detection circuit based on the pulse current method, developed background software integrated with real-time monitoring, judging and analyzing functions, carried out a real discharge simulation test on a real-type partial discharge defect simulation platform of a 10KV switch cabinet, and verified the sensitivity and validity of the high-voltage switch cabinet partial discharge on-line monitoring device based on the pulse current method. The study presented in this paper is of great significance for switch cabinet maintenance and theoretical study on pulse current method on-line detection, and has provided a good implementation method for partial discharge on-line monitoring devices for 10KV distribution network equipment.

Design of Passive Power Filter for Hybrid Series Active Power Filter using Estimation, Detection and Classification Method

NASA Astrophysics Data System (ADS)

Swain, Sushree Diptimayee; Ray, Pravat Kumar; Mohanty, K. B.

2016-06-01

This research paper discover the design of a shunt Passive Power Filter (PPF) in Hybrid Series Active Power Filter (HSAPF) that employs a novel analytic methodology which is superior than FFT analysis. This novel approach consists of the estimation, detection and classification of the signals. The proposed method is applied to estimate, detect and classify the power quality (PQ) disturbance such as harmonics. This proposed work deals with three methods: the harmonic detection through wavelet transform method, the harmonic estimation by Kalman Filter algorithm and harmonic classification by decision tree method. From different type of mother wavelets in wavelet transform method, the db8 is selected as suitable mother wavelet because of its potency on transient response and crouched oscillation at frequency domain. In harmonic compensation process, the detected harmonic is compensated through Hybrid Series Active Power Filter (HSAPF) based on Instantaneous Reactive Power Theory (IRPT). The efficacy of the proposed method is verified in MATLAB/SIMULINK domain and as well as with an experimental set up. The obtained results confirm the superiority of the proposed methodology than FFT analysis. This newly proposed PPF is used to make the conventional HSAPF more robust and stable.

Application of Scan Statistics to Detect Suicide Clusters in Australia

PubMed Central

Cheung, Yee Tak Derek; Spittal, Matthew J.; Williamson, Michelle Kate; Tung, Sui Jay; Pirkis, Jane

2013-01-01

Background Suicide clustering occurs when multiple suicide incidents take place in a small area or/and within a short period of time. In spite of the multi-national research attention and particular efforts in preparing guidelines for tackling suicide clusters, the broader picture of epidemiology of suicide clustering remains unclear. This study aimed to develop techniques in using scan statistics to detect clusters, with the detection of suicide clusters in Australia as example. Methods and Findings Scan statistics was applied to detect clusters among suicides occurring between 2004 and 2008. Manipulation of parameter settings and change of area for scan statistics were performed to remedy shortcomings in existing methods. In total, 243 suicides out of 10,176 (2.4%) were identified as belonging to 15 suicide clusters. These clusters were mainly located in the Northern Territory, the northern part of Western Australia, and the northern part of Queensland. Among the 15 clusters, 4 (26.7%) were detected by both national and state cluster detections, 8 (53.3%) were only detected by the state cluster detection, and 3 (20%) were only detected by the national cluster detection. Conclusions These findings illustrate that the majority of spatial-temporal clusters of suicide were located in the inland northern areas, with socio-economic deprivation and higher proportions of indigenous people. Discrepancies between national and state/territory cluster detection by scan statistics were due to the contrast of the underlying suicide rates across states/territories. Performing both small-area and large-area analyses, and applying multiple parameter settings may yield the maximum benefits for exploring clusters. PMID:23342098

Rapid quantification of viable Legionella in nuclear cooling tower waters using filter cultivation, fluorescent in situ hybridization and solid-phase cytometry.

PubMed

Baudart, J; Guillaume, C; Mercier, A; Lebaron, P; Binet, M

2015-05-01

To develop a rapid and sensitive method to quantify viable Legionella spp. in cooling tower water samples. A rapid, culture-based method capable of quantifying as few as 600 Legionella microcolonies per litre within 2 days in industrial waters was developed. The method combines a short cultivation step of microcolonies on GVPC agar plate, specific detection of Legionella cells by a fluorescent in situ hybridization (FISH) approach, and a sensitive enumeration using a solid-phase cytometer. Following optimization of the cultivation conditions, the qualitative and quantitative performance of the method was assessed and the method was applied to 262 nuclear power plant cooling water samples. The performance of this method was in accordance with the culture method (NF-T 90-431) for Legionella enumeration. The rapid detection of viable Legionella in water is a major concern to the effective monitoring of this pathogenic bacterium in the main water sources involved in the transmission of legionellosis infection (Legionnaires' disease). The new method proposed here appears to be a robust, efficient and innovative means for rapidly quantifying cultivable Legionella in cooling tower water samples within 48 h. © 2015 The Society for Applied Microbiology.

Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology

NASA Technical Reports Server (NTRS)

Forkel, Matthias; Carvalhais, Nuno; Verbesselt, Jan; Mahecha, Miguel D.; Neigh, Christopher S.R.; Reichstein, Markus

2013-01-01

Changing trends in ecosystem productivity can be quantified using satellite observations of Normalized Difference Vegetation Index (NDVI). However, the estimation of trends from NDVI time series differs substantially depending on analyzed satellite dataset, the corresponding spatiotemporal resolution, and the applied statistical method. Here we compare the performance of a wide range of trend estimation methods and demonstrate that performance decreases with increasing inter-annual variability in the NDVI time series. Trend slope estimates based on annual aggregated time series or based on a seasonal-trend model show better performances than methods that remove the seasonal cycle of the time series. A breakpoint detection analysis reveals that an overestimation of breakpoints in NDVI trends can result in wrong or even opposite trend estimates. Based on our results, we give practical recommendations for the application of trend methods on long-term NDVI time series. Particularly, we apply and compare different methods on NDVI time series in Alaska, where both greening and browning trends have been previously observed. Here, the multi-method uncertainty of NDVI trends is quantified through the application of the different trend estimation methods. Our results indicate that greening NDVI trends in Alaska are more spatially and temporally prevalent than browning trends. We also show that detected breakpoints in NDVI trends tend to coincide with large fires. Overall, our analyses demonstrate that seasonal trend methods need to be improved against inter-annual variability to quantify changing trends in ecosystem productivity with higher accuracy.

