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

PubMed

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

2017-03-28

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

Comparison of Relative Bias, Precision, and Efficiency of Sampling Methods for Natural Enemies of Soybean Aphid (Hemiptera: Aphididae).

PubMed

Bannerman, J A; Costamagna, A C; McCornack, B P; Ragsdale, D W

2015-06-01

Generalist natural enemies play an important role in controlling soybean aphid, Aphis glycines (Hemiptera: Aphididae), in North America. Several sampling methods are used to monitor natural enemy populations in soybean, but there has been little work investigating their relative bias, precision, and efficiency. We compare five sampling methods: quadrats, whole-plant counts, sweep-netting, walking transects, and yellow sticky cards to determine the most practical methods for sampling the three most prominent species, which included Harmonia axyridis (Pallas), Coccinella septempunctata L. (Coleoptera: Coccinellidae), and Orius insidiosus (Say) (Hemiptera: Anthocoridae). We show an important time by sampling method interaction indicated by diverging community similarities within and between sampling methods as the growing season progressed. Similarly, correlations between sampling methods for the three most abundant species over multiple time periods indicated differences in relative bias between sampling methods and suggests that bias is not consistent throughout the growing season, particularly for sticky cards and whole-plant samples. Furthermore, we show that sticky cards produce strongly biased capture rates relative to the other four sampling methods. Precision and efficiency differed between sampling methods and sticky cards produced the most precise (but highly biased) results for adult natural enemies, while walking transects and whole-plant counts were the most efficient methods for detecting coccinellids and O. insidiosus, respectively. Based on bias, precision, and efficiency considerations, the most practical sampling methods for monitoring in soybean include walking transects for coccinellid detection and whole-plant counts for detection of small predators like O. insidiosus. Sweep-netting and quadrat samples are also useful for some applications, when efficiency is not paramount. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Efficiency transfer using the GEANT4 code of CERN for HPGe gamma spectrometry.

PubMed

Chagren, S; Tekaya, M Ben; Reguigui, N; Gharbi, F

2016-01-01

In this work we apply the GEANT4 code of CERN to calculate the peak efficiency in High Pure Germanium (HPGe) gamma spectrometry using three different procedures. The first is a direct calculation. The second corresponds to the usual case of efficiency transfer between two different configurations at constant emission energy assuming a reference point detection configuration and the third, a new procedure, consists on the transfer of the peak efficiency between two detection configurations emitting the gamma ray in different energies assuming a "virtual" reference point detection configuration. No pre-optimization of the detector geometrical characteristics was performed before the transfer to test the ability of the efficiency transfer to reduce the effect of the ignorance on their real magnitude on the quality of the transferred efficiency. The obtained and measured efficiencies were found in good agreement for the two investigated methods of efficiency transfer. The obtained agreement proves that Monte Carlo method and especially the GEANT4 code constitute an efficient tool to obtain accurate detection efficiency values. The second investigated efficiency transfer procedure is useful to calibrate the HPGe gamma detector for any emission energy value for a voluminous source using one point source detection efficiency emitting in a different energy as a reference efficiency. The calculations preformed in this work were applied to the measurement exercise of the EUROMET428 project. A measurement exercise where an evaluation of the full energy peak efficiencies in the energy range 60-2000 keV for a typical coaxial p-type HpGe detector and several types of source configuration: point sources located at various distances from the detector and a cylindrical box containing three matrices was performed. Copyright © 2015 Elsevier Ltd. All rights reserved.

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

Highlight on Bottlenecks in Food Allergen Analysis: Detection and Quantification by Mass Spectrometry.

PubMed

Planque, Mélanie; Arnould, Thierry; Renard, Patricia; Delahaut, Philippe; Dieu, Marc; Gillard, Nathlie

2017-07-01

Food laboratories have developed methods for testing allergens in foods. The efficiency of qualitative and quantitative methods is of prime importance in protecting allergic populations. Unfortunately, food laboratories encounter barriers to developing efficient methods. Bottlenecks include the lack of regulatory thresholds, delays in the emergence of reference materials and guidelines, and the need to detect processed allergens. In this study, ultra-HPLC coupled to tandem MS was used to illustrate difficulties encountered in determining method performances. We measured the major influences of both processing and matrix effects on the detection of egg, milk, soy, and peanut allergens in foodstuffs. The main goals of this work were to identify difficulties that food laboratories still encounter in detecting and quantifying allergens and to sensitize researchers to them.

Circulating tumor cell detection: A direct comparison between negative and unbiased enrichment in lung cancer.

PubMed

Xu, Yan; Liu, Biao; Ding, Fengan; Zhou, Xiaodie; Tu, Pin; Yu, Bo; He, Yan; Huang, Peilin

2017-06-01

Circulating tumor cells (CTCs), isolated as a 'liquid biopsy', may provide important diagnostic and prognostic information. Therefore, rapid, reliable and unbiased detection of CTCs are required for routine clinical analyses. It was demonstrated that negative enrichment, an epithelial marker-independent technique for isolating CTCs, exhibits a better efficiency in the detection of CTCs compared with positive enrichment techniques that only use specific anti-epithelial cell adhesion molecules. However, negative enrichment techniques incur significant cell loss during the isolation procedure, and as it is a method that uses only one type of antibody, it is inherently biased. The detection procedure and identification of cell types also relies on skilled and experienced technicians. In the present study, the detection sensitivity of using negative enrichment and a previously described unbiased detection method was compared. The results revealed that unbiased detection methods may efficiently detect >90% of cancer cells in blood samples containing CTCs. By contrast, only 40-60% of CTCs were detected by negative enrichment. Additionally, CTCs were identified in >65% of patients with stage I/II lung cancer. This simple yet efficient approach may achieve a high level of sensitivity. It demonstrates a potential for the large-scale clinical implementation of CTC-based diagnostic and prognostic strategies.

Detection of wood failure by image processing method: influence of algorithm, adhesive and wood species

Treesearch

Lanying Lin; Sheng He; Feng Fu; Xiping Wang

2015-01-01

Wood failure percentage (WFP) is an important index for evaluating the bond strength of plywood. Currently, the method used for detecting WFP is visual inspection, which lacks efficiency. In order to improve it, image processing methods are applied to wood failure detection. The present study used thresholding and K-means clustering algorithms in wood failure detection...

Intraoperative detection of 18F-FDG-avid tissue sites using the increased probe counting efficiency of the K-alpha probe design and variance-based statistical analysis with the three-sigma criteria

PubMed Central

2013-01-01

Background Intraoperative detection of 18F-FDG-avid tissue sites during 18F-FDG-directed surgery can be very challenging when utilizing gamma detection probes that rely on a fixed target-to-background (T/B) ratio (ratiometric threshold) for determination of probe positivity. The purpose of our study was to evaluate the counting efficiency and the success rate of in situ intraoperative detection of 18F-FDG-avid tissue sites (using the three-sigma statistical threshold criteria method and the ratiometric threshold criteria method) for three different gamma detection probe systems. Methods Of 58 patients undergoing 18F-FDG-directed surgery for known or suspected malignancy using gamma detection probes, we identified nine 18F-FDG-avid tissue sites (from amongst seven patients) that were seen on same-day preoperative diagnostic PET/CT imaging, and for which each 18F-FDG-avid tissue site underwent attempted in situ intraoperative detection concurrently using three gamma detection probe systems (K-alpha probe, and two commercially-available PET-probe systems), and then were subsequently surgical excised. Results The mean relative probe counting efficiency ratio was 6.9 (± 4.4, range 2.2–15.4) for the K-alpha probe, as compared to 1.5 (± 0.3, range 1.0–2.1) and 1.0 (± 0, range 1.0–1.0), respectively, for two commercially-available PET-probe systems (P < 0.001). Successful in situ intraoperative detection of 18F-FDG-avid tissue sites was more frequently accomplished with each of the three gamma detection probes tested by using the three-sigma statistical threshold criteria method than by using the ratiometric threshold criteria method, specifically with the three-sigma statistical threshold criteria method being significantly better than the ratiometric threshold criteria method for determining probe positivity for the K-alpha probe (P = 0.05). Conclusions Our results suggest that the improved probe counting efficiency of the K-alpha probe design used in conjunction with the three-sigma statistical threshold criteria method can allow for improved detection of 18F-FDG-avid tissue sites when a low in situ T/B ratio is encountered. PMID:23496877

Gastric cancer screening of a high-risk population in Japan using serum pepsinogen and barium digital radiography.

PubMed

Ohata, Hiroshi; Oka, Masashi; Yanaoka, Kimihiko; Shimizu, Yasuhito; Mukoubayashi, Chizu; Mugitani, Kouichi; Iwane, Masataka; Nakamura, Hideya; Tamai, Hideyuki; Arii, Kenji; Nakata, Hiroya; Yoshimura, Noriko; Takeshita, Tetsuya; Miki, Kazumasa; Mohara, Osamu; Ichinose, Masao

2005-10-01

With the aim of developing more efficient gastric cancer screening programs for use in Japan, we studied a new screening program that combines serum pepsinogen (PG) testing and barium digital radiography (DR). A total of 17 647 middle-aged male subjects underwent workplace screening over a 7-year period using a combination of PG testing and DR. This program's effectiveness, as well as other characteristics of the program, was analyzed. Forty-nine cases of gastric cancer were detected (comprising 88% early cancer cases). The detection rate was 0.28%, and the positive predictive value was 0.85%. The PG test detected 63.3% of cases, DR detected 69.4% of cases, and both tests were positive in 32.7% of cancer cases. The two methods were almost equally effective, and were considerably more effective than conventional screening using photofluorography. Each screening method detected a distinct gastric cancer subgroup; the PG test efficiently detected asymptomatic small early cancer with intestinal type histology, while DR was efficient at detecting cancers with depressed or ulcerated morphology and diffuse type histology. The cost for the detection of a single cancer was much less than that for conventional screening. In fact, it is possible to further reduce the cost of detecting a single cancer to a cost comparable to that of surgically resecting a single gastric cancer. Thus, it is probable that a highly efficient gastric cancer screening system can be implemented by combining the two screening methods. Such a screening program would be beneficial in a population at high risk for gastric cancer.

A Simple Method to Simultaneously Detect and Identify Spikes from Raw Extracellular Recordings.

PubMed

Petrantonakis, Panagiotis C; Poirazi, Panayiota

2015-01-01

The ability to track when and which neurons fire in the vicinity of an electrode, in an efficient and reliable manner can revolutionize the neuroscience field. The current bottleneck lies in spike sorting algorithms; existing methods for detecting and discriminating the activity of multiple neurons rely on inefficient, multi-step processing of extracellular recordings. In this work, we show that a single-step processing of raw (unfiltered) extracellular signals is sufficient for both the detection and identification of active neurons, thus greatly simplifying and optimizing the spike sorting approach. The efficiency and reliability of our method is demonstrated in both real and simulated data.

Vision Based Obstacle Detection in Uav Imaging

NASA Astrophysics Data System (ADS)

Badrloo, S.; Varshosaz, M.

2017-08-01

Detecting and preventing incidence with obstacles is crucial in UAV navigation and control. Most of the common obstacle detection techniques are currently sensor-based. Small UAVs are not able to carry obstacle detection sensors such as radar; therefore, vision-based methods are considered, which can be divided into stereo-based and mono-based techniques. Mono-based methods are classified into two groups: Foreground-background separation, and brain-inspired methods. Brain-inspired methods are highly efficient in obstacle detection; hence, this research aims to detect obstacles using brain-inspired techniques, which try to enlarge the obstacle by approaching it. A recent research in this field, has concentrated on matching the SIFT points along with, SIFT size-ratio factor and area-ratio of convex hulls in two consecutive frames to detect obstacles. This method is not able to distinguish between near and far obstacles or the obstacles in complex environment, and is sensitive to wrong matched points. In order to solve the above mentioned problems, this research calculates the dist-ratio of matched points. Then, each and every point is investigated for Distinguishing between far and close obstacles. The results demonstrated the high efficiency of the proposed method in complex environments.

Flash memory management system and method utilizing multiple block list windows

NASA Technical Reports Server (NTRS)

Chow, James (Inventor); Gender, Thomas K. (Inventor)

2005-01-01

The present invention provides a flash memory management system and method with increased performance. The flash memory management system provides the ability to efficiently manage and allocate flash memory use in a way that improves reliability and longevity, while maintaining good performance levels. The flash memory management system includes a free block mechanism, a disk maintenance mechanism, and a bad block detection mechanism. The free block mechanism provides efficient sorting of free blocks to facilitate selecting low use blocks for writing. The disk maintenance mechanism provides for the ability to efficiently clean flash memory blocks during processor idle times. The bad block detection mechanism provides the ability to better detect when a block of flash memory is likely to go bad. The flash status mechanism stores information in fast access memory that describes the content and status of the data in the flash disk. The new bank detection mechanism provides the ability to automatically detect when new banks of flash memory are added to the system. Together, these mechanisms provide a flash memory management system that can improve the operational efficiency of systems that utilize flash memory.

Coincidence and coherent data analysis methods for gravitational wave bursts in a network of interferometric detectors

NASA Astrophysics Data System (ADS)

Arnaud, Nicolas; Barsuglia, Matteo; Bizouard, Marie-Anne; Brisson, Violette; Cavalier, Fabien; Davier, Michel; Hello, Patrice; Kreckelbergh, Stephane; Porter, Edward K.

2003-11-01

Network data analysis methods are the only way to properly separate real gravitational wave (GW) transient events from detector noise. They can be divided into two generic classes: the coincidence method and the coherent analysis. The former uses lists of selected events provided by each interferometer belonging to the network and tries to correlate them in time to identify a physical signal. Instead of this binary treatment of detector outputs (signal present or absent), the latter method involves first the merging of the interferometer data and looks for a common pattern, consistent with an assumed GW waveform and a given source location in the sky. The thresholds are only applied later, to validate or not the hypothesis made. As coherent algorithms use more complete information than coincidence methods, they are expected to provide better detection performances, but at a higher computational cost. An efficient filter must yield a good compromise between a low false alarm rate (hence triggering on data at a manageable rate) and a high detection efficiency. Therefore, the comparison of the two approaches is achieved using so-called receiving operating characteristics (ROC), giving the relationship between the false alarm rate and the detection efficiency for a given method. This paper investigates this question via Monte Carlo simulations, using the network model developed in a previous article. Its main conclusions are the following. First, a three-interferometer network such as Virgo-LIGO is found to be too small to reach good detection efficiencies at low false alarm rates: larger configurations are suitable to reach a confidence level high enough to validate as true GW a detected event. In addition, an efficient network must contain interferometers with comparable sensitivities: studying the three-interferometer LIGO network shows that the 2-km interferometer with half sensitivity leads to a strong reduction of performances as compared to a network of three interferometers with full sensitivity. Finally, it is shown that coherent analyses are feasible for burst searches and are clearly more efficient than coincidence strategies. Therefore, developing such methods should be an important goal of a worldwide collaborative data analysis.

Comprehensive Detection of Gas Plumes from Multibeam Water Column Images with Minimisation of Noise Interferences

PubMed Central

Zhao, Jianhu; Zhang, Hongmei; Wang, Shiqi

2017-01-01

Multibeam echosounder systems (MBES) can record backscatter strengths of gas plumes in the water column (WC) images that may be an indicator of possible occurrence of gas at certain depths. Manual or automatic detection is generally adopted in finding gas plumes, but frequently results in low efficiency and high false detection rates because of WC images that are polluted by noise. To improve the efficiency and reliability of the detection, a comprehensive detection method is proposed in this paper. In the proposed method, the characteristics of WC background noise are first analyzed and given. Then, the mean standard deviation threshold segmentations are respectively used for the denoising of time-angle and depth-angle images, an intersection operation is performed for the two segmented images to further weaken noise in the WC data, and the gas plumes in the WC data are detected from the intersection image by the morphological constraint. The proposed method was tested by conducting shallow-water and deepwater experiments. In these experiments, the detections were conducted automatically and higher correct detection rates than the traditional methods were achieved. The performance of the proposed method is analyzed and discussed. PMID:29186014

A combined experimental-modelling method for the detection and analysis of pollution in coastal zones

NASA Astrophysics Data System (ADS)

Limić, Nedzad; Valković, Vladivoj

1996-04-01

Pollution of coastal seas with toxic substances can be efficiently detected by examining toxic materials in sediment samples. These samples contain information on the overall pollution from surrounding sources such as yacht anchorages, nearby industries, sewage systems, etc. In an efficient analysis of pollution one must determine the contribution from each individual source. In this work it is demonstrated that a modelling method can be utilized for solving this latter problem. The modelling method is based on a unique interpretation of concentrations in sediments from all sampling stations. The proposed method is a synthesis consisting of the utilization of PIXE as an efficient method of pollution concentration determination and the code ANCOPOL (N. Limic and R. Benis, The computer code ANCOPOL, SimTel/msdos/geology, 1994 [1]) for the calculation of contributions from the main polluters. The efficiency and limits of the proposed method are demonstrated by discussing trace element concentrations in sediments of Punat Bay on the island of Krk in Croatia.

Detection of Viable Cryptosporidium parvum in Soil by Reverse Transcription–Real-Time PCR Targeting hsp70 mRNA ▿

PubMed Central

Liang, Zhanbei; Keeley, Ann

2011-01-01

Extraction of high-quality mRNA from Cryptosporidium parvum is a key step in PCR detection of viable oocysts in environmental samples. Current methods for monitoring oocysts are limited to water samples; therefore, the goal of this study was to develop a rapid and sensitive procedure for Cryptosporidium detection in soil samples. The efficiencies of five RNA extraction methods were compared (mRNA extraction with the Dynabeads mRNA Direct kit after chemical and physical sample treatments, and total RNA extraction methods using the FastRNA Pro Soil-Direct, PowerSoil Total RNA, E.Z.N.A. soil RNA, and Norgen soil RNA purification kits) for the direct detection of Cryptosporidium with oocyst-spiked sandy, loamy, and clay soils by using TaqMan reverse transcription-PCR. The study also evaluated the presence of inhibitors by synthesis and incorporation of an internal positive control (IPC) RNA into reverse transcription amplifications, used different facilitators (bovine serum albumin, yeast RNA, salmon DNA, skim milk powder, casein, polyvinylpyrrolidone, sodium hexametaphosphate, and Salmonella enterica serovar Typhi) to mitigate RNA binding on soil components, and applied various treatments (β-mercaptoethanol and bead beating) to inactivate RNase and ensure the complete lysis of oocysts. The results of spiking studies showed that Salmonella cells most efficiently relieved binding of RNA. With the inclusion of Salmonella during extraction, the most efficient mRNA method was Dynabeads, with a detection limit of 6 × 102 oocysts g−1 of sandy soil. The most efficient total RNA method was PowerSoil, with detection limits of 1.5 × 102, 1.5 × 103, and 1.5 × 104 C. parvum oocysts g−1 soil for sandy, loamy, and clay samples, respectively. PMID:21803904

Development of a novel and highly efficient method of isolating bacteriophages from water.

PubMed

Liu, Weili; Li, Chao; Qiu, Zhi-Gang; Jin, Min; Wang, Jing-Feng; Yang, Dong; Xiao, Zhong-Hai; Yuan, Zhao-Kang; Li, Jun-Wen; Xu, Qun-Ying; Shen, Zhi-Qiang

2017-08-01

Bacteriophages are widely used to the treatment of drug-resistant bacteria and the improvement of food safety through bacterial lysis. However, the limited investigations on bacteriophage restrict their further application. In this study, a novel and highly efficient method was developed for isolating bacteriophage from water based on the electropositive silica gel particles (ESPs) method. To optimize the ESPs method, we evaluated the eluent type, flow rate, pH, temperature, and inoculation concentration of bacteriophage using bacteriophage f2. The quantitative detection reported that the recovery of the ESPs method reached over 90%. The qualitative detection demonstrated that the ESPs method effectively isolated 70% of extremely low-concentration bacteriophage (10 0 PFU/100L). Based on the host bacteria composed of 33 standard strains and 10 isolated strains, the bacteriophages in 18 water samples collected from the three sites in the Tianjin Haihe River Basin were isolated by the ESPs and traditional methods. Results showed that the ESPs method was significantly superior to the traditional method. The ESPs method isolated 32 strains of bacteriophage, whereas the traditional method isolated 15 strains. The sample isolation efficiency and bacteriophage isolation efficiency of the ESPs method were 3.28 and 2.13 times higher than those of the traditional method. The developed ESPs method was characterized by high isolation efficiency, efficient handling of large water sample size and low requirement on water quality. Copyright © 2017. Published by Elsevier B.V.

Nanostructure and Corresponding Quenching Efficiency of Fluorescent DNA Probes.

PubMed

Guo, Wenjuan; Wei, Yanhong; Dai, Zhao; Chen, Guangping; Chu, Yuanyuan; Zhao, Yifei

2018-02-09

Based on the fluorescence resonance energy transfer (FRET) mechanism, fluorescent DNA probes were prepared with a novel DNA hairpin template method, with SiO₂ coated CdTe (CdTe/SiO₂) core/shell nanoparticles used as the fluorescence energy donors and gold (Au) nanoparticles (AuNPs) as the energy acceptors. The nanostructure and energy donor/acceptor ratio in a probe were controlled with this method. The relationship between the nanostructure of the probes and FRET efficiency (quenching efficiency) were investigated. The results indicated that when the donor/acceptor ratios were 2:1, 1:1, and 1:2; the corresponding FRET efficiencies were about 33.6%, 57.5%, and 74.2%, respectively. The detection results indicated that the fluorescent recovery efficiency of the detecting system was linear when the concentration of the target DNA was about 0.0446-2.230 nmol/L. Moreover, the probes showed good sensitivity and stability in different buffer conditions with a low detection limit of about 0.106 nmol/L.

Nanostructure and Corresponding Quenching Efficiency of Fluorescent DNA Probes

PubMed Central

Guo, Wenjuan; Wei, Yanhong; Dai, Zhao; Chen, Guangping; Chu, Yuanyuan; Zhao, Yifei

2018-01-01

Based on the fluorescence resonance energy transfer (FRET) mechanism, fluorescent DNA probes were prepared with a novel DNA hairpin template method, with SiO2 coated CdTe (CdTe/SiO2) core/shell nanoparticles used as the fluorescence energy donors and gold (Au) nanoparticles (AuNPs) as the energy acceptors. The nanostructure and energy donor/acceptor ratio in a probe were controlled with this method. The relationship between the nanostructure of the probes and FRET efficiency (quenching efficiency) were investigated. The results indicated that when the donor/acceptor ratios were 2:1, 1:1, and 1:2; the corresponding FRET efficiencies were about 33.6%, 57.5%, and 74.2%, respectively. The detection results indicated that the fluorescent recovery efficiency of the detecting system was linear when the concentration of the target DNA was about 0.0446–2.230 nmol/L. Moreover, the probes showed good sensitivity and stability in different buffer conditions with a low detection limit of about 0.106 nmol/L. PMID:29425163

Energy efficiency in cognitive radio network: Study of cooperative sensing using different channel sensing methods

NASA Astrophysics Data System (ADS)

Cui, Chenxuan

When cognitive radio (CR) operates, it starts by sensing spectrum and looking for idle bandwidth. There are several methods for CR to make a decision on either the channel is occupied or idle, for example, energy detection scheme, cyclostationary detection scheme and matching filtering detection scheme [1]. Among them, the most common method is energy detection scheme because of its algorithm and implementation simplicities [2]. There are two major methods for sensing, the first one is to sense single channel slot with varying bandwidth, whereas the second one is to sense multiple channels and each with same bandwidth. After sensing periods, samples are compared with a preset detection threshold and a decision is made on either the primary user (PU) is transmitting or not. Sometimes the sensing and decision results can be erroneous, for example, false alarm error and misdetection error may occur. In order to better control error probabilities and improve CR network performance (i.e. energy efficiency), we introduce cooperative sensing; in which several CR within a certain range detect and make decisions on channel availability together. The decisions are transmitted to and analyzed by a data fusion center (DFC) to make a final decision on channel availability. After the final decision is been made, DFC sends back the decision to the CRs in order to tell them to stay idle or start to transmit data to secondary receiver (SR) within a preset transmission time. After the transmission, a new cycle starts again with sensing. This thesis report is organized as followed: Chapter II review some of the papers on optimizing CR energy efficiency. In Chapter III, we study how to achieve maximal energy efficiency when CR senses single channel with changing bandwidth and with constrain on misdetection threshold in order to protect PU; furthermore, a case study is given and we calculate the energy efficiency. In Chapter IV, we study how to achieve maximal energy efficiency when CR senses multiple channels and each channel with same bandwidth, also, we preset a misdetection threshold and calculate the energy efficiency. A comparison will be shown between two sensing methods at the end of the chapter. Finally, Chapter V concludes this thesis.

Bacteriophage-based nanoprobes for rapid bacteria separation

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

[Quant efficiency of the detection as a quality parameter of the visualization equipment].

PubMed

Morgun, O N; Nemchenko, K E; Rogov, Iu V

2003-01-01

The critical parameter of notion "quant efficiency of detection" is defined in the paper. Different methods of specifying the detection quant efficiency (DQE) are under discussion. Thus, techniques of DQE determination for a whole unit and means of DQE finding at terminal space frequency are addressed. The notion of DQE at zero frequency is in the focus of attention. Finally, difficulties occurring in determining the above parameter as well as its disadvantages (as a parameter characterizing the quality of X-ray irradiation visualizing systems) are also discussed.

Highly specific and efficient primers for in-house multiplex PCR detection of Chlamydia trachomatis, Neisseria gonorrhoeae, Mycoplasma hominis and Ureaplasma urealyticum

PubMed Central

2014-01-01

Background Although sophisticated methodologies are available, the use of endpoint polymerase chain reaction (PCR) to detect 16S rDNA genes remains a good approach for estimating the incidence and prevalence of specific infections and for monitoring infections. Considering the importance of the early diagnosis of sexually transmitted infections (STIs), the development of a sensitive and affordable method for identifying pathogens in clinical samples is needed. Highly specific and efficient primers for a multiplex polymerase chain reaction (m-PCR) system were designed in silico to detect the 16S rDNA genes of four bacteria that cause genital infections, and the PCR method was developed. Methods The Genosensor Probe Designer (GPD) (version 1.0a) software was initially used to design highly specific and efficient primers for in-house m-PCR. Single-locus PCR reactions were performed and standardised, and then primers for each locus in turn were added individually in subsequent amplifications until m-PCR was achieved. Amplicons of the expected size were obtained from each of the four bacterial gene fragments. Finally, the analytical specificity and limits of detection were tested. Results Because they did not amplify any product from non-STI tested species, the primers were specific. The detection limits for the Chlamydia trachomatis, Neisseria gonorrhoeae, Mycoplasma hominis and Ureaplasma urealyticum primer sets were 5.12 × 105, 3.9 × 103, 61.19 × 106 and 6.37 × 105 copies of a DNA template, respectively. Conclusions The methodology designed and standardised here could be applied satisfactorily for the simultaneous or individual detection of Chlamydia trachomatis, Neisseria gonorrhoeae, Mycoplasma hominis and Ureaplasma urealyticum. This method is at least as efficient as other previously described methods; however, this method is more affordable for low-income countries. PMID:24997675

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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.

[Optimized application of nested PCR method for detection of malaria].

PubMed

Yao-Guang, Z; Li, J; Zhen-Yu, W; Li, C

2017-04-28

Objective To optimize the application of the nested PCR method for the detection of malaria according to the working practice, so as to improve the efficiency of malaria detection. Methods Premixing solution of PCR, internal primers for further amplification and new designed primers that aimed at two Plasmodium ovale subspecies were employed to optimize the reaction system, reaction condition and specific primers of P . ovale on basis of routine nested PCR. Then the specificity and the sensitivity of the optimized method were analyzed. The positive blood samples and examination samples of malaria were detected by the routine nested PCR and the optimized method simultaneously, and the detection results were compared and analyzed. Results The optimized method showed good specificity, and its sensitivity could reach the pg to fg level. The two methods were used to detect the same positive malarial blood samples simultaneously, the results indicated that the PCR products of the two methods had no significant difference, but the non-specific amplification reduced obviously and the detection rates of P . ovale subspecies improved, as well as the total specificity also increased through the use of the optimized method. The actual detection results of 111 cases of malarial blood samples showed that the sensitivity and specificity of the routine nested PCR were 94.57% and 86.96%, respectively, and those of the optimized method were both 93.48%, and there was no statistically significant difference between the two methods in the sensitivity ( P > 0.05), but there was a statistically significant difference between the two methods in the specificity ( P < 0.05). Conclusion The optimized PCR can improve the specificity without reducing the sensitivity on the basis of the routine nested PCR, it also can save the cost and increase the efficiency of malaria detection as less experiment links.

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images

PubMed Central

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-01-01

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency. PMID:28640236

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

PubMed

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-06-22

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

Development of a methodology for the detection of hospital financial outliers using information systems.

PubMed

Okada, Sachiko; Nagase, Keisuke; Ito, Ayako; Ando, Fumihiko; Nakagawa, Yoshiaki; Okamoto, Kazuya; Kume, Naoto; Takemura, Tadamasa; Kuroda, Tomohiro; Yoshihara, Hiroyuki

2014-01-01

Comparison of financial indices helps to illustrate differences in operations and efficiency among similar hospitals. Outlier data tend to influence statistical indices, and so detection of outliers is desirable. Development of a methodology for financial outlier detection using information systems will help to reduce the time and effort required, eliminate the subjective elements in detection of outlier data, and improve the efficiency and quality of analysis. The purpose of this research was to develop such a methodology. Financial outliers were defined based on a case model. An outlier-detection method using the distances between cases in multi-dimensional space is proposed. Experiments using three diagnosis groups indicated successful detection of cases for which the profitability and income structure differed from other cases. Therefore, the method proposed here can be used to detect outliers. Copyright © 2013 John Wiley & Sons, Ltd.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Experimental study of the influence of the counter and scintillator on the universal curves in the cross-efficiency method in LSC.

PubMed

Cassette, P; Tartès, I

2014-05-01

The cross-efficiency method in LSC is one of the approaches proposed for the extension of the Système International de Référence (SIR) to radionuclides emitting no gamma radiation. This method is based on a so-called "universal cross-efficiency curve", establishing a relationship between the detection efficiency of the radionuclide to be measured and the detection efficiency of a suitable tracer. This paper reports a study at LNHB on the influence of the scintillator and of the LS counter on the cross-efficiency curves. This was done by measuring the cross-efficiency curves obtained for (63)Ni and (55)Fe vs. (3)H, using three different commercial LS counters (Guardian 1414, Tricarb 3170 and Quantulus 1220), three different liquid scintillator cocktails (Ultima Gold, Hionic Fluor and PicoFluor 15 from Perkin Elmer(®)), and for chemical and colour-quenched sources. This study shows that these cross-efficiency curves are dependent on the scintillator, on the counter used and on the nature of the quenching phenomenon, and thus cannot definitively be considered as "universal". © 2013 Published by Elsevier Ltd.

Coherent detection in optical fiber systems.

PubMed

Ip, Ezra; Lau, Alan Pak Tao; Barros, Daniel J F; Kahn, Joseph M

2008-01-21

The drive for higher performance in optical fiber systems has renewed interest in coherent detection. We review detection methods, including noncoherent, differentially coherent, and coherent detection, as well as a hybrid method. We compare modulation methods encoding information in various degrees of freedom (DOF). Polarization-multiplexed quadrature-amplitude modulation maximizes spectral efficiency and power efficiency, by utilizing all four available DOF, the two field quadratures in the two polarizations. Dual-polarization homodyne or heterodyne downconversion are linear processes that can fully recover the received signal field in these four DOF. When downconverted signals are sampled at the Nyquist rate, compensation of transmission impairments can be performed using digital signal processing (DSP). Linear impairments, including chromatic dispersion and polarization-mode dispersion, can be compensated quasi-exactly using finite impulse response filters. Some nonlinear impairments, such as intra-channel four-wave mixing and nonlinear phase noise, can be compensated partially. Carrier phase recovery can be performed using feedforward methods, even when phase-locked loops may fail due to delay constraints. DSP-based compensation enables a receiver to adapt to time-varying impairments, and facilitates use of advanced forward-error-correction codes. We discuss both single- and multi-carrier system implementations. For a given modulation format, using coherent detection, they offer fundamentally the same spectral efficiency and power efficiency, but may differ in practice, because of different impairments and implementation details. With anticipated advances in analog-to-digital converters and integrated circuit technology, DSP-based coherent receivers at bit rates up to 100 Gbit/s should become practical within the next few years.

Beam-steering efficiency optimization method based on a rapid-search algorithm for liquid crystal optical phased array.

PubMed

Xiao, Feng; Kong, Lingjiang; Chen, Jian

2017-06-01

A rapid-search algorithm to improve the beam-steering efficiency for a liquid crystal optical phased array was proposed and experimentally demonstrated in this paper. This proposed algorithm, in which the value of steering efficiency is taken as the objective function and the controlling voltage codes are considered as the optimization variables, consisted of a detection stage and a construction stage. It optimized the steering efficiency in the detection stage and adjusted its search direction adaptively in the construction stage to avoid getting caught in a wrong search space. Simulations had been conducted to compare the proposed algorithm with the widely used pattern-search algorithm using criteria of convergence rate and optimized efficiency. Beam-steering optimization experiments had been performed to verify the validity of the proposed method.

[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.

Can the ZoMBieS method be used to characterise scintillator non-linearity?

PubMed

Bignell, L J

2014-05-01

Measurements of the detection efficiency as a function of deposited electron energy in a liquid scintillation cocktail between 4 keV and 49 keV are obtained using the ZoMBieS method. Comparison is made between the measured data and the Poisson-Birks detection efficiency model. Measurements of the Birks non-linearity parameter, kB, and the linearised scintillation response of each photomultiplier, ω(i), were made using these data. However, the value of kB that best linearises the scintillator response is found to vary depending upon which photomultiplier is used in its determination, and the measured kB and ω(i) vary depending on the external source geometry. The cause of this behaviour is unknown. The triple-coincident detection efficiency appears to be unaffected by any systematic errors. © 2013 Published by Elsevier Ltd.

An efficient abnormal cervical cell detection system based on multi-instance extreme learning machine

NASA Astrophysics Data System (ADS)

Zhao, Lili; Yin, Jianping; Yuan, Lihuan; Liu, Qiang; Li, Kuan; Qiu, Minghui

2017-07-01

Automatic detection of abnormal cells from cervical smear images is extremely demanded in annual diagnosis of women's cervical cancer. For this medical cell recognition problem, there are three different feature sections, namely cytology morphology, nuclear chromatin pathology and region intensity. The challenges of this problem come from feature combination s and classification accurately and efficiently. Thus, we propose an efficient abnormal cervical cell detection system based on multi-instance extreme learning machine (MI-ELM) to deal with above two questions in one unified framework. MI-ELM is one of the most promising supervised learning classifiers which can deal with several feature sections and realistic classification problems analytically. Experiment results over Herlev dataset demonstrate that the proposed method outperforms three traditional methods for two-class classification in terms of well accuracy and less time.

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.

Development of an Itemwise Efficiency Scoring Method: Concurrent, Convergent, Discriminant, and Neuroimaging-Based Predictive Validity Assessed in a Large Community Sample

PubMed Central

Moore, Tyler M.; Reise, Steven P.; Roalf, David R.; Satterthwaite, Theodore D.; Davatzikos, Christos; Bilker, Warren B.; Port, Allison M.; Jackson, Chad T.; Ruparel, Kosha; Savitt, Adam P.; Baron, Robert B.; Gur, Raquel E.; Gur, Ruben C.

2016-01-01

Traditional “paper-and-pencil” testing is imprecise in measuring speed and hence limited in assessing performance efficiency, but computerized testing permits precision in measuring itemwise response time. We present a method of scoring performance efficiency (combining information from accuracy and speed) at the item level. Using a community sample of 9,498 youths age 8-21, we calculated item-level efficiency scores on four neurocognitive tests, and compared the concurrent, convergent, discriminant, and predictive validity of these scores to simple averaging of standardized speed and accuracy-summed scores. Concurrent validity was measured by the scores' abilities to distinguish men from women and their correlations with age; convergent and discriminant validity were measured by correlations with other scores inside and outside of their neurocognitive domains; predictive validity was measured by correlations with brain volume in regions associated with the specific neurocognitive abilities. Results provide support for the ability of itemwise efficiency scoring to detect signals as strong as those detected by standard efficiency scoring methods. We find no evidence of superior validity of the itemwise scores over traditional scores, but point out several advantages of the former. The itemwise efficiency scoring method shows promise as an alternative to standard efficiency scoring methods, with overall moderate support from tests of four different types of validity. This method allows the use of existing item analysis methods and provides the convenient ability to adjust the overall emphasis of accuracy versus speed in the efficiency score, thus adjusting the scoring to the real-world demands the test is aiming to fulfill. PMID:26866796

An Optimal Bahadur-Efficient Method in Detection of Sparse Signals with Applications to Pathway Analysis in Sequencing Association Studies.

PubMed

Dai, Hongying; Wu, Guodong; Wu, Michael; Zhi, Degui

2016-01-01

Next-generation sequencing data pose a severe curse of dimensionality, complicating traditional "single marker-single trait" analysis. We propose a two-stage combined p-value method for pathway analysis. The first stage is at the gene level, where we integrate effects within a gene using the Sequence Kernel Association Test (SKAT). The second stage is at the pathway level, where we perform a correlated Lancaster procedure to detect joint effects from multiple genes within a pathway. We show that the Lancaster procedure is optimal in Bahadur efficiency among all combined p-value methods. The Bahadur efficiency,[Formula: see text], compares sample sizes among different statistical tests when signals become sparse in sequencing data, i.e. ε →0. The optimal Bahadur efficiency ensures that the Lancaster procedure asymptotically requires a minimal sample size to detect sparse signals ([Formula: see text]). The Lancaster procedure can also be applied to meta-analysis. Extensive empirical assessments of exome sequencing data show that the proposed method outperforms Gene Set Enrichment Analysis (GSEA). We applied the competitive Lancaster procedure to meta-analysis data generated by the Global Lipids Genetics Consortium to identify pathways significantly associated with high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, and total cholesterol.

Efficiently detecting outlying behavior in video-game players.

PubMed

Kim, Young Bin; Kang, Shin Jin; Lee, Sang Hyeok; Jung, Jang Young; Kam, Hyeong Ryeol; Lee, Jung; Kim, Young Sun; Lee, Joonsoo; Kim, Chang Hun

2015-01-01

In this paper, we propose a method for automatically detecting the times during which game players exhibit specific behavior, such as when players commonly show excitement, concentration, immersion, and surprise. The proposed method detects such outlying behavior based on the game players' characteristics. These characteristics are captured non-invasively in a general game environment. In this paper, cameras were used to analyze observed data such as facial expressions and player movements. Moreover, multimodal data from the game players (i.e., data regarding adjustments to the volume and the use of the keyboard and mouse) was used to analyze high-dimensional game-player data. A support vector machine was used to efficiently detect outlying behaviors. We verified the effectiveness of the proposed method using games from several genres. The recall rate of the outlying behavior pre-identified by industry experts was approximately 70%. The proposed method can also be used for feedback analysis of various interactive content provided in PC environments.

Efficiently detecting outlying behavior in video-game players

PubMed Central

Kim, Young Bin; Kang, Shin Jin; Lee, Sang Hyeok; Jung, Jang Young; Kam, Hyeong Ryeol; Lee, Jung; Kim, Young Sun; Lee, Joonsoo

2015-01-01

In this paper, we propose a method for automatically detecting the times during which game players exhibit specific behavior, such as when players commonly show excitement, concentration, immersion, and surprise. The proposed method detects such outlying behavior based on the game players’ characteristics. These characteristics are captured non-invasively in a general game environment. In this paper, cameras were used to analyze observed data such as facial expressions and player movements. Moreover, multimodal data from the game players (i.e., data regarding adjustments to the volume and the use of the keyboard and mouse) was used to analyze high-dimensional game-player data. A support vector machine was used to efficiently detect outlying behaviors. We verified the effectiveness of the proposed method using games from several genres. The recall rate of the outlying behavior pre-identified by industry experts was approximately 70%. The proposed method can also be used for feedback analysis of various interactive content provided in PC environments. PMID:26713250

Detection of DNA damage by using hairpin molecular beacon probes and graphene oxide.

PubMed

Zhou, Jie; Lu, Qian; Tong, Ying; Wei, Wei; Liu, Songqin

2012-09-15

A hairpin molecular beacon tagged with carboxyfluorescein in combination with graphene oxide as a quencher reagent was used to detect the DNA damage by chemical reagents. The fluorescence of molecular beacon was quenched sharply by graphene oxide; while in the presence of its complementary DNA the quenching efficiency decreased because their hybridization prevented the strong adsorbability of molecular beacon on graphene oxide. If the complementary DNA was damaged by a chemical reagent and could not form intact duplex structure with molecular beacon, more molecular beacon would adsorb on graphene oxide increasing the quenching efficiency. Thus, damaged DNA could be detected based on different quenching efficiencies afforded by damaged and intact complementary DNA. The damage effects of chlorpyrifos-methyl and three metabolites of styrene such as mandelieaeids, phenylglyoxylieaeids and epoxystyrene on DNA were studied as models. The method for detection of DNA damage was reliable, rapid and simple compared to the biological methods. Copyright © 2012 Elsevier B.V. All rights reserved.

Tracing the conformational changes in BSA using FRET with environmentally-sensitive squaraine probes

NASA Astrophysics Data System (ADS)

Govor, Iryna V.; Tatarets, Anatoliy L.; Obukhova, Olena M.; Terpetschnig, Ewald A.; Gellerman, Gary; Patsenker, Leonid D.

2016-06-01

A new potential method of detecting the conformational changes in hydrophobic proteins such as bovine serum albumin (BSA) is introduced. The method is based on the change in the Förster resonance energy transfer (FRET) efficiency between protein-sensitive fluorescent probes. As compared to conventional FRET based methods, in this new approach the donor and acceptor dyes are not covalently linked to protein molecules. Performance of the new method is demonstrated using the protein-sensitive squaraine probes Square-634 (donor) and Square-685 (acceptor) to detect the urea-induced conformational changes of BSA. The FRET efficiency between these probes can be considered a more sensitive parameter to trace protein unfolding as compared to the changes in fluorescence intensity of each of these probes. Addition of urea followed by BSA unfolding causes a noticeable decrease in the emission intensities of these probes (factor of 5.6 for Square-634 and 3.0 for Square-685), and the FRET efficiency changes by a factor of up to 17. Compared to the conventional method the new approach therefore demonstrates to be a more sensitive way to detect the conformational changes in BSA.

Multi-scale occupancy estimation and modelling using multiple detection methods

USGS Publications Warehouse

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

2008-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Neutron Detection in the A2 Collaboration Experiment on Neutral Pion Photo-production on Neutron

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

Bulychjov, S. A.; Kudryavtsev, A. E.; Kulikov, V. V.

Neutron detection is of crucial importance for the neutral pion photo-production study on a neutron target that now is in progress at MAMI. Two electro-magnetic calorimeters, based on NaI and BaF 2 crystals, are used in the A2 experiment. While these calorimeters are optimized for pion decay photon detection, they have a reason able efficiency for neutron detection also. The paper describes the method, which has been used to measure this efficiency using the same data taken for pion photo-production study on deuterium target with tagged photon been of 800 MeV maximal energy. As a result, the detection efficiency ismore » a rising function of neutron momentum that reaches 40% near 1 GeV/c.« less

Neutron Detection in the A2 Collaboration Experiment on Neutral Pion Photo-production on Neutron

DOE PAGES

Bulychjov, S. A.; Kudryavtsev, A. E.; Kulikov, V. V.; ...

2018-04-09

Neutron detection is of crucial importance for the neutral pion photo-production study on a neutron target that now is in progress at MAMI. Two electro-magnetic calorimeters, based on NaI and BaF 2 crystals, are used in the A2 experiment. While these calorimeters are optimized for pion decay photon detection, they have a reason able efficiency for neutron detection also. The paper describes the method, which has been used to measure this efficiency using the same data taken for pion photo-production study on deuterium target with tagged photon been of 800 MeV maximal energy. As a result, the detection efficiency ismore » a rising function of neutron momentum that reaches 40% near 1 GeV/c.« less

The Development of DNA Based Methods for the Reliable and Efficient Identification of Nicotiana tabacum in Tobacco and Its Derived Products

PubMed Central

Fan, Wei; Li, Rong; Li, Sifan; Ping, Wenli; Li, Shujun; Naumova, Alexandra; Peelen, Tamara; Yuan, Zheng; Zhang, Dabing

2016-01-01

Reliable methods are needed to detect the presence of tobacco components in tobacco products to effectively control smuggling and classify tariff and excise in tobacco industry to control illegal tobacco trade. In this study, two sensitive and specific DNA based methods, one quantitative real-time PCR (qPCR) assay and the other loop-mediated isothermal amplification (LAMP) assay, were developed for the reliable and efficient detection of the presence of tobacco (Nicotiana tabacum) in various tobacco samples and commodities. Both assays targeted the same sequence of the uridine 5′-monophosphate synthase (UMPS), and their specificities and sensitivities were determined with various plant materials. Both qPCR and LAMP methods were reliable and accurate in the rapid detection of tobacco components in various practical samples, including customs samples, reconstituted tobacco samples, and locally purchased cigarettes, showing high potential for their application in tobacco identification, particularly in the special cases where the morphology or chemical compositions of tobacco have been disrupted. Therefore, combining both methods would facilitate not only the detection of tobacco smuggling control, but also the detection of tariff classification and of excise. PMID:27635142

An Energy-Efficient Multi-Tier Architecture for Fall Detection Using Smartphones.

PubMed

Guvensan, M Amac; Kansiz, A Oguz; Camgoz, N Cihan; Turkmen, H Irem; Yavuz, A Gokhan; Karsligil, M Elif

2017-06-23

Automatic detection of fall events is vital to providing fast medical assistance to the causality, particularly when the injury causes loss of consciousness. Optimization of the energy consumption of mobile applications, especially those which run 24/7 in the background, is essential for longer use of smartphones. In order to improve energy-efficiency without compromising on the fall detection performance, we propose a novel 3-tier architecture that combines simple thresholding methods with machine learning algorithms. The proposed method is implemented on a mobile application, called uSurvive, for Android smartphones. It runs as a background service and monitors the activities of a person in daily life and automatically sends a notification to the appropriate authorities and/or user defined contacts when it detects a fall. The performance of the proposed method was evaluated in terms of fall detection performance and energy consumption. Real life performance tests conducted on two different models of smartphone demonstrate that our 3-tier architecture with feature reduction could save up to 62% of energy compared to machine learning only solutions. In addition to this energy saving, the hybrid method has a 93% of accuracy, which is superior to thresholding methods and better than machine learning only solutions.

Method of wavefront tilt correction for optical heterodyne detection systems under strong turbulence

NASA Astrophysics Data System (ADS)

Xiang, Jing-song; Tian, Xin; Pan, Le-chun

2014-07-01

Atmospheric turbulence decreases the heterodyne mixing efficiency of the optical heterodyne detection systems. Wavefront tilt correction is often used to improve the optical heterodyne mixing efficiency. But the performance of traditional centroid tracking tilt correction is poor under strong turbulence conditions. In this paper, a tilt correction method which tracking the peak value of laser spot on focal plane is proposed. Simulation results show that, under strong turbulence conditions, the performance of peak value tracking tilt correction is distinctly better than that of traditional centroid tracking tilt correction method, and the phenomenon of large antenna's performance inferior to small antenna's performance which may be occurred in centroid tracking tilt correction method can also be avoid in peak value tracking tilt correction method.

Real-time PCR method combined with immunomagnetic separation for detecting healthy and heat-injured Salmonella Typhimurium on raw duck wings.

PubMed

Zheng, Qianwang; Mikš-Krajnik, Marta; Yang, Yishan; Xu, Wang; Yuk, Hyun-Gyun

2014-09-01

Conventional culture detection methods are time consuming and labor-intensive. For this reason, an alternative rapid method combining real-time PCR and immunomagnetic separation (IMS) was investigated in this study to detect both healthy and heat-injured Salmonella Typhimurium on raw duck wings. Firstly, the IMS method was optimized by determining the capture efficiency of Dynabeads(®) on Salmonella cells on raw duck wings with different bead incubation (10, 30 and 60 min) and magnetic separation (3, 10 and 30 min) times. Secondly, three Taqman primer sets, Sal, invA and ttr, were evaluated to optimize the real-time PCR protocol by comparing five parameters: inclusivity, exclusivity, PCR efficiency, detection probability and limit of detection (LOD). Thirdly, the optimized real-time PCR, in combination with IMS (PCR-IMS) assay, was compared with a standard ISO and a real-time PCR (PCR) method by analyzing artificially inoculated raw duck wings with healthy and heat-injured Salmonella cells at 10(1) and 10(0) CFU/25 g. Finally, the optimized PCR-IMS assay was validated for Salmonella detection in naturally contaminated raw duck wing samples. Under optimal IMS conditions (30 min bead incubation and 3 min magnetic separation times), approximately 85 and 64% of S. Typhimurium cells were captured by Dynabeads® from pure culture and inoculated raw duck wings, respectively. Although Sal and ttr primers exhibited 100% inclusivity and exclusivity for 16 Salmonella spp. and 36 non-Salmonella strains, the Sal primer showed lower LOD (10(3) CFU/ml) and higher PCR efficiency (94.1%) than the invA and ttr primers. Moreover, for Sal and invA primers, 100% detection probability on raw duck wings suspension was observed at 10(3) and 10(4) CFU/ml with and without IMS, respectively. Thus, the Sal primer was chosen for further experiments. The optimized PCR-IMS method was significantly (P=0.0011) better at detecting healthy Salmonella cells after 7-h enrichment than traditional PCR method. However there was no significant difference between the two methods with longer enrichment time (14 h). The diagnostic accuracy of PCR-IMS was shown to be 98.3% through the validation study. These results indicate that the optimized PCR-IMS method in this study could provide a sensitive, specific and rapid detection method for Salmonella on raw duck wings, enabling 10-h detection. However, a longer enrichment time could be needed for resuscitation and reliable detection of heat-injured cells. Copyright © 2014 Elsevier B.V. All rights reserved.

Automatic Detection of Storm Damages Using High-Altitude Photogrammetric Imaging

NASA Astrophysics Data System (ADS)

Litkey, P.; Nurminen, K.; Honkavaara, E.

2013-05-01

The risks of storms that cause damage in forests are increasing due to climate change. Quickly detecting fallen trees, assessing the amount of fallen trees and efficiently collecting them are of great importance for economic and environmental reasons. Visually detecting and delineating storm damage is a laborious and error-prone process; thus, it is important to develop cost-efficient and highly automated methods. Objective of our research project is to investigate and develop a reliable and efficient method for automatic storm damage detection, which is based on airborne imagery that is collected after a storm. The requirements for the method are the before-storm and after-storm surface models. A difference surface is calculated using two DSMs and the locations where significant changes have appeared are automatically detected. In our previous research we used four-year old airborne laser scanning surface model as the before-storm surface. The after-storm DSM was provided from the photogrammetric images using the Next Generation Automatic Terrain Extraction (NGATE) algorithm of Socet Set software. We obtained 100% accuracy in detection of major storm damages. In this investigation we will further evaluate the sensitivity of the storm-damage detection process. We will investigate the potential of national airborne photography, that is collected at no-leaf season, to automatically produce a before-storm DSM using image matching. We will also compare impact of the terrain extraction algorithm to the results. Our results will also promote the potential of national open source data sets in the management of natural disasters.

A sensitive and efficient method for trace analysis of some phenolic compounds using simultaneous derivatization and air-assisted liquid-liquid microextraction from human urine and plasma samples followed by gas chromatography-nitrogen phosphorous detection.

PubMed

Farajzadeh, Mir Ali; Afshar Mogaddam, Mohammad Reza; Alizadeh Nabil, Ali Akbar

2015-12-01

In present study, a simultaneous derivatization and air-assisted liquid-liquid microextraction method combined with gas chromatography-nitrogen phosphorous detection has been developed for the determination of some phenolic compounds in biological samples. The analytes are derivatized and extracted simultaneously by a fast reaction with 1-flouro-2,4-dinitrobenzene under mild conditions. Under optimal conditions low limits of detection in the range of 0.05-0.34 ng mL(-1) are achievable. The obtained extraction recoveries are between 84 and 97% and the relative standard deviations are less than 7.2% for intraday (n = 6) and interday (n = 4) precisions. The proposed method was demonstrated to be a simple and efficient method for the analysis of phenols in biological samples. Copyright © 2015 John Wiley & Sons, Ltd.

A matched filter approach for blind joint detection of galaxy clusters in X-ray and SZ surveys

NASA Astrophysics Data System (ADS)

Tarrío, P.; Melin, J.-B.; Arnaud, M.

2018-06-01

The combination of X-ray and Sunyaev-Zeldovich (SZ) observations can potentially improve the cluster detection efficiency, when compared to using only one of these probes, since both probe the same medium, the hot ionized gas of the intra-cluster medium. We present a method based on matched multifrequency filters (MMF) for detecting galaxy clusters from SZ and X-ray surveys. This method builds on a previously proposed joint X-ray-SZ extraction method and allows the blind detection of clusters, that is finding new clusters without knowing their position, size, or redshift, by searching on SZ and X-ray maps simultaneously. The proposed method is tested using data from the ROSAT all-sky survey and from the Planck survey. The evaluation is done by comparison with existing cluster catalogues in the area of the sky covered by the deep SPT survey. Thanks to the addition of the X-ray information, the joint detection method is able to achieve simultaneously better purity, better detection efficiency, and better position accuracy than its predecessor Planck MMF, which is based on SZ maps alone. For a purity of 85%, the X-ray-SZ method detects 141 confirmed clusters in the SPT region; to detect the same number of confirmed clusters with Planck MMF, we would need to decrease its purity to 70%. We provide a catalogue of 225 sources selected by the proposed method in the SPT footprint, with masses ranging between 0.7 and 14.5 ×1014 M⊙ and redshifts between 0.01 and 1.2.

Quantification of Humic Substances in Natural Water Using Nitrogen-Doped Carbon Dots.

PubMed

Guan, Yan-Fang; Huang, Bao-Cheng; Qian, Chen; Yu, Han-Qing

2017-12-19

Dissolved organic matter (DOM) is ubiquitous in aqueous environments and plays a significant role in pollutant mitigation, transformation and organic geochemical circulation. DOM is also capable of forming carcinogenic byproducts in the disinfection treatment processes of drinking water. Thus, efficient methods for DOM quantification are highly desired. In this work, a novel sensor for rapid and selective detection of humic substances (HS), a key component of DOM, based on fluorescence quenching of nitrogen-doped carbon quantum dots was developed. The experimental results show that the HS detection range could be broadened to 100 mg/L with a detection limit of 0.2 mg/L. Moreover, the detection was effective within a wide pH range of 3.0 to 12.0, and the interferences of ions on the HS measurement were negligible. A good detection result for real surface water samples further validated the feasibility of the developed detection method. Furthermore, a nonradiation electron transfer mechanism for quenching the nitrogen-doped carbon-dots fluorescence by HS was elucidated. In addition, we prepared a test paper and proved its effectiveness. This work provides a new efficient method for the HS quantification than the frequently used modified Lowry method in terms of sensitivity and detection range.

Extraction of polycyclic aromatic hydrocarbons and organochlorine pesticides from soils: a comparison between Soxhlet extraction, microwave-assisted extraction and accelerated solvent extraction techniques.

PubMed

Wang, Wentao; Meng, Bingjun; Lu, Xiaoxia; Liu, Yu; Tao, Shu

2007-10-29

The methods of simultaneous extraction of polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides (OCPs) from soils using Soxhlet extraction, microwave-assisted extraction (MAE) and accelerated solvent extraction (ASE) were established, and the extraction efficiencies using the three methods were systemically compared from procedural blank, limits of detection and quantification, method recovery and reproducibility, method chromatogram and other factors. In addition, soils with different total organic carbon contents were used to test the extraction efficiencies of the three methods. The results showed that the values obtained in this study were comparable with the values reported by other studies. In some respects such as method recovery and reproducibility, there were no significant differences among the three methods for the extraction of PAHs and OCPs. In some respects such as procedural blank and limits of detection and quantification, there were significant differences among the three methods. Overall, ASE had the best extraction efficiency compared to MAE and Soxhlet extraction, and the extraction efficiencies of MAE and Soxhlet extraction were comparable to each other depending on the property such as TOC content of the studied soil. Considering other factors such as solvent consumption and extraction time, ASE and MAE are preferable to Soxhlet extraction.

The estimation method on diffusion spot energy concentration of the detection system

NASA Astrophysics Data System (ADS)

Gao, Wei; Song, Zongxi; Liu, Feng; Dan, Lijun; Sun, Zhonghan; Du, Yunfei

2016-09-01

We propose a method to estimate the diffusion spot energy of the detection system. We do outdoor observation experiments in Xinglong Observatory, by using a detection system which diffusion spot energy concentration is estimated (the correlation coefficient is approximate 0.9926).The aperture of system is 300mm and limiting magnitude of system is 14.15Mv. Observation experiments show that the highest detecting magnitude of estimated system is 13.96Mv, and the average detecting magnitude of estimated system is about 13.5Mv. The results indicate that this method can be used to evaluate the energy diffusion spot concentration level of detection system efficiently.

The efficiency of concentration methods used to detect enteric viruses in anaerobically digested sludge

PubMed Central

Prado, Tatiana; Guilayn, Wilma de Carvalho Pereira Bonet; Gaspar, Ana Maria Coimbra; Miagostovich, Marize Pereira

2013-01-01

The presence of enteric viruses in biosolids can be underestimated due to the inefficient methods (mainly molecular methods) used to recover the viruses from these matrices. Therefore, the goal of this study was to evaluate the different methods used to recover adenoviruses (AdV), rotavirus species A (RVA), norovirus genogroup II (NoV GII) and the hepatitis A virus (HAV) from biosolid samples at a large urban wastewater treatment plant in Brazil after they had been treated by mesophilic anaerobic digestion. Quantitative polymerase chain reaction (PCR) was used for spiking experiments to compare the detection limits of feasible methods, such as beef extract elution and ultracentrifugation. Tests were performed to detect the inhibition levels and the bacteriophage PP7 was used as an internal control. The results showed that the inhibitors affected the efficiency of the PCR reaction and that beef extract elution is a suitable method for detecting enteric viruses, mainly AdV from biosolid samples. All of the viral groups were detected in the biosolid samples: AdV (90%), RVA, NoV GII (45%) and HAV (18%), indicating the viruses' resistance to the anaerobic treatment process. This is the first study in Brazil to detect the presence of RVA, AdV, NoV GII and HAV in anaerobically digested sludge, highlighting the importance of adequate waste management. PMID:23440119

A Simple and Computationally Efficient Sampling Approach to Covariate Adjustment for Multifactor Dimensionality Reduction Analysis of Epistasis

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

Epistasis or gene-gene interaction is a fundamental component of the genetic architecture of complex traits such as disease susceptibility. Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model-free method to detect epistasis when there are no significant marginal genetic effects. However, in many studies of complex disease, other covariates like age of onset and smoking status could have a strong main effect and may potentially interfere with MDR's ability to achieve its goal. In this paper, we present a simple and computationally efficient sampling method to adjust for covariate effects in MDR. We use simulation to show that after adjustment, MDR has sufficient power to detect true gene-gene interactions. We also compare our method with the state-of-art technique in covariate adjustment. The results suggest that our proposed method performs similarly, but is more computationally efficient. We then apply this new method to an analysis of a population-based bladder cancer study in New Hampshire. PMID:20924193

2D signature for detection and identification of drugs

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Shen, Jingling; Zhang, Cunlin; Zhou, Qingli; Shi, Yulei

2011-06-01

The method of spectral dynamics analysis (SDA-method) is used for obtaining the2D THz signature of drugs. This signature is used for the detection and identification of drugs with similar Fourier spectra by transmitted THz signal. We discuss the efficiency of SDA method for the identification problem of pure methamphetamine (MA), methylenedioxyamphetamine (MDA), 3, 4-methylenedioxymethamphetamine (MDMA) and Ketamine.

