Validation of the ANSR® Listeria Method for Detection of Listeria spp. in Selected Foods.

PubMed

Caballero, Oscar; Alles, Susan; Wendorf, Michael; Gray, R Lucas; Walton, Kayla; Pinkava, Lisa; Mozola, Mark; Rice, Jennifer

2015-01-01

ANSR® Listeria was previously certified as Performance Tested Method(SM) 101202 for detection of Listeria spp. on selected environmental surfaces. This study proposes a matrix extension to the method for detection of Listeria spp. in selected food matrixes. The method is an isothermal nucleic acid amplification assay based on the nicking enzyme amplification reaction technology. Following single-step sample enrichment for 16-24 h, the assay is completed in less than 50 min, requiring only simple instrumentation. Inclusivity testing was performed using a panel of 51 strains of Listeria spp., representing the species L. grayi, L. innocua, L. ivanovii, L. monocytogenes, L. seeligeri, and L. welshimeri. All strains tested were detected by the ANSR assay. Exclusivity testing of 30 strains representing non-Listeria Gram-positive bacteria yielded no evidence of cross-reactivity. Performance of the ANSR method for detection of Listeria spp. was compared to that of reference culture procedures for pasteurized liquid egg, pasteurized 2% milk, Mexican-style cheese, ice cream, smoked salmon, lettuce, cantaloupe, and guacamole. Data obtained in these unpaired studies and analyzed using a probability of detection model demonstrated that there were no statistically significant differences in results between the ANSR and reference culture methods, except for milk at 16 h and cantaloupe. In milk and smoked salmon, ANSR sensitivity was low at 16 h and therefore the recommended incubation time is 24 h. In cantaloupe, ANSR was found to be more sensitive than the reference culture method at both 16 and 24 h in independent laboratory testing. The ANSR Listeria method can be used as an accurate, rapid, and simple alternative to standard culture methods for detection of Listeria spp. in selected food types.

Balancing precision and risk: should multiple detection methods be analyzed separately in N-mixture models?

USGS Publications Warehouse

Graves, Tabitha A.; Royle, J. Andrew; Kendall, Katherine C.; Beier, Paul; Stetz, Jeffrey B.; Macleod, Amy C.

2012-01-01

Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic) and bear rubs (opportunistic). We used hierarchical abundance models (N-mixture models) with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1) lead to the selection of the same variables as important and (2) provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3) yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight), and (4) improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed against those risks. The analysis framework presented here will be useful for other species exhibiting heterogeneity by detection method.

Attachment of second harmonic-active moiety to molecules for detection of molecules at interfaces

DOEpatents

Salafsky, Joshua S.; Eisenthal, Kenneth B.

2005-10-11

This invention provides methods of detecting molecules at an interface, which comprise labeling the molecules with a second harmonic-active moiety and detecting the labeled molecules at the interface using a surface selective technique. The invention also provides methods for detecting a molecule in a medium and for determining the orientation of a molecular species within a planar surface using a second harmonic-active moiety and a surface selective technique.

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

NASA Astrophysics Data System (ADS)

Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

2017-11-01

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

Advancing Explosives Detection Capabilities: Vapor Detection

ScienceCinema

Atkinson, David

2018-05-11

A new, PNNL-developed method provides direct, real-time detection of trace amounts of explosives such as RDX, PETN and C-4. The method selectively ionizes a sample before passing the sample through a mass spectrometer to detect explosive vapors. The method could be used at airports to improve aviation security.

Advancing Explosives Detection Capabilities: Vapor Detection

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

Atkinson, David

2012-10-15

A new, PNNL-developed method provides direct, real-time detection of trace amounts of explosives such as RDX, PETN and C-4. The method selectively ionizes a sample before passing the sample through a mass spectrometer to detect explosive vapors. The method could be used at airports to improve aviation security.

Heap/stack guard pages using a wakeup unit

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

Gooding, Thomas M; Satterfield, David L; Steinmacher-Burow, Burkhard

A method and system for providing a memory access check on a processor including the steps of detecting accesses to a memory device including level-1 cache using a wakeup unit. The method includes invalidating level-1 cache ranges corresponding to a guard page, and configuring a plurality of wakeup address compare (WAC) registers to allow access to selected WAC registers. The method selects one of the plurality of WAC registers, and sets up a WAC register related to the guard page. The method configures the wakeup unit to interrupt on access of the selected WAC register. The method detects access ofmore » the memory device using the wakeup unit when a guard page is violated. The method generates an interrupt to the core using the wakeup unit, and determines the source of the interrupt. The method detects the activated WAC registers assigned to the violated guard page, and initiates a response.« less

Chatter detection in milling process based on VMD and energy entropy

NASA Astrophysics Data System (ADS)

Liu, Changfu; Zhu, Lida; Ni, Chenbing

2018-05-01

This paper presents a novel approach to detect the milling chatter based on Variational Mode Decomposition (VMD) and energy entropy. VMD has already been employed in feature extraction from non-stationary signals. The parameters like number of modes (K) and the quadratic penalty (α) need to be selected empirically when raw signal is decomposed by VMD. Aimed at solving the problem how to select K and α, the automatic selection method of VMD's based on kurtosis is proposed in this paper. When chatter occurs in the milling process, energy will be absorbed to chatter frequency bands. To detect the chatter frequency bands automatically, the chatter detection method based on energy entropy is presented. The vibration signal containing chatter frequency is simulated and three groups of experiments which represent three cutting conditions are conducted. To verify the effectiveness of method presented by this paper, chatter feather extraction has been successfully employed on simulation signals and experimental signals. The simulation and experimental results show that the proposed method can effectively detect the chatter.

A sensitive and selective resonance Rayleigh scattering method for quick detection of avidin using affinity labeling Au nanoparticles

NASA Astrophysics Data System (ADS)

Wang, Qi; Huang, Xi; Fu, Xuan; Deng, Huan; Ma, Meihu; Cai, Zhaoxia

2016-06-01

Avidin is a glycoprotein with antinutritional property, which should be limited in daily food. We developed an affinity biosensor system based on resonance Rayleigh scattering (RRS) and using affinity biotin labeling Au nanoparticles (AuNPs). This method was selective and sensitive for quick avidin detection due to the avidin-biotin affinitive interaction. Under optimal conditions, RRS intensity of biotin-AuNPs increase linearly with an increasing concentration of avidin from 5 to 160 ng/mL. The lower limit of detection was 0.59 ng/mL. This rapid and selective avidin detection method was used in synthetic samples and egg products with recoveries of between 102.97 and 107.92%, thereby demonstrating the feasible and practical application of this assay.

Molecular sieve sensors for selective detection at the nanogram level

DOEpatents

Bein, Thomas; Brown, Kelly D.; Frye, Gregory C.; Brinker, Charles J.

1992-01-01

The invention relates to a selective chemical sensor for selective detection of chemical entities even at the nanogram level. The invention further relates to methods of using the sensor. The sensor comprises: (a) a piezoelectric substrate capable of detecting mass changes resulting from adsorption of material thereon; and (b) a coating applied to the substrate, which selectively sorbs chemical entities of a size smaller than a preselected magnitude.

Diagnosing and ranking retinopathy disease level using diabetic fundus image recuperation approach.

PubMed

Somasundaram, K; Rajendran, P Alli

2015-01-01

Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED) and Optimally Adjusted Morphological Operator (OAMO) effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR) method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time.

Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image Recuperation Approach

PubMed Central

Somasundaram, K.; Alli Rajendran, P.

2015-01-01

Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED) and Optimally Adjusted Morphological Operator (OAMO) effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR) method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time. PMID:25945362

Feature selection from hyperspectral imaging for guava fruit defects detection

NASA Astrophysics Data System (ADS)

Mat Jafri, Mohd. Zubir; Tan, Sou Ching

2017-06-01

Development of technology makes hyperspectral imaging commonly used for defect detection. In this research, a hyperspectral imaging system was setup in lab to target for guava fruits defect detection. Guava fruit was selected as the object as to our knowledge, there is fewer attempts were made for guava defect detection based on hyperspectral imaging. The common fluorescent light source was used to represent the uncontrolled lighting condition in lab and analysis was carried out in a specific wavelength range due to inefficiency of this particular light source. Based on the data, the reflectance intensity of this specific setup could be categorized in two groups. Sequential feature selection with linear discriminant (LD) and quadratic discriminant (QD) function were used to select features that could potentially be used in defects detection. Besides the ordinary training method, training dataset in discriminant was separated in two to cater for the uncontrolled lighting condition. These two parts were separated based on the brighter and dimmer area. Four evaluation matrixes were evaluated which are LD with common training method, QD with common training method, LD with two part training method and QD with two part training method. These evaluation matrixes were evaluated using F1-score with total 48 defected areas. Experiment shown that F1-score of linear discriminant with the compensated method hitting 0.8 score, which is the highest score among all.

Structure-property study of the Raman spectroscopy detection of fusaric acid and analogs

USDA-ARS?s Scientific Manuscript database

Food security can benefit from the development of selective methods to detect toxins. Fusaric acid is a mycotoxin produced by certain fungi occasionally found in agricultural commodities. Raman spectroscopy allows selective detection of analytes associated with certain spectral characteristics relat...

Magnetically-focusing biochip structures for high-speed active biosensing with improved selectivity.

PubMed

Yoo, Haneul; Lee, Dong Jun; Kim, Daesan; Park, Juhun; Chen, Xing; Hong, Seunghun

2018-06-29

We report a magnetically-focusing biochip structure enabling a single layered magnetic trap-and-release cycle for biosensors with an improved detection speed and selectivity. Here, magnetic beads functionalized with specific receptor molecules were utilized to trap target molecules in a solution and transport actively to and away from the sensor surfaces to enhance the detection speed and reduce the non-specific bindings, respectively. Using our method, we demonstrated the high speed detection of IL-13 antigens with the improved detection speed by more than an order of magnitude. Furthermore, the release step in our method was found to reduce the non-specific bindings and improve the selectivity and sensitivity of biosensors. This method is a simple but powerful strategy and should open up various applications such as ultra-fast biosensors for point-of-care services.

Magnetically-focusing biochip structures for high-speed active biosensing with improved selectivity

NASA Astrophysics Data System (ADS)

Yoo, Haneul; Lee, Dong Jun; Kim, Daesan; Park, Juhun; Chen, Xing; Hong, Seunghun

2018-06-01

We report a magnetically-focusing biochip structure enabling a single layered magnetic trap-and-release cycle for biosensors with an improved detection speed and selectivity. Here, magnetic beads functionalized with specific receptor molecules were utilized to trap target molecules in a solution and transport actively to and away from the sensor surfaces to enhance the detection speed and reduce the non-specific bindings, respectively. Using our method, we demonstrated the high speed detection of IL-13 antigens with the improved detection speed by more than an order of magnitude. Furthermore, the release step in our method was found to reduce the non-specific bindings and improve the selectivity and sensitivity of biosensors. This method is a simple but powerful strategy and should open up various applications such as ultra-fast biosensors for point-of-care services.

Increasing selectivity for TNT-based explosive detection by synchronous luminescence and derivative spectroscopy with quantum yields of selected aromatic amines.

PubMed

Sheaff, Chrystal N; Eastwood, Delyle; Wai, Chien M

2007-01-01

The detection of explosive material is at the forefront of current analytical problems. A detection method is desired that is not restricted to detecting only explosive materials, but is also capable of identifying the origin and type of explosive. It is essential that a detection method have the selectivity to distinguish among compounds in a mixture of explosives. The nitro compounds found in explosives have low fluorescent yields or are considered to be non-fluorescent; however, after reduction, the amino compounds exhibit relatively high fluorescence. We discuss how to increase selectivity of explosive detection using fluorescence; this includes synchronous luminescence and derivative spectroscopy with appropriate smoothing. By implementing synchronous luminescence and derivative spectroscopy, we were able to resolve the reduction products of one major TNT-based explosive compound, 2,4-diaminotoluene, and the reduction products of other minor TNT-based explosives in a mixture. We also report for the first time the quantum yields of these important compounds. Relative quantum yields are useful in establishing relative fluorescence intensities and are an important spectroscopic measurement of molecules. Our approach allows for rapid, sensitive, and selective detection with the discrimination necessary to distinguish among various explosives.

Visual detection of glial cell line-derived neurotrophic factor based on a molecular translator and isothermal strand-displacement polymerization reaction.

PubMed

Zhang, Li-Yong; Xing, Tao; Du, Li-Xin; Li, Qing-Min; Liu, Wei-Dong; Wang, Ji-Yue; Cai, Jing

2015-01-01

Glial cell line-derived neurotrophic factor (GDNF) is a small protein that potently promotes the survival of many types of neurons. Detection of GDNF is vital to monitoring the survival of sympathetic and sensory neurons. However, the specific method for GDNF detection is also un-discovered. The purpose of this study is to explore the method for protein detection of GDNF. A novel visual detection method based on a molecular translator and isothermal strand-displacement polymerization reaction (ISDPR) has been proposed for the detection of GDNF. In this study, a molecular translator was employed to convert the input protein to output deoxyribonucleic acid signal, which was further amplified by ISDPR. The product of ISDPR was detected by a lateral flow biosensor within 30 minutes. This novel visual detection method based on a molecular translator and ISDPR has very high sensitivity and selectivity, with a dynamic response ranging from 1 pg/mL to 10 ng/mL, and the detection limit was 1 pg/mL of GDNF. This novel visual detection method exhibits high sensitivity and selectivity, which is very simple and universal for GDNF detection to help disease therapy in clinical practice.

Detecting Selection on Temporal and Spatial Scales: A Genomic Time-Series Assessment of Selective Responses to Devil Facial Tumor Disease

PubMed Central

Brüniche-Olsen, Anna; Austin, Jeremy J.; Jones, Menna E.; Holland, Barbara R.; Burridge, Christopher P.

2016-01-01

Detecting loci under selection is an important task in evolutionary biology. In conservation genetics detecting selection is key to investigating adaptation to the spread of infectious disease. Loci under selection can be detected on a spatial scale, accounting for differences in demographic history among populations, or on a temporal scale, tracing changes in allele frequencies over time. Here we use these two approaches to investigate selective responses to the spread of an infectious cancer—devil facial tumor disease (DFTD)—that since 1996 has ravaged the Tasmanian devil (Sarcophilus harrisii). Using time-series ‘restriction site associated DNA’ (RAD) markers from populations pre- and post DFTD arrival, and DFTD free populations, we infer loci under selection due to DFTD and investigate signatures of selection that are incongruent among methods, populations, and times. The lack of congruence among populations influenced by DFTD with respect to inferred loci under selection, and the direction of that selection, fail to implicate a consistent selective role for DFTD. Instead genetic drift is more likely driving the observed allele frequency changes over time. Our study illustrates the importance of applying methods with different performance optima e.g. accounting for population structure and background selection, and assessing congruence of the results. PMID:26930198

Fringe order correction for the absolute phase recovered by two selected spatial frequency fringe projections in fringe projection profilometry.

PubMed

Ding, Yi; Peng, Kai; Yu, Miao; Lu, Lei; Zhao, Kun

2017-08-01

The performance of the two selected spatial frequency phase unwrapping methods is limited by a phase error bound beyond which errors will occur in the fringe order leading to a significant error in the recovered absolute phase map. In this paper, we propose a method to detect and correct the wrong fringe orders. Two constraints are introduced during the fringe order determination of two selected spatial frequency phase unwrapping methods. A strategy to detect and correct the wrong fringe orders is also described. Compared with the existing methods, we do not need to estimate the threshold associated with absolute phase values to determine the fringe order error, thus making it more reliable and avoiding the procedure of search in detecting and correcting successive fringe order errors. The effectiveness of the proposed method is validated by the experimental results.

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

NASA Astrophysics Data System (ADS)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

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

Max-AUC Feature Selection in Computer-Aided Detection of Polyps in CT Colonography

PubMed Central

Xu, Jian-Wu; Suzuki, Kenji

2014-01-01

We propose a feature selection method based on a sequential forward floating selection (SFFS) procedure to improve the performance of a classifier in computerized detection of polyps in CT colonography (CTC). The feature selection method is coupled with a nonlinear support vector machine (SVM) classifier. Unlike the conventional linear method based on Wilks' lambda, the proposed method selected the most relevant features that would maximize the area under the receiver operating characteristic curve (AUC), which directly maximizes classification performance, evaluated based on AUC value, in the computer-aided detection (CADe) scheme. We presented two variants of the proposed method with different stopping criteria used in the SFFS procedure. The first variant searched all feature combinations allowed in the SFFS procedure and selected the subsets that maximize the AUC values. The second variant performed a statistical test at each step during the SFFS procedure, and it was terminated if the increase in the AUC value was not statistically significant. The advantage of the second variant is its lower computational cost. To test the performance of the proposed method, we compared it against the popular stepwise feature selection method based on Wilks' lambda for a colonic-polyp database (25 polyps and 2624 nonpolyps). We extracted 75 morphologic, gray-level-based, and texture features from the segmented lesion candidate regions. The two variants of the proposed feature selection method chose 29 and 7 features, respectively. Two SVM classifiers trained with these selected features yielded a 96% by-polyp sensitivity at false-positive (FP) rates of 4.1 and 6.5 per patient, respectively. Experiments showed a significant improvement in the performance of the classifier with the proposed feature selection method over that with the popular stepwise feature selection based on Wilks' lambda that yielded 18.0 FPs per patient at the same sensitivity level. PMID:24608058

Max-AUC feature selection in computer-aided detection of polyps in CT colonography.

PubMed

Xu, Jian-Wu; Suzuki, Kenji

2014-03-01

We propose a feature selection method based on a sequential forward floating selection (SFFS) procedure to improve the performance of a classifier in computerized detection of polyps in CT colonography (CTC). The feature selection method is coupled with a nonlinear support vector machine (SVM) classifier. Unlike the conventional linear method based on Wilks' lambda, the proposed method selected the most relevant features that would maximize the area under the receiver operating characteristic curve (AUC), which directly maximizes classification performance, evaluated based on AUC value, in the computer-aided detection (CADe) scheme. We presented two variants of the proposed method with different stopping criteria used in the SFFS procedure. The first variant searched all feature combinations allowed in the SFFS procedure and selected the subsets that maximize the AUC values. The second variant performed a statistical test at each step during the SFFS procedure, and it was terminated if the increase in the AUC value was not statistically significant. The advantage of the second variant is its lower computational cost. To test the performance of the proposed method, we compared it against the popular stepwise feature selection method based on Wilks' lambda for a colonic-polyp database (25 polyps and 2624 nonpolyps). We extracted 75 morphologic, gray-level-based, and texture features from the segmented lesion candidate regions. The two variants of the proposed feature selection method chose 29 and 7 features, respectively. Two SVM classifiers trained with these selected features yielded a 96% by-polyp sensitivity at false-positive (FP) rates of 4.1 and 6.5 per patient, respectively. Experiments showed a significant improvement in the performance of the classifier with the proposed feature selection method over that with the popular stepwise feature selection based on Wilks' lambda that yielded 18.0 FPs per patient at the same sensitivity level.

Detection methods and performance criteria for genetically modified organisms.

PubMed

Bertheau, Yves; Diolez, Annick; Kobilinsky, André; Magin, Kimberly

2002-01-01

Detection methods for genetically modified organisms (GMOs) are necessary for many applications, from seed purity assessment to compliance of food labeling in several countries. Numerous analytical methods are currently used or under development to support these needs. The currently used methods are bioassays and protein- and DNA-based detection protocols. To avoid discrepancy of results between such largely different methods and, for instance, the potential resulting legal actions, compatibility of the methods is urgently needed. Performance criteria of methods allow evaluation against a common standard. The more-common performance criteria for detection methods are precision, accuracy, sensitivity, and specificity, which together specifically address other terms used to describe the performance of a method, such as applicability, selectivity, calibration, trueness, precision, recovery, operating range, limit of quantitation, limit of detection, and ruggedness. Performance criteria should provide objective tools to accept or reject specific methods, to validate them, to ensure compatibility between validated methods, and be used on a routine basis to reject data outside an acceptable range of variability. When selecting a method of detection, it is also important to consider its applicability, its field of applications, and its limitations, by including factors such as its ability to detect the target analyte in a given matrix, the duration of the analyses, its cost effectiveness, and the necessary sample sizes for testing. Thus, the current GMO detection methods should be evaluated against a common set of performance criteria.

A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data

PubMed Central

DeGiorgio, Michael; Lohmueller, Kirk E.; Nielsen, Rasmus

2014-01-01

While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates. PMID:25144706

A model-based approach for identifying signatures of ancient balancing selection in genetic data.

PubMed

DeGiorgio, Michael; Lohmueller, Kirk E; Nielsen, Rasmus

2014-08-01

While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates.

Visual detection of glial cell line-derived neurotrophic factor based on a molecular translator and isothermal strand-displacement polymerization reaction

PubMed Central

Zhang, Li-Yong; Xing, Tao; Du, Li-Xin; Li, Qing-Min; Liu, Wei-Dong; Wang, Ji-Yue; Cai, Jing

2015-01-01

Background Glial cell line-derived neurotrophic factor (GDNF) is a small protein that potently promotes the survival of many types of neurons. Detection of GDNF is vital to monitoring the survival of sympathetic and sensory neurons. However, the specific method for GDNF detection is also un-discovered. The purpose of this study is to explore the method for protein detection of GDNF. Methods A novel visual detection method based on a molecular translator and isothermal strand-displacement polymerization reaction (ISDPR) has been proposed for the detection of GDNF. In this study, a molecular translator was employed to convert the input protein to output deoxyribonucleic acid signal, which was further amplified by ISDPR. The product of ISDPR was detected by a lateral flow biosensor within 30 minutes. Results This novel visual detection method based on a molecular translator and ISDPR has very high sensitivity and selectivity, with a dynamic response ranging from 1 pg/mL to 10 ng/mL, and the detection limit was 1 pg/mL of GDNF. Conclusion This novel visual detection method exhibits high sensitivity and selectivity, which is very simple and universal for GDNF detection to help disease therapy in clinical practice. PMID:25848224

Aqueous nitrite ion determination by selective reduction and gas phase nitric oxide chemiluminescence

NASA Technical Reports Server (NTRS)

Dunham, A. J.; Barkley, R. M.; Sievers, R. E.; Clarkson, T. W. (Principal Investigator)

1995-01-01

An improved method of flow injection analysis for aqueous nitrite ion exploits the sensitivity and selectivity of the nitric oxide (NO) chemilluminescence detector. Trace analysis of nitrite ion in a small sample (5-160 microL) is accomplished by conversion of nitrite ion to NO by aqueous iodide in acid. The resulting NO is transported to the gas phase through a semipermeable membrane and subsequently detected by monitoring the photoemission of the reaction between NO and ozone (O3). Chemiluminescence detection is selective for measurement of NO, and, since the detection occurs in the gas-phase, neither sample coloration nor turbidity interfere. The detection limit for a 100-microL sample is 0.04 ppb of nitrite ion. The precision at the 10 ppb level is 2% relative standard deviation, and 60-180 samples can be analyzed per hour. Samples of human saliva and food extracts were analyzed; the results from a standard colorimetric measurement are compared with those from the new chemiluminescence method in order to further validate the latter method. A high degree of selectivity is obtained due to the three discriminating steps in the process: (1) the nitrite ion to NO conversion conditions are virtually specific for nitrite ion, (2) only volatile products of the conversion will be swept to the gas phase (avoiding turbidity or color in spectrophotometric methods), and (3) the NO chemiluminescence detector selectively detects the emission from the NO + O3 reaction. The method is free of interferences, offers detection limits of low parts per billion of nitrite ion, and allows the analysis of up to 180 microL-sized samples per hour, with little sample preparation and no chromatographic separation. Much smaller samples can be analyzed by this method than in previously reported batch analysis methods, which typically require 5 mL or more of sample and often need chromatographic separations as well.

Comparison of Chromogenic Selective Media for the Detection of Cronobacter spp. (Enterobacter sakazakii).

PubMed

Teramura, Hajime; Fukuda, Noriko; Okada, Yumiko; Ogihara, Hirokazu

2018-01-01

　The four types of chromogenic selective media that are commercially available in Japan were compared for establishing a Japanese standard method for detecting Cronobacter spp. based on ISO/TS 22964:2006. When assessed using 9 standard Cronobacter spp. strains and 29 non-Cronobacter strains, Enterobacter sakazakii isolation agar, Chromocult TM Enterobacter sakazakii agar, CHROMagar TM E. sakazakii, and XM-sakazakii agar demonstrated excellent inclusivity and exclusivity. Using the ISO/TS 22964:2006 method, the recovered numbers of 38 Cronobacter spp. strains, including 29 C. sakazakii isolates obtained from each medium, were equivalent, indicating that there was no significant difference (p > 0.05) among the four types of chromogenic selective media. Thus, we demonstrated that these four chromogenic selective media are suitable alternatives when using the standard method for detecting Cronobacter spp. in Japan, based on the ISO/TS 22964:2006.

AOAC Official MethodSM Matrix Extension Validation Study of Assurance GDSTM for the Detection of Salmonella in Selected Spices.

PubMed

Feldsine, Philip; Kaur, Mandeep; Shah, Khyati; Immerman, Amy; Jucker, Markus; Lienau, Andrew

2015-01-01

Assurance GDSTM for Salmonella Tq has been validated according to the AOAC INTERNATIONAL Methods Committee Guidelines for Validation of Microbiological Methods for Food and Environmental Surfaces for the detection of selected foods and environmental surfaces (Official Method of AnalysisSM 2009.03, Performance Tested MethodSM No. 050602). The method also completed AFNOR validation (following the ISO 16140 standard) compared to the reference method EN ISO 6579. For AFNOR, GDS was given a scope covering all human food, animal feed stuff, and environmental surfaces (Certificate No. TRA02/12-01/09). Results showed that Assurance GDS for Salmonella (GDS) has high sensitivity and is equivalent to the reference culture methods for the detection of motile and non-motile Salmonella. As part of the aforementioned validations, inclusivity and exclusivity studies, stability, and ruggedness studies were also conducted. Assurance GDS has 100% inclusivity and exclusivity among the 100 Salmonella serovars and 35 non-Salmonella organisms analyzed. To add to the scope of the Assurance GDS for Salmonella method, a matrix extension study was conducted, following the AOAC guidelines, to validate the application of the method for selected spices, specifically curry powder, cumin powder, and chili powder, for the detection of Salmonella.

Roka Listeria detection method using transcription mediated amplification to detect Listeria species in select foods and surfaces. Performance Tested Method(SM) 011201.

PubMed

Hua, Yang; Kaplan, Shannon; Reshatoff, Michael; Hu, Ernie; Zukowski, Alexis; Schweis, Franz; Gin, Cristal; Maroni, Brett; Becker, Michael; Wisniewski, Michele

2012-01-01

The Roka Listeria Detection Assay was compared to the reference culture methods for nine select foods and three select surfaces. The Roka method used Half-Fraser Broth for enrichment at 35 +/- 2 degrees C for 24-28 h. Comparison of Roka's method to reference methods requires an unpaired approach. Each method had a total of 545 samples inoculated with a Listeria strain. Each food and surface was inoculated with a different strain of Listeria at two different levels per method. For the dairy products (Brie cheese, whole milk, and ice cream), our method was compared to AOAC Official Method(SM) 993.12. For the ready-to-eat meats (deli chicken, cured ham, chicken salad, and hot dogs) and environmental surfaces (sealed concrete, stainless steel, and plastic), these samples were compared to the U.S. Department of Agriculture/Food Safety and Inspection Service-Microbiology Laboratory Guidebook (USDA/FSIS-MLG) method MLG 8.07. Cold-smoked salmon and romaine lettuce were compared to the U.S. Food and Drug Administration/Bacteriological Analytical Manual, Chapter 10 (FDA/BAM) method. Roka's method had 358 positives out of 545 total inoculated samples compared to 332 positive for the reference methods. Overall the probability of detection analysis of the results showed better or equivalent performance compared to the reference methods.

Colorimetric and fluorescent detection of hydrazine with high sensitivity and excellent selectivity

NASA Astrophysics Data System (ADS)

Shi, Bingjie; Qi, Sujie; Yu, Mingming; Liu, Chunxia; Li, Zhanxian; Wei, Liuhe; Ni, Zhonghai

2018-01-01

It is critical to develop probes for rapid, selective, and sensitive detection of the highly toxic hydrazine in both environmental and biological science. In this work, under mild condition, a novel colorimetric and off-on fluorescent probe was synthesized for rapid recognition of hydrazine with excellent selectivity over other various species including some biological species, metal ions and anions. The limit of quantification (LOQ) value was 1.5 × 10- 4 M-3.2 × 10- 3 M (colorimetric method) and 1.5 × 10- 4 M - 3.2 × 10- 3 M (fluorescent method) with as low as detection limit of 46.2 μM.

Colorimetric method for the detection of melamine using in-situ formed silver nanoparticles via tannic acid

NASA Astrophysics Data System (ADS)

Alam, Md. Fazle; Laskar, Amaj Ahmed; Ahmed, Shahbaz; Shaida, Mohd. Azfar; Younus, Hina

2017-08-01

Melamine toxicity has recently attracted worldwide attention as it causes renal failure and the death of humans and animals. Therefore, developing a simple, fast and sensitive method for the routine detection of melamine is the need of the hour. Herein, we have developed a selective colorimetric method for the detection of melamine in milk samples based upon in-situ formation of silver nanoparticles (AgNPs) via tannic acid. The AgNPs thus formed were characterized by UV-Visible spectrophotometer, transmission electron microscope (TEM), zetasizer and dynamic light scattering (DLS). The AgNPs were used to detect melamine under in vitro condition and in raw milk spiked with melamine. Under optimal conditions, melamine could be selectively detected in vitro within the concentration range of 0.05-1.4 μM with a limit of detection (LOD) of 0.01 μM, which is lower than the strictest melamine safety requirement of 1 ppm. In spiked raw milk, the recovery percentage range was 99.5-106.5% for liquid milk and 98.5-105.5% for powdered milk. The present method shows extreme selectivity with no significant interference with other substances like urea, glucose, glycine, ascorbic acid etc. This assay method does not utilize organic cosolvents, enzymatic reactions, light sensitive dye molecules and sophisticated instrumentation, thereby overcoming some of the limitations of the other conventional methods.

Recurrent bottlenecks in the malaria life cycle obscure signals of positive selection.

PubMed

Chang, Hsiao-Han; Hartl, Daniel L

2015-02-01

Detecting signals of selection in the genome of malaria parasites is a key to identify targets for drug and vaccine development. Malaria parasites have a unique life cycle alternating between vector and host organism with a population bottleneck at each transition. These recurrent bottlenecks could influence the patterns of genetic diversity and the power of existing population genetic tools to identify sites under positive selection. We therefore simulated the site-frequency spectrum of a beneficial mutant allele through time under the malaria life cycle. We investigated the power of current population genetic methods to detect positive selection based on the site-frequency spectrum as well as temporal changes in allele frequency. We found that a within-host selective advantage is difficult to detect using these methods. Although a between-host transmission advantage could be detected, the power is decreased when compared with the classical Wright-Fisher (WF) population model. Using an adjusted null site-frequency spectrum that takes the malaria life cycle into account, the power of tests based on the site-frequency spectrum to detect positive selection is greatly improved. Our study demonstrates the importance of considering the life cycle in genetic analysis, especially in parasites with complex life cycles.

Selective counting and sizing of single virus particles using fluorescent aptamer-based nanoparticle tracking analysis.

PubMed

Szakács, Zoltán; Mészáros, Tamás; de Jonge, Marien I; Gyurcsányi, Róbert E

2018-05-30

Detection and counting of single virus particles in liquid samples are largely limited to narrow size distribution of viruses and purified formulations. To address these limitations, here we propose a calibration-free method that enables concurrently the selective recognition, counting and sizing of virus particles as demonstrated through the detection of human respiratory syncytial virus (RSV), an enveloped virus with a broad size distribution, in throat swab samples. RSV viruses were selectively labeled through their attachment glycoproteins (G) with fluorescent aptamers, which further enabled their identification, sizing and counting at the single particle level by fluorescent nanoparticle tracking analysis. The proposed approach seems to be generally applicable to virus detection and quantification. Moreover, it could be successfully applied to detect single RSV particles in swab samples of diagnostic relevance. Since the selective recognition is associated with the sizing of each detected particle, this method enables to discriminate viral elements linked to the virus as well as various virus forms and associations.

LOSITAN: a workbench to detect molecular adaptation based on a Fst-outlier method.

PubMed

Antao, Tiago; Lopes, Ana; Lopes, Ricardo J; Beja-Pereira, Albano; Luikart, Gordon

2008-07-28

Testing for selection is becoming one of the most important steps in the analysis of multilocus population genetics data sets. Existing applications are difficult to use, leaving many non-trivial, error-prone tasks to the user. Here we present LOSITAN, a selection detection workbench based on a well evaluated Fst-outlier detection method. LOSITAN greatly facilitates correct approximation of model parameters (e.g., genome-wide average, neutral Fst), provides data import and export functions, iterative contour smoothing and generation of graphics in a easy to use graphical user interface. LOSITAN is able to use modern multi-core processor architectures by locally parallelizing fdist, reducing computation time by half in current dual core machines and with almost linear performance gains in machines with more cores. LOSITAN makes selection detection feasible to a much wider range of users, even for large population genomic datasets, by both providing an easy to use interface and essential functionality to complete the whole selection detection process.

Sensitive and molecular size-selective detection of proteins using a chip-based and heteroliganded gold nanoisland by localized surface plasmon resonance spectroscopy

NASA Astrophysics Data System (ADS)

Hong, Surin; Lee, Suseung; Yi, Jongheop

2011-04-01

A highly sensitive and molecular size-selective method for the detection of proteins using heteroliganded gold nanoislands and localized surface plasmon resonance (LSPR) is described. Two different heteroligands with different chain lengths (3-mercaptopionicacid and decanethiol) were used in fabricating nanoholes for the size-dependent separation of a protein in comparison with its aggregate. Their ratios on gold nanoisland were optimized for the sensitive detection of superoxide dismutase (SOD1). This protein has been implicated in the pathology of amyotrophic lateral sclerosis (ALS). Upon exposure of the optimized gold nanoisland to a solution of SOD1 and aggregates thereof, changes in the LSPR spectra were observed which are attributed to the size-selective and covalent chemical binding of SOD1 to the nanoholes. With a lower detection limit of 1.0 ng/ml, the method can be used to selectively detect SOD1 in the presence of aggregates at the molecular level.

Early Recovery of Salmonella from Food Using a 6-Hour Non-selective Pre-enrichment and Reformulation of Tetrathionate Broth.

PubMed

Daquigan, Ninalynn; Grim, Christopher J; White, James R; Hanes, Darcy E; Jarvis, Karen G

2016-01-01

Culture based methods are commonly employed to detect pathogens in food and environmental samples. These methods are time consuming and complex, requiring multiple non-selective and selective enrichment broths, and usually take at least 1 week to recover and identify pathogens. Improving pathogen detection in foods is a primary goal for regulatory agencies and industry. Salmonella detection in food relies on a series of culture steps in broth formulations optimized to resuscitate Salmonella and reduce the abundance of competitive bacteria. Examples of non-selective pre-enrichment broths used to isolate Salmonella from food include Lactose, Universal Pre-enrichment, BPW, and Trypticase Soy broths. Tetrathionate (TT) and Rappaport-Vassiliadis (RV) broths are employed after a 24-h non-selective enrichment to select for Salmonella and hamper the growth of competitive bacteria. In this study, we tested a new formulation of TT broth that lacks brilliant green dye and has lower levels of TT . We employed this TT broth formulation in conjunction with a 6-h non-selective pre-enrichment period and determined that Salmonella recovery was possible one day earlier than standard food culture methods. We tested the shortened culture method in different non-selective enrichment broths, enumerated Salmonella in the non-selective enrichments, and used 16S rRNA gene sequencing to determine the proportional abundances of Salmonella in the TT and RV selective enrichments. Together these data revealed that a 6-h non-selective pre-enrichment reduces the levels of competitive bacteria inoculated into the selective TT and RV broths, enabling the recovery of Salmonella 1 day earlier than standard culture enrichment methods.

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.

Kernel parameter variation-based selective ensemble support vector data description for oil spill detection on the ocean via hyperspectral imaging

NASA Astrophysics Data System (ADS)

Uslu, Faruk Sukru

2017-07-01

Oil spills on the ocean surface cause serious environmental, political, and economic problems. Therefore, these catastrophic threats to marine ecosystems require detection and monitoring. Hyperspectral sensors are powerful optical sensors used for oil spill detection with the help of detailed spectral information of materials. However, huge amounts of data in hyperspectral imaging (HSI) require fast and accurate computation methods for detection problems. Support vector data description (SVDD) is one of the most suitable methods for detection, especially for large data sets. Nevertheless, the selection of kernel parameters is one of the main problems in SVDD. This paper presents a method, inspired by ensemble learning, for improving performance of SVDD without tuning its kernel parameters. Additionally, a classifier selection technique is proposed to get more gain. The proposed approach also aims to solve the small sample size problem, which is very important for processing high-dimensional data in HSI. The algorithm is applied to two HSI data sets for detection problems. In the first HSI data set, various targets are detected; in the second HSI data set, oil spill detection in situ is realized. The experimental results demonstrate the feasibility and performance improvement of the proposed algorithm for oil spill detection problems.

Selective Detection of Peptide-Oligonucleotide Heteroconjugates Utilizing Capillary HPLC-ICPMS

NASA Astrophysics Data System (ADS)

Catron, Brittany; Caruso, Joseph A.; Limbach, Patrick A.

2012-06-01

A method for the selective detection and quantification of peptide:oligonucleotide heteroconjugates, such as those generated by protein:nucleic acid cross-links, using capillary reversed-phase high performance liquid chromatography (cap-RPHPLC) coupled with inductively coupled plasma mass spectrometry detection (ICPMS) is described. The selective detection of phosphorus as 31P+, the only natural isotope, in peptide-oligonucleotide heteroconjugates is enabled by the elemental detection capabilities of the ICPMS. Mobile phase conditions that allow separation of heteroconjugates while maintaining ICPMS compatibility were investigated. We found that trifluoroacetic acid (TFA) mobile phases, used in conventional peptide separations, and hexafluoroisopropanol/triethylamine (HFIP/TEA) mobile phases, used in conventional oligonucleotide separations, both are compatible with ICPMS and enable heteroconjugate separation. The TFA-based separations yielded limits of detection (LOD) of ~40 ppb phosphorus, which is nearly seven times lower than the LOD for HFIP/TEA-based separations. Using the TFA mobile phase, 1-2 pmol of a model heteroconjugate were routinely separated and detected by this optimized capLC-ICPMS method.

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Multiplex Real-Time PCR for Detection of Staphylococcus aureus, mecA and Panton-Valentine Leukocidin (PVL) Genes from Selective Enrichments from Animals and Retail Meat

PubMed Central

Velasco, Valeria; Sherwood, Julie S.; Rojas-García, Pedro P.; Logue, Catherine M.

2014-01-01

The aim of this study was to compare a real-time PCR assay, with a conventional culture/PCR method, to detect S. aureus, mecA and Panton-Valentine Leukocidin (PVL) genes in animals and retail meat, using a two-step selective enrichment protocol. A total of 234 samples were examined (77 animal nasal swabs, 112 retail raw meat, and 45 deli meat). The multiplex real-time PCR targeted the genes: nuc (identification of S. aureus), mecA (associated with methicillin resistance) and PVL (virulence factor), and the primary and secondary enrichment samples were assessed. The conventional culture/PCR method included the two-step selective enrichment, selective plating, biochemical testing, and multiplex PCR for confirmation. The conventional culture/PCR method recovered 95/234 positive S. aureus samples. Application of real-time PCR on samples following primary and secondary enrichment detected S. aureus in 111/234 and 120/234 samples respectively. For detection of S. aureus, the kappa statistic was 0.68–0.88 (from substantial to almost perfect agreement) and 0.29–0.77 (from fair to substantial agreement) for primary and secondary enrichments, using real-time PCR. For detection of mecA gene, the kappa statistic was 0–0.49 (from no agreement beyond that expected by chance to moderate agreement) for primary and secondary enrichment samples. Two pork samples were mecA gene positive by all methods. The real-time PCR assay detected the mecA gene in samples that were negative for S. aureus, but positive for Staphylococcus spp. The PVL gene was not detected in any sample by the conventional culture/PCR method or the real-time PCR assay. Among S. aureus isolated by conventional culture/PCR method, the sequence type ST398, and multi-drug resistant strains were found in animals and raw meat samples. The real-time PCR assay may be recommended as a rapid method for detection of S. aureus and the mecA gene, with further confirmation of methicillin-resistant S. aureus (MRSA) using the standard culture method. PMID:24849624

Multiplex real-time PCR for detection of Staphylococcus aureus, mecA and Panton-Valentine Leukocidin (PVL) genes from selective enrichments from animals and retail meat.

PubMed

Velasco, Valeria; Sherwood, Julie S; Rojas-García, Pedro P; Logue, Catherine M

2014-01-01

The aim of this study was to compare a real-time PCR assay, with a conventional culture/PCR method, to detect S. aureus, mecA and Panton-Valentine Leukocidin (PVL) genes in animals and retail meat, using a two-step selective enrichment protocol. A total of 234 samples were examined (77 animal nasal swabs, 112 retail raw meat, and 45 deli meat). The multiplex real-time PCR targeted the genes: nuc (identification of S. aureus), mecA (associated with methicillin resistance) and PVL (virulence factor), and the primary and secondary enrichment samples were assessed. The conventional culture/PCR method included the two-step selective enrichment, selective plating, biochemical testing, and multiplex PCR for confirmation. The conventional culture/PCR method recovered 95/234 positive S. aureus samples. Application of real-time PCR on samples following primary and secondary enrichment detected S. aureus in 111/234 and 120/234 samples respectively. For detection of S. aureus, the kappa statistic was 0.68-0.88 (from substantial to almost perfect agreement) and 0.29-0.77 (from fair to substantial agreement) for primary and secondary enrichments, using real-time PCR. For detection of mecA gene, the kappa statistic was 0-0.49 (from no agreement beyond that expected by chance to moderate agreement) for primary and secondary enrichment samples. Two pork samples were mecA gene positive by all methods. The real-time PCR assay detected the mecA gene in samples that were negative for S. aureus, but positive for Staphylococcus spp. The PVL gene was not detected in any sample by the conventional culture/PCR method or the real-time PCR assay. Among S. aureus isolated by conventional culture/PCR method, the sequence type ST398, and multi-drug resistant strains were found in animals and raw meat samples. The real-time PCR assay may be recommended as a rapid method for detection of S. aureus and the mecA gene, with further confirmation of methicillin-resistant S. aureus (MRSA) using the standard culture method.

Thin Cloud Detection Method by Linear Combination Model of Cloud Image

NASA Astrophysics Data System (ADS)

Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

2018-04-01

The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.

Identification of selection footprints on the X chromosome in pig.

PubMed

Ma, Yunlong; Zhang, Haihan; Zhang, Qin; Ding, Xiangdong

2014-01-01

Identifying footprints of selection can provide a straightforward insight into the mechanism of artificial selection and further dig out the causal genes related to important traits. In this study, three between-population and two within-population approaches, the Cross Population Extend Haplotype Homozygosity Test (XPEHH), the Cross Population Composite Likelihood Ratio (XPCLR), the F-statistics (Fst), the Integrated Haplotype Score (iHS) and the Tajima's D, were implemented to detect the selection footprints on the X chromosome in three pig breeds using Illumina Porcine60K SNP chip. In the detection of selection footprints using between-population methods, 11, 11 and 7 potential selection regions with length of 15.62 Mb, 12.32 Mb and 9.38 Mb were identified in Landrace, Chinese Songliao and Yorkshire by XPEHH, respectively, and 16, 13 and 17 potential selection regions with length of 15.20 Mb, 13.00 Mb and 19.21 Mb by XPCLR, 4, 2 and 4 potential selection regions with length of 3.20 Mb, 1.60 Mb and 3.20 Mb by Fst. For within-population methods, 7, 10 and 9 potential selection regions with length of 8.12 Mb, 8.40 Mb and 9.99 Mb were identified in Landrace, Chinese Songliao and Yorkshire by iHS, and 4, 3 and 2 potential selection regions with length of 3.20 Mb, 2.40 Mb and 1.60 Mb by Tajima's D. Moreover, the selection regions from different methods were partly overlapped, especially the regions around 22∼25 Mb were detected under selection in Landrace and Yorkshire while no selection in Chinese Songliao by all three between-population methods. Only quite few overlap of selection regions identified by between-population and within-population methods were found. Bioinformatics analysis showed that the genes relevant with meat quality, reproduction and immune were found in potential selection regions. In addition, three out of five significant SNPs associated with hematological traits reported in our genome-wide association study were harbored in potential selection regions.

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

PubMed Central

Pedreschi, Romina; Nørgaard, Jørgen; Maquet, Alain

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

A novel, colorimetric method for biogenic amine detection based on arylalkylamine N-acetyltransferase.

PubMed

Leng, Pei-Qiang; Zhao, Feng-Lan; Yin, Bin-Cheng; Ye, Bang-Ce

2015-05-21

We developed a novel colorimetric method for rapid detection of biogenic amines based on arylalkylamine N-acetyltransferase (aaNAT). The proposed method offers distinct advantages including simple handling, high speed, low cost, good sensitivity and selectivity.

Wavelength band selection method for multispectral target detection.

PubMed

Karlholm, Jörgen; Renhorn, Ingmar

2002-11-10

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

[Development of sample pretreatment techniques-rapid detection coupling methods for food security analysis].

PubMed

Huang, Yichun; Ding, Weiwei; Zhang, Zhuomin; Li, Gongke

2013-07-01

This paper summarizes the recent developments of the rapid detection methods for food security, such as sensors, optical techniques, portable spectral analysis, enzyme-linked immunosorbent assay, portable gas chromatograph, etc. Additionally, the applications of these rapid detection methods coupled with sample pretreatment techniques in real food security analysis are reviewed. The coupling technique has the potential to provide references to establish the selective, precise and quantitative rapid detection methods in food security analysis.

Microfabricated capillary electrophoresis chip and method for simultaneously detecting multiple redox labels

DOEpatents

Mathies, Richard A.; Singhal, Pankaj; Xie, Jin; Glazer, Alexander N.

2002-01-01

This invention relates to a microfabricated capillary electrophoresis chip for detecting multiple redox-active labels simultaneously using a matrix coding scheme and to a method of selectively labeling analytes for simultaneous electrochemical detection of multiple label-analyte conjugates after electrophoretic or chromatographic separation.

Materials, methods and devices to detect and quantify water vapor concentrations in an atmosphere

DOEpatents

Allendorf, Mark D; Robinson, Alex L

2014-12-09

We have demonstrated that a surface acoustic wave (SAW) sensor coated with a nanoporous framework material (NFM) film can perform ultrasensitive water vapor detection at concentrations in air from 0.05 to 12,000 ppmv at 1 atmosphere pressure. The method is extendable to other MEMS-based sensors, such as microcantilevers, or to quartz crystal microbalance sensors. We identify a specific NFM that provides high sensitivity and selectivity to water vapor. However, our approach is generalizable to detection of other species using NFM to provide sensitivity and selectivity.

Method for selective detection of explosives in mass spectrometer or ion mobility spectrometer at parts-per-quadrillion level

DOEpatents

Ewing, Robert G.; Atkinson, David A.; Clowers, Brian H.

2015-09-01

A method for selective detection of volatile and non-volatile explosives in a mass spectrometer or ion mobility spectrometer at a parts-per-quadrillion level without preconcentration is disclosed. The method comprises the steps of ionizing a carrier gas with an ionization source to form reactant ions or reactant adduct ions comprising nitrate ions (NO.sub.3.sup.-); selectively reacting the reactant ions or reactant adduct ions with at least one volatile or non-volatile explosive analyte at a carrier gas pressure of at least about 100 Ton in a reaction region disposed between the ionization source and an ion detector, the reaction region having a length which provides a residence time (tr) for reactant ions therein of at least about 0.10 seconds, wherein the selective reaction yields product ions comprising reactant ions or reactant adduct ions that are selectively bound to the at least one explosive analyte when present therein; and detecting product ions with the ion detector to determine presence or absence of the at least one explosive analyte.

Photoacoustic sensor for medical diagnostics

NASA Astrophysics Data System (ADS)

Wolff, Marcus; Groninga, Hinrich G.; Harde, Hermann

2004-03-01

The development of new optical sensor technologies has a major impact on the progress of diagnostic methods. Of the permanently increasing number of non-invasive breath tests, the 13C-Urea Breath Test (UBT) for the detection of Helicobacter pylori is the most prominent. However, many recent developments, like the detection of cancer by breath test, go beyond gastroenterological applications. We present a new detection scheme for breath analysis that employs an especially compact and simple set-up. Photoacoustic Spectroscopy (PAS) represents an offset-free technique that allows for short absorption paths and small sample cells. Using a single-frequency diode laser and taking advantage of acoustical resonances of the sample cell, we performed extremely sensitive and selective measurements. The smart data processing method contributes to the extraordinary sensitivity and selectivity as well. Also, the reasonable acquisition cost and low operational cost make this detection scheme attractive for many biomedical applications. The experimental set-up and data processing method, together with exemplary isotope-selective measurements on carbon dioxide, are presented.

Sensitive and selective determination of methylenedioxylated amphetamines by high-performance liquid chromatography with fluorimetric detection.

PubMed

Sadeghipour, F; Veuthey, J L

1997-11-07

A rapid, sensitive and selective liquid chromatographic method with fluorimetric detection was developed for the separation and quantification of four methylenedioxylated amphetamines without interference of other drugs of abuse and common substances found in illicit tablets. The method was validated by examining linearity, precision and accuracy as well as detection and quantification limits. Methylenedioxylated amphetamines were quantified in eight tablets from illicit drug seizures and results were quantitatively compared to HPLC-UV analyses. To demonstrate the better sensitivity of the fluorimetric detection, methylenedioxylated amphetamines were analyzed in serum after a liquid-liquid extraction procedure and results were also compared to HPLC-UV analyses.

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.

Selective detection of trace nitroaromatic, nitramine, and nitrate ester explosive residues using a three-step fluorimetric sensing process: a tandem turn-off, turn-on sensor.

PubMed

Sanchez, Jason C; Toal, Sarah J; Wang, Zheng; Dugan, Regina E; Trogler, William C

2007-11-01

Detection of trace quantities of explosive residues plays a key role in military, civilian, and counter-terrorism applications. To advance explosives sensor technology, current methods will need to become cheaper and portable while maintaining sensitivity and selectivity. The detection of common explosives including trinitrotoluene (TNT), cyclotrimethylenetrinitramine, cyclotetramethylene-tetranitramine, pentaerythritol tetranitrate, 2,4,6-trinitrophenyl-N-methylnitramine, and trinitroglycerin may be carried out using a three-step process combining "turn-off" and "turn-on" fluorimetric sensing. This process first detects nitroaromatic explosives by their quenching of green luminescence of polymetalloles (lambda em approximately 400-510 nm). The second step places down a thin film of 2,3-diaminonaphthalene (DAN) while "erasing" the polymetallole luminescence. The final step completes the reaction of the nitramines and/or nitrate esters with DAN resulting in the formation of a blue luminescent traizole complex (lambda(em) = 450 nm) providing a "turn-on" response for nitramine and nitrate ester-based explosives. Detection limits as low as 2 ng are observed. Solid-state detection of production line explosives demonstrates the applicability of this method to real world situations. This method offers a sensitive and selective detection process for a diverse group of the most common high explosives used in military and terrorist applications today.

The Genetic Architecture of Response to Long-Term Artificial Selection for Oil Concentration in the Maize Kernel

PubMed Central

Laurie, Cathy C.; Chasalow, Scott D.; LeDeaux, John R.; McCarroll, Robert; Bush, David; Hauge, Brian; Lai, Chaoqiang; Clark, Darryl; Rocheford, Torbert R.; Dudley, John W.

2004-01-01

In one of the longest-running experiments in biology, researchers at the University of Illinois have selected for altered composition of the maize kernel since 1896. Here we use an association study to infer the genetic basis of dramatic changes that occurred in response to selection for changes in oil concentration. The study population was produced by a cross between the high- and low-selection lines at generation 70, followed by 10 generations of random mating and the derivation of 500 lines by selfing. These lines were genotyped for 488 genetic markers and the oil concentration was evaluated in replicated field trials. Three methods of analysis were tested in simulations for ability to detect quantitative trait loci (QTL). The most effective method was model selection in multiple regression. This method detected ∼50 QTL accounting for ∼50% of the genetic variance, suggesting that >50 QTL are involved. The QTL effect estimates are small and largely additive. About 20% of the QTL have negative effects (i.e., not predicted by the parental difference), which is consistent with hitchhiking and small population size during selection. The large number of QTL detected accounts for the smooth and sustained response to selection throughout the twentieth century. PMID:15611182

Defect Detection in Textures through the Use of Entropy as a Means for Automatically Selecting the Wavelet Decomposition Level.

PubMed

Navarro, Pedro J; Fernández-Isla, Carlos; Alcover, Pedro María; Suardíaz, Juan

2016-07-27

This paper presents a robust method for defect detection in textures, entropy-based automatic selection of the wavelet decomposition level (EADL), based on a wavelet reconstruction scheme, for detecting defects in a wide variety of structural and statistical textures. Two main features are presented. One of the new features is an original use of the normalized absolute function value (NABS) calculated from the wavelet coefficients derived at various different decomposition levels in order to identify textures where the defect can be isolated by eliminating the texture pattern in the first decomposition level. The second is the use of Shannon's entropy, calculated over detail subimages, for automatic selection of the band for image reconstruction, which, unlike other techniques, such as those based on the co-occurrence matrix or on energy calculation, provides a lower decomposition level, thus avoiding excessive degradation of the image, allowing a more accurate defect segmentation. A metric analysis of the results of the proposed method with nine different thresholding algorithms determined that selecting the appropriate thresholding method is important to achieve optimum performance in defect detection. As a consequence, several different thresholding algorithms depending on the type of texture are proposed.

Detecting Image Splicing Using Merged Features in Chroma Space

PubMed Central

Liu, Guangjie; Dai, Yuewei

2014-01-01

Image splicing is an image editing method to copy a part of an image and paste it onto another image, and it is commonly followed by postprocessing such as local/global blurring, compression, and resizing. To detect this kind of forgery, the image rich models, a feature set successfully used in the steganalysis is evaluated on the splicing image dataset at first, and the dominant submodel is selected as the first kind of feature. The selected feature and the DCT Markov features are used together to detect splicing forgery in the chroma channel, which is convinced effective in splicing detection. The experimental results indicate that the proposed method can detect splicing forgeries with lower error rate compared to the previous literature. PMID:24574877

Detecting image splicing using merged features in chroma space.

PubMed

Xu, Bo; Liu, Guangjie; Dai, Yuewei

2014-01-01

Image splicing is an image editing method to copy a part of an image and paste it onto another image, and it is commonly followed by postprocessing such as local/global blurring, compression, and resizing. To detect this kind of forgery, the image rich models, a feature set successfully used in the steganalysis is evaluated on the splicing image dataset at first, and the dominant submodel is selected as the first kind of feature. The selected feature and the DCT Markov features are used together to detect splicing forgery in the chroma channel, which is convinced effective in splicing detection. The experimental results indicate that the proposed method can detect splicing forgeries with lower error rate compared to the previous literature.

ROKU: a novel method for identification of tissue-specific genes.

PubMed

Kadota, Koji; Ye, Jiazhen; Nakai, Yuji; Terada, Tohru; Shimizu, Kentaro

2006-06-12

One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes.

Linear segmentation algorithm for detecting layer boundary with lidar.

PubMed

Mao, Feiyue; Gong, Wei; Logan, Timothy

2013-11-04

The automatic detection of aerosol- and cloud-layer boundary (base and top) is important in atmospheric lidar data processing, because the boundary information is not only useful for environment and climate studies, but can also be used as input for further data processing. Previous methods have demonstrated limitations in defining the base and top, window-size setting, and have neglected the in-layer attenuation. To overcome these limitations, we present a new layer detection scheme for up-looking lidars based on linear segmentation with a reasonable threshold setting, boundary selecting, and false positive removing strategies. Preliminary results from both real and simulated data show that this algorithm cannot only detect the layer-base as accurate as the simple multi-scale method, but can also detect the layer-top more accurately than that of the simple multi-scale method. Our algorithm can be directly applied to uncalibrated data without requiring any additional measurements or window size selections.

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

PubMed

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

2018-01-08

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

Wildfire Detection using by Multi Dimensional Histogram in Boreal Forest

NASA Astrophysics Data System (ADS)

Honda, K.; Kimura, K.; Honma, T.

2008-12-01

Early detection of wildfires is an issue for reduction of damage to environment and human. There are some attempts to detect wildfires by using satellite imagery, which are mainly classified into three methods: Dozier Method(1981-), Threshold Method(1986-) and Contextual Method(1994-). However, the accuracy of these methods is not enough: some commission and omission errors are included in the detected results. In addition, it is not so easy to analyze satellite imagery with high accuracy because of insufficient ground truth data. Kudoh and Hosoi (2003) developed the detection method by using three-dimensional (3D) histogram from past fire data with the NOAA-AVHRR imagery. But their method is impractical because their method depends on their handworks to pick up past fire data from huge data. Therefore, the purpose of this study is to collect fire points as hot spots efficiently from satellite imagery and to improve the method to detect wildfires with the collected data. As our method, we collect past fire data with the Alaska Fire History data obtained by the Alaska Fire Service (AFS). We select points that are expected to be wildfires, and pick up the points inside the fire area of the AFS data. Next, we make 3D histogram with the past fire data. In this study, we use Bands 1, 21 and 32 of MODIS. We calculate the likelihood to detect wildfires with the three-dimensional histogram. As our result, we select wildfires with the 3D histogram effectively. We can detect the troidally spreading wildfire. This result shows the evidence of good wildfire detection. However, the area surrounding glacier tends to rise brightness temperature. It is a false alarm. Burnt area and bare ground are sometimes indicated as false alarms, so that it is necessary to improve this method. Additionally, we are trying various combinations of MODIS bands as the better method to detect wildfire effectively. So as to adjust our method in another area, we are applying our method to tropical forest in Kalimantan, Indonesia and around Chiang Mai, Thailand. But the ground truth data in these areas is lesser than the one in Alaska. Our method needs lots of accurate observed data to make multi-dimensional histogram in the same area. In this study, we can show the system to select wildfire data efficiently from satellite imagery. Furthermore, the development of multi-dimensional histogram from past fire data makes it possible to detect wildfires accurately.

Ischemia episode detection in ECG using kernel density estimation, support vector machine and feature selection

PubMed Central

2012-01-01

Background Myocardial ischemia can be developed into more serious diseases. Early Detection of the ischemic syndrome in electrocardiogram (ECG) more accurately and automatically can prevent it from developing into a catastrophic disease. To this end, we propose a new method, which employs wavelets and simple feature selection. Methods For training and testing, the European ST-T database is used, which is comprised of 367 ischemic ST episodes in 90 records. We first remove baseline wandering, and detect time positions of QRS complexes by a method based on the discrete wavelet transform. Next, for each heart beat, we extract three features which can be used for differentiating ST episodes from normal: 1) the area between QRS offset and T-peak points, 2) the normalized and signed sum from QRS offset to effective zero voltage point, and 3) the slope from QRS onset to offset point. We average the feature values for successive five beats to reduce effects of outliers. Finally we apply classifiers to those features. Results We evaluated the algorithm by kernel density estimation (KDE) and support vector machine (SVM) methods. Sensitivity and specificity for KDE were 0.939 and 0.912, respectively. The KDE classifier detects 349 ischemic ST episodes out of total 367 ST episodes. Sensitivity and specificity of SVM were 0.941 and 0.923, respectively. The SVM classifier detects 355 ischemic ST episodes. Conclusions We proposed a new method for detecting ischemia in ECG. It contains signal processing techniques of removing baseline wandering and detecting time positions of QRS complexes by discrete wavelet transform, and feature extraction from morphology of ECG waveforms explicitly. It was shown that the number of selected features were sufficient to discriminate ischemic ST episodes from the normal ones. We also showed how the proposed KDE classifier can automatically select kernel bandwidths, meaning that the algorithm does not require any numerical values of the parameters to be supplied in advance. In the case of the SVM classifier, one has to select a single parameter. PMID:22703641

The biometric-based module of smart grid system

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Ermoshkina, A.

2015-10-01

Within Smart Grid concept the flexible biometric-based module base on Principal Component Analysis (PCA) and selective Neural Network is developed. The formation of the selective Neural Network the biometric-based module uses the method which includes three main stages: preliminary processing of the image, face localization and face recognition. Experiments on the Yale face database show that (i) selective Neural Network exhibits promising classification capability for face detection, recognition problems; and (ii) the proposed biometric-based module achieves near real-time face detection, recognition speed and the competitive performance, as compared to some existing subspaces-based methods.

Artemisinin-Luminol Chemiluminescence for Forensic Bloodstain Detection Using a Smart Phone as a Detector.

PubMed

Gao, Wenyue; Wang, Chao; Muzyka, Kateryna; Kitte, Shimeles Addisu; Li, Jianping; Zhang, Wei; Xu, Guobao

2017-06-06

Forensic luminol chemiluminescence test is one of the most sensitive and popular methods for the determination of latent bloodstains. It mainly uses hydrogen peroxide or sodium perborate as coreactants. The easy decomposition of hydrogen peroxide and sodium perborate in the presence of many ions significantly affects the selectivity. Artemisinin is a natural peroxide that is quite stable in the presence of common ions. In the present study, artemisinin has been exploited for the forensic bloodstain chemiluminescence detection for the first time. Using smart phone as cost-effective portable detector, the visual detection of bloodstains has been achieved with a dilution factor of blood up to 100 000. Moreover, this system shows excellent selectivity against many common species. It can well differentiate bloodstains from other stains, such as coffee, brown sugar, and black tea. Both favorable sensitivity and selectivity makes the present method promising in forensic detection.

Study on optimization method of test conditions for fatigue crack detection using lock-in vibrothermography

NASA Astrophysics Data System (ADS)

Min, Qing-xu; Zhu, Jun-zhen; Feng, Fu-zhou; Xu, Chao; Sun, Ji-wei

2017-06-01

In this paper, the lock-in vibrothermography (LVT) is utilized for defect detection. Specifically, for a metal plate with an artificial fatigue crack, the temperature rise of the defective area is used for analyzing the influence of different test conditions, i.e. engagement force, excitation intensity, and modulated frequency. The multivariate nonlinear and logistic regression models are employed to estimate the POD (probability of detection) and POA (probability of alarm) of fatigue crack, respectively. The resulting optimal selection of test conditions is presented. The study aims to provide an optimized selection method of the test conditions in the vibrothermography system with the enhanced detection ability.