Comparative study of protoporphyrin IX fluorescence image enhancement methods to improve an optical imaging system for oral cancer detection

NASA Astrophysics Data System (ADS)

Jiang, Ching-Fen; Wang, Chih-Yu; Chiang, Chun-Ping

2011-07-01

Optoelectronics techniques to induce protoporphyrin IX fluorescence with topically applied 5-aminolevulinic acid on the oral mucosa have been developed to noninvasively detect oral cancer. Fluorescence imaging enables wide-area screening for oral premalignancy, but the lack of an adequate fluorescence enhancement method restricts the clinical imaging application of these techniques. This study aimed to develop a reliable fluorescence enhancement method to improve PpIX fluorescence imaging systems for oral cancer detection. Three contrast features, red-green-blue reflectance difference, R/B ratio, and R/G ratio, were developed first based on the optical properties of the fluorescence images. A comparative study was then carried out with one negative control and four biopsy confirmed clinical cases to validate the optimal image processing method for the detection of the distribution of malignancy. The results showed the superiority of the R/G ratio in terms of yielding a better contrast between normal and neoplastic tissue, and this method was less prone to errors in detection. Quantitative comparison with the clinical diagnoses in the four neoplastic cases showed that the regions of premalignancy obtained using the proposed method accorded with the expert's determination, suggesting the potential clinical application of this method for the detection of oral cancer.

A Swiss cheese error detection method for real-time EPID-based quality assurance and error prevention.

PubMed

Passarge, Michelle; Fix, Michael K; Manser, Peter; Stampanoni, Marco F M; Siebers, Jeffrey V

2017-04-01

To develop a robust and efficient process that detects relevant dose errors (dose errors of ≥5%) in external beam radiation therapy and directly indicates the origin of the error. The process is illustrated in the context of electronic portal imaging device (EPID)-based angle-resolved volumetric-modulated arc therapy (VMAT) quality assurance (QA), particularly as would be implemented in a real-time monitoring program. A Swiss cheese error detection (SCED) method was created as a paradigm for a cine EPID-based during-treatment QA. For VMAT, the method compares a treatment plan-based reference set of EPID images with images acquired over each 2° gantry angle interval. The process utilizes a sequence of independent consecutively executed error detection tests: an aperture check that verifies in-field radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment check to examine if rotation, scaling, and translation are within tolerances; pixel intensity check containing the standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each check were determined. To test the SCED method, 12 different types of errors were selected to modify the original plan. A series of angle-resolved predicted EPID images were artificially generated for each test case, resulting in a sequence of precalculated frames for each modified treatment plan. The SCED method was applied multiple times for each test case to assess the ability to detect introduced plan variations. To compare the performance of the SCED process with that of a standard gamma analysis, both error detection methods were applied to the generated test cases with realistic noise variations. Averaged over ten test runs, 95.1% of all plan variations that resulted in relevant patient dose errors were detected within 2° and 100% within 14° (<4% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 89.1% were detected by the SCED method within 2°. Based on the type of check that detected the error, determination of error sources was achieved. With noise ranging from no random noise to four times the established noise value, the averaged relevant dose error detection rate of the SCED method was between 94.0% and 95.8% and that of gamma between 82.8% and 89.8%. An EPID-frame-based error detection process for VMAT deliveries was successfully designed and tested via simulations. The SCED method was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of relevant dose errors. Compared to a typical (3%, 3 mm) gamma analysis, the SCED method produced a higher detection rate for all introduced dose errors, identified errors in an earlier stage, displayed a higher robustness to noise variations, and indicated the error source. © 2017 American Association of Physicists in Medicine.

Non-invasive prenatal detection of achondroplasia using circulating fetal DNA in maternal plasma.

PubMed

Lim, Ji Hyae; Kim, Mee Jin; Kim, Shin Young; Kim, Hye Ok; Song, Mee Jin; Kim, Min Hyoung; Park, So Yeon; Yang, Jae Hyug; Ryu, Hyun Mee

2011-02-01

To perform a reliable non-invasive detection of the fetal achondroplasia using maternal plasma. We developed a quantitative fluorescent-polymerase chain reaction (QF-PCR) method suitable for detection of the FGFR3 mutation (G1138A) causing achondroplasia. This method was applied in a non-invasive detection of the fetal achondroplasia using circulating fetal-DNA (cf-DNA) in maternal plasma. Maternal plasmas were obtained at 27 weeks of gestational age from women carrying an achondroplasia fetus or a normal fetus. Two percent or less achondroplasia DNA was reliably detected by QF-PCR. In a woman carrying a normal fetus, analysis of cf-DNA showed only one peak of the wild-type G allele. In a woman expected an achondroplasia fetus, analysis of cf-DNA showed the two peaks of wild-type G allele and mutant-type A allele and accurately detected the fetal achondroplasia. The non-invasive method using maternal plasma and QF-PCR may be useful for diagnosis of the fetal achondroplasia.

A coloured oil level indicator detection method based on simple linear iterative clustering

NASA Astrophysics Data System (ADS)

Liu, Tianli; Li, Dongsong; Jiao, Zhiming; Liang, Tao; Zhou, Hao; Yang, Guoqing

2017-12-01

A detection method of coloured oil level indicator is put forward. The method is applied to inspection robot in substation, which realized the automatic inspection and recognition of oil level indicator. Firstly, the detected image of the oil level indicator is collected, and the detected image is clustered and segmented to obtain the label matrix of the image. Secondly, the detection image is processed by colour space transformation, and the feature matrix of the image is obtained. Finally, the label matrix and feature matrix are used to locate and segment the detected image, and the upper edge of the recognized region is obtained. If the upper limb line exceeds the preset oil level threshold, the alarm will alert the station staff. Through the above-mentioned image processing, the inspection robot can independently recognize the oil level of the oil level indicator, and instead of manual inspection. It embodies the automatic and intelligent level of unattended operation.

Magnetic imager and method

DOEpatents

Powell, James; Reich, Morris; Danby, Gordon

1997-07-22

A magnetic imager 10 includes a generator 18 for practicing a method of applying a background magnetic field over a concealed object, with the object being effective to locally perturb the background field. The imager 10 also includes a sensor 20 for measuring perturbations of the background field to detect the object. In one embodiment, the background field is applied quasi-statically. And, the magnitude or rate of change of the perturbations may be measured for determining location, size, and/or condition of the object.

A Simple and Direct LC-MS Method for Determination of Genotoxic Impurity Hydroxylamine in Pharmaceutical compounds.