A Novel In Vitro Method for Detecting Undifferentiated Human Pluripotent Stem Cells as Impurities in Cell Therapy Products Using a Highly Efficient Culture System

PubMed Central

Tano, Keiko; Yasuda, Satoshi; Kuroda, Takuya; Saito, Hirohisa; Umezawa, Akihiro; Sato, Yoji

2014-01-01

Innovative applications of cell therapy products (CTPs) derived from human pluripotent stem cells (hPSCs) in regenerative medicine are currently being developed. The presence of residual undifferentiated hPSCs in CTPs is a quality concern associated with tumorigencity. However, no simple in vitro method for direct detection of undifferentiated hPSCs that contaminate CTPs has been developed. Here, we show a novel approach for direct and sensitive detection of a trace amount of undifferentiated human induced pluripotent stem cells (hiPSCs) using a highly efficient amplification method in combination with laminin-521 and Essential 8 medium. Essential 8 medium better facilitated the growth of hiPSCs dissociated into single cells on laminin-521 than in mTeSR1 medium. hiPSCs cultured on laminin-521 in Essential 8 medium were maintained in an undifferentiated state and they maintained the ability to differentiate into various cell types. Essential 8 medium allowed robust hiPSC proliferation plated on laminin-521 at low cell density, whereas mTeSR1 did not enhance the cell growth. The highly efficient culture system using laminin-521 and Essential 8 medium detected hiPSCs spiked into primary human mesenchymal stem cells (hMSCs) or human neurons at the ratio of 0.001%–0.01% as formed colonies. Moreover, this assay method was demonstrated to detect residual undifferentiated hiPSCs in cell preparations during the process of hMSC differentiation from hiPSCs. These results indicate that our highly efficient amplification system using a combination of laminin-521 and Essential 8 medium is able to detect a trace amount of undifferentiated hPSCs contained as impurities in CTPs and would contribute to quality assessment of hPSC-derived CTPs during the manufacturing process. PMID:25347300

Multi-stage approach for structural damage detection problem using basis pursuit and particle swarm optimization

NASA Astrophysics Data System (ADS)

Gerist, Saleheh; Maheri, Mahmoud R.

2016-12-01

In order to solve structural damage detection problem, a multi-stage method using particle swarm optimization is presented. First, a new spars recovery method, named Basis Pursuit (BP), is utilized to preliminarily identify structural damage locations. The BP method solves a system of equations which relates the damage parameters to the structural modal responses using the sensitivity matrix. Then, the results of this stage are subsequently enhanced to the exact damage locations and extents using the PSO search engine. Finally, the search space is reduced by elimination of some low damage variables using micro search (MS) operator embedded in the PSO algorithm. To overcome the noise present in structural responses, a method known as Basis Pursuit De-Noising (BPDN) is also used. The efficiency of the proposed method is investigated by three numerical examples: a cantilever beam, a plane truss and a portal plane frame. The frequency response is used to detect damage in the examples. The simulation results demonstrate the accuracy and efficiency of the proposed method in detecting multiple damage cases and exhibit its robustness regarding noise and its advantages compared to other reported solution algorithms.

Differences in Movement Pattern and Detectability between Males and Females Influence How Common Sampling Methods Estimate Sex Ratio.

PubMed

Rodrigues, João Fabrício Mota; Coelho, Marco Túlio Pacheco

2016-01-01

Sampling the biodiversity is an essential step for conservation, and understanding the efficiency of sampling methods allows us to estimate the quality of our biodiversity data. Sex ratio is an important population characteristic, but until now, no study has evaluated how efficient are the sampling methods commonly used in biodiversity surveys in estimating the sex ratio of populations. We used a virtual ecologist approach to investigate whether active and passive capture methods are able to accurately sample a population's sex ratio and whether differences in movement pattern and detectability between males and females produce biased estimates of sex-ratios when using these methods. Our simulation allowed the recognition of individuals, similar to mark-recapture studies. We found that differences in both movement patterns and detectability between males and females produce biased estimates of sex ratios. However, increasing the sampling effort or the number of sampling days improves the ability of passive or active capture methods to properly sample sex ratio. Thus, prior knowledge regarding movement patterns and detectability for species is important information to guide field studies aiming to understand sex ratio related patterns.

Differences in Movement Pattern and Detectability between Males and Females Influence How Common Sampling Methods Estimate Sex Ratio

PubMed Central

Rodrigues, João Fabrício Mota; Coelho, Marco Túlio Pacheco

2016-01-01

Sampling the biodiversity is an essential step for conservation, and understanding the efficiency of sampling methods allows us to estimate the quality of our biodiversity data. Sex ratio is an important population characteristic, but until now, no study has evaluated how efficient are the sampling methods commonly used in biodiversity surveys in estimating the sex ratio of populations. We used a virtual ecologist approach to investigate whether active and passive capture methods are able to accurately sample a population’s sex ratio and whether differences in movement pattern and detectability between males and females produce biased estimates of sex-ratios when using these methods. Our simulation allowed the recognition of individuals, similar to mark-recapture studies. We found that differences in both movement patterns and detectability between males and females produce biased estimates of sex ratios. However, increasing the sampling effort or the number of sampling days improves the ability of passive or active capture methods to properly sample sex ratio. Thus, prior knowledge regarding movement patterns and detectability for species is important information to guide field studies aiming to understand sex ratio related patterns. PMID:27441554

Evaluation of Two Surface Sampling Methods for Detection of Erwinia herbicola on a Variety of Materials by Culture and Quantitative PCR▿

PubMed Central

Buttner, Mark P.; Cruz, Patricia; Stetzenbach, Linda D.; Cronin, Tracy

2007-01-01

This research was designed to evaluate surface sampling protocols for use with culture and quantitative PCR (QPCR) amplification assay for detection of the gram-negative bacterial biothreat simulant Erwinia herbicola on a variety of surface materials. Surfaces selected for evaluation were wood laminate, glass and computer monitor screens, metal file cabinets, plastic arena seats, nylon seat cushions, finished concrete flooring, and vinyl tile flooring. Laboratory and test chamber studies were performed to evaluate two sampling methods, a sponge and a macrofoam swab, for detection of E. herbicola on surface materials. In laboratory trials, seven materials were inoculated with a known concentration of E. herbicola cells and samples were collected from the surfaces of the materials to determine sampling efficiencies. Culture analysis was ineffective for assessing E. herbicola collection efficiency because very few culturable cells were obtained from surface samples. QPCR demonstrated that E. herbicola DNA was present in high concentrations on all of the surface samples, and sampling efficiencies ranged from 0.7 to 52.2%, depending on the sampling method and the surface material. The swab was generally more efficient than the sponge for collection of E. herbicola from surfaces. Test chamber trials were also performed in which E. herbicola was aerosolized into the chamber and allowed to settle onto test materials. Surface sampling results supported those obtained in laboratory trials. The results of this study demonstrate the capabilities of QPCR to enhance the detection and enumeration of biocontaminants on surface materials and provide information on the comparability of sampling methods. PMID:17416685

Evaluation of two surface sampling methods for detection of Erwinia herbicola on a variety of materials by culture and quantitative PCR.

PubMed

Buttner, Mark P; Cruz, Patricia; Stetzenbach, Linda D; Cronin, Tracy

2007-06-01

This research was designed to evaluate surface sampling protocols for use with culture and quantitative PCR (QPCR) amplification assay for detection of the gram-negative bacterial biothreat simulant Erwinia herbicola on a variety of surface materials. Surfaces selected for evaluation were wood laminate, glass and computer monitor screens, metal file cabinets, plastic arena seats, nylon seat cushions, finished concrete flooring, and vinyl tile flooring. Laboratory and test chamber studies were performed to evaluate two sampling methods, a sponge and a macrofoam swab, for detection of E. herbicola on surface materials. In laboratory trials, seven materials were inoculated with a known concentration of E. herbicola cells and samples were collected from the surfaces of the materials to determine sampling efficiencies. Culture analysis was ineffective for assessing E. herbicola collection efficiency because very few culturable cells were obtained from surface samples. QPCR demonstrated that E. herbicola DNA was present in high concentrations on all of the surface samples, and sampling efficiencies ranged from 0.7 to 52.2%, depending on the sampling method and the surface material. The swab was generally more efficient than the sponge for collection of E. herbicola from surfaces. Test chamber trials were also performed in which E. herbicola was aerosolized into the chamber and allowed to settle onto test materials. Surface sampling results supported those obtained in laboratory trials. The results of this study demonstrate the capabilities of QPCR to enhance the detection and enumeration of biocontaminants on surface materials and provide information on the comparability of sampling methods.

Imaging resolution and properties analysis of super resolution microscopy with parallel detection under different noise, detector and image restoration conditions

NASA Astrophysics Data System (ADS)

Yu, Zhongzhi; Liu, Shaocong; Sun, Shiyi; Kuang, Cuifang; Liu, Xu

2018-06-01

Parallel detection, which can use the additional information of a pinhole plane image taken at every excitation scan position, could be an efficient method to enhance the resolution of a confocal laser scanning microscope. In this paper, we discuss images obtained under different conditions and using different image restoration methods with parallel detection to quantitatively compare the imaging quality. The conditions include different noise levels and different detector array settings. The image restoration methods include linear deconvolution and pixel reassignment with Richard-Lucy deconvolution and with maximum-likelihood estimation deconvolution. The results show that the linear deconvolution share properties such as high-efficiency and the best performance under all different conditions, and is therefore expected to be of use for future biomedical routine research.

Dangerous gas detection based on infrared video

NASA Astrophysics Data System (ADS)

Ding, Kang; Hong, Hanyu; Huang, Likun

2018-03-01

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

Multicolor fluorescent biosensor for multiplexed detection of DNA.

PubMed

Hu, Rong; Liu, Tao; Zhang, Xiao-Bing; Huan, Shuang-Yan; Wu, Cuichen; Fu, Ting; Tan, Weihong

2014-05-20

Development of efficient methods for highly sensitive and rapid screening of specific oligonucleotide sequences is essential to the early diagnosis of serious diseases. In this work, an aggregated cationic perylene diimide (PDI) derivative was found to efficiently quench the fluorescence emission of a variety of anionic oligonucleotide-labeled fluorophores that emit at wavelengths from the visible to NIR region. This broad-spectrum quencher was then adopted to develop a multicolor biosensor via a label-free approach for multiplexed fluorescent detection of DNA. The aggregated perylene derivative exhibits a very high quenching efficiency on all ssDNA-labeled dyes associated with biosensor detection, having efficiency values of 98.3 ± 0.9%, 97 ± 1.1%, and 98.2 ± 0.6% for FAM, TAMRA, and Cy5, respectively. An exonuclease-assisted autocatalytic target recycling amplification was also integrated into the sensing system. High quenching efficiency combined with autocatalytic target recycling amplification afforded the biosensor with high sensitivity toward target DNA, resulting in a detection limit of 20 pM, which is about 50-fold lower than that of traditional unamplified homogeneous fluorescent assay methods. The quencher did not interfere with the catalytic activity of nuclease, and the biosensor could be manipulated in either preaddition or postaddition manner with similar sensitivity. Moreover, the proposed sensing system allows for simultaneous and multicolor analysis of several oligonucleotides in homogeneous solution, demonstrating its potential application in the rapid screening of multiple biotargets.

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.

Detecting glaucomatous change in visual fields: Analysis with an optimization framework.

PubMed

Yousefi, Siamak; Goldbaum, Michael H; Varnousfaderani, Ehsan S; Belghith, Akram; Jung, Tzyy-Ping; Medeiros, Felipe A; Zangwill, Linda M; Weinreb, Robert N; Liebmann, Jeffrey M; Girkin, Christopher A; Bowd, Christopher

2015-12-01

Detecting glaucomatous progression is an important aspect of glaucoma management. The assessment of longitudinal series of visual fields, measured using Standard Automated Perimetry (SAP), is considered the reference standard for this effort. We seek efficient techniques for determining progression from longitudinal visual fields by formulating the problem as an optimization framework, learned from a population of glaucoma data. The longitudinal data from each patient's eye were used in a convex optimization framework to find a vector that is representative of the progression direction of the sample population, as a whole. Post-hoc analysis of longitudinal visual fields across the derived vector led to optimal progression (change) detection. The proposed method was compared to recently described progression detection methods and to linear regression of instrument-defined global indices, and showed slightly higher sensitivities at the highest specificities than other methods (a clinically desirable result). The proposed approach is simpler, faster, and more efficient for detecting glaucomatous changes, compared to our previously proposed machine learning-based methods, although it provides somewhat less information. This approach has potential application in glaucoma clinics for patient monitoring and in research centers for classification of study participants. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed

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

2013-08-01

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

An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data

PubMed Central

Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

2015-01-01

This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems. PMID:26752800

Aerosol detection efficiency in inductively coupled plasma mass spectrometry

NASA Astrophysics Data System (ADS)

Hubbard, Joshua A.; Zigmond, Joseph A.

2016-05-01

An electrostatic size classification technique was used to segregate particles of known composition prior to being injected into an inductively coupled plasma mass spectrometer (ICP-MS). Size-segregated particles were counted with a condensation nuclei counter as well as sampled with an ICP-MS. By injecting particles of known size, composition, and aerosol concentration into the ICP-MS, efficiencies of the order of magnitude aerosol detection were calculated, and the particle size dependencies for volatile and refractory species were quantified. Similar to laser ablation ICP-MS, aerosol detection efficiency was defined as the rate at which atoms were detected in the ICP-MS normalized by the rate at which atoms were injected in the form of particles. This method adds valuable insight into the development of technologies like laser ablation ICP-MS where aerosol particles (of relatively unknown size and gas concentration) are generated during ablation and then transported into the plasma of an ICP-MS. In this study, we characterized aerosol detection efficiencies of volatile species gold and silver along with refractory species aluminum oxide, cerium oxide, and yttrium oxide. Aerosols were generated with electrical mobility diameters ranging from 100 to 1000 nm. In general, it was observed that refractory species had lower aerosol detection efficiencies than volatile species, and there were strong dependencies on particle size and plasma torch residence time. Volatile species showed a distinct transition point at which aerosol detection efficiency began decreasing with increasing particle size. This critical diameter indicated the largest particle size for which complete particle detection should be expected and agreed with theories published in other works. Aerosol detection efficiencies also displayed power law dependencies on particle size. Aerosol detection efficiencies ranged from 10- 5 to 10- 11. Free molecular heat and mass transfer theory was applied, but evaporative phenomena were not sufficient to explain the dependence of aerosol detection on particle diameter. Additional work is needed to correlate experimental data with theory for metal-oxides where thermodynamic property data are sparse relative to pure elements. Lastly, when matrix effects and the diffusion of ions inside the plasma were considered, mass loading was concluded to have had an effect on the dependence of detection efficiency on particle diameter.

Effect of parameters in moving average method for event detection enhancement using phase sensitive OTDR

NASA Astrophysics Data System (ADS)

Kwon, Yong-Seok; Naeem, Khurram; Jeon, Min Yong; Kwon, Il-bum

2017-04-01

We analyze the relations of parameters in moving average method to enhance the event detectability of phase sensitive optical time domain reflectometer (OTDR). If the external events have unique frequency of vibration, then the control parameters of moving average method should be optimized in order to detect these events efficiently. A phase sensitive OTDR was implemented by a pulsed light source, which is composed of a laser diode, a semiconductor optical amplifier, an erbium-doped fiber amplifier, a fiber Bragg grating filter, and a light receiving part, which has a photo-detector and high speed data acquisition system. The moving average method is operated with the control parameters: total number of raw traces, M, number of averaged traces, N, and step size of moving, n. The raw traces are obtained by the phase sensitive OTDR with sound signals generated by a speaker. Using these trace data, the relation of the control parameters is analyzed. In the result, if the event signal has one frequency, then the optimal values of N, n are existed to detect the event efficiently.

A Distributed Signature Detection Method for Detecting Intrusions in Sensor Systems

PubMed Central

Kim, Ilkyu; Oh, Doohwan; Yoon, Myung Kuk; Yi, Kyueun; Ro, Won Woo

2013-01-01

Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on the Wu–Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors. PMID:23529146

A distributed signature detection method for detecting intrusions in sensor systems.

PubMed

Kim, Ilkyu; Oh, Doohwan; Yoon, Myung Kuk; Yi, Kyueun; Ro, Won Woo

2013-03-25

Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on the Wu-Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors.

Detection of protruding lesion in wireless capsule endoscopy videos of small intestine

NASA Astrophysics Data System (ADS)

Wang, Chengliang; Luo, Zhuo; Liu, Xiaoqi; Bai, Jianying; Liao, Guobin

2018-02-01

Wireless capsule endoscopy (WCE) is a developed revolutionary technology with important clinical benefits. But the huge image data brings a heavy burden to the doctors for locating and diagnosing the lesion images. In this paper, a novel and efficient approach is proposed to help clinicians to detect protruding lesion images in small intestine. First, since there are many possible disturbances such as air bubbles and so on in WCE video frames, which add the difficulty of efficient feature extraction, the color-saliency region detection (CSD) method is developed for extracting the potentially saliency region of interest (SROI). Second, a novel color channels modelling of local binary pattern operator (CCLBP) is proposed to describe WCE images, which combines grayscale and color angle. The CCLBP feature is more robust to variation of illumination and more discriminative for classification. Moreover, support vector machine (SVM) classifier with CCLBP feature is utilized to detect protruding lesion images. Experimental results on real WCE images demonstrate that proposed method has higher accuracy on protruding lesion detection than some art-of-state methods.

High efficiency processing for reduced amplitude zones detection in the HRECG signal

NASA Astrophysics Data System (ADS)

Dugarte, N.; Álvarez, A.; Balacco, J.; Mercado, G.; Gonzalez, A.; Dugarte, E.; Olivares, A.

2016-04-01

Summary - This article presents part of a more detailed research proposed in the medium to long term, with the intention of establishing a new philosophy of electrocardiogram surface analysis. This research aims to find indicators of cardiovascular disease in its early stage that may go unnoticed with conventional electrocardiography. This paper reports the development of a software processing which collect some existing techniques and incorporates novel methods for detection of reduced amplitude zones (RAZ) in high resolution electrocardiographic signal (HRECG).The algorithm consists of three stages, an efficient processing for QRS detection, averaging filter using correlation techniques and a step for RAZ detecting. Preliminary results show the efficiency of system and point to incorporation of techniques new using signal analysis with involving 12 leads.

An Energy-Efficient Multi-Tier Architecture for Fall Detection on Smartphones

PubMed Central

Guvensan, M. Amac; Kansiz, A. Oguz; Camgoz, N. Cihan; Turkmen, H. Irem; Yavuz, A. Gokhan; Karsligil, M. Elif

2017-01-01

Automatic detection of fall events is vital to providing fast medical assistance to the causality, particularly when the injury causes loss of consciousness. Optimization of the energy consumption of mobile applications, especially those which run 24/7 in the background, is essential for longer use of smartphones. In order to improve energy-efficiency without compromising on the fall detection performance, we propose a novel 3-tier architecture that combines simple thresholding methods with machine learning algorithms. The proposed method is implemented on a mobile application, called uSurvive, for Android smartphones. It runs as a background service and monitors the activities of a person in daily life and automatically sends a notification to the appropriate authorities and/or user defined contacts when it detects a fall. The performance of the proposed method was evaluated in terms of fall detection performance and energy consumption. Real life performance tests conducted on two different models of smartphone demonstrate that our 3-tier architecture with feature reduction could save up to 62% of energy compared to machine learning only solutions. In addition to this energy saving, the hybrid method has a 93% of accuracy, which is superior to thresholding methods and better than machine learning only solutions. PMID:28644378

Screening DNA chip and event-specific multiplex PCR detection methods for biotech crops.

PubMed

Lee, Seong-Hun

2014-11-01

There are about 80 biotech crop events that have been approved by safety assessment in Korea. They have been controlled by genetically modified organism (GMO) and living modified organism (LMO) labeling systems. The DNA-based detection method has been used as an efficient scientific management tool. Recently, the multiplex polymerase chain reaction (PCR) and DNA chip have been developed as simultaneous detection methods for several biotech crops' events. The event-specific multiplex PCR method was developed to detect five biotech maize events: MIR604, Event 3272, LY 038, MON 88017 and DAS-59122-7. The specificity was confirmed and the sensitivity was 0.5%. The screening DNA chip was developed from four endogenous genes of soybean, maize, cotton and canola respectively along with two regulatory elements and seven genes: P35S, tNOS, pat, bar, epsps1, epsps2, pmi, cry1Ac and cry3B. The specificity was confirmed and the sensitivity was 0.5% for four crops' 12 events: one soybean, six maize, three cotton and two canola events. The multiplex PCR and DNA chip can be available for screening, gene-specific and event-specific analysis of biotech crops as efficient detection methods by saving on workload and time. © 2014 Society of Chemical Industry. © 2014 Society of Chemical Industry.

Efficient synthesis of highly fluorescent carbon dots by microreactor method and their application in Fe3+ ion detection.

PubMed

Rao, Longshi; Tang, Yong; Li, Zongtao; Ding, Xinrui; Liang, Guanwei; Lu, Hanguang; Yan, Caiman; Tang, Kairui; Yu, Binhai

2017-12-01

Rapidly obtaining strong photoluminescence (PL) of carbon dots with high stability is crucial in all practical applications of carbon dots, such as cell imaging and biological detection. In this study, we proposed a rapid, continuous carbon dots synthesis technique by using a microreactor method. By taking advantage of the microreactor, we were able to rapidly synthesized CDs at a large scale in less than 5min, and a high quantum yield of 60.1% was achieved. This method is faster and more efficient than most of the previously reported methods. To explore the relationship between the microreactor structure and CDs PL properties, Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) were carried out. The results show the surface functional groups and element contents influence the PL emission. Subsequent ion detection experiments indicated that CDs are very suitable for use as nanoprobes for Fe 3+ ion detection, and the lowest detection limit for Fe 3+ is 0.239μM, which is superior to many other research studies. This rapid and simple synthesis method will not only aid the development of the quantum dots industrialization but also provide a powerful and portable tool for the rapid and continuous online synthesis of quantum dots supporting their application in cell imaging and safety detection. Copyright © 2017 Elsevier B.V. All rights reserved.

A third-order approximation method for three-dimensional wheel-rail contact

NASA Astrophysics Data System (ADS)

Negretti, Daniele

2012-03-01

Multibody train analysis is used increasingly by railway operators whenever a reliable and time-efficient method to evaluate the contact between wheel and rail is needed; particularly, the wheel-rail contact is one of the most important aspects that affects a reliable and time-efficient vehicle dynamics computation. The focus of the approach proposed here is to carry out such tasks by means of online wheel-rail elastic contact detection. In order to improve efficiency and save time, a main analytical approach is used for the definition of wheel and rail surfaces as well as for contact detection, then a final numerical evaluation is used to locate contact. The final numerical procedure consists in finding the zeros of a nonlinear function in a single variable. The overall method is based on the approximation of the wheel surface, which does not influence the contact location significantly, as shown in the paper.

Camouflage target reconnaissance based on hyperspectral imaging technology

NASA Astrophysics Data System (ADS)

Hua, Wenshen; Guo, Tong; Liu, Xun

2015-08-01

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

Overview of hybridization and detection techniques.

PubMed

Hilario, Elena

2007-01-01

A misconception regarding the sensitivity of nonradioactive methods for screening genomic DNA libraries often hinders the establishment of these environmentally friendly techniques in molecular biology laboratories. Nonradioactive probes, properly prepared and quantified, can detect DNA target molecules to the femtomole range. However, appropriate hybridization techniques and detection methods should also be adopted for an efficient use of nonradioactive techniques. Detailed descriptions of genomic library handling before and during the nonradioactive hybridization and detection are often omitted from publications. This chapter aims to fill this void by providing a collection of technical tips on hybridization and detection techniques.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Detecting and enumerating soil-transmitted helminth eggs in soil: New method development and results from field testing in Kenya and Bangladesh.

PubMed

Steinbaum, Lauren; Kwong, Laura H; Ercumen, Ayse; Negash, Makeda S; Lovely, Amira J; Njenga, Sammy M; Boehm, Alexandria B; Pickering, Amy J; Nelson, Kara L

2017-04-01

Globally, about 1.5 billion people are infected with at least one species of soil-transmitted helminth (STH). Soil is a critical environmental reservoir of STH, yet there is no standard method for detecting STH eggs in soil. We developed a field method for enumerating STH eggs in soil and tested the method in Bangladesh and Kenya. The US Environmental Protection Agency (EPA) method for enumerating Ascaris eggs in biosolids was modified through a series of recovery efficiency experiments; we seeded soil samples with a known number of Ascaris suum eggs and assessed the effect of protocol modifications on egg recovery. We found the use of 1% 7X as a surfactant compared to 0.1% Tween 80 significantly improved recovery efficiency (two-sided t-test, t = 5.03, p = 0.007) while other protocol modifications-including different agitation and flotation methods-did not have a significant impact. Soil texture affected the egg recovery efficiency; sandy samples resulted in higher recovery compared to loamy samples processed using the same method (two-sided t-test, t = 2.56, p = 0.083). We documented a recovery efficiency of 73% for the final improved method using loamy soil in the lab. To field test the improved method, we processed soil samples from 100 households in Bangladesh and 100 households in Kenya from June to November 2015. The prevalence of any STH (Ascaris, Trichuris or hookworm) egg in soil was 78% in Bangladesh and 37% in Kenya. The median concentration of STH eggs in soil in positive samples was 0.59 eggs/g dry soil in Bangladesh and 0.15 eggs/g dry soil in Kenya. The prevalence of STH eggs in soil was significantly higher in Bangladesh than Kenya (chi-square, χ2 = 34.39, p < 0.001) as was the concentration (Mann-Whitney, z = 7.10, p < 0.001). This new method allows for detecting STH eggs in soil in low-resource settings and could be used for standardizing soil STH detection globally.

Quantum dots as optical labels for ultrasensitive detection of polyphenols.

PubMed

Akshath, Uchangi Satyaprasad; Shubha, Likitha R; Bhatt, Praveena; Thakur, Munna Singh

2014-07-15

Considering the fact that polyphenols have versatile activity in-vivo, its detection and quantification is very much important for a healthy diet. Laccase enzyme can convert polyphenols to yield mono/polyquinones which can quench Quantum dots fluorescence. This phenomenon of charge transfer from quinones to QDs was exploited as optical labels to detect polyphenols. CdTe QD may undergo dipolar interaction with quinones as a result of broad spectral absorption due to multiple excitonic states resulting from quantum confinement effects. Thus, "turn-off" fluorescence method was applied for ultrasensitive detection of polyphenols by using laccase. We observed proportionate quenching of QDs fluorescence with respect to polyphenol concentration in the range of 100 µg to 1 ng/mL. Also, quenching of the photoluminescence was highly efficient and stable and could detect individual and total polyphenols with high sensitivity (LOD-1 ng/mL). Moreover, proposed method was highly efficient than any other reported methods in terms of sensitivity, specificity and selectivity. Therefore, a novel optical sensor was developed for the detection of polyphenols at a sensitive level based on the charge transfer mechanism. Copyright © 2014 Elsevier B.V. All rights reserved.

Evaluation of environmental sampling methods for detection of Salmonella enterica in a large animal veterinary hospital.

PubMed

Goeman, Valerie R; Tinkler, Stacy H; Hammac, G Kenitra; Ruple, Audrey

2018-04-01

Environmental surveillance for Salmonella enterica can be used for early detection of contamination; thus routine sampling is an integral component of infection control programs in hospital environments. At the Purdue University Veterinary Teaching Hospital (PUVTH), the technique regularly employed in the large animal hospital for sample collection uses sterile gauze sponges for environmental sampling, which has proven labor-intensive and time-consuming. Alternative sampling methods use Swiffer brand electrostatic wipes for environmental sample collection, which are reportedly effective and efficient. It was hypothesized that use of Swiffer wipes for sample collection would be more efficient and less costly than the use of gauze sponges. A head-to-head comparison between the 2 sampling methods was conducted in the PUVTH large animal hospital and relative agreement, cost-effectiveness, and sampling efficiency were compared. There was fair agreement in culture results between the 2 sampling methods, but Swiffer wipes required less time and less physical effort to collect samples and were more cost-effective.

A laser-based FAIMS detector for detection of ultra-low concentrations of explosives

NASA Astrophysics Data System (ADS)

Akmalov, Artem E.; Chistyakov, Alexander A.; Kotkovskii, Gennadii E.; Sychev, Alexey V.; Tugaenko, Anton V.; Bogdanov, Artem S.; Perederiy, Anatoly N.; Spitsyn, Eugene M.

2014-06-01

A non-contact method for analyzing of explosives traces from surfaces was developed. The method is based on the laser desorption of analyzed molecules from the surveyed surfaces followed by the laser ionization of air sample combined with the field asymmetric ion mobility spectrometry (FAIMS). The pulsed radiation of the fourth harmonic of a portable GSGG: Cr3+ :Nd3+ laser (λ = 266 nm) is used. The laser desorption FAIMS analyzer have been developed. The detection limit of the analyzer equals 40 pg for TNT. The results of detection of trinitrotoluene (TNT), cyclotrimethylenetrinitramine (RDX) and cyclotetramethylenetetranitramine (HMX) are presented. It is shown that laser desorption of nitro-compounds from metals is accompanied by their surface decomposition. A method for detecting and analyzing of small concentrations of explosives in air based on the laser ionization and the FAIMS was developed. The method includes a highly efficient multipass optical scheme of the intracavity fourthharmonic generation of pulsed laser radiation (λ = 266 nm) and the field asymmetric ion mobility (FAIM) spectrometer disposed within a resonator. The ions formation and detection proceed inside a resonant cavity. The laser ion source based on the multi-passage of radiation at λ = 266 nm through the ionization region was elaborated. On the basis of the method the laser FAIMS analyzer has been created. The analyzer provides efficient detection of low concentrations of nitro-compounds in air and shows a detection limit of 10-14 - 10-15 g/cm3 both for RDX and TNT.

Development of a Reverse Transcription Loop-Mediated Isothermal Amplification Method for the Rapid Detection of Subtype H7N9 Avian Influenza Virus

PubMed Central

Bao, Hongmei; Zhao, Yuhui; Wang, Yunhe; Xu, Xiaolong; Shi, Jianzhong; Zeng, Xianying; Wang, Xiurong; Chen, Hualan

2014-01-01

A novel influenza A (H7N9) virus has emerged in China. To rapidly detect this virus from clinical samples, we developed a reverse transcription loop-mediated isothermal amplification (RT-LAMP) method for the detection of the H7N9 virus. The minimum detection limit of the RT-LAMP assay was 0.01 PFU H7N9 virus, making this method 100-fold more sensitive to the detection of the H7N9 virus than conventional RT-PCR. The H7N9 virus RT-LAMP assays can efficiently detect different sources of H7N9 influenza virus RNA (from chickens, pigeons, the environment, and humans). No cross-reactive amplification with the RNA of other subtype influenza viruses or of other avian respiratory viruses was observed. The assays can effectively detect H7N9 influenza virus RNA in drinking water, soil, cloacal swab, and tracheal swab samples that were collected from live poultry markets, as well as human H7N9 virus, in less than 30 min. These results suggest that the H7N9 virus RT-LAMP assays were efficient, practical, and rapid diagnostic methods for the epidemiological surveillance and diagnosis of influenza A (H7N9) virus from different resource samples. PMID:24689044

A rapid detection method for policy-sensitive amines real-time supervision.

PubMed

Zhang, Haixu; Shu, Jinian; Yang, Bo; Zhang, Peng; Ma, Pengkun

2018-02-01

Many organic amines that comprise a benzene ring are policy-sensitive because of their toxicity and links to social harm. However, to date, detection of such compounds mainly relies on offline methods. This study proposes an online pptv (parts per trillion by volume) level of detection method for amines, using the recently-built vacuum ultraviolet photoionization mass spectrometer (VUV-PIMS) combined with a new doping technique. Thus, the dichloromethane doping-assisted photoionization mass spectra of aniline, benzylamine, phenethylamine, amphetamine, and their structural isomers were recorded. The dominant characteristic mass peaks for all amines are those afforded by protonated amines and the amino radical-loss. The signal intensities of the amines were enhanced by 60-130 times compared to those recorded without doping assistance. Under 10s detection time, the sensitivities of aniline and benzylamine in the gas phase were determined as 4.0 and 2.7 countspptv -1 , with limits of detection (LODs) of 36 and 22 pptv, respectively. Notably, the detection efficiency of this method can be tenfold better in future applications since the ion transmission efficiency of the mass spectrometer was intentionally reduced to ~ 10% in this study. Therefore, dichloromethane doping-assisted photoionization mass spectrometry has proven to be a highly promising on-line approach to amine detection in environmental and judicial supervision and shows great potential for application in the biological field. Copyright © 2017 Elsevier B.V. All rights reserved.

A rapid and efficient newly established method to detect COL1A1-PDGFB gene fusion in dermatofibrosarcoma protuberans

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

Yokoyama, Yoko; Shimizu, Akira; Okada, Etsuko

Highlights: Black-Right-Pointing-Pointer We developed new method to rapidly identify COL1A1-PDGFB fusion in DFSP. Black-Right-Pointing-Pointer New PCR method using a single primer pair detected COL1A1-PDGFB fusion in DFSP. Black-Right-Pointing-Pointer This is the first report of DFSP with a novel COL1A1 breakpoint in exon 5. -- Abstract: The detection of fusion transcripts of the collagen type 1{alpha}1 (COL1A1) and platelet-derived growth factor-BB (PDGFB) genes by genetic analysis has recognized as a reliable and valuable molecular tool for the diagnosis of dermatofibrosarcoma protuberans (DFSP). To detect the COL1A1-PDGFB fusion, almost previous reports performed reverse transcription polymerase chain reaction (RT-PCR) using multiplex forward primersmore » from COL1A1. However, it has possible technical difficulties with respect to the handling of multiple primers and reagents in the procedure. The objective of this study is to establish a rapid, easy, and efficient one-step method of PCR using only a single primer pair to detect the fusion transcripts of the COL1A1 and PDGFB in DFSP. To validate new method, we compared the results of RT-PCR in five patients of DFSP between the previous method using multiplex primers and our established one-step RT-PCR using a single primer pair. In all cases of DFSP, the COL1A1-PDGFB fusion was detected by both previous method and newly established one-step PCR. Importantly, we detected a novel COL1A1 breakpoint in exon 5. The newly developed method is valuable to rapidly identify COL1A1-PDGFB fusion transcripts in DFSP.« less

Development of Nested PCR, Multiplex PCR, and Loop-Mediated Isothermal Amplification Assays for Rapid Detection of Cylindrocladium scoparium on Eucalyptus.

PubMed

Qiao, Tian-Min; Zhang, Jing; Li, Shu-Jiang; Han, Shan; Zhu, Tian-Hui

2016-10-01

Eucalyptus dieback disease, caused by Cylindrocladium scoparium , has occurred in last few years in large Eucalyptus planting areas in China and other countries. Rapid, simple, and reliable diagnostic techniques are desired for the early detection of Eucalyptus dieback of C. scoparium prior to formulation of efficient control plan. For this purpose, three PCR-based methods of nested PCR, multiplex PCR, loop-mediated isothermal amplification (LAMP) were developed for detection of C. scoparium based on factor 1-alpha (tef1) and beta-tubulin gene in this study. All of the three methods showed highly specific to C. scoparium . The sensitivities of the nested PCR and LAMP were much higher than the multiplex PCR. The sensitivity of multiplex PCR was also higher than regular PCR. C. scoparium could be detected within 60 min from infected Eucalyptus plants by LAMP, while at least 2 h was needed by the rest two methods. Using different Eucalyptus tissues as samples for C. scoparium detection, all of the three PCR-based methods showed much better detection results than regular PCR. Base on the results from this study, we concluded that any of the three PCR-based methods could be used as diagnostic technology for the development of efficient strategies of Eucalyptus dieback disease control. Particularly, LAMP was the most practical method in field application because of its one-step and rapid reaction, simple operation, single-tube utilization, and simple visualization of amplification products.

Development of Nested PCR, Multiplex PCR, and Loop-Mediated Isothermal Amplification Assays for Rapid Detection of Cylindrocladium scoparium on Eucalyptus

PubMed Central

Qiao, Tian-Min; Zhang, Jing; Li, Shu-Jiang; Han, Shan; Zhu, Tian-Hui

2016-01-01

Eucalyptus dieback disease, caused by Cylindrocladium scoparium, has occurred in last few years in large Eucalyptus planting areas in China and other countries. Rapid, simple, and reliable diagnostic techniques are desired for the early detection of Eucalyptus dieback of C. scoparium prior to formulation of efficient control plan. For this purpose, three PCR-based methods of nested PCR, multiplex PCR, loop-mediated isothermal amplification (LAMP) were developed for detection of C. scoparium based on factor 1-alpha (tef1) and beta-tubulin gene in this study. All of the three methods showed highly specific to C. scoparium. The sensitivities of the nested PCR and LAMP were much higher than the multiplex PCR. The sensitivity of multiplex PCR was also higher than regular PCR. C. scoparium could be detected within 60 min from infected Eucalyptus plants by LAMP, while at least 2 h was needed by the rest two methods. Using different Eucalyptus tissues as samples for C. scoparium detection, all of the three PCR-based methods showed much better detection results than regular PCR. Base on the results from this study, we concluded that any of the three PCR-based methods could be used as diagnostic technology for the development of efficient strategies of Eucalyptus dieback disease control. Particularly, LAMP was the most practical method in field application because of its one-step and rapid reaction, simple operation, single-tube utilization, and simple visualization of amplification products. PMID:27721691

Wavefront reconstruction method based on wavelet fractal interpolation for coherent free space optical communication

NASA Astrophysics Data System (ADS)

Zhang, Dai; Hao, Shiqi; Zhao, Qingsong; Zhao, Qi; Wang, Lei; Wan, Xiongfeng

2018-03-01

Existing wavefront reconstruction methods are usually low in resolution, restricted by structure characteristics of the Shack Hartmann wavefront sensor (SH WFS) and the deformable mirror (DM) in the adaptive optics (AO) system, thus, resulting in weak homodyne detection efficiency for free space optical (FSO) communication. In order to solve this problem, we firstly validate the feasibility of liquid crystal spatial light modulator (LC SLM) using in an AO system. Then, wavefront reconstruction method based on wavelet fractal interpolation is proposed after self-similarity analysis of wavefront distortion caused by atmospheric turbulence. Fast wavelet decomposition is operated to multiresolution analyze the wavefront phase spectrum, during which soft threshold denoising is carried out. The resolution of estimated wavefront phase is then improved by fractal interpolation. Finally, fast wavelet reconstruction is taken to recover wavefront phase. Simulation results reflect the superiority of our method in homodyne detection. Compared with minimum variance estimation (MVE) method based on interpolation techniques, the proposed method could obtain superior homodyne detection efficiency with lower operation complexity. Our research findings have theoretical significance in the design of coherent FSO communication system.

Antibody biosensors for spoilage yeast detection based on impedance spectroscopy.

PubMed

Tubía, I; Paredes, J; Pérez-Lorenzo, E; Arana, S

2018-04-15

Brettanomyces is a yeast species responsible for wine and cider spoilage, producing volatile phenols that result in off-odors and loss of fruity sensorial qualities. Current commercial detection methods for these spoilage species are liable to frequent false positives, long culture times and fungal contamination. In this work, an interdigitated (IDE) biosensor was created to detect Brettanomyces using immunological reactions and impedance spectroscopy analysis. To promote efficient antibody immobilization on the electrodes' surface and to decrease non-specific adsorption, a Self-Assembled Monolayer (SAM) was developed. An impedance spectroscopy analysis, over four yeast strains, confirmed our device's increased efficacy. Compared to label-free sensors, antibody biosensors showed a higher relative impedance. The results also suggested that these biosensors could be a promising method to monitor some spoilage yeasts, offering an efficient alternative to the laborious and expensive traditional methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Rapid Authentication of Ginkgo biloba Herbal Products Using the Recombinase Polymerase Amplification Assay.

PubMed

Liu, Yang; Wang, Xiao-Yue; Wei, Xue-Min; Gao, Zi-Tong; Han, Jian-Ping

2018-05-22

Species adulteration in herbal products (HPs) exposes consumers to health risks. Chemical and morphological methods have their own deficiencies when dealing with the detection of species containing the same active compounds in HPs. In this study, we developed a rapid identification method using the recombinase polymerase amplification (RPA) assay to detect two species, Ginkgo biloba and Sophora japonica (as adulteration), in Ginkgo biloba HPs. Among 36 Ginkgo biloba HP samples, 34 were found to have Ginkgo biloba sequences, and 9 were found to have Sophora japonica sequences. During the authentication process, the RPA-LFS assay showed a higher specificity, sensitivity and efficiency than PCR-based methods. We initially applied the RPA-LSF technique to detect plant species in HPs, demonstrating that this assay can be developed into an efficient tool for the rapid on-site authentication of plant species in Ginkgo biloba HPs.

Pornographic information of Internet views detection method based on the connected areas

NASA Astrophysics Data System (ADS)

Wang, Huibai; Fan, Ajie

2017-01-01

Nowadays online porn video broadcasting and downloading is very popular. In view of the widespread phenomenon of Internet pornography, this paper proposed a new method of pornographic video detection based on connected areas. Firstly, decode the video into a serious of static images and detect skin color on the extracted key frames. If the area of skin color reaches a certain threshold, use the AdaBoost algorithm to detect the human face. Judge the connectivity of the human face and the large area of skin color to determine whether detect the sensitive area finally. The experimental results show that the method can effectively remove the non-pornographic videos contain human who wear less. This method can improve the efficiency and reduce the workload of detection.

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

PubMed

Alfaro-Núñez, Alonzo; Gilbert, M Thomas P

2014-09-01

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

A detection method for X-ray images based on wavelet transforms: the case of the ROSAT PSPC.

NASA Astrophysics Data System (ADS)

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

1996-02-01

The authors have developed a method based on wavelet transforms (WT) to detect efficiently sources in PSPC X-ray images. The multiscale approach typical of WT can be used to detect sources with a large range of sizes, and to estimate their size and count rate. Significance thresholds for candidate detections (found as local WT maxima) have been derived from a detailed study of the probability distribution of the WT of a locally uniform background. The use of the exposure map allows good detection efficiency to be retained even near PSPC ribs and edges. The algorithm may also be used to get upper limits to the count rate of undetected objects. Simulations of realistic PSPC images containing either pure background or background+sources were used to test the overall algorithm performances, and to assess the frequency of spurious detections (vs. detection threshold) and the algorithm sensitivity. Actual PSPC images of galaxies and star clusters show the algorithm to have good performance even in cases of extended sources and crowded fields.

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.

Detecting and enumerating soil-transmitted helminth eggs in soil: New method development and results from field testing in Kenya and Bangladesh

PubMed Central

Kwong, Laura H.; Ercumen, Ayse; Negash, Makeda S.; Lovely, Amira J.; Njenga, Sammy M.; Boehm, Alexandria B.; Pickering, Amy J.; Nelson, Kara L.

2017-01-01

Globally, about 1.5 billion people are infected with at least one species of soil-transmitted helminth (STH). Soil is a critical environmental reservoir of STH, yet there is no standard method for detecting STH eggs in soil. We developed a field method for enumerating STH eggs in soil and tested the method in Bangladesh and Kenya. The US Environmental Protection Agency (EPA) method for enumerating Ascaris eggs in biosolids was modified through a series of recovery efficiency experiments; we seeded soil samples with a known number of Ascaris suum eggs and assessed the effect of protocol modifications on egg recovery. We found the use of 1% 7X as a surfactant compared to 0.1% Tween 80 significantly improved recovery efficiency (two-sided t-test, t = 5.03, p = 0.007) while other protocol modifications—including different agitation and flotation methods—did not have a significant impact. Soil texture affected the egg recovery efficiency; sandy samples resulted in higher recovery compared to loamy samples processed using the same method (two-sided t-test, t = 2.56, p = 0.083). We documented a recovery efficiency of 73% for the final improved method using loamy soil in the lab. To field test the improved method, we processed soil samples from 100 households in Bangladesh and 100 households in Kenya from June to November 2015. The prevalence of any STH (Ascaris, Trichuris or hookworm) egg in soil was 78% in Bangladesh and 37% in Kenya. The median concentration of STH eggs in soil in positive samples was 0.59 eggs/g dry soil in Bangladesh and 0.15 eggs/g dry soil in Kenya. The prevalence of STH eggs in soil was significantly higher in Bangladesh than Kenya (chi-square, χ2 = 34.39, p < 0.001) as was the concentration (Mann-Whitney, z = 7.10, p < 0.001). This new method allows for detecting STH eggs in soil in low-resource settings and could be used for standardizing soil STH detection globally. PMID:28379956

Active link selection for efficient semi-supervised community detection

NASA Astrophysics Data System (ADS)

Yang, Liang; Jin, Di; Wang, Xiao; Cao, Xiaochun

2015-03-01

Several semi-supervised community detection algorithms have been proposed recently to improve the performance of traditional topology-based methods. However, most of them focus on how to integrate supervised information with topology information; few of them pay attention to which information is critical for performance improvement. This leads to large amounts of demand for supervised information, which is expensive or difficult to obtain in most fields. For this problem we propose an active link selection framework, that is we actively select the most uncertain and informative links for human labeling for the efficient utilization of the supervised information. We also disconnect the most likely inter-community edges to further improve the efficiency. Our main idea is that, by connecting uncertain nodes to their community hubs and disconnecting the inter-community edges, one can sharpen the block structure of adjacency matrix more efficiently than randomly labeling links as the existing methods did. Experiments on both synthetic and real networks demonstrate that our new approach significantly outperforms the existing methods in terms of the efficiency of using supervised information. It needs ~13% of the supervised information to achieve a performance similar to that of the original semi-supervised approaches.

Active link selection for efficient semi-supervised community detection

PubMed Central

Yang, Liang; Jin, Di; Wang, Xiao; Cao, Xiaochun

2015-01-01

Several semi-supervised community detection algorithms have been proposed recently to improve the performance of traditional topology-based methods. However, most of them focus on how to integrate supervised information with topology information; few of them pay attention to which information is critical for performance improvement. This leads to large amounts of demand for supervised information, which is expensive or difficult to obtain in most fields. For this problem we propose an active link selection framework, that is we actively select the most uncertain and informative links for human labeling for the efficient utilization of the supervised information. We also disconnect the most likely inter-community edges to further improve the efficiency. Our main idea is that, by connecting uncertain nodes to their community hubs and disconnecting the inter-community edges, one can sharpen the block structure of adjacency matrix more efficiently than randomly labeling links as the existing methods did. Experiments on both synthetic and real networks demonstrate that our new approach significantly outperforms the existing methods in terms of the efficiency of using supervised information. It needs ~13% of the supervised information to achieve a performance similar to that of the original semi-supervised approaches. PMID:25761385

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

NASA Astrophysics Data System (ADS)

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

1997-07-01

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

Development and validation of real-time PCR screening methods for detection of cry1A.105 and cry2Ab2 genes in genetically modified organisms.

PubMed

Dinon, Andréia Z; Prins, Theo W; van Dijk, Jeroen P; Arisi, Ana Carolina M; Scholtens, Ingrid M J; Kok, Esther J

2011-05-01

Primers and probes were developed for the element-specific detection of cry1A.105 and cry2Ab2 genes, based on their DNA sequence as present in GM maize MON89034. Cry genes are present in many genetically modified (GM) plants and they are important targets for developing GMO element-specific detection methods. Element-specific methods can be of use to screen for the presence of GMOs in food and feed supply chains. Moreover, a combination of GMO elements may indicate the potential presence of unapproved GMOs (UGMs). Primer-probe combinations were evaluated in terms of specificity, efficiency and limit of detection. Except for specificity, the complete experiment was performed in 9 PCR runs, on 9 different days and by testing 8 DNA concentrations. The results showed a high specificity and efficiency for cry1A.105 and cry2Ab2 detection. The limit of detection was between 0.05 and 0.01 ng DNA per PCR reaction for both assays. These data confirm the applicability of these new primer-probe combinations for element detection that can contribute to the screening for GM and UGM crops in food and feed samples.

Small target detection using objectness and saliency

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Fast microcalcification detection in ultrasound images using image enhancement and threshold adjacency statistics

NASA Astrophysics Data System (ADS)

Cho, Baek Hwan; Chang, Chuho; Lee, Jong-Ha; Ko, Eun Young; Seong, Yeong Kyeong; Woo, Kyoung-Gu

2013-02-01

The existence of microcalcifications (MCs) is an important marker of malignancy in breast cancer. In spite of the benefits in mass detection for dense breasts, ultrasonography is believed that it might not reliably detect MCs. For computer aided diagnosis systems, however, accurate detection of MCs has the possibility of improving the performance in both Breast Imaging-Reporting and Data System (BI-RADS) lexicon description for calcifications and malignancy classification. We propose a new efficient and effective method for MC detection using image enhancement and threshold adjacency statistics (TAS). The main idea of TAS is to threshold an image and to count the number of white pixels with a given number of adjacent white pixels. Our contribution is to adopt TAS features and apply image enhancement to facilitate MC detection in ultrasound images. We employed fuzzy logic, tophat filter, and texture filter to enhance images for MCs. Using a total of 591 images, the classification accuracy of the proposed method in MC detection showed 82.75%, which is comparable to that of Haralick texture features (81.38%). When combined, the performance was as high as 85.11%. In addition, our method also showed the ability in mass classification when combined with existing features. In conclusion, the proposed method exploiting image enhancement and TAS features has the potential to deal with MC detection in ultrasound images efficiently and extend to the real-time localization and visualization of MCs.

Pre-capture multiplexing improves efficiency and cost-effectiveness of targeted genomic enrichment.

PubMed

Shearer, A Eliot; Hildebrand, Michael S; Ravi, Harini; Joshi, Swati; Guiffre, Angelica C; Novak, Barbara; Happe, Scott; LeProust, Emily M; Smith, Richard J H

2012-11-14

Targeted genomic enrichment (TGE) is a widely used method for isolating and enriching specific genomic regions prior to massively parallel sequencing. To make effective use of sequencer output, barcoding and sample pooling (multiplexing) after TGE and prior to sequencing (post-capture multiplexing) has become routine. While previous reports have indicated that multiplexing prior to capture (pre-capture multiplexing) is feasible, no thorough examination of the effect of this method has been completed on a large number of samples. Here we compare standard post-capture TGE to two levels of pre-capture multiplexing: 12 or 16 samples per pool. We evaluated these methods using standard TGE metrics and determined the ability to identify several classes of genetic mutations in three sets of 96 samples, including 48 controls. Our overall goal was to maximize cost reduction and minimize experimental time while maintaining a high percentage of reads on target and a high depth of coverage at thresholds required for variant detection. We adapted the standard post-capture TGE method for pre-capture TGE with several protocol modifications, including redesign of blocking oligonucleotides and optimization of enzymatic and amplification steps. Pre-capture multiplexing reduced costs for TGE by at least 38% and significantly reduced hands-on time during the TGE protocol. We found that pre-capture multiplexing reduced capture efficiency by 23 or 31% for pre-capture pools of 12 and 16, respectively. However efficiency losses at this step can be compensated by reducing the number of simultaneously sequenced samples. Pre-capture multiplexing and post-capture TGE performed similarly with respect to variant detection of positive control mutations. In addition, we detected no instances of sample switching due to aberrant barcode identification. Pre-capture multiplexing improves efficiency of TGE experiments with respect to hands-on time and reagent use compared to standard post-capture TGE. A decrease in capture efficiency is observed when using pre-capture multiplexing; however, it does not negatively impact variant detection and can be accommodated by the experimental design.

Quality assurance using outlier detection on an automatic segmentation method for the cerebellar peduncles

NASA Astrophysics Data System (ADS)

Li, Ke; Ye, Chuyang; Yang, Zhen; Carass, Aaron; Ying, Sarah H.; Prince, Jerry L.

2016-03-01

Cerebellar peduncles (CPs) are white matter tracts connecting the cerebellum to other brain regions. Automatic segmentation methods of the CPs have been proposed for studying their structure and function. Usually the performance of these methods is evaluated by comparing segmentation results with manual delineations (ground truth). However, when a segmentation method is run on new data (for which no ground truth exists) it is highly desirable to efficiently detect and assess algorithm failures so that these cases can be excluded from scientific analysis. In this work, two outlier detection methods aimed to assess the performance of an automatic CP segmentation algorithm are presented. The first one is a univariate non-parametric method using a box-whisker plot. We first categorize automatic segmentation results of a dataset of diffusion tensor imaging (DTI) scans from 48 subjects as either a success or a failure. We then design three groups of features from the image data of nine categorized failures for failure detection. Results show that most of these features can efficiently detect the true failures. The second method—supervised classification—was employed on a larger DTI dataset of 249 manually categorized subjects. Four classifiers—linear discriminant analysis (LDA), logistic regression (LR), support vector machine (SVM), and random forest classification (RFC)—were trained using the designed features and evaluated using a leave-one-out cross validation. Results show that the LR performs worst among the four classifiers and the other three perform comparably, which demonstrates the feasibility of automatically detecting segmentation failures using classification methods.

Mapping Diffuse Seismicity Using Empirical Matched Field Processing Techniques

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

Wang, J; Templeton, D C; Harris, D B

The objective of this project is to detect and locate more microearthquakes using the empirical matched field processing (MFP) method than can be detected using only conventional earthquake detection techniques. We propose that empirical MFP can complement existing catalogs and techniques. We test our method on continuous seismic data collected at the Salton Sea Geothermal Field during November 2009 and January 2010. In the Southern California Earthquake Data Center (SCEDC) earthquake catalog, 619 events were identified in our study area during this time frame and our MFP technique identified 1094 events. Therefore, we believe that the empirical MFP method combinedmore » with conventional methods significantly improves the network detection ability in an efficient matter.« less

Global Coverage Measurement Planning Strategies for Mobile Robots Equipped with a Remote Gas Sensor

PubMed Central

Arain, Muhammad Asif; Trincavelli, Marco; Cirillo, Marcello; Schaffernicht, Erik; Lilienthal, Achim J.

2015-01-01

The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose an algorithm that leverages a novel method based on convex relaxation for quickly solving sensor placement problems, and for generating an efficient exploration plan for the robot. To demonstrate the applicability of our method to real-world environments, we performed a large number of experimental trials, both on randomly generated maps and on the map of a real environment. Our approach proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions. PMID:25803707

Global coverage measurement planning strategies for mobile robots equipped with a remote gas sensor.

PubMed

Arain, Muhammad Asif; Trincavelli, Marco; Cirillo, Marcello; Schaffernicht, Erik; Lilienthal, Achim J

2015-03-20

The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose an algorithm that leverages a novel method based on convex relaxation for quickly solving sensor placement problems, and for generating an efficient exploration plan for the robot. To demonstrate the applicability of our method to real-world environments, we performed a large number of experimental trials, both on randomly generated maps and on the map of a real environment. Our approach proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions.

Robust obstacle detection for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Qin, Yueming; Zhang, Xiuzhi

2018-03-01

Obstacle detection is of essential importance for Unmanned Surface Vehicles (USV). Although some obstacles (e.g., ships, islands) can be detected by Radar, there are many other obstacles (e.g., floating pieces of woods, swimmers) which are difficult to be detected via Radar because these obstacles have low radar cross section. Therefore, detecting obstacle from images taken onboard is an effective supplement. In this paper, a robust vision-based obstacle detection method for USVs is developed. The proposed method employs the monocular image sequence captured by the camera on the USVs and detects obstacles on the sea surface from the image sequence. The experiment results show that the proposed scheme is efficient to fulfill the obstacle detection task.

Automatic background updating for video-based vehicle detection

NASA Astrophysics Data System (ADS)

Hu, Chunhai; Li, Dongmei; Liu, Jichuan

2008-03-01

Video-based vehicle detection is one of the most valuable techniques for the Intelligent Transportation System (ITS). The widely used video-based vehicle detection technique is the background subtraction method. The key problem of this method is how to subtract and update the background effectively. In this paper an efficient background updating scheme based on Zone-Distribution for vehicle detection is proposed to resolve the problems caused by sudden camera perturbation, sudden or gradual illumination change and the sleeping person problem. The proposed scheme is robust and fast enough to satisfy the real-time constraints of vehicle detection.

A Fast Framework for Abrupt Change Detection Based on Binary Search Trees and Kolmogorov Statistic

PubMed Central

Qi, Jin-Peng; Qi, Jie; Zhang, Qing

2016-01-01

Change-Point (CP) detection has attracted considerable attention in the fields of data mining and statistics; it is very meaningful to discuss how to quickly and efficiently detect abrupt change from large-scale bioelectric signals. Currently, most of the existing methods, like Kolmogorov-Smirnov (KS) statistic and so forth, are time-consuming, especially for large-scale datasets. In this paper, we propose a fast framework for abrupt change detection based on binary search trees (BSTs) and a modified KS statistic, named BSTKS (binary search trees and Kolmogorov statistic). In this method, first, two binary search trees, termed as BSTcA and BSTcD, are constructed by multilevel Haar Wavelet Transform (HWT); second, three search criteria are introduced in terms of the statistic and variance fluctuations in the diagnosed time series; last, an optimal search path is detected from the root to leaf nodes of two BSTs. The studies on both the synthetic time series samples and the real electroencephalograph (EEG) recordings indicate that the proposed BSTKS can detect abrupt change more quickly and efficiently than KS, t-statistic (t), and Singular-Spectrum Analyses (SSA) methods, with the shortest computation time, the highest hit rate, the smallest error, and the highest accuracy out of four methods. This study suggests that the proposed BSTKS is very helpful for useful information inspection on all kinds of bioelectric time series signals. PMID:27413364

A Fast Framework for Abrupt Change Detection Based on Binary Search Trees and Kolmogorov Statistic.

