Immunocapture reverse transcription-polymerase chain reaction combined with nested PCR greatly increases the detection of Prunus necrotic ring spot virus in the peach.

PubMed

Helguera, P R; Taborda, R; Docampo, D M; Ducasse, D A

2001-06-01

A detection system based on nested PCR after IC-RT-PCR (IC-RT-PCR-Nested PCR) was developed to improve indexing of Prunus necrotic ringspot virus in peach trees. Inhibitory effects and inconsistencies of the standard IC-RT-PCR were overcome by this approach. IC-RT-PCR-Nested PCR improved detection by three orders of magnitude compared with DAS-ELISA for the detection of PNRSV in leaves. Several different tissues were evaluated and equally consistent results were observed. The main advantages of the method are its consistency, high sensitivity and easy application in quarantine programs.

Testing the consistency of wildlife data types before combining them: the case of camera traps and telemetry.

PubMed

Popescu, Viorel D; Valpine, Perry; Sweitzer, Rick A

2014-04-01

Wildlife data gathered by different monitoring techniques are often combined to estimate animal density. However, methods to check whether different types of data provide consistent information (i.e., can information from one data type be used to predict responses in the other?) before combining them are lacking. We used generalized linear models and generalized linear mixed-effects models to relate camera trap probabilities for marked animals to independent space use from telemetry relocations using 2 years of data for fishers (Pekania pennanti) as a case study. We evaluated (1) camera trap efficacy by estimating how camera detection probabilities are related to nearby telemetry relocations and (2) whether home range utilization density estimated from telemetry data adequately predicts camera detection probabilities, which would indicate consistency of the two data types. The number of telemetry relocations within 250 and 500 m from camera traps predicted detection probability well. For the same number of relocations, females were more likely to be detected during the first year. During the second year, all fishers were more likely to be detected during the fall/winter season. Models predicting camera detection probability and photo counts solely from telemetry utilization density had the best or nearly best Akaike Information Criterion (AIC), suggesting that telemetry and camera traps provide consistent information on space use. Given the same utilization density, males were more likely to be photo-captured due to larger home ranges and higher movement rates. Although methods that combine data types (spatially explicit capture-recapture) make simple assumptions about home range shapes, it is reasonable to conclude that in our case, camera trap data do reflect space use in a manner consistent with telemetry data. However, differences between the 2 years of data suggest that camera efficacy is not fully consistent across ecological conditions and make the case for integrating other sources of space-use data.

Multimodal Event Detection in Twitter Hashtag Networks

DOE PAGES

Yilmaz, Yasin; Hero, Alfred O.

2016-07-01

In this study, event detection in a multimodal Twitter dataset is considered. We treat the hashtags in the dataset as instances with two modes: text and geolocation features. The text feature consists of a bag-of-words representation. The geolocation feature consists of geotags (i.e., geographical coordinates) of the tweets. Fusing the multimodal data we aim to detect, in terms of topic and geolocation, the interesting events and the associated hashtags. To this end, a generative latent variable model is assumed, and a generalized expectation-maximization (EM) algorithm is derived to learn the model parameters. The proposed method is computationally efficient, and lendsmore » itself to big datasets. Lastly, experimental results on a Twitter dataset from August 2014 show the efficacy of the proposed method.« less

Automatic segmentation of fluorescence lifetime microscopy images of cells using multiresolution community detection--a first study.

PubMed

Hu, D; Sarder, P; Ronhovde, P; Orthaus, S; Achilefu, S; Nussinov, Z

2014-01-01

Inspired by a multiresolution community detection based network segmentation method, we suggest an automatic method for segmenting fluorescence lifetime (FLT) imaging microscopy (FLIM) images of cells in a first pilot investigation on two selected images. The image processing problem is framed as identifying segments with respective average FLTs against the background in FLIM images. The proposed method segments a FLIM image for a given resolution of the network defined using image pixels as the nodes and similarity between the FLTs of the pixels as the edges. In the resulting segmentation, low network resolution leads to larger segments, and high network resolution leads to smaller segments. Furthermore, using the proposed method, the mean-square error in estimating the FLT segments in a FLIM image was found to consistently decrease with increasing resolution of the corresponding network. The multiresolution community detection method appeared to perform better than a popular spectral clustering-based method in performing FLIM image segmentation. At high resolution, the spectral segmentation method introduced noisy segments in its output, and it was unable to achieve a consistent decrease in mean-square error with increasing resolution. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Bisulfite-independent analysis of CpG island methylation enables genome-scale stratification of single cells.

PubMed

Han, Lin; Wu, Hua-Jun; Zhu, Haiying; Kim, Kun-Yong; Marjani, Sadie L; Riester, Markus; Euskirchen, Ghia; Zi, Xiaoyuan; Yang, Jennifer; Han, Jasper; Snyder, Michael; Park, In-Hyun; Irizarry, Rafael; Weissman, Sherman M; Michor, Franziska; Fan, Rong; Pan, Xinghua

2017-06-02

Conventional DNA bisulfite sequencing has been extended to single cell level, but the coverage consistency is insufficient for parallel comparison. Here we report a novel method for genome-wide CpG island (CGI) methylation sequencing for single cells (scCGI-seq), combining methylation-sensitive restriction enzyme digestion and multiple displacement amplification for selective detection of methylated CGIs. We applied this method to analyzing single cells from two types of hematopoietic cells, K562 and GM12878 and small populations of fibroblasts and induced pluripotent stem cells. The method detected 21 798 CGIs (76% of all CGIs) per cell, and the number of CGIs consistently detected from all 16 profiled single cells was 20 864 (72.7%), with 12 961 promoters covered. This coverage represents a substantial improvement over results obtained using single cell reduced representation bisulfite sequencing, with a 66-fold increase in the fraction of consistently profiled CGIs across individual cells. Single cells of the same type were more similar to each other than to other types, but also displayed epigenetic heterogeneity. The method was further validated by comparing the CpG methylation pattern, methylation profile of CGIs/promoters and repeat regions and 41 classes of known regulatory markers to the ENCODE data. Although not every minor methylation differences between cells are detectable, scCGI-seq provides a solid tool for unsupervised stratification of a heterogeneous cell population. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Median Filtering Methods for Non-volcanic Tremor Detection

NASA Astrophysics Data System (ADS)

Damiao, L. G.; Nadeau, R. M.; Dreger, D. S.; Luna, B.; Zhang, H.

2016-12-01

Various properties of median filtering over time and space are used to address challenges posed by the Non-volcanic tremor detection problem. As part of a "Big-Data" effort to characterize the spatial and temporal distribution of ambient tremor throughout the Northern San Andreas Fault system, continuous seismic data from multiple seismic networks with contrasting operational characteristics and distributed over a variety of regions are being used. Automated median filtering methods that are flexible enough to work consistently with these data are required. Tremor is characterized by a low-amplitude, long-duration signal-train whose shape is coherent at multiple stations distributed over a large area. There are no consistent phase arrivals or mechanisms in a given tremor's signal and even the durations and shapes among different tremors vary considerably. A myriad of masquerading noise, anthropogenic and natural-event signals must also be discriminated in order to obtain accurate tremor detections. We present here results of the median methods applied to data from four regions of the San Andreas Fault system in northern California (Geysers Geothermal Field, Napa, Bitterwater and Parkfield) to illustrate the ability of the methods to detect tremor under diverse conditions.

Differential Characteristics Based Iterative Multiuser Detection for Wireless Sensor Networks

PubMed Central

Chen, Xiaoguang; Jiang, Xu; Wu, Zhilu; Zhuang, Shufeng

2017-01-01

High throughput, low latency and reliable communication has always been a hot topic for wireless sensor networks (WSNs) in various applications. Multiuser detection is widely used to suppress the bad effect of multiple access interference in WSNs. In this paper, a novel multiuser detection method based on differential characteristics is proposed to suppress multiple access interference. The proposed iterative receive method consists of three stages. Firstly, a differential characteristics function is presented based on the optimal multiuser detection decision function; then on the basis of differential characteristics, a preliminary threshold detection is utilized to find the potential wrongly received bits; after that an error bit corrector is employed to correct the wrong bits. In order to further lower the bit error ratio (BER), the differential characteristics calculation, threshold detection and error bit correction process described above are iteratively executed. Simulation results show that after only a few iterations the proposed multiuser detection method can achieve satisfactory BER performance. Besides, BER and near far resistance performance are much better than traditional suboptimal multiuser detection methods. Furthermore, the proposed iterative multiuser detection method also has a large system capacity. PMID:28212328

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

PubMed

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

2018-03-01

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

Detection of protein complex from protein-protein interaction network using Markov clustering

NASA Astrophysics Data System (ADS)

Ochieng, P. J.; Kusuma, W. A.; Haryanto, T.

2017-05-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks.

Real-time anomaly detection for very short-term load forecasting

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

Luo, Jian; Hong, Tao; Yue, Meng

Although the recent load information is critical to very short-term load forecasting (VSTLF), power companies often have difficulties in collecting the most recent load values accurately and timely for VSTLF applications. This paper tackles the problem of real-time anomaly detection in most recent load information used by VSTLF. This paper proposes a model-based anomaly detection method that consists of two components, a dynamic regression model and an adaptive anomaly threshold. The case study is developed using the data from ISO New England. This paper demonstrates that the proposed method significantly outperforms three other anomaly detection methods including two methods commonlymore » used in the field and one state-of-the-art method used by a winning team of the Global Energy Forecasting Competition 2014. Lastly, a general anomaly detection framework is proposed for the future research.« less

Real-time anomaly detection for very short-term load forecasting

DOE PAGES

Luo, Jian; Hong, Tao; Yue, Meng

2018-01-06

Although the recent load information is critical to very short-term load forecasting (VSTLF), power companies often have difficulties in collecting the most recent load values accurately and timely for VSTLF applications. This paper tackles the problem of real-time anomaly detection in most recent load information used by VSTLF. This paper proposes a model-based anomaly detection method that consists of two components, a dynamic regression model and an adaptive anomaly threshold. The case study is developed using the data from ISO New England. This paper demonstrates that the proposed method significantly outperforms three other anomaly detection methods including two methods commonlymore » used in the field and one state-of-the-art method used by a winning team of the Global Energy Forecasting Competition 2014. Lastly, a general anomaly detection framework is proposed for the future research.« less

A rapid screen for four corticosteroids in equine synovial fluid.

PubMed

Agrawal, Karan; Ebel, Joseph G; Bischoff, Karyn

2014-06-01

Most antidoping method development in the equine industry has been for plasma and urine, though there has been recent interest in the analysis of synovial fluid for evidence of doping by intra-articular corticosteroid injection. Published methods for corticosteroid analysis in synovial fluid are primarily singleplex methods, do not screen for all corticosteroids of interest and are not adequately sensitive. The purpose of this study is to develop a rapid and sensitive liquid chromatography-tandem mass spectrometry (LC-MS-MS) screening method for the detection of four of the most common intra-articularly administered corticosteroids--betamethasone, methylprednisolone, methylprednisolone acetate and triamcinolone acetonide. Sample preparation consisted of protein precipitation followed by a basified liquid-liquid extraction. LC-MS-MS experiments consisted of a six-min isocratic separation using a Phenomenex Polar-RP stationary phase and a mobile phase consisting of 35% acetonitrile, 5 mM ammonium acetate and 0.1% formic acid in nanopure water. The detection system used was a triple quadrupole mass analyzer with thermospray ionization, and compounds were identified using selective reaction monitoring. The method was validated to the ISO/IEC 17025 standard, and real synovial fluid samples were analyzed to demonstrate the application of the method in an antidoping context. The method was highly selective for the four corticosteroids with limits of detection of 1-3 ng/mL. The extraction efficiency was 50-101%, and the matrix effects were 14-31%. These results indicate that the method is a rapid and sensitive screen for the four corticosteroids in equine synovial fluid, fit for purpose for equine antidoping assays.

Detection and analysis of protein ISGylation.

PubMed

Takeuchi, Tomoharu; Yokosawa, Hideyoshi

2008-01-01

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

Verification of the new detection method for irradiated spices based on microbial survival by collaborative blind trial

NASA Astrophysics Data System (ADS)

Miyahara, M.; Furuta, M.; Takekawa, T.; Oda, S.; Koshikawa, T.; Akiba, T.; Mori, T.; Mimura, T.; Sawada, C.; Yamaguchi, T.; Nishioka, S.; Tada, M.

2009-07-01

An irradiation detection method using the difference of the radiation sensitivity of the heat-treated microorganisms was developed as one of the microbiological detection methods of the irradiated foods. This detection method is based on the difference of the viable cell count before and after heat treatment (70 °C and 10 min). The verification by collaborative blind trial of this method was done by nine inspecting agencies in Japan. The samples used for this trial were five kinds of spices consisting of non-irradiated, 5 kGy irradiated, and 7 kGy irradiated black pepper, allspice, oregano, sage, and paprika, respectively. As a result of this collaboration, a high percentage (80%) of the correct answers was obtained for irradiated black pepper and allspice. However, the method was less successful for irradiated oregano, sage, and paprika. It might be possible to use this detection method for preliminary screening of the irradiated foods but further work is necessary to confirm these findings.

Infrared target tracking via weighted correlation filter

NASA Astrophysics Data System (ADS)

He, Yu-Jie; Li, Min; Zhang, JinLi; Yao, Jun-Ping

2015-11-01

Design of an effective target tracker is an important and challenging task for many applications due to multiple factors which can cause disturbance in infrared video sequences. In this paper, an infrared target tracking method under tracking by detection framework based on a weighted correlation filter is presented. This method consists of two parts: detection and filtering. For the detection stage, we propose a sequential detection method for the infrared target based on low-rank representation. For the filtering stage, a new multi-feature weighted function which fuses different target features is proposed, which takes the importance of the different regions into consideration. The weighted function is then incorporated into a correlation filter to compute a confidence map more accurately, in order to indicate the best target location based on the detection results obtained from the first stage. Extensive experimental results on different video sequences demonstrate that the proposed method performs favorably for detection and tracking compared with baseline methods in terms of efficiency and accuracy.

Validation of quantitative and qualitative methods for detecting allergenic ingredients in processed foods in Japan.

PubMed

Sakai, Shinobu; Adachi, Reiko; Akiyama, Hiroshi; Teshima, Reiko

2013-06-19

A labeling system for food allergenic ingredients was established in Japan in April 2002. To monitor the labeling, the Japanese government announced official methods for detecting allergens in processed foods in November 2002. The official methods consist of quantitative screening tests using enzyme-linked immunosorbent assays (ELISAs) and qualitative confirmation tests using Western blotting or polymerase chain reactions (PCR). In addition, the Japanese government designated 10 μg protein/g food (the corresponding allergenic ingredient soluble protein weight/food weight), determined by ELISA, as the labeling threshold. To standardize the official methods, the criteria for the validation protocol were described in the official guidelines. This paper, which was presented at the Advances in Food Allergen Detection Symposium, ACS National Meeting and Expo, San Diego, CA, Spring 2012, describes the validation protocol outlined in the official Japanese guidelines, the results of interlaboratory studies for the quantitative detection method (ELISA for crustacean proteins) and the qualitative detection method (PCR for shrimp and crab DNAs), and the reliability of the detection methods.

Development of new structural health monitoring techniques

NASA Astrophysics Data System (ADS)

Fekrmandi, Hadi

During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations. A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time. Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop -- DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.

High precision automated face localization in thermal images: oral cancer dataset as test case

NASA Astrophysics Data System (ADS)

Chakraborty, M.; Raman, S. K.; Mukhopadhyay, S.; Patsa, S.; Anjum, N.; Ray, J. G.

2017-02-01

Automated face detection is the pivotal step in computer vision aided facial medical diagnosis and biometrics. This paper presents an automatic, subject adaptive framework for accurate face detection in the long infrared spectrum on our database for oral cancer detection consisting of malignant, precancerous and normal subjects of varied age group. Previous works on oral cancer detection using Digital Infrared Thermal Imaging(DITI) reveals that patients and normal subjects differ significantly in their facial thermal distribution. Therefore, it is a challenging task to formulate a completely adaptive framework to veraciously localize face from such a subject specific modality. Our model consists of first extracting the most probable facial regions by minimum error thresholding followed by ingenious adaptive methods to leverage the horizontal and vertical projections of the segmented thermal image. Additionally, the model incorporates our domain knowledge of exploiting temperature difference between strategic locations of the face. To our best knowledge, this is the pioneering work on detecting faces in thermal facial images comprising both patients and normal subjects. Previous works on face detection have not specifically targeted automated medical diagnosis; face bounding box returned by those algorithms are thus loose and not apt for further medical automation. Our algorithm significantly outperforms contemporary face detection algorithms in terms of commonly used metrics for evaluating face detection accuracy. Since our method has been tested on challenging dataset consisting of both patients and normal subjects of diverse age groups, it can be seamlessly adapted in any DITI guided facial healthcare or biometric applications.

Multiple particle tracking in 3-D+t microscopy: method and application to the tracking of endocytosed quantum dots.

PubMed

Genovesio, Auguste; Liedl, Tim; Emiliani, Valentina; Parak, Wolfgang J; Coppey-Moisan, Maité; Olivo-Marin, Jean-Christophe

2006-05-01

We propose a method to detect and track multiple moving biological spot-like particles showing different kinds of dynamics in image sequences acquired through multidimensional fluorescence microscopy. It enables the extraction and analysis of information such as number, position, speed, movement, and diffusion phases of, e.g., endosomal particles. The method consists of several stages. After a detection stage performed by a three-dimensional (3-D) undecimated wavelet transform, we compute, for each detected spot, several predictions of its future state in the next frame. This is accomplished thanks to an interacting multiple model (IMM) algorithm which includes several models corresponding to different biologically realistic movement types. Tracks are constructed, thereafter, by a data association algorithm based on the maximization of the likelihood of each IMM. The last stage consists of updating the IMM filters in order to compute final estimations for the present image and to improve predictions for the next image. The performances of the method are validated on synthetic image data and used to characterize the 3-D movement of endocytic vesicles containing quantum dots.

Methods and apparatus for rotor blade ice detection

DOEpatents

LeMieux, David Lawrence

2006-08-08

A method for detecting ice on a wind turbine having a rotor and one or more rotor blades each having blade roots includes monitoring meteorological conditions relating to icing conditions and monitoring one or more physical characteristics of the wind turbine in operation that vary in accordance with at least one of the mass of the one or more rotor blades or a mass imbalance between the rotor blades. The method also includes using the one or more monitored physical characteristics to determine whether a blade mass anomaly exists, determining whether the monitored meteorological conditions are consistent with blade icing; and signaling an icing-related blade mass anomaly when a blade mass anomaly is determined to exist and the monitored meteorological conditions are determined to be consistent with icing.

Statistical Methods for Generalized Linear Models with Covariates Subject to Detection Limits.

PubMed

Bernhardt, Paul W; Wang, Huixia J; Zhang, Daowen

2015-05-01

Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study.

Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein⁻Protein Interaction Network.

PubMed

Cao, Buwen; Deng, Shuguang; Qin, Hua; Ding, Pingjian; Chen, Shaopeng; Li, Guanghui

2018-06-15

High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein⁻protein interaction (PPI) networks. In this study, based on penalized matrix decomposition ( PMD ), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMD pc ) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMD pc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR).

CRYPTOSPORIDIUM OOCYST RECOVERY IN WATER BY EPA METHOD 1623: EVALUATION OF A MODIFIED IMS DISSOCIATION

EPA Science Inventory

EPA Methods 1622 and 1623 are the benchmarks for detection of Cryptosporidium spp. oocysts in water. These methods consist of filtration, elution, purification by immunomagnetic separation (IMS), and microscopic analysis after staining with a fluorescein isothiocyanate conjugate...

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.

Measurement Consistency from Magnetic Resonance Images

PubMed Central

Chung, Dongjun; Chung, Moo K.; Durtschi, Reid B.; Lindell, R. Gentry; Vorperian, Houri K.

2010-01-01

Rationale and Objectives In quantifying medical images, length-based measurements are still obtained manually. Due to possible human error, a measurement protocol is required to guarantee the consistency of measurements. In this paper, we review various statistical techniques that can be used in determining measurement consistency. The focus is on detecting a possible measurement bias and determining the robustness of the procedures to outliers. Materials and Methods We review correlation analysis, linear regression, Bland-Altman method, paired t-test, and analysis of variance (ANOVA). These techniques were applied to measurements, obtained by two raters, of head and neck structures from magnetic resonance images (MRI). Results The correlation analysis and the linear regression were shown to be insufficient for detecting measurement inconsistency. They are also very sensitive to outliers. The widely used Bland-Altman method is a visualization technique so it lacks the numerical quantification. The paired t-test tends to be sensitive to small measurement bias. On the other hand, ANOVA performs well even under small measurement bias. Conclusion In almost all cases, using only one method is insufficient and it is recommended to use several methods simultaneously. In general, ANOVA performs the best. PMID:18790405

The reliability and internal consistency of one-shot and flicker change detection for measuring individual differences in visual working memory capacity.

PubMed

Pailian, Hrag; Halberda, Justin

2015-04-01

We investigated the psychometric properties of the one-shot change detection task for estimating visual working memory (VWM) storage capacity-and also introduced and tested an alternative flicker change detection task for estimating these limits. In three experiments, we found that the one-shot whole-display task returns estimates of VWM storage capacity (K) that are unreliable across set sizes-suggesting that the whole-display task is measuring different things at different set sizes. In two additional experiments, we found that the one-shot single-probe variant shows improvements in the reliability and consistency of K estimates. In another additional experiment, we found that a one-shot whole-display-with-click task (requiring target localization) also showed improvements in reliability and consistency. The latter results suggest that the one-shot task can return reliable and consistent estimates of VWM storage capacity (K), and they highlight the possibility that the requirement to localize the changed target is what engenders this enhancement. Through a final series of four experiments, we introduced and tested an alternative flicker change detection method that also requires the observer to localize the changing target and that generates, from response times, an estimate of VWM storage capacity (K). We found that estimates of K from the flicker task correlated with estimates from the traditional one-shot task and also had high reliability and consistency. We highlight the flicker method's ability to estimate executive functions as well as VWM storage capacity, and discuss the potential for measuring multiple abilities with the one-shot and flicker tasks.

Reference point detection for camera-based fingerprint image based on wavelet transformation.

PubMed

Khalil, Mohammed S

2015-04-30

Fingerprint recognition systems essentially require core-point detection prior to fingerprint matching. The core-point is used as a reference point to align the fingerprint with a template database. When processing a larger fingerprint database, it is necessary to consider the core-point during feature extraction. Numerous core-point detection methods are available and have been reported in the literature. However, these methods are generally applied to scanner-based images. Hence, this paper attempts to explore the feasibility of applying a core-point detection method to a fingerprint image obtained using a camera phone. The proposed method utilizes a discrete wavelet transform to extract the ridge information from a color image. The performance of proposed method is evaluated in terms of accuracy and consistency. These two indicators are calculated automatically by comparing the method's output with the defined core points. The proposed method is tested on two data sets, controlled and uncontrolled environment, collected from 13 different subjects. In the controlled environment, the proposed method achieved a detection rate 82.98%. In uncontrolled environment, the proposed method yield a detection rate of 78.21%. The proposed method yields promising results in a collected-image database. Moreover, the proposed method outperformed compare to existing method.

[Significance of bacteria detection with filter paper method on diagnosis of diabetic foot wound infection].

PubMed

Zou, X H; Zhu, Y P; Ren, G Q; Li, G C; Zhang, J; Zou, L J; Feng, Z B; Li, B H

2017-02-20

Objective: To evaluate the significance of bacteria detection with filter paper method on diagnosis of diabetic foot wound infection. Methods: Eighteen patients with diabetic foot ulcer conforming to the study criteria were hospitalized in Liyuan Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology from July 2014 to July 2015. Diabetic foot ulcer wounds were classified according to the University of Texas diabetic foot classification (hereinafter referred to as Texas grade) system, and general condition of patients with wounds in different Texas grade was compared. Exudate and tissue of wounds were obtained, and filter paper method and biopsy method were adopted to detect the bacteria of wounds of patients respectively. Filter paper method was regarded as the evaluation method, and biopsy method was regarded as the control method. The relevance, difference, and consistency of the detection results of two methods were tested. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of filter paper method in bacteria detection were calculated. Receiver operating characteristic (ROC) curve was drawn based on the specificity and sensitivity of filter paper method in bacteria detection of 18 patients to predict the detection effect of the method. Data were processed with one-way analysis of variance and Fisher's exact test. In patients tested positive for bacteria by biopsy method, the correlation between bacteria number detected by biopsy method and that by filter paper method was analyzed with Pearson correlation analysis. Results: (1) There were no statistically significant differences among patients with wounds in Texas grade 1, 2, and 3 in age, duration of diabetes, duration of wound, wound area, ankle brachial index, glycosylated hemoglobin, fasting blood sugar, blood platelet count, erythrocyte sedimentation rate, C-reactive protein, aspartate aminotransferase, serum creatinine, and urea nitrogen (with F values from 0.029 to 2.916, P values above 0.05), while there were statistically significant differences among patients with wounds in Texas grade 1, 2, and 3 in white blood cell count and alanine aminotransferase (with F values 4.688 and 6.833 respectively, P <0.05 or P <0.01). (2) According to the results of biopsy method, 6 patients were tested negative for bacteria, and 12 patients were tested positive for bacteria, among which 10 patients were with bacterial number above 1×10(5)/g, and 2 patients with bacterial number below 1×10(5)/g. According to the results of filter paper method, 8 patients were tested negative for bacteria, and 10 patients were tested positive for bacteria, among which 7 patients were with bacterial number above 1×10(5)/g, and 3 patients with bacterial number below 1×10(5)/g. There were 7 patients tested positive for bacteria both by biopsy method and filter paper method, 8 patients tested negative for bacteria both by biopsy method and filter paper method, and 3 patients tested positive for bacteria by biopsy method but negative by filter paper method. Patients tested negative for bacteria by biopsy method did not tested positive for bacteria by filter paper method. There was directional association between the detection results of two methods ( P =0.004), i. e. if result of biopsy method was positive, result of filter paper method could also be positive. There was no obvious difference in the detection results of two methods ( P =0.250). The consistency between the detection results of two methods was ordinary (Kappa=0.68, P =0.002). (3) The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of filter paper method in bacteria detection were 70%, 100%, 1.00, 0.73, and 83.3%, respectively. Total area under ROC curve of bacteria detection by filter paper method in 18 patients was 0.919 (with 95% confidence interval 0-1.000, P =0.030). (4) There were 13 strains of bacteria detected by biopsy method, with 5 strains of Acinetobacter baumannii, 5 strains of Staphylococcus aureus, 1 strain of Pseudomonas aeruginosa, 1 strain of Streptococcus bovis, and 1 strain of bird Enterococcus . There were 11 strains of bacteria detected by filter paper method, with 5 strains of Acinetobacter baumannii, 3 strains of Staphylococcus aureus, 1 strain of Pseudomonas aeruginosa, 1 strain of Streptococcus bovis, and 1 strain of bird Enterococcus . Except for Staphylococcus aureus, the sensitivity and specificity of filter paper method in the detection of the other 4 bacteria were all 100%. The consistency between filter paper method and biopsy method in detecting Acinetobacter baumannii was good (Kappa=1.00, P <0.01), while that in detecting Staphylococcus aureus was ordinary (Kappa=0.68, P <0.05). (5) There was no obvious correlation between the bacteria number of wounds detected by filter paper method and that by biopsy method ( r =0.257, P =0.419). There was obvious correlation between the bacteria numbers detected by two methods in wounds with Texas grade 1 and 2 (with r values as 0.999, P values as 0.001). There was no obvious correlation between the bacteria numbers detected by two methods in wounds with Texas grade 3 ( r =-0.053, P =0.947). Conclusions: The detection result of filter paper method is in accordance with that of biopsy method in the determination of bacterial infection, and it is of great importance in the diagnosis of local infection of diabetic foot wound.

Saliency detection using mutual consistency-guided spatial cues combination

NASA Astrophysics Data System (ADS)

Wang, Xin; Ning, Chen; Xu, Lizhong

2015-09-01

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

Automated Peak Detection and Matching Algorithm for Gas Chromatography–Differential Mobility Spectrometry

PubMed Central

Fong, Sim S.; Rearden, Preshious; Kanchagar, Chitra; Sassetti, Christopher; Trevejo, Jose; Brereton, Richard G.

2013-01-01

A gas chromatography–differential mobility spectrometer (GC-DMS) involves a portable and selective mass analyzer that may be applied to chemical detection in the field. Existing approaches examine whole profiles and do not attempt to resolve peaks. A new approach for peak detection in the 2D GC-DMS chromatograms is reported. This method is demonstrated on three case studies: a simulated case study; a case study of headspace gas analysis of Mycobacterium tuberculosis (MTb) cultures consisting of three matching GC-DMS and GC-MS chromatograms; a case study consisting of 41 GC-DMS chromatograms of headspace gas analysis of MTb culture and media. PMID:21204557

Atmospheric pollution measurement by optical cross correlation methods - A concept

NASA Technical Reports Server (NTRS)

Fisher, M. J.; Krause, F. R.

1971-01-01

Method combines standard spectroscopy with statistical cross correlation analysis of two narrow light beams for remote sensing to detect foreign matter of given particulate size and consistency. Method is applicable in studies of generation and motion of clouds, nuclear debris, ozone, and radiation belts.

RAPID METHODS FOR MEASURING INDICATOR BACTERIA IN BATHING BEACH WATERS

EPA Science Inventory

The current methods for measuring the quality of recreational waters were developed in the 1970's and were recommended to the States by EPA in 1986. These methods detect and quantify Escherichia coli and enterococci, two bacteria that are consistently associated with fecal wast...

Detecting photovoltaic solar panels using hyperspectral imagery and estimating solar power production

NASA Astrophysics Data System (ADS)

Czirjak, Daniel

2017-04-01

Remote sensing platforms have consistently demonstrated the ability to detect, and in some cases identify, specific targets of interest, and photovoltaic solar panels are shown to have a unique spectral signature that is consistent across multiple manufacturers and construction methods. Solar panels are proven to be detectable in hyperspectral imagery using common statistical target detection methods such as the adaptive cosine estimator, and false alarms can be mitigated through the use of a spectral verification process that eliminates pixels that do not have the key spectral features of photovoltaic solar panel reflectance spectrum. The normalized solar panel index is described and is a key component in the false-alarm mitigation process. After spectral verification, these solar panel arrays are confirmed on openly available literal imagery and can be measured using numerous open-source algorithms and tools. The measurements allow for the assessment of overall solar power generation capacity using an equation that accounts for solar insolation, the area of solar panels, and the efficiency of the solar panels conversion of solar energy to power. Using a known location with readily available information, the methods outlined in this paper estimate the power generation capabilities within 6% of the rated power.

Evaluation of copy number variation detection for a SNP array platform

PubMed Central

2014-01-01

Background Copy Number Variations (CNVs) are usually inferred from Single Nucleotide Polymorphism (SNP) arrays by use of some software packages based on given algorithms. However, there is no clear understanding of the performance of these software packages; it is therefore difficult to select one or several software packages for CNV detection based on the SNP array platform. We selected four publicly available software packages designed for CNV calling from an Affymetrix SNP array, including Birdsuite, dChip, Genotyping Console (GTC) and PennCNV. The publicly available dataset generated by Array-based Comparative Genomic Hybridization (CGH), with a resolution of 24 million probes per sample, was considered to be the “gold standard”. Compared with the CGH-based dataset, the success rate, average stability rate, sensitivity, consistence and reproducibility of these four software packages were assessed compared with the “gold standard”. Specially, we also compared the efficiency of detecting CNVs simultaneously by two, three and all of the software packages with that by a single software package. Results Simply from the quantity of the detected CNVs, Birdsuite detected the most while GTC detected the least. We found that Birdsuite and dChip had obvious detecting bias. And GTC seemed to be inferior because of the least amount of CNVs it detected. Thereafter we investigated the detection consistency produced by one certain software package and the rest three software suits. We found that the consistency of dChip was the lowest while GTC was the highest. Compared with the CNVs detecting result of CGH, in the matching group, GTC called the most matching CNVs, PennCNV-Affy ranked second. In the non-overlapping group, GTC called the least CNVs. With regards to the reproducibility of CNV calling, larger CNVs were usually replicated better. PennCNV-Affy shows the best consistency while Birdsuite shows the poorest. Conclusion We found that PennCNV outperformed the other three packages in the sensitivity and specificity of CNV calling. Obviously, each calling method had its own limitations and advantages for different data analysis. Therefore, the optimized calling methods might be identified using multiple algorithms to evaluate the concordance and discordance of SNP array-based CNV calling. PMID:24555668

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

[Development of a SPA-ELISA method for detecting anti-coronavirus IgG antibodies in serum samples from fulvous fruit bats].

PubMed

Zhou, Jie; Liao, Yu-xue; Chen, Zhong; Li, Yu-chun; Gao, Lu-Lu; Chen, Yi-xiong; Cai, Lian-gong; Chen, Qing; Yu, Shou-yi

2008-05-01

To develop an simple and sensitive method for detecting anti-coronavirus IgG antibodies in bat sera based on enzyme-linked immunosorbent assay (ELISA). A commercial ELISA kit for detecting SARS-CoV antibody was modified for detecting coronavirus antibodies in bat serum samples. The second antibody in the kit was replaced with horseradish peroxidase-conjugated protein-A (HRP-SPA) based on the characteristics of binding between Staphylococcus aureus protein A (SPA) and mammal IgG Fc fragment. The sera of 55 fulvous fruit bats (Rousettus dasymallus) were tested using the SPA-ELISA. The test results of the positive and negative controls in the kit and the serum samples from convalescent ;patient were consistent with expectation. Coronavirus antibody was detected in 2 out of the 55 bat serum samples. Serum neutralization test confirmed the validity of the SPA-ELISA method. This SPA-ELISA method is applicable for detecting coronavirus antibody in bat sera.

Field calibration of blowfly-derived DNA against traditional methods for assessing mammal diversity in tropical forests.

PubMed

Lee, Ping-Shin; Gan, Han Ming; Clements, Gopalasamy Reuben; Wilson, John-James

2016-11-01

Mammal diversity assessments based on DNA derived from invertebrates have been suggested as alternatives to assessments based on traditional methods; however, no study has field-tested both approaches simultaneously. In Peninsular Malaysia, we calibrated the performance of mammal DNA derived from blowflies (Diptera: Calliphoridae) against traditional methods used to detect species. We first compared five methods (cage trapping, mist netting, hair trapping, scat collection, and blowfly-derived DNA) in a forest reserve with no recent reports of megafauna. Blowfly-derived DNA and mist netting detected the joint highest number of species (n = 6). Only one species was detected by multiple methods. Compared to the other methods, blowfly-derived DNA detected both volant and non-volant species. In another forest reserve, rich in megafauna, we calibrated blowfly-derived DNA against camera traps. Blowfly-derived DNA detected more species (n = 11) than camera traps (n = 9), with only one species detected by both methods. The rarefaction curve indicated that blowfly-derived DNA would continue to detect more species with greater sampling effort. With further calibration, blowfly-derived DNA may join the list of traditional field methods. Areas for further investigation include blowfly feeding and dispersal biology, primer biases, and the assembly of a comprehensive and taxonomically-consistent DNA barcode reference library.

Quench Detection and Protection for High Temperature Superconducting Transformers by Using the Active Power Method

NASA Astrophysics Data System (ADS)

Nanato, N.; Kobayashi, Y.

AC high temperature superconducting (HTS) coils have been developed for transformers, motors and so on. Quench detection and protection system are essential for safety operations of the AC HTS facilities. The balance voltage method is universally used for the quench detection and protection, however especially for AC operations, the method has risks in terms of high voltage sparks. Because the method needs a voltage tap soldered to a midpoint of the coil winding and the AC HTS facilities generally operate at high voltages and therefore high voltage sparks may occur at the midpoint with no insulation. We have proposed the active power method for the quench detection and protection. The method requires no voltage tap on the midpoint of the coil winding and therefore it has in-built effectiveness for the AC HTS facilities. In this paper, we show that the method can detect the quench in an HTS transformer and moreover our proposed quench protection circuits which consist of thyristors are simple and useful for the AC HTS facilities.

Investigating the potential use of environmental DNA (eDNA) for genetic monitoring of marine mammals.

PubMed

Foote, Andrew D; Thomsen, Philip Francis; Sveegaard, Signe; Wahlberg, Magnus; Kielgast, Jos; Kyhn, Line A; Salling, Andreas B; Galatius, Anders; Orlando, Ludovic; Gilbert, M Thomas P

2012-01-01

The exploitation of non-invasive samples has been widely used in genetic monitoring of terrestrial species. In aquatic ecosystems, non-invasive samples such as feces, shed hair or skin, are less accessible. However, the use of environmental DNA (eDNA) has recently been shown to be an effective tool for genetic monitoring of species presence in freshwater ecosystems. Detecting species in the marine environment using eDNA potentially offers a greater challenge due to the greater dilution, amount of mixing and salinity compared with most freshwater ecosystems. To determine the potential use of eDNA for genetic monitoring we used specific primers that amplify short mitochondrial DNA sequences to detect the presence of a marine mammal, the harbor porpoise, Phocoena phocoena, in a controlled environment and in natural marine locations. The reliability of the genetic detections was investigated by comparing with detections of harbor porpoise echolocation clicks by static acoustic monitoring devices. While we were able to consistently genetically detect the target species under controlled conditions, the results from natural locations were less consistent and detection by eDNA was less successful than acoustic detections. However, at one site we detected long-finned pilot whale, Globicephala melas, a species rarely sighted in the Baltic. Therefore, with optimization aimed towards processing larger volumes of seawater this method has the potential to compliment current visual and acoustic methods of species detection of marine mammals.

Saliency detection by conditional generative adversarial network

NASA Astrophysics Data System (ADS)

Cai, Xiaoxu; Yu, Hui

2018-04-01

Detecting salient objects in images has been a fundamental problem in computer vision. In recent years, deep learning has shown its impressive performance in dealing with many kinds of vision tasks. In this paper, we propose a new method to detect salient objects by using Conditional Generative Adversarial Network (GAN). This type of network not only learns the mapping from RGB images to salient regions, but also learns a loss function for training the mapping. To the best of our knowledge, this is the first time that Conditional GAN has been used in salient object detection. We evaluate our saliency detection method on 2 large publicly available datasets with pixel accurate annotations. The experimental results have shown the significant and consistent improvements over the state-of-the-art method on a challenging dataset, and the testing speed is much faster.

RAPID, PCR-BASED METHODS FOR MEASURING THE QUALITY OF BATHING BEACH WATERS

EPA Science Inventory

The current methods for measuring the quality of recreational waters were developed in the 1970's and were recommended to the States by EPA in 1986. These methods detect and quantify Escherichia coli and enterococci, two bacteria that are consistently associated with fecal wast...

Effect Size Calculations and Single Subject Designs

ERIC Educational Resources Information Center

Olive, Melissa L.; Smith, Benjamin W.

2005-01-01

This study compared visual analyses with five alternative methods for assessing the magnitude of effect with single subject designs. Each method was successful in detecting intervention effect. When rank ordered, each method was consistent in identifying the participants with the largest effect. We recommend the use of the standard mean difference…

EVALUATION OF CRYPTOSPORIDIUM OOCYST RECOVERY IN WATER BY EPA METHOD 1623 WITH A MODIFIED IMS DISSOCIATION PROCEDURE

EPA Science Inventory

U.S.EPA Methods 1622 and 1623 are used for the detection of waterborne Cryptosporium. These methods consist of filtration, elution, purificaiton by immunomagnetic separation (IMS), and microscopic analysis for oocysts stained by a fluorescent monoclonal antibody and counter stai...

EVALUATION OF CRYPTOSPORIDIUM OOCYST RECOVERY IN WATER BY EPA METHOD 1623 WITH A MODIFIED IMS DISSOCIATION PROCEDURE.

EPA Science Inventory

EPA Methods 1622 and 1623 are the benchmarks for detection of Cryptosporidium spp. oocysts in water. 5-7 These methods consist of filtration, elution, purification by immunomagnetic separation (IMS), and microscopic analysis after staining with a fluorescein isothiocyanate conju...

Automatic Road Gap Detection Using Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Hashemi, S.; Valadan Zoej, M. J.; Mokhtarzadeh, M.

2011-09-01

Automatic feature extraction from aerial and satellite images is a high-level data processing which is still one of the most important research topics of the field. In this area, most of the researches are focused on the early step of road detection, where road tracking methods, morphological analysis, dynamic programming and snakes, multi-scale and multi-resolution methods, stereoscopic and multi-temporal analysis, hyper spectral experiments, are some of the mature methods in this field. Although most researches are focused on detection algorithms, none of them can extract road network perfectly. On the other hand, post processing algorithms accentuated on the refining of road detection results, are not developed as well. In this article, the main is to design an intelligent method to detect and compensate road gaps remained on the early result of road detection algorithms. The proposed algorithm consists of five main steps as follow: 1) Short gap coverage: In this step, a multi-scale morphological is designed that covers short gaps in a hierarchical scheme. 2) Long gap detection: In this step, the long gaps, could not be covered in the previous stage, are detected using a fuzzy inference system. for this reason, a knowledge base consisting of some expert rules are designed which are fired on some gap candidates of the road detection results. 3) Long gap coverage: In this stage, detected long gaps are compensated by two strategies of linear and polynomials for this reason, shorter gaps are filled by line fitting while longer ones are compensated by polynomials.4) Accuracy assessment: In order to evaluate the obtained results, some accuracy assessment criteria are proposed. These criteria are obtained by comparing the obtained results with truly compensated ones produced by a human expert. The complete evaluation of the obtained results whit their technical discussions are the materials of the full paper.

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.

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.

Authenticity examination of compressed audio recordings using detection of multiple compression and encoders' identification.

PubMed

Korycki, Rafal

2014-05-01

Since the appearance of digital audio recordings, audio authentication has been becoming increasingly difficult. The currently available technologies and free editing software allow a forger to cut or paste any single word without audible artifacts. Nowadays, the only method referring to digital audio files commonly approved by forensic experts is the ENF criterion. It consists in fluctuation analysis of the mains frequency induced in electronic circuits of recording devices. Therefore, its effectiveness is strictly dependent on the presence of mains signal in the recording, which is a rare occurrence. Recently, much attention has been paid to authenticity analysis of compressed multimedia files and several solutions were proposed for detection of double compression in both digital video and digital audio. This paper addresses the problem of tampering detection in compressed audio files and discusses new methods that can be used for authenticity analysis of digital recordings. Presented approaches consist in evaluation of statistical features extracted from the MDCT coefficients as well as other parameters that may be obtained from compressed audio files. Calculated feature vectors are used for training selected machine learning algorithms. The detection of multiple compression covers up tampering activities as well as identification of traces of montage in digital audio recordings. To enhance the methods' robustness an encoder identification algorithm was developed and applied based on analysis of inherent parameters of compression. The effectiveness of tampering detection algorithms is tested on a predefined large music database consisting of nearly one million of compressed audio files. The influence of compression algorithms' parameters on the classification performance is discussed, based on the results of the current study. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Does the Presence of Scrapie Affect the Ability of Current Statutory Discriminatory Tests To Detect the Presence of Bovine Spongiform Encephalopathy?

PubMed Central

Chaplin, M. J.; Vickery, C. M.; Simon, S.; Davis, L.; Denyer, M.; Lockey, R.; Stack, M. J.; O'Connor, M. J.; Bishop, K.; Gough, K. C.; Maddison, B. C.; Thorne, L.; Spiropoulos, J.

2015-01-01

Current European Commission (EC) surveillance regulations require discriminatory testing of all transmissible spongiform encephalopathy (TSE)-positive small ruminant (SR) samples in order to classify them as bovine spongiform encephalopathy (BSE) or non-BSE. This requires a range of tests, including characterization by bioassay in mouse models. Since 2005, naturally occurring BSE has been identified in two goats. It has also been demonstrated that more than one distinct TSE strain can coinfect a single animal in natural field situations. This study assesses the ability of the statutory methods as listed in the regulation to identify BSE in a blinded series of brain samples, in which ovine BSE and distinct isolates of scrapie are mixed at various ratios ranging from 99% to 1%. Additionally, these current statutory tests were compared with a new in vitro discriminatory method, which uses serial protein misfolding cyclic amplification (sPMCA). Western blotting consistently detected 50% BSE within a mixture, but at higher dilutions it had variable success. The enzyme-linked immunosorbent assay (ELISA) method consistently detected BSE only when it was present as 99% of the mixture, with variable success at higher dilutions. Bioassay and sPMCA reported BSE in all samples where it was present, down to 1%. sPMCA also consistently detected the presence of BSE in mixtures at 0.1%. While bioassay is the only validated method that allows comprehensive phenotypic characterization of an unknown TSE isolate, the sPMCA assay appears to offer a fast and cost-effective alternative for the screening of unknown isolates when the purpose of the investigation was solely to determine the presence or absence of BSE. PMID:26041899

Computerized analysis of sonograms for the detection of breast lesions

NASA Astrophysics Data System (ADS)

Drukker, Karen; Giger, Maryellen L.; Horsch, Karla; Vyborny, Carl J.

2002-05-01

With a renewed interest in using non-ionizing radiation for the screening of high risk women, there is a clear role for a computerized detection aid in ultrasound. Thus, we are developing a computerized detection method for the localization of lesions on breast ultrasound images. The computerized detection scheme utilizes two methods. Firstly, a radial gradient index analysis is used to distinguish potential lesions from normal parenchyma. Secondly, an image skewness analysis is performed to identify posterior acoustic shadowing. We analyzed 400 cases (757 images) consisting of complex cysts, solid benign lesions, and malignant lesions. The detection method yielded an overall sensitivity of 95% by image, and 99% by case at a false-positive rate of 0.94 per image. In 51% of all images, only the lesion itself was detected, while in 5% of the images only the shadowing was identified. For malignant lesions these numbers were 37% and 9%, respectively. In summary, we have developed a computer detection method for lesions on ultrasound images of the breast, which may ultimately aid in breast cancer screening.

A highly sensitive and specific method for the screening detection of genetically modified organisms based on digital PCR without pretreatment

PubMed Central

Fu, Wei; Zhu, Pengyu; Wang, Chenguang; Huang, Kunlun; Du, Zhixin; Tian, Wenying; Wang, Qin; Wang, Huiyu; Xu, Wentao; Zhu, Shuifang

2015-01-01

Digital PCR has developed rapidly since it was first reported in the 1990s. It was recently reported that an improved method facilitated the detection of genetically modified organisms (GMOs). However, to use this improved method, the samples must be pretreated, which could introduce inaccuracy into the results. In our study, we explored a pretreatment-free digital PCR detection method for the screening for GMOs. We chose the CaMV35s promoter and the NOS terminator as the templates in our assay. To determine the specificity of our method, 9 events of GMOs were collected, including MON810, MON863, TC1507, MIR604, MIR162, GA21, T25, NK603 and Bt176. Moreover, the sensitivity, intra-laboratory and inter-laboratory reproducibility of our detection method were assessed. The results showed that the limit of detection of our method was 0.1%, which was lower than the labeling threshold level of the EU. The specificity and stability among the 9 events were consistent, respectively. The intra-laboratory and inter-laboratory reproducibility were both good. Finally, the perfect fitness for the detection of eight double-blind samples indicated the good practicability of our method. In conclusion, the method in our study would allow more sensitive, specific and stable screening detection of the GMO content of international trading products. PMID:26239916

A highly sensitive and specific method for the screening detection of genetically modified organisms based on digital PCR without pretreatment.

PubMed

Fu, Wei; Zhu, Pengyu; Wang, Chenguang; Huang, Kunlun; Du, Zhixin; Tian, Wenying; Wang, Qin; Wang, Huiyu; Xu, Wentao; Zhu, Shuifang

2015-08-04

Digital PCR has developed rapidly since it was first reported in the 1990 s. It was recently reported that an improved method facilitated the detection of genetically modified organisms (GMOs). However, to use this improved method, the samples must be pretreated, which could introduce inaccuracy into the results. In our study, we explored a pretreatment-free digital PCR detection method for the screening for GMOs. We chose the CaMV35s promoter and the NOS terminator as the templates in our assay. To determine the specificity of our method, 9 events of GMOs were collected, including MON810, MON863, TC1507, MIR604, MIR162, GA21, T25, NK603 and Bt176. Moreover, the sensitivity, intra-laboratory and inter-laboratory reproducibility of our detection method were assessed. The results showed that the limit of detection of our method was 0.1%, which was lower than the labeling threshold level of the EU. The specificity and stability among the 9 events were consistent, respectively. The intra-laboratory and inter-laboratory reproducibility were both good. Finally, the perfect fitness for the detection of eight double-blind samples indicated the good practicability of our method. In conclusion, the method in our study would allow more sensitive, specific and stable screening detection of the GMO content of international trading products.

A Method of Character Detection and Segmentation for Highway Guide Signs

NASA Astrophysics Data System (ADS)

Xu, Jiawei; Zhang, Chongyang

2018-01-01

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

An R-peak detection method that uses an SVD filter and a search back system.

PubMed

Jung, Woo-Hyuk; Lee, Sang-Goog

2012-12-01

In this paper, we present a method for detecting the R-peak of an ECG signal by using an singular value decomposition (SVD) filter and a search back system. The ECG signal was detected in two phases: the pre-processing phase and the decision phase. The pre-processing phase consisted of the stages for the SVD filter, Butterworth High Pass Filter (HPF), moving average (MA), and squaring, whereas the decision phase consisted of a single stage that detected the R-peak. In the pre-processing phase, the SVD filter removed noise while the Butterworth HPF eliminated baseline wander. The MA removed the remaining noise of the signal that had gone through the SVD filter to make the signal smooth, and squaring played a role in strengthening the signal. In the decision phase, the threshold was used to set the interval before detecting the R-peak. When the latest R-R interval (RRI), suggested by Hamilton et al., was greater than 150% of the previous RRI, the method of detecting the R-peak in such an interval was modified to be 150% or greater than the smallest interval of the two most latest RRIs. When the modified search back system was used, the error rate of the peak detection decreased to 0.29%, compared to 1.34% when the modified search back system was not used. Consequently, the sensitivity was 99.47%, the positive predictivity was 99.47%, and the detection error was 1.05%. Furthermore, the quality of the signal in data with a substantial amount of noise was improved, and thus, the R-peak was detected effectively. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Perception of linear acceleration in weightlessness

NASA Technical Reports Server (NTRS)

Arrott, A. P.; Young, L. R.

1987-01-01

Eye movements and subjective detection of acceleration were measured on human experimental subjects during vestibular sled acceleration during the D1 Spacelab Mission. Methods and results are reported on the time to detection of small acceleration steps, the threshold for detection of linear acceleration, perceived motion path, and CLOAT. A consistently shorter time to detection of small acceleration steps is found. Subjective reports of perceived motion during sinusoidal oscillation in weightlessness were qualitatively similar to reports on earth.

Mapping Health Data: Improved Privacy Protection With Donut Method Geomasking

PubMed Central

Hampton, Kristen H.; Fitch, Molly K.; Allshouse, William B.; Doherty, Irene A.; Gesink, Dionne C.; Leone, Peter A.; Serre, Marc L.; Miller, William C.

2010-01-01

A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut method geomasking, each geocoded address is relocated in a random direction by at least a minimum distance, but less than a maximum distance. The authors compared the donut method with current methods of random perturbation and aggregation regarding measures of privacy protection and cluster detection performance by masking multiple disease field simulations under a range of parameters. Both the donut method and random perturbation performed better than aggregation in cluster detection measures. The performance of the donut method in geoprivacy measures was at least 42.7% higher and in cluster detection measures was less than 4.8% lower than that of random perturbation. Results show that the donut method provides a consistently higher level of privacy protection with a minimal decrease in cluster detection performance, especially in areas where the risk to individual geoprivacy is greatest. PMID:20817785

Mapping health data: improved privacy protection with donut method geomasking.

PubMed

Hampton, Kristen H; Fitch, Molly K; Allshouse, William B; Doherty, Irene A; Gesink, Dionne C; Leone, Peter A; Serre, Marc L; Miller, William C

2010-11-01

A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut method geomasking, each geocoded address is relocated in a random direction by at least a minimum distance, but less than a maximum distance. The authors compared the donut method with current methods of random perturbation and aggregation regarding measures of privacy protection and cluster detection performance by masking multiple disease field simulations under a range of parameters. Both the donut method and random perturbation performed better than aggregation in cluster detection measures. The performance of the donut method in geoprivacy measures was at least 42.7% higher and in cluster detection measures was less than 4.8% lower than that of random perturbation. Results show that the donut method provides a consistently higher level of privacy protection with a minimal decrease in cluster detection performance, especially in areas where the risk to individual geoprivacy is greatest.

Automatic QRS complex detection using two-level convolutional neural network.

PubMed

Xiang, Yande; Lin, Zhitao; Meng, Jianyi

2018-01-29

The QRS complex is the most noticeable feature in the electrocardiogram (ECG) signal, therefore, its detection is critical for ECG signal analysis. The existing detection methods largely depend on hand-crafted manual features and parameters, which may introduce significant computational complexity, especially in the transform domains. In addition, fixed features and parameters are not suitable for detecting various kinds of QRS complexes under different circumstances. In this study, based on 1-D convolutional neural network (CNN), an accurate method for QRS complex detection is proposed. The CNN consists of object-level and part-level CNNs for extracting different grained ECG morphological features automatically. All the extracted morphological features are used by multi-layer perceptron (MLP) for QRS complex detection. Additionally, a simple ECG signal preprocessing technique which only contains difference operation in temporal domain is adopted. Based on the MIT-BIH arrhythmia (MIT-BIH-AR) database, the proposed detection method achieves overall sensitivity Sen = 99.77%, positive predictivity rate PPR = 99.91%, and detection error rate DER = 0.32%. In addition, the performance variation is performed according to different signal-to-noise ratio (SNR) values. An automatic QRS detection method using two-level 1-D CNN and simple signal preprocessing technique is proposed for QRS complex detection. Compared with the state-of-the-art QRS complex detection approaches, experimental results show that the proposed method acquires comparable accuracy.

Adaptive Self Tuning

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

Peterson, Matthew; Draelos, Timothy; Knox, Hunter

2017-05-02

The AST software includes numeric methods to 1) adjust STA/LTA signal detector trigger level (TL) values and 2) filter detections for a network of sensors. AST adapts TL values to the current state of the environment by leveraging cooperation within a neighborhood of sensors. The key metric that guides the dynamic tuning is consistency of each sensor with its nearest neighbors: TL values are automatically adjusted on a per station basis to be more or less sensitive to produce consistent agreement of detections in its neighborhood. The AST algorithm adapts in near real-time to changing conditions in an attempt tomore » automatically self-tune a signal detector to identify (detect) only signals from events of interest.« less

SCOUT: simultaneous time segmentation and community detection in dynamic networks

PubMed Central

Hulovatyy, Yuriy; Milenković, Tijana

2016-01-01

Many evolving complex real-world systems can be modeled via dynamic networks. An important problem in dynamic network research is community detection, which finds groups of topologically related nodes. Typically, this problem is approached by assuming either that each time point has a distinct community organization or that all time points share a single community organization. The reality likely lies between these two extremes. To find the compromise, we consider community detection in the context of the problem of segment detection, which identifies contiguous time periods with consistent network structure. Consequently, we formulate a combined problem of segment community detection (SCD), which simultaneously partitions the network into contiguous time segments with consistent community organization and finds this community organization for each segment. To solve SCD, we introduce SCOUT, an optimization framework that explicitly considers both segmentation quality and partition quality. SCOUT addresses limitations of existing methods that can be adapted to solve SCD, which consider only one of segmentation quality or partition quality. In a thorough evaluation, SCOUT outperforms the existing methods in terms of both accuracy and computational complexity. We apply SCOUT to biological network data to study human aging. PMID:27881879

Real-time electrochemical monitoring of isothermal helicase-dependent amplification of nucleic acids.

PubMed

Kivlehan, Francine; Mavré, François; Talini, Luc; Limoges, Benoît; Marchal, Damien

2011-09-21

We described an electrochemical method to monitor in real-time the isothermal helicase-dependent amplification of nucleic acids. The principle of detection is simple and well-adapted to the development of portable, easy-to-use and inexpensive nucleic acids detection technologies. It consists of monitoring a decrease in the electrochemical current response of a reporter DNA intercalating redox probe during the isothermal DNA amplification. The method offers the possibility to quantitatively analyze target nucleic acids in less than one hour at a single constant temperature, and to perform at the end of the isothermal amplification a DNA melt curve analysis for differentiating between specific and non-specific amplifications. To illustrate the potentialities of this approach for the development of a simple, robust and low-cost instrument with high throughput capability, the method was validated with an electrochemical system capable of monitoring up to 48 real-time isothermal HDA reactions simultaneously in a disposable microplate consisting of 48-electrochemical microwells. Results obtained with this approach are comparable to that obtained with a well-established but more sophisticated and expensive fluorescence-based method. This makes for a promising alternative detection method not only for real-time isothermal helicase-dependent amplification of nucleic acid, but also for other isothermal DNA amplification strategies.

Radial line method for rear-view mirror distortion detection

NASA Astrophysics Data System (ADS)

Rahmah, Fitri; Kusumawardhani, Apriani; Setijono, Heru; Hatta, Agus M.; Irwansyah, .

2015-01-01

An image of the object can be distorted due to a defect in a mirror. A rear-view mirror is an important component for the vehicle safety. One of standard parameters of the rear-view mirror is a distortion factor. This paper presents a radial line method for distortion detection of the rear-view mirror. The rear-view mirror was tested for the distortion detection by using a system consisting of a webcam sensor and an image-processing unit. In the image-processing unit, the captured image from the webcam were pre-processed by using smoothing and sharpening techniques and then a radial line method was used to define the distortion factor. It was demonstrated successfully that the radial line method could be used to define the distortion factor. This detection system is useful to be implemented such as in Indonesian's automotive component industry while the manual inspection still be used.

Detection of the Dinozoans Pfiesteria piscicida and P. shumwayae: a review of detection methods and geographic distribution.

PubMed

Rublee, Parke A; Remington, David L; Schaefer, Eric F; Marshall, Michael M

2005-01-01

Molecular methods, including conventional PCR, real-time PCR, denaturing gradient gel electrophoresis, fluorescent fragment detection PCR, and fluorescent in situ hybridization, have all been developed for use in identifying and studying the distribution of the toxic dinoflagellates Pfiesteria piscicida and P. shumwayae. Application of the methods has demonstrated a worldwide distribution of both species and provided insight into their environmental tolerance range and temporal changes in distribution. Genetic variability among geographic locations generally appears low in rDNA genes, and detection of the organisms in ballast water is consistent with rapid dispersal or high gene flow among populations, but additional sequence data are needed to verify this hypothesis. The rapid development and application of these tools serves as a model for study of other microbial taxa and provides a basis for future development of tools that can simultaneously detect multiple targets.

Detection of cyclic-fold bifurcation in electrostatic MEMS transducers by motion-induced current

NASA Astrophysics Data System (ADS)

Park, Sangtak; Khater, Mahmoud; Effa, David; Abdel-Rahman, Eihab; Yavuz, Mustafa

2017-08-01

This paper presents a new detection method of cyclic-fold bifurcations in electrostatic MEMS transducers based on a variant of the harmonic detection of resonance method. The electrostatic transducer is driven by an unbiased harmonic signal at half its natural frequency, ω a   =  1/2 ω o . The response of the transducer consists of static displacement and a series of harmonics at 2 ω a , 4 ω a , and so on. Its motion-induced current is shifted by the excitation frequency, ω a , to appear at 3 ω a , 5 ω a , and higher odd harmonics, providing higher sensitivity to the measurement of harmonic motions. With this method, we successfully detected the variation in the location of the cyclic-fold bifurcation of an encapsulated electrostatic MEMS transducer. We also detected a regime of tapping mode motions subsequent to the bifurcation.

Comparison of Intelligent Systems in Detecting a Child's Mathematical Gift

ERIC Educational Resources Information Center

Pavlekovic, Margita; Zekic-Susac, Marijana; Djurdjevic, Ivana

2009-01-01

This paper compares the efficiency of two intelligent methods: expert systems and neural networks, in detecting children's mathematical gift at the fourth grade of elementary school. The input space for the expert system and the neural network model consisted of 60 variables describing five basic components of a child's mathematical gift…

Accuracy of a Screening Tool for Early Identification of Language Impairment

ERIC Educational Resources Information Center

Uilenburg, Noëlle; Wiefferink, Karin; Verkerk, Paul; van Denderen, Margot; van Schie, Carla; Oudesluys-Murphy, Ann-Marie

2018-01-01

Purpose: A screening tool called the "VTO Language Screening Instrument" (VTO-LSI) was developed to enable more uniform and earlier detection of language impairment. This report, consisting of 2 retrospective studies, focuses on the effects of using the VTO-LSI compared to regular detection procedures. Method: Study 1 retrospectively…

Binderless composite scintillator for neutron detection

DOEpatents

Hodges, Jason P [Knoxville, TN; Crow, Jr; Lowell, M [Oak Ridge, TN; Cooper, Ronald G [Oak Ridge, TN

2009-03-10

Composite scintillator material consisting of a binderless sintered mixture of a Lithium (Li) compound containing .sup.6Li as the neutron converter and Y.sub.2SiO.sub.5:Ce as the scintillation phosphor, and the use of this material as a method for neutron detection. Other embodiments of the invention include various other Li compounds.

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

NASA Astrophysics Data System (ADS)

Zou, Tianhao; Zuo, Zhengrong

2018-02-01

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

Automatic abdominal lymph node detection method based on local intensity structure analysis from 3D x-ray CT images

NASA Astrophysics Data System (ADS)

Nakamura, Yoshihiko; Nimura, Yukitaka; Kitasaka, Takayuki; Mizuno, Shinji; Furukawa, Kazuhiro; Goto, Hidemi; Fujiwara, Michitaka; Misawa, Kazunari; Ito, Masaaki; Nawano, Shigeru; Mori, Kensaku

2013-03-01

This paper presents an automated method of abdominal lymph node detection to aid the preoperative diagnosis of abdominal cancer surgery. In abdominal cancer surgery, surgeons must resect not only tumors and metastases but also lymph nodes that might have a metastasis. This procedure is called lymphadenectomy or lymph node dissection. Insufficient lymphadenectomy carries a high risk for relapse. However, excessive resection decreases a patient's quality of life. Therefore, it is important to identify the location and the structure of lymph nodes to make a suitable surgical plan. The proposed method consists of candidate lymph node detection and false positive reduction. Candidate lymph nodes are detected using a multi-scale blob-like enhancement filter based on local intensity structure analysis. To reduce false positives, the proposed method uses a classifier based on support vector machine with the texture and shape information. The experimental results reveal that it detects 70.5% of the lymph nodes with 13.0 false positives per case.