PubMed

Kumar, Thangarathinam; Ramya, Mohandass; Srinivasan, Viswanathan; Xavier, N

2017-08-01

Hydroxylamine is a known genotoxic impurity compound that needs to be controlled down to ppm level in pharmaceutical processes. It is difficult to detect using conventional analytical techniques due to its physio-chemical properties like lack of chromophore, low molecular weight, absence of carbon atom and high polarity. In addition to that, analysis of the pharmaceutical samples encounters considerable obstruction from matrix components that greatly overshadow the response of hydroxylamine. This study describes a simple, sensitive and direct Liquid Chromatographic-Mass Spectrometric method (LC-MS) for detection of hydroxylamine in pharmaceutical compounds. The LC-MS method was detected up to 0.008 ppm of hydroxylamine with S/N > 3.0 and quantified up to 0.025 ppm of hydroxylamine with S/N ratio >10.0. This validated method can be applied as a generic method to detect the hydroxylamine for pharmaceutical process control and drug substance release. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Checklist and "Pollard Walk" butterfly survey methods on public lands

USGS Publications Warehouse

Royer, Ronald A.; Austin, Jane E.; Newton, Wesley E.

1998-01-01

Checklist and “Pollard Walk” butterfly survey methods were contemporaneously applied to seven public sites in North Dakota during the summer of 1995. Results were compared for effect of method and site on total number of butterflies and total number of species detected per hour. Checklist searching produced significantly more butterfly detections per hour than Pollard Walks at all sites. Number of species detected per hour did not differ significantly either among sites or between methods. Many species were detected by only one method, and at most sites generalist and invader species were more likely to be observed during checklist searches than during Pollard Walks. Results indicate that checklist surveys are a more efficient means for initial determination of a species list for a site, whereas for long-term monitoring the Pollard Walk is more practical and statistically manageable. Pollard Walk transects are thus recommended once a prairie butterfly fauna has been defined for a site by checklist surveys.

Evaluation of different heating methods for the detection of boar taint by means of the human nose.

PubMed

Bekaert, K M; Aluwé, M; Vanhaecke, L; Heres, L; Duchateau, L; Vandendriessche, F; Tuyttens, F A M

2013-05-01

No automated detection system for boar taint detection is currently available, thus boar taint at the slaughterline can currently only be assessed using the singeing method (olfactory scoring). This study compares several heating methods (microwave, soldering iron and pyropen) and evaluates the effect of habituation, cleaning the soldering iron, singeing the fat twice in the same place, and variations in the technical procedures. All methods seem to be suitable for detecting boar taint but the choice of heating method for sensory scoring of boar taint depends on habituation of the trained assessor and specific conditions applied. The pyropen seems to be most suitable because it does not contact the fat and is easy to handle (wireless). Finally, the intensity score may also be influenced by: contamination from not cleaning the soldering iron, singeing the fat twice in the same place, and the effect of habituation. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Application of Time-Frequency Methods to HUMS

NASA Technical Reports Server (NTRS)

Pryor, Anna H.; Mosher, Marianne; Lewicki, David G.; Norvig, Peter (Technical Monitor)

2001-01-01

This paper reports the study of four time-frequency transforms applied to vibration signals and presents a new metric for comparing them for fault detection. The four methods to be described and compared are the Short Time Frequency Transform (STFT), the Choi-Williams Distribution (WV-CW), the Continuous Wavelet Transform (CWT) and the Discrete Wavelet Transform (DWT). Vibration data of bevel gear tooth fatigue cracks, under a variety of operating load levels, are analyzed using these methods. The new metric for automatic fault detection is developed and can be produced from any systematic numerical representation of the vibration signals. This new metric reveals indications of gear damage with all of the methods on this data set. Analysis with the CWT detects mechanical problems with the test rig not found with the other transforms. The WV-CW and CWT use considerably more resources than the STFT and the DWT. More testing of the new metric is needed to determine its value for automatic fault detection and to develop methods of setting the threshold for the metric.

Novel Quantitative Real-Time LCR for the Sensitive Detection of SNP Frequencies in Pooled DNA: Method Development, Evaluation and Application

PubMed Central

Psifidi, Androniki; Dovas, Chrysostomos; Banos, Georgios

2011-01-01

Background Single nucleotide polymorphisms (SNP) have proven to be powerful genetic markers for genetic applications in medicine, life science and agriculture. A variety of methods exist for SNP detection but few can quantify SNP frequencies when the mutated DNA molecules correspond to a small fraction of the wild-type DNA. Furthermore, there is no generally accepted gold standard for SNP quantification, and, in general, currently applied methods give inconsistent results in selected cohorts. In the present study we sought to develop a novel method for accurate detection and quantification of SNP in DNA pooled samples. Methods The development and evaluation of a novel Ligase Chain Reaction (LCR) protocol that uses a DNA-specific fluorescent dye to allow quantitative real-time analysis is described. Different reaction components and thermocycling parameters affecting the efficiency and specificity of LCR were examined. Several protocols, including gap-LCR modifications, were evaluated using plasmid standard and genomic DNA pools. A protocol of choice was identified and applied for the quantification of a polymorphism at codon 136 of the ovine PRNP gene that is associated with susceptibility to a transmissible spongiform encephalopathy in sheep. Conclusions The real-time LCR protocol developed in the present study showed high sensitivity, accuracy, reproducibility and a wide dynamic range of SNP quantification in different DNA pools. The limits of detection and quantification of SNP frequencies were 0.085% and 0.35%, respectively. Significance The proposed real-time LCR protocol is applicable when sensitive detection and accurate quantification of low copy number mutations in DNA pools is needed. Examples include oncogenes and tumour suppressor genes, infectious diseases, pathogenic bacteria, fungal species, viral mutants, drug resistance resulting from point mutations, and genetically modified organisms in food. PMID:21283808

Novel face-detection method under various environments

NASA Astrophysics Data System (ADS)

Jing, Min-Quan; Chen, Ling-Hwei

2009-06-01

We propose a method to detect a face with different poses under various environments. On the basis of skin color information, skin regions are first extracted from an input image. Next, the shoulder part is cut out by using shape information and the head part is then identified as a face candidate. For a face candidate, a set of geometric features is applied to determine if it is a profile face. If not, then a set of eyelike rectangles extracted from the face candidate and the lighting distribution are used to determine if the face candidate is a nonprofile face. Experimental results show that the proposed method is robust under a wide range of lighting conditions, different poses, and races. The detection rate for the HHI face database is 93.68%. For the Champion face database, the detection rate is 95.15%.