PubMed

Qi, Jin-Peng; Qi, Jie; Zhang, Qing

2016-01-01

Change-Point (CP) detection has attracted considerable attention in the fields of data mining and statistics; it is very meaningful to discuss how to quickly and efficiently detect abrupt change from large-scale bioelectric signals. Currently, most of the existing methods, like Kolmogorov-Smirnov (KS) statistic and so forth, are time-consuming, especially for large-scale datasets. In this paper, we propose a fast framework for abrupt change detection based on binary search trees (BSTs) and a modified KS statistic, named BSTKS (binary search trees and Kolmogorov statistic). In this method, first, two binary search trees, termed as BSTcA and BSTcD, are constructed by multilevel Haar Wavelet Transform (HWT); second, three search criteria are introduced in terms of the statistic and variance fluctuations in the diagnosed time series; last, an optimal search path is detected from the root to leaf nodes of two BSTs. The studies on both the synthetic time series samples and the real electroencephalograph (EEG) recordings indicate that the proposed BSTKS can detect abrupt change more quickly and efficiently than KS, t-statistic (t), and Singular-Spectrum Analyses (SSA) methods, with the shortest computation time, the highest hit rate, the smallest error, and the highest accuracy out of four methods. This study suggests that the proposed BSTKS is very helpful for useful information inspection on all kinds of bioelectric time series signals.

Clearing muddied waters: Capture of environmental DNA from turbid waters.

PubMed

Williams, Kelly E; Huyvaert, Kathryn P; Piaggio, Antoinette J

2017-01-01

Understanding the differences in efficiencies of various methods to concentrate, extract, and amplify environmental DNA (eDNA) is vital for best performance of eDNA detection. Aquatic systems vary in characteristics such as turbidity, eDNA concentration, and inhibitor load, thus affecting eDNA capture efficiency. Application of eDNA techniques to the detection of terrestrial invasive or endangered species may require sampling at intermittent water sources that are used for drinking and cooling; these water bodies may often be stagnant and turbid. We present our best practices technique for the detection of wild pig eDNA in water samples, a protocol that will have wide applicability to the detection of elusive vertebrate species. We determined the best practice for eDNA capture in a turbid water system was to concentrate DNA from a 15 mL water sample via centrifugation, purify DNA with the DNeasy mericon Food kit, and remove inhibitors with Zymo Inhibitor Removal Technology columns. Further, we compared the sensitivity of conventional PCR to quantitative PCR and found that quantitative PCR was more sensitive in detecting lower concentrations of eDNA. We show significant differences in efficiencies among methods in each step of eDNA capture, emphasizing the importance of optimizing best practices for the system of interest.

Clearing muddied waters: Capture of environmental DNA from turbid waters

PubMed Central

Huyvaert, Kathryn P.; Piaggio, Antoinette J.

2017-01-01

Understanding the differences in efficiencies of various methods to concentrate, extract, and amplify environmental DNA (eDNA) is vital for best performance of eDNA detection. Aquatic systems vary in characteristics such as turbidity, eDNA concentration, and inhibitor load, thus affecting eDNA capture efficiency. Application of eDNA techniques to the detection of terrestrial invasive or endangered species may require sampling at intermittent water sources that are used for drinking and cooling; these water bodies may often be stagnant and turbid. We present our best practices technique for the detection of wild pig eDNA in water samples, a protocol that will have wide applicability to the detection of elusive vertebrate species. We determined the best practice for eDNA capture in a turbid water system was to concentrate DNA from a 15 mL water sample via centrifugation, purify DNA with the DNeasy mericon Food kit, and remove inhibitors with Zymo Inhibitor Removal Technology columns. Further, we compared the sensitivity of conventional PCR to quantitative PCR and found that quantitative PCR was more sensitive in detecting lower concentrations of eDNA. We show significant differences in efficiencies among methods in each step of eDNA capture, emphasizing the importance of optimizing best practices for the system of interest. PMID:28686659

Aerosol detection efficiency in inductively coupled plasma mass spectrometry

DOE PAGES

Hubbard, Joshua A.; Zigmond, Joseph A.

2016-03-02

We used an electrostatic size classification technique to segregate particles of known composition prior to being injected into an inductively coupled plasma mass spectrometer (ICP-MS). Moreover, we counted size-segregated particles with a condensation nuclei counter as well as sampled with an ICP-MS. By injecting particles of known size, composition, and aerosol concentration into the ICP-MS, efficiencies of the order of magnitude aerosol detection were calculated, and the particle size dependencies for volatile and refractory species were quantified. Similar to laser ablation ICP-MS, aerosol detection efficiency was defined as the rate at which atoms were detected in the ICP-MS normalized bymore » the rate at which atoms were injected in the form of particles. This method adds valuable insight into the development of technologies like laser ablation ICP-MS where aerosol particles (of relatively unknown size and gas concentration) are generated during ablation and then transported into the plasma of an ICP-MS. In this study, we characterized aerosol detection efficiencies of volatile species gold and silver along with refractory species aluminum oxide, cerium oxide, and yttrium oxide. Aerosols were generated with electrical mobility diameters ranging from 100 to 1000 nm. In general, it was observed that refractory species had lower aerosol detection efficiencies than volatile species, and there were strong dependencies on particle size and plasma torch residence time. Volatile species showed a distinct transition point at which aerosol detection efficiency began decreasing with increasing particle size. This critical diameter indicated the largest particle size for which complete particle detection should be expected and agreed with theories published in other works. Aerosol detection efficiencies also displayed power law dependencies on particle size. Aerosol detection efficiencies ranged from 10 -5 to 10 -11. Free molecular heat and mass transfer theory was applied, but evaporative phenomena were not sufficient to explain the dependence of aerosol detection on particle diameter. Additional work is needed to correlate experimental data with theory for metal-oxides where thermodynamic property data are sparse relative to pure elements. Finally, when matrix effects and the diffusion of ions inside the plasma were considered, mass loading was concluded to have had an effect on the dependence of detection efficiency on particle diameter.« less

A simple and sensitive high-throughput GFP screening in woody and herbaceous plants.

PubMed

Hily, Jean-Michel; Liu, Zongrang

2009-03-01

Green fluorescent protein (GFP) has been used widely as a powerful bioluminescent reporter, but its visualization by existing methods in tissues or whole plants and its utilization for high-throughput screening remains challenging in many species. Here, we report a fluorescence image analyzer-based method for GFP detection and its utility for high-throughput screening of transformed plants. Of three detection methods tested, the Typhoon fluorescence scanner was able to detect GFP fluorescence in all Arabidopsis thaliana tissues and apple leaves, while regular fluorescence microscopy detected it only in Arabidopsis flowers and siliques but barely in the leaves of either Arabidopsis or apple. The hand-held UV illumination method failed in all tissues of both species. Additionally, the Typhoon imager was able to detect GFP fluorescence in both green and non-green tissues of Arabidopsis seedlings as well as in imbibed seeds, qualifying it as a high-throughput screening tool, which was further demonstrated by screening the seedlings of primary transformed T(0) seeds. Of the 30,000 germinating Arabidopsis seedlings screened, at least 69 GFP-positive lines were identified, accounting for an approximately 0.23% transformation efficiency. About 14,000 seedlings grown in 16 Petri plates could be screened within an hour, making the screening process significantly more efficient and robust than any other existing high-throughput screening method for transgenic plants.

Characterization of Fissile Assemblies Using Low-Efficiency Detection Systems

DOE PAGES

Chapline, George F.; Verbeke, Jerome M.

2017-02-02

Here, we have investigated the possibility that the amount, chemical form, multiplication, and shape of the fissile material in an assembly can be passively assayed using scintillator detection systems by only measuring the fast neutron pulse height distribution and distribution of time intervals Δt between fast neutrons. We have previously demonstrated that the alpha-ratio can be obtained from the observed pulse height distribution for fast neutrons. In this paper we report that we report that when the distribution of time intervals is plotted as a function of logΔt, the position of the correlated neutron peak is nearly independent of detectormore » efficiency and determines the internal relaxation rate for fast neutrons. If this information is combined with knowledge of the alpha-ratio, then the position of the minimum between the correlated and uncorrelated peaks can be used to rapidly estimate the mass, multiplication, and shape of fissile material. This method does not require a priori knowledge of either the efficiency for neutron detection or the alpha-ratio. Although our method neglects 3-neutron correlations, we have used previously obtained experimental data for metallic and oxide forms of Pu to demonstrate that our method yields good estimates for multiplications as large as 2, and that the only constraint on detector efficiency/observation time is that a peak in the interval time distribution due to correlated neutrons is visible.« less

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

PubMed

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

2015-05-01

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

Rapid methods for the detection of foodborne bacterial pathogens: principles, applications, advantages and limitations

PubMed Central

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

2015-01-01

The incidence of foodborne diseases has increased over the years and resulted in major public health problem globally. Foodborne pathogens can be found in various foods and it is important to detect foodborne pathogens to provide safe food supply and to prevent foodborne diseases. The conventional methods used to detect foodborne pathogen are time consuming and laborious. Hence, a variety of methods have been developed for rapid detection of foodborne pathogens as it is required in many food analyses. Rapid detection methods can be categorized into nucleic acid-based, biosensor-based and immunological-based methods. This review emphasizes on the principles and application of recent rapid methods for the detection of foodborne bacterial pathogens. Detection methods included are simple polymerase chain reaction (PCR), multiplex PCR, real-time PCR, nucleic acid sequence-based amplification (NASBA), loop-mediated isothermal amplification (LAMP) and oligonucleotide DNA microarray which classified as nucleic acid-based methods; optical, electrochemical and mass-based biosensors which classified as biosensor-based methods; enzyme-linked immunosorbent assay (ELISA) and lateral flow immunoassay which classified as immunological-based methods. In general, rapid detection methods are generally time-efficient, sensitive, specific and labor-saving. The developments of rapid detection methods are vital in prevention and treatment of foodborne diseases. PMID:25628612

Detecting Lower Bounds to Quantum Channel Capacities.

PubMed

Macchiavello, Chiara; Sacchi, Massimiliano F

2016-04-08

We propose a method to detect lower bounds to quantum capacities of a noisy quantum communication channel by means of a few measurements. The method is easily implementable and does not require any knowledge about the channel. We test its efficiency by studying its performance for most well-known single-qubit noisy channels and for the generalized Pauli channel in an arbitrary finite dimension.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Eddy current testing for blade edge micro cracks of aircraft engine

NASA Astrophysics Data System (ADS)

Zhang, Wei-min; Xu, Min-dong; Gao, Xuan-yi; Jin, Xin; Qin, Feng

2017-10-01

Based on the problems of low detection efficiency in the micro cracks detection of aircraft engine blades, a differential excitation eddy current testing system was designed and developed. The function and the working principle of the system were described, the problems which contained the manufacture method of simulated cracks, signal generating, signal processing and the signal display method were described. The detection test was carried out by taking a certain model aircraft engine blade with simulated cracks as a tested specimen. The test data was processed by digital low-pass filter in the computer and the crack signals of time domain display and Lissajous figure display were acquired. By comparing the test results, it is verified that Lissajous figure display shows better performance compared to time domain display when the crack angle is small. The test results show that the eddy current testing system designed in this paper is feasible to detect the micro cracks on the aeroengine blade and can effectively improve the detection efficiency of micro cracks in the practical detection work.

Advances in Significance Testing for Cluster Detection

NASA Astrophysics Data System (ADS)

Coleman, Deidra Andrea

Over the past two decades, much attention has been given to data driven project goals such as the Human Genome Project and the development of syndromic surveillance systems. A major component of these types of projects is analyzing the abundance of data. Detecting clusters within the data can be beneficial as it can lead to the identification of specified sequences of DNA nucleotides that are related to important biological functions or the locations of epidemics such as disease outbreaks or bioterrorism attacks. Cluster detection techniques require efficient and accurate hypothesis testing procedures. In this dissertation, we improve upon the hypothesis testing procedures for cluster detection by enhancing distributional theory and providing an alternative method for spatial cluster detection using syndromic surveillance data. In Chapter 2, we provide an efficient method to compute the exact distribution of the number and coverage of h-clumps of a collection of words. This method involves defining a Markov chain using a minimal deterministic automaton to reduce the number of states needed for computation. We allow words of the collection to contain other words of the collection making the method more general. We use our method to compute the distributions of the number and coverage of h-clumps in the Chi motif of H. influenza.. In Chapter 3, we provide an efficient algorithm to compute the exact distribution of multiple window discrete scan statistics for higher-order, multi-state Markovian sequences. This algorithm involves defining a Markov chain to efficiently keep track of probabilities needed to compute p-values of the statistic. We use our algorithm to identify cases where the available approximation does not perform well. We also use our algorithm to detect unusual clusters of made free throw shots by National Basketball Association players during the 2009-2010 regular season. In Chapter 4, we give a procedure to detect outbreaks using syndromic surveillance data while controlling the Bayesian False Discovery Rate (BFDR). The procedure entails choosing an appropriate Bayesian model that captures the spatial dependency inherent in epidemiological data and considers all days of interest, selecting a test statistic based on a chosen measure that provides the magnitude of the maximumal spatial cluster for each day, and identifying a cutoff value that controls the BFDR for rejecting the collective null hypothesis of no outbreak over a collection of days for a specified region.We use our procedure to analyze botulism-like syndrome data collected by the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT).

Detection of Shigella in Milk and Clinical Samples by Magnetic Immunocaptured-Loop-Mediated Isothermal Amplification Assay

PubMed Central

Zhang, Liding; Wei, Qiujiang; Han, Qinqin; Chen, Qiang; Tai, Wenlin; Zhang, Jinyang; Song, Yuzhu; Xia, Xueshan

2018-01-01

Shigella is an important human food-borne zoonosis bacterial pathogen, and can cause clinically severe diarrhea. There is an urgent need to develop a specific, sensitive, and rapid methodology for detection of this pathogen. In this study, loop-mediated isothermal amplification (LAMP) combined with magnetic immunocapture assay (IC-LAMP) was first developed for the detection of Shigella in pure culture, artificial milk, and clinical stool samples. This method exhibited a detection limit of 8.7 CFU/mL. Compared with polymerase chain reaction, IC-LAMP is sensitive, specific, and reliable for monitoring Shigella. Additionally, IC-LAMP is more convenient, efficient, and rapid than ordinary LAMP, as it is more efficiently enriches pathogen cells without extraction of genomic DNA. Under isothermal conditions, the amplification curves and the green fluorescence were detected within 30 min in the presence of genomic DNA template. The overall analysis time was approximately 1 h, including the enrichment and lysis of the bacterial cells, a significantly short detection time. Therefore, the IC-LAMP methodology described here is potentially useful for the efficient detection of Shigella in various samples. PMID:29467730

Neutron detection with a NaI spectrometer using high-energy photons

NASA Astrophysics Data System (ADS)

Holm, Philip; Peräjärvi, Kari; Sihvonen, Ari-Pekka; Siiskonen, Teemu; Toivonen, Harri

2013-01-01

Neutrons can be indirectly detected by high-energy photons. The performance of a 4″×4″×16″ NaI portal monitor was compared to a 3He-based portal monitor with a comparable cross-section of the active volume. Measurements were performed with bare and shielded 252Cf and AmBe sources. With an optimum converter and moderator structure for the NaI detector, the detection efficiencies and minimum detectable activities of the portal monitors were similar. The NaI portal monitor preserved its detection efficiency much better with shielded sources, making the method very interesting for security applications. For heavily shielded sources, the NaI detector was 2-3 times more sensitive than the 3He-based detector.

Novel Method For Low-Rate Ddos Attack Detection

NASA Astrophysics Data System (ADS)

Chistokhodova, A. A.; Sidorov, I. D.

2018-05-01

The relevance of the work is associated with an increasing number of advanced types of DDoS attacks, in particular, low-rate HTTP-flood. Last year, the power and complexity of such attacks increased significantly. The article is devoted to the analysis of DDoS attacks detecting methods and their modifications with the purpose of increasing the accuracy of DDoS attack detection. The article details low-rate attacks features in comparison with conventional DDoS attacks. During the analysis, significant shortcomings of the available method for detecting low-rate DDoS attacks were found. Thus, the result of the study is an informal description of a new method for detecting low-rate denial-of-service attacks. The architecture of the stand for approbation of the method is developed. At the current stage of the study, it is possible to improve the efficiency of an already existing method by using a classifier with memory, as well as additional information.

A Pulse Rate Detection Method for Mouse Application Based on Multi-PPG Sensors

PubMed Central

Chen, Wei-Hao

2017-01-01

Heart rate is an important physiological parameter for healthcare. Among measurement methods, photoplethysmography (PPG) is an easy and convenient method for pulse rate detection. However, as the PPG signal faces the challenge of motion artifacts and is constrained by the position chosen, the purpose of this paper is to implement a comfortable and easy-to-use multi-PPG sensor module combined with a stable and accurate real-time pulse rate detection method on a computer mouse. A weighted average method for multi-PPG sensors is used to adjust the weight of each signal channel in order to raise the accuracy and stability of the detected signal, therefore reducing the disturbance of noise under the environment of moving effectively and efficiently. According to the experiment results, the proposed method can increase the usability and probability of PPG signal detection on palms. PMID:28708112

Characterizations of BC501A and BC537 liquid scintillator detectors.

PubMed

Qin, Jianguo; Lai, Caifeng; Ye, Bangjiao; Liu, Rong; Zhang, Xinwei; Jiang, Li

2015-10-01

Two 2″×2″ liquid scintillator detectors BC537 and BC501A have been characterized for their responses and efficiencies to γ-ray detection. Light output resolution and response functions were derived by least-squares minimization of a simulated response function, fitted to experimental data. The γ-ray response matrix and detection efficiency were simulated with Monte Carlo (MC) methods and validated. For photon energies below 2.4 MeVee, the resolution, as well as the efficiency, of BC501A is better than BC537 scintillator. The situation is reversed when the energy is higher than 2.4 MeVee. BC537 has higher γ-ray detection efficiency than BC501A if the impinging photon energy is more than 2 MeV due to different ratios of C to H/D atoms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation of DNA extraction methods for PCR-based detection of Listeria monocytogenes from vegetables.

PubMed

Vojkovska, H; Kubikova, I; Kralik, P

2015-03-01

Epidemiological data indicate that raw vegetables are associated with outbreaks of Listeria monocytogenes. Therefore, there is a demand for the availability of rapid and sensitive methods, such as PCR assays, for the detection and accurate discrimination of L. monocytogenes. However, the efficiency of PCR methods can be negatively affected by inhibitory compounds commonly found in vegetable matrices that may cause false-negative results. Therefore, the sample processing and DNA isolation steps must be carefully evaluated prior to the introduction of such methods into routine practice. In this study, we compared the ability of three column-based and four magnetic bead-based commercial DNA isolation kits to extract DNA of the model micro-organism L. monocytogenes from raw vegetables. The DNA isolation efficiency of all isolation kits was determined using a triplex real-time qPCR assay designed to specifically detect L. monocytogenes. The kit with best performance, the PowerSoil(™) Microbial DNA Isolation Kit, is suitable for the extraction of amplifiable DNA from L. monocytogenes cells in vegetable with efficiencies ranging between 29.6 and 70.3%. Coupled with the triplex real-time qPCR assay, this DNA isolation kit is applicable to the samples with bacterial loads of 10(3) bacterial cells per gram of L. monocytogenes. Several recent outbreaks of Listeria monocytogenes have been associated with the consumption of fruits and vegetables. Real-time PCR assays allow fast detection and accurate quantification of microbes. However, the success of real-time PCR is dependent on the success with which template DNA can be extracted. The results of this study suggest that the PowerSoil(™) Microbial DNA Isolation Kit can be used for the extraction of amplifiable DNA from L. monocytogenes cells in vegetable with efficiencies ranging between 29.6 and 70.3%. This method is applicable to samples with bacterial loads of 10(3) bacterial cells per gram of L. monocytogenes. © 2014 The Society for Applied Microbiology.

A concatenated coding scheme for error control

NASA Technical Reports Server (NTRS)

Lin, S.

1985-01-01

A concatenated coding scheme for error contol in data communications was analyzed. The inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if either the inner code decoder fails to make a successful decoding or the outer code decoder detects the presence of errors after the inner code decoding. Probability of undetected error of the proposed scheme is derived. An efficient method for computing this probability is presented. Throughout efficiency of the proposed error control scheme incorporated with a selective repeat ARQ retransmission strategy is analyzed.

Saturated fatty acid determination method using paired ion electrospray ionization mass spectrometry coupled with capillary electrophoresis.

PubMed

Lee, Ji-Hyun; Kim, Su-Jin; Lee, Sul; Rhee, Jin-Kyu; Lee, Soo Young; Na, Yun-Cheol

2017-09-01

A sensitive and selective capillary electrophoresis-mass spectrometry (CE-MS) method for determination of saturated fatty acids (FAs) was developed by using dicationic ion-pairing reagents forming singly charged complexes with anionic FAs. For negative ESI detection, 21 anionic FAs at pH 10 were separated using ammonium formate buffer containing 40% acetonitrile modifier in normal polarity mode in CE by optimizing various parameters. This method showed good separation efficiency, but the sensitivity of the method to short-chain fatty acids was quite low, causing acetic and propionic acids to be undetectable even at 100 mgL -1 in negative ESI-MS detection. Out of the four dicationic ion-pairing reagents tested, N,N'-dibutyl 1,1'-pentylenedipyrrolidium infused through a sheath-liquid ion source during CE separation was the best reagent regarding improved sensitivity and favorably complexed with anionic FAs for detection in positive ion ESI-MS. The monovalent complex showed improved ionization efficiency, providing the limits of detection (LODs) for 15 FAs ranging from 0.13 to 2.88 μg/mL and good linearity (R 2  > 0.99) up to 150 μg/mL. Compared to the negative detection results, the effect was remarkable for the detection of short- and medium-chain fatty acids. The optimized CE-paired ion electrospray (PIESI)-MS method was utilized for the determination of FAs in cheese and coffee with simple pretreatment. This method may be extended for sensitive analysis of unsaturated fatty acids. Copyright © 2017 Elsevier B.V. All rights reserved.

Optical Observation, Image-processing, and Detection of Space Debris in Geosynchronous Earth Orbit

NASA Astrophysics Data System (ADS)

Oda, H.; Yanagisawa, T.; Kurosaki, H.; Tagawa, M.

2014-09-01

We report on optical observations and an efficient detection method of space debris in the geosynchronous Earth orbit (GEO). We operate our new Australia Remote Observatory (ARO) where an 18 cm optical telescope with a charged-coupled device (CCD) camera covering a 3.14-degree field of view is used for GEO debris survey, and analyse datasets of successive CCD images using the line detection method (Yanagisawa and Nakajima 2005). In our operation, the exposure time of each CCD image is set to be 3 seconds (or 5 seconds), and the time interval of CCD shutter open is about 4.7 seconds (or 6.7 seconds). In the line detection method, a sufficient number of sample objects are taken from each image based on their shape and intensity, which includes not only faint signals but also background noise (we take 500 sample objects from each image in this paper). Then we search a sequence of sample objects aligning in a straight line in the successive images to exclude the noise sample. We succeed in detecting faint signals (down to about 1.8 sigma of background noise) by applying the line detection method to 18 CCD images. As a result, we detected about 300 GEO objects up to magnitude of 15.5 among 5 nights data. We also calculate orbits of objects detected using the Simplified General Perturbations Satellite Orbit Model 4(SGP4), and identify the objects listed in the two-line-element (TLE) data catalogue publicly provided by the U.S. Strategic Command (USSTRATCOM). We found that a certain amount of our detections are new objects that are not contained in the catalogue. We conclude that our ARO and detection method posse a high efficiency detection of GEO objects despite the use of comparatively-inexpensive observation and analysis system. We also describe the image-processing specialized for the detection of GEO objects (not for usual astronomical objects like stars) in this paper.

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

Minimum Error Bounded Efficient L1 Tracker with Occlusion Detection (PREPRINT)

DTIC Science & Technology

2011-01-01

Minimum Error Bounded Efficient `1 Tracker with Occlusion Detection Xue Mei\\ ∗ Haibin Ling† Yi Wu†[ Erik Blasch‡ Li Bai] \\Assembly Test Technology...proposed BPR-L1 tracker is tested on several challenging benchmark sequences involving chal- lenges such as occlusion and illumination changes. In all...point method de - pends on the value of the regularization parameter λ. In the experiments, we found that the total number of PCG is a few hundred. The

Development of a fast and efficient method for hepatitis A virus concentration from green onion.

PubMed

Zheng, Yan; Hu, Yuan

2017-11-01

Hepatitis A virus (HAV) can cause serious liver disease and even death. HAV outbreaks are associated with the consumption of raw or minimally processed produce, making it a major public health concern. Infections have occurred despite the fact that effective HAV vaccine has been available. Development of a rapid and sensitive HAV detection method is necessary for an investigation of an HAV outbreak. Detection of HAV is complicated by the lack of a reliable culture method. In addition, due to the low infectious dose of HAV, these methods must be very sensitive. Current methods rely on efficient sample preparation and concentration steps followed by sensitive molecular detection techniques. Using green onions which was involved in most recent HAV outbreaks as a representative produce, a method of capturing virus particles was developed using carboxyl-derivatized magnetic beads in this study. Carboxyl beads, like antibody-coated beads or cationic beads, detect HAV at a level as low as 100 pfu/25g of green onions. RNA from virus concentrated in this manner can be released by heat-shock (98°C 5min) for molecular detection without sacrificing sensitivity. Bypassing the RNA extraction procedure saves time and removes multiple manipulation steps, which makes large scale HAV screening possible. In addition, the inclusion of beef extract and pectinase rather than NP40 in the elution buffer improved the HAV liberation from the food matrix over current methods by nearly 10 fold. The method proposed in this study provides a promising tool to improve food risk assessment and protect public health. Published by Elsevier B.V.

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

Preparation of paper scintillator for detecting 3H contaminant.

PubMed

Miyoshi, Hirokazu; Ikeda, Toshiji

2013-09-01

Liquid scintillator (LS)-encapsulated silica was prepared by the sol-gel method and then was added dropwise onto a wipe paper to form a paper scintillator. First, the efficiencies of wipe were determined for both the paper scintillator and the wipe paper using a liquid scintillation counter (LSC). The efficiencies of wipe using the paper scintillator and the wipe paper were 88 and 36 %, respectively. The detection efficiencies were 5.5 % for the paper scintillator, 46 % for the wipe paper using an LS and 0.08 % for the (3)H/(14)C survey meter, respectively, compared with that of a melt-on scintillator of 47 %. Second, an (3)H contaminant on the paper scintillator was successfully detected using a photomultiplier without an LSC or an (3)H/(14)C survey meter. Finally, the paper scintillator was able to detect beta rays of the (3)H contaminant easily without an LS.

Crack Damage Detection Method via Multiple Visual Features and Efficient Multi-Task Learning Model.

PubMed

Wang, Baoxian; Zhao, Weigang; Gao, Po; Zhang, Yufeng; Wang, Zhe

2018-06-02

This paper proposes an effective and efficient model for concrete crack detection. The presented work consists of two modules: multi-view image feature extraction and multi-task crack region detection. Specifically, multiple visual features (such as texture, edge, etc.) of image regions are calculated, which can suppress various background noises (such as illumination, pockmark, stripe, blurring, etc.). With the computed multiple visual features, a novel crack region detector is advocated using a multi-task learning framework, which involves restraining the variability for different crack region features and emphasizing the separability between crack region features and complex background ones. Furthermore, the extreme learning machine is utilized to construct this multi-task learning model, thereby leading to high computing efficiency and good generalization. Experimental results of the practical concrete images demonstrate that the developed algorithm can achieve favorable crack detection performance compared with traditional crack detectors.

Rapid and Efficient Method for the Detection of Microplastic in the Gastrointestinal Tract of Fishes.

PubMed

Roch, Samuel; Brinker, Alexander

2017-04-18

The rising evidence of microplastic pollution impacts on aquatic organisms in both marine and freshwater ecosystems highlights a pressing need for adequate and comparable detection methods. Available tissue digestion protocols are time-consuming (>10 h) and/or require several procedural steps, during which materials can be lost and contaminants introduced. This novel approach comprises an accelerated digestion step using sodium hydroxide and nitric acid in combination to digest all organic material within 1 h plus an additional separation step using sodium iodide which can be used to reduce mineral residues in samples where necessary. This method yielded a microplastic recovery rate of ≥95%, and all tested polymer types were recovered with only minor changes in weight, size, and color with the exception of polyamide. The method was also shown to be effective on field samples from two benthic freshwater fish species, revealing a microplastic burden comparable to that indicated in the literature. As a consequence, the present method saves time, minimizes the loss of material and the risk of contamination, and facilitates the identification of plastic particles and fibers, thus providing an efficient method to detect and quantify microplastics in the gastrointestinal tract of fishes.

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.

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

USGS Publications Warehouse

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

2007-01-01

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

A rapid and sensitive method for the simultaneous analysis of aliphatic and polar molecules containing free carboxyl groups in plant extracts by LC-MS/MS

PubMed Central

2009-01-01

Background Aliphatic molecules containing free carboxyl groups are important intermediates in many metabolic and signalling reactions, however, they accumulate to low levels in tissues and are not efficiently ionized by electrospray ionization (ESI) compared to more polar substances. Quantification of aliphatic molecules becomes therefore difficult when small amounts of tissue are available for analysis. Traditional methods for analysis of these molecules require purification or enrichment steps, which are onerous when multiple samples need to be analyzed. In contrast to aliphatic molecules, more polar substances containing free carboxyl groups such as some phytohormones are efficiently ionized by ESI and suitable for analysis by LC-MS/MS. Thus, the development of a method with which aliphatic and polar molecules -which their unmodified forms differ dramatically in their efficiencies of ionization by ESI- can be simultaneously detected with similar sensitivities would substantially simplify the analysis of complex biological matrices. Results A simple, rapid, specific and sensitive method for the simultaneous detection and quantification of free aliphatic molecules (e.g., free fatty acids (FFA)) and small polar molecules (e.g., jasmonic acid (JA), salicylic acid (SA)) containing free carboxyl groups by direct derivatization of leaf extracts with Picolinyl reagent followed by LC-MS/MS analysis is presented. The presence of the N atom in the esterified pyridine moiety allowed the efficient ionization of 25 compounds tested irrespective of their chemical structure. The method was validated by comparing the results obtained after analysis of Nicotiana attenuata leaf material with previously described analytical methods. Conclusion The method presented was used to detect 16 compounds in leaf extracts of N. attenuata plants. Importantly, the method can be adapted based on the specific analytes of interest with the only consideration that the molecules must contain at least one free carboxyl group. PMID:19939243

A Simple and Efficient Method of Extracting DNA from Aged Bones and Teeth.

PubMed

Liu, Qiqi; Liu, Liyan; Zhang, Minli; Zhang, Qingzhen; Wang, Qiong; Ding, Xiaoran; Shao, Liting; Zhou, Zhe; Wang, Shengqi

2018-05-01

DNA is often difficult to extract from old bones and teeth due to low levels of DNA and high levels of degradation. This study established a simple yet efficient method for extracting DNA from 20 aged bones and teeth (approximately 60 years old). Based on the concentration and STR typing results, the new method of DNA extraction (OM) developed in this study was compared with the PrepFiler™ BTA Forensic DNA Extraction Kit (BM). The total amount of DNA extracted using the OM method was not significantly different from that extracted using the commercial kit (p > 0.05). However, the number of STR loci detected was significantly higher in the samples processed using the OM method than using the BM method (p < 0.05). This study aimed to establish a DNA extraction method for aged bones and teeth to improve the detection rate of STR typing and reduce costs compared to the BM technique. © 2017 American Academy of Forensic Sciences.

Community detection for fluorescent lifetime microscopy image segmentation

NASA Astrophysics Data System (ADS)

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

2014-03-01

Multiresolution community detection (CD) method has been suggested in a recent work as an efficient method for performing unsupervised segmentation of fluorescence lifetime (FLT) images of live cell images containing fluorescent molecular probes.1 In the current paper, we further explore this method in FLT images of ex vivo tissue slices. The image processing problem is framed as identifying clusters with respective average FLTs against a background or "solvent" in FLT imaging microscopy (FLIM) images derived using NIR fluorescent dyes. We have identified significant multiresolution structures using replica correlations in these images, where such correlations are manifested by information theoretic overlaps of the independent solutions ("replicas") attained using the multiresolution CD method from different starting points. In this paper, our method is found to be more efficient than a current state-of-the-art image segmentation method based on mixture of Gaussian distributions. It offers more than 1:25 times diversity based on Shannon index than the latter method, in selecting clusters with distinct average FLTs in NIR FLIM images.

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.

Improved detection of multiple environmental antibiotics through an optimized sample extraction strategy in liquid chromatography-mass spectrometry analysis.

PubMed

Yi, Xinzhu; Bayen, Stéphane; Kelly, Barry C; Li, Xu; Zhou, Zhi

2015-12-01

A solid-phase extraction/liquid chromatography/electrospray ionization/multi-stage mass spectrometry (SPE-LC-ESI-MS/MS) method was optimized in this study for sensitive and simultaneous detection of multiple antibiotics in urban surface waters and soils. Among the seven classes of tested antibiotics, extraction efficiencies of macrolides, lincosamide, chloramphenicol, and polyether antibiotics were significantly improved under optimized sample extraction pH. Instead of only using acidic extraction in many existing studies, the results indicated that antibiotics with low pK a values (<7) were extracted more efficiently under acidic conditions and antibiotics with high pK a values (>7) were extracted more efficiently under neutral conditions. The effects of pH were more obvious on polar compounds than those on non-polar compounds. Optimization of extraction pH resulted in significantly improved sample recovery and better detection limits. Compared with reported values in the literature, the average reduction of minimal detection limits obtained in this study was 87.6% in surface waters (0.06-2.28 ng/L) and 67.1% in soils (0.01-18.16 ng/g dry wt). This method was subsequently applied to detect antibiotics in environmental samples in a heavily populated urban city, and macrolides, sulfonamides, and lincomycin were frequently detected. Antibiotics with highest detected concentrations were sulfamethazine (82.5 ng/L) in surface waters and erythromycin (6.6 ng/g dry wt) in soils. The optimized sample extraction strategy can be used to improve the detection of a variety of antibiotics in environmental surface waters and soils.

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

DOT National Transportation Integrated Search

2002-06-01

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

Addressing the issue of insufficient information in data-based bridge health monitoring : final report.

DOT National Transportation Integrated Search

2015-11-01

One of the most efficient ways to solve the damage detection problem using the statistical pattern recognition : approach is that of exploiting the methods of outlier analysis. Cast within the pattern recognition framework, : damage detection assesse...

A method to calculate the gamma ray detection efficiency of a cylindrical NaI (Tl) crystal

NASA Astrophysics Data System (ADS)

Ahmadi, S.; Ashrafi, S.; Yazdansetad, F.

2018-05-01

Given a wide range application of NaI(Tl) detector in industrial and medical sectors, computation of the related detection efficiency in different distances of a radioactive source, especially for calibration purposes, is the subject of radiation detection studies. In this work, a 2in both in radius and height cylindrical NaI (Tl) scintillator was used, and by changing the radial, axial, and diagonal positions of an isotropic 137Cs point source relative to the detector, the solid angles and the interaction probabilities of gamma photons with the detector's sensitive area have been calculated. The calculations present the geometric and intrinsic efficiency as the functions of detector's dimensions and the position of the source. The calculation model is in good agreement with experiment, and MCNPX simulation.

Earthquake detection through computationally efficient similarity search

PubMed Central

Yoon, Clara E.; O’Reilly, Ossian; Bergen, Karianne J.; Beroza, Gregory C.

2015-01-01

Seismology is experiencing rapid growth in the quantity of data, which has outpaced the development of processing algorithms. Earthquake detection—identification of seismic events in continuous data—is a fundamental operation for observational seismology. We developed an efficient method to detect earthquakes using waveform similarity that overcomes the disadvantages of existing detection methods. Our method, called Fingerprint And Similarity Thresholding (FAST), can analyze a week of continuous seismic waveform data in less than 2 hours, or 140 times faster than autocorrelation. FAST adapts a data mining algorithm, originally designed to identify similar audio clips within large databases; it first creates compact “fingerprints” of waveforms by extracting key discriminative features, then groups similar fingerprints together within a database to facilitate fast, scalable search for similar fingerprint pairs, and finally generates a list of earthquake detections. FAST detected most (21 of 24) cataloged earthquakes and 68 uncataloged earthquakes in 1 week of continuous data from a station located near the Calaveras Fault in central California, achieving detection performance comparable to that of autocorrelation, with some additional false detections. FAST is expected to realize its full potential when applied to extremely long duration data sets over a distributed network of seismic stations. The widespread application of FAST has the potential to aid in the discovery of unexpected seismic signals, improve seismic monitoring, and promote a greater understanding of a variety of earthquake processes. PMID:26665176

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

PubMed

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

2013-12-01

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

Joint detection and localization of multiple anatomical landmarks through learning

NASA Astrophysics Data System (ADS)

Dikmen, Mert; Zhan, Yiqiang; Zhou, Xiang Sean

2008-03-01

Reliable landmark detection in medical images provides the essential groundwork for successful automation of various open problems such as localization, segmentation, and registration of anatomical structures. In this paper, we present a learning-based system to jointly detect (is it there?) and localize (where?) multiple anatomical landmarks in medical images. The contributions of this work exist in two aspects. First, this method takes the advantage from the learning scenario that is able to automatically extract the most distinctive features for multi-landmark detection. Therefore, it is easily adaptable to detect arbitrary landmarks in various kinds of imaging modalities, e.g., CT, MRI and PET. Second, the use of multi-class/cascaded classifier architecture in different phases of the detection stage combined with robust features that are highly efficient in terms of computation time enables a seemingly real time performance, with very high localization accuracy. This method is validated on CT scans of different body sections, e.g., whole body scans, chest scans and abdominal scans. Aside from improved robustness (due to the exploitation of spatial correlations), it gains a run time efficiency in landmark detection. It also shows good scalability performance under increasing number of landmarks.

CNVcaller: highly efficient and widely applicable software for detecting copy number variations in large populations.

PubMed

Wang, Xihong; Zheng, Zhuqing; Cai, Yudong; Chen, Ting; Li, Chao; Fu, Weiwei; Jiang, Yu

2017-12-01

The increasing amount of sequencing data available for a wide variety of species can be theoretically used for detecting copy number variations (CNVs) at the population level. However, the growing sample sizes and the divergent complexity of nonhuman genomes challenge the efficiency and robustness of current human-oriented CNV detection methods. Here, we present CNVcaller, a read-depth method for discovering CNVs in population sequencing data. The computational speed of CNVcaller was 1-2 orders of magnitude faster than CNVnator and Genome STRiP for complex genomes with thousands of unmapped scaffolds. CNV detection of 232 goats required only 1.4 days on a single compute node. Additionally, the Mendelian consistency of sheep trios indicated that CNVcaller mitigated the influence of high proportions of gaps and misassembled duplications in the nonhuman reference genome assembly. Furthermore, multiple evaluations using real sheep and human data indicated that CNVcaller achieved the best accuracy and sensitivity for detecting duplications. The fast generalized detection algorithms included in CNVcaller overcome prior computational barriers for detecting CNVs in large-scale sequencing data with complex genomic structures. Therefore, CNVcaller promotes population genetic analyses of functional CNVs in more species. © The Authors 2017. Published by Oxford University Press.

CNVcaller: highly efficient and widely applicable software for detecting copy number variations in large populations

PubMed Central

Wang, Xihong; Zheng, Zhuqing; Cai, Yudong; Chen, Ting; Li, Chao; Fu, Weiwei

2017-01-01

Abstract Background The increasing amount of sequencing data available for a wide variety of species can be theoretically used for detecting copy number variations (CNVs) at the population level. However, the growing sample sizes and the divergent complexity of nonhuman genomes challenge the efficiency and robustness of current human-oriented CNV detection methods. Results Here, we present CNVcaller, a read-depth method for discovering CNVs in population sequencing data. The computational speed of CNVcaller was 1–2 orders of magnitude faster than CNVnator and Genome STRiP for complex genomes with thousands of unmapped scaffolds. CNV detection of 232 goats required only 1.4 days on a single compute node. Additionally, the Mendelian consistency of sheep trios indicated that CNVcaller mitigated the influence of high proportions of gaps and misassembled duplications in the nonhuman reference genome assembly. Furthermore, multiple evaluations using real sheep and human data indicated that CNVcaller achieved the best accuracy and sensitivity for detecting duplications. Conclusions The fast generalized detection algorithms included in CNVcaller overcome prior computational barriers for detecting CNVs in large-scale sequencing data with complex genomic structures. Therefore, CNVcaller promotes population genetic analyses of functional CNVs in more species. PMID:29220491

Enhanced light extraction of plastic scintillator using large-area photonic crystal structures fabricated by hot embossing.

PubMed

Chen, Xueye; Liu, Bo; Wu, Qiang; Zhu, Zhichao; Zhu, Jingtao; Gu, Mu; Chen, Hong; Liu, Jinliang; Chen, Liang; Ouyang, Xiaoping

2018-04-30

Plastic scintillators are widely used in various radiation measurement systems. However, detection efficiency and signal-to-noise are limited due to the total internal reflection, especially for weak signal detection situations. In the present investigation, large-area photonic crystals consisting of an array of periodic truncated cone holes were prepared based on hot embossing technology aiming at coupling with the surface of plastic scintillator to improve the light extraction efficiency and directionality control. The experimental results show that a maximum enhancement of 64% at 25° emergence angle along Γ-M orientation and a maximum enhancement of 58% at 20° emergence angle along Γ-K orientation were obtained. The proposed fabrication method of photonic crystal scintillator can avoid complicated pattern transfer processes used in most traditional methods, leading to a simple, economical method for large-area preparation. The photonic crystal scintillator demonstrated in this work is of great value for practical applications of nuclear radiation detection.

Surveying drainage culvert use by carnivores: sampling design and cost-benefit analyzes of track-pads vs. video-surveillance methods.

PubMed

Mateus, Ana Rita A; Grilo, Clara; Santos-Reis, Margarida

2011-10-01

Environmental assessment studies often evaluate the effectiveness of drainage culverts as habitat linkages for species, however, the efficiency of the sampling designs and the survey methods are not known. Our main goal was to estimate the most cost-effective monitoring method for sampling carnivore culvert using track-pads and video-surveillance. We estimated the most efficient (lower costs and high detection success) interval between visits (days) when using track-pads and also determined the advantages of using each method. In 2006, we selected two highways in southern Portugal and sampled 15 culverts over two 10-day sampling periods (spring and summer). Using the track-pad method, 90% of the animal tracks were detected using a 2-day interval between visits. We recorded a higher number of crossings for most species using video-surveillance (n = 129) when compared with the track-pad technique (n = 102); however, the detection ability using the video-surveillance method varied with type of structure and species. More crossings were detected in circular culverts (1 m and 1.5 m diameter) than in box culverts (2 m to 4 m width), likely because video cameras had a reduced vision coverage area. On the other hand, carnivore species with small feet such as the common genet Genetta genetta were detected less often using the track-pad surveying method. The cost-benefit analyzes shows that the track-pad technique is the most appropriate technique, but video-surveillance allows year-round surveys as well as the behavior response analyzes of species using crossing structures.

Herpes simplex virus mutant generation and dual-detection methods for gaining insight into latent/lytic cycles in vivo.

PubMed

Sawtell, Nancy M; Thompson, Richard L

2014-01-01

Two important components to a useful strategy to examine viral gene regulation in vivo are (1) a highly efficient protocol to generate viral mutants that limits undesired mutation and retains full replication competency in vivo and (2) an efficient system to detect and quantify viral promoter activity in rare cells in vivo. Our strategy and protocols for generating, characterizing, and employing HSV viral promoter/reporter mutants in vivo are provided in this two-part chapter.

Power-efficient method for IM-DD optical transmission of multiple OFDM signals.

PubMed

Effenberger, Frank; Liu, Xiang

2015-05-18

We propose a power-efficient method for transmitting multiple frequency-division multiplexed (FDM) orthogonal frequency-division multiplexing (OFDM) signals in intensity-modulation direct-detection (IM-DD) optical systems. This method is based on quadratic soft clipping in combination with odd-only channel mapping. We show, both analytically and experimentally, that the proposed approach is capable of improving the power efficiency by about 3 dB as compared to conventional FDM OFDM signals under practical bias conditions, making it a viable solution in applications such as optical fiber-wireless integrated systems where both IM-DD optical transmission and OFDM signaling are important.

Optical distance measurement device and method thereof

DOEpatents

Bowers, Mark W.

2003-05-27

A system and method of efficiently obtaining distance measurements of a target. A modulated optical beam may be used to determine the distance to the target. A first beam splitter may be used to split the optical beam and a second beam splitter may be used to recombine a reference beam with a return ranging beam. An optical mixing detector may be used in a receiver to efficiently detect distance measurement information.

Synthesis of amino-rich silica-coated magnetic nanoparticles for the efficient capture of DNA for PCR.

PubMed

Bai, Yalong; Cui, Yan; Paoli, George C; Shi, Chunlei; Wang, Dapeng; Zhou, Min; Zhang, Lida; Shi, Xianming

2016-09-01

Magnetic separation has great advantages over traditional bio-separation methods and has become popular in the development of methods for the detection of bacterial pathogens, viruses, and transgenic crops. Functionalization of magnetic nanoparticles is a key factor for efficient capture of the target analytes. In this paper, we report the synthesis of amino-rich silica-coated magnetic nanoparticles using a one-pot method. This type of magnetic nanoparticle has a rough surface and a higher density of amino groups than the nanoparticles prepared by a post-modification method. Furthermore, the results of hydrochloric acid treatment indicated that the magnetic nanoparticles were stably coated. The developed amino-rich silica-coated magnetic nanoparticles were used to directly adsorb DNA. After magnetic separation and blocking, the magnetic nanoparticles and DNA complexes were used directly for the polymerase chain reaction (PCR), without onerous and time-consuming purification and elution steps. The results of real-time quantitative PCR showed that the nanoparticles with higher amino group density resulted in improved DNA capture efficiency. The results suggest that amino-rich silica-coated magnetic nanoparticles are of great potential for efficient bio-separation of DNA prior to detection by PCR. Copyright © 2016. Published by Elsevier B.V.

Determination of a Limited Scope Network's Lightning Detection Efficiency

NASA Technical Reports Server (NTRS)

Rompala, John T.; Blakeslee, R.

2008-01-01

This paper outlines a modeling technique to map lightning detection efficiency variations over a region surveyed by a sparse array of ground based detectors. A reliable flash peak current distribution (PCD) for the region serves as the technique's base. This distribution is recast as an event probability distribution function. The technique then uses the PCD together with information regarding: site signal detection thresholds, type of solution algorithm used, and range attenuation; to formulate the probability that a flash at a specified location will yield a solution. Applying this technique to the full region produces detection efficiency contour maps specific to the parameters employed. These contours facilitate a comparative analysis of each parameter's effect on the network's detection efficiency. In an alternate application, this modeling technique gives an estimate of the number, strength, and distribution of events going undetected. This approach leads to a variety of event density contour maps. This application is also illustrated. The technique's base PCD can be empirical or analytical. A process for formulating an empirical PCD specific to the region and network being studied is presented. A new method for producing an analytical representation of the empirical PCD is also introduced.

Quality control of the soil moisture probe response patterns from a green infrastructure site using Dynamic Time Warping (DTW) and association rule learning

NASA Astrophysics Data System (ADS)

Yu, Z.; Bedig, A.; Quigley, M.; Montalto, F. A.

2017-12-01

In-situ field monitoring can help to improve the design and management of decentralized Green Infrastructure (GI) systems in urban areas. Because of the vast quantity of continuous data generated from multi-site sensor systems, cost-effective post-construction opportunities for real-time control are limited; and the physical processes that influence the observed phenomena (e.g. soil moisture) are hard to track and control. To derive knowledge efficiently from real-time monitoring data, there is currently a need to develop more efficient approaches to data quality control. In this paper, we employ dynamic time warping method to compare the similarity of two soil moisture patterns without ignoring the inherent autocorrelation. We also use a rule-based machine learning method to investigate the feasibility of detecting anomalous responses from soil moisture probes. The data was generated from both individual and clusters of probes, deployed in a GI site in Milwaukee, WI. In contrast to traditional QAQC methods, which seek to detect outliers at individual time steps, the new method presented here converts the continuous time series into event-based symbolic sequences from which unusual response patterns can be detected. Different Matching rules are developed on different physical characteristics for different seasons. The results suggest that this method could be used alternatively to detect sensor failure, to identify extreme events, and to call out abnormal change patterns, compared to intra-probe and inter-probe historical observations. Though this algorithm was developed for soil moisture probes, the same approach could easily be extended to advance QAQC efficiency for any continuous environmental datasets.

Application of Reverse Transcriptase -PCR (RT-PCR) for rapid detection of viable Escherichia coli in drinking water samples.

PubMed

Molaee, Neda; Abtahi, Hamid; Ghannadzadeh, Mohammad Javad; Karimi, Masoude; Ghaznavi-Rad, Ehsanollah

2015-01-01

Polymerase chain reaction (PCR) is preferred to other methods for detecting Escherichia coli (E. coli) in water in terms of speed, accuracy and efficiency. False positive result is considered as the major disadvantages of PCR. For this reason, reverse transcriptase-polymerase chain reaction (RT-PCR) can be used to solve this problem. The aim of present study was to determine the efficiency of RT-PCR for rapid detection of viable Escherichia coli in drinking water samples and enhance its sensitivity through application of different filter membranes. Specific primers were designed for 16S rRNA and elongation Factor II genes. Different concentrations of bacteria were passed through FHLP and HAWP filters. Then, RT-PCR was performed using 16srRNA and EF -Tu primers. Contamination of 10 wells was determined by RT-PCR in Arak city. To evaluate RT-PCR efficiency, the results were compared with most probable number (MPN) method. RT-PCR is able to detect bacteria in different concentrations. Application of EF II primers reduced false positive results compared to 16S rRNA primers. The FHLP hydrophobic filters have higher ability to absorb bacteria compared with HAWB hydrophilic filters. So the use of hydrophobic filters will increase the sensitivity of RT-PCR. RT-PCR shows a higher sensitivity compared to conventional water contamination detection method. Unlike PCR, RT-PCR does not lead to false positive results. The use of EF-Tu primers can reduce the incidence of false positive results. Furthermore, hydrophobic filters have a higher ability to absorb bacteria compared to hydrophilic filters.

Deriving the Contribution of Blazars to the Fermi-LAT Extragalactic γ-ray Background at E > 10 GeV with Efficiency Corrections and Photon Statistics

NASA Astrophysics Data System (ADS)

Di Mauro, M.; Manconi, S.; Zechlin, H.-S.; Ajello, M.; Charles, E.; Donato, F.

2018-04-01

The Fermi Large Area Telescope (LAT) Collaboration has recently released the Third Catalog of Hard Fermi-LAT Sources (3FHL), which contains 1556 sources detected above 10 GeV with seven years of Pass 8 data. Building upon the 3FHL results, we investigate the flux distribution of sources at high Galactic latitudes (| b| > 20^\\circ ), which are mostly blazars. We use two complementary techniques: (1) a source-detection efficiency correction method and (2) an analysis of pixel photon count statistics with the one-point probability distribution function (1pPDF). With the first method, using realistic Monte Carlo simulations of the γ-ray sky, we calculate the efficiency of the LAT to detect point sources. This enables us to find the intrinsic source-count distribution at photon fluxes down to 7.5 × 10‑12 ph cm‑2 s‑1. With this method, we detect a flux break at (3.5 ± 0.4) × 10‑11 ph cm‑2 s‑1 with a significance of at least 5.4σ. The power-law indexes of the source-count distribution above and below the break are 2.09 ± 0.04 and 1.07 ± 0.27, respectively. This result is confirmed with the 1pPDF method, which has a sensitivity reach of ∼10‑11 ph cm‑2 s‑1. Integrating the derived source-count distribution above the sensitivity of our analysis, we find that (42 ± 8)% of the extragalactic γ-ray background originates from blazars.

A Sensor System for Detection of Hull Surface Defects

PubMed Central

Navarro, Pedro; Iborra, Andrés; Fernández, Carlos; Sánchez, Pedro; Suardíaz, Juan

2010-01-01

This paper presents a sensor system for detecting defects in ship hull surfaces. The sensor was developed to enable a robotic system to perform grit blasting operations on ship hulls. To achieve this, the proposed sensor system captures images with the help of a camera and processes them in real time using a new defect detection method based on thresholding techniques. What makes this method different is its efficiency in the automatic detection of defects from images recorded in variable lighting conditions. The sensor system was tested under real conditions at a Spanish shipyard, with excellent results. PMID:22163590

Efficiency of the human observer detecting random signals in random backgrounds

PubMed Central

Park, Subok; Clarkson, Eric; Kupinski, Matthew A.; Barrett, Harrison H.

2008-01-01

The efficiencies of the human observer and the channelized-Hotelling observer relative to the ideal observer for signal-detection tasks are discussed. Both signal-known-exactly (SKE) tasks and signal-known-statistically (SKS) tasks are considered. Signal location is uncertain for the SKS tasks, and lumpy backgrounds are used for background uncertainty in both cases. Markov chain Monte Carlo methods are employed to determine ideal-observer performance on the detection tasks. Psychophysical studies are conducted to compute human-observer performance on the same tasks. Efficiency is computed as the squared ratio of the detectabilities of the observer of interest to the ideal observer. Human efficiencies are approximately 2.1% and 24%, respectively, for the SKE and SKS tasks. The results imply that human observers are not affected as much as the ideal observer by signal-location uncertainty even though the ideal observer outperforms the human observer for both tasks. Three different simplified pinhole imaging systems are simulated, and the humans and the model observers rank the systems in the same order for both the SKE and the SKS tasks. PMID:15669610

Surface Modification of Silicon Pillar Arrays To Enhance Fluorescence Detection of Uranium and DNA

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

Lincoln, Danielle R.; Charlton, Jennifer J.; Hatab, Nahla A.

There is an ever-growing need for detection methods that are both sensitive and efficient, such that reagent and sample consumption is minimized. Nanopillar arrays offer an attractive option to fill this need by virtue of their small scale in conjunction with their field enhancement intensity gains. This work investigates the use of nanopillar substrates for the detection of the uranyl ion and DNA, two analytes unalike but for their low quantum efficiencies combined with the need for high-throughput analyses. Here in this paper, the adaptability of these platforms was explored, as methods for the successful surface immobilization of both analytesmore » were developed and compared, resulting in a limit of detection for the uranyl ion of less than 1 ppm with a 0.2 μL sample volume. Moreover, differentiation between single-stranded and double-stranded DNA was possible, including qualitative identification between double-stranded DNA and DNA of the same sequence, but with a 10-base-pair mismatch.« less

[Rapid detection of hot spot mutations of FGFR3 gene with PCR-high resolution melting assay].

PubMed

Li, Shan; Wang, Han; Su, Hua; Gao, Jinsong; Zhao, Xiuli

2017-08-10

To identify the causative mutations in five individuals affected with dyschondroplasia and develop an efficient procedure for detecting hot spot mutations of the FGFR3 gene. Genomic DNA was extracted from peripheral blood samples with a standard phenol/chloroform method. PCR-Sanger sequencing was used to analyze the causative mutations in the five probands. PCR-high resolution melting (HRM) was developed to detect the identified mutations. A c.1138G>A mutation in exon 8 was found in 4 probands, while a c.1620C>G mutation was found in exon 11 of proband 5 whom had a mild phenotype. All patients were successfully distinguished from healthy controls with the PCR-HRM method. The results of HRM analysis were highly consistent with that of Sanger sequencing. The Gly380Arg and Asn540Lys are hot spot mutations of the FGFR3 gene among patients with ACH/HCH. PCR-HRM analysis is more efficient for detecting hot spot mutations of the FGFR3 gene.

Surface Modification of Silicon Pillar Arrays To Enhance Fluorescence Detection of Uranium and DNA

DOE PAGES

Lincoln, Danielle R.; Charlton, Jennifer J.; Hatab, Nahla A.; ...

2017-10-27

There is an ever-growing need for detection methods that are both sensitive and efficient, such that reagent and sample consumption is minimized. Nanopillar arrays offer an attractive option to fill this need by virtue of their small scale in conjunction with their field enhancement intensity gains. This work investigates the use of nanopillar substrates for the detection of the uranyl ion and DNA, two analytes unalike but for their low quantum efficiencies combined with the need for high-throughput analyses. Here in this paper, the adaptability of these platforms was explored, as methods for the successful surface immobilization of both analytesmore » were developed and compared, resulting in a limit of detection for the uranyl ion of less than 1 ppm with a 0.2 μL sample volume. Moreover, differentiation between single-stranded and double-stranded DNA was possible, including qualitative identification between double-stranded DNA and DNA of the same sequence, but with a 10-base-pair mismatch.« less

Efficient Device-Independent Entanglement Detection for Multipartite Systems

NASA Astrophysics Data System (ADS)

Baccari, F.; Cavalcanti, D.; Wittek, P.; Acín, A.

2017-04-01

Entanglement is one of the most studied properties of quantum mechanics for its application in quantum information protocols. Nevertheless, detecting the presence of entanglement in large multipartite states continues to be a great challenge both from the theoretical and the experimental point of view. Most of the known methods either have computational costs that scale inefficiently with the number of particles or require more information on the state than what is attainable in everyday experiments. We introduce a new technique for entanglement detection that provides several important advantages in these respects. First, it scales efficiently with the number of particles, thus allowing for application to systems composed by up to few tens of particles. Second, it needs only the knowledge of a subset of all possible measurements on the state, therefore being apt for experimental implementation. Moreover, since it is based on the detection of nonlocality, our method is device independent. We report several examples of its implementation for well-known multipartite states, showing that the introduced technique has a promising range of applications.

Utilizing a CdTe quantum dots-enzyme hybrid system for the determination of both phenolic compounds and hydrogen peroxide.