Method and apparatus for monitoring characteristics of a flow path having solid components flowing therethrough

DOEpatents

Hoskinson, Reed L [Rigby, ID; Svoboda, John M [Idaho Falls, ID; Bauer, William F [Idaho Falls, ID; Elias, Gracy [Idaho Falls, ID

2008-05-06

A method and apparatus is provided for monitoring a flow path having plurality of different solid components flowing therethrough. For example, in the harvesting of a plant material, many factors surrounding the threshing, separating or cleaning of the plant material and may lead to the inadvertent inclusion of the component being selectively harvested with residual plant materials being discharged or otherwise processed. In accordance with the present invention the detection of the selectively harvested component within residual materials may include the monitoring of a flow path of such residual materials by, for example, directing an excitation signal toward of flow path of material and then detecting a signal initiated by the presence of the selectively harvested component responsive to the excitation signal. The detected signal may be used to determine the presence or absence of a selected plant component within the flow path of residual materials.

Detecting Bias in Selection for Higher Education: Three Different Methods

ERIC Educational Resources Information Center

Kennet-Cohen, Tamar; Turvall, Elliot; Oren, Carmel

2014-01-01

This study examined selection bias in Israeli university admissions with respect to test language and gender, using three approaches for the detection of such bias: Cleary's model of differential prediction, boundary conditions for differential prediction and difference between "d's" (the Constant Ratio Model). The university admissions…

Identification of Selection Footprints on the X Chromosome in Pig

PubMed Central

Zhang, Qin; Ding, Xiangdong

2014-01-01

Identifying footprints of selection can provide a straightforward insight into the mechanism of artificial selection and further dig out the causal genes related to important traits. In this study, three between-population and two within-population approaches, the Cross Population Extend Haplotype Homozygosity Test (XPEHH), the Cross Population Composite Likelihood Ratio (XPCLR), the F-statistics (Fst), the Integrated Haplotype Score (iHS) and the Tajima's D, were implemented to detect the selection footprints on the X chromosome in three pig breeds using Illumina Porcine60K SNP chip. In the detection of selection footprints using between-population methods, 11, 11 and 7 potential selection regions with length of 15.62 Mb, 12.32 Mb and 9.38 Mb were identified in Landrace, Chinese Songliao and Yorkshire by XPEHH, respectively, and 16, 13 and 17 potential selection regions with length of 15.20 Mb, 13.00 Mb and 19.21 Mb by XPCLR, 4, 2 and 4 potential selection regions with length of 3.20 Mb, 1.60 Mb and 3.20 Mb by Fst. For within-population methods, 7, 10 and 9 potential selection regions with length of 8.12 Mb, 8.40 Mb and 9.99 Mb were identified in Landrace, Chinese Songliao and Yorkshire by iHS, and 4, 3 and 2 potential selection regions with length of 3.20 Mb, 2.40 Mb and 1.60 Mb by Tajima's D. Moreover, the selection regions from different methods were partly overlapped, especially the regions around 22 ∼25 Mb were detected under selection in Landrace and Yorkshire while no selection in Chinese Songliao by all three between-population methods. Only quite few overlap of selection regions identified by between-population and within-population methods were found. Bioinformatics analysis showed that the genes relevant with meat quality, reproduction and immune were found in potential selection regions. In addition, three out of five significant SNPs associated with hematological traits reported in our genome-wide association study were harbored in potential selection regions. PMID:24740293

Detection of Listeria monocytogenes from selective enrichment broth using MALDI-TOF Mass Spectrometry.

PubMed

Jadhav, Snehal; Sevior, Danielle; Bhave, Mrinal; Palombo, Enzo A

2014-01-31

Conventional methods used for primary detection of Listeria monocytogenes from foods and subsequent confirmation of presumptive positive samples involve prolonged incubation and biochemical testing which generally require four to five days to obtain a result. In the current study, a simple and rapid proteomics-based MALDI-TOF MS approach was developed to detect L. monocytogenes directly from selective enrichment broths. Milk samples spiked with single species and multiple species cultures were incubated in a selective enrichment broth for 24h, followed by an additional 6h secondary enrichment. As few as 1 colony-forming unit (cfu) of L. monocytogenes per mL of initial selective broth culture could be detected within 30h. On applying the same approach to solid foods previously implicated in listeriosis, namely chicken pâté, cantaloupe and Camembert cheese, detection was achieved within the same time interval at inoculation levels of 10cfu/mL. Unlike the routine application of MALDI-TOF MS for identification of bacteria from solid media, this study proposes a cost-effective and time-saving detection scheme for direct identification of L. monocytogenes from broth cultures.This article is part of a Special Issue entitled: Trends in Microbial Proteomics. Globally, foodborne diseases are major causes of illness and fatalities in humans. Hence, there is a continual need for reliable and rapid means for pathogen detection from food samples. Recent applications of MALDI-TOF MS for diagnostic microbiology focused on detection of microbes from clinical specimens. However, the current study has emphasized its use as a tool for detecting the major foodborne pathogen, Listeria monocytogenes, directly from selective enrichment broths. This proof-of-concept study proposes a detection scheme that is more rapid and simple compared to conventional methods of Listeria detection. Very low levels of the pathogen could be identified from different food samples post-enrichment in selective enrichment broths. Use of this scheme will facilitate rapid and cost-effective testing for this important foodborne pathogen. © 2013.

EPA Method 538: Determination of Selected Organic Contaminants in Drinking Water by Direct Aqueous Injection-Liquid Chromatography/Tandem Mass Spectrometry (DAI-LC/MS/MS)

EPA Pesticide Factsheets

EPA’s Selected Analytical Methods for Environmental Remediation and Recovery (SAM) lists this method for preparation and analysis of drinking water samples to detect and measure acephate, diisopropyl methylphosphonate (DIMP), methamidophos and thiofanox.

Joint Dictionary Learning for Multispectral Change Detection.

PubMed

Lu, Xiaoqiang; Yuan, Yuan; Zheng, Xiangtao

2017-04-01

Change detection is one of the most important applications of remote sensing technology. It is a challenging task due to the obvious variations in the radiometric value of spectral signature and the limited capability of utilizing spectral information. In this paper, an improved sparse coding method for change detection is proposed. The intuition of the proposed method is that unchanged pixels in different images can be well reconstructed by the joint dictionary, which corresponds to knowledge of unchanged pixels, while changed pixels cannot. First, a query image pair is projected onto the joint dictionary to constitute the knowledge of unchanged pixels. Then reconstruction error is obtained to discriminate between the changed and unchanged pixels in the different images. To select the proper thresholds for determining changed regions, an automatic threshold selection strategy is presented by minimizing the reconstruction errors of the changed pixels. Adequate experiments on multispectral data have been tested, and the experimental results compared with the state-of-the-art methods prove the superiority of the proposed method. Contributions of the proposed method can be summarized as follows: 1) joint dictionary learning is proposed to explore the intrinsic information of different images for change detection. In this case, change detection can be transformed as a sparse representation problem. To the authors' knowledge, few publications utilize joint learning dictionary in change detection; 2) an automatic threshold selection strategy is presented, which minimizes the reconstruction errors of the changed pixels without the prior assumption of the spectral signature. As a result, the threshold value provided by the proposed method can adapt to different data due to the characteristic of joint dictionary learning; and 3) the proposed method makes no prior assumption of the modeling and the handling of the spectral signature, which can be adapted to different data.

Training sample selection based on self-training for liver cirrhosis classification using ultrasound images

NASA Astrophysics Data System (ADS)

Fujita, Yusuke; Mitani, Yoshihiro; Hamamoto, Yoshihiko; Segawa, Makoto; Terai, Shuji; Sakaida, Isao

2017-03-01

Ultrasound imaging is a popular and non-invasive tool used in the diagnoses of liver disease. Cirrhosis is a chronic liver disease and it can advance to liver cancer. Early detection and appropriate treatment are crucial to prevent liver cancer. However, ultrasound image analysis is very challenging, because of the low signal-to-noise ratio of ultrasound images. To achieve the higher classification performance, selection of training regions of interest (ROIs) is very important that effect to classification accuracy. The purpose of our study is cirrhosis detection with high accuracy using liver ultrasound images. In our previous works, training ROI selection by MILBoost and multiple-ROI classification based on the product rule had been proposed, to achieve high classification performance. In this article, we propose self-training method to select training ROIs effectively. Evaluation experiments were performed to evaluate effect of self-training, using manually selected ROIs and also automatically selected ROIs. Experimental results show that self-training for manually selected ROIs achieved higher classification performance than other approaches, including our conventional methods. The manually ROI definition and sample selection are important to improve classification accuracy in cirrhosis detection using ultrasound images.

Highly selective and sensitive fluorescent paper sensor for nitroaromatic explosive detection.

PubMed

Ma, Yingxin; Li, Hao; Peng, Shan; Wang, Leyu

2012-10-02

Rapid, sensitive, and selective detection of explosives such as 2,4,6-trinitrotoluene (TNT) and 2,4,6-trinitrophenol (TNP), especially using a facile paper sensor, is in high demand for homeland security and public safety. Although many strategies have been successfully developed for the detection of TNT, it is not easy to differentiate the influence from TNP. Also, few methods were demonstrated for the selective detection of TNP. In this work, via a facile and versatile method, 8-hydroxyquinoline aluminum (Alq(3))-based bluish green fluorescent composite nanospheres were successfully synthesized through self-assembly under vigorous stirring and ultrasonic treatment. These polymer-coated nanocomposites are not only water-stable but also highly luminescent. Based on the dramatic and selective fluorescence quenching of the nanocomposites via adding TNP into the aqueous solution, a sensitive and robust platform was developed for visual detection of TNP in the mixture of nitroaromatics including TNT, 2,4-dinitrotoluene (DNT), and nitrobenzene (NB). Meanwhile, the fluorescence intensity is proportional to the concentration of TNP in the range of 0.05-7.0 μg/mL with the 3σ limit of detection of 32.3 ng/mL. By handwriting or finger printing with TNP solution as ink on the filter paper soaked with the fluorescent nanocomposites, the bluish green fluorescence was instantly and dramatically quenched and the dark patterns were left on the paper. Therefore, a convenient and rapid paper sensor for TNP-selective detection was fabricated.

Vapor permeation-stepwise injection simultaneous determination of methanol and ethanol in biodiesel with voltammetric detection.

PubMed

Shishov, Andrey; Penkova, Anastasia; Zabrodin, Andrey; Nikolaev, Konstantin; Dmitrenko, Maria; Ermakov, Sergey; Bulatov, Andrey

2016-02-01

A novel vapor permeation-stepwise injection (VP-SWI) method for the determination of methanol and ethanol in biodiesel samples is discussed. In the current study, stepwise injection analysis was successfully combined with voltammetric detection and vapor permeation. This method is based on the separation of methanol and ethanol from a sample using a vapor permeation module (VPM) with a selective polymer membrane based on poly(phenylene isophtalamide) (PA) containing high amounts of a residual solvent. After the evaporation into the headspace of the VPM, methanol and ethanol were transported, by gas bubbling, through a PA membrane to a mixing chamber equipped with a voltammetric detector. Ethanol was selectively detected at +0.19 V, and both compounds were detected at +1.20 V. Current subtractions (using a correction factor) were used for the selective determination of methanol. A linear range between 0.05 and 0.5% (m/m) was established for each analyte. The limits of detection were estimated at 0.02% (m/m) for ethanol and methanol. The sample throughput was 5 samples h(-1). The method was successfully applied to the analysis of biodiesel samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Efficient detection of dangling pointer error for C/C++ programs

NASA Astrophysics Data System (ADS)

Zhang, Wenzhe

2017-08-01

Dangling pointer error is pervasive in C/C++ programs and it is very hard to detect. This paper introduces an efficient detector to detect dangling pointer error in C/C++ programs. By selectively leave some memory accesses unmonitored, our method could reduce the memory monitoring overhead and thus achieves better performance over previous methods. Experiments show that our method could achieve an average speed up of 9% over previous compiler instrumentation based method and more than 50% over previous page protection based method.

Ultra-sensitive and selective Hg{sup 2+} detection based on fluorescent carbon dots

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

Liu, Ruihua; Li, Haitao; Kong, Weiqian

2013-07-15

Graphical abstract: Fluorescent carbon dots were efficiently synthesized by one-step sodium hydroxide-assisted reflux method from PEG and demonstrated to show high selectivity toward Hg2+ ions detection. - Highlights: • FCDs were synthesized by one-step sodium hydroxide-assisted reflux method from PEG. • The FCDs emit blue photoluminescence and have upconversion fluorescent property. • The FCDs show ultra-sensitive detective ability for Hg{sup 2+} ions. - Abstract: Fluorescent carbon dots (FCDs) were efficiently synthesized by one-step sodium hydroxide-assisted reflux method from poly(ethylene glycol) (PEG). The obtained FCDs exhibit excellent water-solubility and high stability. Under the UV irradiation, the FCDs could emit bright bluemore » photoluminescence, and also they were found to show excellent up-conversion fluorescence. It was further demonstrated that such FCDs can serve as effective fluorescent sensing platform for Hg{sup 2+} ions detection with ultra-sensitivity and selectivity. The sensing system achieved a limit of detection as low as 1 fM, which is much lower than all the previous reported sensing systems for Hg{sup 2+} ions detection. This FCDs sensing system has been successfully applied for the analysis of Hg{sup 2+} ions in water samples from river, lake, and tap water, showing good practical feasibility.« less

Selective detection of target proteins by peptide-enabled graphene biosensor.

PubMed

Khatayevich, Dmitriy; Page, Tamon; Gresswell, Carolyn; Hayamizu, Yuhei; Grady, William; Sarikaya, Mehmet

2014-04-24

Direct molecular detection of biomarkers is a promising approach for diagnosis and monitoring of numerous diseases, as well as a cornerstone of modern molecular medicine and drug discovery. Currently, clinical applications of biomarkers are limited by the sensitivity, complexity and low selectivity of available indirect detection methods. Electronic 1D and 2D nano-materials such as carbon nanotubes and graphene, respectively, offer unique advantages as sensing substrates for simple, fast and ultrasensitive detection of biomolecular binding. Versatile methods, however, have yet to be developed for simultaneous functionalization and passivation of the sensor surface to allow for enhanced detection and selectivity of the device. Herein, we demonstrate selective detection of a model protein against a background of serum protein using a graphene sensor functionalized via self-assembling multifunctional short peptides. The two peptides are engineered to bind to graphene and undergo co-assembly in the form of an ordered monomolecular film on the substrate. While the probe peptide displays the bioactive molecule, the passivating peptide prevents non-specific protein adsorption onto the device surface, ensuring target selectivity. In particular, we demonstrate a graphene field effect transistor (gFET) biosensor which can detect streptavidin against a background of serum bovine albumin at less than 50 ng/ml. Our nano-sensor design, allows us to restore the graphene surface and utilize each sensor in multiple experiments. The peptide-enabled gFET device has great potential to address a variety of bio-sensing problems, such as studying ligand-receptor interactions, or detection of biomarkers in a clinical setting. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Selection of a new Mycobacterium tuberculosis H37Rv aptamer and its application in the construction of a SWCNT/aptamer/Au-IDE MSPQC H37Rv sensor.

PubMed

Zhang, XiaoQing; Feng, Ye; Yao, QiongQiong; He, Fengjiao

2017-12-15

A rapid and accurate detection method for Mycobacterium tuberculosis (M. tuberculosis) is essential for effectively treating tuberculosis. However, current detection methods cannot meet these clinical requirements because the methods are slow or of low specificity. Consequently, a new highly specific ssDNA aptamer against M. tuberculosis reference strain H37Rv was selected by using the whole-cell systematic evolution of ligands by exponential enrichment technique. The selected aptamer was used to construct a fast and highly specific H37Rv sensor. The probe was produced by immobilizing thiol-modified aptamer on an Au interdigital electrode (Au-IDE) of a multichannel series piezoelectric quartz crystal (MSPQC) through Au-S bonding, and then single-walled carbon nanotubes (SWCNTs) were bonded on the aptamer by π-π stacking. SWCNTs were used as a signal indicator because of their considerable difference in conductivity compared with H37Rv. When H37Rv is present, it replaces the SWCNTs because it binds to the aptamer much more strongly than SWCNTs do. The replacement of SWCNTs by H37Rv resulted in a large change in the electrical properties, and this change was detected by the MSPQC. The proposed sensor is highly selective and can distinguish H37Rv from Mycobacterium smegmatis (M. smegmatis) and Bacillus Calmette-Guerin vaccine (BCG). The detection time was 70min and the detection limit was 100cfu/mL. Compared with conventional methods, this new SWCNT/aptamer/Au-IDE MSPQC H37Rv sensor was specific, rapid, and sensitive, and it holds great potential for the early detection of H37Rv in clinical diagnosis. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of a Pair-Wise Conflict Detection and Resolution Algorithm in a Multiple Aircraft Scenario

NASA Technical Reports Server (NTRS)

Carreno, Victor A.

2002-01-01

The KB3D algorithm is a pairwise conflict detection and resolution (CD&R) algorithm. It detects and generates trajectory vectoring for an aircraft which has been predicted to be in an airspace minima violation within a given look-ahead time. It has been proven, using mechanized theorem proving techniques, that for a pair of aircraft, KB3D produces at least one vectoring solution and that all solutions produced are correct. Although solutions produced by the algorithm are mathematically correct, they might not be physically executable by an aircraft or might not solve multiple aircraft conflicts. This paper describes a simple solution selection method which assesses all solutions generated by KB3D and determines the solution to be executed. The solution selection method and KB3D are evaluated using a simulation in which N aircraft fly in a free-flight environment and each aircraft in the simulation uses KB3D to maintain separation. Specifically, the solution selection method filters KB3D solutions which are procedurally undesirable or physically not executable and uses a predetermined criteria for selection.

Alternative microbial methods: An overview and selection criteria.

PubMed

Jasson, Vicky; Jacxsens, Liesbeth; Luning, Pieternel; Rajkovic, Andreja; Uyttendaele, Mieke

2010-09-01

This study provides an overview and criteria for the selection of a method, other than the reference method, for microbial analysis of foods. In a first part an overview of the general characteristics of rapid methods available, both for enumeration and detection, is given with reference to relevant bibliography. Perspectives on future development and the potential of the rapid method for routine application in food diagnostics are discussed. As various alternative "rapid" methods in different formats are available on the market, it can be very difficult for a food business operator or for a control authority to select the most appropriate method which fits its purpose. Validation of a method by a third party, according to international accepted protocol based upon ISO 16140, may increase the confidence in the performance of a method. A list of at the moment validated methods for enumeration of both utility indicators (aerobic plate count) and hygiene indicators (Enterobacteriaceae, Escherichia coli, coagulase positive Staphylococcus) as well as for detection of the four major pathogens (Salmonella spp., Listeria monocytogenes, E. coli O157 and Campylobacter spp.) is included with reference to relevant websites to check for updates. In a second part of this study, selection criteria are introduced to underpin the choice of the appropriate method(s) for a defined application. The selection criteria link the definition of the context in which the user of the method functions - and thus the prospective use of the microbial test results - with the technical information on the method and its operational requirements and sustainability. The selection criteria can help the end user of the method to obtain a systematic insight into all relevant factors to be taken into account for selection of a method for microbial analysis. Copyright 2010 Elsevier Ltd. All rights reserved.

The detection methods of dynamic objects

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Multiple approaches to detect outliers in a genome scan for selection in ocellated lizards (Lacerta lepida) along an environmental gradient.

PubMed

Nunes, Vera L; Beaumont, Mark A; Butlin, Roger K; Paulo, Octávio S

2011-01-01

Identification of loci with adaptive importance is a key step to understand the speciation process in natural populations, because those loci are responsible for phenotypic variation that affects fitness in different environments. We conducted an AFLP genome scan in populations of ocellated lizards (Lacerta lepida) to search for candidate loci influenced by selection along an environmental gradient in the Iberian Peninsula. This gradient is strongly influenced by climatic variables, and two subspecies can be recognized at the opposite extremes: L. lepida iberica in the northwest and L. lepida nevadensis in the southeast. Both subspecies show substantial morphological differences that may be involved in their local adaptation to the climatic extremes. To investigate how the use of a particular outlier detection method can influence the results, a frequentist method, DFDIST, and a Bayesian method, BayeScan, were used to search for outliers influenced by selection. Additionally, the spatial analysis method was used to test for associations of AFLP marker band frequencies with 54 climatic variables by logistic regression. Results obtained with each method highlight differences in their sensitivity. DFDIST and BayeScan detected a similar proportion of outliers (3-4%), but only a few loci were simultaneously detected by both methods. Several loci detected as outliers were also associated with temperature, insolation or precipitation according to spatial analysis method. These results are in accordance with reported data in the literature about morphological and life-history variation of L. lepida subspecies along the environmental gradient. © 2010 Blackwell Publishing Ltd.

Benzimidazole derivatives: selective fluorescent chemosensors for the picogram detection of picric acid.

PubMed

Xiong, Jin-Feng; Li, Jian-Xiao; Mo, Guang-Zhen; Huo, Jing-Pei; Liu, Jin-Yan; Chen, Xiao-Yun; Wang, Zhao-Yang

2014-12-05

1,3,5-Tri(1H-benzo[d]imidazol-2-yl)benzene derivatives, as a new kind of fluorescent chemosensor for the detection of nitroaromatic explosives, are designed and synthesized by simple N-hydrocarbylation. Among 16 obtained compounds, compound 4g has the best capability for detection of picric acid (PA), having good selectivity and high sensitivity. The detection of PA with 4g solution-coated paper strips at the picogram level is developed. A simple, portable, and low-cost method is provided for detecting PA in solution and contact mode.

A ROC-based feature selection method for computer-aided detection and diagnosis

NASA Astrophysics Data System (ADS)

Wang, Songyuan; Zhang, Guopeng; Liao, Qimei; Zhang, Junying; Jiao, Chun; Lu, Hongbing

2014-03-01

Image-based computer-aided detection and diagnosis (CAD) has been a very active research topic aiming to assist physicians to detect lesions and distinguish them from benign to malignant. However, the datasets fed into a classifier usually suffer from small number of samples, as well as significantly less samples available in one class (have a disease) than the other, resulting in the classifier's suboptimal performance. How to identifying the most characterizing features of the observed data for lesion detection is critical to improve the sensitivity and minimize false positives of a CAD system. In this study, we propose a novel feature selection method mR-FAST that combines the minimal-redundancymaximal relevance (mRMR) framework with a selection metric FAST (feature assessment by sliding thresholds) based on the area under a ROC curve (AUC) generated on optimal simple linear discriminants. With three feature datasets extracted from CAD systems for colon polyps and bladder cancer, we show that the space of candidate features selected by mR-FAST is more characterizing for lesion detection with higher AUC, enabling to find a compact subset of superior features at low cost.

Ellipticity angle of electromagnetic signals and its use for non-energetic detection optimal by the Neumann-Pearson criterion

NASA Astrophysics Data System (ADS)

Gromov, V. A.; Sharygin, G. S.; Mironov, M. V.

2012-08-01

An interval method of radar signal detection and selection based on non-energetic polarization parameter - the ellipticity angle - is suggested. The examined method is optimal by the Neumann-Pearson criterion. The probability of correct detection for a preset probability of false alarm is calculated for different signal/noise ratios. Recommendations for optimization of the given method are provided.

[Rapid detection of caffeine in blood by freeze-out extraction].

PubMed

Bekhterev, V N; Gavrilova, S N; Kozina, E P; Maslakov, I V

2010-01-01

A new method for the detection of caffeine in blood has been proposed based on the combination of extraction and freezing-out to eliminate the influence of sample matrix. Metrological characteristics of the method are presented. Selectivity of detection is achieved by optimal conditions of analysis by high performance liquid chromatography. The method is technically simple and cost-efficient, it ensures rapid performance of the studies.

Navigating the Interface Between Landscape Genetics and Landscape Genomics.

PubMed

Storfer, Andrew; Patton, Austin; Fraik, Alexandra K

2018-01-01

As next-generation sequencing data become increasingly available for non-model organisms, a shift has occurred in the focus of studies of the geographic distribution of genetic variation. Whereas landscape genetics studies primarily focus on testing the effects of landscape variables on gene flow and genetic population structure, landscape genomics studies focus on detecting candidate genes under selection that indicate possible local adaptation. Navigating the transition between landscape genomics and landscape genetics can be challenging. The number of molecular markers analyzed has shifted from what used to be a few dozen loci to thousands of loci and even full genomes. Although genome scale data can be separated into sets of neutral loci for analyses of gene flow and population structure and putative loci under selection for inference of local adaptation, there are inherent differences in the questions that are addressed in the two study frameworks. We discuss these differences and their implications for study design, marker choice and downstream analysis methods. Similar to the rapid proliferation of analysis methods in the early development of landscape genetics, new analytical methods for detection of selection in landscape genomics studies are burgeoning. We focus on genome scan methods for detection of selection, and in particular, outlier differentiation methods and genetic-environment association tests because they are the most widely used. Use of genome scan methods requires an understanding of the potential mismatches between the biology of a species and assumptions inherent in analytical methods used, which can lead to high false positive rates of detected loci under selection. Key to choosing appropriate genome scan methods is an understanding of the underlying demographic structure of study populations, and such data can be obtained using neutral loci from the generated genome-wide data or prior knowledge of a species' phylogeographic history. To this end, we summarize recent simulation studies that test the power and accuracy of genome scan methods under a variety of demographic scenarios and sampling designs. We conclude with a discussion of additional considerations for future method development, and a summary of methods that show promise for landscape genomics studies but are not yet widely used.

Navigating the Interface Between Landscape Genetics and Landscape Genomics

PubMed Central

Storfer, Andrew; Patton, Austin; Fraik, Alexandra K.

2018-01-01

As next-generation sequencing data become increasingly available for non-model organisms, a shift has occurred in the focus of studies of the geographic distribution of genetic variation. Whereas landscape genetics studies primarily focus on testing the effects of landscape variables on gene flow and genetic population structure, landscape genomics studies focus on detecting candidate genes under selection that indicate possible local adaptation. Navigating the transition between landscape genomics and landscape genetics can be challenging. The number of molecular markers analyzed has shifted from what used to be a few dozen loci to thousands of loci and even full genomes. Although genome scale data can be separated into sets of neutral loci for analyses of gene flow and population structure and putative loci under selection for inference of local adaptation, there are inherent differences in the questions that are addressed in the two study frameworks. We discuss these differences and their implications for study design, marker choice and downstream analysis methods. Similar to the rapid proliferation of analysis methods in the early development of landscape genetics, new analytical methods for detection of selection in landscape genomics studies are burgeoning. We focus on genome scan methods for detection of selection, and in particular, outlier differentiation methods and genetic-environment association tests because they are the most widely used. Use of genome scan methods requires an understanding of the potential mismatches between the biology of a species and assumptions inherent in analytical methods used, which can lead to high false positive rates of detected loci under selection. Key to choosing appropriate genome scan methods is an understanding of the underlying demographic structure of study populations, and such data can be obtained using neutral loci from the generated genome-wide data or prior knowledge of a species' phylogeographic history. To this end, we summarize recent simulation studies that test the power and accuracy of genome scan methods under a variety of demographic scenarios and sampling designs. We conclude with a discussion of additional considerations for future method development, and a summary of methods that show promise for landscape genomics studies but are not yet widely used. PMID:29593776

Selective sensing of submicromolar iron(III) with 3,3‧,5,5‧-tetramethylbenzidine as a chromogenic probe

NASA Astrophysics Data System (ADS)

Zhang, Lufeng; Du, Jianxiu

2016-04-01

The development of highly selective and sensitive method for iron(III) detection is of great importance both from human health as well as environmental point of view. We herein reported a simple, selective and sensitive colorimetric method for the detection of Fe(III) at submicromolar level with 3,3,‧5,5‧-tetramethylbenzidine (TMB) as a chromogenic probe. It was observed that Fe(III) could directly oxidize TMB to form a blue solution without adding any extra oxidants. The reaction has a stoichiometric ratio of 1:1 (Fe(III)/TMB) as determined by a molar ratio method. The resultant color change can be perceived by the naked eye or monitored the absorbance change at 652 nm. The method allowed the measurement of Fe(III) in the range 1.0 × 10- 7-1.5 × 10- 4 mol L- 1 with a detection limit of 5.5 × 10- 8 mol L- 1. The relative standard deviation was 0.9% for eleven replicate measurements of 2.5 × 10- 5 mol L- 1 Fe(III) solution. The chemistry showed high selectivity for Fe(III) in contrast to other common cation ions. The practically of the method was evaluated by the determination of Fe in milk samples; good consistency was obtained between the results of this method and atomic absorption spectrophotometry as indicated by statistical analysis.

A MULTI-LABORATORY EVALUATION OF METHODS FOR DETECTING ENTERIC VIRUSES IN SOILS

EPA Science Inventory

Two candidate methods for the recovery and detection of viruses in soil were subjected to round robin comparative testing by members of the American Society for Testing and Materials D19:24:04:04 Subcommittee Task Group. Selection of the methods, designated “Berg” and “Goyal,” wa...

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.

Highly sensitive and selective liquid crystal optical sensor for detection of ammonia.

PubMed

Niu, Xiaofang; Zhong, Yuanbo; Chen, Rui; Wang, Fei; Luo, Dan

2017-06-12

Ammonia detection technologies are very important in environment monitoring. However, most existing technologies are complex and expensive, which limit the useful range of real-time application. Here, we propose a highly sensitive and selective optical sensor for detection of ammonia (NH 3 ) based on liquid crystals (LCs). This optical sensor is realized through the competitive binding between ammonia and liquid crystals on chitosan-Cu 2+ that decorated on glass substrate. We achieve a broad detection range of ammonia from 50 ppm to 1250 ppm, with a low detection limit of 16.6 ppm. This sensor is low-cost, simple, fast, and highly sensitive and selective for detection of ammonia. The proposal LC sensing method can be a sensitive detection platform for other molecule monitors such as proteins, DNAs and other heavy metal ions by modifying sensing molecules.

Highly sensitive and selective detection of dopamine using one-pot synthesized highly photoluminescent silicon nanoparticles.

PubMed

Zhang, Xiaodong; Chen, Xiaokai; Kai, Siqi; Wang, Hong-Yin; Yang, Jingjing; Wu, Fu-Gen; Chen, Zhan

2015-03-17

A simple and highly efficient method for dopamine (DA) detection using water-soluble silicon nanoparticles (SiNPs) was reported. The SiNPs with a high quantum yield of 23.6% were synthesized by using a one-pot microwave-assisted method. The fluorescence quenching capability of a variety of molecules on the synthesized SiNPs has been tested; only DA molecules were found to be able to quench the fluorescence of these SiNPs effectively. Therefore, such a quenching effect can be used to selectively detect DA. All other molecules tested have little interference with the dopamine detection, including ascorbic acid, which commonly exists in cells and can possibly affect the dopamine detection. The ratio of the fluorescence intensity difference between the quenched and unquenched cases versus the fluorescence intensity without quenching (ΔI/I) was observed to be linearly proportional to the DA analyte concentration in the range from 0.005 to 10.0 μM, with a detection limit of 0.3 nM (S/N = 3). To the best of our knowledge, this is the lowest limit for DA detection reported so far. The mechanism of fluorescence quenching is attributed to the energy transfer from the SiNPs to the oxidized dopamine molecules through Förster resonance energy transfer. The reported method of SiNP synthesis is very simple and cheap, making the above sensitive and selective DA detection approach using SiNPs practical for many applications.

Detection of atrial fibrillation after ischemic stroke or transient ischemic attack: a systematic review and meta-analysis.

PubMed

Kishore, Amit; Vail, Andy; Majid, Arshad; Dawson, Jesse; Lees, Kennedy R; Tyrrell, Pippa J; Smith, Craig J

2014-02-01

Atrial fibrillation (AF) confers a high risk of recurrent stroke, although detection methods and definitions of paroxysmal AF during screening vary. We therefore undertook a systematic review and meta-analysis to determine the frequency of newly detected AF using noninvasive or invasive cardiac monitoring after ischemic stroke or transient ischemic attack. Prospective observational studies or randomized controlled trials of patients with ischemic stroke, transient ischemic attack, or both, who underwent any cardiac monitoring for a minimum of 12 hours, were included after electronic searches of multiple databases. The primary outcome was detection of any new AF during the monitoring period. We prespecified subgroup analysis of selected (prescreened or cryptogenic) versus unselected patients and according to duration of monitoring. A total of 32 studies were analyzed. The overall detection rate of any AF was 11.5% (95% confidence interval, 8.9%-14.3%), although the timing, duration, method of monitoring, and reporting of diagnostic criteria used for paroxysmal AF varied. Detection rates were higher in selected (13.4%; 95% confidence interval, 9.0%-18.4%) than in unselected patients (6.2%; 95% confidence interval, 4.4%-8.3%). There was substantial heterogeneity even within specified subgroups. Detection of AF was highly variable, and the review was limited by small sample sizes and marked heterogeneity. Further studies are required to inform patient selection, optimal timing, methods, and duration of monitoring for detection of AF/paroxysmal AF.

Model selection for anomaly detection

NASA Astrophysics Data System (ADS)

Burnaev, E.; Erofeev, P.; Smolyakov, D.

2015-12-01

Anomaly detection based on one-class classification algorithms is broadly used in many applied domains like image processing (e.g. detection of whether a patient is "cancerous" or "healthy" from mammography image), network intrusion detection, etc. Performance of an anomaly detection algorithm crucially depends on a kernel, used to measure similarity in a feature space. The standard approaches (e.g. cross-validation) for kernel selection, used in two-class classification problems, can not be used directly due to the specific nature of a data (absence of a second, abnormal, class data). In this paper we generalize several kernel selection methods from binary-class case to the case of one-class classification and perform extensive comparison of these approaches using both synthetic and real-world data.

Antibody modified gold nanoparticles for fast and selective, colorimetric T7 bacteriophage detection.

PubMed

Lesniewski, Adam; Los, Marcin; Jonsson-Niedziółka, Martin; Krajewska, Anna; Szot, Katarzyna; Los, Joanna M; Niedziolka-Jonsson, Joanna

2014-04-16

Herein, we report a colorimetric immunosensor for T7 bacteriophage based on gold nanoparticles modified with covalently bonded anti-T7 antibodies. The new immunosensor allows for a fast, simple, and selective detection of T7 virus. T7 virions form immunological complexes with the antibody modified gold nanoparticles which causes them to aggregate. The aggregation can be observed with the naked eye as a color change from red to purple, as well as with a UV-vis spectrophotometer. The aggregate formation was confirmed with SEM imaging. Sensor selectivity against the M13 bacteriophage was demonstrated. The limit of detection (LOD) is 1.08 × 10(10) PFU/mL (18 pM) T7. The new method was compared with a traditional plaque test. In contrast to biological tests the colorimetric method allows for detection of all T7 phages, not only those biologically active. This includes phage ghosts and fragments of virions. T7 virus has been chosen as a model organism for adenoviruses. The described method has several advantages over the traditional ones. It is much faster than a standard plaque test. It is more robust since no bacteria-virus interactions are utilized in the detection process. Since antibodies are available for a large variety of pathogenic viruses, the described concept is very flexible and can be adapted to detect many different viruses, not only bacteriophages. Contrary to the classical immunoassays, it is a one-step detection method, and no additional amplification, e.g., enzymatic, is needed to read the result.

Methods, media, and systems for detecting attack on a digital processing device

DOEpatents

Stolfo, Salvatore J.; Li, Wei-Jen; Keromylis, Angelos D.; Androulaki, Elli

2014-07-22

Methods, media, and systems for detecting attack are provided. In some embodiments, the methods include: comparing at least part of a document to a static detection model; determining whether attacking code is included in the document based on the comparison of the document to the static detection model; executing at least part of the document; determining whether attacking code is included in the document based on the execution of the at least part of the document; and if attacking code is determined to be included in the document based on at least one of the comparison of the document to the static detection model and the execution of the at least part of the document, reporting the presence of an attack. In some embodiments, the methods include: selecting a data segment in at least one portion of an electronic document; determining whether the arbitrarily selected data segment can be altered without causing the electronic document to result in an error when processed by a corresponding program; in response to determining that the arbitrarily selected data segment can be altered, arbitrarily altering the data segment in the at least one portion of the electronic document to produce an altered electronic document; and determining whether the corresponding program produces an error state when the altered electronic document is processed by the corresponding program.

Methods, media, and systems for detecting attack on a digital processing device

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

Stolfo, Salvatore J.; Li, Wei-Jen; Keromytis, Angelos D.

Methods, media, and systems for detecting attack are provided. In some embodiments, the methods include: comparing at least part of a document to a static detection model; determining whether attacking code is included in the document based on the comparison of the document to the static detection model; executing at least part of the document; determining whether attacking code is included in the document based on the execution of the at least part of the document; and if attacking code is determined to be included in the document based on at least one of the comparison of the document tomore » the static detection model and the execution of the at least part of the document, reporting the presence of an attack. In some embodiments, the methods include: selecting a data segment in at least one portion of an electronic document; determining whether the arbitrarily selected data segment can be altered without causing the electronic document to result in an error when processed by a corresponding program; in response to determining that the arbitrarily selected data segment can be altered, arbitrarily altering the data segment in the at least one portion of the electronic document to produce an altered electronic document; and determining whether the corresponding program produces an error state when the altered electronic document is processed by the corresponding program.« less

A highly selective and simple fluorescent sensor for mercury (II) ion detection based on cysteamine-capped CdTe quantum dots synthesized by the reflux method.

PubMed

Ding, Xiaojie; Qu, Lingbo; Yang, Ran; Zhou, Yuchen; Li, Jianjun

2015-06-01

Cysteamine (CA)-capped CdTe quantum dots (QDs) (CA-CdTe QDs) were prepared by the reflux method and utilized as an efficient nano-sized fluorescent sensor to detect mercury (II) ions (Hg(2+) ). Under optimum conditions, the fluorescence quenching effect of CA-CdTe QDs was linear at Hg(2+) concentrations in the range of 6.0-450 nmol/L. The detection limit was calculated to be 4.0 nmol/L according to the 3σ IUPAC criteria. The influence of 10-fold Pb(2+) , Cu(2+) and Ag(+) on the determination of Hg(2+) was < 7% (superior to other reports based on crude QDs). Furthermore, the detection sensitivity and selectivity were much improved relative to a sensor based on the CA-CdTe QDs probe, which was prepared using a one-pot synthetic method. This CA-CdTe QDs sensor system represents a new feasibility to improve the detection performance of a QDs sensor by changing the synthesis method. Copyright © 2014 John Wiley & Sons, Ltd.

ROKU: a novel method for identification of tissue-specific genes

PubMed Central

Kadota, Koji; Ye, Jiazhen; Nakai, Yuji; Terada, Tohru; Shimizu, Kentaro

2006-01-01

Background One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. Results We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. Conclusion ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes. PMID:16764735

Methods for gas detection using stationary hyperspectral imaging sensors

DOEpatents

Conger, James L [San Ramon, CA; Henderson, John R [Castro Valley, CA

2012-04-24

According to one embodiment, a method comprises producing a first hyperspectral imaging (HSI) data cube of a location at a first time using data from a HSI sensor; producing a second HSI data cube of the same location at a second time using data from the HSI sensor; subtracting on a pixel-by-pixel basis the second HSI data cube from the first HSI data cube to produce a raw difference cube; calibrating the raw difference cube to produce a calibrated raw difference cube; selecting at least one desired spectral band based on a gas of interest; producing a detection image based on the at least one selected spectral band and the calibrated raw difference cube; examining the detection image to determine presence of the gas of interest; and outputting a result of the examination. Other methods, systems, and computer program products for detecting the presence of a gas are also described.

Evaluation of selective control information detection scheme in orthogonal frequency division multiplexing-based radio-over-fiber and visible light communication links

NASA Astrophysics Data System (ADS)

Dalarmelina, Carlos A.; Adegbite, Saheed A.; Pereira, Esequiel da V.; Nunes, Reginaldo B.; Rocha, Helder R. O.; Segatto, Marcelo E. V.; Silva, Jair A. L.

2017-05-01

Block-level detection is required to decode what may be classified as selective control information (SCI) such as control format indicator in 4G-long-term evolution systems. Using optical orthogonal frequency division multiplexing over radio-over-fiber (RoF) links, we report the experimental evaluation of an SCI detection scheme based on a time-domain correlation (TDC) technique in comparison with the conventional maximum likelihood (ML) approach. When compared with the ML method, it is shown that the TDC method improves detection performance over both 20 and 40 km of standard single mode fiber (SSMF) links. We also report a performance analysis of the TDC scheme in noisy visible light communication channel models after propagation through 40 km of SSMF. Experimental and simulation results confirm that the TDC method is attractive for practical orthogonal frequency division multiplexing-based RoF and fiber-wireless systems. Unlike the ML method, another key benefit of the TDC is that it requires no channel estimation.

A carbon dot-based "off-on" fluorescent probe for highly selective and sensitive detection of phytic acid.

PubMed

Gao, Zhao; Wang, Libing; Su, Rongxin; Huang, Renliang; Qi, Wei; He, Zhimin

2015-08-15

We herein report a facile, one-step pyrolysis synthesis of photoluminescent carbon dots (CDs) using citric acid as the carbon source and lysine as the surface passivation reagent. The as-prepared CDs show narrow size distribution, excellent blue fluorescence and good photo-stability and water dispersivity. The fluorescence of the CDs was found to be effectively quenched by ferric (Fe(III)) ions with high selectivity via a photo-induced electron transfer (PET) process. Upon addition of phytic acid (PA) to the CDs/Fe(III) complex dispersion, the fluorescence of the CDs was significantly recovered, arising from the release of Fe(III) ions from the CDs/Fe(III) complex because PA has a higher affinity for Fe(III) ions compared to CDs. Furthermore, we developed an "off-on" fluorescence assay method for the detection of phytic acid using CDs/Fe(III) as a fluorescent probe. This probe enables the selective detection of PA with a linear range of 0.68-18.69 μM and a limit of detection (signal-to-noise ratio is 3) of 0.36 μM. The assay method demonstrates high selectivity, repeatability, stability and recovery ratio in the detection of the standard and real PA samples. We believe that the facile operation, low-cost, high sensitivity and selectivity render this CD-based "off-on" fluorescent probe an ideal sensing platform for the detection of PA. Copyright © 2015 Elsevier B.V. All rights reserved.

Detection of enteropathogenic Escherichia coli by microchip capillary electrophoresis.

PubMed

Law, Wai S; Li, Sam F Y; Kricka, Larry J

2009-01-01

There is always a need to detect the presence of microorganisms, either as contaminants in food and pharmaceutical industries or bioindicators for disease diagnosis. Hence, it is important to develop efficient, rapid, and simple methods to detect microorganisms. Traditional culturing method is unsatisfactory due to its long incubation time. Molecular methods, although capable of providing a high degree of specificity, are not always useful in providing quick tests of presence or absence of microorganisms. Microchip elec-trophoresis has been recently employed to address problems associated with the detection of microorganisms due to its high versatility, selectivity, sensitivity, and short analysis times. In this work, the potential of PDMS-based microchip electrophoresis in the identification and characterization of microorganism was evaluated. Enteropathogenic E. coli (EPEC) was selected as the model microorganism. To obtain repeat-able separations, sample pretreatment was found to be essential. Microchip electrophoresis with laser-induced fluorescence detection could potentially revolutionize certain aspects of microbiology involving diagnosis, profiling of pathogens, environmental analysis, and many others areas of study.

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

PubMed Central

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

2017-01-01

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

Stripping analysis of nanomolar perchlorate in drinking water with a voltammetric ion-selective electrode based on thin-layer liquid membrane.

PubMed

Kim, Yushin; Amemiya, Shigeru

2008-08-01

A highly sensitive analytical method is required for the assessment of nanomolar perchlorate contamination in drinking water as an emerging environmental problem. We developed the novel approach based on a voltammetric ion-selective electrode to enable the electrochemical detection of "redox-inactive" perchlorate at a nanomolar level without its electrolysis. The perchlorate-selective electrode is based on the submicrometer-thick plasticized poly(vinyl chloride) membrane spin-coated on the poly(3-octylthiophene)-modified gold electrode. The liquid membrane serves as the first thin-layer cell for ion-transfer stripping voltammetry to give low detection limits of 0.2-0.5 nM perchlorate in deionized water, commercial bottled water, and tap water under a rotating electrode configuration. The detection limits are not only much lower than the action limit (approximately 246 nM) set by the U.S. Environmental Protection Agency but also are comparable to the detection limits of the most sensitive analytical methods for detecting perchlorate, that is, ion chromatography coupled with a suppressed conductivity detector (0.55 nM) or electrospray ionization mass spectrometry (0.20-0.25 nM). The mass transfer of perchlorate in the thin-layer liquid membrane and aqueous sample as well as its transfer at the interface between the two phases were studied experimentally and theoretically to achieve the low detection limits. The advantages of ion-transfer stripping voltammetry with a thin-layer liquid membrane against traditional ion-selective potentiometry are demonstrated in terms of a detection limit, a response time, and selectivity.

Gold nanoparticle-sensitized quartz crystal microbalance sensor for rapid and highly selective determination of Cu(II) ions.

PubMed

Jin, Yulong; Huang, Yanyan; Liu, Guoquan; Zhao, Rui

2013-09-21

A novel quartz crystal microbalance (QCM) sensor for rapid, highly selective and sensitive detection of copper ions was developed. As a signal amplifier, gold nanoparticles (Au NPs) were self-assembled onto the surface of the sensor. A simple dip-and-dry method enabled the whole detection procedure to be accomplished within 20 min. High selectivity of the sensor towards copper ions is demonstrated by both individual and coexisting assays with interference ions. This gold nanoparticle mediated amplification allowed a detection limit down to 3.1 μM. Together with good repeatability and regeneration, the QCM sensor was also applied to the analysis of copper contamination in drinking water. This work provides a flexible method for fabricating QCM sensors for the analysis of important small molecules in environmental and biological samples.

Assessment of Hyporheic Zone, Flood-Plain, Soil-Gas, Soil, and Surface-Water Contamination at the McCoys Creek Chemical Training Area, Fort Gordon, Georgia, 2009-2010

USGS Publications Warehouse

Guimaraes, Wladmir B.; Falls, W. Fred; Caldwell, Andral W.; Ratliff, W. Hagan; Wellborn, John B.; Landmeyer, James E.

2011-01-01

The U.S. Geological Survey, in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon, Georgia, assessed the hyporheic zone, flood plain, soil gas, soil, and surface water for contaminants at the McCoys Creek Chemical Training Area (MCTA) at Fort Gordon, from October 2009 to September 2010. The assessment included the detection of organic contaminants in the hyporheic zone, flood plain, soil gas, and surface water. In addition, the organic contaminant assessment included the analysis of organic compounds classified as explosives and chemical agents in selected areas. Inorganic contaminants were assessed in soil and surface-water samples. The assessment was conducted to provide environmental contamination data to the U.S. Army at Fort Gordon pursuant to requirements of the Resource Conservation and Recovery Act Part B Hazardous Waste Permit process. Ten passive samplers were deployed in the hyporheic zone and flood plain, and total petroleum hydrocarbons (TPH) and octane were detected above the method detection level in every sampler. Other organic compounds detected above the method detection level in the hyporheic zone and flood-plain samplers were trichloroethylene, and cis- and trans- 1, 2-dichloroethylene. One trip blank detected TPH below the method detection level but above the nondetection level. The concentrations of TPH in the samplers were many times greater than the concentrations detected in the blank; therefore, all other TPH concentrations detected are considered to represent environmental conditions. Seventy-one soil-gas samplers were deployed in a grid pattern across the MCTA. Three trip blanks and three method blanks were used and not deployed, and TPH was detected above the method detection level in two trip blanks and one method blank. Detection of TPH was observed at all 71 samplers, but because TPH was detected in the trip and method blanks, TPH was censored and, therefore, only 7 of the 71 samplers were reported as detecting TPH. In addition, benzene, toluene, ethylbenzene, and total xylene were detected above the method detection level in 22 samplers. Other compounds detected above the method detection level included naphthalene, octane, undecane, tridecane, 1,2,4-trimethylbenzene, trichloroethylene, perchloroethylene, chloroform, and 1,4-dichlorobenzene. Subsequent to the soil-gas survey, five locations with elevated contaminant mass were selected and a passive sampler was deployed at those locations to detect the presence of organic compounds classified as explosives or chemical agents. No explosives or chemical agents were detected above the method detection level, but some compounds were detected below the method detection level but above the nondetection level. Dimethyl disulfide, benzothiazole, chloroacetophenones, and para-chlorophenyl methyl sulfide were all detected below the method detection level but above the nondetection level. The compounds 2,4-dinitrotoluene, and para-chlorophenyl methyl sulfone were detected in samplers but also were detected in trip blanks and are not considered as present in the MCTA. The same five locations that were selected for sampling of explosives and chemical agents were selected for soil sampling. Metal concentrations in composite soil samples collected at five locations from land surface to a depth of 6 inches did not exceed the U.S. Environmental Protection Agency Regional Screening Levels for Industrial Soil. Concentrations in some compounds were higher than the South Carolina Department of Health and Environmental Control background levels for nearby South Carolina, including aluminum, arsenic, barium, beryllium, chromium, copper, iron, lead, manganese, nickel, and potassium. A surface-water sample was collected from McCoys Creek and analyzed for volatile organic compounds, semivolatile organic compounds, and inorganic compounds (metals). No volatile organic compounds and (or) semivolatile organic compounds were detected at levels above the maximum contaminant level of the U.S. Environmental Protection Agency (USEPA) National Primary Drinking Water Standard, and no inorganic compounds exceeded the maximum contaminant level of the USEPA National Primary Drinking Water Standard or the Georgia In-Stream Water-Quality Standard. Iron was the only inorganic compound detected in the surface-water sample (578 micrograms per liter) that exceeded the USEPA National Secondary Drinking Water Standard of 300 micrograms per liter.

Sol-Gel Matrices For Direct Colorimetric Detection Of Analytes

DOEpatents

Charych, Deborah H.; Sasaki, Darryl; Yamanaka, Stacey

2002-11-26

The present invention relates to methods and compositions for the direct detection of analytes using color changes that occur in immobilized biopolymeric material in response to selective binding of analytes to their surface. In particular, the present invention provides methods and compositions related to the encapsulation of biopolymeric material into metal oxide glass using the sol-gel method.

Sol-gel matrices for direct colorimetric detection of analytes

DOEpatents

Charych, Deborah H.; Sasaki, Darryl; Yamanaka, Stacey

2000-01-01

The present invention relates to methods and compositions for the direct detection of analytes using color changes that occur in immobilized biopolymeric material in response to selective binding of analytes to their surface. In particular, the present invention provides methods and compositions related to the encapsulation of biopolymeric material into metal oxide glass using the sol-gel method.

The invisible AGN catalogue: a mid-infrared-radio selection method for optically faint active galactic nuclei

NASA Astrophysics Data System (ADS)

Truebenbach, Alexandra E.; Darling, Jeremy

2017-06-01

A large fraction of active galactic nuclei (AGN) are 'invisible' in extant optical surveys due to either distance or dust-obscuration. The existence of this large population of dust-obscured, infrared (IR)-bright AGN is predicted by models of galaxy-supermassive black hole coevolution and is required to explain the observed X-ray and IR backgrounds. Recently, IR colour cuts with Wide-field Infrared Survey Explorer have identified a portion of this missing population. However, as the host galaxy brightness relative to that of the AGN increases, it becomes increasingly difficult to differentiate between IR emission originating from the AGN and from its host galaxy. As a solution, we have developed a new method to select obscured AGN using their 20-cm continuum emission to identify the objects as AGN. We created the resulting invisible AGN catalogue by selecting objects that are detected in AllWISE (mid-IR) and FIRST (20 cm), but are not detected in SDSS (optical) or 2MASS (near-IR), producing a final catalogue of 46 258 objects. 30 per cent of the objects are selected by existing selection methods, while the remaining 70 per cent represent a potential previously unidentified population of candidate AGN that are missed by mid-IR colour cuts. Additionally, by relying on a radio continuum detection, this technique is efficient at detecting radio-loud AGN at z ≥ 0.29, regardless of their level of dust obscuration or their host galaxy's relative brightness.

A simple and selective resonance Rayleigh scattering-energy transfer spectral method for determination of trace neomycin sulfate using Cu2O particle as probe

NASA Astrophysics Data System (ADS)

Ouyang, Huixiang; Liang, Aihui; Jiang, Zhiliang

2018-02-01

The stable Cu2O nanocubic (Cu2ONC) sol was prepared, based on graphene oxide (GO) catalysis of glucose-Fehling's reagent reaction, and its absorption and resonance Rayleigh scattering (RRS) spectra, transmission electron microscopy (TEM) and energy dispersive spectroscopy (EDS) were examined. Using the as-prepared Cu2ONC as RRS probe, and coupling with the neomycin sulfate (NEO) complex reaction, a new, simple, sensitive and selective RRS-energy transfer (RRS-ET) method was established for detection of neomycin sulfate, with a linear range of 1.4-112 μM and a detection limit of 0.4 μM. The method has been applied to the detection of neomycin sulfate in samples with satisfactory results.

Amplified electrochemical detection of nucleic acid hybridization via selective preconcentration of unmodified gold nanoparticles.

PubMed

Li, Yuan; Tian, Rui; Zheng, Xingwang; Huang, Rongfu

2016-08-31

The common drawback of optical methods for rapid detection of nucleic acid by exploiting the differential affinity of single-/double-stranded nucleic acids for unmodified gold nanoparticles (AuNPs) is its relatively low sensitivity. In this article, on the basis of selective preconcentration of AuNPs unprotected by single-stranded DNA (ssDNA) binding, a novel electrochemical strategy for nucleic acid sequence identification assay has been developed. Through detecting the redox signal mediated by AuNPs on 1, 6-hexanedithiol blocked gold electrode, the proposed method is able to ensure substantial signal amplification and a low background current. This strategy is demonstrated for quantitative analysis of the target microRNA (let-7a) in human breast adenocarcinoma cells, and a detection limit of 16 fM is readily achieved with desirable specificity and sensitivity. These results indicate that the selective preconcentration of AuNPs for electrochemical signal readout can offer a promising platform for the detection of specific nucleic acid sequence. Copyright © 2016 Elsevier B.V. All rights reserved.

CAPILLARY GAS CHROMATOGRAPHY-ATOMIC EMISSION DETECTION METHOD FOR THE DETERMINATION OF PENTYLATED ORGANOTIN COMPOUNDS: INTERLABORATORY STUDY

EPA Science Inventory

A capillary gas chromatography-atomic emission detection (GC-AED) method was developed for the U. S. Environmental Protection Agency's Environmental Monitoring Systems Laboratory in Las Vegas, NV, for determination of selected organotin compounds. Here we report on an interlabora...

Three-dimensional, position-sensitive radiation detection

DOEpatents

He, Zhong; Zhang, Feng

2010-04-06

Disclosed herein is a method of determining a characteristic of radiation detected by a radiation detector via a multiple-pixel event having a plurality of radiation interactions. The method includes determining a cathode-to-anode signal ratio for a selected interaction of the plurality of radiation interactions based on electron drift time data for the selected interaction, and determining the radiation characteristic for the multiple-pixel event based on both the cathode-to-anode signal ratio and the electron drift time data. In some embodiments, the method further includes determining a correction factor for the radiation characteristic based on an interaction depth of the plurality of radiation interactions, a lateral distance between the selected interaction and a further interaction of the plurality of radiation interactions, and the lateral positioning of the plurality of radiation interactions.

Electrochemical Selective and Simultaneous Detection of Diclofenac and Ibuprofen in Aqueous Solution Using HKUST-1 Metal-Organic Framework-Carbon Nanofiber Composite Electrode.

PubMed

Motoc, Sorina; Manea, Florica; Iacob, Adriana; Martinez-Joaristi, Alberto; Gascon, Jorge; Pop, Aniela; Schoonman, Joop

2016-10-17

In this study, the detection protocols for the individual, selective, and simultaneous determination of ibuprofen (IBP) and diclofenac (DCF) in aqueous solutions have been developed using HKUST-1 metal-organic framework-carbon nanofiber composite (HKUST-CNF) electrode. The morphological and electrical characterization of modified composite electrode prepared by film casting was studied by scanning electronic microscopy and four-point-probe methods. The electrochemical characterization of the electrode by cyclic voltammetry (CV) was considered the reference basis for the optimization of the operating conditions for chronoamperometry (CA) and multiple-pulsed amperometry (MPA). This electrode exhibited the possibility to selectively detect IBP and DCF by simple switching the detection potential using CA. However, the MPA operated under optimum working conditions of four potential levels selected based on CV shape in relation to the potential value, pulse time, and potential level number, and order allowed the selective/simultaneous detection of IBP and DCF characterized by the enhanced detection performance. For this application, the HKUST-CNF electrode exhibited a good stability and reproducibility of the results was achieved.

Electrochemical Selective and Simultaneous Detection of Diclofenac and Ibuprofen in Aqueous Solution Using HKUST-1 Metal-Organic Framework-Carbon Nanofiber Composite Electrode

PubMed Central

Motoc, Sorina; Manea, Florica; Iacob, Adriana; Martinez-Joaristi, Alberto; Gascon, Jorge; Pop, Aniela; Schoonman, Joop

2016-01-01

In this study, the detection protocols for the individual, selective, and simultaneous determination of ibuprofen (IBP) and diclofenac (DCF) in aqueous solutions have been developed using HKUST-1 metal-organic framework-carbon nanofiber composite (HKUST-CNF) electrode. The morphological and electrical characterization of modified composite electrode prepared by film casting was studied by scanning electronic microscopy and four-point-probe methods. The electrochemical characterization of the electrode by cyclic voltammetry (CV) was considered the reference basis for the optimization of the operating conditions for chronoamperometry (CA) and multiple-pulsed amperometry (MPA). This electrode exhibited the possibility to selectively detect IBP and DCF by simple switching the detection potential using CA. However, the MPA operated under optimum working conditions of four potential levels selected based on CV shape in relation to the potential value, pulse time, and potential level number, and order allowed the selective/simultaneous detection of IBP and DCF characterized by the enhanced detection performance. For this application, the HKUST-CNF electrode exhibited a good stability and reproducibility of the results was achieved. PMID:27763509

Hybrid feature selection for supporting lightweight intrusion detection systems

NASA Astrophysics Data System (ADS)

Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

2017-08-01

Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

Selective detection of Co2+ by fluorescent nano probe: Diagnostic approach for analysis of environmental samples and biological activities

NASA Astrophysics Data System (ADS)

Mahajan, Prasad G.; Dige, Nilam C.; Desai, Netaji K.; Patil, Shivajirao R.; Kondalkar, Vijay V.; Hong, Seong-Karp; Lee, Ki Hwan

2018-06-01

Nowadays scientist over the world are engaging to put forth improved methods to detect metal ion in an aqueous medium based on fluorescence studies. A simple, selective and sensitive method was proposed for detection of Co2+ ion using fluorescent organic nanoparticles. We synthesized a fluorescent small molecule viz. 4,4‧-{benzene-1,4-diylbis-[(Z)methylylidenenitrilo]}dibenzoic acid (BMBA) to explore its suitability as sensor for Co2+ ion and biocompatibility in form of nanoparticles. Fluorescence nanoparticles (BMBANPs) prepared by simple reprecipitation method. Aggregation induced enhanced emission of BMBANPs exhibits the narrower particle size of 68 nm and sphere shape morphology. The selective fluorescence quenching was observed by addition of Co2+ and does not affected by presence of other coexisting ion solutions. The photo-physical properties, viz. UV-absorption, fluorescence emission, and lifetime measurements are in support of ligand-metal interaction followed by static fluorescence quenching phenomenon in emission of BMBANPs. Finally, we develop a simple analytical method for selective and sensitive determination of Co2+ ion in environmental samples. The cell culture E. coli, Bacillus sps., and M. tuberculosis H37RV strain in the vicinity of BMBANPs indicates virtuous anti-bacterial and anti-tuberculosis activity which is of additional novel application shown by prepared nanoparticles.

Selective enrichment and determination of monoamine neurotransmitters by CU(II) immobilized magnetic solid phase extraction coupled with high-performance liquid chromatography-fluorescence detection.

PubMed

He, Maofang; Wang, Chaozhan; Wei, Yinmao

2016-01-15

In this paper, iminodiacetic acid-Cu(II) functionalized Fe3O4@SiO2 magnetic nanoparticles were prepared and used as new adsorbents for magnetic solid phase extraction (MSPE) of six monoamine neurotransmitters (MNTs) from rabbit plasma. The selective enrichment of MNTs at pH 5.0 was motivated by the specific coordination interaction between amino groups of MNTs and the immobilized Cu(II). The employed weak acidic extraction condition avoided the oxidation of MNTs, and thus facilitated operation and ensured higher recoveries. Under optimal conditions, the recoveries of six MNTs from rabbit plasma were in the range of 83.9-109.4%, with RSD of 2.0-10.0%. When coupled the Cu(II) immobilized MSPE with high-performance liquid chromatography-fluorescence detection, the method exhibited relatively lower detection limits than the previously reported methods, and the method was successfully used to determine the endogenous MNTs in rabbit plasma. The proposed method has potential application for the determination of MNTs in biological samples. Also, the utilization of coordination interaction to improve the selectivity might open another way to selectively enrich small alkaloids from complex samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Determination of Polychlorinated Biphenyls in Soil and Sediment by Selective Pressurized Liquid Extraction with Immunochemical Detection

EPA Science Inventory

A selective liquid pressurized extraction (SPLE) method was developed as a streamlined sample preparation/cleanup procedure for determining Aroclors and coplanar polychlorinated biphenyls (PCBs) in soil and sediment matrices. The SPLE method was coupled with an enzyme-linked imm...

Selective chromogenic detection of thiol-containing biomolecules using carbonaceous nanospheres loaded with silver nanoparticles as carrier.