Back-tracking of primary particle trajectories for muons detected at the Earth surface

NASA Astrophysics Data System (ADS)

Shutenko, V. V.

2017-01-01

Investigations of cosmic rays on the surface of the Earth allow to derive information of applied character on the conditions of the interplanetary magnetic field and of the geomagnetic field. For this purpose, it is necessary to collate trajectories of particles detected in the ground-based detector to trajectories of primary cosmic rays in the heliosphere. This problem is solved by means of various back-tracking methods. In this work, one of such methods is presented.

Detection of fuze defects by image-processing methods

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

Chung, M.J.

1988-03-01

This paper describes experimental studies of the detection of mechanical defects by the application of computer-processing methods to real-time radiographic images of fuze assemblies. The experimental results confirm that a new algorithm developed at Materials Research Laboratory has potential for the automatic inspection of these assemblies and of others that contain discrete components. The algorithm was applied to images that contain a range of grey levels and has been found to be tolerant to image variations encountered under simulated production conditions.

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

Detecting electroporation by assessing the time constants in the exponential response of human skin to voltage controlled impulse electrical stimulation.

PubMed

Bîrlea, Sinziana I; Corley, Gavin J; Bîrlea, Nicolae M; Breen, Paul P; Quondamatteo, Fabio; OLaighin, Gearóid

2009-01-01

We propose a new method for extracting the electrical properties of human skin based on the time constant analysis of its exponential response to impulse stimulation. As a result of this analysis an adjacent finding has arisen. We have found that stratum corneum electroporation can be detected using this analysis method. We have observed that a one time-constant model is appropriate for describing the electrical properties of human skin at low amplitude applied voltages (<30V), and a two time-constant model best describes skin electrical properties at higher amplitude applied voltages (>30V). Higher voltage amplitudes (>30V) have been proven to create pores in the skin's stratum corneum which offer a new, lower resistance, pathway for the passage of current through the skin. Our data shows that when pores are formed in the stratum corneum they can be detected, in-vivo, due to the fact that a second time constant describes current flow through them.

Preparing cuprous oxide nanomaterials by electrochemical method for non-enzymatic glucose biosensor

NASA Astrophysics Data System (ADS)

Nguyen, Thu-Thuy; Huy, Bui The; Hwang, Seo-Young; Vuong, Nguyen Minh; Pham, Quoc-Thai; Nghia, Nguyen Ngoc; Kirtland, Aaron; Lee, Yong-Ill

2018-05-01

Cuprous oxide (Cu2O) nanostructure has been synthesized using an electrochemical method with a two-electrode system. Cu foils were used as electrodes and NH2(OH) was utilized as the reducing agent. The effects of pH and applied voltages on the morphology of the product were investigated. The morphology and optical properties of Cu2O particles were characterized using scanning electron microscopy, x-ray diffraction, and diffuse reflectance spectra. The synthesized Cu2O nanostructures that formed in the vicinity of the anode at 2 V and pH = 11 showed high uniform distribution, small size, and good electrochemical sensing. These Cu2O nanoparticles were coated on an Indium tin oxide substrate and applied to detect non-enzyme glucose as excellent biosensors. The non-enzyme glucose biosensors exhibited good performance with high response, good selectivity, wide linear detection range, and a low detection limit at 0.4 μM. Synthesized Cu2O nanostructures are potential materials for a non-enzyme glucose biosensor.

A rapid high-performance liquid chromatography-tandem mass spectrometry assay for unambiguous detection of different milk species employed in cheese manufacturing.

PubMed

Bernardi, Nadia; Benetti, Giuseppe; Haouet, Naceur M; Sergi, Manuel; Grotta, Lisa; Marchetti, Sonia; Castellani, Federica; Martino, Giuseppe

2015-12-01

The aim of the study was to investigate the possibility to differentiate the 4 most important species in Italian dairy industry (cow, buffalo, sheep, and goat), applying a bottom-up proteomic approach to assess the milk species involved in cheese production. Selective peptides were detected in milk to use as markers in cheese products. Trypsin-digested milk samples of cow, sheep, goat, and buffalo, analyzed by HPLC-tandem mass spectrometry provided species-specific peptides, some of them recognized by Mascot software (Matrix Science Ltd., Boston, MA) as derived from well-known species specific proteins. A multianalyte multiple reaction monitoring method, built with these specific peptides, was successfully applied to cheeses with different composition, showing high specificity in detection of species involved. Neither aging nor production method seemed to affect the response, demonstrating that chosen peptides well act as species markers for dairy products. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry applied to virus identification

PubMed Central

Calderaro, Adriana; Arcangeletti, Maria-Cristina; Rodighiero, Isabella; Buttrini, Mirko; Gorrini, Chiara; Motta, Federica; Germini, Diego; Medici, Maria-Cristina; Chezzi, Carlo; De Conto, Flora

2014-01-01

Virus detection and/or identification traditionally rely on methods based on cell culture, electron microscopy and antigen or nucleic acid detection. These techniques are good, but often expensive and/or time-consuming; furthermore, they not always lead to virus identification at the species and/or type level. In this study, Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) was tested as an innovative tool to identify human polioviruses and to identify specific viral protein biomarkers in infected cells. The results revealed MALDI-TOF MS to be an effective and inexpensive tool for the identification of the three poliovirus serotypes. The method was firstly applied to Sabin reference strains, and then to isolates from different clinical samples, highlighting its value as a time-saving, sensitive and specific technique when compared to the gold standard neutralization assay and casting new light on its possible application to virus detection and/or identification. PMID:25354905

Preparing cuprous oxide nanomaterials by electrochemical method for non-enzymatic glucose biosensor.

PubMed

Nguyen, Thu-Thuy; Huy, Bui The; Hwang, Seo-Young; Vuong, Nguyen Minh; Pham, Quoc-Thai; Nghia, Nguyen Ngoc; Kirtland, Aaron; Lee, Yong-Ill

2018-05-18

Cuprous oxide (Cu 2 O) nanostructure has been synthesized using an electrochemical method with a two-electrode system. Cu foils were used as electrodes and NH 2 (OH) was utilized as the reducing agent. The effects of pH and applied voltages on the morphology of the product were investigated. The morphology and optical properties of Cu 2 O particles were characterized using scanning electron microscopy, x-ray diffraction, and diffuse reflectance spectra. The synthesized Cu 2 O nanostructures that formed in the vicinity of the anode at 2 V and pH = 11 showed high uniform distribution, small size, and good electrochemical sensing. These Cu 2 O nanoparticles were coated on an Indium tin oxide substrate and applied to detect non-enzyme glucose as excellent biosensors. The non-enzyme glucose biosensors exhibited good performance with high response, good selectivity, wide linear detection range, and a low detection limit at 0.4 μM. Synthesized Cu 2 O nanostructures are potential materials for a non-enzyme glucose biosensor.