Development and Application of Advanced Ophthalmic Imaging Technology to Enhance Military Ocular Health Capabilities

DTIC Science & Technology

2009-04-01

active military personnel and veterans, are affected by three major blinding diseases of the retina and optic nerve: diabetic retinopathy , age-related...disease is detected early. New advanced detection methods are available, but are only interpretable by very experienced specialists. The goal of this...consist of several steps [1-3]: feature detection ; transform model estimation; optimization function design; and optimization strategies. We do not

Comparative studies of copy number variation detection methods for next-generation sequencing technologies.

PubMed

Duan, Junbo; Zhang, Ji-Gang; Deng, Hong-Wen; Wang, Yu-Ping

2013-01-01

Copy number variation (CNV) has played an important role in studies of susceptibility or resistance to complex diseases. Traditional methods such as fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (aCGH) suffer from low resolution of genomic regions. Following the emergence of next generation sequencing (NGS) technologies, CNV detection methods based on the short read data have recently been developed. However, due to the relatively young age of the procedures, their performance is not fully understood. To help investigators choose suitable methods to detect CNVs, comparative studies are needed. We compared six publicly available CNV detection methods: CNV-seq, FREEC, readDepth, CNVnator, SegSeq and event-wise testing (EWT). They are evaluated both on simulated and real data with different experiment settings. The receiver operating characteristic (ROC) curve is employed to demonstrate the detection performance in terms of sensitivity and specificity, box plot is employed to compare their performances in terms of breakpoint and copy number estimation, Venn diagram is employed to show the consistency among these methods, and F-score is employed to show the overlapping quality of detected CNVs. The computational demands are also studied. The results of our work provide a comprehensive evaluation on the performances of the selected CNV detection methods, which will help biological investigators choose the best possible method.

Diagnostic Sensitivity and Specificity of Dark Adaptometry for Detection of Age-Related Macular Degeneration

PubMed Central

Jackson, Gregory R.; Scott, Ingrid U.; Kim, Ivana K.; Quillen, David A.; Iannaccone, Alessandro; Edwards, John G.

2014-01-01

Purpose. Difficulty with night vision is a common complaint of patients with age-related macular degeneration (AMD). Consistent with this complaint, dark adaptation (DA) is substantially impaired in these patients. Because of the severity of the deficit, measurement of DA has been suggested as a means for the diagnosis of AMD. Previous methods for measurement of DA were time intensive (>30 minutes), which made them unsuitable for clinical use. This study evaluated a rapid DA test (≤6.5 minutes) for the detection of AMD. Methods. Dark adaptation was measured by using the AdaptDx dark adaptometer in two groups: subjects with normal retinal health and subjects with AMD. Subjects were assigned to their group by clinical examination and grading of fundus photographs. Subjects were classified as having DA consistent with normal retinal health (rod intercept ≤ 6.5 minutes) or having dark adaptation consistent with AMD (rod intercept > 6.5 minutes). Results. The eligible sample for analysis included 21 normal adults and 127 AMD patients. The rapid test was found to have a diagnostic sensitivity of 90.6% (P < 0.001) and specificity of 90.5% (P < 0.027). Thus, abnormal DA was detected in 115 of 127 AMD patients, and normal DA was found in 19 of 21 normal adults. Conclusions. The high diagnostic sensitivity and specificity compared favorably to long-duration research methods for the measurement of DA, and slit lamp biomicroscopy performed by a retina specialist. These results suggest that a rapid DA test is useful for the detection of AMD. PMID:24550363

Consistently Sampled Correlation Filters with Space Anisotropic Regularization for Visual Tracking

PubMed Central

Shi, Guokai; Xu, Tingfa; Luo, Jiqiang; Li, Yuankun

2017-01-01

Most existing correlation filter-based tracking algorithms, which use fixed patches and cyclic shifts as training and detection measures, assume that the training samples are reliable and ignore the inconsistencies between training samples and detection samples. We propose to construct and study a consistently sampled correlation filter with space anisotropic regularization (CSSAR) to solve these two problems simultaneously. Our approach constructs a spatiotemporally consistent sample strategy to alleviate the redundancies in training samples caused by the cyclical shifts, eliminate the inconsistencies between training samples and detection samples, and introduce space anisotropic regularization to constrain the correlation filter for alleviating drift caused by occlusion. Moreover, an optimization strategy based on the Gauss-Seidel method was developed for obtaining robust and efficient online learning. Both qualitative and quantitative evaluations demonstrate that our tracker outperforms state-of-the-art trackers in object tracking benchmarks (OTBs). PMID:29231876

Application of image recognition-based automatic hyphae detection in fungal keratitis.

PubMed

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.

Cross-checking of Large Evaluated and Experimental Nuclear Reaction Databases

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

Zeydina, O.; Koning, A.J.; Soppera, N.

2014-06-15

Automated methods are presented for the verification of large experimental and evaluated nuclear reaction databases (e.g. EXFOR, JEFF, TENDL). These methods allow an assessment of the overall consistency of the data and detect aberrant values in both evaluated and experimental databases.

Emergency First Responders' Experience with Colorimetric Detection Methods

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

Sandra L. Fox; Keith A. Daum; Carla J. Miller

2007-10-01

Nationwide, first responders from state and federal support teams respond to hazardous materials incidents, industrial chemical spills, and potential weapons of mass destruction (WMD) attacks. Although first responders have sophisticated chemical, biological, radiological, and explosive detectors available for assessment of the incident scene, simple colorimetric detectors have a role in response actions. The large number of colorimetric chemical detection methods available on the market can make the selection of the proper methods difficult. Although each detector has unique aspects to provide qualitative or quantitative data about the unknown chemicals present, not all detectors provide consistent, accurate, and reliable results. Includedmore » here, in a consumer-report-style format, we provide “boots on the ground” information directly from first responders about how well colorimetric chemical detection methods meet their needs in the field and how they procure these methods.« less

Multitask assessment of roads and vehicles network (MARVN)

NASA Astrophysics Data System (ADS)

Yang, Fang; Yi, Meng; Cai, Yiran; Blasch, Erik; Sullivan, Nichole; Sheaff, Carolyn; Chen, Genshe; Ling, Haibin

2018-05-01

Vehicle detection in wide area motion imagery (WAMI) has drawn increasing attention from the computer vision research community in recent decades. In this paper, we present a new architecture for vehicle detection on road using multi-task network, which is able to detect and segment vehicles, estimate their pose, and meanwhile yield road isolation for a given region. The multi-task network consists of three components: 1) vehicle detection, 2) vehicle and road segmentation, and 3) detection screening. Segmentation and detection components share the same backbone network and are trained jointly in an end-to-end way. Unlike background subtraction or frame differencing based methods, the proposed Multitask Assessment of Roads and Vehicles Network (MARVN) method can detect vehicles which are slowing down, stopped, and/or partially occluded in a single image. In addition, the method can eliminate the detections which are located at outside road using yielded road segmentation so as to decrease the false positive rate. As few WAMI datasets have road mask and vehicles bounding box anotations, we extract 512 frames from WPAFB 2009 dataset and carefully refine the original annotations. The resulting dataset is thus named as WAMI512. We extensively compare the proposed method with state-of-the-art methods on WAMI512 dataset, and demonstrate superior performance in terms of efficiency and accuracy.

Influenza detection and prediction algorithms: comparative accuracy trial in Östergötland county, Sweden, 2008-2012.

PubMed

Spreco, A; Eriksson, O; Dahlström, Ö; Timpka, T

2017-07-01

Methods for the detection of influenza epidemics and prediction of their progress have seldom been comparatively evaluated using prospective designs. This study aimed to perform a prospective comparative trial of algorithms for the detection and prediction of increased local influenza activity. Data on clinical influenza diagnoses recorded by physicians and syndromic data from a telenursing service were used. Five detection and three prediction algorithms previously evaluated in public health settings were calibrated and then evaluated over 3 years. When applied on diagnostic data, only detection using the Serfling regression method and prediction using the non-adaptive log-linear regression method showed acceptable performances during winter influenza seasons. For the syndromic data, none of the detection algorithms displayed a satisfactory performance, while non-adaptive log-linear regression was the best performing prediction method. We conclude that evidence was found for that available algorithms for influenza detection and prediction display satisfactory performance when applied on local diagnostic data during winter influenza seasons. When applied on local syndromic data, the evaluated algorithms did not display consistent performance. Further evaluations and research on combination of methods of these types in public health information infrastructures for 'nowcasting' (integrated detection and prediction) of influenza activity are warranted.

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.

Fast detection and characterization of organic and inorganic gunshot residues on the hands of suspects by CMV-GC-MS and LIBS.

PubMed

Tarifa, Anamary; Almirall, José R

2015-05-01

A rapid method for the characterization of both organic and inorganic components of gunshot residues (GSR) is proposed as an alternative tool to facilitate the identification of a suspected shooter. In this study, two fast screening methods were developed and optimized for the detection of organic compounds and inorganic components indicative of GSR presence on the hands of shooters and non-shooters. The proposed methods consist of headspace extraction of volatile organic compounds using a capillary microextraction of volatiles (CMV) device previously reported as a high-efficiency sampler followed by detection by GC-MS. This novel sampling technique has the potential to yield fast results (<2min sampling) and high sensitivity capable of detecting 3ng of diphenylamine (DPA) and 8ng of nitroglycerine (NG). Direct analysis of the headspace of over 50 swabs collected from the hands of suspected shooters (and non-shooters) provides information regarding VOCs present on their hands. In addition, a fast laser induced breakdown spectroscopy (LIBS) screening method for the detection of the inorganic components indicative of the presence of GSR (Sb, Pb and Ba) is described. The sampling method for the inorganics consists of liquid extraction of the target elements from the same cotton swabs (previously analyzed for VOCs) and an additional 30 swab samples followed by spiking 1μL of the extract solution onto a Teflon disk and then analyzed by LIBS. Advantages of LIBS include fast analysis (~12s per sample) and high selectivity and sensitivity, with expected LODs 0.1-18ng for each of the target elements after sampling. The analytical performance of the LIBS method is also compared to previously reported methods (inductively coupled plasma-optical emission spectroscopy). The combination of fast CMV sampling, unambiguous organic compound identification with GC-MS and fast LIBS analysis provides the basis for a new comprehensive screening method for GSR. Copyright © 2015 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2004-05-01

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

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.

TU-G-204-02: Automatic Sclerotic Bone Metastases Detection in the Pelvic Region From Dual Energy CT

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

Fehr, D; Schmidtlein, C; Hwang, S

Purpose: To automatically detect sclerotic bone metastases in the pelvic region using dual energy computed tomography (DECT). Methods: We developed a two stage algorithm to automatically detect sclerotic bone metastases in the pelvis from DECT for patients with multiple bone metastatic lesions and with hip implants. The first stage consists of extracting the bone and marrow regions by using a support vector machine (SVM) classifier. We employed a novel representation of the DECT images using multi-material decomposition, which represents each voxel as a mixture of different physical materials (e.g. bone+water+fat). Following the extraction of bone and marrow, in the secondmore » stage, a bi -histogram equalization method was employed to enhance the contrast to reveal the bone metastases. Next, meanshift segmentation was performed to separate the voxels by their intensity levels. Finally, shape-based filtering was performed to extract the possible locations of the metastatic lesions using multiple shape criteria. We used the following shape parameters: area, eccentricity, major and minor axis, perimeter and skeleton. Results: A radiologist with several years of experience with DECT manually labeled 64 regions consisting of metastatic lesions from 10 different patients. However, the patients had many more metastasic lesions throughout the pelvis. Our method correctly identified 46 of the marked 64 regions (72%). In addition, our method also identified several other lesions, which can then be validated by the radiologist. The missed lesions were typically very large elongated regions consisting of several islands of very small (<4mm) lesions. Conclusion: We developed an algorithm to automatically detect sclerotic lesions in the pelvic region from DECT. Preliminary assessment shows that our algorithm generated lesions agreeing with the radiologist generated candidate regions. Furthermore, our method reveals additional lesions that can be inspected by the radiologist, thereby, reducing radiologist effort in identifying all the lesions with poor contrast from the DECT images.« less

Application of HPLC with ELSD Detection for the Assessment of Azelaic Acid Impurities in Liposomal Formulation

PubMed Central

Han, Stanislaw; Karlowicz-Bodalska, Katarzyna; Ozimek, Lukasz

2013-01-01

In the course of research and development of a new pharmaceutical formulation of azelaic acid in the liposomal form, we developed a rapid and accurate method for the detection of impurities using high-performance liquid chromatography. A chromatographic column from Merck (Purospher Star RP C18, 250–4 mm (5 μm) was used in the assay, and the mobile phase gradient consisted of three phases: A—methanol : water (5 : 95) + 1.5% (v/v) acetic acid; B—water : methanol (5 : 95) + 1.5% (v/v) acetic acid; and C—chloroform. Detection of the impurities and the active substance was performed by an evaporative light-scattering detector. The method was validated for selectivity, system precision, method precision, limit of detection, and response rates. The proposed method can be used to detect impurities in the liposomal formulation of azelaic acid. The method enables separation of azelaic acid from the identified and unidentified impurities and from the excipients used in the drug form. PMID:24228008

Application of HPLC with ELSD detection for the assessment of azelaic acid impurities in liposomal formulation.

PubMed

Han, Stanislaw; Karlowicz-Bodalska, Katarzyna; Szura, Dorota; Ozimek, Lukasz; Musial, Witold

2013-01-01

In the course of research and development of a new pharmaceutical formulation of azelaic acid in the liposomal form, we developed a rapid and accurate method for the detection of impurities using high-performance liquid chromatography. A chromatographic column from Merck (Purospher Star RP C18, 250-4 mm (5 μm) was used in the assay, and the mobile phase gradient consisted of three phases: A--methanol : water (5 : 95) + 1.5% (v/v) acetic acid; B--water : methanol (5 : 95) + 1.5% (v/v) acetic acid; and C--chloroform. Detection of the impurities and the active substance was performed by an evaporative light-scattering detector. The method was validated for selectivity, system precision, method precision, limit of detection, and response rates. The proposed method can be used to detect impurities in the liposomal formulation of azelaic acid. The method enables separation of azelaic acid from the identified and unidentified impurities and from the excipients used in the drug form.

Exploring three faint source detections methods for aperture synthesis radio images

NASA Astrophysics Data System (ADS)

Peracaula, M.; Torrent, A.; Masias, M.; Lladó, X.; Freixenet, J.; Martí, J.; Sánchez-Sutil, J. R.; Muñoz-Arjonilla, A. J.; Paredes, J. M.

2015-04-01

Wide-field radio interferometric images often contain a large population of faint compact sources. Due to their low intensity/noise ratio, these objects can be easily missed by automated detection methods, which have been classically based on thresholding techniques after local noise estimation. The aim of this paper is to present and analyse the performance of several alternative or complementary techniques to thresholding. We compare three different algorithms to increase the detection rate of faint objects. The first technique consists of combining wavelet decomposition with local thresholding. The second technique is based on the structural behaviour of the neighbourhood of each pixel. Finally, the third algorithm uses local features extracted from a bank of filters and a boosting classifier to perform the detections. The methods' performances are evaluated using simulations and radio mosaics from the Giant Metrewave Radio Telescope and the Australia Telescope Compact Array. We show that the new methods perform better than well-known state of the art methods such as SEXTRACTOR, SAD and DUCHAMP at detecting faint sources of radio interferometric images.

Chemical sensing thresholds for mine detection dogs

NASA Astrophysics Data System (ADS)

Phelan, James M.; Barnett, James L.

2002-08-01

Mine detection dogs have been found to be an effective method to locate buried landmines. The capabilities of the canine olfaction method are from a complex combination of training and inherent capacity of the dog for odor detection. The purpose of this effort was to explore the detection thresholds of a limited group of dogs that were trained specifically for landmine detection. Soils were contaminated with TNT and 2,4-DNT to develop chemical vapor standards to present to the dogs. Soils contained ultra trace levels of TNT and DNT, which produce extremely low vapor levels. Three groups of dogs were presented the headspace vapors from the contaminated soils in work environments for each dog group. One positive sample was placed among several that contained clean soils and, the location and vapor source (strength, type) was frequently changed. The detection thresholds for the dogs were determined from measured and extrapolated dilution of soil chemical residues and, estimated soil vapor values using phase partitioning relationships. The results showed significant variances in dog sensing thresholds, where some dogs could sense the lowest levels and others had trouble with even the highest source. The remarkable ultra-trace levels detectable by the dogs are consistent with the ultra-trace chemical residues derived from buried landmines; however, poor performance may go unnoticed without periodic challenge tests at levels consistent with performance requirements.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2008-05-15

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

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

PubMed

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

2014-12-01

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

Bayesian Peptide Peak Detection for High Resolution TOF Mass Spectrometry.

PubMed

Zhang, Jianqiu; Zhou, Xiaobo; Wang, Honghui; Suffredini, Anthony; Zhang, Lin; Huang, Yufei; Wong, Stephen

2010-11-01

In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10 000-15 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert's visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition.

Bayesian Peptide Peak Detection for High Resolution TOF Mass Spectrometry

PubMed Central

Zhang, Jianqiu; Zhou, Xiaobo; Wang, Honghui; Suffredini, Anthony; Zhang, Lin; Huang, Yufei; Wong, Stephen

2011-01-01

In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10 000–15 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert’s visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition. PMID:21544266

Eucapnic Voluntary Hyperventilation to Detect Exercise-Induced Bronchoconstriction in Cystic Fibrosis.

PubMed

Kirkby, Stephen E; Hayes, Don; Parsons, Jonathan P; Wisely, Clayton E; Kopp, Ben; McCoy, Karen S; Mastronarde, John G

2015-10-01

Exercise-induced bronchoconstriction (EIB) has not been well studied in cystic fibrosis (CF), and eucapnic voluntary hyperventilation (EVH) testing has not been used as an objective assessment of EIB in CF to date. A prospective cohort pilot study was completed where standard EVH testing was completed by 10 CF patients with forced expiratory volume in 1 s (FEV1) ≥70% of predicted. All patients also completed a cardiopulmonary exercise test (CPET) with pre- and post-CPET spirometry as a comparative method of detecting EIB. No adverse events occurred with EVH testing. A total of 20% (2/10) patients were diagnosed with EIB by means of EVH. Both patients had clinical symptoms consistent with EIB. No patient had a CPET-based exercise challenge consistent with EIB. EVH testing was safe and effective in the objective assessment for EIB in patients with CF who had well-preserved lung function. It may be a more sensitive method of detecting EIB then exercise challenge.

A novel visual saliency detection method for infrared video sequences

NASA Astrophysics Data System (ADS)

Wang, Xin; Zhang, Yuzhen; Ning, Chen

2017-12-01

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

Innovative electrochemical approach for an early detection of microRNAs.

PubMed

Lusi, E A; Passamano, M; Guarascio, P; Scarpa, A; Schiavo, L

2009-04-01

The recent findings of circulating cell-free tissue specific microRNAs in the systemic circulation and the potential of their use as specific markers of disease highlight the need to make microRNAs testing a routine part of medical care. At the present time, microRNAs are detected by long and laborious techniques such as Northern blot, RT-PCR, and microarrays. The originality of our work consists in performing microRNAs detection through an electrochemical genosensor using a label-free method. We were able to directly detect microRNAs without the need of PCR and a labeling reaction. The test is simple, very fast and ultrasensitive, with a detection limit of 0.1 pmol. Particularly feasible for a routine microRNAs detection in serum and other biological samples, our technical approach would be of great scientific value and become a common method for simple miRNAs routine detection in both clinical and research settings.

INFLUENCE OF DIET ON THE PERFORMANCE OF BOVINE FECAL POLLUTION DETECTION METHODS AND MICROBIAL POPULATION STRUCTURE

EPA Science Inventory

ABSTRACT Background and Aims. Waterborne diseases originating from bovine fecal material are a significant public health issue. Ensuring water quality requires the use of methods that can consistently identify pollution across a broad range of management practices. One practi...

An operant-based detection method for inferring tinnitus in mice.

PubMed

Zuo, Hongyan; Lei, Debin; Sivaramakrishnan, Shobhana; Howie, Benjamin; Mulvany, Jessica; Bao, Jianxin

2017-11-01

Subjective tinnitus is a hearing disorder in which a person perceives sound when no external sound is present. It can be acute or chronic. Because our current understanding of its pathology is incomplete, no effective cures have yet been established. Mouse models are useful for studying the pathophysiology of tinnitus as well as for developing therapeutic treatments. We have developed a new method for determining acute and chronic tinnitus in mice, called sound-based avoidance detection (SBAD). The SBAD method utilizes one paradigm to detect tinnitus and another paradigm to monitor possible confounding factors, such as motor impairment, loss of motivation, and deficits in learning and memory. The SBAD method has succeeded in monitoring both acute and chronic tinnitus in mice. Its detection ability is further validated by functional studies demonstrating an abnormal increase in neuronal activity in the inferior colliculus of mice that had previously been identified as having tinnitus by the SBAD method. The SBAD method provides a new means by which investigators can detect tinnitus in a single mouse accurately and with more control over potential confounding factors than existing methods. This work establishes a new behavioral method for detecting tinnitus in mice. The detection outcome is consistent with functional validation. One key advantage of mouse models is they provide researchers the opportunity to utilize an extensive array of genetic tools. This new method could lead to a deeper understanding of the molecular pathways underlying tinnitus pathology. Copyright © 2017 Elsevier B.V. All rights reserved.

Devices and methods to detect and quantify trace gases

DOEpatents

Allendorf, Mark D.; Robinson, Alex

2016-05-03

Sensing devices based on a surface acoustic wave ("SAW") device coated with an absorbent crystalline or amorphous layer for detecting at least one chemical analyte in a gaseous carrier. Methods for detecting the presence of a chemical analyte in a gaseous carrier using such devices are also disclosed. The sensing devices and methods for their use may be configured for sensing chemical analytes selected from the group consisting of water vapor, carbon dioxide, methanol, ethanol, carbon monoxide, nitric oxide, nitrous oxide, organic amines, organic compounds containing NO.sub.2 groups, halogenated hydrocarbons, acetone, hexane, toluene, isopropanol, alcohols, alkanes, alkenes, benzene, functionalized aromatics, ammonia (NH.sub.3), phosgene (COCl.sub.2), sulfur mustard, nerve agents, sulfur dioxide, tetrahydrofuran (THF) and methyltertbutyl ether (MTBE) and combinations thereof.

DNA methods: critical review of innovative approaches.

PubMed

Kok, Esther J; Aarts, Henk J M; Van Hoef, A M Angeline; Kuiper, Harry A

2002-01-01

The presence of ingredients derived from genetically modified organisms (GMOs) in food products in the market place is subject to a number of European regulations that stipulate which product consisting of or containing GMO-derived ingredients should be labeled as such. In order to maintain these labeling requirements, a variety of different GMO detection methods have been developed to screen for either the presence of DNA or protein derived from (approved) GM varieties. Recent incidents where unapproved GM varieties entered the European market show that more powerful GMO detection and identification methods will be needed to maintain European labeling requirements in an adequate, efficient, and cost-effective way. This report discusses the current state-of-the-art as well as future developments in GMO detection.

Determining the 95% limit of detection for waterborne pathogen analyses from primary concentration to qPCR

USDA-ARS?s Scientific Manuscript database

The limit of detection (LOD) for qPCR-based analyses is not consistently defined or determined in studies on waterborne pathogens. Moreover, the LODs reported often reflect the qPCR assay rather than the entire sample process. Our objective was to develop a method to determine the 95% LOD (lowest co...

Retrieving hydrological connectivity from empirical causality in karst systems

NASA Astrophysics Data System (ADS)

Delforge, Damien; Vanclooster, Marnik; Van Camp, Michel; Poulain, Amaël; Watlet, Arnaud; Hallet, Vincent; Kaufmann, Olivier; Francis, Olivier

2017-04-01

Because of their complexity, karst systems exhibit nonlinear dynamics. Moreover, if one attempts to model a karst, the hidden behavior complicates the choice of the most suitable model. Therefore, both intense investigation methods and nonlinear data analysis are needed to reveal the underlying hydrological connectivity as a prior for a consistent physically based modelling approach. Convergent Cross Mapping (CCM), a recent method, promises to identify causal relationships between time series belonging to the same dynamical systems. The method is based on phase space reconstruction and is suitable for nonlinear dynamics. As an empirical causation detection method, it could be used to highlight the hidden complexity of a karst system by revealing its inner hydrological and dynamical connectivity. Hence, if one can link causal relationships to physical processes, the method should show great potential to support physically based model structure selection. We present the results of numerical experiments using karst model blocks combined in different structures to generate time series from actual rainfall series. CCM is applied between the time series to investigate if the empirical causation detection is consistent with the hydrological connectivity suggested by the karst model.

Motion-compensated detection of heart rate based on the time registration adaptive filter

NASA Astrophysics Data System (ADS)

Yang, Lei; Zhou, Jinsong; Jing, Juanjuan; Li, Yacan; Wei, Lidong; Feng, Lei; He, Xiaoying; Bu, Meixia; Fu, Xilu

2018-01-01

A non-contact heart rate detection method based on the dual-wavelength technique is proposed and demonstrated experimentally. The heart rate is obtained based on the PhotoPlethysmoGraphy (PPG). Each detection module uses the reflection detection probe which is composed of the LED and the photodiode. It is a well-known fact that the differences in the circuits of two detection modules result in different responses of two modules for motion artifacts. It will cause a time delay between the two signals. This poses a great challenge to compensate the motion artifacts during measurements. In order to solve this problem, we have firstly used the time registration and translated the signals to ensure that the two signals are consistent in time domain. Then the adaptive filter is used to compensate the motion artifacts. Moreover, the data obtained by using this non-contact detection system is compared with those of the conventional finger blood volume pulse (BVP) sensor by simultaneously measuring the heart rate of the subject. During the experiment, the left hand remains stationary and is detected by a conventional finger BVP sensor. Meanwhile, the moving palm of right hand is detected by the proposed system. The data obtained from the proposed non-contact system are consistent and comparable with that of the BVP sensor. This method can effectively suppress the interference caused by the two circuit differences and successfully compensate the motion artifacts. This technology can be used in medical and daily heart rate measurement.

Automatic Segmentation of Fluorescence Lifetime Microscopy Images of Cells Using Multi-Resolution Community Detection -A First Study

PubMed Central

Hu, Dandan; Sarder, Pinaki; Ronhovde, Peter; Orthaus, Sandra; Achilefu, Samuel; Nussinov, Zohar

2014-01-01

Inspired by a multi-resolution community detection (MCD) based network segmentation method, we suggest an automatic method for segmenting fluorescence lifetime (FLT) imaging microscopy (FLIM) images of cells in a first pilot investigation on two selected images. The image processing problem is framed as identifying segments with respective average FLTs against the background in FLIM images. The proposed method segments a FLIM image for a given resolution of the network defined using image pixels as the nodes and similarity between the FLTs of the pixels as the edges. In the resulting segmentation, low network resolution leads to larger segments, and high network resolution leads to smaller segments. Further, using the proposed method, the mean-square error (MSE) in estimating the FLT segments in a FLIM image was found to consistently decrease with increasing resolution of the corresponding network. The MCD method appeared to perform better than a popular spectral clustering based method in performing FLIM image segmentation. At high resolution, the spectral segmentation method introduced noisy segments in its output, and it was unable to achieve a consistent decrease in MSE with increasing resolution. PMID:24251410

Radiation detection method and system using the sequential probability ratio test

DOEpatents

Nelson, Karl E [Livermore, CA; Valentine, John D [Redwood City, CA; Beauchamp, Brock R [San Ramon, CA

2007-07-17

A method and system using the Sequential Probability Ratio Test to enhance the detection of an elevated level of radiation, by determining whether a set of observations are consistent with a specified model within a given bounds of statistical significance. In particular, the SPRT is used in the present invention to maximize the range of detection, by providing processing mechanisms for estimating the dynamic background radiation, adjusting the models to reflect the amount of background knowledge at the current point in time, analyzing the current sample using the models to determine statistical significance, and determining when the sample has returned to the expected background conditions.

Single Versus Multiple Events Error Potential Detection in a BCI-Controlled Car Game With Continuous and Discrete Feedback.

PubMed

Kreilinger, Alex; Hiebel, Hannah; Müller-Putz, Gernot R

2016-03-01

This work aimed to find and evaluate a new method for detecting errors in continuous brain-computer interface (BCI) applications. Instead of classifying errors on a single-trial basis, the new method was based on multiple events (MEs) analysis to increase the accuracy of error detection. In a BCI-driven car game, based on motor imagery (MI), discrete events were triggered whenever subjects collided with coins and/or barriers. Coins counted as correct events, whereas barriers were errors. This new method, termed ME method, combined and averaged the classification results of single events (SEs) and determined the correctness of MI trials, which consisted of event sequences instead of SEs. The benefit of this method was evaluated in an offline simulation. In an online experiment, the new method was used to detect erroneous MI trials. Such MI trials were discarded and could be repeated by the users. We found that, even with low SE error potential (ErrP) detection rates, feasible accuracies can be achieved when combining MEs to distinguish erroneous from correct MI trials. Online, all subjects reached higher scores with error detection than without, at the cost of longer times needed for completing the game. Findings suggest that ErrP detection may become a reliable tool for monitoring continuous states in BCI applications when combining MEs. This paper demonstrates a novel technique for detecting errors in online continuous BCI applications, which yields promising results even with low single-trial detection rates.

Evaluation of a colloidal gold immunochromatography assay in the detection of Treponema pallidum specific IgM antibody in syphilis serofast reaction patients: a serologic marker for the relapse and infection of syphilis.

PubMed

Lin, Li-Rong; Tong, Man-Li; Fu, Zuo-Gen; Dan, Bing; Zheng, Wei-Hong; Zhang, Chang-Gong; Yang, Tian-Ci; Zhang, Zhong-Ying

2011-05-01

Syphilis remains as a worldwide public health problem; hence, it is necessary to develop a new diagnostic approach that is easier and faster than conventional tests. A new testing method to detect Treponema pallidum IgM (TP-IgM), named colloidal gold immunochromatography assay (GICA), is presented in place of fluorescent treponemal antibody absorption (FTA-Abs). TP-IgM was detected using GICA developed on syphilis-specific recombinant proteins TPN17 and TPN47. The FTA-Abs IgM test was set as the gold standard. A GICA TP-IgM test was performed to detect syphilis in 1208 patients who received recommended therapy for syphilis for more than 1 year at the Xiamen Center of Clinical Laboratory in China from June 2005 to May 2009. One hundred blood donors were set up as control. The sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio were 98.21%, 99.04%, 93.75%, 99.73%, 102.3, and 0.018, respectively. Detection on 500 interference specimens indicated that the biological false-positive rate of the GICA test was extremely low and was free from other biological and chemical factors. The patients were divided into the following experimental groups based on the results of toluidine red unheated serum test (TRUST) and treponemal pallidum particle agglutination (TPPA): (1) the syphilis serofast reaction (SSR) group consisted of 411 cases with (+) TRUST and (+) TPPA, which exhibited no clinical manifestations of syphilis after 1 year of recommended syphilis treatment; (2) the serum cure group, which was further subdivided into group A, a group that consisted of 251 cases with (-) TRUST and (+) TPPA, and (3) group B, a group that consisted of 546 cases with (-) TRUST and (-) TPPA; and (4) the blood donor control group, which consisted of 100 healthy persons with (-) ELISA-TP and (-) TPPA. We used the FTA-Abs method and the GICA method to detect TP-IgM; the positive rate of TP-IgM in 411 SSR patients was 34.55% and 36.01%, respectively. However, in serum cure group A, the positive rate of TP-IgM was 10.36% and 11.16%, respectively. The χ(2) test revealed that there is a significant difference in the positive rate between these 2 groups (P < 0.01). The TP-IgM positive rate in the same group, as detected by the GICA method and the FTA-Abs method, had no significant difference in statistics. However, as detected by the GICA method and the FTA-Abs method, all the samples in serum cure group B and the control group were negative for TP-IgM. The TP-IgM-positive result demonstrated that active T. pallidum remained in the bodies of SSR patients. In summary, the characteristics of GICA TP-IgM correspond to that of FTA-Abs TP-IgM; this can be used as a serologic marker for the relapse and infection of syphilis in place of the conventional FTA-Abs IgM test. Copyright © 2011 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2016-01-01

Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated by OKTAL-SE. PMID:27447635

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

PubMed

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

2016-07-19

Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated by OKTAL-SE.

Determination of anthelmintic drug residues in milk using UPLC-MS/MS with rapid polarity switching

USDA-ARS?s Scientific Manuscript database

A new UPLC-MS/MS (ultra-performance liquid chromatography coupled to tandem mass spectrometry) method was developed and validated to detect 38 anthelmintic drug residues, consisting of benzimidazoles, avermectins and flukicides. A modified QuEChERS-type extraction method was developed with an added...

Scalable Track Detection in SAR CCD Images

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

Chow, James G; Quach, Tu-Thach

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988,more » up fr om 0.907 obtained by the current state-of-the-art method.« less

Advances in explosives analysis—part II: photon and neutron methods

DOE PAGES

Brown, Kathryn E.; Greenfield, Margo T.; McGrane, Shawn D.; ...

2015-10-07

The number and capability of explosives detection and analysis methods have increased dramatically since publication of the Analytical and Bioanalytical Chemistry special issue devoted to Explosives Analysis [Moore DS, Goodpaster JV, Anal Bioanal Chem 395:245–246, 2009]. Here we review and critically evaluate the latest (the past five years) important advances in explosives detection, with details of the improvements over previous methods, and suggest possible avenues towards further advances in, e.g., stand-off distance, detection limit, selectivity, and penetration through camouflage or packaging. Our review consists of two parts. Part I discussed methods based on animals, chemicals (including colorimetry, molecularly imprinted polymers,more » electrochemistry, and immunochemistry), ions (both ion-mobility spectrometry and mass spectrometry), and mechanical devices. In Part II, we review methods based on photons, from very energetic photons including X-rays and gamma rays down to the terahertz range, and neutrons.« less

Stepwise and stagewise approaches for spatial cluster detection.

PubMed

Xu, Jiale; Gangnon, Ronald E

2016-05-01

Spatial cluster detection is an important tool in many areas such as sociology, botany and public health. Previous work has mostly taken either a hypothesis testing framework or a 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 a tiny step size in each iteration. We study the features and performances of our proposed methods using simulations on idealized grids or real geographic areas. From the simulations, we compare the performance of the proposed methods in terms of estimation accuracy and power. These methods are applied to the the well-known New York leukemia data as well as Indiana poverty data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Advances in explosives analysis—part I. animal, chemical, ion, and mechanical methods

DOE PAGES

Brown, Kathryn E.; Greenfield, Margo T.; McGrane, Shawn D.; ...

2015-10-13

The number and capability of explosives detection and analysis methods have increased substantially since the publication of the Analytical and Bioanalytical Chemistry special issue devoted to Explosives Analysis (Moore and Goodpaster, Anal Bioanal Chem 395(2):245–246, 2009). We review and critically evaluate the latest (the past five years) important advances in explosives detection, with details of the improvements over previous methods, and suggest possible avenues towards further advances in, e.g., stand-off distance, detection limit, selectivity, and penetration through camouflage or packaging. The review consists of two parts. Moreover, Part I, reviews methods based on animals, chemicals (including colorimetry, molecularly imprinted polymers,more » electrochemistry, and immunochemistry), ions (both ion-mobility spectrometry and mass spectrometry), and mechanical devices. Part II will review methods based on photons, from very energetic photons including X-rays and gamma rays down to the terahertz range, and neutrons.« less

Multi-scale occupancy estimation and modelling using multiple detection methods

USGS Publications Warehouse

Nichols, James D.; Bailey, Larissa L.; O'Connell, Allan F.; Talancy, Neil W.; Grant, Evan H. Campbell; Gilbert, Andrew T.; Annand, Elizabeth M.; Husband, Thomas P.; Hines, James E.

2008-01-01

Occupancy estimation and modelling based on detection–nondetection data provide an effective way of exploring change in a species’ distribution across time and space in cases where the species is not always detected with certainty. Today, many monitoring programmes target multiple species, or life stages within a species, requiring the use of multiple detection methods. When multiple methods or devices are used at the same sample sites, animals can be detected by more than one method.We develop occupancy models for multiple detection methods that permit simultaneous use of data from all methods for inference about method-specific detection probabilities. Moreover, the approach permits estimation of occupancy at two spatial scales: the larger scale corresponds to species’ use of a sample unit, whereas the smaller scale corresponds to presence of the species at the local sample station or site.We apply the models to data collected on two different vertebrate species: striped skunks Mephitis mephitis and red salamanders Pseudotriton ruber. For striped skunks, large-scale occupancy estimates were consistent between two sampling seasons. Small-scale occupancy probabilities were slightly lower in the late winter/spring when skunks tend to conserve energy, and movements are limited to males in search of females for breeding. There was strong evidence of method-specific detection probabilities for skunks. As anticipated, large- and small-scale occupancy areas completely overlapped for red salamanders. The analyses provided weak evidence of method-specific detection probabilities for this species.Synthesis and applications. Increasingly, many studies are utilizing multiple detection methods at sampling locations. The modelling approach presented here makes efficient use of detections from multiple methods to estimate occupancy probabilities at two spatial scales and to compare detection probabilities associated with different detection methods. The models can be viewed as another variation of Pollock's robust design and may be applicable to a wide variety of scenarios where species occur in an area but are not always near the sampled locations. The estimation approach is likely to be especially useful in multispecies conservation programmes by providing efficient estimates using multiple detection devices and by providing device-specific detection probability estimates for use in survey design.

Rapid, On-Site, Ultrasensitive Melamine Quantitation Method for Protein Beverages Using Time-Resolved Fluorescence Detection Paper.

PubMed

Li, Guanghua; Wang, Du; Zhou, Aijun; Sun, Yimin; Zhang, Qi; Poapolathep, Amnart; Zhang, Li; Fan, Zhiyong; Zhang, Zhaowei; Li, Peiwu

2018-06-06

To ensure protein beverage safety and prevent illegal melamine use to artificially increase protein content, a rapid, on-site, ultrasensitive detection method for melamine must be developed because melamine is detrimental to human health. Herein, an ultrasensitive time-resolved fluorescence detection paper (TFDP) was developed to detect melamine in protein beverages within 15 min using a one-step sample preparation. The lower limits of detection were 0.89, 0.94, and 1.05 ng/mL, and the linear ranges were 2.67-150, 2.82-150, and 3.15-150 ng/mL (R 2 > 0.982) for peanut, walnut, and coconut beverages, respectively. The recovery rates were 85.86-110.60% with a coefficient of variation <7.80% in the spiking experiment. A high specificity was observed in the interferent experiment. When detecting real protein beverage samples, the TFDP and ultraperformance liquid chromatography-tandem mass spectrometer (UPLC-MS/MS) results were consistent. This method is a promising alternative for rapid, on-site detection of melamine in beverages.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

[Sensitivity and specificity of nested PCR pyrosequencing in hepatitis B virus drug resistance gene testing].

PubMed

Sun, Shumei; Zhou, Hao; Zhou, Bin; Hu, Ziyou; Hou, Jinlin; Sun, Jian

2012-05-01

To evaluate the sensitivity and specificity of nested PCR combined with pyrosequencing in the detection of HBV drug-resistance gene. RtM204I (ATT) mutant and rtM204 (ATG) nonmutant plasmids mixed at different ratios were detected for mutations using nested-PCR combined with pyrosequencing, and the results were compared with those by conventional PCR pyrosequencing to analyze the linearity and consistency of the two methods. Clinical specimens with different viral loads were examined for drug-resistant mutations using nested PCR pyrosequencing and nested PCR combined with dideoxy sequencing (Sanger) for comparison of the detection sensitivity and specificity. The fitting curves demonstrated good linearity of both conventional PCR pyrosequencing and nested PCR pyrosequencing (R(2)>0.99, P<0.05). Nested PCR showed a better consistency with the predicted value than conventional PCR, and was superior to conventional PCR for detection of samples containing 90% mutant plasmid. In the detection of clinical specimens, Sanger sequencing had a significantly lower sensitivity than nested PCR pyrosequencing (92% vs 100%, P<0.01). The detection sensitivity of Sanger sequencing varied with the viral loads, especially in samples with low viral copies (HBV DNA ≤3log10 copies/ml), where the sensitivity was 78%, significantly lower than that of pyrosequencing (100%, P<0.01). Neither of the two methods yielded positive results for the negative control samples, suggesting their good specificity. Compared with nested PCR and Sanger sequencing method, nested PCR pyrosequencing has a higher sensitivity especially in clinical specimens with low viral copies, which can be important for early detection of HBV mutant strains and hence more effective clinical management.

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

Jackson, Timothy D; Hollenbach, Daniel F; Shedlock, Daniel

Radiography by Selective Detection (RSD), was investigated for its ability to determine the presence and types of defects in a UO{sub 2} fuel rod surrounded by zirconium cladding. Images created using a Monte Carlo model compared favorably with actual X-ray backscatter images from mock fuel rods. A fuel rod was modeled as a rectangular parallelepiped with zirconium cladding, and pencil beam X-ray sources of 160 kVp (79 keV avg) and 480 kVp (218 keV avg) were generated using the Monte Carlo N-Particle Transport Code to attempt to image void and palladium (Pd) defects in the interior and on the surfacemore » of the fuel pellet. It was found that the 160 kVp spectrum was unable to detect the presence of interior defects, whereas the 480 kVp spectrum detected them with both the standard and the RSD backscatter methods, though the RSD method was very inefficient. It was also found that both energy spectra were able to detect void and Pd defects on the surface using both imaging methods. Additionally, two mock fuel rods were imaged using a backscatter X-ray imaging system, one consisting of hafnium pellets in a Zircaloy-4 cladding and the other consisting of steel pellets in a Zircalloy-4 cladding which was then encased in a steel cladding (a double encapsulation configuration employed in irradiation and experiments). It was found that the system was capable of detecting individual HfO{sub 2} pellets in a Zircaloy-4 cladding and may be capable of detecting individual steel pellets in the double-encapsulated sample. It is expected that the system would also be capable of detecting individual UO{sub 2} pellets in a Zircaloy-4 cladding, though no UO{sub 2} fuel rod was available for imaging.« less

Detecting Gear Tooth Fatigue Cracks in Advance of Complete Fracture

NASA Technical Reports Server (NTRS)

Zakrajsek, James J.; Lewicki, David G.

1996-01-01

Results of using vibration-based methods to detect gear tooth fatigue cracks are presented. An experimental test rig was used to fail a number of spur gear specimens through bending fatigue. The gear tooth fatigue crack in each test was initiated through a small notch in the fillet area of a tooth on the gear. The primary purpose of these tests was to verify analytical predictions of fatigue crack propagation direction and rate as a function of gear rim thickness. The vibration signal from a total of three tests was monitored and recorded for gear fault detection research. The damage consisted of complete rim fracture on the two thin rim gears and single tooth fracture on the standard full rim test gear. Vibration-based fault detection methods were applied to the vibration signal both on-line and after the tests were completed. The objectives of this effort were to identify methods capable of detecting the fatigue crack and to determine how far in advance of total failure positive detection was given. Results show that the fault detection methods failed to respond to the fatigue crack prior to complete rim fracture in the thin rim gear tests. In the standard full rim gear test all of the methods responded to the fatigue crack in advance of tooth fracture; however, only three of the methods responded to the fatigue crack in the early stages of crack propagation.

A simplified implementation of edge detection in MATLAB is faster and more sensitive than fast fourier transform for actin fiber alignment quantification.

PubMed

Kemeny, Steven Frank; Clyne, Alisa Morss

2011-04-01

Fiber alignment plays a critical role in the structure and function of cells and tissues. While fiber alignment quantification is important to experimental analysis and several different methods for quantifying fiber alignment exist, many studies focus on qualitative rather than quantitative analysis perhaps due to the complexity of current fiber alignment methods. Speed and sensitivity were compared in edge detection and fast Fourier transform (FFT) for measuring actin fiber alignment in cells exposed to shear stress. While edge detection using matrix multiplication was consistently more sensitive than FFT, image processing time was significantly longer. However, when MATLAB functions were used to implement edge detection, MATLAB's efficient element-by-element calculations and fast filtering techniques reduced computation cost 100 times compared to the matrix multiplication edge detection method. The new computation time was comparable to the FFT method, and MATLAB edge detection produced well-distributed fiber angle distributions that statistically distinguished aligned and unaligned fibers in half as many sample images. When the FFT sensitivity was improved by dividing images into smaller subsections, processing time grew larger than the time required for MATLAB edge detection. Implementation of edge detection in MATLAB is simpler, faster, and more sensitive than FFT for fiber alignment quantification.

Improved Conflict Detection for Reducing Operational Errors in Air Traffic Control

NASA Technical Reports Server (NTRS)

Paielli, Russell A.; Erzberger, Hainz

2003-01-01

An operational error is an incident in which an air traffic controller allows the separation between two aircraft to fall below the minimum separation standard. The rates of such errors in the US have increased significantly over the past few years. This paper proposes new detection methods that can help correct this trend by improving on the performance of Conflict Alert, the existing software in the Host Computer System that is intended to detect and warn controllers of imminent conflicts. In addition to the usual trajectory based on the flight plan, a "dead-reckoning" trajectory (current velocity projection) is also generated for each aircraft and checked for conflicts. Filters for reducing common types of false alerts were implemented. The new detection methods were tested in three different ways. First, a simple flightpath command language was developed t o generate precisely controlled encounters for the purpose of testing the detection software. Second, written reports and tracking data were obtained for actual operational errors that occurred in the field, and these were "replayed" to test the new detection algorithms. Finally, the detection methods were used to shadow live traffic, and performance was analysed, particularly with regard to the false-alert rate. The results indicate that the new detection methods can provide timely warnings of imminent conflicts more consistently than Conflict Alert.

An intelligent detecting system for permeability prediction of MBR.

PubMed

Han, Honggui; Zhang, Shuo; Qiao, Junfei; Wang, Xiaoshuang

2018-01-01

The membrane bioreactor (MBR) has been widely used to purify wastewater in wastewater treatment plants. However, a critical difficulty of the MBR is membrane fouling. To reduce membrane fouling, in this work, an intelligent detecting system is developed to evaluate the performance of MBR by predicting the membrane permeability. This intelligent detecting system consists of two main parts. First, a soft computing method, based on the partial least squares method and the recurrent fuzzy neural network, is designed to find the nonlinear relations between the membrane permeability and the other variables. Second, a complete new platform connecting the sensors and the software is built, in order to enable the intelligent detecting system to handle complex algorithms. Finally, the simulation and experimental results demonstrate the reliability and effectiveness of the proposed intelligent detecting system, underlying the potential of this system for the online membrane permeability for detecting membrane fouling of MBR.

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

PubMed

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

2009-02-01

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

Microbial detection method based on sensing molecular hydrogen

NASA Technical Reports Server (NTRS)

Wilkins, J. R.; Stoner, G. E.; Boykin, E. H.

1974-01-01

A simple method for detecting bacteria, based on the time of hydrogen evolution, was developed and tested against various members of the Enterobacteriaceae group. The test system consisted of (1) two electrodes, platinum and a reference electrode, (2) a buffer amplifier, and (3) a strip-chart recorder. Hydrogen evolution was measured by an increase in voltage in the negative (cathodic) direction. A linear relationship was established between inoculum size and the time hydrogen was detected (lag period). Lag times ranged from 1 h for 1 million cells/ml to 7 h for 1 cell/ml. For each 10-fold decrease in inoculum, length of the lag period increased 60 to 70 min. Based on the linear relationship between inoculum and lag period, these results indicate the potential application of the hydrogen-sensing method for rapidly detecting coliforms and other gas-producing microorganisms in a variety of clinical, food, and other samples.

Flag-based detection of weak gas signatures in long-wave infrared hyperspectral image sequences

NASA Astrophysics Data System (ADS)

Marrinan, Timothy; Beveridge, J. Ross; Draper, Bruce; Kirby, Michael; Peterson, Chris

2016-05-01

We present a flag manifold based method for detecting chemical plumes in long-wave infrared hyperspectral movies. The method encodes temporal and spatial information related to a hyperspectral pixel into a flag, or nested sequence of linear subspaces. The technique used to create the flags pushes information about the background clutter, ambient conditions, and potential chemical agents into the leading elements of the flags. Exploiting this temporal information allows for a detection algorithm that is sensitive to the presence of weak signals. This method is compared to existing techniques qualitatively on real data and quantitatively on synthetic data to show that the flag-based algorithm consistently performs better on data when the SINRdB is low, and beats the ACE and MF algorithms in probability of detection for low probabilities of false alarm even when the SINRdB is high.

[A computer tomography assisted method for the automatic detection of region of interest in dynamic kidney images].

PubMed

Jing, Xueping; Zheng, Xiujuan; Song, Shaoli; Liu, Kai

2017-12-01

Glomerular filtration rate (GFR), which can be estimated by Gates method with dynamic kidney single photon emission computed tomography (SPECT) imaging, is a key indicator of renal function. In this paper, an automatic computer tomography (CT)-assisted detection method of kidney region of interest (ROI) is proposed to achieve the objective and accurate GFR calculation. In this method, the CT coronal projection image and the enhanced SPECT synthetic image are firstly generated and registered together. Then, the kidney ROIs are delineated using a modified level set algorithm. Meanwhile, the background ROIs are also obtained based on the kidney ROIs. Finally, the value of GFR is calculated via Gates method. Comparing with the clinical data, the GFR values estimated by the proposed method were consistent with the clinical reports. This automatic method can improve the accuracy and stability of kidney ROI detection for GFR calculation, especially when the kidney function has been severely damaged.

Monostatic ultra-wideband GPR antenna for through wall detection

NASA Astrophysics Data System (ADS)

Ali, Jawad; Abdullah, Noorsaliza; Yahya, Roshayati; Naeem, Taimoor

2017-11-01

The aim of this paper is to present a monostatic arc-shaped ultra-wideband (UWB) printed monopole antenna system with 3-16 GHz frequency bandwidth suitable for through-wall detection. Ground penetrating radar (GPR) technique is used for detection with the gain of 6.2 dB achieved for the proposed antenna using defected ground structure (DGS) method. To serve the purpose, a simulation experiment of through-wall detection model is constructed which consists of a monostatic antenna act as transmitter and receiver, concrete wall and human skin model. The time domain reflection of obtained result is then analysed for target detection.

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

PubMed

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

2016-03-15

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

Source Detection with Bayesian Inference on ROSAT All-Sky Survey Data Sample

NASA Astrophysics Data System (ADS)

Guglielmetti, F.; Voges, W.; Fischer, R.; Boese, G.; Dose, V.

2004-07-01

We employ Bayesian inference for the joint estimation of sources and background on ROSAT All-Sky Survey (RASS) data. The probabilistic method allows for detection improvement of faint extended celestial sources compared to the Standard Analysis Software System (SASS). Background maps were estimated in a single step together with the detection of sources without pixel censoring. Consistent uncertainties of background and sources are provided. The source probability is evaluated for single pixels as well as for pixel domains to enhance source detection of weak and extended sources.

Microbial Profiles and Detection Techniques in Peri-Implant Diseases: a Systematic Review

PubMed Central

Padial-Molina, Miguel; López-Martínez, Jesús; O’Valle, Francisco

2016-01-01

ABSTRACT Objectives To describe the microbial profiles of peri-implant diseases and the main detection methods. Material and Methods A literature search was performed in MEDLINE via PubMed database to identify studies on microbial composition of peri-implant surfaces in humans published in the last 5 years. Studies had to have clear implant status definition for health, peri-implant mucositis and/or peri-implantitis and specifically study microbial composition of the peri-implant sulcus. Results A total of 194 studies were screened and 47 included. Peri-implant sites are reported to be different microbial ecosystems compared to periodontal sites. However, differences between periodontal and peri-implant health and disease are not consistent across all studies, possibly due to the bias introduced by the microbial detection technique. New methods non species-oriented are being used to find ‘unexpected’ microbiota not previously described in these scenarios. Conclusions Microbial profile of peri-implant diseases usually includes classic periodontopathogens. However, correlation between studies is difficult, particularly because of the use of different detection methods. New metagenomic techniques should be promoted for future studies to avoid detection bias. PMID:27833735

Feature-Based Retinal Image Registration Using D-Saddle Feature

PubMed Central

Hasikin, Khairunnisa; A. Karim, Noor Khairiah; Ahmedy, Fatimah

2017-01-01

Retinal image registration is important to assist diagnosis and monitor retinal diseases, such as diabetic retinopathy and glaucoma. However, registering retinal images for various registration applications requires the detection and distribution of feature points on the low-quality region that consists of vessels of varying contrast and sizes. A recent feature detector known as Saddle detects feature points on vessels that are poorly distributed and densely positioned on strong contrast vessels. Therefore, we propose a multiresolution difference of Gaussian pyramid with Saddle detector (D-Saddle) to detect feature points on the low-quality region that consists of vessels with varying contrast and sizes. D-Saddle is tested on Fundus Image Registration (FIRE) Dataset that consists of 134 retinal image pairs. Experimental results show that D-Saddle successfully registered 43% of retinal image pairs with average registration accuracy of 2.329 pixels while a lower success rate is observed in other four state-of-the-art retinal image registration methods GDB-ICP (28%), Harris-PIIFD (4%), H-M (16%), and Saddle (16%). Furthermore, the registration accuracy of D-Saddle has the weakest correlation (Spearman) with the intensity uniformity metric among all methods. Finally, the paired t-test shows that D-Saddle significantly improved the overall registration accuracy of the original Saddle. PMID:29204257

Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers.

PubMed

Shu, Ting; Zhang, Bob; Tang, Yuan Yan

2017-01-01

At present, heart disease is the number one cause of death worldwide. Traditionally, heart disease is commonly detected using blood tests, electrocardiogram, cardiac computerized tomography scan, cardiac magnetic resonance imaging, and so on. However, these traditional diagnostic methods are time consuming and/or invasive. In this paper, we propose an effective noninvasive computerized method based on facial images to quantitatively detect heart disease. Specifically, facial key block color features are extracted from facial images and analyzed using the Probabilistic Collaborative Representation Based Classifier. The idea of facial key block color analysis is founded in Traditional Chinese Medicine. A new dataset consisting of 581 heart disease and 581 healthy samples was experimented by the proposed method. In order to optimize the Probabilistic Collaborative Representation Based Classifier, an analysis of its parameters was performed. According to the experimental results, the proposed method obtains the highest accuracy compared with other classifiers and is proven to be effective at heart disease detection.

Shadow-Based Vehicle Detection in Urban Traffic

PubMed Central

Ibarra-Arenado, Manuel; Tjahjadi, Tardi; Pérez-Oria, Juan; Robla-Gómez, Sandra; Jiménez-Avello, Agustín

2017-01-01

Vehicle detection is a fundamental task in Forward Collision Avoiding Systems (FACS). Generally, vision-based vehicle detection methods consist of two stages: hypotheses generation and hypotheses verification. In this paper, we focus on the former, presenting a feature-based method for on-road vehicle detection in urban traffic. Hypotheses for vehicle candidates are generated according to the shadow under the vehicles by comparing pixel properties across the vertical intensity gradients caused by shadows on the road, and followed by intensity thresholding and morphological discrimination. Unlike methods that identify the shadow under a vehicle as a road region with intensity smaller than a coarse lower bound of the intensity for road, the thresholding strategy we propose determines a coarse upper bound of the intensity for shadow which reduces false positives rates. The experimental results are promising in terms of detection performance and robustness in day time under different weather conditions and cluttered scenarios to enable validation for the first stage of a complete FACS. PMID:28448465

Point pattern match-based change detection in a constellation of previously detected objects

DOEpatents

Paglieroni, David W.

2016-06-07

A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

Hybrid Clustering And Boundary Value Refinement for Tumor Segmentation using Brain MRI

NASA Astrophysics Data System (ADS)

Gupta, Anjali; Pahuja, Gunjan

2017-08-01

The method of brain tumor segmentation is the separation of tumor area from Brain Magnetic Resonance (MR) images. There are number of methods already exist for segmentation of brain tumor efficiently. However it’s tedious task to identify the brain tumor from MR images. The segmentation process is extraction of different tumor tissues such as active, tumor, necrosis, and edema from the normal brain tissues such as gray matter (GM), white matter (WM), as well as cerebrospinal fluid (CSF). As per the survey study, most of time the brain tumors are detected easily from brain MR image using region based approach but required level of accuracy, abnormalities classification is not predictable. The segmentation of brain tumor consists of many stages. Manually segmenting the tumor from brain MR images is very time consuming hence there exist many challenges in manual segmentation. In this research paper, our main goal is to present the hybrid clustering which consists of Fuzzy C-Means Clustering (for accurate tumor detection) and level set method(for handling complex shapes) for the detection of exact shape of tumor in minimal computational time. using this approach we observe that for a certain set of images 0.9412 sec of time is taken to detect tumor which is very less in comparison to recent existing algorithm i.e. Hybrid clustering (Fuzzy C-Means and K Means clustering).

HPLC detection of soluble carbohydrates involved in mannitol and trehalose metabolism in the edible mushroom Agaricus bisporus.

PubMed

Wannet, W J; Hermans, J H; van Der Drift, C; Op Den Camp, H J

2000-02-01

A convenient and sensitive method was developed to separate and detect various types of carbohydrates (polyols, mono- and disaccharides, and phosphorylated sugars) simultaneously using high-performance liquid chromatography (HPLC). The method consists of a chromatographic separation on a CarboPac PA1 anion-exchange analytical column followed by pulsed amperometric detection. In a single run (43 min) 13 carbohydrates were readily resolved. Calibration plots were linear over the ranges of 5-25 microM to 1. 0-1.5 mM. The reliable and fast analysis technique, avoiding derivatization steps and long run times, was used to determine the levels of carbohydrates involved in mannitol and trehalose metabolism in the edible mushroom Agaricus bisporus. Moreover, the method was used to study the trehalose phosphorylase reaction.

Anabolic agents: recent strategies for their detection and protection from inadvertent doping

PubMed Central

Geyer, Hans; Schänzer, Wilhelm; Thevis, Mario

2014-01-01

According to the World Anti-Doping Agency (WADA) Prohibited List, anabolic agents consist of exogenous anabolic androgenic steroids (AAS), endogenous AAS and other anabolic agents such as clenbuterol and selective androgen receptor modulators (SARMs). Currently employed strategies for their improved detection include the prolongation of the detection windows for exogenous AAS, non-targeted and indirect analytical approaches for the detection of modified steroids (designer steroids), the athlete’s biological passport and isotope ratio mass spectrometry for the detection of the misuse of endogenous AAS, as well as preventive doping research for the detection of SARMs. The recent use of these strategies led to 4–80-fold increases of adverse analytical findings for exogenous AAS, to the detection of the misuse of new designer steroids, to adverse analytical findings of different endogenous AAS and to the first adverse analytical findings of SARMs. The strategies of the antidoping research are not only focused on the development of methods to catch the cheating athlete but also to protect the clean athlete from inadvertent doping. Within the past few years several sources of inadvertent doping with anabolic agents have been identified. Among these are nutritional supplements adulterated with AAS, meat products contaminated with clenbuterol, mycotoxin (zearalenone) contamination leading to zeranol findings, and natural products containing endogenous AAS. The protection strategy consists of further investigations in case of reasonable suspicion of inadvertent doping, publication of the results, education of athletes and development of methods to differentiate between intentional and unintentional doping. PMID:24632537

Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis*

PubMed Central

Gillet, Ludovic C.; Navarro, Pedro; Tate, Stephen; Röst, Hannes; Selevsek, Nathalie; Reiter, Lukas; Bonner, Ron; Aebersold, Ruedi

2012-01-01

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400–1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics. PMID:22261725

Wavefront detection method of a single-sensor based adaptive optics system.

PubMed

Wang, Chongchong; Hu, Lifa; Xu, Huanyu; Wang, Yukun; Li, Dayu; Wang, Shaoxin; Mu, Quanquan; Yang, Chengliang; Cao, Zhaoliang; Lu, Xinghai; Xuan, Li

2015-08-10

In adaptive optics system (AOS) for optical telescopes, the reported wavefront sensing strategy consists of two parts: a specific sensor for tip-tilt (TT) detection and another wavefront sensor for other distortions detection. Thus, a part of incident light has to be used for TT detection, which decreases the light energy used by wavefront sensor and eventually reduces the precision of wavefront correction. In this paper, a single Shack-Hartmann wavefront sensor based wavefront measurement method is presented for both large amplitude TT and other distortions' measurement. Experiments were performed for testing the presented wavefront method and validating the wavefront detection and correction ability of the single-sensor based AOS. With adaptive correction, the root-mean-square of residual TT was less than 0.2 λ, and a clear image was obtained in the lab. Equipped on a 1.23-meter optical telescope, the binary stars with angle distance of 0.6″ were clearly resolved using the AOS. This wavefront measurement method removes the separate TT sensor, which not only simplifies the AOS but also saves light energy for subsequent wavefront sensing and imaging, and eventually improves the detection and imaging capability of the AOS.

Induced electric currents in the Alaska oil pipeline measured by gradient, fluxgate, and SQUID magnetometers

NASA Technical Reports Server (NTRS)

Campbell, W. H.; Zimmerman, J. E.

1979-01-01

The field gradient method for observing the electric currents in the Alaska pipeline provided consistent values for both the fluxgate and SQUID method of observation. These currents were linearly related to the regularly measured electric and magnetic field changes. Determinations of pipeline current were consistent with values obtained by a direct connection, current shunt technique at a pipeline site about 9.6 km away. The gradient method has the distinct advantage of portability and buried- pipe capability. Field gradients due to the pipe magnetization, geological features, or ionospheric source currents do not seem to contribute a measurable error to such pipe current determination. The SQUID gradiometer is inherently sensitive enough to detect very small currents in a linear conductor at 10 meters, or conversely, to detect small currents of one amphere or more at relatively great distances. It is fairly straightforward to achieve imbalance less than one part in ten thousand, and with extreme care, one part in one million or better.

A novel method for the identification of inorganic and organic gunshot residue particles of lead-free ammunitions from the hands of shooters using scanning laser ablation-ICPMS and Raman micro-spectroscopy.