PubMed

Hu, Bo; Zhao, Yang; Zhu, Hai-Zhou; Yu, Shu-Hong

2011-04-26

Thiol-containing biomolecules show strong affinity with noble metal nanostructures and could not only stably protect them but also control the self-assembly process of these special nanostructures. A highly selective and sensitive chromogenic detection method has been designed for the low and high molecular weight thiol-containing biomolecules, including cysteine, glutathione, dithiothreitol, and bovine serum albumin, using a new type of carbonaceous nanospheres loaded with silver nanoparticles (Ag NPs) as carrier. This strategy relies upon the place-exchange process between the reporter dyes on the surface of Ag NPs and the thiol groups of thiol-containing biomolecules. The concentration of biomolecules can be determined by monitoring with the fluorescence intensity of reporter dyes dispersed in solution. This new chromogenic assay method could selectively detect these biomolecules in the presence of various other amino acids and monosaccharides and even sensitively detect the thiol-containing biomolecules with different molecular weight, even including proteins.

Selective and comprehensive analysis of organohalogen compounds by GC × GC-HRTofMS and MS/MS.

PubMed

Hashimoto, Shunji; Zushi, Yasuyuki; Takazawa, Yoshikatsu; Ieda, Teruyo; Fushimi, Akihiro; Tanabe, Kiyoshi; Shibata, Yasuyuki

2018-03-01

Thousands of organohalogen compounds, including hazardous chemicals such as polychlorinated biphenyls (PCBs) and other persistent organic pollutants (POPs), were selectively and simultaneously detected and identified with simple, or no, purification from environmental sample extracts by using several advanced methods. The methods used were software extraction from two-dimensional gas chromatography-high-resolution time-of-flight mass spectrometry (GC × GC-HRTofMS) data, measurement by negative chemical ionization with HRTofMS, and neutral loss scanning (NLS) with GC × GC-MS/MS. Global and selective detection of organochlorines and bromines in environmental samples such as sediments and fly ash was achieved by NLS using GC × GC-MS/MS (QQQ), with the expected losses of 35 Cl and 79 Br. We confirmed that negative chemical ionization was effective for sensitive and selective ionization of organohalogens, even using GC × GC-HRTofMS. The 2D total ion chromatograms obtained by using negative chemical ionization and selective extraction of organohalogens using original software from data measured by electron impact ionization were very similar; the software thus functioned well to extract organohalogens. Combining measurements made by using these different methods will help to detect organohalogens selectively and globally. However, to compare the data obtained by individual measurements, the retention times of the peaks on the 2D chromatograms need to match.

Development of a Novel Loop-Mediated Isothermal Amplification (LAMP) Assay for the Detection of Rickettsia spp.

PubMed

Hanaoka, Nozomu; Matsutani, Minenosuke; Satoh, Masaaki; Ogawa, Motohiko; Shirai, Mutsunori; Ando, Shuji

2017-01-24

We developed a novel loop-mediated isothermal amplification (LAMP) method to detect Rickettsia spp., including Rickettsia prowazekii and R. typhi. Species-specific LAMP primers were developed for orthologous genes conserved among Rickettsia spp. The selected modified primers could detect all the Rickettsia spp. tested. The LAMP method was successfully used to detect 100 DNA copies of Rickettsia spp. within approximately 60 min at 63℃. Therefore, this method may be an excellent tool for the early diagnosis of rickettsiosis in a laboratory or in the field.

Joint study of lipopolysaccharide suspensions with thermal lensing and optoacoustic methods

NASA Astrophysics Data System (ADS)

Orlova, Nataliya V.; Brusnichkin, Anton V.; Proskurnin, Mikhail A.; Fokin, Andrey V.; Ovchinnikov, Oleg B.; Egerev, Sergey V.

2004-07-01

Pyrogens being introduced intravenously increase body temperature that leads to hazardous consequences and even to lethal outcome. One of the widespread pyrogen systems is presented by suspensions composed of bacterial endotoxins (or lypopolysaccharides, LPS). The aim of the work is to compare experimentally two methods for the determination of LPS at the submicrogram level and below. Both methods suppose that the LPS suspension is irradiated by a laser pulse. The thermal lens (TL) method (microsecond to millisecond irradiation cycle) detects LPS by a direct pick-up of the transient thermal field. The optoacoustic (OA) method (nanosecond laser pulses) has a potential to use non-thermal constitutents of the LPS response and to provide some selectivity of LPS detection with respect to optically uniform contaminants in the sample. In experiments, the selectivity was enhanced by means of analytical reagents, methylene blue and Stains All dyes. It was shown that both methods are mutually complementary. Then, their detectability potential increases and reaches 10 ppb if there occur ion pairs of LPS and cationic dye.

Highly specific and cost-efficient detection of Salmonella Paratyphi A combining aptamers with single-walled carbon nanotubes.

PubMed

Yang, Ming; Peng, Zhihui; Ning, Yi; Chen, Yongzhe; Zhou, Qin; Deng, Le

2013-05-22

In this paper, a panel of single-stranded DNA aptamers with high affinity and specificity against Salmonella Paratyphi A was selected from an enriched oligonucleotide pool by a whole-cell-Systematic Evolution of Ligands by Exponential Enrichment (SELEX) procedure, during which four other Salmonella serovars were used as counter-selection targets. It was determined through a fluorescence assay that the selected aptamers had high binding ability and specificity to this pathogen. The dissociation constant of these aptamers were up to nanomolar range, and aptamer Apt22 with the lowest Kd (47 ± 3 nM) was used in cell imaging experiments. To detect this bacteria with high specificity and cost-efficiently, a novel useful detection method was also constructed based on the noncovalent self-assembly of single-walled carbon nanotubes (SWNTs) and DNAzyme-labeled aptamer detection probes. The amounts of target bacteria could be quantified by exploiting chemoluminescence intensity changes at 420 nm and the detection limit of the method was 103 cfu/mL. This study demonstrated the applicability of Salmonella specific aptamers and their potential for use in the detection of Salmonella in food, clinical and environmental samples.

Digital transillumination in caries detection versus radiographic and clinical methods: an in-vivo study

PubMed Central

Lara-Capi, Cynthia; Lingström, Peter; Lai, Gianfranco; Cocco, Fabio; Simark-Mattsson, Charlotte; Campus, Guglielmo

2017-01-01

Objectives: This article aimed to evaluate: (a) the agreement between a near-infrared light transillumination device and clinical and radiographic examinations in caries lesion detection and (b) the reliability of images captured by the transillumination device. Methods: Two calibrated examiners evaluated the caries status in premolars and molars on 52 randomly selected subjects by comparing the transillumination device with a clinical examination for the occlusal surfaces and by comparing the transillumination device with a radiographic examination (bitewing radiographs) for the approximal surfaces. Forty-eight trained dental hygienists evaluated and reevaluated 30 randomly selected images 1-month later. Results: A high concordance between transillumination method and clinical examination (kappa = 0.99) was detected for occlusal caries lesions, while for approximal surfaces, the transillumination device identified a higher number of lesions with respect to bitewing (kappa = 0.91). At the dentinal level, the two methods identified the same number of caries lesions (kappa = 1), whereas more approximal lesions were recorded using the transillumination device in the enamel (kappa = 0.24). The intraexaminer reliability was substantial/almost perfect in 59.4% of the participants. Conclusions: The transillumination method showed a high concordance compared with traditional methods (clinical examination and bitewing radiographs). Caries detection reliability using the transillumination device images showed a high intraexaminer agreement. Transillumination showed to be a reliable method and as effective as traditional methods in caries detection. PMID:28191797

Unsupervised online classifier in sleep scoring for sleep deprivation studies.

PubMed

Libourel, Paul-Antoine; Corneyllie, Alexandra; Luppi, Pierre-Hervé; Chouvet, Guy; Gervasoni, Damien

2015-05-01

This study was designed to evaluate an unsupervised adaptive algorithm for real-time detection of sleep and wake states in rodents. We designed a Bayesian classifier that automatically extracts electroencephalogram (EEG) and electromyogram (EMG) features and categorizes non-overlapping 5-s epochs into one of the three major sleep and wake states without any human supervision. This sleep-scoring algorithm is coupled online with a new device to perform selective paradoxical sleep deprivation (PSD). Controlled laboratory settings for chronic polygraphic sleep recordings and selective PSD. Ten adult Sprague-Dawley rats instrumented for chronic polysomnographic recordings. The performance of the algorithm is evaluated by comparison with the score obtained by a human expert reader. Online detection of PS is then validated with a PSD protocol with duration of 72 hours. Our algorithm gave a high concordance with human scoring with an average κ coefficient > 70%. Notably, the specificity to detect PS reached 92%. Selective PSD using real-time detection of PS strongly reduced PS amounts, leaving only brief PS bouts necessary for the detection of PS in EEG and EMG signals (4.7 ± 0.7% over 72 h, versus 8.9 ± 0.5% in baseline), and was followed by a significant PS rebound (23.3 ± 3.3% over 150 minutes). Our fully unsupervised data-driven algorithm overcomes some limitations of the other automated methods such as the selection of representative descriptors or threshold settings. When used online and coupled with our sleep deprivation device, it represents a better option for selective PSD than other methods like the tedious gentle handling or the platform method. © 2015 Associated Professional Sleep Societies, LLC.

Galaxy clusters in the cosmic web

NASA Astrophysics Data System (ADS)

Acebrón, A.; Durret, F.; Martinet, N.; Adami, C.; Guennou, L.

2014-12-01

Simulations of large scale structure formation in the universe predict that matter is essentially distributed along filaments at the intersection of which lie galaxy clusters. We have analysed 9 clusters in the redshift range 0.4

Selection of regularization parameter for l1-regularized damage detection

NASA Astrophysics Data System (ADS)

Hou, Rongrong; Xia, Yong; Bao, Yuequan; Zhou, Xiaoqing

2018-06-01

The l1 regularization technique has been developed for structural health monitoring and damage detection through employing the sparsity condition of structural damage. The regularization parameter, which controls the trade-off between data fidelity and solution size of the regularization problem, exerts a crucial effect on the solution. However, the l1 regularization problem has no closed-form solution, and the regularization parameter is usually selected by experience. This study proposes two strategies of selecting the regularization parameter for the l1-regularized damage detection problem. The first method utilizes the residual and solution norms of the optimization problem and ensures that they are both small. The other method is based on the discrepancy principle, which requires that the variance of the discrepancy between the calculated and measured responses is close to the variance of the measurement noise. The two methods are applied to a cantilever beam and a three-story frame. A range of the regularization parameter, rather than one single value, can be determined. When the regularization parameter in this range is selected, the damage can be accurately identified even for multiple damage scenarios. This range also indicates the sensitivity degree of the damage identification problem to the regularization parameter.

Tumor suppressor molecules and methods of use

DOEpatents

Welch, Peter J.; Barber, Jack R.

2004-09-07

The invention provides substantially pure tumor suppressor nucleic acid molecules and tumor suppressor polypeptides. The invention also provides hairpin ribozymes and antibodies selective for these tumor suppressor molecules. Also provided are methods of detecting a neoplastic cell in a sample using detectable agents specific for the tumor suppressor nucleic acids and polypeptides.

Technique for Increasing the Selectivity of the Method of Laser Fragmentation/Laser-Induced Fluorescence

NASA Astrophysics Data System (ADS)

Bobrovnikov, S. M.; Gorlov, E. V.; Zharkov, V. I.

2018-05-01

A technique for increasing the selectivity of the method of detecting high-energy materials (HEMs) based on laser fragmentation of HEM molecules with subsequent laser excitation of fluorescence of the characteristic NO fragments from the first vibrational level of the ground state is suggested.

Android malware detection based on evolutionary super-network

NASA Astrophysics Data System (ADS)

Yan, Haisheng; Peng, Lingling

2018-04-01

In the paper, an android malware detection method based on evolutionary super-network is proposed in order to improve the precision of android malware detection. Chi square statistics method is used for selecting characteristics on the basis of analyzing android authority. Boolean weighting is utilized for calculating characteristic weight. Processed characteristic vector is regarded as the system training set and test set; hyper edge alternative strategy is used for training super-network classification model, thereby classifying test set characteristic vectors, and it is compared with traditional classification algorithm. The results show that the detection method proposed in the paper is close to or better than traditional classification algorithm. The proposed method belongs to an effective Android malware detection means.

On the use of feature selection to improve the detection of sea oil spills in SAR images

NASA Astrophysics Data System (ADS)

Mera, David; Bolon-Canedo, Veronica; Cotos, J. M.; Alonso-Betanzos, Amparo

2017-03-01

Fast and effective oil spill detection systems are crucial to ensure a proper response to environmental emergencies caused by hydrocarbon pollution on the ocean's surface. Typically, these systems uncover not only oil spills, but also a high number of look-alikes. The feature extraction is a critical and computationally intensive phase where each detected dark spot is independently examined. Traditionally, detection systems use an arbitrary set of features to discriminate between oil spills and look-alikes phenomena. However, Feature Selection (FS) methods based on Machine Learning (ML) have proved to be very useful in real domains for enhancing the generalization capabilities of the classifiers, while discarding the existing irrelevant features. In this work, we present a generic and systematic approach, based on FS methods, for choosing a concise and relevant set of features to improve the oil spill detection systems. We have compared five FS methods: Correlation-based feature selection (CFS), Consistency-based filter, Information Gain, ReliefF and Recursive Feature Elimination for Support Vector Machine (SVM-RFE). They were applied on a 141-input vector composed of features from a collection of outstanding studies. Selected features were validated via a Support Vector Machine (SVM) classifier and the results were compared with previous works. Test experiments revealed that the classifier trained with the 6-input feature vector proposed by SVM-RFE achieved the best accuracy and Cohen's kappa coefficient (87.1% and 74.06% respectively). This is a smaller feature combination with similar or even better classification accuracy than previous works. The presented finding allows to speed up the feature extraction phase without reducing the classifier accuracy. Experiments also confirmed the significance of the geometrical features since 75.0% of the different features selected by the applied FS methods as well as 66.67% of the proposed 6-input feature vector belong to this category.

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 nanomaterials in the bioanalytical detection of disease-related genes.

PubMed

Zhu, Xiaoqian; Li, Jiao; He, Hanping; Huang, Min; Zhang, Xiuhua; Wang, Shengfu

2015-12-15

In the diagnosis of genetic diseases and disorders, nanomaterials-based gene detection systems have significant advantages over conventional diagnostic systems in terms of simplicity, sensitivity, specificity, and portability. In this review, we describe the application of nanomaterials for disease-related genes detection in different methods excluding PCR-related method, such as colorimetry, fluorescence-based methods, electrochemistry, microarray methods, surface-enhanced Raman spectroscopy (SERS), quartz crystal microbalance (QCM) methods, and dynamic light scattering (DLS). The most commonly used nanomaterials are gold, silver, carbon and semiconducting nanoparticles. Various nanomaterials-based gene detection methods are introduced, their respective advantages are discussed, and selected examples are provided to illustrate the properties of these nanomaterials and their emerging applications for the detection of specific nucleic acid sequences. Copyright © 2015. Published by Elsevier B.V.

Data-driven region-of-interest selection without inflating Type I error rate.

PubMed

Brooks, Joseph L; Zoumpoulaki, Alexia; Bowman, Howard

2017-01-01

In ERP and other large multidimensional neuroscience data sets, researchers often select regions of interest (ROIs) for analysis. The method of ROI selection can critically affect the conclusions of a study by causing the researcher to miss effects in the data or to detect spurious effects. In practice, to avoid inflating Type I error rate (i.e., false positives), ROIs are often based on a priori hypotheses or independent information. However, this can be insensitive to experiment-specific variations in effect location (e.g., latency shifts) reducing power to detect effects. Data-driven ROI selection, in contrast, is nonindependent and uses the data under analysis to determine ROI positions. Therefore, it has potential to select ROIs based on experiment-specific information and increase power for detecting effects. However, data-driven methods have been criticized because they can substantially inflate Type I error rate. Here, we demonstrate, using simulations of simple ERP experiments, that data-driven ROI selection can indeed be more powerful than a priori hypotheses or independent information. Furthermore, we show that data-driven ROI selection using the aggregate grand average from trials (AGAT), despite being based on the data at hand, can be safely used for ROI selection under many circumstances. However, when there is a noise difference between conditions, using the AGAT can inflate Type I error and should be avoided. We identify critical assumptions for use of the AGAT and provide a basis for researchers to use, and reviewers to assess, data-driven methods of ROI localization in ERP and other studies. © 2016 Society for Psychophysiological Research.

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.

Chemiluminescence of creatinine/H2O2/Co(2+) and its application for selective creatinine detection.

PubMed

Hanif, Saima; John, Peter; Gao, Wenyue; Saqib, Muhammad; Qi, Liming; Xu, Guobao

2016-01-15

Creatinine is an important biomarker in clinical diagnosis and biomonitoring programs as well as urinary metabolomic/metabonomics research. Current methods are either nonselective, time consuming or require heavy and expensive instruments. In this study, chemiluminescence of creatinine with hydrogen peroxide has been reported for the first time, and its chemiluminescence is remarkably enhanced in the presence of cobalt ions. By utilizing these phenomena, we have developed a sensitive and selective chemiluminescence method for creatinine determination by coupling with flow injection analysis. The calibration curve is linear in the range of 1×10(-7)-3×10(-5)mol/L with a limit of detection (S/N=3) of 7.2×10(-8)mol/L, which is adequate for detecting creatinine in the clinically accepted range. The relative standard deviation for seven measurements of 3×10(-5)mol/L creatinine is 1.2%. The chemiluminescence method was then utilized to detect creatinine in human urine samples after simple dilution with water. It takes less than 1min each measurement and the recoveries for spiked urine samples were 100-103%. The interference study demonstrates that some common species in urine, such as amino acids, ascorbic acid and creatine, have negligible effects on creatinine detection. The present method does not use expensive instruments, enzymes and separation technique. This method has the advantages of sensitivity, selectivity, simplicity, rapidity, and low cost. It holds great promise for basic or comprehensive metabolic panel, drug screening, anti-dopping, and urinary metabolomic/metabonomics research. Copyright © 2015 Elsevier B.V. All rights reserved.

Nanobioprobe mediated DNA aptamers for explosive detection.

PubMed

Priyanka; Shorie, Munish; Bhalla, Vijayender; Pathania, Preeti; Suri, C Raman

2014-02-04

Specific nucleic acid aptamers using the microtiter plate based modified SELEX method against explosive trinitrotoluene are reported. Efficient partitioning of dsDNA was carried out using streptavidin labeled gold nanoprobes for the selection of specific aptamers. The selected binders having an affinity of ~10(-7) M were used in the newly developed electrochemical aptasensor, exhibiting a detection limit of around 1 ppb for trinitrotoluene.

A portable synthesis of water-soluble carbon dots for highly sensitive and selective detection of chlorogenic acid based on inner filter effect

NASA Astrophysics Data System (ADS)

Yang, Huan; Yang, Liu; Yuan, Yusheng; Pan, Shuang; Yang, Jidong; Yan, Jingjing; Zhang, Hui; Sun, Qianqian; Hu, Xiaoli

2018-01-01

In this work, a simple and facile hydrothermal method for synthesis of water-soluble carbon dots (CDs) with malic acid and urea, and were then employed as a high-performance fluorescent probe for selective and sensitive determination of chlorogenic acid (CGA) based on inner filter effect. The as-synthesized CDs was systematically characterized by Transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), Energy disperse spectroscopy (EDS), UV-vis absorption spectroscopy, spectrofluorophotometry, and the results indicated that the sizes of CDs were mainly distributed in the range of 1.0 nm-3.0 nm with an average diameter of 2.1 nm. More significantly, the as-prepared CDs possessed remarkable selectivity and sensitivity towards CGA with the linear range of 0.15 μmol L- 1-60 μmol L- 1 and the detection limit for CGA was 45 nmol L- 1 (3σ/k). The practical applications of CDs for detection of CGA have already been successfully demonstrated in Honeysuckle. This sensitive, selective method has a great application prospect in the pharmaceutical and biological analysis field owing to its simplicity and rapidity for the detection of CGA.

System and method for detecting cells or components thereof

DOEpatents

Porter, Marc D [Ames, IA; Lipert, Robert J [Ames, IA; Doyle, Robert T [Ames, IA; Grubisha, Desiree S [Corona, CA; Rahman, Salma [Ames, IA

2009-01-06

A system and method for detecting a detectably labeled cell or component thereof in a sample comprising one or more cells or components thereof, at least one cell or component thereof of which is detectably labeled with at least two detectable labels. In one embodiment, the method comprises: (i) introducing the sample into one or more flow cells of a flow cytometer, (ii) irradiating the sample with one or more light sources that are absorbed by the at least two detectable labels, the absorption of which is to be detected, and (iii) detecting simultaneously the absorption of light by the at least two detectable labels on the detectably labeled cell or component thereof with an array of photomultiplier tubes, which are operably linked to two or more filters that selectively transmit detectable emissions from the at least two detectable labels.

Evaluation of methods for detection of fluorescence labeled subcellular objects in microscope images.

PubMed

Ruusuvuori, Pekka; Aijö, Tarmo; Chowdhury, Sharif; Garmendia-Torres, Cecilia; Selinummi, Jyrki; Birbaumer, Mirko; Dudley, Aimée M; Pelkmans, Lucas; Yli-Harja, Olli

2010-05-13

Several algorithms have been proposed for detecting fluorescently labeled subcellular objects in microscope images. Many of these algorithms have been designed for specific tasks and validated with limited image data. But despite the potential of using extensive comparisons between algorithms to provide useful information to guide method selection and thus more accurate results, relatively few studies have been performed. To better understand algorithm performance under different conditions, we have carried out a comparative study including eleven spot detection or segmentation algorithms from various application fields. We used microscope images from well plate experiments with a human osteosarcoma cell line and frames from image stacks of yeast cells in different focal planes. These experimentally derived images permit a comparison of method performance in realistic situations where the number of objects varies within image set. We also used simulated microscope images in order to compare the methods and validate them against a ground truth reference result. Our study finds major differences in the performance of different algorithms, in terms of both object counts and segmentation accuracies. These results suggest that the selection of detection algorithms for image based screens should be done carefully and take into account different conditions, such as the possibility of acquiring empty images or images with very few spots. Our inclusion of methods that have not been used before in this context broadens the set of available detection methods and compares them against the current state-of-the-art methods for subcellular particle detection.

a Single-Exposure Dual-Energy Computed Radiography Technique for Improved Nodule Detection and Classification in Chest Imaging

NASA Astrophysics Data System (ADS)

Zink, Frank Edward

The detection and classification of pulmonary nodules is of great interest in chest radiography. Nodules are often indicative of primary cancer, and their detection is particularly important in asymptomatic patients. The ability to classify nodules as calcified or non-calcified is important because calcification is a positive indicator that the nodule is benign. Dual-energy methods offer the potential to improve both the detection and classification of nodules by allowing the formation of material-selective images. Tissue-selective images can improve detection by virtue of the elimination of obscuring rib structure. Bone -selective images are essentially calcium images, allowing classification of the nodule. A dual-energy technique is introduced which uses a computed radiography system to acquire dual-energy chest radiographs in a single-exposure. All aspects of the dual-energy technique are described, with particular emphasis on scatter-correction, beam-hardening correction, and noise-reduction algorithms. The adaptive noise-reduction algorithm employed improves material-selective signal-to-noise ratio by up to a factor of seven with minimal sacrifice in selectivity. A clinical comparison study is described, undertaken to compare the dual-energy technique to conventional chest radiography for the tasks of nodule detection and classification. Observer performance data were collected using the Free Response Observer Characteristic (FROC) method and the bi-normal Alternative FROC (AFROC) performance model. Results of the comparison study, analyzed using two common multiple observer statistical models, showed that the dual-energy technique was superior to conventional chest radiography for detection of nodules at a statistically significant level (p < .05). Discussion of the comparison study emphasizes the unique combination of data collection and analysis techniques employed, as well as the limitations of comparison techniques in the larger context of technology assessment.

A novel fluorescent aptasensor for the highly sensitive and selective detection of cardiac troponin I based on a graphene oxide platform.

PubMed

Liu, Dongkui; Lu, Xing; Yang, Yiwen; Zhai, Yunyun; Zhang, Jian; Li, Lei

2018-05-04

Acute myocardial infarction (AMI) is one of the leading risks to global health. Thus, the rapid, accurate early diagnosis of AMI is highly critical. Human cardiac troponin I (cTnI) has been regarded as a golden biomarker for AMI due to its excellent selectivity. In this work, a novel fluorescent aptasensor based on a graphene oxide (GO) platform was developed for the highly sensitive and selective detection of cTnI. GO binds to the fluorescent anti-cTnI aptamer and quenches its fluorescence. In the presence of cTnI, the fluorescent anti-cTnI aptamer leaves the surface of GO, combines with cTnI because of the powerful affinity of the fluorescent anti-cTnI aptamer and cTnI, and then restores the fluorescence of the fluorescent anti-cTnI aptamer. Fluorescence-enhanced detection is highly sensitive and selective to cTnI. The method exhibited good analytical performance with a reasonable dynamic linearity at the concentration range of 0.10-6.0 ng/mL and a low detection limit of 0.07 ng/mL (S/N = 3). The fluorescent aptasensor also exhibited high selectivity toward cTnI compared with other interference proteins. The proposed method may be a potentially useful tool for cTnI determination in human serum. Graphical abstract A novel fluorescent aptasensor for the highly sensitive and selective detection of cardiac troponin I based on a graphene oxide platform.

Analysis of Urinary Metabolites of Nerve and Blister Chemical Warfare Agents

DTIC Science & Technology

2014-08-01

of CWAs. The analysis methods use UHPLC-MS/MS in Multiple Reaction Monitoring ( MRM ) mode to enhance the selectivity and sensitivity of the method...Chromatography Mass Spectrometry LOD Limit Of Detection LOQ Limit of Quantitation MRM Multiple Reaction Monitoring MSMS Tandem mass...urine [1]. Those analysis methods use UHPLC- MS/MS in Multiple Reaction Monitoring ( MRM ) mode to enhance the selectivity and sensitivity of the method

Sensitive, Selective Test For Hydrazines

NASA Technical Reports Server (NTRS)

Roundbehler, David; Macdonald, Stephen

1993-01-01

Derivatives of hydrazines formed, then subjected to gas chromatography and detected via chemiluminescence. In method of detecting and quantifying hydrazine vapors, vapors reacted with dinitro compound to enhance sensitivity and selectivity. Hydrazine (HZ), monomethyl hydrazine, (MMH), and unsymmetrical dimethylhydrazine (UDMH) analyzed quantitatively and qualitatively, either alone or in mixtures. Vapors collected and reacted with 2,4-dinitrobenzaldehyde, (DNB), making it possible to concentrate hydrazine in derivative form, thereby increasing sensitivity to low initial concentrations. Increases selectivity because only those constituents of sample reacting with DNB concentrated for analysis.

Applying spatial analysis tools in public health: an example using SaTScan to detect geographic targets for colorectal cancer screening interventions.

PubMed

Sherman, Recinda L; Henry, Kevin A; Tannenbaum, Stacey L; Feaster, Daniel J; Kobetz, Erin; Lee, David J

2014-03-20

Epidemiologists are gradually incorporating spatial analysis into health-related research as geocoded cases of disease become widely available and health-focused geospatial computer applications are developed. One health-focused application of spatial analysis is cluster detection. Using cluster detection to identify geographic areas with high-risk populations and then screening those populations for disease can improve cancer control. SaTScan is a free cluster-detection software application used by epidemiologists around the world to describe spatial clusters of infectious and chronic disease, as well as disease vectors and risk factors. The objectives of this article are to describe how spatial analysis can be used in cancer control to detect geographic areas in need of colorectal cancer screening intervention, identify issues commonly encountered by SaTScan users, detail how to select the appropriate methods for using SaTScan, and explain how method selection can affect results. As an example, we used various methods to detect areas in Florida where the population is at high risk for late-stage diagnosis of colorectal cancer. We found that much of our analysis was underpowered and that no single method detected all clusters of statistical or public health significance. However, all methods detected 1 area as high risk; this area is potentially a priority area for a screening intervention. Cluster detection can be incorporated into routine public health operations, but the challenge is to identify areas in which the burden of disease can be alleviated through public health intervention. Reliance on SaTScan's default settings does not always produce pertinent results.

Optical and Electrochemical Aptasensors for Sensitive Detection of Streptomycin in Blood Serum and Milk.

PubMed

Ramezani, Mohammad; Abnous, Khalil; Taghdisi, Seyed Mohammad

2017-01-01

Detection and quantitation of antibiotic residues in blood serum and foodstuffs are in great demand. We have developed aptasensors for detection of streptomycin using electrochemical and optical methods. In the first method, an electrochemical aptasensor was developed for sensitive and selective detection of streptomycin, based on combination of exonuclease I (Exo I), complementary strand of aptamer (CS), arch shaped structure of aptamer (Apt)-CS conjugate, and gold electrode. The designed electrochemical aptasensor exhibited high selectivity toward streptomycin with a limit of detection (LOD) as low as 11.4 nM. Moreover, the developed electrochemical aptasensor was successfully used to detect streptomycin in milk and serum with LODs of 14.1 and 15.3 nM, respectively. In the second method, fluorescence quenching and colorimetric aptasensors were designed for detection of streptomycin based on aqueous gold nanoparticles (AuNPs) and double-stranded DNA (dsDNA). In the absence of streptomycin, aptamer/FAM-labeled complementary strand dsDNA is stable, resulting in the aggregation of AuNPs by salt bridge and an obvious color change from red to blue and strong emission of fluorescence. The colorimetric and fluorescence quenching aptasensors showed excellent selectivity toward streptomycin with limit of detections as low as 73.1 and 47.6 nM, respectively. The presented aptasensors were successfully used to detect streptomycin in milk and serum. For serum, LODs were determined to be 58.2 and 102.4 nM for fluorescence quenching and colorimetric aptasensors, respectively. For milk, LODs were calculated to be 56.2 and 108.7 nM for fluorescence quenching and colorimetric aptasensors, respectively.

Sequential projection pursuit for optimised vibration-based damage detection in an experimental wind turbine blade

NASA Astrophysics Data System (ADS)

Hoell, Simon; Omenzetter, Piotr

2018-02-01

To advance the concept of smart structures in large systems, such as wind turbines (WTs), it is desirable to be able to detect structural damage early while using minimal instrumentation. Data-driven vibration-based damage detection methods can be competitive in that respect because global vibrational responses encompass the entire structure. Multivariate damage sensitive features (DSFs) extracted from acceleration responses enable to detect changes in a structure via statistical methods. However, even though such DSFs contain information about the structural state, they may not be optimised for the damage detection task. This paper addresses the shortcoming by exploring a DSF projection technique specialised for statistical structural damage detection. High dimensional initial DSFs are projected onto a low-dimensional space for improved damage detection performance and simultaneous computational burden reduction. The technique is based on sequential projection pursuit where the projection vectors are optimised one by one using an advanced evolutionary strategy. The approach is applied to laboratory experiments with a small-scale WT blade under wind-like excitations. Autocorrelation function coefficients calculated from acceleration signals are employed as DSFs. The optimal numbers of projection vectors are identified with the help of a fast forward selection procedure. To benchmark the proposed method, selections of original DSFs as well as principal component analysis scores from these features are additionally investigated. The optimised DSFs are tested for damage detection on previously unseen data from the healthy state and a wide range of damage scenarios. It is demonstrated that using selected subsets of the initial and transformed DSFs improves damage detectability compared to the full set of features. Furthermore, superior results can be achieved by projecting autocorrelation coefficients onto just a single optimised projection vector.

Developing a new case based computer-aided detection scheme and an adaptive cueing method to improve performance in detecting mammographic lesions

PubMed Central

Tan, Maxine; Aghaei, Faranak; Wang, Yunzhi; Zheng, Bin

2017-01-01

The purpose of this study is to evaluate a new method to improve performance of computer-aided detection (CAD) schemes of screening mammograms with two approaches. In the first approach, we developed a new case based CAD scheme using a set of optimally selected global mammographic density, texture, spiculation, and structural similarity features computed from all four full-field digital mammography (FFDM) images of the craniocaudal (CC) and mediolateral oblique (MLO) views by using a modified fast and accurate sequential floating forward selection feature selection algorithm. Selected features were then applied to a “scoring fusion” artificial neural network (ANN) classification scheme to produce a final case based risk score. In the second approach, we combined the case based risk score with the conventional lesion based scores of a conventional lesion based CAD scheme using a new adaptive cueing method that is integrated with the case based risk scores. We evaluated our methods using a ten-fold cross-validation scheme on 924 cases (476 cancer and 448 recalled or negative), whereby each case had all four images from the CC and MLO views. The area under the receiver operating characteristic curve was AUC = 0.793±0.015 and the odds ratio monotonically increased from 1 to 37.21 as CAD-generated case based detection scores increased. Using the new adaptive cueing method, the region based and case based sensitivities of the conventional CAD scheme at a false positive rate of 0.71 per image increased by 2.4% and 0.8%, respectively. The study demonstrated that supplementary information can be derived by computing global mammographic density image features to improve CAD-cueing performance on the suspicious mammographic lesions. PMID:27997380

Radionuclide detection devices and associated methods

DOEpatents

Mann, Nicholas R [Rigby, ID; Lister, Tedd E [Idaho Falls, ID; Tranter, Troy J [Idaho Falls, ID

2011-03-08

Radionuclide detection devices comprise a fluid cell comprising a flow channel for a fluid stream. A radionuclide collector is positioned within the flow channel and configured to concentrate one or more radionuclides from the fluid stream onto at least a portion of the radionuclide collector. A scintillator for generating scintillation pulses responsive to an occurrence of a decay event is positioned proximate at least a portion of the radionuclide collector and adjacent to a detection system for detecting the scintillation pulses. Methods of selectively detecting a radionuclide are also provided.

Biochemical Sensors Using Carbon Nanotube Arrays

NASA Technical Reports Server (NTRS)

Meyyappan, Meyya (Inventor); Cassell, Alan M. (Inventor); Li, Jun (Inventor)

2011-01-01

Method and system for detecting presence of biomolecules in a selected subset, or in each of several selected subsets, in a fluid. Each of an array of two or more carbon nanotubes ("CNTs") is connected at a first CNT end to one or more electronics devices, each of which senses a selected electrochemical signal that is generated when a target biomolecule in the selected subset becomes attached to a functionalized second end of the CNT, which is covalently bonded with a probe molecule. This approach indicates when target biomolecules in the selected subset are present and indicates presence or absence of target biomolecules in two or more selected subsets. Alternatively, presence of absence of an analyte can be detected.

Comparison of statistical methods for detection of serum lipid biomarkers for mesothelioma and asbestos exposure.

PubMed

Xu, Rengyi; Mesaros, Clementina; Weng, Liwei; Snyder, Nathaniel W; Vachani, Anil; Blair, Ian A; Hwang, Wei-Ting

2017-07-01

We compared three statistical methods in selecting a panel of serum lipid biomarkers for mesothelioma and asbestos exposure. Serum samples from mesothelioma, asbestos-exposed subjects and controls (40 per group) were analyzed. Three variable selection methods were considered: top-ranked predictors from univariate model, stepwise and least absolute shrinkage and selection operator. Crossed-validated area under the receiver operating characteristic curve was used to compare the prediction performance. Lipids with high crossed-validated area under the curve were identified. Lipid with mass-to-charge ratio of 372.31 was selected by all three methods comparing mesothelioma versus control. Lipids with mass-to-charge ratio of 1464.80 and 329.21 were selected by two models for asbestos exposure versus control. Different methods selected a similar set of serum lipids. Combining candidate biomarkers can improve prediction.

A simple and rapid creatinine sensing via DLS selectivity, using calix[4]arene thiol functionalized gold nanoparticles.

PubMed

Sutariya, Pinkesh G; Pandya, Alok; Lodha, Anand; Menon, Shobhana K

2016-01-15

A new, simple, ultra-sensitive and selective approach has been reported for the "on spot" colorimetric detection of creatinine based on calix[4]arene functionalized gold nanoparticles (AuNPs) with excellent discrimination in the presence of other biomolecules. The lower detection limit of the method is 2.16nM. The gold nanoparticles and p-tert-butylcalix[4]arene were synthesized by microwave assisted method. Specifically, in our study, we used dynamic light scattering (DLS) which is a powerful method for the determination of small changes in particle size, improved selectivity and sensitivity of the creatinine detection system over colorimetric method. The nanoassembly is characterized by Transmission electron microscopy (TEM), DLS, UV-vis and ESI-MS spectroscopy, which demonstrates the binding affinity due its ability of hydrogen bonding and electrostatic interaction between -NH group of creatinine and pSDSC4. It exhibits fast response time (<60s) to creatinine and has long shelf-life (>5 weeks). The developed pSDSC4-AuNPs based creatinine biosensor will be established as simple, reliable and accurate tool for the determination of creatinine in human urine samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Reduction in training time of a deep learning model in detection of lesions in CT

NASA Astrophysics Data System (ADS)

Makkinejad, Nazanin; Tajbakhsh, Nima; Zarshenas, Amin; Khokhar, Ashfaq; Suzuki, Kenji

2018-02-01

Deep learning (DL) emerged as a powerful tool for object detection and classification in medical images. Building a well-performing DL model, however, requires a huge number of images for training, and it takes days to train a DL model even on a cutting edge high-performance computing platform. This study is aimed at developing a method for selecting a "small" number of representative samples from a large collection of training samples to train a DL model for the could be used to detect polyps in CT colonography (CTC), without compromising the classification performance. Our proposed method for representative sample selection (RSS) consists of a K-means clustering algorithm. For the performance evaluation, we applied the proposed method to select samples for the training of a massive training artificial neural network based DL model, to be used for the classification of polyps and non-polyps in CTC. Our results show that the proposed method reduce the training time by a factor of 15, while maintaining the classification performance equivalent to the model trained using the full training set. We compare the performance using area under the receiveroperating- characteristic curve (AUC).

Human papillomavirus detection and typing using a nested-PCR-RFLP assay.

PubMed

Coser, Janaina; Boeira, Thaís da Rocha; Fonseca, André Salvador Kazantzi; Ikuta, Nilo; Lunge, Vagner Ricardo

2011-01-01

It is clinically important to detect and type human papillomavirus (HPV) in a sensitive and specific manner. Development of a nested-polymerase chain reaction-restriction fragment length polymorphism (nested-PCR-RFLP) assay to detect and type HPV based on the analysis of L1 gene. Analysis of published DNA sequence of mucosal HPV types to select sequences of new primers. Design of an original nested-PCR assay using the new primers pair selected and classical MY09/11 primers. HPV detection and typing in cervical samples using the nested-PCR-RFLP assay. The nested-PCR-RFLP assay detected and typed HPV in cervical samples. Of the total of 128 clinical samples submitted to simple PCR and nested-PCR for detection of HPV, 37 (28.9%) were positive for the virus by both methods and 25 samples were positive only by nested-PCR (67.5% increase in detection rate compared with single PCR). All HPV positive samples were effectively typed by RFLP assay. The method of nested-PCR proved to be an effective diagnostic tool for HPV detection and typing.

Visual and light scattering spectrometric method for the detection of melamine using uracil 5‧-triphosphate sodium modified gold nanoparticles

NASA Astrophysics Data System (ADS)

Liang, Lijiao; Zhen, Shujun; Huang, Chengzhi

2017-02-01

A highly selective method was presented for colorimetric determination of melamine using uracil 5‧-triphosphate sodium modified gold nanoparticles (UTP-Au NPs) in this paper. Specific hydrogen-bonding interaction between uracil base (U) and melamine resulted in the aggregation of AuNPs, displaying variations of localized surface plasmon resonance (LSPR) features such as color change from red to blue and enhanced localized surface plasmon resonance light scattering (LSPR-LS) signals. Accordingly, the concentration of melamine could be quantified based on naked eye or a spectrometric method. This method was simple, inexpensive, environmental friendly and highly selective, which has been successfully used for the detection of melamine in pretreated liquid milk products with high recoveries.

Current methods for detecting the presence of botulinum neurotoxins in food and other biological samples

USDA-ARS?s Scientific Manuscript database

Current methods for detecting the presence of botulinum neurotoxins in food and other biological samples Botulinum neurotoxins (BoNTs), the causative agents of botulism, are among the most lethal human bacterial toxins and the causative agent of botulism. BoNTs are also classified as Select Agents ...

Detection of the nipple in automated 3D breast ultrasound using coronal slab-average-projection and cumulative probability map

NASA Astrophysics Data System (ADS)

Kim, Hannah; Hong, Helen

2014-03-01

We propose an automatic method for nipple detection on 3D automated breast ultrasound (3D ABUS) images using coronal slab-average-projection and cumulative probability map. First, to identify coronal images that appeared remarkable distinction between nipple-areola region and skin, skewness of each coronal image is measured and the negatively skewed images are selected. Then, coronal slab-average-projection image is reformatted from selected images. Second, to localize nipple-areola region, elliptical ROI covering nipple-areola region is detected using Hough ellipse transform in coronal slab-average-projection image. Finally, to separate the nipple from areola region, 3D Otsu's thresholding is applied to the elliptical ROI and cumulative probability map in the elliptical ROI is generated by assigning high probability to low intensity region. False detected small components are eliminated using morphological opening and the center point of detected nipple region is calculated. Experimental results show that our method provides 94.4% nipple detection rate.

Post-capillary reaction detection in capillary electrophoresis based on the streptavidin-biotin interaction. Optimization and application to single cell analysis.

PubMed

Feltus, A; Hentz, N G; Daunert, S

2001-05-25

A class-selective post-capillary reaction detection method for capillary electrophoresis is described in which a streptavidin-fluorescein isothiocyanate (streptavidin-FITC) conjugate is used to detect biotin moieties. The selective binding of biotin moieties to the streptavidin-FITC conjugate causes an enhancement of fluorescence proportional to the concentration of biotin present. After capillary electrophoresis the separated analytes react with streptavidin-FITC in a coaxial reactor and are then detected either by a benchtop spectrofluorometer (2.5 microM detection limit) or by an epi-fluorescence microscope (1 x 10(-7) M detection limit). The method is used to examine biotinylated species in a crude mammalian cell lysate which was found to contain 83+/-3 fmol in 3600 cell volumes. In addition, it is used to examine the uptake of biotin by individual sea urchin oocytes. The results indicate that, in the oocytes, biocytin is the prevalent form of biotin and its concentration varies widely between cells (mean=2+/-2 microM).

Rapid and selective detection of E. coli O157:H7 combining phagomagnetic separation with enzymatic colorimetry.

PubMed

Zhang, Yun; Yan, Chenghui; Yang, Hang; Yu, Junping; Wei, Hongping

2017-11-01

Mammal IgG antibodies are normally used in conventional immunoassays for E. coli O157:H7, which could lead to false positive results from the presence of protein A producing S. aureus. In this study, a natural specific bacteriophage was isolated and then conjugated with magnetic beads as a capture element in a sandwich format for the rapid and selective detection of E. coli O157:H7. To the best of our knowledge, it was the first time to utilize a natural bacteriophage to develop a phagomagnetic separation combined with colorimetric assay for E. coli O157:H7. The method has an overall time less than 2h with a detection limit of 4.9×10 4 CFU/mL. No interference from S. aureus was observed. Furthermore, the proposed method was successfully applied to detect E. coli O157:H7 in spiked skim milk. The proposed detection system provided a potential method for E. coli O157:H7 and other pathogenic bacteria in food samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2015-01-01

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

Detection of lead(II) ions with a DNAzyme and isothermal strand displacement signal amplification.

PubMed

Li, Wenying; Yang, Yue; Chen, Jian; Zhang, Qingfeng; Wang, Yan; Wang, Fangyuan; Yu, Cong

2014-03-15

A DNAzyme based method for the sensitive and selective quantification of lead(II) ions has been developed. A DNAzyme that requires Pb(2+) for activation was selected. An RNA containing DNA substrate was cleaved by the DNAzyme in the presence of Pb(2+). The 2',3'-cyclic phosphate of the cleaved 5'-part of the substrate was efficiently removed by Exonuclease III. The remaining part of the single stranded DNA (9 or 13 base long) was subsequently used as the primer for the strand displacement amplification reaction (SDAR). The method is highly sensitive, 200 pM lead(II) could be easily detected. A number of interference ions were tested, and the sensor showed good selectivity. Underground water samples were also tested, which demonstrated the feasibility of the current approach for real sample applications. It is feasible that our method could be used for DNAzyme or aptazyme based new sensing method developments for the quantification of other target analytes with high sensitivity and selectivity. © 2013 Elsevier B.V. All rights reserved.

Selective detection of dopamine in the presence of ascorbic acid via fluorescence quenching of InP/ZnS quantum dots.

PubMed

Ankireddy, Seshadri Reddy; Kim, Jongsung

2015-01-01

Dopamine is a neurotransmitter of the catecholamine family and has many important roles, especially in human brain. Several diseases of the nervous system, such as Parkinson's disease, attention deficit hyperactivity disorder, restless legs syndrome, are believed to be related to deficiency of dopamine. Several studies have been performed to detect dopamine by using electrochemical analysis. In this study, quantum dots (QDs) were used as sensing media for the detection of dopamine. The surface of the QDs was modified with l-cysteine by coupling reaction to increase the selectivity of dopamine. The fluorescence of cysteine-capped indium phosphide/zinc sulfide QDs was quenched by dopamine with various concentrations in the presence of ascorbic acid. This method shows good selectivity for dopamine detection, and the detection limit was 5 nM.

The effect of feature selection methods on computer-aided detection of masses in mammograms

NASA Astrophysics Data System (ADS)

Hupse, Rianne; Karssemeijer, Nico

2010-05-01

In computer-aided diagnosis (CAD) research, feature selection methods are often used to improve generalization performance of classifiers and shorten computation times. In an application that detects malignant masses in mammograms, we investigated the effect of using a selection criterion that is similar to the final performance measure we are optimizing, namely the mean sensitivity of the system in a predefined range of the free-response receiver operating characteristics (FROC). To obtain the generalization performance of the selected feature subsets, a cross validation procedure was performed on a dataset containing 351 abnormal and 7879 normal regions, each region providing a set of 71 mass features. The same number of noise features, not containing any information, were added to investigate the ability of the feature selection algorithms to distinguish between useful and non-useful features. It was found that significantly higher performances were obtained using feature sets selected by the general test statistic Wilks' lambda than using feature sets selected by the more specific FROC measure. Feature selection leads to better performance when compared to a system in which all features were used.

Label-free and pH-sensitive colorimetric materials for the sensing of urea

NASA Astrophysics Data System (ADS)

Li, Lu; Long, Yue; Gao, Jin-Ming; Song, Kai; Yang, Guoqiang

2016-02-01

This communication demonstrates a facile method for naked-eye detection of urea based on the structure color change of pH-sensitive photonic crystals. The insertion of urease provides excellent selectivity over other molecules. The detection of urea in different concentration ranges could be realized by changing the molar ratio between the functional monomer and cross-linker.This communication demonstrates a facile method for naked-eye detection of urea based on the structure color change of pH-sensitive photonic crystals. The insertion of urease provides excellent selectivity over other molecules. The detection of urea in different concentration ranges could be realized by changing the molar ratio between the functional monomer and cross-linker. Electronic supplementary information (ESI) available: Materials and chemicals, characterization, experimental details, and SEM images. See DOI: 10.1039/c5nr07690k

Sample Selection for Training Cascade Detectors.

PubMed

Vállez, Noelia; Deniz, Oscar; Bueno, Gloria

2015-01-01

Automatic detection systems usually require large and representative training datasets in order to obtain good detection and false positive rates. Training datasets are such that the positive set has few samples and/or the negative set should represent anything except the object of interest. In this respect, the negative set typically contains orders of magnitude more images than the positive set. However, imbalanced training databases lead to biased classifiers. In this paper, we focus our attention on a negative sample selection method to properly balance the training data for cascade detectors. The method is based on the selection of the most informative false positive samples generated in one stage to feed the next stage. The results show that the proposed cascade detector with sample selection obtains on average better partial AUC and smaller standard deviation than the other compared cascade detectors.

A Label-Free Aptasensor for Ochratoxin a Detection Based on the Structure Switch of Aptamer.

PubMed

Liu, Feng; Ding, Ailing; Zheng, Jiushang; Chen, Jiucun; Wang, Bin

2018-06-01

A label-free sensing platform is developed based on switching the structure of aptamer for highly sensitive and selective fluorescence detection of ochratoxin A (OTA). OTA induces the structure of aptamer, transforms into G-quadruplex and produces strong fluorescence in the presence of zinc(II)-protoporphyrin IX probe due to the specific bind to G-quadruplex. The simple method exhibits high sensitivity towards OTA with a detection limit of 0.03 nM and excellent selectivity over other mycotoxins. In addition, the successful detection of OTA in real samples represents a promising application in food safety.

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Detection of Salmonella spp. in veterinary samples by combining selective enrichment and real-time PCR.

PubMed

Goodman, Laura B; McDonough, Patrick L; Anderson, Renee R; Franklin-Guild, Rebecca J; Ryan, James R; Perkins, Gillian A; Thachil, Anil J; Glaser, Amy L; Thompson, Belinda S

2017-11-01

Rapid screening for enteric bacterial pathogens in clinical environments is essential for biosecurity. Salmonella found in veterinary hospitals, particularly Salmonella enterica serovar Dublin, can pose unique challenges for culture and testing because of its poor growth. Multiple Salmonella serovars including Dublin are emerging threats to public health given increasing prevalence and antimicrobial resistance. We adapted an automated food testing method to veterinary samples and evaluated the performance of the method in a variety of matrices including environmental samples ( n = 81), tissues ( n = 52), feces ( n = 148), and feed ( n = 29). A commercial kit was chosen as the basis for this approach in view of extensive performance characterizations published by multiple independent organizations. A workflow was established for efficiently and accurately testing veterinary matrices and environmental samples by use of real-time PCR after selective enrichment in Rappaport-Vassiliadis soya (RVS) medium. Using this method, the detection limit for S. Dublin improved by 100-fold over subculture on selective agars (eosin-methylene blue, brilliant green, and xylose-lysine-deoxycholate). Overall, the procedure was effective in detecting Salmonella spp. and provided next-day results.

On-line solid-phase microextraction of triclosan, bisphenol A, chlorophenols, and selected pharmaceuticals in environmental water samples by high-performance liquid chromatography-ultraviolet detection.

PubMed

Kim, Dalho; Han, Jungho; Choi, Yongwook

2013-01-01

A method using on-line solid-phase microextraction (SPME) on a carbowax-templated fiber followed by liquid chromatography (LC) with ultraviolet (UV) detection was developed for the determination of triclosan in environmental water samples. Along with triclosan, other selected phenolic compounds, bisphenol A, and acidic pharmaceuticals were studied. Previous SPME/LC or stir-bar sorptive extraction/LC-UV for polar analytes showed lack of sensitivity. In this study, the calculated octanol-water distribution coefficient (log D) values of the target analytes at different pH values were used to estimate polarity of the analytes. The lack of sensitivity observed in earlier studies is identified as a lack of desorption by strong polar-polar interactions between analyte and solid-phase. Calculated log D values were useful to understand or predict the interaction between analyte and solid phase. Under the optimized conditions, the method detection limit of selected analytes by using on-line SPME-LC-UV method ranged from 5 to 33 ng L(-1), except for very polar 3-chlorophenol and 2,4-dichlorophenol which was obscured in wastewater samples by an interfering substance. This level of detection represented a remarkable improvement over the conventional existing methods. The on-line SPME-LC-UV method, which did not require derivatization of analytes, was applied to the determination of TCS including phenolic compounds and acidic pharmaceuticals in tap water and river water and municipal wastewater samples.

Single-layer MnO2 nanosheets for sensitive and selective detection of glutathione by a colorimetric method

NASA Astrophysics Data System (ADS)

Di, Weihua; Zhang, Xiang; Qin, Weiping

2017-04-01

The rapid, sensitive and selective detection of glutathione (GSH) is of great importance in the biological systems. In this work, a template-free and one-step method was used to synthesize the single-layer MnO2 nanosheets via a redox reaction. The resulting product was characterized by XRD, TEM, FTIR, XPS and UV-vis absorption. The addition of GSH results in the change of solution color depth owing to the occurrence of a redox reaction between MnO2 and GSH, enabling colorimetric detection of GSH. At a pH of 3.6, the proposed sensor gives a linear calibration over a GSH concentration range of 10-100 μM, with a rapid response of less than 2 min and a low detection limit of 0.5 μM. The relative standard deviation for seven repeated determinations of GSH is lower than 5.6%. Furthermore, the chemical response of the synthesized MnO2 nanosheets toward GSH is selective. Owing to the advantages with good water solubility, rapid response, high sensitivity, good biocompatibility and operation simplicity, this two-dimensional MnO2-based sensing material might be potential for detecting GSH in biological applications.

Peptide-activated gold nanoparticles for selective visual sensing of virus

NASA Astrophysics Data System (ADS)

Sajjanar, Basavaraj; Kakodia, Bhuvna; Bisht, Deepika; Saxena, Shikha; Singh, Arvind Kumar; Joshi, Vinay; Tiwari, Ashok Kumar; Kumar, Satish

2015-05-01

In this study, we report peptide-gold nanoparticles (AuNP)-based visual sensor for viruses. Citrate-stabilized AuNP (20 ± 1.9 nm) were functionalized with strong sulfur-gold interface using cysteinylated virus-specific peptide. Peptide-Cys-AuNP formed complexes with the viruses which made them to aggregate. The aggregation can be observed with naked eye and also with UV-Vis spectrophotometer as a color change from bright red to purple. The test allows for fast and selective detection of specific viruses. Spectroscopic measurements showed high linear correlation ( R 2 = 0.995) between the changes in optical density ratio (OD610/OD520) with the different concentrations of virus. The new method was compared with the hemagglutinating (HA) test for Newcastle disease virus (NDV). The results indicated that peptide-Cys-AuNP was more sensitive and can visually detect minimum number of virus particles present in the biological samples. The limit of detection for the NDV was 0.125 HA units of the virus. The method allows for selective detection and quantification of the NDV, and requires no isolation of viral RNA and PCR experiments. This strategy may be utilized for detection of other important human and animal viral pathogens.

An interlaboratory study on efficient detection of Shiga toxin-producing Escherichia coli O26, O103, O111, O121, O145, and O157 in food using real-time PCR assay and chromogenic agar.

PubMed

Hara-Kudo, Yukiko; Konishi, Noriko; Ohtsuka, Kayoko; Iwabuchi, Kaori; Kikuchi, Rie; Isobe, Junko; Yamazaki, Takumiko; Suzuki, Fumie; Nagai, Yuhki; Yamada, Hiroko; Tanouchi, Atsuko; Mori, Tetsuya; Nakagawa, Hiroshi; Ueda, Yasufumi; Terajima, Jun

2016-08-02

To establish an efficient detection method for Shiga toxin (Stx)-producing Escherichia coli (STEC) O26, O103, O111, O121, O145, and O157 in food, an interlaboratory study using all the serogroups of detection targets was firstly conducted. We employed a series of tests including enrichment, real-time PCR assays, and concentration by immunomagnetic separation, followed by plating onto selective agar media (IMS-plating methods). This study was particularly focused on the efficiencies of real-time PCR assays in detecting stx and O-antigen genes of the six serogroups and of IMS-plating methods onto selective agar media including chromogenic agar. Ground beef and radish sprouts samples were inoculated with the six STEC serogroups either at 4-6CFU/25g (low levels) or at 22-29CFU/25g (high levels). The sensitivity of stx detection in ground beef at both levels of inoculation with all six STEC serogroups was 100%. The sensitivity of stx detection was also 100% in radish sprouts at high levels of inoculation with all six STEC serogroups, and 66.7%-91.7% at low levels of inoculation. The sensitivity of detection of O-antigen genes was 100% in both ground beef and radish sprouts at high inoculation levels, while at low inoculation levels, it was 95.8%-100% in ground beef and 66.7%-91.7% in radish sprouts. The sensitivity of detection with IMS-plating was either the same or lower than those of the real-time PCR assays targeting stx and O-antigen genes. The relationship between the results of IMS-plating methods and Ct values of real-time PCR assays were firstly analyzed in detail. Ct values in most samples that tested negative in the IMS-plating method were higher than the maximum Ct values in samples that tested positive in the IMS-plating method. This study indicates that all six STEC serogroups in food contaminated with more than 29CFU/25g were detected by real-time PCR assays targeting stx and O-antigen genes and IMS-plating onto selective agar media. Therefore, screening of stx and O-antigen genes followed by isolation of STECs by IMS-plating methods may be an efficient method to detect the six STEC serogroups. Copyright © 2016 Elsevier B.V. All rights reserved.

EEG-based mild depressive detection using feature selection methods and classifiers.

PubMed

Li, Xiaowei; Hu, Bin; Sun, Shuting; Cai, Hanshu

2016-11-01

Depression has become a major health burden worldwide, and effectively detection of such disorder is a great challenge which requires latest technological tool, such as Electroencephalography (EEG). This EEG-based research seeks to find prominent frequency band and brain regions that are most related to mild depression, as well as an optimal combination of classification algorithms and feature selection methods which can be used in future mild depression detection. An experiment based on facial expression viewing task (Emo_block and Neu_block) was conducted, and EEG data of 37 university students were collected using a 128 channel HydroCel Geodesic Sensor Net (HCGSN). For discriminating mild depressive patients and normal controls, BayesNet (BN), Support Vector Machine (SVM), Logistic Regression (LR), k-nearest neighbor (KNN) and RandomForest (RF) classifiers were used. And BestFirst (BF), GreedyStepwise (GSW), GeneticSearch (GS), LinearForwordSelection (LFS) and RankSearch (RS) based on Correlation Features Selection (CFS) were applied for linear and non-linear EEG features selection. Independent Samples T-test with Bonferroni correction was used to find the significantly discriminant electrodes and features. Data mining results indicate that optimal performance is achieved using a combination of feature selection method GSW based on CFS and classifier KNN for beta frequency band. Accuracies achieved 92.00% and 98.00%, and AUC achieved 0.957 and 0.997, for Emo_block and Neu_block beta band data respectively. T-test results validate the effectiveness of selected features by search method GSW. Simplified EEG system with only FP1, FP2, F3, O2, T3 electrodes was also explored with linear features, which yielded accuracies of 91.70% and 96.00%, AUC of 0.952 and 0.972, for Emo_block and Neu_block respectively. Classification results obtained by GSW + KNN are encouraging and better than previously published results. In the spatial distribution of features, we find that left parietotemporal lobe in beta EEG frequency band has greater effect on mild depression detection. And fewer EEG channels (FP1, FP2, F3, O2 and T3) combined with linear features may be good candidates for usage in portable systems for mild depression detection. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Assessment of NDE reliability data

NASA Technical Reports Server (NTRS)

Yee, B. G. W.; Couchman, J. C.; Chang, F. H.; Packman, D. F.

1975-01-01

Twenty sets of relevant nondestructive test (NDT) reliability data were identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations was formulated, and a model to grade the quality and validity of the data sets was developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, were formulated for each NDE method. A comprehensive computer program was written and debugged to calculate the probability of flaw detection at several confidence limits by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. An example of the calculated reliability of crack detection in bolt holes by an automatic eddy current method is presented.

Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

PubMed

Stephan, Wolfgang

2016-01-01

In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

Detection Progress of Selected Drugs in TLC

PubMed Central

Pyka, Alina

2014-01-01

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

[Application of characteristic NIR variables selection in portable detection of soluble solids content of apple by near infrared spectroscopy].

PubMed

Fan, Shu-Xiang; Huang, Wen-Qian; Li, Jiang-Bo; Guo, Zhi-Ming; Zhaq, Chun-Jiang

2014-10-01

In order to detect the soluble solids content(SSC)of apple conveniently and rapidly, a ring fiber probe and a portable spectrometer were applied to obtain the spectroscopy of apple. Different wavelength variable selection methods, including unin- formative variable elimination (UVE), competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA) were pro- posed to select effective wavelength variables of the NIR spectroscopy of the SSC in apple based on PLS. The back interval LS- SVM (BiLS-SVM) and GA were used to select effective wavelength variables based on LS-SVM. Selected wavelength variables and full wavelength range were set as input variables of PLS model and LS-SVM model, respectively. The results indicated that PLS model built using GA-CARS on 50 characteristic variables selected from full-spectrum which had 1512 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.962, 0.403°Brix respectively for SSC. The proposed method of GA-CARS could effectively simplify the portable detection model of SSC in apple based on near infrared spectroscopy and enhance the predictive precision. The study can provide a reference for the development of portable apple soluble solids content spectrometer.

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

A Bayesian method for detecting stellar flares

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

A liquid chromatography-mass spectrometric method for the determination of oak moss allergens atranol and chloroatranol in perfumes.

PubMed

Bossi, Rossana; Rastogi, Suresh C; Bernard, Guillaume; Gimenez-Arnau, Elena; Johansen, Jeanne D; Lepoittevin, Jean-Pierre; Menné, Torkil

2004-05-01

This paper describes a validated liquid chromatographic-tandem mass spectrometric method for quantitative analysis of the potential oak moss allergens atranol and chloroatranol in perfumes and similar products. The method employs LC-MS-MS with electrospray ionization (ESI) in negative mode. The compounds are analysed by selective reaction monitoring (SRM) of 2 or 3 ions for each compound in order to obtain high selectivity and sensitivity. The method has been validated for the following parameters: linearity; repeatability; recovery; limit of detection; and limit of quantification. The limits of detection, 5.0 ng/mL and 2.4 ng/mL, respectively, for atranol and chloroatranol, achieved by this method allowed identification of these compounds at concentrations below those causing allergic skin reactions in oak-moss-sensitive patients. The recovery of chloratranol from spiked perfumes was 96+/-4%. Low recoveries (49+/-5%) were observed for atranol in spiked perfumes, indicating ion suppression caused by matrix components. The method has been applied to the analysis of 10 randomly selected perfumes and similar products.

Romer Labs RapidChek®Listeria monocytogenes Test System for the Detection of L. monocytogenes on Selected Foods and Environmental Surfaces.