Modified screening and ranking algorithm for copy number variation detection.

PubMed

Xiao, Feifei; Min, Xiaoyi; Zhang, Heping

2015-05-01

Copy number variation (CNV) is a type of structural variation, usually defined as genomic segments that are 1 kb or larger, which present variable copy numbers when compared with a reference genome. The screening and ranking algorithm (SaRa) was recently proposed as an efficient approach for multiple change-points detection, which can be applied to CNV detection. However, some practical issues arise from application of SaRa to single nucleotide polymorphism data. In this study, we propose a modified SaRa on CNV detection to address these issues. First, we use the quantile normalization on the original intensities to guarantee that the normal mean model-based SaRa is a robust method. Second, a novel normal mixture model coupled with a modified Bayesian information criterion is proposed for candidate change-point selection and further clustering the potential CNV segments to copy number states. Simulations revealed that the modified SaRa became a robust method for identifying change-points and achieved better performance than the circular binary segmentation (CBS) method. By applying the modified SaRa to real data from the HapMap project, we illustrated its performance on detecting CNV segments. In conclusion, our modified SaRa method improves SaRa theoretically and numerically, for identifying CNVs with high-throughput genotyping data. The modSaRa package is implemented in R program and freely available at http://c2s2.yale.edu/software/modSaRa. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Underwater Turbulence Detection Using Gated Wavefront Sensing Technique

PubMed Central

Bi, Ying; Xu, Xiping; Chow, Eddy Mun Tik

2018-01-01

Laser sensing has been applied in various underwater applications, ranging from underwater detection to laser underwater communications. However, there are several great challenges when profiling underwater turbulence effects. Underwater detection is greatly affected by the turbulence effect, where the acquired image suffers excessive noise, blurring, and deformation. In this paper, we propose a novel underwater turbulence detection method based on a gated wavefront sensing technique. First, we elaborate on the operating principle of gated wavefront sensing and wavefront reconstruction. We then setup an experimental system in order to validate the feasibility of our proposed method. The effect of underwater turbulence on detection is examined at different distances, and under different turbulence levels. The experimental results obtained from our gated wavefront sensing system indicate that underwater turbulence can be detected and analyzed. The proposed gated wavefront sensing system has the advantage of a simple structure and high detection efficiency for underwater environments. PMID:29518889

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.

Automated feature extraction in color retinal images by a model based approach.

PubMed

Li, Huiqi; Chutatape, Opas

2004-02-01

Color retinal photography is an important tool to detect the evidence of various eye diseases. Novel methods to extract the main features in color retinal images have been developed in this paper. Principal component analysis is employed to locate optic disk; A modified active shape model is proposed in the shape detection of optic disk; A fundus coordinate system is established to provide a better description of the features in the retinal images; An approach to detect exudates by the combined region growing and edge detection is proposed. The success rates of disk localization, disk boundary detection, and fovea localization are 99%, 94%, and 100%, respectively. The sensitivity and specificity of exudate detection are 100% and 71%, correspondingly. The success of the proposed algorithms can be attributed to the utilization of the model-based methods. The detection and analysis could be applied to automatic mass screening and diagnosis of the retinal diseases.

Objective-lens-free Fiber-based Position Detection with Nanometer Resolution in a Fiber Optical Trapping System.

PubMed

Ti, Chaoyang; Ho-Thanh, Minh-Tri; Wen, Qi; Liu, Yuxiang

2017-10-13

Position detection with high accuracy is crucial for force calibration of optical trapping systems. Most existing position detection methods require high-numerical-aperture objective lenses, which are bulky, expensive, and difficult to miniaturize. Here, we report an affordable objective-lens-free, fiber-based position detection scheme with 2 nm spatial resolution and 150 MHz bandwidth. This fiber based detection mechanism enables simultaneous trapping and force measurements in a compact fiber optical tweezers system. In addition, we achieved more reliable signal acquisition with less distortion compared with objective based position detection methods, thanks to the light guiding in optical fibers and small distance between the fiber tips and trapped particle. As a demonstration of the fiber based detection, we used the fiber optical tweezers to apply a force on a cell membrane and simultaneously measure the cellular response.

Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

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

Abdulbaqi, Hayder Saad; Department of Physics, College of Education, University of Al-Qadisiya, Al-Qadisiya; Jafri, Mohd Zubir Mat

Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introducemore » a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.« less

Application of tetraplex PCR for detection of Vibrio cholerae, V. parahaemolyticus, V. vulnificus and V. mimicus in cockle.

PubMed

Senachai, Pachara; Chomvarin, Chariya; Namwat, Wises; Wongboot, Warawan; Wongwajana, Suwin; Tangkanakul, Waraluk

2013-03-01

A tetraplex PCR method was developed for simultaneous detection of Vibrio cholerae, V. parahaemolyticus, V. vulnificus and V. mimicus in cockle samples in comparison with conventional culture method. Specific primers targeting ompW of V. cholerae, tl of V. parahaemolyticus, hsp60 of V. vulnificus and sodB of V. mimicus were employed in the same PCR. Detection limit of the tetraplex PCR assay was 104 cfu/ml (400 cfu/PCR reaction) for pure cultures of all four species of Vibrio. In Vibrio spiked cockle samples, the limit of detection after 6 hours enrichment in alkaline peptone water was 1 cfu/10 g of cockle tissue for three Vibrio spp, except for V. mimicus that was 102 cfu/10 g of cockle tissue. When the tetraplex PCR and culture methods were applied to 100 cockle samples, V. parahaemolyticus, V. vulnificus, V. cholerae and V. mimicus were detected in 100, 98, 80 and 9% of the samples by tetraplex PCR and in 76, 42, 0 and 0% by the culture method, respectively. This developed tetraplex PCR method should be suitable for simultaneous and rapid detection of Vibrio species in food samples and for food safety assessment.

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images

PubMed Central

Wang, Yuliang; Zhang, Zaicheng; Wang, Huimin; Bi, Shusheng

2015-01-01

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells. PMID:26066315

A method of multiplex PCR for detection of field released Beauveria bassiana, a fungal entomopathogen applied for pest management in jute (Corchorus olitorius).