PubMed

Abrego, Zuriñe; Grijalba, Nagore; Unceta, Nora; Maguregui, Maite; Sanchez, Alicia; Fernández-Isla, Alberto; Goicolea, M Aranzazu; Barrio, Ramón J

2014-12-07

A method based on scanning laser ablation and inductively coupled plasma-mass spectrometry (SLA-ICPMS) and Raman micro-spectroscopy for the detection and identification of compounds consistent with gunshot residue particles (GSR) has been developed. The method has been applied to the characterization of particles resulting from the discharge of firearms using lead-free ammunition. Modified tape lifts were used to collect the inorganic and organic residues from skin surfaces in a single sample. Using SLA-ICPMS, aggregates related to the composition of the ammunition, such as Cu-Zn-Sn, Zr-Sr, Cu-Zn, Al-Ti, or Al-Sr-Zr were detected, but this composition is only consistent with GSR from lead-free ammunitions. Additional evidence was provided by micro-Raman spectroscopy, which identified the characteristic organic groups of the particles as centralite, diphenylamine or their nitrated derivatives, which are indicative of GSR.

Study of Wearable Knee Assistive Instruments for Walk Rehabilitation

NASA Astrophysics Data System (ADS)

Zhu, Yong; Nakamura, Masahiro; Ito, Noritaka; Fujimoto, Hiroshi; Horikuchi, Kenichi; Wakabayashi, Shojiro; Takahashi, Rei; Terada, Hidetsugu; Haro, Hirotaka

A wearable Knee Assistive Instrument for the walk rehabilitation was newly developed. Especially, this system aimed at supporting the rehabilitation for the post-TKA (Total Knee Arthroplasty) which is a popular surgery for aging people. This system consisted of an assisting mechanism for the knee joint, a hip joint support system and a foot pressure sensor system. The driving system of this robot consisted of a CPU board which generated the walking pattern, a Li-ion battery, DC motors with motor drivers, contact sensors to detect the state of foot and potentiometers to detect the hip joint angle. The control method was proposed to reproduce complex motion of knee joint as much as possible, and to increase hip or knee flexion angle. Especially, this method used the timing that heel left from the floor. This method included that the lower limb was raised to prevent a subject's fall. Also, the prototype of knee assisting system was tested. It was confirmed that the assisting system is useful.

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

PubMed

Li, Miao; Li, Jun; Zhou, Yiyu

2015-12-08

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

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

PubMed Central

Li, Miao; Li, Jun; Zhou, Yiyu

2015-01-01

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

Absolute quantification of DNA methylation using microfluidic chip-based digital PCR.

PubMed

Wu, Zhenhua; Bai, Yanan; Cheng, Zule; Liu, Fangming; Wang, Ping; Yang, Dawei; Li, Gang; Jin, Qinghui; Mao, Hongju; Zhao, Jianlong

2017-10-15

Hypermethylation of CpG islands in the promoter region of many tumor suppressor genes downregulates their expression and in a result promotes tumorigenesis. Therefore, detection of DNA methylation status is a convenient diagnostic tool for cancer detection. Here, we reported a novel method for the integrative detection of methylation by the microfluidic chip-based digital PCR. This method relies on methylation-sensitive restriction enzyme HpaII, which cleaves the unmethylated DNA strands while keeping the methylated ones intact. After HpaII treatment, the DNA methylation level is determined quantitatively by the microfluidic chip-based digital PCR with the lower limit of detection equal to 0.52%. To validate the applicability of this method, promoter methylation of two tumor suppressor genes (PCDHGB6 and HOXA9) was tested in 10 samples of early stage lung adenocarcinoma and their adjacent non-tumorous tissues. The consistency was observed in the analysis of these samples using our method and a conventional bisulfite pyrosequencing. Combining high sensitivity and low cost, the microfluidic chip-based digital PCR method might provide a promising alternative for the detection of DNA methylation and early diagnosis of epigenetics-related diseases. Copyright © 2017 Elsevier B.V. All rights reserved.

Site survey method and apparatus

DOEpatents

Oldham, James G.; Spencer, Charles R.; Begley, Carl L.; Meyer, H. Robert

1991-06-18

The disclosure of the invention is directed to a site survey ground vehicle based apparatus and method for automatically detecting source materials, such as radioactivity, marking the location of the source materials, such as with paint, and mapping the location of the source materials on a site. The apparatus of the invention is also useful for collecting and analyzing samples. The apparatus includes a ground vehicle, detectors mounted at the front of the ground vehicle, and individual detector supports which follow somewhat irregular terrain to allow consistent and accurate detection, and autolocation equipment.

Site survey method and apparatus

DOEpatents

Oldham, J.G.; Spencer, C.R.; Begley, C.L.; Meyer, H.R.

1991-06-18

The disclosure of the invention is directed to a site survey ground vehicle based apparatus and method for automatically detecting source materials, such as radioactivity, marking the location of the source materials, such as with paint, and mapping the location of the source materials on a site. The apparatus of the invention is also useful for collecting and analyzing samples. The apparatus includes a ground vehicle, detectors mounted at the front of the ground vehicle, and individual detector supports which follow somewhat irregular terrain to allow consistent and accurate detection, and autolocation equipment. 19 figures.

Method for detecting pollutants. [through chemical reactions and heat treatment

NASA Technical Reports Server (NTRS)

Rogowski, R. S.; Richards, R. R.; Conway, E. J. (Inventor)

1976-01-01

A method is described for detecting and measuring trace amounts of pollutants of the group consisting of ozone, nitrogen dioxide, and carbon monoxide in a gaseous environment. A sample organic solid material that will undergo a chemical reaction with the test pollutant is exposed to the test environment and thereafter, when heated in the temperature range of 100-200 C., undergoes chemiluminescence that is measured and recorded as a function of concentration of the test pollutant. The chemiluminescence of the solid organic material is specific to the pollutant being tested.

Consistent Practices for the Probability of Detection (POD) of Fracture Critical Metallic Components Project

NASA Technical Reports Server (NTRS)

Hughitt, Brian; Generazio, Edward (Principal Investigator); Nichols, Charles; Myers, Mika (Principal Investigator); Spencer, Floyd (Principal Investigator); Waller, Jess (Principal Investigator); Wladyka, Jordan (Principal Investigator); Aldrin, John; Burke, Eric; Cerecerez, Laura;

Microbial detection method based on sensing molecular hydrogen

NASA Technical Reports Server (NTRS)

Wilkins, J. R.; Stoner, G. E.; Boykin, E. H.

1974-01-01

An approach involving the measurement of hydrogen evolution by test organisms was used to detect and enumerate various members of the Enterobacteriaceae group. The experimental setup for measuring hydrogen evolution consisted of a test tube containing two electrodes plus broth and organisms. The test tube was kept in a water bath at a temperature of 35 C. It is pointed out that the hydrogen-sensing method, coupled with the pressure transducer technique reported by Wilkins (1974) could be used in various experiments in which gas production by microorganisms is being measured.

Automated Test Case Generator for Phishing Prevention Using Generative Grammars and Discriminative Methods

ERIC Educational Resources Information Center

Palka, Sean

2015-01-01

This research details a methodology designed for creating content in support of various phishing prevention tasks including live exercises and detection algorithm research. Our system uses probabilistic context-free grammars (PCFG) and variable interpolation as part of a multi-pass method to create diverse and consistent phishing email content on…

Estimating site occupancy and detection probability parameters for meso- and large mammals in a coastal eosystem

USGS Publications Warehouse

O'Connell, Allan F.; Talancy, Neil W.; Bailey, Larissa L.; Sauer, John R.; Cook, Robert; Gilbert, Andrew T.

2006-01-01

Large-scale, multispecies monitoring programs are widely used to assess changes in wildlife populations but they often assume constant detectability when documenting species occurrence. This assumption is rarely met in practice because animal populations vary across time and space. As a result, detectability of a species can be influenced by a number of physical, biological, or anthropogenic factors (e.g., weather, seasonality, topography, biological rhythms, sampling methods). To evaluate some of these influences, we estimated site occupancy rates using species-specific detection probabilities for meso- and large terrestrial mammal species on Cape Cod, Massachusetts, USA. We used model selection to assess the influence of different sampling methods and major environmental factors on our ability to detect individual species. Remote cameras detected the most species (9), followed by cubby boxes (7) and hair traps (4) over a 13-month period. Estimated site occupancy rates were similar among sampling methods for most species when detection probabilities exceeded 0.15, but we question estimates obtained from methods with detection probabilities between 0.05 and 0.15, and we consider methods with lower probabilities unacceptable for occupancy estimation and inference. Estimated detection probabilities can be used to accommodate variation in sampling methods, which allows for comparison of monitoring programs using different protocols. Vegetation and seasonality produced species-specific differences in detectability and occupancy, but differences were not consistent within or among species, which suggests that our results should be considered in the context of local habitat features and life history traits for the target species. We believe that site occupancy is a useful state variable and suggest that monitoring programs for mammals using occupancy data consider detectability prior to making inferences about species distributions or population change.

Vision Sensor-Based Road Detection for Field Robot Navigation

PubMed Central

Lu, Keyu; Li, Jian; An, Xiangjing; He, Hangen

2015-01-01

Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging road scenes. More specifically, for a given road image captured by an on-board vision sensor, we introduce a multiple population genetic algorithm (MPGA)-based approach for efficient road vanishing point detection. Superpixel-level seeds are then selected in an unsupervised way using a clustering strategy. Then, according to the GrowCut framework, the seeds proliferate and iteratively try to occupy their neighbors. After convergence, the initial road segment is obtained. Finally, in order to achieve a globally-consistent road segment, the initial road segment is refined using the conditional random field (CRF) framework, which integrates high-level information into road detection. We perform several experiments to evaluate the common performance, scale sensitivity and noise sensitivity of the proposed method. The experimental results demonstrate that the proposed method exhibits high robustness compared to the state of the art. PMID:26610514

Detection of blob objects in microscopic zebrafish images based on gradient vector diffusion.

PubMed

Li, Gang; Liu, Tianming; Nie, Jingxin; Guo, Lei; Malicki, Jarema; Mara, Andrew; Holley, Scott A; Xia, Weiming; Wong, Stephen T C

2007-10-01

The zebrafish has become an important vertebrate animal model for the study of developmental biology, functional genomics, and disease mechanisms. It is also being used for drug discovery. Computerized detection of blob objects has been one of the important tasks in quantitative phenotyping of zebrafish. We present a new automated method that is able to detect blob objects, such as nuclei or cells in microscopic zebrafish images. This method is composed of three key steps. The first step is to produce a diffused gradient vector field by a physical elastic deformable model. In the second step, the flux image is computed on the diffused gradient vector field. The third step performs thresholding and nonmaximum suppression based on the flux image. We report the validation and experimental results of this method using zebrafish image datasets from three independent research labs. Both sensitivity and specificity of this method are over 90%. This method is able to differentiate closely juxtaposed or connected blob objects, with high sensitivity and specificity in different situations. It is characterized by a good, consistent performance in blob object detection.

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.

Automatic comic page image understanding based on edge segment analysis

NASA Astrophysics Data System (ADS)

Liu, Dong; Wang, Yongtao; Tang, Zhi; Li, Luyuan; Gao, Liangcai

2013-12-01

Comic page image understanding aims to analyse the layout of the comic page images by detecting the storyboards and identifying the reading order automatically. It is the key technique to produce the digital comic documents suitable for reading on mobile devices. In this paper, we propose a novel comic page image understanding method based on edge segment analysis. First, we propose an efficient edge point chaining method to extract Canny edge segments (i.e., contiguous chains of Canny edge points) from the input comic page image; second, we propose a top-down scheme to detect line segments within each obtained edge segment; third, we develop a novel method to detect the storyboards by selecting the border lines and further identify the reading order of these storyboards. The proposed method is performed on a data set consisting of 2000 comic page images from ten printed comic series. The experimental results demonstrate that the proposed method achieves satisfactory results on different comics and outperforms the existing methods.

Detection of influenza antigenic variants directly from clinical samples using polyclonal antibody based proximity ligation assays

PubMed Central

Martin, Brigitte E.; Jia, Kun; Sun, Hailiang; Ye, Jianqiang; Hall, Crystal; Ware, Daphne; Wan, Xiu-Feng

2016-01-01

Identification of antigenic variants is the key to a successful influenza vaccination program. The empirical serological methods to determine influenza antigenic properties require viral propagation. Here a novel quantitative PCR-based antigenic characterization method using polyclonal antibody and proximity ligation assays, or so-called polyPLA, was developed and validated. This method can detect a viral titer that is less than 1000 TCID50/mL. Not only can this method differentiate between different HA subtypes of influenza viruses but also effectively identify antigenic drift events within the same HA subtype of influenza viruses. Applications in H3N2 seasonal influenza data showed that the results from this novel method are consistent with those from the conventional serological assays. This method is not limited to the detection of antigenic variants in influenza but also other pathogens. It has the potential to be applied through a large-scale platform in disease surveillance requiring minimal biosafety and directly using clinical samples. PMID:25546251

Efficient airport detection using region-based fully convolutional neural networks

NASA Astrophysics Data System (ADS)

Xin, Peng; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Lv, Chao

2018-04-01

This paper presents a model for airport detection using region-based fully convolutional neural networks. To achieve fast detection with high accuracy, we shared the conv layers between the region proposal procedure and the airport detection procedure and used graphics processing units (GPUs) to speed up the training and testing time. For lack of labeled data, we transferred the convolutional layers of ZF net pretrained by ImageNet to initialize the shared convolutional layers, then we retrained the model using the alternating optimization training strategy. The proposed model has been tested on an airport dataset consisting of 600 images. Experiments show that the proposed method can distinguish airports in our dataset from similar background scenes almost real-time with high accuracy, which is much better than traditional methods.

Detection of acoustic waves by NMR using a radiofrequency field gradient

NASA Astrophysics Data System (ADS)

Madelin, Guillaume; Baril, Nathalie; Lewa, Czeslaw J.; Franconi, Jean-Michel; Canioni, Paul; Thiaudiére, Eric; de Certaines, Jacques D.

2003-03-01

A B1 field gradient-based method previously described for the detection of mechanical vibrations has been applied to detect oscillatory motions in condensed matter originated from acoustic waves. A ladder-shaped coil generating a quasi-constant RF-field gradient was associated with a motion-encoding NMR sequence consisting in a repetitive binomial 1 3¯3 1¯ RF pulse train (stroboscopic acquisition). The NMR response of a gel phantom subject to acoustic wave excitation in the 20-200 Hz range was investigated. Results showed a linear relationship between the NMR signal and the wave amplitude and a spectroscopic selectivity of the NMR sequence with respect to the input acoustic frequency. Spin displacements as short as a few tens of nanometers were able to be detected with this method.

Detection of acoustic waves by NMR using a radiofrequency field gradient.

PubMed

Madelin, Guillaume; Baril, Nathalie; Lewa, Czeslaw J; Franconi, Jean Michel; Canioni, Paul; Thiaudiére, Eric; de Certaines, Jacques D

2003-03-01

A B(1) field gradient-based method previously described for the detection of mechanical vibrations has been applied to detect oscillatory motions in condensed matter originated from acoustic waves. A ladder-shaped coil generating a quasi-constant RF-field gradient was associated with a motion-encoding NMR sequence consisting in a repetitive binomial 13;31; RF pulse train (stroboscopic acquisition). The NMR response of a gel phantom subject to acoustic wave excitation in the 20-200 Hz range was investigated. Results showed a linear relationship between the NMR signal and the wave amplitude and a spectroscopic selectivity of the NMR sequence with respect to the input acoustic frequency. Spin displacements as short as a few tens of nanometers were able to be detected with this method.

Sentinel lymph node detection by an optical method using scattered photons

PubMed Central

Tellier, Franklin; Ravelo, Rasata; Simon, Hervé; Chabrier, Renée; Steibel, Jérôme; Poulet, Patrick

2010-01-01

We present a new near infrared optical probe for the sentinel lymph node detection, based on the recording of scattered photons. A two wavelengths setup was developed to improve the detection threshold of an injected dye: the Patent Blue V dye. The method used consists in modulating each laser diode at a given frequency. A Fast Fourier Transform of the recorded signal separates both components. The signal amplitudes are used to compute relative Patent Blue V concentration. Results on the probe using phantoms model and small animal experimentation exhibit a sensitivity threshold of 3.2 µmol/L, which is thirty fold better than the eye visible threshold. PMID:21258517

Methods for the preparation and analysis of solids and suspended solids for methylmercury

USGS Publications Warehouse

DeWild, John F.; Olund, Shane D.; Olson, Mark L.; Tate, Michael T.

2004-01-01

This report presents the methods and method performance data for the determination of methylmercury concentrations in solids and suspended solids. Using the methods outlined here, the U.S. Geological Survey's Wisconsin District Mercury Laboratory can consistently detect methylmercury in solids and suspended solids at environmentally relevant concentrations. Solids can be analyzed wet or freeze dried with a minimum detection limit of 0.08 ng/g (as-processed). Suspended solids must first be isolated from aqueous matrices by filtration. The minimum detection limit for suspended solids is 0.01 ng per filter resulting in a minimum reporting limit ranging from 0.2 ng/L for a 0.05 L filtered volume to 0.01 ng/L for a 1.0 L filtered volume. Maximum concentrations for both matrices can be extended to cover nearly any amount of methylmercury by limiting sample size.

Dataset of anomalies and malicious acts in a cyber-physical subsystem.

PubMed

Laso, Pedro Merino; Brosset, David; Puentes, John

2017-10-01

This article presents a dataset produced to investigate how data and information quality estimations enable to detect aNomalies and malicious acts in cyber-physical systems. Data were acquired making use of a cyber-physical subsystem consisting of liquid containers for fuel or water, along with its automated control and data acquisition infrastructure. Described data consist of temporal series representing five operational scenarios - Normal, aNomalies, breakdown, sabotages, and cyber-attacks - corresponding to 15 different real situations. The dataset is publicly available in the .zip file published with the article, to investigate and compare faulty operation detection and characterization methods for cyber-physical systems.

Rapid diagnosis of common deletional α-thalassemia in the Chinese population by qPCR based on identical primer homologous fragments.

PubMed

Long, Ju

2016-05-01

In China, -(SEA), -α(3.7) and -α(4.2) are common deletional α-thalassemia alleles. Gap-PCR is the currently used detection method for these alleles, whose disadvantages include time-consuming procedure and increased potential for PCR product contamination. Therefore, this detection method needs to be improved. Based on identical-primer homologous fragments, a qPCR system was developed for deletional α-thalassemia genotyping, which was composed of a group of quantitatively-related primers and their corresponding probes plus two groups of qualitatively-related primers and their corresponding probes. In order to verify the accuracy of the qPCR system, known genotype samples and random samples are employed. The standard curve result demonstrated that designed primers and probes all yielded good amplification efficiency. In the tests of known genotype samples and random samples, sample detection results were consistent with verification results. In detecting αα, -(SEA), -α(3.7) and -α(4.2) alleles, deletional α-thalassemia alleles are accurately detected by this method. In addition, this method is provided with a wider detection range, greater speed and reduced PCR product contamination risk when compared with current common gap-PCR detection reagents. Copyright © 2016 Elsevier B.V. All rights reserved.

A Mass Spectrometric Analysis Method Based on PPCA and SVM for Early Detection of Ovarian Cancer.

PubMed

Wu, Jiang; Ji, Yanju; Zhao, Ling; Ji, Mengying; Ye, Zhuang; Li, Suyi

2016-01-01

Background. Surfaced-enhanced laser desorption-ionization-time of flight mass spectrometry (SELDI-TOF-MS) technology plays an important role in the early diagnosis of ovarian cancer. However, the raw MS data is highly dimensional and redundant. Therefore, it is necessary to study rapid and accurate detection methods from the massive MS data. Methods. The clinical data set used in the experiments for early cancer detection consisted of 216 SELDI-TOF-MS samples. An MS analysis method based on probabilistic principal components analysis (PPCA) and support vector machine (SVM) was proposed and applied to the ovarian cancer early classification in the data set. Additionally, by the same data set, we also established a traditional PCA-SVM model. Finally we compared the two models in detection accuracy, specificity, and sensitivity. Results. Using independent training and testing experiments 10 times to evaluate the ovarian cancer detection models, the average prediction accuracy, sensitivity, and specificity of the PCA-SVM model were 83.34%, 82.70%, and 83.88%, respectively. In contrast, those of the PPCA-SVM model were 90.80%, 92.98%, and 88.97%, respectively. Conclusions. The PPCA-SVM model had better detection performance. And the model combined with the SELDI-TOF-MS technology had a prospect in early clinical detection and diagnosis of ovarian cancer.

Development and validation of a reverse transcription quantitative polymerase chain reaction for tilapia lake virus detection in clinical samples and experimentally challenged fish.

PubMed

Tattiyapong, P; Sirikanchana, K; Surachetpong, W

2018-02-01

Tilapia lake virus (TiLV) is an emerging pathogen associated with high mortalities of wild and farm-raised tilapia in different countries. In this study, a SYBR green-based reverse transcription quantitative polymerase chain reaction (RT-qPCR) assay targeting segment three of the virus was developed to detect and quantify TiLV in clinical samples and experimentally challenged fish. All 30 field samples with clinical signs and history consistent with TiLV infection were positive for TiLV as detected by the developed RT-qPCR method. The RT-qPCR technique provided 100 and 10,000 times more sensitive for virus detection than those offered by the RT-PCR and virus isolation in cell culture methods, respectively. The detection limit of the RT-qPCR method was as low as two viral copies/μl. Moreover, the RT-qPCR technique could be applied for TiLV detection in various fish tissues including gills, liver, brain, heart, anterior kidney and spleen. Significantly, this study delivered an accurate and reliable method for rapid detection of TiLV viruses that facilitates active surveillance programme and disease containment. © 2017 John Wiley & Sons Ltd.

HacDivSel: Two new methods (haplotype-based and outlier-based) for the detection of divergent selection in pairs of populations

PubMed Central

2017-01-01

The detection of genomic regions involved in local adaptation is an important topic in current population genetics. There are several detection strategies available depending on the kind of genetic and demographic information at hand. A common drawback is the high risk of false positives. In this study we introduce two complementary methods for the detection of divergent selection from populations connected by migration. Both methods have been developed with the aim of being robust to false positives. The first method combines haplotype information with inter-population differentiation (FST). Evidence of divergent selection is concluded only when both the haplotype pattern and the FST value support it. The second method is developed for independently segregating markers i.e. there is no haplotype information. In this case, the power to detect selection is attained by developing a new outlier test based on detecting a bimodal distribution. The test computes the FST outliers and then assumes that those of interest would have a different mode. We demonstrate the utility of the two methods through simulations and the analysis of real data. The simulation results showed power ranging from 60–95% in several of the scenarios whilst the false positive rate was controlled below the nominal level. The analysis of real samples consisted of phased data from the HapMap project and unphased data from intertidal marine snail ecotypes. The results illustrate that the proposed methods could be useful for detecting locally adapted polymorphisms. The software HacDivSel implements the methods explained in this manuscript. PMID:28423003

Automated detection of retinal nerve fiber layer defects on fundus images: false positive reduction based on vessel likelihood

NASA Astrophysics Data System (ADS)

Muramatsu, Chisako; Ishida, Kyoko; Sawada, Akira; Hatanaka, Yuji; Yamamoto, Tetsuya; Fujita, Hiroshi

2016-03-01

Early detection of glaucoma is important to slow down or cease progression of the disease and for preventing total blindness. We have previously proposed an automated scheme for detection of retinal nerve fiber layer defect (NFLD), which is one of the early signs of glaucoma observed on retinal fundus images. In this study, a new multi-step detection scheme was included to improve detection of subtle and narrow NFLDs. In addition, new features were added to distinguish between NFLDs and blood vessels, which are frequent sites of false positives (FPs). The result was evaluated with a new test dataset consisted of 261 cases, including 130 cases with NFLDs. Using the proposed method, the initial detection rate was improved from 82% to 98%. At the sensitivity of 80%, the number of FPs per image was reduced from 4.25 to 1.36. The result indicates the potential usefulness of the proposed method for early detection of glaucoma.

Full-text automated detection of surgical site infections secondary to neurosurgery in Rennes, France.

PubMed

Campillo-Gimenez, Boris; Garcelon, Nicolas; Jarno, Pascal; Chapplain, Jean Marc; Cuggia, Marc

2013-01-01

The surveillance of Surgical Site Infections (SSI) contributes to the management of risk in French hospitals. Manual identification of infections is costly, time-consuming and limits the promotion of preventive procedures by the dedicated teams. The introduction of alternative methods using automated detection strategies is promising to improve this surveillance. The present study describes an automated detection strategy for SSI in neurosurgery, based on textual analysis of medical reports stored in a clinical data warehouse. The method consists firstly, of enrichment and concept extraction from full-text reports using NOMINDEX, and secondly, text similarity measurement using a vector space model. The text detection was compared to the conventional strategy based on self-declaration and to the automated detection using the diagnosis-related group database. The text-mining approach showed the best detection accuracy, with recall and precision equal to 92% and 40% respectively, and confirmed the interest of reusing full-text medical reports to perform automated detection of SSI.

Evaluation of a polymerase chain reaction-based system for detection of Salmonella enteritidis, Escherichia coli O157:H7, Listeria spp., and Listeria monocytogenes on fresh fruits and vegetables.

PubMed

Shearer, A E; Strapp, C M; Joerger, R D

2001-06-01

A polymerase chain reaction (PCR)-based detection system, BAX, was evaluated for its sensitivity in detecting Salmonella Enteritidis, Escherichia coli O157:H7, Listeria sp., and Listeria monocytogenes on fresh produce. Fifteen different types of produce (alfalfa sprouts, green peppers, parsley, white cabbage, radishes, onions, carrots, mushrooms, leaf lettuce, tomatoes, strawberries, cantaloupe, mango, apples, and oranges) were inoculated, in separate studies, with Salmonella Enteritidis, E. coli O157:H7, and L. monocytogenes down to the predicted level of 1 CFU per 25-g sample. Detection by BAX was compared to recovery of the inoculated bacteria by culture methods according to the Food and Drug Administration's (FDA) Bacteriological Analytical Manual (BAM). BAX was essentially as sensitive as the culture-based method in detecting Salmonella Enteritidis and L. monocytogenes and more sensitive than the culture-based method for the detection of E. coli O157:H7 on green pepper, carrot, radish, and sprout samples. Detection of the pathogenic bacteria in samples spiked with a predicted number of less than 10 CFU was possible for most produce samples, but both methods failed to detect L. monocytogenes on carrot samples and one of two mushroom and onion samples spiked with less than 100 CFU. Both BAX and the culture method were also unable to consistently recover low numbers of E. coli O157:H7 from alfalfa sprouts. The PCR method allowed detection of Salmonella Enteritidis, E. coli O157:H7, and L. monocytogenes at least 2 days earlier than the conventional culture methods.

Consistency of influenza A virus detection test results across respiratory specimen collection methods using real-time reverse transcription-PCR.

PubMed

Spencer, Sarah; Gaglani, Manjusha; Naleway, Allison; Reynolds, Sue; Ball, Sarah; Bozeman, Sam; Henkle, Emily; Meece, Jennifer; Vandermause, Mary; Clipper, Lydia; Thompson, Mark

2013-11-01

In our prospective cohort study, we compared the performance of nasopharyngeal, oropharyngeal, and nasal swabs for the detection of influenza virus using real-time reverse transcription-PCR assay. Joint consideration of results from oropharyngeal and nasal swabs was as effective as consideration of results from nasopharyngeal swabs alone, as measured by sensitivity and noninferiority analysis.

Thin Film Research. Volume 2

DTIC Science & Technology

1985-05-30

consisting of quarterwave layers by detecting the -- extrema of transmission or reflectance at a particular wavelength. This method is extremely stable for the...technique, which is based on an envelope method , and gives some experimental *results. L"( iL -2- I. Introduction The refractive index and the...constants determination :ecnnique by computer simulation, we have applied the method to various layers of titanium dioxide. This technique can then

Evaluation of a Method for Rapid Detection of Listeria monocytogenes in Dry-Cured Ham Based on Impedanciometry Combined with Chromogenic Agar.

PubMed

Labrador, Mirian; Rota, María C; Pérez, Consuelo; Herrera, Antonio; Bayarri, Susana

2018-05-01

The food industry is in need of rapid, reliable methodologies for the detection of Listeria monocytogenes in ready-to-eat products, as an alternative to the International Organization of Standardization (ISO) 11290-1 reference method. The aim of this study was to evaluate impedanciometry combined with chromogenic agar culture for the detection of L. monocytogenes in dry-cured ham. The experimental setup consisted in assaying four strains of L. monocytogenes and two strains of Listeria innocua in pure culture. The method was evaluated according to the ISO 16140:2003 standard through a comparative study with the ISO reference method with 119 samples of dry-cured ham. Significant determination coefficients ( R 2 of up to 0.99) for all strains assayed in pure culture were obtained. The comparative study results had 100% accuracy, 100% specificity, and 100% sensitivity. Impedanciometry followed by chromogenic agar culture was capable of detecting 1 CFU/25 g of food. L. monocytogenes was not detected in the 65 commercial samples tested. The method evaluated herein represents a promising alternative for the food industry in its efforts to control L. monocytogenes. Overall analysis time is shorter and the method permits a straightforward analysis of a large number of samples with reliable results.

A KPI-based process monitoring and fault detection framework for large-scale processes.

PubMed

Zhang, Kai; Shardt, Yuri A W; Chen, Zhiwen; Yang, Xu; Ding, Steven X; Peng, Kaixiang

2017-05-01

Large-scale processes, consisting of multiple interconnected subprocesses, are commonly encountered in industrial systems, whose performance needs to be determined. A common approach to this problem is to use a key performance indicator (KPI)-based approach. However, the different KPI-based approaches are not developed with a coherent and consistent framework. Thus, this paper proposes a framework for KPI-based process monitoring and fault detection (PM-FD) for large-scale industrial processes, which considers the static and dynamic relationships between process and KPI variables. For the static case, a least squares-based approach is developed that provides an explicit link with least-squares regression, which gives better performance than partial least squares. For the dynamic case, using the kernel representation of each subprocess, an instrument variable is used to reduce the dynamic case to the static case. This framework is applied to the TE benchmark process and the hot strip mill rolling process. The results show that the proposed method can detect faults better than previous methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

The Effect of Two Methods of Pomegranate (Punica granatum L) Juice Extraction on Quality During Storage at 4°C

PubMed Central

Antunes, Dulce

2004-01-01

The effect of two extraction methods of pomegranate juice on its quality and stability was evaluated. The first method consisted of separation of the seeds from fruits and centrifugation. The second method consisted of squeezing fruit halves with an electric lemon squeezer. During a period of 72 hours of cold storage at 4°C, the juices were evaluated for the presence of sugars, organic acids, and anthocyanins. Delphinidin 3-glucoside was identified to be the major anthocyanin present at the level of 45–69 mg/L. Among the organic acids, oxalic and tartaric acids dominated. The major sugars detected in pomegranate juice were glucose and sucrose. No significant differences in the content of sugars, organic acids, or anthocyanins in juices obtained through application of the two different extraction methods were detected, with the exception of the drastic decrease of cyanidin 3,5-diglucoside level in juice obtained by seed centrifugation. The pH did not show differences between treatments. Titrable acidity and the level of sugars expressed as °Brix decreased after 32 and 15 hours after extraction, respectively, when juice was obtained by centrifuging the seeds. PMID:15577198

The Effect of Two Methods of Pomegranate (Punica granatum L) Juice Extraction on Quality During Storage at $4^\\circ$ C.

PubMed

Miguel, Graça; Dandlen, Susana; Antunes, Dulce; Neves, Alcinda; Martins, Denise

2004-01-01

The effect of two extraction methods of pomegranate juice on its quality and stability was evaluated. The first method consisted of separation of the seeds from fruits and centrifugation. The second method consisted of squeezing fruit halves with an electric lemon squeezer. During a period of 72 hours of cold storage at $4^\\circ$ C, the juices were evaluated for the presence of sugars, organic acids, and anthocyanins. Delphinidin 3-glucoside was identified to be the major anthocyanin present at the level of 45-69 mg/L. Among the organic acids, oxalic and tartaric acids dominated. The major sugars detected in pomegranate juice were glucose and sucrose. No significant differences in the content of sugars, organic acids, or anthocyanins in juices obtained through application of the two different extraction methods were detected, with the exception of the drastic decrease of cyanidin $3,5$ -diglucoside level in juice obtained by seed centrifugation. The pH did not show differences between treatments. Titrable acidity and the level of sugars expressed as ${}^{\\circ}$ Brix decreased after 32 and 15 hours after extraction, respectively, when juice was obtained by centrifuging the seeds.

Quick and simple estimation of bacteria using a fluorescent paracetamol dimer-Au nanoparticle composite

NASA Astrophysics Data System (ADS)

Sahoo, Amaresh Kumar; Sharma, Shilpa; Chattopadhyay, Arun; Ghosh, Siddhartha Sankar

2012-02-01

Rapid, simple and sensitive detection of bacterial contamination is critical for safeguarding public health and the environment. Herein, we report an easy method of detection as well as enumeration of the bacterial cell number on the basis of fluorescence quenching of a non-antibacterial fluorescent nanocomposite, consisting of paracetamol dimer (PD) and Au nanoparticles (NPs), in the presence of bacteria. The composite was synthesized by reaction of paracetamol (p-hydroxyacetanilide) with HAuCl4. The Au NPs of the composite were characterized using UV-Vis spectroscopy, transmission electron microscopy (TEM), X-ray diffraction and selected area electron diffraction analysis. The paracetamol dimer in the composite showed emission peak at 435 nm when excited at 320 nm. The method successfully detected six bacterial strains with a sensitivity of 100 CFU mL-1. The Gram-positive and Gram-negative bacteria quenched the fluorescence of the composite differently, making it possible to distinguish between the two. The TEM analysis showed interaction of the composite with bacteria without any apparent damage to the bacteria. The chi-square test established the accuracy of the method. Quick, non-specific and highly sensitive detection of bacteria over a broad range of logarithmic dilutions within a short span of time demonstrates the potential of this method as an alternative to conventional methods.Rapid, simple and sensitive detection of bacterial contamination is critical for safeguarding public health and the environment. Herein, we report an easy method of detection as well as enumeration of the bacterial cell number on the basis of fluorescence quenching of a non-antibacterial fluorescent nanocomposite, consisting of paracetamol dimer (PD) and Au nanoparticles (NPs), in the presence of bacteria. The composite was synthesized by reaction of paracetamol (p-hydroxyacetanilide) with HAuCl4. The Au NPs of the composite were characterized using UV-Vis spectroscopy, transmission electron microscopy (TEM), X-ray diffraction and selected area electron diffraction analysis. The paracetamol dimer in the composite showed emission peak at 435 nm when excited at 320 nm. The method successfully detected six bacterial strains with a sensitivity of 100 CFU mL-1. The Gram-positive and Gram-negative bacteria quenched the fluorescence of the composite differently, making it possible to distinguish between the two. The TEM analysis showed interaction of the composite with bacteria without any apparent damage to the bacteria. The chi-square test established the accuracy of the method. Quick, non-specific and highly sensitive detection of bacteria over a broad range of logarithmic dilutions within a short span of time demonstrates the potential of this method as an alternative to conventional methods. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr11837h

Adenosine Monophosphate-Based Detection of Bacterial Spores

NASA Technical Reports Server (NTRS)

Kern, Roger G.; Chen, Fei; Venkateswaran, Kasthuri; Hattori, Nori; Suzuki, Shigeya

2009-01-01

A method of rapid detection of bacterial spores is based on the discovery that a heat shock consisting of exposure to a temperature of 100 C for 10 minutes causes the complete release of adenosine monophosphate (AMP) from the spores. This method could be an alternative to the method described in the immediately preceding article. Unlike that method and related prior methods, the present method does not involve germination and cultivation; this feature is an important advantage because in cases in which the spores are those of pathogens, delays involved in germination and cultivation could increase risks of infection. Also, in comparison with other prior methods that do not involve germination, the present method affords greater sensitivity. At present, the method is embodied in a laboratory procedure, though it would be desirable to implement the method by means of a miniaturized apparatus in order to make it convenient and economical enough to encourage widespread use.

Assessing the Suitability of Historical PM(2.5) Element Measurements for Trend Analysis.

PubMed

Hyslop, Nicole P; Trzepla, Krystyna; White, Warren H

2015-08-04

The IMPROVE (Interagency Monitoring of Protected Visual Environments) network has characterized fine particulate matter composition at locations throughout the United States since 1988. A main objective of the network is to evaluate long-term trends in aerosol concentrations. Measurements inevitably advance over time, but changes in measurement technique have the potential to confound the interpretation of long-term trends. Problems of interpretation typically arise from changing biases, and changes in bias can be difficult to identify without comparison data that are consistent throughout the measurement series, which rarely exist. We created a consistent measurement series for exactly this purpose by reanalyzing the 15-year archives (1995-2009) of aerosol samples from three sites - Great Smoky Mountains National Park, Mount Rainier National Park, and Point Reyes National Seashore-as single batches using consistent analytical methods. In most cases, trend estimates based on the original and reanalysis measurements are statistically different for elements that were not measured above the detection limit consistently over the years (e.g., Na, Cl, Si, Ti, V, Mn). The original trends are more reliable for elements consistently measured above the detection limit. All but one of the 23 site-element series with detection rates >80% had statistically indistinguishable original and reanalysis trends (overlapping 95% confidence intervals).

A visual model for object detection based on active contours and level-set method.

PubMed

Satoh, Shunji

2006-09-01

A visual model for object detection is proposed. In order to make the detection ability comparable with existing technical methods for object detection, an evolution equation of neurons in the model is derived from the computational principle of active contours. The hierarchical structure of the model emerges naturally from the evolution equation. One drawback involved with initial values of active contours is alleviated by introducing and formulating convexity, which is a visual property. Numerical experiments show that the proposed model detects objects with complex topologies and that it is tolerant of noise. A visual attention model is introduced into the proposed model. Other simulations show that the visual properties of the model are consistent with the results of psychological experiments that disclose the relation between figure-ground reversal and visual attention. We also demonstrate that the model tends to perceive smaller regions as figures, which is a characteristic observed in human visual perception.

Coherent detection of position errors in inter-satellite laser communications

NASA Astrophysics Data System (ADS)

Xu, Nan; Liu, Liren; Liu, De'an; Sun, Jianfeng; Luan, Zhu

2007-09-01

Due to the improved receiver sensitivity and wavelength selectivity, coherent detection became an attractive alternative to direct detection in inter-satellite laser communications. A novel method to coherent detection of position errors information is proposed. Coherent communication system generally consists of receive telescope, local oscillator, optical hybrid, photoelectric detector and optical phase lock loop (OPLL). Based on the system composing, this method adds CCD and computer as position error detector. CCD captures interference pattern while detection of transmission data from the transmitter laser. After processed and analyzed by computer, target position information is obtained from characteristic parameter of the interference pattern. The position errors as the control signal of PAT subsystem drive the receiver telescope to keep tracking to the target. Theoretical deviation and analysis is presented. The application extends to coherent laser rang finder, in which object distance and position information can be obtained simultaneously.

Detection and quantification of beef and pork materials in meat products by duplex droplet digital PCR.

PubMed

Cai, Yicun; He, Yuping; Lv, Rong; Chen, Hongchao; Wang, Qiang; Pan, Liangwen

2017-01-01

Meat products often consist of meat from multiple animal species, and inaccurate food product adulteration and mislabeling can negatively affect consumers. Therefore, a cost-effective and reliable method for identification and quantification of animal species in meat products is required. In this study, we developed a duplex droplet digital PCR (dddPCR) detection and quantification system to simultaneously identify and quantify the source of meat in samples containing a mixture of beef (Bos taurus) and pork (Sus scrofa) in a single digital PCR reaction tube. Mixed meat samples of known composition were used to test the accuracy and applicability of this method. The limit of detection (LOD) and the limit of quantification (LOQ) of this detection and quantification system were also identified. We conclude that our dddPCR detection and quantification system is suitable for quality control and routine analyses of meat products.

Longitudinal study of Escherichia coli O157 shedding and super shedding in dairy heifers.

PubMed

Williams, K J; Ward, M P; Dhungyel, O P

2015-04-01

A longitudinal study was conducted to assess the methods available for detection of Escherichia coli O157 and to investigate the prevalence and occurrence of long-term shedding and super shedding in a cohort of Australian dairy heifers. Samples were obtained at approximately weekly intervals from heifers at pasture under normal management systems. Selective sampling techniques were used with the aim of identifying heifers with a higher probability of shedding or super shedding. Rectoanal mucosal swabs (RAMS) and fecal samples were obtained from each heifer. Direct culture of feces was used for detection and enumeration. Feces and RAMS were tested by enrichment culture. Selected samples were further tested retrospectively by immunomagnetic separation of enriched samples. Of 784 samples obtained, 154 (19.6%) were detected as positive using culture methods. Adjusting for selective sampling, the prevalence was 71 (15.6%) of 454. In total, 66 samples were detected as positive at >10(2) CFU/g of which 8 were >10(4) CFU/g and classed as super shedding. A significant difference was observed in detection by enriched culture of RAMS and feces. Dairy heifers within this cohort exhibited variable E. coli O157 shedding, consistent with previous estimates of shedding. Super shedding was detected at a low frequency and inconsistently from individual heifers. All detection methods identified some samples as positive that were not detected by any other method, indicating that the testing methods used will influence survey results.

Comparing viral metagenomics methods using a highly multiplexed human viral pathogens reagent

PubMed Central

Li, Linlin; Deng, Xutao; Mee, Edward T.; Collot-Teixeira, Sophie; Anderson, Rob; Schepelmann, Silke; Minor, Philip D.; Delwart, Eric

2014-01-01

Unbiased metagenomic sequencing holds significant potential as a diagnostic tool for the simultaneous detection of any previously genetically described viral nucleic acids in clinical samples. Viral genome sequences can also inform on likely phenotypes including drug susceptibility or neutralization serotypes. In this study, different variables of the laboratory methods often used to generate viral metagenomics libraries on the efficiency of viral detection and virus genome coverage were compared. A biological reagent consisting of 25 different human RNA and DNA viral pathogens was used to estimate the effect of filtration and nuclease digestion, DNA/RNA extraction methods, pre-amplification and the use of different library preparation kits on the detection of viral nucleic acids. Filtration and nuclease treatment led to slight decreases in the percentage of viral sequence reads and number of viruses detected. For nucleic acid extractions silica spin columns improved viral sequence recovery relative to magnetic beads and Trizol extraction. Pre-amplification using random RT-PCR while generating more viral sequence reads resulted in detection of fewer viruses, more overlapping sequences, and lower genome coverage. The ScriptSeq library preparation method retrieved more viruses and a greater fraction of their genomes than the TruSeq and Nextera methods. Viral metagenomics sequencing was able to simultaneously detect up to 22 different viruses in the biological reagent analyzed including all those detected by qPCR. Further optimization will be required for the detection of viruses in biologically more complex samples such as tissues, blood, or feces. PMID:25497414

Disposable amperometric biosensor based on nanostructured bacteriophages for glucose detection

NASA Astrophysics Data System (ADS)

Kang, Yu Ri; Hwang, Kyung Hoon; Kim, Ju Hwan; Nam, Chang Hoon; Kim, Soo Won

2010-10-01

The selection of electrode material profoundly influences biosensor science and engineering, as it heavily influences biosensor sensitivity. Here we propose a novel electrochemical detection method using a working electrode consisting of bio-nanowires from genetically modified filamentous phages and nanoparticles. fd-tet p8MMM filamentous phages displaying a three-methionine (MMM) peptide on the major coat protein pVIII (designated p8MMM phages) were immobilized on the active area of an electrochemical sensor through physical adsorption and chemical bonding. Bio-nanowires composed of p8MMM phages and silver nanoparticles facilitated sensitive, rapid and selective detection of particular molecules. We explored whether the composite electrode with bio-nanowires was an effective platform to detect the glucose oxidase. The current response of the bio-nanowire sensor was high at various glucose concentrations (0.1 µm-0.1 mM). This method provides a considerable advantage to demonstrate analyte detection over low concentration ranges. Especially, phage-enabled bio-nanowires can serve as receptors with high affinity and specificity for the detection of particular biomolecules and provide a convenient platform for designing site-directed multifunctional scaffolds based on bacteriophages and may serve as a simple method for label-free detection.

Application of Reverse Transcriptase-PCR-DGGE as a rapid method for routine determination of Vibrio spp. in foods.

PubMed

Chahorm, Kanchana; Prakitchaiwattana, Cheunjit

2018-01-02

The aim of this research was to evaluate the feasibility of PCR-DGGE and Reverse Transcriptase-PCR-DGGE techniques for rapid detection of Vibrio species in foods. Primers GC567F and 680R were initially evaluated for amplifying DNA and cDNA of ten references Vibrio species by PCR method. The GC-clamp PCR amplicons were separated according to their sequences by the DGGE using 10% (w/v) polyacrylamide gel containing 45-70% urea and formamide denaturants. Two pair of Vibrio species, which could not be differentiated on the gel, was Vibrio fluvialis - Vibrio furnissii and Vibrio parahaemolyticus - Vibrio harveyi. To determine the detection limit, in the community of 10 reference strains containing the same viable population, distinct DNA bands of 3 species; Vibrio cholerae, Vibrio mimicus and Vibrio alginolyticus were consistently observed by PCR-DGGE technique. In fact, 5 species; Vibrio cholerae, Vibrio mimicus, Vibrio alginolyticus, Vibrio parahaemolyticus and Vibrio fluvialis consistently observed by Reverse Transcriptase-PCR-DGGE. In the community containing different viable population increasing from 10 2 to 10 5 CFU/mL, PCR-DGGE analysis only detected the two most prevalent species, while RT-PCR-DGGE detected the five most prevalent species. Therefore, Reverse Transcriptase-PCR-DGGE was also selected for detection of various Vibrio cell conditions, including viable cell (VC), injured cells from frozen cultures (IVC) and injured cells from frozen cultures with pre-enrichment (PIVC). It was found that cDNA band of all cell conditions gave the same migratory patterns, except that multiple cDNA bands of Plesiomonas shigelloides under IVC and PIVC conditions were found. When Reverse Transcriptase-PCR-DGGE was used for detecting Vibrio parahaemolyticus in the pathogen-spiked food samples, Vibrio parahaemolyticus could be detected in the spiked samples containing at least 10 2 CFU/g of this pathogen. The results obtained also corresponded to standard method (USFDA, 2004). In comparison with the detection of the Vibrio profiles in fourteen food samples using standard method, Reverse Transcriptase-PCR-DGGE resulted in 100%, 75% and 50% similarity in 3, 1 and 6 food samples, respectively. Copyright © 2017 Elsevier B.V. All rights reserved.

Unsupervised iterative detection of land mines in highly cluttered environments.

PubMed

Batman, Sinan; Goutsias, John

2003-01-01

An unsupervised iterative scheme is proposed for land mine detection in heavily cluttered scenes. This scheme is based on iterating hybrid multispectral filters that consist of a decorrelating linear transform coupled with a nonlinear morphological detector. Detections extracted from the first pass are used to improve results in subsequent iterations. The procedure stops after a predetermined number of iterations. The proposed scheme addresses several weaknesses associated with previous adaptations of morphological approaches to land mine detection. Improvement in detection performance, robustness with respect to clutter inhomogeneities, a completely unsupervised operation, and computational efficiency are the main highlights of the method. Experimental results reveal excellent performance.

Minimum detectable gas concentration performance evaluation method for gas leak infrared imaging detection systems.

PubMed

Zhang, Xu; Jin, Weiqi; Li, Jiakun; Wang, Xia; Li, Shuo

2017-04-01

Thermal imaging technology is an effective means of detecting hazardous gas leaks. Much attention has been paid to evaluation of the performance of gas leak infrared imaging detection systems due to several potential applications. The minimum resolvable temperature difference (MRTD) and the minimum detectable temperature difference (MDTD) are commonly used as the main indicators of thermal imaging system performance. This paper establishes a minimum detectable gas concentration (MDGC) performance evaluation model based on the definition and derivation of MDTD. We proposed the direct calculation and equivalent calculation method of MDGC based on the MDTD measurement system. We build an experimental MDGC measurement system, which indicates the MDGC model can describe the detection performance of a thermal imaging system to typical gases. The direct calculation, equivalent calculation, and direct measurement results are consistent. The MDGC and the minimum resolvable gas concentration (MRGC) model can effectively describe the performance of "detection" and "spatial detail resolution" of thermal imaging systems to gas leak, respectively, and constitute the main performance indicators of gas leak detection systems.

DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks.

PubMed

Li, Chao; Wang, Xinggang; Liu, Wenyu; Latecki, Longin Jan

2018-04-01

Mitotic count is a critical predictor of tumor aggressiveness in the breast cancer diagnosis. Nowadays mitosis counting is mainly performed by pathologists manually, which is extremely arduous and time-consuming. In this paper, we propose an accurate method for detecting the mitotic cells from histopathological slides using a novel multi-stage deep learning framework. Our method consists of a deep segmentation network for generating mitosis region when only a weak label is given (i.e., only the centroid pixel of mitosis is annotated), an elaborately designed deep detection network for localizing mitosis by using contextual region information, and a deep verification network for improving detection accuracy by removing false positives. We validate the proposed deep learning method on two widely used Mitosis Detection in Breast Cancer Histological Images (MITOSIS) datasets. Experimental results show that we can achieve the highest F-score on the MITOSIS dataset from ICPR 2012 grand challenge merely using the deep detection network. For the ICPR 2014 MITOSIS dataset that only provides the centroid location of mitosis, we employ the segmentation model to estimate the bounding box annotation for training the deep detection network. We also apply the verification model to eliminate some false positives produced from the detection model. By fusing scores of the detection and verification models, we achieve the state-of-the-art results. Moreover, our method is very fast with GPU computing, which makes it feasible for clinical practice. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantitative thin-layer chromatography/mass spectrometry analysis of caffeine using a surface sampling probe electrospray ionization tandem mass spectrometry system.

PubMed

Ford, Michael J; Deibel, Michael A; Tomkins, Bruce A; Van Berkel, Gary J

2005-07-15

Quantitative determination of caffeine on reversed-phase C8 thin-layer chromatography plates using a surface sampling electrospray ionization system with tandem mass spectrometry detection is reported. The thin-layer chromatography/electrospray tandem mass spectrometry method employed a deuterium-labeled caffeine internal standard and selected reaction monitoring detection. Up to nine parallel caffeine bands on a single plate were sampled in a single surface scanning experiment requiring 35 min at a surface scan rate of 44 mum/s. A reversed-phase HPLC/UV caffeine assay was developed in parallel to assess the mass spectrometry method performance. Limits of detection for the HPLC/UV and thin-layer chromatography/electrospray tandem mass spectrometry methods determined from the calibration curve statistics were 0.20 ng injected (0.50 muL) and 1.0 ng spotted on the plate, respectively. Spike recoveries with standards and real samples ranged between 97 and 106% for both methods. The caffeine content of three diet soft drinks (Diet Coke, Diet Cherry Coke, Diet Pepsi) and three diet sport drinks (Diet Turbo Tea, Speed Stack Grape, Speed Stack Fruit Punch) was measured. The HPLC/UV and mass spectrometry determinations were in general agreement, and these values were consistent with the quoted values for two of the three diet colas. In the case of Diet Cherry Coke and the diet sports drinks, the determined caffeine amounts using both methods were consistently higher (by approximately 8% or more) than the literature values.

[Application of MALDI-TOF-MS in gene testing for non-syndromic hearing loss].

PubMed

Zeng, Yun; Jiang, Dan; Feng, Da-fei; Jin, Dong-dong; Wu, Xiao-hui; Ding, Yan-li; Zou, Jing

2013-12-01

To investigate the feasibility of Matrix-Assisted Laser Desorption-Ionization Time of Flight Mass Spectrometry (MALDI-TOF-MS) , according to the genetic test of non-syndromic hearing loss (NSHL), and check using the direct sequencing. Peripheral blood was collected from 454 NSHL patients. DNA samples were extracted and 20 loci of the four common disease-causing genes were analysed by MALDI-TOF-MS, including GJB2 (35delG, 167delT, 176_191del16, 235delC, 299_300delAT ), GJB3 (538C→T, 547G→A), SLC26A4 (281C→T, 589G→A, IVS7-2A→G, 1174A→T, 1226G→A, 1229C→T, IVS15+5G→A, 1975G→C, 2027T→A, 2162C→T, 2168A→G), and mitochondrial 12S rRNA (1494C→T, 1555A→G). Direct sequencing was also used to analyse the aforementioned 20 loci in order to validate the accuracy of MALDI-TOF-MS. Among the 454 patients, 166 cases (36.56%) of disease-causing mutations were detected, which included 69 cases (21.15%) of GJB2 gene mutation, four cases (0.88%) of GJB3 gene mutation, 64 cases (14.10%) of SLC26A4 gene mutation, and three cases (0.66%) of mitochondrial 12S rRNA gene mutation. Moreover, the results obtained from direct sequencing and MALDI-TOF-MS were consistent, and the results showed that the two methods were consistent. The MALDI-TOF-MS detection method was designed based on the hearing loss-related mutation hotspots seen in the Chinese population, and it has a high detection rate for NSHL related mutations. In comparison to the conventional detection methods, MALDI-TOF-MS has the following advantages: more detection sites, greater coverage, accurate, high throughput and low cost. Therefore, this method is capable of satisfying the needs of clinical detection for hearing impairment and it is suitable for large-scale implementation.

Efficient IDUA Gene Mutation Detection with Combined Use of dHPLC and Dried Blood Samples

PubMed Central

Duarte, Ana Joana; Vieira, Luis

2013-01-01

Objectives. Development of a simple mutation directed method in order to allow lowering the cost of mutation testing using an easily obtainable biological material. Assessment of the feasibility of such method was tested using a GC-rich amplicon. Design and Methods. A method of denaturing high-performance liquid chromatography (dHPLC) was improved and implemented as a technique for the detection of variants in exon 9 of the IDUA gene. The optimized method was tested in 500 genomic DNA samples obtained from dried blood spots (DBS). Results. With this dHPLC approach it was possible to detect different variants, including the common p.Trp402Ter mutation in the IDUA gene. The high GC content did not interfere with the resolution and reliability of this technique, and discrimination of G-C transversions was also achieved. Conclusion. This PCR-based dHPLC method is proved to be a rapid, a sensitive, and an excellent option for screening numerous samples obtained from DBS. Furthermore, it resulted in the consistent detection of clearly distinguishable profiles of the common p.Trp402Ter IDUA mutation with an advantageous balance of cost and technical requirements. PMID:27335677

Cosmic non-TEM radiation and synthetic feed array sensor system in ASIC mixed signal technology

NASA Astrophysics Data System (ADS)

Centureli, F.; Scotti, G.; Tommasino, P.; Trifiletti, A.; Romano, F.; Cimmino, R.; Saitto, A.

2014-08-01

The paper deals with the opportunity to introduce "Not strictly TEM waves" Synthetic detection Method (NTSM), consisting in a Three Axis Digital Beam Processing (3ADBP), to enhance the performances of radio telescope and sensor systems. Current Radio Telescopes generally use the classic 3D "TEM waves" approximation Detection Method, which consists in a linear tomography process (Single or Dual axis beam forming processing) neglecting the small z component. The Synthetic FEED ARRAY three axis Sensor SYSTEM is an innovative technique using a synthetic detection of the generic "NOT strictly TEM Waves radiation coming from the Cosmo, which processes longitudinal component of Angular Momentum too. Than the simultaneous extraction from radiation of both the linear and quadratic information component, may reduce the complexity to reconstruct the Early Universe in the different requested scales. This next order approximation detection of the observed cosmologic processes, may improve the efficacy of the statistical numerical model used to elaborate the same information acquired. The present work focuses on detection of such waves at carrier frequencies in the bands ranging from LF to MMW. The work shows in further detail the new generation of on line programmable and reconfigurable Mixed Signal ASIC technology that made possible the innovative Synthetic Sensor. Furthermore the paper shows the ability of such technique to increase the Radio Telescope Array Antenna performances.

Modeling and Detecting Feature Interactions among Integrated Services of Home Network Systems

NASA Astrophysics Data System (ADS)

Igaki, Hiroshi; Nakamura, Masahide

This paper presents a framework for formalizing and detecting feature interactions (FIs) in the emerging smart home domain. We first establish a model of home network system (HNS), where every networked appliance (or the HNS environment) is characterized as an object consisting of properties and methods. Then, every HNS service is defined as a sequence of method invocations of the appliances. Within the model, we next formalize two kinds of FIs: (a) appliance interactions and (b) environment interactions. An appliance interaction occurs when two method invocations conflict on the same appliance, whereas an environment interaction arises when two method invocations conflict indirectly via the environment. Finally, we propose offline and online methods that detect FIs before service deployment and during execution, respectively. Through a case study with seven practical services, it is shown that the proposed framework is generic enough to capture feature interactions in HNS integrated services. We also discuss several FI resolution schemes within the proposed framework.

Temporally consistent probabilistic detection of new multiple sclerosis lesions in brain MRI.

PubMed

Elliott, Colm; Arnold, Douglas L; Collins, D Louis; Arbel, Tal

2013-08-01

Detection of new Multiple Sclerosis (MS) lesions on magnetic resonance imaging (MRI) is important as a marker of disease activity and as a potential surrogate for relapses. We propose an approach where sequential scans are jointly segmented, to provide a temporally consistent tissue segmentation while remaining sensitive to newly appearing lesions. The method uses a two-stage classification process: 1) a Bayesian classifier provides a probabilistic brain tissue classification at each voxel of reference and follow-up scans, and 2) a random-forest based lesion-level classification provides a final identification of new lesions. Generative models are learned based on 364 scans from 95 subjects from a multi-center clinical trial. The method is evaluated on sequential brain MRI of 160 subjects from a separate multi-center clinical trial, and is compared to 1) semi-automatically generated ground truth segmentations and 2) fully manual identification of new lesions generated independently by nine expert raters on a subset of 60 subjects. For new lesions greater than 0.15 cc in size, the classifier has near perfect performance (99% sensitivity, 2% false detection rate), as compared to ground truth. The proposed method was also shown to exceed the performance of any one of the nine expert manual identifications.

Method for targetless tracking subpixel in-plane movements.

PubMed

Espinosa, Julian; Perez, Jorge; Ferrer, Belen; Mas, David

2015-09-01

We present a targetless motion tracking method for detecting planar movements with subpixel accuracy. This method is based on the computation and tracking of the intersection of two nonparallel straight-line segments in the image of a moving object in a scene. The method is simple and easy to implement because no complex structures have to be detected. It has been tested and validated using a lab experiment consisting of a vibrating object that was recorded with a high-speed camera working at 1000 fps. We managed to track displacements with an accuracy of hundredths of pixel or even of thousandths of pixel in the case of tracking harmonic vibrations. The method is widely applicable because it can be used for distance measuring amplitude and frequency of vibrations with a vision system.

Detection limit for rate fluctuations in inhomogeneous Poisson processes

NASA Astrophysics Data System (ADS)

Shintani, Toshiaki; Shinomoto, Shigeru

2012-04-01

Estimations of an underlying rate from data points are inevitably disturbed by the irregular occurrence of events. Proper estimation methods are designed to avoid overfitting by discounting the irregular occurrence of data, and to determine a constant rate from irregular data derived from a constant probability distribution. However, it can occur that rapid or small fluctuations in the underlying density are undetectable when the data are sparse. For an estimation method, the maximum degree of undetectable rate fluctuations is uniquely determined as a phase transition, when considering an infinitely long series of events drawn from a fluctuating density. In this study, we analytically examine an optimized histogram and a Bayesian rate estimator with respect to their detectability of rate fluctuation, and determine whether their detectable-undetectable phase transition points are given by an identical formula defining a degree of fluctuation in an underlying rate. In addition, we numerically examine the variational Bayes hidden Markov model in its detectability of rate fluctuation, and determine whether the numerically obtained transition point is comparable to those of the other two methods. Such consistency among these three principled methods suggests the presence of a theoretical limit for detecting rate fluctuations.

Detection limit for rate fluctuations in inhomogeneous Poisson processes.

PubMed

Shintani, Toshiaki; Shinomoto, Shigeru

2012-04-01

Estimations of an underlying rate from data points are inevitably disturbed by the irregular occurrence of events. Proper estimation methods are designed to avoid overfitting by discounting the irregular occurrence of data, and to determine a constant rate from irregular data derived from a constant probability distribution. However, it can occur that rapid or small fluctuations in the underlying density are undetectable when the data are sparse. For an estimation method, the maximum degree of undetectable rate fluctuations is uniquely determined as a phase transition, when considering an infinitely long series of events drawn from a fluctuating density. In this study, we analytically examine an optimized histogram and a Bayesian rate estimator with respect to their detectability of rate fluctuation, and determine whether their detectable-undetectable phase transition points are given by an identical formula defining a degree of fluctuation in an underlying rate. In addition, we numerically examine the variational Bayes hidden Markov model in its detectability of rate fluctuation, and determine whether the numerically obtained transition point is comparable to those of the other two methods. Such consistency among these three principled methods suggests the presence of a theoretical limit for detecting rate fluctuations.

A novel colloidal gold labeled antigen for the detection of Deoxynivalenol using an immunochromatographic assay method

NASA Astrophysics Data System (ADS)

Jin, Yu; Liu, Renrong; Zhu, Lixin; Chen, Zhenzhen

2017-11-01

In this paper, an immunochromatographic assay card was developed for the detection of DON in feed and cereals using a novel colloidal gold labeling method. For the colloidal gold immunochromatographic rapid detection (GICD) card, a monoclonal antibody DON-mAb and a goat anti-chicken IgY were drawn on NC membrane as the test line (T line) and the control line (C line) respectively. A gold labeled DON-CBSA conjugate and a gold labeled chicken IgY were sprayed onto the conjugate pad. The GICD card has cut-off levels of 50ng/mL for DON, which is invulnerable to matrix interference, and applicable to a wide range of samples. The GICD detecting results of feed and grain samples were compared with the results of ELISA testing, which showed good consistency.

Consistency of Influenza A Virus Detection Test Results across Respiratory Specimen Collection Methods Using Real-Time Reverse Transcription-PCR

PubMed Central

Gaglani, Manjusha; Naleway, Allison; Reynolds, Sue; Ball, Sarah; Bozeman, Sam; Henkle, Emily; Meece, Jennifer; Vandermause, Mary; Clipper, Lydia; Thompson, Mark

2013-01-01

In our prospective cohort study, we compared the performance of nasopharyngeal, oropharyngeal, and nasal swabs for the detection of influenza virus using real-time reverse transcription-PCR assay. Joint consideration of results from oropharyngeal and nasal swabs was as effective as consideration of results from nasopharyngeal swabs alone, as measured by sensitivity and noninferiority analysis. PMID:24108606

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

PubMed Central

Kim, Sungho; Lee, Joohyoung

2014-01-01

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

Detection of White Root Disease (Rigidoporus Microporus) in Various Soil Types in the Rubber Plantations Based on The Serological Reaction

NASA Astrophysics Data System (ADS)

Indriani Dalimunthe, Cici; Tistama, Radite; Wahyuni, Sri

2017-12-01

The Conventional detection of White Root Disease (Rigidoporus microporus, WRD) still uses the visual method based on an abnormal color of leaf or mycelium growth on the tap root neck. The method was less effective and less efficient. The serological technique uses yolk chicken antibodies induced by immunization with mycelium extract. The purpose of this research was to examine the consistency of selected antibodies in detecting root fungi at various soil types in the rubber plantations. This research used a Completely Randomized Design non-factorial with twelve (12) treatments and two (2) replications. The results showed that the antibodies could detect WRD in various soils types. The serological detection was higher precisely than visual observation. The development of WRD mycelium varies depending on the soil types and it was different in the each estate area. In addition, this research is expected to get a serology kit to detect early symptoms of WRD in the rubber plants.