PubMed

Yuan, Jipei; Guo, Weiwei; Wang, Erkang

2008-02-15

In this paper, we attempt to construct a simple and sensitive detection method for both phenolic compounds and hydrogen peroxide, with the successful combination of the unique property of quantum dots and the specificity of enzymatic reactions. In the presence of H2O2 and horseradish peroxidase, phenolic compounds can quench quantum dots' photoluminescence efficiently, and the extent of quenching is severalfold to more than 100-fold increase. Quinone intermediates produced from the enzymatic catalyzed oxidation of phenolic compounds were believed to play the main role in the photoluminescence quenching. Using a quantum dots-enzyme system, the detection limits for phenolic compounds and hydrogen peroxide were detected to be approximately 10(-7) mol L(-1). The coupling of efficient quenching of quantum dot photoluminescence by quinone and the effective enzymatic reactions make this a simple and sensitive method for phenolic compound detection and great potential in the development of H2O2 biosensors for various analytes.

Planetary-scale surface water detection from space

NASA Astrophysics Data System (ADS)

Donchyts, G.; Baart, F.; Winsemius, H.; Gorelick, N.

2017-12-01

Accurate, efficient and high-resolution methods of surface water detection are needed for a better water management. Datasets on surface water extent and dynamics are crucial for a better understanding of natural and human-made processes, and as an input data for hydrological and hydraulic models. In spite of considerable progress in the harmonization of freely available satellite data, producing accurate and efficient higher-level surface water data products remains very challenging. This presentation will provide an overview of existing methods for surface water extent and change detection from multitemporal and multi-sensor satellite imagery. An algorithm to detect surface water changes from multi-temporal satellite imagery will be demonstrated as well as its open-source implementation (http://aqua-monitor.deltares.nl). This algorithm was used to estimate global surface water changes at high spatial resolution. These changes include climate change, land reclamation, reservoir construction/decommissioning, erosion/accretion, and many other. This presentation will demonstrate how open satellite data and open platforms such as Google Earth Engine have helped with this research.

Carboxylated multiwalled carbon nanotubes/polydimethylsiloxane, a new coating for 96-blade solid-phase microextraction for determination of phenolic compounds in water.

PubMed

Kueseng, Pamornrat; Pawliszyn, Janusz

2013-11-22

A new thin-film, carboxylated multiwalled carbon nanotubes/polydimethylsiloxane (MWCNTs-COOH/PDMS) coating was developed for 96-blade solid-phase microextraction (SPME) system followed by high performance liquid chromatography with ultraviolet detection (HPLC-UV). The method provided good extraction efficiency (64-90%) for three spiked levels, with relative standard deviations (RSD)≤6%, and detection limits between 1 and 2 μg/L for three phenolic compounds. The MWCNTs-COOH/PDMS 96-blade SPME system presents advantages over traditional methods due to its simplicity of use, easy coating preparation, low cost and high sample throughput (2.1 min per sample). The developed coating is reusable for a minimum of 110 extractions with good extraction efficiency. The coating provided higher extraction efficiency (3-8 times greater) than pure PDMS coatings. Copyright © 2013 Elsevier B.V. All rights reserved.

Research on the self-absorption corrections for PGNAA of large samples

NASA Astrophysics Data System (ADS)

Yang, Jian-Bo; Liu, Zhi; Chang, Kang; Li, Rui

2017-02-01

When a large sample is analysed with the prompt gamma neutron activation analysis (PGNAA) neutron self-shielding and gamma self-absorption affect the accuracy, the correction method for the detection efficiency of the relative H of each element in a large sample is described. The influences of the thickness and density of the cement samples on the H detection efficiency, as well as the impurities Fe2O3 and SiO2 on the prompt γ ray yield for each element in the cement samples, were studied. The phase functions for Ca, Fe, and Si on H with changes in sample thickness and density were provided to avoid complicated procedures for preparing the corresponding density or thickness scale for measuring samples under each density or thickness value and to present a simplified method for the measurement efficiency scale for prompt-gamma neutron activation analysis.

Decision support system for the detection and grading of hard exudates from color fundus photographs

NASA Astrophysics Data System (ADS)

Jaafar, Hussain F.; Nandi, Asoke K.; Al-Nuaimy, Waleed

2011-11-01

Diabetic retinopathy is a major cause of blindness, and its earliest signs include damage to the blood vessels and the formation of lesions in the retina. Automated detection and grading of hard exudates from the color fundus image is a critical step in the automated screening system for diabetic retinopathy. We propose novel methods for the detection and grading of hard exudates and the main retinal structures. For exudate detection, a novel approach based on coarse-to-fine strategy and a new image-splitting method are proposed with overall sensitivity of 93.2% and positive predictive value of 83.7% at the pixel level. The average sensitivity of the blood vessel detection is 85%, and the success rate of fovea localization is 100%. For exudate grading, a polar fovea coordinate system is adopted in accordance with medical criteria. Because of its competitive performance and ability to deal efficiently with images of variable quality, the proposed technique offers promising and efficient performance as part of an automated screening system for diabetic retinopathy.

Multiview face detection based on position estimation over multicamera surveillance system

NASA Astrophysics Data System (ADS)

Huang, Ching-chun; Chou, Jay; Shiu, Jia-Hou; Wang, Sheng-Jyh

2012-02-01

In this paper, we propose a multi-view face detection system that locates head positions and indicates the direction of each face in 3-D space over a multi-camera surveillance system. To locate 3-D head positions, conventional methods relied on face detection in 2-D images and projected the face regions back to 3-D space for correspondence. However, the inevitable false face detection and rejection usually degrades the system performance. Instead, our system searches for the heads and face directions over the 3-D space using a sliding cube. Each searched 3-D cube is projected onto the 2-D camera views to determine the existence and direction of human faces. Moreover, a pre-process to estimate the locations of candidate targets is illustrated to speed-up the searching process over the 3-D space. In summary, our proposed method can efficiently fuse multi-camera information and suppress the ambiguity caused by detection errors. Our evaluation shows that the proposed approach can efficiently indicate the head position and face direction on real video sequences even under serious occlusion.

Gold Nanoparticle-Based Facile Detection of Human Serum Albumin and Its Application as an INHIBIT Logic Gate.

PubMed

Huang, Zhenzhen; Wang, Haonan; Yang, Wensheng

2015-05-06

In this work, a facile colorimetric method is developed for quantitative detection of human serum albumin (HSA) based on the antiaggregation effect of gold nanoparticles (Au NPs) in the presence of HSA. The citrate-capped Au NPs undergo a color change from red to blue when melamine is added as a cross-linker to induce the aggregation of the NPs. Such an aggregation is efficiently suppressed upon the adsorption of HSA on the particle surface. This method provides the advantages of simplicity and cost-efficiency for quantitative detection of HSA with a detection limit of ∼1.4 nM by monitoring the colorimetric changes of the Au NPs with UV-vis spectroscopy. In addition, this approach shows good selectivity for HSA over various amino acids, peptides, and proteins and is qualified for detection of HSA in a biological sample. Such an antiaggregation effect can be further extended to fabricate an INHIBIT logic gate by using HSA and melamine as inputs and the color changes of Au NPs as outputs, which may have application potentials in point-of-care medical diagnosis.

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-05-01

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

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-09-01

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

What percentage of the Cuban HIV-AIDS epidemic is known?

PubMed

de Arazoza, Héctor; Lounes, Rachid; Pérez, Jorge; Hoang, Thu

2003-01-01

The data for the Cuban HIV-AIDS epidemic from 1986 to 2000 were presented. With the purpose of evaluating the efficiency of the HIV detection system, two methods were used to estimate the size of the HIV-infected population, backcalculation and a dynamical model. From these models it can be estimated that in the worst scenario 75% of the HIV-infected persons are known and in the best case 87% of the total number of persons that have been infected with HIV have been detected by the National Program. These estimates can be taken as a measure of the efficiency of the detection program for HIV-infected persons.

Infrared target tracking via weighted correlation filter

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

A NEW METHOD FOR FINDING POINT SOURCES IN HIGH-ENERGY NEUTRINO DATA

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

Fang, Ke; Miller, M. Coleman

The IceCube collaboration has reported the first detection of high-energy astrophysical neutrinos, including ∼50 high-energy starting events, but no individual sources have been identified. It is therefore important to develop the most sensitive and efficient possible algorithms to identify the point sources of these neutrinos. The most popular current method works by exploring a dense grid of possible directions to individual sources, and identifying the single direction with the maximum probability of having produced multiple detected neutrinos. This method has numerous strengths, but it is computationally intensive and because it focuses on the single best location for a point source,more » additional point sources are not included in the evidence. We propose a new maximum likelihood method that uses the angular separations between all pairs of neutrinos in the data. Unlike existing autocorrelation methods for this type of analysis, which also use angular separations between neutrino pairs, our method incorporates information about the point-spread function and can identify individual point sources. We find that if the angular resolution is a few degrees or better, then this approach reduces both false positive and false negative errors compared to the current method, and is also more computationally efficient up to, potentially, hundreds of thousands of detected neutrinos.« less

An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method

PubMed Central

Devasenapathy, Deepa; Kannan, Kathiravan

2015-01-01

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate. PMID:25793221

An energy-efficient cluster-based vehicle detection on road network using intention numeration method.

PubMed

Devasenapathy, Deepa; Kannan, Kathiravan

2015-01-01

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

Evaluation of seven aquatic sampling methods for amphibians and other aquatic fauna

USGS Publications Warehouse

Gunzburger, M.S.

2007-01-01

To design effective and efficient research and monitoring programs researchers must have a thorough understanding of the capabilities and limitations of their sampling methods. Few direct comparative studies exist for aquatic sampling methods for amphibians. The objective of this study was to simultaneously employ seven aquatic sampling methods in 10 wetlands to compare amphibian species richness and number of individuals detected with each method. Four sampling methods allowed counts of individuals (metal dipnet, D-frame dipnet, box trap, crayfish trap), whereas the other three methods allowed detection of species (visual encounter, aural, and froglogger). Amphibian species richness was greatest with froglogger, box trap, and aural samples. For anuran species, the sampling methods by which each life stage was detected was related to relative length of larval and breeding periods and tadpole size. Detection probability of amphibians varied across sampling methods. Box trap sampling resulted in the most precise amphibian count, but the precision of all four count-based methods was low (coefficient of variation > 145 for all methods). The efficacy of the four count sampling methods at sampling fish and aquatic invertebrates was also analyzed because these predatory taxa are known to be important predictors of amphibian habitat distribution. Species richness and counts were similar for fish with the four methods, whereas invertebrate species richness and counts were greatest in box traps. An effective wetland amphibian monitoring program in the southeastern United States should include multiple sampling methods to obtain the most accurate assessment of species community composition at each site. The combined use of frogloggers, crayfish traps, and dipnets may be the most efficient and effective amphibian monitoring protocol. ?? 2007 Brill Academic Publishers.

A superhydrophobic cone to facilitate the xenomonitoring of filarial parasites, malaria, and trypanosomes using mosquito excreta/feces.

PubMed

Cook, Darren A N; Pilotte, Nils; Minetti, Corrado; Williams, Steven A; Reimer, Lisa J

2017-11-06

Background: Molecular xenomonitoring (MX), the testing of insect vectors for the presence of human pathogens, has the potential to provide a non-invasive and cost-effective method for monitoring the prevalence of disease within a community. Current MX methods require the capture and processing of large numbers of mosquitoes, particularly in areas of low endemicity, increasing the time, cost and labour required. Screening the excreta/feces (E/F) released from mosquitoes, rather than whole carcasses, improves the throughput by removing the need to discriminate vector species since non-vectors release ingested pathogens in E/F. It also enables larger numbers of mosquitoes to be processed per pool. However, this new screening approach requires a method of efficiently collecting E/F. Methods: We developed a cone with a superhydrophobic surface to allow for the efficient collection of E/F. Using mosquitoes exposed to either Plasmodium falciparum , Brugia malayi or Trypanosoma brucei brucei, we tested the performance of the superhydrophobic cone alongside two other collection methods. Results: All collection methods enabled the detection of DNA from the three parasites. Using the superhydrophobic cone to deposit E/F into a small tube provided the highest number of positive samples (16 out of 18) and facilitated detection of parasite DNA in E/F from individual mosquitoes. Further tests showed that following a simple washing step, the cone can be reused multiple times, further improving its cost-effectiveness. Conclusions: Incorporating the superhydrophobic cone into mosquito traps or holding containers could provide a simple and efficient method for collecting E/F. Where this is not possible, swabbing the container or using the washing method facilitates the detection of the three parasites used in this study.

Detecting Signage and Doors for Blind Navigation and Wayfinding

PubMed Central

Wang, Shuihua; Yang, Xiaodong; Tian, Yingli

2013-01-01

Signage plays a very important role to find destinations in applications of navigation and wayfinding. In this paper, we propose a novel framework to detect doors and signage to help blind people accessing unfamiliar indoor environments. In order to eliminate the interference information and improve the accuracy of signage detection, we first extract the attended areas by using a saliency map. Then the signage is detected in the attended areas by using a bipartite graph matching. The proposed method can handle multiple signage detection. Furthermore, in order to provide more information for blind users to access the area associated with the detected signage, we develop a robust method to detect doors based on a geometric door frame model which is independent to door appearances. Experimental results on our collected datasets of indoor signage and doors demonstrate the effectiveness and efficiency of our proposed method. PMID:23914345

Detecting Signage and Doors for Blind Navigation and Wayfinding.

PubMed

Wang, Shuihua; Yang, Xiaodong; Tian, Yingli

2013-07-01

Signage plays a very important role to find destinations in applications of navigation and wayfinding. In this paper, we propose a novel framework to detect doors and signage to help blind people accessing unfamiliar indoor environments. In order to eliminate the interference information and improve the accuracy of signage detection, we first extract the attended areas by using a saliency map. Then the signage is detected in the attended areas by using a bipartite graph matching. The proposed method can handle multiple signage detection. Furthermore, in order to provide more information for blind users to access the area associated with the detected signage, we develop a robust method to detect doors based on a geometric door frame model which is independent to door appearances. Experimental results on our collected datasets of indoor signage and doors demonstrate the effectiveness and efficiency of our proposed method.

Love-Wave Sensors Combined with Microfluidics for Fast Detection of Biological Warfare Agents

PubMed Central

Matatagui, Daniel; Fontecha, José Luis; Fernández, María Jesús; Gràcia, Isabel; Cané, Carles; Santos, José Pedro; Horrillo, María Carmen

2014-01-01

The following paper examines a time-efficient method for detecting biological warfare agents (BWAs). The method is based on a system of a Love-wave immunosensor combined with a microfluidic chip which detects BWA samples in a dynamic mode. In this way a continuous flow-through of the sample is created, promoting the reaction between antigen and antibody and allowing a fast detection of the BWAs. In order to prove this method, static and dynamic modes have been simulated and different concentrations of BWA simulants have been tested with two immunoreactions: phage M13 has been detected using the mouse monoclonal antibody anti-M13 (AM13), and the rabbit immunoglobulin (Rabbit IgG) has been detected using the polyclonal antibody goat anti-rabbit (GAR). Finally, different concentrations of each BWA simulants have been detected with a fast response time and a desirable level of discrimination among them has been achieved. PMID:25029282

Position sensitive radioactivity detection for gas and liquid chromatography

DOEpatents

Cochran, Joseph L.; McCarthy, John F.; Palumbo, Anthony V.; Phelps, Tommy J.

2001-01-01

A method and apparatus are provided for the position sensitive detection of radioactivity in a fluid stream, particularly in the effluent fluid stream from a gas or liquid chromatographic instrument. The invention represents a significant advance in efficiency and cost reduction compared with current efforts.

Multi-Objective Community Detection Based on Memetic Algorithm

PubMed Central

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646

Multi-objective community detection based on memetic algorithm.

PubMed

Wu, Peng; Pan, Li

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.

High-energy X-ray detection by hafnium-doped organic-inorganic hybrid scintillators prepared by sol-gel method

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

Sun, Yan; Koshimizu, Masanori, E-mail: koshi@qpc.che.tohoku.ac.jp; Yahaba, Natsuna

2014-04-28

With the aim of enhancing the efficiency with which plastic scintillators detect high-energy X-rays, hafnium-doped organic-inorganic hybrid scintillators were fabricated via a sol-gel method. Transmission electron microscopy of sampled material reveals the presence of Hf{sub x}Si{sub 1−x}O{sub 2} nanoparticles, dispersed in a polymer matrix that constitutes the active material of the X-ray detector. With Hf{sub x}Si{sub 1−x}O{sub 2} nanoparticles incorporated in the polymer matrix, the absorption edge and the luminescence wavelength is shifted, which we attribute to Mie scattering. The detection efficiency for 67.4-keV X-rays in a 0.6-mm-thick piece of this material is two times better than the same thicknessmore » of a commercial plastic scintillator-NE142.« less

Enhanced speed in fluorescence imaging using beat frequency multiplexing

NASA Astrophysics Data System (ADS)

Mikami, Hideharu; Kobayashi, Hirofumi; Wang, Yisen; Hamad, Syed; Ozeki, Yasuyuki; Goda, Keisuke

2016-03-01

Fluorescence imaging using radiofrequency-tagged emission (FIRE) is an emerging technique that enables higher imaging speed (namely, temporal resolution) in fluorescence microscopy compared to conventional fluorescence imaging techniques such as confocal microscopy and wide-field microscopy. It works based on the principle that it uses multiple intensity-modulated fields in an interferometric setup as excitation fields and applies frequency-division multiplexing to fluorescence signals. Unfortunately, despite its high potential, FIRE has limited imaging speed due to two practical limitations: signal bandwidth and signal detection efficiency. The signal bandwidth is limited by that of an acousto-optic deflector (AOD) employed in the setup, which is typically 100-200 MHz for the spectral range of fluorescence excitation (400-600 nm). The signal detection efficiency is limited by poor spatial mode-matching between two interfering fields to produce a modulated excitation field. Here we present a method to overcome these limitations and thus to achieve higher imaging speed than the prior version of FIRE. Our method achieves an increase in signal bandwidth by a factor of two and nearly optimal mode matching, which enables the imaging speed limited by the lifetime of the target fluorophore rather than the imaging system itself. The higher bandwidth and better signal detection efficiency work synergistically because higher bandwidth requires higher signal levels to avoid the contribution of shot noise and amplifier noise to the fluorescence signal. Due to its unprecedentedly high-speed performance, our method has a wide variety of applications in cancer detection, drug discovery, and regenerative medicine.

Unique blood culture for diagnosis of bloodstream infections in emergency departments: a prospective multicentre study.

PubMed

Dargère, S; Parienti, J-J; Roupie, E; Gancel, P-E; Wiel, E; Smaiti, N; Loiez, C; Joly, L-M; Lemée, L; Pestel-Caron, M; du Cheyron, D; Verdon, R; Leclercq, R; Cattoir, V

2014-11-01

Detection of microorganisms by blood cultures (BCs) is essential in managing patients with bacteraemia. Rather than the number of punctures, the volume of blood drawn is considered paramount in efficient and reliable detection of microorganisms. We performed a 1-year prospective multicentre study in adult emergency departments of three French university hospitals comparing two methods for BCs: a unique blood culture (UBC) collecting a large volume of blood (40 mL) and the standard method of multiple blood cultures (MBC). The performances of both methods for bacterial contamination and efficient microbial detection were compared, each patient serving as his own control. Amongst the 2314 patients included, three hundred were positive for pathogens (n=245) or contaminants (n=55). Out of the 245 patients, 11 were positive for pathogens by UBC but negative by MBC and seven negative by UBC but positive by MBC (p 0.480). In the subgroup of 137 patients with only two BCs, UBC was superior to MBC (p 0.044). Seven and 17 patients had contaminated BCs by UBC and MBC only, respectively (p 0.062). Considering the sums of pathogens missed and contaminants, UBC significantly outperformed MBC (p 0.045). Considering the complete picture of cost savings, efficient detection of microorganisms and decrease in contaminations, UBC offers an interesting alternative to MBC. © 2014 The Authors Clinical Microbiology and Infection © 2014 European Society of Clinical Microbiology and Infectious Diseases.

Addition of Carbon to the Culture Medium Improves the Detection Efficiency of Aflatoxin Synthetic Fungi

PubMed Central

Suzuki, Tadahiro; Iwahashi, Yumiko

2016-01-01

Aflatoxin (AF) is a harmful secondary metabolite that is synthesized by the Aspergillus species. Although AF detection techniques have been developed, techniques for detection of AF synthetic fungi are still required. Techniques such as plate culture methods are continually being modified for this purpose. However, plate culture methods require refinement because they suffer from several issues. In this study, activated charcoal powder (carbon) was added to a culture medium containing cyclodextrin (CD) to enhance the contrast of fluorescence and improve the detection efficiency for AF synthetic fungi. Two culture media, potato dextrose agar and yeast extract sucrose agar, were investigated using both plate and liquid cultures. The final concentrations of CD and carbon in the media were 3 mg/mL and 0.3 mg/mL, respectively. Addition of carbon improved the visibility of fluorescence by attenuating approximately 30% of light scattering. Several fungi that could not be detected with only CD in the medium were detected with carbon addition. The carbon also facilitated fungal growth in the potato dextrose liquid medium. The results suggest that addition of carbon to media can enhance the observation of AF-derived fluorescence. PMID:27854283

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.

Location of Biomarkers and Reagents within Agarose Beads of a Programmable Bio-nano-chip

PubMed Central

Jokerst, Jesse V.; Chou, Jie; Camp, James P.; Wong, Jorge; Lennart, Alexis; Pollard, Amanda A.; Floriano, Pierre N.; Christodoulides, Nicolaos; Simmons, Glennon W.; Zhou, Yanjie; Ali, Mehnaaz F.

2012-01-01

The slow development of cost-effective medical microdevices with strong analytical performance characteristics is due to a lack of selective and efficient analyte capture and signaling. The recently developed programmable bio-nano-chip (PBNC) is a flexible detection device with analytical behavior rivaling established macroscopic methods. The PBNC system employs ≈300 μm-diameter bead sensors composed of agarose “nanonets” that populate a microelectromechanical support structure with integrated microfluidic elements. The beads are an efficient and selective protein-capture medium suitable for the analysis of complex fluid samples. Microscopy and computational studies probe the 3D interior of the beads. The relative contributions that the capture and detection of moieties, analyte size, and bead porosity make to signal distribution and intensity are reported. Agarose pore sizes ranging from 45 to 620 nm are examined and those near 140 nm provide optimal transport characteristics for rapid (<15 min) tests. The system exhibits efficient (99.5%) detection of bead-bound analyte along with low (≈2%) nonspecific immobilization of the detection probe for carcinoembryonic antigen assay. Furthermore, the role analyte dimensions play in signal distribution is explored, and enhanced methods for assay building that consider the unique features of biomarker size are offered. PMID:21290601

The Cluster AgeS Experiment (CASE). Detecting Aperiodic Photometric Variability with the Friends of Friends Algorithm

NASA Astrophysics Data System (ADS)

Rozyczka, M.; Narloch, W.; Pietrukowicz, P.; Thompson, I. B.; Pych, W.; Poleski, R.

2018-03-01

We adapt the friends of friends algorithm to the analysis of light curves, and show that it can be succesfully applied to searches for transient phenomena in large photometric databases. As a test case we search OGLE-III light curves for known dwarf novae. A single combination of control parameters allows us to narrow the search to 1% of the data while reaching a ≍90% detection efficiency. A search involving ≍2% of the data and three combinations of control parameters can be significantly more effective - in our case a 100% efficiency is reached. The method can also quite efficiently detect semi-regular variability. In particular, 28 new semi-regular variables have been found in the field of the globular cluster M22, which was examined earlier with the help of periodicity-searching algorithms.

Semi-automating the manual literature search for systematic reviews increases efficiency.

PubMed

Chapman, Andrea L; Morgan, Laura C; Gartlehner, Gerald

2010-03-01

To minimise retrieval bias, manual literature searches are a key part of the search process of any systematic review. Considering the need to have accurate information, valid results of the manual literature search are essential to ensure scientific standards; likewise efficient approaches that minimise the amount of personnel time required to conduct a manual literature search are of great interest. The objective of this project was to determine the validity and efficiency of a new manual search method that utilises the scopus database. We used the traditional manual search approach as the gold standard to determine the validity and efficiency of the proposed scopus method. Outcome measures included completeness of article detection and personnel time involved. Using both methods independently, we compared the results based on accuracy of the results, validity and time spent conducting the search, efficiency. Regarding accuracy, the scopus method identified the same studies as the traditional approach indicating its validity. In terms of efficiency, using scopus led to a time saving of 62.5% compared with the traditional approach (3 h versus 8 h). The scopus method can significantly improve the efficiency of manual searches and thus of systematic reviews.

Detection limits of Legionella pneumophila in environmental samples after co-culture with Acanthamoeba polyphaga

PubMed Central

2013-01-01

Background The efficiency of recovery and the detection limit of Legionella after co-culture with Acanthamoeba polyphaga are not known and so far no investigations have been carried out to determine the efficiency of the recovery of Legionella spp. by co-culture and compare it with that of conventional culturing methods. This study aimed to assess the detection limits of co-culture compared to culture for Legionella pneumophila in compost and air samples. Compost and air samples were spiked with known concentrations of L. pneumophila. Direct culturing and co-culture with amoebae were used in parallel to isolate L. pneumophila and recovery standard curves for both methods were produced for each sample. Results The co-culture proved to be more sensitive than the reference method, detecting 102-103 L. pneumophila cells in 1 g of spiked compost or 1 m3 of spiked air, as compared to 105-106 cells in 1 g of spiked compost and 1 m3 of spiked air. Conclusions Co-culture with amoebae is a useful, sensitive and reliable technique to enrich L. pneumophila in environmental samples that contain only low amounts of bacterial cells. PMID:23442526

Detecting communities in large networks

NASA Astrophysics Data System (ADS)

Capocci, A.; Servedio, V. D. P.; Caldarelli, G.; Colaiori, F.

2005-07-01

We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.

X-ray detection capabilities of plastic scintillators incorporated with hafnium oxide nanoparticles surface-modified with phenyl propionic acid

NASA Astrophysics Data System (ADS)

Hiyama, Fumiyuki; Noguchi, Takio; Koshimizu, Masanori; Kishimoto, Shunji; Haruki, Rie; Nishikido, Fumihiko; Yanagida, Takayuki; Fujimoto, Yutaka; Aida, Tsutomu; Takami, Seiichi; Adschiri, Tadafumi; Asai, Keisuke

2018-01-01

We synthesized plastic scintillators incorporated with HfO2 nanoparticles as detectors for X-ray synchrotron radiation. Nanoparticles with sizes of less than 10 nm were synthesized with the subcritical hydrothermal method. The detection efficiency of high-energy X-ray photons improved by up to 3.3 times because of the addition of the nanoparticles. Nanosecond time resolution was successfully achieved for all the scintillators. These results indicate that this method is applicable for the preparation of plastic scintillators to detect X-ray synchrotron radiation.

Nonparametric method for failures detection and localization in the actuating subsystem of aircraft control system

NASA Astrophysics Data System (ADS)

Karpenko, S. S.; Zybin, E. Yu; Kosyanchuk, V. V.

2018-02-01

In this paper we design a nonparametric method for failures detection and localization in the aircraft control system that uses the measurements of the control signals and the aircraft states only. It doesn’t require a priori information of the aircraft model parameters, training or statistical calculations, and is based on algebraic solvability conditions for the aircraft model identification problem. This makes it possible to significantly increase the efficiency of detection and localization problem solution by completely eliminating errors, associated with aircraft model uncertainties.

DETECTORS AND EXPERIMENTAL METHODS: Measurement of the response function and the detection efficiency of an organic liquid scintillator for neutrons between 1 and 30 MeV

NASA Astrophysics Data System (ADS)

Huang, Han-Xiong; Ruan, Xi-Chao; Chen, Guo-Chang; Zhou, Zu-Ying; Li, Xia; Bao, Jie; Nie, Yang-Bo; Zhong, Qi-Ping

2009-08-01

The light output function of a varphi50.8 mm × 50.8 mm BC501A scintillation detector was measured in the neutron energy region of 1 to 30 MeV by fitting the pulse height (PH) spectra for neutrons with the simulations from the NRESP code at the edge range. Using the new light output function, the neutron detection efficiency was determined with two Monte-Carlo codes, NEFF and SCINFUL. The calculated efficiency was corrected by comparing the simulated PH spectra with the measured ones. The determined efficiency was verified at the near threshold region and normalized with a Proton-Recoil-Telescope (PRT) at the 8-14 MeV energy region.

Detection of ESBL among ampc producing enterobacteriaceae using inhibitor-based method

PubMed Central

Bakthavatchalu, Sasirekha; Shakthivel, Uma; Mishra, Tannu

2013-01-01

Introduction The occurrence of multiple β-lactamases among bacteria only limits the therapeutic options but also poses a challenge. A study using boronic acid (BA), an AmpC enzyme inhibitor, was designed to detect the combined expression of AmpC β-lactamases and extended-spectrum β-lactamases (ESBLs) in bacterial isolates further different phenotypic methods are compared to detect ESBL and AmpC. Methods A total of 259 clinical isolates of Enterobacteriaceae were isolated and screened for ESBL production by (i) CLSI double-disk diffusion method (ii) cefepime- clavulanic acid method (iii) boronic disk potentiation method. AmpC production was detected using cefoxitin alone and in combination with boronic acid and confirmation was done by three dimensional disk methods. Isolates were also subjected to detailed antibiotic susceptibility test. Results Among 259 isolates, 20.46% were coproducers of ESBL and AmpC, 26.45% were ESBL and 5.40% were AmpC. All of the 53 AmpC and ESBL coproducers were accurately detected by boronic acid disk potentiation method. Conclusion The BA disk test using Clinical and Laboratory Standards Institute methodology is simple and very efficient method that accurately detects the isolates that harbor both AmpCs and ESBLs. PMID:23504148

Multiplex surface plasmon resonance imaging platform for label-free detection of foodborne pathogens

USDA-ARS?s Scientific Manuscript database

Salmonellae are among the leading causes of foodborne outbreaks in the United States, and more rapid and efficient detection methods are needed. Surface plasmon resonance imaging (SPRi) is an emerging optical technique, which allows for rapid and label-free screening of multiple targets simultaneous...

Surface plasmon resonance imaging for label-free detection of foodborne pathogens and toxins

USDA-ARS?s Scientific Manuscript database

More rapid and efficient detection methods for foodborne pathogenic bacteria and toxins are needed to address the long assay time and limitations in multiplex capacity. Surface plasmon resonance imaging (SPRi) is an emerging optical technique, which allows for rapid and label-free screening of multi...

ConvNetQuake: Convolutional Neural Network for Earthquake Detection and Location

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Integrated software for the detection of epileptogenic zones in refractory epilepsy.

PubMed

Mottini, Alejandro; Miceli, Franco; Albin, Germán; Nuñez, Margarita; Ferrándo, Rodolfo; Aguerrebere, Cecilia; Fernandez, Alicia

2010-01-01

In this paper we present an integrated software designed to help nuclear medicine physicians in the detection of epileptogenic zones (EZ) by means of ictal-interictal SPECT and MR images. This tool was designed to be flexible, friendly and efficient. A novel detection method was included (A-contrario) along with the classical detection method (Subtraction analysis). The software's performance was evaluated with two separate sets of validation studies: visual interpretation of 12 patient images by an experimented observer and objective analysis of virtual brain phantom experiments by proposed numerical observers. Our results support the potential use of the proposed software to help nuclear medicine physicians in the detection of EZ in clinical practice.

Efficient video-equipped fire detection approach for automatic fire alarm systems

NASA Astrophysics Data System (ADS)

Kang, Myeongsu; Tung, Truong Xuan; Kim, Jong-Myon

2013-01-01

This paper proposes an efficient four-stage approach that automatically detects fire using video capabilities. In the first stage, an approximate median method is used to detect video frame regions involving motion. In the second stage, a fuzzy c-means-based clustering algorithm is employed to extract candidate regions of fire from all of the movement-containing regions. In the third stage, a gray level co-occurrence matrix is used to extract texture parameters by tracking red-colored objects in the candidate regions. These texture features are, subsequently, used as inputs of a back-propagation neural network to distinguish between fire and nonfire. Experimental results indicate that the proposed four-stage approach outperforms other fire detection algorithms in terms of consistently increasing the accuracy of fire detection in both indoor and outdoor test videos.

Efficient monitoring of the blood-stage infection in a malaria rodent model by the rotating-crystal magneto-optical method

NASA Astrophysics Data System (ADS)

Orbán, Ágnes; Rebelo, Maria; Molnár, Petra; Albuquerque, Inês S.; Butykai, Adam; Kézsmárki, István

2016-03-01

Intense research efforts have been focused on the improvement of the efficiency and sensitivity of malaria diagnostics, especially in resource-limited settings for the detection of asymptomatic infections. Our recently developed magneto-optical (MO) method allows the accurate quantification of malaria pigment crystals (hemozoin) in blood by their magnetically induced rotation. First evaluations of the method using β-hematin crystals and in vitro P. falciparum cultures implied its potential for high-sensitivity malaria diagnosis. To further investigate this potential, here we study the performance of the method in monitoring the in vivo onset and progression of the blood-stage infection in a rodent malaria model. Our results show that the MO method can detect the first generation of intraerythrocytic P. berghei parasites 66-76 hours after sporozoite injection, demonstrating similar sensitivity to Giesma-stained light microscopy and exceeding that of flow cytometric techniques. Magneto-optical measurements performed during and after the treatment of P. berghei infections revealed that both the follow up under treatment and the detection of later reinfections are feasible with this new technique. The present study demonstrates that the MO method - besides being label and reagent-free, automated and rapid - has a high in vivo sensitivity and is ready for in-field evaluation.

A rapid silica spin column-based method of RNA extraction from fruit trees for RT-PCR detection of viruses.

PubMed

Yang, Fan; Wang, Guoping; Xu, Wenxing; Hong, Ni

2017-09-01

Efficient recovery of high quality RNA is very important for successful RT-PCR detection of plant RNA viruses. High levels of polyphenols and polysaccharides in plant tissues can irreversibly bind to and/or co-precipitate with RNA, which influences RNA isolation. In this study, a silica spin column-based RNA isolation method was developed by using commercially available silica columns combined with the application of a tissue lysis solution, and binding and washing buffers with high concentration guanidinium thiocyanate (GuSCN, 50% w/v), which helps remove plant proteins, polysaccharides and polyphenolic compounds. The method was successfully used to extract high quality RNA from citrus (Citrus aurantifolia), grapevine (Vitis vinifera), peach (Prunus persica), pear (Pyrus spp.), taro (Colocosia esculenta) and tobacco (Nicotiana benthamiana) samples. The method was comparable to conventional CTAB method in RNA isolation efficiency, but it was more sample-adaptable and cost-effective than commercial kits. High quality RNA isolated using silica spin column-based method was successfully used for the RT-PCR and/or multiplex RT-PCR amplification of woody fruit tree viruses and a viroid. The study provided a useful tool for the detection and characterization of plant viruses. Copyright © 2017 Elsevier B.V. All rights reserved.

Efficient induction of dopaminergic neuron differentiation from induced pluripotent stem cells reveals impaired mitophagy in PARK2 neurons.

PubMed

Suzuki, Sadafumi; Akamatsu, Wado; Kisa, Fumihiko; Sone, Takefumi; Ishikawa, Kei-Ichi; Kuzumaki, Naoko; Katayama, Hiroyuki; Miyawaki, Atsushi; Hattori, Nobutaka; Okano, Hideyuki

2017-01-29

Patient-specific induced pluripotent stem cells (iPSCs) show promise for use as tools for in vitro modeling of Parkinson's disease. We sought to improve the efficiency of dopaminergic (DA) neuron induction from iPSCs by the using surface markers expressed in DA progenitors to increase the significance of the phenotypic analysis. By sorting for a CD184 high /CD44 - fraction during neural differentiation, we obtained a population of cells that were enriched in DA neuron precursor cells and achieved higher differentiation efficiencies than those obtained through the same protocol without sorting. This high efficiency method of DA neuronal induction enabled reliable detection of reactive oxygen species (ROS) accumulation and vulnerable phenotypes in PARK2 iPSCs-derived DA neurons. We additionally established a quantitative system using the mt-mKeima reporter system to monitor mitophagy in which mitochondria fuse with lysosomes and, by combining this system with the method of DA neuronal induction described above, determined that mitophagy is impaired in PARK2 neurons. These findings suggest that the efficiency of DA neuron induction is important for the precise detection of cellular phenotypes in modeling Parkinson's disease. Copyright © 2016. Published by Elsevier Inc.

The study of efficiency of endogenous and exogenous preventive methods of tooth enamel remineralisation by FTIR microscopy using synchrotron radiation

NASA Astrophysics Data System (ADS)

Goloshchapov, D. L.; Kashkarov, V. M.; Seredin, P. V.; Ippolitov, Y. A.; Plotnikova, Y. A.; Bambery, K.

2016-08-01

The efficiency carious preventive methods was detected with the use of equipment for IR-spectromicroscopy and high-intensive synchrotron radiation. The results of the experiment are indicative of the use of exogenous caries prevention alone (use of a toothpaste) being inadequate in saturating hard dental tissues by mineral groups and, thus, keeping teeth healthy, as this method is only short-lived. The use of endogenous methods (mineral tablets based on calcium glycerophosphate) in combination with exogenous prevention enhances prevention as part of remineralisation of dental tissues.

Entropy Beacon: A Hairpin-Free DNA Amplification Strategy for Efficient Detection of Nucleic Acids

PubMed Central

2015-01-01

Here, we propose an efficient strategy for enzyme- and hairpin-free nucleic acid detection called an entropy beacon (abbreviated as Ebeacon). Different from previously reported DNA hybridization/displacement-based strategies, Ebeacon is driven forward by increases in the entropy of the system, instead of free energy released from new base-pair formation. Ebeacon shows high sensitivity, with a detection limit of 5 pM target DNA in buffer and 50 pM in cellular homogenate. Ebeacon also benefits from the hairpin-free amplification strategy and zero-background, excellent thermostability from 20 °C to 50 °C, as well as good resistance to complex environments. In particular, based on the huge difference between the breathing rate of a single base pair and two adjacent base pairs, Ebeacon also shows high selectivity toward base mutations, such as substitution, insertion, and deletion and, therefore, is an efficient nucleic acid detection method, comparable to most reported enzyme-free strategies. PMID:26505212

Correlated ion and neutral time of flight technique combined with velocity map imaging: Quantitative measurements for dissociation processes in excited molecular nano-systems

NASA Astrophysics Data System (ADS)

Berthias, F.; Feketeová, L.; Della Negra, R.; Dupasquier, T.; Fillol, R.; Abdoul-Carime, H.; Farizon, B.; Farizon, M.; Märk, T. D.

2018-01-01

The combination of the Dispositif d'Irradiation d'Agrégats Moléculaire with the correlated ion and neutral time of flight-velocity map imaging technique provides a new way to explore processes occurring subsequent to the excitation of charged nano-systems. The present contribution describes in detail the methods developed for the quantitative measurement of branching ratios and cross sections for collision-induced dissociation processes of water cluster nano-systems. These methods are based on measurements of the detection efficiency of neutral fragments produced in these dissociation reactions. Moreover, measured detection efficiencies are used here to extract the number of neutral fragments produced for a given charged fragment.

Direct Detection Electron Energy-Loss Spectroscopy: A Method to Push the Limits of Resolution and Sensitivity.

PubMed

Hart, James L; Lang, Andrew C; Leff, Asher C; Longo, Paolo; Trevor, Colin; Twesten, Ray D; Taheri, Mitra L

2017-08-15

In many cases, electron counting with direct detection sensors offers improved resolution, lower noise, and higher pixel density compared to conventional, indirect detection sensors for electron microscopy applications. Direct detection technology has previously been utilized, with great success, for imaging and diffraction, but potential advantages for spectroscopy remain unexplored. Here we compare the performance of a direct detection sensor operated in counting mode and an indirect detection sensor (scintillator/fiber-optic/CCD) for electron energy-loss spectroscopy. Clear improvements in measured detective quantum efficiency and combined energy resolution/energy field-of-view are offered by counting mode direct detection, showing promise for efficient spectrum imaging, low-dose mapping of beam-sensitive specimens, trace element analysis, and time-resolved spectroscopy. Despite the limited counting rate imposed by the readout electronics, we show that both core-loss and low-loss spectral acquisition are practical. These developments will benefit biologists, chemists, physicists, and materials scientists alike.

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

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks

PubMed Central

Jung, Sungmo; Kim, Jong Hyun; Kim, Seoksoo

2012-01-01

Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods. PMID:23202190

Calibration of 4π NaI(Tl) detectors with coincidence summing correction using new numerical procedure and ANGLE4 software

NASA Astrophysics Data System (ADS)

Badawi, Mohamed S.; Jovanovic, Slobodan I.; Thabet, Abouzeid A.; El-Khatib, Ahmed M.; Dlabac, Aleksandar D.; Salem, Bohaysa A.; Gouda, Mona M.; Mihaljevic, Nikola N.; Almugren, Kholud S.; Abbas, Mahmoud I.

2017-03-01

The 4π NaI(Tl) γ-ray detectors are consisted of the well cavity with cylindrical cross section, and the enclosing geometry of measurements with large detection angle. This leads to exceptionally high efficiency level and a significant coincidence summing effect, much more than a single cylindrical or coaxial detector especially in very low activity measurements. In the present work, the detection effective solid angle in addition to both full-energy peak and total efficiencies of well-type detectors, were mainly calculated by the new numerical simulation method (NSM) and ANGLE4 software. To obtain the coincidence summing correction factors through the previously mentioned methods, the simulation of the coincident emission of photons was modeled mathematically, based on the analytical equations and complex integrations over the radioactive volumetric sources including the self-attenuation factor. The measured full-energy peak efficiencies and correction factors were done by using 152Eu, where an exact adjustment is required for the detector efficiency curve, because neglecting the coincidence summing effect can make the results inconsistent with the whole. These phenomena, in general due to the efficiency calibration process and the coincidence summing corrections, appear jointly. The full-energy peak and the total efficiencies from the two methods typically agree with discrepancy 10%. The discrepancy between the simulation, ANGLE4 and measured full-energy peak after corrections for the coincidence summing effect was on the average, while not exceeding 14%. Therefore, this technique can be easily applied in establishing the efficiency calibration curves of well-type detectors.

Effects of rainfall events on the occurrence and detection efficiency of viruses in river water impacted by combined sewer overflows.

PubMed

Hata, Akihiko; Katayama, Hiroyuki; Kojima, Keisuke; Sano, Shoichi; Kasuga, Ikuro; Kitajima, Masaaki; Furumai, Hiroaki

2014-01-15

Rainfall events can introduce large amount of microbial contaminants including human enteric viruses into surface water by intermittent discharges from combined sewer overflows (CSOs). The present study aimed to investigate the effect of rainfall events on viral loads in surface waters impacted by CSO and the reliability of molecular methods for detection of enteric viruses. The reliability of virus detection in the samples was assessed by using process controls for virus concentration, nucleic acid extraction and reverse transcription (RT)-quantitative PCR (qPCR) steps, which allowed accurate estimation of virus detection efficiencies. Recovery efficiencies of poliovirus in river water samples collected during rainfall events (<10%) were lower than those during dry weather conditions (>10%). The log10-transformed virus concentration efficiency was negatively correlated with suspended solid concentration (r(2)=0.86) that increased significantly during rainfall events. Efficiencies of DNA extraction and qPCR steps determined with adenovirus type 5 and a primer sharing control, respectively, were lower in dry weather. However, no clear relationship was observed between organic water quality parameters and efficiencies of these two steps. Observed concentrations of indigenous enteric adenoviruses, GII-noroviruses, enteroviruses, and Aichi viruses increased during rainfall events even though the virus concentration efficiency was presumed to be lower than in dry weather. The present study highlights the importance of using appropriate process controls to evaluate accurately the concentration of water borne enteric viruses in natural waters impacted by wastewater discharge, stormwater, and CSOs. © 2013.

Family-Based Rare Variant Association Analysis: A Fast and Efficient Method of Multivariate Phenotype Association Analysis.

PubMed

Wang, Longfei; Lee, Sungyoung; Gim, Jungsoo; Qiao, Dandi; Cho, Michael; Elston, Robert C; Silverman, Edwin K; Won, Sungho

2016-09-01

Family-based designs have been repeatedly shown to be powerful in detecting the significant rare variants associated with human diseases. Furthermore, human diseases are often defined by the outcomes of multiple phenotypes, and thus we expect multivariate family-based analyses may be very efficient in detecting associations with rare variants. However, few statistical methods implementing this strategy have been developed for family-based designs. In this report, we describe one such implementation: the multivariate family-based rare variant association tool (mFARVAT). mFARVAT is a quasi-likelihood-based score test for rare variant association analysis with multiple phenotypes, and tests both homogeneous and heterogeneous effects of each variant on multiple phenotypes. Simulation results show that the proposed method is generally robust and efficient for various disease models, and we identify some promising candidate genes associated with chronic obstructive pulmonary disease. The software of mFARVAT is freely available at http://healthstat.snu.ac.kr/software/mfarvat/, implemented in C++ and supported on Linux and MS Windows. © 2016 WILEY PERIODICALS, INC.

The Genetic-Algorithm-Based Normal Boundary Intersection (GANBI) Method; An Efficient Approach to Pareto Multiobjective Optimization for Engineering Design

DTIC Science & Technology

2006-05-15

alarm performance in a cost-effective manner is the use of track - before - detect strategies, in which multiple sensor detections must occur within the...corresponding to the traditional sensor coverage problem. Also, in the track - before - detect context, reference is made to the field-level functions of...detection and false alarm as successful search and false search, respectively, because the track - before - detect process serves as a searching function

Rogue athletes and recombinant DNA technology: challenges for doping control.

PubMed

Azzazy, Hassan M E; Mansour, Mai M H

2007-10-01

The quest for athletic excellence holds no limit for some athletes, and the advances in recombinant DNA technology have handed these athletes the ultimate doping weapons: recombinant proteins and gene doping. Some detection methods are now available for several recombinant proteins that are commercially available as pharmaceuticals and being abused by dopers. However, researchers are struggling to come up with efficient detection methods in preparation for the imminent threat of gene doping, expected in the 2008 Olympics. This Forum article presents the main detection strategies for recombinant proteins and the forthcoming detection strategies for gene doping as well as the prime analytical challenges facing them.

A method for detecting small targets based on cumulative weighted value of target properties

NASA Astrophysics Data System (ADS)

Jin, Xing; Sun, Gang; Wang, Wei-hua; Liu, Fang; Chen, Zeng-ping

2015-03-01

Laser detection based on the "cat's eye effect" has become the hot research project for its initiative compared to the passivity of sound detection and infrared detection. And the target detection is one of the core technologies in this system. The paper puts forward a method for detecting small targets based on cumulative weighted value of target properties using given data. Firstly, we make a frame difference to the images, then make image processing based on Morphology Principles. Secondly, we segment images, and screen the targets; then find some interesting locations. Finally, comparing to a quantity of frames, we locate the target. We did an exam to 394 true frames, the experimental result shows that the mathod can detect small targets efficiently.

Efficiency of playback for assessing the occurrence of five bird species in Brazilian Atlantic Forest fragments.

PubMed

Boscolo, Danilo; Metzger, Jean Paul; Vielliard, Jacques M E

2006-12-01

Playback of bird songs is a useful technique for species detection; however, this method is usually not standardized. We tested playback efficiency for five Atlantic Forest birds (White-browed Warbler Basileuterus leucoblepharus, Giant Antshrike Batara cinerea, Swallow-tailed Manakin Chiroxiphia caudata, Whiteshouldered Fire-eye Pyriglena leucoptera and Surucua Trogon Trogon surrucura) for different time of the day, season of the year and species abundance at the Morro Grande Forest Reserve (South-eastern Brazil) and at thirteen forest fragments in a nearby landscape. Vocalizations were broadcasted monthly at sunrise, noon and sunset, during one year. For B. leucoblepharus, C. caudata and T. surrucura, sunrise and noon were more efficient than sunset. Batara cinerea presented higher efficiency from July to October. Playback expanded the favourable period for avifaunal surveys in tropical forest, usually restricted to early morning in the breeding season. The playback was efficient in detecting the presence of all species when the abundance was not too low. But only B. leucoblepharus and T. surrucura showed abundance values significantly related to this efficiency. The present study provided a precise indication of the best daily and seasonal periods and a confidence interval to maximize the efficiency of playback to detect the occurrence of these forest species.

Deriving the Contribution of Blazars to the Fermi-LAT Extragalactic γ-ray Background at E > 10 GeV with Efficiency Corrections and Photon Statistics

DOE PAGES

Di Mauro, M.; Manconi, S.; Zechlin, H. -S.; ...

2018-03-29

Here, the Fermi Large Area Telescope (LAT) Collaboration has recently released the Third Catalog of Hard Fermi-LAT Sources (3FHL), which contains 1556 sources detected above 10 GeV with seven years of Pass 8 data. Building upon the 3FHL results, we investigate the flux distribution of sources at high Galactic latitudes (more » $$|b| \\gt 20^\\circ $$), which are mostly blazars. We use two complementary techniques: (1) a source-detection efficiency correction method and (2) an analysis of pixel photon count statistics with the one-point probability distribution function (1pPDF). With the first method, using realistic Monte Carlo simulations of the γ-ray sky, we calculate the efficiency of the LAT to detect point sources. This enables us to find the intrinsic source-count distribution at photon fluxes down to 7.5 × 10 –12 ph cm –2 s –1. With this method, we detect a flux break at (3.5 ± 0.4) × 10 –11 ph cm –2 s –1 with a significance of at least 5.4σ. The power-law indexes of the source-count distribution above and below the break are 2.09 ± 0.04 and 1.07 ± 0.27, respectively. This result is confirmed with the 1pPDF method, which has a sensitivity reach of ~10 –11 ph cm –2 s –1. Integrating the derived source-count distribution above the sensitivity of our analysis, we find that (42 ± 8)% of the extragalactic γ-ray background originates from blazars.« less

Deriving the Contribution of Blazars to the Fermi-LAT Extragalactic γ-ray Background at E > 10 GeV with Efficiency Corrections and Photon Statistics

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

Di Mauro, M.; Manconi, S.; Zechlin, H. -S.

Here, the Fermi Large Area Telescope (LAT) Collaboration has recently released the Third Catalog of Hard Fermi-LAT Sources (3FHL), which contains 1556 sources detected above 10 GeV with seven years of Pass 8 data. Building upon the 3FHL results, we investigate the flux distribution of sources at high Galactic latitudes (more » $$|b| \\gt 20^\\circ $$), which are mostly blazars. We use two complementary techniques: (1) a source-detection efficiency correction method and (2) an analysis of pixel photon count statistics with the one-point probability distribution function (1pPDF). With the first method, using realistic Monte Carlo simulations of the γ-ray sky, we calculate the efficiency of the LAT to detect point sources. This enables us to find the intrinsic source-count distribution at photon fluxes down to 7.5 × 10 –12 ph cm –2 s –1. With this method, we detect a flux break at (3.5 ± 0.4) × 10 –11 ph cm –2 s –1 with a significance of at least 5.4σ. The power-law indexes of the source-count distribution above and below the break are 2.09 ± 0.04 and 1.07 ± 0.27, respectively. This result is confirmed with the 1pPDF method, which has a sensitivity reach of ~10 –11 ph cm –2 s –1. Integrating the derived source-count distribution above the sensitivity of our analysis, we find that (42 ± 8)% of the extragalactic γ-ray background originates from blazars.« less

Development and evaluation of a gas chromatographic method for the determination of triazine herbicides in natural water samples

USGS Publications Warehouse

Steinheimer, T.R.; Brooks, M.G.

1984-01-01

A multi-residue method is described for the determination of triazine herbicides in natural water samples. The technique uses solvent extraction followed by gas chromatographic separation and detection employing nitrogen-selective devices. Seven compounds can be determined simultaneously at a nominal detection limit of 0.1 ??g/L in a 1-litre sample. Three different natural water samples were used for error analysis via evaluation of recovery efficiencies and estimation of overall method precision. As an alternative to liquid-liquid partition (solvent extraction) for removal of compounds of interest from water, solid-phase extraction (SPE) techniques employing chromatographic grade silicas with chemically modified surfaces have been examined. SPE is found to provide rapid and efficient concentration with quantitative recovery of some triazine herbicides from natural water samples. Concentration factors of 500 to 1000 times are obtained readily by the SPE technique.A multi-residue method is described for the determination of triazine herbicides in natural water samples. The technique uses solvent extraction followed by gas chromatographic separation and detection employing nitrogen-selective devices. Seven compounds can be determined simultaneously at a nominal detection limit of 0. 1 mu g/L in a 1-litre sample. As an alternative to liquid-liquid partition (solvent extraction) for removal of compounds of interest from water, solid-phase extraction (SPE) techniques employing chromatographic grade silicas with chemically modified surfaces have been examined. SPE is found to provide rapid and efficient concentration with quantitative recovery of some triazine herbicides from natural water samples. Concentration factors of 500 to 1000 times are obtained readily by the SPE technique.

Evolutionary method for finding communities in bipartite networks.

PubMed

Zhan, Weihua; Zhang, Zhongzhi; Guan, Jihong; Zhou, Shuigeng

2011-06-01

An important step in unveiling the relation between network structure and dynamics defined on networks is to detect communities, and numerous methods have been developed separately to identify community structure in different classes of networks, such as unipartite networks, bipartite networks, and directed networks. Here, we show that the finding of communities in such networks can be unified in a general framework-detection of community structure in bipartite networks. Moreover, we propose an evolutionary method for efficiently identifying communities in bipartite networks. To this end, we show that both unipartite and directed networks can be represented as bipartite networks, and their modularity is completely consistent with that for bipartite networks, the detection of modular structure on which can be reformulated as modularity maximization. To optimize the bipartite modularity, we develop a modified adaptive genetic algorithm (MAGA), which is shown to be especially efficient for community structure detection. The high efficiency of the MAGA is based on the following three improvements we make. First, we introduce a different measure for the informativeness of a locus instead of the standard deviation, which can exactly determine which loci mutate. This measure is the bias between the distribution of a locus over the current population and the uniform distribution of the locus, i.e., the Kullback-Leibler divergence between them. Second, we develop a reassignment technique for differentiating the informative state a locus has attained from the random state in the initial phase. Third, we present a modified mutation rule which by incorporating related operations can guarantee the convergence of the MAGA to the global optimum and can speed up the convergence process. Experimental results show that the MAGA outperforms existing methods in terms of modularity for both bipartite and unipartite networks.

SiPM electro-optical detection system noise suppression method

NASA Astrophysics Data System (ADS)

Bi, Xiangli; Yang, Suhui; Hu, Tao; Song, Yiheng

2014-11-01

In this paper, the single photon detection principle of Silicon Photomultipliers (SiPM) device is introduced. The main noise factors that infect the sensitivity of the electro-optical detection system are analyzed, including background light noise, detector dark noise, preamplifier noise and signal light noise etc. The Optical, electrical and thermodynamic methods are used to suppress the SiPM electro-optical detection system noise, which improved the response sensitivity of the detector. Using SiPM optoelectronic detector with a even high sensitivity, together with small field large aperture optical system, high cutoff narrow bandwidth filters, low-noise operational amplifier circuit, the modular design of functional circuit, semiconductor refrigeration technology, greatly improved the sensitivity of optical detection system, reduced system noise and achieved long-range detection of weak laser radiation signal. Theoretical analysis and experimental results show that the proposed methods are reasonable and efficient.

Nonstationary EO/IR Clutter Suppression and Dim Object Tracking

DTIC Science & Technology

2010-01-01

Brown, A., and Brown, J., Enhanced Algorithms for EO /IR Electronic Stabilization, Clutter Suppression, and Track - Before - Detect for Multiple Low...estimation-suppression and nonlinear filtering-based multiple-object track - before - detect . These algorithms are suitable for integration into...In such cases, it is imperative to develop efficient real or near-real time tracking before detection methods. This paper continues the work started

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).

Comparison of soft-input-soft-output detection methods for dual-polarized quadrature duobinary system

NASA Astrophysics Data System (ADS)

Chang, Chun; Huang, Benxiong; Xu, Zhengguang; Li, Bin; Zhao, Nan

2018-02-01

Three soft-input-soft-output (SISO) detection methods for dual-polarized quadrature duobinary (DP-QDB), including maximum-logarithmic-maximum-a-posteriori-probability-algorithm (Max-log-MAP)-based detection, soft-output-Viterbi-algorithm (SOVA)-based detection, and a proposed SISO detection, which can all be combined with SISO decoding, are presented. The three detection methods are investigated at 128 Gb/s in five-channel wavelength-division-multiplexing uncoded and low-density-parity-check (LDPC) coded DP-QDB systems by simulations. Max-log-MAP-based detection needs the returning-to-initial-states (RTIS) process despite having the best performance. When the LDPC code with a code rate of 0.83 is used, the detecting-and-decoding scheme with the SISO detection does not need RTIS and has better bit error rate (BER) performance than the scheme with SOVA-based detection. The former can reduce the optical signal-to-noise ratio (OSNR) requirement (at BER=10-5) by 2.56 dB relative to the latter. The application of the SISO iterative detection in LDPC-coded DP-QDB systems makes a good trade-off between requirements on transmission efficiency, OSNR requirement, and transmission distance, compared with the other two SISO methods.

Detection method of visible and invisible nipples on digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Chae, Seung-Hoon; Jeong, Ji-Wook; Lee, Sooyeul; Chae, Eun Young; Kim, Hak Hee; Choi, Young-Wook

2015-03-01

Digital Breast Tomosynthesis(DBT) with 3D breast image can improve detection sensitivity of breast cancer more than 2D mammogram on dense breast. The nipple location information is needed to analyze DBT. The nipple location is invaluable information in registration and as a reference point for classifying mass or micro-calcification clusters. Since there are visible nipple and invisible nipple in 2D mammogram or DBT, the nipple detection of breast must be possible to detect visible and invisible nipple of breast. The detection method of visible nipple using shape information of nipple is simple and highly efficient. However, it is difficult to detect invisible nipple because it doesn't have prominent shape. Mammary glands in breast connect nipple, anatomically. The nipple location is detected through analyzing location of mammary glands in breast. In this paper, therefore, we propose a method to detect the nipple on a breast, which has a visible or invisible nipple using changes of breast area and mammary glands, respectively. The result shows that our proposed method has average error of 2.54+/-1.47mm.