PubMed

Juck, Gregory; Gonzalez, Verapaz; Allen, Ann-Christine Olsson; Sutzko, Meredith; Seward, Kody; Muldoon, Mark T

2018-04-27

The Romer Labs RapidChek ® Listeria monocytogenes test system (Performance Tested Method ℠ 011805) was validated against the U.S. Department of Agriculture-Food Safety and Inspection Service Microbiology Laboratory Guidebook (USDA-FSIS/MLG), U.S. Food and Drug Association Bacteriological Analytical Manual (FDA/BAM), and AOAC Official Methods of Analysis ℠ (AOAC/OMA) cultural reference methods for the detection of L. monocytogenes on selected foods including hot dogs, frozen cooked breaded chicken, frozen cooked shrimp, cured ham, and ice cream, and environmental surfaces including stainless steel and plastic in an unpaired study design. The RapidChek method uses a proprietary enrichment media system, a 44-48 h enrichment at 30 ± 1°C, and detects L. monocytogenes on an immunochromatographic lateral flow device within 10 min. Different L. monocytogenes strains were used to spike each of the matrixes. Samples were confirmed based on the reference method confirmations and an alternate confirmation method. A total of 140 low-level spiked samples were tested by the RapidChek method after enrichment for 44-48 h in parallel with the cultural reference method. There were 88 RapidChek presumptive positives. One of the presumptive positives was not confirmed culturally. Additionally, one of the culturally confirmed samples did not exhibit a presumptive positive. No difference between the alternate confirmation method and reference confirmation method was observed. The respective cultural reference methods (USDA-FSIS/MLG, FDA/BAM, and AOAC/OMA) produced a total of 63 confirmed positive results. Nonspiked samples from all foods were reported as negative for L. monocytogenes by all methods. Probability of detection analysis demonstrated no significant differences in the number of positive samples detected by the RapidChek method and the respective cultural reference method.

Detection and quantification of the selective EP4 receptor antagonist CJ-023423 (grapiprant) in canine plasma by HPLC with spectrofluorimetric detection.

PubMed

Vito, Virgina De; Saba, Alessandro; Lee, Hong-Ki; Owen, Helen; Poapolathep, Amnart; Giorgi, Mario

2016-01-25

Grapiprant, a novel pharmacologically active ingredient, acts as a selective EP4 receptor antagonist whose physiological ligand is prostaglandin E2 (PGE2). It is currently under development for use in humans and dogs for the control of pain and inflammation associated with osteoarthritis. The aim of the present study was to develop an easy and sensitive method to quantify grapiprant in canine plasma and to apply the method in a canine patient. Several parameters, both in the extraction and detection method were evaluated. The final mobile phase consisted of ACN:AcONH4 (20 mM) solution, pH 4 (70:30, v/v) at a flow rate of 1 mL/min. The elution of grapiprant and IS (metoclopramide) was carried out in isocratic mode through a Synergi Polar-RP 80A analytical column (150 mm × 4.6 mm). The best excitation and emission wavelengths were 320 and 365 nm, respectively. Grapiprant was extracted from the plasma using CHCl3, which gave a recovery of 88.1 ± 10.22% and a lower limit of quantification (LLOQ) of 10 ng/mL. The method was validated in terms of linearity, limit of detection (LOD), LLOQ, selectivity, accuracy and precision, extraction recovery, stability, and inter-laboratory cross validation, according to international guidelines. The chromatographic runs were specific with no interfering peaks at the retention times of the analyte and IS, as confirmed by HPLC-MS experiments. In conclusion, this was a simple and effective method using HPLC-FL to detect grapiprant in plasma, which may be useful for future pharmacokinetic studies. Copyright © 2015 Elsevier B.V. All rights reserved.

Delamination Defect Detection Using Ultrasonic Guided Waves in Advanced Hybrid Structural Elements

NASA Astrophysics Data System (ADS)

Yan, Fei; Qi, Kevin ``Xue''; Rose, Joseph L.; Weiland, Hasso

2010-02-01

Nondestructive testing for multilayered structures is challenging because of increased numbers of layers and plate thicknesses. In this paper, ultrasonic guided waves are applied to detect delamination defects inside a 23-layer Alcoa Advanced Hybrid Structural plate. A semi-analytical finite element (SAFE) method generates dispersion curves and wave structures in order to select appropriate wave structures to detect certain defects. One guided wave mode and frequency is chosen to achieve large in-plane displacements at regions of interest. The interactions of the selected mode with defects are simulated using finite element models. Experiments are conducted and compared with bulk wave measurements. It is shown that guided waves can detect deeply embedded damages inside thick multilayer fiber-metal laminates with suitable mode and frequency selection.

Detection of Hydroxyapatite in Calcified Cardiovascular Tissues

PubMed Central

Lee, Jae Sam; Morrisett, Joel D.; Tung, Ching-Hsuan

2012-01-01

Objective The objective of this study is to develop a method for selective detection of the calcific (hydroxyapatite) component in human aortic smooth muscle cells in vitro and in calcified cardiovascular tissues ex vivo. This method uses a novel optical molecular imaging contrast dye, Cy-HABP-19, to target calcified cells and tissues. Methods A peptide that mimics the binding affinity of osteocalcin was used to label hydroxyapatite in vitro and ex vivo. Morphological changes in vascular smooth muscle cells were evaluated at an early stage of the mineralization process induced by extrinsic stimuli, osteogenic factors and a magnetic suspension cell culture. Hydroxyapatite components were detected in monolayers of these cells in the presence of osteogenic factors and a magnetic suspension environment. Results Atherosclerotic plaque contains multiple components including lipidic, fibrotic, thrombotic, and calcific materials. Using optical imaging and the Cy-HABP-19 molecular imaging probe, we demonstrated that hydroxyapatite components could be selectively distinguished from various calcium salts in human aortic smooth muscle cells in vitro and in calcified cardiovascular tissues, carotid endarterectomy samples and aortic valves, ex vivo. Conclusion Hydroxyapatite deposits in cardiovascular tissues were selectively detected in the early stage of the calcification process using our Cy-HABP-19 probe. This new probe makes it possible to study the earliest events associated with vascular hydroxyapatite deposition at the cellular and molecular levels. This target-selective molecular imaging probe approach holds high potential for revealing early pathophysiological changes, leading to progression, regression, or stabilization of cardiovascular diseases. PMID:22877867

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.

Automatic reference selection for quantitative EEG interpretation: identification of diffuse/localised activity and the active earlobe reference, iterative detection of the distribution of EEG rhythms.

PubMed

Wang, Bei; Wang, Xingyu; Ikeda, Akio; Nagamine, Takashi; Shibasaki, Hiroshi; Nakamura, Masatoshi

2014-01-01

EEG (Electroencephalograph) interpretation is important for the diagnosis of neurological disorders. The proper adjustment of the montage can highlight the EEG rhythm of interest and avoid false interpretation. The aim of this study was to develop an automatic reference selection method to identify a suitable reference. The results may contribute to the accurate inspection of the distribution of EEG rhythms for quantitative EEG interpretation. The method includes two pre-judgements and one iterative detection module. The diffuse case is initially identified by pre-judgement 1 when intermittent rhythmic waveforms occur over large areas along the scalp. The earlobe reference or averaged reference is adopted for the diffuse case due to the effect of the earlobe reference depending on pre-judgement 2. An iterative detection algorithm is developed for the localised case when the signal is distributed in a small area of the brain. The suitable averaged reference is finally determined based on the detected focal and distributed electrodes. The presented technique was applied to the pathological EEG recordings of nine patients. One example of the diffuse case is introduced by illustrating the results of the pre-judgements. The diffusely intermittent rhythmic slow wave is identified. The effect of active earlobe reference is analysed. Two examples of the localised case are presented, indicating the results of the iterative detection module. The focal and distributed electrodes are detected automatically during the repeating algorithm. The identification of diffuse and localised activity was satisfactory compared with the visual inspection. The EEG rhythm of interest can be highlighted using a suitable selected reference. The implementation of an automatic reference selection method is helpful to detect the distribution of an EEG rhythm, which can improve the accuracy of EEG interpretation during both visual inspection and automatic interpretation. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Systematic cloning of human minisatellites from ordered array charomid libraries.

PubMed

Armour, J A; Povey, S; Jeremiah, S; Jeffreys, A J

1990-11-01

We present a rapid and efficient method for the isolation of minisatellite loci from human DNA. The method combines cloning a size-selected fraction of human MboI DNA fragments in a charomid vector with hybridization screening of the library in ordered array. Size-selection of large MboI fragments enriches for the longer, more variable minisatellites and reduces the size of the library required. The library was screened with a series of multi-locus probes known to detect a large number of hypervariable loci in human DNA. The gridded library allowed both the rapid processing of positive clones and the comparative evaluation of the different multi-locus probes used, in terms of both the relative success in detecting hypervariable loci and the degree of overlap between the sets of loci detected. We report 23 new human minisatellite loci isolated by this method, which map to 14 autosomes and the sex chromosomes.

Selective identification and quantification of saccharin by liquid chromatography and fluorescence detection.

PubMed

Bruno, Sergio N F; Cardoso, Carlos R; Maciel, Márcia Mosca A; Vokac, Lidmila; da Silva Junior, Ademário I

2014-09-15

High-pressure liquid chromatography with ultra-violet detection (HPLC-UV) is one of the most commonly used methods to identify and quantify saccharin in non-alcoholic beverages. However, due to the wide variety of interfering UV spectra in saccharin-containing beverage matrices, the same method cannot be used to measure this analyte accurately. We have developed a new, highly effective method to identify and quantify saccharin using HPLC with fluorescence detection (HPLC-FLD). The excitation wavelength (250 nm) and emission wavelength (440 nm) chosen increased selectivity for all matrices and ensured few changes were required in the mobile phase or other parameters. The presence of saccharin in non-diet beverages - a fraud commonly used to replace more expensive sucrose - was confirmed by comparing coincident peaks as well as the emission spectra of standards and samples. Copyright © 2014 Elsevier Ltd. All rights reserved.

A review on creatinine measurement techniques.

PubMed

Mohabbati-Kalejahi, Elham; Azimirad, Vahid; Bahrami, Manouchehr; Ganbari, Ahmad

2012-08-15

This paper reviews the entire recent global tendency for creatinine measurement. Creatinine biosensors involve complex relationships between biology and micro-mechatronics to which the blood is subjected. Comparison between new and old methods shows that new techniques (e.g. Molecular Imprinted Polymers based algorithms) are better than old methods (e.g. Elisa) in terms of stability and linear range. All methods and their details for serum, plasma, urine and blood samples are surveyed. They are categorized into five main algorithms: optical, electrochemical, impedometrical, Ion Selective Field-Effect Transistor (ISFET) based technique and chromatography. Response time, detection limit, linear range and selectivity of reported sensors are discussed. Potentiometric measurement technique has the lowest response time of 4-10 s and the lowest detection limit of 0.28 nmol L(-1) belongs to chromatographic technique. Comparison between various techniques of measurements indicates that the best selectivity belongs to MIP based and chromatographic techniques. Copyright © 2012 Elsevier B.V. All rights reserved.

76 FR 61647 - Receipt of Several Pesticide Petitions Filed for Residues of Pesticide Chemicals in or on Various...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-05

... was required for gas chromatography with mass selective detection (GC/MSD) but not for liquid... detection (LOD = 0.01) and a gas liquid chromatography (GLC) method with a flame photometric detection (LOD... quantification by high performance liquid chromatography with tandem mass spectrometric detection (HPLC/MS/MS...

Enhancing the mathematical properties of new haplotype homozygosity statistics for the detection of selective sweeps.

PubMed

Garud, Nandita R; Rosenberg, Noah A

2015-06-01

Soft selective sweeps represent an important form of adaptation in which multiple haplotypes bearing adaptive alleles rise to high frequency. Most statistical methods for detecting selective sweeps from genetic polymorphism data, however, have focused on identifying hard selective sweeps in which a favored allele appears on a single haplotypic background; these methods might be underpowered to detect soft sweeps. Among exceptions is the set of haplotype homozygosity statistics introduced for the detection of soft sweeps by Garud et al. (2015). These statistics, examining frequencies of multiple haplotypes in relation to each other, include H12, a statistic designed to identify both hard and soft selective sweeps, and H2/H1, a statistic that conditional on high H12 values seeks to distinguish between hard and soft sweeps. A challenge in the use of H2/H1 is that its range depends on the associated value of H12, so that equal H2/H1 values might provide different levels of support for a soft sweep model at different values of H12. Here, we enhance the H12 and H2/H1 haplotype homozygosity statistics for selective sweep detection by deriving the upper bound on H2/H1 as a function of H12, thereby generating a statistic that normalizes H2/H1 to lie between 0 and 1. Through a reanalysis of resequencing data from inbred lines of Drosophila, we show that the enhanced statistic both strengthens interpretations obtained with the unnormalized statistic and leads to empirical insights that are less readily apparent without the normalization. Copyright © 2015 Elsevier Inc. All rights reserved.

Method for immunodiagnostic detection of dioxins at low concentrations

DOEpatents

Vanderlaan, Martin; Stanker, Larry H.; Watkins, Bruce E.; Petrovic, Peter; Gorbach, Siegbert

1995-01-01

A method is described for the use of monoclonal antibodies in a sensitive immunoassay for halogenated dioxins and dibenzofurans in industrial samples which contain impurities. Appropriate sample preparation and selective enzyme amplification of the immunoassay sensitivity permits detection of dioxin contaminants in industrial or environmental samples at concentrations in the range of a few parts per trillion.

[Methods of hygromycin B phosphotransferase activity assay in transgenic plant].

PubMed

Zhuo, Qin; Yang, Xiaoguang

2004-07-01

Hygromycin B phosphotransferase (HPT) is a widely used selectable marker protein of transgenic plant. Detection of its activity is critical to studies on the development of various transgenic plants, silence of inserted gene, marker-free system development and safety assessment of transgenic food. In this paper, several methods for detecting the activity of this enzyme were reviewed.

Developing operation algorithms for vision subsystems in autonomous mobile robots

NASA Astrophysics Data System (ADS)

Shikhman, M. V.; Shidlovskiy, S. V.

2018-05-01

The paper analyzes algorithms for selecting keypoints on the image for the subsequent automatic detection of people and obstacles. The algorithm is based on the histogram of oriented gradients and the support vector method. The combination of these methods allows successful selection of dynamic and static objects. The algorithm can be applied in various autonomous mobile robots.

WGA-based lectin affinity gel electrophoresis: A novel method for the detection of O-GlcNAc-modified proteins.

PubMed

Kubota, Yuji; Fujioka, Ko; Takekawa, Mutsuhiro

2017-01-01

Post-translational modification with O-linked β-N-acetylglucosamine (O-GlcNAc) occurs selectively on serine and/or threonine residues of cytoplasmic and nuclear proteins, and dynamically regulates their molecular functions. Since conventional strategies to evaluate the O-GlcNAcylation level of a specific protein require time-consuming steps, the development of a rapid and easy method for the detection and quantification of an O-GlcNAcylated protein has been a challenging issue. Here, we describe a novel method in which O-GlcNAcylated and non-O-GlcNAcylated forms of proteins are separated by lectin affinity gel electrophoresis using wheat germ agglutinin (WGA), which primarily binds to N-acetylglucosamine residues. Electrophoresis of cell lysates through a gel containing copolymerized WGA selectively induced retardation of the mobility of O-GlcNAcylated proteins, thereby allowing the simultaneous visualization of both the O-GlcNAcylated and the unmodified forms of proteins. This method is therefore useful for the quantitative detection of O-GlcNAcylated proteins.

Selective detection of cavitation bubbles by triplet pulse sequence in high-intensity focused ultrasound treatment

NASA Astrophysics Data System (ADS)

Iwasaki, Ryosuke; Nagaoka, Ryo; Yoshizawa, Shin; Umemura, Shin-ichiro

2018-07-01

Acoustic cavitation bubbles are known to enhance the heating effect in high-intensity focused ultrasound (HIFU) treatment. The detection of cavitation bubbles with high sensitivity and selectivity is required to predict the therapeutic and side effects of cavitation, and ensure the efficacy and safety of the treatment. A pulse inversion (PI) technique has been widely used for imaging microbubbles through enhancing the second-harmonic component of echo signals. However, it has difficulty in separating the nonlinear response of microbubbles from that due to nonlinear propagation. In this study, a triplet pulse (3P) method was investigated to specifically image cavitation bubbles by extracting the 1.5th fractional harmonic component. The proposed 3P method depicted cavitation bubbles with a contrast ratio significantly higher than those in conventional imaging methods with and without PI. The results suggest that the 3P method is effective for specifically detecting microbubbles in cavitation-enhanced HIFU treatment.

A Minimum Spanning Forest Based Method for Noninvasive Cancer Detection with Hyperspectral Imaging

PubMed Central

Pike, Robert; Lu, Guolan; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2016-01-01

Goal The purpose of this paper is to develop a classification method that combines both spectral and spatial information for distinguishing cancer from healthy tissue on hyperspectral images in an animal model. Methods An automated algorithm based on a minimum spanning forest (MSF) and optimal band selection has been proposed to classify healthy and cancerous tissue on hyperspectral images. A support vector machine (SVM) classifier is trained to create a pixel-wise classification probability map of cancerous and healthy tissue. This map is then used to identify markers that are used to compute mutual information for a range of bands in the hyperspectral image and thus select the optimal bands. An MSF is finally grown to segment the image using spatial and spectral information. Conclusion The MSF based method with automatically selected bands proved to be accurate in determining the tumor boundary on hyperspectral images. Significance Hyperspectral imaging combined with the proposed classification technique has the potential to provide a noninvasive tool for cancer detection. PMID:26285052

Curvature correction of retinal OCTs using graph-based geometry detection

NASA Astrophysics Data System (ADS)

Kafieh, Raheleh; Rabbani, Hossein; Abramoff, Michael D.; Sonka, Milan

2013-05-01

In this paper, we present a new algorithm as an enhancement and preprocessing step for acquired optical coherence tomography (OCT) images of the retina. The proposed method is composed of two steps, first of which is a denoising algorithm with wavelet diffusion based on a circular symmetric Laplacian model, and the second part can be described in terms of graph-based geometry detection and curvature correction according to the hyper-reflective complex layer in the retina. The proposed denoising algorithm showed an improvement of contrast-to-noise ratio from 0.89 to 1.49 and an increase of signal-to-noise ratio (OCT image SNR) from 18.27 to 30.43 dB. By applying the proposed method for estimation of the interpolated curve using a full automatic method, the mean ± SD unsigned border positioning error was calculated for normal and abnormal cases. The error values of 2.19 ± 1.25 and 8.53 ± 3.76 µm were detected for 200 randomly selected slices without pathological curvature and 50 randomly selected slices with pathological curvature, respectively. The important aspect of this algorithm is its ability in detection of curvature in strongly pathological images that surpasses previously introduced methods; the method is also fast, compared to the relatively low speed of similar methods.

Robust Smoothing: Smoothing Parameter Selection and Applications to Fluorescence Spectroscopy∂

PubMed Central

Lee, Jong Soo; Cox, Dennis D.

2009-01-01

Fluorescence spectroscopy has emerged in recent years as an effective way to detect cervical cancer. Investigation of the data preprocessing stage uncovered a need for a robust smoothing to extract the signal from the noise. Various robust smoothing methods for estimating fluorescence emission spectra are compared and data driven methods for the selection of smoothing parameter are suggested. The methods currently implemented in R for smoothing parameter selection proved to be unsatisfactory, and a computationally efficient procedure that approximates robust leave-one-out cross validation is presented. PMID:20729976

Selective turn-on fluorescent probes for imaging hydrogen sulfide in living cells.

PubMed

Montoya, Leticia A; Pluth, Michael D

2012-05-16

Hydrogen sulfide (H(2)S) is an important biological messenger but few biologically-compatible methods are available for its detection. Here we report two bright fluorescent probes that are selective for H(2)S over cysteine, glutathione and other reactive sulfur, nitrogen, and oxygen species. Both probes are demonstrated to detect H(2)S in live cells. This journal is © The Royal Society of Chemistry 2012

Unambiguous detection of nitrated explosive vapours by fluorescence quenching of dendrimer films

NASA Astrophysics Data System (ADS)

Geng, Yan; Ali, Mohammad A.; Clulow, Andrew J.; Fan, Shengqiang; Burn, Paul L.; Gentle, Ian R.; Meredith, Paul; Shaw, Paul E.

2015-09-01

Unambiguous and selective standoff (non-contact) infield detection of nitro-containing explosives and taggants is an important goal but difficult to achieve with standard analytical techniques. Oxidative fluorescence quenching is emerging as a high sensitivity method for detecting such materials but is prone to false positives--everyday items such as perfumes elicit similar responses. Here we report thin films of light-emitting dendrimers that detect vapours of explosives and taggants selectively--fluorescence quenching is not observed for a range of common interferents. Using a combination of neutron reflectometry, quartz crystal microbalance and photophysical measurements we show that the origin of the selectivity is primarily electronic and not the diffusion kinetics of the analyte or its distribution in the film. The results are a major advance in the development of sensing materials for the standoff detection of nitro-based explosive vapours, and deliver significant insights into the physical processes that govern the sensing efficacy.

Selective detection of dopamine in the presence of ascorbic acid via fluorescence quenching of InP/ZnS quantum dots

PubMed Central

Ankireddy, Seshadri Reddy; Kim, Jongsung

2015-01-01

Dopamine is a neurotransmitter of the catecholamine family and has many important roles, especially in human brain. Several diseases of the nervous system, such as Parkinson’s disease, attention deficit hyperactivity disorder, restless legs syndrome, are believed to be related to deficiency of dopamine. Several studies have been performed to detect dopamine by using electrochemical analysis. In this study, quantum dots (QDs) were used as sensing media for the detection of dopamine. The surface of the QDs was modified with l-cysteine by coupling reaction to increase the selectivity of dopamine. The fluorescence of cysteine-capped indium phosphide/zinc sulfide QDs was quenched by dopamine with various concentrations in the presence of ascorbic acid. This method shows good selectivity for dopamine detection, and the detection limit was 5 nM. PMID:26347250

Fast Selective Detection of Pyocyanin Using Cyclic Voltammetry

PubMed Central

Alatraktchi, Fatima AlZahra’a; Breum Andersen, Sandra; Krogh Johansen, Helle; Molin, Søren; Svendsen, Winnie E.

2016-01-01

Pyocyanin is a virulence factor uniquely produced by the pathogen Pseudomonas aeruginosa. The fast and selective detection of pyocyanin in clinical samples can reveal important information about the presence of this microorganism in patients. Electrochemical sensing of the redox-active pyocyanin is a route to directly quantify pyocyanin in real time and in situ in hospitals and clinics. The selective quantification of pyocyanin is, however, limited by other redox-active compounds existing in human fluids and by other metabolites produced by pathogenic bacteria. Here we present a direct selective method to detect pyocyanin in a complex electroactive environment using commercially available electrodes. It is shown that cyclic voltammetry measurements between −1.0 V to 1.0 V reveal a potential detection window of pyocyanin of 0.58–0.82 V that is unaffected by other redox-active interferents. The linear quantification of pyocyanin has an R2 value of 0.991 across the clinically relevant concentration range of 2–100 µM. The proposed method was tested on human saliva showing a standard deviation of 2.5% ± 1% (n = 5) from the known added pyocyanin concentration to the samples. This inexpensive procedure is suggested for clinical use in monitoring the presence and state of P. aeruginosa infection in patients. PMID:27007376

Fast Selective Detection of Pyocyanin Using Cyclic Voltammetry.

PubMed

Alatraktchi, Fatima AlZahra'a; Andersen, Sandra Breum; Johansen, Helle Krogh; Molin, Søren; Svendsen, Winnie E

2016-03-19

Pyocyanin is a virulence factor uniquely produced by the pathogen Pseudomonas aeruginosa. The fast and selective detection of pyocyanin in clinical samples can reveal important information about the presence of this microorganism in patients. Electrochemical sensing of the redox-active pyocyanin is a route to directly quantify pyocyanin in real time and in situ in hospitals and clinics. The selective quantification of pyocyanin is, however, limited by other redox-active compounds existing in human fluids and by other metabolites produced by pathogenic bacteria. Here we present a direct selective method to detect pyocyanin in a complex electroactive environment using commercially available electrodes. It is shown that cyclic voltammetry measurements between -1.0 V to 1.0 V reveal a potential detection window of pyocyanin of 0.58-0.82 V that is unaffected by other redox-active interferents. The linear quantification of pyocyanin has an R² value of 0.991 across the clinically relevant concentration range of 2-100 µM. The proposed method was tested on human saliva showing a standard deviation of 2.5% ± 1% (n = 5) from the known added pyocyanin concentration to the samples. This inexpensive procedure is suggested for clinical use in monitoring the presence and state of P. aeruginosa infection in patients.

Network intrusion detection by the coevolutionary immune algorithm of artificial immune systems with clonal selection

NASA Astrophysics Data System (ADS)

Salamatova, T.; Zhukov, V.

2017-02-01

The paper presents the application of the artificial immune systems apparatus as a heuristic method of network intrusion detection for algorithmic provision of intrusion detection systems. The coevolutionary immune algorithm of artificial immune systems with clonal selection was elaborated. In testing different datasets the empirical results of evaluation of the algorithm effectiveness were achieved. To identify the degree of efficiency the algorithm was compared with analogs. The fundamental rules based of solutions generated by this algorithm are described in the article.

Melamine detection in infant formula powder using near- and mid-infrared spectroscopy.

PubMed

Mauer, Lisa J; Chernyshova, Alona A; Hiatt, Ashley; Deering, Amanda; Davis, Reeta

2009-05-27

Near- and mid-infrared spectroscopy methods (NIR, FTIR-ATR, FTIR-DRIFT) were evaluated for the detection and quantification of melamine in infant formula powder. Partial least-squares (PLS) models were established for correlating spectral data to melamine concentration: R(2) > 0.99, RMSECV ≤ 0.9, and RPD ≥ 12. Factorization analysis of spectra was able to differentiate unadulterated infant formula powder from samples containing 1 ppm melamine with no misclassifications, a confidence level of 99.99%, and selectivity > 2. These nondestructive methods require little or no sample preparation. The NIR method has an assay time of 1 min, and a 2 min total time to detection. The FTIR methods require up to 5 min for melamine detection. Therefore, NIR and FTIR methods enable rapid detection of 1 ppm melamine in infant formula powder.

Potential Landslide Early Detection Near Wenchuan by a Qualitatively Multi-Baseline Dinsar Method

NASA Astrophysics Data System (ADS)

Dai, K.; Chen, G.; Xu, Q.; Li, Z.; Qu, T.; Hu, L.; Lu, H.

2018-04-01

Early detection of landslides is important for disaster prevention, which was still very hard work with traditional surveying methods. Interferometric Synthetic Aperture Radar (InSAR) technology provided us the ability to monitor displacements along the slope with wide coverage and high accuracy. In this paper, we proposed a qualitatively multi-baseline DInSAR method to early detect and map the potential landslides. Two sections of China National Highway 317 and 213 were selected as study area. With this method 10 potential landslide areas were early detected and mapped in a quick and effective way. One of them (i.e. Shidaguan landslide) collapsed on August 2017, which was coincident with our results, suggesting that this method could become an effective way to acquire the landslide early detection map to assist the future disaster prevention work.

A model of directional selection applied to the evolution of drug resistance in HIV-1.

PubMed

Seoighe, Cathal; Ketwaroo, Farahnaz; Pillay, Visva; Scheffler, Konrad; Wood, Natasha; Duffet, Rodger; Zvelebil, Marketa; Martinson, Neil; McIntyre, James; Morris, Lynn; Hide, Winston

2007-04-01

Understanding how pathogens acquire resistance to drugs is important for the design of treatment strategies, particularly for rapidly evolving viruses such as HIV-1. Drug treatment can exert strong selective pressures and sites within targeted genes that confer resistance frequently evolve far more rapidly than the neutral rate. Rapid evolution at sites that confer resistance to drugs can be used to help elucidate the mechanisms of evolution of drug resistance and to discover or corroborate novel resistance mutations. We have implemented standard maximum likelihood methods that are used to detect diversifying selection and adapted them for use with serially sampled reverse transcriptase (RT) coding sequences isolated from a group of 300 HIV-1 subtype C-infected women before and after single-dose nevirapine (sdNVP) to prevent mother-to-child transmission. We have also extended the standard models of codon evolution for application to the detection of directional selection. Through simulation, we show that the directional selection model can provide a substantial improvement in sensitivity over models of diversifying selection. Five of the sites within the RT gene that are known to harbor mutations that confer resistance to nevirapine (NVP) strongly supported the directional selection model. There was no evidence that other mutations that are known to confer NVP resistance were selected in this cohort. The directional selection model, applied to serially sampled sequences, also had more power than the diversifying selection model to detect selection resulting from factors other than drug resistance. Because inference of selection from serial samples is unlikely to be adversely affected by recombination, the methods we describe may have general applicability to the analysis of positive selection affecting recombining coding sequences when serially sampled data are available.

Species Specific Bacterial Spore Detection Using Lateral-Flow Immunoassay with DPA-Triggered Tb Luminescence

NASA Technical Reports Server (NTRS)

Ponce, Adrian

2003-01-01

A method of detecting bacterial spores incorporates (1) A method of lateral-flow immunoassay in combination with (2) A method based on the luminescence of Tb3+ ions to which molecules of dipicolinic acid (DPA) released from the spores have become bound. The present combination of lateral-flow immunoassay and DPA-triggered Tb luminescence was developed as a superior alternative to a prior lateral-flow immunoassay method in which detection involves the visual observation and/or measurement of red light scattered from colloidal gold nanoparticles. The advantage of the present combination method is that it affords both (1) High selectivity for spores of the species of bacteria that one seeks to detect (a characteristic of lateral-flow immunoassay in general) and (2) Detection sensitivity much greater (by virtue of the use of DPA-triggered Tb luminescence instead of gold nanoparticles) than that of the prior lateral-flow immunoassay method

Arrayed Micro-Ring Spectrometer System and Method of Use

NASA Technical Reports Server (NTRS)

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

2012-01-01

A spectrometer system includes an array of micro-zone plates (MZP) each having coaxially-aligned ring gratings, a sample plate for supporting and illuminating a sample, and an array of photon detectors for measuring a spectral characteristic of the predetermined wavelength. The sample plate emits an evanescent wave in response to incident light, which excites molecules of the sample to thereby cause an emission of secondary photons. A method of detecting the intensity of a selected wavelength of incident light includes directing the incident light onto an array of MZP, diffracting a selected wavelength of the incident light onto a target focal point using the array of MZP, and detecting the intensity of the selected portion using an array of photon detectors. An electro-optic layer positioned adjacent to the array of MZP may be excited via an applied voltage to select the wavelength of the incident light.

Molecularly imprinted covalent organic polymers for the selective extraction of benzoxazole fluorescent whitening agents from food samples.

PubMed

Ding, Hui; Wang, Rongyu; Wang, Xiao; Ji, Wenhua

2018-06-21

Molecularly imprinted covalent organic polymers were constructed by an imine-linking reaction between 1,3,5-triformylphloroglucinol and 2,6-diaminopyridine and used for the selective solid-phase extraction of benzoxazole fluorescent whitening agents from food samples. Binding experiments showed that imprinting sites on molecularly imprinted polymers had higher selectivity for targets compared with those of the corresponding non-imprinted polymers. Parameters affecting the solid-phase extraction procedure were examined. Under optimal conditions, actual samples were treated and the eluent was analyzed with high-performance liquid chromatography with diode-array detection. The results showed that the established method owned the wide linearity, satisfactory detection limits and quantification limits, and acceptable recoveries. Thus, this developed method possesses the practical potential to the selectively determine benzoxazole fluorescent whitening agents in complex food samples. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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

PubMed

Kishikawa, Naoya

2010-10-01

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

Can machine learning complement traditional medical device surveillance? A case study of dual-chamber implantable cardioverter-defibrillators.

PubMed

Ross, Joseph S; Bates, Jonathan; Parzynski, Craig S; Akar, Joseph G; Curtis, Jeptha P; Desai, Nihar R; Freeman, James V; Gamble, Ginger M; Kuntz, Richard; Li, Shu-Xia; Marinac-Dabic, Danica; Masoudi, Frederick A; Normand, Sharon-Lise T; Ranasinghe, Isuru; Shaw, Richard E; Krumholz, Harlan M

2017-01-01

Machine learning methods may complement traditional analytic methods for medical device surveillance. Using data from the National Cardiovascular Data Registry for implantable cardioverter-defibrillators (ICDs) linked to Medicare administrative claims for longitudinal follow-up, we applied three statistical approaches to safety-signal detection for commonly used dual-chamber ICDs that used two propensity score (PS) models: one specified by subject-matter experts (PS-SME), and the other one by machine learning-based selection (PS-ML). The first approach used PS-SME and cumulative incidence (time-to-event), the second approach used PS-SME and cumulative risk (Data Extraction and Longitudinal Trend Analysis [DELTA]), and the third approach used PS-ML and cumulative risk (embedded feature selection). Safety-signal surveillance was conducted for eleven dual-chamber ICD models implanted at least 2,000 times over 3 years. Between 2006 and 2010, there were 71,948 Medicare fee-for-service beneficiaries who received dual-chamber ICDs. Cumulative device-specific unadjusted 3-year event rates varied for three surveyed safety signals: death from any cause, 12.8%-20.9%; nonfatal ICD-related adverse events, 19.3%-26.3%; and death from any cause or nonfatal ICD-related adverse event, 27.1%-37.6%. Agreement among safety signals detected/not detected between the time-to-event and DELTA approaches was 90.9% (360 of 396, k =0.068), between the time-to-event and embedded feature-selection approaches was 91.7% (363 of 396, k =-0.028), and between the DELTA and embedded feature selection approaches was 88.1% (349 of 396, k =-0.042). Three statistical approaches, including one machine learning method, identified important safety signals, but without exact agreement. Ensemble methods may be needed to detect all safety signals for further evaluation during medical device surveillance.

Mentha-Stabilized Silver Nanoparticles for High-Performance Colorimetric Detection of Al(III) in Aqueous Systems.

PubMed

Sharma, Rekha; Dhillon, Ankita; Kumar, Dinesh

2018-03-26

The present paper reports a facile and selective colorimetric method for the detection of potential environmental and health hazardous metal ions using green synthesized silver nanoparticles (AgNPs). Here the organic functional groups present in the plant extract (Mentha arvensis) are used as reductants and stabilizers in the synthesis of AgNPs. They also provide a suitable binding site to the (Al(III)) analyte in the detection mechanism. The leaf extract of Mentha arvensis was used to synthesize AgNPs at room-temperature and at 80 °C. The AgNPs synthesized at 80 °C exhibit excellent selective colorimetric detection of Al(III). The as-synthesized AgNPs have been characterized, and the synthesis, stabilization of NPs and detection mechanism has also been illustrated by using UV-vis, XPS, FTIR, TEM, EDX, SEM, AAS, and TGA analytical tools and techniques. The selectivity of detection probe was supported by the reaction between probe and metal ions followed first-order kinetics having the highest value of the regression coefficient (R 2  = 0.99) for Al(III) and the analysis of thermodynamic parameters. The prepared sensor showed a lower limit of detection (LOD) of 1 nM (S/N = 3.2) in real water samples. The proposed method can be successfully utilized for the detection of Al(III) from both drinking and real water samples at the nanomolar level.

A malware detection scheme based on mining format information.

PubMed

Bai, Jinrong; Wang, Junfeng; Zou, Guozhong

2014-01-01

Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files. Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance. When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998. We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware. Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates.

A Malware Detection Scheme Based on Mining Format Information

PubMed Central

Bai, Jinrong; Wang, Junfeng; Zou, Guozhong

2014-01-01

Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files. Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance. When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998. We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware. Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates. PMID:24991639

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

PubMed

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

2010-03-01

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

Automated Detection of Knickpoints and Knickzones Across Transient Landscapes

NASA Astrophysics Data System (ADS)

Gailleton, B.; Mudd, S. M.; Clubb, F. J.

2017-12-01

Mountainous regions are ubiquitously dissected by river channels, which transmit climate and tectonic signals to the rest of the landscape by adjusting their long profiles. Fluvial response to allogenic forcing is often expressed through the upstream propagation of steepened reaches, referred to as knickpoints or knickzones. The identification and analysis of these steepened reaches has numerous applications in geomorphology, such as modelling long-term landscape evolution, understanding controls on fluvial incision, and constraining tectonic uplift histories. Traditionally, the identification of knickpoints or knickzones from fluvial profiles requires manual selection or calibration. This process is both time-consuming and subjective, as different workers may select different steepened reaches within the profile. We propose an objective, statistically-based method to systematically pick knickpoints/knickzones on a landscape scale using an outlier-detection algorithm. Our method integrates river profiles normalised by drainage area (Chi, using the approach of Perron and Royden, 2013), then separates the chi-elevation plots into a series of transient segments using the method of Mudd et al. (2014). This method allows the systematic detection of knickpoints across a DEM, regardless of size, using a high-performance algorithm implemented in the open-source Edinburgh Land Surface Dynamics Topographic Tools (LSDTopoTools) software package. After initial knickpoint identification, outliers are selected using several sorting and binning methods based on the Median Absolute Deviation, to avoid the influence sample size. We test our method on a series of DEMs and grid resolutions, and show that our method consistently identifies accurate knickpoint locations across each landscape tested.

Simultaneous detection of perchlorate and bromate using rapid high-performance ion exchange chromatography-tandem mass spectrometry and perchlorate removal in drinking water.

PubMed

West, Danielle M; Mu, Ruipu; Gamagedara, Sanjeewa; Ma, Yinfa; Adams, Craig; Eichholz, Todd; Burken, Joel G; Shi, Honglan

2015-06-01

Perchlorate and bromate occurrence in drinking water causes health concerns due to their effects on thyroid function and carcinogenicity, respectively. The purpose of this study was threefold: (1) to advance a sensitive method for simultaneous rapid detection of perchlorate and bromate in drinking water system, (2) to systematically study the occurrence of these two contaminants in Missouri drinking water treatment systems, and (3) to examine effective sorbents for minimizing perchlorate in drinking water. A rapid high-performance ion exchange chromatography-tandem mass spectrometry (HPIC-MS/MS) method was advanced for simultaneous detection of perchlorate and bromate in drinking water. The HPIC-MS/MS method was rapid, required no preconcentration of the water samples, and had detection limits for perchlorate and bromate of 0.04 and 0.01 μg/L, respectively. The method was applied to determine perchlorate and bromate concentrations in total of 23 selected Missouri drinking water treatment systems during differing seasons. The water systems selected include different source waters: groundwater, lake water, river water, and groundwater influenced by surface water. The concentrations of perchlorate and bromate were lower than or near to method detection limits in most of the drinking water samples monitored. The removal of perchlorate by various adsorbents was studied. A cationic organoclay (TC-99) exhibited effective removal of perchlorate from drinking water matrices.

Multifunctional inorganic-organic hybrid nanospheres for rapid and selective luminescence detection of TNT in mixed nitroaromatics via magnetic separation.

PubMed

Ma, Yingxin; Huang, Sheng; Wang, Leyu

2013-11-15

Rapid, sensitive and selective detection of 2,4,6-trinitrotoluene (TNT) in aqueous solution differentiating from other nitroaromatics and independent of complicated instruments is in high demand for public safety and environmental monitoring. Despite of many methods for TNT detection, it is hard to differentiate TNT from 2,4,6-trinitrophenol (TNP) due to their highly similar structures and properties. In this work, via a simple and versatile method, LaF3ːCe(3+)-Tb(3+)and Fe3O4 nanoparticle-codoped multifunctional nanospheres were prepared through self-assembly of the building blocks. The luminescence of these nanocomposites was dramatically quenched via adding nitroaromatics into the aqueous solution. After the magnetic separation, however, the interference of other nitroaromatics including 2,4,6-trinitrophenol (TNP), 2,4-dinitrotoluene (DNT), and nitrobenzene (NB) was effectively overcome due to the removal of these coexisting nitroaromatics from the surface of nanocomposites. Due to the formation of TNT(-)-RCONH3(+), the TNT was attached to the surface of the nanocomposites and was quantitatively detected by the postexposure luminescence quenching. Meanwhile, the luminescence intensity is negatively proportional to the concentration of TNT in the range of 0.01-5.0 μg/mL with the 3σ limit of detection (LOD) of 10.2 ng/mL. Therefore, the as-developed method provides a novel strategy for rapid and selective detection of TNT in the mixture solution of nitroaromatics by postexposure luminescence quenching. Copyright © 2013 Elsevier B.V. All rights reserved.

Unsupervised Online Classifier in Sleep Scoring for Sleep Deprivation Studies

PubMed Central

Libourel, Paul-Antoine; Corneyllie, Alexandra; Luppi, Pierre-Hervé; Chouvet, Guy; Gervasoni, Damien

2015-01-01

Study Objective: This study was designed to evaluate an unsupervised adaptive algorithm for real-time detection of sleep and wake states in rodents. Design: We designed a Bayesian classifier that automatically extracts electroencephalogram (EEG) and electromyogram (EMG) features and categorizes non-overlapping 5-s epochs into one of the three major sleep and wake states without any human supervision. This sleep-scoring algorithm is coupled online with a new device to perform selective paradoxical sleep deprivation (PSD). Settings: Controlled laboratory settings for chronic polygraphic sleep recordings and selective PSD. Participants: Ten adult Sprague-Dawley rats instrumented for chronic polysomnographic recordings Measurements: The performance of the algorithm is evaluated by comparison with the score obtained by a human expert reader. Online detection of PS is then validated with a PSD protocol with duration of 72 hours. Results: Our algorithm gave a high concordance with human scoring with an average κ coefficient > 70%. Notably, the specificity to detect PS reached 92%. Selective PSD using real-time detection of PS strongly reduced PS amounts, leaving only brief PS bouts necessary for the detection of PS in EEG and EMG signals (4.7 ± 0.7% over 72 h, versus 8.9 ± 0.5% in baseline), and was followed by a significant PS rebound (23.3 ± 3.3% over 150 minutes). Conclusions: Our fully unsupervised data-driven algorithm overcomes some limitations of the other automated methods such as the selection of representative descriptors or threshold settings. When used online and coupled with our sleep deprivation device, it represents a better option for selective PSD than other methods like the tedious gentle handling or the platform method. Citation: Libourel PA, Corneyllie A, Luppi PH, Chouvet G, Gervasoni D. Unsupervised online classifier in sleep scoring for sleep deprivation studies. SLEEP 2015;38(5):815–828. PMID:25325478

Efficient feature selection using a hybrid algorithm for the task of epileptic seizure detection

NASA Astrophysics Data System (ADS)

Lai, Kee Huong; Zainuddin, Zarita; Ong, Pauline

2014-07-01

Feature selection is a very important aspect in the field of machine learning. It entails the search of an optimal subset from a very large data set with high dimensional feature space. Apart from eliminating redundant features and reducing computational cost, a good selection of feature also leads to higher prediction and classification accuracy. In this paper, an efficient feature selection technique is introduced in the task of epileptic seizure detection. The raw data are electroencephalography (EEG) signals. Using discrete wavelet transform, the biomedical signals were decomposed into several sets of wavelet coefficients. To reduce the dimension of these wavelet coefficients, a feature selection method that combines the strength of both filter and wrapper methods is proposed. Principal component analysis (PCA) is used as part of the filter method. As for wrapper method, the evolutionary harmony search (HS) algorithm is employed. This metaheuristic method aims at finding the best discriminating set of features from the original data. The obtained features were then used as input for an automated classifier, namely wavelet neural networks (WNNs). The WNNs model was trained to perform a binary classification task, that is, to determine whether a given EEG signal was normal or epileptic. For comparison purposes, different sets of features were also used as input. Simulation results showed that the WNNs that used the features chosen by the hybrid algorithm achieved the highest overall classification accuracy.

APTS and rGO co-functionalized pyrenated fluorescent nanonets for representative vapor phase nitroaromatic explosive detection

NASA Astrophysics Data System (ADS)

Guo, Linjuan; Zu, Baiyi; Yang, Zheng; Cao, Hongyu; Zheng, Xuefang; Dou, Xincun

2014-01-01

For the first time, flexible PVP/pyrene/APTS/rGO fluorescent nanonets were designed and synthesized via a one-step electrospinning method to detect representative subsaturated nitroaromatic explosive vapor. The functional fluorescent nanonets, which were highly stable in air, showed an 81% quenching efficiency towards TNT vapor (~10 ppb) with an exposure time of 540 s at room temperature. The nice performance of the nanonets was ascribed to the synergistic effects induced by the specific adsorption properties of APTS, the fast charge transfer properties and the effective π-π interaction with pyrene and TNT of rGO. Compared to the analogues of TNT, the PVP/pyrene/APTS/rGO nanonets showed notable selectivity towards TNT and DNT vapors. The explored functionalization method opens up brand new insight into sensitive and selective detection of vapor phase nitroaromatic explosives.For the first time, flexible PVP/pyrene/APTS/rGO fluorescent nanonets were designed and synthesized via a one-step electrospinning method to detect representative subsaturated nitroaromatic explosive vapor. The functional fluorescent nanonets, which were highly stable in air, showed an 81% quenching efficiency towards TNT vapor (~10 ppb) with an exposure time of 540 s at room temperature. The nice performance of the nanonets was ascribed to the synergistic effects induced by the specific adsorption properties of APTS, the fast charge transfer properties and the effective π-π interaction with pyrene and TNT of rGO. Compared to the analogues of TNT, the PVP/pyrene/APTS/rGO nanonets showed notable selectivity towards TNT and DNT vapors. The explored functionalization method opens up brand new insight into sensitive and selective detection of vapor phase nitroaromatic explosives. Electronic supplementary information (ESI) available: Vapor pressure of TNT and its analogues, fluorescence quenching kinetics, fluorescence quenching efficiencies and additional SEM images. See DOI: 10.1039/c3nr04960d

Developing Methods for Detection of Munitions and Explosives of Concern in Offshore Wind Energy Areas

NASA Astrophysics Data System (ADS)

DuVal, C.; Trembanis, A. C.; Miller, J. K.; Carton, G.

2016-12-01

Munitions and Explosives of Concern (MEC) have been acknowledged globally as a topic of concern. Increasing use of coastal and continental shelf environments for renewable energy development and other activities has and continues to place humans in contact with legacy military munitions. The Bureau of Ocean Energy Management (BOEM) recognized the need to develop guidance concerning methods for MEC detection in the case of offshore energy development. The study was designed to identify the most likely MEC to be encountered in the Atlantic Outer Continental Shelf (OCS) Wind Energy Areas (WEA), review available technologies and develop a process for selecting appropriate technologies and methodologies for their detection. The process for selecting and optimizing technologies and methods for detection of MEC in BOEM OCS WEAs was developed and tested through the synthesis of historical research, physical site characterization, remote sensing technology review, and in-field trials. To test the selected approach, designated personnel were tasked with seeding a portion of the Delaware WEA with munitions surrogates, while a second group of researchers not privy to the surrogate locations, tested and optimized the selected methodology. The effectiveness of a methodology will be related to ease of detection and other associated parameters. The approach for the in-field trial consists of a combination of wide-area assessment surveying by vessel mounted 230/550 kHz Edgetech 6205 Phase Measuring sonar and near-seafloor surveying using a Teledyne Gavia autonomous underwater vehicle (AUV) equipped with high-resolution 900/1800 kHz Marine Sonics side-scan sonar, Geometrics G880-AUV cesium-vapor magnetometer, and 2 megapixel Point Grey color camera. Survey parameters (e.g. track-line spacing, coverage overlap, AUV altitude) were varied to determine the optimal survey methods, as well as simulate MEC burial to test magnetometer range performance. Preliminary results indicate the combination of high-resolution, near-bed side-scan sonar and magnetometry yields promising results for MEC identification, addressing the potential for both surficial and buried MEC.

Mid-infrared spectroscopy combined with chemometrics to detect Sclerotinia stem rot on oilseed rape (Brassica napus L.) leaves.

PubMed

Zhang, Chu; Feng, Xuping; Wang, Jian; Liu, Fei; He, Yong; Zhou, Weijun

2017-01-01

Detection of plant diseases in a fast and simple way is crucial for timely disease control. Conventionally, plant diseases are accurately identified by DNA, RNA or serology based methods which are time consuming, complex and expensive. Mid-infrared spectroscopy is a promising technique that simplifies the detection procedure for the disease. Mid-infrared spectroscopy was used to identify the spectral differences between healthy and infected oilseed rape leaves. Two different sample sets from two experiments were used to explore and validate the feasibility of using mid-infrared spectroscopy in detecting Sclerotinia stem rot (SSR) on oilseed rape leaves. The average mid-infrared spectra showed differences between healthy and infected leaves, and the differences varied among different sample sets. Optimal wavenumbers for the 2 sample sets selected by the second derivative spectra were similar, indicating the efficacy of selecting optimal wavenumbers. Chemometric methods were further used to quantitatively detect the oilseed rape leaves infected by SSR, including the partial least squares-discriminant analysis, support vector machine and extreme learning machine. The discriminant models using the full spectra and the optimal wavenumbers of the 2 sample sets were effective for classification accuracies over 80%. The discriminant results for the 2 sample sets varied due to variations in the samples. The use of two sample sets proved and validated the feasibility of using mid-infrared spectroscopy and chemometric methods for detecting SSR on oilseed rape leaves. The similarities among the selected optimal wavenumbers in different sample sets made it feasible to simplify the models and build practical models. Mid-infrared spectroscopy is a reliable and promising technique for SSR control. This study helps in developing practical application of using mid-infrared spectroscopy combined with chemometrics to detect plant disease.

Method for photon activation positron annihilation analysis

DOEpatents

Akers, Douglas W.

2006-06-06

A non-destructive testing method comprises providing a specimen having at least one positron emitter therein; determining a threshold energy for activating the positron emitter; and determining whether a half-life of the positron emitter is less than a selected half-life. If the half-life of the positron emitter is greater than or equal to the selected half-life, then activating the positron emitter by bombarding the specimen with photons having energies greater than the threshold energy and detecting gamma rays produced by annihilation of positrons in the specimen. If the half-life of the positron emitter is less then the selected half-life, then alternately activating the positron emitter by bombarding the specimen with photons having energies greater then the threshold energy and detecting gamma rays produced by positron annihilation within the specimen.

Detection and Identification of Salmonella spp. in Surface Water by Molecular Technology in Taiwan

NASA Astrophysics Data System (ADS)

Tseng, S. F.; Hsu, B. M.; Huang, K. H.; Hsiao, H. Y.; Kao, P. M.; Shen, S. M.; Tsai, H. F.; Chen, J. S.

2012-04-01

Salmonella spp. is classified to gram-negative bacterium and is one of the most important causal agents of waterborne diseases. The genus of Salmonella comprises more than 2,500 serotypes and its taxonomy is also very complicated. In tradition, the detection of Salmonella in environmental water samples by routines culture methods using selective media and characterization of suspicious colonies based on biochemical tests and serological assay are generally time and labor consuming. To overcome this disadvantage, it is desirable to use effective method which provides a higher discrimination and more rapid identification about Salmonella in environmental water. The aim of this study is to investigate the occurrence of Salmonella using novel procedures of detection method and to identify the serovars of Salmonella isolates from 157 surface water samples in Taiwan. The procedures include membrane filtration, non-selective pre-enrichment, selective enrichment of Salmonella, and then isolation of Salmonella strains by selective culture plates. The selective enrichment and culture plates were both detected by PCR. Finally, we used biochemical tests and serological assay to confirm the serovars of Salmonella and also used Pulsed-field gel electrophoresis (PFGE) to identify their sarovar catagories by the genetic pattern. In this study, 44 water samples (28%) were indentified as Salmonella. The 44 positive water samples by culture method were further identified as S. Agona(1/44), S. Albany (10/44), S. Bareilly (13/44),S. Choleraesuis (2/44),S. Derby (4/44),S. Isangi (3/44),S.Kedougou(3/44),S. Mbandaka(1/44),S.Newport (3/44), S. Oranienburg(1/44), S. Potsdam (1/44),S. Typhimurium (1/44), andS. Weltevreden(1/44) by PFGE. The presence of Salmonella in surface water indicates the possibility of waterborne transmission in drinking watershed if water is not adequately treated. Therefore, the authorities need to have operating systems that currently provide adequate source protection and maintaining the system to prevent disease. Keywords: Salmonella spp.; biochemical tests; Serological assay; PCR; PFGE

Energy conservation using face detection

NASA Astrophysics Data System (ADS)

Deotale, Nilesh T.; Kalbande, Dhananjay R.; Mishra, Akassh A.

2011-10-01

Computerized Face Detection, is concerned with the difficult task of converting a video signal of a person to written text. It has several applications like face recognition, simultaneous multiple face processing, biometrics, security, video surveillance, human computer interface, image database management, digital cameras use face detection for autofocus, selecting regions of interest in photo slideshows that use a pan-and-scale and The Present Paper deals with energy conservation using face detection. Automating the process to a computer requires the use of various image processing techniques. There are various methods that can be used for Face Detection such as Contour tracking methods, Template matching, Controlled background, Model based, Motion based and color based. Basically, the video of the subject are converted into images are further selected manually for processing. However, several factors like poor illumination, movement of face, viewpoint-dependent Physical appearance, Acquisition geometry, Imaging conditions, Compression artifacts makes Face detection difficult. This paper reports an algorithm for conservation of energy using face detection for various devices. The present paper suggests Energy Conservation can be done by Detecting the Face and reducing the brightness of complete image and then adjusting the brightness of the particular area of an image where the face is located using histogram equalization.

Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines

PubMed Central

Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

2016-01-01

In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved. PMID:27136561

Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines.

PubMed

Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

2016-04-29

In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved.

An isotope dilution ultra high performance liquid chromatography-tandem mass spectrometry method for the simultaneous determination of sugars and humectants in tobacco products.

PubMed

Wang, Liqun; Cardenas, Roberto Bravo; Watson, Clifford

2017-09-08

CDC's Division of Laboratory Sciences developed and validated a new method for the simultaneous detection and measurement of 11 sugars, alditols and humectants in tobacco products. The method uses isotope dilution ultra high performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) and has demonstrated high sensitivity, selectivity, throughput and accuracy, with recoveries ranging from 90% to 113%, limits of detection ranging from 0.0002 to 0.0045μg/mL and coefficients of variation (CV%) ranging from 1.4 to 14%. Calibration curves for all analytes were linear with linearity R 2 values greater than 0.995. Quantification of tobacco components is necessary to characterize tobacco product components and their potential effects on consumer appeal, smoke chemistry and toxicology, and to potentially help distinguish tobacco product categories. The researchers analyzed a variety of tobacco products (e.g., cigarettes, little cigars, cigarillos) using the new method and documented differences in the abundance of selected analytes among product categories. Specifically, differences were detected in levels of selected sugars found in little cigars and cigarettes, which could help address appeal potential and have utility when product category is unknown, unclear, or miscategorized. Copyright © 2017. Published by Elsevier B.V.

Molecularly imprinted solid-phase extraction combined with electrochemical oxidation fluorimetry for the determination of methotrexate in human serum and urine

NASA Astrophysics Data System (ADS)

Chen, Suming; Zhang, Zhujun

2008-06-01

The method of synthesis and evaluation of molecularly imprinted polymers was reported. As a selective solid-phase extraction sorbent, the polymers were coupled with electrochemical fluorimetry detection for the efficient determination of methotrexate in serum and urine. Methotrexate was preconcentrated in the molecularly imprinted solid-phase extraction microcolumn packed with molecularly imprinted polymers, and then eluted. The eluate was detected by fluorescence spectrophotometer after electrochemical oxidation. The conditions of preconcentration, elution, electrochemical oxidation and determination were carefully studied. Under the selected experimental conditions, the calibration graph of the fluorescence intensity versus methotrexate concentration was linear from 4 × 10 -9 g mL -1 to 5 × 10 -7 g mL -1, and the detection limit was 8.2 × 10 -10 g mL -1 (3 σ). The relative standard deviation was 3.92% ( n = 7) for 1 × 10 -7 g mL -1 methotrexate. The experiments showed that the selectivity and sensitivity of fluorimetry could be greatly improved by the proposed method. This method has been successfully applied to the determination of methotrexate. At the same time, the binding characteristics of the polymers to the methotrexate were evaluated by batch and dynamic methods.

Determination of secondary and tertiary amines as N-nitrosamine precursors in drinking water system using ultra-fast liquid chromatography-tandem mass spectrometry.

PubMed

Wu, Qihua; Shi, Honglan; Ma, Yinfa; Adams, Craig; Eichholz, Todd; Timmons, Terry; Jiang, Hua

2015-01-01

N-Nitrosamines are potent mutagenic and carcinogenic emerging water disinfection by-products (DBPs). The most effective strategy to control the formation of these DBPs is minimizing their precursors from source water. Secondary and tertiary amines are dominating precursors of N-nitrosamines formation during drinking water disinfection process. Therefore, the screening and removal of these amines in source water are very essential for preventing the formation of N-nitrosamines. A rapid, simple, and sensitive ultrafast liquid chromatography-tandem mass spectrometry (UFLC-MS/MS) method has been developed in this study to determine seven amines, including dimethylamine, ethylmethylamine, diethylamine, dipropylamine, trimethylamine, 3-(dimethylaminomethyl)indole, and 4-dimethylaminoantipyrine, as major precursors of N-nitrosamines in drinking water system. No sample preparation process is needed except a simple filtration. Separation and detection can be achieved in 11 min per sample. The method detection limits of selected amines are ranging from 0.02 μg/L to 1 μg/L except EMA (5 μg/L), and good calibration linearity was achieved. The developed method was applied to determine the selected precursors in source water and drinking water samples collected from Midwest area of the United States. In most of water samples, the concentrations of selected precursors of N-nitrosamines were below their method detection limits. Dimethylamine was detected in some of water samples at the concentration up to 25.4 μg/L. Copyright © 2014 Elsevier B.V. All rights reserved.

Method and device for the detection of phenol and related compounds. [in an electrochemical cell

NASA Technical Reports Server (NTRS)

Schiller, J. G.; Liu, C. C. (Inventor)

1979-01-01

A method is described which permits the selective oxidation and potentiometric detection of phenol and related compounds in an electrochemical cell. An anode coated with a gel immobilized oxidative enzyme and a cathode are each placed in an electrolyte solution. The potential of the cell is measured by a potentiometer connected to the electrodes.

Method and apparatus for simultaneous detection and measurement of charged particles at one or more levels of particle flux for analysis of same

DOEpatents

Denton, M Bonner [Tucson, AZ; Sperline, Roger , Koppenaal, David W. , Barinaga, Charles J. , Hieftje, Gary , Barnes, IV, James H.; Atlas, Eugene [Irvine, CA

2009-03-03

A charged particle detector and method are disclosed providing for simultaneous detection and measurement of charged particles at one or more levels of particle flux in a measurement cycle. The detector provides multiple and independently selectable levels of integration and/or gain in a fully addressable readout manner.

Assessment of groundwater, soil-gas, and soil contamination at the Vietnam Armor Training Facility, Fort Gordon, Georgia, 2009-2010

USGS Publications Warehouse

Guimaraes, Wladmir B.; Falls, W. Fred; Caldwell, Andral W.; Ratliff, W. Hagan; Wellborn, John B.; Landmeyer, James E.

2011-01-01

The U.S. Geological Survey, in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon, Georgia, assessed the groundwater, soil gas, and soil for contaminants at the Vietnam Armor Training Facility (VATF) at Fort Gordon, from October 2009 to September 2010. The assessment included the detection of organic compounds in the groundwater and soil gas, and inorganic compounds in the soil. In addition, organic contaminant assessment included organic compounds classified as explosives and chemical agents in selected areas. The assessment was conducted to provide environmental contamination data to the U.S. Army at Fort Gordon pursuant to requirements of the Resource Conservation and Recovery Act Part B Hazardous Waste Permit process. Four passive samplers were deployed in groundwater wells at the VATF in Fort Gordon. Total petroleum hydrocarbons were detected above the method detection level at all four wells. The only other volatile organic compounds detected above their method detection level were undecane and pentadecane, which were detected in two of the four wells sampled. Soil-gas samplers were deployed at 72 locations in a grid pattern across the VATF. Total petroleum hydrocarbons were detected in 71 of the 72 samplers (one sampler was destroyed in the field and not analyzed) at levels above the method detection level, and the combined mass of benzene, toluene, ethylbenzene, and total xylene was detected above the detection level in 31 of the 71 samplers that were analyzed. Other volatile organic compounds detected above their respective method detection levels were naphthalene, 2-methyl-naphthalene, tridecane, 1,2,4-trimethylbenzene, and perchloroethene. Subsequent to the soil-gas survey, four areas determined to have elevated contaminant mass were selected and sampled for explosives and chemical agents. No detections of explosives or chemical agents above their respective method detection levels were found at any of the sampling locations. The same four locations that were sampled for explosives and chemical agents were selected for the collection of soil samples. A fifth location also was selected on the basis of the elevated contaminant mass of the soil-gas survey. No metals that exceeded the Regional Screening Levels for Industrial Soils as classified by the U.S. Environmental Protection Agency were detected at any of the five VATF locations. The soil samples also were compared to values from the ambient, uncontaminated (background) levels for soils in South Carolina, as classified by the South Carolina Department of Health and Environmental Control. Because South Carolina is adjacent to Georgia and the soils in the coastal plain are similar, these comparisons are valid. No similar values are available for Georgia to use for comparison purposes. The metals that were detected above the ambient background levels for South Carolina, as classified by the South Carolina Department of Health and Environmental Control, include aluminum, arsenic, barium, beryllium, calcium, chromium, copper, iron, lead, magnesium, manganese, nickel, potassium, sodium, and zinc.

Highly selective and sensitive method for Cu2 + detection based on chiroptical activity of L-Cysteine mediated Au nanorod assemblies

NASA Astrophysics Data System (ADS)

Abbasi, Shahryar; Khani, Hamzeh

2017-11-01

Herein, we demonstrated a simple and efficient method to detect Cu2 + based on amplified optical activity in the chiral nanoassemblies of gold nanorods (Au NRs). L-Cysteine can induce side-by-side or end-to-end assembly of Au NRs with an evident plasmonic circular dichroism (PCD) response due to coupling between surface plasmon resonances (SPR) of Au NRs and the chiral signal of L-Cys. Because of the obvious stronger plasmonic circular dichrosim (CD) response of the side-by-side assembly compared with the end-to-end assemblies, SS assembled Au NRs was selected as a sensitive platform and used for Cu2 + detection. In the presence of Cu2 +, Cu2 + can catalyze O2 oxidation of cysteine to cystine. With an increase in Cu2 + concentration, the L-Cysteine-mediated assembly of Au NRs decreased because of decrease in the free cysteine thiol groups, and the PCD signal decreased. Taking advantage of this method, Cu2 + could be detected in the concentration range of 20 pM-5 nM. Under optimal conditions, the calculated detection limit was found to be 7 pM.

PCR-based Methodologies Used to Detect and Differentiate the Burkholderia pseudomallei complex: B. pseudomallei, B. mallei, and B. thailandensis.