Development and validation of a FISH-based method for the detection and quantification of E. coli and coliform bacteria in water samples.

PubMed

Hügler, Michael; Böckle, Karin; Eberhagen, Ingrid; Thelen, Karin; Beimfohr, Claudia; Hambsch, Beate

2011-01-01

Monitoring of microbiological contaminants in water supplies requires fast and sensitive methods for the specific detection of indicator organisms or pathogens. We developed a protocol for the simultaneous detection of E. coli and coliform bacteria based on the Fluorescence in situ Hybridization (FISH) technology. This protocol consists of two approaches. The first allows the direct detection of single E. coli and coliform bacterial cells on the filter membranes. The second approach includes incubation of the filter membranes on a nutrient agar plate and subsequent detection of the grown micro-colonies. Both approaches were validated using drinking water samples spiked with pure cultures and naturally contaminated water samples. The effects of heat, chlorine and UV disinfection were also investigated. The micro-colony approach yielded very good results for all samples and conditions tested, and thus can be thoroughly recommended for usage as an alternative method to detect E. coli and coliform bacteria in water samples. However, during this study, some limitations became visible for the single cell approach. The method cannot be applied for water samples which have been disinfected by UV irradiation. In addition, our results indicated that green fluorescent dyes are not suitable to be used with chlorine disinfected samples.

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

Development of a recombinase polymerase amplification assay for Vibrio parahaemolyticus detection with an internal amplification control.

PubMed

Yang, Huan-Lan; Wei, Shuang; Gooneratne, Ravi; Mutukumira, Anthony N; Ma, Xue-Jun; Tang, Shu-Ze; Wu, Xi-Yang

2018-04-01

A novel RPA-IAC assay using recombinase polymerase and an internal amplification control (IAC) for Vibrio parahaemolyticus detection was developed. Specific primers were designed based on the coding sequence for the toxR gene in V. parahaemolyticus. The recombinase polymerase amplification (RPA) reaction was conducted at a constant low temperature of 37 °C for 20 min. Assay specificity was validated by using 63 Vibrio strains and 10 non-Vibrio bacterial species. In addition, a competitive IAC was employed to avoid false-negative results, which co-amplified simultaneously with the target sequence. The sensitivity of the assay was determined as 3 × 10 3 CFU/mL, which is decidedly more sensitive than the established PCR method. This method was then used to test seafood samples that were collected from local markets. Seven out of 53 different raw seafoods were detected as V. parahaemolyticus-positive, which were consistent with those obtained using traditional culturing method and biochemical assay. This novel RPA-IAC assay provides a rapid, specific, sensitive, and more convenient detection method for V. parahaemolyticus.

Development of a fractionation method for the detection and identification of oak ellagitannins in red wines.

PubMed

García-Estévez, Ignacio; Escribano-Bailón, M Teresa; Rivas-Gonzalo, Julián C; Alcalde-Eon, Cristina

2010-02-15

During maturation and ageing in oak barrels wines improve their organoleptic properties. Ellagitannins can be released from wood to the wine and be involved in oxidation reactions and seem to influence the astringency and colour properties of the wine. Nevertheless, the ellagitannins levels are lower than those of other wine constituents and, consequently, they are not easily detected. This study has developed a two-step fractionation method consisting of a solid phase extraction in C-18 Sep-Pak cartridges followed by size exclusion chromatography in hand-packed Sephadex LH-20 minicolumn for the detection of oak ellagitannins in different types of wines. An HPLC method has also been developed which allows the separation of compounds with the same m/z ratios, facilitating the ellagitannin identification by means of the mass spectrometric analyses. The main oak ellagitannins (grandinin, vescalagin, roburin E and castalagin) were isolated, detected separately and identified in a spiked wine and in three real ones, proving the usefulness of the fractionation method. Copyright 2009 Elsevier B.V. All rights reserved.

The practical application of signal detection theory to image quality assessment in x-ray image intensifier-TV fluoroscopy.

PubMed

Marshall, N W

2001-06-01

This paper applies a published version of signal detection theory to x-ray image intensifier fluoroscopy data and compares the results with more conventional subjective image quality measures. An eight-bit digital framestore was used to acquire temporally contiguous frames of fluoroscopy data from which the modulation transfer function (MTF(u)) and noise power spectrum were established. These parameters were then combined to give detective quantum efficiency (DQE(u)) and used in conjunction with signal detection theory to calculate contrast-detail performance. DQE(u) was found to lie between 0.1 and 0.5 for a range of fluoroscopy systems. Two separate image quality experiments were then performed in order to assess the correspondence between the objective and subjective methods. First, image quality for a given fluoroscopy system was studied as a function of doserate using objective parameters and a standard subjective contrast-detail method. Following this, the two approaches were used to assess three different fluoroscopy units. Agreement between objective and subjective methods was good; doserate changes were modelled correctly while both methods ranked the three systems consistently.

A simple method of DNA isolation from jute (Corchorus olitorius) seed suitable for PCR-based detection of the pathogen Macrophomina phaseolina (Tassi) Goid.

PubMed

Biswas, C; Dey, P; Satpathy, S; Sarkar, S K; Bera, A; Mahapatra, B S

2013-02-01

A simple method was developed for isolating DNA from jute seed, which contains high amounts of mucilage and secondary metabolites, and a PCR protocol was standardized for detecting the seedborne pathogen Macrophomina phaseolina. The cetyl trimethyl ammonium bromide method was modified with increased salt concentration and a simple sodium acetate treatment to extract genomic as well as fungal DNA directly from infected jute seed. The Miniprep was evaluated along with five other methods of DNA isolation in terms of yield and quality of DNA and number of PCR positive samples. The Miniprep consistently recovered high amounts of DNA with good spectral qualities at A260/A280. The DNA isolated from jute seed was found suitable for PCR amplification. Macrophomina phaseolina could be detected by PCR from artificially inoculated as well as naturally infected jute seeds. The limit of PCR-based detection of M. phaseolina in jute seed was determined to be 0·62 × 10(-7) CFU g(-1) seed. © 2012 The Society for Applied Microbiology.

Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique

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

Teramoto, Atsushi, E-mail: teramoto@fujita-hu.ac.jp; Fujita, Hiroshi; Yamamuro, Osamu

Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using anmore » active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules using PET/CT images.« less

Detection and localization of change points in temporal networks with the aid of stochastic block models

NASA Astrophysics Data System (ADS)

De Ridder, Simon; Vandermarliere, Benjamin; Ryckebusch, Jan

2016-11-01

A framework based on generalized hierarchical random graphs (GHRGs) for the detection of change points in the structure of temporal networks has recently been developed by Peel and Clauset (2015 Proc. 29th AAAI Conf. on Artificial Intelligence). We build on this methodology and extend it to also include the versatile stochastic block models (SBMs) as a parametric family for reconstructing the empirical networks. We use five different techniques for change point detection on prototypical temporal networks, including empirical and synthetic ones. We find that none of the considered methods can consistently outperform the others when it comes to detecting and locating the expected change points in empirical temporal networks. With respect to the precision and the recall of the results of the change points, we find that the method based on a degree-corrected SBM has better recall properties than other dedicated methods, especially for sparse networks and smaller sliding time window widths.

Effect of specimen storage, antibiotics, and feminine hygiene products on the detection of group B Streptococcus by culture and the STREP B OIA test.

PubMed

Ostroff, R M; Steaffens, J W

1995-07-01

Agar culture from vaginal swabs is the routine method for diagnosis of maternal Group B Streptococcus (GBS) colonization. Swab specimens are often transported to a clinical laboratory for processing. In these studies, specimen transport was simulated by inoculating swabs with GBS and storing them at selected temperatures and with or without transport medium. The recovery of viable GBS was assessed by agar culture. GBS antigen was detected immunologically with an Optical ImmunoAssay (OIA) method. Swabs that were stored with transport medium harbored viable but rapidly declining numbers of GBS. In contrast, a strong OIA signal was maintained. Recovery of viable GBS organisms declined more quickly when swabs were stored in the absence of transport medium, whereas detection of GBS antigen remained consistent. Both methods were tested for interference from either antibiotics or feminine hygiene products. These compounds inhibited the detection of GBS by culture but had no detrimental effect on the OIA result.

Normal and polar-organic-phase high-performance liquid chromatographic enantioresolution of omeprazole, rabeprazole, lansoprazole and pantoprazole using monochloro-methylated cellulose-based chiral stationary phase and determination of dexrabeprazole.

PubMed

Dixit, Shuchi; Dubey, Rituraj; Bhushan, Ravi

2014-01-01

Enantioresolution of four anti-ulcer drugs (chiral sulfoxides), namely, omeprazole, rabeprazole, lansoprazole and pantoprazole, was carried out by high-performance liquid chromatography using a polysaccharide-based chiral stationary phase consisting of monochloromethylated cellulose (Lux cellulose-2) under normal and polar-organic-phase conditions with ultraviolet detection at 285 nm. The method was validated for linearity, accuracy, precision, robustness and limit of detection. The optimized enantioresolution method was compared for both the elution modes. The optimized method was further utilized to check the enantiomeric purity of dexrabeprazole. Copyright © 2013 John Wiley & Sons, Ltd.

Method of analyzing multiple sample simultaneously by detecting absorption and systems for use in such a method

DOEpatents

Yeung, Edward S.; Gong, Xiaoyi

2004-09-07

The present invention provides a method of analyzing multiple samples simultaneously by absorption detection. The method comprises: (i) providing a planar array of multiple containers, each of which contains a sample comprising at least one absorbing species, (ii) irradiating the planar array of multiple containers with a light source and (iii) detecting absorption of light with a detetion means that is in line with the light source at a distance of at leaat about 10 times a cross-sectional distance of a container in the planar array of multiple containers. The absorption of light by a sample indicates the presence of an absorbing species in it. The method can further comprise: (iv) measuring the amount of absorption of light detected in (iii) indicating the amount of the absorbing species in the sample. Also provided by the present invention is a system for use in the abov metho.The system comprises; (i) a light source comrnpising or consisting essentially of at leaat one wavelength of light, the absorption of which is to be detected, (ii) a planar array of multiple containers, and (iii) a detection means that is in line with the light source and is positioned in line with and parallel to the planar array of multiple contiainers at a distance of at least about 10 times a cross-sectional distance of a container.

TPH detection in groundwater: Identification and elimination of positive interferences

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

Zemo, D.A.; Synowiec, K.A.

1996-01-01

Groundwater assessment programs frequently require total petroleum hydrocarbon (TPH) analyses (Methods 8015M and 418.1). TPH analyses are often unreliable indicators of water quality because these methods are not constituent-specific and are vulnerable to significant sources of positive interferences. These positive interferences include: (a) non-dissolved petroleum constituents; (b) soluble, non-petroleum hydrocarbons (e.g., biodegradation products); and (c) turbidity, commonly introduced into water samples during sample collection. In this paper, we show that the portion of a TPH concentration not directly the result of water-soluble petroleum constituents can be attributed solely to these positive interferences. To demonstrate the impact of these interferences, wemore » conducted a field experiment at a site affected by degraded crude oil. Although TPH was consistently detected in groundwater samples, BTEX was not detected. PNAs were not detected, except for very low concentrations of fluorene (<5 ug/1). Filtering and silica gel cleanup steps were added to sampling and analyses to remove particulates and biogenic by-products. Results showed that filtering lowered the Method 8015M concentrations and reduced the Method 418.1 concentrations to non-detectable. Silica gel cleanup reduced the Method 8015M concentrations to non-detectable. We conclude from this study that the TPH results from groundwater samples are artifacts of positive interferences caused by both particulates and biogenic materials and do not represent dissolved-phase petroleum constituents.« less

TPH detection in groundwater: Identification and elimination of positive interferences

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

Zemo, D.A.; Synowiec, K.A.

1996-12-31

Groundwater assessment programs frequently require total petroleum hydrocarbon (TPH) analyses (Methods 8015M and 418.1). TPH analyses are often unreliable indicators of water quality because these methods are not constituent-specific and are vulnerable to significant sources of positive interferences. These positive interferences include: (a) non-dissolved petroleum constituents; (b) soluble, non-petroleum hydrocarbons (e.g., biodegradation products); and (c) turbidity, commonly introduced into water samples during sample collection. In this paper, we show that the portion of a TPH concentration not directly the result of water-soluble petroleum constituents can be attributed solely to these positive interferences. To demonstrate the impact of these interferences, wemore » conducted a field experiment at a site affected by degraded crude oil. Although TPH was consistently detected in groundwater samples, BTEX was not detected. PNAs were not detected, except for very low concentrations of fluorene (<5 ug/1). Filtering and silica gel cleanup steps were added to sampling and analyses to remove particulates and biogenic by-products. Results showed that filtering lowered the Method 8015M concentrations and reduced the Method 418.1 concentrations to non-detectable. Silica gel cleanup reduced the Method 8015M concentrations to non-detectable. We conclude from this study that the TPH results from groundwater samples are artifacts of positive interferences caused by both particulates and biogenic materials and do not represent dissolved-phase petroleum constituents.« less

[Study of the Detecting System of CH4 and SO2 Based on Spectral Absorption Method and UV Fluorescence Method].

PubMed

Wang, Shu-tao; Wang, Zhi-fang; Liu, Ming-hua; Wei, Meng; Chen, Dong-ying; Wang, Xing-long

2016-01-01

According to the spectral absorption characteristics of polluting gases and fluorescence characteristics, a time-division multiplexing detection system is designed. Through this system we can detect Methane (CH4) and sulfur dioxide (SO2) by using spectral absorption method and the SO2 can be detected by using UV fluorescence method. The system consists of four parts: a combination of a light source which could be switched, the common optical path, the air chamber and the signal processing section. The spectral absorption characteristics and fluorescence characteristics are measured first. Then the experiment of detecting CH4 and SO2 through spectral absorption method and the experiment of detecting SO2 through UV fluorescence method are conducted, respectively. Through measuring characteristics of spectral absorption and fluorescence, we get excitation wavelengths of SO2 and CH4 measured by spectral absorption method at the absorption peak are 280 nm and 1.64 μm, respectively, and the optimal excitation wavelength of SO2 measured by UV fluorescence method is 220 nm. we acquire the linear relation between the concentration of CH4 and relative intensity and the linear relation between the concentration of SO2 and output voltage after conducting the experiment of spectral absorption method, and the linearity are 98.7%, 99.2% respectively. Through the experiment of UV fluorescence method we acquire that the relation between the concentration of SO2 and the voltage is linear, and the linearity is 99.5%. Research shows that the system is able to be applied to detect the polluted gas by absorption spectrum method and UV fluorescence method. Combing these two measurement methods decreases the costing and the volume, and this system can also be used to measure the other gases. Such system has a certain value of application.

Space and time resolved representation of a vacuum arc light emission

NASA Astrophysics Data System (ADS)

Georgescu, N.; Sandolache, G.; Zoita, V.

1999-04-01

An optoelectronic multichannel detection system for the study of the visible light emission of a vacuum circuit breaker arc is described. The system consists of two multiple slit collimator assemblies coupled directly to the arc discharge chamber and an electronic detection part. The light emitted by the arc is collected by the two collimator assemblies and is transmitted through optical fibres to the electronic detection part. By using a new, simple computational method two-dimensional plots of the vacuum arc light emission at different times are obtained.

Note: Focus error detection device for thermal expansion-recovery microscopy (ThERM).

PubMed

Domené, E A; Martínez, O E

2013-01-01

An innovative focus error detection method is presented that is only sensitive to surface curvature variations, canceling both thermoreflectance and photodefelection effects. The detection scheme consists of an astigmatic probe laser and a four-quadrant detector. Nonlinear curve fitting of the defocusing signal allows the retrieval of a cutoff frequency, which only depends on the thermal diffusivity of the sample and the pump beam size. Therefore, a straightforward retrieval of the thermal diffusivity of the sample is possible with microscopic lateral resolution and high axial resolution (~100 pm).

Quantification of Protozoa and Viruses from Small Water Volumes

PubMed Central

Bonilla, J. Alfredo; Bonilla, Tonya D.; Abdelzaher, Amir M.; Scott, Troy M.; Lukasik, Jerzy; Solo-Gabriele, Helena M.; Palmer, Carol J.

2015-01-01

Large sample volumes are traditionally required for the analysis of waterborne pathogens. The need for large volumes greatly limits the number of samples that can be processed. The goals of this study were to compare extraction and detection procedures for quantifying protozoan parasites and viruses from small volumes of marine water. The intent was to evaluate a logistically simpler method of sample collection and processing that would facilitate direct pathogen measures as part of routine monitoring programs. Samples were collected simultaneously using a bilayer device with protozoa capture by size (top filter) and viruses capture by charge (bottom filter). Protozoan detection technologies utilized for recovery of Cryptosporidium spp. and Giardia spp. were qPCR and the more traditional immunomagnetic separation—IFA-microscopy, while virus (poliovirus) detection was based upon qPCR versus plaque assay. Filters were eluted using reagents consistent with the downstream detection technologies. Results showed higher mean recoveries using traditional detection methods over qPCR for Cryptosporidium (91% vs. 45%) and poliovirus (67% vs. 55%) whereas for Giardia the qPCR-based methods were characterized by higher mean recoveries (41% vs. 28%). Overall mean recoveries are considered high for all detection technologies. Results suggest that simultaneous filtration may be suitable for isolating different classes of pathogens from small marine water volumes. More research is needed to evaluate the suitability of this method for detecting pathogens at low ambient concentration levels. PMID:26114244

Quantification of Protozoa and Viruses from Small Water Volumes.

PubMed

Bonilla, J Alfredo; Bonilla, Tonya D; Abdelzaher, Amir M; Scott, Troy M; Lukasik, Jerzy; Solo-Gabriele, Helena M; Palmer, Carol J

2015-06-24

Large sample volumes are traditionally required for the analysis of waterborne pathogens. The need for large volumes greatly limits the number of samples that can be processed. The aims of this study were to compare extraction and detection procedures for quantifying protozoan parasites and viruses from small volumes of marine water. The intent was to evaluate a logistically simpler method of sample collection and processing that would facilitate direct pathogen measures as part of routine monitoring programs. Samples were collected simultaneously using a bilayer device with protozoa capture by size (top filter) and viruses capture by charge (bottom filter). Protozoan detection technologies utilized for recovery of Cryptosporidium spp. and Giardia spp. were qPCR and the more traditional immunomagnetic separation-IFA-microscopy, while virus (poliovirus) detection was based upon qPCR versus plaque assay. Filters were eluted using reagents consistent with the downstream detection technologies. Results showed higher mean recoveries using traditional detection methods over qPCR for Cryptosporidium (91% vs. 45%) and poliovirus (67% vs. 55%) whereas for Giardia the qPCR-based methods were characterized by higher mean recoveries (41% vs. 28%). Overall mean recoveries are considered high for all detection technologies. Results suggest that simultaneous filtration may be suitable for isolating different classes of pathogens from small marine water volumes. More research is needed to evaluate the suitability of this method for detecting pathogens at low ambient concentration levels.

Removal of infused water predominantly during insertion (water exchange) is consistently associated with an increase in adenoma detection rate - review of data in randomized controlled trials (RCTs) of water-related methods

PubMed Central

Harker, JO; Leung, JW; Siao-Salera, RM; Mann, SK; Ramirez, FC; Friedland, S; Amato, A; Radaelli, F; Paggi, S; Terruzzi, V; Hsieh, YH

2011-01-01

Introduction Variation in outcomes in RcTs comparing water-related methods and air insufflation raises challenging questions regarding the new approach. This report reviews impact of water exchange - simultaneous infusion and removal of infused water during insertion on adenoma detection rate (ADR) defined as proportion of patients with a least one adenoma of any size. Methods Medline (2008–2011) searches, abstract of 2011 Digestive Disease Week (DDW) meeting and personal communications were considered to identify RcTs that compared water-related methods and air insufflation to aid insertion of colonoscope. Results Since 2008, eleven reports of RcTs (6 published, 1 submitted and 4 abstracts, n=1728) described ADR in patients randomized to be examined by air and water-related methods. The water-related methods differed in timing of removal of the infused water -predominantly during insertion (water exchange) (n=825) or predominantly during withdrawal (water immersion) (n=903). Water immersion was associated with both increases and decreases in ADR compared to respective air method patients and the net overall change (-7%) was significant. On the other hand water exchange was associated with increases in ADR consistently and the net changes (overall, 8%; proximal overall, 11%; and proximal <10 mm, 12%) were all significant. Conclusion Comparative data generated the hypothesis that significantly larger increases in overall and proximal colon ADRs were associated with water exchange than water immersion or air insufflation during insertion. The hypothesis should be evaluated by RCTs to elucidate the mechanism of water exchange on adenoma detection. PMID:22163082

Robust curb detection with fusion of 3D-Lidar and camera data.

PubMed

Tan, Jun; Li, Jian; An, Xiangjing; He, Hangen

2014-05-21

Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes.

Automatic Detection of Acromegaly From Facial Photographs Using Machine Learning Methods.

PubMed

Kong, Xiangyi; Gong, Shun; Su, Lijuan; Howard, Newton; Kong, Yanguo

2018-01-01

Automatic early detection of acromegaly is theoretically possible from facial photographs, which can lessen the prevalence and increase the cure probability. In this study, several popular machine learning algorithms were used to train a retrospective development dataset consisting of 527 acromegaly patients and 596 normal subjects. We firstly used OpenCV to detect the face bounding rectangle box, and then cropped and resized it to the same pixel dimensions. From the detected faces, locations of facial landmarks which were the potential clinical indicators were extracted. Frontalization was then adopted to synthesize frontal facing views to improve the performance. Several popular machine learning methods including LM, KNN, SVM, RT, CNN, and EM were used to automatically identify acromegaly from the detected facial photographs, extracted facial landmarks, and synthesized frontal faces. The trained models were evaluated using a separate dataset, of which half were diagnosed as acromegaly by growth hormone suppression test. The best result of our proposed methods showed a PPV of 96%, a NPV of 95%, a sensitivity of 96% and a specificity of 96%. Artificial intelligence can automatically early detect acromegaly with a high sensitivity and specificity. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

A critical review of three methods used for the measurement of mercury (Hg2+)-dissolved organic matter stability constants

USGS Publications Warehouse

Gasper, J.D.; Aiken, G.R.; Ryan, J.N.

2007-01-01

Three experimental techniques - ion exchange, liquid-liquid extraction with competitive ligand exchange, and solid-phase extraction with competitive ligand exchange (CLE-SPE) - were evaluated as methods for determining conditional stability constants (K) for the binding of mercury (Hg2+) to dissolved organic matter (DOM). To determine the utility of a given method to measure stability constants at environmentally relevant experimental conditions, experimental results should meet three criteria: (1) the data must be experimentally valid, in that they were acquired under conditions that meet all the requirements of the experimental method, (2) the Hg:DOM ratio should be determined and it should fall within levels that are consistent with environmental conditions, and (3) the stability constants must fall within the detection window of the method. The ion exchange method was found to be limited by its detection window, which constrains the method to stability constants with log K values less than about 14. The liquid-liquid extraction method was found to be complicated by the ability of Hg-DOM complexes to partition into the organic phase. The CLE-SPE method was found to be the most suitable of these methods for the measurement of Hg-DOM stability constants. Stability constants for DOM isolates measured using the CLE-SPE method at environmentally relevant Hg:DOM ratios were log K = 25-30 (M-1). These values are consistent with the strong Hg2+ binding expected for reduced S-containing binding sites. ?? 2007 Elsevier Ltd. All rights reserved.

Centrifugal compressor surge detecting method based on wavelet analysis of unsteady pressure fluctuations in typical stages

NASA Astrophysics Data System (ADS)

Izmaylov, R.; Lebedev, A.

2015-08-01

Centrifugal compressors are complex energy equipment. Automotive control and protection system should meet the requirements: of operation reliability and durability. In turbocompressors there are at least two dangerous areas: surge and rotating stall. Antisurge protecting systems usually use parametric or feature methods. As a rule industrial system are parametric. The main disadvantages of anti-surge parametric systems are difficulties in mass flow measurements in natural gas pipeline compressor. The principal idea of feature method is based on the experimental fact: as a rule just before the onset of surge rotating or precursor stall established in compressor. In this case the problem consists in detecting of unsteady pressure or velocity fluctuations characteristic signals. Wavelet analysis is the best method for detecting onset of rotating stall in spite of high level of spurious signals (rotating wakes, turbulence, etc.). This method is compatible with state of the art DSP systems of industrial control. Examples of wavelet analysis application for detecting onset of rotating stall in typical stages centrifugal compressor are presented. Experimental investigations include unsteady pressure measurement and sophisticated data acquisition system. Wavelet transforms used biorthogonal wavelets in Mathlab systems.

TERMA Framework for Biomedical Signal Analysis: An Economic-Inspired Approach.

PubMed

Elgendi, Mohamed

2016-11-02

Biomedical signals contain features that represent physiological events, and each of these events has peaks. The analysis of biomedical signals for monitoring or diagnosing diseases requires the detection of these peaks, making event detection a crucial step in biomedical signal processing. Many researchers have difficulty detecting these peaks to investigate, interpret and analyze their corresponding events. To date, there is no generic framework that captures these events in a robust, efficient and consistent manner. A new method referred to for the first time as two event-related moving averages ("TERMA") involves event-related moving averages and detects events in biomedical signals. The TERMA framework is flexible and universal and consists of six independent LEGO building bricks to achieve high accuracy detection of biomedical events. Results recommend that the window sizes for the two moving averages ( W 1 and W 2 ) have to follow the inequality ( 8 × W 1 ) ≥ W 2 ≥ ( 2 × W 1 ) . Moreover, TERMA is a simple yet efficient event detector that is suitable for wearable devices, point-of-care devices, fitness trackers and smart watches, compared to more complex machine learning solutions.

Biomedical journals lack a consistent method to detect outcome reporting bias: a cross-sectional analysis.

PubMed

Huan, L N; Tejani, A M; Egan, G

2014-10-01

An increasing amount of recently published literature has implicated outcome reporting bias (ORB) as a major contributor to skewing data in both randomized controlled trials and systematic reviews; however, little is known about the current methods in place to detect ORB. This study aims to gain insight into the detection and management of ORB by biomedical journals. This was a cross-sectional analysis involving standardized questions via email or telephone with the top 30 biomedical journals (2012) ranked by impact factor. The Cochrane Database of Systematic Reviews was excluded leaving 29 journals in the sample. Of 29 journals, 24 (83%) responded to our initial inquiry of which 14 (58%) answered our questions and 10 (42%) declined participation. Five (36%) of the responding journals indicated they had a specific method to detect ORB, whereas 9 (64%) did not have a specific method in place. The prevalence of ORB in the review process seemed to differ with 4 (29%) journals indicating ORB was found commonly, whereas 7 (50%) indicated ORB was uncommon or never detected by their journal previously. The majority (n = 10/14, 72%) of journals were unwilling to report or make discrepancies found in manuscripts available to the public. Although the minority, there were some journals (n = 4/14, 29%) which described thorough methods to detect ORB. Many journals seemed to lack a method with which to detect ORB and its estimated prevalence was much lower than that reported in literature suggesting inadequate detection. There exists a potential for overestimation of treatment effects of interventions and unclear risks. Fortunately, there are journals within this sample which appear to utilize comprehensive methods for detection of ORB, but overall, the data suggest improvements at the biomedical journal level for detecting and minimizing the effect of this bias are needed. © 2014 John Wiley & Sons Ltd.

Combined electrophoresis-electrospray interface and method

DOEpatents

Smith, Richard D.; Udseth, Harold R.; Barinaga, Charles J.

1995-01-01

An improvement to the system and method for analyzing molecular constituents of a composition sample that comprises improvements to an electrospray ionization source for interfacing to mass spectrometers and other detection devices. The improvement consists of establishing a unique electrical circuit pattern and nozzle configuration, a metallic coated and conical shaped capillary outlet, coupled with sizing of the capillary to obtain maximum sensitivity.

Optimization of o-phtaldialdehyde/2-mercaptoethanol postcolumn reaction for the hydrophilic interaction liquid chromatography determination of memantine utilizing a silica hydride stationary phase.

PubMed

Douša, Michal; Pivoňková, Veronika; Sýkora, David

2016-08-01

A rapid procedure for the determination of memantine based on hydrophilic interaction chromatography with fluorescence detection was developed. Fluorescence detection after postcolumn derivatization with o-phtaldialdehyde/2-mercaptoethanol was performed at excitation and emission wavelengths of 345 and 450 nm, respectively. The postcolumn reaction conditions such as reaction temperature, derivatization reagent flow rate, and reagents concentration were studied due to steric hindrance of amino group of memantine. The derivatization reaction was applied for the hydrophilic interaction liquid chromatography method which was based on Cogent Silica-C stationary phase with a mobile phase consisting of a mixture of 10 mmol/L citric acid and 10 mmol/L o-phosphoric acid (pH 6.0) with acetonitrile using an isocratic composition of 2:8 v/v. The benefit of the reported approach consists in a simple sample pretreatment and a quick and sensitive hydrophilic interaction chromatography method. The developed method was validated in terms of linearity, accuracy, precision, and selectivity according to the International Conference on Harmonisation guidelines. The developed method was successfully applied for the analysis of commercial memantine tablets. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Turbulence detection using radiosondes: plugging the gaps in the observation of turbulence

NASA Astrophysics Data System (ADS)

Marlton, Graeme; Harrison, Giles; Williams, Paul; Nicoll, Keri

2014-05-01

Turbulence costs the airline industry tens of millions of dollars each year, through damage to aircraft and injury to passengers. Clear-air turbulence (CAT) is particularly problematic, as it cannot be detected using remote sensing methods and we lack consistent observations to validate forecast models. Here we describe two specially adapted meteorological radiosondes that are used to measure turbulence. The first sensor consists of a Hall-effect magnetometer, which uses the Earth's magnetic field as a reference point, allowing the motion of the sonde to be measured. The second consists of an accelerometer that measures the accelerations the balloon encounters. A solar radiation sensor is mounted at the top of the package, to determine whether the sonde is in cloud. Results from multiple flights over Reading, UK in different conditions, show both sensors detecting turbulent regions near jet boundaries and above cloud tops, with the accelerometer recording values in excess of 6g in these regions. Case studies will show how these observations can be used to test the performance of a selection of empirical turbulence diagnostics initialised from ERA-interim data.

Possibility of the detection and identification of substance at long distance using the noisy reflected THz pulse under real conditions

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Trofimov, Vladislav V.

2015-05-01

We show possibility of the detection and identification of substance at long distance (several metres, for example) using the THz pulse reflected from the object under the real conditions: at room temperature and humidity of about 70%. The main feature of this report consists in a demonstration of the detection and identification of substance using the computer processing of the noisy THz pulse. Amplitude of the useful signal is less than the amplitude of a noise. Nevertheless, it is possible to detect "fingerprint" frequencies of substance if these frequencies are known and the SDA method is used together with new assessments for probability estimation for presence of detected frequencies. Essential restrictions of the commonly used THz TDS method for the detection and identification under real conditions (at long distance about 3.5 m and at a high relative humidity more than 50%) are demonstrated using the physical experiment with chocolate bar and thick paper bag. We show also that the THz TDS method detects spectral features of dangerous substances even in the THz signals measured in laboratory conditions (at distance 30-40 cm from the receiver and at a low relative humidity less than 2%); the n-Si and p-Si semiconductors were used as neutral substances. However, the integral correlation and likeness criteria, based on SDA method, allow us to detect the absence of dangerous substances in the samples. Current results show feasibility of using the discussed method of the THz pulsed spectroscopy for the counter-terrorism problem.

Protocol for the use of a rapid real-time PCR method for the detection of HIV-1 proviral DNA using double-stranded primer.

PubMed

Pau, Chou-Pong; Wells, Susan K; Granade, Timothy C

2012-01-01

This chapter describes a real-time PCR method for the detection of HIV-1 proviral DNA in whole blood samples using a novel double-stranded primer system. The assay utilizes a simple commercially available DNA extraction method and a rapid and easy-to-perform real-time PCR protocol to consistently detect a minimum of four copies of HIV-1 group M proviral DNA in as little as 90 min after sample (whole blood) collection. Co-amplification of the human RNase P gene serves as an internal control to monitor the efficiency of both the DNA extraction and amplification. Once the assay is validated properly, it may be suitable as an alternative confirmation test for HIV-1 infections in a variety of HIV testing venues including the mother-to-child transmission testing sites, clinics, and diagnostic testing centers.

Error detection and reduction in blood banking.

PubMed

Motschman, T L; Moore, S B

1996-12-01

Error management plays a major role in facility process improvement efforts. By detecting and reducing errors, quality and, therefore, patient care improve. It begins with a strong organizational foundation of management attitude with clear, consistent employee direction and appropriate physical facilities. Clearly defined critical processes, critical activities, and SOPs act as the framework for operations as well as active quality monitoring. To assure that personnel can detect an report errors they must be trained in both operational duties and error management practices. Use of simulated/intentional errors and incorporation of error detection into competency assessment keeps employees practiced, confident, and diminishes fear of the unknown. Personnel can clearly see that errors are indeed used as opportunities for process improvement and not for punishment. The facility must have a clearly defined and consistently used definition for reportable errors. Reportable errors should include those errors with potentially harmful outcomes as well as those errors that are "upstream," and thus further away from the outcome. A well-written error report consists of who, what, when, where, why/how, and follow-up to the error. Before correction can occur, an investigation to determine the underlying cause of the error should be undertaken. Obviously, the best corrective action is prevention. Correction can occur at five different levels; however, only three of these levels are directed at prevention. Prevention requires a method to collect and analyze data concerning errors. In the authors' facility a functional error classification method and a quality system-based classification have been useful. An active method to search for problems uncovers them further upstream, before they can have disastrous outcomes. In the continual quest for improving processes, an error management program is itself a process that needs improvement, and we must strive to always close the circle of quality assurance. Ultimately, the goal of better patient care will be the reward.

Bacteriophage-based nanoprobes for rapid bacteria separation

NASA Astrophysics Data System (ADS)

Chen, Juhong; Duncan, Bradley; Wang, Ziyuan; Wang, Li-Sheng; Rotello, Vincent M.; Nugen, Sam R.

2015-10-01

The lack of practical methods for bacterial separation remains a hindrance for the low-cost and successful development of rapid detection methods from complex samples. Antibody-tagged magnetic particles are commonly used to pull analytes from a liquid sample. While this method is well-established, improvements in capture efficiencies would result in an increase of the overall detection assay performance. Bacteriophages represent a low-cost and more consistent biorecognition element as compared to antibodies. We have developed nanoscale bacteriophage-tagged magnetic probes, where T7 bacteriophages were bound to magnetic nanoparticles. The nanoprobe allowed the specific recognition and attachment to E. coli cells. The phage magnetic nanprobes were directly compared to antibody-conjugated magnetic nanoprobes. The capture efficiencies of bacteriophages and antibodies on nanoparticles for the separation of E. coli K12 at varying concentrations were determined. The results indicated a similar bacteria capture efficiency between the two nanoprobes.The lack of practical methods for bacterial separation remains a hindrance for the low-cost and successful development of rapid detection methods from complex samples. Antibody-tagged magnetic particles are commonly used to pull analytes from a liquid sample. While this method is well-established, improvements in capture efficiencies would result in an increase of the overall detection assay performance. Bacteriophages represent a low-cost and more consistent biorecognition element as compared to antibodies. We have developed nanoscale bacteriophage-tagged magnetic probes, where T7 bacteriophages were bound to magnetic nanoparticles. The nanoprobe allowed the specific recognition and attachment to E. coli cells. The phage magnetic nanprobes were directly compared to antibody-conjugated magnetic nanoprobes. The capture efficiencies of bacteriophages and antibodies on nanoparticles for the separation of E. coli K12 at varying concentrations were determined. The results indicated a similar bacteria capture efficiency between the two nanoprobes. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr03779d

Comparison of Automated Microarray Detection with Real-Time PCR Assays for Detection of Respiratory Viruses in Specimens Obtained from Children▿

PubMed Central

Raymond, Frédéric; Carbonneau, Julie; Boucher, Nancy; Robitaille, Lynda; Boisvert, Sébastien; Wu, Whei-Kuo; De Serres, Gaston; Boivin, Guy; Corbeil, Jacques

2009-01-01

Respiratory virus infections are a major health concern and represent the primary cause of testing consultation and hospitalization for young children. We developed and compared two assays that allow the detection of up to 23 different respiratory viruses that frequently infect children. The first method consisted of single TaqMan quantitative real-time PCR assays in a 96-well-plate format. The second consisted of a multiplex PCR followed by primer extension and microarray hybridization in an integrated molecular diagnostic device, the Infiniti analyzer. Both of our assays can detect adenoviruses of groups A, B, C, and E; coronaviruses HKU1, 229E, NL63, and OC43; enteroviruses A, B, C, and D; rhinoviruses of genotypes A and B; influenza viruses A and B; human metapneumoviruses (HMPV) A and B, human respiratory syncytial viruses (HRSV) A and B; and parainfluenza viruses of types 1, 2, and 3. These tests were used to identify viruses in 221 nasopharyngeal aspirates obtained from children hospitalized for respiratory tract infections. Respiratory viruses were detected with at least one of the two methods in 81.4% of the 221 specimens: 10.0% were positive for HRSV A, 38.0% for HRSV B, 13.1% for influenzavirus A, 8.6% for any coronaviruses, 13.1% for rhinoviruses or enteroviruses, 7.2% for adenoviruses, 4.1% for HMPV, and 1.5% for parainfluenzaviruses. Multiple viral infections were found in 13.1% of the specimens. The two methods yielded concordant results for 94.1% of specimens. These tests allowed a thorough etiological assessment of respiratory viruses infecting children in hospital settings and would assist public health interventions. PMID:19158263

Comparison of automated microarray detection with real-time PCR assays for detection of respiratory viruses in specimens obtained from children.

PubMed

Raymond, Frédéric; Carbonneau, Julie; Boucher, Nancy; Robitaille, Lynda; Boisvert, Sébastien; Wu, Whei-Kuo; De Serres, Gaston; Boivin, Guy; Corbeil, Jacques

2009-03-01

Respiratory virus infections are a major health concern and represent the primary cause of testing consultation and hospitalization for young children. We developed and compared two assays that allow the detection of up to 23 different respiratory viruses that frequently infect children. The first method consisted of single TaqMan quantitative real-time PCR assays in a 96-well-plate format. The second consisted of a multiplex PCR followed by primer extension and microarray hybridization in an integrated molecular diagnostic device, the Infiniti analyzer. Both of our assays can detect adenoviruses of groups A, B, C, and E; coronaviruses HKU1, 229E, NL63, and OC43; enteroviruses A, B, C, and D; rhinoviruses of genotypes A and B; influenza viruses A and B; human metapneumoviruses (HMPV) A and B, human respiratory syncytial viruses (HRSV) A and B; and parainfluenza viruses of types 1, 2, and 3. These tests were used to identify viruses in 221 nasopharyngeal aspirates obtained from children hospitalized for respiratory tract infections. Respiratory viruses were detected with at least one of the two methods in 81.4% of the 221 specimens: 10.0% were positive for HRSV A, 38.0% for HRSV B, 13.1% for influenzavirus A, 8.6% for any coronaviruses, 13.1% for rhinoviruses or enteroviruses, 7.2% for adenoviruses, 4.1% for HMPV, and 1.5% for parainfluenzaviruses. Multiple viral infections were found in 13.1% of the specimens. The two methods yielded concordant results for 94.1% of specimens. These tests allowed a thorough etiological assessment of respiratory viruses infecting children in hospital settings and would assist public health interventions.

Quantifying spontaneous metastasis in a syngeneic mouse melanoma model using real time PCR.

PubMed

Deng, Wentao; McLaughlin, Sarah L; Klinke, David J

2017-08-07

Modeling metastasis in vivo with animals is a priority for both revealing mechanisms of tumor dissemination and developing therapeutic methods. While conventional intravenous injection of tumor cells provides an efficient and consistent system for studying tumor cell extravasation and colonization, studying spontaneous metastasis derived from orthotopic tumor sites has the advantage of modeling more aspects of the metastatic cascade, but is challenging as it is difficult to detect small numbers of metastatic cells. In this work, we developed an approach for quantifying spontaneous metastasis in the syngeneic mouse B16 system using real time PCR. We first transduced B16 cells with lentivirus expressing firefly luciferase Luc2 gene for bioluminescence imaging. Next, we developed a real time quantitative PCR (qPCR) method for the detection of luciferase-expressing, metastatic tumor cells in mouse lungs and other organs. To illustrate the approach, we quantified lung metastasis in both spontaneous and experimental scenarios using B16F0 and B16F10 cells in C57BL/6Ncrl and NOD-Scid Gamma (NSG) mice. We tracked B16 melanoma metastasis with both bioluminescence imaging and qPCR, which were found to be self-consistent. Using this assay, we can quantitatively detect one Luc2 positive tumor cell out of 10 4 tissue cells, which corresponds to a metastatic burden of 1.8 × 10 4 metastatic cells per whole mouse lung. More importantly, the qPCR method was at least a factor of 10 more sensitive in detecting metastatic cell dissemination and should be combined with bioluminescence imaging as a high-resolution, end-point method for final metastatic cell quantitation. Given the rapid growth of primary tumors in many mouse models, assays with improved sensitivity can provide better insight into biological mechanisms that underpin tumor metastasis.

Zero leakage separable and semipermanent ducting joints

NASA Technical Reports Server (NTRS)

Mischel, H. T.

1973-01-01

A study program has been conducted to explore new methods of achieving zero leakage, separable and semipermanent, ducting joints for space flight vehicles. The study consisted of a search of literature of existing zero leakage methods, the generation of concepts of new methods of achieving the desired zero leakage criteria and the development of detailed analysis and design of a selected concept. Other techniques of leak detection were explored with a view toward improving this area.

EDRN Standard Operating Procedures (SOP) — EDRN Public Portal

Cancer.gov

The NCI’s Early Detection Research Network is developing a number of standard operating procedures for assays, methods, and protocols for collection and processing of biological samples, and other reference materials to assist investigators to conduct experiments in a consistent, reliable manner. These SOPs are established by the investigators of the Early Detection Research Network to maintain constancy throughout the Network. These SOPs represent neither a consensus, nor are the recommendations of NCI.

Energy-Consistent Multiscale Algorithms for Granular Flows

DTIC Science & Technology

2014-08-07

Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection...not been able to be captured comprehensively in models. The consequences of these advancements are broad and deep. The GEM method has revolutionized...the algorithm to detect contact needs to be redesign to be able to detect contact points, even in non-convex surfaces. To achieve this, we developed

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

PubMed

Zou, Zhengxia; Shi, Zhenwei

2018-03-01

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

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.

Recombinant Temporal Aberration Detection Algorithms for Enhanced Biosurveillance

PubMed Central

Murphy, Sean Patrick; Burkom, Howard

2008-01-01

Objective Broadly, this research aims to improve the outbreak detection performance and, therefore, the cost effectiveness of automated syndromic surveillance systems by building novel, recombinant temporal aberration detection algorithms from components of previously developed detectors. Methods This study decomposes existing temporal aberration detection algorithms into two sequential stages and investigates the individual impact of each stage on outbreak detection performance. The data forecasting stage (Stage 1) generates predictions of time series values a certain number of time steps in the future based on historical data. The anomaly measure stage (Stage 2) compares features of this prediction to corresponding features of the actual time series to compute a statistical anomaly measure. A Monte Carlo simulation procedure is then used to examine the recombinant algorithms’ ability to detect synthetic aberrations injected into authentic syndromic time series. Results New methods obtained with procedural components of published, sometimes widely used, algorithms were compared to the known methods using authentic datasets with plausible stochastic injected signals. Performance improvements were found for some of the recombinant methods, and these improvements were consistent over a range of data types, outbreak types, and outbreak sizes. For gradual outbreaks, the WEWD MovAvg7+WEWD Z-Score recombinant algorithm performed best; for sudden outbreaks, the HW+WEWD Z-Score performed best. Conclusion This decomposition was found not only to yield valuable insight into the effects of the aberration detection algorithms but also to produce novel combinations of data forecasters and anomaly measures with enhanced detection performance. PMID:17947614

Interactions between pre-processing and classification methods for event-related-potential classification: best-practice guidelines for brain-computer interfacing.

PubMed

Farquhar, J; Hill, N J

2013-04-01

Detecting event related potentials (ERPs) from single trials is critical to the operation of many stimulus-driven brain computer interface (BCI) systems. The low strength of the ERP signal compared to the noise (due to artifacts and BCI irrelevant brain processes) makes this a challenging signal detection problem. Previous work has tended to focus on how best to detect a single ERP type (such as the visual oddball response). However, the underlying ERP detection problem is essentially the same regardless of stimulus modality (e.g., visual or tactile), ERP component (e.g., P300 oddball response, or the error-potential), measurement system or electrode layout. To investigate whether a single ERP detection method might work for a wider range of ERP BCIs we compare detection performance over a large corpus of more than 50 ERP BCI datasets whilst systematically varying the electrode montage, spectral filter, spatial filter and classifier training methods. We identify an interesting interaction between spatial whitening and regularised classification which made detection performance independent of the choice of spectral filter low-pass frequency. Our results show that pipeline consisting of spectral filtering, spatial whitening, and regularised classification gives near maximal performance in all cases. Importantly, this pipeline is simple to implement and completely automatic with no expert feature selection or parameter tuning required. Thus, we recommend this combination as a "best-practice" method for ERP detection problems.

Validation of a sensitive PCR assay for the detection of Chelonid fibropapilloma-associated herpesvirus in latent turtle infections.

PubMed

Alfaro-Núñez, Alonzo; Gilbert, M Thomas P

2014-09-01

The Chelonid fibropapilloma-associated herpesvirus (CFPHV) is hypothesized to be the causative agent of fibropapillomatosis, a neoplastic disease in sea turtles, given its consistent detection by PCR in fibropapilloma tumours. CFPHV has also been detected recently by PCR in tissue samples from clinically healthy (non exhibiting fibropapilloma tumours) turtles, thus representing presumably latent infections of the pathogen. Given that template copy numbers of viruses in latent infections can be very low, extremely sensitive PCR assays are needed to optimize detection efficiency. In this study, efficiency of several PCR assays designed for CFPHV detection is explored and compared to a method published previously. The results show that adoption of a triplet set of singleplex PCR assays outperforms other methods, with an approximately 3-fold increase in detection success in comparison to the standard assay. Thus, a new assay for the detection of CFPHV DNA markers is presented, and adoption of its methodology is recommended in future CFPHV screens among sea turtles. Copyright © 2014 Elsevier B.V. All rights reserved.

Laser-induced heating integrated with a microfluidic platform for real-time DNA replication and detection

NASA Astrophysics Data System (ADS)

Hung, Min-Sheng; Ho, Chia-Chin; Chen, Chih-Pin

2016-08-01

This study developed a microfluidic platform for replicating and detecting DNA in real time by integrating a laser and a microfluidic device composed of polydimethylsiloxane. The design of the microchannels consisted of a laser-heating area and a detection area. An infrared laser was used as the heating source for DNA replication, and the laser power was adjusted to heat the solutions directly. In addition, strong biotin-avidin binding was used to capture and detect the replicated products. The biotin on one end was bound to avidin and anchored to the surface of the microchannels, whereas the biotin on the other end was bound to the quantum dots (Qdots). The results showed that the fluorescent intensity of the Qdots bound to the replicated products in the detection area increased with the number of thermal cycles created by the laser. When the number of thermal cycles was ≥10, the fluorescent intensity of the Qdots was directly detectable on the surface of the microchannels. The proposed method is more sensitive than detection methods entailing gel electrophoresis.

A non-reference evaluation method for edge detection of wear particles in ferrograph images

NASA Astrophysics Data System (ADS)

Wang, Jingqiu; Bi, Ju; Wang, Lianjun; Wang, Xiaolei

2018-02-01

Edges are one of the most important features of wear particles in a ferrograph image and are widely used to extract parameters, recognize types of wear particles, and assist in the identification of the wear mode and severity. Edge detection is a critical step in ferrograph image processing and analysis. Till date, there has been no single algorithm that guarantees the production of good quality edges in ferrograph images for a variety of applications. Therefore, it is desirable to have a reliable evaluation method for measuring the performance of various edge detection algorithms and for aiding in the selection of the optimal parameter and algorithm for ferrographic applications. In this paper, a new non-reference method for the objective evaluation of wear particle edge detection is proposed. In this method, a comprehensive index of edge evaluation is composed of three components, i.e., the reconstruction based similarity sub-index between the original image and the reconstructed image, the confidence degree sub-index used to show the true or false degree of the edge pixels, and the edge form sub-index that is used to determine the direction consistency and width uniformity of the edges. Two experiments are performed to illustrate the validity of the proposed method. First, this method is used to select the best parameters for an edge detection algorithm, and it is then used to compare the results obtained using various edge detection algorithms and determine the best algorithm. Experimental results of various real ferrograph images verify the effectiveness of the proposed method.

A single step reversed-phase high performance liquid chromatography separation of polar and non-polar lipids.

PubMed

Olsson, Petter; Holmbäck, Jan; Herslöf, Bengt

2014-11-21

This paper reports a simple chromatographic system to separate lipids classes as well as their molecular species. By the use of phenyl coated silica as stationary phase in combination with a simple mobile phase consisting of methanol and water, all tested lipid classes elute within 30 min. Furthermore, a method to accurately predict retention times of specific lipid components for this type of chromatography is presented. Common detection systems were used, namely evaporative light scattering detection (ELSD), charged aerosol detection (CAD), electrospray mass spectrometry (ESI-MS), and UV detection. Copyright © 2014 Elsevier B.V. All rights reserved.

Optical detection of tracer species in strongly scattering media.

PubMed

Brauser, Eric M; Rose, Peter E; McLennan, John D; Bartl, Michael H

2015-03-01

A combination of optical absorption and scattering is used to detect tracer species in a strongly scattering medium. An optical setup was developed, consisting of a dual-beam scattering detection scheme in which sample scattering beam overlaps with the characteristic absorption feature of quantum dot tracer species, while the reference scattering beam is outside any absorption features of the tracer. This scheme was successfully tested in engineered breakthrough tests typical of wastewater and subsurface fluid analysis, as well as in batch analysis of oil and gas reservoir fluids and biological samples. Tracers were detected even under highly scattering conditions, conditions in which conventional absorption or fluorescence methods failed.

[Method of detection of residual tissues in recurrent operations on the thyroid gland].

PubMed

Gostimskiĭ, A V; Romanchishen, A F; Zaĭtseva, I V; Kuznetsova, Iu V

2014-01-01

A search of residual tissues is complicated in recurrent operations on the thyroid gland. The Saint-Petersburg Centre of Surgery of the Endocrine System and Oncology developed the method of detection of residual tissues of the thyroid gland with the aim of preoperative chromothyroidolymphography under control of ultrasound. The method consisted of US performance during 15-20 minutes before the operation and an introduction of 1% sterile water solution of methylene blue in revealed residual tissues of the thyroid gland. The volume of injected coloring agent was 0.5-2 ml in the residual tissue volume smaller than 9 cm3 and 2-3 ml injected in case of more than 9 cm3. The residual tissues of the thyroid gland accurately visualized during the following operation. Described method gives the possibility to detect all regions of residual tissues which should be removed and at the same time it shortens a revision and surgery trauma.

Direct analysis of organic priority pollutants by IMS

NASA Technical Reports Server (NTRS)

Giam, C. S.; Reed, G. E.; Holliday, T. L.; Chang, L.; Rhodes, B. J.

1995-01-01

Many routine methods for monitoring of trace amounts of atmospheric organic pollutants consist of several steps. Typical steps are: (1) collection of the air sample; (2) trapping of organics from the sample; (3) extraction of the trapped organics; and (4) identification of the organics in the extract by GC (gas chromatography), HPLC (High Performance Liquid Chromatography), or MS (Mass Spectrometry). These methods are often cumbersome and time consuming. A simple and fast method for monitoring atmospheric organics using an IMS (Ion Mobility Spectrometer) is proposed. This method has a short sampling time and does not require extraction of the organics since the sample is placed directly in the IMS. The purpose of this study was to determine the responses in the IMS to organic 'priority pollutants'. Priority pollutants including representative polycyclic aromatic hydrocarbons (PAHs), phthalates, phenols, chlorinated pesticides, and polychlorinated biphenyls (PCB's) were analyzed in both the positive and negative detection mode at ambient atmospheric pressure. Detection mode and amount detected are presented.

Quantitative Caffeine Analysis Using a Surface Sampling Probe Electrospray Ionization Tandem Mass Spectrometry System

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

Ford, Michael J; Deibel, Michael A.; Tomkins, Bruce A

Quantitative determination of caffeine on reversed-phase C8 thin-layer chromatography plates using a surface sampling electrospray ionization system with tandem mass spectrometry detection is reported. The thin-layer chromatography/electrospray tandem mass spectrometry method employed a deuterium-labeled caffeine internal standard and selected reaction monitoring detection. Up to nine parallel caffeine bands on a single plate were sampled in a single surface scanning experiment requiring 35 min at a surface scan rate of 44 {mu}m/s. A reversed-phase HPLC/UV caffeine assay was developed in parallel to assess the mass spectrometry method performance. Limits of detection for the HPLC/UV and thin-layer chromatography/electrospray tandem mass spectrometry methodsmore » determined from the calibration curve statistics were 0.20 ng injected (0.50 {mu}L) and 1.0 ng spotted on the plate, respectively. Spike recoveries with standards and real samples ranged between 97 and 106% for both methods. The caffeine content of three diet soft drinks (Diet Coke, Diet Cherry Coke, Diet Pepsi) and three diet sport drinks (Diet Turbo Tea, Speed Stack Grape, Speed Stack Fruit Punch) was measured. The HPLC/UV and mass spectrometry determinations were in general agreement, and these values were consistent with the quoted values for two of the three diet colas. In the case of Diet Cherry Coke and the diet sports drinks, the determined caffeine amounts using both methods were consistently higher (by 8% or more) than the literature values.« less

[Comparison between old and new methods for detection of allergenic substances (egg and milk)].

PubMed

Watanabe, Hiroko; Akaboshi, Chie; Saita, Kiyotaka; Sekido, Haruko; Hashiguchi, Shigeki; Watabe, Kenjiro; Tanaka, Kouki

2011-01-01

The old ELISA method for detection of allergenic substances (egg and milk) in Kanagawa prefecture from 2003 to 2007, employed before improvement of the food allergen labeling system, yielded detection rates of 20% for egg and 30% for milk. In 2005, after improvement of the labeling system, the detection rate using the new ELISA in solutions containing 1% SDS and 7% 2-mercaptoethanol increased by about 10% for egg, but decreased by half for milk. There were 4 positive samples (over 10 µg/g) for both egg and milk proteins, on account of contamination by ingredients at the manufacturing line and the lack of proper food labeling. In 2009, the contamination levels of egg and milk proteins in labeled commercial foods were low. In a comparison between the new and old methods with the same samples, both the new ELISA and Western-blot analyses showed an increase in the detection rate of egg protein. In relation to milk protein, the detection rates were decreased with the new ELISA, although the ELISA detection rate and consistency rates with Western-blot analysis were increased. On the other hand, in the case of a protein content below 5 µg/g, it was impossible to determine ovomucoid and casein by Western-blot analysis.

DNA detection and single nucleotide mutation identification using SERS for molecular diagnostics and global health

NASA Astrophysics Data System (ADS)

Ngo, Hoan T.; Gandra, Naveen; Fales, Andrew M.; Taylor, Steve M.; Vo-Dinh, Tuan

2017-02-01

Nucleic acid-based molecular diagnostics at the point-of-care (POC) and in resource-limited settings is still a challenge. We present a sensitive yet simple DNA detection method with single nucleotide polymorphism (SNP) identification capability. The detection scheme involves sandwich hybridization of magnetic beads conjugated with capture probes, target sequences, and ultrabright surface-enhanced Raman Scattering (SERS) nanorattles conjugated with reporter probes. Upon hybridization, the sandwich probes are concentrated at the detection focus controlled by a magnetic system for SERS measurements. The ultrabright SERS nanorattles, consisting 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 ultrasensitive signal detection. Specific DNA sequences of the malaria parasite Plasmodium falciparum and dengue virus 1 (DENV1) were used as the model marker system. Detection limit of approximately 100 attomoles was achieved. Single nucleotide polymorphism (SNP) discrimination of wild type malaria DNA and mutant malaria DNA, which confers resistance to artemisinin drugs, was also demonstrated. The results demonstrate the molecular diagnostic potential of the nanorattle-based method to both detect and genotype infectious pathogens. The method's simplicity makes it a suitable candidate for molecular diagnosis at the POC and in resource-limited settings.

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

ENHANCED DAPI STAINING FOR CRYPTOSPORIDIUM IN WATER SAMPLES

EPA Science Inventory

The U.S. Environmental Protection Agency's Method 1623 is used to detect and quantify the presence of {ital Cryptosporidium} spp. oocysts in water. The protocol consists of concentrating a sample, staining this concentrate with a fluorescent antibody, and examining the sample mi...

Workshop targets development of geodetic transient detection methods: 2009 SCEC Annual Meeting: Workshop on transient anomalous strain detection; Palm Springs, California, 12-13 September 2009

USGS Publications Warehouse

Murray-Moraleda, Jessica R.; Lohman, Rowena

2010-01-01

The Southern California Earthquake Center (SCEC) is a community of researchers at institutions worldwide working to improve understanding of earthquakes and mitigate earthquake risk. One of SCEC's priority objectives is to “develop a geodetic network processing system that will detect anomalous strain transients.” Given the growing number of continuously recording geodetic networks consisting of hundreds of stations, an automated means for systematically searching data for transient signals, especially in near real time, is critical for network operations, hazard monitoring, and event response. The SCEC Transient Detection Test Exercise began in 2008 to foster an active community of researchers working on this problem, explore promising methods, and combine effective approaches in novel ways. A workshop was held in California to assess what has been learned thus far and discuss areas of focus as the project moves forward.

Polyhydroquinone-graphene composite as new redox species for sensitive electrochemical detection of cytokeratins antigen 21-1

NASA Astrophysics Data System (ADS)

Wang, Huiqiang; Rong, Qinfeng; Ma, Zhanfang

2016-07-01

Polyhydroquinone-graphene composite as a new redox species was synthesized simply by a microwave-assisted one-pot method through oxidative polymerization of hydroquinone by graphene oxide, which exhibited excellent electrochemical redox activity at 0.124 V and can remarkably promote electron transfer. The as-prepared composite was used as immunosensing substrate in a label-free electrochemical immunosensor for the detection of cytokeratins antigen 21-1, a kind of biomarker of lung cancer. The proposed immunosensor showed wide liner range from 10 pg mL-1 to 200 ng mL-1 with a detection limit 2.3 pg mL-1, and displayed a good stability and selectivity. In addition, this method has been used for the analysis of human serum sample, and the detection results showed good consistence with those of ELISA. The present substrate can be easily extended to other polymer-based nanocomposites.

Gold Nanorods as Plasmonic Sensors for Particle Diffusion.

PubMed

Wulf, Verena; Knoch, Fabian; Speck, Thomas; Sönnichsen, Carsten

2016-12-01

Plasmonic gold nanoparticles are normally used as sensor to detect analytes permanently bound to their surface. If the interaction between the analyte and the nanosensor surface is negligible, it only diffuses through the sensor's sensing volume, causing a small temporal shift of the plasmon resonance position. By using a very sensitive and fast detection scheme, we are able to detect these small fluctuations in the plasmon resonance. With the help of a theoretical model consistent with our detection geometry, we determine the analyte's diffusion coefficient. The method is verified by observing the trends upon changing diffusor size and medium viscosity, and the diffusion coefficients obtained were found to reflect reduced diffusion close to a solid interface. Our method, which we refer to as NanoPCS (for nanoscale plasmon correlation spectroscopy), is of practical importance for any application involving the diffusion of analytes close to nanoparticles.

Method for outlier detection: a tool to assess the consistency between laboratory data and ultraviolet-visible absorbance spectra in wastewater samples.

PubMed

Zamora, D; Torres, A

2014-01-01

Reliable estimations of the evolution of water quality parameters by using in situ technologies make it possible to follow the operation of a wastewater treatment plant (WWTP), as well as improving the understanding and control of the operation, especially in the detection of disturbances. However, ultraviolet (UV)-Vis sensors have to be calibrated by means of a local fingerprint laboratory reference concentration-value data-set. The detection of outliers in these data-sets is therefore important. This paper presents a method for detecting outliers in UV-Vis absorbances coupled to water quality reference laboratory concentrations for samples used for calibration purposes. Application to samples from the influent of the San Fernando WWTP (Medellín, Colombia) is shown. After the removal of outliers, improvements in the predictability of the influent concentrations using absorbance spectra were found.

Three-phase general border detection method for dermoscopy images using non-uniform illumination correction.

PubMed

Norton, Kerri-Ann; Iyatomi, Hitoshi; Celebi, M Emre; Ishizaki, Sumiko; Sawada, Mizuki; Suzaki, Reiko; Kobayashi, Ken; Tanaka, Masaru; Ogawa, Koichi

2012-08-01

Computer-aided diagnosis of dermoscopy images has shown great promise in developing a quantitative, objective way of classifying skin lesions. An important step in the classification process is lesion segmentation. Many studies have been successful in segmenting melanocytic skin lesions (MSLs), but few have focused on non-melanocytic skin lesions (NoMSLs), as the wide variety of lesions makes accurate segmentation difficult. We developed an automatic segmentation program for detecting borders of skin lesions in dermoscopy images. The method consists of a pre-processing phase, general lesion segmentation phase, including illumination correction, and bright region segmentation phase. We tested our method on a set of 107 NoMSLs and a set of 319 MSLs. Our method achieved precision/recall scores of 84.5% and 88.5% for NoMSLs, and 93.9% and 93.8% for MSLs, in comparison with manual extractions from four or five dermatologists. The accuracy of our method was competitive or better than five recently published methods. Our new method is the first method for detecting borders of both non-melanocytic and melanocytic skin lesions. © 2011 John Wiley & Sons A/S.