PubMed

Biswas, Chinmay; Dey, Piyali; Gotyal, B S; Satpathy, Subrata

2015-04-01

The fungal entomopathogen Beauveria bassiana is a promising biocontrol agent for many pests. Some B. bassiana strains have been found effective against jute pests. To monitor the survival of field released B. bassiana a rapid and efficient detection technique is essential. Conventional methods such as plating method or direct culture method which are based on cultivation on selective media followed by microscopy are time consuming and not so sensitive. PCR based methods are rapid, sensitive and reliable. A single primer PCR may fail to amplify some of the strains. However, multiplex PCR increases the possibility of detection as it uses multiple primers. Therefore, in the present investigation a multiplex PCR protocol was developed by multiplexing three primers SCA 14, SCA 15 and SCB 9 to detect field released B. bassiana strains from soil as well as foliage of jute field. Using our multiplex PCR protocol all the five B. bassiana strains could be detected from soil and three strains viz., ITCC 6063, ITCC 4563 and ITCC 4796 could be detected even from the crop foliage after 45 days of spray.

Comparison of traditional and molecular analytical methods for detecting biological agents in raw and drinking water following ultrafiltration

USGS Publications Warehouse

Francy, D.S.; Bushon, R.N.; Brady, A.M.G.; Bertke, E.E.; Kephart, C.M.; Likirdopulos, C.A.; Mailot, B.E.; Schaefer, F. W.; Lindquist, H.D. Alan

2009-01-01

Aims: To compare the performance of traditional methods to quantitative polymerase chain reaction (qPCR) for detecting five biological agents in large-volume drinking-water samples concentrated by ultrafiltration (UF). Methods and Results: Drinking-water samples (100 l) were seeded with Bacillus anthracis, Cryptospordium parvum, Francisella tularensis, Salmonella Typhi, and Vibrio cholerae and concentrated by UF. Recoveries by traditional methods were variable between samples and between some replicates; recoveries were not determined by qPCR. Francisella tularensis and V. cholerae were detected in all 14 samples after UF, B. anthracis was detected in 13, and C. parvum was detected in 9 out of 14 samples. Numbers found by qPCR after UF were significantly or nearly related to those found by traditional methods for all organisms except for C. parvum. A qPCR assay for S. Typhi was not available. Conclusions: qPCR can be used to rapidly detect biological agents after UF as well as traditional methods, but additional work is needed to improve qPCR assays for several biological agents, determine recoveries by qPCR, and expand the study to other areas. Significance and Impact of the Study: To our knowledge, this is the first study to compare the use of traditional and qPCR methods to detect biological agents in large-volume drinking-water samples. ?? 2009 The Society for Applied Microbiology.

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

PubMed Central

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

2014-01-01

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

Real-time PCR detection of Didemnum perlucidum (Monniot, 1983) and Didemnum vexillum (Kott, 2002) in an applied routine marine biosecurity context.

PubMed

Simpson, Tiffany J S; Dias, P Joana; Snow, Michael; Muñoz, Julieta; Berry, Tina

2017-05-01

Prevention and early detection are well recognized as the best strategies for minimizing the risks posed by nonindigenous species (NIS) that have the potential to become marine pests. Central to this is the ability to rapidly and accurately identify the presence of NIS, often from complex environmental samples like biofouling and ballast water. Molecular tools have been increasingly applied to assist with the identification of NIS and can prove particularly useful for taxonomically difficult groups like ascidians. In this study, we have developed real-time PCR assays suited to the specific identification of the ascidians Didemnum perlucidum and Didemnum vexillum. Despite being recognized as important global pests, this is the first time specific molecular detection methods have been developed that can support the early identification and detection of these species from a broad range of environmental sample types. These fast, robust and high-throughput assays represent powerful tools for routine marine biosecurity surveillance, as detection and confirmation of the early presence of species could assist in the timely establishment of emergency responses and control strategies. This study applied the developed assays to confirm the ability to detect Didemnid eDNA in water samples. While previous work has focused on detection of marine larvae from water samples, the development of real-time PCR assays specifically aimed at detecting eDNA of sessile invertebrate species in the marine environment represents a world first and a significant step forwards in applied marine biosecurity surveillance. Demonstrated success in the detection of D. perlucidum eDNA from water samples at sites where it could not be visually identified suggests value in incorporating such assays into biosecurity survey designs targeting Didemnid species. © 2016 John Wiley & Sons Ltd.

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.

PCR-based detection of a rare linear DNA in cell culture.

PubMed

Saveliev, Sergei V.

2002-11-11

The described method allows for detection of rare linear DNA fragments generated during genomic deletions. The predicted limit of the detection is one DNA molecule per 10(7) or more cells. The method is based on anchor PCR and involves gel separation of the linear DNA fragment and chromosomal DNA before amplification. The detailed chemical structure of the ends of the linear DNA can be defined with the use of additional PCR-based protocols. The method was applied to study the short-lived linear DNA generated during programmed genomic deletions in a ciliate. It can be useful in studies of spontaneous DNA deletions in cell culture or for tracking intracellular modifications at the ends of transfected DNA during gene therapy trials.

PCR-based detection of a rare linear DNA in cell culture

PubMed Central

2002-01-01

The described method allows for detection of rare linear DNA fragments generated during genomic deletions. The predicted limit of the detection is one DNA molecule per 107 or more cells. The method is based on anchor PCR and involves gel separation of the linear DNA fragment and chromosomal DNA before amplification. The detailed chemical structure of the ends of the linear DNA can be defined with the use of additional PCR-based protocols. The method was applied to study the short-lived linear DNA generated during programmed genomic deletions in a ciliate. It can be useful in studies of spontaneous DNA deletions in cell culture or for tracking intracellular modifications at the ends of transfected DNA during gene therapy trials. PMID:12734566

Bilinear Time-frequency Analysis for Lamb Wave Signal Detected by Electromagnetic Acoustic Transducer

NASA Astrophysics Data System (ADS)

Sun, Wenxiu; Liu, Guoqiang; Xia, Hui; Xia, Zhengwu

2018-03-01

Accurate acquisition of the detection signal travel time plays a very important role in cross-hole tomography. The experimental platform of aluminum plate under the perpendicular magnetic field is established and the bilinear time-frequency analysis methods, Wigner-Ville Distribution (WVD) and the pseudo-Wigner-Ville distribution (PWVD), are applied to analyse the Lamb wave signals detected by electromagnetic acoustic transducer (EMAT). By extracting the same frequency component of the time-frequency spectrum as the excitation frequency, the travel time information can be obtained. In comparison with traditional linear time-frequency analysis method such as short-time Fourier transform (STFT), the bilinear time-frequency analysis method PWVD is more appropriate in extracting travel time and recognizing patterns of Lamb wave.