Evaluation of a Novel Magneto-Optical Method for the Detection of Malaria Parasites

PubMed Central

Orbán, Ágnes; Butykai, Ádám; Molnár, András; Pröhle, Zsófia; Fülöp, Gergö; Zelles, Tivadar; Forsyth, Wasan; Hill, Danika; Müller, Ivo; Schofield, Louis; Rebelo, Maria; Hänscheid, Thomas; Karl, Stephan; Kézsmárki, István

2014-01-01

Improving the efficiency of malaria diagnosis is one of the main goals of current malaria research. We have recently developed a magneto-optical (MO) method which allows high-sensitivity detection of malaria pigment (hemozoin crystals) in blood via the magnetically induced rotational motion of the hemozoin crystals. Here, we evaluate this MO technique for the detection of Plasmodium falciparum in infected erythrocytes using in-vitro parasite cultures covering the entire intraerythrocytic life cycle. Our novel method detected parasite densities as low as ∼40 parasites per microliter of blood (0.0008% parasitemia) at the ring stage and less than 10 parasites/µL (0.0002% parasitemia) in the case of the later stages. These limits of detection, corresponding to approximately 20 pg/µL of hemozoin produced by the parasites, exceed that of rapid diagnostic tests and compete with the threshold achievable by light microscopic observation of blood smears. The MO diagnosis requires no special training of the operator or specific reagents for parasite detection, except for an inexpensive lysis solution to release intracellular hemozoin. The devices can be designed to a portable format for clinical and in-field tests. Besides testing its diagnostic performance, we also applied the MO technique to investigate the change in hemozoin concentration during parasite maturation. Our preliminary data indicate that this method may offer an efficient tool to determine the amount of hemozoin produced by the different parasite stages in synchronized cultures. Hence, it could eventually be used for testing the susceptibility of parasites to antimalarial drugs. PMID:24824542

Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

PubMed

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

2017-01-01

Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

Efficient Detection of Copy Number Mutations in PMS2 Exons with a Close Homolog.

PubMed

Herman, Daniel S; Smith, Christina; Liu, Chang; Vaughn, Cecily P; Palaniappan, Selvi; Pritchard, Colin C; Shirts, Brian H

2018-07-01

Detection of 3' PMS2 copy-number mutations that cause Lynch syndrome is difficult because of highly homologous pseudogenes. To improve the accuracy and efficiency of clinical screening for these mutations, we developed a new method to analyze standard capture-based, next-generation sequencing data to identify deletions and duplications in PMS2 exons 9 to 15. The approach captures sequences using PMS2 targets, maps sequences randomly among regions with equal mapping quality, counts reads aligned to homologous exons and introns, and flags read count ratios outside of empirically derived reference ranges. The method was trained on 1352 samples, including 8 known positives, and tested on 719 samples, including 17 known positives. Clinical implementation of the first version of this method detected new mutations in the training (N = 7) and test (N = 2) sets that had not been identified by our initial clinical testing pipeline. The described final method showed complete sensitivity in both sample sets and false-positive rates of 5% (training) and 7% (test), dramatically decreasing the number of cases needing additional mutation evaluation. This approach leveraged the differences between gene and pseudogene to distinguish between PMS2 and PMS2CL copy-number mutations. These methods enable efficient and sensitive Lynch syndrome screening for 3' PMS2 copy-number mutations and may be applied similarly to other genomic regions with highly homologous pseudogenes. Copyright © 2018 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2015-01-05

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2013-01-01

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

A facile and efficient approach for pore-opening detection of anodic aluminum oxide membranes

NASA Astrophysics Data System (ADS)

Cui, Jiewu; Wu, Yucheng; Wang, Yan; Zheng, Hongmei; Xu, Guangqing; Zhang, Xinyi

2012-05-01

The well aligned porous anodic aluminum oxide (AAO) membrane is fabricated by a two-step anodization method. The oxide barrier layer of AAO membrane must be removed to get through-hole membrane for synthesizing nanowires and nanotubes of metals, semiconductors and conducting polymers. Removal of the barrier layer of oxide and pore-extending is of significant importance for the preparation of AAO membrane with through-hole pore morphology and desired pore diameter. The conventional method for pore opening is that AAO membrane after removing of aluminum substrate is immersed in chemical etching solution, which is completely empirical and results in catastrophic damage for AAO membrane frequently. A very simple and efficient approach based on capillary action for detecting pore opening of AAO membrane is introduced in this paper, this method can achieve the detection for pore opening visually and control the pore diameter precisely to get desired morphology and the pore diameter of AAO membrane. Two kinds of AAO membranes with different pore shape were obtained by different pore opening methods. In addition, one-dimensional gradient gold nanowires are also fabricated by electrodeposition based on AAO membranes.

Determination of desipramine in biological samples using liquid-liquid-liquid microextraction combined with in-syringe derivatization, gas chromatography, and nitrogen/phosphorus detection.

PubMed

Saraji, Mohammad; Mehrafza, Narges; Bidgoli, Ali Akbar Hajialiakbari; Jafari, Mohammad Taghi

2012-10-01

A method was established for the determination of desipramine in biological samples using liquid-liquid-liquid microextraction followed by in-syringe derivatization and gas chromatography-nitrogen phosphorus detection. The extraction method was based on the use of two immiscible organic solvents. n-Dodecane was impregnated in the pores of the hollow fiber and methanol was placed inside the lumen of the fiber as the acceptor phase. Acetic anhydride was used as the reagent for the derivatization of the analyte inside the syringe barrel. Parameters that affect the extraction efficiency (composition of donor and acceptor phase, ionic strength, sample temperature, and extraction time) as well as derivatization efficiency (amount of acetic anhydride and reaction time and temperature) were investigated. The limit of detection was 0.02 μg/L with intra and interday RSDs of 2.6 and 7.7%, respectively. The linearity of the method was in the range of 0.2-20 μg/L (r(2) = 0.9986). The method was successfully applied to determine desipramine in human plasma and urine. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2014-01-01

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

Production integrated nondestructive testing of composite materials and material compounds - an overview

NASA Astrophysics Data System (ADS)

Straß, B.; Conrad, C.; Wolter, B.

2017-03-01

Composite materials and material compounds are of increasing importance, because of the steadily rising relevance of resource saving lightweight constructions. Quality assurance with appropriate Nondestructive Testing (NDT) methods is a key aspect for reliable and efficient production. Quality changes have to be detected already in the manufacturing flow in order to take adequate corrective actions. For materials and compounds the classical NDT methods for defectoscopy, like X-ray and Ultrasound (US) are still predominant. Nevertheless, meanwhile fast, contactless NDT methods, like air-borne ultrasound, dynamic thermography and special Eddy-Current techniques are available in order to detect cracks, voids, pores and delaminations but also for characterizing fiber content, distribution and alignment. In Metal-Matrix Composites US back-scattering can be used for this purpose. US run-time measurements allow the detection of thermal stresses at the metal-matrix interface. Another important area is the necessity for NDT in joining. To achieve an optimum material utilization and product safety as well as the best possible production efficiency, there is a need for NDT methods for in-line inspection of the joint quality while joining or immediately afterwards. For this purpose EMAT (Electromagnetic Acoustic Transducer) technique or Acoustic Emission testing can be used.

A comprehensive model for x-ray projection imaging system efficiency and image quality characterization in the presence of scattered radiation

NASA Astrophysics Data System (ADS)

Monnin, P.; Verdun, F. R.; Bosmans, H.; Rodríguez Pérez, S.; Marshall, N. W.

2017-07-01

This work proposes a method for assessing the detective quantum efficiency (DQE) of radiographic imaging systems that include both the x-ray detector and the antiscatter device. Cascaded linear analysis of the antiscatter device efficiency (DQEASD) with the x-ray detector DQE is used to develop a metric of system efficiency (DQEsys); the new metric is then related to the existing system efficiency parameters of effective DQE (eDQE) and generalized DQE (gDQE). The effect of scatter on signal transfer was modelled through its point spread function (PSF), leading to an x-ray beam transfer function (BTF) that multiplies with the classical presampling modulation transfer function (MTF) to give the system MTF. Expressions are then derived for the influence of scattered radiation on signal-difference to noise ratio (SDNR) and contrast-detail (c-d) detectability. The DQEsys metric was tested using two digital mammography systems, for eight x-ray beams (four with and four without scatter), matched in terms of effective energy. The model was validated through measurements of contrast, SDNR and MTF for poly(methyl)methacrylate thicknesses covering the range of scatter fractions expected in mammography. The metric also successfully predicted changes in c-d detectability for different scatter conditions. Scatter fractions for the four beams with scatter were established with the beam stop method using an extrapolation function derived from the scatter PSF, and validated through Monte Carlo (MC) simulations. Low-frequency drop of the MTF from scatter was compared to both theory and MC calculations. DQEsys successfully quantified the influence of the grid on SDNR and accurately gave the break-even object thickness at which system efficiency was improved by the grid. The DQEsys metric is proposed as an extension of current detector characterization methods to include a performance evaluation in the presence of scattered radiation, with an antiscatter device in place.

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.

Millimeter-Wave Spectroscopy for Analytical Chemistry: Thermal Evolution of Low Volatility Impurities and Detection with a Fourier Transform Molecular Rotational Resonance Spectrometer (tev Ft-Mrr

NASA Astrophysics Data System (ADS)

Harris, Brent; Fields, Shelby S.; Neill, Justin L.; Pulliam, Robin; Muckle, Matt; Pate, Brooks

2016-06-01

Recent advances in Fourier transform millimeter-wave spectroscopy techniques have renewed the application reach of molecular rotational spectroscopy for analytical chemistry. We present a sampling method for sub ppm analysis of low volatility impurities by thermal evolution from solid powders using a millimeter-wave Fourier transform molecular rotational resonance (FT-MRR) spectrometer for detection. This application of FT-MRR is relevant to the manufacturing of safe oral pharmaceuticals. Low volatility impurities can be challenging to detect at 1 ppm levels with chromatographic techniques. One such example of a potentially mutagenic impurity is acetamide (v.p. 1 Torr at 40 C, m.p. 80 C). We measured the pure reference spectrum of acetamide by flowing the sublimated vapor pressure of acetamide crystals through the FT-MRR spectrometer. The spectrometer lower detection level (LDL) for a broadband (> 20 GHz, 10 min.) spectrum is 300 nTorr, 30 pmol, or 2 ng. For a 50 mg powder, perfect sample transfer efficiency can yield a w/w % detection limit of 35 ppb. We extended the sampling method for the acetamide reference measurement to an acetaminophen sample spiked with 5000 ppm acetamide in order to test the sample transfer efficiency when liberated from an pharmaceutical powder. A spectral reference matching algorithm detected the presence of several impurities including acetaldehyde, acetic acid, and acetonitrile that evolved at the melting point of acetaminophen, demonstrating the capability of FT-MRR for identification without a routine chemical standard. The method detection limit (MDL) without further development is less than 10 ppm w/w %. Resolved FT-MRR mixture spectra will be presented with a description of sampling methods.

Detection Copy Number Variants from NGS with Sparse and Smooth Constraints.

PubMed

Zhang, Yue; Cheung, Yiu-Ming; Xu, Bo; Su, Weifeng

2017-01-01

It is known that copy number variations (CNVs) are associated with complex diseases and particular tumor types, thus reliable identification of CNVs is of great potential value. Recent advances in next generation sequencing (NGS) data analysis have helped manifest the richness of CNV information. However, the performances of these methods are not consistent. Reliably finding CNVs in NGS data in an efficient way remains a challenging topic, worthy of further investigation. Accordingly, we tackle the problem by formulating CNVs identification into a quadratic optimization problem involving two constraints. By imposing the constraints of sparsity and smoothness, the reconstructed read depth signal from NGS is anticipated to fit the CNVs patterns more accurately. An efficient numerical solution tailored from alternating direction minimization (ADM) framework is elaborated. We demonstrate the advantages of the proposed method, namely ADM-CNV, by comparing it with six popular CNV detection methods using synthetic, simulated, and empirical sequencing data. It is shown that the proposed approach can successfully reconstruct CNV patterns from raw data, and achieve superior or comparable performance in detection of the CNVs compared to the existing counterparts.

Secure detection in quantum key distribution by real-time calibration of receiver

NASA Astrophysics Data System (ADS)

Marøy, Øystein; Makarov, Vadim; Skaar, Johannes

2017-12-01

The single-photon detectionefficiency of the detector unit is crucial for the security of common quantum key distribution protocols like Bennett-Brassard 1984 (BB84). A low value for the efficiency indicates a possible eavesdropping attack that exploits the photon receiver’s imperfections. We present a method for estimating the detection efficiency, and calculate the corresponding secure key generation rate. The estimation is done by testing gated detectors using a randomly activated photon source inside the receiver unit. This estimate gives a secure rate for any detector with non-unity single-photon detection efficiency, both inherit or due to blinding. By adding extra optical components to the receiver, we make sure that the key is extracted from photon states for which our estimate is valid. The result is a quantum key distribution scheme that is secure against any attack that exploits detector imperfections.

Apparatus and method using a holographic optical element for converting a spectral distribution to image points

NASA Technical Reports Server (NTRS)

McGill, Matthew J. (Inventor); Scott, Vibart S. (Inventor); Marzouk, Marzouk (Inventor)

2001-01-01

A holographic optical element transforms a spectral distribution of light to image points. The element comprises areas, each of which acts as a separate lens to image the light incident in its area to an image point. Each area contains the recorded hologram of a point source object. The image points can be made to lie in a line in the same focal plane so as to align with a linear array detector. A version of the element has been developed that has concentric equal areas to match the circular fringe pattern of a Fabry-Perot interferometer. The element has high transmission efficiency, and when coupled with high quantum efficiency solid state detectors, provides an efficient photon-collecting detection system. The element may be used as part of the detection system in a direct detection Doppler lidar system or multiple field of view lidar system.

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).

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

Extraction of total nucleic acid based on silica-coated magnetic particles for RT-qPCR detection of plant RNA virus/viroid.

PubMed

Sun, Ning; Deng, Congliang; Zhao, Xiaoli; Zhou, Qi; Ge, Guanglu; Liu, Yi; Yan, Wenlong; Xia, Qiang

2014-02-01

In this study, a nucleic acid extraction method based on silica-coated magnetic particles (SMPs) and RT-qPCR assay was developed to detect Arabis mosaic virus (ArMV), Lily symptomless virus (LSV), Hop stunt viroid (HSVd) and grape yellow speckle viroid 1 (GYSVd-1). The amplification sequences of RT-qPCR were reversely transcribed in vitro as RNA standard templates. The standard curves covered six or seven orders of magnitude with a detection limit of 100 copies per each assay. Extraction efficiency of the SMPs method was evaluated by recovering spiked ssRNAs from plant samples and compared to two commercial kits (TRIzol and RNeasy Plant mini kit). Results showed that the recovery rate of SMPs method was comparable to the commercial kits when spiked ssRNAs were extracted from lily leaves, whereas it was two or three times higher than commercial kits when spiked ssRNAs were extracted from grapevine leaves. SMPs method was also used to extract viral nucleic acid from15 ArMV-positive lily leaf samples and 15 LSV-positive lily leaf samples. SMPs method did not show statistically significant difference from other methods on detecting ArMV, but LSV. The SMPs method has the same level of virus load as the TRIzol, and its mean virus load of was 0.5log10 lower than the RNeasy Plant mini kit. Nucleic acid was extracted from 19 grapevine-leaf samples with SMPs and the two commercial kits and subsequently screened for HSVd and GYSVd-1 by RT-qPCR. Regardless of HSVd or GYSVd-1, SMPs method outperforms other methods on both positive rate and the viroid load. In conclusion, SMPs method was able to efficiently extract the nucleic acid of RNA viruses or viroids, especially grapevine viroids, from lily-leaf or grapevine-leaf samples for RT-qPCR detection. Copyright © 2013 Elsevier B.V. All rights reserved.

Tunable generation and adsorption of energetic compounds in the vapor phase at trace levels: a tool for testing and developing sensitive and selective substrates for explosive detection.

PubMed

Bonnot, Karine; Bernhardt, Pierre; Hassler, Dominique; Baras, Christian; Comet, Marc; Keller, Valérie; Spitzer, Denis

2010-04-15

Among various methods for landmine detection, as well as soil and water pollution monitoring, the detection of explosive compounds in air is becoming an important and inevitable challenge for homeland security applications, due to the threatening increase in terrorist explosive bombs used against civil populations. However, in the last case, there is a crucial need for the detection of vapor phase traces or subtraces (in the ppt range or even lower). A novel and innovative generator for explosive trace vapors was designed and developed. It allowed the generation of theoretical concentrations as low as 0.24 ppq for hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in air according to Clapeyron equations. The accurate generation of explosive concentrations at subppt levels was verified for RDX and 2,4,6-trinitrotoluene (TNT) using a gas chromatograph coupled to an electron capture detector (GC-ECD). First, sensing material experiments were conducted on a nanostructured tungsten oxide. The sensing efficiency of this material determined as its adsorption capacity toward 54 ppb RDX was calculated to be five times higher than the sensing efficiency of a 54 ppb TNT vapor. The material sensing efficiency showed no dependence on the mass of material used. The results showed that the device allowed the calibration and discrimination between materials for highly sensitive and accurate sensing detection in air of low vapor pressure explosives such as TNT or RDX at subppb levels. The designed device and method showed promising features for nanosensing applications in the field of ultratrace explosive detection. The current perspectives are to decrease the testing scale and the detection levels to ppt or subppt concentration of explosives in air.

Improved and Robust Detection of Cell Nuclei from Four Dimensional Fluorescence Images

PubMed Central

Bashar, Md. Khayrul; Yamagata, Kazuo; Kobayashi, Tetsuya J.

2014-01-01

Segmentation-free direct methods are quite efficient for automated nuclei extraction from high dimensional images. A few such methods do exist but most of them do not ensure algorithmic robustness to parameter and noise variations. In this research, we propose a method based on multiscale adaptive filtering for efficient and robust detection of nuclei centroids from four dimensional (4D) fluorescence images. A temporal feedback mechanism is employed between the enhancement and the initial detection steps of a typical direct method. We estimate the minimum and maximum nuclei diameters from the previous frame and feed back them as filter lengths for multiscale enhancement of the current frame. A radial intensity-gradient function is optimized at positions of initial centroids to estimate all nuclei diameters. This procedure continues for processing subsequent images in the sequence. Above mechanism thus ensures proper enhancement by automated estimation of major parameters. This brings robustness and safeguards the system against additive noises and effects from wrong parameters. Later, the method and its single-scale variant are simplified for further reduction of parameters. The proposed method is then extended for nuclei volume segmentation. The same optimization technique is applied to final centroid positions of the enhanced image and the estimated diameters are projected onto the binary candidate regions to segment nuclei volumes.Our method is finally integrated with a simple sequential tracking approach to establish nuclear trajectories in the 4D space. Experimental evaluations with five image-sequences (each having 271 3D sequential images) corresponding to five different mouse embryos show promising performances of our methods in terms of nuclear detection, segmentation, and tracking. A detail analysis with a sub-sequence of 101 3D images from an embryo reveals that the proposed method can improve the nuclei detection accuracy by 9 over the previous methods, which used inappropriate large valued parameters. Results also confirm that the proposed method and its variants achieve high detection accuracies ( 98 mean F-measure) irrespective of the large variations of filter parameters and noise levels. PMID:25020042

Fast trace determination of nine odorant and estrogenic chloro- and bromo-phenolic compounds in real water samples through automated solid-phase extraction coupled with liquid chromatography tandem mass spectrometry.

PubMed

Yuan, Su-Fen; Liu, Ze-Hua; Lian, Hai-Xian; Yang, Chuang-Tao; Lin, Qing; Yin, Hua; Lin, Zhang; Dang, Zhi

2018-02-01

A fast and reliable method was developed for simultaneous trace determination of nine odorous and estrogenic chloro- and bromo-phenolic compounds (CPs and BPs) in water samples using solid-phase extraction (SPE) coupled with liquid chromatography tandem mass spectrometry (LC-MS/MS). For sample preparation, the extraction efficiencies of two widely applied cartridges Oasis HLB and Sep-Pak C18 were compared, and the Oasis HLB cartridge showed much better extraction performance; pH of water sample also plays important role on extraction, and pH = 2-3 was found to be most appropriate. For separation of the target compounds, small addition of ammonium hydroxide can obviously improve the detection sensitivity, and the optimized addition concentration was determined as 0.2%. The developed efficient method was validated and showed excellent linearity (R 2  > 0.995), low limit of detection (LOD, 1.9-6.2 ng/L), and good recovery efficiencies of 57-95% in surface and tap water with low relative standard deviation (RSD, 1.3-17.4%). The developed method was finally applied to one tap and one surface water samples and most of these nine targets were detected, but all of them were below their odor thresholds, and their estrogen equivalent (EEQ) were also very low.

An effective and efficient compression algorithm for ECG signals with irregular periods.

PubMed

Chou, Hsiao-Hsuan; Chen, Ying-Jui; Shiau, Yu-Chien; Kuo, Te-Son

2006-06-01

This paper presents an effective and efficient preprocessing algorithm for two-dimensional (2-D) electrocardiogram (ECG) compression to better compress irregular ECG signals by exploiting their inter- and intra-beat correlations. To better reveal the correlation structure, we first convert the ECG signal into a proper 2-D representation, or image. This involves a few steps including QRS detection and alignment, period sorting, and length equalization. The resulting 2-D ECG representation is then ready to be compressed by an appropriate image compression algorithm. We choose the state-of-the-art JPEG2000 for its high efficiency and flexibility. In this way, the proposed algorithm is shown to outperform some existing arts in the literature by simultaneously achieving high compression ratio (CR), low percent root mean squared difference (PRD), low maximum error (MaxErr), and low standard derivation of errors (StdErr). In particular, because the proposed period sorting method rearranges the detected heartbeats into a smoother image that is easier to compress, this algorithm is insensitive to irregular ECG periods. Thus either the irregular ECG signals or the QRS false-detection cases can be better compressed. This is a significant improvement over existing 2-D ECG compression methods. Moreover, this algorithm is not tied exclusively to JPEG2000. It can also be combined with other 2-D preprocessing methods or appropriate codecs to enhance the compression performance in irregular ECG cases.

MIL-101(Cr)@GO for dispersive micro-solid-phase extraction of pharmaceutical residue in chicken breast used in microwave-assisted coupling with HPLC-MS/MS detection.

PubMed

Wang, Yudan; Dai, Xinpeng; He, Xi; Chen, Lin; Hou, Xiaohong

2017-10-25

In this work, MIL-101(Cr)@GO (Graphite Oxide) was synthesized using a hydrothermal synthesis method and was applied as a dispersive micro-solid-phase extraction (D-μ-SPE) sorbent for the efficient concentration of four residual drugs (metronidazole, MNZ; tinidazole, TNZ; chloramphenicol, CAP; sulfamethoxazole, SMX). Meanwhile, the extraction process was optimized by combining it with microwave-assisted extraction. Factors affecting the D-μ-SPE efficiency, such as selection of sorbent materials, pH of the sample solution, salting-out effect, amount of used material, extraction time, desorption solvent and desorption time, were studied. Under the optimal extraction conditions, the linearity ranged from 10 to 1000ngkg -1 and 1-100ngkg -1 (r 2 ≥0.9928) for the target analytes. The limits of detection were between 0.08 and 1.02ngkg -1 , and the limits of quantitation were between 0.26 and 3.40ngkg -1 . Additionally, the developed method also exhibited good precision (RSD≤2.5%), repeatability (RSD≤4.3%), high recoveries (88.9%-102.3%) and low matrix effects (78.2%-95.1%). The proposed method proved to be an efficient and reliable approach for the determination of the analytes. Finally, we successfully detected the four drugs in chicken breast. Copyright © 2017 Elsevier B.V. All rights reserved.

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

ERIC Educational Resources Information Center

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

2009-01-01

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

Social Network Aided Plagiarism Detection

ERIC Educational Resources Information Center

Zrnec, Aljaž; Lavbic, Dejan

2017-01-01

The prevalence of different kinds of electronic devices and the volume of content on the Web have increased the amount of plagiarism, which is considered an unethical act. If we want to be efficient in the detection and prevention of these acts, we have to improve today's methods of discovering plagiarism. The paper presents a research study where…

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

PubMed

Si, Weijian; Wang, Liwei; Qu, Zhiyu

2016-11-23

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

Magnetic bead-quantum dot assay for detection of a biomarker for traumatic brain injury

NASA Astrophysics Data System (ADS)

Kim, Chloe; Searson, Peter C.

2015-10-01

Current diagnostic methods for traumatic brain injury (TBI), which accounts for 15% of all emergency room visits, are limited to neuroimaging modalities. The challenges of accurate diagnosis and monitoring of TBI have created the need for a simple and sensitive blood test to detect brain-specific biomarkers. Here we report on an assay for detection of S100B, a putative biomarker for TBI, using antibody-conjugated magnetic beads for capture of the protein, and antibody-conjugated quantum dots for optical detection. From Western Blot, we show efficient antigen capture and concentration by the magnetic beads. Using magnetic bead capture and quantum dot detection in serum samples, we show a wide detection range and detection limit below the clinical cut-off level.Current diagnostic methods for traumatic brain injury (TBI), which accounts for 15% of all emergency room visits, are limited to neuroimaging modalities. The challenges of accurate diagnosis and monitoring of TBI have created the need for a simple and sensitive blood test to detect brain-specific biomarkers. Here we report on an assay for detection of S100B, a putative biomarker for TBI, using antibody-conjugated magnetic beads for capture of the protein, and antibody-conjugated quantum dots for optical detection. From Western Blot, we show efficient antigen capture and concentration by the magnetic beads. Using magnetic bead capture and quantum dot detection in serum samples, we show a wide detection range and detection limit below the clinical cut-off level. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr05608j

Detection of Perlger-Huet anomaly based on augmented fast marching method and speeded up robust features.

PubMed

Sun, Minglei; Yang, Shaobao; Jiang, Jinling; Wang, Qiwei

2015-01-01

Pelger-Huet anomaly (PHA) and Pseudo Pelger-Huet anomaly (PPHA) are neutrophil with abnormal morphology. They have the bilobed or unilobed nucleus and excessive clumping chromatin. Currently, detection of this kind of cell mainly depends on the manual microscopic examination by a clinician, thus, the quality of detection is limited by the efficiency and a certain subjective consciousness of the clinician. In this paper, a detection method for PHA and PPHA is proposed based on karyomorphism and chromatin distribution features. Firstly, the skeleton of the nucleus is extracted using an augmented Fast Marching Method (AFMM) and width distribution is obtained through distance transform. Then, caryoplastin in the nucleus is extracted based on Speeded Up Robust Features (SURF) and a K-nearest-neighbor (KNN) classifier is constructed to analyze the features. Experiment shows that the sensitivity and specificity of this method achieved 87.5% and 83.33%, which means that the detection accuracy of PHA is acceptable. Meanwhile, the detection method should be helpful to the automatic morphological classification of blood cells.

High-Accuracy Ultrasound Contrast Agent Detection Method for Diagnostic Ultrasound Imaging Systems.

PubMed

Ito, Koichi; Noro, Kazumasa; Yanagisawa, Yukari; Sakamoto, Maya; Mori, Shiro; Shiga, Kiyoto; Kodama, Tetsuya; Aoki, Takafumi

2015-12-01

An accurate method for detecting contrast agents using diagnostic ultrasound imaging systems is proposed. Contrast agents, such as microbubbles, passing through a blood vessel during ultrasound imaging are detected as blinking signals in the temporal axis, because their intensity value is constantly in motion. Ultrasound contrast agents are detected by evaluating the intensity variation of a pixel in the temporal axis. Conventional methods are based on simple subtraction of ultrasound images to detect ultrasound contrast agents. Even if the subject moves only slightly, a conventional detection method will introduce significant error. In contrast, the proposed technique employs spatiotemporal analysis of the pixel intensity variation over several frames. Experiments visualizing blood vessels in the mouse tail illustrated that the proposed method performs efficiently compared with conventional approaches. We also report that the new technique is useful for observing temporal changes in microvessel density in subiliac lymph nodes containing tumors. The results are compared with those of contrast-enhanced computed tomography. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

[Application of the mixed programming with Labview and Matlab in biomedical signal analysis].

PubMed

Yu, Lu; Zhang, Yongde; Sha, Xianzheng

2011-01-01

This paper introduces the method of mixed programming with Labview and Matlab, and applies this method in a pulse wave pre-processing and feature detecting system. The method has been proved suitable, efficient and accurate, which has provided a new kind of approach for biomedical signal analysis.

Principal curve detection in complicated graph images

NASA Astrophysics Data System (ADS)

Liu, Yuncai; Huang, Thomas S.

2001-09-01

Finding principal curves in an image is an important low level processing in computer vision and pattern recognition. Principal curves are those curves in an image that represent boundaries or contours of objects of interest. In general, a principal curve should be smooth with certain length constraint and allow either smooth or sharp turning. In this paper, we present a method that can efficiently detect principal curves in complicated map images. For a given feature image, obtained from edge detection of an intensity image or thinning operation of a pictorial map image, the feature image is first converted to a graph representation. In graph image domain, the operation of principal curve detection is performed to identify useful image features. The shortest path and directional deviation schemes are used in our algorithm os principal verve detection, which is proven to be very efficient working with real graph images.

[The spectrum of human chromosomal aberrations detected by routine and differential (GTG) staining].

PubMed

Ponomareva, A V; Matveeva, V G; Osipova, L P

2001-01-01

As a result of sample cytogenetic studies of 23 persons living on the territory of Yamal-Nentsy Autonomous District and chronically exposed to the small doses of radiation the data on the frequency and spectrum of chromosome aberrations, detected by the routine and differential (GTG) staining were obtained. Comparative efficiency of these methods was determined. The absence of significant differences for the spectrum and frequencies of chromosome aberrations revealed by both methods was shown.

Inductance and resistance measurement method for vessel detection and coil powering in all-surface inductive heating systems composed of outer squircle coils

NASA Astrophysics Data System (ADS)

Kilic, Veli Tayfun; Unal, Emre; Demir, Hilmi Volkan

2017-05-01

In this work, we investigate a method proposed for vessel detection and coil powering in an all-surface inductive heating system composed of outer squircle coils. Besides conventional circular coils, coils with different shapes such as outer squircle coils are used for and enable efficient all-surface inductive heating. Validity of the method, which relies on measuring inductance and resistance values of a loaded coil at different frequencies, is experimentally demonstrated for a coil with shape different from conventional circular coil. Simple setup was constructed with a small coil to model an all-surface inductive heating system. Inductance and resistance maps were generated by measuring coil's inductance and resistance values at different frequencies loaded by a plate made of different materials and located at various positions. Results show that in an induction hob for various coil geometries it is possible to detect a vessel's presence, to identify its material type and to specify its position on the hob surface by considering inductance and resistance of the coil measured on at least two different frequencies. The studied method is important in terms of enabling safe, efficient and user flexible heating in an all-surface inductive heating system by automatically detecting the vessel's presence and powering on only the coils that are loaded by the vessel with predetermined current levels.

The research and development of the non-contact detection of the tubing internal thread with a line structured light

NASA Astrophysics Data System (ADS)

Hu, Yuanyuan; Xu, Yingying; Hao, Qun; Hu, Yao

2013-12-01

The tubing internal thread plays an irreplaceable role in the petroleum equipment. The unqualified tubing can directly lead to leakage, slippage and bring huge losses for oil industry. For the purpose of improving efficiency and precision of tubing internal thread detection, we develop a new non-contact tubing internal thread measurement system based on the laser triangulation principle. Firstly, considering that the tubing thread had a small diameter and relatively smooth surface, we built a set of optical system with a line structured light to irradiate the internal thread surface and obtain an image which contains the internal thread profile information through photoelectric sensor. Secondly, image processing techniques were used to do the edge detection of the internal thread from the obtained image. One key method was the sub-pixel technique which greatly improved the detection accuracy under the same hardware conditions. Finally, we restored the real internal thread contour information on the basis of laser triangulation method and calculated tubing thread parameters such as the pitch, taper and tooth type angle. In this system, the profile of several thread teeth can be obtained at the same time. Compared with other existing scanning methods using point light and stepper motor, this system greatly improves the detection efficiency. Experiment results indicate that this system can achieve the high precision and non-contact measurement of the tubing internal thread.

System and method for anomaly detection

DOEpatents

Scherrer, Chad

2010-06-15

A system and method for detecting one or more anomalies in a plurality of observations is provided. In one illustrative embodiment, the observations are real-time network observations collected from a stream of network traffic. The method includes performing a discrete decomposition of the observations, and introducing derived variables to increase storage and query efficiencies. A mathematical model, such as a conditional independence model, is then generated from the formatted data. The formatted data is also used to construct frequency tables which maintain an accurate count of specific variable occurrence as indicated by the model generation process. The formatted data is then applied to the mathematical model to generate scored data. The scored data is then analyzed to detect anomalies.

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.

Trace vapor detection of hydrogen peroxide: An effective approach to identification of improvised explosive devices

NASA Astrophysics Data System (ADS)

Xu, Miao

Vapor detection has been proven as one of the practical, noninvasive methods suitable for explosives detection among current explosive detection technologies. Optical methods (especially colorimetric and fluorescence spectral methods) are low in cost, provide simple instrumentation alignment, while still maintaining high sensitivity and selectivity, these factors combined facilitate broad field applications. Trace vapor detection of hydrogen peroxide (H2O2) represents an effective approach to noninvasive detection of peroxide-based explosives, though development of such a sensor system with high reliability and sufficient sensitivity (reactivity) still remains challenging. Three vapor sensor systems for H2O2 were proposed and developed in this study, which exploited specific chemical reaction towards H2O2 to ensure the selectivity, and materials surface engineering to afford efficient air sampling. The combination of these features enables expedient, cost effective, reliable detection of peroxide explosives. First, an expedient colorimetric sensor for H2O2 vapor was developed, which utilized the specific interaction between Ti(oxo) and H2O2 to offer a yellow color development. The Ti(oxo) salt can be blended into a cellulose microfibril network to produce tunable interface that can react with H2O2. The vapor detection limit can reach 400 ppb. To further improve the detection sensitivity, a naphthalimide based fluorescence turn-on sensor was designed and developed. The sensor mechanism was based on H2O2-mediated oxidation of a boronate fluorophore, which is nonfluorescent in ICT band, but becomes strongly fluorescent upon conversion into the phenol state. The detection limit of this sensory material was improved to be below 10 ppb. However, some technical factors such as sensor concentration, local environment, and excitation intensity were found difficult to control to make the sensor system sufficiently reproducible. To solve the problem, we developed a ratiometric fluorescence sensor, which allows for dual-band emission monitoring and thus enhances the detection reliability. Moreover, the significant spectral overlap between the fluorescence of the pristine sensor and the absorption of the reacted state enables effective Foster Resonance Energy Transfer (FRET). This FRET process can significantly enhance the fluorescence sensing efficiency in comparison to the normal single-band sensor system, for which the sensing efficiency is solely determined by the stoichiometric conversion of sensor molecules.

Using leaf optical properties to detect ozone effects on foliar biochemistry

USDA-ARS?s Scientific Manuscript database

Efficient methods for accurate and meaningful high-throughput plant phenotyping are limiting the development and breeding of stress-tolerant crops. A number of emerging techniques, specifically remote sensing methods, have been identified as promising tools for plant phenotyping. These remote-sensin...

Fighting detection using interaction energy force

NASA Astrophysics Data System (ADS)

Wateosot, Chonthisa; Suvonvorn, Nikom

2017-02-01

Fighting detection is an important issue in security aimed to prevent criminal or undesirable events in public places. Many researches on computer vision techniques have studied to detect the specific event in crowded scenes. In this paper we focus on fighting detection using social-based Interaction Energy Force (IEF). The method uses low level features without object extraction and tracking. The interaction force is modeled using the magnitude and direction of optical flows. A fighting factor is developed under this model to detect fighting events using thresholding method. An energy map of interaction force is also presented to identify the corresponding events. The evaluation is performed using NUSHGA and BEHAVE datasets. The results show the efficiency with high accuracy regardless of various conditions.

Nano-fabricated perpendicular magnetic anisotropy electrodes for lateral spin valves and observation of Nernst-Ettingshausen related signals

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

Chejanovsky, N.; Sharoni, A., E-mail: amos.sharoni@biu.ac.il

2014-08-21

Lateral spin valves (LSVs) are efficient structures for characterizing spin currents in spintronics devices. Most LSVs are based on ferromagnetic (FM) electrodes for spin-injection and detection. While there are advantages for using perpendicular magnetic anisotropy (PMA) FM, e.g., stability to nano-scaling, these have almost not been studied. This is mainly due to difficulties in fabricating PMA FMs in a lateral geometry. We present here an efficient method, based on ion-milling through an AlN mask, for fabrication of LSVs with multi-layered PMA FMs such as Co/Pd and Co/Ni. We demonstrate, using standard permalloy FMs, that the method enables efficient spin injection.more » We show the multi-layer electrodes retain their PMA properties as well as spin injection and detection in PMA LSVs. In addition, we find a large asymmetric voltage signal which increases with current. We attribute this to a Nernst-Ettingshausen effect caused by local Joule heating and the perpendicular magnetic easy axis.« less

An Efficient and Examinable Illegal Fallow Fields Detecting Method with Spatio-Temporal Information Integration

NASA Astrophysics Data System (ADS)

Chang, Chia-Hao; Chu, Tzu-How

2017-04-01

To control the rice production and farm usage in Taiwan, Agriculture and Food Agency (AFA) has published a series of policies to subsidize farmers to plant different crops or to practice fallow science 1983. Because of no efficient and examinable mechanism to verify the fallow fields surveyed by township office, illegal fallow fields were still repeated each year. In this research, we used remote sensing images, GIS data of Fields, and application records of fallow fields to establish an illegal fallow fields detecting method in Yulin County in central Taiwan. This method included: 1. collected multi-temporal images from FS-2 or SPOT series with 4 time periods; 2. combined the application records and GIS data of fields to verify the location of fallow fields; 3. conducted ground truth survey and classified images with ISODATA and Maximum Likelihood Classification (MLC); 4. defined the land cover type of fallow fields by zonal statistic; 5. verified accuracy with ground truth; 6. developed potential illegal fallow fields survey method and benefit estimation. We use 190 fallow fields with 127 legal and 63 illegal as ground truth and accuracies of illegal fallow field interpretation in producer and user are 71.43% and 38.46%. If township office surveyed 117 classified illegal fallow fields, 45 of 63 illegal fallow fields will be detected. By using our method, township office can save 38.42% of the manpower to detect illegal fallow fields and receive an examinable 71.43% producer accuracy.

Variable threshold method for ECG R-peak detection.

PubMed

Kew, Hsein-Ping; Jeong, Do-Un

2011-10-01

In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.

Electrochemiluminescence-PCR detection of genetically modified organisms

NASA Astrophysics Data System (ADS)

Liu, Jinfeng; Xing, Da; Shen, Xingyan; Zhu, Debin

2005-01-01

The detection methods for genetically modified (GM) components in foods have been developed recently. But many of them are complicated and time-consuming; some of them need to use the carcinogenic substance, and can"t avoid false-positive results. In this study, an electrochemiluminescence polymerase chain reaction (ECL-PCR) method for detection GM tobaccos is proposed. The Cauliflower mosaic virus 35S (CaMV35S) promoter was amplified by PCR, Then hybridized with a Ru(bpy)32+ (TBR)-labeled and a biotinylated probe. The hybridization products were captured onto streptavidin-coated paramagnetic beads, and detected by measuring the electrochemiluminescence (ECL) signal of the TBR label. Whether the tobaccos contain GM components was discriminated by detecting the ECL signal of CaMV35S promoter. The experiment results show that the detection limit for CaMV35S promoter is 100 fmol, and the GM components can be clearly identified in GM tobaccos. The ECL-PCR method provide a new means in GMOs detection due to its safety, simplicity and high efficiency.

Techniques of EMG signal analysis: detection, processing, classification and applications

PubMed Central

Hussain, M.S.; Mohd-Yasin, F.

2006-01-01

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications. PMID:16799694

Change Detection of Mobile LIDAR Data Using Cloud Computing

NASA Astrophysics Data System (ADS)

Liu, Kun; Boehm, Jan; Alis, Christian

2016-06-01

Change detection has long been a challenging problem although a lot of research has been conducted in different fields such as remote sensing and photogrammetry, computer vision, and robotics. In this paper, we blend voxel grid and Apache Spark together to propose an efficient method to address the problem in the context of big data. Voxel grid is a regular geometry representation consisting of the voxels with the same size, which fairly suites parallel computation. Apache Spark is a popular distributed parallel computing platform which allows fault tolerance and memory cache. These features can significantly enhance the performance of Apache Spark and results in an efficient and robust implementation. In our experiments, both synthetic and real point cloud data are employed to demonstrate the quality of our method.

Improvement of density resolution in short-pulse hard x-ray radiographic imaging using detector stacks

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

Borm, B.; Gärtner, F.; Khaghani, D.

2016-09-15

We demonstrate that stacking several imaging plates (IPs) constitutes an easy method to increase hard x-ray detection efficiency. Used to record x-ray radiographic images produced by an intense-laser driven hard x-ray backlighter source, the IP stacks resulted in a significant improvement of the radiograph density resolution. We attribute this to the higher quantum efficiency of the combined detectors, leading to a reduced photon noise. Electron-photon transport simulations of the interaction processes in the detector reproduce the observed contrast improvement. Increasing the detection efficiency to enhance radiographic imaging capabilities is equally effective as increasing the x-ray source yield, e.g., by amore » larger drive laser energy.« less

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

PubMed

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

2016-09-01

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

[Multiplex real-time PCR method for rapid detection of Marburg virus and Ebola virus].

PubMed

Yang, Yu; Bai, Lin; Hu, Kong-Xin; Yang, Zhi-Hong; Hu, Jian-Ping; Wang, Jing

2012-08-01

Marburg virus and Ebola virus are acute infections with high case fatality rates. A rapid, sensitive detection method was established to detect Marburg virus and Ebola virus by multiplex real-time fluorescence quantitative PCR. Designing primers and Taqman probes from highly conserved sequences of Marburg virus and Ebola virus through whole genome sequences alignment, Taqman probes labeled by FAM and Texas Red, the sensitivity of the multiplex real-time quantitative PCR assay was optimized by evaluating the different concentrations of primers and Probes. We have developed a real-time PCR method with the sensitivity of 30.5 copies/microl for Marburg virus positive plasmid and 28.6 copies/microl for Ebola virus positive plasmids, Japanese encephalitis virus, Yellow fever virus, Dengue virus were using to examine the specificity. The Multiplex real-time PCR assays provide a sensitive, reliable and efficient method to detect Marburg virus and Ebola virus simultaneously.

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

PubMed

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Yao, Rui; Zhang, Yanning; Jiang, Lei

2011-08-01

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

Research about Memory Detection Based on the Embedded Platform

NASA Astrophysics Data System (ADS)

Sun, Hao; Chu, Jian

As is known to us all, the resources of memory detection of the embedded systems are very limited. Taking the Linux-based embedded arm as platform, this article puts forward two efficient memory detection technologies according to the characteristics of the embedded software. Especially for the programs which need specific libraries, the article puts forwards portable memory detection methods to help program designers to reduce human errors,improve programming quality and therefore make better use of the valuable embedded memory resource.

Designing occupancy studies when false-positive detections occur

USGS Publications Warehouse

Clement, Matthew

2016-01-01

1.Recently, estimators have been developed to estimate occupancy probabilities when false-positive detections occur during presence-absence surveys. Some of these estimators combine different types of survey data to improve estimates of occupancy. With these estimators, there is a tradeoff between the number of sample units surveyed, and the number and type of surveys at each sample unit. Guidance on efficient design of studies when false positives occur is unavailable. 2.For a range of scenarios, I identified survey designs that minimized the mean square error of the estimate of occupancy. I considered an approach that uses one survey method and two observation states and an approach that uses two survey methods. For each approach, I used numerical methods to identify optimal survey designs when model assumptions were met and parameter values were correctly anticipated, when parameter values were not correctly anticipated, and when the assumption of no unmodelled detection heterogeneity was violated. 3.Under the approach with two observation states, false positive detections increased the number of recommended surveys, relative to standard occupancy models. If parameter values could not be anticipated, pessimism about detection probabilities avoided poor designs. Detection heterogeneity could require more or fewer repeat surveys, depending on parameter values. If model assumptions were met, the approach with two survey methods was inefficient. However, with poor anticipation of parameter values, with detection heterogeneity, or with removal sampling schemes, combining two survey methods could improve estimates of occupancy. 4.Ignoring false positives can yield biased parameter estimates, yet false positives greatly complicate the design of occupancy studies. Specific guidance for major types of false-positive occupancy models, and for two assumption violations common in field data, can conserve survey resources. This guidance can be used to design efficient monitoring programs and studies of species occurrence, species distribution, or habitat selection, when false positives occur during surveys.

Design of a novel noninvasive spectrometer for pesticide residues monitor

NASA Astrophysics Data System (ADS)

Ren, Zhong; Liu, Guodong; Huang, Zhen

2014-11-01

Although the gas or liquid chromatography had been widely used into pesticide residues monitoring, some drawbacks such as time-consuming, complicated operation and especially the destructivity for samples were existed. To overcome the limits of destructive detection methods, the noninvasive detection method based on spectroscopy was used to detect the pesticide residues in this paper. To overcome low resolution and light-efficiency due to the drawbacks of the classical plane and holography concave gratings, a novel noninvasive spectrometer for pesticide residues monitor (PRM) based on volume holography transmission (VHT) grating was designed. Meanwhile, a custom-built splitting light system for PRM based on the VHT grating was developed. In addition, the linear charge coupled device (CCD) with combined data acquisition (DAQ) card and the virtual-PRM based on LabVIEW were respectively used as the spectral acquisition hardware and software-platform. Experimental results showed that the spectral resolution of this spectrometer reached 2nm, and the VHT grating's diffraction efficiency was gotten via the simulation experiment.

Accounting for Limited Detection Efficiency and Localization Precision in Cluster Analysis in Single Molecule Localization Microscopy

PubMed Central

Shivanandan, Arun; Unnikrishnan, Jayakrishnan; Radenovic, Aleksandra

2015-01-01

Single Molecule Localization Microscopy techniques like PhotoActivated Localization Microscopy, with their sub-diffraction limit spatial resolution, have been popularly used to characterize the spatial organization of membrane proteins, by means of quantitative cluster analysis. However, such quantitative studies remain challenged by the techniques’ inherent sources of errors such as a limited detection efficiency of less than 60%, due to incomplete photo-conversion, and a limited localization precision in the range of 10 – 30nm, varying across the detected molecules, mainly depending on the number of photons collected from each. We provide analytical methods to estimate the effect of these errors in cluster analysis and to correct for them. These methods, based on the Ripley’s L(r) – r or Pair Correlation Function popularly used by the community, can facilitate potentially breakthrough results in quantitative biology by providing a more accurate and precise quantification of protein spatial organization. PMID:25794150

Paper-based archiving of biological samples from fish for detecting betanodavirus.

PubMed

Navaneeth Krishnan, A; Bhuvaneswari, T; Ezhil Praveena, P; Jithendran, K P

2016-07-01

This study was carried out to evaluate the efficiency of the Flinders Technology Associates (FTA(®)) card (Whatman(®)) as a sampling device and storage platform for RNA from betanodavirus-infected biological samples (viz., larvae, broodstock, cell culture supernatants and rearing seawater spiked with infected materials). The study showed that FTA cards can be used to detect betanodaviruses by reverse transcription-polymerase chain reaction (RT-PCR). The diagnostic efficiency of RT-PCR from all sample types on FTA cards decreased after 21 days of storage at 4 °C, although the virus could be detected up to 28 days by nested RT-PCR. The FTA card protocol thus provides a supplementary method for quick and easy collection of samples, preservation of RNA on a dry storage basis, and detection of betanodavirus-infected fish.

Measurement of tritium with high efficiency by using liquid scintillation counter with plastic scintillator.

PubMed

Furuta, Etsuko; Ohyama, Ryu-ichiro; Yokota, Shigeaki; Nakajo, Toshiya; Yamada, Yuka; Kawano, Takao; Uda, Tatsuhiko; Watanabe, Yasuo

2014-11-01

The detection efficiencies of tritium samples by using liquid scintillation counter with hydrophilic plastic scintillator (PS) was approximately 48% when the sample of 20 μL was held between 2 PS sheets treated by plasma. The activity and count rates showed a good relationship between 400 Bq to 410 KBq mL(-1). The calculated detection limit of 2 min measurement by the PS was 13 Bq mL(-1) when a confidence was 95%. The plasma method for PS produces no radioactive waste. Copyright © 2014 Elsevier Ltd. All rights reserved.

Efficient and Accurate Algorithm for Cleaved Fragments Prediction (CFPA) in Protein Sequences Dataset Based on Consensus and Its Variants: A Novel Degradomics Prediction Application.

PubMed

El-Assaad, Atlal; Dawy, Zaher; Nemer, Georges; Hajj, Hazem; Kobeissy, Firas H

2017-01-01

Degradomics is a novel discipline that involves determination of the proteases/substrate fragmentation profile, called the substrate degradome, and has been recently applied in different disciplines. A major application of degradomics is its utility in the field of biomarkers where the breakdown products (BDPs) of different protease have been investigated. Among the major proteases assessed, calpain and caspase proteases have been associated with the execution phases of the pro-apoptotic and pro-necrotic cell death, generating caspase/calpain-specific cleaved fragments. The distinction between calpain and caspase protein fragments has been applied to distinguish injury mechanisms. Advanced proteomics technology has been used to identify these BDPs experimentally. However, it has been a challenge to identify these BDPs with high precision and efficiency, especially if we are targeting a number of proteins at one time. In this chapter, we present a novel bioinfromatic detection method that identifies BDPs accurately and efficiently with validation against experimental data. This method aims at predicting the consensus sequence occurrences and their variants in a large set of experimentally detected protein sequences based on state-of-the-art sequence matching and alignment algorithms. After detection, the method generates all the potential cleaved fragments by a specific protease. This space and time-efficient algorithm is flexible to handle the different orientations that the consensus sequence and the protein sequence can take before cleaving. It is O(mn) in space complexity and O(Nmn) in time complexity, with N number of protein sequences, m length of the consensus sequence, and n length of each protein sequence. Ultimately, this knowledge will subsequently feed into the development of a novel tool for researchers to detect diverse types of selected BDPs as putative disease markers, contributing to the diagnosis and treatment of related disorders.

Clustering Categorical Data Using Community Detection Techniques

PubMed Central

2017-01-01

With the advent of the k-modes algorithm, the toolbox for clustering categorical data has an efficient tool that scales linearly in the number of data items. However, random initialization of cluster centers in k-modes makes it hard to reach a good clustering without resorting to many trials. Recently proposed methods for better initialization are deterministic and reduce the clustering cost considerably. A variety of initialization methods differ in how the heuristics chooses the set of initial centers. In this paper, we address the clustering problem for categorical data from the perspective of community detection. Instead of initializing k modes and running several iterations, our scheme, CD-Clustering, builds an unweighted graph and detects highly cohesive groups of nodes using a fast community detection technique. The top-k detected communities by size will define the k modes. Evaluation on ten real categorical datasets shows that our method outperforms the existing initialization methods for k-modes in terms of accuracy, precision, and recall in most of the cases. PMID:29430249

A method of immediate detection of objects with a near-zero apparent motion in series of CCD-frames

NASA Astrophysics Data System (ADS)

Savanevych, V. E.; Khlamov, S. V.; Vavilova, I. B.; Briukhovetskyi, A. B.; Pohorelov, A. V.; Mkrtichian, D. E.; Kudak, V. I.; Pakuliak, L. K.; Dikov, E. N.; Melnik, R. G.; Vlasenko, V. P.; Reichart, D. E.

2018-01-01

The paper deals with a computational method for detection of the solar system minor bodies (SSOs), whose inter-frame shifts in series of CCD-frames during the observation are commensurate with the errors in measuring their positions. These objects have velocities of apparent motion between CCD-frames not exceeding three rms errors (3σ) of measurements of their positions. About 15% of objects have a near-zero apparent motion in CCD-frames, including the objects beyond the Jupiter's orbit as well as the asteroids heading straight to the Earth. The proposed method for detection of the object's near-zero apparent motion in series of CCD-frames is based on the Fisher f-criterion instead of using the traditional decision rules that are based on the maximum likelihood criterion. We analyzed the quality indicators of detection of the object's near-zero apparent motion applying statistical and in situ modeling techniques in terms of the conditional probability of the true detection of objects with a near-zero apparent motion. The efficiency of method being implemented as a plugin for the Collection Light Technology (CoLiTec) software for automated asteroids and comets detection has been demonstrated. Among the objects discovered with this plugin, there was the sungrazing comet C/2012 S1 (ISON). Within 26 min of the observation, the comet's image has been moved by three pixels in a series of four CCD-frames (the velocity of its apparent motion at the moment of discovery was equal to 0.8 pixels per CCD-frame; the image size on the frame was about five pixels). Next verification in observations of asteroids with a near-zero apparent motion conducted with small telescopes has confirmed an efficiency of the method even in bad conditions (strong backlight from the full Moon). So, we recommend applying the proposed method for series of observations with four or more frames.

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

PubMed

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

2018-03-01

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

Investigation of the mixing efficiency of a chaotic micromixer using thermal lens spectrometry.

PubMed

Ghaleb, Khalil Abbas; Stephan, Khaled; Pittet, Patrick; Ferrigno, Rosaria; Georges, Joseph

2006-05-01

This work investigates the efficiency of a chaotic micromixer using thermal lens spectrometry. The outlet of the mixing device was connected to a thermal lens detection head integrating the probe beam optical fibers and the sample capillary. The chaotic micromixer consisted of a Y-shaped poly(dimethylsiloxane) (PDMS) microchip in which ribbed herringbone microstructures were etched on the floor of the main channel. Due to the solvent composition dependence of the thermal lens response, the photothermal method was shown to be highly sensitive to nonhomogeneous mixing compared to fluorescence detection. The apparatus was applied to the determination of Fe2+ with 1,10-phenanthroline using flow injection analysis; a limit of detection of 11 microg L(-1) of iron was obtained.

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

PubMed Central

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

2014-01-01

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

Background noise cancellation for improved acoustic detection of manatee vocalizations

NASA Astrophysics Data System (ADS)

Yan, Zheng; Niezrecki, Christopher; Beusse, Diedrich O.

2005-06-01

The West Indian manatee (Trichechus manatus latirostris) has become endangered partly because of an increase in the number of collisions with boats. A device to alert boaters of the presence of manatees, so that a collision can be avoided, is desired. A practical implementation of the technology is dependent on the hydrophone spacing and range of detection. These parameters are primarily dependent on the manatee vocalization strength, the decay of the signal's strength with distance, and the background noise levels. An efficient method to extend the detection range by using background noise cancellation is proposed in this paper. An adaptive line enhancer (ALE) that can detect and track narrow band signals buried in broadband noise is implemented to cancel the background noise. The results indicate that the ALE algorithm can efficiently extract the manatee calls from the background noise. The improved signal-to-noise ratio of the signal can be used to extend the range of detection of manatee vocalizations and reduce the false alarm and missing detection rate in their natural habitat. .

Background noise cancellation for improved acoustic detection of manatee vocalizations

NASA Astrophysics Data System (ADS)

Yan, Zheng; Niezrecki, Christopher; Beusse, Diedrich O.

2005-04-01

The West Indian manatee (Trichechus manatus latirostris) has become endangered partly because of an increase in the number of collisions with boats. A device to alert boaters of the presence of manatees, so that a collision can be avoided, is desired. Practical implementation of the technology is dependent on the hydrophone spacing and range of detection. These parameters are primarily dependent on the manatee vocalization strength, the decay of the signal strength with distance, and the background noise levels. An efficient method to extend the detection range by using background noise cancellation is proposed in this paper. An adaptive line enhancer (ALE) that can detect and track narrowband signals buried in broadband noise is implemented to cancel the background noise. The results indicate that the ALE algorithm can efficiently extract the manatee calls from the background noise. The improved signal-to-noise ratio of the signal can be used to extend the range of detection of manatee vocalizations and reduce the false alarm and missing detection rate in their natural habitat.

Development and Application of Quantitative Detection Method for Viral Hemorrhagic Septicemia Virus (VHSV) Genogroup IVa

PubMed Central

Kim, Jong-Oh; Kim, Wi-Sik; Kim, Si-Woo; Han, Hyun-Ja; Kim, Jin Woo; Park, Myoung Ae; Oh, Myung-Joo

2014-01-01

Viral hemorrhagic septicemia virus (VHSV) is a problematic pathogen in olive flounder (Paralichthys olivaceus) aquaculture farms in Korea. Thus, it is necessary to develop a rapid and accurate diagnostic method to detect this virus. We developed a quantitative RT-PCR (qRT-PCR) method based on the nucleocapsid (N) gene sequence of Korean VHSV isolate (Genogroup IVa). The slope and R2 values of the primer set developed in this study were −0.2928 (96% efficiency) and 0.9979, respectively. Its comparison with viral infectivity calculated by traditional quantifying method (TCID50) showed a similar pattern of kinetic changes in vitro and in vivo. The qRT-PCR method reduced detection time compared to that of TCID50, making it a very useful tool for VHSV diagnosis. PMID:24859343

A novel sensitivity-based method for damage detection of structures under unknown periodic excitations

NASA Astrophysics Data System (ADS)

Naseralavi, S. S.; Salajegheh, E.; Fadaee, M. J.; Salajegheh, J.

2014-06-01

This paper presents a technique for damage detection in structures under unknown periodic excitations using the transient displacement response. The method is capable of identifying the damage parameters without finding the input excitations. We first define the concept of displacement space as a linear space in which each point represents displacements of structure under an excitation and initial condition. Roughly speaking, the method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering this novel geometrical viewpoint, an equation called kernel parallelization equation (KPE) is derived for damage detection under unknown periodic excitations and a sensitivity-based algorithm for solving KPE is proposed accordingly. The method is evaluated via three case studies under periodic excitations, which confirm the efficiency of the proposed method.

Stability Analysis of Radial Turning Process for Superalloys

NASA Astrophysics Data System (ADS)

Jiménez, Alberto; Boto, Fernando; Irigoien, Itziar; Sierra, Basilio; Suarez, Alfredo

2017-09-01

Stability detection in machining processes is an essential component for the design of efficient machining processes. Automatic methods are able to determine when instability is happening and prevent possible machine failures. In this work a variety of methods are proposed for detecting stability anomalies based on the measured forces in the radial turning process of superalloys. Two different methods are proposed to determine instabilities. Each one is tested on real data obtained in the machining of Waspalloy, Haynes 282 and Inconel 718. Experimental data, in both Conventional and High Pressure Coolant (HPC) environments, are set in four different states depending on materials grain size and Hardness (LGA, LGS, SGA and SGS). Results reveal that PCA method is useful for visualization of the process and detection of anomalies in online processes.

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments

PubMed Central

Avalappampatty Sivasamy, Aneetha; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T2 method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T2 statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better. PMID:26357668

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments.

PubMed

Sivasamy, Aneetha Avalappampatty; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T(2) method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T(2) statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better.

An assessment of the efficiency of fungal DNA extraction methods for maximizing the detection of medically important fungi using PCR.