Single-pixel imaging by Hadamard transform and its application for hyperspectral imaging

NASA Astrophysics Data System (ADS)

Mizutani, Yasuhiro; Shibuya, Kyuki; Taguchi, Hiroki; Iwata, Tetsuo; Takaya, Yasuhiro; Yasui, Takeshi

2016-10-01

In this paper, we report on comparisons of single-pixel imagings using Hadamard Transform (HT) and the ghost imaging (GI) in the view point of the visibility under weak light conditions. For comparing the two methods, we have discussed about qualities of images based on experimental results and numerical analysis. To detect images by the TH method, we have illuminated the Hadamard-pattern mask and calculated by orthogonal transform. On the other hand, the GH method can detect images by illuminating random patterns and a correlation measurement. For comparing two methods under weak light intensity, we have controlled illuminated intensities of a DMD projector about 0.1 in signal-to-noise ratio. Though a process speed of the HT image was faster then an image via the GI, the GI method has an advantage of detection under weak light condition. An essential difference between the HT and the GI method is discussed about reconstruction process. Finally, we also show a typical application of the single-pixel imaging such as hyperspectral images by using dual-optical frequency combs. An optical setup consists of two fiber lasers, spatial light modulated for generating patten illumination, and a single pixel detector. We are successful to detect hyperspectrul images in a range from 1545 to 1555 nm at 0.01nm resolution.

Multinomial N-mixture models improve the applicability of electrofishing for developing population estimates of stream-dwelling Smallmouth Bass

USGS Publications Warehouse

Mollenhauer, Robert; Brewer, Shannon K.

2017-01-01

Failure to account for variable detection across survey conditions constrains progressive stream ecology and can lead to erroneous stream fish management and conservation decisions. In addition to variable detection’s confounding long-term stream fish population trends, reliable abundance estimates across a wide range of survey conditions are fundamental to establishing species–environment relationships. Despite major advancements in accounting for variable detection when surveying animal populations, these approaches remain largely ignored by stream fish scientists, and CPUE remains the most common metric used by researchers and managers. One notable advancement for addressing the challenges of variable detection is the multinomial N-mixture model. Multinomial N-mixture models use a flexible hierarchical framework to model the detection process across sites as a function of covariates; they also accommodate common fisheries survey methods, such as removal and capture–recapture. Effective monitoring of stream-dwelling Smallmouth Bass Micropterus dolomieu populations has long been challenging; therefore, our objective was to examine the use of multinomial N-mixture models to improve the applicability of electrofishing for estimating absolute abundance. We sampled Smallmouth Bass populations by using tow-barge electrofishing across a range of environmental conditions in streams of the Ozark Highlands ecoregion. Using an information-theoretic approach, we identified effort, water clarity, wetted channel width, and water depth as covariates that were related to variable Smallmouth Bass electrofishing detection. Smallmouth Bass abundance estimates derived from our top model consistently agreed with baseline estimates obtained via snorkel surveys. Additionally, confidence intervals from the multinomial N-mixture models were consistently more precise than those of unbiased Petersen capture–recapture estimates due to the dependency among data sets in the hierarchical framework. We demonstrate the application of this contemporary population estimation method to address a longstanding stream fish management issue. We also detail the advantages and trade-offs of hierarchical population estimation methods relative to CPUE and estimation methods that model each site separately.

Sequential structural damage diagnosis algorithm using a change point detection method

NASA Astrophysics Data System (ADS)

Noh, H.; Rajagopal, R.; Kiremidjian, A. S.

2013-11-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method. The general change point detection 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, unless we are looking for a known specific type of damage. Therefore, we introduce an additional algorithm that 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 a set of experimental data collected from a four-story steel special moment-resisting frame and multiple sets of simulated data. Various features of different dimensions have been explored, and the algorithm was able to identify damage, particularly when it uses multidimensional damage sensitive features and lower false alarm rates, with a known post-damage feature distribution. For unknown feature distribution cases, the post-damage distribution was consistently estimated and the detection delays were only a few time steps longer than the delays from the general 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.

Detection of Cu2+ in Water Based on Histidine-Gold Labeled Multiwalled Carbon Nanotube Electrochemical Sensor

PubMed Central

Zhu, Rilong; Zhou, Gangqiang; Tang, Fengxia; Wang, Yeyao

2017-01-01

Based on the strong interaction between histidine and copper ions and the signal enhancement effect of gold-labeling carbon nanotubes, an electrochemical sensor is established and used to measure copper ions in river water. In this study the results show that the concentrations of copper ion have well linear relationship with the peak current in the range of 10−11–10−7 mol/L, and the limit of detection is 10−12 mol/L. When using this method to detect copper ions in the Xiangjiang River, the test results are consistent with the atomic absorption method. This study shows that the sensor is convenient to be used in daily monitoring of copper ions in river water. PMID:28408929

Parallel image-acquisition in continuous-wave electron paramagnetic resonance imaging with a surface coil array: Proof-of-concept experiments

NASA Astrophysics Data System (ADS)

Enomoto, Ayano; Hirata, Hiroshi

2014-02-01

This article describes a feasibility study of parallel image-acquisition using a two-channel surface coil array in continuous-wave electron paramagnetic resonance (CW-EPR) imaging. Parallel EPR imaging was performed by multiplexing of EPR detection in the frequency domain. The parallel acquisition system consists of two surface coil resonators and radiofrequency (RF) bridges for EPR detection. To demonstrate the feasibility of this method of parallel image-acquisition with a surface coil array, three-dimensional EPR imaging was carried out using a tube phantom. Technical issues in the multiplexing method of EPR detection were also clarified. We found that degradation in the signal-to-noise ratio due to the interference of RF carriers is a key problem to be solved.

Fetal head detection and measurement in ultrasound images by an iterative randomized Hough transform

NASA Astrophysics Data System (ADS)

Lu, Wei; Tan, Jinglu; Floyd, Randall C.

2004-05-01

This paper describes an automatic method for measuring the biparietal diameter (BPD) and head circumference (HC) in ultrasound fetal images. A total of 217 ultrasound images were segmented by using a K-Mean classifier, and the head skull was detected in 214 of the 217 cases by an iterative randomized Hough transform developed for detection of incomplete curves in images with strong noise without user intervention. The automatic measurements were compared with conventional manual measurements by sonographers and a trained panel. The inter-run variations and differences between the automatic and conventional measurements were small compared with published inter-observer variations. The results showed that the automated measurements were as reliable as the expert measurements and more consistent. This method has great potential in clinical applications.

Determination of limonin in grapefruit juice and other citrus juices by high-performance liquid chromatography.

PubMed

Van Beek, T A; Blaakmeer, A

1989-03-03

A method has been developed for the quantitation of the bitter component limonin in grapefruit juice and other citrus juices. The sample clean-up consisted of centrifugation, filtration and a selective, rapid and reproducible purification with a C2 solid-phase extraction column. The limonin concentration was determined by high-performance liquid chromatography on a C18 column with UV detection at 210 nm. A linear response was obtained from 0.0 to 45 ppm limonin. The minimum detectable amount was 2 ng. The minimum concentration which was detected without concentration with good precision was 0.1 ppm. The method was also used for the determination of limonin in different types of oranges, including navel oranges, mandarins, lemons, limes, pomelos and uglis.

A new method for text detection and recognition in indoor scene for assisting blind people

NASA Astrophysics Data System (ADS)

Jabnoun, Hanen; Benzarti, Faouzi; Amiri, Hamid

2017-03-01

Developing assisting system of handicapped persons become a challenging ask in research projects. Recently, a variety of tools are designed to help visually impaired or blind people object as a visual substitution system. The majority of these tools are based on the conversion of input information into auditory or tactile sensory information. Furthermore, object recognition and text retrieval are exploited in the visual substitution systems. Text detection and recognition provides the description of the surrounding environments, so that the blind person can readily recognize the scene. In this work, we aim to introduce a method for detecting and recognizing text in indoor scene. The process consists on the detection of the regions of interest that should contain the text using the connected component. Then, the text detection is provided by employing the images correlation. This component of an assistive blind person should be simple, so that the users are able to obtain the most informative feedback within the shortest time.

Failure Detecting Method of Fault Current Limiter System with Rectifier

NASA Astrophysics Data System (ADS)

Tokuda, Noriaki; Matsubara, Yoshio; Asano, Masakuni; Ohkuma, Takeshi; Sato, Yoshibumi; Takahashi, Yoshihisa

A fault current limiter (FCL) is extensively needed to suppress fault current, particularly required for trunk power systems connecting high-voltage transmission lines, such as 500kV class power system which constitutes the nucleus of the electric power system. We proposed a new type FCL system (rectifier type FCL), consisting of solid-state diodes, DC reactor and bypass AC reactor, and demonstrated the excellent performances of this FCL by developing the small 6.6kV and 66kV model. It is important to detect the failure of power devices used in the rectifier under the normal operating condition, for keeping the excellent reliability of the power system. In this paper, we have proposed a new failure detecting method of power devices most suitable for the rectifier type FCL. This failure detecting system is simple and compact. We have adapted the proposed system to the 66kV prototype single-phase model and successfully demonstrated to detect the failure of power devices.

Reverse phase protein microarrays: fluorometric and colorimetric detection.

PubMed

Gallagher, Rosa I; Silvestri, Alessandra; Petricoin, Emanuel F; Liotta, Lance A; Espina, Virginia

2011-01-01

The Reverse Phase Protein Microarray (RPMA) is an array platform used to quantitate proteins and their posttranslationally modified forms. RPMAs are applicable for profiling key cellular signaling pathways and protein networks, allowing direct comparison of the activation state of proteins from multiple samples within the same array. The RPMA format consists of proteins immobilized directly on a nitrocellulose substratum. The analyte is subsequently probed with a primary antibody and a series of reagents for signal amplification and detection. Due to the diversity, low concentration, and large dynamic range of protein analytes, RPMAs require stringent signal amplification methods, high quality image acquisition, and software capable of precisely analyzing spot intensities on an array. Microarray detection strategies can be either fluorescent or colorimetric. The choice of a detection system depends on (a) the expected analyte concentration, (b) type of microarray imaging system, and (c) type of sample. The focus of this chapter is to describe RPMA detection and imaging using fluorescent and colorimetric (diaminobenzidine (DAB)) methods.

[High resolution melting analysis for detecting of JAK2V617F mutation in patients with myeloproliferative neoplasms].

PubMed

Chen, Hai-Hua; Yang, Ji-Long; Lu, Hui-Fang; Zhou, Wei-Jun; Yao, Fei; Deng, Lan

2014-02-01

This study was purposed to investigate the feasibility of high resolution melting (HRM) in the detection of JAK2V617F mutation in patients with myeloproliferative neoplasm (MPN). The 29 marrow samples randomly selected from patients with clinically diagnosed MPN from January 2008 to January 2011 were detected by HRM method. The results of HRM analysis were compared with that detected by allele specific polymerase chain reaction (AS-PCR) and DNA direct sequencing. The results showed that the JAK2V617F mutations were detected in 11 (37.9%, 11/29) cases by HRM, and its comparability with the direct sequencing result was 100%. While the consistency of AS-PCR with the direct sequencing was moderate (Kappa = 0.179, P = 0.316). It is concluded that the HRM analysis may be an optimal method for clinical screening of JAK2V617F mutation due to its simplicity and promptness with a high specificity.

Real-time fluorescence loop mediated isothermal amplification for the diagnosis of malaria.

PubMed

Lucchi, Naomi W; Demas, Allison; Narayanan, Jothikumar; Sumari, Deborah; Kabanywanyi, Abdunoor; Kachur, S Patrick; Barnwell, John W; Udhayakumar, Venkatachalam

2010-10-29

Molecular diagnostic methods can complement existing tools to improve the diagnosis of malaria. However, they require good laboratory infrastructure thereby restricting their use to reference laboratories and research studies. Therefore, adopting molecular tools for routine use in malaria endemic countries will require simpler molecular platforms. The recently developed loop-mediated isothermal amplification (LAMP) method is relatively simple and can be improved for better use in endemic countries. In this study, we attempted to improve this method for malaria diagnosis by using a simple and portable device capable of performing both the amplification and detection (by fluorescence) of LAMP in one platform. We refer to this as the RealAmp method. Published genus-specific primers were used to test the utility of this method. DNA derived from different species of malaria parasites was used for the initial characterization. Clinical samples of P. falciparum were used to determine the sensitivity and specificity of this system compared to microscopy and a nested PCR method. Additionally, directly boiled parasite preparations were compared with a conventional DNA isolation method. The RealAmp method was found to be simple and allowed real-time detection of DNA amplification. The time to amplification varied but was generally less than 60 minutes. All human-infecting Plasmodium species were detected. The sensitivity and specificity of RealAmp in detecting P. falciparum was 96.7% and 91.7% respectively, compared to microscopy and 98.9% and 100% respectively, compared to a standard nested PCR method. In addition, this method consistently detected P. falciparum from directly boiled blood samples. This RealAmp method has great potential as a field usable molecular tool for diagnosis of malaria. This tool can provide an alternative to conventional PCR based diagnostic methods for field use in clinical and operational programs.

A thesis on the Development of an Automated SWIFT Edge Detection Algorithm

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

Trujillo, Christopher J.

Throughout the world, scientists and engineers such as those at Los Alamos National Laboratory, perform research and testing unique only to applications aimed towards advancing technology, and understanding the nature of materials. With this testing, comes a need for advanced methods of data acquisition and most importantly, a means of analyzing and extracting the necessary information from such acquired data. In this thesis, I aim to produce an automated method implementing advanced image processing techniques and tools to analyze SWIFT image datasets for Detonator Technology at Los Alamos National Laboratory. Such an effective method for edge detection and point extractionmore » can prove to be advantageous in analyzing such unique datasets and provide for consistency in producing results.« less

Development of a rapid optic bacteria detecting system based on ATP bioluminescence

NASA Astrophysics Data System (ADS)

Liu, Jun Tao; Luo, JinPing; Liu, XiaoHong; Cai, XinXia

2014-12-01

A rapid optic bacteria detecting system based on the principle of Adenosine triphosphate(ATP) bioluminescence was presented in this paper. This system consisted of bioluminescence-based biosensor and the high-sensitivity optic meter. A photon counting photomultiplier tube (PMT) module was used to improve the detection sensitivity, and a NIOS II/f processor based on a Field Programmable Gate Array(FPGA) was used to control the system. In this work, Micrococcus luteus were chosen as the test sample. Several Micrococcus luteus suspension with different concentration was tested by both T2011 and plate counting method. By comparing the two group results, an calibration curve was obtained from the bioluminescence intensity for Micrococcus luteus in the range of 2.3×102 ~ 2.3×106 CFU/mL with a good correlation coefficient of 0.960. An impacting Air microorganism sampler was used to capture Airborne Bacteria, and 8 samples were collected in different place. The TBC results of 8 samples by T2011 were between 10 ~ 2×103 cfu/mL, consistent with that of plate counting method, which indicated that 8 samples were between 10 ~ 3×103 cfu/mL. For total airborne bacteria count was small, correlation coefficient was poor. Also no significant difference was found between T2011 and plate counting method by statistical analyses.

Rapid Isolation of Phenol Degrading Bacteria by Fourier Transform Infrared (FTIR) Spectroscopy.

PubMed

Li, Fei; Song, Wen-jun; Wei, Ji-ping; Wang, Su-ying; Liu, Chong-ji

2015-05-01

Phenol is an important chemical engineering material and ubiquitous in industry wastewater, its existence has become a thorny issue in many developed and developing country. More and more stringent standards for effluent all over the world with human realizing the toxicity of phenol have been announced. Many advanced biological methods are applied to industrial wastewater treatment with low cost, high efficiency and no secondary pollution, but the screening of function microorganisms is certain cumbersome process. In our study a rapid procedure devised for screening bacteria on solid medium can degrade phenol coupled with attenuated total reflection fourier transform infrared (ATR-FTIR) which is a detection method has the characteristics of efficient, fast, high fingerprint were used. Principal component analysis (PCA) is a method in common use to extract fingerprint peaks effectively, it couples with partial least squares (PLS) statistical method could establish a credible model. The model we created using PCA-PLS can reach 99. 5% of coefficient determination and validation data get 99. 4%, which shows the promising fitness and forecasting of the model. The high fitting model is used for predicting the concentration of phenol at solid medium where the bacteria were grown. The highly consistent result of two screening methods, solid cultural with ATR-FTIR detected and traditional liquid cultural detected by GC methods, suggests the former can rapid isolate the bacteria which can degrade substrates as well as traditional cumbersome liquid cultural method. Many hazardous substrates widely existed in industry wastewater, most of them has specialize fingerprint peaks detected by ATR-FTIR, thereby this detected method could be used as a rapid detection for isolation of functional microorganisms those can degrade many other toxic substrates.

Combined electrophoresis-electrospray interface and method

DOEpatents

Smith, R.D.; Udseth, H.R.; Barinaga, C.J.

1995-06-13

An improvement to the system and method is disclosed for analyzing molecular constituents of a composition sample that comprises improvements to an electrospray ionization source for interfacing to mass spectrometers and other detection devices. The improvement consists of establishing a unique electrical circuit pattern and nozzle configuration, a metallic coated and conical shaped capillary outlet, coupled with sizing of the capillary to obtain maximum sensitivity. 10 figs.

Comparative analysis of methods for detecting interacting loci

PubMed Central

2011-01-01

Background Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. Results We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. Conclusion This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list. PMID:21729295

Comparative analysis of methods for detecting interacting loci.

PubMed

Chen, Li; Yu, Guoqiang; Langefeld, Carl D; Miller, David J; Guy, Richard T; Raghuram, Jayaram; Yuan, Xiguo; Herrington, David M; Wang, Yue

2011-07-05

Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list.

Quantification of astaxanthin in shrimp waste hydrolysate by HPLC.

PubMed

López-Cervantes, J; Sánchez-Machado, D I; Gutiérrez-Coronado, M A; Ríos-Vázquez, N J

2006-10-01

In the present study, a simple and rapid reversed-phase HPLC method for the determination of astaxanthin in shrimp waste hydrolysate has been developed and validated. The analytical procedure involves the direct extraction of astaxanthin from the lipid fraction with methanol. The analytical column, SS Exil ODS, was operated at 25C. The mobile phase consisted of a mixture of water:methanol:dichloromethane:acetonitrile (4.5:28:22:45.5 v/v/v/v) at a flow rate of 1.0 mL/min. Detection and identification were performed using a photodiode array detector (lambda(detection) = 476 nm). The proposed HPLC method showed adequate linearity, repeatability and accuracy.

[Development of a Computer-aided Diagnosis System to Distinguish between Benign and Malignant Mammary Tumors in Dynamic Magnetic Resonance Images: Automatic Detection of the Position with the Strongest Washout Effect in the Tumor].

PubMed

Miyazaki, Yoshiaki; Tabata, Nobuyuki; Taroura, Tomomi; Shinozaki, Kenji; Kubo, Yuichiro; Tokunaga, Eriko; Taguchi, Kenichi

We propose a computer-aided diagnostic (CAD) system that uses time-intensity curves to distinguish between benign and malignant mammary tumors. Many malignant tumors show a washout pattern in time-intensity curves. Therefore, we designed a program that automatically detects the position with the strongest washout effect using the technique, such as the subtraction technique, which extracts only the washout area in the tumor, and by scanning data in 2×2 pixel region of interest (ROI). Operation of this independently developed program was verified using a phantom system that simulated tumors. In three cases of malignant tumors, the washout pattern detection rate in images with manually set ROI was ≤6%, whereas the detection rate with our novel method was 100%. In one case of a benign tumor, when the same method was used, we checked that there was no washout effect and detected the persistent pattern. Thus, the distinction between benign and malignant tumors using our method was completely consistent with the pathological diagnoses made. Our novel method is therefore effective for differentiating between benign and malignant mammary tumors in dynamic magnetic resonance images.

Unsupervised, low latency anomaly detection of algorithmically generated domain names by generative probabilistic modeling.

PubMed

Raghuram, Jayaram; Miller, David J; Kesidis, George

2014-07-01

We propose a method for detecting anomalous domain names, with focus on algorithmically generated domain names which are frequently associated with malicious activities such as fast flux service networks, particularly for bot networks (or botnets), malware, and phishing. Our method is based on learning a (null hypothesis) probability model based on a large set of domain names that have been white listed by some reliable authority. Since these names are mostly assigned by humans, they are pronounceable, and tend to have a distribution of characters, words, word lengths, and number of words that are typical of some language (mostly English), and often consist of words drawn from a known lexicon. On the other hand, in the present day scenario, algorithmically generated domain names typically have distributions that are quite different from that of human-created domain names. We propose a fully generative model for the probability distribution of benign (white listed) domain names which can be used in an anomaly detection setting for identifying putative algorithmically generated domain names. Unlike other methods, our approach can make detections without considering any additional (latency producing) information sources, often used to detect fast flux activity. Experiments on a publicly available, large data set of domain names associated with fast flux service networks show encouraging results, relative to several baseline methods, with higher detection rates and low false positive rates.

Unsupervised, low latency anomaly detection of algorithmically generated domain names by generative probabilistic modeling

PubMed Central

Raghuram, Jayaram; Miller, David J.; Kesidis, George

2014-01-01

We propose a method for detecting anomalous domain names, with focus on algorithmically generated domain names which are frequently associated with malicious activities such as fast flux service networks, particularly for bot networks (or botnets), malware, and phishing. Our method is based on learning a (null hypothesis) probability model based on a large set of domain names that have been white listed by some reliable authority. Since these names are mostly assigned by humans, they are pronounceable, and tend to have a distribution of characters, words, word lengths, and number of words that are typical of some language (mostly English), and often consist of words drawn from a known lexicon. On the other hand, in the present day scenario, algorithmically generated domain names typically have distributions that are quite different from that of human-created domain names. We propose a fully generative model for the probability distribution of benign (white listed) domain names which can be used in an anomaly detection setting for identifying putative algorithmically generated domain names. Unlike other methods, our approach can make detections without considering any additional (latency producing) information sources, often used to detect fast flux activity. Experiments on a publicly available, large data set of domain names associated with fast flux service networks show encouraging results, relative to several baseline methods, with higher detection rates and low false positive rates. PMID:25685511

Detection of Drug-Resistant Mycobacterium tuberculosis.

PubMed

Engström, Anna; Juréen, Pontus

2015-01-01

Tuberculosis (TB) remains a global health problem. The increasing prevalence of drug-resistant Mycobacterium tuberculosis, the causative agent of TB, demands new measures to combat the situation. Rapid and accurate diagnosis of the pathogen and its drug susceptibility pattern is essential for timely initiation of optimal treatment, and, ultimately, control of the disease. We have developed a molecular method for detection of first- and second-line drug resistance in M. tuberculosis by Pyrosequencing(®). The method consists of seven Pyrosequencing assays for the detection of mutations in the genes or promoter regions, which are most commonly responsible for resistance to the drugs rifampicin, isoniazid, ethambutol, amikacin, kanamycin, capreomycin, and fluoroquinolones. The method was validated on clinical isolates and it was shown that the sensitivity and specificity of the method were comparable to those of Sanger sequencing. In the protocol in this chapter we describe the steps necessary for setting up and performing Pyrosequencing for M. tuberculosis. The first part of the protocol describes the assay development and the second part of the protocol describes utilization of the method.

Gross beta determination in drinking water using scintillating fiber array detector.

PubMed

Lv, Wen-Hui; Yi, Hong-Chang; Liu, Tong-Qing; Zeng, Zhi; Li, Jun-Li; Zhang, Hui; Ma, Hao

2018-04-04

A scintillating fiber array detector for measuring gross beta counting is developed to monitor the real-time radioactivity in drinking water. The detector, placed in a stainless-steel tank, consists of 1096 scintillating fibers, both sides of which are connected to a photomultiplier tube. The detector parameters, including working voltage, background counting rate and stability, are tested, and the detection efficiency is calibrated using standard potassium chloride solution. Water samples are measured with the detector and the results are compared with those by evaporation method. The results show consistency with those by evaporation method. The background counting rate of the detector is 38.131 ± 0.005 cps, and the detection efficiency for β particles is 0.37 ± 0.01 cps/(Bq/l). The MDAC of this system can be less than 1.0 Bq/l for β particles in 120 min without pre-concentration. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development and validation of chemometrics-assisted spectrophotometric and liquid chromatographic methods for the simultaneous determination of two multicomponent mixtures containing bronchodilator drugs.

PubMed

El-Gindy, Alaa; Emara, Samy; Shaaban, Heba

2007-02-19

Three methods are developed for the determination of two multicomponent mixtures containing guaiphenesine (GU) with salbutamol sulfate (SL), methylparaben (MP) and propylparaben (PP) [mixture 1]; and acephylline piperazine (AC) with bromhexine hydrochloride (BX), methylparaben (MP) and propylparaben (PP) [mixture 2]. The resolution of the two multicomponent mixtures has been accomplished by using numerical spectrophotometric methods such as partial least squares (PLS-1) and principal component regression (PCR) applied to UV absorption spectra of the two mixtures. In addition HPLC method was developed using a RP 18 column at ambient temperature with mobile phase consisting of acetonitrile-0.05 M potassium dihydrogen phosphate, pH 4.3 (60:40, v/v), with UV detection at 243 nm for mixture 1, and mobile phase consisting of acetonitrile-0.05 M potassium dihydrogen phosphate, pH 3 (50:50, v/v), with UV detection at 245 nm for mixture 2. The methods were validated in terms of accuracy, specificity, precision and linearity in the range of 20-60 microg ml(-1) for GU, 1-3 microg ml(-1) for SL, 20-80 microg ml(-1) for AC, 0.2-1.8 microgml(-1) for PP and 1-5 microg ml(-1) for BX and MP. The proposed methods were successfully applied for the determination of the two multicomponent combinations in laboratory prepared mixtures and commercial syrups.

Text String Detection from Natural Scenes by Structure-based Partition and Grouping

PubMed Central

Yi, Chucai; Tian, YingLi

2012-01-01

Text information in natural scene images serves as important clues for many image-based applications such as scene understanding, content-based image retrieval, assistive navigation, and automatic geocoding. However, locating text from complex background with multiple colors is a challenging task. In this paper, we explore a new framework to detect text strings with arbitrary orientations in complex natural scene images. Our proposed framework of text string detection consists of two steps: 1) Image partition to find text character candidates based on local gradient features and color uniformity of character components. 2) Character candidate grouping to detect text strings based on joint structural features of text characters in each text string such as character size differences, distances between neighboring characters, and character alignment. By assuming that a text string has at least three characters, we propose two algorithms of text string detection: 1) adjacent character grouping method, and 2) text line grouping method. The adjacent character grouping method calculates the sibling groups of each character candidate as string segments and then merges the intersecting sibling groups into text string. The text line grouping method performs Hough transform to fit text line among the centroids of text candidates. Each fitted text line describes the orientation of a potential text string. The detected text string is presented by a rectangle region covering all characters whose centroids are cascaded in its text line. To improve efficiency and accuracy, our algorithms are carried out in multi-scales. The proposed methods outperform the state-of-the-art results on the public Robust Reading Dataset which contains text only in horizontal orientation. Furthermore, the effectiveness of our methods to detect text strings with arbitrary orientations is evaluated on the Oriented Scene Text Dataset collected by ourselves containing text strings in non-horizontal orientations. PMID:21411405

Text string detection from natural scenes by structure-based partition and grouping.

PubMed

Yi, Chucai; Tian, YingLi

2011-09-01

Text information in natural scene images serves as important clues for many image-based applications such as scene understanding, content-based image retrieval, assistive navigation, and automatic geocoding. However, locating text from a complex background with multiple colors is a challenging task. In this paper, we explore a new framework to detect text strings with arbitrary orientations in complex natural scene images. Our proposed framework of text string detection consists of two steps: 1) image partition to find text character candidates based on local gradient features and color uniformity of character components and 2) character candidate grouping to detect text strings based on joint structural features of text characters in each text string such as character size differences, distances between neighboring characters, and character alignment. By assuming that a text string has at least three characters, we propose two algorithms of text string detection: 1) adjacent character grouping method and 2) text line grouping method. The adjacent character grouping method calculates the sibling groups of each character candidate as string segments and then merges the intersecting sibling groups into text string. The text line grouping method performs Hough transform to fit text line among the centroids of text candidates. Each fitted text line describes the orientation of a potential text string. The detected text string is presented by a rectangle region covering all characters whose centroids are cascaded in its text line. To improve efficiency and accuracy, our algorithms are carried out in multi-scales. The proposed methods outperform the state-of-the-art results on the public Robust Reading Dataset, which contains text only in horizontal orientation. Furthermore, the effectiveness of our methods to detect text strings with arbitrary orientations is evaluated on the Oriented Scene Text Dataset collected by ourselves containing text strings in nonhorizontal orientations.

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

PubMed

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

2015-02-01

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

lidar change detection using building models

NASA Astrophysics Data System (ADS)

Kim, Angela M.; Runyon, Scott C.; Jalobeanu, Andre; Esterline, Chelsea H.; Kruse, Fred A.

2014-06-01

Terrestrial LiDAR scans of building models collected with a FARO Focus3D and a RIEGL VZ-400 were used to investigate point-to-point and model-to-model LiDAR change detection. LiDAR data were scaled, decimated, and georegistered to mimic real world airborne collects. Two physical building models were used to explore various aspects of the change detection process. The first model was a 1:250-scale representation of the Naval Postgraduate School campus in Monterey, CA, constructed from Lego blocks and scanned in a laboratory setting using both the FARO and RIEGL. The second model at 1:8-scale consisted of large cardboard boxes placed outdoors and scanned from rooftops of adjacent buildings using the RIEGL. A point-to-point change detection scheme was applied directly to the point-cloud datasets. In the model-to-model change detection scheme, changes were detected by comparing Digital Surface Models (DSMs). The use of physical models allowed analysis of effects of changes in scanner and scanning geometry, and performance of the change detection methods on different types of changes, including building collapse or subsistence, construction, and shifts in location. Results indicate that at low false-alarm rates, the point-to-point method slightly outperforms the model-to-model method. The point-to-point method is less sensitive to misregistration errors in the data. Best results are obtained when the baseline and change datasets are collected using the same LiDAR system and collection geometry.

Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.

PubMed

Kim, Jihun; Kim, Jonghong; Jang, Gil-Jin; Lee, Minho

2017-03-01

Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection. A CNN can be used to enhance the input images before lane detection by excluding noise and obstacles that are irrelevant to the edge detection result. However, training conventional CNNs requires considerable computation and a big dataset. Therefore, we suggest a new learning algorithm for CNNs using an extreme learning machine (ELM). The ELM is a fast learning method used to calculate network weights between output and hidden layers in a single iteration and thus, can dramatically reduce learning time while producing accurate results with minimal training data. A conventional ELM can be applied to networks with a single hidden layer; as such, we propose a stacked ELM architecture in the CNN framework. Further, we modify the backpropagation algorithm to find the targets of hidden layers and effectively learn network weights while maintaining performance. Experimental results confirm that the proposed method is effective in reducing learning time and improving performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Rapid detection of Shigella and enteroinvasive Escherichia coli in produce enrichments by a conventional multiplex PCR assay.

PubMed

Binet, Rachel; Deer, Deanne M; Uhlfelder, Samantha J

2014-06-01

Faster detection of contaminated foods can prevent adulterated foods from being consumed and minimize the risk of an outbreak of foodborne illness. A sensitive molecular detection method is especially important for Shigella because ingestion of as few as 10 of these bacterial pathogens can cause disease. The objectives of this study were to compare the ability of four DNA extraction methods to detect Shigella in six types of produce, post-enrichment, and to evaluate a new and rapid conventional multiplex assay that targets the Shigella ipaH, virB and mxiC virulence genes. This assay can detect less than two Shigella cells in pure culture, even when the pathogen is mixed with background microflora, and it can also differentiate natural Shigella strains from a control strain and eliminate false positive results due to accidental laboratory contamination. The four DNA extraction methods (boiling, PrepMan Ultra [Applied Biosystems], InstaGene Matrix [Bio-Rad], DNeasy Tissue kit [Qiagen]) detected 1.6 × 10(3)Shigella CFU/ml post-enrichment, requiring ∼18 doublings to one cell in 25 g of produce pre-enrichment. Lower sensitivity was obtained, depending on produce type and extraction method. The InstaGene Matrix was the most consistent and sensitive and the multiplex assay accurately detected Shigella in less than 90 min, outperforming, to the best of our knowledge, molecular assays currently in place for this pathogen. Published by Elsevier Ltd.

Contactless Inductive Bubble Detection in a Liquid Metal Flow

PubMed Central

Gundrum, Thomas; Büttner, Philipp; Dekdouk, Bachir; Peyton, Anthony; Wondrak, Thomas; Galindo, Vladimir; Eckert, Sven

2016-01-01

The detection of bubbles in liquid metals is important for many technical applications. The opaqueness and the high temperature of liquid metals set high demands on the measurement system. The high electrical conductivity of the liquid metal can be exploited for contactless methods based on electromagnetic induction. We will present a measurement system which consists of one excitation coil and a pickup coil system on the opposite sides of the pipe. With this sensor we were able to detect bubbles in a sodium flow inside a stainless steel pipe and bubbles in a column filled with a liquid Gallium alloy. PMID:26751444

Ammonium detection by formation of colored zebra-bands in a detecting tube.

PubMed

Hori, Tatsuaki; Niki, Keizou; Kiso, Yoshiaki; Oguchi, Tatsuo; Kamimoto, Yuki; Yamada, Toshiro; Nagai, Masahiro

2010-06-15

Ammonium ion was colorized by means of a diazo coupling reaction with 2-phenylphenol, where the color development reaction was conducted within 3min by using boric acid as a catalyst. The resulting colored solution (0.5ml) was supplied by suction to a detecting tube consisting of a nonwoven fabric test strip (2mm wide, 1mm thick, 150mm long) impregnated with benzylcetyldimethylammonium chloride in a stripe pattern and enclosed in a heat-shrinkable tube. When the colored solution was supplied to the detecting tube, blue zebra-bands formed, and the ammonium concentration was determined by counting the number of zebra-bands. The detection range was 1-20mg-Nl(-1). Ammonium ion in actual domestic wastewater samples was successfully detected by means of this method.

Development of a robust chromatographic method for the detection of chlorophenols in cork oak forest soils.

PubMed

McLellan, Iain; Hursthouse, Andrew; Morrison, Calum; Varela, Adélia; Pereira, Cristina Silva

2014-02-01

A major concern for the cork and wine industry is 'cork taint' which is associated with chloroanisoles, the microbial degradation metabolites of chlorophenols. The use of chlorophenolic compounds as pesticides within cork forests was prohibited in 1993 in the European Union (EU) following the introduction of industry guidance. However, cork produced outside the EU is still thought to be affected and simple, robust methods for chlorophenol analysis are required for wider environmental assessment by industry and local environmental regulators. Soil samples were collected from three common-use forests in Tunisia and from one privately owned forest in Sardinia, providing examples of varied management practice and degree of human intervention. These provided challenge samples for the optimisation of a HPLC-UV detection method. It produced recoveries consistently >75% against a soil CRM (ERM-CC008) for pentachlorophenol. The optimised method, with ultraviolet (diode array) detection is able to separate and quantify 16 different chlorophenols at field concentrations greater than the limits of detection ranging from 6.5 to 191.3 μg/kg (dry weight). Application to a range of field samples demonstrated the absence of widespread contamination in forest soils at sites sampled in Sardinia and Tunisia.

[A wavelet-transform-based method for the automatic detection of late-type stars].

PubMed

Liu, Zhong-tian; Zhao, Rrui-zhen; Zhao, Yong-heng; Wu, Fu-chao

2005-07-01

The LAMOST project, the world largest sky survey project, urgently needs an automatic late-type stars detection system. However, to our knowledge, no effective methods for automatic late-type stars detection have been reported in the literature up to now. The present study work is intended to explore possible ways to deal with this issue. Here, by "late-type stars" we mean those stars with strong molecule absorption bands, including oxygen-rich M, L and T type stars and carbon-rich C stars. Based on experimental results, the authors find that after a wavelet transform with 5 scales on the late-type stars spectra, their frequency spectrum of the transformed coefficient on the 5th scale consistently manifests a unimodal distribution, and the energy of frequency spectrum is largely concentrated on a small neighborhood centered around the unique peak. However, for the spectra of other celestial bodies, the corresponding frequency spectrum is of multimodal and the energy of frequency spectrum is dispersible. Based on such a finding, the authors presented a wavelet-transform-based automatic late-type stars detection method. The proposed method is shown by extensive experiments to be practical and of good robustness.

Multipath interference test method using synthesized chirped signal from directly modulated DFB-LD with digital-signal-processing technique.

PubMed

Aida, Kazuo; Sugie, Toshihiko

2011-12-12

We propose a method of testing transmission fiber lines and distributed amplifiers. Multipath interference (MPI) is detected as a beat spectrum between a multipath signal and a direct signal using a synthesized chirped test signal with lightwave frequencies of f(1) and f(2) periodically emitted from a distributed feedback laser diode (DFB-LD). This chirped test pulse is generated using a directly modulated DFB-LD with a drive signal calculated using a digital signal processing technique (DSP). A receiver consisting of a photodiode and an electrical spectrum analyzer (ESA) detects a baseband power spectrum peak appearing at the frequency of the test signal frequency deviation (f(1)-f(2)) as a beat spectrum of self-heterodyne detection. Multipath interference is converted from the spectrum peak power. This method improved the minimum detectable MPI to as low as -78 dB. We discuss the detailed design and performance of the proposed test method, including a DFB-LD drive signal calculation algorithm with DSP for synthesis of the chirped test signal and experiments on single-mode fibers with discrete reflections. © 2011 Optical Society of America

Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach.

PubMed

Abd El Aziz, Mohamed; Selim, I M; Xiong, Shengwu

2017-06-30

This paper presents a new approach for the automatic detection of galaxy morphology from datasets based on an image-retrieval approach. Currently, there are several classification methods proposed to detect galaxy types within an image. However, in some situations, the aim is not only to determine the type of galaxy within the queried image, but also to determine the most similar images for query image. Therefore, this paper proposes an image-retrieval method to detect the type of galaxies within an image and return with the most similar image. The proposed method consists of two stages, in the first stage, a set of features is extracted based on shape, color and texture descriptors, then a binary sine cosine algorithm selects the most relevant features. In the second stage, the similarity between the features of the queried galaxy image and the features of other galaxy images is computed. Our experiments were performed using the EFIGI catalogue, which contains about 5000 galaxies images with different types (edge-on spiral, spiral, elliptical and irregular). We demonstrate that our proposed approach has better performance compared with the particle swarm optimization (PSO) and genetic algorithm (GA) methods.

Automatic Microaneurysms Detection Based on Multifeature Fusion Dictionary Learning

PubMed Central

Wang, Zhenzhu; Du, Wenyou

2017-01-01

Recently, microaneurysm (MA) detection has attracted a lot of attention in the medical image processing community. Since MAs can be seen as the earliest lesions in diabetic retinopathy, their detection plays a critical role in diabetic retinopathy diagnosis. In this paper, we propose a novel MA detection approach named multifeature fusion dictionary learning (MFFDL). The proposed method consists of four steps: preprocessing, candidate extraction, multifeature dictionary learning, and classification. The novelty of our proposed approach lies in incorporating the semantic relationships among multifeatures and dictionary learning into a unified framework for automatic detection of MAs. We evaluate the proposed algorithm by comparing it with the state-of-the-art approaches and the experimental results validate the effectiveness of our algorithm. PMID:28421125

Automatic Microaneurysms Detection Based on Multifeature Fusion Dictionary Learning.

PubMed

Zhou, Wei; Wu, Chengdong; Chen, Dali; Wang, Zhenzhu; Yi, Yugen; Du, Wenyou

2017-01-01

Recently, microaneurysm (MA) detection has attracted a lot of attention in the medical image processing community. Since MAs can be seen as the earliest lesions in diabetic retinopathy, their detection plays a critical role in diabetic retinopathy diagnosis. In this paper, we propose a novel MA detection approach named multifeature fusion dictionary learning (MFFDL). The proposed method consists of four steps: preprocessing, candidate extraction, multifeature dictionary learning, and classification. The novelty of our proposed approach lies in incorporating the semantic relationships among multifeatures and dictionary learning into a unified framework for automatic detection of MAs. We evaluate the proposed algorithm by comparing it with the state-of-the-art approaches and the experimental results validate the effectiveness of our algorithm.

Wind turbine extraction from high spatial resolution remote sensing images based on saliency detection

NASA Astrophysics Data System (ADS)

Chen, Jingbo; Yue, Anzhi; Wang, Chengyi; Huang, Qingqing; Chen, Jiansheng; Meng, Yu; He, Dongxu

2018-01-01

The wind turbine is a device that converts the wind's kinetic energy into electrical power. Accurate and automatic extraction of wind turbine is instructive for government departments to plan wind power plant projects. A hybrid and practical framework based on saliency detection for wind turbine extraction, using Google Earth image at spatial resolution of 1 m, is proposed. It can be viewed as a two-phase procedure: coarsely detection and fine extraction. In the first stage, we introduced a frequency-tuned saliency detection approach for initially detecting the area of interest of the wind turbines. This method exploited features of color and luminance, was simple to implement, and was computationally efficient. Taking into account the complexity of remote sensing images, in the second stage, we proposed a fast method for fine-tuning results in frequency domain and then extracted wind turbines from these salient objects by removing the irrelevant salient areas according to the special properties of the wind turbines. Experiments demonstrated that our approach consistently obtains higher precision and better recall rates. Our method was also compared with other techniques from the literature and proves that it is more applicable and robust.

Searching for exoplanets using artificial intelligence

NASA Astrophysics Data System (ADS)

Pearson, Kyle A.; Palafox, Leon; Griffith, Caitlin A.

2018-02-01

In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labor intensive and subject to human error, the results of which are difficult to quantify. Here we present a new method of detecting exoplanet candidates in large planetary search projects which, unlike current methods uses a neural network. Neural networks, also called "deep learning" or "deep nets" are designed to give a computer perception into a specific problem by training it to recognize patterns. Unlike past transit detection algorithms deep nets learn to recognize planet features instead of relying on hand-coded metrics that humans perceive as the most representative. Our convolutional neural network is capable of detecting Earth-like exoplanets in noisy time-series data with a greater accuracy than a least-squares method. Deep nets are highly generalizable allowing data to be evaluated from different time series after interpolation without compromising performance. As validated by our deep net analysis of Kepler light curves, we detect periodic transits consistent with the true period without any model fitting. Our study indicates that machine learning will facilitate the characterization of exoplanets in future analysis of large astronomy data sets.

Near‐surface void detection using a seismic landstreamer and horizontal velocity and attenuation tomography

USGS Publications Warehouse

Buckley, Sean F.; Lane, John W.

2012-01-01

The detection and characterization of subsurface voids plays an important role in the study of karst formations and clandestine tunnels. Horizontal velocity and attenuation tomography (HVAT) using offset‐fan shooting and a towed seismic land streamer is a simple, rapid, minimally invasive method that shows promise for detecting near‐surface voids and providing information on the orientation of linear voids. HVAT surveys were conducted over a known subsurface steam tunnel on the University of Connecticut Depot Campus, Storrs, Connecticut. First‐arrival travel‐time and amplitude data were used to produce two‐dimensional (2D) horizontal (map view) velocity and attenuation tomograms. In addition, attenuation tomograms were produced based on normalized total trace energy (TTE). Both the velocity and TTE attenuation tomograms depict an anomaly consistent with the location and orientation of the known tunnel; the TTE method, however, requires significantly less processing time, and therefore may provide a path forward to semi‐automated, near real‐time detection of near‐surface voids. Further study is needed to assess the utility of the HVAT method to detect deeper voids and the effects of a more complex geology on HVAT results.

A compact imaging spectroscopic system for biomolecular detections on plasmonic chips.

PubMed

Lo, Shu-Cheng; Lin, En-Hung; Wei, Pei-Kuen; Tsai, Wan-Shao

2016-10-17

In this study, we demonstrate a compact imaging spectroscopic system for high-throughput detection of biomolecular interactions on plasmonic chips, based on a curved grating as the key element of light diffraction and light focusing. Both the curved grating and the plasmonic chips are fabricated on flexible plastic substrates using a gas-assisted thermal-embossing method. A fiber-coupled broadband light source and a camera are included in the system. Spectral resolution within 1 nm is achieved in sensing environmental index solutions and protein bindings. The detected sensitivities of the plasmonic chip are comparable with a commercial spectrometer. An extra one-dimensional scanning stage enables high-throughput detection of protein binding on a designed plasmonic chip consisting of several nanoslit arrays with different periods. The detected resonance wavelengths match well with the grating equation under an air environment. Wavelength shifts between 1 and 9 nm are detected for antigens of various concentrations binding with antibodies. A simple, mass-productive and cost-effective method has been demonstrated on the imaging spectroscopic system for real-time, label-free, highly sensitive and high-throughput screening of biomolecular interactions.

Improvement of antigen detection efficiency with the use of two-dimensional photonic crystal as a substrate

NASA Astrophysics Data System (ADS)

Dovzhenko, Dmitriy; Terekhin, Vladimir; Vokhmincev, Kirill; Sukhanova, Alyona; Nabiev, Igor

2017-01-01

Multiplex detection of different antigens in human serum in order to reveal diseases at the early stage is of interest nowadays. There are a lot of biosensors, which use the fluorescent labels for specific detection of analytes. For instance, common method for detection of antigens in human serum samples is enzyme-linked immunosorbent assay (ELISA). One of the most effective ways to improve the sensitivity of this detection method is the use of a substrate that could enhance the fluorescent signal and make it easier to collect. Two-dimensional (2D) photonic crystals are very suitable structures for these purposes because of the ability to enhance the luminescent signal, control the light propagation and perform the analysis directly on its surface. In our study we have calculated optimal parameters for 2D-dimensional photonic crystal consisting of the array of silicon nano-rods, fabricated such photonic crystal on a silicon substrate using reactive ion etching and showed the possibility of its efficient application as a substrate for ELISA detection of human cancer antigens.

SU-G-JeP4-03: Anomaly Detection of Respiratory Motion by Use of Singular Spectrum Analysis

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

Kotoku, J; Kumagai, S; Nakabayashi, S

Purpose: The implementation and realization of automatic anomaly detection of respiratory motion is a very important technique to prevent accidental damage during radiation therapy. Here, we propose an automatic anomaly detection method using singular value decomposition analysis. Methods: The anomaly detection procedure consists of four parts:1) measurement of normal respiratory motion data of a patient2) calculation of a trajectory matrix representing normal time-series feature3) real-time monitoring and calculation of a trajectory matrix of real-time data.4) calculation of an anomaly score from the similarity of the two feature matrices. Patient motion was observed by a marker-less tracking system using a depthmore » camera. Results: Two types of motion e.g. cough and sudden stop of breathing were successfully detected in our real-time application. Conclusion: Automatic anomaly detection of respiratory motion using singular spectrum analysis was successful in the cough and sudden stop of breathing. The clinical use of this algorithm will be very hopeful. This work was supported by JSPS KAKENHI Grant Number 15K08703.« less

Peroxyoxalate chemiluminescence detection of condensates of malondialdehyde with thiobarbituric acids using a flow system.

PubMed

Nakashima, K; Nagata, M; Takahashi, M; Akiyama, S

1992-01-01

The peroxyoxalate chemiluminescence(CL) detection method for the evaluation of the CL intensity of malondialdehyde(MDA) condensates with seven 2-thiobarbituric acid derivatives is described. The method consists of a flow injection technique together with a CL detection system using bis(2,4,6-trichlorophenyl) oxalate(TCPO) and hydrogen peroxide as chemiluminogenic reagents. Linear correlations between CL intensity and concentration are obtained for pmol levels of condensates. Among the condensates, 1,3-diethyl-2-thiobarbituric acid(DETBA)-MDA shows the largest CL intensity. High performance liquid chromatography (HPLC)/CL detection of DETBA-MDA and 1,3-diphenyl-2-thiobarbituric acid(DPTBA)-MDA using a mixture of TCPO and hydrogen peroxide in acetonitrile as a postcolumn reagent solution is also described. The detection limits for DETBA-MDA and DPTBA-MDA are 20 and 200 fmol, respectively, per 20 microL injection at a signal-to-noise ratio of 2. This HPLC/CL detection system was applied to the determination of MDA in rat brains by using DETBA as a fluorescent derivatizing reagent.

Fast detection of air contaminants using immunobiological methods

NASA Astrophysics Data System (ADS)

Schmitt, Katrin; Bolwien, Carsten; Sulz, Gerd; Koch, Wolfgang; Dunkhorst, Wilhelm; Lödding, Hubert; Schwarz, Katharina; Holländer, Andreas; Klockenbring, Torsten; Barth, Stefan; Seidel, Björn; Hofbauer, Wolfgang; Rennebarth, Torsten; Renzl, Anna

2009-05-01

The fast and direct identification of possibly pathogenic microorganisms in air is gaining increasing interest due to their threat for public health, e.g. in clinical environments or in clean rooms of food or pharmaceutical industries. We present a new detection method allowing the direct recognition of relevant germs or bacteria via fluorescence-labeled antibodies within less than one hour. In detail, an air-sampling unit passes particles in the relevant size range to a substrate which contains antibodies with fluorescence labels for the detection of a specific microorganism. After the removal of the excess antibodies the optical detection unit comprising reflected-light and epifluorescence microscopy can identify the microorganisms by fast image processing on a single-particle level. First measurements with the system to identify various test particles as well as interfering influences have been performed, in particular with respect to autofluorescence of dust particles. Specific antibodies for the detection of Aspergillus fumigatus spores have been established. The biological test system consists of protein A-coated polymer particles which are detected by a fluorescence-labeled IgG. Furthermore the influence of interfering particles such as dust or debris is discussed.

Retinopathy online challenge: automatic detection of microaneurysms in digital color fundus photographs.

PubMed

Niemeijer, Meindert; van Ginneken, Bram; Cree, Michael J; Mizutani, Atsushi; Quellec, Gwénolé; Sanchez, Clara I; Zhang, Bob; Hornero, Roberto; Lamard, Mathieu; Muramatsu, Chisako; Wu, Xiangqian; Cazuguel, Guy; You, Jane; Mayo, Agustín; Li, Qin; Hatanaka, Yuji; Cochener, Béatrice; Roux, Christian; Karray, Fakhri; Garcia, María; Fujita, Hiroshi; Abramoff, Michael D

2010-01-01

The detection of microaneurysms in digital color fundus photographs is a critical first step in automated screening for diabetic retinopathy (DR), a common complication of diabetes. To accomplish this detection numerous methods have been published in the past but none of these was compared with each other on the same data. In this work we present the results of the first international microaneurysm detection competition, organized in the context of the Retinopathy Online Challenge (ROC), a multiyear online competition for various aspects of DR detection. For this competition, we compare the results of five different methods, produced by five different teams of researchers on the same set of data. The evaluation was performed in a uniform manner using an algorithm presented in this work. The set of data used for the competition consisted of 50 training images with available reference standard and 50 test images where the reference standard was withheld by the organizers (M. Niemeijer, B. van Ginneken, and M. D. Abràmoff). The results obtained on the test data was submitted through a website after which standardized evaluation software was used to determine the performance of each of the methods. A human expert detected microaneurysms in the test set to allow comparison with the performance of the automatic methods. The overall results show that microaneurysm detection is a challenging task for both the automatic methods as well as the human expert. There is room for improvement as the best performing system does not reach the performance of the human expert. The data associated with the ROC microaneurysm detection competition will remain publicly available and the website will continue accepting submissions.

A self-adapting system for the automated detection of inter-ictal epileptiform discharges.

PubMed

Lodder, Shaun S; van Putten, Michel J A M

2014-01-01

Scalp EEG remains the standard clinical procedure for the diagnosis of epilepsy. Manual detection of inter-ictal epileptiform discharges (IEDs) is slow and cumbersome, and few automated methods are used to assist in practice. This is mostly due to low sensitivities, high false positive rates, or a lack of trust in the automated method. In this study we aim to find a solution that will make computer assisted detection more efficient than conventional methods, while preserving the detection certainty of a manual search. Our solution consists of two phases. First, a detection phase finds all events similar to epileptiform activity by using a large database of template waveforms. Individual template detections are combined to form "IED nominations", each with a corresponding certainty value based on the reliability of their contributing templates. The second phase uses the ten nominations with highest certainty and presents them to the reviewer one by one for confirmation. Confirmations are used to update certainty values of the remaining nominations, and another iteration is performed where ten nominations with the highest certainty are presented. This continues until the reviewer is satisfied with what has been seen. Reviewer feedback is also used to update template accuracies globally and improve future detections. Using the described method and fifteen evaluation EEGs (241 IEDs), one third of all inter-ictal events were shown after one iteration, half after two iterations, and 74%, 90%, and 95% after 5, 10 and 15 iterations respectively. Reviewing fifteen iterations for the 20-30 min recordings 1 took approximately 5 min. The proposed method shows a practical approach for combining automated detection with visual searching for inter-ictal epileptiform activity. Further evaluation is needed to verify its clinical feasibility and measure the added value it presents.

Quantitative analysis of concrete using portable x-ray fluorescence: Method development and validation

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

Washington, Aaron L.; Narrows, William; Christian, Jonathan H.

During Decommissioning and Demolition (D&D) activities at SRS, it is important that the building be screened for radionuclides and heavy metals to ensure that the proper safety and disposal metrics are in place. A major source of contamination at DOE facilities is the accumulation of mercury contamination, from nuclear material processing and Liquid Waste System (LWS). This buildup of mercury could possibly cause harm to any demolition crew or the environment should this material be released. The current standard method is to take core samples in various places in the facility and use X-ray fluorescence (XRF) to detect the contamination.more » This standard method comes with a high financial value due to the security levels of these sample facilities with unknown contamination levels. Here in we propose the use of portable XRF units to detect for this contamination on-site. To validate this method, the instrument has to be calibrated to detect the heavy metal contamination, be both precise with the known elemental concentrations and consistent with its actual results of a sample concrete and pristine contaminant, and be able to detect changes in the sample concrete’s composition. After receiving the various concrete samples with their compositions found by a XRF wave-dispersive method, the calibration factor’s linear regressions were adjusted to give the baseline concentration of the concrete with no contamination. Samples of both concrete and concrete/flyash were evaluated; their standard deviations revealed that the measurements were consistent with the known composition. Finally, the samples were contaminated with different concentrations of sodium tungsten dihydrate, allowed to air dry, and measured. When the contaminated samples were analyzed, the heavy metal contamination was seen within the spectrum of the instrument, but there was not a trend of quantification based on the concentration of the solution.« less

Rapid identification and quantification of tumor cells using an electrocatalytic method based on gold nanoparticles.

PubMed

de la Escosura-Muñiz, Alfredo; Sánchez-Espinel, Christian; Díaz-Freitas, Belén; González-Fernández, Africa; Maltez-da Costa, Marisa; Merkoçi, Arben

2009-12-15

There is a high demand for simple, rapid, efficient, and user-friendly alternative methods for the detection of cells in general and, in particular, for the detection of cancer cells. A biosensor able to detect cells would be an all-in-one dream device for such applications. The successful integration of nanoparticles into cell detection assays could allow for the development of this novel class of cell sensors. Indeed, their application could well have a great future in diagnostics, as well as other fields. As an example of a novel biosensor, we report here an electrocatalytic device for the specific identification of tumor cells that quantifies gold nanoparticles (AuNPs) coupled with an electrotransducing platform/sensor. Proliferation and adherence of tumor cells are achieved on the electrotransducer/detector, which consists of a mass-produced screen-printed carbon electrode (SPCE). In situ identification/quantification of tumor cells is achieved with a detection limit of 4000 cells per 700 microL of suspension. This novel and selective cell-sensing device is based on the reaction of cell surface proteins with specific antibodies conjugated with AuNPs. Final detection requires only a couple of minutes, taking advantage of the catalytic properties of AuNPs on hydrogen evolution. The proposed detection method does not require the chemical agents used in most existing assays for the detection of AuNPs. It allows for the miniaturization of the system and is much cheaper than other expensive and sophisticated methods used for tumor cell detection. We envisage that this device could operate in a simple way as an immunosensor or DNA sensor. Moreover, it could be used, even by inexperienced staff, for the detection of protein molecules or DNA strands.

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

Automated detection of geological landforms on Mars using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Palafox, Leon F.; Hamilton, Christopher W.; Scheidt, Stephen P.; Alvarez, Alexander M.

2017-04-01

The large volume of high-resolution images acquired by the Mars Reconnaissance Orbiter has opened a new frontier for developing automated approaches to detecting landforms on the surface of Mars. However, most landform classifiers focus on crater detection, which represents only one of many geological landforms of scientific interest. In this work, we use Convolutional Neural Networks (ConvNets) to detect both volcanic rootless cones and transverse aeolian ridges. Our system, named MarsNet, consists of five networks, each of which is trained to detect landforms of different sizes. We compare our detection algorithm with a widely used method for image recognition, Support Vector Machines (SVMs) using Histogram of Oriented Gradients (HOG) features. We show that ConvNets can detect a wide range of landforms and has better accuracy and recall in testing data than traditional classifiers based on SVMs.

Automated detection of geological landforms on Mars using Convolutional Neural Networks.

PubMed

Palafox, Leon F; Hamilton, Christopher W; Scheidt, Stephen P; Alvarez, Alexander M

2017-04-01

The large volume of high-resolution images acquired by the Mars Reconnaissance Orbiter has opened a new frontier for developing automated approaches to detecting landforms on the surface of Mars. However, most landform classifiers focus on crater detection, which represents only one of many geological landforms of scientific interest. In this work, we use Convolutional Neural Networks (ConvNets) to detect both volcanic rootless cones and transverse aeolian ridges. Our system, named MarsNet, consists of five networks, each of which is trained to detect landforms of different sizes. We compare our detection algorithm with a widely used method for image recognition, Support Vector Machines (SVMs) using Histogram of Oriented Gradients (HOG) features. We show that ConvNets can detect a wide range of landforms and has better accuracy and recall in testing data than traditional classifiers based on SVMs.

Evaluation of Beckman Coulter DxI 800 immunoassay system using clinically oriented performance goals.

PubMed

Akbas, Neval; Schryver, Patricia G; Algeciras-Schimnich, Alicia; Baumann, Nikola A; Block, Darci R; Budd, Jeffrey R; Gaston, S J Stephen; Klee, George G

2014-11-01

We evaluated the analytical performance of 24 immunoassays using the Beckman Coulter DxI 800 immunoassay systems at Mayo Clinic, Rochester, MN for trueness, precision, detection limits, linearity, and consistency (across instruments and reagent lots). Clinically oriented performance goals were defined using the following methods: trueness-published desirable accuracy limits, precision-published desirable biologic variation; detection limits - 0.1 percentile of patient test values, linearity - 50% of total error, and consistency-percentage test values crossing key decision points. Local data were collected for precision, linearity, and consistency. Data were provided by Beckman Coulter, Inc. for trueness and detection limits. All evaluated assays except total thyroxine were within the proposed goals for trueness. Most of the assays met the proposed goals for precision (86% of intra-assay results and 75% of inter-assay results). Five assays had more than 15% of the test results below the minimum detection limits. Carcinoembryonic antigen, total thyroxine and free triiodothyronine exceeded the proposed goals of ±6.3%, ±5% and ±5.7% for dilution linearity. All evaluated assays were within the proposed goals for instrument consistency. Lot-to-lot consistency results for cortisol, ferritin and total thyroxine exceeded the proposed goals of 3.3%, 11.4% and 7% at one medical decision level, while vitamin B12 exceeded the proposed goals of 5.2% and 3.8% at two decision levels. The Beckman Coulter DxI 800 immunoassay system meets most of these proposed goals, even though these clinically focused performance goals represent relatively stringent limits. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Development of a fast screening and confirmatory method by liquid chromatography-quadrupole-time-of-flight mass spectrometry for glucuronide-conjugated methyltestosterone metabolite in tilapia.

PubMed

Amarasinghe, Kande; Chu, Pak-Sin; Evans, Eric; Reimschuessel, Renate; Hasbrouck, Nicholas; Jayasuriya, Hiranthi

2012-05-23

This paper describes the development of a fast method to screen and confirm methyltestosterone 17-O-glucuronide (MT-glu) in tilapia bile. The method consists of solid-phase extraction (SPE) followed by high-performance liquid chromatography-mass spectrometry. The system used was an Agilent 6530 Q-TOF with an Agilent Jet stream electrospray ionization interface. The glucuronide detected in the bile was characterized as MT-glu by comparison with a chemically synthesized standard. MT-glu was detected in bile for up to 7 days after dosing. Semiquantification was done with matrix-matched calibration curves, because MT-glu showed signal suppression due to matrix effects. This method provides a suitable tool to monitor the illegal use of methyltestosterone in tilapia culture.

To See or Not to See: Investigating Detectability of Ganges River Dolphins Using a Combined Visual-Acoustic Survey

PubMed Central

Richman, Nadia I.; Gibbons, James M.; Turvey, Samuel T.; Akamatsu, Tomonari; Ahmed, Benazir; Mahabub, Emile; Smith, Brian D.; Jones, Julia P. G.

2014-01-01

Detection of animals during visual surveys is rarely perfect or constant, and failure to account for imperfect detectability affects the accuracy of abundance estimates. Freshwater cetaceans are among the most threatened group of mammals, and visual surveys are a commonly employed method for estimating population size despite concerns over imperfect and unquantified detectability. We used a combined visual-acoustic survey to estimate detectability of Ganges River dolphins (Platanista gangetica gangetica) in four waterways of southern Bangladesh. The combined visual-acoustic survey resulted in consistently higher detectability than a single observer-team visual survey, thereby improving power to detect trends. Visual detectability was particularly low for dolphins close to meanders where these habitat features temporarily block the view of the preceding river surface. This systematic bias in detectability during visual-only surveys may lead researchers to underestimate the importance of heavily meandering river reaches. Although the benefits of acoustic surveys are increasingly recognised for marine cetaceans, they have not been widely used for monitoring abundance of freshwater cetaceans due to perceived costs and technical skill requirements. We show that acoustic surveys are in fact a relatively cost-effective approach for surveying freshwater cetaceans, once it is acknowledged that methods that do not account for imperfect detectability are of limited value for monitoring. PMID:24805782

To see or not to see: investigating detectability of Ganges River dolphins using a combined visual-acoustic survey.