PubMed

Lowe, Woan; March, Jordon K; Bunnell, Annette J; O'Neill, Kim L; Robison, Richard A

2014-01-01

Methods for the rapid detection and differentiation of the Burkholderia pseudomallei complex comprising B. pseudomallei, B. mallei, and B. thailandensis, have been the topic of recent research due to the high degree of phenotypic and genotypic similarities of these species. B. pseudomallei and B. mallei are recognized by the CDC as tier 1 select agents. The high mortality rates of glanders and melioidosis, their potential use as bioweapons, and their low infectious dose, necessitate the need for rapid and accurate detection methods. Although B. thailandensis is generally avirulent in mammals, this species displays very similar phenotypic characteristics to that of B. pseudomallei. Optimal identification of these species remains problematic, due to the difficulty in developing a sensitive, selective, and accurate assay. The development of PCR technologies has revolutionized diagnostic testing and these detection methods have become popular due to their speed, sensitivity, and accuracy. The purpose of this review is to provide a comprehensive overview and evaluation of the advancements in PCR-based detection and differentiation methodologies for the B. pseudomallei complex, and examine their potential uses in diagnostic and environmental testing.

Highly selective and sensitive determination of Cu2+ in drink and water samples based on a 1,8-diaminonaphthalene derived fluorescent sensor

NASA Astrophysics Data System (ADS)

Sun, Tao; Li, Yang; Niu, Qingfen; Li, Tianduo; Liu, Yan

2018-04-01

A new simple and efficient fluorescent sensor L based on 1,8-diaminonaphthalene Schiff-base for highly sensitive and selective determination of Cu2+ in drink and water has been developed. This Cu2+-selective detection over other tested metal ions displayed an obvious color change from blue to colorless easily detected by naked eye. The detection limit is determined to be as low as 13.2 nM and the response time is very fast within 30 s. The 1:1 binding mechanism was well confirmed by fluorescence measurements, IR analysis and DFT calculations. Importantly, this sensor L was employed for quick detection of Cu2+ in drink and environmental water samples with satisfactory results, providing a simple, rapid, reliable and feasible Cu2+-sensing method.

Chemical Fingerprinting of Materials Developed Due to Environmental Issues

NASA Technical Reports Server (NTRS)

Smith, Doris A.; McCool, A. (Technical Monitor)

2000-01-01

Instrumental chemical analysis methods are developed and used to chemically fingerprint new and modified External Tank materials made necessary by changing environmental requirements. Chemical fingerprinting can detect and diagnose variations in material composition. To chemically characterize each material, fingerprint methods are selected from an extensive toolbox based on the material's chemistry and the ability of the specific methods to detect the material's critical ingredients. Fingerprint methods have been developed for a variety of materials including Thermal Protection System foams, adhesives, primers, and composites.

Decisions that Make a Difference in Detecting Differential Item Functioning

ERIC Educational Resources Information Center

Sireci, Stephen G.; Rios, Joseph A.

2013-01-01

There are numerous statistical procedures for detecting items that function differently across subgroups of examinees that take a test or survey. However, in endeavouring to detect items that may function differentially, selection of the statistical method is only one of many important decisions. In this article, we discuss the important decisions…

Method and apparatus for selectively detecting one of two immiscible liquids in the presence of the other liquid

DOEpatents

Cry, J.W.; Kirkham, R.R.; McBride, J.F.; Simmons, C.S.; Gee, G.W.

1990-02-06

Oil is detected in the presence of water by placing a translucent, porous body of hydrophobic material in contact with the oil and water and detecting the amount by which light incident on the body is attenuated on propagation through the body. 4 figs.

A parameter selection for Raman spectroscopy-based detection of chemical contaminants in food powders

USDA-ARS?s Scientific Manuscript database

Raman spectroscopy technique has proven to be a reliable method for detection of chemical contaminants in food ingredients and products. To detect each contaminant particle in a food sample, it is important to determine the effective depth of penetration of laser through the food sample and the corr...

Reconfigurable environmentally adaptive computing

NASA Technical Reports Server (NTRS)

Coxe, Robin L. (Inventor); Galica, Gary E. (Inventor)

2008-01-01

Described are methods and apparatus, including computer program products, for reconfigurable environmentally adaptive computing technology. An environmental signal representative of an external environmental condition is received. A processing configuration is automatically selected, based on the environmental signal, from a plurality of processing configurations. A reconfigurable processing element is reconfigured to operate according to the selected processing configuration. In some examples, the environmental condition is detected and the environmental signal is generated based on the detected condition.

[Selective removal of tannins from Polygonum cuspidatum extracts using collagen fiber adsorbent].

PubMed

Li, Juan; Liao, Xuepin; Shu, Xingxu; Shi, Bi

2010-03-01

To investigate the selective removal of tannins from Polygonum cuspidatum extracts by using collagen fiber adsorbent, and to evaluate the adsorption and desorption performances of collagen fiber adsorbent to tannins. The adsorbent was prepared from bovine skin collagen fiber through crosslinking reaction of glutaraldehyde, and then used for the selective removal of tannins from P. cuspidatum extracts. Gelatin-turbidity method, gelatin-ultraviolet spectrometry method and HPLC were used for detection of tannins in the solutions. Ethanol-water solutions with varying concentration were used to test their desorption ability of tannins in order to choose proper desorption solution. On the basis of batch experimental results, the column adsorption and desorption tests were carried out, by using gelatin-turbidity method for detection of tannins. The collagen fiber adsorbent exhibited excellent adsorption selectivity to tannins. It was found that tannins of P. cuspidatum were completely removed, while nearly no adsorption of active components (resveratrol as representative) was found. Moreover, the collagen fiber adsorbent could be regenerated by using 30% ethanol-water solution and then reused. The collagen fiber adsorbent can be considered as a promising material for selective removal of tannins from P. cuspidatum extracts.

Fluorescent microplate assay method for high-throughput detection of lipase transesterification activity.

PubMed

Zheng, Jianyong; Wei, Wei; Lan, Xing; Zhang, Yinjun; Wang, Zhao

2018-05-15

This study describes a sensitive and fluorescent microplate assay method to detect lipase transesterification activity. Lipase-catalyzed transesterification between butyryl 4-methyl umbelliferone (Bu-4-Mu) and methanol in tert-butanol was selected as the model reaction. The release of 4-methylumbelliferone (4-Mu) in the reaction was determined by detecting the fluorescence intensity at λ ex 330 nm and λ em 390 nm. Several lipases were used to investigate the accuracy and efficiency of the proposed method. Apparent Michaelis constant (Km) was calculated for transesterification between Bu-4-Mu and methanol by the lipases. The main advantages of the assay method include high sensitivity, inexpensive reagents, and simple detection process. Copyright © 2018 Elsevier Inc. All rights reserved.

Methods of automated absence seizure detection, interference by stimulation, and possibilities for prediction in genetic absence models.

PubMed

van Luijtelaar, Gilles; Lüttjohann, Annika; Makarov, Vladimir V; Maksimenko, Vladimir A; Koronovskii, Alexei A; Hramov, Alexander E

2016-02-15

Genetic rat models for childhood absence epilepsy have become instrumental in developing theories on the origin of absence epilepsy, the evaluation of new and experimental treatments, as well as in developing new methods for automatic seizure detection, prediction, and/or interference of seizures. Various methods for automated off and on-line analyses of ECoG in rodent models are reviewed, as well as data on how to interfere with the spike-wave discharges by different types of invasive and non-invasive electrical, magnetic, and optical brain stimulation. Also a new method for seizure prediction is proposed. Many selective and specific methods for off- and on-line spike-wave discharge detection seem excellent, with possibilities to overcome the issue of individual differences. Moreover, electrical deep brain stimulation is rather effective in interrupting ongoing spike-wave discharges with low stimulation intensity. A network based method is proposed for absence seizures prediction with a high sensitivity but a low selectivity. Solutions that prevent false alarms, integrated in a closed loop brain stimulation system open the ways for experimental seizure control. The presence of preictal cursor activity detected with state of the art time frequency and network analyses shows that spike-wave discharges are not caused by sudden and abrupt transitions but that there are detectable dynamic events. Their changes in time-space-frequency characteristics might yield new options for seizure prediction and seizure control. Copyright © 2015 Elsevier B.V. All rights reserved.

DNA aptamer-based colorimetric detection platform for Salmonella Enteritidis.

PubMed

Bayraç, Ceren; Eyidoğan, Füsun; Avni Öktem, Hüseyin

2017-12-15

Food safety is a major issue to protect public health and a key challenge is to find detection methods for identification of hazards in food. Food borne infections affects millions of people each year and among pathogens, Salmonella Enteritidis is most widely found bacteria causing food borne diseases. Therefore, simple, rapid, and specific detection methods are needed for food safety. In this study, we demonstrated the selection of DNA aptamers with high affinity and specificity against S. Enteritidis via Cell Systematic Evolution of Ligands by Exponential Enrichment (Cell-SELEX) and development of sandwich type aptamer-based colorimetric platforms for its detection. Two highly specific aptamers, crn-1 and crn-2, were developed through 12 rounds of selection with K d of 0.971µM and 0.309µM, respectively. Both aptamers were used to construct sandwich type capillary detection platforms. With the detection limit of 10 3 CFU/mL, crn-1 and crn-2 based platforms detected target bacteria specifically based on color change. This platform is also suitable for detection of S. Enteritidis in complex food matrix. Thus, this is the first to demonstrate use of Salmonella aptamers for development of the colorimetric aptamer-based detection platform in its identification and detection with naked eye in point-of-care. Copyright © 2017 Elsevier B.V. All rights reserved.

A statistical method (cross-validation) for bone loss region detection after spaceflight

PubMed Central

Zhao, Qian; Li, Wenjun; Li, Caixia; Chu, Philip W.; Kornak, John; Lang, Thomas F.

2010-01-01

Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes. PMID:20632144

A new strategy for in vivo spectral editing. Application to GABA editing using selective homonuclear polarization transfer spectroscopy

NASA Astrophysics Data System (ADS)

Shen, Jun; Yang, Jehoon; Choi, In-Young; Li, Shizhe Steve; Chen, Zhengguang

2004-10-01

A novel single-shot in vivo spectral editing method is proposed in which the signal to be detected, is regenerated anew from the thermal equilibrium magnetization of a source to which it is J-coupled. The thermal equilibrium magnetization of the signal to be detected together with those of overlapping signals are suppressed by single-shot gradient dephasing prior to the signal regeneration process. Application of this new strategy to in vivo GABA editing using selective homonuclear polarization transfer allows complete suppression of overlapping creatine and glutathione while detecting the GABA-4 methylene resonance at 3.02 ppm with an editing yield similar to that of conventional editing methods. The NAA methyl group at 2.02 ppm was simultaneously detected and can be used as an internal navigator echo for correcting the zero order phase and frequency shifts and as an internal reference for concentration. This new method has been demonstrated for robust in vivo GABA editing in the rat brain and for study of GABA synthesis after acute vigabatrin administration.

An efficient ratiometric fluorescence sensor based on metal-organic frameworks and quantum dots for highly selective detection of 6-mercaptopurine.

PubMed

Jin, Meng; Mou, Zhao-Li; Zhang, Rui-Ling; Liang, Si-Si; Zhang, Zhi-Qi

2017-05-15

The development of a simple and accurate quantitative method for the determination of 6-mercaptopurine (6-MP) is of great importance because of its serious side effects. Ratiometric fluorescence (RF) sensors are not subject to interference from environmental factors, and exhibit enhanced precision and accuracy. Therefore, a novel RF sensor for the selective detection of 6-MP was developed based on a dual-emission nanosensor. The nanosensor was fabricated by combining a blue-emission metal-organic framework (MOF) NH 2 -MIL-53(Al) (λ em =425nm) with green-emission 3-mercaptopropionic acid-capped CdTe quantum dots (MPA-CdTe QDs) (λ em =528nm) under a single excitation wavelength (335nm). Upon addition of 6-MP, the fluorescence of NH 2 -MIL-53(Al) in the nanohybrid was selectively quenched due to strong inner filter effects, while the fluorescence of the MPA-CdTe QDs was enhanced. The novel RF sensor exhibited higher selectivity towards 6-MP than CdTe QDs alone, and higher sensitivity than MOFs alone. 6-MP could be detected in the range of 0-50μM with a detection limit of 0.15μM (S/N=3). The developed sensor was applied for the determination of 6-MP in human urine samples and satisfactory results were obtained. Overall, a novel and efficient fluorescence-based method was developed for the detection of 6-MP in biosamples. Copyright © 2016 Elsevier B.V. All rights reserved.

Multi-residue screening of prioritised human pharmaceuticals, illicit drugs and bactericides in sediments and sludge.

PubMed

Langford, Katherine H; Reid, Malcolm; Thomas, Kevin V

2011-08-01

A robust multi-residue method was developed for the analysis of a selection of pharmaceutical compounds, illicit drugs and personal care product bactericides in sediments and sludges. Human pharmaceuticals were selected for analysis in Scottish sewage sludge and freshwater sediments based on prescription, physico-chemical and occurrence data. The method was suitable for the analysis of the selected illicit drugs amphetamine, benzoylecgonine, cocaine, and methamphetamine, the pharmaceuticals atenolol, bendroflumethiazide, carbamazepine, citalopram, diclofenac, fluoxetine, ibuprofen, and salbutamol, and the bactericides triclosan and triclocarban in sewage sludge and freshwater sediment. The method provided an overall recovery of between 56 and 128%, RSDs of between 2 and 19% and LODs of between 1 and 50 ng g(-1). Using the methodology the human pharmaceuticals atenolol, carbamazepine and citalopram and the bactericides triclosan and triclocarban were detected in Scottish sewage sludge. The illicit drugs cocaine, its metabolite benzoylecgonine, amphetamine and methamphetamine were not detected in any of the samples analysed. Triclosan and triclocarban were present at the highest concentrations with triclocarban detected in all but one sample and showing a pattern of co-occurrence in both sludge and sediment samples.

Gold nanoparticles generated through "green route" bind Hg2+ with a concomitant blue shift in plasmon absorption peak.

PubMed

Radhakumary, C; Sreenivasan, K

2011-07-21

We discuss here a quick, simple, economic and ecofriendly method through a completely green route for the selective detection of Hg(2+) in aqueous samples. Here we exploited the ability of chitosan to generate gold nanoparticles and subsequently to act as a stabilizer for the formed nanoparticles. When chitosan stabilized gold nanoparticles (CH-Au NPs) are interacted with Hg(2+) a blue shift for its localized surface plasmon resonance absorbance (LSPR) band is observed. The blue shift is reasoned to be due to the formation of a thin layer of mercury over gold. A concentration as low as 0.01 ppm to a maximum of 100 ppm Hg(2+) can be detected based on this blue shift of the CH-Au NPs. While all other reported methods demand complex reaction steps and costly chemicals, the method we reported here is a simple, rapid and selective approach for the detection of Hg(2+). Our results also show that the CH-Au NPs have excellent selectivity to Hg(2+) over common cations namely, Pb(2+), Cd(2+), Mn(2+), Fe(2+), Ag(1+), Ce(4+), Ni(2+), and Cu(2+).

Adaptive 4d Psi-Based Change Detection

NASA Astrophysics Data System (ADS)

Yang, Chia-Hsiang; Soergel, Uwe

2018-04-01

In a previous work, we proposed a PSI-based 4D change detection to detect disappearing and emerging PS points (3D) along with their occurrence dates (1D). Such change points are usually caused by anthropic events, e.g., building constructions in cities. This method first divides an entire SAR image stack into several subsets by a set of break dates. The PS points, which are selected based on their temporal coherences before or after a break date, are regarded as change candidates. Change points are then extracted from these candidates according to their change indices, which are modelled from their temporal coherences of divided image subsets. Finally, we check the evolution of the change indices for each change point to detect the break date that this change occurred. The experiment validated both feasibility and applicability of our method. However, two questions still remain. First, selection of temporal coherence threshold associates with a trade-off between quality and quantity of PS points. This selection is also crucial for the amount of change points in a more complex way. Second, heuristic selection of change index thresholds brings vulnerability and causes loss of change points. In this study, we adapt our approach to identify change points based on statistical characteristics of change indices rather than thresholding. The experiment validates this adaptive approach and shows increase of change points compared with the old version. In addition, we also explore and discuss optimal selection of temporal coherence threshold.

Application of surface enhanced Raman scattering and competitive adaptive reweighted sampling on detecting furfural dissolved in transformer oil

NASA Astrophysics Data System (ADS)

Chen, Weigen; Zou, Jingxin; Wan, Fu; Fan, Zhou; Yang, Dingkun

2018-03-01

Detecting the dissolving furfural in mineral oil is an essential technical method to evaluate the ageing condition of oil-paper insulation and the degradation of mechanical properties. Compared with the traditional detection method, Raman spectroscopy is obviously convenient and timesaving in operation. This study explored the method of applying surface enhanced Raman scattering (SERS) on quantitative analysis of the furfural dissolved in oil. Oil solution with different concentration of furfural were prepared and calibrated by high-performance liquid chromatography. Confocal laser Raman spectroscopy (CLRS) and SERS technology were employed to acquire Raman spectral data. Monte Carlo cross validation (MCCV) was used to eliminate the outliers in sample set, then competitive adaptive reweighted sampling (CARS) was developed to select an optimal combination of informative variables that most reflect the chemical properties of concern. Based on selected Raman spectral features, support vector machine (SVM) combined with particle swarm algorithm (PSO) was used to set up a furfural quantitative analysis model. Finally, the generalization ability and prediction precision of the established method were verified by the samples made in lab. In summary, a new spectral method is proposed to quickly detect furfural in oil, which lays a foundation for evaluating the ageing of oil-paper insulation in oil immersed electrical equipment.

Detection of Peanut Allergen Ara h 6 in Commercially Processed Foods using a Single-Walled Carbon Nanotube-Based Biosensor.

PubMed

Sobhan, Abdus; Oh, Jun-Hyun; Park, Mi-Kyung; Lee, Jinyoung

2018-06-12

Background : The peanut protein Arachis hypogaea (Ara h) 6 is one ofthe most serious food allergens that contributes to food-related, life-threatening problems worldwide. The extremely low allergic dose demands for more selective and rapid methods for detecting Ara h 6. Objective : The goal of this study was to develop a single-walled carbon nanotube (SWCNT)-based biosensor for the rapid detection of Ara h 6 in commercial food products. Methods : The detection principle of this biosensor was based on the binding of Ara h 6 to the anti-Ara h 6 antibody (pAb) through 1-pyrenibutanoic acid succinimidyl ester. The resistance difference (ΔR) was calculated via linear sweep voltammetry using a potentiostat. Results : The ∆R increased as the Ara h 6 concentrations increased above the range of 10 0 -10 7 pg/L. A specificity analysis showed that the anti-Ara h 6 pAb selectively interacted with Ara h 6 molecules in the buffer solution (pH 7.4). Conclusions : This research proposes that an SWCNT-based biosensor in self-assembly with antibodies could be an effective tool for the rapid detection of allergen proteins in food. Highlights : The developed biosensor exhibited higher sensitivity and selectivity. Application studies resulted in precise Ara h 6 detection in peanut-containing processed food.

Method Of Signal Amplification In Multi-Chromophore Luminescence Sensors

DOEpatents

Levitsky, Igor A.; Krivoshlykov, Sergei G.

2004-02-03

A fluorescence-based method for highly sensitive and selective detection of analyte molecules is proposed. The method employs the energy transfer between two or more fluorescent chromophores in a carefully selected polymer matrix. In one preferred embodiment, signal amplification has been achieved in the fluorescent sensing of dimethyl methylphosphonate (DMMP) using two dyes, 3-aminofluoranthene (AM) and Nile Red (NR), in a hydrogen bond acidic polymer matrix. The selected polymer matrix quenches the fluorescence of both dyes and shifts dye emission and absorption spectra relative to more inert matrices. Upon DMMP sorption, the AM fluorescence shifts to the red at the same time the NR absorption shifts to the blue, resulting in better band overlap and increased energy transfer between chromophores. In another preferred embodiment, the sensitive material is incorporated into an optical fiber system enabling efficient excitation of the dye and collecting the fluorescent signal form the sensitive material on the remote end of the system. The proposed method can be applied to multichromophore luminescence sensor systems incorporating N-chromophores leading to N-fold signal amplification and improved selectivity. The method can be used in all applications where highly sensitive detection of basic gases, such as dimethyl methylphosphonate (DMMP), Sarin, Soman and other chemical warfare agents having basic properties, is required, including environmental monitoring, chemical industry and medicine.

Overview of field gamma spectrometries based on Si-photomultiplier

NASA Astrophysics Data System (ADS)

Denisov, Viktor; Korotaev, Valery; Titov, Aleksandr; Blokhina, Anastasia; Kleshchenok, Maksim

2017-05-01

Design of optical-electronic devices and systems involves the selection of such technical patterns that under given initial requirements and conditions are optimal according to certain criteria. The original characteristic of the OES for any purpose, defining its most important feature ability is a threshold detection. Based on this property, will be achieved the required functional quality of the device or system. Therefore, the original criteria and optimization methods have to subordinate to the idea of a better detectability. Generally reduces to the problem of optimal selection of the expected (predetermined) signals in the predetermined observation conditions. Thus the main purpose of optimization of the system when calculating its detectability is the choice of circuits and components that provide the most effective selection of a target.

An improved method to detect correct protein folds using partial clustering.

PubMed

Zhou, Jianjun; Wishart, David S

2013-01-16

Structure-based clustering is commonly used to identify correct protein folds among candidate folds (also called decoys) generated by protein structure prediction programs. However, traditional clustering methods exhibit a poor runtime performance on large decoy sets. We hypothesized that a more efficient "partial" clustering approach in combination with an improved scoring scheme could significantly improve both the speed and performance of existing candidate selection methods. We propose a new scheme that performs rapid but incomplete clustering on protein decoys. Our method detects structurally similar decoys (measured using either C(α) RMSD or GDT-TS score) and extracts representatives from them without assigning every decoy to a cluster. We integrated our new clustering strategy with several different scoring functions to assess both the performance and speed in identifying correct or near-correct folds. Experimental results on 35 Rosetta decoy sets and 40 I-TASSER decoy sets show that our method can improve the correct fold detection rate as assessed by two different quality criteria. This improvement is significantly better than two recently published clustering methods, Durandal and Calibur-lite. Speed and efficiency testing shows that our method can handle much larger decoy sets and is up to 22 times faster than Durandal and Calibur-lite. The new method, named HS-Forest, avoids the computationally expensive task of clustering every decoy, yet still allows superior correct-fold selection. Its improved speed, efficiency and decoy-selection performance should enable structure prediction researchers to work with larger decoy sets and significantly improve their ab initio structure prediction performance.

An improved method to detect correct protein folds using partial clustering

PubMed Central

2013-01-01

Background Structure-based clustering is commonly used to identify correct protein folds among candidate folds (also called decoys) generated by protein structure prediction programs. However, traditional clustering methods exhibit a poor runtime performance on large decoy sets. We hypothesized that a more efficient “partial“ clustering approach in combination with an improved scoring scheme could significantly improve both the speed and performance of existing candidate selection methods. Results We propose a new scheme that performs rapid but incomplete clustering on protein decoys. Our method detects structurally similar decoys (measured using either Cα RMSD or GDT-TS score) and extracts representatives from them without assigning every decoy to a cluster. We integrated our new clustering strategy with several different scoring functions to assess both the performance and speed in identifying correct or near-correct folds. Experimental results on 35 Rosetta decoy sets and 40 I-TASSER decoy sets show that our method can improve the correct fold detection rate as assessed by two different quality criteria. This improvement is significantly better than two recently published clustering methods, Durandal and Calibur-lite. Speed and efficiency testing shows that our method can handle much larger decoy sets and is up to 22 times faster than Durandal and Calibur-lite. Conclusions The new method, named HS-Forest, avoids the computationally expensive task of clustering every decoy, yet still allows superior correct-fold selection. Its improved speed, efficiency and decoy-selection performance should enable structure prediction researchers to work with larger decoy sets and significantly improve their ab initio structure prediction performance. PMID:23323835

[Research on fast detecting tomato seedlings nitrogen content based on NIR characteristic spectrum selection].

PubMed

Wu, Jing-zhu; Wang, Feng-zhu; Wang, Li-li; Zhang, Xiao-chao; Mao, Wen-hua

2015-01-01

In order to improve the accuracy and robustness of detecting tomato seedlings nitrogen content based on near-infrared spectroscopy (NIR), 4 kinds of characteristic spectrum selecting methods were studied in the present paper, i. e. competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variables elimination (MCUVE), backward interval partial least squares (BiPLS) and synergy interval partial least squares (SiPLS). There were totally 60 tomato seedlings cultivated at 10 different nitrogen-treatment levels (urea concentration from 0 to 120 mg . L-1), with 6 samples at each nitrogen-treatment level. They are in different degrees of over nitrogen, moderate nitrogen, lack of nitrogen and no nitrogen status. Each sample leaves were collected to scan near-infrared spectroscopy from 12 500 to 3 600 cm-1. The quantitative models based on the above 4 methods were established. According to the experimental result, the calibration model based on CARS and MCUVE selecting methods show better performance than those based on BiPLS and SiPLS selecting methods, but their prediction ability is much lower than that of the latter. Among them, the model built by BiPLS has the best prediction performance. The correlation coefficient (r), root mean square error of prediction (RMSEP) and ratio of performance to standard derivate (RPD) is 0. 952 7, 0. 118 3 and 3. 291, respectively. Therefore, NIR technology combined with characteristic spectrum selecting methods can improve the model performance. But the characteristic spectrum selecting methods are not universal. For the built model based or single wavelength variables selection is more sensitive, it is more suitable for the uniform object. While the anti-interference ability of the model built based on wavelength interval selection is much stronger, it is more suitable for the uneven and poor reproducibility object. Therefore, the characteristic spectrum selection will only play a better role in building model, combined with the consideration of sample state and the model indexes.

[On necessity to modify biochemical methods for detecting organophosphorus componds in chemical weapons extinction objects (review of literature)].

PubMed

Prokofieva, D S; Shmurak, V I; Sadovnikov, S V; Gontcharov, N V

2015-01-01

The article covers problems of biochemical methods assessing organophosphorus toxic compounds in objects of chemical weapons extinction. The authors present results of works developing new, more specific and selective biochemical methods.

Reference set for performance testing of pediatric vaccine safety signal detection methods and systems.

PubMed

Brauchli Pernus, Yolanda; Nan, Cassandra; Verstraeten, Thomas; Pedenko, Mariia; Osokogu, Osemeke U; Weibel, Daniel; Sturkenboom, Miriam; Bonhoeffer, Jan

2016-12-12

Safety signal detection in spontaneous reporting system databases and electronic healthcare records is key to detection of previously unknown adverse events following immunization. Various statistical methods for signal detection in these different datasources have been developed, however none are geared to the pediatric population and none specifically to vaccines. A reference set comprising pediatric vaccine-adverse event pairs is required for reliable performance testing of statistical methods within and across data sources. The study was conducted within the context of the Global Research in Paediatrics (GRiP) project, as part of the seventh framework programme (FP7) of the European Commission. Criteria for the selection of vaccines considered in the reference set were routine and global use in the pediatric population. Adverse events were primarily selected based on importance. Outcome based systematic literature searches were performed for all identified vaccine-adverse event pairs and complemented by expert committee reports, evidence based decision support systems (e.g. Micromedex), and summaries of product characteristics. Classification into positive (PC) and negative control (NC) pairs was performed by two independent reviewers according to a pre-defined algorithm and discussed for consensus in case of disagreement. We selected 13 vaccines and 14 adverse events to be included in the reference set. From a total of 182 vaccine-adverse event pairs, we classified 18 as PC, 113 as NC and 51 as unclassifiable. Most classifications (91) were based on literature review, 45 were based on expert committee reports, and for 46 vaccine-adverse event pairs, an underlying pathomechanism was not plausible classifying the association as NC. A reference set of vaccine-adverse event pairs was developed. We propose its use for comparing signal detection methods and systems in the pediatric population. Published by Elsevier Ltd.

Can machine learning complement traditional medical device surveillance? A case study of dual-chamber implantable cardioverter–defibrillators

PubMed Central

Ross, Joseph S; Bates, Jonathan; Parzynski, Craig S; Akar, Joseph G; Curtis, Jeptha P; Desai, Nihar R; Freeman, James V; Gamble, Ginger M; Kuntz, Richard; Li, Shu-Xia; Marinac-Dabic, Danica; Masoudi, Frederick A; Normand, Sharon-Lise T; Ranasinghe, Isuru; Shaw, Richard E; Krumholz, Harlan M

2017-01-01

Background Machine learning methods may complement traditional analytic methods for medical device surveillance. Methods and results Using data from the National Cardiovascular Data Registry for implantable cardioverter–defibrillators (ICDs) linked to Medicare administrative claims for longitudinal follow-up, we applied three statistical approaches to safety-signal detection for commonly used dual-chamber ICDs that used two propensity score (PS) models: one specified by subject-matter experts (PS-SME), and the other one by machine learning-based selection (PS-ML). The first approach used PS-SME and cumulative incidence (time-to-event), the second approach used PS-SME and cumulative risk (Data Extraction and Longitudinal Trend Analysis [DELTA]), and the third approach used PS-ML and cumulative risk (embedded feature selection). Safety-signal surveillance was conducted for eleven dual-chamber ICD models implanted at least 2,000 times over 3 years. Between 2006 and 2010, there were 71,948 Medicare fee-for-service beneficiaries who received dual-chamber ICDs. Cumulative device-specific unadjusted 3-year event rates varied for three surveyed safety signals: death from any cause, 12.8%–20.9%; nonfatal ICD-related adverse events, 19.3%–26.3%; and death from any cause or nonfatal ICD-related adverse event, 27.1%–37.6%. Agreement among safety signals detected/not detected between the time-to-event and DELTA approaches was 90.9% (360 of 396, k=0.068), between the time-to-event and embedded feature-selection approaches was 91.7% (363 of 396, k=−0.028), and between the DELTA and embedded feature selection approaches was 88.1% (349 of 396, k=−0.042). Conclusion Three statistical approaches, including one machine learning method, identified important safety signals, but without exact agreement. Ensemble methods may be needed to detect all safety signals for further evaluation during medical device surveillance. PMID:28860874

Evaluation of redundancy analysis to identify signatures of local adaptation.

PubMed

Capblancq, Thibaut; Luu, Keurcien; Blum, Michael G B; Bazin, Eric

2018-05-26

Ordination is a common tool in ecology that aims at representing complex biological information in a reduced space. In landscape genetics, ordination methods such as principal component analysis (PCA) have been used to detect adaptive variation based on genomic data. Taking advantage of environmental data in addition to genotype data, redundancy analysis (RDA) is another ordination approach that is useful to detect adaptive variation. This paper aims at proposing a test statistic based on RDA to search for loci under selection. We compare redundancy analysis to pcadapt, which is a nonconstrained ordination method, and to a latent factor mixed model (LFMM), which is a univariate genotype-environment association method. Individual-based simulations identify evolutionary scenarios where RDA genome scans have a greater statistical power than genome scans based on PCA. By constraining the analysis with environmental variables, RDA performs better than PCA in identifying adaptive variation when selection gradients are weakly correlated with population structure. Additionally, we show that if RDA and LFMM have a similar power to identify genetic markers associated with environmental variables, the RDA-based procedure has the advantage to identify the main selective gradients as a combination of environmental variables. To give a concrete illustration of RDA in population genomics, we apply this method to the detection of outliers and selective gradients on an SNP data set of Populus trichocarpa (Geraldes et al., 2013). The RDA-based approach identifies the main selective gradient contrasting southern and coastal populations to northern and continental populations in the northwestern American coast. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Fast detection of peroxidase (POD) activity in tomato leaves which infected with Botrytis cinerea using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Kong, Wenwen; Liu, Fei; Zhang, Chu; Bao, Yidan; Yu, Jiajia; He, Yong

2014-01-01

Tomatoes are cultivated around the world and gray mold is one of its most prominent and destructive diseases. An early disease detection method can decrease losses caused by plant diseases and prevent the spread of diseases. The activity of peroxidase (POD) is very important indicator of disease stress for plants. The objective of this study is to examine the possibility of fast detection of POD activity in tomato leaves which infected with Botrytis cinerea using hyperspectral imaging data. Five pre-treatment methods were investigated. Genetic algorithm-partial least squares (GA-PLS) was applied to select optimal wavelengths. A new fast learning neural algorithm named extreme learning machine (ELM) was employed as multivariate analytical tool in this study. 21 optimal wavelengths were selected by GA-PLS and used as inputs of three calibration models. The optimal prediction result was achieved by ELM model with selected wavelengths, and the r and RMSEP in validation were 0.8647 and 465.9880 respectively. The results indicated that hyperspectral imaging could be considered as a valuable tool for POD activity prediction. The selected wavelengths could be potential resources for instrument development.

A primitive study of voxel feature generation by multiple stacked denoising autoencoders for detecting cerebral aneurysms on MRA

NASA Astrophysics Data System (ADS)

Nemoto, Mitsutaka; Hayashi, Naoto; Hanaoka, Shouhei; Nomura, Yukihiro; Miki, Soichiro; Yoshikawa, Takeharu; Ohtomo, Kuni

2016-03-01

The purpose of this study is to evaluate the feasibility of a novel feature generation, which is based on multiple deep neural networks (DNNs) with boosting, for computer-assisted detection (CADe). It is hard and time-consuming to optimize the hyperparameters for DNNs such as stacked denoising autoencoder (SdA). The proposed method allows using SdA based features without the burden of the hyperparameter setting. The proposed method was evaluated by an application for detecting cerebral aneurysms on magnetic resonance angiogram (MRA). A baseline CADe process included four components; scaling, candidate area limitation, candidate detection, and candidate classification. Proposed feature generation method was applied to extract the optimal features for candidate classification. Proposed method only required setting range of the hyperparameters for SdA. The optimal feature set was selected from a large quantity of SdA based features by multiple SdAs, each of which was trained using different hyperparameter set. The feature selection was operated through ada-boost ensemble learning method. Training of the baseline CADe process and proposed feature generation were operated with 200 MRA cases, and the evaluation was performed with 100 MRA cases. Proposed method successfully provided SdA based features just setting the range of some hyperparameters for SdA. The CADe process by using both previous voxel features and SdA based features had the best performance with 0.838 of an area under ROC curve and 0.312 of ANODE score. The results showed that proposed method was effective in the application for detecting cerebral aneurysms on MRA.

Chemosensors for detection of nitroaromatic compounds (explosives)

NASA Astrophysics Data System (ADS)

Zyryanov, G. V.; Kopchuk, D. S.; Kovalev, I. S.; Nosova, E. V.; Rusinov, V. L.; Chupakhin, O. N.

2014-09-01

The key types of low-molecular-mass chemosensors for the detection of nitroaromatic compounds representing energetic substances (explosives) are analyzed. The coordination and chemical properties of these chemosensors and structural features of their complexes with nitroaromatic compounds are considered. The causes and methods for attaining high selectivity of recognition are demonstrated. The primary attention is paid to the use of low-molecular-mass chemosensors for visual detection of explosives of this class by colorimetric and photometric methods. Examples of using photo- and chemiluminescence for this purpose are described. A separate section is devoted to electrochemical methods of detection of nitroaromatic compounds. Data published from 2000 to 2014 are mainly covered. The bibliography includes 245 references.

Nitric oxide selective electrodes.

PubMed

Davies, Ian R; Zhang, Xueji

2008-01-01

Since nitric oxide (NO) was identified as the endothelial-derived relaxing factor in the late 1980s, many approaches have attempted to provide an adequate means for measuring physiological levels of NO. Although several techniques have been successful in achieving this aim, the electrochemical method has proved the only technique that can reliably measure physiological levels of NO in vitro, in vivo, and in real time. We describe here the development of electrochemical sensors for NO, including the fabrication of sensors, the detection principle, calibration, detection limits, selectivity, and response time. Furthermore, we look at the many experimental applications where NO selective electrodes have been successfully used.

The determination of fenspiride in human plasma and urine by liquid chromatography with electrochemical or ultraviolet detection.

PubMed

Sauveur, C; Baune, A; Vergnes, N; Jeanniot, J P

1989-01-01

A selective and sensitive method for the determination of fenspiride in biological fluids is described. The method involves liquid-liquid extraction followed by separation on a reversed-phase column with electrochemical detection for low levels of the drug in plasma (less than or equal to 100 ng ml-1) or UV absorption for higher concentrations in plasma or urine. The method is suitable for pharmacokinetic analyses and drug monitoring studies.

A SVM-based quantitative fMRI method for resting-state functional network detection.

PubMed

Song, Xiaomu; Chen, Nan-kuei

2014-09-01

Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Identifying or measuring selected substances or toxins in a subject using resonant raman signals

NASA Technical Reports Server (NTRS)

Borchert, Mark S. (Inventor); Lambert, James L. (Inventor)

2005-01-01

Methods and systems of the present invention identify the presence of and/or the concentration of a selected analyte in a subject by: (a) illuminating a selected region of the eye of a subject with an optical excitation beam, wherein the excitation beam wavelength is selected to generate a resonant Raman spectrum of the selected analyte with a signal strength that is at least 100 times greater than Raman spectrums generated by non-resonant wavelengths and/or relative to signals of normal constituents present in the selected region of the eye; (b) detecting a resonant Raman spectrum corresponding to the selected illuminated region of the eye; and (c) identifying the presence, absence and/or the concentration of the selected analyte in the subject based on said detecting step. The apparatus may also be configured to be able to obtain biometric data of the eye to identify (confirm the identity of) the subject.

[The clinical value of sentinel lymph node detection in laryngeal and hypopharyngeal carcinoma patients with clinically negative neck by methylene blue method and radiolabeled tracer method].

PubMed

Zhao, Xin; Xiao, Dajiang; Ni, Jianming; Zhu, Guochen; Yuan, Yuan; Xu, Ting; Zhang, Yongsheng

2014-11-01

To investigate the clinical value of sentinel lymph node (SLN) detection in laryngeal and hypopharyngeal carcinoma patients with clinically negative neck (cN0) by methylene blue method, radiolabeled tracer method and combination of these two methods. Thirty-three patients with cN0 laryngeal carcinoma and six patients with cN0 hypopharyngeal carcinoma underwent SLN detection using both of methylene blue and radiolabeled tracer method. All these patients were accepted received the injection of radioactive isotope 99 Tc(m)-sulfur colloid (SC) and methylene blue into the carcinoma before surgery, then all these patients underwent intraopertive lymphatic mapping with a handheld gamma-detecting probe and blue-dyed SLN. After the mapping of SLN, selected neck dissections and tumor resections were peformed. The results of SLN detection by radiolabeled tracer, dye and combination of both methods were compared. The detection rate of SLN by radiolabeled tracer, methylene blue and combined method were 89.7%, 79.5%, 92.3% respectively. The number of detected SLN was significantly different between radiolabeled tracer method and combined method, and also between methylene blue method and combined method. The detection rate of methylene blue and radiolabeled tracer method were significantly different from combined method (P < 0.05). Nine patients were found to have lymph node metastasis by final pathological examination. The accuracy and negative rate of SLN detection of the combined method were 97.2% and 11.1%. The combined method using radiolabeled tracer and methylene blue can improve the detection rate and accuracy of sentinel lymph node detection. Furthermore, sentinel lymph node detection can accurately represent the cervical lymph node status in cN0 laryngeal and hypopharyngeal carcinoma.

Quantitative Method of Measuring Metastatic Activity

NASA Technical Reports Server (NTRS)

Morrison, Dennis R. (Inventor)

1999-01-01

The metastatic potential of tumors can be evaluated by the quantitative detection of urokinase and DNA. The cell sample selected for examination is analyzed for the presence of high levels of urokinase and abnormal DNA using analytical flow cytometry and digital image analysis. Other factors such as membrane associated uroldnase, increased DNA synthesis rates and certain receptors can be used in the method for detection of potentially invasive tumors.

A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks.

PubMed

Alauthaman, Mohammad; Aslam, Nauman; Zhang, Li; Alasem, Rafe; Hossain, M A

2018-01-01

In recent years, Botnets have been adopted as a popular method to carry and spread many malicious codes on the Internet. These malicious codes pave the way to execute many fraudulent activities including spam mail, distributed denial-of-service attacks and click fraud. While many Botnets are set up using centralized communication architecture, the peer-to-peer (P2P) Botnets can adopt a decentralized architecture using an overlay network for exchanging command and control data making their detection even more difficult. This work presents a method of P2P Bot detection based on an adaptive multilayer feed-forward neural network in cooperation with decision trees. A classification and regression tree is applied as a feature selection technique to select relevant features. With these features, a multilayer feed-forward neural network training model is created using a resilient back-propagation learning algorithm. A comparison of feature set selection based on the decision tree, principal component analysis and the ReliefF algorithm indicated that the neural network model with features selection based on decision tree has a better identification accuracy along with lower rates of false positives. The usefulness of the proposed approach is demonstrated by conducting experiments on real network traffic datasets. In these experiments, an average detection rate of 99.08 % with false positive rate of 0.75 % was observed.

Antidepressants detection and quantification in whole blood samples by GC-MS/MS, for forensic purposes.

PubMed

Truta, Liliana; Castro, André L; Tarelho, Sónia; Costa, Pedro; Sales, M Goreti F; Teixeira, Helena M

2016-09-05

Depression is among the most prevalent psychiatric disorders of our society, leading to an increase in antidepressant drug consumption that needs to be accurately determined in whole blood samples in Forensic Toxicology Laboratories. For this purpose, this work presents a new gas chromatography tandem mass spectrometry (GC-MS/MS) method targeting the simultaneous and rapid determination of 14 common Antidepressants in whole blood: 13 Antidepressants (amitriptyline, citalopram, clomipramine, dothiepin, fluoxetine, imipramine, mianserin, mirtazapine, nortryptiline, paroxetine, sertraline, trimipramine and venlafaxine) and 1 Metabolite (N-desmethylclomipramine). Solid-phase extraction was used prior to chromatographic separation. Chromatographic and MS/MS parameters were selected to improve sensitivity, peak resolution and unequivocal identification of the eluted analyte. The detection was performed on a triple quadrupole tandem MS in selected ion monitoring (SIM) mode in tandem, using electronic impact ionization. Clomipramine-D3 and trimipramine-D3 were used as deutered internal standards. The validation parameters included linearity, limits of detection, lower limit of quantification, selectivity/specificity, extraction efficiency, carry-over, precision and robustness, and followed internationally accepted guidelines. Limits of quantification and detection were lower than therapeutic and sub-therapeutic concentration ranges. Overall, the method offered good selectivity, robustness and quick response (<16min) for typical concentration ranges, both for therapeutic and lethal levels. Copyright © 2016 Elsevier B.V. All rights reserved.

Robust statistical methods for hit selection in RNA interference high-throughput screening experiments.

PubMed

Zhang, Xiaohua Douglas; Yang, Xiting Cindy; Chung, Namjin; Gates, Adam; Stec, Erica; Kunapuli, Priya; Holder, Dan J; Ferrer, Marc; Espeseth, Amy S

2006-04-01

RNA interference (RNAi) high-throughput screening (HTS) experiments carried out using large (>5000 short interfering [si]RNA) libraries generate a huge amount of data. In order to use these data to identify the most effective siRNAs tested, it is critical to adopt and develop appropriate statistical methods. To address the questions in hit selection of RNAi HTS, we proposed a quartile-based method which is robust to outliers, true hits and nonsymmetrical data. We compared it with the more traditional tests, mean +/- k standard deviation (SD) and median +/- 3 median of absolute deviation (MAD). The results suggested that the quartile-based method selected more hits than mean +/- k SD under the same preset error rate. The number of hits selected by median +/- k MAD was close to that by the quartile-based method. Further analysis suggested that the quartile-based method had the greatest power in detecting true hits, especially weak or moderate true hits. Our investigation also suggested that platewise analysis (determining effective siRNAs on a plate-by-plate basis) can adjust for systematic errors in different plates, while an experimentwise analysis, in which effective siRNAs are identified in an analysis of the entire experiment, cannot. However, experimentwise analysis may detect a cluster of true positive hits placed together in one or several plates, while platewise analysis may not. To display hit selection results, we designed a specific figure called a plate-well series plot. We thus suggest the following strategy for hit selection in RNAi HTS experiments. First, choose the quartile-based method, or median +/- k MAD, for identifying effective siRNAs. Second, perform the chosen method experimentwise on transformed/normalized data, such as percentage inhibition, to check the possibility of hit clusters. If a cluster of selected hits are observed, repeat the analysis based on untransformed data to determine whether the cluster is due to an artifact in the data. If no clusters of hits are observed, select hits by performing platewise analysis on transformed data. Third, adopt the plate-well series plot to visualize both the data and the hit selection results, as well as to check for artifacts.

Sea Ice Detection Based on an Improved Similarity Measurement Method Using Hyperspectral Data.

PubMed

Han, Yanling; Li, Jue; Zhang, Yun; Hong, Zhonghua; Wang, Jing

2017-05-15

Hyperspectral remote sensing technology can acquire nearly continuous spectrum information and rich sea ice image information, thus providing an important means of sea ice detection. However, the correlation and redundancy among hyperspectral bands reduce the accuracy of traditional sea ice detection methods. Based on the spectral characteristics of sea ice, this study presents an improved similarity measurement method based on linear prediction (ISMLP) to detect sea ice. First, the first original band with a large amount of information is determined based on mutual information theory. Subsequently, a second original band with the least similarity is chosen by the spectral correlation measuring method. Finally, subsequent bands are selected through the linear prediction method, and a support vector machine classifier model is applied to classify sea ice. In experiments performed on images of Baffin Bay and Bohai Bay, comparative analyses were conducted to compare the proposed method and traditional sea ice detection methods. Our proposed ISMLP method achieved the highest classification accuracies (91.18% and 94.22%) in both experiments. From these results the ISMLP method exhibits better performance overall than other methods and can be effectively applied to hyperspectral sea ice detection.

Sea Ice Detection Based on an Improved Similarity Measurement Method Using Hyperspectral Data

PubMed Central

Han, Yanling; Li, Jue; Zhang, Yun; Hong, Zhonghua; Wang, Jing

2017-01-01

Hyperspectral remote sensing technology can acquire nearly continuous spectrum information and rich sea ice image information, thus providing an important means of sea ice detection. However, the correlation and redundancy among hyperspectral bands reduce the accuracy of traditional sea ice detection methods. Based on the spectral characteristics of sea ice, this study presents an improved similarity measurement method based on linear prediction (ISMLP) to detect sea ice. First, the first original band with a large amount of information is determined based on mutual information theory. Subsequently, a second original band with the least similarity is chosen by the spectral correlation measuring method. Finally, subsequent bands are selected through the linear prediction method, and a support vector machine classifier model is applied to classify sea ice. In experiments performed on images of Baffin Bay and Bohai Bay, comparative analyses were conducted to compare the proposed method and traditional sea ice detection methods. Our proposed ISMLP method achieved the highest classification accuracies (91.18% and 94.22%) in both experiments. From these results the ISMLP method exhibits better performance overall than other methods and can be effectively applied to hyperspectral sea ice detection. PMID:28505135

AOTF hyperspectral microscope imaging for foodborne bacteria detection

USDA-ARS?s Scientific Manuscript database

Food safety is an important public health issue worldwide. Researchers have developed many different methods for detecting foodborne pathogens; however, most technologies currently being used have limitations, in terms of speed, sensitivity and selectivity, for practical use in the food industry. Ac...

Meningococcal X polysaccharide quantification by high-performance anion-exchange chromatography using synthetic N-acetylglucosamine-4-phosphate as standard.

PubMed

Micoli, F; Adamo, R; Proietti, D; Gavini, M; Romano, M R; MacLennan, C A; Costantino, P; Berti, F

2013-11-15

A method for meningococcal X (MenX) polysaccharide quantification by high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD) is described. The polysaccharide is hydrolyzed by strong acidic treatment, and the peak of glucosamine-4-phosphate (4P-GlcN) is detected and measured after chromatography. In the selected conditions of hydrolysis, 4P-GlcN is the prevalent species formed, with GlcN detected for less than 5% in moles. As standard for the analysis, the monomeric unit of MenX polysaccharide, N-acetylglucosamine-4-phosphate (4P-GlcNAc), was used. This method for MenX quantification is highly selective and sensitive, and it constitutes an important analytical tool for the development of a conjugate vaccine against MenX. Copyright © 2013 Elsevier Inc. All rights reserved.

New highly sensitive and selective fluorescent terbium complex for the detection of aluminium ions

NASA Astrophysics Data System (ADS)

Anwar, Zeinab M.; Ibrahim, Ibrahim A.; Kamel, Rasha M.; Abdel-Salam, Enas T.; El-Asfoury, Mahmoud H.

2018-02-01

A highly sensitive and selective spectrofluorimetric method has been developed for the rapid determination of aluminium ions. The method is based on the fluorescence enhancement of Tb complex with 3,4-dimetyl-thieno[2,3 b] thiophene-2,5-dicarboxylic acid (LN) after addition trace amount of aluminium ions. The fluorescence of the probe is monitored at the characteristic an emission wavelength of Tb3+ at 545 nm with excitation at 300 nm. Optimum detection was obtained in DMSO-H2O (2:8, v/v) and at pH 6.0 using MOPSO buffer. Under the optimum conditions linear calibration curves were obtained from 0.5 μ mol L-1 to 20 μ mol L-1 with detection limit of 0.1 μ mol L-1. Effect of interference of other ions was studied.

Highly selective colorimetric bacteria sensing based on protein-capped nanoparticles.

PubMed

Qiu, Suyan; Lin, Zhenyu; Zhou, Yaomin; Wang, Donggen; Yuan, Lijuan; Wei, Yihua; Dai, Tingcan; Luo, Linguang; Chen, Guonan

2015-02-21

A rapid and cost-effective colorimetric sensor has been developed for the detection of bacteria (Bacillus subtilis was selected as an example). The sensor was designed to rely on lysozyme-capped AuNPs with the advantages of effective amplification and high specificity. In the sensing system, lysozyme was able to bind strongly to Bacillus subtilis, which effectively induced a color change of the solution from light purple to purplish red. The lowest concentration of Bacillus subtilis detectable by the naked eye was 4.5 × 10(3) colony-forming units (CFU) mL(-1). Similar results were discernable from UV-Vis absorption measurements. A good specificity was observed through a statistical analysis method using the SPSS software (version 17.0). This simple colorimetric sensor may therefore be a rapid and specific method for a bacterial detection assay in complex samples.

Bond-selective photoacoustic imaging by converting molecular vibration into acoustic waves

PubMed Central

Hui, Jie; Li, Rui; Phillips, Evan H.; Goergen, Craig J.; Sturek, Michael; Cheng, Ji-Xin

2016-01-01

The quantized vibration of chemical bonds provides a way of detecting specific molecules in a complex tissue environment. Unlike pure optical methods, for which imaging depth is limited to a few hundred micrometers by significant optical scattering, photoacoustic detection of vibrational absorption breaks through the optical diffusion limit by taking advantage of diffused photons and weak acoustic scattering. Key features of this method include both high scalability of imaging depth from a few millimeters to a few centimeters and chemical bond selectivity as a novel contrast mechanism for photoacoustic imaging. Its biomedical applications spans detection of white matter loss and regeneration, assessment of breast tumor margins, and diagnosis of vulnerable atherosclerotic plaques. This review provides an overview of the recent advances made in vibration-based photoacoustic imaging and various biomedical applications enabled by this new technology. PMID:27069873

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

PubMed

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

2018-07-05

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

Assessment of groundwater, soil-gas, and soil contamination at the Vietnam Armor Training Facility, Fort Gordon, Georgia, 2009-2011

USGS Publications Warehouse

Guimaraes, Wladmir B.; Falls, W. Fred; Caldwell, Andral W.; Ratliff, W. Hagan; Wellborn, John B.; Landmeyer, James E.

2012-01-01

The U.S. Geological Survey, in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon, Georgia, assessed the groundwater, soil gas, and soil for contaminants at the Vietnam Armor Training Facility (VATF) at Fort Gordon, from October 2009 to September 2011. The assessment included the detection of organic compounds in the groundwater and soil gas, and inorganic compounds in the soil. In addition, organic contaminant assessment included organic compounds classified as explosives and chemical agents in selected areas. The assessment was conducted to provide environmental contamination data to the U.S. Army at Fort Gordon pursuant to requirements of the Resource Conservation and Recovery Act Part B Hazardous Waste Permit process. This report is a revision of "Assessment of soil-gas, surface-water, and soil contamination at the Vietnam Armor Training Facility, Fort Gordon, Georgia, 2009-2010," Open-File Report 2011-1200, and supersedes that report to include results of additional samples collected in July 2011. Four passive samplers were deployed in groundwater wells at the VATF in Fort Gordon. Total petroleum hydrocarbons and benzene and octane were detected above the method detection level at all four wells. The only other volatile organic compounds detected above their method detection level were undecane and pentadecane, which were detected in two of the four wells. Soil-gas samplers were deployed at 72 locations in a grid pattern across the VATF on June 3, 2010, and then later retrieved on June 9, 2010. Total petroleum hydrocarbons were detected in 71 of the 72 samplers (one sampler was destroyed in the field and not analyzed) at levels above the method detection level, and the combined mass of benzene, toluene, ethylbenzene, and total xylene (BTEX) was detected above the detection level in 31 of the 71 samplers that were analyzed. Other volatile organic compounds detected above their respective method detection levels were naphthalene, 2-methyl-naphthalene, tridecane, 1,2,4-trimethylbenzene, and perchloroethylene. After the results of the 71 soil-gas samplers were received, 31 additional passive soil-gas samplers were deployed on July 14, 2011, and retrieved on July 18, 2011. These 31 samplers were deployed on a larger areal scale to better define the extent of the contamination. Total petroleum hydrocarbons were detected above their method detection level at all 31 samplers, whereas BTEX was detected above its method detection level at 17 of the 31 samplers. Other organic compounds detected above their method detection levels were naphthalene, 2-methyl-naphthalene, octane, undecane, tridecane, pentadecane, 1,2,4-trimethylbenzene, 1,3,5-trimethylbenzene, chloroform, and perchloroethylene. Subsequent to the 2010 soil-gas survey, four areas determined to have elevated contaminant mass were selected and sampled for explosives and chemical agents. No detections of explosives or chemical agents above their respective method detection levels were found at any of the sampling locations. The same four locations that were sampled for explosives and chemical agents were selected for the collection of soil samples. A fifth location also was selected on the basis of the elevated contaminant mass of the soil-gas survey. No metals that exceeded the Regional Screening Levels for Industrial Soils, as classified by the U.S. Environmental Protection Agency, were detected at any of the five VATF locations. The soil samples also were compared to values from the ambient, uncontaminated (background) levels for soils in South Carolina, as classified by the South Carolina Department of Health and Environmental Control. Because South Carolina is adjacent to Georgia and the soils in the Coastal Plain are similar, these comparisons are valid. No similar values are available for Georgia to use for comparison purposes. The metals that were detected above the ambient background levels for South Carolina, as classified by the South Carolina Department of Health and Environmental Control, include aluminum, arsenic, barium, beryllium, calcium, chromium, copper, iron, lead, magnesium, manganese, nickel, potassium, sodium, and zinc.

Posture Detection Based on Smart Cushion for Wheelchair Users

PubMed Central

Ma, Congcong; Li, Wenfeng; Gravina, Raffaele; Fortino, Giancarlo

2017-01-01

The postures of wheelchair users can reveal their sitting habit, mood, and even predict health risks such as pressure ulcers or lower back pain. Mining the hidden information of the postures can reveal their wellness and general health conditions. In this paper, a cushion-based posture recognition system is used to process pressure sensor signals for the detection of user’s posture in the wheelchair. The proposed posture detection method is composed of three main steps: data level classification for posture detection, backward selection of sensor configuration, and recognition results compared with previous literature. Five supervised classification techniques—Decision Tree (J48), Support Vector Machines (SVM), Multilayer Perceptron (MLP), Naive Bayes, and k-Nearest Neighbor (k-NN)—are compared in terms of classification accuracy, precision, recall, and F-measure. Results indicate that the J48 classifier provides the highest accuracy compared to other techniques. The backward selection method was used to determine the best sensor deployment configuration of the wheelchair. Several kinds of pressure sensor deployments are compared and our new method of deployment is shown to better detect postures of the wheelchair users. Performance analysis also took into account the Body Mass Index (BMI), useful for evaluating the robustness of the method across individual physical differences. Results show that our proposed sensor deployment is effective, achieving 99.47% posture recognition accuracy. Our proposed method is very competitive for posture recognition and robust in comparison with other former research. Accurate posture detection represents a fundamental basic block to develop several applications, including fatigue estimation and activity level assessment. PMID:28353684

EPA Method 200.8: Determination of Trace Elements in Waters and Wastes by Inductively Coupled Plasma-Mass Spectrometry

EPA Pesticide Factsheets

\\tEPA’s Selected Analytical Methods for Environmental Remediation and Recovery (SAM) lists this method for preparation and analysis of drinking water samples to detect and measure compounds containing arsenic, thallium and vanadium.

Practical Approaches for Detecting Selection in Microbial Genomes.

PubMed

Hedge, Jessica; Wilson, Daniel J

2016-02-01

Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers through the fundamentals underpinning popular methods for measuring selection in pathogens. These methods are transferable to a wide variety of organisms, and the exercises provided are designed for researchers with any level of programming experience.

ELEGANT ENVIRONMENTAL IMMUNOASSAYS

EPA Science Inventory

Immunochemical methods are based on selective antibodies directed to a particular target analyte. The specific binding between antibody and analyte can be used for detection and quantitation. Methods such as the enzyme-linked immunosorbent assay (ELISA) can provide a sensitiv...

The Empirical Selection of Anchor Items Using a Multistage Approach

ERIC Educational Resources Information Center

Craig, Brandon

2017-01-01

The purpose of this study was to determine if using a multistage approach for the empirical selection of anchor items would lead to more accurate DIF detection rates than the anchor selection methods proposed by Kopf, Zeileis, & Strobl (2015b). A simulation study was conducted in which the sample size, percentage of DIF, and balance of DIF…

Automatic Detection of Seizures with Applications

NASA Technical Reports Server (NTRS)

Olsen, Dale E.; Harris, John C.; Cutchis, Protagoras N.; Cristion, John A.; Lesser, Ronald P.; Webber, W. Robert S.

1993-01-01

There are an estimated two million people with epilepsy in the United States. Many of these people do not respond to anti-epileptic drug therapy. Two devices can be developed to assist in the treatment of epilepsy. The first is a microcomputer-based system designed to process massive amounts of electroencephalogram (EEG) data collected during long-term monitoring of patients for the purpose of diagnosing seizures, assessing the effectiveness of medical therapy, or selecting patients for epilepsy surgery. Such a device would select and display important EEG events. Currently many such events are missed. A second device could be implanted and would detect seizures and initiate therapy. Both of these devices require a reliable seizure detection algorithm. A new algorithm is described. It is believed to represent an improvement over existing seizure detection algorithms because better signal features were selected and better standardization methods were used.

Capped Mesoporous Silica Nanoparticles for the Selective and Sensitive Detection of Cyanide.

PubMed

Sayed, Sameh El; Licchelli, Maurizio; Martínez-Máñez, Ramón; Sancenón, Félix

2017-10-18

The development of easy and affordable methods for the detection of cyanide is of great significance due to the high toxicity of this anion and the potential risks associated with its pollution. Herein, optical detection of cyanide in water has been achieved by using a hybrid organic-inorganic nanomaterial. Mesoporous silica nanoparticles were loaded with [Ru(bipy) 3 ] 2+ , functionalized with macrocyclic nickel(II) complex subunits, and capped with a sterically hindering anion (hexametaphosphate). Cyanide selectively induces demetallation of nickel(II) complexes and the removal of capping anions from the silica surface, allowing the release of the dye and the consequent increase in fluorescence intensity. The response of the capped nanoparticles in aqueous solution is highly selective and sensitive towards cyanide with a limit of detection of 2 μm. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification, preparation and UHPLC determination of process-related impurity in zolmitriptan.

PubMed

Douša, Michal; Gibala, Petr; Rádl, Stanislav; Klecán, Ondřej; Mandelová, Zuzana; Břicháč, Jiří; Pekárek, Tomáš

2012-01-25

A new impurity was detected and determined using gradient ion-pair UHPLC method with UV detection in zolmitriptan (ZOL). Using MS, NMR and IR study the impurity was identified as (4S,4'S)-4,4'-(2,2'-(4-(dimethylamino)butane-1,1-diyl)bis(3-(2-(dimethylamino) ethyl)-1H-indole-5,2-diyl))bis(methylene)di(oxazolidin-2-one) (ZOL-dimer). The standard of ZOL-dimer was consequently prepared via organic synthesis followed by semipreparative HPLC purification. The UHPLC method was optimized in order to selectively detect and quantify other known and unknown process-related impurities and degradation products of ZOL as well. The presented method which was validated with respect to linearity, accuracy, precision and selectivity has an advantage of a very quick UHPLC chromatographic separation (less than 7 min including re-equilibration time) and therefore is highly suitable for routine analysis of related substances and stability studies of ZOL. Copyright © 2011 Elsevier B.V. All rights reserved.

Responsive Photonic Crystal Carbohydrate Hydrogel Sensor Materials for Selective and Sensitive Lectin Protein Detection.

PubMed

Cai, Zhongyu; Sasmal, Aniruddha; Liu, Xinyu; Asher, Sanford A

2017-10-27

Lectin proteins, such as the highly toxic lectin protein, ricin, and the immunochemically important lectin, jacalin, play significant roles in many biological functions. It is highly desirable to develop a simple but efficient method to selectively detect lectin proteins. Here we report the development of carbohydrate containing responsive hydrogel sensing materials for the selective detection of lectin proteins. The copolymerization of a vinyl linked carbohydrate monomer with acrylamide and acrylic acid forms a carbohydrate hydrogel that shows specific "multivalent" binding to lectin proteins. The resulting carbohydrate hydrogels are attached to 2-D photonic crystals (PCs) that brightly diffract visible light. This diffraction provides an optical readout that sensitively monitors the hydrogel volume. We utilize lactose, galactose, and mannose containing hydrogels to fabricate a series of 2-D PC sensors that show strong selective binding to the lectin proteins ricin, jacalin, and concanavalin A (Con A). This binding causes a carbohydrate hydrogel shrinkage which significantly shifts the diffraction wavelength. The resulting 2-D PC sensors can selectively detect the lectin proteins ricin, jacalin, and Con A. These unoptimized 2-D PC hydrogel sensors show a limit of detection (LoD) of 7.5 × 10 -8 M for ricin, a LoD of 2.3 × 10 -7 M for jacalin, and a LoD of 3.8 × 10 -8 M for Con A, respectively. This sensor fabrication approach may enable numerous sensors for the selective detection of numerous lectin proteins.