Recent advances in chemiluminescence detection coupled with capillary electrophoresis and microchip capillary electrophoresis.

PubMed

Liu, Yuxuan; Huang, Xiangyi; Ren, Jicun

2016-01-01

CE is an ideal analytical method for extremely volume-limited biological microenvironments. However, the small injection volume makes it a challenge to achieve highly sensitive detection. Chemiluminescence (CL) detection is characterized by providing low background with excellent sensitivity because of requiring no light source. The coupling of CL with CE and MCE has become a powerful analytical method. So far, this method has been widely applied to chemical analysis, bioassay, drug analysis, and environment analysis. In this review, we first introduce some developments for CE-CL and MCE-CL systems, and then put the emphasis on the applications in the last 10 years. Finally, we discuss the future prospects. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Wear Detection of Drill Bit by Image-based Technique

NASA Astrophysics Data System (ADS)

Sukeri, Maziyah; Zulhilmi Paiz Ismadi, Mohd; Rahim Othman, Abdul; Kamaruddin, Shahrul

2018-03-01

Image processing for computer vision function plays an essential aspect in the manufacturing industries for the tool condition monitoring. This study proposes a dependable direct measurement method to measure the tool wear using image-based analysis. Segmentation and thresholding technique were used as the means to filter and convert the colour image to binary datasets. Then, the edge detection method was applied to characterize the edge of the drill bit. By using cross-correlation method, the edges of original and worn drill bits were correlated to each other. Cross-correlation graphs were able to detect the difference of the worn edge despite small difference between the graphs. Future development will focus on quantifying the worn profile as well as enhancing the sensitivity of the technique.

Extraction and Determination of Cyproheptadine in Human Urine by DLLME-HPLC Method.

PubMed

Maham, Mehdi; Kiarostami, Vahid; Waqif-Husain, Syed; Abroomand-Azar, Parviz; Tehrani, Mohammad Saber; Khoeini Sharifabadi, Malihe; Afrouzi, Hossein; Shapouri, Mahmoudreza; Karami-Osboo, Rouhollah

2013-01-01

Novel dispersive liquid-liquid microextraction (DLLME), coupled with high performance liquid chromatography with photodiode array detection (HPLC-DAD) has been applied for the extraction and determination of cyproheptadine (CPH), an antihistamine, in human urine samples. In this method, 0.6 mL of acetonitrile (disperser solvent) containing 30 μL of carbon tetrachloride (extraction solvent) was rapidly injected by a syringe into 5 mL urine sample. After centrifugation, the sedimented phase containing enriched analyte was dissolved in acetonitrile and an aliquot of this solution injected into the HPLC system for analysis. Development of DLLME procedure includes optimization of some important parameters such as kind and volume of extraction and disperser solvent, pH and salt addition. The proposed method has good linearity in the range of 0.02-4.5 μg mL(-1) and low detection limit (13.1 ng mL(-1)). The repeatability of the method, expressed as relative standard deviation was 4.9% (n = 3). This method has also been applied to the analysis of real urine samples with satisfactory relative recoveries in the range of 91.6-101.0%.

Nondestructive online testing method for friction stir welding using acoustic emission

NASA Astrophysics Data System (ADS)

Levikhina, Anastasiya

2017-12-01

The paper reviews the possibility of applying the method of acoustic emission for online monitoring of the friction stir welding process. It is shown that acoustic emission allows the detection of weld defects and their location in real time. The energy of an acoustic signal and the median frequency are suggested to be used as informative parameters. The method of calculating the median frequency with the use of a short time Fourier transform is applied for the identification of correlations between the defective weld structure and properties of the acoustic emission signals received during welding.

A method for the detection of the refractive index of irregular shape solid pigments in light absorbing liquid matrix.

PubMed

Niskanen, Ilpo; Räty, Jukka; Peiponen, Kai-Erik

2010-06-15

The immersion liquid method is powerful for the measurement of the refractive index of solid particles in a liquid matrix. However, this method applies best for cases when the liquid matrix is transparent. A problem is usually how to assess the refractive index of a pigment when it is in a colored host liquid. In this article we introduce a method, and show that by combining so-called multifunction spectrophotometer, immersion liquid method and detection of light transmission and reflection we can assess the refractive index of a pigment in a colored liquid, and also the extinction or absorption coefficient of the host liquid.

Using Thermal Radiation in Detection of Negative Obstacles

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.; Matthies, Larry H.

2009-01-01

A method of automated detection of negative obstacles (potholes, ditches, and the like) ahead of ground vehicles at night involves processing of imagery from thermal-infrared cameras aimed at the terrain ahead of the vehicles. The method is being developed as part of an overall obstacle-avoidance scheme for autonomous and semi-autonomous offroad robotic vehicles. The method could also be applied to help human drivers of cars and trucks avoid negative obstacles -- a development that may entail only modest additional cost inasmuch as some commercially available passenger cars are already equipped with infrared cameras as aids for nighttime operation.

Molecular Methods for the Detection of Mycoplasma and Ureaplasma Infections in Humans

PubMed Central

Waites, Ken B.; Xiao, Li; Paralanov, Vanya; Viscardi, Rose M.; Glass, John I.