PubMed

Richman, Nadia I; Gibbons, James M; Turvey, Samuel T; Akamatsu, Tomonari; Ahmed, Benazir; Mahabub, Emile; Smith, Brian D; Jones, Julia P G

2014-01-01

Detection of animals during visual surveys is rarely perfect or constant, and failure to account for imperfect detectability affects the accuracy of abundance estimates. Freshwater cetaceans are among the most threatened group of mammals, and visual surveys are a commonly employed method for estimating population size despite concerns over imperfect and unquantified detectability. We used a combined visual-acoustic survey to estimate detectability of Ganges River dolphins (Platanista gangetica gangetica) in four waterways of southern Bangladesh. The combined visual-acoustic survey resulted in consistently higher detectability than a single observer-team visual survey, thereby improving power to detect trends. Visual detectability was particularly low for dolphins close to meanders where these habitat features temporarily block the view of the preceding river surface. This systematic bias in detectability during visual-only surveys may lead researchers to underestimate the importance of heavily meandering river reaches. Although the benefits of acoustic surveys are increasingly recognised for marine cetaceans, they have not been widely used for monitoring abundance of freshwater cetaceans due to perceived costs and technical skill requirements. We show that acoustic surveys are in fact a relatively cost-effective approach for surveying freshwater cetaceans, once it is acknowledged that methods that do not account for imperfect detectability are of limited value for monitoring.

Detection of lobular structures in normal breast tissue.

PubMed

Apou, Grégory; Schaadt, Nadine S; Naegel, Benoît; Forestier, Germain; Schönmeyer, Ralf; Feuerhake, Friedrich; Wemmert, Cédric; Grote, Anne

2016-07-01

Ongoing research into inflammatory conditions raises an increasing need to evaluate immune cells in histological sections in biologically relevant regions of interest (ROIs). Herein, we compare different approaches to automatically detect lobular structures in human normal breast tissue in digitized whole slide images (WSIs). This automation is required to perform objective and consistent quantitative studies on large data sets. In normal breast tissue from nine healthy patients immunohistochemically stained for different markers, we evaluated and compared three different image analysis methods to automatically detect lobular structures in WSIs: (1) a bottom-up approach using the cell-based data for subsequent tissue level classification, (2) a top-down method starting with texture classification at tissue level analysis of cell densities in specific ROIs, and (3) a direct texture classification using deep learning technology. All three methods result in comparable overall quality allowing automated detection of lobular structures with minor advantage in sensitivity (approach 3), specificity (approach 2), or processing time (approach 1). Combining the outputs of the approaches further improved the precision. Different approaches of automated ROI detection are feasible and should be selected according to the individual needs of biomarker research. Additionally, detected ROIs could be used as a basis for quantification of immune infiltration in lobular structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

Robust Curb Detection with Fusion of 3D-Lidar and Camera Data

PubMed Central

Tan, Jun; Li, Jian; An, Xiangjing; He, Hangen

2014-01-01

Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes. PMID:24854364

Rapid and label-free bioanalytical method of alpha fetoprotein detection using LSPR chip

NASA Astrophysics Data System (ADS)

Kim, Dongjoo; Kim, Jinwoon; Kwak, Cheol Hwan; Heo, Nam Su; Oh, Seo Yeong; Lee, Hoomin; Lee, Go-Woon; Vilian, A. T. Ezhil; Han, Young-Kyu; Kim, Woo-Sik; Kim, Gi-bum; Kwon, Soonjo; Huh, Yun Suk

2017-07-01

Alpha fetoprotein (AFP) is a cancer marker, particularly for hepatocellular carcinoma. Normal levels of AFP are less than 20 ng/mL; however, its levels can reach more than 400 ng/mL in patients with HCC. Enzyme linked immunosorbent assay (ELISA) and radioimmunoassay (RIA) have been employed for clinical diagnosis of AFP; however, these methods are time consuming and labor intensive. In this study, we developed a localized surface plasmon resonance (LSPR) based biosensor for simple and rapid detection of AFP. This biosensor consists of a UV-Vis spectrometer, a cuvette cell, and a biosensor chip nanopatterned with gold nanoparticles (AuNPs). In our LSPR biosensor, binding of AFP to the surface of the sensor chip led to an increasing magnitude of the LSPR signals, which was measured by an ultraviolet-visible (UV-Vis) spectrometer. Our LSPR biosensor showed sufficient detectability of AFP at concentrations of 1 ng/mL to 1 μg/mL. Moreover, the overall procedure for detection of AFP was completed within 20 min. This biosensor could also be utilized for a point of care test (POCT) by employing a portable UV-Vis spectrometer. Owing to the simplicity and rapidity of the detection process, our LSPR biosensor is expected to replace traditional diagnostic methods for the early detection of diseases.

Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases

PubMed Central

2014-01-01

Background Adverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays. Methods We used a set of complex detection rules to take account of the patient’s clinical and biological context and the chronological relationship between the causes and the expected outcome. The dataset consisted of 3,444 inpatient stays in a French general hospital. An automated review was performed for all data and the results were compared with those of an expert chart review. The complex detection rules’ analytical quality was evaluated for ADEs. Results In terms of recall, 89.5% of ADEs with hyperkalaemia “with or without an abnormal symptom” were automatically identified (including all three serious ADEs). In terms of precision, 63.7% of the automatically identified ADEs with hyperkalaemia were true ADEs. Conclusions The use of context-sensitive rules appears to improve the automated detection of ADEs with hyperkalaemia. This type of tool may have an important role in pharmacoepidemiology via the routine analysis of large inter-hospital databases. PMID:25212108

Gap Detection and Temporal Modulation Transfer Function as Behavioral Estimates of Auditory Temporal Acuity Using Band-Limited Stimuli in Young and Older Adults

PubMed Central

Shen, Yi

2015-01-01

Purpose Gap detection and the temporal modulation transfer function (TMTF) are 2 common methods to obtain behavioral estimates of auditory temporal acuity. However, the agreement between the 2 measures is not clear. This study compares results from these 2 methods and their dependencies on listener age and hearing status. Method Gap detection thresholds and the parameters that describe the TMTF (sensitivity and cutoff frequency) were estimated for young and older listeners who were naive to the experimental tasks. Stimuli were 800-Hz-wide noises with upper frequency limits of 2400 Hz, presented at 85 dB SPL. A 2-track procedure (Shen & Richards, 2013) was used for the efficient estimation of the TMTF. Results No significant correlation was found between gap detection threshold and the sensitivity or the cutoff frequency of the TMTF. No significant effect of age and hearing loss on either the gap detection threshold or the TMTF cutoff frequency was found, while the TMTF sensitivity improved with increasing hearing threshold and worsened with increasing age. Conclusion Estimates of temporal acuity using gap detection and TMTF paradigms do not seem to provide a consistent description of the effects of listener age and hearing status on temporal envelope processing. PMID:25087722

CONFOCAL LASER SCANNING MICROSCOPY OF WHOLE MOUSE OVARIES: EXCELLENT MORPHOLOGY, APOPTOSIS DETECTION, AND SPECTROSCOPY

EPA Science Inventory

Background: Ovaries consist of numerous follicles, oocytes, and granulosa cells in different stages of development. Many of these follicles will undergo an apoptotic process during the lifetime of the animal. By using proper tissue preparation methods, the events within the whole...

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

PubMed Central

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

2016-01-01

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

On-line/on-site analysis of heavy metals in water and soils by laser induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Meng, Deshuo; Zhao, Nanjing; Wang, Yuanyuan; Ma, Mingjun; Fang, Li; Gu, Yanhong; Jia, Yao; Liu, Jianguo

2017-11-01

The enrichment method of heavy metal in water with graphite and aluminum electrode was studied, and combined with plasma restraint device for improving the sensitivity of detection and reducing the limit of detection (LOD) of elements. For aluminum electrode enrichment, the LODs of Cd, Pb and Ni can be as low as several ppb. For graphite enrichment, the measurement time can be less than 3 min. The results showed that the graphite enrichment and aluminum electrode enrichment method can effectively improve the LIBS detection ability. The graphite enrichment method combined with plasma spatial confinement is more suitable for on-line monitoring of industrial waste water, the aluminum electrode enrichment method can be used for trace heavy metal detection in water. A LIBS method and device for soil heavy metals analysis was also developed, and a mobile LIBS system was tested in outfield. The measurement results deduced from LIBS and ICP-MS had a good consistency. The results provided an important application support for rapid and on-site monitoring of heavy metals in soil. (Left: the mobile LIBS system for analysis of heavy metals in soils. Top right: the spatial confinement device. Bottom right: automatic graphite enrichment device for on0line analysis of heavy metals in water).

Accurate Detection of Methicillin-Resistant Staphylococcus aureus in Mixtures by Use of Single-Bacterium Duplex Droplet Digital PCR.

PubMed

Luo, Jun; Li, Junhua; Yang, Hang; Yu, Junping; Wei, Hongping

2017-10-01

Accurate and rapid identification of methicillin-resistant Staphylococcus aureus (MRSA) is needed to screen MRSA carriers and improve treatment. The current widely used duplex PCR methods are not able to differentiate MRSA from coexisting methicillin-susceptible S. aureus (MSSA) or other methicillin-resistant staphylococci. In this study, we aimed to develop a direct method for accurate and rapid detection of MRSA in clinical samples from open environments, such as nasal swabs. The new molecular assay is based on detecting the cooccurrence of nuc and mecA markers in a single bacterial cell by utilizing droplet digital PCR (ddPCR) with the chimeric lysin ClyH for cell lysis. The method consists of (i) dispersion of an intact single bacterium into nanoliter droplets, (ii) temperature-controlled release of genomic DNA (gDNA) by ClyH at 37°C, and (iii) amplification and detection of the markers ( nuc and mecA ) using standard TaqMan chemistries with ddPCR. Results were analyzed based on MRSA index ratios used for indicating the presence of the duplex-positive markers in droplets. The method was able to achieve an absolute limit of detection (LOD) of 2,900 CFU/ml for MRSA in nasal swabs spiked with excess amounts of Escherichia coli , MSSA, and other mecA -positive bacteria within 4 h. Initial testing of 104 nasal swabs showed that the method had 100% agreement with the standard culture method, while the normal duplex qPCR method had only about 87.5% agreement. The single-bacterium duplex ddPCR assay is rapid and powerful for more accurate detection of MRSA directly from clinical specimens. Copyright © 2017 American Society for Microbiology.

Accurate Detection of Methicillin-Resistant Staphylococcus aureus in Mixtures by Use of Single-Bacterium Duplex Droplet Digital PCR

PubMed Central

Luo, Jun; Li, Junhua; Yang, Hang; Yu, Junping

2017-01-01

ABSTRACT Accurate and rapid identification of methicillin-resistant Staphylococcus aureus (MRSA) is needed to screen MRSA carriers and improve treatment. The current widely used duplex PCR methods are not able to differentiate MRSA from coexisting methicillin-susceptible S. aureus (MSSA) or other methicillin-resistant staphylococci. In this study, we aimed to develop a direct method for accurate and rapid detection of MRSA in clinical samples from open environments, such as nasal swabs. The new molecular assay is based on detecting the cooccurrence of nuc and mecA markers in a single bacterial cell by utilizing droplet digital PCR (ddPCR) with the chimeric lysin ClyH for cell lysis. The method consists of (i) dispersion of an intact single bacterium into nanoliter droplets, (ii) temperature-controlled release of genomic DNA (gDNA) by ClyH at 37°C, and (iii) amplification and detection of the markers (nuc and mecA) using standard TaqMan chemistries with ddPCR. Results were analyzed based on MRSA index ratios used for indicating the presence of the duplex-positive markers in droplets. The method was able to achieve an absolute limit of detection (LOD) of 2,900 CFU/ml for MRSA in nasal swabs spiked with excess amounts of Escherichia coli, MSSA, and other mecA-positive bacteria within 4 h. Initial testing of 104 nasal swabs showed that the method had 100% agreement with the standard culture method, while the normal duplex qPCR method had only about 87.5% agreement. The single-bacterium duplex ddPCR assay is rapid and powerful for more accurate detection of MRSA directly from clinical specimens. PMID:28724560

Automated detection scheme of architectural distortion in mammograms using adaptive Gabor filter

NASA Astrophysics Data System (ADS)

Yoshikawa, Ruriha; Teramoto, Atsushi; Matsubara, Tomoko; Fujita, Hiroshi

2013-03-01

Breast cancer is a serious health concern for all women. Computer-aided detection for mammography has been used for detecting mass and micro-calcification. However, there are challenges regarding the automated detection of the architectural distortion about the sensitivity. In this study, we propose a novel automated method for detecting architectural distortion. Our method consists of the analysis of the mammary gland structure, detection of the distorted region, and reduction of false positive results. We developed the adaptive Gabor filter for analyzing the mammary gland structure that decides filter parameters depending on the thickness of the gland structure. As for post-processing, healthy mammary glands that run from the nipple to the chest wall are eliminated by angle analysis. Moreover, background mammary glands are removed based on the intensity output image obtained from adaptive Gabor filter. The distorted region of the mammary gland is then detected as an initial candidate using a concentration index followed by binarization and labeling. False positives in the initial candidate are eliminated using 23 types of characteristic features and a support vector machine. In the experiments, we compared the automated detection results with interpretations by a radiologist using 50 cases (200 images) from the Digital Database of Screening Mammography (DDSM). As a result, true positive rate was 82.72%, and the number of false positive per image was 1.39. There results indicate that the proposed method may be useful for detecting architectural distortion in mammograms.

Application of COLD-PCR for improved detection of KRAS mutations in clinical samples.

PubMed

Zuo, Zhuang; Chen, Su S; Chandra, Pranil K; Galbincea, John M; Soape, Matthew; Doan, Steven; Barkoh, Bedia A; Koeppen, Hartmut; Medeiros, L Jeffrey; Luthra, Rajyalakshmi

2009-08-01

KRAS mutations have been detected in approximately 30% of all human tumors, and have been shown to predict response to some targeted therapies. The most common KRAS mutation-detection strategy consists of conventional PCR and direct sequencing. This approach has a 10-20% detection sensitivity depending on whether pyrosequencing or Sanger sequencing is used. To improve detection sensitivity, we compared our conventional method with the recently described co-amplification-at-lower denaturation-temperature PCR (COLD-PCR) method, which selectively amplifies minority alleles. In COLD-PCR, the critical denaturation temperature is lowered to 80 degrees C (vs 94 degrees C in conventional PCR). The sensitivity of COLD-PCR was determined by assessing serial dilutions. Fifty clinical samples were used, including 20 fresh bone-marrow aspirate specimens and the formalin-fixed paraffin-embedded (FFPE) tissue of 30 solid tumors. Implementation of COLD-PCR was straightforward and required no additional cost for reagents or instruments. The method was specific and reproducible. COLD-PCR successfully detected mutations in all samples that were positive by conventional PCR, and enhanced the mutant-to-wild-type ratio by >4.74-fold, increasing the mutation detection sensitivity to 1.5%. The enhancement of mutation detection by COLD-PCR inversely correlated with the tumor-cell percentage in a sample. In conclusion, we validated the utility and superior sensitivity of COLD-PCR for detecting KRAS mutations in a variety of hematopoietic and solid tumors using either fresh or fixed, paraffin-embedded tissue.

TERMA Framework for Biomedical Signal Analysis: An Economic-Inspired Approach

PubMed Central

Elgendi, Mohamed

2016-01-01

Biomedical signals contain features that represent physiological events, and each of these events has peaks. The analysis of biomedical signals for monitoring or diagnosing diseases requires the detection of these peaks, making event detection a crucial step in biomedical signal processing. Many researchers have difficulty detecting these peaks to investigate, interpret and analyze their corresponding events. To date, there is no generic framework that captures these events in a robust, efficient and consistent manner. A new method referred to for the first time as two event-related moving averages (“TERMA”) involves event-related moving averages and detects events in biomedical signals. The TERMA framework is flexible and universal and consists of six independent LEGO building bricks to achieve high accuracy detection of biomedical events. Results recommend that the window sizes for the two moving averages (W1 and W2) have to follow the inequality (8×W1)≥W2≥(2×W1). Moreover, TERMA is a simple yet efficient event detector that is suitable for wearable devices, point-of-care devices, fitness trackers and smart watches, compared to more complex machine learning solutions. PMID:27827852

Maximal Neighbor Similarity Reveals Real Communities in Networks

PubMed Central

Žalik, Krista Rizman

2015-01-01

An important problem in the analysis of network data is the detection of groups of densely interconnected nodes also called modules or communities. Community structure reveals functions and organizations of networks. Currently used algorithms for community detection in large-scale real-world networks are computationally expensive or require a priori information such as the number or sizes of communities or are not able to give the same resulting partition in multiple runs. In this paper we investigate a simple and fast algorithm that uses the network structure alone and requires neither optimization of pre-defined objective function nor information about number of communities. We propose a bottom up community detection algorithm in which starting from communities consisting of adjacent pairs of nodes and their maximal similar neighbors we find real communities. We show that the overall advantage of the proposed algorithm compared to the other community detection algorithms is its simple nature, low computational cost and its very high accuracy in detection communities of different sizes also in networks with blurred modularity structure consisting of poorly separated communities. All communities identified by the proposed method for facebook network and E-Coli transcriptional regulatory network have strong structural and functional coherence. PMID:26680448

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

Behroozi, Peter S.; Wechsler, Risa H.; Wu, Hao-Yi

We present a new algorithm for generating merger trees and halo catalogs which explicitly ensures consistency of halo properties (mass, position, and velocity) across time steps. Our algorithm has demonstrated the ability to improve both the completeness (through detecting and inserting otherwise missing halos) and purity (through detecting and removing spurious objects) of both merger trees and halo catalogs. In addition, our method is able to robustly measure the self-consistency of halo finders; it is the first to directly measure the uncertainties in halo positions, halo velocities, and the halo mass function for a given halo finder based on consistencymore » between snapshots in cosmological simulations. We use this algorithm to generate merger trees for two large simulations (Bolshoi and Consuelo) and evaluate two halo finders (ROCKSTAR and BDM). We find that both the ROCKSTAR and BDM halo finders track halos extremely well; in both, the number of halos which do not have physically consistent progenitors is at the 1%-2% level across all halo masses. Our code is publicly available at http://code.google.com/p/consistent-trees. Our trees and catalogs are publicly available at http://hipacc.ucsc.edu/Bolshoi/.« less

An investigation of gear mesh failure prediction techniques. M.S. Thesis - Cleveland State Univ.

NASA Technical Reports Server (NTRS)

Zakrajsek, James J.

1989-01-01

A study was performed in which several gear failure prediction methods were investigated and applied to experimental data from a gear fatigue test apparatus. The primary objective was to provide a baseline understanding of the prediction methods and to evaluate their diagnostic capabilities. The methods investigated use the signal average in both the time and frequency domain to detect gear failure. Data from eleven gear fatigue tests were recorded at periodic time intervals as the gears were run from initiation to failure. Four major failure modes, consisting of heavy wear, tooth breakage, single pits, and distributed pitting were observed among the failed gears. Results show that the prediction methods were able to detect only those gear failures which involved heavy wear or distributed pitting. None of the methods could predict fatigue cracks, which resulted in tooth breakage, or single pits. It is suspected that the fatigue cracks were not detected because of limitations in data acquisition rather than in methodology. Additionally, the frequency response between the gear shaft and the transducer was found to significantly affect the vibration signal. The specific frequencies affected were filtered out of the signal average prior to application of the methods.

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Container Surface Evaluation by Function Estimation

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

Wendelberger, James G.

Container images are analyzed for specific surface features, such as, pits, cracks, and corrosion. The detection of these features is confounded with complicating features. These complication features include: shape/curvature, welds, edges, scratches, foreign objects among others. A method is provided to discriminate between the various features. The method consists of estimating the image background, determining a residual image and post processing to determine the features present. The methodology is not finalized but demonstrates the feasibility of a method to determine the kind and size of the features present.

Safe and private pedestrian detection by a low-cost fiber optic specklegram

NASA Astrophysics Data System (ADS)

Rodriguez-Cuevas, A.; Rodriguez-Cobo, L.; Lomer, M.; Lopez-Higuera, J. M.

2017-04-01

Surveillance is becoming more and more important in the recent years. In many cities, cameras have been set to look after parks, streets, roads, facilities and so on, however this fact is rising concerns about privacy. In this work, an alternative surveillance method which gather at once security and privacy has been propose and tested. Based on fiber optic specklegram technology; a system consisting of a fiber optic, a coherent light source and a photodetector has been placed under a carpet for detecting people walking over it and its accuracy, regarding measuring the steps, have been measured. Results suggest that using low exposed geometries along the carpet and basic processing methods, it is possible to detect with more than 95% of accuracy the number of steps done by the person walking over the carpet.

Ring trial among National Reference Laboratories for parasites to detect Trichinella spiralis larvae in pork samples according to the EU directive 2075/2005.

PubMed

Marucci, Gianluca; Pezzotti, Patrizio; Pozio, Edoardo

2009-02-23

To control Trichinella spp. infection in the European Union, all slaughtered pigs should be tested by one of the approved digestion methods described in EU directive 2075/2005. The aim of the present work was to evaluate, by a ring trial, the sensitivity of the digestion method used at the National Reference Laboratories for Parasites (NRLP). These Laboratories are responsible for the quality of the detection method in their own country. Of the 27 EU countries, only three (Hungary, Luxembourg and Malta) did not participate in the ring trial. Each participating laboratory received 10 samples of 100g of minced pork containing 3-5 larvae (3 samples), 10-20 larvae (3 samples), 30-50 larvae (3 samples), and one negative control. In each positive sample, there were living Trichinella spiralis larvae without the collagen capsule, obtained by partial artificial digestion of muscle tissue from infected mice. No false positive sample was found in any laboratories, whereas nine laboratories (37.5%) failed to detect some positive samples with the percentage of false negatives ranging from 11 to 100%. The variation between expected and reported larval counts observed among the participating laboratories was statistically significant. There was a direct correlation between the consistency of the results and the use of a validated/accredited digestion method. Conversely, there was no correlation between the consistency of the results and the number of digestions performed yearly by the NRLP. These results support the importance of validating the test.

Quantitative Thin-Layer Chromatography/Mass Spectrometry Analysis of Caffeine Using a Surface Sampling Probe Electrospray Ionization Tandem Mass Spectrometry System

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

Ford, Michael J; Deibel, Michael A.; Tomkins, Bruce A

Quantitative determination of caffeine on reversed-phase C8 thin-layer chromatography plates using a surface sampling electrospray ionization system with tandem mass spectrometry detection is reported. The thin-layer chromatography/electrospray tandem mass spectrometry method employed a deuterium-labeled caffeine internal standard and selected reaction monitoring detection. Up to nine parallel caffeine bands on a single plate were sampled in a single surface scanning experiment requiring 35 min at a surface scan rate of 44 {mu}m/s. A reversed-phase HPLC/UV caffeine assay was developed in parallel to assess the mass spectrometry method performance. Limits of detection for the HPLC/UV and thin-layer chromatography/electrospray tandem mass spectrometry methodsmore » determined from the calibration curve statistics were 0.20 ng injected (0.50 {mu}L) and 1.0 ng spotted on the plate, respectively. Spike recoveries with standards and real samples ranged between 97 and 106% for both methods. The caffeine content of three diet soft drinks (Diet Coke, Diet Cherry Coke, Diet Pepsi) and three diet sport drinks (Diet Turbo Tea, Speed Stack Grape, Speed Stack Fruit Punch) was measured. The HPLC/UV and mass spectrometry determinations were in general agreement, and these values were consistent with the quoted values for two of the three diet colas. In the case of Diet Cherry Coke and the diet sports drinks, the determined caffeine amounts using both methods were consistently higher (by 8% or more) than the literature values.« less

METHOD AND APPARATUS FOR MEASURING RADIATION

DOEpatents

Reeder, S.D.

1962-04-17

A chemical dosimeter for measuring the progress of a radiation-induced oxidation-reduction reaction is described. The dosimeter comprises a container filled with an aqueous chemical oxidation-reduction system which reacts quantitatively to the radiation. An anode of the group consisting of antimony and tungsten and a cathode of the group consisting of gold and platnium are inserted into the system. Means are provided to stir the system and a potential sensing device is connected across the anode and cathode to detect voltage changes. (AEC)

Learning to predict where human gaze is using quaternion DCT based regional saliency detection

NASA Astrophysics Data System (ADS)

Li, Ting; Xu, Yi; Zhang, Chongyang

2014-09-01

Many current visual attention approaches used semantic features to accurately capture human gaze. However, these approaches demand high computational cost and can hardly be applied to daily use. Recently, some quaternion-based saliency detection models, such as PQFT (phase spectrum of Quaternion Fourier Transform), QDCT (Quaternion Discrete Cosine Transform), have been proposed to meet real-time requirement of human gaze tracking tasks. However, current saliency detection methods used global PQFT and QDCT to locate jump edges of the input, which can hardly detect the object boundaries accurately. To address the problem, we improved QDCT-based saliency detection model by introducing superpixel-wised regional saliency detection mechanism. The local smoothness of saliency value distribution is emphasized to distinguish noises of background from salient regions. Our algorithm called saliency confidence can distinguish the patches belonging to the salient object and those of the background. It decides whether the image patches belong to the same region. When an image patch belongs to a region consisting of other salient patches, this patch should be salient as well. Therefore, we use saliency confidence map to get background weight and foreground weight to do the optimization on saliency map obtained by QDCT. The optimization is accomplished by least square method. The optimization approach we proposed unifies local and global saliency by combination of QDCT and measuring the similarity between each image superpixel. We evaluate our model on four commonly-used datasets (Toronto, MIT, OSIE and ASD) using standard precision-recall curves (PR curves), the mean absolute error (MAE) and area under curve (AUC) measures. In comparison with most state-of-art models, our approach can achieve higher consistency with human perception without training. It can get accurate human gaze even in cluttered background. Furthermore, it achieves better compromise between speed and accuracy.

Range of protein detection by selected/multiple reaction monitoring mass spectrometry in an unfractionated human cell culture lysate.

PubMed

Ebhardt, H Alexander; Sabidó, Eduard; Hüttenhain, Ruth; Collins, Ben; Aebersold, Ruedi

2012-04-01

Selected or multiple reaction monitoring is a targeted mass spectrometry method (S/MRM-MS), in which many peptides are simultaneously and consistently analyzed during a single liquid chromatography-mass spectrometry (LC-S/MRM-MS) measurement. These capabilities make S/MRM-MS an attractive method to monitor a consistent set of proteins over various experimental conditions. To increase throughput for S/MRM-MS it is advantageous to use scheduled methods and unfractionated protein extracts. Here, we established the practically measurable dynamic range of proteins reliably detectable and quantifiable in an unfractionated protein extract from a human cell line using LC-S/MRM-MS. Initially, we analyzed S/MRM transition peak groups in terms of interfering signals and compared S/MRM transition peak groups to MS1-triggered MS2 spectra using dot-product analysis. Finally, using unfractionated protein extract from human cell lysate, we quantified the upper boundary of copies per cell to be 35 million copies per cell, while 7500 copies per cell represents a lower boundary using a single 35 min linear gradient LC-S/MRM-MS measurement on a current, standard commercial instrument. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Heart rate measurement based on face video sequence

NASA Astrophysics Data System (ADS)

Xu, Fang; Zhou, Qin-Wu; Wu, Peng; Chen, Xing; Yang, Xiaofeng; Yan, Hong-jian

2015-03-01

This paper proposes a new non-contact heart rate measurement method based on photoplethysmography (PPG) theory. With this method we can measure heart rate remotely with a camera and ambient light. We collected video sequences of subjects, and detected remote PPG signals through video sequences. Remote PPG signals were analyzed with two methods, Blind Source Separation Technology (BSST) and Cross Spectral Power Technology (CSPT). BSST is a commonly used method, and CSPT is used for the first time in the study of remote PPG signals in this paper. Both of the methods can acquire heart rate, but compared with BSST, CSPT has clearer physical meaning, and the computational complexity of CSPT is lower than that of BSST. Our work shows that heart rates detected by CSPT method have good consistency with the heart rates measured by a finger clip oximeter. With good accuracy and low computational complexity, the CSPT method has a good prospect for the application in the field of home medical devices and mobile health devices.

Sequential analysis as a tool for detection of amikacin ototoxicity in the treatment of multidrug-resistant tuberculosis.

PubMed

Vasconcelos, Karla Anacleto de; Frota, Silvana Maria Monte Coelho; Ruffino-Netto, Antonio; Kritski, Afrânio Lineu

2018-04-01

To investigate early detection of amikacin-induced ototoxicity in a population treated for multidrug-resistant tuberculosis (MDR-TB), by means of three different tests: pure-tone audiometry (PTA); high-frequency audiometry (HFA); and distortion-product otoacoustic emission (DPOAE) testing. This was a longitudinal prospective cohort study involving patients aged 18-69 years with a diagnosis of MDR-TB who had to receive amikacin for six months as part of their antituberculosis drug regimen for the first time. Hearing was assessed before treatment initiation and at two and six months after treatment initiation. Sequential statistics were used to analyze the results. We included 61 patients, but the final population consisted of 10 patients (7 men and 3 women) because of sequential analysis. Comparison of the test results obtained at two and six months after treatment initiation with those obtained at baseline revealed that HFA at two months and PTA at six months detected hearing threshold shifts consistent with ototoxicity. However, DPOAE testing did not detect such shifts. The statistical method used in this study makes it possible to conclude that, over the six-month period, amikacin-associated hearing threshold shifts were detected by HFA and PTA, and that DPOAE testing was not efficient in detecting such shifts.

Magnetoelastic Effect-Based Transmissive Stress Detection for Steel Strips: Theory and Experiment

PubMed Central

Zhang, Qingdong; Su, Yuanxiao; Zhang, Liyuan; Bi, Jia; Luo, Jiang

2016-01-01

For the deficiencies of traditional stress detection methods for steel strips in industrial production, this paper proposes a non-contact stress detection scheme based on the magnetoelastic effect. The theoretical model of the transmission-type stress detection is established, in which the output voltage and the tested stress obey a linear relation. Then, a stress detection device is built for the experiment, and Q235 steel under uniaxial tension is tested as an example. The result shows that the output voltage rises linearly with the increase of the tensile stress, consistent with the theoretical prediction. To ensure the accuracy of the stress detection method in actual application, the temperature compensation, magnetic shielding and some other key technologies are investigated to reduce the interference of the external factors, such as environment temperature and surrounding magnetic field. The present research develops the theoretical and experimental foundations for the magnetic stress detection system, which can be used for online non-contact monitoring of strip flatness-related stress (tension distribution or longitudinal residual stress) in the steel strip rolling process, the quality evaluation of strip flatness after rolling, the life and safety assessment of metal construction and other industrial production links. PMID:27589742

CNVcaller: highly efficient and widely applicable software for detecting copy number variations in large populations.

PubMed

Wang, Xihong; Zheng, Zhuqing; Cai, Yudong; Chen, Ting; Li, Chao; Fu, Weiwei; Jiang, Yu

2017-12-01

The increasing amount of sequencing data available for a wide variety of species can be theoretically used for detecting copy number variations (CNVs) at the population level. However, the growing sample sizes and the divergent complexity of nonhuman genomes challenge the efficiency and robustness of current human-oriented CNV detection methods. Here, we present CNVcaller, a read-depth method for discovering CNVs in population sequencing data. The computational speed of CNVcaller was 1-2 orders of magnitude faster than CNVnator and Genome STRiP for complex genomes with thousands of unmapped scaffolds. CNV detection of 232 goats required only 1.4 days on a single compute node. Additionally, the Mendelian consistency of sheep trios indicated that CNVcaller mitigated the influence of high proportions of gaps and misassembled duplications in the nonhuman reference genome assembly. Furthermore, multiple evaluations using real sheep and human data indicated that CNVcaller achieved the best accuracy and sensitivity for detecting duplications. The fast generalized detection algorithms included in CNVcaller overcome prior computational barriers for detecting CNVs in large-scale sequencing data with complex genomic structures. Therefore, CNVcaller promotes population genetic analyses of functional CNVs in more species. © The Authors 2017. Published by Oxford University Press.

CNVcaller: highly efficient and widely applicable software for detecting copy number variations in large populations

PubMed Central

Wang, Xihong; Zheng, Zhuqing; Cai, Yudong; Chen, Ting; Li, Chao; Fu, Weiwei

2017-01-01

Abstract Background The increasing amount of sequencing data available for a wide variety of species can be theoretically used for detecting copy number variations (CNVs) at the population level. However, the growing sample sizes and the divergent complexity of nonhuman genomes challenge the efficiency and robustness of current human-oriented CNV detection methods. Results Here, we present CNVcaller, a read-depth method for discovering CNVs in population sequencing data. The computational speed of CNVcaller was 1–2 orders of magnitude faster than CNVnator and Genome STRiP for complex genomes with thousands of unmapped scaffolds. CNV detection of 232 goats required only 1.4 days on a single compute node. Additionally, the Mendelian consistency of sheep trios indicated that CNVcaller mitigated the influence of high proportions of gaps and misassembled duplications in the nonhuman reference genome assembly. Furthermore, multiple evaluations using real sheep and human data indicated that CNVcaller achieved the best accuracy and sensitivity for detecting duplications. Conclusions The fast generalized detection algorithms included in CNVcaller overcome prior computational barriers for detecting CNVs in large-scale sequencing data with complex genomic structures. Therefore, CNVcaller promotes population genetic analyses of functional CNVs in more species. PMID:29220491

Determining the relative susceptibility of four prion protein genotypes to atypical scrapie

USDA-ARS?s Scientific Manuscript database

Atypical scrapie is a sheep prion (PrPSc) disease whose epidemiology is consistent with a sporadic origin and is associated with specific polymorphisms of the normal cellular prion protein (PrPC). We describe a mass spectrometry-based method of detecting and quantifying the polymorphisms of sheep P...

Asbestos-Containing Materials in School Buildings: A Guidance Document. Part 2.

ERIC Educational Resources Information Center

Sawyer, Robert N.; Spooner, Charles M.

Part 2 of the Environmental Protection Agency (EPA) guidance manuals consists of more detailed information on asbestos identification and control methods. Available information on sprayed asbestos-containing materials in buildings is summarized. Guidelines are presented for the detection and monitoring, removal or encapsulation, and disposal of…

Processing can alter the properties of peanut extract preparations.

USDA-ARS?s Scientific Manuscript database

As peanut allergy is an increasing public health risk, affecting over 1% of the United States and United Kingdom school children; it is important that methods and reagents for accurate diagnosis of food allergy, and detection of allergenic foods are reliable and consistent. Given that most current e...

Reliability and Validity of the Evidence-Based Practice Confidence (EPIC) Scale

ERIC Educational Resources Information Center

Salbach, Nancy M.; Jaglal, Susan B.; Williams, Jack I.

2013-01-01

Introduction: The reliability, minimal detectable change (MDC), and construct validity of the evidence-based practice confidence (EPIC) scale were evaluated among physical therapists (PTs) in clinical practice. Methods: A longitudinal mail survey was conducted. Internal consistency and test-retest reliability were estimated using Cronbach's alpha…

Consumer Health Education. Breast Cancer.

ERIC Educational Resources Information Center

Arkansas Univ., Fayetteville, Cooperative Extension Service.

This short booklet is designed to be used by health educators when teaching women about breast cancer and its early detection and the procedure for breast self-examination. It includes the following: (1) A one-page teaching plan consisting of objectives, subject matter, methods (including titles of films and printed materials), target audience,…

Understanding environmental DNA detection probabilities: A case study using a stream-dwelling char Salvelinus fontinalis

USGS Publications Warehouse

Wilcox, Taylor M; Mckelvey, Kevin S.; Young, Michael K.; Sepulveda, Adam; Shepard, Bradley B.; Jane, Stephen F; Whiteley, Andrew R.; Lowe, Winsor H.; Schwartz, Michael K.

2016-01-01

Environmental DNA sampling (eDNA) has emerged as a powerful tool for detecting aquatic animals. Previous research suggests that eDNA methods are substantially more sensitive than traditional sampling. However, the factors influencing eDNA detection and the resulting sampling costs are still not well understood. Here we use multiple experiments to derive independent estimates of eDNA production rates and downstream persistence from brook trout (Salvelinus fontinalis) in streams. We use these estimates to parameterize models comparing the false negative detection rates of eDNA sampling and traditional backpack electrofishing. We find that using the protocols in this study eDNA had reasonable detection probabilities at extremely low animal densities (e.g., probability of detection 0.18 at densities of one fish per stream kilometer) and very high detection probabilities at population-level densities (e.g., probability of detection > 0.99 at densities of ≥ 3 fish per 100 m). This is substantially more sensitive than traditional electrofishing for determining the presence of brook trout and may translate into important cost savings when animals are rare. Our findings are consistent with a growing body of literature showing that eDNA sampling is a powerful tool for the detection of aquatic species, particularly those that are rare and difficult to sample using traditional methods.

A tree canopy height delineation method based on Morphological Reconstruction—Open Crown Decomposition

NASA Astrophysics Data System (ADS)

Liu, Q.; Jing, L.; Li, Y.; Tang, Y.; Li, H.; Lin, Q.

2016-04-01

For the purpose of forest management, high resolution LIDAR and optical remote sensing imageries are used for treetop detection, tree crown delineation, and classification. The purpose of this study is to develop a self-adjusted dominant scales calculation method and a new crown horizontal cutting method of tree canopy height model (CHM) to detect and delineate tree crowns from LIDAR, under the hypothesis that a treetop is radiometric or altitudinal maximum and tree crowns consist of multi-scale branches. The major concept of the method is to develop an automatic selecting strategy of feature scale on CHM, and a multi-scale morphological reconstruction-open crown decomposition (MRCD) to get morphological multi-scale features of CHM by: cutting CHM from treetop to the ground; analysing and refining the dominant multiple scales with differential horizontal profiles to get treetops; segmenting LiDAR CHM using watershed a segmentation approach marked with MRCD treetops. This method has solved the problems of false detection of CHM side-surface extracted by the traditional morphological opening canopy segment (MOCS) method. The novel MRCD delineates more accurate and quantitative multi-scale features of CHM, and enables more accurate detection and segmentation of treetops and crown. Besides, the MRCD method can also be extended to high optical remote sensing tree crown extraction. In an experiment on aerial LiDAR CHM of a forest of multi-scale tree crowns, the proposed method yielded high-quality tree crown maps.

Swab Protocol for Rapid Laboratory Diagnosis of Cutaneous Anthrax

PubMed Central

Marston, Chung K.; Bhullar, Vinod; Baker, Daniel; Rahman, Mahmudur; Hossain, M. Jahangir; Chakraborty, Apurba; Khan, Salah Uddin; Hoffmaster, Alex R.

2012-01-01

The clinical laboratory diagnosis of cutaneous anthrax is generally established by conventional microbiological methods, such as culture and directly straining smears of clinical specimens. However, these methods rely on recovery of viable Bacillus anthracis cells from swabs of cutaneous lesions and often yield negative results. This study developed a rapid protocol for detection of B. anthracis on clinical swabs. Three types of swabs, flocked-nylon, rayon, and polyester, were evaluated by 3 extraction methods, the swab extraction tube system (SETS), sonication, and vortex. Swabs were spiked with virulent B. anthracis cells, and the methods were compared for their efficiency over time by culture and real-time PCR. Viability testing indicated that the SETS yielded greater recovery of B. anthracis from 1-day-old swabs; however, reduced viability was consistent for the 3 extraction methods after 7 days and nonviability was consistent by 28 days. Real-time PCR analysis showed that the PCR amplification was not impacted by time for any swab extraction method and that the SETS method provided the lowest limit of detection. When evaluated using lesion swabs from cutaneous anthrax outbreaks, the SETS yielded culture-negative, PCR-positive results. This study demonstrated that swab extraction methods differ in their efficiency of recovery of viable B. anthracis cells. Furthermore, the results indicated that culture is not reliable for isolation of B. anthracis from swabs at ≥7 days. Thus, we recommend the use of the SETS method with subsequent testing by culture and real-time PCR for diagnosis of cutaneous anthrax from clinical swabs of cutaneous lesions. PMID:23035192

Methods for synthesizing semiconductor quality chalcopyrite crystals for nonlinear optical and radiation detection applications and the like

DOEpatents

Stowe, Ashley; Burger, Arnold

2016-05-10

A method for synthesizing I-III-VI.sub.2 compounds, including: melting a Group III element; adding a Group I element to the melted Group III element at a rate that allows the Group I and Group III elements to react thereby providing a single phase I-III compound; and adding a Group VI element to the single phase I-III compound under heat, with mixing, and/or via vapor transport. The Group III element is melted at a temperature of between about 200 degrees C. and about 700 degrees C. Preferably, the Group I element consists of a neutron absorber and the group III element consists of In or Ga. The Group VI element and the single phase I-III compound are heated to a temperature of between about 700 degrees C. and about 1000 degrees C. Preferably, the Group VI element consists of S, Se, or Te. Optionally, the method also includes doping with a Group IV element activator.

Enhanced light extraction of plastic scintillator using large-area photonic crystal structures fabricated by hot embossing.

PubMed

Chen, Xueye; Liu, Bo; Wu, Qiang; Zhu, Zhichao; Zhu, Jingtao; Gu, Mu; Chen, Hong; Liu, Jinliang; Chen, Liang; Ouyang, Xiaoping

2018-04-30

Plastic scintillators are widely used in various radiation measurement systems. However, detection efficiency and signal-to-noise are limited due to the total internal reflection, especially for weak signal detection situations. In the present investigation, large-area photonic crystals consisting of an array of periodic truncated cone holes were prepared based on hot embossing technology aiming at coupling with the surface of plastic scintillator to improve the light extraction efficiency and directionality control. The experimental results show that a maximum enhancement of 64% at 25° emergence angle along Γ-M orientation and a maximum enhancement of 58% at 20° emergence angle along Γ-K orientation were obtained. The proposed fabrication method of photonic crystal scintillator can avoid complicated pattern transfer processes used in most traditional methods, leading to a simple, economical method for large-area preparation. The photonic crystal scintillator demonstrated in this work is of great value for practical applications of nuclear radiation detection.

Spectroscopic Detection of Caries Lesions

PubMed Central

Ruohonen, Mika; Palo, Katri; Alander, Jarmo

2013-01-01

Background. A caries lesion causes changes in the optical properties of the affected tissue. Currently a caries lesion can be detected only at a relatively late stage of development. Caries diagnosis also suffers from high interobserver variance. Methods. This is a pilot study to test the suitability of an optical diffuse reflectance spectroscopy for caries diagnosis. Reflectance visible/near-infrared spectroscopy (VIS/NIRS) was used to measure caries lesions and healthy enamel on extracted human teeth. The results were analysed with a computational algorithm in order to find a rule-based classification method to detect caries lesions. Results. The classification indicated that the measured points of enamel could be assigned to one of three classes: healthy enamel, a caries lesion, and stained healthy enamel. The features that enabled this were consistent with theory. Conclusions. It seems that spectroscopic measurements can help to reduce false positives at in vitro setting. However, further research is required to evaluate the strength of the evidence for the method's performance. PMID:27006907

Determination of fenoterol in human plasma by HPLC with fluorescence detection after derivatization.

PubMed

Meineke, Ingolf; Steinmetz, Hannelore; Kramer, Skaidrit; Gleiter, Christoph H

2002-06-20

A new method for the determination of fenoterol is described, which uses HPLC separation with fluorescence detection. Dobutamine is employed as an internal standard. The separation was achieved on a short reversed phase column with a mobile phase consisting of water, acetonitrile and methanol. Prior to chromatography both analytes are derivatized with 9-chloroformyl-carbazole. Isolation of the analytes from plasma is carried out by liquid-liquid extraction into 2-butanol after protein precipitation with acetonitrile. The method is capable of estimating fenoterol concentrations in the sub-nanogram per ml range with sufficient accuracy and precision. The determination of fenoterol can now be carried out in the average laboratory without radiolabelled material.

Method and an apparatus for non-invasively determining the quantity of an element in a body organ

DOEpatents

Vartsky, D.; Ellis, K.J.; Cohn, S.H.

1980-06-27

An apparatus and a method for determining in a body organ the amount of an element with the aid of a gaseous gamma ray source, where the element and the source are paired in predetermined pairs, and with the aid of at least one detector selected from the group consisting of Ge(Li) and NaI(Tl). Gamma rays are directed towards the organ, thereby resonantly scattering the gamma rays from nuclei of the element in the organ; the intensity of the gamma rays is detected by the detector; and the amount of the element in the organ is then substantially proportional to the detected intensity of the gamma rays.

Computerized method for detection of vertebral fractures on lateral chest radiographs based on morphometric data

NASA Astrophysics Data System (ADS)

Kasai, Satoshi; Li, Feng; Shiraishi, Junji; Li, Qiang; Straus, Christopher; Vokes, Tamara; MacMahon, Heber; Doi, Kunio

2007-03-01

Vertebral fractures are the most common osteoporosis-related fractures. It is important to detect vertebral fractures, because they are associated with increased risk of subsequent fractures, and because pharmacologic therapy can reduce the risk of subsequent fractures. Although vertebral fractures are often not clinically recognized, they can be visualized on lateral chest radiographs taken for other purposes. However, only 15-60% of vertebral fractures found on lateral chest radiographs are mentioned in radiology reports. The purpose of this study was to develop a computerized method for detection of vertebral fractures on lateral chest radiographs in order to assist radiologists' image interpretation. Our computerized method is based on the automated identification of upper and lower vertebral edges. In order to develop the scheme, radiologists provided morphometric data for each identifiable vertebra, which consisted of six points for each vertebra, for 25 normals and 20 cases with severe fractures. Anatomical information was obtained from morphometric data of normal cases in terms of vertebral heights, heights of vertebral disk spaces, and vertebral centerline. Computerized detection of vertebral fractures was based on the reduction in the heights of fractured vertebrae compared to adjacent vertebrae and normal reference data. Vertebral heights from morphometric data on normal cases were used as reference. On 138 chest radiographs (20 with fractures) the sensitivity of our method for detection of fracture cases was 95% (19/20) with 0.93 (110/118) false-positives per image. In conclusion, the computerized method would be useful for detection of potentially overlooked vertebral fractures on lateral chest radiographs.

Damage assessment in composite laminates via broadband Lamb wave.

PubMed

Gao, Fei; Zeng, Liang; Lin, Jing; Shao, Yongsheng

2018-05-01

Time of flight (ToF) based method for damage detection using Lamb waves is widely used. However, due to the energy dissipation of Lamb waves and the non-ignorable size of damage in composite structure, the performance of damage detection is restricted. The objective of this research is to establish an improved method to locate and assess damages in composite structure. To choose appropriate excitation parameters, the propagation characters of Lamb waves in quasi-isotropic composite laminates are firstly studied and the broadband excitation is designed. Subsequently, the pulse compression technique is adopted for energy concentration and high-accuracy distance estimation. On this basis, the gravity center of intersections of path loci is employed for damage localization and the convex envelop of identified damage edge points is taken for damage contour estimation. As a result, both damage location and size can be evaluated, thereby providing the information for quantitative damage detection. The experiment consisting of five different sizes of damage is carried for method verification and the identified results show the efficiency of the proposed method. Copyright © 2018 Elsevier B.V. All rights reserved.

Automated detection of nerve fiber layer defects on retinal fundus images using fully convolutional network for early diagnosis of glaucoma

NASA Astrophysics Data System (ADS)

Watanabe, Ryusuke; Muramatsu, Chisako; Ishida, Kyoko; Sawada, Akira; Hatanaka, Yuji; Yamamoto, Tetsuya; Fujita, Hiroshi

2017-03-01

Early detection of glaucoma is important to slow down progression of the disease and to prevent total vision loss. We have been studying an automated scheme for detection of a retinal nerve fiber layer defect (NFLD), which is one of the earliest signs of glaucoma on retinal fundus images. In our previous study, we proposed a multi-step detection scheme which consists of Gabor filtering, clustering and adaptive thresholding. The problems of the previous method were that the number of false positives (FPs) was still large and that the method included too many rules. In attempt to solve these problems, we investigated the end-to-end learning system without pre-specified features. A deep convolutional neural network (DCNN) with deconvolutional layers was trained to detect NFLD regions. In this preliminary investigation, we investigated effective ways of preparing the input images and compared the detection results. The optimal result was then compared with the result obtained by the previous method. DCNN training was carried out using original images of abnormal cases, original images of both normal and abnormal cases, ellipse-based polar transformed images, and transformed half images. The result showed that use of both normal and abnormal cases increased the sensitivity as well as the number of FPs. Although NFLDs are visualized with the highest contrast in green plane, the use of color images provided higher sensitivity than the use of green image only. The free response receiver operating characteristic curve using the transformed color images, which was the best among seven different sets studied, was comparable to that of the previous method. Use of DCNN has a potential to improve the generalizability of automated detection method of NFLDs and may be useful in assisting glaucoma diagnosis on retinal fundus images.

Real-time PCR using SYBR Green for the detection of Shigella spp. in food and stool samples.

PubMed

Mokhtari, W; Nsaibia, S; Gharbi, A; Aouni, M

2013-02-01

Shigella spp are exquisitely fastidious Gram negative organisms that frequently get missed in the detection by traditional culture methods. For this reason, this work has adapted a classical PCR for detection of Shigella in food and stool specimens to real-time PCR using the SYBR Green format. This method follows a melting curve analysis to be more rapid and provide both qualitative and quantitative data about the targeted pathogen. A total of 117 stool samples with diarrhea and 102 food samples were analyzed in Public Health Regional Laboratory of Nabeul by traditional culture methods and real-time PCR. To validate the real-time PCR assay, an experiment was conducted with both spiked and naturally contaminated stool samples. All Shigella strains tested were ipaH positive and all non-Shigella strains yielded no amplification products. The melting temperature (T(m) = 81.5 ± 0.5 °C) was consistently specific for the amplicon. Correlation coefficients of standard curves constructed using the quantification cycle (C(q)) versus copy numbers of Shigella showed good linearity (R² = 0.995; slope = 2.952) and the minimum level of detection was 1.5 × 10³ CFU/g feces. All food samples analyzed were negative for Shigella by standard culture methods, whereas ipaH was detected in 8.8% culture negative food products. Moreover, the ipaH specific PCR system increased the detection rate over that by culture alone from 1.7% to 11.1% among patients with diarrhea. The data presented here shows that the SYBR Green I was suitable for use in the real-time PCR assay, which provided a specific, sensitive and efficient method for the detection and quantification of Shigella spp in food and stool samples. Copyright © 2012 Elsevier Ltd. All rights reserved.

A multistage approach to improve performance of computer-aided detection of pulmonary embolisms depicted on CT images: preliminary investigation.

PubMed

Park, Sang Cheol; Chapman, Brian E; Zheng, Bin

2011-06-01

This study developed a computer-aided detection (CAD) scheme for pulmonary embolism (PE) detection and investigated several approaches to improve CAD performance. In the study, 20 computed tomography examinations with various lung diseases were selected, which include 44 verified PE lesions. The proposed CAD scheme consists of five basic steps: 1) lung segmentation; 2) PE candidate extraction using an intensity mask and tobogganing region growing; 3) PE candidate feature extraction; 4) false-positive (FP) reduction using an artificial neural network (ANN); and 5) a multifeature-based k-nearest neighbor for positive/negative classification. In this study, we also investigated the following additional methods to improve CAD performance: 1) grouping 2-D detected features into a single 3-D object; 2) selecting features with a genetic algorithm (GA); and 3) limiting the number of allowed suspicious lesions to be cued in one examination. The results showed that 1) CAD scheme using tobogganing, an ANN, and grouping method achieved the maximum detection sensitivity of 79.2%; 2) the maximum scoring method achieved the superior performance over other scoring fusion methods; 3) GA was able to delete "redundant" features and further improve CAD performance; and 4) limiting the maximum number of cued lesions in an examination reduced FP rate by 5.3 times. Combining these approaches, CAD scheme achieved 63.2% detection sensitivity with 18.4 FP lesions per examination. The study suggested that performance of CAD schemes for PE detection depends on many factors that include 1) optimizing the 2-D region grouping and scoring methods; 2) selecting the optimal feature set; and 3) limiting the number of allowed cueing lesions per examination.

Escherichia coli biosensors for environmental, food industry and biological warfare agent detection

NASA Astrophysics Data System (ADS)

Allil, R. C. S. B.; Werneck, M. M.; da Silva-Neto, J. L.; Miguel, M. A. L.; Rodrigues, D. M. C.; Wandermur, G. L.; Rambauske, D. C.

2013-06-01

This work has the objective to research and develop a plastic optical fiber biosensor based taper and mPOF LPG techniques to detect Escherichia coli by measurements of index of refraction. Generally, cell detection is crucial in microbiological analysis of clinical, food, water or environmental samples. However, methods current employed are time consuming, taking at least 72 hours in order to produce reliable responses as they depend on sample collection and cell culture in controlled conditions. The delay in obtaining the results of the analysis can result in contamination of a great number of consumers. Plastic Optical Fiber (POF) biosensors consist in a viable alternative for rapid and inexpensive scheme for cells detection. A study the sensitivity of these sensors for microbiological detection, fiber Tapers and Long Period Grating (LPG) both in poly-methyl-methacrylate (PMMA) were realized as possible candidates to take part of a biosensor system to detect Escherichia coli in water samples. In this work we adopted the immunocapture technique, which consists of quantifying bacteria in a liquid sample, attract-ing and fixing the bacteria on the surface of the polymer optical fiber, by the antigen-antibody reaction. The results were obtained by optical setup that consists in a side of the fiber a LED coupled to a photodetector through a POF with the taper in the middle of it. On the other side of the POF a photodetector receives this light producting a photocurrent. The output voltage is fed into the microcontroller A/D input port and its output data is sent via USB to a LabView software running in a microcomputer. The results showed the possibility of the POF in biosensor application capable to detect E. coli for environmental and food industry and for detecting and identifying biological-warfare agents using a very rapid response sensor, applicable to field detection prototypes.

Image velocimetry for clouds with relaxation labeling based on deformation consistency

NASA Astrophysics Data System (ADS)

Horinouchi, Takeshi; Murakami, Shin-ya; Kouyama, Toru; Ogohara, Kazunori; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2017-08-01

Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking.

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

PubMed

Nguyen, Van-Han; Pyun, Jae-Young

2015-03-19

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

Rapid Detection and Enumeration of Giardia lamblia Cysts in Water Samples by Immunomagnetic Separation and Flow Cytometric Analysis ▿ †

PubMed Central

Keserue, Hans-Anton; Füchslin, Hans Peter; Egli, Thomas

2011-01-01

Giardia lamblia is an important waterborne pathogen and is among the most common intestinal parasites of humans worldwide. Its fecal-oral transmission leads to the presence of cysts of this pathogen in the environment, and so far, quantitative rapid screening methods are not available for various matrices, such as surface waters, wastewater, or food. Thus, it is necessary to establish methods that enable reliable rapid detection of a single cyst in 10 to 100 liters of drinking water. Conventional detection relies on cyst concentration, isolation, and confirmation by immunofluorescence microscopy (IFM), resulting in low recoveries and high detection limits. Many different immunomagnetic separation (IMS) procedures have been developed for separation and cyst purification, so far with variable but high losses of cysts. A method was developed that requires less than 100 min and consists of filtration, resuspension, IMS, and flow cytometric (FCM) detection. MACS MicroBeads were used for IMS, and a reliable flow cytometric detection approach was established employing 3 different parameters for discrimination from background signals, i.e., green and red fluorescence (resulting from the distinct pattern emitted by the fluorescein dye) and sideward scatter for size discrimination. With spiked samples, recoveries exceeding 90% were obtained, and false-positive results were never encountered for negative samples. Additionally, the method was applicable to naturally occurring cysts in wastewater and has the potential to be automated. PMID:21685159

a Landsat Time-Series Stacks Model for Detection of Cropland Change

NASA Astrophysics Data System (ADS)

Chen, J.; Chen, J.; Zhang, J.

2017-09-01

Global, timely, accurate and cost-effective cropland monitoring with a fine spatial resolution will dramatically improve our understanding of the effects of agriculture on greenhouse gases emissions, food safety, and human health. Time-series remote sensing imagery have been shown particularly potential to describe land cover dynamics. The traditional change detection techniques are often not capable of detecting land cover changes within time series that are severely influenced by seasonal difference, which are more likely to generate pseuso changes. Here,we introduced and tested LTSM ( Landsat time-series stacks model), an improved Continuous Change Detection and Classification (CCDC) proposed previously approach to extract spectral trajectories of land surface change using a dense Landsat time-series stacks (LTS). The method is expected to eliminate pseudo changes caused by phenology driven by seasonal patterns. The main idea of the method is that using all available Landsat 8 images within a year, LTSM consisting of two term harmonic function are estimated iteratively for each pixel in each spectral band .LTSM can defines change area by differencing the predicted and observed Landsat images. The LTSM approach was compared with change vector analysis (CVA) method. The results indicated that the LTSM method correctly detected the "true change" without overestimating the "false" one, while CVA pointed out "true change" pixels with a large number of "false changes". The detection of change areas achieved an overall accuracy of 92.37 %, with a kappa coefficient of 0.676.

Performance Evaluation of a Salivary Amylase Biosensor for Stress Assessment in Military Field Research.

PubMed

Peng, Henry T; Savage, Erin; Vartanian, Oshin; Smith, Shane; Rhind, Shawn G; Tenn, Catherine; Bjamason, Stephen

2016-05-01

A convenient biosensor for real-time measurement of biomarkers for in-field psychophysiological stress research and military operations is desirable. We evaluated a hand-held device for measuring salivary amylase as a stress marker in medical technicians undergoing combat casualty care training using two different modalities in operating room and field settings. Salivary amylase activity was measured by two biosensor methods: directly sampling saliva with a test strip placed under the tongue or pipetting a fixed volume of precollected saliva onto the test strip, followed by analyzing the sample on the strip using a biosensor. The two methods were compared for their accuracy and sensitivity to detect the stress response using an enzyme assay method as a standard. The measurements from the under-the-tongue method were not as consistent with those from the standard assay method as the values obtained from the pipetting method. The under-the-tongue method did not detect any significant increase in the amylase activity due to stress in the operating room (P > 0.1), in contrast to the significant increases observed using the pipetting method and assay method with a significance level less than 0.05 and 0.1, respectively. Furthermore, the under-the-tongue method showed no increased amylase activity in the field testing, while both the pipetting method and assay method showed increased amylase activity in the same group (P < 0.1). The accuracy and consistency of the biosensors need to be improved when used to directly measure salivary amylase activity under the tongue for stress assessment in military medical training. © 2015 Her Majesty the Queen in Right of Canada. Journal of Clinical Laboratory Analysis published by Wiley Periodicals, Inc. Reproduced with the permission DRDC Editorial Board.

Detection of related substances in polyene phosphatidyl choline extracted from soybean and in its commercial capsule by comprehensive supercritical fluid chromatography with mass spectrometry compared with HPLC with evaporative light scattering detection.

PubMed

Jiang, Qikun; Liu, Wanjun; Li, Xiaoting; Zhang, Tianhong; Wang, Yongjun; Liu, Xiaohong

2016-01-01

Supercritical fluid chromatography with tandem mass spectrometry was used to comprehensively profile polyene phosphatidyl choline (PPC) extracted from soybean. We achieved an efficient chromatographic analysis using a BEH-2EP column (3 × 100 mm(2) , 1.7 μm) with a mobile phase consisting of CO2 and a cosolvent in gradient combination at a flow rate of 1.0 mL/min. The cosolvent consisted of methanol, acetonitrile, and water (containing 10 mM ammonium acetate and 0.2% formic acid). The total single-run time was 7 min. We used this method to accurately detect ten different phospholipids (PLs) during extraction. The limits of quantification for phosphatidyl choline, lyso-phosphatidylcholine (LPC), phosphatidic acid (PA), sphingomyelin, phosphatidyl glycerol, phosphatidyl inositol (PI), cholesterol, cardiolipin, phosphatidyl serine, and phosphatidyl ethanolamine (PE) were 20.6, 19.52, 1.21, 2.38, 0.50, 2.28, 54.3, 0.60, 0.65, and 4.85 ng/mL, respectively. However, adopting the high-performance liquid chromatography with evaporative light scattering detection method issued by the China Food and Drug Administration, only PA, LPC, PE, PI, and PPC could be analyzed accurately, and the limits of quantification were 33.89, 60.5, 30.3, 10.9, and 61.79 μg/mL, respectively. The total single-run time was at the least 20 min. Consequently, the supercritical fluid chromatography with tandem mass spectrometry method was more suitable for the analysis of related PLs. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detection of Clostridium botulinum type C cells in the gastrointestinal tracts of Mozambique tilapia (Oreochromis mossambicus) by polymerase chain reaction

USGS Publications Warehouse

Nol, P.; Williamson, J.L.; Rocke, T.E.; Yuill, Thomas M.

2004-01-01

We established a method of directly detecting Clostridium botulinum type C cells, while minimizing spore detection, in the intestinal contents of Mozambique tilapia (Oreochromis mossambicus). This technique involved extraction of predominantly cellular DNA from tilapia intestinal tracts and used a polymerase chain reaction assay to detect presence of type C1 toxin gene. We consistently detected C. botulinum type C cells in tilapia gastrointestinal contents at a level of 7.5×104 cells per 0.25 g material or 1.9×103 cells. This technique is useful for determining prevalence of the potentially active organisms within a given population of fish and may be adapted to other types of C. botulinum and vertebrate populations as well.

A Self-Adapting System for the Automated Detection of Inter-Ictal Epileptiform Discharges

PubMed Central

Lodder, Shaun S.; van Putten, Michel J. A. M.

2014-01-01

Purpose Scalp EEG remains the standard clinical procedure for the diagnosis of epilepsy. Manual detection of inter-ictal epileptiform discharges (IEDs) is slow and cumbersome, and few automated methods are used to assist in practice. This is mostly due to low sensitivities, high false positive rates, or a lack of trust in the automated method. In this study we aim to find a solution that will make computer assisted detection more efficient than conventional methods, while preserving the detection certainty of a manual search. Methods Our solution consists of two phases. First, a detection phase finds all events similar to epileptiform activity by using a large database of template waveforms. Individual template detections are combined to form “IED nominations”, each with a corresponding certainty value based on the reliability of their contributing templates. The second phase uses the ten nominations with highest certainty and presents them to the reviewer one by one for confirmation. Confirmations are used to update certainty values of the remaining nominations, and another iteration is performed where ten nominations with the highest certainty are presented. This continues until the reviewer is satisfied with what has been seen. Reviewer feedback is also used to update template accuracies globally and improve future detections. Key Findings Using the described method and fifteen evaluation EEGs (241 IEDs), one third of all inter-ictal events were shown after one iteration, half after two iterations, and 74%, 90%, and 95% after 5, 10 and 15 iterations respectively. Reviewing fifteen iterations for the 20–30 min recordings 1took approximately 5 min. Significance The proposed method shows a practical approach for combining automated detection with visual searching for inter-ictal epileptiform activity. Further evaluation is needed to verify its clinical feasibility and measure the added value it presents. PMID:24454813

An efficient method for automatic morphological abnormality detection from human sperm images.