PubMed

Karakousis, A; Tan, L; Ellis, D; Alexiou, H; Wormald, P J

2006-04-01

To date, no single reported DNA extraction method is suitable for the efficient extraction of DNA from all fungal species. The efficiency of extraction is of particular importance in PCR-based medical diagnostic applications where the quantity of fungus in a tissue biopsy may be limited. We subjected 16 medically relevant fungi to physical, chemical and enzymatic cell wall disruption methods which constitutes the first step in extracting DNA. Examination by light microscopy showed that grinding with mortar and pestle was the most efficient means of disrupting the rigid fungal cell walls of hyphae and conidia. We then trialled several published DNA isolation protocols to ascertain the most efficient method of extraction. Optimal extraction was achieved by incorporating a lyticase and proteinase K enzymatic digestion step and adapting a DNA extraction procedure from a commercial kit (MO BIO) to generate high yields of high quality DNA from all 16 species. DNA quality was confirmed by the successful PCR amplification of the conserved region of the fungal 18S small-subunit rRNA multicopy gene.

Measuring the performance of two stationary interrogation systems for detecting downstream and upstream movement of PIT-tagged salmonids

USGS Publications Warehouse

Connolly, P.J.; Jezorek, I.G.; Martens, K.D.; Prentice, E.F.

2008-01-01

We tested the performance of two stationary interrogation systems designed for detecting the movement of fish with passive integrated transponder (PIT) tags. These systems allowed us to determine the direction of fish movement with high detection efficiency and high precision in a dynamic stream environment. We describe an indirect method for deriving an estimate for detection efficiency and the associated variance that does not rely on a known number of fish passing the system. By using six antennas arranged in a longitudinal series of three arrays, we attained detection efficiencies for downstream- and upstream-moving fish exceeding 96% during high-flow periods and approached 100% during low-flow periods for the two interrogation systems we tested. Because these systems did not rely on structural components, such as bridges or culverts, they were readily adaptable to remote, natural stream sites. Because of built-in redundancy, these systems were able to perform even with a loss of one or more antennas owing to dislodgement or electrical failure. However, the reduction in redundancy resulted in decreased efficiency and precision and the potential loss of ability to determine the direction of fish movement. What we learned about these systems should be applicable to a wide variety of other antenna configurations and to other types of PIT tags and transceivers.

Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Huang, Zifang; Luo, Hongli

In recent years, pervasive computing infrastructures have greatly improved the interaction between human and system. As we put more reliance on these computing infrastructures, we also face threats of network intrusion and/or any new forms of undesirable IT-based activities. Hence, network security has become an extremely important issue, which is closely connected with homeland security, business transactions, and people's daily life. Accurate and efficient intrusion detection technologies are required to safeguard the network systems and the critical information transmitted in the network systems. In this chapter, a novel network intrusion detection framework for mining and detecting sequential intrusion patterns is proposed. The proposed framework consists of a Collateral Representative Subspace Projection Modeling (C-RSPM) component for supervised classification, and an inter-transactional association rule mining method based on Layer Divided Modeling (LDM) for temporal pattern analysis. Experiments on the KDD99 data set and the traffic data set generated by a private LAN testbed show promising results with high detection rates, low processing time, and low false alarm rates in mining and detecting sequential intrusion detections.

A comparison of DNA fragmentation methods - Applications for the biochip technology.

PubMed

Sapojnikova, Nelly; Asatiani, Nino; Kartvelishvili, Tamar; Asanishvili, Lali; Zinkevich, Vitaly; Bogdarina, Irina; Mitchell, Julian; Al-Humam, Abdulmohsen

2017-08-20

The efficiency of hybridization signal detection in a biochip is affected by the method used for test DNA preparation, such as fragmentation, amplification and fluorescent labelling. DNA fragmentation is the commonest methods used and it is recognised as a critical step in biochip analysis. Currently methods used for DNA fragmentation are based either on sonication or on the enzymatic digestion. In this study, we compared the effect of different types of enzymatic DNA fragmentations, using DNase I to generate ssDNA breaks, NEBNext dsDNA fragmentase and SaqAI restrictase, on DNA labelling. DNA from different Desulfovibrio species was used as a substrate for these enzymes. Of the methods used, DNA fragmented by NEBNext dsDNA Fragmentase digestion was subsequently labelled with the greatest efficiency. As a result of this, the use of this enzyme to fragment target DNA increases the sensitivity of biochip-based detection significantly, and this is an important consideration when determining the presence of targeted DNA in ecological and medical samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Perrin and Förster unified: Dual-laser triple-polarization FRET (3polFRET) for interactions at the Förster-distance and beyond.

PubMed

Ungvári, Tamás; Gogolák, Péter; Bagdány, Miklós; Damjanovich, László; Bene, László

2016-04-01

Dual laser flow cytometric energy transfer (FCET)--elaborated by Trón et al. in 1984--is an efficient and rapid way of measuring FRET on large cell populations. FRET efficiency and the donor and acceptor concentrations are determined from one donor and two acceptor signals. In this communication this method is extended towards the domain of receptor dynamics by the detection of polarized components of the three intensities. By enabling a complete description of the proximity and dynamics of FRET-systems, the new measuring scheme allows a more refined description of both the structure and dynamics of cell surface receptor clusters at the nano-scale and beyond. Associated donor fraction, limiting anisotropy and rotational correlation time of the donor, acceptor anisotropy and cell-by-cell estimation of the orientation factor for FRET (κ2) are available in the steady state on a single FRET sample in a very rapid and statistically efficient way offered by flow cytometry. For a more sensitive detection of conformational changes the "polarized FRET indices"--quantities composed from FRET efficiency and anisotropies--are proposed. The method is illustrated by measurements on a FRET system with changing FRET-fraction and on a two donor-one acceptor-system, when the existence of receptor trimers are proven by the detection of "hetero-FRET induced homo-FRET relief", i.e. the diminishing of homo-FRET between the two donors in the presence of a donor quencher. The method also offers higher sensitivity for assessing conformational changes at the nano-scale, due to its capability for the simultaneous detection of changes of proximity and relative orientations of the FRET donor and acceptor. Although the method has been introduced in the context of FRET, it is more general: It can be used for monitoring triple-anisotropy correlations also in those cases when FRET actually does not occur, e.g. for interactions occuring beyond the Förster-distance R0. Interpretation of κ2 has been extended. Copyright © 2016 Elsevier B.V. All rights reserved.

Fast T Wave Detection Calibrated by Clinical Knowledge with Annotation of P and T Waves

PubMed Central

Elgendi, Mohamed; Eskofier, Bjoern; Abbott, Derek

2015-01-01

Background There are limited studies on the automatic detection of T waves in arrhythmic electrocardiogram (ECG) signals. This is perhaps because there is no available arrhythmia dataset with annotated T waves. There is a growing need to develop numerically-efficient algorithms that can accommodate the new trend of battery-driven ECG devices. Moreover, there is also a need to analyze long-term recorded signals in a reliable and time-efficient manner, therefore improving the diagnostic ability of mobile devices and point-of-care technologies. Methods Here, the T wave annotation of the well-known MIT-BIH arrhythmia database is discussed and provided. Moreover, a simple fast method for detecting T waves is introduced. A typical T wave detection method has been reduced to a basic approach consisting of two moving averages and dynamic thresholds. The dynamic thresholds were calibrated using four clinically known types of sinus node response to atrial premature depolarization (compensation, reset, interpolation, and reentry). Results The determination of T wave peaks is performed and the proposed algorithm is evaluated on two well-known databases, the QT and MIT-BIH Arrhythmia databases. The detector obtained a sensitivity of 97.14% and a positive predictivity of 99.29% over the first lead of the validation databases (total of 221,186 beats). Conclusions We present a simple yet very reliable T wave detection algorithm that can be potentially implemented on mobile battery-driven devices. In contrast to complex methods, it can be easily implemented in a digital filter design. PMID:26197321

High-resolution melting (HRM) assay for the detection of recurrent BRCA1/BRCA2 germline mutations in Tunisian breast/ovarian cancer families.

PubMed

Riahi, Aouatef; Kharrat, Maher; Lariani, Imen; Chaabouni-Bouhamed, Habiba

2014-12-01

Germline deleterious mutations in the BRCA1/BRCA2 genes are associated with an increased risk for the development of breast and ovarian cancer. Given the large size of these genes the detection of such mutations represents a considerable technical challenge. Therefore, the development of cost-effective and rapid methods to identify these mutations became a necessity. High resolution melting analysis (HRM) is a rapid and efficient technique extensively employed as high-throughput mutation scanning method. The purpose of our study was to assess the specificity and sensitivity of HRM for BRCA1 and BRCA2 genes scanning. As a first step we estimate the ability of HRM for detection mutations in a set of 21 heterozygous samples harboring 8 different known BRCA1/BRCA2 variations, all samples had been preliminarily investigated by direct sequencing, and then we performed a blinded analysis by HRM in a set of 68 further sporadic samples of unknown genotype. All tested heterozygous BRCA1/BRCA2 variants were easily identified. However the HRM assay revealed further alteration that we initially had not searched (one unclassified variant). Furthermore, sequencing confirmed all the HRM detected mutations in the set of unknown samples, including homozygous changes, indicating that in this cohort, with the optimized assays, the mutations detections sensitivity and specificity were 100 %. HRM is a simple, rapid and efficient scanning method for known and unknown BRCA1/BRCA2 germline mutations. Consequently the method will allow for the economical screening of recurrent mutations in Tunisian population.

A novel method for overlapping community detection using Multi-objective optimization

NASA Astrophysics Data System (ADS)

Ebrahimi, Morteza; Shahmoradi, Mohammad Reza; Heshmati, Zainabolhoda; Salehi, Mostafa

2018-09-01

The problem of community detection as one of the most important applications of network science can be addressed effectively by multi-objective optimization. In this paper, we aim to present a novel efficient method based on this approach. Also, in this study the idea of using all Pareto fronts to detect overlapping communities is introduced. The proposed method has two main advantages compared to other multi-objective optimization based approaches. The first advantage is scalability, and the second is the ability to find overlapping communities. Despite most of the works, the proposed method is able to find overlapping communities effectively. The new algorithm works by extracting appropriate communities from all the Pareto optimal solutions, instead of choosing the one optimal solution. Empirical experiments on different features of separated and overlapping communities, on both synthetic and real networks show that the proposed method performs better in comparison with other methods.

Multi person detection and tracking based on hierarchical level-set method

NASA Astrophysics Data System (ADS)

Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

2018-04-01

In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

A novel method based on learning automata for automatic lesion detection in breast magnetic resonance imaging.

PubMed

Salehi, Leila; Azmi, Reza

2014-07-01

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. In this way, magnetic resonance imaging (MRI) is emerging as a powerful tool for the detection of breast cancer. Breast MRI presently has two major challenges. First, its specificity is relatively poor, and it detects many false positives (FPs). Second, the method involves acquiring several high-resolution image volumes before, during, and after the injection of a contrast agent. The large volume of data makes the task of interpretation by the radiologist both complex and time-consuming. These challenges have led to the development of the computer-aided detection systems to improve the efficiency and accuracy of the interpretation process. Detection of suspicious regions of interests (ROIs) is a critical preprocessing step in dynamic contrast-enhanced (DCE)-MRI data evaluation. In this regard, this paper introduces a new automatic method to detect the suspicious ROIs for breast DCE-MRI based on region growing. The results indicate that the proposed method is thoroughly able to identify suspicious regions (accuracy of 75.39 ± 3.37 on PIDER breast MRI dataset). Furthermore, the FP per image in this method is averagely 7.92, which shows considerable improvement comparing to other methods like ROI hunter.

Detection of Organophosphorus Pesticides in Wheat by Ionic Liquid-Based Dispersive Liquid-Liquid Microextraction Combined with HPLC

PubMed Central

Quan, Ji; Hu, Zeshu

2018-01-01

Food safety issues closely related to human health have always received widespread attention from the world society. As a basic food source, wheat is the fundamental support of human survival; therefore, the detection of pesticide residues in wheat is very necessary. In this work, the ultrasonic-assisted ionic liquid-dispersive liquid-liquid microextraction (DLLME) method was firstly proposed, and the extraction and analysis of three organophosphorus pesticides were carried out by combining high-performance liquid chromatography (HPLC). The extraction efficiencies of three ionic liquids with bis(trifluoromethylsulfonyl)imide (Tf2N) anion were compared by extracting organophosphorus in wheat samples. It was found that the use of 1-octyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([OMIM][Tf2N]) had both high enrichment efficiency and appropriate extraction recovery. Finally, the method was used for the determination of three wheat samples, and the recoveries of them were 74.8–112.5%, 71.8–104.5%, and 83.8–115.5%, respectively. The results show that the method proposed is simple, fast, and efficient, which can be applied to the extraction of organic matters in wheat samples. PMID:29854562

LP-LPA: A link influence-based label propagation algorithm for discovering community structures in networks

NASA Astrophysics Data System (ADS)

Berahmand, Kamal; Bouyer, Asgarali

2018-03-01

Community detection is an essential approach for analyzing the structural and functional properties of complex networks. Although many community detection algorithms have been recently presented, most of them are weak and limited in different ways. Label Propagation Algorithm (LPA) is a well-known and efficient community detection technique which is characterized by the merits of nearly-linear running time and easy implementation. However, LPA has some significant problems such as instability, randomness, and monster community detection. In this paper, an algorithm, namely node’s label influence policy for label propagation algorithm (LP-LPA) was proposed for detecting efficient community structures. LP-LPA measures link strength value for edges and nodes’ label influence value for nodes in a new label propagation strategy with preference on link strength and for initial nodes selection, avoid of random behavior in tiebreak states, and efficient updating order and rule update. These procedures can sort out the randomness issue in an original LPA and stabilize the discovered communities in all runs of the same network. Experiments on synthetic networks and a wide range of real-world social networks indicated that the proposed method achieves significant accuracy and high stability. Indeed, it can obviously solve monster community problem with regard to detecting communities in networks.

Efficient computational methods to study new and innovative signal detection techniques in SETI

NASA Technical Reports Server (NTRS)

Deans, Stanley R.

1991-01-01

The purpose of the research reported here is to provide a rapid computational method for computing various statistical parameters associated with overlapped Hann spectra. These results are important for the Targeted Search part of the Search for ExtraTerrestrial Intelligence (SETI) Microwave Observing Project.

A hybrid approach for efficient anomaly detection using metaheuristic methods

PubMed Central

Ghanem, Tamer F.; Elkilani, Wail S.; Abdul-kader, Hatem M.

2014-01-01

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms. PMID:26199752

A hybrid approach for efficient anomaly detection using metaheuristic methods.

PubMed

Ghanem, Tamer F; Elkilani, Wail S; Abdul-Kader, Hatem M

2015-07-01

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

Comparison of flow cytometry, fluorescence microscopy and spectrofluorometry for analysis of gene electrotransfer efficiency.

PubMed

Marjanovič, Igor; Kandušer, Maša; Miklavčič, Damijan; Keber, Mateja Manček; Pavlin, Mojca

2014-12-01

In this study, we compared three different methods used for quantification of gene electrotransfer efficiency: fluorescence microscopy, flow cytometry and spectrofluorometry. We used CHO and B16 cells in a suspension and plasmid coding for GFP. The aim of this study was to compare and analyse the results obtained by fluorescence microscopy, flow cytometry and spectrofluorometry and in addition to analyse the applicability of spectrofluorometry for quantifying gene electrotransfer on cells in a suspension. Our results show that all the three methods detected similar critical electric field strength, around 0.55 kV/cm for both cell lines. Moreover, results obtained on CHO cells showed that the total fluorescence intensity and percentage of transfection exhibit similar increase in response to increase electric field strength for all the three methods. For B16 cells, there was a good correlation at low electric field strengths, but at high field strengths, flow cytometer results deviated from results obtained by fluorescence microscope and spectrofluorometer. Our study showed that all the three methods detected similar critical electric field strengths and high correlations of results were obtained except for B16 cells at high electric field strengths. The results also demonstrated that flow cytometry measures higher values of percentage transfection compared to microscopy. Furthermore, we have demonstrated that spectrofluorometry can be used as a simple and consistent method to determine gene electrotransfer efficiency on cells in a suspension.

Multitask assessment of roads and vehicles network (MARVN)

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Brain's tumor image processing using shearlet transform

NASA Astrophysics Data System (ADS)

Cadena, Luis; Espinosa, Nikolai; Cadena, Franklin; Korneeva, Anna; Kruglyakov, Alexey; Legalov, Alexander; Romanenko, Alexey; Zotin, Alexander

2017-09-01

Brain tumor detection is well known research area for medical and computer scientists. In last decades there has been much research done on tumor detection, segmentation, and classification. Medical imaging plays a central role in the diagnosis of brain tumors and nowadays uses methods non-invasive, high-resolution techniques, especially magnetic resonance imaging and computed tomography scans. Edge detection is a fundamental tool in image processing, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image has discontinuities. Shearlets is the most successful frameworks for the efficient representation of multidimensional data, capturing edges and other anisotropic features which frequently dominate multidimensional phenomena. The paper proposes an improved brain tumor detection method by automatically detecting tumor location in MR images, its features are extracted by new shearlet transform.

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

DOEpatents

Ray, Mark D.; Sedlacek, Arthur J.

2003-08-19

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

Detection method based on Kalman filter for high speed rail defect AE signal on wheel-rail rolling rig

NASA Astrophysics Data System (ADS)

Hao, Qiushi; Shen, Yi; Wang, Yan; Zhang, Xin

2018-01-01

Nondestructive test (NDT) of rails has been carried out intermittently in traditional approaches, which highly restricts the detection efficiency under rapid development of high speed railway nowadays. It is necessary to put forward a dynamic rail defect detection method for rail health monitoring. Acoustic emission (AE) as a practical real-time detection technology takes advantage of dynamic AE signal emitted from plastic deformation of material. Detection capacities of AE on rail defects have been verified due to its sensitivity and dynamic merits. Whereas the application under normal train service circumstance has been impeded by synchronous background noises, which are directly linked to the wheel speed. In this paper, surveys on a wheel-rail rolling rig are performed to investigate defect AE signals with varying speed. A dynamic denoising method based on Kalman filter is proposed and its detection effectiveness and flexibility are demonstrated by theory and computational results. Moreover, after comparative analysis of modelling precision at different speeds, it is predicted that the method is also applicable for high speed condition beyond experiments.

Detection of Coronal Mass Ejections Using Multiple Features and Space-Time Continuity

NASA Astrophysics Data System (ADS)

Zhang, Ling; Yin, Jian-qin; Lin, Jia-ben; Feng, Zhi-quan; Zhou, Jin

2017-07-01

Coronal Mass Ejections (CMEs) release tremendous amounts of energy in the solar system, which has an impact on satellites, power facilities and wireless transmission. To effectively detect a CME in Large Angle Spectrometric Coronagraph (LASCO) C2 images, we propose a novel algorithm to locate the suspected CME regions, using the Extreme Learning Machine (ELM) method and taking into account the features of the grayscale and the texture. Furthermore, space-time continuity is used in the detection algorithm to exclude the false CME regions. The algorithm includes three steps: i) define the feature vector which contains textural and grayscale features of a running difference image; ii) design the detection algorithm based on the ELM method according to the feature vector; iii) improve the detection accuracy rate by using the decision rule of the space-time continuum. Experimental results show the efficiency and the superiority of the proposed algorithm in the detection of CMEs compared with other traditional methods. In addition, our algorithm is insensitive to most noise.

Fault detection and diagnosis in asymmetric multilevel inverter using artificial neural network

NASA Astrophysics Data System (ADS)

Raj, Nithin; Jagadanand, G.; George, Saly

2018-04-01

The increased component requirement to realise multilevel inverter (MLI) fallout in a higher fault prospect due to power semiconductors. In this scenario, efficient fault detection and diagnosis (FDD) strategies to detect and locate the power semiconductor faults have to be incorporated in addition to the conventional protection systems. Even though a number of FDD methods have been introduced in the symmetrical cascaded H-bridge (CHB) MLIs, very few methods address the FDD in asymmetric CHB-MLIs. In this paper, the gate-open circuit FDD strategy in asymmetric CHB-MLI is presented. Here, a single artificial neural network (ANN) is used to detect and diagnose the fault in both binary and trinary configurations of the asymmetric CHB-MLIs. In this method, features of the output voltage of the MLIs are used as to train the ANN for FDD method. The results prove the validity of the proposed method in detecting and locating the fault in both asymmetric MLI configurations. Finally, the ANN response to the input parameter variation is also analysed to access the performance of the proposed ANN-based FDD strategy.

The development of methods for the detection of Salmonella in chickens by a combination of immunomagnetic separation and PCRs.

PubMed

Dai, Fengying; Zhang, Miao; Xu, Dixin; Yang, Yin; Wang, Jiaxiao; Li, Mingzhen; Du, Meihong

2017-11-01

Micro- and nanoimmunomagnetic beads (MIMBs and NIMBs) used for immunomagnetic separation (IMS) with PCR were studied for the rapid detection of Salmonella. The capture efficiency of the two different IMBs was evaluated by a conventional plate counting method, and the binding pattern was studied using scanning electron microscopy. The specificity of the IMBs was tested with Salmonella, Shigella flexneri, enterohemorrhagic Escherichia coli O157:H7, and Listeria monocytogenes. By comparing the pre-enrichment IMS and the IMS enrichment steps with a 5.5-H enrichment time, this study developed a rapid and sensitive method for the detection of Salmonella in chicken. The method was implemented by IMS enrichment and PCR with MIMBs and NIMBs, with a total analysis time of 8 H. We showed that the method was sensitive based on NIMBs with a detection limit of 10° CFU for Salmonella in 25 g of chicken. © 2016 International Union of Biochemistry and Molecular Biology, Inc.

Checklist and "Pollard Walk" butterfly survey methods on public lands

USGS Publications Warehouse

Royer, Ronald A.; Austin, Jane E.; Newton, Wesley E.

1998-01-01

Checklist and “Pollard Walk” butterfly survey methods were contemporaneously applied to seven public sites in North Dakota during the summer of 1995. Results were compared for effect of method and site on total number of butterflies and total number of species detected per hour. Checklist searching produced significantly more butterfly detections per hour than Pollard Walks at all sites. Number of species detected per hour did not differ significantly either among sites or between methods. Many species were detected by only one method, and at most sites generalist and invader species were more likely to be observed during checklist searches than during Pollard Walks. Results indicate that checklist surveys are a more efficient means for initial determination of a species list for a site, whereas for long-term monitoring the Pollard Walk is more practical and statistically manageable. Pollard Walk transects are thus recommended once a prairie butterfly fauna has been defined for a site by checklist surveys.

Study on methenamine detection in starch products through SERS technology

NASA Astrophysics Data System (ADS)

Cui, Yu; Qu, Zhou

2016-01-01

Using silver sol as a strengthened base, this paper concludes that l0ppb-0.1ppb methenamine aqueous solution has a better signal in 1052cm-1 Raman feature. And the lower limit of the aqueous solution is about 0.1ppb. Adding corresponding amount methenamine in vermicelli sample, the lower limit is about 10ppm. This is a safest and pollution-free detection process. Furthermore, the pretreatment process is simple, which will be finished in 20 minutes. Hence, it is better than other detection methods. SERS technology provides a simple, rapid and efficient detection method for field measurement and real time detection modulating disk of component, laser zooming system. Through the use of laser diode, Laser-beam riding guided system is likely to have smaller shape and very light.

Morphogenesis of early stage melanoma

NASA Astrophysics Data System (ADS)

Chatelain, Clément; Amar, Martine Ben

2015-08-01

Melanoma early detection is possible by simple skin examination and can insure a high survival probability when successful. However it requires efficient methods for identifying malignant lesions from common moles. This paper provides an overview first of the biological and physical mechanisms controlling melanoma early evolution, and then of the clinical tools available today for detecting melanoma in vivo at an early stage. It highlights the lack of diagnosis methods rationally linking macroscopic observables to the microscopic properties of the tissue, which define the malignancy of the tumor. The possible inputs of multiscale models for improving these methods are shortly discussed.

Damage diagnosis algorithm using a sequential change point detection method with an unknown distribution for damage

NASA Astrophysics Data System (ADS)

Noh, Hae Young; Rajagopal, Ram; Kiremidjian, Anne S.

2012-04-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method for the cases where the post-damage feature distribution is unknown a priori. This algorithm extracts features from structural vibration data using time-series analysis and then declares damage using the change point detection method. The change point detection method asymptotically minimizes detection delay for a given false alarm rate. The conventional method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori. Therefore, our algorithm estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using multiple sets of simulated data and a set of experimental data collected from a four-story steel special moment-resisting frame. Our algorithm was able to estimate the post-damage distribution consistently and resulted in detection delays only a few seconds longer than the delays from the conventional method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

A long-term target detection approach in infrared image sequence

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

DNA methods: critical review of innovative approaches.

PubMed

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

2002-01-01

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

Detection of mouse liver cancer via a parallel iterative shrinkage method in hybrid optical/microcomputed tomography imaging

NASA Astrophysics Data System (ADS)

Wu, Ping; Liu, Kai; Zhang, Qian; Xue, Zhenwen; Li, Yongbao; Ning, Nannan; Yang, Xin; Li, Xingde; Tian, Jie

2012-12-01

Liver cancer is one of the most common malignant tumors worldwide. In order to enable the noninvasive detection of small liver tumors in mice, we present a parallel iterative shrinkage (PIS) algorithm for dual-modality tomography. It takes advantage of microcomputed tomography and multiview bioluminescence imaging, providing anatomical structure and bioluminescence intensity information to reconstruct the size and location of tumors. By incorporating prior knowledge of signal sparsity, we associate some mathematical strategies including specific smooth convex approximation, an iterative shrinkage operator, and affine subspace with the PIS method, which guarantees the accuracy, efficiency, and reliability for three-dimensional reconstruction. Then an in vivo experiment on the bead-implanted mouse has been performed to validate the feasibility of this method. The findings indicate that a tiny lesion less than 3 mm in diameter can be localized with a position bias no more than 1 mm the computational efficiency is one to three orders of magnitude faster than the existing algorithms; this approach is robust to the different regularization parameters and the lp norms. Finally, we have applied this algorithm to another in vivo experiment on an HCCLM3 orthotopic xenograft mouse model, which suggests the PIS method holds the promise for practical applications of whole-body cancer detection.

Underwater Turbulence Detection Using Gated Wavefront Sensing Technique

PubMed Central

Bi, Ying; Xu, Xiping; Chow, Eddy Mun Tik

2018-01-01

Laser sensing has been applied in various underwater applications, ranging from underwater detection to laser underwater communications. However, there are several great challenges when profiling underwater turbulence effects. Underwater detection is greatly affected by the turbulence effect, where the acquired image suffers excessive noise, blurring, and deformation. In this paper, we propose a novel underwater turbulence detection method based on a gated wavefront sensing technique. First, we elaborate on the operating principle of gated wavefront sensing and wavefront reconstruction. We then setup an experimental system in order to validate the feasibility of our proposed method. The effect of underwater turbulence on detection is examined at different distances, and under different turbulence levels. The experimental results obtained from our gated wavefront sensing system indicate that underwater turbulence can be detected and analyzed. The proposed gated wavefront sensing system has the advantage of a simple structure and high detection efficiency for underwater environments. PMID:29518889

Infrared dim target detection based on visual attention

NASA Astrophysics Data System (ADS)

Wang, Xin; Lv, Guofang; Xu, Lizhong

2012-11-01

Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. Based on human visual attention mechanisms, an automatic detection algorithm for infrared dim target is presented. After analyzing the characteristics of infrared dim target images, the method firstly designs Difference of Gaussians (DoG) filters to compute the saliency map. Then the salient regions where the potential targets exist in are extracted by searching through the saliency map with a control mechanism of winner-take-all (WTA) competition and inhibition-of-return (IOR). At last, these regions are identified by the characteristics of the dim IR targets, so the true targets are detected, and the spurious objects are rejected. The experiments are performed for some real-life IR images, and the results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

Column-coupling strategies for multidimensional electrophoretic separation techniques.

PubMed

Kler, Pablo A; Sydes, Daniel; Huhn, Carolin

2015-01-01

Multidimensional electrophoretic separations represent one of the most common strategies for dealing with the analysis of complex samples. In recent years we have been witnessing the explosive growth of separation techniques for the analysis of complex samples in applications ranging from life sciences to industry. In this sense, electrophoretic separations offer several strategic advantages such as excellent separation efficiency, different methods with a broad range of separation mechanisms, and low liquid consumption generating less waste effluents and lower costs per analysis, among others. Despite their impressive separation efficiency, multidimensional electrophoretic separations present some drawbacks that have delayed their extensive use: the volumes of the columns, and consequently of the injected sample, are significantly smaller compared to other analytical techniques, thus the coupling interfaces between two separations components must be very efficient in terms of providing geometrical precision with low dead volume. Likewise, very sensitive detection systems are required. Additionally, in electrophoretic separation techniques, the surface properties of the columns play a fundamental role for electroosmosis as well as the unwanted adsorption of proteins or other complex biomolecules. In this sense the requirements for an efficient coupling for electrophoretic separation techniques involve several aspects related to microfluidics and physicochemical interactions of the electrolyte solutions and the solid capillary walls. It is interesting to see how these multidimensional electrophoretic separation techniques have been used jointly with different detection techniques, for intermediate detection as well as for final identification and quantification, particularly important in the case of mass spectrometry. In this work we present a critical review about the different strategies for coupling two or more electrophoretic separation techniques and the different intermediate and final detection methods implemented for such separations.

Successful application of frequency-domain airborne electromagnetic system with a grounded electric source

NASA Astrophysics Data System (ADS)

Kang, L.; Lin, J.; Liu, C.; Zhou, H.; Ren, T.; Yao, Y.

2017-12-01

A new frequency-domain AEM system with a grounded electric source, which was called ground-airborne frequency-domain electromagnetic (GAFEM) system, was proposed to extend penetration depth without compromising the resolution and detection efficiency. In GAFEM system, an electric source was placed on the ground to enlarge the strength of response signals. UVA was chosen as aircraft to reduce interaction noise and improve its ability to adapt to complex terrain. Multi-source and multi-frequency emission method has been researched and applied to improve the efficiency of GAFEM system. 2n pseudorandom sequence was introduced as transmitting waveform, to ensure resolution and detection efficiency. Inversion-procedure based on full-space apparent resistivity formula was built to realize GAFEM method and extend the survey area to non-far field. Based on GAFEM system, two application was conducted in Changchun, China, to map the deep conductive structure. As shown in the results of this exploration, GAFEM system shows its effectiveness to conductive structure, obtaining a depth of about 1km with a source-receiver distance of over 6km. And it shows the same level of resolution with CSAMT method with an over 10 times of efficiency. This extended a range of important applications where the terrain is too complex to be accessed or large penetration depth is required in a large survey area.

Detection of gamma-neutron radiation by solid-state scintillation detectors. Detection of gamma-neutron radiation by novel solid-state scintillation detectors

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

Ryzhikov, V.; Grinyov, B.; Piven, L.

It is known that solid-state scintillators can be used for detection of both gamma radiation and neutron flux. In the past, neutron detection efficiencies of such solid-state scintillators did not exceed 5-7%. At the same time it is known that the detection efficiency of the gamma-neutron radiation characteristic of nuclear fissionable materials is by an order of magnitude higher than the efficiency of detection of neutron fluxes alone. Thus, an important objective is the creation of detection systems that are both highly efficient in gamma-neutron detection and also capable of exhibiting high gamma suppression for use in the role ofmore » detection of neutron radiation. In this work, we present the results of our experimental and theoretical studies on the detection efficiency of fast neutrons from a {sup 239}Pu-Be source by the heavy oxide scintillators BGO, GSO, CWO and ZWO, as well as ZnSe(Te, O). The most probable mechanism of fast neutron interaction with nuclei of heavy oxide scintillators is the inelastic scattering (n, n'γ) reaction. In our work, fast neutron detection efficiencies were determined by the method of internal counting of gamma-quanta that emerge in the scintillator from (n, n''γ) reactions on scintillator nuclei with the resulting gamma energies of ∼20-300 keV. The measured efficiency of neutron detection for the scintillation crystals we considered was ∼40-50 %. The present work included a detailed analysis of detection efficiency as a function of detector and area of the working surface, as well as a search for new ways to create larger-sized detectors of lower cost. As a result of our studies, we have found an unusual dependence of fast neutron detection efficiency upon thickness of the oxide scintillators. An explanation for this anomaly may involve the competition of two factors that accompany inelastic scattering on the heavy atomic nuclei. The transformation of the energy spectrum of neutrons involved in the (n, n'γ) reactions towards lower energies and the isotropic character of scattering of the secondary neutrons may lead to the observed limitation of the length of effective interaction, since a fraction of the secondary neutrons that propagate in the forward direction are not subject to further inelastic scattering because of their substantially lower energy. At these reduced energies, it is the capture cross-section (n, γ) that becomes predominant, resulting in lower detection efficiency. Based on these results, several types of detectors have been envisioned for application in detection systems for nuclear materials. The testing results for one such detector are presented in this work. We have studied the possibility of creation of a composite detector with scintillator granules placed inside a transparent polymer material. Because of the low transparency of such a dispersed scintillator, better light collection conditions are ensured by incorporation of a light guide between the scintillator layers. This guide is made of highly transparent polymer material. The use of a high-transparency hydrogen-containing polymer material for light guides not only ensures optimum conditions of light collection in the detector, but also allows certain deceleration of neutron radiation, increasing its interaction efficiency with the composite scintillation panels; accordingly, the detector signal is increased by 5-8%. When fast neutrons interact with the scintillator material, the resulting inelastic scattering gamma-quanta emerge, having different energies and different delay times with respect to the moment of the neutron interaction with the nucleus of the scintillator material (delay times ranging from 1x10{sup -9} to 1.3x10{sup -6} s). These internally generated gamma-quanta interact with the scintillator, and the resulting scintillation light is recorded by the photo-receiver. Since neutron sources are also strong sources of low-energy gamma-radiation, the use of dispersed ZnSe(Te) scintillator material provides high gamma-radiation detection efficiency in that energy range. This new type of gamma-neutron detector is based on a 'sandwich' structure using a ZnSe composite film and light guide with a fast neutron detection efficiency of about 6%. Its high detection efficiency of low-energy gamma-radiation allows a substantial increase (by an order of magnitude) in the efficiency of detection of neutron sources and transuranic materials by means of simultaneous detection of accompanying gamma-radiation. The design and fabrication technology of this detector allows the creation of gamma-neutron detectors characterized by high sensitivity at relatively low costs (as compared with analogs using oxide scintillators) for portable inspection systems. The sandwich structure can be comprised of any number of plates, with no limitations on thickness or area.« less

Multigrid contact detection method

NASA Astrophysics Data System (ADS)

He, Kejing; Dong, Shoubin; Zhou, Zhaoyao

2007-03-01

Contact detection is a general problem of many physical simulations. This work presents a O(N) multigrid method for general contact detection problems (MGCD). The multigrid idea is integrated with contact detection problems. Both the time complexity and memory consumption of the MGCD are O(N) . Unlike other methods, whose efficiencies are influenced strongly by the object size distribution, the performance of MGCD is insensitive to the object size distribution. We compare the MGCD with the no binary search (NBS) method and the multilevel boxing method in three dimensions for both time complexity and memory consumption. For objects with similar size, the MGCD is as good as the NBS method, both of which outperform the multilevel boxing method regarding memory consumption. For objects with diverse size, the MGCD outperform both the NBS method and the multilevel boxing method. We use the MGCD to solve the contact detection problem for a granular simulation system based on the discrete element method. From this granular simulation, we get the density property of monosize packing and binary packing with size ratio equal to 10. The packing density for monosize particles is 0.636. For binary packing with size ratio equal to 10, when the number of small particles is 300 times as the number of big particles, the maximal packing density 0.824 is achieved.

Highly Sensitive GMO Detection Using Real-Time PCR with a Large Amount of DNA Template: Single-Laboratory Validation.

PubMed

Mano, Junichi; Hatano, Shuko; Nagatomi, Yasuaki; Futo, Satoshi; Takabatake, Reona; Kitta, Kazumi

2018-03-01

Current genetically modified organism (GMO) detection methods allow for sensitive detection. However, a further increase in sensitivity will enable more efficient testing for large grain samples and reliable testing for processed foods. In this study, we investigated real-time PCR-based GMO detection methods using a large amount of DNA template. We selected target sequences that are commonly introduced into many kinds of GM crops, i.e., 35S promoter and nopaline synthase (NOS) terminator. This makes the newly developed method applicable to a wide range of GMOs, including some unauthorized ones. The estimated LOD of the new method was 0.005% of GM maize events; to the best of our knowledge, this method is the most sensitive among the GM maize detection methods for which the LOD was evaluated in terms of GMO content. A 10-fold increase in the DNA amount as compared with the amount used under common testing conditions gave an approximately 10-fold reduction in the LOD without PCR inhibition. Our method is applicable to various analytical samples, including processed foods. The use of other primers and fluorescence probes would permit highly sensitive detection of various recombinant DNA sequences besides the 35S promoter and NOS terminator.

Simultaneous Detection of Genetically Modified Organisms in a Mixture by Multiplex PCR-Chip Capillary Electrophoresis.

PubMed

Patwardhan, Supriya; Dasari, Srikanth; Bhagavatula, Krishna; Mueller, Steffen; Deepak, Saligrama Adavigowda; Ghosh, Sudip; Basak, Sanjay

2015-01-01

An efficient PCR-based method to trace genetically modified food and feed products is in demand due to regulatory requirements and contaminant issues in India. However, post-PCR detection with conventional methods has limited sensitivity in amplicon separation that is crucial in multiplexing. The study aimed to develop a sensitive post-PCR detection method by using PCR-chip capillary electrophoresis (PCR-CCE) to detect and identify specific genetically modified organisms in their genomic DNA mixture by targeting event-specific nucleotide sequences. Using the PCR-CCE approach, novel multiplex methods were developed to detect MON531 cotton, EH 92-527-1 potato, Bt176 maize, GT73 canola, or GA21 maize simultaneously when their genomic DNAs in mixtures were amplified using their primer mixture. The repeatability RSD (RSDr) of the peak migration time was 0.06 and 3.88% for the MON531 and Bt176, respectively. The RSD (RSDR) of the Cry1Ac peak ranged from 0.12 to 0.40% in multiplex methods. The method was sensitive in resolving amplicon of size difference up to 4 bp. The PCR-CCE method is suitable to detect multiple genetically modified events in a composite DNA sample by tagging their event specific sequences.

Study on the Automatic Detection Method and System of Multifunctional Hydrocephalus Shunt

NASA Astrophysics Data System (ADS)

Sun, Xuan; Wang, Guangzhen; Dong, Quancheng; Li, Yuzhong

2017-07-01

Aiming to the difficulty of micro pressure detection and the difficulty of micro flow control in the testing process of hydrocephalus shunt, the principle of the shunt performance detection was analyzed.In this study, the author analyzed the principle of several items of shunt performance detection,and used advanced micro pressure sensor and micro flow peristaltic pump to overcome the micro pressure detection and micro flow control technology.At the same time,This study also puted many common experimental projects integrated, and successfully developed the automatic detection system for a shunt performance detection function, to achieve a test with high precision, high efficiency and automation.

Immunoliposome-based immunomagnetic concentration and separation assay for rapid detection of Cronobacter sakazakii.

PubMed

Shukla, Shruti; Lee, Gibaek; Song, Xinjie; Park, Sunhyun; Kim, Myunghee

2016-03-15

This study aimed to develop an immunoliposome-based immunomagnetic concentration and separation assay for the rapid detection of Cronobacter sakazakii (C. sakazakii), an acute opportunistic foodborne pathogenic bacterium, in both pure culture and infant formula. To develop the assay, magnetic nanoparticles (diameter 30 nm) were coated with immunoglobulin G (IgG), specifically anti-C. sakazakii IgG, and applied for the sensitive and efficient detection of C. sakazakii using immunoliposomes. The binding efficiency of anti-C. sakazakii IgG to the magnetic nanoparticles was 86.23 ± 0.59%. The assay developed in this study detected as few as 3.3 × 10(3) CFUmL(-1) of C. sakazakii in pure culture within 2h 30 min; in comparison, an indirect non-competitive enzyme-linked immunosorbent assay was able to detect 6.2 × 10(5) CFUmL(-1) of C. sakazakii in pure culture after 17 h. The developed assay did not show any cross-reactivity with other Cronobacter spp. or pathogens belonging to other genera. In addition, the method was able to detect 10(3) CFUmL(-1) of C. sakazakii in infant formula without any pre-incubation. These results confirm that the immunoliposome-based immunomagnetic concentration and separation assay may facilitate highly sensitive, efficient, and rapid detection of C. sakazakii. Copyright © 2015 Elsevier B.V. All rights reserved.

Improved Determination of the Neutron Lifetime

NASA Astrophysics Data System (ADS)

Yue, A.

2013-10-01

The most precise determination of the neutron lifetime using the beam method reported a result of τn = (886 . 3 +/- 3 . 4) s. The dominant uncertainties were attributed to the absolute determination of the fluence of the neutron beam (2.7 s). The fluence was determined with a monitor that counted the neutron-induced charged particles from absorption in a thin, well-characterized 6Li deposit. The detection efficiency of the monitor was calculated from the areal density of the deposit, the detector solid angle, and the ENDF/B-VI 6Li(n,t)4He thermal neutron cross section. We have used a second, totally-absorbing neutron detector to directly measure the detection efficiency of the monitor on a monochromatic neutron beam of precisely known wavelength. This method does not rely on the 6Li(n,t)4He cross section or any other nuclear data. The monitor detection efficiency was measured to an uncertainty of 0.06%, which represents a five-fold improvement in uncertainty. We have verified the temporal stability of the monitor with ancillary measurements, and the measured neutron monitor efficiency has been used to improve the fluence determination in the past lifetime experiment. An updated neutron lifetime based on the improved fluence determination will be presented. Work done in collaboration with M. Dewey, D. Gilliam, J. Nico, National Institute of Standards and Technology; G. Greene, University of Tennessee / Oak Ridge National Laboratory; A. Laptev, Los Alamos National Laboratory; W. Snow, Indiana University; and F. Wietfeldt, Tulane University.

Automatic detection of sleep apnea based on EEG detrended fluctuation analysis and support vector machine.

PubMed

Zhou, Jing; Wu, Xiao-ming; Zeng, Wei-jie

2015-12-01

Sleep apnea syndrome (SAS) is prevalent in individuals and recently, there are many studies focus on using simple and efficient methods for SAS detection instead of polysomnography. However, not much work has been done on using nonlinear behavior of the electroencephalogram (EEG) signals. The purpose of this study is to find a novel and simpler method for detecting apnea patients and to quantify nonlinear characteristics of the sleep apnea. 30 min EEG scaling exponents that quantify power-law correlations were computed using detrended fluctuation analysis (DFA) and compared between six SAS and six healthy subjects during sleep. The mean scaling exponents were calculated every 30 s and 360 control values and 360 apnea values were obtained. These values were compared between the two groups and support vector machine (SVM) was used to classify apnea patients. Significant difference was found between EEG scaling exponents of the two groups (p < 0.001). SVM was used and obtained high and consistent recognition rate: average classification accuracy reached 95.1% corresponding to the sensitivity 93.2% and specificity 98.6%. DFA of EEG is an efficient and practicable method and is helpful clinically in diagnosis of sleep apnea.

Fast Edge Detection and Segmentation of Terrestrial Laser Scans Through Normal Variation Analysis

NASA Astrophysics Data System (ADS)

Che, E.; Olsen, M. J.

2017-09-01

Terrestrial Laser Scanning (TLS) utilizes light detection and ranging (lidar) to effectively and efficiently acquire point cloud data for a wide variety of applications. Segmentation is a common procedure of post-processing to group the point cloud into a number of clusters to simplify the data for the sequential modelling and analysis needed for most applications. This paper presents a novel method to rapidly segment TLS data based on edge detection and region growing. First, by computing the projected incidence angles and performing the normal variation analysis, the silhouette edges and intersection edges are separated from the smooth surfaces. Then a modified region growing algorithm groups the points lying on the same smooth surface. The proposed method efficiently exploits the gridded scan pattern utilized during acquisition of TLS data from most sensors and takes advantage of parallel programming to process approximately 1 million points per second. Moreover, the proposed segmentation does not require estimation of the normal at each point, which limits the errors in normal estimation propagating to segmentation. Both an indoor and outdoor scene are used for an experiment to demonstrate and discuss the effectiveness and robustness of the proposed segmentation method.

Absolute and angular efficiencies of a microchannel-plate position-sensitive detector

NASA Technical Reports Server (NTRS)

Gao, R. S.; Gibner, P. S.; Newman, J. H.; Smith, K. A.; Stebbings, R. F.

1984-01-01

This paper presents a characterization of a commercially available position-sensitive detector of energetic ions and neutrals. The detector consists of two microchannel plates followed by a resistive position-encoding anode. The work includes measurement of absolute efficiencies of H(+), He(+), and O(+) ions in the energy range between 250 and 5000 eV, measurement of relative detection efficiencies as a function of particle impact angle, and a simple method for accurate measurement of the time at which a particle strikes the detector.

An efficient sampling algorithm for uncertain abnormal data detection in biomedical image processing and disease prediction.

PubMed

Liu, Fei; Zhang, Xi; Jia, Yan

2015-01-01

In this paper, we propose a computer information processing algorithm that can be used for biomedical image processing and disease prediction. A biomedical image is considered a data object in a multi-dimensional space. Each dimension is a feature that can be used for disease diagnosis. We introduce a new concept of the top (k1,k2) outlier. It can be used to detect abnormal data objects in the multi-dimensional space. This technique focuses on uncertain space, where each data object has several possible instances with distinct probabilities. We design an efficient sampling algorithm for the top (k1,k2) outlier in uncertain space. Some improvement techniques are used for acceleration. Experiments show our methods' high accuracy and high efficiency.

A label-free silicon quantum dots-based photoluminescence sensor for ultrasensitive detection of pesticides.

PubMed

Yi, Yinhui; Zhu, Gangbing; Liu, Chang; Huang, Yan; Zhang, Youyu; Li, Haitao; Zhao, Jiangna; Yao, Shouzhuo

2013-12-03

Sensitive, rapid, and simple detection methods for the screening of extensively used organophosphorus pesticides and highly toxic nerve agents are in urgent demand. A novel label-free silicon quantum dots (SiQDs)-based sensor was designed for ultrasensitive detection of pesticides. This sensing strategy involves the reaction of acetylcholine chloride (ACh) with acetylcholinesterase (AChE) to form choline that is in turn catalytically oxidized by choline oxidase (ChOx) to produce betaine and H2O2 which can quench the photoluminescence (PL) of SiQDs. Upon the addition of pesticides, the activity of AChE is inhibited, leading to the decrease of the generated H2O2, and hence the PL of SiQDs increases. By measuring the increase in SiQDs PL, the inhibition efficiency of pesticide to AChE activity was evaluated. It was found that the inhibition efficiency was linearly dependent on the logarithm of the pesticides concentration. Consequently, pesticides, such as carbaryl, parathion, diazinon, and phorate, were determined with the SiQDs PL sensing method. The lowest detectable concentrations for carbaryl, parathion, diazinon, and phorate reached 7.25 × 10(-9), 3.25 × 10(-8), 6.76 × 10(-8), and 1.9 × 10(-7) g/L, respectively, which were much lower than those previously reported. The detecting results of pesticide residues in food samples via this method agree well with those from high-performance liquid chromatography. The simple strategy reported here should be suitable for on-site pesticides detection, especially in combination with other portable platforms.

Automatic Recognition of Road Signs

NASA Astrophysics Data System (ADS)

Inoue, Yasuo; Kohashi, Yuuichirou; Ishikawa, Naoto; Nakajima, Masato

2002-11-01

The increase in traffic accidents is becoming a serious social problem with the recent rapid traffic increase. In many cases, the driver"s carelessness is the primary factor of traffic accidents, and the driver assistance system is demanded for supporting driver"s safety. In this research, we propose the new method of automatic detection and recognition of road signs by image processing. The purpose of this research is to prevent accidents caused by driver"s carelessness, and call attention to a driver when the driver violates traffic a regulation. In this research, high accuracy and the efficient sign detecting method are realized by removing unnecessary information except for a road sign from an image, and detect a road sign using shape features. At first, the color information that is not used in road signs is removed from an image. Next, edges except for circular and triangle ones are removed to choose sign shape. In the recognition process, normalized cross correlation operation is carried out to the two-dimensional differentiation pattern of a sign, and the accurate and efficient method for detecting the road sign is realized. Moreover, the real-time operation in a software base was realized by holding down calculation cost, maintaining highly precise sign detection and recognition. Specifically, it becomes specifically possible to process by 0.1 sec(s)/frame using a general-purpose PC (CPU: Pentium4 1.7GHz). As a result of in-vehicle experimentation, our system could process on real time and has confirmed that detection and recognition of a sign could be performed correctly.

Geologic Carbon Sequestration Leakage Detection: A Physics-Guided Machine Learning Approach

NASA Astrophysics Data System (ADS)

Lin, Y.; Harp, D. R.; Chen, B.; Pawar, R.

2017-12-01

One of the risks of large-scale geologic carbon sequestration is the potential migration of fluids out of the storage formations. Accurate and fast detection of this fluids migration is not only important but also challenging, due to the large subsurface uncertainty and complex governing physics. Traditional leakage detection and monitoring techniques rely on geophysical observations including pressure. However, the resulting accuracy of these methods is limited because of indirect information they provide requiring expert interpretation, therefore yielding in-accurate estimates of leakage rates and locations. In this work, we develop a novel machine-learning technique based on support vector regression to effectively and efficiently predict the leakage locations and leakage rates based on limited number of pressure observations. Compared to the conventional data-driven approaches, which can be usually seem as a "black box" procedure, we develop a physics-guided machine learning method to incorporate the governing physics into the learning procedure. To validate the performance of our proposed leakage detection method, we employ our method to both 2D and 3D synthetic subsurface models. Our novel CO2 leakage detection method has shown high detection accuracy in the example problems.

A method of multiplex PCR for detection of field released Beauveria bassiana, a fungal entomopathogen applied for pest management in jute (Corchorus olitorius).

PubMed

Biswas, Chinmay; Dey, Piyali; Gotyal, B S; Satpathy, Subrata

2015-04-01

The fungal entomopathogen Beauveria bassiana is a promising biocontrol agent for many pests. Some B. bassiana strains have been found effective against jute pests. To monitor the survival of field released B. bassiana a rapid and efficient detection technique is essential. Conventional methods such as plating method or direct culture method which are based on cultivation on selective media followed by microscopy are time consuming and not so sensitive. PCR based methods are rapid, sensitive and reliable. A single primer PCR may fail to amplify some of the strains. However, multiplex PCR increases the possibility of detection as it uses multiple primers. Therefore, in the present investigation a multiplex PCR protocol was developed by multiplexing three primers SCA 14, SCA 15 and SCB 9 to detect field released B. bassiana strains from soil as well as foliage of jute field. Using our multiplex PCR protocol all the five B. bassiana strains could be detected from soil and three strains viz., ITCC 6063, ITCC 4563 and ITCC 4796 could be detected even from the crop foliage after 45 days of spray.

A special purpose knowledge-based face localization method

NASA Astrophysics Data System (ADS)

Hassanat, Ahmad; Jassim, Sabah

2008-04-01

This paper is concerned with face localization for visual speech recognition (VSR) system. Face detection and localization have got a great deal of attention in the last few years, because it is an essential pre-processing step in many techniques that handle or deal with faces, (e.g. age, face, gender, race and visual speech recognition). We shall present an efficient method for localization human's faces in video images captured on mobile constrained devices, under a wide variation in lighting conditions. We use a multiphase method that may include all or some of the following steps starting with image pre-processing, followed by a special purpose edge detection, then an image refinement step. The output image will be passed through a discrete wavelet decomposition procedure, and the computed LL sub-band at a certain level will be transformed into a binary image that will be scanned by using a special template to select a number of possible candidate locations. Finally, we fuse the scores from the wavelet step with scores determined by color information for the candidate location and employ a form of fuzzy logic to distinguish face from non-face locations. We shall present results of large number of experiments to demonstrate that the proposed face localization method is efficient and achieve high level of accuracy that outperforms existing general-purpose face detection methods.

Fast T Wave Detection Calibrated by Clinical Knowledge with Annotation of P and T Waves.

PubMed

Elgendi, Mohamed; Eskofier, Bjoern; Abbott, Derek

2015-07-21

There are limited studies on the automatic detection of T waves in arrhythmic electrocardiogram (ECG) signals. This is perhaps because there is no available arrhythmia dataset with annotated T waves. There is a growing need to develop numerically-efficient algorithms that can accommodate the new trend of battery-driven ECG devices. Moreover, there is also a need to analyze long-term recorded signals in a reliable and time-efficient manner, therefore improving the diagnostic ability of mobile devices and point-of-care technologies. Here, the T wave annotation of the well-known MIT-BIH arrhythmia database is discussed and provided. Moreover, a simple fast method for detecting T waves is introduced. A typical T wave detection method has been reduced to a basic approach consisting of two moving averages and dynamic thresholds. The dynamic thresholds were calibrated using four clinically known types of sinus node response to atrial premature depolarization (compensation, reset, interpolation, and reentry). The determination of T wave peaks is performed and the proposed algorithm is evaluated on two well-known databases, the QT and MIT-BIH Arrhythmia databases. The detector obtained a sensitivity of 97.14% and a positive predictivity of 99.29% over the first lead of the validation databases (total of 221,186 beats). We present a simple yet very reliable T wave detection algorithm that can be potentially implemented on mobile battery-driven devices. In contrast to complex methods, it can be easily implemented in a digital filter design.

Selective isolation and noninvasive analysis of circulating cancer stem cells through Raman imaging.

PubMed

Cho, Hyeon-Yeol; Hossain, Md Khaled; Lee, Jin-Ho; Han, Jiyou; Lee, Hun Joo; Kim, Kyeong-Jun; Kim, Jong-Hoon; Lee, Ki-Bum; Choi, Jeong-Woo

2018-04-15

Circulating cancer stem cells (CCSCs), a rare circulating tumor cell (CTC) type, recently arose as a useful resource for monitoring and characterizing both cancers and their metastatic derivatives. However, due to the scarcity of CCSCs among hematologic cells in the blood and the complexity of the phenotype confirmation process, CCSC research can be extremely challenging. Hence, we report a nanoparticle-mediated Raman imaging method for CCSC characterization which profiles CCSCs based on their surface marker expression phenotypes. We have developed an integrated combinatorial Raman-Active Nanoprobe (RAN) system combined with a microfluidic chip to successfully process complete blood samples. CCSCs and CTCs were detected (90% efficiency) and classified in accordance with their respective surface marker expression via completely distinct Raman signals of RANs. Selectively isolated CCSCs (93% accuracy) were employed for both in vitro and in vivo tumor phenotyping to identify the tumorigenicity of the CCSCs. We utilized our new method to predict metastasis by screening blood samples from xenograft models, showing that upon CCSC detection, all subjects exhibited liver metastasis. Having highly efficient detection and noninvasive isolation capabilities, we have demonstrated that our RAN-based Raman imaging method will be valuable for predicting cancer metastasis and relapse via CCSC detection. Moreover, the exclusion of peak overlapping in CCSC analysis with our Raman imaging method will allow to expand the RAN families for various cancer types, therefore, increasing therapeutic efficacy by providing detailed molecular features of tumor subtypes. Copyright © 2017 Elsevier B.V. All rights reserved.

Rapid and simultaneous detection of Salmonella spp., Escherichia coli O157, and Listeria monocytogenes by magnetic capture hybridization and multiplex real-time PCR.

PubMed

Carloni, Elisa; Rotundo, Luca; Brandi, Giorgio; Amagliani, Giulia

2018-05-25

The application of rapid, specific, and sensitive methods for pathogen detection and quantification is very advantageous in diagnosis of human pathogens in several applications, including food analysis. The aim of this study was the evaluation of a method for the multiplexed detection and quantification of three significant foodborne pathogenic species (Escherichia coli O157, Salmonella spp., and Listeria monocytogenes). The assay combines specific DNA extraction by multiplex magnetic capture hybridization (mMCH) with multiplex real-time PCR. The amplification assay showed linearity in the range 10 6 -10 genomic units (GU)/PCR for each co-amplified species. The sensitivity corresponded to 1 GU/PCR for E. coli O157 and L. monocytogenes, and 10 GU/PCR for Salmonella spp. The immobilization process and the hybrid capture of the MCH showed good efficiency and reproducibility for all targets, allowing the combination in equal amounts of the different nanoparticle types in mMCH. MCH and mMCH efficiencies were similar. The detection limit of the method was 10 CFU in samples with individual pathogens and 10 2  CFU in samples with combination of the three pathogens in unequal amounts (amount's differences of 2 or 3 log). In conclusion, this multiplex molecular platform can be applied to determine the presence of target species in food samples after culture enrichment. In this way, this method could be a time-saving and sensitive tool to be used in routine diagnosis.

Downdating a time-varying square root information filter

NASA Technical Reports Server (NTRS)

Muellerschoen, Ronald J.

1990-01-01

A new method to efficiently downdate an estimate and covariance generated by a discrete time Square Root Information Filter (SRIF) is presented. The method combines the QR factor downdating algorithm of Gill and the decentralized SRIF algorithm of Bierman. Efficient removal of either measurements or a priori information is possible without loss of numerical integrity. Moreover, the method includes features for detecting potential numerical degradation. Performance on a 300 parameter system with 5800 data points shows that the method can be used in real time and hence is a promising tool for interactive data analysis. Additionally, updating a time-varying SRIF filter with either additional measurements or a priori information proceeds analogously.

Angle-resolved diffraction grating biosensor based on porous silicon

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

Lv, Changwu; Li, Peng; Jia, Zhenhong, E-mail: jzhh@xju.edu.cn

2016-03-07

In this study, an optical biosensor based on a porous silicon composite structure was fabricated using a simple method. This structure consists of a thin, porous silicon surface diffraction grating and a one-dimensional porous silicon photonic crystal. An angle-resolved diffraction efficiency spectrum was obtained by measuring the diffraction efficiency at a range of incident angles. The angle-resolved diffraction efficiency of the 2nd and 3rd orders was studied experimentally and theoretically. The device was sensitive to the change of refractive index in the presence of a biomolecule indicated by the shift of the diffraction efficiency spectrum. The sensitivity of this sensormore » was investigated through use of an 8 base pair antifreeze protein DNA hybridization. The shifts of the angle-resolved diffraction efficiency spectrum showed a relationship with the change of the refractive index, and the detection limit of the biosensor reached 41.7 nM. This optical device is highly sensitive, inexpensive, and simple to fabricate. Using shifts in diffraction efficiency spectrum to detect biological molecules has not yet been explored, so this study establishes a foundation for future work.« less

Evaluation of Immunomagnetic Separation Method for the Recovery of Hepatitis A Virus and GI.1 and GII.4 Norovirus Strains Seeded on Oyster and Mussel.