A selective and sensitive method for quantitation of lysergic acid diethylamide (LSD) in whole blood by gas chromatography-ion trap tandem mass spectrometry.

PubMed

Libong, Danielle; Bouchonnet, Stéphane; Ricordel, Ivan

2003-01-01

A gas chromatography-ion trap tandem mass spectrometry (GC-ion trap MS-MS) method for detection and quantitation of LSD in whole blood is presented. The sample preparation process, including a solid-phase extraction step with Bond Elut cartridges, was performed with 2 mL of whole blood. Eight microliters of the purified extract was injected with a cold on-column injection method. Positive chemical ionization was performed using acetonitrile as reagent gas; LSD was detected in the MS-MS mode. The chromatograms obtained from blood extracts showed the great selectivity of the method. GC-MS quantitation was performed using lysergic acid methylpropylamide as the internal standard. The response of the MS was linear for concentrations ranging from 0.02 ng/mL (detection threshold) to 10.0 ng/mL. Several parameters such as the choice of the capillary column, the choice of the internal standard and that of the ionization mode (positive CI vs. EI) were rationalized. Decomposition pathways under both ionization modes were studied. Within-day and between-day stability were evaluated.

A GC-MS method for the detection and quantitation of ten major drugs of abuse in human hair samples.

PubMed

Orfanidis, A; Mastrogianni, O; Koukou, A; Psarros, G; Gika, H; Theodoridis, G; Raikos, N

2017-03-15

A sensitive analytical method has been developed in order to identify and quantify major drugs of abuse (DOA), namely morphine, codeine, 6-monoacetylmorphine, cocaine, ecgonine methyl ester, benzoylecgonine, amphetamine, methamphetamine, methylenedioxymethamphetamine and methylenedioxyamphetamine in human hair. Samples of hair were extracted with methanol under ultrasonication at 50°C after a three step rinsing process to remove external contamination and dirt hair. Derivatization with BSTFA was selected in order to increase detection sensitivity of GC/MS analysis. Optimization of derivatization parameters was based on experiments for the selection of derivatization time, temperature and volume of derivatising agent. Validation of the method included evaluation of linearity which ranged from 2 to 350ng/mg of hair mean concentration for all DOA, evaluation of sensitivity, accuracy, precision and repeatability. Limits of detection ranged from 0.05 to 0.46ng/mg of hair. The developed method was applied for the analysis of hair samples obtained from three human subjects and were found positive in cocaine, and opiates. Published by Elsevier B.V.

Modern Approach to Medical Diagnostics - the Use of Separation Techniques in Microorganisms Detection.

PubMed

Chylewska, Agnieszka; Ogryzek, M; Makowski, Mariusz

2017-10-23

New analytical and molecular methods for microorganisms are being developed on various features of identification i.e. selectivity, specificity, sensitivity, rapidity and discrimination of the viable cell. The presented review was established following the current trends in improved pathogens separation and detection methods and their subsequent use in medical diagnosis. This contribution also focuses on the development of analytical and biological methods in the analysis of microorganisms, with special attention paid to bio-samples containing microbes (blood, urine, lymph, wastewater). First, the paper discusses microbes characterization, their structure, surface, properties, size and then it describes pivotal points in the bacteria, viruses and fungi separation procedure obtained by researchers in the last 30 years. According to the above, detection techniques can be classified into three categories, which were, in our opinion, examined and modified most intensively during this period: electrophoretic, nucleic-acid-based, and immunological methods. The review covers also the progress, limitations and challenges of these approaches and emphasizes the advantages of new separative techniques in selective fractionating of microorganisms. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Detection of Delamination in Concrete Bridge Decks Using Mfcc of Acoustic Impact Signals

NASA Astrophysics Data System (ADS)

Zhang, G.; Harichandran, R. S.; Ramuhalli, P.

2010-02-01

Delamination of the concrete cover is a commonly observed damage in concrete bridge decks. The delamination is typically initiated by corrosion of the upper reinforcing bars and promoted by freeze-thaw cycling and traffic loading. The detection of delamination is important for bridge maintenance and acoustic non-destructive evaluation (NDE) is widely used due to its low cost, speed, and easy implementation. In traditional acoustic approaches, the inspector sounds the surface of the deck by impacting it with a hammer or bar, or by dragging a chain, and assesses delamination by the "hollowness" of the sound. The detection of the delamination is subjective and requires extensive training. To improve performance, this paper proposes an objective method for delamination detection. In this method, mel-frequency cepstral coefficients (MFCC) of the signal are extracted. Some MFCC are then selected as features for detection purposes using a mutual information criterion. Finally, the selected features are used to train a classifier which is subsequently used for detection. In this work, a simple quadratic Bayesian classifier is used. Different numbers of features are used to compare the performance of the detection method. The results show that the performance first increases with the number of features, but then decreases after an optimal value. The optimal number of features based on the recorded signals is four, and the mean error rate is only 3.3% when four features are used. Therefore, the proposed algorithm has sufficient accuracy to be used in field detection.

Proton-Detected 15N NMR-Spectroscopy and Imaging

NASA Astrophysics Data System (ADS)

Freeman, D.; Sailasuta, N.; Sukumar, S.; Hurd, R. E.

1993-10-01

Proton detection of nitrogen-15, using gradients for coherence selection, was determined to be an effective method for obtaining spectra of 15N-labeled metabolites from extracts and biopsies of tissue infused with [15N] ammonium chloride. The advantage of gradient selection of coherence was best demonstrated by the almost complete single-shot elimination of solvent water in extracts and tissue water in biopsies. As a single-acquisition editing method in which only protons attached to 15N are detected, the potential limitations of dynamic range and motion are also reduced. Gradient-enhanced heteronuclear multiple-quantum coherence (1H[15N] HMQC) was compared with conventional HMQC, and despite selection of only one of the two heteronuclear pathways, GE-HMQC was found to be more effective for resolving the desired signal for dilute solutions; and with a single scan. In addition, effective water elimination made it possible to use the resolution advantage of a frequency-encoding dimension in proton-detected 15N imaging experiments. The limit of detection of the method at 500 MHz was 0.7 mM in 16 scans from a total volume of 400 μl. Signals from tissue extracts were observable in less than one minute for kidney, heart, brain, and muscle. Proton-detected 15N GE-HMQC images with a voxel size of 39 × 78 × 625 μm were obtained at 600 MHz from a 4 mM (1.6 μmol) 15N urea sample in less than four hours. Distribution of [15N] urea in the kidney was observed in a 600 MHz GE-HMQC image of the papilla and some cortical structures.

Recent advances on aptamer-based biosensors to detection of platelet-derived growth factor.

PubMed

Razmi, Nasrin; Baradaran, Behzad; Hejazi, Maryam; Hasanzadeh, Mohammad; Mosafer, Jafar; Mokhtarzadeh, Ahad; de la Guardia, Miguel

2018-08-15

Platelet-derived growth factor (PDGF-BB), a significant serum cytokine, is an important protein biomarker in diagnosis and recognition of cancer, which straightly rolled in proceeding of various cell transformations, including tumor growth and its development. Fibrosis, atherosclerosis are certain appalling diseases, which PDGF-BB is near to them. Generally, the expression amount of PDGF-BB increases in human life-threatening tumors serving as an indicator for tumor angiogenesis. Thus, identification and quantification of PDGF-BB in biomedical fields are particularly important. Affinity chromatography, immunohistochemical methods and enzyme-linked immunosorbent assay (ELISA), conventional methods for PDGF-BB detection, requiring high-cost and complicated instrumentation, take too much time and offer deficient sensitivity and selectivity, which restrict their usage in real applications. Hence, it is essential to design and build enhanced systems and platforms for the recognition and quantification of protein biomarkers. In the past few years, biosensors especially aptasensors have been received noticeable attention for the detection of PDGF-BB owing to their high sensitivity, selectivity, accuracy, fast response, and low cost. Since the role and importance of developing aptasensors in cancer diagnosis is undeniable. In this review, optical and electrochemical aptasensors, which have been applied by many researchers for PDGF-BB cancer biomarker detection, have been mentioned and merits and demerits of them have been explained and compared. Efforts related to design and development of aptamer-based biosensors using nanoparticles for sensitive and selective detection of PDGF-BB have been reviewed considering: Aptamer importance as recognition elements, principal, application and the recent improvements and developments of aptamer based optical and electrochemical methods. In addition, commercial biosensors and future perspectives for rapid and on-site detection of PDGF-BB have been summarized. Copyright © 2018 Elsevier B.V. All rights reserved.

Taxus ingredients in the red arils of Taxus baccata L. determined by HPLC-MS/MS.

PubMed

Siegle, Lydia; Pietsch, Jörg

2018-02-09

Taxus baccata L. is an evergreen conifer whose plant parts are cardiotoxic. Only the red arils of the berries are described as non-toxic and taxane-free. Extraction and HPLC-MS/MS methods were developed for the investigation of the Taxus compounds 3,5-dimethoxyphenol, 10-deacetylbaccatin III, baccatin III, cephalomannine, taxol A and taxinine M in the red arils of the yew berries. MethodologyA liquid-liquid extraction method for the red arils of the fruits from three yews were developed. An accurate (ESI+) HPLC-MS/MS method was performed for the simultaneous detection and determination of the target compounds in multiple reaction monitoring (MRM) mode. All Taxus agents obtained were detected in the red arils. Highest concentrations were determined for baccatin III and 10-deacetylbaccatin III. The developed quantitative method is reliable and selective and was successfully applied for quantification of selected Taxus ingredients in red arils of Taxus baccata. It was disproved that the red arils of the berries do not contain the selected Taxus compounds. Copyright © 2018 John Wiley & Sons, Ltd.

[Wavelength Selection in Hemolytic Evaluation Systems with Spectrophotometry Detection].

PubMed

Zhang, Hong; Su, Baochang; Ye, Xunda; Luo, Man

2016-04-01

Spectrophotometry is a simple hemolytic evaluation method commonly used in new drugs,biomedical materials and blood products.It is for the quantitative analysis of the characteristic absorption peaks of hemoglobin.Therefore,it is essential to select the correct detection wavelength when the evaluation system has influences on the conformation of hemoglobin.Based on the study of changes in the characteristic peaks over time of the hemolysis supernatant in four systems,namely,cell culture medium,phosphate buffered saline(PBS),physiological saline and banked blood preservation solution,using continuous wavelength scanning,the selections of detection wavelength were proposed as follows.In the cell culture medium system,the wavelength of 415 nm should be selected within 4h;,near 408 nm should be selected within 4~72h.In PBS system,within 4h,541 nm,577nm or 415 nm should be selected;4~72h,541 nm,577nm or near 406 nm should be selected.In physiological saline system,within 4h,414 nm should be selected;4~72h,near 405 nm should be selected;within 12 h,541nm or 577 nm could also be selected.In banked blood preservation solution system,within 72 h,415nm,540 nm or 576 nm should be selected.

A Fully Automated Method to Detect and Segment a Manufactured Object in an Underwater Color Image

NASA Astrophysics Data System (ADS)

Barat, Christian; Phlypo, Ronald

2010-12-01

We propose a fully automated active contours-based method for the detection and the segmentation of a moored manufactured object in an underwater image. Detection of objects in underwater images is difficult due to the variable lighting conditions and shadows on the object. The proposed technique is based on the information contained in the color maps and uses the visual attention method, combined with a statistical approach for the detection and an active contour for the segmentation of the object to overcome the above problems. In the classical active contour method the region descriptor is fixed and the convergence of the method depends on the initialization. With our approach, this dependence is overcome with an initialization using the visual attention results and a criterion to select the best region descriptor. This approach improves the convergence and the processing time while providing the advantages of a fully automated method.

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.

Dynamic surface-enhanced Raman spectroscopy and Chemometric methods for fast detection and intelligent identification of methamphetamine and 3, 4-Methylenedioxy methamphetamine in human urine

NASA Astrophysics Data System (ADS)

Weng, Shizhuang; Dong, Ronglu; Zhu, Zede; Zhang, Dongyan; Zhao, Jinling; Huang, Linsheng; Liang, Dong

2018-01-01

Conventional Surface-Enhanced Raman Spectroscopy (SERS) for fast detection of drugs in urine on the portable Raman spectrometer remains challenges because of low sensitivity and unreliable Raman signal, and spectra process with manual intervention. Here, we develop a novel detection method of drugs in urine using chemometric methods and dynamic SERS (D-SERS) with mPEG-SH coated gold nanorods (GNRs). D-SERS combined with the uniform GNRs can obtain giant enhancement, and the signal is also of high reproducibility. On the basis of the above advantages, we obtained the spectra of urine, urine with methamphetamine (MAMP), urine with 3, 4-Methylenedioxy Methamphetamine (MDMA) using D-SERS. Simultaneously, some chemometric methods were introduced for the intelligent and automatic analysis of spectra. Firstly, the spectra at the critical state were selected through using K-means. Then, the spectra were proposed by random forest (RF) with feature selection and principal component analysis (PCA) to develop the recognition model. And the identification accuracy of model were 100%, 98.7% and 96.7%, respectively. To validate the effect in practical issue further, the drug abusers'urine samples with 0.4, 3, 30 ppm MAMP were detected using D-SERS and identified by the classification model. The high recognition accuracy of > 92.0% can meet the demand of practical application. Additionally, the parameter optimization of RF classification model was simple. Compared with the general laboratory method, the detection process of urine's spectra using D-SERS only need 2 mins and 2 μL samples volume, and the identification of spectra based on chemometric methods can be finish in seconds. It is verified that the proposed approach can provide the accurate, convenient and rapid detection of drugs in urine.

Capillary electrophoresis with indirect UV detection for the determination of stabilizers and citrates present in human albumin solutions.

PubMed

Jaworska, Małgorzata; Cygan, Paulina; Wilk, Małgorzata; Anuszewska, Elzbieta

2009-08-15

Sodium caprylate and N-acetyltryptophan are the most frequently used stabilizers that protect the albumin from aggregation or heat induced denaturation. In turn citrates - excipients remaining after fractionation process - can be treated as by-product favoring leaching aluminum out of glass containers whilst albumin solution is stored. With ionic nature these substances have all the markings of a subject for capillary electrophoresis analysis. Thus CE methods were proposed as new approach for quality control of human albumin solution in terms of determination of stabilizers and citrates residue. Human albumin solutions both 5% and 20% from various manufacturers were tested. Indirect detection mode was set to provide sufficient detectability of analytes lacking of chromophores. As being anions analytes were separated with reversed electroosmotic flow. As a result of method optimization two background electrolytes based on p-hydroxybenzoic acid and 2,6-pyridinedicarboxylic acid were selected for stabilizers and citrates separation, respectively. The optimized methods were successfully validated. For citrates that require quantification below 100microM the method demonstrated the precision less than 4% and the limit of detection at 4microM. In order to check the new methods accuracy and applicability the samples were additionally tested with selected reference methods. The proposed methods allow reliable quantification of stabilizers and citrates in human albumin solution that was confirmed by method validation as well as result comparison with reference methods. The CE methods are considered to be suitable for quality control yet simplifying and reducing cost of analysis.

Selective and sensitive optical chemosensor for detection of Ag(I) ions based on 2(4-hydroxy pent-3-en-2-ylideneamine) phenol in aqueous samples

NASA Astrophysics Data System (ADS)

Mirzaei, Mohammad; Saeed, Jaber

2011-11-01

A selective and sensitive chemosensor, based on the 2(4-hydroxy pent-3-en-2-ylideneamine) phenol (HPYAP) as chromophore, has been developed for colorimetric and visual detection of Ag(I) ions. HPYAP shows a considerable chromogenic behavior toward Ag(I) ions by changing the color of the solution from pale-yellow to very chromatic-yellow, which can be easily detected with the naked-eye. The chemosensor exhibited selective absorbance enhancement to Ag(I) ions in water samples over other metal ions at 438 nm, with a linear range of 0.4-500 μM ( r2 = 0.999) and a limit of detection 0.07 μM of Ag(I) ions with UV-vis spectrophotometer detection. The relative standard deviation (RSD) for 100 μM Ag(I) ions was 2.05% ( n = 7). The proposed method was applied for the determination Ag(I) ions in water and waste water samples.

Spatially Resolved Chemical Imaging for Biosignature Analysis: Terrestrial and Extraterrestrial Examples

NASA Astrophysics Data System (ADS)

Bhartia, R.; Wanger, G.; Orphan, V. J.; Fries, M.; Rowe, A. R.; Nealson, K. H.; Abbey, W. J.; DeFlores, L. P.; Beegle, L. W.

2014-12-01

Detection of in situ biosignatures on terrestrial and planetary missions is becoming increasingly more important. Missions that target the Earth's deep biosphere, Mars, moons of Jupiter (including Europa), moons of Saturn (Titan and Enceladus), and small bodies such as asteroids or comets require methods that enable detection of materials for both in-situ analysis that preserve context and as a means to select high priority sample for return to Earth. In situ instrumentation for biosignature detection spans a wide range of analytical and spectroscopic methods that capitalize on amino acid distribution, chirality, lipid composition, isotopic fractionation, or textures that persist in the environment. Many of the existing analytical instruments are bulk analysis methods and while highly sensitive, these require sample acquisition and sample processing. However, by combining with triaging spectroscopic methods, biosignatures can be targeted on a surface and preserve spatial context (including mineralogy, textures, and organic distribution). To provide spatially correlated chemical analysis at multiple spatial scales (meters to microns) we have employed a dual spectroscopic approach that capitalizes on high sensitivity deep UV native fluorescence detection and high specificity deep UV Raman analysis.. Recently selected as a payload on the Mars 2020 mission, SHERLOC incorporates these optical methods for potential biosignatures detection on Mars. We present data from both Earth analogs that operate as our only examples known biosignatures and meteorite samples that provide an example of abiotic organic formation, and demonstrate how provenance effects the spatial distribution and composition of organics.

Qualitative and quantitative analysis of the diuretic component ergone in Polyporus umbellatus by HPLC with fluorescence detection and HPLC-APCI-MS/MS.

PubMed

Zhao, Ying-Yong; Zhao, Ye; Zhang, Yong-Min; Lin, Rui-Chao; Sun, Wen-Ji

2009-06-01

Polyporus umbellatus is a widely used anti-aldosteronic diuretic in Traditional Chinese medicine (TCM). A new, sensitive and selective high-performance liquid chromatography-fluorescence detector (HPLC-FLD) and high-performance liquid chromatography-atmospheric pressure chemical ionization-mass spectrometry (HPLC-APCI-MS/MS) method for quantitative and qualitative determination of ergosta-4,6,8(14),22-tetraen-3-one(ergone), which is the main diuretic component, was provided for quality control of P. umbellatus crude drug. The ergone in the ethanolic extract of P. umbellatus was unambiguously characterized by HPLC-APCI, and further confirmed by comparing with a standard compound. The trace ergone was detected by the sensitive and selective HPLC-FLD. Linearity (r2 > 0.9998) and recoveries of low, medium and high concentration (100.5%, 100.2% and 100.4%) were consistent with the experimental criteria. The limit of detection (LOD) of ergone was around 0.2 microg/mL. Our results indicated that the content of ergone in P. umbellatus varied significantly from habitat to habitat with contents ranging from 2.13 +/- 0.02 to 59.17 +/- 0.05 microg/g. Comparison among HPLC-FLD and HPLC-UV or HPLC-APCI-MS/MS demonstrated that the HPLC-FLD and HPLC-APCI-MS/MS methods gave similar quantitative results for the selected herb samples, the HPLC-UV methods gave lower quantitative results than HPLC-FLD and HPLC-APCI-MS/MS methods. The established new HPLC-FLD method has the advantages of being rapid, simple, selective and sensitive, and could be used for the routine analysis of P. umbellatus crude drug.

Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

2018-05-01

In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

Continental-scale footprint of balancing and positive selection in a small rodent (Microtus arvalis).

PubMed

Fischer, Martin C; Foll, Matthieu; Heckel, Gerald; Excoffier, Laurent

2014-01-01

Genetic adaptation to different environmental conditions is expected to lead to large differences between populations at selected loci, thus providing a signature of positive selection. Whereas balancing selection can maintain polymorphisms over long evolutionary periods and even geographic scale, thus leads to low levels of divergence between populations at selected loci. However, little is known about the relative importance of these two selective forces in shaping genomic diversity, partly due to difficulties in recognizing balancing selection in species showing low levels of differentiation. Here we address this problem by studying genomic diversity in the European common vole (Microtus arvalis) presenting high levels of differentiation between populations (average F ST = 0.31). We studied 3,839 Amplified Fragment Length Polymorphism (AFLP) markers genotyped in 444 individuals from 21 populations distributed across the European continent and hence over different environmental conditions. Our statistical approach to detect markers under selection is based on a Bayesian method specifically developed for AFLP markers, which treats AFLPs as a nearly codominant marker system, and therefore has increased power to detect selection. The high number of screened populations allowed us to detect the signature of balancing selection across a large geographic area. We detected 33 markers potentially under balancing selection, hence strong evidence of stabilizing selection in 21 populations across Europe. However, our analyses identified four-times more markers (138) being under positive selection, and geographical patterns suggest that some of these markers are probably associated with alpine regions, which seem to have environmental conditions that favour adaptation. We conclude that despite favourable conditions in this study for the detection of balancing selection, this evolutionary force seems to play a relatively minor role in shaping the genomic diversity of the common vole, which is more influenced by positive selection and neutral processes like drift and demographic history.

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

PubMed

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

2011-07-15

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

Simplified Identification of mRNA or DNA in Whole Cells

NASA Technical Reports Server (NTRS)

Almeida, Eduardo; Kadambi, Geeta

2007-01-01

A recently invented method of detecting a selected messenger ribonucleic acid (mRNA) or deoxyribonucleic acid (DNA) sequence offers two important advantages over prior such methods: it is simpler and can be implemented by means of compact equipment. The simplification and miniaturization achieved by this invention are such that this method is suitable for use outside laboratories, in field settings in which space and power supplies may be limited. The present method is based partly on hybridization of nucleic acid, which is a powerful technique for detection of specific complementary nucleic acid sequences and is increasingly being used for detection of changes in gene expression in microarrays containing thousands of gene probes.

Thresholding Based on Maximum Weighted Object Correlation for Rail Defect Detection

NASA Astrophysics Data System (ADS)

Li, Qingyong; Huang, Yaping; Liang, Zhengping; Luo, Siwei

Automatic thresholding is an important technique for rail defect detection, but traditional methods are not competent enough to fit the characteristics of this application. This paper proposes the Maximum Weighted Object Correlation (MWOC) thresholding method, fitting the features that rail images are unimodal and defect proportion is small. MWOC selects a threshold by optimizing the product of object correlation and the weight term that expresses the proportion of thresholded defects. Our experimental results demonstrate that MWOC achieves misclassification error of 0.85%, and outperforms the other well-established thresholding methods, including Otsu, maximum correlation thresholding, maximum entropy thresholding and valley-emphasis method, for the application of rail defect detection.

Multiple applications of ion chromatography oligosaccharide fingerprint profiles to solve a variety of sugar and sugar-biofuel industry problems.

PubMed

Eggleston, Gillian; Borges, Eduardo

2015-03-25

Sugar crops contain a broad variety of carbohydrates used for human consumption and the production of biofuels and bioproducts. Ion chromatography with integrated pulsed amperometric detection (IC-IPAD) can be used to simultaneously detect mono-, di-, and oligosaccharides, oligosaccharide isomers, mannitol, and ethanol in complex matrices from sugar crops. By utilizing a strong NaOH/NaOAc gradient method over 45 min, oligosaccharides of at least 2-12 dp can be detected. Fingerprint IC oligosaccharide profiles are extremely selective, sensitive, and reliable and can detect deterioration product metabolites from as low as 100 colony-forming units/mL lactic acid bacteria. The IC fingerprints can also be used to (i) monitor freeze deterioration, (ii) optimize harvesting methods and cut-to-crush times, (iii) differentiate between white refined sugar from sugar cane and from sugar beets, (iv) verify the activities of carbohydrate enzymes, (v) select yeasts for ethanol fermentations, and (vi) isolate and diagnose infections and processing problems in sugar factories.

Leak locating microphone, method and system for locating fluid leaks in pipes

DOEpatents

Kupperman, David S.; Spevak, Lev

1994-01-01

A leak detecting microphone inserted directly into fluid within a pipe includes a housing having a first end being inserted within the pipe and a second opposed end extending outside the pipe. A diaphragm is mounted within the first housing end and an acoustic transducer is coupled to the diaphragm for converting acoustical signals to electrical signals. A plurality of apertures are provided in the housing first end, the apertures located both above and below the diaphragm, whereby to equalize fluid pressure on either side of the diaphragm. A leak locating system and method are provided for locating fluid leaks within a pipe. A first microphone is installed within fluid in the pipe at a first selected location and sound is detected at the first location. A second microphone is installed within fluid in the pipe at a second selected location and sound is detected at the second location. A cross-correlation is identified between the detected sound at the first and second locations for identifying a leak location.

Silver nanoparticles-based colorimetric array for the detection of Thiophanate-methyl

NASA Astrophysics Data System (ADS)

Zheng, Mingda; Wang, Yingying; Wang, Chenge; Wei, Wei; Ma, Shuang; Sun, Xiaohan; He, Jiang

2018-06-01

A simple and selective colorimetric sensor based on citrate capped silver nanoparticles (Cit-AgNPs) is proposed for the detection of Thiophanate-methyl (TM) with high sensitivity and selectivity. The method based on the color change of Cit-AgNPs from yellow to cherry red with the addition of TM to Cit-AgNPs that caused a red-shift on the surface plasmon resonance (SPR) band from 394 nm to 525 nm due to the hydrogen-bonding and substitution. The density functional theory (DFT) method was also calculated the interactions between the TM and citrate ions. Under the optimized conditions, a linear relationship between the absorption ratio (A525nm/A394nm) and TM concentration was found in the range of 2-100 μM with correlation coefficient (R2) of 0.988. The detection limit of TM was 0.12 μM by UV-vis spectrometer. Moreover, the applicability of colorimetric sensor is successfully verified by the detection of TM in environmental samples with good recoveries.

Detection of tire tread particles using laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Prochazka, David; Bilík, Martin; Prochazková, Petra; Klus, Jakub; Pořízka, Pavel; Novotný, Jan; Novotný, Karel; Ticová, Barbora; Bradáč, Albert; Semela, Marek; Kaiser, Jozef

2015-06-01

The objective of this paper is a study of the potential of laser induced breakdown spectroscopy (LIBS) for detection of tire tread particles. Tire tread particles may represent pollutants; simultaneously, it is potentially possible to exploit detection of tire tread particles for identification of optically imperceptible braking tracks at locations of road accidents. The paper describes the general composition of tire treads and selection of an element suitable for detection using the LIBS method. Subsequently, the applicable spectral line is selected considering interferences with lines of elements that might be present together with the detected particles, and optimization of measurement parameters such as incident laser energy, gate delay and gate width is performed. In order to eliminate the matrix effect, measurements were performed using 4 types of tires manufactured by 3 different producers. An adhesive tape was used as a sample carrier. The most suitable adhesive tape was selected from 5 commonly available tapes, on the basis of their respective LIBS spectra. Calibration standards, i.e. an adhesive tape with different area content of tire tread particles, were prepared for the selected tire. A calibration line was created on the basis of the aforementioned calibration standards. The linear section of this line was used for determination of the detection limit value applicable to the selected tire. Considering the insignificant influence of matrix of various types of tires, it is possible to make a simple recalculation of the detection limit value on the basis of zinc content in a specific tire.

Recommendations for the treatment of aging in standard technical specifications

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

Orton, R.D.; Allen, R.P.

1995-09-01

As part of the US Nuclear Regulatory Commission`s Nuclear Plant Aging Research Program, Pacific Northwest Laboratory (PNL) evaluated the standard technical specifications for nuclear power plants to determine whether the current surveillance requirements (SRs) were effective in detecting age-related degradation. Nuclear Plant Aging Research findings for selected systems and components were reviewed to identify the stressors and operative aging mechanisms and to evaluate the methods available to detect, differentiate, and trend the resulting aging degradation. Current surveillance and testing requirements for these systems and components were reviewed for their effectiveness in detecting degraded conditions and for potential contributions to prematuremore » degradation. When the current surveillance and testing requirements appeared ineffective in detecting aging degradation or potentially could contribute to premature degradation, a possible deficiency in the SRs was identified that could result in undetected degradation. Based on this evaluation, PNL developed recommendations for inspection, surveillance, trending, and condition monitoring methods to be incorporated in the SRs to better detect age- related degradation of these selected systems and components.« less

Rapid sample screening method for authenticity controlling vanilla flavors using a CE microchip approach with electrochemical detection.

PubMed

Avila, Mónica; González, María Cristina; Zougagh, Mohammed; Escarpa, Alberto; Ríos, Angel

2007-11-01

Five vanilla-related flavors of food significance, vanillic alcohol (VOH), ethyl maltol (EMA), maltol (MAL), ethyl vanillin (EVA) and vanillin (VAN), were separated using CE microchips with electrochemical detection (CE-ED microchips). A +2 kV driving voltage for both injection and separation operation steps, using a borate buffer (pH 9.5, 20 mM) and 1 M nitric acid in the detection reservoir allowed the selective and sensitive detection of the target analytes in less than 200 s with reproducible control of EOF (RSD(migration times)<3%). The analysis in selected real vanilla samples was focusing on VAN and EVA because VAN is a basic fragrance compound of the vanilla aroma, whereas EVA is an unequivocal proof of adulteration of vanilla flavors. Fast detection of all relevant flavors (200 s) with an acceptable resolution (R(s) >1.5) and a high accuracy (recoveries higher than 90%) were obtained with independence of the matrices and samples examined. These results showed the reliability of the method and the potential use of CE microchips in the food control field for fraudulent purposes.

Electrochemiluminescence assay of Cu2+ by using one-step electrodeposition synthesized CdS/ZnS quantum dots.

PubMed

Zhao, Guanhui; Li, Xiaojian; Zhao, Yongbei; Li, Yueyuan; Cao, Wei; Wei, Qin

2017-08-21

A sensitive and selective method was proposed to detect Cu 2+ based on the electrochemiluminescence quenching of CdS/ZnS quantum dots (QDs). Herein, CdS/ZnS QDs were one-step electrodeposited directly on a gold electrode from an electrolyte (containing Cd(NO 3 ) 2 , Zn(NO 3 ) 2 , EDTA and Na 2 S 2 O 3 ) by cycling the potential from 0 to -1.8 V. The prepared CdS/ZnS QDs exhibited excellent solubility and strong and stable cathodic ECL activity. Meanwhile, Nafion was used to immobilize CdS/ZnS QDs. The quenching effect of Cu 2+ on the cathodic ECL of CdS/ZnS QDs was found to be selective and concentration dependent. The linear range for Cu 2+ detection was from 2.5 nM to 200 nM with a detection limit of 0.95 nM. Furthermore, the designed method for the detection of Cu 2+ can provide a reference for the detection of other heavy metal ions.

Searching for patterns in remote sensing image databases using neural networks

NASA Technical Reports Server (NTRS)

Paola, Justin D.; Schowengerdt, Robert A.

1995-01-01

We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.

An experimental sample of the field gamma-spectrometer based on solid state Si-photomultiplier

NASA Astrophysics Data System (ADS)

Denisov, Viktor; Korotaev, Valery; Titov, Aleksandr; Blokhina, Anastasia; Kleshchenok, Maksim

2017-05-01

Design of optical-electronic devices and systems involves the selection of such technical patterns that under given initial requirements and conditions are optimal according to certain criteria. The original characteristic of the OES for any purpose, defining its most important feature ability is a threshold detection. Based on this property, will be achieved the required functional quality of the device or system. Therefore, the original criteria and optimization methods have to subordinate to the idea of a better detectability. Generally reduces to the problem of optimal selection of the expected (predetermined) signals in the predetermined observation conditions. Thus the main purpose of optimization of the system when calculating its detectability is the choice of circuits and components that provide the most effective selection of a target.

Comparison of different methods for MP detection: What can we learn from them, and why asking the right question before measurements matters?

PubMed

Elert, Anna M; Becker, Roland; Duemichen, Erik; Eisentraut, Paul; Falkenhagen, Jana; Sturm, Heinz; Braun, Ulrike

2017-12-01

In recent years, an increasing trend towards investigating and monitoring the contamination of the environment by microplastics (MP) (plastic pieces < 5 mm) has been observed worldwide. Nonetheless, a reliable methodology that would facilitate and automate the monitoring of MP is still lacking. With the goal of selecting practical and standardized methods, and considering the challenges in microplastics detection, we present here a critical evaluation of two vibrational spectroscopies, Raman and Fourier transform infrared (FTIR) spectroscopy, and two extraction methods: thermal extraction desorption gas chromatography mass spectrometry (TED-GC-MS) and liquid extraction with subsequent size exclusion chromatography (SEC) using a soil with known contents of PE, PP, PS and PET as reference material. The obtained results were compared in terms of measurement time, technique handling, detection limits and requirements for sample preparation. The results showed that in designing and selecting the right methodology, the scientific question that determines what needs to be understood is significant, and should be considered carefully prior to analysis. Depending on whether the object of interest is quantification of the MP particles in the sample, or merely a quick estimate of sample contamination with plastics, the appropriate method must be selected. To obtain overall information about MP in environmental samples, the combination of several parallel approaches should be considered. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genome-wide detection of selection signatures in Chinese indigenous Laiwu pigs revealed candidate genes regulating fat deposition in muscle.

PubMed

Chen, Minhui; Wang, Jiying; Wang, Yanping; Wu, Ying; Fu, Jinluan; Liu, Jian-Feng

2018-05-18

Currently, genome-wide scans for positive selection signatures in commercial breed have been investigated. However, few studies have focused on selection footprints of indigenous breeds. Laiwu pig is an invaluable Chinese indigenous pig breed with extremely high proportion of intramuscular fat (IMF), and an excellent model to detect footprint as the result of natural and artificial selection for fat deposition in muscle. In this study, based on GeneSeek Genomic profiler Porcine HD data, three complementary methods, F ST , iHS (integrated haplotype homozygosity score) and CLR (composite likelihood ratio), were implemented to detect selection signatures in the whole genome of Laiwu pigs. Totally, 175 candidate selected regions were obtained by at least two of the three methods, which covered 43.75 Mb genomic regions and corresponded to 1.79% of the genome sequence. Gene annotation of the selected regions revealed a list of functionally important genes for feed intake and fat deposition, reproduction, and immune response. Especially, in accordance to the phenotypic features of Laiwu pigs, among the candidate genes, we identified several genes, NPY1R, NPY5R, PIK3R1 and JAKMIP1, involved in the actions of two sets of neurons, which are central regulators in maintaining the balance between food intake and energy expenditure. Our results identified a number of regions showing signatures of selection, as well as a list of functionally candidate genes with potential effect on phenotypic traits, especially fat deposition in muscle. Our findings provide insights into the mechanisms of artificial selection of fat deposition and further facilitate follow-up functional studies.

[Sensitive and selective HPLC methods with prechromatographic derivatization for the determination of cyclamate in foods].

PubMed

Rüter, J; Raczek, D I

1992-06-01

A sensitive and selective high pressure liquid chromatography (HPLC) procedure for the determination of sodium cyclamate in juices and preserves is presented. The method depends on the oxidation of cyclamate to cyclohexylamine, which then is converted prechromatographically into a fluorescent derivative. It is analyzed by HPLC on a C18:reversed-phase column and determined with fluorescence detection (excitation at 350 nm, emission at 440-650 nm). The detection limit of sodium cyclamate was 0.5-5 mg/kg, depending on the nature and dilution of the samples. The relative standard deviations thus obtained were +/- 1.0 to +/- 2.6%. The average recovery was 90%.

Current methods for detecting ethylene in plants

PubMed Central

Cristescu, Simona M.; Mandon, Julien; Arslanov, Denis; De Pessemier, Jérôme; Hermans, Christian; Harren, Frans J. M.

2013-01-01

Background In view of ethylene's critical developmental and physiological roles the gaseous hormone remains an active research topic for plant biologists. Progress has been made to understand the ethylene biosynthesis pathway and the mechanisms of perception and action. Still numerous questions need to be answered and findings to be validated. Monitoring gas production will very often complete the picture of any ethylene research topic. Therefore the search for suitable ethylene measuring methods for various plant samples either in the field, greenhouses, laboratories or storage facilities is strongly motivated. Scope This review presents an update of the current methods for ethylene monitoring in plants. It focuses on the three most-used methods – gas chromatography detection, electrochemical sensing and optical detection – and compares them in terms of sensitivity, selectivity, time response and price. Guidelines are provided for proper selection and application of the described sensor methodologies and some specific applications are illustrated of laser-based detector for monitoring ethylene given off by Arabidopsis thaliana upon various nutritional treatments. Conclusions Each method has its advantages and limitations. The choice for the suitable ethylene sensor needs careful consideration and is driven by the requirements for a specific application. PMID:23243188

Evaluation of different methods to detect microbial hygiene indicators relevant in the dairy industry.

PubMed

Hervert, C J; Alles, A S; Martin, N H; Boor, K J; Wiedmann, M

2016-09-01

It is estimated that 19% of the total food loss from retail, food service, and households comes from dairy products. A portion of this loss may be attributed to premature spoilage of products due to lapses in sanitation and postpasteurization contamination at the processing level. Bacterial groups including coliforms, Enterobacteriaceae (EB), and total gram-negative organisms represent indicators of poor sanitation or postpasteurization contamination in dairy products worldwide. Although Petrifilms (3M, St. Paul, MN) and traditional selective media are commonly used for the testing of these indicator organism groups throughout the US dairy industry, new rapid methods are also being developed. This project was designed to evaluate the ability of different methods to detect coliforms, EB, and other gram-negative organisms isolated from various dairy products and dairy processing environments. Using the Food Microbe Tracker database, a collection of 211 coliform, EB, and gram-negative bacterial isolates representing 25 genera associated with dairy products was assembled for this study. We tested the selected isolates in pure culture (at levels of approximately 15 to 300 cells/test) to evaluate the ability of 3M Coliform Petrifilm to detect coliforms, 3M Enterobacteriaceae Petrifilm, violet red bile glucose agar, and an alternative flow cytometry-based method (bioMérieux D-Count, Marcy-l'Étoile, France) to detect EB, and crystal violet tetrazolium agar to detect total gram-negative organisms. Of the 211 gram-negative isolates tested, 82% (174/211) had characteristic growth on crystal violet tetrazolium agar. Within this set of 211 gram-negative organisms, 175 isolates representing 19 EB genera were screened for detection using EB selective/differential testing methods. We observed positive results for 96% (168/175), 90% (158/175), and 86% (151/175) of EB isolates when tested on EB Petrifilm, violet red bile glucose agar, and D-Count, respectively; optimization of the cut-off thresholds for the D-Count may further improve its sensitivity and specificity, but will require additional data and may vary in food matrices. Additionally, 74% (129/175) of the EB isolates tested positive as coliforms. The data obtained from this study identify differences in detection between 5 microbial hygiene indicator tests and highlight the benefits of EB and total gram-negative testing methods. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

IMMUNOCHEMICAL APPLICATIONS IN ENVIRONMENTAL SCIENCE

EPA Science Inventory

Immunochemical methods are based on selective antibodies combining with a particular target analyte or analyte group. The specific binding between antibody and analyte can be used to detect environmental contaminants in a variety of sample matrixes. Immunoassay methods provide ...

Integrated Droplet-Based Microextraction with ESI-MS for Removal of Matrix Interference in Single-Cell Analysis.

PubMed

Zhang, Xiao-Chao; Wei, Zhen-Wei; Gong, Xiao-Yun; Si, Xing-Yu; Zhao, Yao-Yao; Yang, Cheng-Dui; Zhang, Si-Chun; Zhang, Xin-Rong

2016-04-29

Integrating droplet-based microfluidics with mass spectrometry is essential to high-throughput and multiple analysis of single cells. Nevertheless, matrix effects such as the interference of culture medium and intracellular components influence the sensitivity and the accuracy of results in single-cell analysis. To resolve this problem, we developed a method that integrated droplet-based microextraction with single-cell mass spectrometry. Specific extraction solvent was used to selectively obtain intracellular components of interest and remove interference of other components. Using this method, UDP-Glc-NAc, GSH, GSSG, AMP, ADP and ATP were successfully detected in single MCF-7 cells. We also applied the method to study the change of unicellular metabolites in the biological process of dysfunctional oxidative phosphorylation. The method could not only realize matrix-free, selective and sensitive detection of metabolites in single cells, but also have the capability for reliable and high-throughput single-cell analysis.

Stochastic model search with binary outcomes for genome-wide association studies.

PubMed

Russu, Alberto; Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-06-01

The spread of case-control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model.

A highly sensitive and selective aptamer-based colorimetric sensor for the rapid detection of PCB 77.

PubMed

Cheng, Ruojie; Liu, Siyao; Shi, Huijie; Zhao, Guohua

2018-01-05

A highly sensitive, specific and simple colorimetric sensor based on aptamer was established for the detection of polychlorinated biphenyls (PCB 77). The use of unmodified gold nanoparticles as a colorimetric probe for aptamer sensors enabled the highly sensitive and selective detection of polychlorinated biphenyls (PCB 77). A linear range of 0.5nM to 900nM was obtained for the colorimetric assay with a minimum detection limit of 0.05nM. In addition, by the methods of circular dichroism, UV and naked eyes, we found that the 35 base fragments retained after cutting 5 bases from the 5 'end of aptamer plays the most significant role in the PCB 77 specific recognition process. We found a novel way to truncated nucleotides to optimize the detection of PCB 77, and the selected nucleotides also could achieve high affinity with PCB 77. At the same time, the efficient detection of the PCB 77 by our colorimetric sensor in the complex environmental water samples was realized, which shows a good application prospect. Copyright © 2017 Elsevier B.V. All rights reserved.

Bubble measuring instrument and method

NASA Technical Reports Server (NTRS)

Magari, Patrick J. (Inventor); Kline-Schoder, Robert (Inventor)

2003-01-01

Method and apparatus are provided for a non-invasive bubble measuring instrument operable for detecting, distinguishing, and counting gaseous embolisms such as bubbles over a selectable range of bubble sizes of interest. A selected measurement volume in which bubbles may be detected is insonified by two distinct frequencies from a pump transducer and an image transducer, respectively. The image transducer frequency is much higher than the pump transducer frequency. The relatively low-frequency pump signal is used to excite bubbles to resonate at a frequency related to their diameter. The image transducer is operated in a pulse-echo mode at a controllable repetition rate that transmits bursts of high-frequency ultrasonic signal to the measurement volume in which bubbles may be detected and then receives the echo. From the echo or received signal, a beat signal related to the repetition rate may be extracted and used to indicate the presence or absence of a resonant bubble. In a preferred embodiment, software control maintains the beat signal at a preselected frequency while varying the pump transducer frequency to excite bubbles of different diameters to resonate depending on the range of bubble diameters selected for investigation.

Bubble Measuring Instrument and Method

NASA Technical Reports Server (NTRS)

Kline-Schoder, Robert (Inventor); Magari, Patrick J. (Inventor)

2002-01-01

Method and apparatus are provided for a non-invasive bubble measuring instrument operable for detecting, distinguishing, and counting gaseous embolisms such as bubbles over a selectable range of bubble sizes of interest. A selected measurement volume in which bubbles may be detected is insonified by two distinct frequencies from a pump transducer and an image transducer. respectively. The image transducer frequency is much higher than the pump transducer frequency. The relatively low-frequency pump signal is used to excite bubbles to resonate at a frequency related to their diameter. The image transducer is operated in a pulse-echo mode at a controllable repetition rate that transmits bursts of high-frequency ultrasonic signal to the measurement volume in which bubbles may be detected and then receives the echo. From the echo or received signal, a beat signal related to the repetition rate may be extracted and used to indicate the presence or absence of a resonant bubble. In a preferred embodiment, software control maintains the beat signal at a preselected frequency while varying the pump transducer frequency to excite bubbles of different diameters to resonate depending on the range of bubble diameters selected for investigation.

A LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) FOR NONLINEAR SYSTEM IDENTIFICATION

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Lofberg, Johan; Brenner, Martin J.

2006-01-01

Identification of parametric nonlinear models involves estimating unknown parameters and detecting its underlying structure. Structure computation is concerned with selecting a subset of parameters to give a parsimonious description of the system which may afford greater insight into the functionality of the system or a simpler controller design. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear systems. The LASSO minimises the residual sum of squares by the addition of a 1 penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. The performance of this LASSO structure detection method was evaluated by using it to estimate the structure of a nonlinear polynomial model. Applicability of the method to more complex systems such as those encountered in aerospace applications was shown by identifying a parsimonious system description of the F/A-18 Active Aeroelastic Wing using flight test data.

Detection of genomic signatures of recent selection in commercial broiler chickens.

PubMed

Fu, Weixuan; Lee, William R; Abasht, Behnam

2016-08-26

Identification of the genomic signatures of recent selection may help uncover causal polymorphisms controlling traits relevant to recent decades of selective breeding in livestock. In this study, we aimed at detecting signatures of recent selection in commercial broiler chickens using genotype information from single nucleotide polymorphisms (SNPs). A total of 565 chickens from five commercial purebred lines, including three broiler sire (male) lines and two broiler dam (female) lines, were genotyped using the 60K SNP Illumina iSelect chicken array. To detect genomic signatures of recent selection, we applied two methods based on population comparison, cross-population extended haplotype homozygosity (XP-EHH) and cross-population composite likelihood ratio (XP-CLR), and further analyzed the results to find genomic regions under recent selection in multiple purebred lines. A total of 321 candidate selection regions spanning approximately 1.45 % of the chicken genome in each line were detected by consensus of results of both XP-EHH and XP-CLR methods. To minimize false discovery due to genetic drift, only 42 of the candidate selection regions that were shared by 2 or more purebred lines were considered as high-confidence selection regions in the study. Of these 42 regions, 20 were 50 kb or less while 4 regions were larger than 0.5 Mb. In total, 91 genes could be found in the 42 regions, among which 19 regions contained only 1 or 2 genes, and 9 regions were located at gene deserts. Our results provide a genome-wide scan of recent selection signatures in five purebred lines of commercial broiler chickens. We found several candidate genes for recent selection in multiple lines, such as SOX6 (Sex Determining Region Y-Box 6) and cTR (Thyroid hormone receptor beta). These genes may have been under recent selection due to their essential roles in growth, development and reproduction in chickens. Furthermore, our results suggest that in some candidate regions, the same or opposite alleles have been under recent selection in multiple lines. Most of the candidate genes in the selection regions are novel, and as such they should be of great interest for future research into the genetic architecture of traits relevant to modern broiler breeding.

Quantitative method of measuring cancer cell urokinase and metastatic potential

NASA Technical Reports Server (NTRS)

Morrison, Dennis R. (Inventor)

1993-01-01

The metastatic potential of tumors can be evaluated by the quantitative detection of urokinase and DNA. The cell sample selected for examination is analyzed for the presence of high levels of urokinase and abnormal DNA using analytical flow cytometry and digital image analysis. Other factors such as membrane associated urokinase, increased DNA synthesis rates and certain receptors can be used in the method for detection of potentially invasive tumors.

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.

Highly selective and sensitive method for Cu2+ detection based on chiroptical activity of L-Cysteine mediated Au nanorod assemblies.

PubMed

Abbasi, Shahryar; Khani, Hamzeh

2017-11-05

Herein, we demonstrated a simple and efficient method to detect Cu 2+ based on amplified optical activity in the chiral nanoassemblies of gold nanorods (Au NRs). L-Cysteine can induce side-by-side or end-to-end assembly of Au NRs with an evident plasmonic circular dichroism (PCD) response due to coupling between surface plasmon resonances (SPR) of Au NRs and the chiral signal of L-Cys. Because of the obvious stronger plasmonic circular dichrosim (CD) response of the side-by-side assembly compared with the end-to-end assemblies, SS assembled Au NRs was selected as a sensitive platform and used for Cu 2+ detection. In the presence of Cu 2+ , Cu 2+ can catalyze O 2 oxidation of cysteine to cystine. With an increase in Cu 2+ concentration, the L-Cysteine-mediated assembly of Au NRs decreased because of decrease in the free cysteine thiol groups, and the PCD signal decreased. Taking advantage of this method, Cu 2+ could be detected in the concentration range of 20pM-5nM. Under optimal conditions, the calculated detection limit was found to be 7pM. Copyright © 2017 Elsevier B.V. All rights reserved.

A high-performance seizure detection algorithm based on Discrete Wavelet Transform (DWT) and EEG

PubMed Central

Chen, Duo; Wan, Suiren; Xiang, Jing; Bao, Forrest Sheng

2017-01-01

In the past decade, Discrete Wavelet Transform (DWT), a powerful time-frequency tool, has been widely used in computer-aided signal analysis of epileptic electroencephalography (EEG), such as the detection of seizures. One of the important hurdles in the applications of DWT is the settings of DWT, which are chosen empirically or arbitrarily in previous works. The objective of this study aimed to develop a framework for automatically searching the optimal DWT settings to improve accuracy and to reduce computational cost of seizure detection. To address this, we developed a method to decompose EEG data into 7 commonly used wavelet families, to the maximum theoretical level of each mother wavelet. Wavelets and decomposition levels providing the highest accuracy in each wavelet family were then searched in an exhaustive selection of frequency bands, which showed optimal accuracy and low computational cost. The selection of frequency bands and features removed approximately 40% of redundancies. The developed algorithm achieved promising performance on two well-tested EEG datasets (accuracy >90% for both datasets). The experimental results of the developed method have demonstrated that the settings of DWT affect its performance on seizure detection substantially. Compared with existing seizure detection methods based on wavelet, the new approach is more accurate and transferable among datasets. PMID:28278203

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.

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

PubMed

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

2013-08-01

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

[Influence of Spectral Pre-Processing on PLS Quantitative Model of Detecting Cu in Navel Orange by LIBS].

PubMed

Li, Wen-bing; Yao, Lin-tao; Liu, Mu-hua; Huang, Lin; Yao, Ming-yin; Chen, Tian-bing; He, Xiu-wen; Yang, Ping; Hu, Hui-qin; Nie, Jiang-hui

2015-05-01

Cu in navel orange was detected rapidly by laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) for quantitative analysis, then the effect on the detection accuracy of the model with different spectral data ptetreatment methods was explored. Spectral data for the 52 Gannan navel orange samples were pretreated by different data smoothing, mean centralized and standard normal variable transform. Then 319~338 nm wavelength section containing characteristic spectral lines of Cu was selected to build PLS models, the main evaluation indexes of models such as regression coefficient (r), root mean square error of cross validation (RMSECV) and the root mean square error of prediction (RMSEP) were compared and analyzed. Three indicators of PLS model after 13 points smoothing and processing of the mean center were found reaching 0. 992 8, 3. 43 and 3. 4 respectively, the average relative error of prediction model is only 5. 55%, and in one word, the quality of calibration and prediction of this model are the best results. The results show that selecting the appropriate data pre-processing method, the prediction accuracy of PLS quantitative model of fruits and vegetables detected by LIBS can be improved effectively, providing a new method for fast and accurate detection of fruits and vegetables by LIBS.

Design and Evaluation of Perceptual-based Object Group Selection Techniques

NASA Astrophysics Data System (ADS)

Dehmeshki, Hoda

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

Synthesis of molecular imprinted polymers for selective extraction of domperidone from human serum using high performance liquid chromatography with fluorescence detection.

PubMed

Salehi, Simin; Rasoul-Amini, Sara; Adib, Noushin; Shekarchi, Maryam

2016-08-01

In this study a novel method is described for selective quantization of domperidone in biological matrices applying molecular imprinted polymers (MIPs) as a sample clean up procedure using high performance liquid chromatography coupled with a fluorescence detector. MIPs were synthesized with chloroform as the porogen, ethylene glycol dimethacrylate as the crosslinker, methacrylic acid as the monomer, and domperidone as the template molecule. The new imprinted polymer was used as a molecular sorbent for separation of domperidone from serum. Molecular recognition properties, binding capacity and selectivity of MIPs were determined. The results demonstrated exceptional affinity for domperidone in biological fluids. The domperidone analytical method using MIPs was verified according to validation parameters, such as selectivity, linearity (5-80ng/mL, r(2)=0.9977), precision and accuracy (10-40ng/mL, intra-day=1.7-5.1%, inter-day=4.5-5.9%, and accuracy 89.07-98.9%).The limit of detection (LOD) and quantization (LOQ) of domperidone was 0.0279 and 0.092ng/mL, respectively. The simplicity and suitable validation parameters makes this a highly valuable selective bioequivalence method for domperidone analysis in human serum. Copyright © 2016 Elsevier B.V. All rights reserved.

New ELISA-based method for the detection of O-GlcNAc transferase activity in vitro.

PubMed

Qi, Jieqiong; Wang, Ruihong; Zeng, Yazhen; Yu, Wengong; Gu, Yuchao

2017-08-09

O-GlcNAcylation is a dynamic, reversible, post-translational modification that regulates many cellular processes. O-GlcNAc transferase (OGT) is the sole enzyme transferring N-acetylglucosamine from uridine diphosphate (UDP)-GlcNAc to selected serine/threonine residues of cytoplasm and nucleus proteins. Aberrant of OGT activity is associated with several diseases, suggesting OGT as a novel therapeutic target. In this study, we created a new enzyme linked immunosorbent assays (ELISA)-based method for detection of OGT activity. First, casein kinase II (CKII), a well-known OGT substrate, was coated onto ELISA plate. Second, the GlcNAc transferred by OGT from UDP-GlcNAc to CKII was detected using an antibody to O-GlcNAc and then the horseradish peroxidase (HRP)-labeled secondary antibody. At last, 3,3',5,5'-tetramethylbenzidine (TMB), the substrate of HRP, was used to detect the O-GlcNAcylation level of CKII which reflected the activity of OGT. Based on a series of optimization experiments, the RL2 antibody was selected for O-GlcNAc detection and the concentrations of CKII, OGT, and UDP-GlcNAc were determined in this study. ST045849, a commercial OGT inhibitor, was used to verify the functionality of the system. Altogether, this study showed a method that could be applied to detect OGT activity and screen OGT inhibitors.

Simultaneous determination of nickel and copper by H-point standard addition method-first-order derivative spectrophotometry in plant samples after separation and preconcentration on modified natural clinoptilolite as a new sorbent.

PubMed

Roohparvar, Rasool; Taher, Mohammad Ali; Mohadesi, Alireza

2008-01-01

For the simultaneous determination of nickel(ll) and copper(ll) in plant samples, a rapid and accurate method was developed. In this method, solid-phase extraction (SPE) and first-order derivative spectrophotometry (FDS) are combined, and the result is coupled with the H-point standard addition method (HPSAM). Compared with normal spectrophotometry, derivative spectrophotometry offers the advantages of increased selectivity and sensitivity. As there is no need for carrying out any pretreatment of the sample, the spectrophotometry method is easy, but because of a high detection limit, it is not so practical. In order to decrease the detection limit, it is suggested to combine spectrophotometry with a preconcentration method such as SPE. In the present work, after separation and preconcentration of Ni(ll) and Cu(ll) on modified clinoptilolite zeolite that is loaded with 2-[1-(2-hydroxy-5-sulforphenyl)-3-phenyl-5-formaza-no]-benzoic acid monosodium salt (zincon) as a selective chromogenic reagent, FDS-HPSAM, which is a simple and selective spectrophotometric method, has been applied for simultaneous determination of these ions. With optimum conditions, the detection limit in original solutions is 0.7 and 0.5 ng/mL, respectively, for nickel and copper. The linear concentration ranges in the proposed method for nickel and copper ions in original solutions are 1.1 to 3.0 x 10(3) and 0.9 to 2.0 x 10(3) ng/mL, respectively. The recommended procedure is applied to successful determination of Cu(ll) and Ni(ll) in standard and real samples.

Regional Principal Color Based Saliency Detection

PubMed Central

Lou, Jing; Ren, Mingwu; Wang, Huan

2014-01-01

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

Method for identifying and quantifying nucleic acid sequence aberrations

DOEpatents

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

1998-01-01

A method for detecting nucleic acid sequence aberrations by detecting nucleic acid sequences having both a first and a second nucleic acid sequence type, the presence of the first and second sequence type on the same nucleic acid sequence indicating the presence of a nucleic acid sequence aberration. The method uses a first hybridization probe which includes a nucleic acid sequence that is complementary to a first sequence type and a first complexing agent capable of attaching to a second complexing agent and a second hybridization probe which includes a nucleic acid sequence that selectively hybridizes to the second nucleic acid sequence type over the first sequence type and includes a detectable marker for detecting the second hybridization probe.

Method for identifying and quantifying nucleic acid sequence aberrations

DOEpatents

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

1998-07-21

A method is disclosed for detecting nucleic acid sequence aberrations by detecting nucleic acid sequences having both a first and a second nucleic acid sequence type, the presence of the first and second sequence type on the same nucleic acid sequence indicating the presence of a nucleic acid sequence aberration. The method uses a first hybridization probe which includes a nucleic acid sequence that is complementary to a first sequence type and a first complexing agent capable of attaching to a second complexing agent and a second hybridization probe which includes a nucleic acid sequence that selectively hybridizes to the second nucleic acid sequence type over the first sequence type and includes a detectable marker for detecting the second hybridization probe. 11 figs.

Detection of Atrial Fibrillation Using Artifical Neural Network with Power Spectrum Density of RR Interval of Electrocardiogram

NASA Astrophysics Data System (ADS)

Afdala, Adfal; Nuryani, Nuryani; Satrio Nugroho, Anto

2017-01-01

Atrial fibrillation (AF) is a disorder of the heart with fairly high mortality in adults. AF is a common heart arrythmia which is characterized by a missing or irregular contraction of atria. Therefore, finding a method to detect atrial fibrillation is necessary. In this article a system to detect atrial fibrillation has been proposed. Detection system utilized backpropagation artifical neural network. Data input in this method includes power spectrum density of R-peaks interval of electrocardiogram which is selected by wrapping method. This research uses parameter learning rate, momentum, epoch and hidden layer. System produces good performance with accuracy, sensitivity, and specificity of 83.55%, 86.72 % and 81.47 %, respectively.

Improving detection of low SNR targets using moment-based detection

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Capture and detection of Staphylococcus aureus with dual labeled aptamers to cell surface components.

PubMed

Ramlal, Shylaja; Mondal, Bhairab; Lavu, Padma Sudharani; N, Bhavanashri; Kingston, Joseph

2018-01-16

In the present study, a high throughput whole cell SELEX method has been applied successfully in selecting specific aptamers against whole cells of Staphylococcus aureus, a potent food poisoning bacterium. A total ten rounds of SELEX and three rounds of intermittent counter SELEX, was performed to obtain specific aptamers. Obtained oligonucleotide pool were cloned, sequenced and then grouped into different families based on their primary sequence homology and secondary structure similarity. FITC labeled sequences from different families were selected for further characterization via flow cytometry analysis. The dissociation constant (K d ) values of specific and higher binders ranged from 34 to 128nM. Binding assays to assess the selectivity of aptamer RAB10, RAB 20, RAB 28 and RAB 35 demonstrated high affinity against S. aureus and low binding affinity for other bacteria. To demonstrate the potential use of the aptamer a sensitive dual labeled sandwich detection system was developed using aptamer RAB10 and RAB 35 with a detection limit of 10 2 CFU/mL. Furthermore detection from mixed cell population and spiked sample emphasized the robustness as well as applicability of the developed method. Altogether, the established assay could be a reliable detection tool for the routine investigation of Staphylococcus aureus in samples from food and clinical sources. Copyright © 2017. Published by Elsevier B.V.

A highly sensitive and selective optical sensor for Pb2+ by using conjugated polymers and label-free oligonucleotides.

PubMed

Lu, Yan; Li, Xiang; Wang, Gongke; Tang, Wen

2013-01-15

The detection of Pb(2+) with DNA-based biosensor is usually susceptible to severe interference from Hg(2+) because of the T-Hg(2+)-T interaction between Hg(2+) and T residues. In this study, we developed a rapid, sensitive, selective and label-free sensor for the detection of Pb(2+) in the presence of Hg(2+) based on the Pb(2+)-induced G-quadruplex formation with cationic water-soluble conjugated polymer (PMNT) as a "polymeric stain" to transduce optical signal. We selected a specific sequence oligonucleotide, TBAA (5'-GGAAGGTGTGGAAGG-3'), which can form a G-quadruplex structure upon the addition of Pb(2+). This strategy provided a promising alternative to Pb(2+) determination in the presence of Hg(2+) instead of the universal masking agents of Hg(2+) (such as CN(-), SCN(-)). Based on this observation, a simple "mix-and-detect" optical sensor for the detection of Pb(2+) was proposed due to the distinguishable optical properties of PMNT-ssDNA and PMNT-(G-quadruplex) complexes. By this method, we could identify micromolar Pb(2+) concentrations within 5min even with the naked eye. Furthermore, the detection limit was improved to the nanomolar range by the fluorometric method. We also successfully utilized this biosensor for the determination of Pb(2+) in tap water samples. Copyright © 2012 Elsevier B.V. All rights reserved.