2012-01-01

Mycoplasma and Ureaplasma species are well-known human pathogens responsible for a broad array of inflammatory conditions involving the respiratory and urogenital tracts of neonates, children, and adults. Greater attention is being given to these organisms in diagnostic microbiology, largely as a result of improved methods for their laboratory detection, made possible by powerful molecular-based techniques that can be used for primary detection in clinical specimens. For slow-growing species, such as Mycoplasma pneumoniae and Mycoplasma genitalium, molecular-based detection is the only practical means for rapid microbiological diagnosis. Most molecular-based methods used for detection and characterization of conventional bacteria have been applied to these organisms. A complete genome sequence is available for one or more strains of all of the important human pathogens in the Mycoplasma and Ureaplasma genera. Information gained from genome analyses and improvements in efficiency of DNA sequencing are expected to significantly advance the field of molecular detection and genotyping during the next few years. This review provides a summary and critical review of methods suitable for detection and characterization of mycoplasmas and ureaplasmas of humans, with emphasis on molecular genotypic techniques. PMID:22819362

Imaging of underground karst water channels using an improved multichannel transient Rayleigh wave detecting method

PubMed Central

Zheng, Xuhui; Liu, Lei; Li, Gao; Zhou, Fubiao; Xu, Jiemin

2018-01-01

Geological and hydrogeological conditions in karst areas are complicated from the viewpoint of engineering. The construction of underground structures in these areas is often disturbed by the gushing of karst water, which may delay the construction schedule, result in economic losses, and even cause heavy casualties. In this paper, an innovative method of multichannel transient Rayleigh wave detecting is proposed by introducing the concept of arrival time difference phase between channels (TDP). Overcoming the restriction of the space-sampling law, the proposed method can extract the phase velocities of different frequency components from only two channels of transient Rayleigh wave recorded on two adjacent detecting points. This feature greatly improves the work efficiency and lateral resolution of transient Rayleigh wave detecting. The improved multichannel transient Rayleigh wave detecting method is applied to the detection of karst caves and fractures in rock mass of the foundation pit of Yan’an Road Station of Guiyang Metro. The imaging of the detecting results clearly reveals the distribution of karst water inflow channels, which provided significant guidance for water plugging and enabled good control over karst water gushing in the foundation pit. PMID:29883492

Imaging of underground karst water channels using an improved multichannel transient Rayleigh wave detecting method.

PubMed

Zheng, Xuhui; Liu, Lei; Sun, Jinzhong; Li, Gao; Zhou, Fubiao; Xu, Jiemin

2018-01-01

Geological and hydrogeological conditions in karst areas are complicated from the viewpoint of engineering. The construction of underground structures in these areas is often disturbed by the gushing of karst water, which may delay the construction schedule, result in economic losses, and even cause heavy casualties. In this paper, an innovative method of multichannel transient Rayleigh wave detecting is proposed by introducing the concept of arrival time difference phase between channels (TDP). Overcoming the restriction of the space-sampling law, the proposed method can extract the phase velocities of different frequency components from only two channels of transient Rayleigh wave recorded on two adjacent detecting points. This feature greatly improves the work efficiency and lateral resolution of transient Rayleigh wave detecting. The improved multichannel transient Rayleigh wave detecting method is applied to the detection of karst caves and fractures in rock mass of the foundation pit of Yan'an Road Station of Guiyang Metro. The imaging of the detecting results clearly reveals the distribution of karst water inflow channels, which provided significant guidance for water plugging and enabled good control over karst water gushing in the foundation pit.

Limb locomotion--speed distribution analysis as a new method for stance phase detection.

PubMed

Peham, C; Scheidl, M; Licka, T

1999-10-01

The stance phase is used for the determination of many parameters in motion analysis. In this technical note the authors present a new kinematical method for determination of stance phase. From the high-speed video data, the speed distribution of the horizontal motion of the distal limb is calculated. The speed with the maximum occurrence within the motion cycle defines the stance phase, and this speed is used as threshold for beginning and end of the stance phase. In seven horses the results obtained with the presented method were compared to synchronous stance phase determination using a force plate integrated in a hard track. The mean difference between the results was 10.8 ms, equalling 1.44% of mean stance phase duration. As a test, the presented method was applied to a horse trotting on the treadmill, and to a human walking on concrete. This article describes an easy and safe method for stance phase determination in continuous kinematic data and proves the reliability of the method by comparing it to kinetic stance phase detection. This method may be applied in several species and all gaits, on the treadmill and on firm ground.

Spoof Detection for Finger-Vein Recognition System Using NIR Camera.

PubMed

Nguyen, Dat Tien; Yoon, Hyo Sik; Pham, Tuyen Danh; Park, Kang Ryoung

2017-10-01

Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake) finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD), is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor) based on the observations of the researchers about the difference between real (live) and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR) camera-based finger-vein recognition system using convolutional neural network (CNN) to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA) for dimensionality reduction of feature space and support vector machine (SVM) for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared to CNN-based methods and other previous handcrafted methods.

Spoof Detection for Finger-Vein Recognition System Using NIR Camera

PubMed Central

Nguyen, Dat Tien; Yoon, Hyo Sik; Pham, Tuyen Danh; Park, Kang Ryoung

2017-01-01

Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake) finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD), is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor) based on the observations of the researchers about the difference between real (live) and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR) camera-based finger-vein recognition system using convolutional neural network (CNN) to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA) for dimensionality reduction of feature space and support vector machine (SVM) for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared to CNN-based methods and other previous handcrafted methods. PMID:28974031

An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System

PubMed Central

Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

2017-01-01

In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequency-domain and achieves computational complexity reduction. PMID:28230763

Sensitive DNA detection and SNP discrimination using ultrabright SERS nanorattles and magnetic beads for malaria diagnostics.

PubMed

Ngo, Hoan T; Gandra, Naveen; Fales, Andrew M; Taylor, Steve M; Vo-Dinh, Tuan

2016-07-15

One of the major obstacles to implement nucleic acid-based molecular diagnostics at the point-of-care (POC) and in resource-limited settings is the lack of sensitive and practical DNA detection methods that can be seamlessly integrated into portable platforms. Herein we present a sensitive yet simple DNA detection method using a surface-enhanced Raman scattering (SERS) nanoplatform: the ultrabright SERS nanorattle. The method, referred to as the nanorattle-based method, involves sandwich hybridization of magnetic beads that are loaded with capture probes, target sequences, and ultrabright SERS nanorattles that are loaded with reporter probes. Upon hybridization, a magnet was applied to concentrate the hybridization sandwiches at a detection spot for SERS measurements. The ultrabright SERS nanorattles, composed of a core and a shell with resonance Raman reporters loaded in the gap space between the core and the shell, serve as SERS tags for signal detection. Using this method, a specific DNA sequence of the malaria parasite Plasmodium falciparum could be detected with a detection limit of approximately 100 attomoles. Single nucleotide polymorphism (SNP) discrimination of wild type malaria DNA and mutant malaria DNA, which confers resistance to artemisinin drugs, was also demonstrated. These test models demonstrate the molecular diagnostic potential of the nanorattle-based method to both detect and genotype infectious pathogens. Furthermore, the method's simplicity makes it a suitable candidate for integration into portable platforms for POC and in resource-limited settings applications. Copyright © 2016. Published by Elsevier B.V.