PubMed

Ha, Ji-Hyoung; Choi, Changsun; Ha, Sang-Do

2014-12-01

Outbreaks of viral diseases are frequently associated with the consumption of minimally processed shellfish. Among the viruses in these outbreaks, hepatitis A virus (HAV) and human norovirus (NoV) have been increasingly reported as the most common food-borne pathogens. These viruses must be concentrated in tested samples in order to be detected. In this study, a method for the detection of NoV and HAV in shellfish using an immuno-magnetic separation (IMS) procedure combined with reverse transcriptase (RT)-PCR was developed. The IMS/RT-PCR method was applied to investigate the recovery rates of HAV, NoV GI.1, and GII.4 from oyster and mussel. Based on IMS/RT-PCR results, recovery rates for HAV from oyster and mussel test samples were 2.4 and 1.1%, respectively. The NoV GI.1 recovery rates from oyster and mussel samples were 4.9-9.2% (mean 6.9%) and 4.3-8.6% (mean 6.2%), respectively, and the NoV GII.4 recovery rates were 8.8 and 8.5%, respectively. These results verified that HAV, NoV GI.1, and GII.4 can be detected in all the test samples using the IMS/RT-PCR method, although the three inoculated viruses were recovered with low efficiency. In conclusion, the IMS/RT-PCR method can be used to efficiently and rapidly detect viruses such as HAV and NoV in shellfish such as oyster and mussel.

Cryptosporidium Oocyst Detection in Water Samples: Floatation Technique Enhanced with Immunofluorescence Is as Effective as Immunomagnetic Separation Method

PubMed Central

Koompapong, Khuanchai; Sutthikornchai, Chantira

2009-01-01

Cryptosporidium can cause gastrointestinal diseases worldwide, consequently posing public health problems and economic burden. Effective techniques for detecting contaminated oocysts in water are important to prevent and control the contamination. Immunomagnetic separation (IMS) method has been widely employed recently due to its efficiency, but, it is costly. Sucrose floatation technique is generally used for separating organisms by using their different specific gravity. It is effective and cheap but time consuming as well as requiring highly skilled personnel. Water turbidity and parasite load in water sample are additional factors affecting to the recovery rate of those 2 methods. We compared the efficiency of IMS and sucrose floatation methods to recover the spiked Cryptosporidium oocysts in various turbidity water samples. Cryptosporidium oocysts concentration at 1, 101, 102, and 103 per 10 µl were spiked into 3 sets of 10 ml-water turbidity (5, 50, and 500 NTU). The recovery rate of the 2 methods was not different. Oocyst load at the concentration < 102 per 10 ml yielded unreliable results. Water turbidity at 500 NTU decreased the recovery rate of both techniques. The combination of sucrose floatation and immunofluorescense assay techniques (SF-FA) showed higher recovery rate than IMS and immunofluorescense assay (IMS-FA). We used this SF-FA to detect Cryptosporidium and Giardia from the river water samples and found 9 and 19 out of 30 (30% and 63.3%) positive, respectively. Our results favored sucrose floatation technique enhanced with immunofluorescense assay for detecting contaminated protozoa in water samples in general laboratories and in the real practical setting. PMID:19967082

Cryptosporidium oocyst detection in water samples: floatation technique enhanced with immunofluorescence is as effective as immunomagnetic separation method.

PubMed

Koompapong, Khuanchai; Sutthikornchai, Chantira; Sukthana, Yowalark

2009-12-01

Cryptosporidium can cause gastrointestinal diseases worldwide, consequently posing public health problems and economic burden. Effective techniques for detecting contaminated oocysts in water are important to prevent and control the contamination. Immunomagnetic separation (IMS) method has been widely employed recently due to its efficiency, but, it is costly. Sucrose floatation technique is generally used for separating organisms by using their different specific gravity. It is effective and cheap but time consuming as well as requiring highly skilled personnel. Water turbidity and parasite load in water sample are additional factors affecting to the recovery rate of those 2 methods. We compared the efficiency of IMS and sucrose floatation methods to recover the spiked Cryptosporidium oocysts in various turbidity water samples. Cryptosporidium oocysts concentration at 1, 10(1), 10(2), and 10(3) per 10 microl were spiked into 3 sets of 10 ml-water turbidity (5, 50, and 500 NTU). The recovery rate of the 2 methods was not different. Oocyst load at the concentration < 10(2) per 10 ml yielded unreliable results. Water turbidity at 500 NTU decreased the recovery rate of both techniques. The combination of sucrose floatation and immunofluorescense assay techniques (SF-FA) showed higher recovery rate than IMS and immunofluorescense assay (IMS-FA). We used this SF-FA to detect Cryptosporidium and Giardia from the river water samples and found 9 and 19 out of 30 (30% and 63.3%) positive, respectively. Our results favored sucrose floatation technique enhanced with immunofluorescense assay for detecting contaminated protozoa in water samples in general laboratories and in the real practical setting.

Cell sorting using efficient light shaping approaches

NASA Astrophysics Data System (ADS)

Bañas, Andrew; Palima, Darwin; Villangca, Mark; Glückstad, Jesper

2016-03-01

Early detection of diseases can save lives. Hence, there is emphasis in sorting rare disease-indicating cells within small dilute quantities such as in the confines of lab-on-a-chip devices. In our work, we use optical forces to isolate red blood cells detected by machine vision. This approach is gentler, less invasive and more economical compared to conventional FACS systems. As cells are less responsive to plastic or glass beads commonly used in the optical manipulation literature, and since laser safety would be an issue in clinical use, we develop efficient approaches in utilizing lasers and light modulation devices. The Generalized Phase Contrast (GPC) method that can be used for efficiently illuminating spatial light modulators or creating well-defined contiguous optical traps is supplemented by diffractive techniques capable of integrating the available light and creating 2D or 3D beam distributions aimed at the positions of the detected cells. Furthermore, the beam shaping freedom provided by GPC can allow optimizations in the beam's propagation and its interaction with the catapulted cells.

A novel algorithm for solving the true coincident counting issues in Monte Carlo simulations for radiation spectroscopy.

PubMed

Guan, Fada; Johns, Jesse M; Vasudevan, Latha; Zhang, Guoqing; Tang, Xiaobin; Poston, John W; Braby, Leslie A

2015-06-01

Coincident counts can be observed in experimental radiation spectroscopy. Accurate quantification of the radiation source requires the detection efficiency of the spectrometer, which is often experimentally determined. However, Monte Carlo analysis can be used to supplement experimental approaches to determine the detection efficiency a priori. The traditional Monte Carlo method overestimates the detection efficiency as a result of omitting coincident counts caused mainly by multiple cascade source particles. In this study, a novel "multi-primary coincident counting" algorithm was developed using the Geant4 Monte Carlo simulation toolkit. A high-purity Germanium detector for ⁶⁰Co gamma-ray spectroscopy problems was accurately modeled to validate the developed algorithm. The simulated pulse height spectrum agreed well qualitatively with the measured spectrum obtained using the high-purity Germanium detector. The developed algorithm can be extended to other applications, with a particular emphasis on challenging radiation fields, such as counting multiple types of coincident radiations released from nuclear fission or used nuclear fuel.

Efficient detection of a CW signal with a linear frequency drift

NASA Technical Reports Server (NTRS)

Swarztrauber, Paul N.; Bailey, David H.

1989-01-01

An efficient method is presented for the detection of a continuous wave (CW) signal with a frequency drift that is linear in time. Signals of this type occur in transmissions between any two locations that are accelerating relative to one another, e.g., transmissions from the Voyager spacecraft. We assume that both the frequency and the drift are unknown. We also assume that the signal is weak compared to the Gaussian noise. The signal is partitioned into subsequences whose discrete Fourier transforms provide a sequence of instantaneous spectra at equal time intervals. These spectra are then accumulated with a shift that is proportional to time. When the shift is equal to the frequency drift, the signal to noise ratio increases and detection occurs. Here, we show how to compute these accumulations for many shifts in an efficient manner using a variety of Fast Fourier Transformations (FFT). Computing time is proportional to L log L where L is the length of the time series.

Scalable Track Detection in SAR CCD Images

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

Chow, James G; Quach, Tu-Thach

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

Whole exome sequencing is an efficient, sensitive and specific method of mutation detection in osteogenesis imperfecta and Marfan syndrome

PubMed Central

McInerney-Leo, Aideen M; Marshall, Mhairi S; Gardiner, Brooke; Coucke, Paul J; Van Laer, Lut; Loeys, Bart L; Summers, Kim M; Symoens, Sofie; West, Jennifer A; West, Malcolm J; Paul Wordsworth, B; Zankl, Andreas; Leo, Paul J; Brown, Matthew A; Duncan, Emma L

2013-01-01

Osteogenesis imperfecta (OI) and Marfan syndrome (MFS) are common Mendelian disorders. Both conditions are usually diagnosed clinically, as genetic testing is expensive due to the size and number of potentially causative genes and mutations. However, genetic testing may benefit patients, at-risk family members and individuals with borderline phenotypes, as well as improving genetic counseling and allowing critical differential diagnoses. We assessed whether whole exome sequencing (WES) is a sensitive method for mutation detection in OI and MFS. WES was performed on genomic DNA from 13 participants with OI and 10 participants with MFS who had known mutations, with exome capture followed by massive parallel sequencing of multiplexed samples. Single nucleotide polymorphisms (SNPs) and small indels were called using Genome Analysis Toolkit (GATK) and annotated with ANNOVAR. CREST, exomeCopy and exomeDepth were used for large deletion detection. Results were compared with the previous data. Specificity was calculated by screening WES data from a control population of 487 individuals for mutations in COL1A1, COL1A2 and FBN1. The target capture of five exome capture platforms was compared. All 13 mutations in the OI cohort and 9/10 in the MFS cohort were detected (sensitivity=95.6%) including non-synonymous SNPs, small indels (<10 bp), and a large UTR5/exon 1 deletion. One mutation was not detected by GATK due to strand bias. Specificity was 99.5%. Capture platforms and analysis programs differed considerably in their ability to detect mutations. Consumable costs for WES were low. WES is an efficient, sensitive, specific and cost-effective method for mutation detection in patients with OI and MFS. Careful selection of platform and analysis programs is necessary to maximize success. PMID:24501682

A Versatile Nanowire Platform for Highly Efficient Isolation and Direct PCR-free Colorimetric Detection of Human Papillomavirus DNA from Unprocessed Urine

PubMed Central

Lee, HyungJae; Choi, Mihye; Hwang, Sang-Hyun; Cho, Youngnam

2018-01-01

Purpose: As human papillomavirus (HPV) is primarily responsible for the development of cervical cancer, significant efforts have been devoted to develop novel strategies for detecting and identifying HPV DNA in urine. The analysis of target DNA sequences in urine offers a potential alternative to conventional methods as a non-invasive clinical screening and diagnostic assessment tool for the detection of HPV. However, the lack of efficient approaches to isolate and directly detect HPV DNA in urine has restricted its potential clinical use. In this study, we demonstrated a novel approach of using polyethylenimine-conjugated magnetic polypyrrole nanowires (PEI-mPpy NWs) for the extraction, identification, and PCR-free colorimetric detection of high-risk strains of HPV DNA sequences, particularly HPV-16 and HPV-18, in urine specimens of cervical cancer patients. Materials and Methods: We fabricated and characterized polyethylenimine-conjugated magnetic nanowires (PEI/mPpy NWs). PEI/mPpy NWs-based HPV DNA isolation and detection strategy appears to be a cost-effective and practical technology with greater sensitivity and accuracy than other urine-based methods. Results: The analytical and clinical performance of PEI-mPpy NWs was evaluated and compared with those of cervical swabs, demonstrating a superior type-specific concordance rate of 100% between urine and cervical swabs, even when using a small volume of urine (300 µL). Conclusion: We envision that PEI-mPpy NWs provide substantive evidence for clinical diagnosis and management of HPV-associated disease with their excellent performance in the recovery and detection of HPV DNA from minimal amounts of urine samples. PMID:29290816

Characterizing and simulation the scintillation properties of zinc oxide nanowires in AAO membrane for medical imaging applications

NASA Astrophysics Data System (ADS)

Esfandi, F.; Saramad, S.; Rezaei Shahmirzadi, M.

2017-07-01

In this work, a new method is proposed for extracting some X-ray detection properties of ZnO nanowires electrodeposited on Anodized Aluminum Oxide (AAO) nanoporous template. The results show that the detection efficiency for 12μm thickness of zinc oxide nano scintillator at an energy of 9.8 keV, near the K-edge of ZnO (9.65 keV), is 24%. The X-rays that interact with AAO can also generate electrons that reach the nano scintillator. The scintillation events of these electrons are seen as a low energy tail in the spectrum. In addition, it is found that all the X-rays that are absorbed in 300 nm thickness of the gold layer on the top of the zinc oxide nanowires can participate in the scintillation process with an efficiency of 6%. Hence, the scintillation detection efficiency of the whole detector for 9.8 keV X-ray energy is 30%. The simulation results from Geant4 and the experimental detected photons per MeV energy deposition are also used to extract the light yield of the zinc oxide nano scintillator. The results show that the light yield of the zinc oxide nanowires deposited by the electrochemical method is approximately the same as for single crystal zinc oxide scintillator (9000). Much better spatial resolution of this nano scintillator in comparison to the bulk ones is an advantage which candidates this nano scintillator for medical imaging applications.

TEAM: efficient two-locus epistasis tests in human genome-wide association study.

PubMed

Zhang, Xiang; Huang, Shunping; Zou, Fei; Wang, Wei

2010-06-15

As a promising tool for identifying genetic markers underlying phenotypic differences, genome-wide association study (GWAS) has been extensively investigated in recent years. In GWAS, detecting epistasis (or gene-gene interaction) is preferable over single locus study since many diseases are known to be complex traits. A brute force search is infeasible for epistasis detection in the genome-wide scale because of the intensive computational burden. Existing epistasis detection algorithms are designed for dataset consisting of homozygous markers and small sample size. In human study, however, the genotype may be heterozygous, and number of individuals can be up to thousands. Thus, existing methods are not readily applicable to human datasets. In this article, we propose an efficient algorithm, TEAM, which significantly speeds up epistasis detection for human GWAS. Our algorithm is exhaustive, i.e. it does not ignore any epistatic interaction. Utilizing the minimum spanning tree structure, the algorithm incrementally updates the contingency tables for epistatic tests without scanning all individuals. Our algorithm has broader applicability and is more efficient than existing methods for large sample study. It supports any statistical test that is based on contingency tables, and enables both family-wise error rate and false discovery rate controlling. Extensive experiments show that our algorithm only needs to examine a small portion of the individuals to update the contingency tables, and it achieves at least an order of magnitude speed up over the brute force approach.

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.

Color image segmentation to detect defects on fresh ham

NASA Astrophysics Data System (ADS)

Marty-Mahe, Pascale; Loisel, Philippe; Brossard, Didier

2003-04-01

We present in this paper the color segmentation methods that were used to detect appearance defects on 3 dimensional shape of fresh ham. The use of color histograms turned out to be an efficient solution to characterize the healthy skin, but a special care must be taken to choose the color components because of the 3 dimensional shape of ham.

Global Contrast Based Salient Region Detection.

PubMed

Cheng, Ming-Ming; Mitra, Niloy J; Huang, Xiaolei; Torr, Philip H S; Hu, Shi-Min

2015-03-01

Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information.

Optimized detection of steering via linear criteria for arbitrary-dimensional states

NASA Astrophysics Data System (ADS)

Zheng, Yu-Lin; Zhen, Yi-Zheng; Cao, Wen-Fei; Li, Li; Chen, Zeng-Bing; Liu, Nai-Le; Chen, Kai

2017-03-01

Einstein-Podolsky-Rosen (EPR) steering, as a new form of nonlocality, stands between entanglement and Bell nonlocality, implying promising applications for quantum information tasks. The problem of detecting EPR steering plays an important role in characterization of quantum nonlocality. Despite some significant progress, one still faces a practical issue: how to detect EPR steering in an experimentally friendly fashion. Resorting to an EPR steering inequality, one is required to apply a strategy as efficiently as possible for any selected measurement settings on the two subsystems, one of which may not be trusted. Inspired by the recent powerful linear criteria proposed by Saunders et al. [D. J. Saunders, S. J. Jones, H. M. Wiseman, and G. J. Pryde, Nat. Phys. 6, 845 (2010)., 10.1038/nphys1766], we present an optimized method of certifying steering for an arbitrary-dimensional state in a cost-effective manner. We provide a practical way to signify steering via only a few settings to optimally violate the steering inequality. Our method leads to steering detections in a highly efficient way, and can be performed with any number of settings, for an arbitrary bipartite mixed state, which can reduce experimental overheads significantly.

Carbon nanostructures as immobilization platform for DNA: A review on current progress in electrochemical DNA sensors.

PubMed

Rasheed, P Abdul; Sandhyarani, N

2017-11-15

Development of a sensitive, specific and cost-effective DNA detection method is motivated by increasing demand for the early stage diagnosis of genetic diseases. Recent developments in the design and fabrication of efficient sensor platforms based on nanostructures make the highly sensitive sensors which could indicate very low detection limit to the level of few molecules, a realistic possibility. Electrochemical detection methods are widely used in DNA diagnostics as it provide simple, accurate and inexpensive platform for DNA detection. In addition, the electrochemical DNA sensors provide direct electronic signal without the use of expensive signal transduction equipment and facilitates the immobilization of single stranded DNA (ssDNA) probe sequences on a wide variety of electrode substrates. It has been found that a range of nanomaterials such as metal nanoparticles (MNPs), carbon based nanomaterials, quantum dots (QDs), magnetic nanoparticles and polymeric NPs have been introduced in the sensor design to enhance the sensing performance of electrochemical DNA sensor. In this review, we discuss recent progress in the design and fabrication of efficient electrochemical genosensors based on carbon nanostructures such as carbon nanotubes, graphene, graphene oxide and nanodiamonds. Copyright © 2017 Elsevier B.V. All rights reserved.

Bomb swab: Can trace explosive particle sampling and detection be improved?

PubMed

Fisher, Danny; Zach, Raya; Matana, Yossef; Elia, Paz; Shustack, Shiran; Sharon, Yarden; Zeiri, Yehuda

2017-11-01

The marked increase in international terror in recent years requires the development of highly efficient methods to detect trace amounts of explosives at airports, border crossings and check points. The preferred analytical method worldwide is the ion mobility spectrometry (IMS) that is capable of detecting most explosives at the nano-gram level. Sample collection for the IMS analysis is based on swabbing of a passenger's belongings to collect possible explosive residues. The present study examines a wide range of issues related to swab-based particle collection and analysis, in the hope of gaining deeper understanding into this technique that will serve to improve the detection process. The adhesion of explosive particles to three typical materials, plastic, metal and glass, were measured using atomic force microscopy (AFM). We found that a strong contribution of capillary forces to adhesion on glass and metal surfaces renders these substrates more promising materials upon which to find and collect explosive residues. The adhesion of explosives to different swipe materials was also examined. Here we found that Muslin, Nomex ® and polyamide membrane surfaces are the most promising materials for use as swipes. Subsequently, the efficiency of multiple swipe use - for collecting explosive residues from a glass surface using Muslin, Nomex ® and Teflon™ swipes - was examined. The study suggests that swipes used in about 5-10 "sampling and analysis cycles" have higher efficiency as compared to new unused swipes. The reason for this behavior was found to be related to the increased roughness of the swipe surface following a few swab measurements. Lastly, GC-MS analysis was employed to examine the nature of contaminants collected by the three types of swipe. The relative amounts of different contaminants are reported. The existence and interference of these contaminants have to be considered in relation to the detection efficiency of the various explosives by the IMS. Copyright © 2017 Elsevier B.V. All rights reserved.

Determination of N-vinyl-2-pyrrolidone and N-methyl-2-pyrrolidone in drugs using polypyrrole-based headspace solid-phase microextraction and gas chromatography-nitrogen-phosphorous detection.

PubMed

Mehdinia, Ali; Ghassempour, Alireza; Rafati, Hasan; Heydari, Rouhollah

2007-03-21

A headspace solid-phase microextraction and gas chromatography-nitrogen-phosphorous detection (HS-SPME-GC-NPD) method using polypyrrole (PPy) fibers has been introduced to determine two derivatives of pyrrolidone; N-vinyl-2-pyrrolidone (NVP) and N-methyl-2-pyrrolidone (NMP). Two types of PPy fibers, prepared using organic and aqueous media, were compared in terms of extraction efficiency and thermal stability. It was found that PPy film prepared using organic medium (i.e. acetonitrile) had higher extraction efficiency and more thermal stability compared to the film prepared in aqueous medium. To enhance the sensitivity of HS-SPME, the effects of pH, ionic strength, extraction time, extraction temperature and the headspace volume on the extraction efficiency were optimized. Using the results of this research, high sensitivity and selectivity had been achieved due to the combination of the high extraction efficiency of PPy film prepared in organic medium and the high sensitivity and selectivity of nitrogen-phosphorous detection. Linear range of the analytes was found to be between 1.0 and 1000 microg L(-1) with regression coefficients (R(2)) of 0.998 and 0.997 for NVP and NMP, consequently. Limits of detection (LODs) were 0.074 and 0.081 microg L(-1) for NVP and NMP, respectively. Relative standard deviation (R.S.D.) for five replications of analyses was found to be less than 6.0%. In real samples the mean recoveries were 94.81% and 94.15% for NVP and NMP, respectively. The results demonstrated the suitability of the HS-SPME technique for analyzing NVP and NMP in two different pharmaceutical matrices. In addition, the method was used for simultaneous detection of NVP, 2-pyrrolidone (2-Pyr), gamma-butyrolactone (GBL) and ethanolamine (EA) compounds.

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

PubMed

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

2018-05-15

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

Development of luminol-N-hydroxyphthalimide chemiluminescence system for highly selective and sensitive detection of superoxide dismutase, uric acid and Co2.

PubMed

Saqib, Muhammad; Qi, Liming; Hui, Pan; Nsabimana, Anaclet; Halawa, Mohamed Ibrahim; Zhang, Wei; Xu, Guobao

2018-01-15

N-hydroxyphthalimide (NHPI), a well known reagent in organic synthesis and biochemical applications, has been developed as a stable and efficient chemiluminescence coreactant for the first time. It reacts with luminol much faster than N-hydroxysuccinimide, eliminating the need of a prereaction coil used in N-hydroxysuccinimide system. Without using prereaction coil, the chemiluminescence peak intensities of luminol-NHPI system are about 102 and 26 times greater than that of luminol-N-hydroxysuccinimide system and classical luminol-hydrogen peroxide system, respectively. The luminol-NHPI system achieves the highly sensitive detection of luminol (LOD = 70pM) and NHPI (LOD = 910nM). Based on their excellent quenching efficiencies, superoxide dismutase and uric acid are sensitively detected with LODs of 3ng/mL and 10pM, respectively. Co 2+ is also detected a LOD of 30pM by its remarkable enhancing effect. Noteworthily, our method is at least 4 orders of magnitude more sensitive than previously reported uric acid detection methods, and can detect uric acid in human urine and Co 2+ in tap and lake water real samples with excellent recoveries in the range of 96.35-102.70%. This luminol-NHPI system can be an important candidate for biochemical, clinical and environmental analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Efficient Terahertz Wide-Angle NUFFT-Based Inverse Synthetic Aperture Imaging Considering Spherical Wavefront.

PubMed

Gao, Jingkun; Deng, Bin; Qin, Yuliang; Wang, Hongqiang; Li, Xiang

2016-12-14

An efficient wide-angle inverse synthetic aperture imaging method considering the spherical wavefront effects and suitable for the terahertz band is presented. Firstly, the echo signal model under spherical wave assumption is established, and the detailed wavefront curvature compensation method accelerated by 1D fast Fourier transform (FFT) is discussed. Then, to speed up the reconstruction procedure, the fast Gaussian gridding (FGG)-based nonuniform FFT (NUFFT) is employed to focus the image. Finally, proof-of-principle experiments are carried out and the results are compared with the ones obtained by the convolution back-projection (CBP) algorithm. The results demonstrate the effectiveness and the efficiency of the presented method. This imaging method can be directly used in the field of nondestructive detection and can also be used to provide a solution for the calculation of the far-field RCSs (Radar Cross Section) of targets in the terahertz regime.

Interquantile Shrinkage in Regression Models

PubMed Central

Jiang, Liewen; Wang, Huixia Judy; Bondell, Howard D.

2012-01-01

Conventional analysis using quantile regression typically focuses on fitting the regression model at different quantiles separately. However, in situations where the quantile coefficients share some common feature, joint modeling of multiple quantiles to accommodate the commonality often leads to more efficient estimation. One example of common features is that a predictor may have a constant effect over one region of quantile levels but varying effects in other regions. To automatically perform estimation and detection of the interquantile commonality, we develop two penalization methods. When the quantile slope coefficients indeed do not change across quantile levels, the proposed methods will shrink the slopes towards constant and thus improve the estimation efficiency. We establish the oracle properties of the two proposed penalization methods. Through numerical investigations, we demonstrate that the proposed methods lead to estimations with competitive or higher efficiency than the standard quantile regression estimation in finite samples. Supplemental materials for the article are available online. PMID:24363546

Molecular Methods for the Detection of Mycoplasma and Ureaplasma Infections in Humans

PubMed Central

Waites, Ken B.; Xiao, Li; Paralanov, Vanya; Viscardi, Rose M.; Glass, John I.

2012-01-01

Mycoplasma and Ureaplasma species are well-known human pathogens responsible for a broad array of inflammatory conditions involving the respiratory and urogenital tracts of neonates, children, and adults. Greater attention is being given to these organisms in diagnostic microbiology, largely as a result of improved methods for their laboratory detection, made possible by powerful molecular-based techniques that can be used for primary detection in clinical specimens. For slow-growing species, such as Mycoplasma pneumoniae and Mycoplasma genitalium, molecular-based detection is the only practical means for rapid microbiological diagnosis. Most molecular-based methods used for detection and characterization of conventional bacteria have been applied to these organisms. A complete genome sequence is available for one or more strains of all of the important human pathogens in the Mycoplasma and Ureaplasma genera. Information gained from genome analyses and improvements in efficiency of DNA sequencing are expected to significantly advance the field of molecular detection and genotyping during the next few years. This review provides a summary and critical review of methods suitable for detection and characterization of mycoplasmas and ureaplasmas of humans, with emphasis on molecular genotypic techniques. PMID:22819362

Imaging of underground karst water channels using an improved multichannel transient Rayleigh wave detecting method

PubMed Central

Zheng, Xuhui; Liu, Lei; Li, Gao; Zhou, Fubiao; Xu, Jiemin

2018-01-01

Geological and hydrogeological conditions in karst areas are complicated from the viewpoint of engineering. The construction of underground structures in these areas is often disturbed by the gushing of karst water, which may delay the construction schedule, result in economic losses, and even cause heavy casualties. In this paper, an innovative method of multichannel transient Rayleigh wave detecting is proposed by introducing the concept of arrival time difference phase between channels (TDP). Overcoming the restriction of the space-sampling law, the proposed method can extract the phase velocities of different frequency components from only two channels of transient Rayleigh wave recorded on two adjacent detecting points. This feature greatly improves the work efficiency and lateral resolution of transient Rayleigh wave detecting. The improved multichannel transient Rayleigh wave detecting method is applied to the detection of karst caves and fractures in rock mass of the foundation pit of Yan’an Road Station of Guiyang Metro. The imaging of the detecting results clearly reveals the distribution of karst water inflow channels, which provided significant guidance for water plugging and enabled good control over karst water gushing in the foundation pit. PMID:29883492

Imaging of underground karst water channels using an improved multichannel transient Rayleigh wave detecting method.

PubMed

Zheng, Xuhui; Liu, Lei; Sun, Jinzhong; Li, Gao; Zhou, Fubiao; Xu, Jiemin

2018-01-01

Geological and hydrogeological conditions in karst areas are complicated from the viewpoint of engineering. The construction of underground structures in these areas is often disturbed by the gushing of karst water, which may delay the construction schedule, result in economic losses, and even cause heavy casualties. In this paper, an innovative method of multichannel transient Rayleigh wave detecting is proposed by introducing the concept of arrival time difference phase between channels (TDP). Overcoming the restriction of the space-sampling law, the proposed method can extract the phase velocities of different frequency components from only two channels of transient Rayleigh wave recorded on two adjacent detecting points. This feature greatly improves the work efficiency and lateral resolution of transient Rayleigh wave detecting. The improved multichannel transient Rayleigh wave detecting method is applied to the detection of karst caves and fractures in rock mass of the foundation pit of Yan'an Road Station of Guiyang Metro. The imaging of the detecting results clearly reveals the distribution of karst water inflow channels, which provided significant guidance for water plugging and enabled good control over karst water gushing in the foundation pit.

PEEK tube-based online solid-phase microextraction-high-performance liquid chromatography for the determination of yohimbine in rat plasma and its application in pharmacokinetics study.

PubMed

Xiang, Xiaowei; Shang, Bing; Wang, Xiaozheng; Chen, Qinhua

2017-04-01

Yohimbine is a novel compound for the treatment of erectile dysfunction derived from natural products, and pharmacokinetic study is important for its further development as a new medicine. In this work, we developed a novel PEEK tube-based solid-phase microextraction (SPME)-HPLC method for analysis of yohimbine in plasma and further for pharmacokinetic study. Poly (AA-EGDMA) was synthesized inside a PEEK tube as the sorbent for microextraction of yohimbine, and parameters that could influence extraction efficiency were systematically investigated. Under optimum conditions, the PEEK tube-based SPME method exhibits excellent enrichment efficiency towards yohimbine. By using berberine as internal standard, an online SPME-HPLC method was developed for analysis of yohimbine in human plasma sample. The method has wide linear range (2-1000 ng/mL) with an R 2 of 0.9962; the limit of detection was determined and was as low as 0.1 ng/mL using UV detection. Finally, a pharmacokinetic study of yohimbine was carried out by the online SPME-HPLC method and the results have been compared with those of reported methods. Copyright © 2016 John Wiley & Sons, Ltd.

Detecting Signals of Disproportionate Reporting from Singapore's Spontaneous Adverse Event Reporting System: An Application of the Sequential Probability Ratio Test.

PubMed

Chan, Cheng Leng; Rudrappa, Sowmya; Ang, Pei San; Li, Shu Chuen; Evans, Stephen J W

2017-08-01

The ability to detect safety concerns from spontaneous adverse drug reaction reports in a timely and efficient manner remains important in public health. This paper explores the behaviour of the Sequential Probability Ratio Test (SPRT) and ability to detect signals of disproportionate reporting (SDRs) in the Singapore context. We used SPRT with a combination of two hypothesised relative risks (hRRs) of 2 and 4.1 to detect signals of both common and rare adverse events in our small database. We compared SPRT with other methods in terms of number of signals detected and whether labelled adverse drug reactions were detected or the reaction terms were considered serious. The other methods used were reporting odds ratio (ROR), Bayesian Confidence Propagation Neural Network (BCPNN) and Gamma Poisson Shrinker (GPS). The SPRT produced 2187 signals in common with all methods, 268 unique signals, and 70 signals in common with at least one other method, and did not produce signals in 178 cases where two other methods detected them, and there were 403 signals unique to one of the other methods. In terms of sensitivity, ROR performed better than other methods, but the SPRT method found more new signals. The performances of the methods were similar for negative predictive value and specificity. Using a combination of hRRs for SPRT could be a useful screening tool for regulatory agencies, and more detailed investigation of the medical utility of the system is merited.

Classification methods to detect sleep apnea in adults based on respiratory and oximetry signals: a systematic review.

PubMed

Uddin, M B; Chow, C M; Su, S W

2018-03-26

Sleep apnea (SA), a common sleep disorder, can significantly decrease the quality of life, and is closely associated with major health risks such as cardiovascular disease, sudden death, depression, and hypertension. The normal diagnostic process of SA using polysomnography is costly and time consuming. In addition, the accuracy of different classification methods to detect SA varies with the use of different physiological signals. If an effective, reliable, and accurate classification method is developed, then the diagnosis of SA and its associated treatment will be time-efficient and economical. This study aims to systematically review the literature and present an overview of classification methods to detect SA using respiratory and oximetry signals and address the automated detection approach. Sixty-two included studies revealed the application of single and multiple signals (respiratory and oximetry) for the diagnosis of SA. Both airflow and oxygen saturation signals alone were effective in detecting SA in the case of binary decision-making, whereas multiple signals were good for multi-class detection. In addition, some machine learning methods were superior to the other classification methods for SA detection using respiratory and oximetry signals. To deal with the respiratory and oximetry signals, a good choice of classification method as well as the consideration of associated factors would result in high accuracy in the detection of SA. An accurate classification method should provide a high detection rate with an automated (independent of human action) analysis of respiratory and oximetry signals. Future high-quality automated studies using large samples of data from multiple patient groups or record batches are recommended.

A concatenated coding scheme for error control

NASA Technical Reports Server (NTRS)

Kasami, T.; Fujiwara, T.; Lin, S.

1986-01-01

In this paper, a concatenated coding scheme for error control in data communications is presented and analyzed. In this scheme, the inner code is used for both error correction and detection; however, the outer code is used only for error detection. A retransmission is requested if either the inner code decoder fails to make a successful decoding or the outer code decoder detects the presence of errors after the inner code decoding. Probability of undetected error (or decoding error) of the proposed scheme is derived. An efficient method for computing this probability is presented. Throughput efficiency of the proposed error control scheme incorporated with a selective-repeat ARQ retransmission strategy is also analyzed. Three specific examples are presented. One of the examples is proposed for error control in the NASA Telecommand System.

Detecting the Presence of Bacterial DNA and RNA by Polymerase Chain Reaction to Diagnose Suspected Periprosthetic Joint Infection after Antibiotic Therapy.

PubMed

Fang, Xin-Yu; Li, Wen-Bo; Zhang, Chao-Fan; Huang, Zi-da; Zeng, Hui-Yi; Dong, Zheng; Zhang, Wen-Ming

2018-02-01

To explore the diagnostic efficiency of DNA-based and RNA-based quantitative polymerase chain reaction (qPCR) analyses for periprosthetic joint infection (PJI). To determine the detection limit of DNA-based and RNA-based qPCR in vitro, Staphylococcus aureus and Escherichia coli strains were added to sterile synovial fluid obtained from a patient with knee osteoarthritis. Serial dilutions of samples were analyzed by DNA-based and RNA-based qPCR. Clinically, patients who were suspected of having PJI and eventually underwent revision arthroplasty in our hospital from July 2014 to December 2016 were screened. Preoperative puncture or intraoperative collection was performed on patients who met the inclusion and exclusion criteria to obtain synovial fluid. DNA-based and RNA-based PCR analyses and culture were performed on each synovial fluid sample. The patients' demographic characteristics, medical history, and laboratory test results were recorded. The diagnostic efficiency of both PCR assays was compared with culture methods. The in vitro analysis demonstrated that DNA-based qPCR assay was highly sensitive, with the detection limit being 1200 colony forming units (CFU)/mL of S. aureus and 3200 CFU/mL of E. coli. Meanwhile, The RNA-based qPCR assay could detect 2300 CFU/mL of S. aureus and 11 000 CFU/mL of E. coli. Clinically, the sensitivity, specificity, and accuracy were 65.7%, 100%, and 81.6%, respectively, for the culture method; 81.5%, 84.8%, and 83.1%, respectively, for DNA-based qPCR; and 73.6%, 100%, and 85.9%, respectively, for RNA-based qPCR. DNA-based qPCR could detect suspected PJI with high sensitivity after antibiotic therapy. RNA-based qPCR could reduce the false positive rates of DNA-based assays. qPCR-based methods could improve the efficiency of PJI diagnosis. © 2018 Chinese Orthopaedic Association and John Wiley & Sons Australia, Ltd.

Instrumentation for noninvasive express-diagnostics bacteriophages and viruses by optical method

NASA Astrophysics Data System (ADS)

Moguilnaia, Tatiana A.; Andreev, Gleb I.; Agibalov, Andrey A.; Botikov, Andrey G.; Kosenkov, Evgeniy; Saguitova, Elena

2004-03-01

The theoretical and the experimental researches of spectra of absent-minded radiation in medium containing viruses were carried out. The information on spectra luminescence 31 viruses was written down.The new method the express - analysis of viruses in organism of the man was developed. It shall be mentioned that the proposed method of express diagnostics allows detection of infection agent in the organism several hours after infection. It makes it suitable for high efficient testing in blood services for detection and rejection of potential donors infected with such viruses as hepatitis, herpes, Epstein-Barre, cytomegalovirus, and immunodeficiency. Methods of serum diagnostics used for that purpose can detect antibodies to virus only 1-3 months after the person has been infected. The device for the express analysis of 31 viruses of the man was created.

Fully correcting the meteor speed distribution for radar observing biases

NASA Astrophysics Data System (ADS)

Moorhead, Althea V.; Brown, Peter G.; Campbell-Brown, Margaret D.; Heynen, Denis; Cooke, William J.

2017-09-01

Meteor radars such as the Canadian Meteor Orbit Radar (CMOR) have the ability to detect millions of meteors, making it possible to study the meteoroid environment in great detail. However, meteor radars also suffer from a number of detection biases; these biases must be fully corrected for in order to derive an accurate description of the meteoroid population. We present a bias correction method for patrol radars that accounts for the full form of ionization efficiency and mass distribution. This is an improvement over previous methods such as that of Taylor (1995), which requires power-law distributions for ionization efficiency and a single mass index. We apply this method to the meteor speed distribution observed by CMOR and find a significant enhancement of slow meteors compared to earlier treatments. However, when the data set is severely restricted to include only meteors with very small uncertainties in speed, the fraction of slow meteors is substantially reduced, indicating that speed uncertainties must be carefully handled.

Monte Carlo simulation studies on scintillation detectors and image reconstruction of brain-phantom tumors in TOFPET

PubMed Central

Mondal, Nagendra Nath

2009-01-01

This study presents Monte Carlo Simulation (MCS) results of detection efficiencies, spatial resolutions and resolving powers of a time-of-flight (TOF) PET detector systems. Cerium activated Lutetium Oxyorthosilicate (Lu2SiO5: Ce in short LSO), Barium Fluoride (BaF2) and BriLanCe 380 (Cerium doped Lanthanum tri-Bromide, in short LaBr3) scintillation crystals are studied in view of their good time and energy resolutions and shorter decay times. The results of MCS based on GEANT show that spatial resolution, detection efficiency and resolving power of LSO are better than those of BaF2 and LaBr3, although it possesses inferior time and energy resolutions. Instead of the conventional position reconstruction method, newly established image reconstruction (talked about in the previous work) method is applied to produce high-tech images. Validation is a momentous step to ensure that this imaging method fulfills all purposes of motivation discussed by reconstructing images of two tumors in a brain phantom. PMID:20098551

New Method for Accurate Calibration of Micro-Channel Plate based Detection Systems and its use in the Fast Plasma Investigation of NASA's Magnetospheric MultiScale Mission

NASA Astrophysics Data System (ADS)

Gliese, U.; Avanov, L. A.; Barrie, A.; Kujawski, J. T.; Mariano, A. J.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Zeuch, M.; Pollock, C. J.; Jacques, A. D.

2013-12-01

The Fast Plasma Investigation (FPI) of the NASA Magnetospheric MultiScale (MMS) mission employs 16 Dual Electron Spectrometers (DESs) and 16 Dual Ion Spectrometers (DISs) with 4 of each type on each of 4 spacecraft to enable fast (30ms for electrons; 150ms for ions) and spatially differentiated measurements of full the 3D particle velocity distributions. This approach presents a new and challenging aspect to the calibration and operation of these instruments on ground and in flight. The response uniformity and reliability of their calibration and the approach to handling any temporal evolution of these calibrated characteristics all assume enhanced importance in this application, where we attempt to understand the meaning of particle distributions within the ion and electron diffusion regions. Traditionally, the micro-channel plate (MCP) based detection systems for electrostatic particle spectrometers have been calibrated by setting a fixed detection threshold and, subsequently, measuring a detection system count rate plateau curve to determine the MCP voltage that ensures the count rate has reached a constant value independent of further variation in the MCP voltage. This is achieved when most of the MCP pulse height distribution (PHD) is located at higher values (larger pulses) than the detection amplifier threshold. This method is adequate in single-channel detection systems and in multi-channel detection systems with very low crosstalk between channels. However, in dense multi-channel systems, it can be inadequate. Furthermore, it fails to fully and individually characterize each of the fundamental parameters of the detection system. We present a new detection system calibration method that enables accurate and repeatable measurement and calibration of MCP gain, MCP efficiency, signal loss due to variation in gain and efficiency, crosstalk from effects both above and below the MCP, noise margin, and stability margin in one single measurement. The fundamental concepts of this method, named threshold scan, will be presented. It will be shown how to derive all the individual detection system parameters. This new method has been successfully applied to achieve a highly accurate calibration of the 16 Dual Electron Spectrometers and 16 Dual Ion Spectrometers of the MMS mission. The practical application of the method will be presented together with the achieved calibration results and their significance. Finally, it will be shown how this method will be applied to ensure the best possible in flight calibration during the mission.

The detection error of thermal test low-frequency cable based on M sequence correlation algorithm

NASA Astrophysics Data System (ADS)

Wu, Dongliang; Ge, Zheyang; Tong, Xin; Du, Chunlin

2018-04-01

The problem of low accuracy and low efficiency of off-line detecting on thermal test low-frequency cable faults could be solved by designing a cable fault detection system, based on FPGA export M sequence code(Linear feedback shift register sequence) as pulse signal source. The design principle of SSTDR (Spread spectrum time-domain reflectometry) reflection method and hardware on-line monitoring setup figure is discussed in this paper. Testing data show that, this detection error increases with fault location of thermal test low-frequency cable.

Analysis of chemical warfare agents by gas chromatography-mass spectrometry: methods for their direct detection and derivatization approaches for the analysis of their degradation products

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

Valdez, Carlos A.; Leif, Roald N.; Hok, Saphon

Abstract Chemical warfare agents (CWAs) are unarguably one of the most feared toxic substances produced by mankind. Their inception in conventional warfare can be traced as far back as the Middle Ages but their full breakthrough as central players in bellic conflicts was not realized until World War I. Since then, more modern CWAs along with efficient methods for their manufacture have emerged and violently shaped the way modern warfare and diplomatic relations are conducted. Owing to their mass destruction ability, counter methods to mitigate their impact appeared almost immediately on par with their development. These efforts have focused onmore » their efficient destruction, development of medical countermeasures and their detection by modern analytical chemistry methods. The following review seeks to provide the reader with a broad introduction on their direct detection by gas chromatography-mass spectrometry (GC-MS) and the various sample derivatization methods available for the analysis of their degradation products. The review concentrates on three of the main CWA classes and includes the nerve agents, the blistering agents and lastly, the incapacitating agents. Each section begins with a brief introduction of the CWA along with discussions of reports dealing with their detection in the intact form by GC-MS. Furthermore, as products arising from their degradation carry as much importance as the agents themselves in the field of forensic analysis, the available derivatization methods of these species are presented for each CWA highlighting some examples from our lab in the Forensic Science Center at the Lawrence Livermore National Laboratory.« less

Analysis of chemical warfare agents by gas chromatography-mass spectrometry: methods for their direct detection and derivatization approaches for the analysis of their degradation products

DOE PAGES

Valdez, Carlos A.; Leif, Roald N.; Hok, Saphon; ...

2017-07-25

Abstract Chemical warfare agents (CWAs) are unarguably one of the most feared toxic substances produced by mankind. Their inception in conventional warfare can be traced as far back as the Middle Ages but their full breakthrough as central players in bellic conflicts was not realized until World War I. Since then, more modern CWAs along with efficient methods for their manufacture have emerged and violently shaped the way modern warfare and diplomatic relations are conducted. Owing to their mass destruction ability, counter methods to mitigate their impact appeared almost immediately on par with their development. These efforts have focused onmore » their efficient destruction, development of medical countermeasures and their detection by modern analytical chemistry methods. The following review seeks to provide the reader with a broad introduction on their direct detection by gas chromatography-mass spectrometry (GC-MS) and the various sample derivatization methods available for the analysis of their degradation products. The review concentrates on three of the main CWA classes and includes the nerve agents, the blistering agents and lastly, the incapacitating agents. Each section begins with a brief introduction of the CWA along with discussions of reports dealing with their detection in the intact form by GC-MS. Furthermore, as products arising from their degradation carry as much importance as the agents themselves in the field of forensic analysis, the available derivatization methods of these species are presented for each CWA highlighting some examples from our lab in the Forensic Science Center at the Lawrence Livermore National Laboratory.« less

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

PubMed

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

2015-01-01

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

Prospects of detection of the first sources with SKA using matched filters

NASA Astrophysics Data System (ADS)

Ghara, Raghunath; Choudhury, T. Roy; Datta, Kanan K.; Mellema, Garrelt; Choudhuri, Samir; Majumdar, Suman; Giri, Sambit K.

2018-05-01

The matched filtering technique is an efficient method to detect H ii bubbles and absorption regions in radio interferometric observations of the redshifted 21-cm signal from the epoch of reionization and the Cosmic Dawn. Here, we present an implementation of this technique to the upcoming observations such as the SKA1-low for a blind search of absorption regions at the Cosmic Dawn. The pipeline explores four dimensional parameter space on the simulated mock visibilities using a MCMC algorithm. The framework is able to efficiently determine the positions and sizes of the absorption/H ii regions in the field of view.

Chromatographic separation and detection of contaminants from whole milk powder using a chitosan-modified silver nanoparticles surface-enhanced Raman scattering device.

PubMed

Li, Dan; Lv, Di Y; Zhu, Qing X; Li, Hao; Chen, Hui; Wu, Mian M; Chai, Yi F; Lu, Feng

2017-06-01

Methods for the on-site analysis of food contaminants are in high demand. Although portable Raman spectroscopy is commonly used to test food on-site, it can be challenge to achieve this goal with rapid detection and inexpensive substrate. In this study, we detected trace food contaminants in samples of whole milk powder using the methods that combined chromatography with surface-enhanced Raman scattering detection (SERS). We developed a simple and efficient technique to fabricate the paper with chitosan-modified silver nanoparticles as a SERS-active substrate. The soaking time of paper and the concentration of chitosan solution were optimized for chromatographic separation and SERS detection. We then studied the separation properties for real applications including complex sample matrices, and detected melamine at 1mg/L, dicyandiamide at 100mg/L and sodium sulfocyanate at 10mg/L in whole milk powder. As such, our methods have great potential for field-based detection of milk contaminants. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of immobilized synthetic anti-lipopolysaccharide peptides for the isolation and detection of bacteria.

PubMed

Sandetskaya, N; Engelmann, B; Brandenburg, K; Kuhlmeier, D

2015-08-01

The molecular detection of microorganisms in liquid samples generally requires their enrichment or isolation. The aim of our study was to evaluate the capture and pre-concentration of bacteria by immobilized particular cationic antimicrobial peptides, called synthetic anti-lipopolysaccharide peptides (SALP). For the proof-of-concept and screening of different SALP, the peptides were covalently immobilized on glass slides, and the binding of bacteria was confirmed by microscopic examination of the slides or their scanning, in case of fluorescent bacterial cells. The most efficient SALP was further tethered to magnetic beads. SALP beads were used for the magnetic capture of Escherichia coli in liquid samples. The efficiency of this strategy was evaluated using polymerase chain reaction (PCR). Covalently immobilized SALP were capable of capturing bacteria in liquid samples. However, PCR was hampered by the unspecific binding of DNA to the positively charged peptide. We developed a method for DNA recovery by the enzymatic digestion of the peptide, which allowed for a successful PCR, though the method had its own adverse impact on the detection and, thus, did not allow for the reliable quantitative analysis of the pathogen enrichment. Immobilized SALP can be used as capture molecules for bacteria in liquid samples and can be recommended for the design of the assays or decontamination of the fluids. For the accurate subsequent detection of bacteria, DNA-independent methods should be used.

Multi-Element CZT Array for Nuclear Safeguards Applications

NASA Astrophysics Data System (ADS)

Kwak, S.-W.; Lee, A.-R.; Shin, J.-K.; Park, U.-R.; Park, S.; Kim, Y.; Chung, H.

2016-12-01

Due to its electronic properties, a cadmium zinc telluride (CZT) detector has been used as a hand-held portable nuclear measurement instrument. However, a CZT detector has low detection efficiency because of a limitation of its single crystal growth. To address its low efficiency, we have constructed a portable four-CZT array based gamma-ray spectrometer consisting of a CZT array, electronics for signal processing and software. Its performance has been characterized in terms of energy resolution and detection efficiency using radioactive sources and nuclear materials. Experimental results showed that the detection efficiency of the four-CZT array based gamma-ray spectrometer was much higher than that of a single CZT detector in the array. The FWHMs of the CZT array were 9, 18, and 21 keV at 185.7, 662, and 1,332 keV, respectively. Some gamma-rays in a range of 100 keV to 200 keV were not clear in a single crystal detector while those from the CZT array system were observed to be clear. The energy resolution of the CZT array system was only slightely worse than those of the single CZT detectors. By combining several single crystals and summing signals from each single detector at a digital electronic circuit, the detection efficiency of a CZT array system increased without degradation of its energy resolution. The technique outlined in this paper shows a very promising method for designing a CZT-based gamma-ray spectroscopy that overcomes the fundamental limitations of a small volume CZT detector.

A Precise Visual Method for Narrow Butt Detection in Specular Reflection Workpiece Welding

PubMed Central

Zeng, Jinle; Chang, Baohua; Du, Dong; Hong, Yuxiang; Chang, Shuhe; Zou, Yirong

2016-01-01

During the complex path workpiece welding, it is important to keep the welding torch aligned with the groove center using a visual seam detection method, so that the deviation between the torch and the groove can be corrected automatically. However, when detecting the narrow butt of a specular reflection workpiece, the existing methods may fail because of the extremely small groove width and the poor imaging quality. This paper proposes a novel detection method to solve these issues. We design a uniform surface light source to get high signal-to-noise ratio images against the specular reflection effect, and a double-line laser light source is used to obtain the workpiece surface equation relative to the torch. Two light sources are switched on alternately and the camera is synchronized to capture images when each light is on; then the position and pose between the torch and the groove can be obtained nearly at the same time. Experimental results show that our method can detect the groove effectively and efficiently during the welding process. The image resolution is 12.5 μm and the processing time is less than 10 ms per frame. This indicates our method can be applied to real-time narrow butt detection during high-speed welding process. PMID:27649173

A Precise Visual Method for Narrow Butt Detection in Specular Reflection Workpiece Welding.

PubMed

Zeng, Jinle; Chang, Baohua; Du, Dong; Hong, Yuxiang; Chang, Shuhe; Zou, Yirong

2016-09-13

During the complex path workpiece welding, it is important to keep the welding torch aligned with the groove center using a visual seam detection method, so that the deviation between the torch and the groove can be corrected automatically. However, when detecting the narrow butt of a specular reflection workpiece, the existing methods may fail because of the extremely small groove width and the poor imaging quality. This paper proposes a novel detection method to solve these issues. We design a uniform surface light source to get high signal-to-noise ratio images against the specular reflection effect, and a double-line laser light source is used to obtain the workpiece surface equation relative to the torch. Two light sources are switched on alternately and the camera is synchronized to capture images when each light is on; then the position and pose between the torch and the groove can be obtained nearly at the same time. Experimental results show that our method can detect the groove effectively and efficiently during the welding process. The image resolution is 12.5 μm and the processing time is less than 10 ms per frame. This indicates our method can be applied to real-time narrow butt detection during high-speed welding process.

Synthesis of amino-rich silica coated magnetic nanoparticles and their application in the capture of DNA for PCR

USDA-ARS?s Scientific Manuscript database

Magnetic separation has great advantages over traditional bioseparation methods and has become popular in the development of methods for the detection of bacterial pathogens, viruses, and transgenic crops. Functionalization of magnetic nanoparticles is a key factor in allowing efficient capture of t...

Global challenges/chemistry solutions: Promoting personal safety and national security

USDA-ARS?s Scientific Manuscript database

Joe Alper: Can you provide a little background about why there is a need for this type of assay? Mark Carter: Ricin is considered a biosecurity threat agent. A more efficient detection method was required. Joe Alper: How are these type of assays done today, or are current methods unsuitable for ...

Assessment of Air Emissions from Oil and Natural Gas Well Pads Using Mobile Remote and Onsite Direct Measurements

EPA Science Inventory

An enhanced ability to efficiently detect large maintenance related emissions is required to ensure sustainable oil and gas development. To help achieve this goal, a new remote inspection method, Other Test Method (OTM) 33A, was developed and utilized to quantify short-term metha...

Non-iterative Voltage Stability

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

Makarov, Yuri V.; Vyakaranam, Bharat; Hou, Zhangshuan

2014-09-30

This report demonstrates promising capabilities and performance characteristics of the proposed method using several power systems models. The new method will help to develop a new generation of highly efficient tools suitable for real-time parallel implementation. The ultimate benefit obtained will be early detection of system instability and prevention of system blackouts in real time.

Performance assessment of Beijing Lightning Network (BLNET) and comparison with other lightning location networks across Beijing

NASA Astrophysics Data System (ADS)

Srivastava, Abhay; Tian, Ye; Qie, Xiushu; Wang, Dongfang; Sun, Zhuling; Yuan, Shanfeng; Wang, Yu; Chen, Zhixiong; Xu, Wenjing; Zhang, Hongbo; Jiang, Rubin; Su, Debin

2017-11-01

The performances of Beijing Lightning Network (BLNET) operated in Beijing-Tianjin-Hebei urban cluster area have been evaluated in terms of detection efficiency and relative location accuracy. A self-reference method has been used to show the detection efficiency of BLNET, for which fast antenna waveforms have been manually examined. Based on the fast antenna verification, the average detection efficiency of BLNET is 97.4% for intracloud (IC) flashes, 73.9% for cloud-to-ground (CG) flashes and 93.2% for the total flashes. Result suggests the CG detection of regional dense network is highly precise when the thunderstorm passes over the network; however it changes day to day when the thunderstorms are outside the network. Further, the CG stroke data from three different lightning location networks across Beijing are compared. The relative detection efficiency of World Wide Lightning Location Network (WWLLN) and Chinese Meteorology Administration - Lightning Detection Network (CMA-LDN, also known as ADTD) are approximately 12.4% (16.8%) and 36.5% (49.4%), respectively, comparing with fast antenna (BLNET). The location of BLNET is in middle, while WWLLN and CMA-LDN average locations are southeast and northwest, respectively. Finally, the IC pulses and CG return stroke pulses have been compared with the S-band Doppler radar. This type of study is useful to know the approximate situation in a region and improve the performance of lightning location networks in the absence of ground truth. Two lightning flashes occurred on tower in the coverage of BLNET show that the horizontal location error was 52.9 m and 250 m, respectively.

An incremental community detection method for social tagging systems using locality-sensitive hashing.

PubMed

Wu, Zhenyu; Zou, Ming

2014-10-01

An increasing number of users interact, collaborate, and share information through social networks. Unprecedented growth in social networks is generating a significant amount of unstructured social data. From such data, distilling communities where users have common interests and tracking variations of users' interests over time are important research tracks in fields such as opinion mining, trend prediction, and personalized services. However, these tasks are extremely difficult considering the highly dynamic characteristics of the data. Existing community detection methods are time consuming, making it difficult to process data in real time. In this paper, dynamic unstructured data is modeled as a stream. Tag assignments stream clustering (TASC), an incremental scalable community detection method, is proposed based on locality-sensitive hashing. Both tags and latent interactions among users are incorporated in the method. In our experiments, the social dynamic behaviors of users are first analyzed. The proposed TASC method is then compared with state-of-the-art clustering methods such as StreamKmeans and incremental k-clique; results indicate that TASC can detect communities more efficiently and effectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis of SMELS and reference materials for validation of the k0-based internal monostandard NAA method using in-situ detection efficiency

NASA Astrophysics Data System (ADS)

Acharya, R.; Swain, K. K.; Reddy, A. V. R.

2010-10-01

Three synthetic multielement standards (SMELS I, II and III) and two reference materials (RMs), SL-3 and Soil-7 of IAEA were analyzed for validation of the k0-based internal monostandard neutron activation analysis (IM-NAA) method utilizing in-situ relative detection efficiency. The internal monostandards used in SMELS and RMs were Au and Sc, respectively. The samples were irradiated in Apsara and Dhruva reactors, BARC and radioactive assay was carried out using a 40% relative efficiency HPGe detector coupled to an 8 k MCA. Concentrations of 23 elements were determined in both SMELS and RMs. In the case of RMs, concentrations of a few elements, whose certified values are not available, could also be determined. The % deviations for the elements determined in SMELS with respect to the assigned values and RMs with respect to certified values were within ±8%. The Z-score values at 95% confidence level for most of the elements in both the materials were within ±1.

Real-Time PCR Assay for Detection and Enumeration of Dekkera bruxellensis in Wine

PubMed Central

Phister, Trevor G.; Mills, David A.

2003-01-01

Traditional methods to detect the spoilage yeast Dekkera bruxellensis from wine involve lengthy enrichments. To overcome this difficulty, we developed a quantitative real-time PCR method to directly detect and enumerate D. bruxellensis in wine. Specific PCR primers to D. bruxellensis were designed to the 26S rRNA gene, and nontarget yeast and bacteria common to the winery environment were not amplified. The assay was linear over a range of cell concentrations (6 log units) and could detect as little as 1 cell per ml in wine. The addition of large amounts of nontarget yeasts did not impact the efficiency of the assay. This method will be helpful to identify possible routes of D. bruxellensis infection in winery environments. Moreover, the time involved in performing the assay (3 h) should enable winemakers to more quickly make wine processing decisions in order to reduce the threat of spoilage by D. bruxellensis. PMID:14660395

Green synthesis of carbon dots from pork and application as nanosensors for uric acid detection

NASA Astrophysics Data System (ADS)

Zhao, Chunxi; Jiao, Yang; Hu, Feng; Yang, Yaling

2018-02-01

In this work, a green, simple, economical method was developed in the synthesis of fluorescent carbon dots using pork as carbon source. The as-prepared carbon dots exhibit exceptional advantages including high fluorescent quantum yield (17.3%) and satisfactory chemical stability. The fluorescence of carbon dots based nanosensor can be selectively and efficiently quenched by uric acid. This phenomenon was used to develop a fluorescent method for facile detection of uric acid within a linear range of 0.1-100 μM and 100-500 μM, with a detection limit of 0.05 μM (S/N = 3). Finally, the proposed method was successfully applied in the determination of uric acid in human serum and urine samples with satisfactory recoveries, which suggested that the new nanosensors have great prospect toward the detection of uric acid in human fluids.