One-pot fabrication of FRET-based fluorescent probe for detecting copper ion and sulfide anion in 100% aqueous media

NASA Astrophysics Data System (ADS)

Lv, Kun; Chen, Jian; Wang, Hong; Zhang, Peisheng; Yu, Maolin; Long, Yunfei; Yi, Pinggui

2017-04-01

The design of effective tools for detecting copper ion (Cu2 +) and sulfide anion (S2 -) is of great importance due to the abnormal level of Cu2 + and S2 - has been associated with an increase in risk of many diseases. Herein, we report on the fabrication of fluorescence resonance energy transfer (FRET) based fluorescent probe PF (PEI-FITC) for detecting Cu2 + and S2 - in 100% aqueous media via a facile one-pot method by covalent linking fluorescein isothiocyanate (FITC) with branched-polyethylenimine (b-PEI). PF could selectively coordinate with Cu2 + among 10 metal ions to form PF-Cu2 + complex, resulting in fluorescence quenching through FRET mechanism. Furthermore, the in situ generated PF-Cu2 + complex can be used to selectively detect S2 - based on the displacement approach, resulting in an off-on type sensing. There is no obvious interference from other anions, such as Cl-, NO3-, ClO4-, SO42 -, HCO3-, CO32 -, Br-, HPO42 -, F- and S2O32 -. In addition, PF was successfully used to determine Cu2 + and S2 - in human serum and tap water samples. Therefore, the FRET-based probe PF may provide a new method for selective detection of multifarious analysts in biological and environmental applications, and even hold promise for application in more complicated systems.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Distribution majorization of corner points by reinforcement learning for moving object detection

NASA Astrophysics Data System (ADS)

Wu, Hao; Yu, Hao; Zhou, Dongxiang; Cheng, Yongqiang

2018-04-01

Corner points play an important role in moving object detection, especially in the case of free-moving camera. Corner points provide more accurate information than other pixels and reduce the computation which is unnecessary. Previous works only use intensity information to locate the corner points, however, the information that former and the last frames provided also can be used. We utilize the information to focus on more valuable area and ignore the invaluable area. The proposed algorithm is based on reinforcement learning, which regards the detection of corner points as a Markov process. In the Markov model, the video to be detected is regarded as environment, the selections of blocks for one corner point are regarded as actions and the performance of detection is regarded as state. Corner points are assigned to be the blocks which are seperated from original whole image. Experimentally, we select a conventional method which uses marching and Random Sample Consensus algorithm to obtain objects as the main framework and utilize our algorithm to improve the result. The comparison between the conventional method and the same one with our algorithm show that our algorithm reduce 70% of the false detection.

A facile strategy for achieving high selective Zn(II) fluorescence probe by regulating the solvent polarity.

PubMed

Wang, Haoping; Kang, Tiantian; Wang, Xiaoju; Feng, Liheng

2018-07-01

A simple Schiff base comprised of tris(2-aminoethyl)amine and salicylaldehyde was designed and synthesized by one-step reaction. Although this compound has poor selectivity for metal ions in acetonitrile, it shows high selectivity and sensitivity detection for Zn(II) ions through adjusting the solvent polarity (the volume ratio of CH 3 CN/H 2 O). In other words, this work provides a facile way to realize a transformation from poor to excellent feature for fluorescent probes. The bonding mode of this probe with Zn(II) ions was verified by 1 H NMR and MS assays. The stoichiometric ratio of the probe with Zn(II) is 1:1 (mole), which matches with the Job-plot assay. The detection limitation of the probe for Zn(II) is up to 1 × 10 -8 mol/L. The electrochemical property of the probe combined with Zn(II) was investigated by cyclic voltammetry method, and the result agreed with the theoretical calculation by the Gaussian 09 software. The probe for Zn(II) could be applied in practical samples and biological systems. The main contribution of this work lies in providing a very simple method to realize the selectivity transformation for poor selective probes. The providing way is a simple, easy and low-cost method for obtaining high selectively fluorescence probes. Copyright © 2018 Elsevier B.V. All rights reserved.

Monoclonal antibodies for the separate detection of halodeoxyuridines and method for their use

DOEpatents

Vanderlaan, M.; Watkins, B.E.; Stanker, L.H.

1991-10-01

Monoclonal antibodies are described which have specific affinities for halogenated nucleoside analogs and are preferentially selective for one particular halogen. Such antibodies, when incorporated into immunochemical reagents, may be used to identify and independently quantify the cell division character of more than one population or subpopulation in flow cytometric measurements. Independent assessment of division activity in cell sub-populations facilitates selection of appropriate time and dose for administration of anti-proliferative agents. The hybridomas which secrete halogen selective antibodies and the method of making them are described. 14 figures.

Monoclonal antibodies for the separate detection of halodeoxyuridines and method for their use

DOEpatents

Vanderlaan, Martin; Watkins, Bruce E.; Stanker, Larry H.

1991-01-01

Monoclonal antibodies are described which have specific affinities for halogenated nucleoside analogs and are preferentially selective for one particular halogen. Such antibodies, when incorporated into immunochemical reagents, may be used to identify and independently quantify the cell division character of more than one population or subpopulation in flow cytometric measurements. Independent assessment of division activity in cell sub-populations facilitates selection of appropriate time and dose for administration of anti-proliferative agents. The hybridomas which secrete halogen selective antibodies and the method of making them are described.

Stochastic model search with binary outcomes for genome-wide association studies

PubMed Central

Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-01-01

Objective The spread of case–control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Materials and methods Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. Results BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. Discussion BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. Conclusion The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model. PMID:22534080

Artificial-epitope mapping for CK-MB assay.

PubMed

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

2011-06-07

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

T-wave end detection using neural networks and Support Vector Machines.

PubMed

Suárez-León, Alexander Alexeis; Varon, Carolina; Willems, Rik; Van Huffel, Sabine; Vázquez-Seisdedos, Carlos Román

2018-05-01

In this paper we propose a new approach for detecting the end of the T-wave in the electrocardiogram (ECG) using Neural Networks and Support Vector Machines. Both, Multilayer Perceptron (MLP) neural networks and Fixed-Size Least-Squares Support Vector Machines (FS-LSSVM) were used as regression algorithms to determine the end of the T-wave. Different strategies for selecting the training set such as random selection, k-means, robust clustering and maximum quadratic (Rényi) entropy were evaluated. Individual parameters were tuned for each method during training and the results are given for the evaluation set. A comparison between MLP and FS-LSSVM approaches was performed. Finally, a fair comparison of the FS-LSSVM method with other state-of-the-art algorithms for detecting the end of the T-wave was included. The experimental results show that FS-LSSVM approaches are more suitable as regression algorithms than MLP neural networks. Despite the small training sets used, the FS-LSSVM methods outperformed the state-of-the-art techniques. FS-LSSVM can be successfully used as a T-wave end detection algorithm in ECG even with small training set sizes. Copyright © 2018 Elsevier Ltd. All rights reserved.

A clustering algorithm for determining community structure in complex networks

NASA Astrophysics Data System (ADS)

Jin, Hong; Yu, Wei; Li, ShiJun

2018-02-01

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

Carbon dots based fluorescent sensor for sensitive determination of hydroquinone.

PubMed

Ni, Pengjuan; Dai, Haichao; Li, Zhen; Sun, Yujing; Hu, Jingting; Jiang, Shu; Wang, Yilin; Li, Zhuang

2015-11-01

In this paper, a novel biosensor based on Carbon dots (C-dots) for sensitive detection of hydroquinone (H2Q) is reported. It is interesting to find that the fluorescence of the C-dots could be quenched by H2Q directly. The possible quenching mechanism is proposed, which shows that the quenching effect may be caused by the electron transfer from C-dots to oxidized H2Q-quinone. Based on the above principle, a novel C-dots based fluorescent probe has been successfully applied to detect H2Q. Under the optimal condition, detection limit down to 0.1 μM is obtained, which is far below U.S. Environmental Protection Agency estimated wastewater discharge limit of 0.5 mg/L. Moreover, the proposed method shows high selectivity for H2Q over a number of potential interfering species. Finally, several water samples spiked with H2Q are analyzed utilizing the sensing method with satisfactory recovery. The proposed method is simple with high sensitivity and excellent selectivity, which provides a new approach for the detection of various analytes that can be transformed into quinone. Copyright © 2015 Elsevier B.V. All rights reserved.

Automatic Building Damage Detection Method Using High-Resolution Remote Sensing Images and 3d GIS Model

NASA Astrophysics Data System (ADS)

Tu, Jihui; Sui, Haigang; Feng, Wenqing; Song, Zhina

2016-06-01

In this paper, a novel approach of building damaged detection is proposed using high resolution remote sensing images and 3D GIS-Model data. Traditional building damage detection method considers to detect damaged building due to earthquake, but little attention has been paid to analyze various building damaged types(e.g., trivial damaged, severely damaged and totally collapsed.) Therefore, we want to detect the different building damaged type using 2D and 3D feature of scenes because the real world we live in is a 3D space. The proposed method generalizes that the image geometric correction method firstly corrects the post-disasters remote sensing image using the 3D GIS model or RPC parameters, then detects the different building damaged types using the change of the height and area between the pre- and post-disasters and the texture feature of post-disasters. The results, evaluated on a selected study site of the Beichuan earthquake ruins, Sichuan, show that this method is feasible and effective in building damage detection. It has also shown that the proposed method is easily applicable and well suited for rapid damage assessment after natural disasters.

APTS and rGO co-functionalized pyrenated fluorescent nanonets for representative vapor phase nitroaromatic explosive detection.

PubMed

Guo, Linjuan; Zu, Baiyi; Yang, Zheng; Cao, Hongyu; Zheng, Xuefang; Dou, Xincun

2014-01-01

For the first time, flexible PVP/pyrene/APTS/rGO fluorescent nanonets were designed and synthesized via a one-step electrospinning method to detect representative subsaturated nitroaromatic explosive vapor. The functional fluorescent nanonets, which were highly stable in air, showed an 81% quenching efficiency towards TNT vapor (∼10 ppb) with an exposure time of 540 s at room temperature. The nice performance of the nanonets was ascribed to the synergistic effects induced by the specific adsorption properties of APTS, the fast charge transfer properties and the effective π-π interaction with pyrene and TNT of rGO. Compared to the analogues of TNT, the PVP/pyrene/APTS/rGO nanonets showed notable selectivity towards TNT and DNT vapors. The explored functionalization method opens up brand new insight into sensitive and selective detection of vapor phase nitroaromatic explosives.

Proteomic methods for analysis of S-nitrosation⋄

PubMed Central

Kettenhofen, Nicholas; Broniowska, Katarzyna; Keszler, Agnes; Zhang, Yanhong; Hogg, Neil

2007-01-01

This review discusses proteomic methods to detect and identify S-nitrosated proteins. Protein S-nitrosation, the post-translational modification of thiol residues to form S-nitrosothiols, has been suggested to be a mechanism of cellular redox signaling by which nitric oxide can alter cellular function through modification of protein thiol residues. It has become apparent that methods that will detect and identify low levels of S-nitrosated protein in complex protein mixtures are required in order to fully appreciate the range, extent and selectivity of this modification in both physiological and pathological conditions. While many advances have been made in the detection of either total cellular S-nitrosation or individual S-nitrosothiols, proteomic methods for the detection of S-nitrosation are in relative infancy. This review will discuss the major methods that have been used for the proteomic analysis of protein S-nitrosation and discuss the pros and cons of this methodology. PMID:17360249

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

Research on technology of online gas chromatograph for SF6 decomposition products

NASA Astrophysics Data System (ADS)

Li, L.; Fan, X. P.; Zhou, Y. Y.; Tang, N.; Zou, Z. L.; Liu, M. Z.; Huang, G. J.

2017-12-01

Sulfur hexafluoride (SF6) decomposition products were qualitatively and quantitatively analyzed by several gas chromatographs in the laboratory. Test conditions and methods were selected and optimized to minimize and eliminate the SF6’ influences on detection of other trace components. The effective separation and detection of selected characteristic gases were achieved. And by comparison among different types of gas chromatograph, it was found that GPTR-S101 can effectively separate and detect SF6 decomposition products and has best the best detection limit and sensitivity. On the basis of GPTR-S101, online gas chromatograph for SF6decomposition products (GPTR-S201) was developed. It lays the foundation for further online monitoring and diagnosis of SF6.

Incipient Fault Detection for Rolling Element Bearings under Varying Speed Conditions.

PubMed

Xue, Lang; Li, Naipeng; Lei, Yaguo; Li, Ningbo

2017-06-20

Varying speed conditions bring a huge challenge to incipient fault detection of rolling element bearings because both the change of speed and faults could lead to the amplitude fluctuation of vibration signals. Effective detection methods need to be developed to eliminate the influence of speed variation. This paper proposes an incipient fault detection method for bearings under varying speed conditions. Firstly, relative residual (RR) features are extracted, which are insensitive to the varying speed conditions and are able to reflect the degradation trend of bearings. Then, a health indicator named selected negative log-likelihood probability (SNLLP) is constructed to fuse a feature set including RR features and non-dimensional features. Finally, based on the constructed SNLLP health indicator, a novel alarm trigger mechanism is designed to detect the incipient fault. The proposed method is demonstrated using vibration signals from bearing tests and industrial wind turbines. The results verify the effectiveness of the proposed method for incipient fault detection of rolling element bearings under varying speed conditions.

Incipient Fault Detection for Rolling Element Bearings under Varying Speed Conditions

PubMed Central

Xue, Lang; Li, Naipeng; Lei, Yaguo; Li, Ningbo

2017-01-01

Varying speed conditions bring a huge challenge to incipient fault detection of rolling element bearings because both the change of speed and faults could lead to the amplitude fluctuation of vibration signals. Effective detection methods need to be developed to eliminate the influence of speed variation. This paper proposes an incipient fault detection method for bearings under varying speed conditions. Firstly, relative residual (RR) features are extracted, which are insensitive to the varying speed conditions and are able to reflect the degradation trend of bearings. Then, a health indicator named selected negative log-likelihood probability (SNLLP) is constructed to fuse a feature set including RR features and non-dimensional features. Finally, based on the constructed SNLLP health indicator, a novel alarm trigger mechanism is designed to detect the incipient fault. The proposed method is demonstrated using vibration signals from bearing tests and industrial wind turbines. The results verify the effectiveness of the proposed method for incipient fault detection of rolling element bearings under varying speed conditions. PMID:28773035

"Turn-off" fluorescent data array sensor based on double quantum dots coupled with chemometrics for highly sensitive and selective detection of multicomponent pesticides.

PubMed

Fan, Yao; Liu, Li; Sun, Donglei; Lan, Hanyue; Fu, Haiyan; Yang, Tianming; She, Yuanbin; Ni, Chuang

2016-04-15

As a popular detection model, the fluorescence "turn-off" sensor based on quantum dots (QDs) has already been successfully employed in the detections of many materials, especially in the researches on the interactions between pesticides. However, the previous studies are mainly focused on simple single track or the comparison based on similar concentration of drugs. In this work, a new detection method based on the fluorescence "turn-off" model with water-soluble ZnCdSe and CdSe QDs simultaneously as the fluorescent probes is established to detect various pesticides. The fluorescence of the two QDs can be quenched by different pesticides with varying degrees, which leads to the differences in positions and intensities of two peaks. By combining with chemometrics methods, all the pesticides can be qualitative and quantitative respectively even in real samples with the limit of detection was 2 × 10(-8) mol L(-1) and a recognition rate of 100%. This work is, to the best of our knowledge, the first report on the detection of pesticides based on the fluorescence quenching phenomenon of double quantum dots combined with chemometrics methods. What's more, the excellent selectivity of the system has been verified in different mediums such as mixed ion disruption, waste water, tea and water extraction liquid drugs. Copyright © 2016 Elsevier B.V. All rights reserved.

Simultaneous determination of triple therapy for Helicobacter pylori in human plasma by reversed phase chromatography with online wavelength switching

NASA Astrophysics Data System (ADS)

Ahmed, Sameh; Atia, Noha N.

2015-02-01

The infection of gastric mucosa by Helicobacter pylori (HP) is an essential cofactor in the aetiology of gastroduodenal ulcer and gastric carcinoma. Because of the bacterial resistance, combination therapy containing omeprazole (OME), tinidazole (TNZ) and clarithromycin (CLA) is commonly used for eradication of HP. However, the simultaneous determination of the triple therapy in human plasma was not reported. A simple, reproducible, and selective HPLC method was developed for the simultaneous determination of the triple therapy mixture used for management of HP infections in human plasma. An HPLC procedure based on a liquid-liquid extraction, enrichment of the analytes and subsequent reversed-phase chromatography with UV detection was used. To enable sensitive and selective detection, the method involved the use of online wavelength switching detection, with two different detection wavelengths; 280 nm for detection of OME and TNZ and 210 nm for detection of CLA. Separations were performed on C18 analytical column with acetonitrile-10 mM phosphate buffer of pH = 3.0 at flow rate of 1.0 mL min-1. The linear ranges in human plasma were 0.05-10 μg mL-1 with correlation coefficients >0.9990. The detection limits in human plasma were 0.02-0.07 μg mL-1. Validation parameters were assessed in compliance with US-FDA guidelines. The method proved to be valuable for the therapeutic drug monitoring after oral administration of triple therapy tablets.

Probing the symmetry of the potential of localized surface plasmon resonances with phase-shaped electron beams.

PubMed

Guzzinati, Giulio; Béché, Armand; Lourenço-Martins, Hugo; Martin, Jérôme; Kociak, Mathieu; Verbeeck, Jo

2017-04-12

Plasmonics, the science and technology of the interaction of light with metallic objects, is fundamentally changing the way we can detect, generate and manipulate light. Although the field is progressing swiftly, thanks to the availability of nanoscale manufacturing and analysis methods, fundamental properties such as the plasmonic excitations' symmetries cannot be accessed directly, leading to a partial, sometimes incorrect, understanding of their properties. Here we overcome this limitation by deliberately shaping the wave function of an electron beam to match a plasmonic excitations' symmetry in a modified transmission electron microscope. We show experimentally and theoretically that this offers selective detection of specific plasmon modes within metallic nanoparticles, while excluding modes with other symmetries. This method resembles the widespread use of polarized light for the selective excitation of plasmon modes with the advantage of locally probing the response of individual plasmonic objects and a far wider range of symmetry selection criteria.

Highly selective detection of individual nuclear spins with rotary echo on an electron spin probe

PubMed Central

Mkhitaryan, V. V.; Jelezko, F.; Dobrovitski, V. V.

2015-01-01

We consider an electronic spin, such as a nitrogen-vacancy center in diamond, weakly coupled to a large number of nuclear spins, and subjected to the Rabi driving with a periodically alternating phase. We show that by switching the driving phase synchronously with the precession of a given nuclear spin, the interaction to this spin is selectively enhanced, while the rest of the bath remains decoupled. The enhancement is of resonant character. The key feature of the suggested scheme is that the width of the resonance is adjustable, and can be greatly decreased by increasing the driving strength. Thus, the resonance can be significantly narrowed, by a factor of 10–100 in comparison with the existing detection methods. Significant improvement in selectivity is explained analytically and confirmed by direct numerical many-spin simulations. The method can be applied to a wide range of solid-state systems. PMID:26497777

Circulating Tumor Cells: Moving Biological Insights into Detection

PubMed Central

Chen, Lichan; Bode, Ann M; Dong, Zigang

2017-01-01

Circulating tumor cells (CTCs) have shown promising potential as liquid biopsies that facilitate early detection, prognosis, therapeutic target selection and monitoring treatment response. CTCs in most cancer patients are low in abundance and heterogeneous in morphological and phenotypic profiles, which complicate their enrichment and subsequent characterization. Several methodologies for CTC enrichment and characterization have been developed over the past few years. However, integrating recent advances in CTC biology into these methodologies and the selection of appropriate enrichment and characterization methods for specific applications are needed to improve the reliability of CTC biopsies. In this review, we summarize recent advances in the studies of CTC biology, including the mechanisms of their generation and their potential forms of existence in blood, as well as the current CTC enrichment technologies. We then critically examine the selection of methods for appropriately enriching CTCs for further investigation of their clinical applications. PMID:28819450

Induction heating apparatus and methods of operation thereof

DOEpatents

Richardson, John G.

2006-08-01

Methods of operation of an induction melter include providing material within a cooled crucible proximate an inductor. A desired electromagnetic flux skin depth for heating the material within the crucible may be selected, and a frequency of an alternating current for energizing the inductor and for producing the desired skin depth may be selected. The alternating current frequency may be adjusted after energizing the inductor to maintain the desired electromagnetic flux skin depth. The desired skin depth may be substantially maintained as the temperature of the material varies. An induction heating apparatus includes a sensor configured to detect changes in at least one physical characteristic of a material to be heated in a crucible, and a controller configured for selectively varying a frequency of an alternating current for energizing an inductor at least partially in response to changes in the physical characteristic to be detected by the sensor.

Selection of test paths for solder joint intermittent connection faults under DC stimulus

NASA Astrophysics Data System (ADS)

Huakang, Li; Kehong, Lv; Jing, Qiu; Guanjun, Liu; Bailiang, Chen

2018-06-01

The test path of solder joint intermittent connection faults under direct-current stimulus is examined in this paper. According to the physical structure of the circuit, a network model is established first. A network node is utilised to represent the test node. The path edge refers to the number of intermittent connection faults in the path. Then, the selection criteria of the test path based on the node degree index are proposed and the solder joint intermittent connection faults are covered using fewer test paths. Finally, three circuits are selected to verify the method. To test if the intermittent fault is covered by the test paths, the intermittent fault is simulated by a switch. The results show that the proposed method can detect the solder joint intermittent connection fault using fewer test paths. Additionally, the number of detection steps is greatly reduced without compromising fault coverage.

Detection of biomarkers for Hepatocellular Carcinoma using a hybrid univariate gene selection methods

PubMed Central

2012-01-01

Background Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC). The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC. Results In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators) in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery) databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers) genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy). A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer) in the top ten genes of the list of intersected genes. Conclusions To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when used individually according to biological interpretation and the examination of gene expression signal profiles. PMID:22867264

Multiple-Bit Differential Detection of OQPSK

NASA Technical Reports Server (NTRS)

Simon, Marvin

2005-01-01

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

Boronic Acid Functionalized Au Nanoparticles for Selective MicroRNA Signal Amplification in Fiber-Optic Surface Plasmon Resonance Sensing System.

PubMed

Qian, Siyu; Lin, Ming; Ji, Wei; Yuan, Huizhen; Zhang, Yang; Jing, Zhenguo; Zhao, Jianzhang; Masson, Jean-François; Peng, Wei

2018-05-25

MicroRNA (miRNA) regulates gene expression and plays a fundamental role in multiple biological processes. However, if both single-stranded RNA and DNA can bind with capture DNA on the sensing surface, selectively amplifying the complementary RNA signal is still challenging for researchers. Fiber-optic surface plasmon resonance (SPR) sensors are small, accurate, and convenient tools for monitoring biological interaction. In this paper, we present a high sensitivity microRNA detection technique using phenylboronic acid functionalized Au nanoparticles (PBA-AuNPs) in fiber-optic SPR sensing systems. Due to the inherent difficulty directly detecting the hybridized RNA on the sensing surface, the PBA-AuNPs were used to selectively amplify the signal of target miRNA. The result shows that the method has high selectivity and sensitivity for miRNA, with a detection limit at 2.7 × 10 -13 M (0.27 pM). This PBA-AuNPs amplification strategy is universally applicable for RNA detection with various sensing technologies, such as surface-enhanced Raman spectroscopy and electrochemistry, among others.

Highly selective and sensitive detection of miRNA based on toehold-mediated strand displacement reaction and DNA tetrahedron substrate.

PubMed

Li, Wei; Jiang, Wei; Ding, Yongshun; Wang, Lei

2015-09-15

MicroRNAs (miRNAs) play important roles in a variety of biological processes and have been regarded as tumor biomarkers in cancer diagnosis and prognosis. In this work, a single-molecule counting method for miRNA analysis was proposed based on toehold-mediated strand displacement reaction (SDR) and DNA tetrahedron substrate. Firstly, a specially designed DNA tetrahedron was assembled with a hairpin at one of the vertex, which has an overhanging toehold domain. Then, the DNA tetrahedron was immobilized on the epoxy-functional glass slide by epoxy-amine reaction, forming a DNA tetrahedron substrate. Next, the target miRNA perhybridized with the toehold domain and initiated a strand displacement reaction along with the unfolding of the hairpin, realizing the selective recognization of miRNA. Finally, a biotin labeled detection DNA was hybridized with the new emerging single strand and the streptavidin coated QDs were used as fluorescent probes. Fluorescent images were acquired via epi-fluorescence microscopy, the numbers of fluorescence dots were counted one by one for quantification. The detection limit is 5 fM, which displayed an excellent sensitivity. Moreover, the proposed method which can accurately be identified the target miRNA among its family members, demonstrated an admirable selectivity. Furthermore, miRNA analysis in total RNA samples from human lung tissues was performed, suggesting the feasibility of this method for quantitative detection of miRNA in biomedical research and early clinical diagnostics. Copyright © 2015 Elsevier B.V. All rights reserved.

In house validation of a high resolution mass spectrometry Orbitrap-based method for multiple allergen detection in a processed model food.

PubMed

Pilolli, Rosa; De Angelis, Elisabetta; Monaci, Linda

2018-02-13

In recent years, mass spectrometry (MS) has been establishing its role in the development of analytical methods for multiple allergen detection, but most analyses are being carried out on low-resolution mass spectrometers such as triple quadrupole or ion traps. In this investigation, performance provided by a high resolution (HR) hybrid quadrupole-Orbitrap™ MS platform for the multiple allergens detection in processed food matrix is presented. In particular, three different acquisition modes were compared: full-MS, targeted-selected ion monitoring with data-dependent fragmentation (t-SIM/dd2), and parallel reaction monitoring. In order to challenge the HR-MS platform, the sample preparation was kept as simple as possible, limited to a 30-min ultrasound-aided protein extraction followed by clean-up with disposable size exclusion cartridges. Selected peptide markers tracing for five allergenic ingredients namely skim milk, whole egg, soy flour, ground hazelnut, and ground peanut were monitored in home-made cookies chosen as model processed matrix. Timed t-SIM/dd2 was found the best choice as a good compromise between sensitivity and accuracy, accomplishing the detection of 17 peptides originating from the five allergens in the same run. The optimized method was validated in-house through the evaluation of matrix and processing effects, recoveries, and precision. The selected quantitative markers for each allergenic ingredient provided quantification of 60-100 μg ingred /g allergenic ingredient/matrix in incurred cookies.

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

PubMed

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

1998-10-01

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

Three-step HPLC-ESI-MS/MS procedure for screening and identifying non-target flavonoid derivatives

NASA Astrophysics Data System (ADS)

Rak, Gábor; Fodor, Péter; Abrankó, László

2010-02-01

A three-step HPLC-ESI-MS/MS procedure is designed for screening and identification of non-target flavonoid derivatives of selected flavonoid aglycones. In this method the five commonly appearing aglycones (apigenin, luteolin, myricetin, naringenin and quercetin) were selected. The method consists of three individual mass spectrometric experiments of which the first two were implemented within a single chromatographic acquisition. The third step was carried out during a replicate chromatographic run using the same RP-HPLC conditions. The first step, a multiple reaction monitoring (MRM) scan of the aglycones was performed to define the number of derivatives relating to the selected aglycones. For this purpose the characteristic aglycone parts of the unknowns were used as specific tags of the molecules, which were generated as in-source fragments. Secondly, a full scan MS experiment is performed to identify the masses of the potential derivatives of the selected aglycones. Finally, the third step had the capability to confirm the supposed derivatives. The developed method was applied to a commercially available black currant juice to demonstrate its capability to detect and identify various flavonoid glycosides without any preliminary information about their presence in the sample. As a result 13 compounds were detected and identified in total. Namely, 3 different myricetin glycosides and the myricetin aglycone 2 luteolin glycosides plus the aglycone and 3 quercetin glycosides plus the aglycone could be identified from the tested black currant sample. In the case of apigenin and naringenin only the aglycones could be detected.

Fundamentals, achievements and challenges in the electrochemical sensing of pathogens.

PubMed

Monzó, Javier; Insua, Ignacio; Fernandez-Trillo, Francisco; Rodriguez, Paramaconi

2015-11-07

Electrochemical sensors are powerful tools widely used in industrial, environmental and medical applications. The versatility of electrochemical methods allows for the investigation of chemical composition in real time and in situ. Electrochemical detection of specific biological molecules is a powerful means for detecting disease-related markers. In the last 10 years, highly-sensitive and specific methods have been developed to detect waterborne and foodborne pathogens. In this review, we classify the different electrochemical techniques used for the qualitative and quantitative detection of pathogens. The robustness of electrochemical methods allows for accurate detection even in heterogeneous and impure samples. We present a fundamental description of the three major electrochemical sensing methods used in the detection of pathogens and the advantages and disadvantages of each of these methods. In each section, we highlight recent breakthroughs, including the utilisation of microfluidics, immunomagnetic separation and multiplexing for the detection of multiple pathogens in a single device. We also include recent studies describing new strategies for the design of future immunosensing systems and protocols. The high sensitivity and selectivity, together with the portability and the cost-effectiveness of the instrumentation, enhances the demand for further development in the electrochemical detection of microbes.

"Contrasting patterns of selection at Pinus pinaster Ait. Drought stress candidate genes as revealed by genetic differentiation analyses".

PubMed

Eveno, Emmanuelle; Collada, Carmen; Guevara, M Angeles; Léger, Valérie; Soto, Alvaro; Díaz, Luis; Léger, Patrick; González-Martínez, Santiago C; Cervera, M Teresa; Plomion, Christophe; Garnier-Géré, Pauline H

2008-02-01

The importance of natural selection for shaping adaptive trait differentiation among natural populations of allogamous tree species has long been recognized. Determining the molecular basis of local adaptation remains largely unresolved, and the respective roles of selection and demography in shaping population structure are actively debated. Using a multilocus scan that aims to detect outliers from simulated neutral expectations, we analyzed patterns of nucleotide diversity and genetic differentiation at 11 polymorphic candidate genes for drought stress tolerance in phenotypically contrasted Pinus pinaster Ait. populations across its geographical range. We compared 3 coalescent-based methods: 2 frequentist-like, including 1 approach specifically developed for biallelic single nucleotide polymorphisms (SNPs) here and 1 Bayesian. Five genes showed outlier patterns that were robust across methods at the haplotype level for 2 of them. Two genes presented higher F(ST) values than expected (PR-AGP4 and erd3), suggesting that they could have been affected by the action of diversifying selection among populations. In contrast, 3 genes presented lower F(ST) values than expected (dhn-1, dhn2, and lp3-1), which could represent signatures of homogenizing selection among populations. A smaller proportion of outliers were detected at the SNP level suggesting the potential functional significance of particular combinations of sites in drought-response candidate genes. The Bayesian method appeared robust to low sample sizes, flexible to assumptions regarding migration rates, and powerful for detecting selection at the haplotype level, but the frequentist-like method adapted to SNPs was more efficient for the identification of outlier SNPs showing low differentiation. Population-specific effects estimated in the Bayesian method also revealed populations with lower immigration rates, which could have led to favorable situations for local adaptation. Outlier patterns are discussed in relation to the different genes' putative involvement in drought tolerance responses, from published results in transcriptomics and association mapping in P. pinaster and other related species. These genes clearly constitute relevant candidates for future association studies in P. pinaster.

An imbalance fault detection method based on data normalization and EMD for marine current turbines.

PubMed

Zhang, Milu; Wang, Tianzhen; Tang, Tianhao; Benbouzid, Mohamed; Diallo, Demba

2017-05-01

This paper proposes an imbalance fault detection method based on data normalization and Empirical Mode Decomposition (EMD) for variable speed direct-drive Marine Current Turbine (MCT) system. The method is based on the MCT stator current under the condition of wave and turbulence. The goal of this method is to extract blade imbalance fault feature, which is concealed by the supply frequency and the environment noise. First, a Generalized Likelihood Ratio Test (GLRT) detector is developed and the monitoring variable is selected by analyzing the relationship between the variables. Then, the selected monitoring variable is converted into a time series through data normalization, which makes the imbalance fault characteristic frequency into a constant. At the end, the monitoring variable is filtered out by EMD method to eliminate the effect of turbulence. The experiments show that the proposed method is robust against turbulence through comparing the different fault severities and the different turbulence intensities. Comparison with other methods, the experimental results indicate the feasibility and efficacy of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach.

PubMed

Nasir, Muhammad; Attique Khan, Muhammad; Sharif, Muhammad; Lali, Ikram Ullah; Saba, Tanzila; Iqbal, Tassawar

2018-02-21

Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for highly equipped environment. The recent advancements in computerized solutions for these diagnoses are highly promising with improved accuracy and efficiency. In this article, we proposed a method for the classification of melanoma and benign skin lesions. Our approach integrates preprocessing, lesion segmentation, features extraction, features selection, and classification. Preprocessing is executed in the context of hair removal by DullRazor, whereas lesion texture and color information are utilized to enhance the lesion contrast. In lesion segmentation, a hybrid technique has been implemented and results are fused using additive law of probability. Serial based method is applied subsequently that extracts and fuses the traits such as color, texture, and HOG (shape). The fused features are selected afterwards by implementing a novel Boltzman Entropy method. Finally, the selected features are classified by Support Vector Machine. The proposed method is evaluated on publically available data set PH2. Our approach has provided promising results of sensitivity 97.7%, specificity 96.7%, accuracy 97.5%, and F-score 97.5%, which are significantly better than the results of existing methods available on the same data set. The proposed method detects and classifies melanoma significantly good as compared to existing methods. © 2018 Wiley Periodicals, Inc.

The selective determination of sulfates, sulfonates and phosphates in urine by CE-MS.

PubMed

Bunz, Svenja-Catharina; Weinmann, Wolfgang; Neusüss, Christian

2010-04-01

Metabolite identification and metabolite profiling are of major importance in the pharmaceutical and clinical context. However, highly polar and ionic substances are rarely included as analytical tools are missing. In this study, we present a new method for the determination of urinary sulfates, sulfonates, phosphates and other anions of strong acids. The method comprises a CE separation using an acidic BGE (pH

A combined enrichment/polymerase chain reaction based method for the routine screening of Streptococcus agalactiae in pregnant women.

PubMed

Munari, F M; De-Paris, F; Salton, G D; Lora, P S; Giovanella, P; Machado, A B M P; Laybauer, L S; Oliveira, K R P; Ferri, C; Silveira, J L S; Laurino, C C F C; Xavier, R M; Barth, A L; Echeverrigaray, S; Laurino, J P

2012-01-01

Group B Streptococcus (GBS) is the most common cause of life-threatening infection in neonates. Guidelines from CDC recommend universal screening of pregnant women for rectovaginal GBS colonization. The objective of this study was to compare the performance of a combined enrichment/PCR based method targeting the atr gene in relation to culture using enrichment with selective broth medium (standard method) to identify the presence of GBS in pregnant women. Rectovaginal GBS samples from women at ≥36 weeks of pregnancy were obtained with a swab and analyzed by the two methods. A total of 89 samples were evaluated. The prevalence of positive results for GBS detection was considerable higher when assessed by the combined enrichment/PCR method than with the standard method (35.9% versus 22.5%, respectively). The results demonstrated that the use of selective enrichment broth followed by PCR targeting the atr gene is a highly sensitive, specific and accurate test for GBS screening in pregnant women, allowing the detection of the bacteria even in lightly colonized patients. This PCR methodology may provide a useful diagnostic tool for GBS detection and contributes for a more accurate and effective intrapartum antibiotic and lower newborn mortality and morbidity.

Epileptic Seizure Detection Based on Time-Frequency Images of EEG Signals using Gaussian Mixture Model and Gray Level Co-Occurrence Matrix Features.

PubMed

Li, Yang; Cui, Weigang; Luo, Meilin; Li, Ke; Wang, Lina

2018-01-25

The electroencephalogram (EEG) signal analysis is a valuable tool in the evaluation of neurological disorders, which is commonly used for the diagnosis of epileptic seizures. This paper presents a novel automatic EEG signal classification method for epileptic seizure detection. The proposed method first employs a continuous wavelet transform (CWT) method for obtaining the time-frequency images (TFI) of EEG signals. The processed EEG signals are then decomposed into five sub-band frequency components of clinical interest since these sub-band frequency components indicate much better discriminative characteristics. Both Gaussian Mixture Model (GMM) features and Gray Level Co-occurrence Matrix (GLCM) descriptors are then extracted from these sub-band TFI. Additionally, in order to improve classification accuracy, a compact feature selection method by combining the ReliefF and the support vector machine-based recursive feature elimination (RFE-SVM) algorithm is adopted to select the most discriminative feature subset, which is an input to the SVM with the radial basis function (RBF) for classifying epileptic seizure EEG signals. The experimental results from a publicly available benchmark database demonstrate that the proposed approach provides better classification accuracy than the recently proposed methods in the literature, indicating the effectiveness of the proposed method in the detection of epileptic seizures.

[Effect of Parasep® feces centrifuge tube method on detecting schistosome eggs].

PubMed

Ma, Nian; Zhang, Hua-ming; Liu, Xiong; Xiao, Chuan-yun; Wen, Xiao-hong; Li, Xia; Dong, Li-chun; Cui, Cai-xia; Tu, Zu-wu

2014-08-01

To evaluate the effect of the Parasep® feces centrifuge tube method on detecting schistosome eggs. A total of 803 residents aged from 6-65 years were selected in 2 schistosomiasis endemic villages, Jiangling County, Hubei Province, and their stool samples were collected and detected parallelly by the Kato-Katz technique, nylon silk egg hatching method, and Parasep® feces centrifuge tube method at the same time. Among the 803 people, 15 cases were found of schistosome egg positive, and the positive rate was 1.87%. The positive rates of the Kato-Katz technique, nylon silk egg hatching method, and Parasep® feces centrifuge tube method were 0.75%, 1.49% and 1.12%, respectively. The schistosome eggs got with the Parasep® feces centrifuge tube method were clear and easy to identify. In low endemic areas of schistosomiasis, the Parasep® feces centrifuge tube method can be used as schistosomiasis japonica etiology diagnosis method.

Peak tree: a new tool for multiscale hierarchical representation and peak detection of mass spectrometry data.

PubMed

Zhang, Peng; Li, Houqiang; Wang, Honghui; Wong, Stephen T C; Zhou, Xiaobo

2011-01-01

Peak detection is one of the most important steps in mass spectrometry (MS) analysis. However, the detection result is greatly affected by severe spectrum variations. Unfortunately, most current peak detection methods are neither flexible enough to revise false detection results nor robust enough to resist spectrum variations. To improve flexibility, we introduce peak tree to represent the peak information in MS spectra. Each tree node is a peak judgment on a range of scales, and each tree decomposition, as a set of nodes, is a candidate peak detection result. To improve robustness, we combine peak detection and common peak alignment into a closed-loop framework, which finds the optimal decomposition via both peak intensity and common peak information. The common peak information is derived and loopily refined from the density clustering of the latest peak detection result. Finally, we present an improved ant colony optimization biomarker selection method to build a whole MS analysis system. Experiment shows that our peak detection method can better resist spectrum variations and provide higher sensitivity and lower false detection rates than conventional methods. The benefits from our peak-tree-based system for MS disease analysis are also proved on real SELDI data.

Decoration of silicon nanostructures with copper particles for simultaneous selective capture and mass spectrometry detection of His-tagged model peptide.

PubMed

Coffinier, Yannick; Kurylo, Ievgen; Drobecq, Hervé; Szunerits, Sabine; Melnyk, Oleg; Zaitsev, Vladimir N; Boukherroub, Rabah

2014-10-21

We present in this work a simple and fast preparation method of a new affinity surface-assisted laser/desorption ionization mass spectrometry (SALDI-MS) substrate based on silicon nanostructures decorated with copper particles. The silicon nanostructures were fabricated by the metal-assisted chemical etching (MACE) method. Then, superhydrophilic areas surrounded by superhydrophobic regions were formed through hydrosilylation reaction of 1-octadecene, followed by local degradation of the octadecyl layer. After that, copper particles were deposited in the hydrophilic areas by using the electroless method. We have demonstrated that these surfaces were able to perform high selective capture of model His-tag peptide even in a complex mixture such as serum solution. Then, the captured peptide was detected by mass spectrometry at a femtomolar level without the need of organic matrix.

Determination of Low Concentrations of Acetochlor in Water by Automated Solid-Phase Extraction and Gas Chromatography with Mass-Selective Detection

USGS Publications Warehouse

Lindley, C.E.; Stewart, J.T.; Sandstrom, M.W.

1996-01-01

A sensitive and reliable gas chromatographic/mass spectrometric (GC/MS) method for determining acetochlor in environmental water samples was developed. The method involves automated extraction of the herbicide from a filtered 1 L water sample through a C18 solid-phase extraction column, elution from the column with hexane-isopropyl alcohol (3 + 1), and concentration of the extract with nitrogen gas. The herbicide is quantitated by capillary/column GC/MS with selected-ion monitoring of 3 characteristic ions. The single-operator method detection limit for reagent water samples is 0.0015 ??g/L. Mean recoveries ranged from about 92 to 115% for 3 water matrixes fortified at 0.05 and 0.5 ??g/L. Average single-operator precision, over the course of 1 week, was better than 5%.

Detector location selection based on VIP analysis in near-infrared detection of dural hematoma.

PubMed

Sun, Qiuming; Zhang, Yanjun; Ma, Jun; Tian, Feng; Wang, Huiquan; Liu, Dongyuan

2018-03-01

Detection of dural hematoma based on multi-channel near-infrared differential absorbance has the advantages of rapid and non-invasive detection. The location and number of detectors around the light source are critical for reducing the pathological characteristics of the prediction model on dural hematoma degree. Therefore, rational selection of detector numbers and their distances from the light source is very important. In this paper, a detector position screening method based on Variable Importance in the Projection (VIP) analysis is proposed. A preliminary modeling based on Partial Least Squares method (PLS) for the prediction of dural position μ a was established using light absorbance information from 30 detectors located 2.0-5.0 cm from the light source with a 0.1 cm interval. The mean relative error (MRE) of the dural position μ a prediction model was 4.08%. After VIP analysis, the number of detectors was reduced from 30 to 4 and the MRE of the dural position μ a prediction was reduced from 4.08% to 2.06% after the reduction in detector numbers. The prediction model after VIP detector screening still showed good prediction of the epidural position μ a . This study provided a new approach and important reference on the selection of detector location in near-infrared dural hematoma detection.

An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox

PubMed Central

Jing, Luyang; Wang, Taiyong; Zhao, Ming; Wang, Peng

2017-01-01

A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections. To address these two challenges, we propose an adaptive multi-sensor data fusion method based on deep convolutional neural networks (DCNN) for fault diagnosis. The proposed method can learn features from raw data and optimize a combination of different fusion levels adaptively to satisfy the requirements of any fault diagnosis task. The proposed method is tested through a planetary gearbox test rig. Handcraft features, manual-selected fusion levels, single sensory data, and two traditional intelligent models, back-propagation neural networks (BPNN) and a support vector machine (SVM), are used as comparisons in the experiment. The results demonstrate that the proposed method is able to detect the conditions of the planetary gearbox effectively with the best diagnosis accuracy among all comparative methods in the experiment. PMID:28230767

Paramagnetic particles coupled with an automated flow injection analysis as a tool for influenza viral protein detection.

PubMed

Krejcova, Ludmila; Dospivova, Dana; Ryvolova, Marketa; Kopel, Pavel; Hynek, David; Krizkova, Sona; Hubalek, Jaromir; Adam, Vojtech; Kizek, Rene

2012-11-01

Currently, the influenza virus infects millions of individuals every year. Since the influenza virus represents one of the greatest threats, it is necessary to develop a diagnostic technique that can quickly, inexpensively, and accurately detect the virus to effectively treat and control seasonal and pandemic strains. This study presents an alternative to current detection methods. The flow-injection analysis-based biosensor, which can rapidly and economically analyze a wide panel of influenza virus strains by using paramagnetic particles modified with glycan, can selectively bind to specific viral A/H5N1/Vietnam/1203/2004 protein-labeled quantum dots. Optimized detection of cadmium sulfide quantum dots (CdS QDs)-protein complexes connected to paramagnetic microbeads was performed using differential pulse voltammetry on the surface of a hanging mercury drop electrode (HMDE) and/or glassy carbon electrode (GCE). Detection limit (3 S/N) estimations based on cadmium(II) ions quantification were 0.1 μg/mL or 10 μg/mL viral protein at HMDE or GCE, respectively. Viral protein detection was directly determined using differential pulse voltammetry Brdicka reaction. The limit detection (3 S/N) of viral protein was estimated as 0.1 μg/mL. Streptavidin-modified paramagnetic particles were mixed with biotinylated selective glycan to modify their surfaces. Under optimized conditions (250 μg/mL of glycan, 30-min long interaction with viral protein, 25°C and 400 rpm), the viral protein labeled with quantum dots was selectively isolated and its cadmium(II) content was determined. Cadmium was present in detectable amounts of 10 ng per mg of protein. Using this method, submicrogram concentrations of viral proteins can be identified. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Pedestrian Detection Based on Adaptive Selection of Visible Light or Far-Infrared Light Camera Image by Fuzzy Inference System and Convolutional Neural Network-Based Verification.

PubMed

Kang, Jin Kyu; Hong, Hyung Gil; Park, Kang Ryoung

2017-07-08

A number of studies have been conducted to enhance the pedestrian detection accuracy of intelligent surveillance systems. However, detecting pedestrians under outdoor conditions is a challenging problem due to the varying lighting, shadows, and occlusions. In recent times, a growing number of studies have been performed on visible light camera-based pedestrian detection systems using a convolutional neural network (CNN) in order to make the pedestrian detection process more resilient to such conditions. However, visible light cameras still cannot detect pedestrians during nighttime, and are easily affected by shadows and lighting. There are many studies on CNN-based pedestrian detection through the use of far-infrared (FIR) light cameras (i.e., thermal cameras) to address such difficulties. However, when the solar radiation increases and the background temperature reaches the same level as the body temperature, it remains difficult for the FIR light camera to detect pedestrians due to the insignificant difference between the pedestrian and non-pedestrian features within the images. Researchers have been trying to solve this issue by inputting both the visible light and the FIR camera images into the CNN as the input. This, however, takes a longer time to process, and makes the system structure more complex as the CNN needs to process both camera images. This research adaptively selects a more appropriate candidate between two pedestrian images from visible light and FIR cameras based on a fuzzy inference system (FIS), and the selected candidate is verified with a CNN. Three types of databases were tested, taking into account various environmental factors using visible light and FIR cameras. The results showed that the proposed method performs better than the previously reported methods.

Revisiting negative selection algorithms.

PubMed

Ji, Zhou; Dasgupta, Dipankar

2007-01-01

This paper reviews the progress of negative selection algorithms, an anomaly/change detection approach in Artificial Immune Systems (AIS). Following its initial model, we try to identify the fundamental characteristics of this family of algorithms and summarize their diversities. There exist various elements in this method, including data representation, coverage estimate, affinity measure, and matching rules, which are discussed for different variations. The various negative selection algorithms are categorized by different criteria as well. The relationship and possible combinations with other AIS or other machine learning methods are discussed. Prospective development and applicability of negative selection algorithms and their influence on related areas are then speculated based on the discussion.

Transient dominant host-range selection using Chinese hamster ovary cells to generate marker-free recombinant viral vectors from vaccinia virus.

PubMed

Liu, Liang; Cooper, Tamara; Eldi, Preethi; Garcia-Valtanen, Pablo; Diener, Kerrilyn R; Howley, Paul M; Hayball, John D

2017-04-01

Recombinant vaccinia viruses (rVACVs) are promising antigen-delivery systems for vaccine development that are also useful as research tools. Two common methods for selection during construction of rVACV clones are (i) co-insertion of drug resistance or reporter protein genes, which requires the use of additional selection drugs or detection methods, and (ii) dominant host-range selection. The latter uses VACV variants rendered replication-incompetent in host cell lines by the deletion of host-range genes. Replicative ability is restored by co-insertion of the host-range genes, providing for dominant selection of the recombinant viruses. Here, we describe a new method for the construction of rVACVs using the cowpox CP77 protein and unmodified VACV as the starting material. Our selection system will expand the range of tools available for positive selection of rVACV during vector construction, and it is substantially more high-fidelity than approaches based on selection for drug resistance.

Detection of hydroxyapatite in calcified cardiovascular tissues.

PubMed

Lee, Jae Sam; Morrisett, Joel D; Tung, Ching-Hsuan

2012-10-01

The objective of this study is to develop a method for selective detection of the calcific (hydroxyapatite) component in human aortic smooth muscle cells in vitro and in calcified cardiovascular tissues ex vivo. This method uses a novel optical molecular imaging contrast dye, Cy-HABP-19, to target calcified cells and tissues. A peptide that mimics the binding affinity of osteocalcin was used to label hydroxyapatite in vitro and ex vivo. Morphological changes in vascular smooth muscle cells were evaluated at an early stage of the mineralization process induced by extrinsic stimuli, osteogenic factors and a magnetic suspension cell culture. Hydroxyapatite components were detected in monolayers of these cells in the presence of osteogenic factors and a magnetic suspension environment. Atherosclerotic plaque contains multiple components including lipidic, fibrotic, thrombotic, and calcific materials. Using optical imaging and the Cy-HABP-19 molecular imaging probe, we demonstrated that hydroxyapatite components could be selectively distinguished from various calcium salts in human aortic smooth muscle cells in vitro and in calcified cardiovascular tissues, carotid endarterectomy samples and aortic valves, ex vivo. Hydroxyapatite deposits in cardiovascular tissues were selectively detected in the early stage of the calcification process using our Cy-HABP-19 probe. This new probe makes it possible to study the earliest events associated with vascular hydroxyapatite deposition at the cellular and molecular levels. This target-selective molecular imaging probe approach holds high potential for revealing early pathophysiological changes, leading to progression, regression, or stabilization of cardiovascular diseases. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Novel primers and PCR protocols for the specific detection and quantification of Sphingobium suberifaciens in situ

USDA-ARS?s Scientific Manuscript database

The pathogen causing corky root on lettuce, Sphingobium suberifaciens, is recalcitrant to standard epidemiological methods. Primers were selected from 16S rDNA sequences useful for the specific detection and quantification of S. suberifaciens. Conventional (PCR) and quantitative (qPCR) PCR protocols...

Capillary atmospheric pressure electron capture ionization (cAPECI): a highly efficient ionization method for nitroaromatic compounds.

PubMed

Derpmann, Valerie; Mueller, David; Bejan, Iustinian; Sonderfeld, Hannah; Wilberscheid, Sonja; Koppmann, Ralf; Brockmann, Klaus J; Benter, Thorsten

2014-03-01

We report on a novel method for atmospheric pressure ionization of compounds with elevated electron affinity (e.g., nitroaromatic compounds) or gas phase acidity (e.g., phenols), respectively. The method is based on the generation of thermal electrons by the photo-electric effect, followed by electron capture of oxygen when air is the gas matrix yielding O2(-) or of the analyte directly with nitrogen as matrix. Charge transfer or proton abstraction by O2(-) leads to the ionization of the analytes. The interaction of UV-light with metals is a clean method for the generation of thermal electrons at atmospheric pressure. Furthermore, only negative ions are generated and neutral radical formation is minimized, in contrast to discharge- or dopant assisted methods. Ionization takes place inside the transfer capillary of the mass spectrometer leading to comparably short transfer times of ions to the high vacuum region of the mass spectrometer. This strongly reduces ion transformation processes, resulting in mass spectra that more closely relate to the neutral analyte distribution. cAPECI is thus a soft and selective ionization method with detection limits in the pptV range. In comparison to standard ionization methods (e.g., PTR), cAPECI is superior with respect to both selectivity and achievable detection limits. cAPECI demonstrates to be a promising ionization method for applications in relevant fields as, for example, explosives detection and atmospheric chemistry.

A Robust Shape Reconstruction Method for Facial Feature Point Detection.

PubMed

Tan, Shuqiu; Chen, Dongyi; Guo, Chenggang; Huang, Zhiqi

2017-01-01

Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed and applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression and gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction method for the face alignment problems. Instead of a direct regression between the feature space and the shape space, the concept of shape increment reconstruction is introduced. Moreover, a set of coupled overcomplete dictionaries termed the shape increment dictionary and the local appearance dictionary are learned in a regressive manner to select robust features and fit shape increments. Additionally, to make the learned model more generalized, we select the best matched parameter set through extensive validation tests. Experimental results on three public datasets demonstrate that the proposed method achieves a better robustness over the state-of-the-art methods.

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

PubMed Central

Dziedzinska, Radka

2017-01-01

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

Research and Development of Non-Spectroscopic MEMS-Based Sensor Arrays for Targeted Gas Detection

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

Loui, A; McCall, S K

2011-10-24

The ability to monitor the integrity of gas volumes is of interest to the stockpile surveillance community. Specifically, the leak detection of noble gases, at relevant concentration ranges and distinguished from other chemical species that may be simultaneously present, is particularly challenging. Aside from the laboratory-based method of gas chromatography-mass spectrometry (GC-MS), where samples may be collected by solid-phase microextraction (SPME) or cryofocusing, the other major approaches for gas-phase detection employ lasers typically operating in the mid-infrared wavelength region. While mass spectrometry can readily detect noble gases - the helium leak detector is an obvious example - laser-based methods suchmore » as infrared (IR) or Raman spectroscopy are completely insensitive to them as their monatomic nature precludes a non-zero dipole moment or changes in polarizability upon excitation. Therefore, noble gases can only be detected by one of two methods: (1) atomic emission spectroscopies which require the generation of plasmas through laser-induced breakdown, electrical arcing, or similar means; (2) non-spectroscopic methods which measure one or more physical properties (e.g., mass, thermal conductivity, density). In this report, we present our progress during Fiscal Year 2011 (FY11) in the research and development of a non-spectroscopic method for noble gas detection. During Fiscal Year 2010 (FY10), we demonstrated via proof-of-concept experiments that the combination of thermal conductivity detection (TCD) and coating-free damped resonance detection (CFDRD) using micro-electromechanical systems (MEMS) could provide selective sensing of these inert species. Since the MEMS-based TCD technology was directly adapted from a brassboard prototype commissioned by a previous chemical sensing project, FY11 efforts focused on advancing the state of the newer CFDRD method. This work, guided by observations previously reported in the open literature, has not only resulted in a substantially measureable increase in selectivity but has also revealed a potential method for mitigating or eliminating thermal drift that does not require a secondary reference sensor. The design of an apparatus to test this drift compensation scheme will be described. We will conclude this report with a discussion of planned efforts in Fiscal Year 2012 (FY12).« less

A comparative study of cultural methods for the detection of Salmonella in feed and feed ingredients

PubMed Central

Koyuncu, Sevinc; Haggblom, Per

2009-01-01

Background Animal feed as a source of infection to food producing animals is much debated. In order to increase our present knowledge about possible feed transmission it is important to know that the present isolation methods for Salmonella are reliable also for feed materials. In a comparative study the ability of the standard method used for isolation of Salmonella in feed in the Nordic countries, the NMKL71 method (Nordic Committee on Food Analysis) was compared to the Modified Semisolid Rappaport Vassiliadis method (MSRV) and the international standard method (EN ISO 6579:2002). Five different feed materials were investigated, namely wheat grain, soybean meal, rape seed meal, palm kernel meal, pellets of pig feed and also scrapings from a feed mill elevator. Four different levels of the Salmonella serotypes S. Typhimurium, S. Cubana and S. Yoruba were added to each feed material, respectively. For all methods pre-enrichment in Buffered Peptone Water (BPW) were carried out followed by enrichments in the different selective media and finally plating on selective agar media. Results The results obtained with all three methods showed no differences in detection levels, with an accuracy and sensitivity of 65% and 56%, respectively. However, Müller-Kauffmann tetrathionate-novobiocin broth (MKTTn), performed less well due to many false-negative results on Brilliant Green agar (BGA) plates. Compared to other feed materials palm kernel meal showed a higher detection level with all serotypes and methods tested. Conclusion The results of this study showed that the accuracy, sensitivity and specificity of the investigated cultural methods were equivalent. However, the detection levels for different feed and feed ingredients varied considerably. PMID:19192298

SPIDERS: selection of spectroscopic targets using AGN candidates detected in all-sky X-ray surveys

NASA Astrophysics Data System (ADS)

Dwelly, T.; Salvato, M.; Merloni, A.; Brusa, M.; Buchner, J.; Anderson, S. F.; Boller, Th.; Brandt, W. N.; Budavári, T.; Clerc, N.; Coffey, D.; Del Moro, A.; Georgakakis, A.; Green, P. J.; Jin, C.; Menzel, M.-L.; Myers, A. D.; Nandra, K.; Nichol, R. C.; Ridl, J.; Schwope, A. D.; Simm, T.

2017-07-01

SPIDERS (SPectroscopic IDentification of eROSITA Sources) is a Sloan Digital Sky Survey IV (SDSS-IV) survey running in parallel to the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) cosmology project. SPIDERS will obtain optical spectroscopy for large numbers of X-ray-selected active galactic nuclei (AGN) and galaxy cluster members detected in wide-area eROSITA, XMM-Newton and ROSAT surveys. We describe the methods used to choose spectroscopic targets for two sub-programmes of SPIDERS X-ray selected AGN candidates detected in the ROSAT All Sky and the XMM-Newton Slew surveys. We have exploited a Bayesian cross-matching algorithm, guided by priors based on mid-IR colour-magnitude information from the Wide-field Infrared Survey Explorer survey, to select the most probable optical counterpart to each X-ray detection. We empirically demonstrate the high fidelity of our counterpart selection method using a reference sample of bright well-localized X-ray sources collated from XMM-Newton, Chandra and Swift-XRT serendipitous catalogues, and also by examining blank-sky locations. We describe the down-selection steps which resulted in the final set of SPIDERS-AGN targets put forward for spectroscopy within the eBOSS/TDSS/SPIDERS survey, and present catalogues of these targets. We also present catalogues of ˜12 000 ROSAT and ˜1500 XMM-Newton Slew survey sources that have existing optical spectroscopy from SDSS-DR12, including the results of our visual inspections. On completion of the SPIDERS programme, we expect to have collected homogeneous spectroscopic redshift information over a footprint of ˜7500 deg2 for >85 per cent of the ROSAT and XMM-Newton Slew survey sources having optical counterparts in the magnitude range 17 < r < 22.5, producing a large and highly complete sample of bright X-ray-selected AGN suitable for statistical studies of AGN evolution and clustering.

NDE detectability of fatigue type cracks in high strength alloys

NASA Technical Reports Server (NTRS)

Christner, B. K.; Rummel, W. D.

1983-01-01

Specimens suitable for investigating the reliability of production nondestructive evaluation (NDE) to detect tightly closed fatigue cracks in high strength alloys representative of those materials used in spacecraft engine/booster construction were produced. Inconel 718 was selected as representative of nickel base alloys and Haynes 188 was selected as representative of cobalt base alloys used in this application. Cleaning procedures were developed to insure the reusability of the test specimens and a flaw detection reliability assessment of the fluorescent penetrant inspection method was performed using the test specimens produced to characterize their use for future reliability assessments and to provide additional NDE flaw detection reliability data for high strength alloys. The statistical analysis of the fluorescent penetrant inspection data was performed to determine the detection reliabilities for each inspection at a 90% probability/95% confidence level.

The occurrence of Campylobacter in river water and waterfowl within a watershed in southern Ontario, Canada.

PubMed

Van Dyke, M I; Morton, V K; McLellan, N L; Huck, P M

2010-09-01

Quantitative PCR and a culture method were used to investigate Campylobacter occurrence over 3 years in a watershed located in southern Ontario, Canada that is used as a source of drinking water. Direct DNA extraction from river water followed by quantitative PCR analysis detected thermophilic campylobacters at low concentrations (<130 cells 100 ml(-1) ) in 57-79% of samples taken from five locations. By comparison, a culture-based method detected Campylobacter in 0-23% of samples. Water quality parameters such as total Escherichia coli were not highly correlated with Campylobacter levels, although higher pathogen concentrations were observed at colder water temperatures (<10°C). Strains isolated from river water were primarily nalidixic acid-susceptible Campylobacter lari, and selected isolates were identified as Campylobacter lari ssp. concheus. Campylobacter from wild birds (seagulls, ducks and geese) were detected at a similar rate using PCR (32%) and culture-based (29%) methods, and although Campylobacter jejuni was isolated most frequently, C. lari ssp. concheus was also detected. Campylobacter were frequently detected at low concentrations in the watershed. Higher prevalence rates using quantitative PCR was likely because of the formation of viable but nonculturable cells and low recovery of the culture method. In addition to animal and human waste, waterfowl can be an important contributor of Campylobacter in the environment. Results of this study show that Campylobacter in surface water can be an important vector for human disease transmission and that method selection is important in determining pathogen occurrence in a water environment. © 2010 The Authors. Journal compilation © 2010 The Society for Applied Microbiology.

Evaluating prestressing strands and post-tensioning cables in concrete structures using nondestructive methods.

DOT National Transportation Integrated Search

2015-11-01

The objectives were to evaluate the ability of different NDE methods to detect and quantify : defects associated with corrosion of steel reinforcement and grout defects in post-tensioning : applications; and to evaluate the effectiveness of selected ...

Simultaneous Planck , Swift , and Fermi observations of X-ray and γ -ray selected blazars

DOE PAGES

Giommi, P.; Polenta, G.; Lähteenmäki, A.; ...

2012-05-22

We present simultaneous Planck, Swift, Fermi, and ground-based data for 105 blazars belonging to three samples with flux limits in the soft X-ray, hard X-ray, and γ-ray bands, with additional 5GHz flux-density limits to ensure a good probability of a Planck detection. We compare our results to those of a companion paper presenting simultaneous Planck and multi-frequency observations of 104 radio-loud northern active galactic nuclei selected at radio frequencies. While we confirm several previous results, our unique data set allows us to demonstrate that the selection method strongly influences the results, producing biases that cannot be ignored. Almost all themore » BL Lac objects have been detected by the Fermi Large AreaTelescope (LAT), whereas 30% to 40% of the flat-spectrum radio quasars (FSRQs) in the radio, soft X-ray, and hard X-ray selected samples are still below the γ-ray detection limit even after integrating 27 months of Fermi-LAT data. The radio to sub-millimetre spectral slope of blazars is quite flat, with >α> ~ 0 up to about 70GHz, above which it steepens to ~ -0.65. The BL Lacs have significantly flatter spectra than FSRQs at higher frequencies. The distribution of the rest-frame synchrotron peak frequency (ν peak S) in the spectral energy distribution (SED) of FSRQs is the same in all the blazar samples with peak S> = 10 13.1 ± 0.1 Hz, while the mean inverse Compton peak frequency, >ν peak IC>, ranges from 1021 to 1022 Hz. The distributions of ν peak S and ν peak IC of BL Lacs are much broader and are shifted to higher energies than those of FSRQs; their shapes strongly depend on the selection method. The Compton dominance of blazars, defined as the ratio of the inverse Compton to synchrotron peak luminosities, ranges from less than 0.2 to nearly 100, with only FSRQs reaching values larger than about 3. Its distribution is broad and depends strongly on the selection method, with γ-ray selected blazars peaking at ~7 or more, and radio-selected blazars at values close to 1, thus implying that the common assumption that the blazar power budget is largely dominated by high-energy emission is a selection effect. A comparison of our multi-frequency data with theoretical predictions shows that simple homogeneous SSC models cannot explain the simultaneous SEDs of most of the γ-ray detected blazars in all samples. The SED of the blazars that were not detected by Fermi-LAT may instead be consistent with SSC emission. Our data challenge the correlation between bolometric luminosity and ν peak S predicted by the blazar sequence.« less

The search for loci under selection: trends, biases and progress.