PubMed

Ghasemian, Fatemeh; Mirroshandel, Seyed Abolghasem; Monji-Azad, Sara; Azarnia, Mahnaz; Zahiri, Ziba

2015-12-01

Sperm morphology analysis (SMA) is an important factor in the diagnosis of human male infertility. This study presents an automatic algorithm for sperm morphology analysis (to detect malformation) using images of human sperm cells. The SMA method was used to detect and analyze different parts of the human sperm. First of all, SMA removes the image noises and enhances the contrast of the image to a great extent. Then it recognizes the different parts of sperm (e.g., head, tail) and analyzes the size and shape of each part. Finally, the algorithm classifies each sperm as normal or abnormal. Malformations in the head, midpiece, and tail of a sperm, can be detected by the SMA method. In contrast to other similar methods, the SMA method can work with low resolution and non-stained images. Furthermore, an image collection created for the SMA, has also been described in this study. This benchmark consists of 1457 sperm images from 235 patients, and is known as human sperm morphology analysis dataset (HSMA-DS). The proposed algorithm was tested on HSMA-DS. The experimental results show the high ability of SMA to detect morphological deformities from sperm images. In this study, the SMA algorithm produced above 90% accuracy in sperm abnormality detection task. Another advantage of the proposed method is its low computation time (that is, less than 9s), as such, the expert can quickly decide to choose the analyzed sperm or select another one. Automatic and fast analysis of human sperm morphology can be useful during intracytoplasmic sperm injection for helping embryologists to select the best sperm in real time. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Development and Validation of the Suprathreshold Stochastic Resonance-Based Image Processing Method for the Detection of Abdomino-pelvic Tumor on PET/CT Scans.

PubMed

Saroha, Kartik; Pandey, Anil Kumar; Sharma, Param Dev; Behera, Abhishek; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-01-01

The detection of abdomino-pelvic tumors embedded in or nearby radioactive urine containing 18F-FDG activity is a challenging task on PET/CT scan. In this study, we propose and validate the suprathreshold stochastic resonance-based image processing method for the detection of these tumors. The method consists of the addition of noise to the input image, and then thresholding it that creates one frame of intermediate image. One hundred such frames were generated and averaged to get the final image. The method was implemented using MATLAB R2013b on a personal computer. Noisy image was generated using random Poisson variates corresponding to each pixel of the input image. In order to verify the method, 30 sets of pre-diuretic and its corresponding post-diuretic PET/CT scan images (25 tumor images and 5 control images with no tumor) were included. For each sets of pre-diuretic image (input image), 26 images (at threshold values equal to mean counts multiplied by a constant factor ranging from 1.0 to 2.6 with increment step of 0.1) were created and visually inspected, and the image that most closely matched with the gold standard (corresponding post-diuretic image) was selected as the final output image. These images were further evaluated by two nuclear medicine physicians. In 22 out of 25 images, tumor was successfully detected. In five control images, no false positives were reported. Thus, the empirical probability of detection of abdomino-pelvic tumors evaluates to 0.88. The proposed method was able to detect abdomino-pelvic tumors on pre-diuretic PET/CT scan with a high probability of success and no false positives.

Rapid detection of Streptococcus pneumoniae by real-time fluorescence loop-mediated isothermal amplification

PubMed Central

Guo, Xu-Guang; Zhou, Shan

2014-01-01

Background and aim of study A significant human pathogenic bacterium, Streptococcus pneumoniae was recognized as a major cause of pneumonia, and is the subject of many humoral immunity studies. Diagnosis is generally made based on clinical suspicion along with a positive culture from a sample from virtually any place in the body. But the testing time is too long. This study is to establish a rapid diagnostic method to identification of Streptococcus pneumoniae. Methods Our laboratory has recently developed a new platform called real-amp, which combines loop-mediated isothermal amplification (LAMP) with a portable tube scanner real-time isothermal instrument for the rapid detection of Streptococcus pneumonia. Two pairs of amplification primers required for this method were derived from a conserved DNA sequence unique to the Streptococcus pneumoniae. The amplification was carried out at 63 degree Celsius using SYBR Green for 60 minutes with the tube scanner set to collect fluorescence signals. Clinical samples of Streptococcus pneumoniae and other bacteria were used to determine the sensitivity and specificity of the primers by comparing with traditional culture method. Results The new set of primers consistently detected in laboratory-maintained isolates of Streptococcus pneumoniae from our hospital. The new primers also proved to be more sensitive than the published species-specific primers specifically developed for the LAMP method in detecting Streptococcus pneumoniae. Conclusions This study demonstrates that the Streptococcus pneumoniae LAMP primers developed here have the ability to accurately detect Streptococcus pneumoniae infections by real-time fluorescence LAMP. PMID:25276360

An Indirect Adaptive Control Scheme in the Presence of Actuator and Sensor Failures

NASA Technical Reports Server (NTRS)

Sun, Joy Z.; Josh, Suresh M.

2009-01-01

The problem of controlling a system in the presence of unknown actuator and sensor faults is addressed. The system is assumed to have groups of actuators, and groups of sensors, with each group consisting of multiple redundant similar actuators or sensors. The types of actuator faults considered consist of unknown actuators stuck in unknown positions, as well as reduced actuator effectiveness. The sensor faults considered include unknown biases and outages. The approach employed for fault detection and estimation consists of a bank of Kalman filters based on multiple models, and subsequent control reconfiguration to mitigate the effect of biases caused by failed components as well as to obtain stability and satisfactory performance using the remaining actuators and sensors. Conditions for fault identifiability are presented, and the adaptive scheme is applied to an aircraft flight control example in the presence of actuator failures. Simulation results demonstrate that the method can rapidly and accurately detect faults and estimate the fault values, thus enabling safe operation and acceptable performance in spite of failures.

Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering.

PubMed

Guo, Xuan; Meng, Yu; Yu, Ning; Pan, Yi

2014-04-10

Taking the advantage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS.

Assessing Environmental Exposure to β-N-Methylamino-L-Alanine (BMAA) in Complex Sample Matrices: a Comparison of the Three Most Popular LC-MS/MS Methods.

PubMed

Baker, Teesha C; Tymm, Fiona J M; Murch, Susan J

2018-01-01

β-N-Methylamino-L-alanine (BMAA) is a naturally occurring non-protein amino acid produced by cyanobacteria, accumulated through natural food webs, found in mammalian brain tissues. Recent evidence indicates an association between BMAA and neurological disease. The accurate detection and quantification of BMAA in food and environmental samples are critical to understanding BMAA metabolism and limiting human exposure. To date, there have been more than 78 reports on BMAA in cyanobacteria and human samples, but different methods give conflicting data and divergent interpretations in the literature. The current work was designed to determine whether orthogonal chromatography and mass spectrometry methods give consistent data interpretation from a single sample matrix using the three most common analytical methods. The methods were recreated as precisely as possible from the literature with optimization of the mass spectrometry parameters specific to the instrument. Four sample matrices, cyanobacteria, human brain, blue crab, and Spirulina, were analyzed as 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) derivatives, propyl chloroformate (PCF) derivatives separated by reverse phase chromatography, or underivatized extracts separated by HILIC chromatography. The three methods agreed on positive detection of BMAA in cyanobacteria and no detected BMAA in the sample of human brain matrix. Interpretation was less clear for a sample of blue crab which was strongly positive for BMAA by AQC and PCF but negative by HILIC and for four spirulina raw materials that were negative by PCF but positive by AQC and HILIC. Together, these data demonstrate that the methods gave different results and that the choices in interpretation of the methods determined whether BMAA was detected. Failure to detect BMAA cannot be considered proof of absence.

Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering

PubMed Central

2014-01-01

Backgroud Taking the advan tage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. Results In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Conclusions Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS. PMID:24717145

Dental non-linear image registration and collection method with 3D reconstruction and change detection

NASA Astrophysics Data System (ADS)

Rahmes, Mark; Fagan, Dean; Lemieux, George

2017-03-01

The capability of a software algorithm to automatically align same-patient dental bitewing and panoramic x-rays over time is complicated by differences in collection perspectives. We successfully used image correlation with an affine transform for each pixel to discover common image borders, followed by a non-linear homography perspective adjustment to closely align the images. However, significant improvements in image registration could be realized if images were collected from the same perspective, thus facilitating change analysis. The perspective differences due to current dental image collection devices are so significant that straightforward change analysis is not possible. To address this, a new custom dental tray could be used to provide the standard reference needed for consistent positioning of a patient's mouth. Similar to sports mouth guards, the dental tray could be fabricated in standard sizes from plastic and use integrated electronics that have been miniaturized. In addition, the x-ray source needs to be consistently positioned in order to collect images with similar angles and scales. Solving this pose correction is similar to solving for collection angle in aerial imagery for change detection. A standard collection system would provide a method for consistent source positioning using real-time sensor position feedback from a digital x-ray image reference. Automated, robotic sensor positioning could replace manual adjustments. Given an image set from a standard collection, a disparity map between images can be created using parallax from overlapping viewpoints to enable change detection. This perspective data can be rectified and used to create a three-dimensional dental model reconstruction.

Augmenting Amyloid PET Interpretations With Quantitative Information Improves Consistency of Early Amyloid Detection.

PubMed

Harn, Nicholas R; Hunt, Suzanne L; Hill, Jacqueline; Vidoni, Eric; Perry, Mark; Burns, Jeffrey M

2017-08-01

Establishing reliable methods for interpreting elevated cerebral amyloid-β plaque on PET scans is increasingly important for radiologists, as availability of PET imaging in clinical practice increases. We examined a 3-step method to detect plaque in cognitively normal older adults, focusing on the additive value of quantitative information during the PET scan interpretation process. Fifty-five F-florbetapir PET scans were evaluated by 3 experienced raters. Scans were first visually interpreted as having "elevated" or "nonelevated" plaque burden ("Visual Read"). Images were then processed using a standardized quantitative analysis software (MIMneuro) to generate whole brain and region of interest SUV ratios. This "Quantitative Read" was considered elevated if at least 2 of 6 regions of interest had an SUV ratio of more than 1.1. The final interpretation combined both visual and quantitative data together ("VisQ Read"). Cohen kappa values were assessed as a measure of interpretation agreement. Plaque was elevated in 25.5% to 29.1% of the 165 total Visual Reads. Interrater agreement was strong (kappa = 0.73-0.82) and consistent with reported values. Quantitative Reads were elevated in 45.5% of participants. Final VisQ Reads changed from initial Visual Reads in 16 interpretations (9.7%), with most changing from "nonelevated" Visual Reads to "elevated." These changed interpretations demonstrated lower plaque quantification than those initially read as "elevated" that remained unchanged. Interrater variability improved for VisQ Reads with the addition of quantitative information (kappa = 0.88-0.96). Inclusion of quantitative information increases consistency of PET scan interpretations for early detection of cerebral amyloid-β plaque accumulation.

[Rapid detection of hot spot mutations of FGFR3 gene with PCR-high resolution melting assay].

PubMed

Li, Shan; Wang, Han; Su, Hua; Gao, Jinsong; Zhao, Xiuli

2017-08-10

To identify the causative mutations in five individuals affected with dyschondroplasia and develop an efficient procedure for detecting hot spot mutations of the FGFR3 gene. Genomic DNA was extracted from peripheral blood samples with a standard phenol/chloroform method. PCR-Sanger sequencing was used to analyze the causative mutations in the five probands. PCR-high resolution melting (HRM) was developed to detect the identified mutations. A c.1138G>A mutation in exon 8 was found in 4 probands, while a c.1620C>G mutation was found in exon 11 of proband 5 whom had a mild phenotype. All patients were successfully distinguished from healthy controls with the PCR-HRM method. The results of HRM analysis were highly consistent with that of Sanger sequencing. The Gly380Arg and Asn540Lys are hot spot mutations of the FGFR3 gene among patients with ACH/HCH. PCR-HRM analysis is more efficient for detecting hot spot mutations of the FGFR3 gene.

A new luminol chemiluminescence sensor for glucose based on pH-dependent graphene oxide.

PubMed

Hao, Minjia; Liu, Na; Ma, Zhanfang

2013-08-07

In this study, graphene oxide (GO) was found to catalyze the luminol-O2 reaction, which yielded a novel chemiluminescence (CL). Remarkably, the CL emission could be tuned by modulating the pH of the GO dispersion. Transmission electron microscopy, CL spectra, electron spin resonance spectra studies were carried out to investigate the CL mechanism. The results indicate that the CL emission was attributed to the intrinsic catalytic effect of GO acting as the radical generation proliferators and electron transfer accelerators. Based on the GO catalyzed luminol-O2 system, we successfully developed a new CL sensor to detect glucose. Under the optimized conditions, glucose could be assayed in the range of 0.05 mM to 5 mM with a detection limit of 0.044 mM. For the detection of clinical serum samples, it is well consistent with the data determined by commercially available method in hospital, indicating that the new CL method provides a possible application for the detection of glucose in clinical diagnostics.

Market analysis of food products for detection of allergenic walnut (Juglans regia) and pecan (Carya illinoinensis) by real-time PCR.

PubMed

López-Calleja, Inés María; de la Cruz, Silvia; González, Isabel; García, Teresa; Martín, Rosario

2015-06-15

Two real-time polymerase chain reaction (PCR)-based assays for detection of walnut (Juglans regia) and pecan (Carya illinoinensis) traces in a wide range of processed foods are described here. The method consists on a real-time PCR assay targeting the ITS1 region, using a nuclease (TaqMan) probe labeled with FAM and BBQ. The method was positive for walnut and pecan respectively, and negative for all other heterologous plants and animals tested. Using a series of model samples with defined raw walnut in wheat flour and heat-treated walnut in wheat flour with a range of concentrations of 0.1-100,000 mg kg(-1), a practical detection limit of 0.1 mg kg(-1) of walnut content was estimated. Identical binary mixtures were done for pecan, reaching the same limit of detection of 0.1 mg kg(-1). The assay was successfully trialed on a total of 232 commercial foodstuffs. Copyright © 2015 Elsevier Ltd. All rights reserved.

A correlation analysis-based detection and delineation of ECG characteristic events using template waveforms extracted by ensemble averaging of clustered heart cycles.

PubMed

Homaeinezhad, M R; Erfanianmoshiri-Nejad, M; Naseri, H

2014-01-01

The goal of this study is to introduce a simple, standard and safe procedure to detect and to delineate P and T waves of the electrocardiogram (ECG) signal in real conditions. The proposed method consists of four major steps: (1) a secure QRS detection and delineation algorithm, (2) a pattern recognition algorithm designed for distinguishing various ECG clusters which take place between consecutive R-waves, (3) extracting template of the dominant events of each cluster waveform and (4) application of the correlation analysis in order to delineate automatically the P- and T-waves in noisy conditions. The performance characteristics of the proposed P and T detection-delineation algorithm are evaluated versus various ECG signals whose qualities are altered from the best to the worst cases based on the random-walk noise theory. Also, the method is applied to the MIT-BIH Arrhythmia and the QT databases for comparing some parts of its performance characteristics with a number of P and T detection-delineation algorithms. The conducted evaluations indicate that in a signal with low quality value of about 0.6, the proposed method detects the P and T events with sensitivity Se=85% and positive predictive value of P+=89%, respectively. In addition, at the same quality, the average delineation errors associated with those ECG events are 45 and 63ms, respectively. Stable delineation error, high detection accuracy and high noise tolerance were the most important aspects considered during development of the proposed method. © 2013 Elsevier Ltd. All rights reserved.

Methods for Integrated Air Sampling and DNA Analysis for Detection of Airborne Fungal Spores

PubMed Central

Williams, Roger H.; Ward, Elaine; McCartney, H. Alastair

2001-01-01

Integrated air sampling and PCR-based methods for detecting airborne fungal spores, using Penicillium roqueforti as a model fungus, are described. P. roqueforti spores were collected directly into Eppendorf tubes using a miniature cyclone-type air sampler. They were then suspended in 0.1% Nonidet P-40, and counted using microscopy. Serial dilutions of the spores were made. Three methods were used to produce DNA for PCR tests: adding untreated spores to PCRs, disrupting spores (fracturing of spore walls to release the contents) using Ballotini beads, and disrupting spores followed by DNA purification. Three P. roqueforti-specific assays were tested: single-step PCR, nested PCR, and PCR followed by Southern blotting and probing. Disrupting the spores was found to be essential for achieving maximum sensitivity of the assay. Adding untreated spores to the PCR did allow the detection of P. roqueforti, but this was never achieved when fewer than 1,000 spores were added to the PCR. By disrupting the spores, with or without subsequent DNA purification, it was possible to detect DNA from a single spore. When known quantities of P. roqueforti spores were added to air samples consisting of high concentrations of unidentified fungal spores, pollen, and dust, detection sensitivity was reduced. P. roqueforti DNA could not be detected using untreated or disrupted spore suspensions added to the PCRs. However, using purified DNA, it was possible to detect 10 P. roqueforti spores in a background of 4,500 other spores. For all DNA extraction methods, nested PCR was more sensitive than single-step PCR or PCR followed by Southern blotting. PMID:11375150

Linking landscape characteristics to local grizzly bear abundance using multiple detection methods in a hierarchical model

USGS Publications Warehouse

Graves, T.A.; Kendall, Katherine C.; Royle, J. Andrew; Stetz, J.B.; Macleod, A.C.

2011-01-01

Few studies link habitat to grizzly bear Ursus arctos abundance and these have not accounted for the variation in detection or spatial autocorrelation. We collected and genotyped bear hair in and around Glacier National Park in northwestern Montana during the summer of 2000. We developed a hierarchical Markov chain Monte Carlo model that extends the existing occupancy and count models by accounting for (1) spatially explicit variables that we hypothesized might influence abundance; (2) separate sub-models of detection probability for two distinct sampling methods (hair traps and rub trees) targeting different segments of the population; (3) covariates to explain variation in each sub-model of detection; (4) a conditional autoregressive term to account for spatial autocorrelation; (5) weights to identify most important variables. Road density and per cent mesic habitat best explained variation in female grizzly bear abundance; spatial autocorrelation was not supported. More female bears were predicted in places with lower road density and with more mesic habitat. Detection rates of females increased with rub tree sampling effort. Road density best explained variation in male grizzly bear abundance and spatial autocorrelation was supported. More male bears were predicted in areas of low road density. Detection rates of males increased with rub tree and hair trap sampling effort and decreased over the sampling period. We provide a new method to (1) incorporate multiple detection methods into hierarchical models of abundance; (2) determine whether spatial autocorrelation should be included in final models. Our results suggest that the influence of landscape variables is consistent between habitat selection and abundance in this system.

In vitro interactions between splenocytes and dansylamide dye-embedded nanoparticles detected by flow cytometry

PubMed Central

Nyland, Jennifer F.; Bai, Jennifer J. K.; Katz, Howard E.; Silbergeld, Ellen K.

2009-01-01

Engineered nanoparticles (NPs) possess a range of biological activity. In vitro methods for assessing toxicity and efficacy would be enhanced by simultaneous quantitative information on the behavior of NPs in culture systems and signals of cell response. We have developed a method for visualizing NPs within cells using standard flow cytometric techniques and uniquely designed spherical siloxane NPs with an embedded (covalently bound) dansylamide dye. This method allowed NP visualization without obscuring detection of relevant biomarkers of cell subtype, activation state, and other events relevant to assessing bioactivity. We determined that NPs penetrated cells and induced a range of biological signals consistent with activation and costimulation. These results indicate that NPs may affect cell function at concentrations below those inducing cytotoxicity or apoptosis and demonstrate a novel method to image both localization of NPs and cell-level effects. PMID:19523425

Detecting Abrupt Changes in a Piecewise Locally Stationary Time Series

PubMed Central

Last, Michael; Shumway, Robert

2007-01-01

Non-stationary time series arise in many settings, such as seismology, speech-processing, and finance. In many of these settings we are interested in points where a model of local stationarity is violated. We consider the problem of how to detect these change-points, which we identify by finding sharp changes in the time-varying power spectrum. Several different methods are considered, and we find that the symmetrized Kullback-Leibler information discrimination performs best in simulation studies. We derive asymptotic normality of our test statistic, and consistency of estimated change-point locations. We then demonstrate the technique on the problem of detecting arrival phases in earthquakes. PMID:19190715

Ionospheric gravity wave measurements with the USU dynasonde

NASA Technical Reports Server (NTRS)

Berkey, Frank T.; Deng, Jun Yuan

1992-01-01

A method for the measurement of ionospheric Gravity Wave (GW) using the USU Dynasonde is outlined. This method consists of a series of individual procedures, which includes functions for data acquisition, adaptive scaling, polarization discrimination, interpolation and extrapolation, digital filtering, windowing, spectrum analysis, GW detection, and graphics display. Concepts of system theory are applied to treat the ionosphere as a system. An adaptive ionogram scaling method was developed for automatically extracting ionogram echo traces from noisy raw sounding data. The method uses the well known Least Mean Square (LMS) algorithm to form a stochastic optimal estimate of the echo trace which is then used to control a moving window. The window tracks the echo trace, simultaneously eliminating the noise and interference. Experimental results show that the proposed method functions as designed. Case studies which extract GW from ionosonde measurements were carried out using the techniques described. Geophysically significant events were detected and the resultant processed results are illustrated graphically. This method was also developed for real time implementation in mind.

Refining historical limits method to improve disease cluster detection, New York City, New York, USA.

PubMed

Levin-Rector, Alison; Wilson, Elisha L; Fine, Annie D; Greene, Sharon K

2015-02-01

Since the early 2000s, the Bureau of Communicable Disease of the New York City Department of Health and Mental Hygiene has analyzed reportable infectious disease data weekly by using the historical limits method to detect unusual clusters that could represent outbreaks. This method typically produced too many signals for each to be investigated with available resources while possibly failing to signal during true disease outbreaks. We made method refinements that improved the consistency of case inclusion criteria and accounted for data lags and trends and aberrations in historical data. During a 12-week period in 2013, we prospectively assessed these refinements using actual surveillance data. The refined method yielded 74 signals, a 45% decrease from what the original method would have produced. Fewer and less biased signals included a true citywide increase in legionellosis and a localized campylobacteriosis cluster subsequently linked to live-poultry markets. Future evaluations using simulated data could complement this descriptive assessment.

A combined experimental-modelling method for the detection and analysis of pollution in coastal zones

NASA Astrophysics Data System (ADS)

Limić, Nedzad; Valković, Vladivoj

1996-04-01

Pollution of coastal seas with toxic substances can be efficiently detected by examining toxic materials in sediment samples. These samples contain information on the overall pollution from surrounding sources such as yacht anchorages, nearby industries, sewage systems, etc. In an efficient analysis of pollution one must determine the contribution from each individual source. In this work it is demonstrated that a modelling method can be utilized for solving this latter problem. The modelling method is based on a unique interpretation of concentrations in sediments from all sampling stations. The proposed method is a synthesis consisting of the utilization of PIXE as an efficient method of pollution concentration determination and the code ANCOPOL (N. Limic and R. Benis, The computer code ANCOPOL, SimTel/msdos/geology, 1994 [1]) for the calculation of contributions from the main polluters. The efficiency and limits of the proposed method are demonstrated by discussing trace element concentrations in sediments of Punat Bay on the island of Krk in Croatia.

Simultaneous determination of eight water-soluble vitamins in supplemented foods by liquid chromatography.

PubMed

Zafra-Gómez, Alberto; Garballo, Antonio; Morales, Juan C; García-Ayuso, Luis E

2006-06-28

A fast, simple, and reliable method for the isolation and determination of the vitamins thiamin, riboflavin, niacin, pantothenic acid, pyridoxine, folic acid, cyanocobalamin, and ascorbic acid in food samples is proposed. The most relevant advantages of the proposed method are the simultaneous determination of the eight more common vitamins in enriched food products and a reduction of the time required for quantitative extraction, because the method consists merely of the addition of a precipitation solution and centrifugation of the sample. Furthermore, this method saves a substantial amount of reagents as compared with official methods, and minimal sample manipulation is achieved due to the few steps required. The chromatographic separation is carried out on a reverse phase C18 column, and the vitamins are detected at different wavelengths by either fluorescence or UV-visible detection. The proposed method was applied to the determination of water-soluble vitamins in supplemented milk, infant nutrition products, and milk powder certified reference material (CRM 421, BCR) with recoveries ranging from 90 to 100%.

Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation

PubMed Central

Broumandan, Ali; Lachapelle, Gérard

2018-01-01

Location information is one of the most vital information required to achieve intelligent and context-aware capability for various applications such as driverless cars. However, related security and privacy threats are a major holdback. With increasing focus on using Global Navigation Satellite Systems (GNSS) for autonomous navigation and related applications, it is important to provide robust navigation solutions, yet signal spoofing for illegal or covert transportation and misleading receiver timing is increasing and now frequent. Hence, detection and mitigation of spoofing attacks has become an important topic. Several contributions on spoofing detection have been made, focusing on different layers of a GNSS receiver. This paper focuses on spoofing detection utilizing self-contained sensors, namely inertial measurement units (IMUs) and vehicle odometer outputs. A spoofing detection approach based on a consistency check between GNSS and IMU/odometer mechanization is proposed. To detect a spoofing attack, the method analyses GNSS and IMU/odometer measurements independently during a pre-selected observation window and cross checks the solutions provided by GNSS and inertial navigation solution (INS)/odometer mechanization. The performance of the proposed method is verified in real vehicular environments. Mean spoofing detection time and detection performance in terms of receiver operation characteristics (ROC) in sub-urban and dense urban environments are evaluated. PMID:29695064

Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation.

PubMed

Broumandan, Ali; Lachapelle, Gérard

2018-04-24

Location information is one of the most vital information required to achieve intelligent and context-aware capability for various applications such as driverless cars. However, related security and privacy threats are a major holdback. With increasing focus on using Global Navigation Satellite Systems (GNSS) for autonomous navigation and related applications, it is important to provide robust navigation solutions, yet signal spoofing for illegal or covert transportation and misleading receiver timing is increasing and now frequent. Hence, detection and mitigation of spoofing attacks has become an important topic. Several contributions on spoofing detection have been made, focusing on different layers of a GNSS receiver. This paper focuses on spoofing detection utilizing self-contained sensors, namely inertial measurement units (IMUs) and vehicle odometer outputs. A spoofing detection approach based on a consistency check between GNSS and IMU/odometer mechanization is proposed. To detect a spoofing attack, the method analyses GNSS and IMU/odometer measurements independently during a pre-selected observation window and cross checks the solutions provided by GNSS and inertial navigation solution (INS)/odometer mechanization. The performance of the proposed method is verified in real vehicular environments. Mean spoofing detection time and detection performance in terms of receiver operation characteristics (ROC) in sub-urban and dense urban environments are evaluated.

Method for combined biometric and chemical analysis of human fingerprints.

PubMed

Staymates, Jessica L; Orandi, Shahram; Staymates, Matthew E; Gillen, Greg

This paper describes a method for combining direct chemical analysis of latent fingerprints with subsequent biometric analysis within a single sample. The method described here uses ion mobility spectrometry (IMS) as a chemical detection method for explosives and narcotics trace contamination. A collection swab coated with a high-temperature adhesive has been developed to lift latent fingerprints from various surfaces. The swab is then directly inserted into an IMS instrument for a quick chemical analysis. After the IMS analysis, the lifted print remains intact for subsequent biometric scanning and analysis using matching algorithms. Several samples of explosive-laden fingerprints were successfully lifted and the explosives detected with IMS. Following explosive detection, the lifted fingerprints remained of sufficient quality for positive match scores using a prepared gallery consisting of 60 fingerprints. Based on our results ( n  = 1200), there was no significant decrease in the quality of the lifted print post IMS analysis. In fact, for a small subset of lifted prints, the quality was improved after IMS analysis. The described method can be readily applied to domestic criminal investigations, transportation security, terrorist and bombing threats, and military in-theatre settings.

Rapid and sensitive detection of Zika virus by reverse transcription loop-mediated isothermal amplification.

PubMed

Wang, Xuan; Yin, Fenggui; Bi, Yuhai; Cheng, Gong; Li, Jing; Hou, Lidan; Li, Yunlong; Yang, Baozhi; Liu, Wenjun; Yang, Limin

2016-12-01

Zika virus (ZIKV) is an arbovirus that recently emerged and has expanded worldwide, causing a global threat and raising international concerns. Current molecular diagnostics, e.g., real-time PCR and reverse transcription PCR (RT-PCR), are time consuming, expensive, and can only be deployed in a laboratory instead of for field diagnostics. This study aimed to develop a one-step reverse transcription loop-mediated isothermal amplification (RT-LAMP) platform showing sensitivity, specificity, and more convenience than previous methods, being easily distributed and implemented. Specific primers were designed and screened to target the entire ZIKV genome. The analytical sensitivity and specificity of the assay were evaluated and compared with traditional PCR and quantitative real-time PCR. Three different simulated clinical sample quick preparation protocols were evaluated to establish a rapid and straightforward treatment procedure for clinical specimens in open field detection. The RT-LAMP assay for detection of ZIKV demonstrated superior specificity and sensitivity compared to traditional PCR at the optimum reaction temperature. For the ZIKV RNA standard, the limit of detection was 20 copies/test. For the simulated ZIKV clinical samples, the limit of detection was 0.02 pfu/test, which was one order of magnitude higher than RT-PCR and similar to real-time PCR. The detection limit of simulated ZIKV specimens prepared using a protease quick processing method was consistent with that of samples prepared using commercial nucleic acid extraction kits, indicating that our ZIKV detection method could be used in point-of-care testing. The RT-LAMP assay had excellent sensitivity and specificity for detecting ZIKV and can be deployed together with a rapid specimen processing method, offering the possibility for ZIKV diagnosis outside of the laboratory. Copyright © 2016 Elsevier B.V. All rights reserved.

Noninvasive detection of macular pigments in the human eye.

PubMed

Gellermann, Werner; Bernstein, Paul S

2004-01-01

There is currently strong interest in developing noninvasive technologies for the detection of macular carotenoid pigments in the human eye. These pigments, consisting of lutein and zeaxanthin, are taken up from the diet and are thought to play an important role in the prevention of age-related macular degeneration, the leading cause of blindness in the elderly in the Western world. It may be possible to prevent or delay the onset of this debilitating disease with suitable dietary intervention strategies. We review the most commonly used detection techniques based on heterochromatic flicker photometry, fundus reflectometry, and autofluorescense techniques and put them in perspective with recently developed more molecule-specific Raman detection methods. (c) 2004 Society of Photo-Optical Instrumentation Engineers.

Hierarchical detection of red lesions in retinal images by multiscale correlation filtering

NASA Astrophysics Data System (ADS)

Zhang, Bob; Wu, Xiangqian; You, Jane; Li, Qin; Karray, Fakhri

2009-02-01

This paper presents an approach to the computer aided diagnosis (CAD) of diabetic retinopathy (DR) -- a common and severe complication of long-term diabetes which damages the retina and cause blindness. Since red lesions are regarded as the first signs of DR, there has been extensive research on effective detection and localization of these abnormalities in retinal images. In contrast to existing algorithms, a new approach based on Multiscale Correlation Filtering (MSCF) and dynamic thresholding is developed. This consists of two levels, Red Lesion Candidate Detection (coarse level) and True Red Lesion Detection (fine level). The approach was evaluated using data from Retinopathy On-line Challenge (ROC) competition website and we conclude our method to be effective and efficient.

Rhythm-based heartbeat duration normalization for atrial fibrillation detection.

PubMed

Islam, Md Saiful; Ammour, Nassim; Alajlan, Naif; Aboalsamh, Hatim

2016-05-01

Screening of atrial fibrillation (AF) for high-risk patients including all patients aged 65 years and older is important for prevention of risk of stroke. Different technologies such as modified blood pressure monitor, single lead ECG-based finger-probe, and smart phone using plethysmogram signal have been emerging for this purpose. All these technologies use irregularity of heartbeat duration as a feature for AF detection. We have investigated a normalization method of heartbeat duration for improved AF detection. AF is an arrhythmia in which heartbeat duration generally becomes irregularly irregular. From a window of heartbeat duration, we estimate the possible rhythm of the majority of heartbeats and normalize duration of all heartbeats in the window based on the rhythm so that we can measure the irregularity of heartbeats for both AF and non-AF rhythms in the same scale. Irregularity is measured by the entropy of distribution of the normalized duration. Then we classify a window of heartbeats as AF or non-AF by thresholding the measured irregularity. The effect of this normalization is evaluated by comparing AF detection performances using duration with the normalization, without normalization, and with other existing normalizations. Sensitivity and specificity of AF detection using normalized heartbeat duration were tested on two landmark databases available online and compared with results of other methods (with/without normalization) by receiver operating characteristic (ROC) curves. ROC analysis showed that the normalization was able to improve the performance of AF detection and it was consistent for a wide range of sensitivity and specificity for use of different thresholds. Detection accuracy was also computed for equal rates of sensitivity and specificity for different methods. Using normalized heartbeat duration, we obtained 96.38% accuracy which is more than 4% improvement compared to AF detection without normalization. The proposed normalization method was found useful for improving performance and robustness of AF detection. Incorporation of this method in a screening device could be crucial to reduce the risk of AF-related stroke. In general, the incorporation of the rhythm-based normalization in an AF detection method seems important for developing a robust AF screening device. Copyright © 2016 Elsevier Ltd. All rights reserved.

Line Transect Surveys Underdetect Terrestrial Mammals: Implications for the Sustainability of Subsistence Hunting

PubMed Central

Levi, Taal; Oliveira, Luiz F. B.; Luzar, Jeffrey B.; Overman, Han; Read, Jane M.

2016-01-01

Conservation of Neotropical game species must take into account the livelihood and food security needs of local human populations. Hunting management decisions should therefore rely on abundance and distribution data that are as representative as possible of true population sizes and dynamics. We simultaneously applied a commonly used encounter-based method and an infrequently used sign-based method to estimate hunted vertebrate abundance in a 48,000-km2 indigenous landscape in southern Guyana. Diurnal direct encounter data collected during three years along 216, four-kilometer -long transects consistently under-detected many diurnal and nocturnal mammal species readily detected through sign. Of 32 species analyzed, 31 were detected by both methods; however, encounters did not detect one and under-detected another 12 of the most heavily hunted species relative to sign, while sign under-detected 12 never or rarely collected species relative to encounters. The six most important game animals in the region, all ungulates, were not encountered at 11–40% of village and control sites or on 29–72% of transects where they were detected by sign. Using the sign methodology, we find that tapirs, one of the terrestrial vertebrates considered most sensitive to overexploitation, are present at many sites where they were never visually detected during distance sampling. We find that this is true for many other species as well. These high rates of under-detection suggest that behavioral changes in hunted populations may affect apparent occurrence and abundance of these populations. Accumulation curves (detection of species on transects) were much steeper for sign for 12 of 16 hunted species than for encounters, but that pattern was reversed for 12 of 16 species unhunted in our area. We conclude that collection of sign data is an efficient and effective method of monitoring hunted vertebrate populations that complements encounter and camera-trapping methods in areas impacted by hunting. Sign surveys may be the most viable method for large-scale, management-oriented studies in remote areas, particularly those focused on community-based wildlife management. PMID:27074025

Detection of goal events in soccer videos

NASA Astrophysics Data System (ADS)

Kim, Hyoung-Gook; Roeber, Steffen; Samour, Amjad; Sikora, Thomas

2005-01-01

In this paper, we present an automatic extraction of goal events in soccer videos by using audio track features alone without relying on expensive-to-compute video track features. The extracted goal events can be used for high-level indexing and selective browsing of soccer videos. The detection of soccer video highlights using audio contents comprises three steps: 1) extraction of audio features from a video sequence, 2) event candidate detection of highlight events based on the information provided by the feature extraction Methods and the Hidden Markov Model (HMM), 3) goal event selection to finally determine the video intervals to be included in the summary. For this purpose we compared the performance of the well known Mel-scale Frequency Cepstral Coefficients (MFCC) feature extraction method vs. MPEG-7 Audio Spectrum Projection feature (ASP) extraction method based on three different decomposition methods namely Principal Component Analysis( PCA), Independent Component Analysis (ICA) and Non-Negative Matrix Factorization (NMF). To evaluate our system we collected five soccer game videos from various sources. In total we have seven hours of soccer games consisting of eight gigabytes of data. One of five soccer games is used as the training data (e.g., announcers' excited speech, audience ambient speech noise, audience clapping, environmental sounds). Our goal event detection results are encouraging.

Determination of moclobemide in human plasma by high-performance liquid chromatography with spectrophotometric detection.

PubMed

Amini, Hossein; Shahmir, Badri; Ahmadiani, Abolhassan

2004-08-05

A simple and sensitive high-performance liquid chromatographic (HPLC) method with spectrophotometric detection was developed for the determination of moclobemide in human plasma. Plasma samples were extracted under basic conditions with dichloromethane followed by back-extraction into diluted phosphoric acid. Isocratic separation was employed on an ODS column (250 mm x 4.6 mm, 5 microm) at room temperature. The mobile phase consisted of 5 mM NaH2PO4-acetonitrile-triethylamine (1000:350:10 (v/v/v), pH 3.4). Analyses were run at a flow-rate of 1.0 ml/min and ultraviolet (UV) detection was carried out at 240 nm. The method was specific and sensitive with a quantification limit of 15.6 ng/ml and a detection limit of 5 ng/ml at a signal-to-noise ratio of 3:1. The mean absolute recovery was about 98.2%, while the intra- and inter-day coefficient of variation and percent error values of the assay method were all at acceptable levels. Linearity was assessed in the range of 15.6-2000 ng/ml in plasma with a correlation coefficient of greater than 0.999. This method has been used to analyze several hundred human plasma samples for bioavailibility studies.

An in vitro study to find the incidence of mesiobuccal 2 canal in permanent maxillary first molars using three different methods.

PubMed

Vasundhara, V; Lashkari, Krishna Prasada

2017-01-01

In-vitro study was done to evaluate the incidence of MB2 canals using three different methods (CBCT, CLINICAL ANALYSIS AND DENTAL LOUPES) and to compare the efficacy of the three methods in identifying the incidence of MB2 canals in maxillary permanent first molars. The study sample consisted of 120 extracted intact permanent maxillary molars. These extracted teeth were subjected to CBCT. Later the teeth were access opened with naked eye to find the incidence of MB2 canal, and then the teeth were visualised under dental loupe to locate MB2 canal if they were missed under naked eye. Results was statistically analysed by Mc Nemar's tests with Bonferroni correction, Chi square test and Cochran's Q test. CBCT showed high incidence (68.3%) of MB2 canal in maxillary first molars and it showed to be a reliable method in detecting MB2 canal. When compared to dental loupe (52.5%) and naked eye (25%), the dental loupe improved the detection of MB2 canal. Within the parameter of this study in detecting the incidence of MB2 canal, using CBCT dental loupes and naked eye, detection of MB2 canal was significantly higher with CBCT followed by dental loupe and least with naked eye.

Quantifying spatial and temporal trends in beach-dune volumetric changes using spatial statistics

NASA Astrophysics Data System (ADS)

Eamer, Jordan B. R.; Walker, Ian J.

2013-06-01

Spatial statistics are generally underutilized in coastal geomorphology, despite offering great potential for identifying and quantifying spatial-temporal trends in landscape morphodynamics. In particular, local Moran's Ii provides a statistical framework for detecting clusters of significant change in an attribute (e.g., surface erosion or deposition) and quantifying how this changes over space and time. This study analyzes and interprets spatial-temporal patterns in sediment volume changes in a beach-foredune-transgressive dune complex following removal of invasive marram grass (Ammophila spp.). Results are derived by detecting significant changes in post-removal repeat DEMs derived from topographic surveys and airborne LiDAR. The study site was separated into discrete, linked geomorphic units (beach, foredune, transgressive dune complex) to facilitate sub-landscape scale analysis of volumetric change and sediment budget responses. Difference surfaces derived from a pixel-subtraction algorithm between interval DEMs and the LiDAR baseline DEM were filtered using the local Moran's Ii method and two different spatial weights (1.5 and 5 m) to detect statistically significant change. Moran's Ii results were compared with those derived from a more spatially uniform statistical method that uses a simpler student's t distribution threshold for change detection. Morphodynamic patterns and volumetric estimates were similar between the uniform geostatistical method and Moran's Ii at a spatial weight of 5 m while the smaller spatial weight (1.5 m) consistently indicated volumetric changes of less magnitude. The larger 5 m spatial weight was most representative of broader site morphodynamics and spatial patterns while the smaller spatial weight provided volumetric changes consistent with field observations. All methods showed foredune deflation immediately following removal with increased sediment volumes into the spring via deposition at the crest and on lobes in the lee, despite erosion on the stoss slope and dune toe. Generally, the foredune became wider by landward extension and the seaward slope recovered from erosion to a similar height and form to that of pre-restoration despite remaining essentially free of vegetation.

High-sensitivity assay for monitoring ESR1 mutations in circulating cell-free DNA of breast cancer patients receiving endocrine therapy.

PubMed

Lupini, Laura; Moretti, Anna; Bassi, Cristian; Schirone, Alessio; Pedriali, Massimo; Querzoli, Patrizia; Roncarati, Roberta; Frassoldati, Antonio; Negrini, Massimo

2018-03-12

Approximately 70% of breast cancers (BCs) express estrogen receptor alpha (ERα) and are treated with endocrine therapy. However, the effectiveness of this therapy is limited by innate or acquired resistance in approximately one-third of patients. Activating mutations in the ESR1 gene that encodes ERα promote critical resistance mechanisms. Here, we developed a high sensitivity approach based on enhanced-ice-COLD-PCR for detecting ESR1 mutations. The method produced an enrichment up to 100-fold and allowed the unambiguous detection of ESR1 mutations even when they consisted of only 0.01% of the total ESR1 allelic fraction. After COLD-PCR enrichment, methods based on next-generation sequencing or droplet-digital PCR were employed to detect and quantify ESR1 mutations. We applied the method to detect ESR1 mutations in circulating free DNA from the plasma of 56 patients with metastatic ER-positive BC. Fifteen of these patients were found to have ESR1 mutations at codons 536-538. This study demonstrates the utility of the enhanced-ice-COLD-PCR approach for simplifying and improving the detection of ESR1 tumor mutations in liquid biopsies. Because of its high sensitivity, the approach may potentially be applicable to patients with non-metastatic disease.

Long-term object tracking combined offline with online learning

NASA Astrophysics Data System (ADS)

Hu, Mengjie; Wei, Zhenzhong; Zhang, Guangjun

2016-04-01

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

Rapid and sensitive detection of mink circovirus by recombinase polymerase amplification.

PubMed

Ge, Junwei; Shi, Yunjia; Cui, Xingyang; Gu, Shanshan; Zhao, Lili; Chen, Hongyan

2018-06-01

To date, the pathogenic role of mink circovirus (MiCV) remains unclear, and its prevalence and economic importance are unknown. Therefore, a rapid and sensitive molecular diagnosis is necessary for disease management and epidemiological surveillance. However, only PCR methods can identify MiCV infection at present. In this study, we developed a nested PCR and established a novel recombinase polymerase amplification (RPA) assay for MiCV detection. Sensitivity analysis showed that the detection limit of nested PCR and RPA assay was 10 1 copies/reaction, and these methods were more sensitive than conventional PCR, which has a detection limit of 10 5 copies/reaction. The RPA assay had no cross-reactivity with other related viral pathogens, and amplification was completed in less than 20 min with a simple device. Further assessment of clinical samples showed that the two assays were accurate in identifying positive and negative conventional PCR samples. The detection rate of MiCV by the RPA assay in clinical samples was 38.09%, which was 97% consistent with that by the nested PCR. The developed nested PCR is a highly sensitive tool for practical use, and the RPA assay is a simple, sensitive, and potential alternative method for rapid and accurate MiCV diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Psychotropics and weak opioid analgesics in plasma samples of older hip fracture patients - detection frequencies and consistency with drug records.

PubMed

Waade, Ragnhild Birkeland; Molden, Espen; Martinsen, Mette Irene; Hermann, Monica; Ranhoff, Anette Hylen

2017-07-01

To determine use of psychotropic drugs and weak opioids in hip fracture patients by analysing plasma samples at admission, and compare detected drug frequencies with prescription registry data and drug records. Plasma from 250 hip fracture patients aged ≥65 years sampled at hospital admission were analysed by ultra-performance liquid chromatography-tandem mass spectrometry methods for detection of psychotropic drugs and weak opioid analgesics (alcohol also determined). Odds ratios for drugs detected in plasma of hip fracture patients vs. prescription frequencies of the same drugs in an age-, time- and region-matched reference population were calculated. Moreover, recorded and measured drugs were compared. Psychotropic drugs and/or weak opioid analgesics were detected in 158 (63%) of the patients (median age 84 years; 76% females), while alcohol was found in 19 patients (7.6%). The occurrence of diazepam (odds ratio 1.6; 95% confidence interval 1.1-2.4), nitrazepam (2.3; 1.3-4.1), selective serotonin reuptake inhibitors (1.9; 1.3-2.9) and mirtazapine (2.3; 1.2-4.3) was significantly higher in plasma samples of hip fracture patients than in prescription data from the reference population. Poor consistency between recorded and measured drugs was disclosed for z-hypnotics and benzodiazepines; e.g. diazepam was detected in 29 (11.6%), but only recorded in six (2.4%) of the patients. Plasma analysis shows that use of antidepressants and benzodiazepines in hip fracture patients is significantly more frequent than respective prescription frequencies in the general elderly population. Moreover, consistency between recorded and actual use of psychotropic fall-risk drugs is poor at hospital admission of hip fracture patients. © 2017 The British Pharmacological Society.

Variability-selected active galactic nuclei from supernova search in the Chandra deep field south

NASA Astrophysics Data System (ADS)

Trevese, D.; Boutsia, K.; Vagnetti, F.; Cappellaro, E.; Puccetti, S.

2008-09-01

Context: Variability is a property shared by virtually all active galactic nuclei (AGNs), and was adopted as a criterion for their selection using data from multi epoch surveys. Low Luminosity AGNs (LLAGNs) are contaminated by the light of their host galaxies, and cannot therefore be detected by the usual colour techniques. For this reason, their evolution in cosmic time is poorly known. Consistency with the evolution derived from X-ray detected samples has not been clearly established so far, also because the low luminosity population consists of a mixture of different object types. LLAGNs can be detected by the nuclear optical variability of extended objects. Aims: Several variability surveys have been, or are being, conducted for the detection of supernovae (SNe). We propose to re-analyse these SNe data using a variability criterion optimised for AGN detection, to select a new AGN sample and study its properties. Methods: We analysed images acquired with the wide field imager at the 2.2 m ESO/MPI telescope, in the framework of the STRESS supernova survey. We selected the AXAF field centred on the Chandra Deep Field South where, besides the deep X-ray survey, various optical data exist, originating in the EIS and COMBO-17 photometric surveys and the spectroscopic database of GOODS. Results: We obtained a catalogue of 132 variable AGN candidates. Several of the candidates are X-ray sources. We compare our results with an HST variability study of X-ray and IR detected AGNs, finding consistent results. The relatively high fraction of confirmed AGNs in our sample (60%) allowed us to extract a list of reliable AGN candidates for spectroscopic follow-up observations. Table [see full text] is only available in electronic form at http://www.aanda.org

Multitarget detection algorithm for automotive FMCW radar

NASA Astrophysics Data System (ADS)

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

2012-06-01

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

High speed radiation scanning technique for simultaneously determining the pitch and eccentricity of an encased oil

DOEpatents

Foster, Billy E.

1976-01-01

A method of determining the pitch and eccentricity of the winding of a coil unit is provided. It specifically relates to nondestructively examining completely encased heating coils used to simulate the heat generated from fuel rods in reactor studies. The method comprises (1) the use of an x-ray transmission technique through the axial centerline of the coil unit after the winding of the coil unit has been completely encased, (2) the use of a radiation detection instrument to monitor the transmitted radiation, and (3) the use of recording instrumentation calibrated as a function of the distance between windings. A change in the pitch of the winding is detected by a general increase or decrease in the distance between recorded peaks of the transmitted radiation. Eccentricity is detected by a consistent variation in distance between peaks occuring in alternate pairs.

Application of NIR Raman spectroscopy for detecting and characterizing early dental caries

NASA Astrophysics Data System (ADS)

Ko, A. C.; Choo-Smith, L.-P.; Zhu, R.; Hewko, M.; Dong, C.; Cleghorn, B.; Sowa, M. G.

2006-02-01

Early dental caries detection facilitates implementation of non-surgical methods for arresting caries progression and promoting tooth remineralization. We present a method based on Raman spectroscopy with near-IR laser excitation to provide biochemical contrast for detecting and characterizing incipient carious lesions found in extracted human teeth. Changes in Raman spectra are observed in PO 4 3- vibrations arising from hydroxyapatite of mineralized tooth tissue. Examination of various intensities of the PO 4 3- ν2, ν3, ν4 vibrations showed consistent increased intensities in spectra of carious lesions compared to sound enamel. The spectral changes are attributed to demineralization-induced alterations of enamel crystallite morphology and/or orientation. This hypothesis is supported by reduced Raman polarization anisotropy derived from polarized Raman spectra of carious lesions. Polarized Raman spectral imaging of carious lesions found on whole (i.e. un-sectioned) tooth samples will also be presented.

A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm

PubMed Central

Zhu, Bohui; Ding, Yongsheng; Hao, Kuangrong

2013-01-01

This paper presents a novel maximum margin clustering method with immune evolution (IEMMC) for automatic diagnosis of electrocardiogram (ECG) arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the ECG signal is detected; then, features are extracted from ECG signal to cluster different types of arrhythmias by the IEMMC algorithm. Three types of performance evaluation indicators are used to assess the effect of the IEMMC method for ECG arrhythmias, such as sensitivity, specificity, and accuracy. Compared with K-means and iterSVR algorithms, the IEMMC algorithm reflects better performance not only in clustering result but also in terms of global search ability and convergence ability, which proves its effectiveness for the detection of ECG arrhythmias. PMID:23690875

Automatic textual annotation of video news based on semantic visual object extraction

NASA Astrophysics Data System (ADS)

Boujemaa, Nozha; Fleuret, Francois; Gouet, Valerie; Sahbi, Hichem

2003-12-01

In this paper, we present our work for automatic generation of textual metadata based on visual content analysis of video news. We present two methods for semantic object detection and recognition from a cross modal image-text thesaurus. These thesaurus represent a supervised association between models and semantic labels. This paper is concerned with two semantic objects: faces and Tv logos. In the first part, we present our work for efficient face detection and recogniton with automatic name generation. This method allows us also to suggest the textual annotation of shots close-up estimation. On the other hand, we were interested to automatically detect and recognize different Tv logos present on incoming different news from different Tv Channels. This work was done jointly with the French Tv Channel TF1 within the "MediaWorks" project that consists on an hybrid text-image indexing and retrieval plateform for video news.

Vision-based surface defect inspection for thick steel plates

NASA Astrophysics Data System (ADS)

Yun, Jong Pil; Kim, Dongseob; Kim, KyuHwan; Lee, Sang Jun; Park, Chang Hyun; Kim, Sang Woo

2017-05-01

There are several types of steel products, such as wire rods, cold-rolled coils, hot-rolled coils, thick plates, and electrical sheets. Surface stains on cold-rolled coils are considered defects. However, surface stains on thick plates are not considered defects. A conventional optical structure is composed of a camera and lighting module. A defect inspection system that uses a dual lighting structure to distinguish uneven defects and color changes by surface noise is proposed. In addition, an image processing algorithm that can be used to detect defects is presented in this paper. The algorithm consists of a Gabor filter that detects the switching pattern and employs the binarization method to extract the shape of the defect. The optics module and detection algorithm optimized using a simulator were installed at a real plant, and the experimental results conducted on thick steel plate images obtained from the steel production line show the effectiveness of the proposed method.

Visual Inspection of Water Leakage from Ground Penetrating Radar Radargram

NASA Astrophysics Data System (ADS)

Halimshah, N. N.; Yusup, A.; Mat Amin, Z.; Ghazalli, M. D.

2015-10-01

Water loss in town and suburban is currently a significant issue which reflect the performance of water supply management in Malaysia. Consequently, water supply distribution system has to be maintained in order to prevent shortage of water supply in an area. Various techniques for detecting a mains water leaks are available but mostly are time-consuming, disruptive and expensive. In this paper, the potential of Ground Penetrating Radar (GPR) as a non-destructive method to correctly and efficiently detect mains water leaks has been examined. Several experiments were designed and conducted to prove that GPR can be used as tool for water leakage detection. These include instrument validation test and soil compaction test to clarify the maximum dry density (MDD) of soil and simulation studies on water leakage at a test bed consisting of PVC pipe burying in sand to a depth of 40 cm. Data from GPR detection are processed using the Reflex 2D software. Identification of water leakage was visually inspected from the anomalies in the radargram based on GPR reflection coefficients. The results have ascertained the capability and effectiveness of the GPR in detecting water leakage which could help avoiding difficulties with other leak detection methods.

Quantile regression for the statistical analysis of immunological data with many non-detects.

PubMed

Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

2012-07-07

Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

A Field-Based Cleaning Protocol for Sampling Devices Used in Life-Detection Studies

NASA Astrophysics Data System (ADS)

Eigenbrode, Jennifer; Benning, Liane G.; Maule, Jake; Wainwright, Norm; Steele, Andrew; Amundsen, Hans E. F.

2009-06-01

Analytical approaches to extant and extinct life detection involve molecular detection often at trace levels. Thus, removal of biological materials and other organic molecules from the surfaces of devices used for sampling is essential for ascertaining meaningful results. Organic decontamination to levels consistent with null values on life-detection instruments is particularly challenging at remote field locations where Mars analog field investigations are carried out. Here, we present a seven-step, multi-reagent decontamination method that can be applied to sampling devices while in the field. In situ lipopolysaccharide detection via low-level endotoxin assays and molecular detection via gas chromatography-mass spectrometry were used to test the effectiveness of the decontamination protocol for sampling of glacial ice with a coring device and for sampling of sediments with a rover scoop during deployment at Arctic Mars-analog sites in Svalbard, Norway. Our results indicate that the protocols and detection technique sufficiently remove and detect low levels of molecular constituents necessary for life-detection tests.

A field-based cleaning protocol for sampling devices used in life-detection studies.

PubMed

Eigenbrode, Jennifer; Benning, Liane G; Maule, Jake; Wainwright, Norm; Steele, Andrew; Amundsen, Hans E F

2009-06-01

Analytical approaches to extant and extinct life detection involve molecular detection often at trace levels. Thus, removal of biological materials and other organic molecules from the surfaces of devices used for sampling is essential for ascertaining meaningful results. Organic decontamination to levels consistent with null values on life-detection instruments is particularly challenging at remote field locations where Mars analog field investigations are carried out. Here, we present a seven-step, multi-reagent decontamination method that can be applied to sampling devices while in the field. In situ lipopolysaccharide detection via low-level endotoxin assays and molecular detection via gas chromatography-mass spectrometry were used to test the effectiveness of the decontamination protocol for sampling of glacial ice with a coring device and for sampling of sediments with a rover scoop during deployment at Arctic Mars-analog sites in Svalbard, Norway. Our results indicate that the protocols and detection technique sufficiently remove and detect low levels of molecular constituents necessary for life-detection tests.

A Note on Three Statistical Tests in the Logistic Regression DIF Procedure

ERIC Educational Resources Information Center

Paek, Insu

2012-01-01

Although logistic regression became one of the well-known methods in detecting differential item functioning (DIF), its three statistical tests, the Wald, likelihood ratio (LR), and score tests, which are readily available under the maximum likelihood, do not seem to be consistently distinguished in DIF literature. This paper provides a clarifying…

75 FR 33317 - Request for Information (RFI) on the National Institutes of Health Plan To Develop the Genetic...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-11

... consistent with recommendations of the HHS Secretary's Advisory Committee on Genetics, Health, and Society... molecular basis, including, for example, information about what the test detects and what methods the test... and providing information on the molecular basis of genetic tests, such as detailed information about...

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.

Topic detection using paragraph vectors to support active learning in systematic reviews.

PubMed

Hashimoto, Kazuma; Kontonatsios, Georgios; Miwa, Makoto; Ananiadou, Sophia

2016-08-01

Systematic reviews require expert reviewers to manually screen thousands of citations in order to identify all relevant articles to the review. Active learning text classification is a supervised machine learning approach that has been shown to significantly reduce the manual annotation workload by semi-automating the citation screening process of systematic reviews. In this paper, we present a new topic detection method that induces an informative representation of studies, to improve the performance of the underlying active learner. Our proposed topic detection method uses a neural network-based vector space model to capture semantic similarities between documents. We firstly represent documents within the vector space, and cluster the documents into a predefined number of clusters. The centroids of the clusters are treated as latent topics. We then represent each document as a mixture of latent topics. For evaluation purposes, we employ the active learning strategy using both our novel topic detection method and a baseline topic model (i.e., Latent Dirichlet Allocation). Results obtained demonstrate that our method is able to achieve a high sensitivity of eligible studies and a significantly reduced manual annotation cost when compared to the baseline method. This observation is consistent across two clinical and three public health reviews. The tool introduced in this work is available from https://nactem.ac.uk/pvtopic/. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Fuzzy-logic detection and probability of hail exploiting short-range X-band weather radar

NASA Astrophysics Data System (ADS)

Capozzi, Vincenzo; Picciotti, Errico; Mazzarella, Vincenzo; Marzano, Frank Silvio; Budillon, Giorgio

2018-03-01

This work proposes a new method for hail precipitation detection and probability, based on single-polarization X-band radar measurements. Using a dataset consisting of reflectivity volumes, ground truth observations and atmospheric sounding data, a probability of hail index, which provides a simple estimate of the hail potential, has been trained and adapted within Naples metropolitan environment study area. The probability of hail has been calculated starting by four different hail detection methods. The first two, based on (1) reflectivity data and temperature measurements and (2) on vertically-integrated liquid density product, respectively, have been selected from the available literature. The other two techniques are based on combined criteria of the above mentioned methods: the first one (3) is based on the linear discriminant analysis, whereas the other one (4) relies on the fuzzy-logic approach. The latter is an innovative criterion based on a fuzzyfication step performed through ramp membership functions. The performances of the four methods have been tested using an independent dataset: the results highlight that the fuzzy-oriented combined method performs slightly better in terms of false alarm ratio, critical success index and area under the relative operating characteristic. An example of application of the proposed hail detection and probability products is also presented for a relevant hail event, occurred on 21 July 2014.

Comparison of ZetaPlus 60S and nitrocellulose membrane filters for the simultaneous concentration of F-RNA coliphages, porcine teschovirus and porcine adenovirus from river water.

PubMed

Jones, T H; Muehlhauser, V; Thériault, G

2014-09-01

Increasing attention is being paid to the impact of agricultural activities on water quality to understand the impact on public health. F-RNA coliphages have been proposed as viral indicators of fecal contamination while porcine teschovirus (PTV) and porcine adenovirus (PAdV) are proposed indicators of fecal contamination of swine origin. Viruses and coliphages are present in water in very low concentrations and must be concentrated to permit their detection. There is little information comparing the effectiveness of the methods for concentrating F-RNA coliphages with concentration methods for other viruses and vice versa. The objective of this study was to compare 5 current published methods for recovering F-RNA coliphages, PTV and PAdV from river water samples concentrated by electronegative nitrocellulose membrane filters (methods A and B) or electropositive Zeta Plus 60S filters (methods C-E). Method A is used routinely for the detection of coliphages (Méndez et al., 2004) and method C (Brassard et al., 2005) is the official method in Health Canada's compendium for the detection of viruses in bottled mineral or spring water. When river water was inoculated with stocks of F-RNA MS2, PAdV, and PTV to final concentrations of 1×10(6) PFU/100 mL, 1×10(5) gc/100 mL and 3×10(5) gc/100 mL, respectively, a significantly higher recovery for each virus was consistently obtained for method A with recoveries of 52% for MS2, 95% for PAdV, and 1.5% for PTV. When method A was compared with method C for the detection of F-coliphages, PAdV and PTV in river water samples, viruses were detected with higher frequencies and at higher mean numbers with method A than with method C. With method A, F-coliphages were detected in 11/12 samples (5-154 PFU/100 mL), PTV in 12/12 samples (397-10,951 gc/100 mL), PAdV in 1/12 samples (15 gc/100 mL), and F-RNA GIII in 1/12 samples (750 gc/100 mL) while F-RNA genotypes I, II, and IV were not detected by qRT-PCR. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

Microelectrode array recordings of cardiac action potentials as a high throughput method to evaluate pesticide toxicity.

PubMed

Natarajan, A; Molnar, P; Sieverdes, K; Jamshidi, A; Hickman, J J

2006-04-01

The threat of environmental pollution, biological warfare agent dissemination and new diseases in recent decades has increased research into cell-based biosensors. The creation of this class of sensors could specifically aid the detection of toxic chemicals and their effects in the environment, such as pyrethroid pesticides. Pyrethroids are synthetic pesticides that have been used increasingly over the last decade to replace other pesticides like DDT. In this study we used a high-throughput method to detect pyrethroids by using multielectrode extracellular recordings from cardiac cells. The data from this cell-electrode hybrid system was compared to published results obtained with patch-clamp electrophysiology and also used as an alternative method to further understand pyrethroid effects. Our biosensor consisted of a confluent monolayer of cardiac myocytes cultured on microelectrode arrays (MEA) composed of 60 substrate-integrated electrodes. Spontaneous activity of these beating cells produced extracellular field potentials in the range of 100 microV to nearly 1200 microV with a beating frequency of 0.5-4 Hz. All of the tested pyrethroids; alpha-Cypermethrin, Tetramethrin and Tefluthrin, produced similar changes in the electrophysiological properties of the cardiac myocytes, namely reduced beating frequency and amplitude. The sensitivity of our toxin detection method was comparable to earlier patch-clamp studies, which indicates that, in specific applications, high-throughput extracellular methods can replace single-cell studies. Moreover, the similar effect of all three pyrethroids on the measured parameters suggests, that not only detection of the toxins but, their classification might also be possible with this method. Overall our results support the idea that whole cell biosensors might be viable alternatives when compared to current toxin detection methods.

Searching for co-orbital planets by combining transit and radial-velocity measurements

NASA Astrophysics Data System (ADS)

Robutel, p.; Leleu, A.; Correia, A.; Lillo-Box, J.

2017-09-01

Co-orbital planetary systems consist of two planets orbiting with the same period a central star. If co-orbital bodies are common in the solar system and are also a natural output of planetary formation models, so far none have been found in extrasolar systems. This lack may be due to observational biases, since the main detection methods are unable to spot co-orbital companions when they are small or near the Lagrangian equilibrium points. We propose a simple method, based on an idea from Ford & Gaudi (2006), that allows the detection of co-orbital companions, and relies on a single parameter proportional to the mass ratio of the two planets. This method is applied to archival radial velocity data of 46 close-in transiting planets among which a few are strong candidates to harbor a co-orbital companion.