Using Informatics-, Bioinformatics- and Genomics-Based Approaches for the Molecular Surveillance and Detection of Biothreat Agents

NASA Astrophysics Data System (ADS)

Seto, Donald

The convergence and wealth of informatics, bioinformatics and genomics methods and associated resources allow a comprehensive and rapid approach for the surveillance and detection of bacterial and viral organisms. Coupled with the continuing race for the fastest, most cost-efficient and highest-quality DNA sequencing technology, that is, "next generation sequencing", the detection of biological threat agents by `cheaper and faster' means is possible. With the application of improved bioinformatic tools for the understanding of these genomes and for parsing unique pathogen genome signatures, along with `state-of-the-art' informatics which include faster computational methods, equipment and databases, it is feasible to apply new algorithms to biothreat agent detection. Two such methods are high-throughput DNA sequencing-based and resequencing microarray-based identification. These are illustrated and validated by two examples involving human adenoviruses, both from real-world test beds.

Optical arc sensor using energy harvesting power source

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

Choi, Kyoo Nam, E-mail: knchoi@inu.ac.kr; Rho, Hee Hyuk, E-mail: rdoubleh0902@inu.ac.kr

Wireless sensors without external power supply gained considerable attention due to convenience both in installation and operation. Optical arc detecting sensor equipping with self sustaining power supply using energy harvesting method was investigated. Continuous energy harvesting method was attempted using thermoelectric generator to supply standby power in micro ampere scale and operating power in mA scale. Peltier module with heat-sink was used for high efficiency electricity generator. Optical arc detecting sensor with hybrid filter showed insensitivity to fluorescent and incandescent lamps under simulated distribution panel condition. Signal processing using integrating function showed selective arc discharge detection capability to different arcmore » energy levels, with a resolution below 17 J energy difference, unaffected by bursting arc waveform. The sensor showed possibility for application to arc discharge detecting sensor in power distribution panel. Also experiment with proposed continuous energy harvesting method using thermoelectric power showed possibility as a self sustainable power source of remote sensor.« less

Optical arc sensor using energy harvesting power source

NASA Astrophysics Data System (ADS)

Choi, Kyoo Nam; Rho, Hee Hyuk

2016-06-01

Wireless sensors without external power supply gained considerable attention due to convenience both in installation and operation. Optical arc detecting sensor equipping with self sustaining power supply using energy harvesting method was investigated. Continuous energy harvesting method was attempted using thermoelectric generator to supply standby power in micro ampere scale and operating power in mA scale. Peltier module with heat-sink was used for high efficiency electricity generator. Optical arc detecting sensor with hybrid filter showed insensitivity to fluorescent and incandescent lamps under simulated distribution panel condition. Signal processing using integrating function showed selective arc discharge detection capability to different arc energy levels, with a resolution below 17J energy difference, unaffected by bursting arc waveform. The sensor showed possibility for application to arc discharge detecting sensor in power distribution panel. Also experiment with proposed continuous energy harvesting method using thermoelectric power showed possibility as a self sustainable power source of remote sensor.

Practical results from a mathematical analysis of guard patrols

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

Indusi, Joseph P.

1978-12-01

Using guard patrols as a primary detection mechanism is not generally viewed as a highly efficient detection method when compared to electronic means. Many factors such as visibility, alertness, and the space-time coincidence of guard and adversary presence all have an effect on the probability of detection. Mathematical analysis of the guard patrol detection problem is related to that of classical search theory originally developed for naval search operations. The results of this analysis tend to support the current practice of using guard forces to assess and respond to previously detected intrusions and not as the primary detection mechanism. 6more » refs.« less

Seeking to Improve Low Energy Neutral Atom Detection in Space

NASA Technical Reports Server (NTRS)

Shappirio, M.; Coplan, M.; Chornay, D.; Collier, M.; Herrero, F.; Ogilvie, K.; Williams, E.

2007-01-01

The detection of energetic neutral atoms allows for the remote examination of the interactions between plasmas and neutral populations in space. Before these neutral atoms can be measured, they must first be converted to ions. For the low energy end of this spectrum, interaction with a conversion surface is often the most efficient method to convert neutrals into ions. It is generally thought that the most efficient surfaces are low work functions materials. However, by their very nature, these surfaces are highly reactive and unstable, and therefore are not suitable for space missions where conditions cannot be controlled as they are in a laboratory. We therefore are looking to optimize a stable surface for conversion efficiency. Conversion efficiency can be increased either by changing the incident angle of the neutral particles to be grazing incidence and using stable surfaces with high conversion efficiencies. We have examined how to increase the angle of incidence from -80 degrees to -89 degrees, while maintaining or improving the total active conversion surface area without increasing the overall volume of the instrument. We are developing a method to micro-machine silicon, which will reduce the volume to surface area ratio by a factor of 60. We have also examined the material properties that affect the conversion efficiency of the surface for stable surfaces. Some of the parameters we have examined are work function, smoothness, and bond structure. We find that for stable surfaces, the most important property is the smoothness of the surface.

Application of Time-Frequency Domain Transform to Three-Dimensional Interpolation of Medical Images.

PubMed

Lv, Shengqing; Chen, Yimin; Li, Zeyu; Lu, Jiahui; Gao, Mingke; Lu, Rongrong

2017-11-01

Medical image three-dimensional (3D) interpolation is an important means to improve the image effect in 3D reconstruction. In image processing, the time-frequency domain transform is an efficient method. In this article, several time-frequency domain transform methods are applied and compared in 3D interpolation. And a Sobel edge detection and 3D matching interpolation method based on wavelet transform is proposed. We combine wavelet transform, traditional matching interpolation methods, and Sobel edge detection together in our algorithm. What is more, the characteristics of wavelet transform and Sobel operator are used. They deal with the sub-images of wavelet decomposition separately. Sobel edge detection 3D matching interpolation method is used in low-frequency sub-images under the circumstances of ensuring high frequency undistorted. Through wavelet reconstruction, it can get the target interpolation image. In this article, we make 3D interpolation of the real computed tomography (CT) images. Compared with other interpolation methods, our proposed method is verified to be effective and superior.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Electrostatic monitoring

DOEpatents

Orr, Christopher Henry; Luff, Craig Janson; Dockray, Thomas; Macarthur, Duncan Whittemore

2001-01-01

The apparatus and method provide a technique for more simply measuring alpha and/or beta emissions arising from items or locations. The technique uses indirect monitoring of the emissions by detecting ions generated by the emissions, the ions being attracted electrostatically to electrodes for discharge of collection. The apparatus and method employ a chamber which is sealed around the item or location during monitoring with no air being drawn into or expelled from the chamber during the monitoring process. A simplified structure and operations arises as a result, but without impairing the efficiency and accuracy of the detection technique.

Comparison of direct 13C and indirect 1H-[13C] MR detection methods for the study of dynamic metabolic turnover in the human brain

NASA Astrophysics Data System (ADS)

Chen, Hao; De Feyter, Henk M.; Brown, Peter B.; Rothman, Douglas L.; Cai, Shuhui; de Graaf, Robin A.

2017-10-01

A wide range of direct 13C and indirect 1H-[13C] MR detection methods exist to probe dynamic metabolic pathways in the human brain. Choosing an optimal detection method is difficult as sequence-specific features regarding spatial localization, broadband decoupling, spectral resolution, power requirements and sensitivity complicate a straightforward comparison. Here we combine density matrix simulations with experimentally determined values for intrinsic 1H and 13C sensitivity, T1 and T2 relaxation and transmit efficiency to allow selection of an optimal 13C MR detection method for a given application and magnetic field. The indirect proton-observed, carbon-edited (POCE) detection method provides the highest accuracy at reasonable RF power deposition both at 4 T and 7 T. The various polarization transfer methods all have comparable performances, but may become infeasible at 7 T due to the high RF power deposition. 2D MR methods have limited value for the metabolites considered (primarily glutamate, glutamine and γ-amino butyric acid (GABA)), but may prove valuable when additional information can be extracted, such as isotopomers or lipid composition. While providing the lowest accuracy, the detection of non-protonated carbons is the simplest to implement with the lowest RF power deposition. The magnetic field homogeneity is one of the most important parameters affecting the detection accuracy for all metabolites and all acquisition methods.

Absolute ion detection efficiencies of microchannel plates and funnel microchannel plates for multi-coincidence detection

NASA Astrophysics Data System (ADS)

Fehre, K.; Trojanowskaja, D.; Gatzke, J.; Kunitski, M.; Trinter, F.; Zeller, S.; Schmidt, L. Ph. H.; Stohner, J.; Berger, R.; Czasch, A.; Jagutzki, O.; Jahnke, T.; Dörner, R.; Schöffler, M. S.

2018-04-01

Modern momentum imaging techniques allow for the investigation of complex molecules in the gas phase by detection of several fragment ions in coincidence. For these studies, it is of great importance that the single-particle detection efficiency ɛ is as high as possible, as the overall efficiency scales with ɛn, i.e., the power of the number of detected particles. Here we present measured absolute detection efficiencies for protons of several micro-channel plates (MCPs), including efficiency enhanced "funnel MCPs." Furthermore, the relative detection efficiency for two-, three-, four-, and five-body fragmentation of CHBrClF has been examined. The "funnel" MCPs exhibit an efficiency of approximately 90%, gaining a factor of 24 (as compared to "normal" MCPs) in the case of a five-fold ion coincidence detection.

Digital signal processing techniques for coherent optical communication

NASA Astrophysics Data System (ADS)

Goldfarb, Gilad

Coherent detection with subsequent digital signal processing (DSP) is developed, analyzed theoretically and numerically and experimentally demonstrated in various fiber-optic transmission scenarios. The use of DSP in conjunction with coherent detection unleashes the benefits of coherent detection which rely on the preservaton of full information of the incoming field. These benefits include high receiver sensitivity, the ability to achieve high spectral-efficiency and the use of advanced modulation formats. With the immense advancements in DSP speeds, many of the problems hindering the use of coherent detection in optical transmission systems have been eliminated. Most notably, DSP alleviates the need for hardware phase-locking and polarization tracking, which can now be achieved in the digital domain. The complexity previously associated with coherent detection is hence significantly diminished and coherent detection is once gain considered a feasible detection alternative. In this thesis, several aspects of coherent detection (with or without subsequent DSP) are addressed. Coherent detection is presented as a means to extend the dispersion limit of a duobinary signal using an analog decision-directed phase-lock loop. Analytical bit-error ratio estimation for quadrature phase-shift keying signals is derived. To validate the promise for high spectral efficiency, the orthogonal-wavelength-division multiplexing scheme is suggested. In this scheme the WDM channels are spaced at the symbol rate, thus achieving the spectral efficiency limit. Theory, simulation and experimental results demonstrate the feasibility of this approach. Infinite impulse response filtering is shown to be an efficient alternative to finite impulse response filtering for chromatic dispersion compensation. Theory, design considerations, simulation and experimental results relating to this topic are presented. Interaction between fiber dispersion and nonlinearity remains the last major challenge deterministic effects pose for long-haul optical data transmission. Experimental results which demonstrate the possibility to digitally mitigate both dispersion and nonlinearity are presented. Impairment compensation is achieved using backward propagation by implementing the split-step method. Efficient realizations of the dispersion compensation operator used in this implementation are considered. Infinite-impulse response and wavelet-based filtering are both investigated as a means to reduce the required computational load associated with signal backward-propagation. Possible future research directions conclude this dissertation.

A sensitive and efficient method for determination of N-acetylhexosamines and N-acetylneuraminic acid in breast milk and milk-based products by high-performance liquid chromatography via UV detection and mass spectrometry identification.

PubMed

Chuanxiang, Wu; Lian, Xia; Lijie, Liu; Fengli, Qu; Zhiwei, Sun; Xianen, Zhao; Jinmao, You

2016-02-01

A sensitive and efficient method of high performance liquid chromatography using 1-(2-naphthyl)-3-methyl-5-pyrazolone (NMP) as pre-column derivatization reagent coupled with UV detection (HPLC-UV) and online mass spectrometry identification was established for determination of the most common N-Acetylhexosamines (N-acetyl-d-glucosamine (GlcNAc) and N-acetyl-d-galactosamine (GalNAc)) and N-acetylneuraminic acid (Neu5Ac). In order to obtain the highest liberation level of the three monosaccharides without destruction of Neu5Ac or conversion of GlcNAc/GalNAc to GlcN/GalN in the hydrolysis procedure, the pivotal parameters affecting the liberation of N-acetylhexosamines/Neu5Ac from sample were investigated with response surface methodology (RSM). Under the optimized condition, maximum yield was obtained. The effects of key parameters on derivatization, separation and detection were also investigated. At optimized conditions, three monosaccharides were labeled fast and entirely, and all derivatives exhibited a good baseline resolution and high detection sensitivity. The developed method was linear over the calibration range 0.25-12μM, with R(2)>0.9991. The detection limits of the method were between 0.48 and 2.01pmol. Intra- and inter-day precisions for the three monosaccharides (GlcNAc, GalNAc and Neu5Ac) were found to be in the range of 3.07-4.02% and 3.69-4.67%, respectively. Individual monosaccharide recovery from spiked milk was in the range of 81%-97%. The sensitivity of the method, the facility of the derivatization procedure and the reliability of the hydrolysis conditions suggest the proposed method has a high potential for utilization in routine trace N-acetylhexosamines and Neu5Ac analysis in biological samples. Copyright © 2015 Elsevier B.V. All rights reserved.

G-CNV: A GPU-Based Tool for Preparing Data to Detect CNVs with Read-Depth Methods.

PubMed

Manconi, Andrea; Manca, Emanuele; Moscatelli, Marco; Gnocchi, Matteo; Orro, Alessandro; Armano, Giuliano; Milanesi, Luciano

2015-01-01

Copy number variations (CNVs) are the most prevalent types of structural variations (SVs) in the human genome and are involved in a wide range of common human diseases. Different computational methods have been devised to detect this type of SVs and to study how they are implicated in human diseases. Recently, computational methods based on high-throughput sequencing (HTS) are increasingly used. The majority of these methods focus on mapping short-read sequences generated from a donor against a reference genome to detect signatures distinctive of CNVs. In particular, read-depth based methods detect CNVs by analyzing genomic regions with significantly different read-depth from the other ones. The pipeline analysis of these methods consists of four main stages: (i) data preparation, (ii) data normalization, (iii) CNV regions identification, and (iv) copy number estimation. However, available tools do not support most of the operations required at the first two stages of this pipeline. Typically, they start the analysis by building the read-depth signal from pre-processed alignments. Therefore, third-party tools must be used to perform most of the preliminary operations required to build the read-depth signal. These data-intensive operations can be efficiently parallelized on graphics processing units (GPUs). In this article, we present G-CNV, a GPU-based tool devised to perform the common operations required at the first two stages of the analysis pipeline. G-CNV is able to filter low-quality read sequences, to mask low-quality nucleotides, to remove adapter sequences, to remove duplicated read sequences, to map the short-reads, to resolve multiple mapping ambiguities, to build the read-depth signal, and to normalize it. G-CNV can be efficiently used as a third-party tool able to prepare data for the subsequent read-depth signal generation and analysis. Moreover, it can also be integrated in CNV detection tools to generate read-depth signals.

In-injection port thermal desorption for explosives trace evidence analysis.

PubMed

Sigman, M E; Ma, C Y

1999-10-01

A gas chromatographic method utilizing thermal desorption of a dry surface wipe for the analysis of explosives trace chemical evidence has been developed and validated using electron capture and negative ion chemical ionization mass spectrometric detection. Thermal desorption was performed within a split/splitless injection port with minimal instrument modification. Surface-abraded Teflon tubing provided the solid support for sample collection and desorption. Performance was characterized by desorption efficiency, reproducibility, linearity of the calibration, and method detection and quantitation limits. Method validation was performed with a series of dinitrotoluenes, trinitrotoluene, two nitroester explosives, and one nitramine explosive. The method was applied to the sampling of a single piece of debris from an explosion containing trinitrotoluene.

Brief Report: A mass spectrometry assay to simultaneously analyze ROS1 and RET fusion gene expression in non-small cell lung cancer

PubMed Central

Wijesinghe, Priyanga; Bepler, Gerold

2014-01-01

Introduction ROS1 and RET gene fusions were recently discovered in non-small cell lung cancer (NSCLC) as potential therapeutic targets with small molecule kinase inhibitors. The conventional screening methods of these fusions are time consuming and require samples of high quality and quantity. Here, we describe a novel and efficient method by coupling the power of multiplexing PCR and the sensitivity of mass spectrometry. Methods The multiplex mass spectrometry platform simultaneously tests samples for the expression of nine ROS1 and six RET fusion genes. The assay incorporates detection of wild-type exon junctions immediately upstream and downstream of the fusion junction to exclude false negative results. To flag false positives, the system also comprises two independent assays for each fusion gene junction. Results The characteristic mass spectrometric peaks of the gene fusions were obtained using engineered plasmid constructs. Specific assays targeting the wild-type gene exon junctions were validated using cDNA from lung tissue of healthy individuals. The system was further validated using cDNA derived from NSCLC cell lines that express endogenous fusion genes. The expressed ROS1-SLC34A2 and CCDC6-RET gene fusions from the NSCLC cell lines HCC78 and LC-2/ad, respectively, were accurately detected by the novel assay. The assay is extremely sensitive, capable of detecting an event in test specimens containing 0.5% positive tumors. Conclusion The novel multiplexed assay is robustly capable of detecting 15 different clinically relevant RET and ROS1 fusion variants. The benefits of this detection method include exceptionally low sample input, high cost efficiency, flexibility, and rapid turnover. PMID:25384172

Detecting exact breakpoints of deletions with diversity in hepatitis B viral genomic DNA from next-generation sequencing data.

PubMed

Cheng, Ji-Hong; Liu, Wen-Chun; Chang, Ting-Tsung; Hsieh, Sun-Yuan; Tseng, Vincent S

2017-10-01

Many studies have suggested that deletions of Hepatitis B Viral (HBV) are associated with the development of progressive liver diseases, even ultimately resulting in hepatocellular carcinoma (HCC). Among the methods for detecting deletions from next-generation sequencing (NGS) data, few methods considered the characteristics of virus, such as high evolution rates and high divergence among the different HBV genomes. Sequencing high divergence HBV genome sequences using the NGS technology outputs millions of reads. Thus, detecting exact breakpoints of deletions from these big and complex data incurs very high computational cost. We proposed a novel analytical method named VirDelect (Virus Deletion Detect), which uses split read alignment base to detect exact breakpoint and diversity variable to consider high divergence in single-end reads data, such that the computational cost can be reduced without losing accuracy. We use four simulated reads datasets and two real pair-end reads datasets of HBV genome sequence to verify VirDelect accuracy by score functions. The experimental results show that VirDelect outperforms the state-of-the-art method Pindel in terms of accuracy score for all simulated datasets and VirDelect had only two base errors even in real datasets. VirDelect is also shown to deliver high accuracy in analyzing the single-end read data as well as pair-end data. VirDelect can serve as an effective and efficient bioinformatics tool for physiologists with high accuracy and efficient performance and applicable to further analysis with characteristics similar to HBV on genome length and high divergence. The software program of VirDelect can be downloaded at https://sourceforge.net/projects/virdelect/. Copyright © 2017. Published by Elsevier Inc.

Study of vesicle size distribution dependence on pH value based on nanopore resistive pulse method

NASA Astrophysics Data System (ADS)

Lin, Yuqing; Rudzevich, Yauheni; Wearne, Adam; Lumpkin, Daniel; Morales, Joselyn; Nemec, Kathleen; Tatulian, Suren; Lupan, Oleg; Chow, Lee

2013-03-01

Vesicles are low-micron to sub-micron spheres formed by a lipid bilayer shell and serve as potential vehicles for drug delivery. The size of vesicle is proposed to be one of the instrumental variables affecting delivery efficiency since the size is correlated to factors like circulation and residence time in blood, the rate for cell endocytosis, and efficiency in cell targeting. In this work, we demonstrate accessible and reliable detection and size distribution measurement employing a glass nanopore device based on the resistive pulse method. This novel method enables us to investigate the size distribution dependence of pH difference across the membrane of vesicles with very small sample volume and rapid speed. This provides useful information for optimizing the efficiency of drug delivery in a pH sensitive environment.

Automated grain extraction and classification by combining improved region growing segmentation and shape descriptors in electromagnetic mill classification system

NASA Astrophysics Data System (ADS)

Budzan, Sebastian

2018-04-01

In this paper, the automatic method of grain detection and classification has been presented. As input, it uses a single digital image obtained from milling process of the copper ore with an high-quality digital camera. The grinding process is an extremely energy and cost consuming process, thus granularity evaluation process should be performed with high efficiency and time consumption. The method proposed in this paper is based on the three-stage image processing. First, using Seeded Region Growing (SRG) segmentation with proposed adaptive thresholding based on the calculation of Relative Standard Deviation (RSD) all grains are detected. In the next step results of the detection are improved using information about the shape of the detected grains using distance map. Finally, each grain in the sample is classified into one of the predefined granularity class. The quality of the proposed method has been obtained by using nominal granularity samples, also with a comparison to the other methods.

Detection, identification and differentiation of Pectobacterium and Dickeya species causing potato blackleg and tuber soft rot: a review

PubMed Central

Czajkowski, R; Pérombelon, MCM; Jafra, S; Lojkowska, E; Potrykus, M; van der Wolf, JM; Sledz, W

2015-01-01

The soft rot Enterobacteriaceae (SRE) Pectobacterium and Dickeya species (formerly classified as pectinolytic Erwinia spp.) cause important diseases on potato and other arable and horticultural crops. They may affect the growing potato plant causing blackleg and are responsible for tuber soft rot in storage thereby reducing yield and quality. Efficient and cost-effective detection and identification methods are essential to investigate the ecology and pathogenesis of the SRE as well as in seed certification programmes. The aim of this review was to collect all existing information on methods available for SRE detection. The review reports on the sampling and preparation of plant material for testing and on over thirty methods to detect, identify and differentiate the soft rot and blackleg causing bacteria to species and subspecies level. These include methods based on biochemical characters, serology, molecular techniques which rely on DNA sequence amplification as well as several less-investigated ones. PMID:25684775

An Accurate Framework for Arbitrary View Pedestrian Detection in Images

NASA Astrophysics Data System (ADS)

Fan, Y.; Wen, G.; Qiu, S.

2018-01-01

We consider the problem of detect pedestrian under from images collected under various viewpoints. This paper utilizes a novel framework called locality-constrained affine subspace coding (LASC). Firstly, the positive training samples are clustered into similar entities which represent similar viewpoint. Then Principal Component Analysis (PCA) is used to obtain the shared feature of each viewpoint. Finally, the samples that can be reconstructed by linear approximation using their top- k nearest shared feature with a small error are regarded as a correct detection. No negative samples are required for our method. Histograms of orientated gradient (HOG) features are used as the feature descriptors, and the sliding window scheme is adopted to detect humans in images. The proposed method exploits the sparse property of intrinsic information and the correlations among the multiple-views samples. Experimental results on the INRIA and SDL human datasets show that the proposed method achieves a higher performance than the state-of-the-art methods in form of effect and efficiency.

Essential Limitations of the Standard THz TDS Method for Substance Detection and Identification and a Way of Overcoming Them

PubMed Central

Trofimov, Vyacheslav A.; Varentsova, Svetlana A.

2016-01-01

Low efficiency of the standard THz TDS method of the detection and identification of substances based on a comparison of the spectrum for the signal under investigation with a standard signal spectrum is demonstrated using the physical experiments conducted under real conditions with a thick paper bag as well as with Si-based semiconductors under laboratory conditions. In fact, standard THz spectroscopy leads to false detection of hazardous substances in neutral samples, which do not contain them. This disadvantage of the THz TDS method can be overcome by using time-dependent THz pulse spectrum analysis. For a quality assessment of the standard substance spectral features presence in the signal under analysis, one may use time-dependent integral correlation criteria. PMID:27070617

Essential Limitations of the Standard THz TDS Method for Substance Detection and Identification and a Way of Overcoming Them.

PubMed

Trofimov, Vyacheslav A; Varentsova, Svetlana A

2016-04-08

Low efficiency of the standard THz TDS method of the detection and identification of substances based on a comparison of the spectrum for the signal under investigation with a standard signal spectrum is demonstrated using the physical experiments conducted under real conditions with a thick paper bag as well as with Si-based semiconductors under laboratory conditions. In fact, standard THz spectroscopy leads to false detection of hazardous substances in neutral samples, which do not contain them. This disadvantage of the THz TDS method can be overcome by using time-dependent THz pulse spectrum analysis. For a quality assessment of the standard substance spectral features presence in the signal under analysis, one may use time-dependent integral correlation criteria.

Multi-input multioutput orthogonal frequency division multiplexing radar waveform design for improving the detection performance of space-time adaptive processing

NASA Astrophysics Data System (ADS)

Wang, Hongyan

2017-04-01

This paper addresses the waveform optimization problem for improving the detection performance of multi-input multioutput (MIMO) orthogonal frequency division multiplexing (OFDM) radar-based space-time adaptive processing (STAP) in the complex environment. By maximizing the output signal-to-interference-and-noise-ratio (SINR) criterion, the waveform optimization problem for improving the detection performance of STAP, which is subjected to the constant modulus constraint, is derived. To tackle the resultant nonlinear and complicated optimization issue, a diagonal loading-based method is proposed to reformulate the issue as a semidefinite programming one; thereby, this problem can be solved very efficiently. In what follows, the optimized waveform can be obtained to maximize the output SINR of MIMO-OFDM such that the detection performance of STAP can be improved. The simulation results show that the proposed method can improve the output SINR detection performance considerably as compared with that of uncorrelated waveforms and the existing MIMO-based STAP method.

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.

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.

Detection of Toxoplasma gondii oocysts in water: proposition of a strategy and evaluation in Champagne-Ardenne Region, France.

PubMed

Aubert, D; Villena, I

2009-03-01

Water is a vehicle for disseminating human and veterinary toxoplasmosis due to oocyst contamination. Several outbreaks of toxoplasmosis throughout the world have been related to contaminated drinking water. We have developed a method for the detection of Toxoplasma gondii oocysts in water and we propose a strategy for the detection of multiple waterborne parasites, including Cryptosporidium spp. and Giardia. Water samples were filtered to recover Toxoplasma oocysts and, after the detection of Cryptosporidium oocysts and Giardia cysts by immunofluorescence, as recommended by French norm procedure NF T 90-455, the samples were purified on a sucrose density gradient. Detection of Toxoplasma was based on PCR amplification and mouse inoculation to determine the presence and infectivity of recovered oocysts. After experimental seeding assays, we determined that the PCR assay was more sensitive than the bioassay. This strategy was then applied to 482 environmental water samples collected since 2001. We detected Toxoplasma DNA in 37 environmental samples (7.7%), including public drinking water; however, none of them were positive by bioassay. This strategy efficiently detects Toxoplasma oocysts in water and may be suitable as a public health sentinel method. Alternative methods can be used in conjunction with this one to determine the infectivity of parasites that were detected by molecular methods.

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

PubMed

Kemeny, Steven Frank; Clyne, Alisa Morss

2011-04-01

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

Quick detection of QRS complexes and R-waves using a wavelet transform and K-means clustering.

PubMed

Xia, Yong; Han, Junze; Wang, Kuanquan

2015-01-01

Based on the idea of telemedicine, 24-hour uninterrupted monitoring on electrocardiograms (ECG) has started to be implemented. To create an intelligent ECG monitoring system, an efficient and quick detection algorithm for the characteristic waveforms is needed. This paper aims to give a quick and effective method for detecting QRS-complexes and R-waves in ECGs. The real ECG signal from the MIT-BIH Arrhythmia Database is used for the performance evaluation. The method proposed combined a wavelet transform and the K-means clustering algorithm. A wavelet transform is adopted in the data analysis and preprocessing. Then, based on the slope information of the filtered data, a segmented K-means clustering method is adopted to detect the QRS region. Detection of the R-peak is based on comparing the local amplitudes in each QRS region, which is different from other approaches, and the time cost of R-wave detection is reduced. Of the tested 8 records (total 18201 beats) from the MIT-BIH Arrhythmia Database, an average R-peak detection sensitivity of 99.72 and a positive predictive value of 99.80% are gained; the average time consumed detecting a 30-min original signal is 5.78s, which is competitive with other methods.

Research on the method of improving the accuracy of CMM (coordinate measuring machine) testing aspheric surface

NASA Astrophysics Data System (ADS)

Cong, Wang; Xu, Lingdi; Li, Ang

2017-10-01

Large aspheric surface which have the deviation with spherical surface are being used widely in various of optical systems. Compared with spherical surface, Large aspheric surfaces have lots of advantages, such as improving image quality, correcting aberration, expanding field of view, increasing the effective distance and make the optical system compact, lightweight. Especially, with the rapid development of space optics, space sensor resolution is required higher and viewing angle is requred larger. Aspheric surface will become one of the essential components in the optical system. After finishing Aspheric coarse Grinding surface profile error is about Tens of microns[1].In order to achieve the final requirement of surface accuracy,the aspheric surface must be quickly modified, high precision testing is the basement of rapid convergence of the surface error . There many methods on aspheric surface detection[2], Geometric ray detection, hartmann detection, ronchi text, knifeedge method, direct profile test, interferometry, while all of them have their disadvantage[6]. In recent years the measure of the aspheric surface become one of the import factors which are restricting the aspheric surface processing development. A two meter caliber industrial CMM coordinate measuring machine is avaiable, but it has many drawbacks such as large detection error and low repeatability precision in the measurement of aspheric surface coarse grinding , which seriously affects the convergence efficiency during the aspherical mirror processing. To solve those problems, this paper presents an effective error control, calibration and removal method by calibration mirror position of the real-time monitoring and other effective means of error control, calibration and removal by probe correction and the measurement mode selection method to measure the point distribution program development. This method verified by real engineer examples, this method increases the original industrial-grade coordinate system nominal measurement accuracy PV value of 7 microns to 4microns, Which effectively improves the grinding efficiency of aspheric mirrors and verifies the correctness of the method. This paper also investigates the error detection and operation control method, the error calibration of the CMM and the random error calibration of the CMM .

Electrochemical detection of nitromethane vapors combined with a solubilization device.

PubMed

Delile, Sébastien; Aussage, Adeline; Maillou, Thierry; Palmas, Pascal; Lair, Virginie; Cassir, Michel

2015-01-01

During the past decade, the number of terrorism acts has increased and the need for efficient explosive detectors has become an urgent worldwide necessity. A prototype, Nebulex™, was recently developed in our laboratory. Basically, it couples the solubilization of an analyte from the atmosphere by a nebulization process and in-situ detection. This article presents the development and integration of an electrochemical sensor for the detection of nitromethane, a common chemical product that can be used to make an improvised explosive device. A gold screen-printed electrode was used in a flow-cell and a detection limit of 4.5 µM was achieved by square wave voltammetry. The detection method was also determined to be selective toward nitromethane over a large panel of interfering compounds. Detection tests with the Nebulex™ were thus carried out using a custom-made calibrated nitromethane vapor generator. Detection times of less than one minute were obtained for nitromethane contents of 8 and 90 ppmv. Further measurements were performed in a room-measurement configuration leading to detection times in the range of 1-2 min, clearly demonstrating the system's efficiency under quasi-real conditions. Copyright © 2014 Elsevier B.V. All rights reserved.

A new optical method for a fast and simple detection of ephedrine

NASA Astrophysics Data System (ADS)

Varriale, Antonio; Staiano, Maria; Strianese, Maria; Marzullo, Vincenzo; Ruggiero, Giuseppe; Secchi, Alberto; Dispenza, Massimiliano; Fiorello, Anna Maria; D'Auria, Sabato

2011-11-01

In this work we describe the synthesis of a new ephedrine derivative with a carbon linker featuring an amino reactive group, and its conjugation to the glutamine binding protein (GlnBP) from E. coli as a carrier protein for the production of polyclonal antibodies in rabbits against ephedrine. Proof-of-principle results that an efficient SPR-based indirect competitive immunoassay for the detection and quantification of ephedrine are presented. The detection limit of this assay was found to be about 33ng/ml.

System and method for automated object detection in an image

DOEpatents

Kenyon, Garrett T.; Brumby, Steven P.; George, John S.; Paiton, Dylan M.; Schultz, Peter F.

2015-10-06

A contour/shape detection model may use relatively simple and efficient kernels to detect target edges in an object within an image or video. A co-occurrence probability may be calculated for two or more edge features in an image or video using an object definition. Edge features may be differentiated between in response to measured contextual support, and prominent edge features may be extracted based on the measured contextual support. The object may then be identified based on the extracted prominent edge features.

Scan statistics with local vote for target detection in distributed system

NASA Astrophysics Data System (ADS)

Luo, Junhai; Wu, Qi

2017-12-01

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

Evaluation of culture-based techniques and 454 pyrosequencing for the analysis of fungal diversity in potting media and organic fertilizers.

PubMed

Al-Sadi, A M; Al-Mazroui, S S; Phillips, A J L

2015-08-01

Potting media and organic fertilizers (OFs) are commonly used in agricultural systems. However, there is a lack of studies on the efficiency of culture-based techniques in assessing the level of fungal diversity in these products. A study was conducted to investigate the efficiency of seven culture-based techniques and pyrosequencing for characterizing fungal diversity in potting media and OFs. Fungal diversity was evaluated using serial dilution, direct plating and baiting with carrot slices, potato slices, radish seeds, cucumber seeds and cucumber cotyledons. Identity of all the isolates was confirmed on the basis of the internal transcribed spacer region of the ribosomal RNA (ITS rRNA) sequence data. The direct plating technique was found to be superior over other culture-based techniques in the number of fungal species detected. It was also found to be simple and the least time consuming technique. Comparing the efficiency of direct plating with 454 pyrosequencing revealed that pyrosequencing detected 12 and 15 times more fungal species from potting media and OFs respectively. Analysis revealed that there were differences between potting media and OFs in the dominant phyla, classes, orders, families, genera and species detected. Zygomycota (52%) and Chytridiomycota (60%) were the predominant phyla in potting media and OFs respectively. The superiority of pyrosequencing over cultural methods could be related to the ability to detect obligate fungi, slow growing fungi and fungi that exist at low population densities. The evaluated methods in this study, especially direct plating and pyrosequencing, may be used as tools to help detect and reduce movement of unwanted fungi between countries and regions. © 2015 The Society for Applied Microbiology.

Cross-platform evaluation of commercial real-time SYBR green RT-PCR kits for sensitive and rapid detection of European bat Lyssavirus type 1.

PubMed

Picard-Meyer, Evelyne; Peytavin de Garam, Carine; Schereffer, Jean Luc; Marchal, Clotilde; Robardet, Emmanuelle; Cliquet, Florence

2015-01-01

This study evaluates the performance of five two-step SYBR Green RT-qPCR kits and five one-step SYBR Green qRT-PCR kits using real-time PCR assays. Two real-time thermocyclers showing different throughput capacities were used. The analysed performance evaluation criteria included the generation of standard curve, reaction efficiency, analytical sensitivity, intra- and interassay repeatability as well as the costs and the practicability of kits, and thermocycling times. We found that the optimised one-step PCR assays had a higher detection sensitivity than the optimised two-step assays regardless of the machine used, while no difference was detected in reaction efficiency, R (2) values, and intra- and interreproducibility between the two methods. The limit of detection at the 95% confidence level varied between 15 to 981 copies/µL and 41 to 171 for one-step kits and two-step kits, respectively. Of the ten kits tested, the most efficient kit was the Quantitect SYBR Green qRT-PCR with a limit of detection at 95% of confidence of 20 and 22 copies/µL on the thermocyclers Rotor gene Q MDx and MX3005P, respectively. The study demonstrated the pivotal influence of the thermocycler on PCR performance for the detection of rabies RNA, as well as that of the master mixes.

Cross-Platform Evaluation of Commercial Real-Time SYBR Green RT-PCR Kits for Sensitive and Rapid Detection of European Bat Lyssavirus Type 1

PubMed Central

Picard-Meyer, Evelyne; Peytavin de Garam, Carine; Schereffer, Jean Luc; Marchal, Clotilde; Robardet, Emmanuelle; Cliquet, Florence

2015-01-01

This study evaluates the performance of five two-step SYBR Green RT-qPCR kits and five one-step SYBR Green qRT-PCR kits using real-time PCR assays. Two real-time thermocyclers showing different throughput capacities were used. The analysed performance evaluation criteria included the generation of standard curve, reaction efficiency, analytical sensitivity, intra- and interassay repeatability as well as the costs and the practicability of kits, and thermocycling times. We found that the optimised one-step PCR assays had a higher detection sensitivity than the optimised two-step assays regardless of the machine used, while no difference was detected in reaction efficiency, R 2 values, and intra- and interreproducibility between the two methods. The limit of detection at the 95% confidence level varied between 15 to 981 copies/µL and 41 to 171 for one-step kits and two-step kits, respectively. Of the ten kits tested, the most efficient kit was the Quantitect SYBR Green qRT-PCR with a limit of detection at 95% of confidence of 20 and 22 copies/µL on the thermocyclers Rotor gene Q MDx and MX3005P, respectively. The study demonstrated the pivotal influence of the thermocycler on PCR performance for the detection of rabies RNA, as well as that of the master mixes. PMID:25785274

Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads

PubMed Central

Schröder, Jan; Hsu, Arthur; Boyle, Samantha E.; Macintyre, Geoff; Cmero, Marek; Tothill, Richard W.; Johnstone, Ricky W.; Shackleton, Mark; Papenfuss, Anthony T.

2014-01-01

Motivation: Methods for detecting somatic genome rearrangements in tumours using next-generation sequencing are vital in cancer genomics. Available algorithms use one or more sources of evidence, such as read depth, paired-end reads or split reads to predict structural variants. However, the problem remains challenging due to the significant computational burden and high false-positive or false-negative rates. Results: In this article, we present Socrates (SOft Clip re-alignment To idEntify Structural variants), a highly efficient and effective method for detecting genomic rearrangements in tumours that uses only split-read data. Socrates has single-nucleotide resolution, identifies micro-homologies and untemplated sequence at break points, has high sensitivity and high specificity and takes advantage of parallelism for efficient use of resources. We demonstrate using simulated and real data that Socrates performs well compared with a number of existing structural variant detection tools. Availability and implementation: Socrates is released as open source and available from http://bioinf.wehi.edu.au/socrates. Contact: papenfuss@wehi.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24389656

Development of a microplate-based fluorescence immunoassay using quantum dot streptavidin conjugates for enumeration of putative marine bacteria, Alteromonas sp., associated with a benthic harpacticoid copepod.

PubMed

Beckman, Erin M; Kawaguchi, Tomohiro; Chandler, G Thomas; Decho, Alan W

2008-12-01

Attached bacteria inhabit the surfaces of many marine animals--a process that may play important roles in the survival and transport through aquatic systems. However, efficient detection of these bacteria has been problematic, especially small aquatic animals such as benthic harpacticoid copepod. Quantum dots (QD) have recently emerged as a significant tool in immunofluorescence detection because of their unique properties compared to other fluorescent probes. In the present study, a polyclonal antibody was raised against the Gram-negative marine bacterium, Alteromonas sp. A microplate-based immunofluorescence bioassay using QD strepavidin conjugates was developed for quantifying putative Alteromonas sp. cells located on the surfaces of a marine harpacticoid copepod, Microarthridion littorale. The number of attached Alteromonas sp. was estimated to be 10(2)+/-8 CFU using this method. The QD approach, coupled to a microplate assay can potentially provide an efficient and accurate method for rapidly detecting multiple bacteria species attached to small invertebrate animals because of their unique excitation and emission characteristics.

Measurement of O-GlcNAcylated endothelial nitric oxide synthase by using 2',5'-ADP-Sepharose pull-down assay.

PubMed

Long, Yang; Yan, Jianghong; Luo, Suxin; Liu, Zhenguo; Xia, Yong

2017-11-15

Endothelial nitric oxide synthase (eNOS) plays central roles in cardiovascular regulation and disease. eNOS function is critically affected by O-linked N-acetylglucosamine (O-GlcNAc) modification. The present method for measuring O-GlcNAcylated eNOS relies on immunoprecipitation. Such method exhibits low detection efficiency and is also costly. We here report a simplified assay by employing the high binding affinity of eNOS with the 2',5'-ADP-Sepharose resins. Together with the O-GlcNAc antibody, this assay readily allows the detection of O-GlcNAcylated eNOS in both cultured endothelial cells and rat vascular tissues. By using this assay, we demonstrate that eNOS O-GlcNAcylation is markedly elevated in the vessels of diabetic rats. Thus, a 2',5'-ADP-Sepharose-based pull-down assay is developed to measure O-GlcNAcylated eNOS. This assay is simple and efficient in detecting O-GlcNAcylated eNOS in cultured cells and animal tissues under both normal and disease conditions. Copyright © 2017 Elsevier Inc. All rights reserved.

AnRAD: A Neuromorphic Anomaly Detection Framework for Massive Concurrent Data Streams.

PubMed

Chen, Qiuwen; Luley, Ryan; Wu, Qing; Bishop, Morgan; Linderman, Richard W; Qiu, Qinru

2018-05-01

The evolution of high performance computing technologies has enabled the large-scale implementation of neuromorphic models and pushed the research in computational intelligence into a new era. Among the machine learning applications, unsupervised detection of anomalous streams is especially challenging due to the requirements of detection accuracy and real-time performance. Designing a computing framework that harnesses the growing computing power of the multicore systems while maintaining high sensitivity and specificity to the anomalies is an urgent research topic. In this paper, we propose anomaly recognition and detection (AnRAD), a bioinspired detection framework that performs probabilistic inferences. We analyze the feature dependency and develop a self-structuring method that learns an efficient confabulation network using unlabeled data. This network is capable of fast incremental learning, which continuously refines the knowledge base using streaming data. Compared with several existing anomaly detection approaches, our method provides competitive detection quality. Furthermore, we exploit the massive parallel structure of the AnRAD framework. Our implementations of the detection algorithm on the graphic processing unit and the Xeon Phi coprocessor both obtain substantial speedups over the sequential implementation on general-purpose microprocessor. The framework provides real-time service to concurrent data streams within diversified knowledge contexts, and can be applied to large problems with multiple local patterns. Experimental results demonstrate high computing performance and memory efficiency. For vehicle behavior detection, the framework is able to monitor up to 16000 vehicles (data streams) and their interactions in real time with a single commodity coprocessor, and uses less than 0.2 ms for one testing subject. Finally, the detection network is ported to our spiking neural network simulator to show the potential of adapting to the emerging neuromorphic architectures.

Fast Sparse Coding for Range Data Denoising with Sparse Ridges Constraint.

PubMed

Gao, Zhi; Lao, Mingjie; Sang, Yongsheng; Wen, Fei; Ramesh, Bharath; Zhai, Ruifang

2018-05-06

Light detection and ranging (LiDAR) sensors have been widely deployed on intelligent systems such as unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) to perform localization, obstacle detection, and navigation tasks. Thus, research into range data processing with competitive performance in terms of both accuracy and efficiency has attracted increasing attention. Sparse coding has revolutionized signal processing and led to state-of-the-art performance in a variety of applications. However, dictionary learning, which plays the central role in sparse coding techniques, is computationally demanding, resulting in its limited applicability in real-time systems. In this study, we propose sparse coding algorithms with a fixed pre-learned ridge dictionary to realize range data denoising via leveraging the regularity of laser range measurements in man-made environments. Experiments on both synthesized data and real data demonstrate that our method obtains accuracy comparable to that of sophisticated sparse coding methods, but with much higher computational efficiency.

Remote health monitoring of heart failure with data mining via CART method on HRV features.

PubMed

Pecchia, Leandro; Melillo, Paolo; Bracale, Marcello

2011-03-01

Disease management programs, which use no advanced information and computer technology, are as effective as telemedicine but more efficient because less costly. We proposed a platform to enhance effectiveness and efficiency of home monitoring using data mining for early detection of any worsening in patient's condition. These worsenings could require more complex and expensive care if not recognized. In this letter, we briefly describe the remote health monitoring platform we designed and realized, which supports heart failure (HF) severity assessment offering functions of data mining based on the classification and regression tree method. The system developed achieved accuracy and a precision of 96.39% and 100.00% in detecting HF and of 79.31% and 82.35% in distinguishing severe versus mild HF, respectively. These preliminary results were achieved on public databases of signals to improve their reproducibility. Clinical trials involving local patients are still running and will require longer experimentation.

Triazole-based Zn²⁺-specific molecular marker for fluorescence bioimaging.

PubMed

Sinha, Sougata; Mukherjee, Trinetra; Mathew, Jomon; Mukhopadhyay, Subhra K; Ghosh, Subrata

2014-04-25

Fluorescence bioimaging potential, both in vitro and in vivo, of a yellow emissive triazole-based molecular marker has been investigated and demonstrated. Three different kinds of cells, viz Bacillus thuringiensis, Candida albicans, and Techoma stans pollen grains were used to investigate the intracellular zinc imaging potential of 1 (in vitro studies). Fluorescence imaging of translocation of zinc through the stem of small herb, Peperomia pellucida, having transparent stem proved in vivo bioimaging capability of 1. This approach will enable in screening cell permeability and biostability of a newly developed probe. Similarly, the current method for detection and localization of zinc in Gram seed sprouts could be an easy and potential alternative of the existing analytical methods to investigate the efficiency of various strategies applied for increasing zinc-content in cereal crops. The probe-zinc ensemble has efficiently been applied for detecting phosphate-based biomolecules. Copyright © 2014 Elsevier B.V. All rights reserved.

Robust boundary detection of left ventricles on ultrasound images using ASM-level set method.

PubMed

Zhang, Yaonan; Gao, Yuan; Li, Hong; Teng, Yueyang; Kang, Yan

2015-01-01

Level set method has been widely used in medical image analysis, but it has difficulties when being used in the segmentation of left ventricular (LV) boundaries on echocardiography images because the boundaries are not very distinguish, and the signal-to-noise ratio of echocardiography images is not very high. In this paper, we introduce the Active Shape Model (ASM) into the traditional level set method to enforce shape constraints. It improves the accuracy of boundary detection and makes the evolution more efficient. The experiments conducted on the real cardiac ultrasound image sequences show a positive and promising result.

Detection algorithm for glass bottle mouth defect by continuous wavelet transform based on machine vision

NASA Astrophysics Data System (ADS)

Qian, Jinfang; Zhang, Changjiang

2014-11-01

An efficient algorithm based on continuous wavelet transform combining with pre-knowledge, which can be used to detect the defect of glass bottle mouth, is proposed. Firstly, under the condition of ball integral light source, a perfect glass bottle mouth image is obtained by Japanese Computar camera through the interface of IEEE-1394b. A single threshold method based on gray level histogram is used to obtain the binary image of the glass bottle mouth. In order to efficiently suppress noise, moving average filter is employed to smooth the histogram of original glass bottle mouth image. And then continuous wavelet transform is done to accurately determine the segmentation threshold. Mathematical morphology operations are used to get normal binary bottle mouth mask. A glass bottle to be detected is moving to the detection zone by conveyor belt. Both bottle mouth image and binary image are obtained by above method. The binary image is multiplied with normal bottle mask and a region of interest is got. Four parameters (number of connected regions, coordinate of centroid position, diameter of inner cycle, and area of annular region) can be computed based on the region of interest. Glass bottle mouth detection rules are designed by above four parameters so as to accurately detect and identify the defect conditions of glass bottle. Finally, the glass bottles of Coca-Cola Company are used to verify the proposed algorithm. The experimental results show that the proposed algorithm can accurately detect the defect conditions of the glass bottles and have 98% detecting accuracy.

Automatic detection of kidney in 3D pediatric ultrasound images using deep neural networks

NASA Astrophysics Data System (ADS)

Tabrizi, Pooneh R.; Mansoor, Awais; Biggs, Elijah; Jago, James; Linguraru, Marius George

2018-02-01

Ultrasound (US) imaging is the routine and safe diagnostic modality for detecting pediatric urology problems, such as hydronephrosis in the kidney. Hydronephrosis is the swelling of one or both kidneys because of the build-up of urine. Early detection of hydronephrosis can lead to a substantial improvement in kidney health outcomes. Generally, US imaging is a challenging modality for the evaluation of pediatric kidneys with different shape, size, and texture characteristics. The aim of this study is to present an automatic detection method to help kidney analysis in pediatric 3DUS images. The method localizes the kidney based on its minimum volume oriented bounding box) using deep neural networks. Separate deep neural networks are trained to estimate the kidney position, orientation, and scale, making the method computationally efficient by avoiding full parameter training. The performance of the method was evaluated using a dataset of 45 kidneys (18 normal and 27 diseased kidneys diagnosed with hydronephrosis) through the leave-one-out cross validation method. Quantitative results show the proposed detection method could extract the kidney position, orientation, and scale ratio with root mean square values of 1.3 +/- 0.9 mm, 6.34 +/- 4.32 degrees, and 1.73 +/- 0.04, respectively. This method could be helpful in automating kidney segmentation for routine clinical evaluation.

Review of Methods for the Detection and Determination of Malachite Green and Leuco-Malachite Green in Aquaculture.

PubMed

Zhou, Xinhui; Zhang, Jiaran; Pan, Zhongli; Li, Daoliang

2018-05-14

Malachite green (MG) has been widely used in the aquaculture industry as a fungicide and parasiticide because of its high efficiency and low cost, and it is commonly found in aquatic products and environmental water. However, MG and its primary metabolite, leuco-malachite green (LMG), are also toxic inorganic contaminants that are hazardous to the health of humans and other organisms. A variety of methods have been proposed in recent years for detecting and monitoring MG and LMG. This article was compiled as a general review of the methods proposed for MG and LMG detection, and several important detection parameters, such as the limit of detection, recovery and relative standard deviation, were tabulated. The analytical methods for the determination of MG and LMG in various matrices include high-performance liquid chromatography separation-based methods, liquid chromatography tandem mass spectrometry, surface-enhanced Raman spectroscopy, electrochemical methods, immunological assays, spectrophotometry and fluorescent methods which were described in detail in this article. In addition, some sample preparation techniques were also described. This review can provide expert guidance to the reader on the advantages, disadvantages and applicability of the different methodologies. This review also discussed challenges and several perspectives on the future trends in the determination of MG and LMG.

Locating Structural Centers: A Density-Based Clustering Method for Community Detection

PubMed Central

Liu, Gongshen; Li, Jianhua; Nees, Jan P.

2017-01-01

Uncovering underlying community structures in complex networks has received considerable attention because of its importance in understanding structural attributes and group characteristics of networks. The algorithmic identification of such structures is a significant challenge. Local expanding methods have proven to be efficient and effective in community detection, but most methods are sensitive to initial seeds and built-in parameters. In this paper, we present a local expansion method by density-based clustering, which aims to uncover the intrinsic network communities by locating the structural centers of communities based on a proposed structural centrality. The structural centrality takes into account local density of nodes and relative distance between nodes. The proposed algorithm expands a community from the structural center to the border with a single local search procedure. The local expanding procedure follows a heuristic strategy as allowing it to find complete community structures. Moreover, it can identify different node roles (cores and outliers) in communities by defining a border region. The experiments involve both on real-world and artificial networks, and give a comparison view to evaluate the proposed method. The result of these experiments shows that the proposed method performs more efficiently with a comparative clustering performance than current state of the art methods. PMID:28046030

Semi-automated solid phase extraction method for the mass spectrometric quantification of 12 specific metabolites of organophosphorus pesticides, synthetic pyrethroids, and select herbicides in human urine.

PubMed

Davis, Mark D; Wade, Erin L; Restrepo, Paula R; Roman-Esteva, William; Bravo, Roberto; Kuklenyik, Peter; Calafat, Antonia M

2013-06-15

Organophosphate and pyrethroid insecticides and phenoxyacetic acid herbicides represent important classes of pesticides applied in commercial and residential settings. Interest in assessing the extent of human exposure to these pesticides exists because of their widespread use and their potential adverse health effects. An analytical method for measuring 12 biomarkers of several of these pesticides in urine has been developed. The target analytes were extracted from one milliliter of urine by a semi-automated solid phase extraction technique, separated from each other and from other urinary biomolecules by reversed-phase high performance liquid chromatography, and detected using tandem mass spectrometry with isotope dilution quantitation. This method can be used to measure all the target analytes in one injection with similar repeatability and detection limits of previous methods which required more than one injection. Each step of the procedure was optimized to produce a robust, reproducible, accurate, precise and efficient method. The required selectivity and sensitivity for trace-level analysis (e.g., limits of detection below 0.5ng/mL) was achieved using a narrow diameter analytical column, higher than unit mass resolution for certain analytes, and stable isotope labeled internal standards. The method was applied to the analysis of 55 samples collected from adult anonymous donors with no known exposure to the target pesticides. This efficient and cost-effective method is adequate to handle the large number of samples required for national biomonitoring surveys. Published by Elsevier B.V.

Using microwave heating to improve the desorption efficiency of high molecular weight VOC from beaded activated carbon.

PubMed

Fayaz, Mohammadreza; Shariaty, Pooya; Atkinson, John D; Hashisho, Zaher; Phillips, John H; Anderson, James E; Nichols, Mark

2015-04-07

Incomplete regeneration of activated carbon loaded with organic compounds results in heel build-up that reduces the useful life of the adsorbent. In this study, microwave heating was tested as a regeneration method for beaded activated carbon (BAC) loaded with n-dodecane, a high molecular weight volatile organic compound. Energy consumption and desorption efficiency for microwave-heating regeneration were compared with conductive-heating regeneration. The minimum energy needed to completely regenerate the adsorbent (100% desorption efficiency) using microwave regeneration was 6% of that needed with conductive heating regeneration, owing to more rapid heating rates and lower heat loss. Analyses of adsorbent pore size distribution and surface chemistry confirmed that neither heating method altered the physical/chemical properties of the BAC. Additionally, gas chromatography (with flame ionization detector) confirmed that neither regeneration method detectably altered the adsorbate composition during desorption. By demonstrating improvements in energy consumption and desorption efficiency and showing stable adsorbate and adsorbent properties, this paper suggests that microwave heating is an attractive method for activated carbon regeneration particularly when high-affinity VOC adsorbates are present.

Sequencing small genomic targets with high efficiency and extreme accuracy

PubMed Central

Schmitt, Michael W.; Fox, Edward J.; Prindle, Marc J.; Reid-Bayliss, Kate S.; True, Lawrence D.; Radich, Jerald P.; Loeb, Lawrence A.

2015-01-01

The detection of minority variants in mixed samples demands methods for enrichment and accurate sequencing of small genomic intervals. We describe an efficient approach based on sequential rounds of hybridization with biotinylated oligonucleotides, enabling more than one-million fold enrichment of genomic regions of interest. In conjunction with error correcting double-stranded molecular tags, our approach enables the quantification of mutations in individual DNA molecules. PMID:25849638

Efficient airport detection using region-based fully convolutional neural networks

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Convolutional neural network for earthquake detection and location

PubMed Central

Perol, Thibaut; Gharbi, Michaël; Denolle, Marine

2018-01-01

The recent evolution of induced seismicity in Central United States calls for exhaustive catalogs to improve seismic hazard assessment. Over the last decades, the volume of seismic data has increased exponentially, creating a need for efficient algorithms to reliably detect and locate earthquakes. Today’s most elaborate methods scan through the plethora of continuous seismic records, searching for repeating seismic signals. We leverage the recent advances in artificial intelligence and present ConvNetQuake, a highly scalable convolutional neural network for earthquake detection and location from a single waveform. We apply our technique to study the induced seismicity in Oklahoma, USA. We detect more than 17 times more earthquakes than previously cataloged by the Oklahoma Geological Survey. Our algorithm is orders of magnitude faster than established methods. PMID:29487899

[Study of automatic marine oil spills detection using imaging spectroscopy].

PubMed

Liu, De-Lian; Han, Liang; Zhang, Jian-Qi

2013-11-01

To reduce artificial auxiliary works in oil spills detection process, an automatic oil spill detection method based on adaptive matched filter is presented. Firstly, the characteristics of reflectance spectral signature of C-H bond in oil spill are analyzed. And an oil spill spectral signature extraction model is designed by using the spectral feature of C-H bond. It is then used to obtain the reference spectral signature for the following oil spill detection step. Secondly, the characteristics of reflectance spectral signature of sea water, clouds, and oil spill are compared. The bands which have large difference in reflectance spectral signatures of the sea water, clouds, and oil spill are selected. By using these bands, the sea water pixels are segmented. And the background parameters are then calculated. Finally, the classical adaptive matched filter from target detection algorithms is improved and introduced for oil spill detection. The proposed method is applied to the real airborne visible infrared imaging spectrometer (AVIRIS) hyperspectral image captured during the deepwater horizon oil spill in the Gulf of Mexico for oil spill detection. The results show that the proposed method has, high efficiency, does not need artificial auxiliary work, and can be used for automatic detection of marine oil spill.

Parallel heuristics for scalable community detection

DOE PAGES

Lu, Hao; Halappanavar, Mahantesh; Kalyanaraman, Ananth

2015-08-14

Community detection has become a fundamental operation in numerous graph-theoretic applications. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is an iterative heuristic for modularity optimization. Originally developed in 2008, the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method ismore » also inherently sequential, thereby limiting its scalability. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose heuristics that are designed to break the sequential barrier. For evaluation purposes, we implemented our heuristics using OpenMP multithreading, and tested them over real world graphs derived from multiple application domains. Compared to the serial Louvain implementation, our parallel implementation is able to produce community outputs with a higher modularity for most of the inputs tested, in comparable number or fewer iterations, while providing real speedups of up to 16x using 32 threads.« less

Improving detection of copy-number variation by simultaneous bias correction and read-depth segmentation.

PubMed

Szatkiewicz, Jin P; Wang, WeiBo; Sullivan, Patrick F; Wang, Wei; Sun, Wei

2013-02-01

Structural variation is an important class of genetic variation in mammals. High-throughput sequencing (HTS) technologies promise to revolutionize copy-number variation (CNV) detection but present substantial analytic challenges. Converging evidence suggests that multiple types of CNV-informative data (e.g. read-depth, read-pair, split-read) need be considered, and that sophisticated methods are needed for more accurate CNV detection. We observed that various sources of experimental biases in HTS confound read-depth estimation, and note that bias correction has not been adequately addressed by existing methods. We present a novel read-depth-based method, GENSENG, which uses a hidden Markov model and negative binomial regression framework to identify regions of discrete copy-number changes while simultaneously accounting for the effects of multiple confounders. Based on extensive calibration using multiple HTS data sets, we conclude that our method outperforms existing read-depth-based CNV detection algorithms. The concept of simultaneous bias correction and CNV detection can serve as a basis for combining read-depth with other types of information such as read-pair or split-read in a single analysis. A user-friendly and computationally efficient implementation of our method is freely available.