PubMed

Ahrens, Collin W; Rymer, Paul D; Stow, Adam; Bragg, Jason; Dillon, Shannon; Umbers, Kate D L; Dudaniec, Rachael Y

2018-03-01

Detecting genetic variants under selection using F ST outlier analysis (OA) and environmental association analyses (EAAs) are popular approaches that provide insight into the genetic basis of local adaptation. Despite the frequent use of OA and EAA approaches and their increasing attractiveness for detecting signatures of selection, their application to field-based empirical data have not been synthesized. Here, we review 66 empirical studies that use Single Nucleotide Polymorphisms (SNPs) in OA and EAA. We report trends and biases across biological systems, sequencing methods, approaches, parameters, environmental variables and their influence on detecting signatures of selection. We found striking variability in both the use and reporting of environmental data and statistical parameters. For example, linkage disequilibrium among SNPs and numbers of unique SNP associations identified with EAA were rarely reported. The proportion of putatively adaptive SNPs detected varied widely among studies, and decreased with the number of SNPs analysed. We found that genomic sampling effort had a greater impact than biological sampling effort on the proportion of identified SNPs under selection. OA identified a higher proportion of outliers when more individuals were sampled, but this was not the case for EAA. To facilitate repeatability, interpretation and synthesis of studies detecting selection, we recommend that future studies consistently report geographical coordinates, environmental data, model parameters, linkage disequilibrium, and measures of genetic structure. Identifying standards for how OA and EAA studies are designed and reported will aid future transparency and comparability of SNP-based selection studies and help to progress landscape and evolutionary genomics. © 2018 John Wiley & Sons Ltd.

Robust Cell Detection of Histopathological Brain Tumor Images Using Sparse Reconstruction and Adaptive Dictionary Selection

PubMed Central

Su, Hai; Xing, Fuyong; Yang, Lin

2016-01-01

Successful diagnostic and prognostic stratification, treatment outcome prediction, and therapy planning depend on reproducible and accurate pathology analysis. Computer aided diagnosis (CAD) is a useful tool to help doctors make better decisions in cancer diagnosis and treatment. Accurate cell detection is often an essential prerequisite for subsequent cellular analysis. The major challenge of robust brain tumor nuclei/cell detection is to handle significant variations in cell appearance and to split touching cells. In this paper, we present an automatic cell detection framework using sparse reconstruction and adaptive dictionary learning. The main contributions of our method are: 1) A sparse reconstruction based approach to split touching cells; 2) An adaptive dictionary learning method used to handle cell appearance variations. The proposed method has been extensively tested on a data set with more than 2000 cells extracted from 32 whole slide scanned images. The automatic cell detection results are compared with the manually annotated ground truth and other state-of-the-art cell detection algorithms. The proposed method achieves the best cell detection accuracy with a F1 score = 0.96. PMID:26812706

Fluorescent Sensing of Fluoride in Cellular System

PubMed Central

Jiao, Yang; Zhu, Baocun; Chen, Jihua; Duan, Xiaohong

2015-01-01

Fluoride ions have the important roles in a lot of physiological activities related with biological and medical system, such as water fluoridation, caries treatment, and bone disease treatment. Great efforts have been made to develop new methods and strategies for F- detection in the past decades. Traditional methods for the detection of F- including ion chromatography, ion-selective electrodes, and spectroscopic techniques have the limitations in the biomedicine research. The fluorescent probes for F- are very promising that overcome some drawbacks of traditional fluoride detection methods. These probes exhibit high selectivity, high sensitivity as well as quick response to the detection of fluoride anions. The review commences with a brief description of photophysical mechanisms for fluorescent probes for fluoride, including photo induced electron transfer (PET), intramolecular charge transfer (ICT), fluorescence resonance energy transfer (FRET), and excited-state intramolecular proton transfer (ESIPT). Followed by a discussion about common dyes for fluorescent fluoride probes, such as anthracene, naphalimide, pyrene, BODIPY, fluorescein, rhodamine, resorufin, coumarin, cyanine, and near-infrared (NIR) dyes. We divide the fluorescent probes for fluoride in cellular application systems into nine groups, for example, type of hydrogen bonds, type of cleavage of Si-O bonds, type of Si-O bond cleavage and cylization reactions, etc. We also review the recent reported carriers in the delivery of fluorescent fluoride probes. Seventy-four typical fluorescent fluoride probes are listed and compared in detail, including quantum yield, reaction medium, excitation and emission wavelengths, linear detection range, selectivity for F-, mechanism, and analytical applications. Finally, we discuss the future challenges of the application of fluorescent fluoride probes in cellular system and in vivo. We wish that more and more excellent fluorescent fluoride probes will be developed and applied in the biomedicine field in the future. PMID:25553106

Computer-aided detection of bladder mass within non-contrast-enhanced region of CT Urography (CTU)

NASA Astrophysics Data System (ADS)

Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Weizer, Alon; Zhou, Chuan

2016-03-01

We are developing a computer-aided detection system for bladder cancer in CT urography (CTU). We have previously developed methods for detection of bladder masses within the contrast-enhanced region of the bladder. In this study, we investigated methods for detection of bladder masses within the non-contrast enhanced region. The bladder was first segmented using a newly developed deep-learning convolutional neural network in combination with level sets. The non-contrast-enhanced region was separated from the contrast-enhanced region with a maximum-intensityprojection- based method. The non-contrast region was smoothed and a gray level threshold was employed to segment the bladder wall and potential masses. The bladder wall was transformed into a straightened thickness profile, which was analyzed to identify lesion candidates as a prescreening step. The lesion candidates were segmented using our autoinitialized cascaded level set (AI-CALS) segmentation method, and 27 morphological features were extracted for each candidate. Stepwise feature selection with simplex optimization and leave-one-case-out resampling were used for training and validation of a false positive (FP) classifier. In each leave-one-case-out cycle, features were selected from the training cases and a linear discriminant analysis (LDA) classifier was designed to merge the selected features into a single score for classification of the left-out test case. A data set of 33 cases with 42 biopsy-proven lesions in the noncontrast enhanced region was collected. During prescreening, the system obtained 83.3% sensitivity at an average of 2.4 FPs/case. After feature extraction and FP reduction by LDA, the system achieved 81.0% sensitivity at 2.0 FPs/case, and 73.8% sensitivity at 1.5 FPs/case.

Simulation Experiment on Landing Site Selection Using a Simple Geometric Approach

NASA Astrophysics Data System (ADS)

Zhao, W.; Tong, X.; Xie, H.; Jin, Y.; Liu, S.; Wu, D.; Liu, X.; Guo, L.; Zhou, Q.

2017-07-01

Safe landing is an important part of the planetary exploration mission. Even fine scale terrain hazards (such as rocks, small craters, steep slopes, which would not be accurately detected from orbital reconnaissance) could also pose a serious risk on planetary lander or rover and scientific instruments on-board it. In this paper, a simple geometric approach on planetary landing hazard detection and safe landing site selection is proposed. In order to achieve full implementation of this algorithm, two easy-to-compute metrics are presented for extracting the terrain slope and roughness information. Unlike conventional methods which must do the robust plane fitting and elevation interpolation for DEM generation, in this work, hazards is identified through the processing directly on LiDAR point cloud. For safe landing site selection, a Generalized Voronoi Diagram is constructed. Based on the idea of maximum empty circle, the safest landing site can be determined. In this algorithm, hazards are treated as general polygons, without special simplification (e.g. regarding hazards as discrete circles or ellipses). So using the aforementioned method to process hazards is more conforming to the real planetary exploration scenario. For validating the approach mentioned above, a simulated planetary terrain model was constructed using volcanic ash with rocks in indoor environment. A commercial laser scanner mounted on a rail was used to scan the terrain surface at different hanging positions. The results demonstrate that fairly hazard detection capability and reasonable site selection was obtained compared with conventional method, yet less computational time and less memory usage was consumed. Hence, it is a feasible candidate approach for future precision landing selection on planetary surface.

Oligonucleotide probes functionalization of nanogap electrodes.

PubMed

Zaffino, Rosa Letizia; Mir, Mònica; Samitier, Josep

2017-11-01

Nanogap electrodes have attracted a lot of consideration as promising platform for molecular electronic and biomolecules detection. This is mainly for their higher aspect ratio, and because their electrical properties are easily accessed by current-voltage measurements. Nevertheless, application of standard current-voltages measurements used to characterize nanogap response, and/or to modify specific nanogap electrodes properties, represents an issue. Since the strength of electrical fields in nanoscaled devices can reach high values, even at low voltages. Here, we analyzed the effects induced by different methods of surface modification of nanogap electrodes, in test-voltage application, employed for the electrical detection of a desoxyribonucleic acid (DNA) target. Nanogap electrodes were functionalized with two antisymmetric oligo-probes designed to have 20 terminal bases complementary to the edges of the target, which after hybridization bridges the nanogap, closing the electrical circuit. Two methods of functionalization were studied for this purpose; a random self-assembling of a mixture of the two oligo-probes (OPs) used in the platform, and a selective method that controls the position of each OP at selected side of nanogap electrodes. We used for this aim, the electrophoretic effect induced on negatively charged probes by the application of an external direct current voltage. The results obtained with both functionalization methods where characterized and compared in terms of electrode surface covering, calculated by using voltammetry analysis. Moreover, we contrasted the electrical detection of a DNA target in the nanogap platform either in site-selective and in randomly assembled nanogap. According to our results, a denser, although not selective surface functionalization, is advantageous for such kind of applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Optimal chroma-like channel design for passive color image splicing detection

NASA Astrophysics Data System (ADS)

Zhao, Xudong; Li, Shenghong; Wang, Shilin; Li, Jianhua; Yang, Kongjin

2012-12-01

Image splicing is one of the most common image forgeries in our daily life and due to the powerful image manipulation tools, image splicing is becoming easier and easier. Several methods have been proposed for image splicing detection and all of them worked on certain existing color channels. However, the splicing artifacts vary in different color channels and the selection of color model is important for image splicing detection. In this article, instead of finding an existing color model, we propose a color channel design method to find the most discriminative channel which is referred to as optimal chroma-like channel for a given feature extraction method. Experimental results show that both spatial and frequency features extracted from the designed channel achieve higher detection rate than those extracted from traditional color channels.

Fast cat-eye effect target recognition based on saliency extraction

NASA Astrophysics Data System (ADS)

Li, Li; Ren, Jianlin; Wang, Xingbin

2015-09-01

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

An online sleep apnea detection method based on recurrence quantification analysis.

PubMed

Nguyen, Hoa Dinh; Wilkins, Brek A; Cheng, Qi; Benjamin, Bruce Allen

2014-07-01

This paper introduces an online sleep apnea detection method based on heart rate complexity as measured by recurrence quantification analysis (RQA) statistics of heart rate variability (HRV) data. RQA statistics can capture nonlinear dynamics of a complex cardiorespiratory system during obstructive sleep apnea. In order to obtain a more robust measurement of the nonstationarity of the cardiorespiratory system, we use different fixed amount of neighbor thresholdings for recurrence plot calculation. We integrate a feature selection algorithm based on conditional mutual information to select the most informative RQA features for classification, and hence, to speed up the real-time classification process without degrading the performance of the system. Two types of binary classifiers, i.e., support vector machine and neural network, are used to differentiate apnea from normal sleep. A soft decision fusion rule is developed to combine the results of these classifiers in order to improve the classification performance of the whole system. Experimental results show that our proposed method achieves better classification results compared with the previous recurrence analysis-based approach. We also show that our method is flexible and a strong candidate for a real efficient sleep apnea detection system.

Peroxyoxalate chemiluminescence detection for the highly sensitive determination of fluorescence-labeled chlorpheniramine with Suzuki coupling reaction.

PubMed

Adutwum, Lawrence Asamoah; Kishikawa, Naoya; Ohyama, Kaname; Harada, Shiro; Nakashima, Kenichiro; Kuroda, Naotaka

2010-09-01

A sensitive and selective high performance liquid chromatography-peroxyoxalate chemiluminescence (PO-CL) method has been developed for the simultaneous determination of chlorpheniramine (CPA) and monodesmethyl chlorpheniramine (MDCPA) in human serum. The method combines fluorescent labeling with 4-(4,5-diphenyl-1H-imidazole-2-yl)phenyl boronic acid using Suzuki coupling reaction with PO-CL detection. CPA and MDCPA were extracted from human serum by liquid-liquid extraction with n-hexane. Excess labeling reagent, which interfered with trace level determination of analytes, was removed by solid-phase extraction using a C18 cartridge. Separation of derivatives of both analytes was achieved isocratically on a silica column with a mixture of acetonitrile and 60 mM imidazole-HNO(3) buffer (pH 7.2; 85:15, v/v) containing 0.015% triethylamine. The proposed method exhibited a good linearity with a correlation coefficient of 0.999 for CPA and MDCPA within the concentration range of 0.5-100 ng/mL. The limits of detection (S/N = 3) were 0.14 and 0.16 ng/mL for CPA and MDCPA, respectively. Using the proposed method, CPA could be selectively determined in human serum after oral administration.

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

Methods of analysis by the U. S. Geological Survey National Water Quality Laboratory - determination of organonitrogen herbicides in water by solid-phase extraction and capillary-column gas chromatography/mass spectrometry with selected-ion monitoring

USGS Publications Warehouse

Sandstrom, Mark W.; Wydoski, Duane S.; Schroeder, Michael P.; Zamboni, Jana L.; Foreman, William T.

1992-01-01

A method for the isolation of organonitrogen herbicides from natural water samples using solid-phase extraction and analysis by capillary-column gas chromatography/mass spectrometry with selected-ion monitoring is described. Water samples are filtered to remove suspended particulate matter and then are pumped through disposable solid-phase extraction cartridges containing octadecyl-bonded porous silica to remove the herbicides. The cartridges are dried using carbon dioxide, and adsorbed herbicides are removed from the cartridges by elution with 1.8 milliliters of hexaneisopropanol (3:1). Extracts of the eluants are analyzed by capillary-column gas chromatography/mass spectrometry with selected-ion monitoring of at least three characteristic ions. The method detection limits are dependent on sample matrix and each particular herbicide. The method detection limits, based on a 100-milliliter sample size, range from 0.02 to 0.25 microgram per liter. Recoveries averaged 80 to 115 percent for the 23 herbicides and 2 metabolites in 1 reagent-water and 2 natural-water samples fortified at levels of 0.2 and 2.0 micrograms per liter.

A Colorimetric and Fluorescent Probe for the Detection of Cu2+ in a Complete Aqueous Solution.

PubMed

Xu, Jing; Wang, Zuokai; Liu, Caiyun; Xu, Zhenghe; Zhu, Baocun; Wang, Ning; Wang, Kun; Wang, Jiangting

2018-01-01

The fluorescent probe has become an important method for the detection of heavy metal ions. In the present work, a new and simple fluorescent probe, Cu-P, for detecting copper ion (Cu 2+ ) was designed and synthesized. The probe has shown high sensitivity and selectivity toward Cu 2+ . The detection limit was 13 nM (based on the 3σ/slope). A significant color change from yellow to pink was observed; thus, the probe Cu-P could serve as a "naked-eye" indicator for Cu 2+ . Furthermore, the proposed probe was used to detect Cu 2+ in real water and soil extract samples, with the result being satisfactory. Therefore, our proposed probe would provide a promising method for the detection of Cu 2+ in the environment.

Electrochemical detection of dopamine using porphyrin-functionalized graphene.

PubMed

Wu, Li; Feng, Lingyan; Ren, Jinsong; Qu, Xiaogang

2012-04-15

A new type of porphyrin-functionalized graphene was synthesized and used for highly selective and sensitive detection of dopamine (DA). The aromatic π-π stacking and electrostatic attraction between positively-charged dopamine and negatively-charged porphyrin-modified graphene can accelerate the electron transfer whereas weakening ascorbic acid (AA) and uric acid (UA) oxidation on the porphyrin-functionalized graphene-modified electrode. Differential pulse voltammetry was used for electrochemical detection, the separation of the oxidation peak potentials for AA-DA, DA-UA and UA-AA is about 188 mV, 144 mV and 332 mV, which allows selectively determining DA. The detection limit of DA can be as low as 0.01 μM. More importantly, the sensor we presented can detect DA in the presence of large excess of ascorbic acid and uric acid. With good sensitivity and selectivity, the present method was applied to the determination of DA in real hydrochloride injection sample, human urine and serum samples, respectively, and the results was satisfactory. Copyright © 2012 Elsevier B.V. All rights reserved.

Force sensor

DOEpatents

Grahn, A.R.

1993-05-11

A force sensor and related method for determining force components is described. The force sensor includes a deformable medium having a contact surface against which a force can be applied, a signal generator for generating signals that travel through the deformable medium to the contact surface, a signal receptor for receiving the signal reflected from the contact surface, a generation controller, a reception controller, and a force determination apparatus. The signal generator has one or more signal generation regions for generating the signals. The generation controller selects and activates the signal generation regions. The signal receptor has one or more signal reception regions for receiving signals and for generating detections signals in response thereto. The reception controller selects signal reception regions and detects the detection signals. The force determination apparatus measures signal transit time by timing activation and detection and, optionally, determines force components for selected cross-field intersections. The timer which times by activation and detection can be any means for measuring signal transit time. A cross-field intersection is defined by the overlap of a signal generation region and a signal reception region.

Force sensor

DOEpatents

Grahn, Allen R.

1993-01-01

A force sensor and related method for determining force components. The force sensor includes a deformable medium having a contact surface against which a force can be applied, a signal generator for generating signals that travel through the deformable medium to the contact surface, a signal receptor for receiving the signal reflected from the contact surface, a generation controller, a reception controller, and a force determination apparatus. The signal generator has one or more signal generation regions for generating the signals. The generation controller selects and activates the signal generation regions. The signal receptor has one or more signal reception regions for receiving signals and for generating detections signals in response thereto. The reception controller selects signal reception regions and detects the detection signals. The force determination apparatus measures signal transit time by timing activation and detection and, optionally, determines force components for selected cross-field intersections. The timer which times by activation and detection can be any means for measuring signal transit time. A cross-field intersection is defined by the overlap of a signal generation region and a signal reception region.

A novel colorimetric triple-helix molecular switch aptasensor for ultrasensitive detection of tetracycline.

PubMed

Ramezani, Mohammad; Mohammad Danesh, Noor; Lavaee, Parirokh; Abnous, Khalil; Mohammad Taghdisi, Seyed

2015-08-15

Detection methods of antibiotic residues in blood serum and animal derived foods are of great interest. In this study a colorimetric aptasensor was designed for sensitive, selective and fast detection of tetracycline based on triple-helix molecular switch (THMS) and gold nanoparticles (AuNPs). As a biosensor, THMS shows distinct advantages including high stability, sensitivity and preserving the selectivity and affinity of the original aptamer. In the absence of tetracycline, THMS is stable, leading to the aggregation of AuNPs by salt and an obvious color change from red to blue. In the presence of tetracycline, aptamer binds to its target, signal transduction probe (STP) leaves the THMS and adsorbs on the surface of AuNPs. So the well-dispersed AuNPs remain stable against salt-induced aggregation with a red color. The presented aptasensor showed high selectivity toward tetracyclines with a limit of detection as low as 266 pM for tetracycline. The designed aptasensor was successfully applied to detect tetracycline in serum and milk. Copyright © 2015 Elsevier B.V. All rights reserved.

Method and apparatus for detection of fluorescently labeled materials

DOEpatents

Stern, David; Fiekowsky, Peter

2004-05-25

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

In Vitro Selection of a Single-Stranded DNA Molecular Recognition Element against the Pesticide Fipronil and Sensitive Detection in River Water

PubMed Central

Sooter, Letha J.

2017-01-01

Fipronil is a commonly used insecticide that has been shown to have environmental and human health risks. The current standard methods of detection for fipronil and its metabolites, such as GC-MS, are time consuming and labor intensive. In this study, a variant of systematic evolution of ligands by exponential enrichment (SELEX), was utilized to identify the first single-stranded DNA (ssDNA) molecular recognition element (MRE) that binds to fipronil with high affinity (Kd = 48 ± 8 nM). The selected MRE displayed low cross binding activity on various environmentally relevant, structurally unrelated herbicides and pesticides, in addition to broad-spectrum binding activity on major metabolites of fipronil and a structurally similar pesticide in prepared river samples. Additionally, a proof-of-principle fluorescent detection assay was developed by using the selected ssDNA MRE as a signal-reporting element, with a limit of detection of 105 nM in a prepared river water sample. PMID:29283416

A Luminescent Cocaine Detection Platform Using a Split G-Quadruplex-Selective Iridium(III) Complex and a Three-Way DNA Junction Architecture.

PubMed

Ma, Dik-Lung; Wang, Modi; He, Bingyong; Yang, Chao; Wang, Wanhe; Leung, Chung-Hang

2015-09-02

In this study, a series of 10 in-house cyclometalated iridium(III) complexes bearing different auxiliary ligands were tested for their selectivity toward split G-quadruplex in order to construct a label-free switch-on cocaine detection platform employing a three-way junction architecture and a G-quadruplex motif as a signal output unit. Through two rounds of screening, we discovered that the iridium(III) complex 7 exhibited excellent selectivity toward the intermolecular G-quadruplex motif. A detection limit as low as 30 nM for cocaine can be achieved by this sensing approach with a linear relationship between luminescence intensity and cocaine concentration established from 30 to 300 nM. Furthermore, this sensing approach could detect cocaine in diluted oral fluid. We hope that our simple, signal-on, label-free oligonucleotide-based sensing method for cocaine using a three-way DNA junction architecture could act as a useful platform in bioanalytical research.

Development of a recombinant human ovarian (BG1) cell line containing estrogen receptor α and β for improved detection of estrogenic/antiestrogenic chemicals.

PubMed

Brennan, Jennifer C; Bassal, Arzoo; He, Guochun; Denison, Michael S

2016-01-01

Estrogenic endocrine-disrupting chemicals are found in environmental and biological samples, commercial and consumer products, food, and numerous other sources. Given their ubiquitous nature and potential for adverse effects, a critical need exists for rapidly detecting these chemicals. The authors developed an estrogen-responsive recombinant human ovarian (BG1Luc4E2) cell line recently accepted by the US Environmental Protection Agency (USEPA) and Organisation for Economic Co-operation and Development (OECD) as a bioanalytical method to detect estrogen receptor (ER) agonists/antagonists. Unfortunately, these cells appear to contain only 1 of the 2 known ER isoforms, ERα but not ERβ, and the differential ligand selectivity of these ERs indicates that the currently accepted screening method only detects a subset of total estrogenic chemicals. To improve the estrogen screening bioassay, BG1Luc4E2 cells were stably transfected with an ERβ expression plasmid and positive clones identified using ERβ-selective ligands (genistein and Br-ERβ-041). A highly responsive clone (BG1LucERβc9) was identified that exhibited greater sensitivity and responsiveness to ERβ-selective ligands than BG1Luc4E2 cells, and quantitative reverse-transcription polymerase chain reaction confirmed the presence of ERβ expression in these cells. Screening of pesticides and industrial chemicals identified chemicals that preferentially stimulated ERβ-dependent reporter gene expression. Together, these results not only demonstrate the utility of this dual-ER recombinant cell line for detecting a broader range of estrogenic chemicals than the current BG1Luc4E2 cell line, but screening with both cell lines allows identification of ERα- and ERβ-selective chemicals. © 2015 SETAC.

Development of a recombinant human ovarian (BG1) cell line containing estrogen receptor α and β for improved detection of estrogenic/antiestrogenic chemicals

PubMed Central

Brennan, Jennifer C.; Bassal, Arzoo; He, Guochun; Denison, Michael S.

2016-01-01

Estrogenic endocrine disrupting chemicals are found in environmental and biological samples, commercial and consumer products, food, and numerous other sources. Given their ubiquitous nature and potential for adverse effects, there is a critical need for rapidly detecting these chemicals. We developed an estrogen-responsive recombinant human ovarian (BG1Luc4E2) cell line recently accepted by the USEPA and OECD as a bioanalytical method to detect estrogen receptor (ER) agonists/antagonists. Unfortunately, these cells appear to contain only one of the two known ER isoforms, ERα but not ERβ, and the differential ligand selectivity of these ERs indicates that the currently accepted screening method only detects a subset of total estrogenic chemicals. To improve the estrogen screening bioassay, BG1Luc4E2 cells were stably transfected with an ERβ expression plasmid and positive clones identified using ERβ-selective ligands (genistein and Br-ERβ-041). A highly responsive clone (BG1LucERβc9) was identified that exhibited greater sensitivity and responsiveness to ERβ-selective ligands than BG1Luc4E2 cells and qRT-PCR confirmed the presence of ERβ expression in these cells. Screening of pesticides and industrial chemicals identified chemicals that preferentially stimulated ERβ-dependent reporter gene expression. Together, these results not only demonstrate the utility of this dual ER recombinant cell line for detecting a broader range of estrogenic chemicals than the current BG1Luc4E2 cell line, but screening with both cell lines allows identification of ERα and ERβ-selective chemicals. PMID:26139245

A hybrid feature selection method using multiclass SVM for diagnosis of erythemato-squamous disease

NASA Astrophysics Data System (ADS)

Maryam, Setiawan, Noor Akhmad; Wahyunggoro, Oyas

2017-08-01

The diagnosis of erythemato-squamous disease is a complex problem and difficult to detect in dermatology. Besides that, it is a major cause of skin cancer. Data mining implementation in the medical field helps expert to diagnose precisely, accurately, and inexpensively. In this research, we use data mining technique to developed a diagnosis model based on multiclass SVM with a novel hybrid feature selection method to diagnose erythemato-squamous disease. Our hybrid feature selection method, named ChiGA (Chi Square and Genetic Algorithm), uses the advantages from filter and wrapper methods to select the optimal feature subset from original feature. Chi square used as filter method to remove redundant features and GA as wrapper method to select the ideal feature subset with SVM used as classifier. Experiment performed with 10 fold cross validation on erythemato-squamous diseases dataset taken from University of California Irvine (UCI) machine learning database. The experimental result shows that the proposed model based multiclass SVM with Chi Square and GA can give an optimum feature subset. There are 18 optimum features with 99.18% accuracy.

Molecularly imprinted microspheres synthesized by a simple, fast, and universal suspension polymerization for selective extraction of the topical anesthetic benzocaine in human serum and fish tissues.

PubMed

Sun, Hui; Lai, Jia-Ping; Chen, Fang; Zhu, De-Rong

2015-02-01

A simple, fast, and universal suspension polymerization method was used to synthesize the molecularly imprinted microspheres (MIMs) for the topical anesthetic benzocaine (BZC). The desired diameter (10-20 μm) and uniform morphology of the MIMs were obtained easily by changing one or more of the synthesis conditions, including type and amount of surfactant, stirring rate, and ratio of organic to water phase. The MIMs obtained were used as a molecular-imprinting solid-phase-extraction (MISPE) material for extraction of BZC in human serum and fish tissues. The MISPE results revealed that the BZC in these biosamples could be enriched effectively after the MISPE operation. The recoveries of BZC on MIMs cartridges were higher than 90% (n = 3). Finally, an MISPE-HPLC method with UV detection was developed for highly selective extraction and fast detection of trace BZC in human serum and fish tissues. The developed method could also be used for the enrichment and detection of BZC in other complex biosamples.

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

PubMed

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

2014-01-01

A new peak detection method has been developed for rapid selection of peptide and its fragment ion peaks for protein identification using tandem mass spectrometry. The algorithm applies classification of peak intensities present in the defined mass range to determine the noise level. A threshold is then given to select ion peaks according to the determined noise level in each mass range. This algorithm was initially designed for the peak detection of low resolution peptide mass spectra, such as matrix-assisted laser desorption/ionization Time-of-Flight (MALDI-TOF) mass spectra. But it can also be applied to other type of mass spectra. This method has demonstrated obtaining a good rate of number of real ions to noises for even poorly fragmented peptide spectra. The effect of using peak lists generated from this method produces improved protein scores in database search results. The reliability of the protein identifications is increased by finding more peptide identifications. This software tool is freely available at the Mass++ home page (http://www.first-ms3d.jp/english/achievement/software/).

Peptide Peak Detection for Low Resolution MALDI-TOF Mass Spectrometry

PubMed Central

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

2014-01-01

A new peak detection method has been developed for rapid selection of peptide and its fragment ion peaks for protein identification using tandem mass spectrometry. The algorithm applies classification of peak intensities present in the defined mass range to determine the noise level. A threshold is then given to select ion peaks according to the determined noise level in each mass range. This algorithm was initially designed for the peak detection of low resolution peptide mass spectra, such as matrix-assisted laser desorption/ionization Time-of-Flight (MALDI-TOF) mass spectra. But it can also be applied to other type of mass spectra. This method has demonstrated obtaining a good rate of number of real ions to noises for even poorly fragmented peptide spectra. The effect of using peak lists generated from this method produces improved protein scores in database search results. The reliability of the protein identifications is increased by finding more peptide identifications. This software tool is freely available at the Mass++ home page (http://www.first-ms3d.jp/english/achievement/software/). PMID:26819872

Identification, characterization, synthesis and HPLC quantification of new process-related impurities and degradation products in retigabine.

PubMed

Douša, Michal; Srbek, Jan; Rádl, Stanislav; Cerný, Josef; Klecán, Ondřej; Havlíček, Jaroslav; Tkadlecová, Marcela; Pekárek, Tomáš; Gibala, Petr; Nováková, Lucie

2014-06-01

Two new impurities were described and determined using gradient HPLC method with UV detection in retigabine (RET). Using LC-HRMS, NMR and IR analysis the impurities were identified as RET-dimer I: diethyl {4,4'-diamino-6,6'-bis[(4-fluorobenzyl)amino]biphenyl-3,3'-diyl}biscarbamate and RET-dimer II: ethyl {2-amino-5-[{2-amino-4-[(4-fluorobenzyl) amino] phenyl} (ethoxycarbonyl) amino]-4-[(4-fluorobenzyl)amino] phenyl}carbamate. Reference standards of these impurities were synthesized followed by semipreparative HPLC purification. The mechanism of the formation of these impurities is also discussed. An HPLC method was optimized in order to separate, selectively detect and quantify all process-related impurities and degradation products of RET. The presented method, which was validated in terms of linearity, limit of detection (LOD), limit of quantification (LOQ) and selectivity is very quick (less than 11min including re-equilibration time) and therefore highly suitable for routine analysis of RET related substances as well as stability studies. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessment of strobilurin fungicides' content in soya-based drinks by liquid micro-extraction and liquid chromatography with tandem mass spectrometry.

PubMed

Campillo, Natalia; Iniesta, María Jesús; Viñas, Pilar; Hernández-Córdoba, Manuel

2015-01-01

Seven strobilurin fungicides were pre-concentrated from soya-based drinks using dispersive liquid-liquid micro-extraction (DLLME) with a prior protein precipitation step in acid medium. The enriched phase was analysed by liquid chromatography (LC) with dual detection, using diode array detection (DAD) and electrospray-ion trap tandem mass spectrometry (ESI-IT-MS/MS). After selecting 1-undecanol and methanol as the extractant and disperser solvents, respectively, for DLLME, the Taguchi experimental method, an orthogonal array design, was applied to select the optimal solvent volumes and salt concentration in the aqueous phase. The matrix effect was evaluated and quantification was carried out using external aqueous calibration for DAD and matrix-matched calibration method for MS/MS. Detection limits in the 4-130 and 0.8-4.5 ng g(-1) ranges were obtained for DAD and MS/MS, respectively. The DLLME-LC-DAD-MS method was applied to the analysis of 10 different samples, none of which was found to contain residues of the studied fungicides.

A novel method for the rapid detection of benzo(a)pyrene in liquid milk by dimethyl sulfoxide selectively enhanced synchronous fluorescence spectrometry.

PubMed

Lin, Li-Rong; Luo, He-Dong; Li, Xiu-Ying; Li, Na; Zhou, Na; Jia, Yu-Zhu; Liu, Yi-Hong; Li, Yao-Qun

2014-01-01

Based on the high solubility efficiency and strong fluorescence response of benzo(a)pyrene (BaP) in dimethyl sulfoxide in combination with the high-performance derivative constant-energy synchronous fluorescence spectroscopic (DCESFS) technique, a simple, sensitive and economic method was developed for the determination of BaP in liquid milk. This method comprises ultrasound-assisted solvent extraction, solvent replacement and DCESFS detection. No saponification or other tedious clean-up procedures were needed. The recoveries of BaP in different milk samples were greater than 82%. Detection limits in full- and low-fat milk were 0.03 and 0.04 μg kg(-1), respectively.

Indigo Carmine-Cu complex probe exhibiting dual colorimetric/fluorimetric sensing for selective determination of mono hydrogen phosphate ion and its logic behavior

NASA Astrophysics Data System (ADS)

Tavallali, Hossein; Deilamy-Rad, Gohar; Moaddeli, Ali; Asghari, Khadijeh

2017-08-01

A new selective probe based on copper complex of Indigo Carmine (IC-Cu2) for colorimetric, naked-eye, and fluorimetric recognition of mono hydrogen phosphate (MHP) ion in H2O/DMSO (4:1 v/v, 1.0 mmol L- 1 HEPES buffer solution pH 7.5) was developed. Detection limit of HPO42 - determination, achieved by fluorimetric and 3lorimetric method, are 0.071 and 1.46 μmol L- 1, respectively. Potential, therefore is clearly available in IC-Cu2 complex to detect HPO42 - in micromolar range via dual visible color change and fluorescence response. Present method shows high selectivity toward HPO42 - over other phosphate species and other anions and was successfully utilized for analysis of P2O5 content of a fertilizer sample. The results obtained by proposed chemosensor presented good agreement with those obtained the colorimetric reference method. INHIBIT and IMPLICATION logic gates operating at molecular level have been achieved using Cu2 + and HPO42 - as chemical inputs and UV-Vis absorbance signal as output.

Paleogene stratigraphy of the Solomons Island, Maryland corehole

USGS Publications Warehouse

Gibson, Thomas G.; Bybell, Laurel M.

1994-01-01

Purge and trap capillary gas chromatography/mass spectrometry is a rapid, precise, accurate method for determining volatile organic compounds in samples of surface water and ground water. The method can be used to determine 59 selected compounds, including chlorofluorohydrocarbons, aromatic hydrocarbons, and halogenated hydrocarbons. The volatile organic compounds are removed from the sample matrix by actively purging the sample with helium. The volatile organic compounds are collected onto a sorbant trap, thermally desorbed, separated by a Megabore gas chromatographic capillary column, ionized by electron impact, and determined by a full-scan quadrupole mass spectrometer. Compound identification is confirmed by the gas chromatographic retention time and by the resultant mass spectrum. Unknown compounds detected in a sample can be tentatively identified by comparing the unknown mass spectrum to reference spectra in the mass-spectra computer-data system library compiled by the National Institute of Standards and Technology. Method detection limits for the selected compounds range from 0.05 to 0.2 microgram per liter. Recoveries for the majority of the selected compounds ranged from 80 to 120 percent, with relative standard deviations of less than 10 percent.

Poly(1-vinylimidazole) functionalized magnetic ion imprinted polymer for fast and selective extraction of trace gold in geological, environmental and biological samples followed by graphite furnace atomic absorption spectrometry detection

NASA Astrophysics Data System (ADS)

Zhao, Bingshan; He, Man; Chen, Beibei; Xu, Hongrun; Hu, Bin

2018-05-01

In this study, poly(1-vinylimidazole) functionalized gold ion imprinted polymer coated magnetic nanoparticles (MNPs@PVIM-Au-IIP) were prepared and characterized. The adsorption behaviors of the prepared MNPs@PVIM-Au-IIP toward gold ions (Au(III)) were studied, it was found that MNPs@PVIM-Au-IIP has good selectivity, high adsorption capacity (185.4 mg g-1) and fast adsorption kinetic for Au(III). Based on it, a new method of ion imprinted magnetic solid phase extraction (II-MSPE) coupled with graphite furnace atomic absorption spectrometry (GFAAS) detection was proposed for the analysis of trace Au(III) in real samples with complicated matrix. Factors affecting MSPE including sample pH, desorption reagent, elution concentration and volume, elution time, sample volume and adsorption time were optimized. With high enrichment factor of 100-fold, the detection limit of the proposed method is 7.9 ng L-1 for Au(III) with the relative standard deviation of 7.4% (c = 50 ng L-1, n = 7). In order to validate the accuracy of the proposed method, the Certified Reference Material of GBW07293 geological sample (platinpalladium ore) was analyzed, and the determined value was in good agreement with the certified value. The proposed II-MSPE-GFAAS method is simple, fast, selective, sensitive and has been successfully applied in the determination of trace Au in ore, sediment, environmental water and human urine samples with satisfactory results.

Novel ion imprinted magnetic mesoporous silica for selective magnetic solid phase extraction of trace Cd followed by graphite furnace atomic absorption spectrometry detection

NASA Astrophysics Data System (ADS)

Zhao, Bingshan; He, Man; Chen, Beibei; Hu, Bin

2015-05-01

Determination of trace Cd in environmental, biological and food samples is of great significance to toxicological research and environmental pollution monitoring. While the direct determination of Cd in real-world samples is difficult due to its low concentration and the complex matrix. Herein, a novel Cd(II)-ion imprinted magnetic mesoporous silica (Cd(II)-II-MMS) was prepared and was employed as a selective magnetic solid-phase extraction (MSPE) material for extraction of trace Cd in real-world samples followed by graphite furnace atomic absorption spectrometry (GFAAS) detection. Under the optimized conditions, the detection limit of the proposed method was 6.1 ng L- 1 for Cd with the relative standard deviation (RSD) of 4.0% (c = 50 ng L- 1, n = 7), and the enrichment factor was 50-fold. To validate the proposed method, Certified Reference Materials of GSBZ 50009-88 environmental water, ZK018-1 lyophilized human urine and NIES10-b rice flour were analyzed and the determined values were in a good agreement with the certified values. The proposed method exhibited a robust anti-interference ability due to the good selectivity of Cd(II)-II-MMS toward Cd(II). It was successfully employed for the determination of trace Cd(II) in environmental water, human urine and rice samples with recoveries of 89.3-116%, demonstrating that the proposed method has good application potential in real world samples with complex matrix.

Method for detection of selected chemicals in an open environment

NASA Technical Reports Server (NTRS)

Duong, Tuan (Inventor); Ryan, Margaret (Inventor)

2009-01-01

The present invention relates to a space-invariant independent component analysis and electronic nose for detection of selective chemicals in an unknown environment, and more specifically, an approach to analysis of sensor responses to mixtures of unknown chemicals by an electronic nose in an open and changing environment. It is intended to fill the gap between an alarm, which has little or no ability to distinguish among chemical compounds causing a response, and an analytical instrument, which can distinguish all compounds present but with no real-time or continuous event monitoring ability.

Detection of selection signatures in Piemontese and Marchigiana cattle, two breeds with similar production aptitudes but different selection histories.

PubMed

Sorbolini, Silvia; Marras, Gabriele; Gaspa, Giustino; Dimauro, Corrado; Cellesi, Massimo; Valentini, Alessio; Macciotta, Nicolò Pp

2015-06-23

Domestication and selection are processes that alter the pattern of within- and between-population genetic variability. They can be investigated at the genomic level by tracing the so-called selection signatures. Recently, sequence polymorphisms at the genome-wide level have been investigated in a wide range of animals. A common approach to detect selection signatures is to compare breeds that have been selected for different breeding goals (i.e. dairy and beef cattle). However, genetic variations in different breeds with similar production aptitudes and similar phenotypes can be related to differences in their selection history. In this study, we investigated selection signatures between two Italian beef cattle breeds, Piemontese and Marchigiana, using genotyping data that was obtained with the Illumina BovineSNP50 BeadChip. The comparison was based on the fixation index (Fst), combined with a locally weighted scatterplot smoothing (LOWESS) regression and a control chart approach. In addition, analyses of Fst were carried out to confirm candidate genes. In particular, data were processed using the varLD method, which compares the regional variation of linkage disequilibrium between populations. Genome scans confirmed the presence of selective sweeps in the genomic regions that harbour candidate genes that are known to affect productive traits in cattle such as DGAT1, ABCG2, CAPN3, MSTN and FTO. In addition, several new putative candidate genes (for example ALAS1, ABCB8, ACADS and SOD1) were detected. This study provided evidence on the different selection histories of two cattle breeds and the usefulness of genomic scans to detect selective sweeps even in cattle breeds that are bred for similar production aptitudes.

A hierarchical approach for online temporal lobe seizure detection in long-term intracranial EEG recordings

NASA Astrophysics Data System (ADS)

Liang, Sheng-Fu; Chen, Yi-Chun; Wang, Yu-Lin; Chen, Pin-Tzu; Yang, Chia-Hsiang; Chiueh, Herming

2013-08-01

Objective. Around 1% of the world's population is affected by epilepsy, and nearly 25% of patients cannot be treated effectively by available therapies. The presence of closed-loop seizure-triggered stimulation provides a promising solution for these patients. Realization of fast, accurate, and energy-efficient seizure detection is the key to such implants. In this study, we propose a two-stage on-line seizure detection algorithm with low-energy consumption for temporal lobe epilepsy (TLE). Approach. Multi-channel signals are processed through independent component analysis and the most representative independent component (IC) is automatically selected to eliminate artifacts. Seizure-like intracranial electroencephalogram (iEEG) segments are fast detected in the first stage of the proposed method and these seizures are confirmed in the second stage. The conditional activation of the second-stage signal processing reduces the computational effort, and hence energy, since most of the non-seizure events are filtered out in the first stage. Main results. Long-term iEEG recordings of 11 patients who suffered from TLE were analyzed via leave-one-out cross validation. The proposed method has a detection accuracy of 95.24%, a false alarm rate of 0.09/h, and an average detection delay time of 9.2 s. For the six patients with mesial TLE, a detection accuracy of 100.0%, a false alarm rate of 0.06/h, and an average detection delay time of 4.8 s can be achieved. The hierarchical approach provides a 90% energy reduction, yielding effective and energy-efficient implementation for real-time epileptic seizure detection. Significance. An on-line seizure detection method that can be applied to monitor continuous iEEG signals of patients who suffered from TLE was developed. An IC selection strategy to automatically determine the most seizure-related IC for seizure detection was also proposed. The system has advantages of (1) high detection accuracy, (2) low false alarm, (3) short detection latency, and (4) energy-efficient design for hardware implementation.

Seamless image stitching by homography refinement and structure deformation using optimal seam pair detection

NASA Astrophysics Data System (ADS)

Lee, Daeho; Lee, Seohyung

2017-11-01

We propose an image stitching method that can remove ghost effects and realign the structure misalignments that occur in common image stitching methods. To reduce the artifacts caused by different parallaxes, an optimal seam pair is selected by comparing the cross correlations from multiple seams detected by variable cost weights. Along the optimal seam pair, a histogram of oriented gradients is calculated, and feature points for matching are detected. The homography is refined using the matching points, and the remaining misalignment is eliminated using the propagation of deformation vectors calculated from matching points. In multiband blending, the overlapping regions are determined from a distance between the matching points to remove overlapping artifacts. The experimental results show that the proposed method more robustly eliminates misalignments and overlapping artifacts than the existing method that uses single seam detection and gradient features.

Boosting instance prototypes to detect local dermoscopic features.

PubMed

Situ, Ning; Yuan, Xiaojing; Zouridakis, George

2010-01-01

Local dermoscopic features are useful in many dermoscopic criteria for skin cancer detection. We address the problem of detecting local dermoscopic features from epiluminescence (ELM) microscopy skin lesion images. We formulate the recognition of local dermoscopic features as a multi-instance learning (MIL) problem. We employ the method of diverse density (DD) and evidence confidence (EC) function to convert MIL to a single-instance learning (SIL) problem. We apply Adaboost to improve the classification performance with support vector machines (SVMs) as the base classifier. We also propose to boost the selection of instance prototypes through changing the data weights in the DD function. We validate the methods on detecting ten local dermoscopic features from a dataset with 360 images. We compare the performance of the MIL approach, its boosting version, and a baseline method without using MIL. Our results show that boosting can provide performance improvement compared to the other two methods.

Modeling HIV-1 Drug Resistance as Episodic Directional Selection

PubMed Central

Murrell, Ben; de Oliveira, Tulio; Seebregts, Chris; Kosakovsky Pond, Sergei L.; Scheffler, Konrad

2012-01-01

The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance. PMID:22589711

Modeling HIV-1 drug resistance as episodic directional selection.

PubMed

Murrell, Ben; de Oliveira, Tulio; Seebregts, Chris; Kosakovsky Pond, Sergei L; Scheffler, Konrad

2012-01-01

The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.

Template reporter bacteriophage platform and multiple bacterial detection assays based thereon

NASA Technical Reports Server (NTRS)

Goodridge, Lawrence (Inventor)

2007-01-01

The invention is a method for the development of assays for the simultaneous detection of multiple bacteria. A bacteria of interest is selected. A host bacteria containing plasmid DNA from a T even bacteriophage that infects the bacteria of interest is infected with T4 reporter bacteriophage. After infection, the progeny bacteriophage are plating onto the bacteria of interest. The invention also includes single-tube, fast and sensitive assays which utilize the novel method.

Detection of heavy metal by paper-based microfluidics.

PubMed

Lin, Yang; Gritsenko, Dmitry; Feng, Shaolong; Teh, Yi Chen; Lu, Xiaonan; Xu, Jie

2016-09-15

Heavy metal pollution has shown great threat to the environment and public health worldwide. Current methods for the detection of heavy metals require expensive instrumentation and laborious operation, which can only be accomplished in centralized laboratories. Various microfluidic paper-based analytical devices have been developed recently as simple, cheap and disposable alternatives to conventional ones for on-site detection of heavy metals. In this review, we first summarize current development of paper-based analytical devices and discuss the selection of paper substrates, methods of device fabrication, and relevant theories in these devices. We then compare and categorize recent reports on detection of heavy metals using paper-based microfluidic devices on the basis of various detection mechanisms, such as colorimetric, fluorescent, and electrochemical methods. To finalize, the future development and trend in this field are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Highly sensitive chemiluminescent point mutation detection by circular strand-displacement amplification reaction.

PubMed

Shi, Chao; Ge, Yujie; Gu, Hongxi; Ma, Cuiping

2011-08-15

Single nucleotide polymorphism (SNP) genotyping is attracting extensive attentions owing to its direct connections with human diseases including cancers. Here, we have developed a highly sensitive chemiluminescence biosensor based on circular strand-displacement amplification and the separation by magnetic beads reducing the background signal for point mutation detection at room temperature. This method took advantage of both the T4 DNA ligase recognizing single-base mismatch with high selectivity and the strand-displacement reaction of polymerase to perform signal amplification. The detection limit of this method was 1.3 × 10(-16)M, which showed better sensitivity than that of most of those reported detection methods of SNP. Additionally, the magnetic beads as carrier of immobility was not only to reduce the background signal, but also may have potential apply in high through-put screening of SNP detection in human genome. Copyright © 2011 Elsevier B.V. All rights reserved.

Optimization of a sensitive method for the determination of nitro musk fragrances in waters by solid-phase microextraction and gas chromatography with micro electron capture detection using factorial experimental design.

PubMed

Polo, Maria; Garcia-Jares, Carmen; Llompart, Maria; Cela, Rafael

2007-08-01

A solid-phase microextraction method (SPME) followed by gas chromatography with micro electron capture detection for determining trace levels of nitro musk fragrances in residual waters was optimized. Four nitro musks, musk xylene, musk moskene, musk tibetene and musk ketone, were selected for the optimization of the method. Factors affecting the extraction process were studied using a multivariate approach. Two extraction modes (direct SPME and headspace SPME) were tried at different extraction temperatures using two fiber coatings [Carboxen-polydimethylsiloxane (CAR/PDMS) and polydimethylsiloxane-divinylbenzene (PDMS/DVB)] selected among five commercial tested fibers. Sample agitation and the salting-out effect were also factors studied. The main effects and interactions between the factors were studied for all the target compounds. An extraction temperature of 100 degrees C and sampling the headspace over the sample, using either CAR/PDMS or PDMS/DVB as fiber coatings, were found to be the experimental conditions that led to a more effective extraction. High sensitivity, with detection limits in the low nanogram per liter range, and good linearity and repeatability were achieved for all nitro musks. Since the method proposed performed well for real samples, it was applied to different water samples, including wastewater and sewage, in which some of the target compounds (musk xylene and musk ketone) were detected and quantified.

Real-Time PCR with an Internal Control for Detection of All Known Human Adenovirus Serotypes▿

PubMed Central

Damen, Marjolein; Minnaar, René; Glasius, Patricia; van der Ham, Alwin; Koen, Gerrit; Wertheim, Pauline; Beld, Marcel

2008-01-01

The “gold standard” for the diagnosis of adenovirus (AV) infection is virus culture, which is rather time-consuming. Especially for immunocompromised patients, in whom severe infections with AV have been described, rapid diagnosis is important. Therefore, an internally controlled AV real-time PCR assay detecting all known human AV serotypes was developed. Primers were chosen from the hexon region, which is the most conserved region, and in order to cover all known serotypes, degenerate primers were used. The internal control (IC) DNA contained the same primer binding sites as the AV DNA control but had a shuffled probe region compared to the conserved 24-nucleotide consensus AV hexon probe region (the target). The IC DNA was added to the clinical sample in order to monitor extraction and PCR efficiency. The sensitivity and the linearity of the AV PCR were determined. For testing the specificity of this PCR assay for human AVs, a selection of 51 AV prototype strains and 66 patient samples positive for other DNA viruses were tested. Moreover, a comparison of the AV PCR method described herein with culture and antigen (Ag) detection was performed with a selection of 151 clinical samples. All 51 AV serotypes were detected in the selection of AV prototype strains. Concordant results from culture or Ag detection and PCR were found for 139 (92.1%) of 151 samples. In 12 cases (7.9%), PCR was positive while the culture was negative. In conclusion, a sensitive, internally controlled nonnested AV real-time PCR assay which is able to detect all known AV serotypes with higher sensitivity than a culture or Ag detection method was developed. PMID:18923006

Dithizone as novel and efficient chromogenic probe for cyanide detection in aqueous media through nucleophilic addition into diazenylthione moiety.

PubMed

Tavallali, Hossein; Deilamy-Rad, Gohar; Parhami, Abolfath; Kiyani, Sajede

2014-01-01

A new selective chemodosimeter probe was developed by the introduction of dithizone (DTZ) as a simple and available dye for detection of cyanide in aqueous media which enables recognition of cyanide over other competing anions such as acetate, dihydrogen phosphate, fluoride and benzoate through covalent bonding. The sensing properties of DTZ were investigated in DMSO/H2O (1:9) and have demonstrated a very high selectivity toward the cyanide anions. A reasonable recognition mechanism was suggested using UV-Vis, (1)H NMR and FTIR spectroscopy techniques. Time dependent density function theory (TDDFT) computations of UV-Vis excitation for DTZ2-CN adduct agreed well with our experimental findings. The detection limit of the new chromogenic probe was measured to be 0.48 μmol L(-1) which is much lower than most recently reported chromogenic probes for cyanide determination. The analytical utility of the method for the analysis of cyanide ions in electroplating wastewater (EPWW), human serum, tap and mineral water samples was demonstrated and the results were compared successfully with the conventional reference method. The short time response and the detection by the naked eye make the method available for the detection and quantitative determination of cyanide in a variety of real samples. Copyright © 2013 Elsevier B.V. All rights reserved.

Track-based event recognition in a realistic crowded environment

NASA Astrophysics Data System (ADS)

van Huis, Jasper R.; Bouma, Henri; Baan, Jan; Burghouts, Gertjan J.; Eendebak, Pieter T.; den Hollander, Richard J. M.; Dijk, Judith; van Rest, Jeroen H.

2014-10-01

Automatic detection of abnormal behavior in CCTV cameras is important to improve the security in crowded environments, such as shopping malls, airports and railway stations. This behavior can be characterized at different time scales, e.g., by small-scale subtle and obvious actions or by large-scale walking patterns and interactions between people. For example, pickpocketing can be recognized by the actual snatch (small scale), when he follows the victim, or when he interacts with an accomplice before and after the incident (longer time scale). This paper focusses on event recognition by detecting large-scale track-based patterns. Our event recognition method consists of several steps: pedestrian detection, object tracking, track-based feature computation and rule-based event classification. In the experiment, we focused on single track actions (walk, run, loiter, stop, turn) and track interactions (pass, meet, merge, split). The experiment includes a controlled setup, where 10 actors perform these actions. The method is also applied to all tracks that are generated in a crowded shopping mall in a selected time frame. The results show that most of the actions can be detected reliably (on average 90%) at a low false positive rate (1.1%), and that the interactions obtain lower detection rates (70% at 0.3% FP). This method may become one of the components that assists operators to find threatening behavior and enrich the selection of videos that are to be observed.

Detection of cerebrospinal fluid leakage by specific measurement of transferrin glycoforms.

PubMed

Kwon, Seok-Joon; Zhang, Fuming; Dordick, Jonathan S; Sonstein, William J; Linhardt, Robert J

2015-10-01

A simple and rapid detection of cerebrospinal fluid (CSF) leakage would benefit spine surgeons making critical postoperative decisions on patient care. We have assessed novel approaches to selectively determine CSF β2-transferrin (β2TF), an asialo-transferrin (aTF) biomarker, without interference from serum sialo-transferrin (sTF) in test samples. First, we performed mild periodate oxidation to selectively generate aldehyde groups in sTF for capture with magnetic hydrazide microparticles, and selective removal with a magnetic separator. Using this protocol sTF was selectively removed from mixtures of CSF and serum containing CSF aTF (β2TF) and serum sTF, respectively. Second, a two-step enzymatic method was developed with neuraminidase and galactose oxidase for generating aldehyde groups in sTF present in CSF and serum mixtures for magnetic hydrazide microparticle capture. After selectively removing sTF from mixtures of CSF and serum, ELISA could detect significant TF signal only in CSF, while the TF signal in serum was negligible. The new approach for selective removal of only sTF in test samples will be promising for the required intervention by a spine surgeon. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detecting selection signatures between Duroc and Duroc synthetic pig populations using high-density SNP chip.

PubMed

Edea, Z; Hong, J-K; Jung, J-H; Kim, D-W; Kim, Y-M; Kim, E-S; Shin, S S; Jung, Y C; Kim, K-S

2017-08-01

The development of high throughput genotyping techniques has facilitated the identification of selection signatures of pigs. The detection of genomic selection signals in a population subjected to differential selection pressures may provide insights into the genes associated with economically and biologically important traits. To identify genomic regions under selection, we genotyped 488 Duroc (D) pigs and 155 D × Korean native pigs (DKNPs) using the Porcine SNP70K BeadChip. By applying the F ST and extended haplotype homozygosity (EHH-Rsb) methods, we detected genes under directional selection associated with growth/stature (DOCK7, PLCB4, HS2ST1, FBP2 and TG), carcass and meat quality (TG, COL14A1, FBXO5, NR3C1, SNX7, ARHGAP26 and DPYD), number of teats (LOC100153159 and LRRC1), pigmentation (MME) and ear morphology (SOX5), which are all mostly near or at fixation. These results could be a basis for investigating the underlying mutations associated with observed phenotypic variation. Validation using genome-wide association analysis would also facilitate the inclusion of some of these markers in genetic evaluation programs. © 2017 Stichting International Foundation for Animal Genetics.

N-Hydroxysuccinimide as an effective chemiluminescence coreactant for highly selective and sensitive detection.

PubMed

Saqib, Muhammad; Li, Suping; Gao, Wenyue; Majeed, Saadat; Qi, Liming; Liu, Zhongyuan; Xu, Guobao

2016-12-01

The development of novel coreactants for chemiluminescence is very important to improve performance and widen its applications without using any other catalyst. N-Hydroxysuccinimide (NHS), a highly popular amine-reactive, activating, or protecting reagent in biochemical applications and organic synthesis, has been explored as an efficient and stable chemiluminescence coreactant for the first time. The chemiluminescence intensity of the newly developed luminol-NHS system is about 22 times higher than that of the traditional luminol-H 2 O 2 system. Chemiluminescence of this system is dramatically enhanced by Co 2+ . This new chemiluminescence system is then applied for the highly selective and ultrasensitive detection of Co 2+ with limit of detection (0.01 nM) better than those of several conventional analytical methods. This system also enables the efficient detection of luminol (LOD = 7 pM) and NHS (LOD = 3.0 μM) with excellent sensitivity. This chemiluminescence method was then also utilized to detect Co 2+ in tap water and blue silica gel with excellent recoveries in the range 99.20-103.07 %. This novel chemiluminescence system has several advantages, including simple, cost-effective, highly sensitive, selective, and wide linear range. We expect that this chemiluminescence system will be a promising candidate for chemical and biological sensing. Graphical Abstract Comparison of CL peak intensities of classical luminol-H 2 O 2 CL system and newly developed luminol-NHS CL system.

Transfer Rate Edited experiment for the selective detection of Chemical Exchange via Saturation Transfer (TRE-CEST).

PubMed

Friedman, Joshua I; Xia, Ding; Regatte, Ravinder R; Jerschow, Alexej

2015-07-01

Chemical Exchange Saturation Transfer (CEST) magnetic resonance experiments have become valuable tools in magnetic resonance for the detection of low concentration solutes with far greater sensitivity than direct detection methods. Accurate measures of rates of chemical exchange provided by CEST are of particular interest to biomedical imaging communities where variations in chemical exchange can be related to subtle variations in biomarker concentration, temperature and pH within tissues using MRI. Despite their name, however, traditional CEST methods are not truly selective for chemical exchange and instead detect all forms of magnetization transfer including through-space NOE. This ambiguity crowds CEST spectra and greatly complicates subsequent data analysis. We have developed a Transfer Rate Edited CEST experiment (TRE-CEST) that uses two different types of solute labeling in order to selectively amplify signals of rapidly exchanging proton species while simultaneously suppressing 'slower' NOE-dominated magnetization transfer processes. This approach is demonstrated in the context of both NMR and MRI, where it is used to detect the labile amide protons of proteins undergoing chemical exchange (at rates⩾30s(-1)) while simultaneously eliminating signals originating from slower (∼5s(-1)) NOE-mediated magnetization transfer processes. TRE-CEST greatly expands the utility of CEST experiments in complex systems, and in-vivo, in particular, where it is expected to improve the quantification of chemical exchange and magnetization transfer rates while enabling new forms of imaging contrast. Copyright © 2015 Elsevier Inc. All rights reserved.

Transfer Rate Edited experiment for the selective detection of Chemical Exchange via Saturation Transfer (TRE-CEST)

NASA Astrophysics Data System (ADS)

Friedman, Joshua I.; Xia, Ding; Regatte, Ravinder R.; Jerschow, Alexej

2015-07-01

Chemical Exchange Saturation Transfer (CEST) magnetic resonance experiments have become valuable tools in magnetic resonance for the detection of low concentration solutes with far greater sensitivity than direct detection methods. Accurate measures of rates of chemical exchange provided by CEST are of particular interest to biomedical imaging communities where variations in chemical exchange can be related to subtle variations in biomarker concentration, temperature and pH within tissues using MRI. Despite their name, however, traditional CEST methods are not truly selective for chemical exchange and instead detect all forms of magnetization transfer including through-space NOE. This ambiguity crowds CEST spectra and greatly complicates subsequent data analysis. We have developed a Transfer Rate Edited CEST experiment (TRE-CEST) that uses two different types of solute labeling in order to selectively amplify signals of rapidly exchanging proton species while simultaneously suppressing 'slower' NOE-dominated magnetization transfer processes. This approach is demonstrated in the context of both NMR and MRI, where it is used to detect the labile amide protons of proteins undergoing chemical exchange (at rates ⩾ 30 s-1) while simultaneously eliminating signals originating from slower (∼5 s-1) NOE-mediated magnetization transfer processes. TRE-CEST greatly expands the utility of CEST experiments in complex systems, and in-vivo, in particular, where it is expected to improve the quantification of chemical exchange and magnetization transfer rates while enabling new forms of imaging contrast.

Comparison of Different EHG Feature Selection Methods for the Detection of Preterm Labor

PubMed Central

Alamedine, D.; Khalil, M.; Marque, C.

2013-01-01

Numerous types of linear and nonlinear features have been extracted from the electrohysterogram (EHG) in order to classify labor and pregnancy contractions. As a result, the number of available features is now very large. The goal of this study is to reduce the number of features by selecting only the relevant ones which are useful for solving the classification problem. This paper presents three methods for feature subset selection that can be applied to choose the best subsets for classifying labor and pregnancy contractions: an algorithm using the Jeffrey divergence (JD) distance, a sequential forward selection (SFS) algorithm, and a binary particle swarm optimization (BPSO) algorithm. The two last methods are based on a classifier and were tested with three types of classifiers. These methods have allowed us to identify common features which are relevant for contraction classification. PMID:24454536

Segmentation of suspicious objects in an x-ray image using automated region filling approach

NASA Astrophysics Data System (ADS)

Fu, Kenneth; Guest, Clark; Das, Pankaj

2009-08-01

To accommodate the flow of commerce, cargo inspection systems require a high probability of detection and low false alarm rate while still maintaining a minimum scan speed. Since objects of interest (high atomic-number metals) will often be heavily shielded to avoid detection, any detection algorithm must be able to identify such objects despite the shielding. Since pixels of a shielded object have a greater opacity than the shielding, we use a clustering method to classify objects in the image by pixel intensity levels. We then look within each intensity level region for sub-clusters of pixels with greater opacity than the surrounding region. A region containing an object has an enclosed-contour region (a hole) inside of it. We apply a region filling technique to fill in the hole, which represents a shielded object of potential interest. One method for region filling is seed-growing, which puts a "seed" starting point in the hole area and uses a selected structural element to fill out that region. However, automatic seed point selection is a hard problem; it requires additional information to decide if a pixel is within an enclosed region. Here, we propose a simple, robust method for region filling that avoids the problem of seed point selection. In our approach, we calculate the gradient Gx and Gy at each pixel in a binary image, and fill in 1s between a pair of x1 Gx(x1,y)=-1 and x2 Gx(x2,y)=1, and do the same thing in y-direction. The intersection of the two results will be filled region. We give a detailed discussion of our algorithm, discuss the strengths this method has over other methods, and show results of using our method.