Determination of Biogenic Amines in Seawater Using Capillary Electrophoresis with Capacitively Coupled Contactless Conductivity Detection.

PubMed

Gubartallah, Elbaleeq A; Makahleh, Ahmad; Quirino, Joselito P; Saad, Bahruddin

2018-05-08

A rapid and green analytical method based on capillary electrophoresis with capacitively coupled contactless conductivity detection (C⁴D) for the determination of eight environmental pollutants, the biogenic amines (putrescine, cadaverine, spermidine, spermine, tyramine, 2-phenylamine, histamine and tryptamine), is described. The separation was achieved under normal polarity mode at 24 °C and 25 kV with a hydrodynamic injection (50 mbar for 5 s) and using a bare fused-silica capillary (95 cm length × 50 µm i.d.) (detection length of 10.5 cm from the outlet end of the capillary). The optimized background electrolyte consisted of 400 mM malic acid. C⁴D parameters were set at a fixed amplitude (50 V) and frequency (600 kHz). Under the optimum conditions, the method exhibited good linearity over the range of 1.0⁻100 µg mL −1 ( R ² ≥ 0.981). The limits of detection based on signal to noise (S/N) ratios of 3 and 10 were ≤0.029 µg mL −1 . The method was used for the determination of seawater samples that were spiked with biogenic amines. Good recoveries (77⁻93%) were found.

A simple multi-scale Gaussian smoothing-based strategy for automatic chromatographic peak extraction.

PubMed

Fu, Hai-Yan; Guo, Jun-Wei; Yu, Yong-Jie; Li, He-Dong; Cui, Hua-Peng; Liu, Ping-Ping; Wang, Bing; Wang, Sheng; Lu, Peng

2016-06-24

Peak detection is a critical step in chromatographic data analysis. In the present work, we developed a multi-scale Gaussian smoothing-based strategy for accurate peak extraction. The strategy consisted of three stages: background drift correction, peak detection, and peak filtration. Background drift correction was implemented using a moving window strategy. The new peak detection method is a variant of the system used by the well-known MassSpecWavelet, i.e., chromatographic peaks are found at local maximum values under various smoothing window scales. Therefore, peaks can be detected through the ridge lines of maximum values under these window scales, and signals that are monotonously increased/decreased around the peak position could be treated as part of the peak. Instrumental noise was estimated after peak elimination, and a peak filtration strategy was performed to remove peaks with signal-to-noise ratios smaller than 3. The performance of our method was evaluated using two complex datasets. These datasets include essential oil samples for quality control obtained from gas chromatography and tobacco plant samples for metabolic profiling analysis obtained from gas chromatography coupled with mass spectrometry. Results confirmed the reasonability of the developed method. Copyright © 2016 Elsevier B.V. All rights reserved.

Automatic screening and classification of diabetic retinopathy and maculopathy using fuzzy image processing.

PubMed

Rahim, Sarni Suhaila; Palade, Vasile; Shuttleworth, James; Jayne, Chrisina

2016-12-01

Digital retinal imaging is a challenging screening method for which effective, robust and cost-effective approaches are still to be developed. Regular screening for diabetic retinopathy and diabetic maculopathy diseases is necessary in order to identify the group at risk of visual impairment. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images by employing fuzzy image processing techniques. The paper first introduces the existing systems for diabetic retinopathy screening, with an emphasis on the maculopathy detection methods. The proposed medical decision support system consists of four parts, namely: image acquisition, image preprocessing including four retinal structures localisation, feature extraction and the classification of diabetic retinopathy and maculopathy. A combination of fuzzy image processing techniques, the Circular Hough Transform and several feature extraction methods are implemented in the proposed system. The paper also presents a novel technique for the macula region localisation in order to detect the maculopathy. In addition to the proposed detection system, the paper highlights a novel online dataset and it presents the dataset collection, the expert diagnosis process and the advantages of our online database compared to other public eye fundus image databases for diabetic retinopathy purposes.

An ontology-based annotation of cardiac implantable electronic devices to detect therapy changes in a national registry.

PubMed

Rosier, Arnaud; Mabo, Philippe; Chauvin, Michel; Burgun, Anita

2015-05-01

The patient population benefitting from cardiac implantable electronic devices (CIEDs) is increasing. This study introduces a device annotation method that supports the consistent description of the functional attributes of cardiac devices and evaluates how this method can detect device changes from a CIED registry. We designed the Cardiac Device Ontology, an ontology of CIEDs and device functions. We annotated 146 cardiac devices with this ontology and used it to detect therapy changes with respect to atrioventricular pacing, cardiac resynchronization therapy, and defibrillation capability in a French national registry of patients with implants (STIDEFIX). We then analyzed a set of 6905 device replacements from the STIDEFIX registry. Ontology-based identification of therapy changes (upgraded, downgraded, or similar) was accurate (6905 cases) and performed better than straightforward analysis of the registry codes (F-measure 1.00 versus 0.75 to 0.97). This study demonstrates the feasibility and effectiveness of ontology-based functional annotation of devices in the cardiac domain. Such annotation allowed a better description and in-depth analysis of STIDEFIX. This method was useful for the automatic detection of therapy changes and may be reused for analyzing data from other device registries.

A broad range assay for rapid detection and etiologic characterization of bacterial meningitis: performance testing in samples from sub-Sahara.

PubMed

Won, Helen; Yang, Samuel; Gaydos, Charlotte; Hardick, Justin; Ramachandran, Padmini; Hsieh, Yu-Hsiang; Kecojevic, Alexander; Njanpop-Lafourcade, Berthe-Marie; Mueller, Judith E; Tameklo, Tsidi Agbeko; Badziklou, Kossi; Gessner, Bradford D; Rothman, Richard E

2012-09-01

This study aimed to conduct a pilot evaluation of broad-based multiprobe polymerase chain reaction (PCR) in clinical cerebrospinal fluid (CSF) samples compared to local conventional PCR/culture methods used for bacterial meningitis surveillance. A previously described PCR consisting of initial broad-based detection of Eubacteriales by a universal probe, followed by Gram typing, and pathogen-specific probes was designed targeting variable regions of the 16S rRNA gene. The diagnostic performance of the 16S rRNA assay in "127 CSF samples was evaluated in samples from patients from Togo, Africa, by comparison to conventional PCR/culture methods. Our probes detected Neisseria meningitidis, Streptococcus pneumoniae, and Haemophilus influenzae. Uniprobe sensitivity and specificity versus conventional PCR were 100% and 54.6%, respectively. Sensitivity and specificity of uniprobe versus culture methods were 96.5% and 52.5%, respectively. Gram-typing probes correctly typed 98.8% (82/83) and pathogen-specific probes identified 96.4% (80/83) of the positives. This broad-based PCR algorithm successfully detected and provided species level information for multiple bacterial meningitis agents in clinical samples. Copyright © 2012 Elsevier Inc. All rights reserved.

A broad range assay for rapid detection and etiologic characterization of bacterial meningitis: performance testing in samples from sub-Sahara☆, ☆☆,★

PubMed Central

Won, Helen; Yang, Samuel; Gaydos, Charlotte; Hardick, Justin; Ramachandran, Padmini; Hsieh, Yu-Hsiang; Kecojevic, Alexander; Njanpop-Lafourcade, Berthe-Marie; Mueller, Judith E.; Tameklo, Tsidi Agbeko; Badziklou, Kossi; Gessner, Bradford D.; Rothman, Richard E.

2012-01-01

This study aimed to conduct a pilot evaluation of broad-based multiprobe polymerase chain reaction (PCR) in clinical cerebrospinal fluid (CSF) samples compared to local conventional PCR/culture methods used for bacterial meningitis surveillance. A previously described PCR consisting of initial broad-based detection of Eubacteriales by a universal probe, followed by Gram typing, and pathogen-specific probes was designed targeting variable regions of the 16S rRNA gene. The diagnostic performance of the 16S rRNA assay in “”127 CSF samples was evaluated in samples from patients from Togo, Africa, by comparison to conventional PCR/culture methods. Our probes detected Neisseria meningitidis, Streptococcus pneumoniae, and Haemophilus influenzae. Uniprobe sensitivity and specificity versus conventional PCR were 100% and 54.6%, respectively. Sensitivity and specificity of uniprobe versus culture methods were 96.5% and 52.5%, respectively. Gram-typing probes correctly typed 98.8% (82/83) and pathogen-specific probes identified 96.4% (80/83) of the positives. This broad-based PCR algorithm successfully detected and provided species level information for multiple bacterial meningitis agents in clinical samples. PMID:22809694

Detection of longitudinal ulcer using roughness value for computer aided diagnosis of Crohn's disease

NASA Astrophysics Data System (ADS)

Oda, Masahiro; Kitasaka, Takayuki; Furukawa, Kazuhiro; Watanabe, Osamu; Ando, Takafumi; Goto, Hidemi; Mori, Kensaku

2011-03-01

The purpose of this paper is to present a new method to detect ulcers, which is one of the symptoms of Crohn's disease, from CT images. Crohn's disease is an inflammatory disease of the digestive tract. Crohn's disease commonly affects the small intestine. An optical or a capsule endoscope is used for small intestine examinations. However, these endoscopes cannot pass through intestinal stenosis parts in some cases. A CT image based diagnosis allows a physician to observe whole intestine even if intestinal stenosis exists. However, because of the complicated shape of the small and large intestines, understanding of shapes of the intestines and lesion positions are difficult in the CT image based diagnosis. Computer-aided diagnosis system for Crohn's disease having automated lesion detection is required for efficient diagnosis. We propose an automated method to detect ulcers from CT images. Longitudinal ulcers make rough surface of the small and large intestinal wall. The rough surface consists of combination of convex and concave parts on the intestinal wall. We detect convex and concave parts on the intestinal wall by a blob and an inverse-blob structure enhancement filters. A lot of convex and concave parts concentrate on roughed parts. We introduce a roughness value to differentiate convex and concave parts concentrated on the roughed parts from the other on the intestinal wall. The roughness value effectively reduces false positives of ulcer detection. Experimental results showed that the proposed method can detect convex and concave parts on the ulcers.

Development and validation of a high-performance liquid chromatography method for determination of lisinopril in human plasma by magnetic solid-phase extraction and pre-column derivatization.

PubMed

Rastkari, Noushin; Ahmadkhaniha, Reza

2018-03-01

A sensitive, reliable and simple HPLC method was developed for the determination of lisinopril in human plasma. The method consists of extraction and clean-up steps based on magnetic solid-phase extraction and pre-column derivatization with a fluorescent reagent. The mobile phase consisted of a mixture of methanol-sodium dihydrogen phosphate (pH 3.0; 0.005 m; 75:25, v/v). The flow rate was set at 0.7 mL/min. Fluorescence detection was performed at 470nm excitation and 530nm emission wavelengths. Total chromatography run time was 5 min. The average extraction recovery of lisinopril and fluvoxamine (internal standard) was ≥82.8%. The limits of detection and quantification were determined as 1 and 3 ng/mL respectively. The method exhibited a linear calibration line over the concentration range of 3-1000 ng/mL with coefficient of determination (r 2 ) of ≥0.98. The within-run and between-run precisions were satisfactory with values of CV of 1.8-12.8% (accuracy from 99.2 to 94.7%) and 2.4-13.7% (accuracy from 99.5 to 92.2%), respectively. These developments led to considerable improvement in method sensitivity and reliability. The method was validated according to the US Food and Drug Administration guidelines. Therefore, it can be considered as a suitable method for determination of lisinopril in plasma samples. Copyright © 2017 John Wiley & Sons, Ltd.

[Thinking about the present primary open angle glaucoma early diagnosis concepts and methods].

PubMed

Ren, Zeqin

2014-05-01

Early diagnosis of primary open-angle glaucoma has not been clear and consistent in concepts and methods. At present, according to the pathophysiology process of optic nerve damage and its detection technology, early diagnosis on the concept still belongs to the early clinical diagnosis instead of preclinical diagnosis, and on the method depends on the fundus as morphological index combined with the visual field as functional index. The direction of early clinical diagnosis mainly lies in exploring more effective diagnosis index, rather than blindly adopt new diagnostic technology.

Finding a fox: an evaluation of survey methods to estimate abundance of a small desert carnivore.

PubMed

Dempsey, Steven J; Gese, Eric M; Kluever, Bryan M

2014-01-01

The status of many carnivore species is a growing concern for wildlife agencies, conservation organizations, and the general public. Historically, kit foxes (Vulpes macrotis) were classified as abundant and distributed in the desert and semi-arid regions of southwestern North America, but is now considered rare throughout its range. Survey methods have been evaluated for kit foxes, but often in populations where abundance is high and there is little consensus on which technique is best to monitor abundance. We conducted a 2-year study to evaluate four survey methods (scat deposition surveys, scent station surveys, spotlight survey, and trapping) for detecting kit foxes and measuring fox abundance. We determined the probability of detection for each method, and examined the correlation between the relative abundance as estimated by each survey method and the known minimum kit fox abundance as determined by radio-collared animals. All surveys were conducted on 15 5-km transects during the 3 biological seasons of the kit fox. Scat deposition surveys had both the highest detection probabilities (p = 0.88) and were most closely related to minimum known fox abundance (r2 = 0.50, P = 0.001). The next best method for kit fox detection was the scent station survey (p = 0.73), which had the second highest correlation to fox abundance (r2 = 0.46, P<0.001). For detecting kit foxes in a low density population we suggest using scat deposition transects during the breeding season. Scat deposition surveys have low costs, resilience to weather, low labor requirements, and pose no risk to the study animals. The breeding season was ideal for monitoring kit fox population size, as detections consisted of the resident population and had the highest detection probabilities. Using appropriate monitoring techniques will be critical for future conservation actions for this rare desert carnivore.

Finding a Fox: An Evaluation of Survey Methods to Estimate Abundance of a Small Desert Carnivore

PubMed Central

Dempsey, Steven J.; Gese, Eric M.; Kluever, Bryan M.

2014-01-01

The status of many carnivore species is a growing concern for wildlife agencies, conservation organizations, and the general public. Historically, kit foxes (Vulpes macrotis) were classified as abundant and distributed in the desert and semi-arid regions of southwestern North America, but is now considered rare throughout its range. Survey methods have been evaluated for kit foxes, but often in populations where abundance is high and there is little consensus on which technique is best to monitor abundance. We conducted a 2-year study to evaluate four survey methods (scat deposition surveys, scent station surveys, spotlight survey, and trapping) for detecting kit foxes and measuring fox abundance. We determined the probability of detection for each method, and examined the correlation between the relative abundance as estimated by each survey method and the known minimum kit fox abundance as determined by radio-collared animals. All surveys were conducted on 15 5-km transects during the 3 biological seasons of the kit fox. Scat deposition surveys had both the highest detection probabilities (p = 0.88) and were most closely related to minimum known fox abundance (r2 = 0.50, P = 0.001). The next best method for kit fox detection was the scent station survey (p = 0.73), which had the second highest correlation to fox abundance (r2 = 0.46, P<0.001). For detecting kit foxes in a low density population we suggest using scat deposition transects during the breeding season. Scat deposition surveys have low costs, resilience to weather, low labor requirements, and pose no risk to the study animals. The breeding season was ideal for monitoring kit fox population size, as detections consisted of the resident population and had the highest detection probabilities. Using appropriate monitoring techniques will be critical for future conservation actions for this rare desert carnivore. PMID:25148102

Direct determination of neonicotinoid insecticides in an analytically challenging crop such as Chinese chives using selective ELISAs.

PubMed

Watanabe, Eiki; Miyake, Shiro

2018-06-05

Easy-to-use commercial kit-based enzyme-linked immunosorbent assays (ELISAs) have been used to detect neonicotinoid dinotefuran, clothianidin and imidacloprid in Chinese chives, which are considered a troublesome matrix for chromatographic techniques. Based on their high water solubility, water was used as an extractant. Matrix interference could be avoided substantially just diluting sample extracts. Average recoveries of insecticides from spiked samples were 85-113%, with relative standard deviation of <15%. The concentrations of insecticides detected from the spiked samples with the proposed ELISA methods correlated well with those by the reference high-performance liquid chromatography (HPLC) method. The residues analyzed by the ELISA methods were consistently 1.24 times that found by the HPLC method, attributable to loss of analyte during sample clean-up for HPLC analyses. It was revealed that the ELISA methods can be applied easily to pesticide residue analysis in troublesome matrix such as Chinese chives.

Poisson denoising on the sphere

NASA Astrophysics Data System (ADS)

Schmitt, J.; Starck, J. L.; Fadili, J.; Grenier, I.; Casandjian, J. M.

2009-08-01

In the scope of the Fermi mission, Poisson noise removal should improve data quality and make source detection easier. This paper presents a method for Poisson data denoising on sphere, called Multi-Scale Variance Stabilizing Transform on Sphere (MS-VSTS). This method is based on a Variance Stabilizing Transform (VST), a transform which aims to stabilize a Poisson data set such that each stabilized sample has an (asymptotically) constant variance. In addition, for the VST used in the method, the transformed data are asymptotically Gaussian. Thus, MS-VSTS consists in decomposing the data into a sparse multi-scale dictionary (wavelets, curvelets, ridgelets...), and then applying a VST on the coefficients in order to get quasi-Gaussian stabilized coefficients. In this present article, the used multi-scale transform is the Isotropic Undecimated Wavelet Transform. Then, hypothesis tests are made to detect significant coefficients, and the denoised image is reconstructed with an iterative method based on Hybrid Steepest Descent (HST). The method is tested on simulated Fermi data.

Measurement of Postmortem Pupil Size: A New Method with Excellent Reliability and Its Application to Pupil Changes in the Early Postmortem Period.

PubMed

Fleischer, Luise; Sehner, Susanne; Gehl, Axel; Riemer, Martin; Raupach, Tobias; Anders, Sven

2017-05-01

Measurement of postmortem pupil width is a potential component of death time estimation. However, no standardized measurement method has been described. We analyzed a total of 71 digital images for pupil-iris ratio using the software ImageJ. Images were analyzed three times by four different examiners. In addition, serial images from 10 cases were taken between 2 and 50 h postmortem to detect spontaneous pupil changes. Intra- and inter-rater reliability of the method was excellent (ICC > 0.95). The method is observer independent and yields consistent results, and images can be digitally stored and re-evaluated. The method seems highly eligible for forensic and scientific purposes. While statistical analysis of spontaneous pupil changes revealed a significant polynomial of quartic degree for postmortem time (p = 0.001), an obvious pattern was not detected. These results do not indicate suitability of spontaneous pupil changes for forensic death time estimation, as formerly suggested. © 2016 American Academy of Forensic Sciences.

Research of the orbital evolution of asteroid 2012 DA14 (in Russian)

NASA Astrophysics Data System (ADS)

Zausaev, A. F.; Denisov, S. S.; Derevyanka, A. E.

Research of the orbital evolution of asteroid 2012 DA14 on the time interval from 1800 to 2206 is made, an object close approaches with Earth and the Moon are detected, the probability of impact with Earth is calculated. The used mathematical model is consistent with the DE405, the integration was performed using a modified Everhart's method of 27th order, the probability of collision is calculated using the Monte Carlo method.

Efficient video-equipped fire detection approach for automatic fire alarm systems

NASA Astrophysics Data System (ADS)

Kang, Myeongsu; Tung, Truong Xuan; Kim, Jong-Myon

2013-01-01

This paper proposes an efficient four-stage approach that automatically detects fire using video capabilities. In the first stage, an approximate median method is used to detect video frame regions involving motion. In the second stage, a fuzzy c-means-based clustering algorithm is employed to extract candidate regions of fire from all of the movement-containing regions. In the third stage, a gray level co-occurrence matrix is used to extract texture parameters by tracking red-colored objects in the candidate regions. These texture features are, subsequently, used as inputs of a back-propagation neural network to distinguish between fire and nonfire. Experimental results indicate that the proposed four-stage approach outperforms other fire detection algorithms in terms of consistently increasing the accuracy of fire detection in both indoor and outdoor test videos.

Virtual-Lattice Based Intrusion Detection Algorithm over Actuator-Assisted Underwater Wireless Sensor Networks

PubMed Central

Yan, Jing; Li, Xiaolei; Luo, Xiaoyuan; Guan, Xinping

2017-01-01

Due to the lack of a physical line of defense, intrusion detection becomes one of the key issues in applications of underwater wireless sensor networks (UWSNs), especially when the confidentiality has prime importance. However, the resource-constrained property of UWSNs such as sparse deployment and energy constraint makes intrusion detection a challenging issue. This paper considers a virtual-lattice-based approach to the intrusion detection problem in UWSNs. Different from most existing works, the UWSNs consist of two kinds of nodes, i.e., sensor nodes (SNs), which cannot move autonomously, and actuator nodes (ANs), which can move autonomously according to the performance requirement. With the cooperation of SNs and ANs, the intruder detection probability is defined. Then, a virtual lattice-based monitor (VLM) algorithm is proposed to detect the intruder. In order to reduce the redundancy of communication links and improve detection probability, an optimal and coordinative lattice-based monitor patrolling (OCLMP) algorithm is further provided for UWSNs, wherein an equal price search strategy is given for ANs to find the shortest patrolling path. Under VLM and OCLMP algorithms, the detection probabilities are calculated, while the topology connectivity can be guaranteed. Finally, simulation results are presented to show that the proposed method in this paper can improve the detection accuracy and save the energy consumption compared with the conventional methods. PMID:28531127

Hybrid Monte Carlo/Deterministic Methods for Accelerating Active Interrogation Modeling

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

Peplow, Douglas E.; Miller, Thomas Martin; Patton, Bruce W

2013-01-01

The potential for smuggling special nuclear material (SNM) into the United States is a major concern to homeland security, so federal agencies are investigating a variety of preventive measures, including detection and interdiction of SNM during transport. One approach for SNM detection, called active interrogation, uses a radiation source, such as a beam of neutrons or photons, to scan cargo containers and detect the products of induced fissions. In realistic cargo transport scenarios, the process of inducing and detecting fissions in SNM is difficult due to the presence of various and potentially thick materials between the radiation source and themore » SNM, and the practical limitations on radiation source strength and detection capabilities. Therefore, computer simulations are being used, along with experimental measurements, in efforts to design effective active interrogation detection systems. The computer simulations mostly consist of simulating radiation transport from the source to the detector region(s). Although the Monte Carlo method is predominantly used for these simulations, difficulties persist related to calculating statistically meaningful detector responses in practical computing times, thereby limiting their usefulness for design and evaluation of practical active interrogation systems. In previous work, the benefits of hybrid methods that use the results of approximate deterministic transport calculations to accelerate high-fidelity Monte Carlo simulations have been demonstrated for source-detector type problems. In this work, the hybrid methods are applied and evaluated for three example active interrogation problems. Additionally, a new approach is presented that uses multiple goal-based importance functions depending on a particle s relevance to the ultimate goal of the simulation. Results from the examples demonstrate that the application of hybrid methods to active interrogation problems dramatically increases their calculational efficiency.« less

Impedimetric detection of bacteria by using a microfluidic chip and silver nanoparticle based signal enhancement.

PubMed

Wang, Renjie; Xu, Yi; Sors, Thomas; Irudayaraj, Joseph; Ren, Wen; Wang, Rong

2018-02-19

The authors describe a method that can significantly improve the performance of impedimetric detection of bacteria. A multifunctional microfluidic chip was designed consisting of interdigitated microelectrodes and a micro-mixing zone with a Tesla structure. This maximizes the coating of bacterial surfaces with nanoparticles and results in improved impedimetric detection. The method was applied to the detection of Escherichia coli O157:H7 (E. coli). Silver enhancement was accomplished by coating E.coli with the cationic polymer diallyldimethylammonium chloride (PDDA) to form positively charged E. coli/PDDA complexes. Then, gold nanoparticles (AuNPs) were added, and the resulting E. coli/PDDA/AuNPs complexes were collected at interdigitated electrodes via positive dielectrophoresis (pDEP). A silver adduct was then formed on the E. coli/PDDA/AuNP complexes by using silver enhancement solutions and by using the AuNPs as catalysts. The combination of pDEP based capture and of using silver adducts reduces impedance by increasing the conductivity of the solution and the double layer capacitance around the microelectrodes. Impedance decreases linearly in the 2 × 10 3 -2 × 10 5  cfu·mL -1 E. coli concentration range, with a 500 cfu·mL -1 detection limit. Egg shell wash samples and tap water spiked with E. coli were successfully used for validation, and this demonstrates the practical application of this method. Graphical abstract Schematic representation of the AuNP@Ag enhancement method integrated with multifunctional microfluidic chip platform for impedimetric quantitation of bacteria. The method significantly improves the performance of impedimetric detection of bacteria.

[Contrast of Z-Pinch X-Ray Yield Measure Technique].

PubMed

Li, Mo; Wang, Liang-ping; Sheng, Liang; Lu, Yi

2015-03-01

Resistive bolometer and scintillant detection system are two mainly Z-pinch X-ray yield measure techniques which are based on different diagnostic principles. Contrasting the results from two methods can help with increasing precision of X-ray yield measurement. Experiments with different load material and shape were carried out on the "QiangGuang-I" facility. For Al wire arrays, X-ray yields measured by the two techniques were largely consistent. However, for insulating coating W wire arrays, X-ray yields taken from bolometer changed with load parameters while data from scintillant detection system hardly changed. Simulation and analysis draw conclusions as follows: (1) Scintillant detection system is much more sensitive to X-ray photons with low energy and its spectral response is wider than the resistive bolometer. Thus, results from the former method are always larger than the latter. (2) The responses of the two systems are both flat to Al plasma radiation. Thus, their results are consistent for Al wire array loads. (3) Radiation form planar W wire arrays is mainly composed of sub-keV soft X-ray. X-ray yields measured by the bolometer is supposed to be accurate because of the nickel foil can absorb almost all the soft X-ray. (4) By contrast, using planar W wire arrays, data from scintillant detection system hardly change with load parameters. A possible explanation is that while the distance between wires increases, plasma temperature at stagnation reduces and spectra moves toward the soft X-ray region. Scintillator is much more sensitive to the soft X-ray below 200 eV. Thus, although the total X-ray yield reduces with large diameter load, signal from the scintillant detection system is almost the same. (5) Both Techniques affected by electron beams produced by the loads.

Determining the 95% limit of detection for waterborne pathogen analyses from primary concentration to qPCR.

PubMed

Stokdyk, Joel P; Firnstahl, Aaron D; Spencer, Susan K; Burch, Tucker R; Borchardt, Mark A

2016-06-01

The limit of detection (LOD) for qPCR-based analyses is not consistently defined or determined in studies on waterborne pathogens. Moreover, the LODs reported often reflect the qPCR assay alone rather than the entire sample process. Our objective was to develop an approach to determine the 95% LOD (lowest concentration at which 95% of positive samples are detected) for the entire process of waterborne pathogen detection. We began by spiking the lowest concentration that was consistently positive at the qPCR step (based on its standard curve) into each procedural step working backwards (i.e., extraction, secondary concentration, primary concentration), which established a concentration that was detectable following losses of the pathogen from processing. Using the fraction of positive replicates (n = 10) at this concentration, we selected and analyzed a second, and then third, concentration. If the fraction of positive replicates equaled 1 or 0 for two concentrations, we selected another. We calculated the LOD using probit analysis. To demonstrate our approach we determined the 95% LOD for Salmonella enterica serovar Typhimurium, adenovirus 41, and vaccine-derived poliovirus Sabin 3, which were 11, 12, and 6 genomic copies (gc) per reaction (rxn), respectively (equivalent to 1.3, 1.5, and 4.0 gc L(-1) assuming the 1500 L tap-water sample volume prescribed in EPA Method 1615). This approach limited the number of analyses required and was amenable to testing multiple genetic targets simultaneously (i.e., spiking a single sample with multiple microorganisms). An LOD determined this way can facilitate study design, guide the number of required technical replicates, aid method evaluation, and inform data interpretation. Published by Elsevier Ltd.

Determining the 95% limit of detection for waterborne pathogen analyses from primary concentration to qPCR

USGS Publications Warehouse

Stokdyk, Joel P.; Firnstahl, Aaron; Spencer, Susan K.; Burch, Tucker R; Borchardt, Mark A.

2016-01-01

The limit of detection (LOD) for qPCR-based analyses is not consistently defined or determined in studies on waterborne pathogens. Moreover, the LODs reported often reflect the qPCR assay alone rather than the entire sample process. Our objective was to develop an approach to determine the 95% LOD (lowest concentration at which 95% of positive samples are detected) for the entire process of waterborne pathogen detection. We began by spiking the lowest concentration that was consistently positive at the qPCR step (based on its standard curve) into each procedural step working backwards (i.e., extraction, secondary concentration, primary concentration), which established a concentration that was detectable following losses of the pathogen from processing. Using the fraction of positive replicates (n = 10) at this concentration, we selected and analyzed a second, and then third, concentration. If the fraction of positive replicates equaled 1 or 0 for two concentrations, we selected another. We calculated the LOD using probit analysis. To demonstrate our approach we determined the 95% LOD for Salmonella enterica serovar Typhimurium, adenovirus 41, and vaccine-derived poliovirus Sabin 3, which were 11, 12, and 6 genomic copies (gc) per reaction (rxn), respectively (equivalent to 1.3, 1.5, and 4.0 gc L−1 assuming the 1500 L tap-water sample volume prescribed in EPA Method 1615). This approach limited the number of analyses required and was amenable to testing multiple genetic targets simultaneously (i.e., spiking a single sample with multiple microorganisms). An LOD determined this way can facilitate study design, guide the number of required technical replicates, aid method evaluation, and inform data interpretation.

Community Detection on the GPU

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

Naim, Md; Manne, Fredrik; Halappanavar, Mahantesh

We present and evaluate a new GPU algorithm based on the Louvain method for community detection. Our algorithm is the first for this problem that parallelizes the access to individual edges. In this way we can fine tune the load balance when processing networks with nodes of highly varying degrees. This is achieved by scaling the number of threads assigned to each node according to its degree. Extensive experiments show that we obtain speedups up to a factor of 270 compared to the sequential algorithm. The algorithm consistently outperforms other recent shared memory implementations and is only one order ofmore » magnitude slower than the current fastest parallel Louvain method running on a Blue Gene/Q supercomputer using more than 500K threads.« less

Detection of Agar, by Analysis of Sugar Markers, Associated with Bacillus Anthracis Spores, After Culture

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

Wunschel, David S.; Colburn, Heather A.; Fox, Alvin

2008-08-01

Detection of small quantities of agar associated with spores of Bacillus anthracis could provide key information regarding its source or growth characteristics. Agar, widely used in growth of bacteria on solid surfaces, consists primarily of repeating polysaccharide units of 3,6-anhydro-L-galactose (AGal) and galactose (Gal) with sulfated and O-methylated galactoses present as minor constituents. Two variants of the alditol acetate procedure were evaluated for detection of potential agar markers associated with spores. The first method employed a reductive hydrolysis step, to stabilize labile anhydrogalactose, by converting to anhydrogalactitol. The second eliminated the reductive hydrolysis step simplifying the procedure. Anhydrogalactitol, derived frommore » agar, was detected using both derivatization methods followed by gas chromatography-mass spectrometry (GC-MS) analysis. However, challenges with artefactual background (reductive hydrolysis) or marker destruction (hydrolysis) lead to the search for alternative sugar markers. A minor agar component, 6-O-methyl galactose (6-O-M gal), was readily detected in agar-grown but not broth-grown bacteria. Detection was optimized by the use of gas chromatography-tandem mass spectrometry (GC-MS-MS). With appropriate choice of sugar marker and analytical procedure, detection of sugar markers for agar has considerable potential in microbial forensics.« less

A Unimodal Model for Double Observer Distance Sampling Surveys.

PubMed

Becker, Earl F; Christ, Aaron M

2015-01-01

Distance sampling is a widely used method to estimate animal population size. Most distance sampling models utilize a monotonically decreasing detection function such as a half-normal. Recent advances in distance sampling modeling allow for the incorporation of covariates into the distance model, and the elimination of the assumption of perfect detection at some fixed distance (usually the transect line) with the use of double-observer models. The assumption of full observer independence in the double-observer model is problematic, but can be addressed by using the point independence assumption which assumes there is one distance, the apex of the detection function, where the 2 observers are assumed independent. Aerially collected distance sampling data can have a unimodal shape and have been successfully modeled with a gamma detection function. Covariates in gamma detection models cause the apex of detection to shift depending upon covariate levels, making this model incompatible with the point independence assumption when using double-observer data. This paper reports a unimodal detection model based on a two-piece normal distribution that allows covariates, has only one apex, and is consistent with the point independence assumption when double-observer data are utilized. An aerial line-transect survey of black bears in Alaska illustrate how this method can be applied.

Portable detection system of vegetable oils based on laser induced fluorescence

NASA Astrophysics Data System (ADS)

Zhu, Li; Zhang, Yinchao; Chen, Siying; Chen, He; Guo, Pan; Mu, Taotao

2015-11-01

Food safety, especially edible oils, has attracted more and more attention recently. Many methods and instruments have emerged to detect the edible oils, which include oils classification and adulteration. It is well known than the adulteration is based on classification. Then, in this paper, a portable detection system, based on laser induced fluorescence, is proposed and designed to classify the various edible oils, including (olive, rapeseed, walnut, peanut, linseed, sunflower, corn oils). 532 nm laser modules are used in this equipment. Then, all the components are assembled into a module (100*100*25mm). A total of 700 sets of fluorescence data (100 sets of each type oil) are collected. In order to classify different edible oils, principle components analysis and support vector machine have been employed in the data analysis. The training set consisted of 560 sets of data (80 sets of each oil) and the test set consisted of 140 sets of data (20 sets of each oil). The recognition rate is up to 99%, which demonstrates the reliability of this potable system. With nonintrusive and no sample preparation characteristic, the potable system can be effectively applied for food detection.

Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning

PubMed Central

Xu, Yuan; Ding, Kun; Huo, Chunlei; Zhong, Zisha; Li, Haichang; Pan, Chunhong

2015-01-01

Very high resolution (VHR) image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (i.e., in what degree the changes have happened), while they ignore the change pattern description (i.e., how the changes changed), which is of equal importance in characterizing the change signatures. Moreover, the simultaneous consideration of the classification robust to the registration noise and the multiscale region-consistent fusion is often neglected in change decision. To overcome such drawbacks, in this paper, a novel VHR image change detection method is proposed based on sparse change descriptor and robust discriminative dictionary learning. Sparse change descriptor combines the change degree component and the change pattern component, which are encoded by the sparse representation error and the morphological profile feature, respectively. Robust change decision is conducted by multiscale region-consistent fusion, which is implemented by the superpixel-level cosparse representation with robust discriminative dictionary and the conditional random field model. Experimental results confirm the effectiveness of the proposed change detection technique. PMID:25918748

Analysis and Characterization of Polychlorinated Hydroxybornanes as Metabolites of Toxaphene Using a Polar Bear Model.

PubMed

Reger, Lea; Gallistl, Christoph; Skírnisson, Karl; Vetter, Walter

2017-08-01

Abiotic and biotic transformation of toxaphene (camphechlor) results in the selective enrichment of recalcitrant congeners while other, less persistent compounds of technical toxaphene (CTTs) are degraded. Until now, there has been little knowledge on oxidation transformation of toxaphene. For instance, the existence of hydroxylated CTTs (OH-CTTs) in authentic environmental and food samples has not been proven. For this reason, we synthesized a mixture consisting of tetra- to heptachlorinated OH-CTTs and simplified it by countercurrent chromatography (CCC). Thus, 227 OH-CTTs were detected in the CCC fractions (12 tetra-, 117 penta-, 81 hexa-, and 17 heptachlorinated OH-CTTs), which was >50% more than detected before the fractionation. One CCC fraction consisting of only 18 OH-CTTs was used to develop a sample cleanup method which aimed to remove CTTs, isobaric PCBs, and sample matrix. The final cleanup procedure consisted of (i) gel permeation chromatography (GPC) and adsorption chromatography using (ii) deactivated and (iii) activated silica gel. Hence, up to 320 and 4350 μg/kg lipid weight of octa- and nonachlorinated CTTs were detected in four liver samples and adipose tissue of polar bears, respectively. Furthermore, the presence of one hexachlorinated OH-CTT isomer could be verified in the samples, which was about 1% of the octachlorinated CTTs determined in the liver samples.

The relationship between species detection probability and local extinction probability

USGS Publications Warehouse

Alpizar-Jara, R.; Nichols, J.D.; Hines, J.E.; Sauer, J.R.; Pollock, K.H.; Rosenberry, C.S.

2004-01-01

In community-level ecological studies, generally not all species present in sampled areas are detected. Many authors have proposed the use of estimation methods that allow detection probabilities that are < 1 and that are heterogeneous among species. These methods can also be used to estimate community-dynamic parameters such as species local extinction probability and turnover rates (Nichols et al. Ecol Appl 8:1213-1225; Conserv Biol 12:1390-1398). Here, we present an ad hoc approach to estimating community-level vital rates in the presence of joint heterogeneity of detection probabilities and vital rates. The method consists of partitioning the number of species into two groups using the detection frequencies and then estimating vital rates (e.g., local extinction probabilities) for each group. Estimators from each group are combined in a weighted estimator of vital rates that accounts for the effect of heterogeneity. Using data from the North American Breeding Bird Survey, we computed such estimates and tested the hypothesis that detection probabilities and local extinction probabilities were negatively related. Our analyses support the hypothesis that species detection probability covaries negatively with local probability of extinction and turnover rates. A simulation study was conducted to assess the performance of vital parameter estimators as well as other estimators relevant to questions about heterogeneity, such as coefficient of variation of detection probabilities and proportion of species in each group. Both the weighted estimator suggested in this paper and the original unweighted estimator for local extinction probability performed fairly well and provided no basis for preferring one to the other.

Augmented Reality for Real-Time Detection and Interpretation of Colorimetric Signals Generated by Paper-Based Biosensors.

PubMed

Russell, Steven M; Doménech-Sánchez, Antonio; de la Rica, Roberto

2017-06-23

Colorimetric tests are becoming increasingly popular in point-of-need analyses due to the possibility of detecting the signal with the naked eye, which eliminates the utilization of bulky and costly instruments only available in laboratories. However, colorimetric tests may be interpreted incorrectly by nonspecialists due to disparities in color perception or a lack of training. Here we solve this issue with a method that not only detects colorimetric signals but also interprets them so that the test outcome is understandable for anyone. It consists of an augmented reality (AR) app that uses a camera to detect the colored signals generated by a nanoparticle-based immunoassay, and that yields a warning symbol or message when the concentration of analyte is higher than a certain threshold. The proposed method detected the model analyte mouse IgG with a limit of detection of 0.3 μg mL -1 , which was comparable to the limit of detection afforded by classical densitometry performed with a nonportable device. When adapted to the detection of E. coli, the app always yielded a "hazard" warning symbol when the concentration of E. coli in the sample was above the infective dose (10 6 cfu mL -1 or higher). The proposed method could help nonspecialists make a decision about drinking from a potentially contaminated water source by yielding an unambiguous message that is easily understood by anyone. The widespread availability of smartphones along with the inexpensive paper test that requires no enzymes to generate the signal makes the proposed assay promising for analyses in remote locations and developing countries.

Development and Validation of a Precise, Single HPLC Method for the Determination of Tolperisone Impurities in API and Pharmaceutical Dosage Forms.

PubMed

Raju, Thummala Veera Raghava; Seshadri, Raja Kumar; Arutla, Srinivas; Mohan, Tharlapu Satya Sankarsana Jagan; Rao, Ivaturi Mrutyunjaya; Nittala, Someswara Rao

2013-01-01

A novel, sensitive, stability-indicating HPLC method has been developed for the quantitative estimation of Tolperisone-related impurities in both bulk drugs and pharmaceutical dosage forms. Effective chromatographic separation was achieved on a C18 stationary phase with a simple mobile phase combination delivered in a simple gradient programme, and quantitation was by ultraviolet detection at 254 nm. The mobile phase consisted of a buffer and acetonitrile delivered at a flow rate 1.0 ml/min. The buffer consisted of 0.01 M potassium dihydrogen phosphate with the pH adjusted to 8.0 by using diethylamine. In the developed HPLC method, the resolution between Tolperisone and its four potential impurities was found to be greater than 2.0. Regression analysis showed an R value (correlation coefficient) of greater than 0.999 for the Tolperisone impurities. This method was capable of detecting all four impurities of Tolperisone at a level of 0.19 μg/mL with respect to the test concentration of 1000 μg/mL for a 10 µl injection volume. The tablets were subjected to the stress conditions of hydrolysis, oxidation, photolysis, and thermal degradation. Considerable degradation was found to occur in base hydrolysis, water hydrolysis, and oxidation. The stress samples were assayed against a qualified reference standard and the mass balance was found to be close to 100%. The established method was validated and found to be linear, accurate, precise, specific, robust, and rugged.

Development of T m -shift genotyping method for detection of cat-derived Giardia lamblia.

PubMed

Pan, Weida; Fu, Yeqi; Abdullahi, Auwalu Yusuf; Wang, Mingwei; Shi, Xianli; Yang, Fang; Yu, Xingang; Yan, Xinxin; Zhang, Pan; Hang, Jianxiong; Li, Guoqing

2017-04-01

To develop T m -shift genotyping method for detection of cat-derived Giardia lamblia, two sets of primers with two GC-rich tails of unequal length attached to their 5'-end were designed according to two SNPs (BG434 and BG170) of β-giardin (bg) gene, and specific PCR products were identified by inspection of a melting curve on real-time PCR thermocycler. A series of experiments on the stability, sensitivity, and accuracy of T m -shift method was tested, and clinical samples were also detected. The results showed that two sets of primers based on SNP could distinguish accurately between assemblages A and F. Coefficient of variation of T m values of assemblage A and F was 0.14 and 0.07% in BG434 and 0.10 and 0.11% in BG170, respectively. The lowest detection concentration was 4.52 × 10 -5 and 4.88 × 10 -5  ng/μL samples of assemblage A and F standard plasmids. The T m -shift genotyping results of ten DNA samples from the cat-derived G. lamblia were consistent with their known genotypes. The detection rate of clinical samples by T m -shift was higher than that by microscopy, and their genotyping results were in complete accordance with sequencing results. It is concluded that the T m -shift genotyping method is rapid, specific, and sensitive and may provide a new technological mean for molecular detection and epidemiological investigation of the cat-derived G. lamblia.

Advanced detection and measurement of cells on membrane from peripheral blood by laser scanning cytometry (LSC) in early stage breast cancer patients.

PubMed

Sanislo, L; Kuliffay, P; Sedlak, J; Kausitz, J; Galbavy, S

2010-01-01

The aim of our study was the potential detection of circulating tumour cells (CTCs) in early stage breast cancer patients. Our approach was cell microfiltration through polycarbonate membrane as a concentration method suitable for CTC selection in peripheral blood. The isolated cells on membrane were further analysed by laser scanning cytometry. Sixteen patients were enrolled in the study, of which 13 had early stage breast carcinoma and 3 patients had metastatic breast carcinoma. The analyses were performed from 9 ml of peripheral blood, in one patient blood was drawn twice. Blood samples were taken after adjuvant chemotherapy but prior to adjuvant radiotherapy. The control group consisted of 12 clinically healthy subjects. In the control group 3 subjects out of 12 had 1 CTC, the mean CTC numbers being 0.25 +/- 0.45. In the early stage breast cancer patients 0-36 CTCs were detected (mean 13.9 +/- 12.9 CTCs. 10 patients out of 13 had more than 2 CTCs (62%). The detection and measurement of cells on membrane is a simple and reproducible method of detection of CTCs in peripheral blood. Sensitivity of the method is 88.5%. Detection of CTCs seems to be a promising method for the monitoring of adjuvant therapy in early stage breast cancer patients and for the identification of high risk patients in whom elevated numbers of CTCs are persisting following the termination of adjuvant therapy (Tab. 1, Fig. 4, Ref. 35). Full Text (Free, PDF) www.bmj.sk.

Spatial Analysis of Land Subsidence and Flood Pattern Based on DInSAR Method in Sentinel Sar Imagery and Weighting Method in Geo-Hazard Parameters Combination in North Jakarta Region

NASA Astrophysics Data System (ADS)

Prasetyo, Y.; Yuwono, B. D.; Ramadhanis, Z.

2018-02-01

The reclamation program carried out in most cities in North Jakarta is directly adjacent to the Jakarta Bay. Beside this program, the density of population and development center in North Jakarta office has increased the need for underground water excessively. As a result of these things, land subsidence in North Jakarta area is relatively high and so intense. The research methodology was developed based on the method of remote sensing and geographic information systems, expected to describe the spatial correlation between the land subsidence and flood phenomenon in North Jakarta. The DInSAR (Differential Interferometric Synthetic Aperture Radar) method with satellite image data Radar (SAR Sentinel 1A) for the years 2015 to 2016 acquisitions was used in this research. It is intended to obtain a pattern of land subsidence in North Jakarta and then combined with flood patterns. For the preparation of flood threat zoning pattern, this research has been modeling in spatial technique based on a weighted parameter of rainfall, elevation, flood zones and land use. In the final result, we have obtained a flood hazard zonation models then do the overlap against DInSAR processing results. As a result of the research, Geo-hazard modelling has a variety results as: 81% of flood threat zones consist of rural area, 12% consists of un-built areas and 7% consists of water areas. Furthermore, the correlation of land subsidence to flood risk zone is divided into three levels of suitability with 74% in high class, 22% in medium class and 4% in low class. For the result of spatial correlation area between land subsidence and flood risk zone are 77% detected in rural area, 17% detected in un-built area and 6% detected in a water area. Whereas the research product is the geo-hazard maps in North Jakarta as the basis of the spatial correlation analysis between the land subsidence and flooding phenomena.double point.

Fully automated macular pathology detection in retina optical coherence tomography images using sparse coding and dictionary learning

NASA Astrophysics Data System (ADS)

Sun, Yankui; Li, Shan; Sun, Zhongyang

2017-01-01

We propose a framework for automated detection of dry age-related macular degeneration (AMD) and diabetic macular edema (DME) from retina optical coherence tomography (OCT) images, based on sparse coding and dictionary learning. The study aims to improve the classification performance of state-of-the-art methods. First, our method presents a general approach to automatically align and crop retina regions; then it obtains global representations of images by using sparse coding and a spatial pyramid; finally, a multiclass linear support vector machine classifier is employed for classification. We apply two datasets for validating our algorithm: Duke spectral domain OCT (SD-OCT) dataset, consisting of volumetric scans acquired from 45 subjects-15 normal subjects, 15 AMD patients, and 15 DME patients; and clinical SD-OCT dataset, consisting of 678 OCT retina scans acquired from clinics in Beijing-168, 297, and 213 OCT images for AMD, DME, and normal retinas, respectively. For the former dataset, our classifier correctly identifies 100%, 100%, and 93.33% of the volumes with DME, AMD, and normal subjects, respectively, and thus performs much better than the conventional method; for the latter dataset, our classifier leads to a correct classification rate of 99.67%, 99.67%, and 100.00% for DME, AMD, and normal images, respectively.

Fully automated macular pathology detection in retina optical coherence tomography images using sparse coding and dictionary learning.

PubMed

Sun, Yankui; Li, Shan; Sun, Zhongyang

2017-01-01

We propose a framework for automated detection of dry age-related macular degeneration (AMD) and diabetic macular edema (DME) from retina optical coherence tomography (OCT) images, based on sparse coding and dictionary learning. The study aims to improve the classification performance of state-of-the-art methods. First, our method presents a general approach to automatically align and crop retina regions; then it obtains global representations of images by using sparse coding and a spatial pyramid; finally, a multiclass linear support vector machine classifier is employed for classification. We apply two datasets for validating our algorithm: Duke spectral domain OCT (SD-OCT) dataset, consisting of volumetric scans acquired from 45 subjects—15 normal subjects, 15 AMD patients, and 15 DME patients; and clinical SD-OCT dataset, consisting of 678 OCT retina scans acquired from clinics in Beijing—168, 297, and 213 OCT images for AMD, DME, and normal retinas, respectively. For the former dataset, our classifier correctly identifies 100%, 100%, and 93.33% of the volumes with DME, AMD, and normal subjects, respectively, and thus performs much better than the conventional method; for the latter dataset, our classifier leads to a correct classification rate of 99.67%, 99.67%, and 100.00% for DME, AMD, and normal images, respectively.

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.

Application of loop-mediated isothermal amplification with propidium monoazide treatment to detect live Salmonella in chicken carcasses.

PubMed

Youn, S Y; Jeong, O M; Choi, B K; Jung, S C; Kang, M S

2017-02-01

Raw chicken products are major causes of human foodborne salmonellosis worldwide. In particular, there is a significant risk of human exposure to Salmonella originating from the chicken slaughtering process. Controlling the contamination of chicken carcasses by Salmonella has been a considerable challenge in chicken-slaughtering facilities and involves routine microbiological monitoring using reliable detection methods. Simple and rapid detection methods, particularly those capable of determining cell viability, will significantly facilitate routine monitoring of Salmonella Here, we report an invA-based loop-mediated isothermal amplification method coupled with a simple propidium monoazide treatment (PMA-LAMP) for simple and rapid detection and quantification of viable Salmonella in rinse water of chicken carcasses. In this study, PMA-LAMP consistently gave negative results for isopropanol-killed Salmonella with concentrations up to 8.0 × 10 6 CFU/reaction. The detection limit of PMA-LAMP was 8.0 × 10 1 CFU/reaction with viable Salmonella in both pure culture and rinse water of chicken carcasses, and 10-fold lower than a conventional polymerase chain reaction coupled with PMA (PMA-PCR) targeting invA There was a high correlation (R 2 = 0.99 to 0.976) between LAMP time threshold (T T ) values and viable Salmonella with a quantification range of 1.0 × 10 3 to 1.0 × 10 8 CFU/mL in pure culture and rinse water of chicken carcasses. The PMA-LAMP assay took less than 2 h to detect Salmonella contaminated in test samples. Therefore, this simple and rapid method will be a very useful tool to detect live Salmonella contamination of chicken carcasses without pre-enrichment at the slaughterhouse where sanitizing treatments are commonly used. © 2016 Poultry Science Association Inc.

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.

Novel Maximum-based Timing Acquisition for Spread-Spectrum Communications

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

Sibbetty, Taylor; Moradiz, Hussein; Farhang-Boroujeny, Behrouz

This paper proposes and analyzes a new packet detection and timing acquisition method for spread spectrum systems. The proposed method provides an enhancement over the typical thresholding techniques that have been proposed for direct sequence spread spectrum (DS-SS). The effective implementation of thresholding methods typically require accurate knowledge of the received signal-to-noise ratio (SNR), which is particularly difficult to estimate in spread spectrum systems. Instead, we propose a method which utilizes a consistency metric of the location of maximum samples at the output of a filter matched to the spread spectrum waveform to achieve acquisition, and does not require knowledgemore » of the received SNR. Through theoretical study, we show that the proposed method offers a low probability of missed detection over a large range of SNR with a corresponding probability of false alarm far lower than other methods. Computer simulations that corroborate our theoretical results are also presented. Although our work here has been motivated by our previous study of a filter bank multicarrier spread-spectrum (FB-MC-SS) system, the proposed method is applicable to DS-SS systems as well.« less

Neonatal Jaundice Detection System.

PubMed

Aydın, Mustafa; Hardalaç, Fırat; Ural, Berkan; Karap, Serhat

2016-07-01

Neonatal jaundice is a common condition that occurs in newborn infants in the first week of life. Today, techniques used for detection are required blood samples and other clinical testing with special equipment. The aim of this study is creating a non-invasive system to control and to detect the jaundice periodically and helping doctors for early diagnosis. In this work, first, a patient group which is consisted from jaundiced babies and a control group which is consisted from healthy babies are prepared, then between 24 and 48 h after birth, 40 jaundiced and 40 healthy newborns are chosen. Second, advanced image processing techniques are used on the images which are taken with a standard smartphone and the color calibration card. Segmentation, pixel similarity and white balancing methods are used as image processing techniques and RGB values and pixels' important information are obtained exactly. Third, during feature extraction stage, with using colormap transformations and feature calculation, comparisons are done in RGB plane between color change values and the 8-color calibration card which is specially designed. Finally, in the bilirubin level estimation stage, kNN and SVR machine learning regressions are used on the dataset which are obtained from feature extraction. At the end of the process, when the control group is based on for comparisons, jaundice is succesfully detected for 40 jaundiced infants and the success rate is 85 %. Obtained bilirubin estimation results are consisted with bilirubin results which are obtained from the standard blood test and the compliance rate is 85 %.

Determination of bupropion using liquid chromatography with fluorescence detection in pharmaceutical preparations, human plasma and human urine.

PubMed

Ulu, Sevgi Tatar; Tuncel, Muzaffer

2012-05-01

A novel pre-column derivatization reversed-phase high-performance liquid chromatography with fluorescence detection is described for the determination of bupropion in pharmaceutical preparation, human plasma and human urine using mexiletine as internal standard. The proposed method is based on the reaction of 4-chloro-7-nitrobenzofurazan (NBD-Cl) with bupropion to produce a fluorescent derivative. The derivative formed is monitored on a C18 (150 mm × 4.6 mm i.d., 5 µm) column using a mobile phase consisting of methanol-water 75:25 (v/v), at a flow-rate of 1.2 mL/min and detected fluorimetrically at λ(ex) = 458 and λ(em) = 533 nm. The assay was linear over the concentration ranges of 5-500 and 10-500 ng/mL for plasma and urine, respectively. The limits of detection and quantification were calculated to be 0.24 and 0.72 ng/mL for plasma and urine, respectively (inter-day results). The recoveries obtained for plasma and urine were 97.12% ± 0.45 and 96.00% ± 0.45, respectively. The method presents good performance in terms of precision, accuracy, specificity, linearity, detection and quantification limits and robustness. The proposed method is applied to determine bupropion in commercially available tablets. The results were compared with an ultraviolet spectrophotometry method using t- and F-tests. © The Author [2012]. Published by Oxford University Press. All rights reserved.

Partial Discharge Monitoring on Metal-Enclosed Switchgear with Distributed Non-Contact Sensors.

PubMed

Zhang, Chongxing; Dong, Ming; Ren, Ming; Huang, Wenguang; Zhou, Jierui; Gao, Xuze; Albarracín, Ricardo

2018-02-11

Metal-enclosed switchgear, which are widely used in the distribution of electrical energy, play an important role in power distribution networks. Their safe operation is directly related to the reliability of power system as well as the power quality on the consumer side. Partial discharge detection is an effective way to identify potential faults and can be utilized for insulation diagnosis of metal-enclosed switchgear. The transient earth voltage method, an effective non-intrusive method, has substantial engineering application value for estimating the insulation condition of switchgear. However, the practical application effectiveness of TEV detection is not satisfactory because of the lack of a TEV detection application method, i.e., a method with sufficient technical cognition and analysis. This paper proposes an innovative online PD detection system and a corresponding application strategy based on an intelligent feedback distributed TEV wireless sensor network, consisting of sensing, communication, and diagnosis layers. In the proposed system, the TEV signal or status data are wirelessly transmitted to the terminal following low-energy signal preprocessing and acquisition by TEV sensors. Then, a central server analyzes the correlation of the uploaded data and gives a fault warning level according to the quantity, trend, parallel analysis, and phase resolved partial discharge pattern recognition. In this way, a TEV detection system and strategy with distributed acquisition, unitized fault warning, and centralized diagnosis is realized. The proposed system has positive significance for reducing the fault rate of medium voltage switchgear and improving its operation and maintenance level.

Nondestructive Inspection System for Special Nuclear Material Using Inertial Electrostatic Confinement Fusion Neutrons and Laser Compton Scattering Gamma-Rays

NASA Astrophysics Data System (ADS)

Ohgaki, H.; Daito, I.; Zen, H.; Kii, T.; Masuda, K.; Misawa, T.; Hajima, R.; Hayakawa, T.; Shizuma, T.; Kando, M.; Fujimoto, S.

2017-07-01

A Neutron/Gamma-ray combined inspection system for hidden special nuclear materials (SNMs) in cargo containers has been developed under a program of Japan Science and Technology Agency in Japan. This inspection system consists of an active neutron-detection system for fast screening and a laser Compton backscattering gamma-ray source in coupling with nuclear resonance fluorescence (NRF) method for precise inspection. The inertial electrostatic confinement fusion device has been adopted as a neutron source and two neutron-detection methods, delayed neutron noise analysis method and high-energy neutron-detection method, have been developed to realize the fast screening system. The prototype system has been constructed and tested in the Reactor Research Institute, Kyoto University. For the generation of the laser Compton backscattering gamma-ray beam, a race track microtron accelerator has been used to reduce the size of the system. For the NRF measurement, an array of LaBr3(Ce) scintillation detectors has been adopted to realize a low-cost detection system. The prototype of the gamma-ray system has been demonstrated in the Kansai Photon Science Institute, National Institutes for Quantum and Radiological Science and Technology. By using numerical simulations based on the data taken from these prototype systems and the inspection-flow, the system designed by this program can detect 1 kg of highly enriched 235U (HEU) hidden in an empty 20-ft container within several minutes.

[Full Sibling Identification by IBS Scoring Method and Establishment of the Query Table of Its Critical Value].

PubMed

Li, R; Li, C T; Zhao, S M; Li, H X; Li, L; Wu, R G; Zhang, C C; Sun, H Y

2017-04-01

To establish a query table of IBS critical value and identification power for the detection systems with different numbers of STR loci under different false judgment standards. Samples of 267 pairs of full siblings and 360 pairs of unrelated individuals were collected and 19 autosomal STR loci were genotyped by Golden e ye™ 20A system. The full siblings were determined using IBS scoring method according to the 'Regulation for biological full sibling testing'. The critical values and identification power for the detection systems with different numbers of STR loci under different false judgment standards were calculated by theoretical methods. According to the formal IBS scoring criteria, the identification power of full siblings and unrelated individuals was 0.764 0 and the rate of false judgment was 0. The results of theoretical calculation were consistent with that of sample observation. The query table of IBS critical value for identification of full sibling detection systems with different numbers of STR loci was successfully established. The IBS scoring method defined by the regulation has high detection efficiency and low false judgment rate, which provides a relatively conservative result. The query table of IBS critical value for identification of full sibling detection systems with different numbers of STR loci provides an important reference data for the result judgment of full sibling testing and owns a considerable practical value. Copyright© by the Editorial Department of Journal of Forensic Medicine

Towards high-throughput molecular detection of Plasmodium: new approaches and molecular markers

PubMed Central

Steenkeste, Nicolas; Incardona, Sandra; Chy, Sophy; Duval, Linda; Ekala, Marie-Thérèse; Lim, Pharath; Hewitt, Sean; Sochantha, Tho; Socheat, Doung; Rogier, Christophe; Mercereau-Puijalon, Odile; Fandeur, Thierry; Ariey, Frédéric

2009-01-01

Background Several strategies are currently deployed in many countries in the tropics to strengthen malaria control toward malaria elimination. To measure the impact of any intervention, there is a need to detect malaria properly. Mostly, decisions still rely on microscopy diagnosis. But sensitive diagnosis tools enabling to deal with a large number of samples are needed. The molecular detection approach offers a much higher sensitivity, and the flexibility to be automated and upgraded. Methods Two new molecular methods were developed: dot18S, a Plasmodium-specific nested PCR based on the 18S rRNA gene followed by dot-blot detection of species by using species-specific probes and CYTB, a Plasmodium-specific nested PCR based on cytochrome b gene followed by species detection using SNP analysis. The results were compared to those obtained with microscopic examination and the "standard" 18S rRNA gene based nested PCR using species specific primers. 337 samples were diagnosed. Results Compared to the microscopy the three molecular methods were more sensitive, greatly increasing the estimated prevalence of Plasmodium infection, including P. malariae and P. ovale. A high rate of mixed infections was uncovered with about one third of the villagers infected with more than one malaria parasite species. Dot18S and CYTB sensitivity outranged the "standard" nested PCR method, CYTB being the most sensitive. As a consequence, compared to the "standard" nested PCR method for the detection of Plasmodium spp., the sensitivity of dot18S and CYTB was respectively 95.3% and 97.3%. Consistent detection of Plasmodium spp. by the three molecular methods was obtained for 83% of tested isolates. Contradictory results were mostly related to detection of Plasmodium malariae and Plasmodium ovale in mixed infections, due to an "all-or-none" detection effect at low-level parasitaemia. Conclusion A large reservoir of asymptomatic infections was uncovered using the molecular methods. Dot18S and CYTB, the new methods reported herein are highly sensitive, allow parasite DNA extraction as well as genus- and species-specific diagnosis of several hundreds of samples, and are amenable to high-throughput scaling up for larger sample sizes. Such methods provide novel information on malaria prevalence and epidemiology and are suited for active malaria detection. The usefulness of such sensitive malaria diagnosis tools, especially in low endemic areas where eradication plans are now on-going, is discussed in this paper. PMID:19402894

The determination of levofloxacin by flow injection analysis using UV detection, potentiometry, and conductometry in pharmaceutical preparations.

PubMed

Altiokka, G; Atkosar, Z; Can, N O

2002-10-15

A flow injection analysis (FIA) using UV detection, potentiometry and conductometry for levofloxacin (LVF) are described in this study. The best solvent system was found to consist of 0.2 M acetate buffer at pH 3 having 10% MeOH. A flow rate of 1 ml min(-1) was pumped and active material was detected at 288 nm. The detection limit (LOD) and limit of quantification (LOQ) for FIA were calculated to be 3 x 10(-7) M (S/N = 3) and 1 x 10(-7) M (S/N = 10), respectively. In the analysis of tablets, the RSD values were found to be 0.83, 0.98 and 0.99 for FIA, potentiometric and conductometric methods, respectively. Copyright 2002 Elsevier Science B.V.

High efficiency processing for reduced amplitude zones detection in the HRECG signal

NASA Astrophysics Data System (ADS)

Dugarte, N.; Álvarez, A.; Balacco, J.; Mercado, G.; Gonzalez, A.; Dugarte, E.; Olivares, A.

2016-04-01

Summary - This article presents part of a more detailed research proposed in the medium to long term, with the intention of establishing a new philosophy of electrocardiogram surface analysis. This research aims to find indicators of cardiovascular disease in its early stage that may go unnoticed with conventional electrocardiography. This paper reports the development of a software processing which collect some existing techniques and incorporates novel methods for detection of reduced amplitude zones (RAZ) in high resolution electrocardiographic signal (HRECG).The algorithm consists of three stages, an efficient processing for QRS detection, averaging filter using correlation techniques and a step for RAZ detecting. Preliminary results show the efficiency of system and point to incorporation of techniques new using signal analysis with involving 12 leads.